Without a consolidation strategy to follow MTX-based chemotherapy, the likelihood of PCNSL relapse is high, with a median PFS of 21.5 months after a complete response (CR) [13]. Historically, consolidation consisted of whole brain radiation therapy (WBRT) though it is unclear whether WBRT results in an overall survival (OS) benefit and it is associated with long-term neurotoxicity [13]. Whether a lower than standard dose of WBRT adequately addresses the issue of neurotoxicity remains to be seen [14]. Increasingly, myeloablative high-dose chemotherapy followed by autologous stem cell transplant (HDC-ASCT) is the preferred consolidation strategy for eligible patients. Such an approach after MTX-based therapy yields response rates of more than 90% [15] with median PFS of 74 months in one study [15] and not-reached in others [16,17]. For patients who are elderly or frail, non-myeloablative chemotherapy with high-dose cytarabine with or without etoposide may be considered [8,10,18]. Maintenance chemotherapy in lieu of consolidation is also a reasonable treatment approach [19,20]. In clinical trials, targeted or immunotherapies are also being explored for this purpose.

Despite aggressive treatment for PCNSL, approximately 15% of patients have refractory disease [21] and relapse rates are high, particularly in patents who are not candidates for HDC-ASCT. Traditional strategies for salvage therapy include MTX-rechallenge [22,23], alternate cytotoxic chemotherapy regimens [24–26], and WBRT [27,28]. Prognosis for relapsed disease is poor with a PFS of only about a year with aggressive salvage therapy [29]. As a result, there is a desperate need for novel therapeutic strategies. Recent developments in the understanding of the pathogenesis of PCNSL have led to the investigation and use of new, targeted approaches.

#### **2. Pathophysiology**

A vast majority of PCNSL cases are comprised of a diffuse large B cell lymphoma (DLBCL) and express pan-B cell markers CD20, CD19, CD22, and CD79a. Other lymphomatous malignancies such as T-cell lymphoma, Burkitt lymphoma, and lower grade lymphoproliferative neoplasms have been described but are less common and may warrant special considerations with regard to treatment strategy.

Histologically, DLBCL in the brain is highly proliferative with an angiocentric growth pattern. Based on the Hans criteria [30] and immunohistochemistry, a majority (>75%) of PCNSL cases are classified as activated B-cell-like (ABC)/nongerminal center subtype [31–33]. However further evidence with immunoglobulin heavy chain gene mutational signatures and immunophenotyping suggest PCNSL has germinal center origin or exposure [31,34–37] and increasingly, there is evidence PCNSL may demonstrate an overlapping state of differentiation with concurrent expression of germinal center markers such as BCL6 and activation markers such as cyclin D2 or MUM1/Interferon Regulatory Factor 4 (IRF4) [31,38]. Ultimately the relevance of differentiating between ABC or germinal center subtype in PCNSL is unclear and unlike in systemic lymphoma where the ABC subtype confers a poorer prognosis, there is no clear survival advantage associated with any particular subtype of PCNSL [39].

Single nucleotide variants and copy number alterations are frequent genetic events in PCNSL. *MYD88, CD79B*, *CARD11*, and *TNFAIP3* are amongst the most frequently mutated genes. Systemically, *MYD88* mutations are associated with the ABC subtype; but in PC-NSL, *MYD88*, and *CD79B* have been described in both ABC and GCB subtypes of disease. *MYD88* missense mutations (most common L265P [40]) lead to constitutive activation of the TLR pathway [41], while alterations in *CD79B* activate the BCR pathway [42]. Mutations in the coiled-coil domain of *CARD11* result in downstream activation of both pathways [43] while alterations to *TNFAIP3* can result in a loss of pathway inhibition. Ultimately, the BCR/TLR pathways result in upregulation of nuclear factor kappaB (NFκB), a protein transcription factor that promotes neoplastic proliferation and prevents apoptosis [44]. Copy number alterations may also contribute to pathogenesis. Losses are common at 6p21.33 (*HLA-B*, *HLA-C*), 6q21-23 (*TNFAIP3*), and 9p21.3 (*CDKN2A*). Copy number gains may be seen at 12q (*MDM2*, *CDK4*) and 9p24.1 (*PD-L1*, *PD-L2*). Somatic hypermutation (SHM) is also thought to play a role in PCNSL pathogenesis and may offer further rationale for use of immunotherapy. Genetic features of vitreoretinal lymphoma (VRL) have significant overlap with PCNSL, and result in probable activation of the TLR pathway. Mutations in *MYD88* may be more common in VRL (and not limited to L265P) while *CD79B* mutations appear less common [45]. SHM genes may be similarly mutated.

Increasingly, evidence suggests the tumor microenvironment also plays an important role in PCNSL. IL-10 is a cytokine that may serve as a prognostic biomarker and also appears to lead to activation of signal transducer and activator of transcription 3 (STAT3) [46]. The Janus kinase 2 (JAK2)/STAT3 pathway results in transcription of target genes involved in cellular proliferation, survival, and angiogenesis. STAT3 is expressed in a variety of malignancies including PCNSL [46]. Tumor-associated macrophages (TAMs) interact with PCNSL cells and promote tumor invasion, proliferation, and an immunosuppressed environment. Quantification of TAMs may be important in prognosis [47]. TAMs also overexpress *PD-L1*, suggesting a potential target for immunotherapy.

Overall, PCNSL appears to be biologically distinct from systemic lymphoma and is increasingly considered a separate entity [48–50]. Genetic alterations seen in PCNSL including activation of the B-cell receptor (BCR) and Toll-like receptor (TLR) signaling pathways most closely resemble those observed in testicular lymphoma [51–53], suggesting similar pathogenesis between these two immunoprivileged sites. Improved understanding of the unique molecular profile of PCNSL has allowed for the recent investigation of multiple targeted strategies (Table 1).

**Table 1.** Recent prospective trials of novel agents.

**Table 1.** *Cont.*

CR: complete response; M: methotrexate; mOS: median overall survival; mo: months mPFS: median progression-free survival; NR: not reached; NS: not specified; ORR: overall response rate; PCNSL: primary central nervous system lymphoma; PR: partial response; R/R: relapsed/refractory; TMZ: temozolomide; y: years.

#### **3. Molecular Targets**

#### *3.1. BCR/TLR Pathway*

Discovery of alterations involving the BCR and TLR pathways has led to the most significant recent breakthroughs in the treatment of PCNSL. The BCR signaling pathway can be targeted at different signaling nodes. Upstream, the pathway may be downregulated through targeting phosphatidylinositol-3 kinase (PI3K). Downstream, immunomodulatory drugs like lenalidomide may be used to inhibit IRF4, which affects NFκB function. Proteosome inhibitors may prevent release of NFκB to the nucleus, where it results in alteration of gene expression. Unfortunately, proteasome inhibitors are often too bulky to cross the blood–brain barrier (BBB).

Bruton's tyrosine kinase (BTK), the central signaling node of the pathway, can be targeted with ibrutinib. A prospective study of ibrutinib 560 mg daily in 52 patients with relapsed/refractory PCNSL demonstrated a response rate of 52% [60]. A higher dose of 840 mg daily may result in increased cerebrospinal fluid (CSF) concentration and remains well tolerated [55,59] though the clinical benefit of this higher dosing schedule is unknown and additional data suggests the enzymatic IC50 is not proportional to dose [40]. Response to ibrutinib occurs quickly with one 'window study' demonstrating a response rate of 83% to only two weeks of single-agent ibrutinib, prior to the addition of further chemotherapy [40]. Notably, these high response rates are in contrast the experience in systemic lymphoma where single agent ibrutinib may result in a response rate of only 25% [62]. While this may be in part due a higher incidence of BCR/TLR alterations in PCNSL such as *MYD88*, it is important to note that even PCNSL patients without obvious genomic alterations in the BCR pathway demonstrate ibrutinib response [60]. It is also worth noting that while concurrent *CD79B* and *MYD88* mutations appear to sensitize systemic lymphoma to ibrutinib [62], this same combination was associated with a poorer response in CNS disease, perhaps due to decreased dependence on the BCR pathway [55]. These mutations appear to coincide in approximately 37% of cases of PCNSL [40]. *CARD11* and *TNFAIP3* mutations are potential sources of ibrutinib resistance given their activity downstream BTK. While this has been described in systemic lymphoma [62,63] and PCNSL with ibrutinib monotherapy [55], adequate responses were seen in patients with these

potential resistance mechanisms when ibrutinib was used in combination with cytotoxic chemotherapy [59].

Despite high rates of radiographic response, the progression-free survival provided by ibrutinib monotherapy is less than 5 months, suggesting early development of resistance [55,60]. With ibrutinib combination treatment, that PFS is extended to approximately 9 months in pre-treated patients [59]. Multiple studies are now incorporating ibrutinib into combination therapy, paired with agents such as lenalidomide (NCT03703167), copanlisib (NCT03581942), checkpoint inhibition (NCT04421560, NCT03770416), and traditional chemotherapy (NCT04066920, NCT02315326).

Ibrutinib has been incorporated to the National Comprehensive Cancer Network (NCCN) guidelines for treatment of relapsed/refractory PCNSL. Studies investigating ibrutinib for use in newly diagnosed patients are currently underway (Table 2). Some newly diagnosed patients were included in a study of ibrutinib in combination with temozolomide, etoposide, liposomal doxorubicin, rituximab, and intrathecal cytarabine (DA-TEDDI-R) but the regimen was associated with high rates of toxicity, specifically aspergillosis in 39% of treated patients [40]. The same combination is now being used with prophylactic anti-fungal agents (NCT02203526). In the upfront setting, ibrutinib is also being studied in combination with MTX, vincristine, procarbazine, rituximab (NCT02315326, NCT04446962), and is being studied as maintenance therapy following response to induction therapy (NCT02623010).

**Table 2.** Ongoing trials of novel agents.

**Table 2.** *Cont.*

IT: intrathecal; MTX: methotrexate; TMZ: temozolomide.

It is unclear whether the next generation of BTK inhibitors such as tirabrutinib and acalabrutinib will offer any advantage over ibrutinib. Tirabrutinib was recently studied in a phase I/II dose escalation trial in Japan for treatment of relapsed/refractory PCNSL. Overall response rate (ORR) was 64% though PFS was only 2.9 months. Tirabrutinib is highly selective for BTK, theoretically reducing toxicity. Nevertheless, nearly half the patients (47.7%) experienced a grade 3 or greater adverse event including three cases of grade 3 skin reaction (2, erythema multiforme) and one case of a grade 5 interstitial lung disease and concurrent *Pneumocystis jirovecii* (PJP) in a patient not treated with PJP prophylaxis [61]. A phase II study in the United States is anticipated (NCT04947319). Acalabrutinib, another second generation BTK inhibitor, is currently being studied in patients with relapsed/refractory primary and secondary CNS lymphoma (NCT04548648, NCT04462328).

#### *3.2. PI3K/mTOR Pathway*

PI3K is a family of kinases that function as second messengers in multiple signal transduction pathways. Mammalian target of rapamycin (mTOR) is a ubiquitously expressed member of the PI3K family of proteins and a potential therapeutic target. The PI3K/AKT/mTOR pathway is highly conserved regulating cell growth and proliferation [64]. It functions via influence on BTK resulting in activation of NFκB via the BCR pathway but also leads to the activation of independent signaling pathways [41,42]. Inhibition of mTOR has demonstrated modest activity in the treatment of mantle cell lymphoma and systemic DLBCL [65,66].

Temsirolimus, an mTOR inhibitor, was the first targeted agent studied in the treatment of PCNSL. A phase 2 study of relapsed/refractory PCNSL patients yielded a response rate of 54%, notably higher than that observed with systemic lymphoma, but with a PFS of only 2.1 months. Importantly, CSF pharmacokinetics in fourteen samples failed to confirm presence of temsirolimus in all but one specimen which contained a marginal concentration of drug [54]. This was in contrast to a glioma study which demonstrated presence of intratumoral temsirolimus with tissue/blood concentration ratios ranging from 0.69–3.37 [67]. The mismatch between observed response and duration of control may speak to the importance of selecting a therapeutic agent that will treat both the intraparenchymal and leptomeningeal compartments or be a function of early development of resistance mechanisms.

A study of buparlisib, a pan-PI3K inhibitor resulted in even lower response rates (25%) [68]. Again, while pharmacokinetic data from a surgical glioma study demonstrate intratumoral concentrations on par with those in plasma [69], CSF concentrations were subtherapeutic in the CNS lymphoma population [68]. Further complicating the picture is evidence indicating incomplete blockade of the PI3K/AKT/mTOR pathway, even when intratumoral concentrations are achieved [69].

Current studies are underway with additional agents targeting this pathway. PQR309, a dual PI3K/mTOR inhibitor, has shown promise in the preclinical setting. Paxalisib is a PI3K/mTOR inhibitor with CNS penetrance. Each are being studied as monotherapy for patients with relapsed/refractory PCNSL (NCT02669511, NCT04906096). Copanlisib, another PI3K inhibitor, is being used in combination with ibrutinib (NCT03581942) in order to address increased activation of the PI3K/AKT/mTOR pathway observed in *CD79B* mutant lymphomas. Preclinical data suggest synergistic cell death with dual PI3K pathway inhibition and ibrutinib [55].

#### *3.3. Immunomedulatory Drugs*

Lenalidomide and pomalidomide are second and third generation immunomodulatory drugs (IMiDs) with the potential for direct and indirect antineoplastic effects. IMiDs suppress IRF4 which interfaces with NFκB, as well as MYC, frequently upregulated in PC-NSL [8]. They also block the PI3K/AKT pathway, resulting in anti-angiogenic effects [70], and appear to impact the immune microenvironment by modulating tumor-associated macrophages [71].

Lenalidomide has been studied as monotherapy for treatment of recurrent/relapsed PCNSL and SCNSL. Response was seen in 9 of 14 patients (64%) including within the leptomeningeal and ocular compartments. CSF analysis suggested dose-dependent increases in lenalidomide concentration with a CSF/plasma partition coefficient of >20% following the 15 and 20 mg dose levels [56]. A phase 2 study of lenalidomide in combination with systemic rituximab for relapsed/refractory PCNSL yielded an ORR 35.6% with median PFS and OS 7.8 and 17.7 months with a follow up of 19.2 months [58]. The combination was well tolerated and is now being studied in conjunction with ibrutinib (NCT03703167) for treatment of relapsed/refractory PCNSL. A retrospective study of rituximab/lenalidomide/ibrutinib demonstrated response in 8 of 14 heavily pre-treated patients [72]. Multiple combinations using lenalidomide are being studied for both newly diagnosed and relapsed disease (Table 2).

Another potential role for lenalidomide is use as a maintenance agent. In a retrospective study, low doses of 5–10 mg daily appeared to potentiate response to salvage therapy, resulting in longer PFS following salvage therapy than with initial treatment [56]. A small prospective cohort of lenalidomide maintenance following induction therapy with lenalidomide and rituximab induction did not yield as positive results [58]. The role of lenalidomide maintenance following induction treatment for newly diagnosed disease is currently under investigation (NCT04120350, NCT03495960, NCT04627753).

Pomalidomide is a third-generation agent that was studied in combination with dexamethasone in a phase I study of relapsed/refractory PCNSL and primary VRL patients [57]. ORR was 48% with a PFS of 5.3 months in all-comers and 9 months in responders. Notably, one patient had pseudoprogression after 4 cycles of treatment. CSF analysis was performed

in one patient; pomalidomide was detected with a CSF-to-plasma ration of 19 and 17% [57], consistent with pre-clinical data [71]. Pomalidomide is now being studied in combination with immunotherapy (NCT03798314).

IMiDs seem to be fairly well tolerated with toxicities most commonly consisting of marrow suppression, infection, and fatigue.

#### **4. Targeting the Immune System**

Increasingly, evidence suggests immune evasion and immune response modulation play a role in PCNSL pathogenesis and *PD-L1* upregulation has been well-described [52]. Two small retrospective studies have reported encouraging outcomes. Nayak et al., treated five patients (four PCNSL, one isolated SCNSL from testicular primary) with the anti-PD-1 agent nivolumab. All five had objective radiographic responses with four patients achieving a CR. PFS appeared promising at >13 months in all patients, and all were alive at a median follow up of 17 months [73]. The study was of course limited by its retrospective nature and several patients received either concurrent therapy (rituximab) or had initiated nivolumab immediately following brain radiation. Still, it lent support for further investigation into use of immunotherapy. A second, more recent retrospective study reported six patients with PCNSL (3) and isolated SCNSL (3) treated with anti-PD-1 therapy, pembrolizumab (5) or nivolumab (1). Ambady et al., achieved CR in three of six patients and reported progressive disease in the remaining. Interestingly, one patient who achieved an initial CR progressed after therapy was discontinued but was able to re-attain a CR upon re-initiation of immunotherapy [74]. PD-1 blockade tends to be welltolerated and has the potential to offer a viable alternative treatment strategy to patients who are elderly or frail. Prospective studies are ongoing exploring its use as monotherapy (NCT02857426) and in conjunction with other agents such as ibrutinib (NCT03770416, NCT04421560), lenalidomide (NCT04609046), or pomalidomide (NCT03798314). PD-1 blockade is also being explored as a potential maintenance or consolidation strategy (NCT04401774, NCT04022980).

Targeting tumors with chimeric antigen receptor T (CAR-T) cells is a novel strategy that utilizes a patients' own genetically engineered T cells to identify and bind a tumor-specific target antigen. CD19-targeted CAR-T cells have been studied in systemic DLBCL with encouraging results [75]. Initially patients with CNS disease were excluded from studies out of concern for neurotoxicity and the potential for limited efficacy at immunoprivileged sites. However, CAR-T cells have been identified in the CSF [75] and an index patient with SCNSL and concurrent systemic disease demonstrated a CR in the brain following treatment with CD-19 directed CAR-T cell therapy [76]. More recently, a retrospective report of patients with SCNSL treated with off-label tisagenlecleucel, another CD19-directed CAR-T, yielded responses in four of eight patients (two CR, two partial response at 28 days) [77]. Notably T-cell expansion was evident even in patients with isolated CNS disease. The treatment was tolerated well with no reports of greater than grade 1 neurotoxicity [77]. Preliminary data from an ongoing clinical trial enrolling patients with PCNSL reported high rates of toxicity with all patients developing at least grade 1 cytokine release syndrome and neurotoxicity, though all toxicities were reversible [78]. At initial disease response, three of five patients had achieved CR while the remaining 2 appeared to have stable disease. Additional prospective studies of CD19 CAR-T agents tisagenlecleucel (NCT04134117) and axicabtagene ciloleucel (NCT04608487) are underway in patients with CNS lymphoma, with results eagerly awaited. Newer generations of CAR-T cells are in development and may allow for modulation of the tumor microenvironment simultaneous with direct tumor killing. This newer generation of agents known as T-cells redirected for antigen-unrestricted cytokine-initiated killing (TRUCKs) express an additional transgenic inducible-cytokine to be released upon tumor-antigen binding, inducing a pro-inflammatory response and potentially mitigating the immunosuppressive lymphoma microenvironment [79].

Bi-specific T-cell engagers (BiTEs) are engineered bi-specific monoclonal antibodies with two single-chain variable domains of different antibodies. One domain targets the CD3 receptor on T cells while the other targets a tumor-specific antigen. BiTEs form a link between T cells and tumor, triggering cellular death via target cell lysis in the absence of regular major histocompatibility complex (MHC) class I/peptide antigen recognition [80]. Blinatumomab, a CD19/CD3-BiTE has been approved for use in the treatment of B-cell precursor acute lymphoblastic leukemia with minimal residual disease. It and a variety of CD20/CD3-BiTEs are undergoing investigation for treatment of systemic DLBCL [81]. At this time, studies are not enrolling patients with CNS disease due to concerns for neurotoxicity; however, this may be a treatment strategy in the future.

#### **5. Other Targets**

Other potential therapeutic targets are being explored in PCSNL. Loss of CDKN2A is frequently observed [52] and may be targeted by cyclin dependent kinase inhibitors. A small prospective study of abemaciclib in CNS lymphoma is ongoing (NCT03220646). Venetoclax, a targeted agent against BCL-2, appears to penetrate the BBB—though at lower concentrations—and may have some efficacy in CNS lymphoproliferative disease [82,83]. A prospective study of venetoclax with obinutuzumab, an anti-CD20 monoclonal antibody, was halted due to low enrollment (NCT04073147).

Selinexor, an inhibitor of exportin 1, blocks nuclear export, leading to accumulation of tumor suppressor proteins in the nucleus and resultant cell death. It is currently approved for the treatment of refractory multiple myeloma, relapsed systemic diffuse large B-cell lymphoma, and is planned to be studied for treatment of PCNSL. Pre-clinical data suggest selinexor may have synergy with ibrutinib, potentially paving the way for future studies [84].

#### **6. Challenges to Drug Development and Delivery**

Development of new targeted treatments has been difficult. One challenge is that PCNSL is a rare disease, limiting the ability to perform statistically significant head-tohead comparisons of treatment strategies. Prior to large-scale clinical studies however, it is important to achieve adequate understanding of drug pharmacokinetics in the CNS. Many targeted drugs such as proteasome inhibitors are too large to penetrate the BBB. Increasingly, it is being recognized that drug concentrations need to be explored in both the leptomeningeal compartment and intraparenchymal tumor tissue as one appears to be a poor surrogate for the other. Differences in concentration may be a result of frequent breakdown of the BBB in intraparenchymal disease.

Penetration of the BBB remains a challenge in the treatment of CNS malignancies, including PCNSL. One potential strategy to enhance drug delivery is disruption of the BBB, which can potentially be achieved with drugs, ultrasound, or osmotic disruption. One multi-center study of BBB disruption (BBBD) using mannitol followed by intra-arterial (IA) MTX yielded an ORR of 81.9% (CRR 57.8%) with an OS of 3.1 years [85]. This compared favorably to historical controls, particularly considering that approximately half the patients enrolled did not undergo consolidation treatment. Another strategy for BBBD include delivery of low doses of tumor necrosis factor-alpha (TNF) to the vasculature. This has been followed by delivery of systemic lymphoma regimens with otherwise poor CNS penetration (rituximab/cyclophosphamide/doxorubicin/vincristine/prednisone or R-CHOP) with good response rates [86].

Development of drug resistance is also a complicating factor, particularly for molecular strategies targeting only a single pathway. Combination studies are one potential strategy to reduce resistance. For example, while ibrutinib is associated with a short PFS when used as monotherapy, response appears more durable when it is used in combination. As a result, ibrutinib is now under investigation as part of a number of potential treatment regimens (Table 2). These studies are ongoing, and it remains to be seen whether this strategy will improve efficacy and long-term control in PCNSL.

#### **7. Future Directions**

The efficacy of MTX has meant that the investigation of most of these novel treatment strategies has been in the relapsed/refractory setting. Only recently are studies starting to incorporate the use of some of these newer agents into upfront treatment, and largely in combination with MTX. It remains to be seen whether any of these agents will obviate the need for MTX and for the most part, this is not being studied except in patients who are considered ineligible for MTX-based therapy. While MTX is effective, it necessitates frequent hospitalizations, leading to time away from work and family. Additionally, it confers risk of MTX-related toxicity, as well as complications associated with inpatient admission such as delirium, urinary tract infections, and thromboembolic events. Many of the novel therapies are oral and most can be administered in the outpatient setting. If they prove to be as effective as MTX, this may lead to a new treatment paradigm for PCNSL.

As we continue to develop novel strategies for this disease, it will become increasingly important to develop minimally invasive biomarkers. Traditionally, patients are monitored for recurrence with routine MRIs and possibly CSF sampling and ocular exams, depending on their presentation. Monitoring of biomarkers such as interleukin-10 (IL-10) may help monitor treatment response and allow for early detection of relapse [56,87]. Detection of circulating tumor DNA (ctDNA) may serve a similar role while allowing for detection and confirmation of genetic arrangements. While this technology has been unsuccessful in the serum of patients with PCNSL [88] in CSF, ctDNA has been used to detect molecular alterations [59,89]. Studies are ongoing to determine whether detection of ctDNA in the CSF is of prognostic import and can be used to monitor treatment response (NCT04401774). Monitoring of ctDNA in the CSF may also allow for monitoring of the presence of targetable mutations.

#### **8. Conclusions**

Advances in our understanding of the molecular drivers of PCNSL have led to the development of novel drug strategies. We must ensure these drugs penetrate the CNS, create responses, and that these responses are durable. Combination therapy may be one way to avoid early resistance. Harnessing of the immune system is another strategy. Further genetic characterization and monitoring will be crucial in furthering our understanding and predicting response.

**Author Contributions:** Conceptualization, L.R.S. and C.G.; Investigation, L.R.S. and C.G.; Resources, L.R.S. and C.G.; Writing—original draft preparation, L.R.S.; Writing—review and editing, L.R.S. and C.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This article was supported, in part, by the MSK Cancer Center Support Grant (P30 CA008748), National Institute of Health. CG was supported by grants from Cycle for Survival Equinox and the Leukemia & Lymphoma Society.

**Conflicts of Interest:** L.R.S. served as a consultant for Debiopharm and receives research funding from BTG, plc. C.G. is a consultant for BTG, KITE, and ONO.

#### **References**

## *Review* **Enhancing T Cell Chemotaxis and Infiltration in Glioblastoma**

**Kirit Singh \*, Kelly M. Hotchkiss, Kisha K. Patel , Daniel S. Wilkinson, Aditya A. Mohan, Sarah L. Cook and John H. Sampson \***

> Duke Brain Tumor Immunotherapy Program, Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA<EMAIL_ADDRESS>(K.M.H<EMAIL_ADDRESS>(K.K.P<EMAIL_ADDRESS>(D.S.W<EMAIL_ADDRESS>(A.A.M<EMAIL_ADDRESS>(S.L.C.) **\*** Correspondence<EMAIL_ADDRESS>(K.S<EMAIL_ADDRESS>(J.H.S.)

> **Simple Summary:** Immunotherapy in glioblastoma has so far failed to yield a survival benefit. This failure can be attributed to a paucity of immune cells at the tumor site which can be reinvigorated to kill tumor cells. Therefore, driving effector immune cells such as cytotoxic T lymphocytes to the tumor is a necessary pre-requisite of any effective immunotherapy approach. In this review, we will discuss therapeutic approaches possible for trafficking T cells from the periphery to travel through the blood–brain barrier and tissue of the brain to reach the tumor.

> **Abstract:** Glioblastoma is an immunologically 'cold' tumor, which are characterized by absent or minimal numbers of tumor-infiltrating lymphocytes (TILs). For those tumors that have been invaded by lymphocytes, they are profoundly exhausted and ineffective. While many immunotherapy approaches seek to reinvigorate immune cells at the tumor, this requires TILs to be present. Therefore, to unleash the full potential of immunotherapy in glioblastoma, the trafficking of lymphocytes to the tumor is highly desirable. However, the process of T cell recruitment into the central nervous system (CNS) is tightly regulated. Naïve T cells may undergo an initial licensing process to enter the migratory phenotype necessary to enter the CNS. T cells then must express appropriate integrins and selectin ligands to interact with transmembrane proteins at the blood–brain barrier (BBB). Finally, they must interact with antigen-presenting cells and undergo further licensing to enter the parenchyma. These T cells must then navigate the tumor microenvironment, which is rich in immunosuppressive factors. Altered tumoral metabolism also interferes with T cell motility. In this review, we will describe these processes and their mediators, along with potential therapeutic approaches to enhance trafficking. We also discuss safety considerations for such approaches as well as potential counteragents.

> **Keywords:** immunotherapy; glioblastoma; blood–brain barrier; central nervous system; T cells; T lymphocytes

#### **1. Introduction**

Immune surveillance of the central nervous system (CNS) is essential for environmental homeostasis and pathogen clearance. Without immune surveillance, opportunistic infections in the CNS commonly develop [1]. However, the entry of immune cells into the CNS is tightly controlled by the blood–brain barrier (BBB) and the blood–cerebrospinal fluid (BCSF) barrier. These formidable barriers lack fenestrations, exhibit a low degree of pinocytosis, and are sealed together by a network of intracellular junctions [2,3]. While this close control is desirable in health to avoid runaway immune responses in the CNS, restricted immune cell entry severely hampers the effectiveness of immunotherapy in glioblastoma [4]. This is further complicated by the immunosuppressive tumor microenvironment (TME), which consists of endothelial cells, pericytes, fibroblasts, and regulatory immune cells [5]. The TME drives effector immune cell exhaustion, thereby shielding solid malignancies from immune attack [6]. While immune checkpoint inhibition (ICI) seeks to

**Citation:** Singh, K.; Hotchkiss, K.M.; Patel, K.K.; Wilkinson, D.S.; Mohan, A.A.; Cook, S.L.; Sampson, J.H. Enhancing T Cell Chemotaxis and Infiltration in Glioblastoma. *Cancers* **2021**, *13*, 5367. https://doi.org/10.3390/ cancers13215367

Academic Editor: Edward Pan

Received: 27 September 2021 Accepted: 25 October 2021 Published: 26 October 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

reverse this exhausted state and 'release the brakes' on regional T cells, it is notable that the evaluation of resected stage IV gliomas are either devoid or demonstrate limited numbers of tumor-infiltrating lymphocytes (TILs) [7,8]. This would suggest that ICI will struggle owing to the lack of targets to reinvigorate. Indeed, initial trials of ICI in glioblastoma have failed [9]. However, when ICI is combined with increased numbers of functional TILs in pre-clinical models, long-term survival can be achieved [10,11]. Therefore, we require therapeutic strategies that can both recruit effector cells to the tumor site and ensure they remain functional.

While the CNS does host several immune cell classes, including T cells, these immune cells are clustered away from the tumor-bearing parenchyma in regions such as the choroid plexus, the meninges (containing the subarachnoid and perivascular spaces), and the CSF [12–17]. The clinical implications of this clustering were recognized as long ago as 1923, where Murphy and Sturm confirmed Shirai's initial finding that foreign tumors in the parenchyma could grow, but tumors implanted close to the ventricles (and thus the immune interfaces) were rejected [18]. Fortunately, immune responses in the CNS can be bolstered by an adaptive response originating from the periphery. Medawar demonstrated in 1948 that tumors implanted into brain tissue can be rejected following exposure to tumor antigens outside of the CNS [19]. Recruitment of peripheral T cells into the parenchyma also occurs in multiple sclerosis (MS) and its animal analogue experimental autoimmune encephalitis (EAE) [20].

Even though adaptive immune clearance of tumors is possible, glioblastoma possesses several mechanisms that suppress the recruitment and functioning of T cells. Glioblastoma expresses decreased levels of lymphangiogenesis-promoting factors such as VEGF-C, reducing potential routes for T cell ingress, while the highly immunosuppressive tumor microenvironment (TME) blunts the response of any lymphocytes that reach the tumor [21–23]. Therefore, in this review we will discuss the physiological processes that drive T cell trafficking from the periphery, tumoral infiltration, and potential therapeutic options for their enhancement. We will also discuss safety considerations, given the potential for T cell infiltration to drive inflammation and neurodegeneration in the CNS [24,25].

#### **2. T Cell Trafficking from the Periphery to the Blood–Brain Barrier**

The mechanism by which T cells leave the circulation and enter inflamed tissues is well characterized and has been reviewed in detail elsewhere [26–28]. In brief, the expression of selectins on endothelial cells results in the slowing and rolling of leukocytes. The leukocyte crawls along the endothelial layer, where stimulating chemokines trigger the activation of integrins, which ultimately result in the leukocyte being firmly captured [29–31]. Engagement of endothelial adhesion molecules by integrins results in immune cells being drawn to endothelial junctions, permitting their diapedesis (crossing) into the tissue [32]. T cell trafficking across the BBB involves a similar process of rolling, capture, and diapedesis [33]. However, certain aspects of this process differ from the periphery. In the resting state, the constitutive expression of selectin is largely absent in the CNS, with the exception of blood vessels in the sub arachnoid space [34,35]. T cell rolling on the BBB is instead driven by the cell surface integrin LFA-1, which binds to intercellular adhesion molecule-1 (ICAM-1) on the endothelium. These T cells are captured and cross via G protein-coupled receptor (GPCR) signaling [36].

In the pathological state, the release of inflammatory cytokines induces the expression of chemokines and adhesion molecules that recruit effector T cells to the CNS [37,38]. Transcription and expression of E- or P-selectins on the BBB adheres to P-selectin glycoprotein ligand-1 on CD8<sup>+</sup> T cells, inducing their slowing on the endothelial surface [39]. Binding is again mediated by GPCR signaling, which activates the integrins LFA-1 and VLA-4 on the T cells that bind to ICAM-1 and VCAM-1, respectively [40]. Other factors at the BBB also interact with VLA-4, including transmembrane proteins described as junctional adhesional molecules (JAM). So far, JAM-B and JAML have been implicated in CD8 chemotaxis blockade of JAM-B results in the reduced CNS infiltration of CD8+ T cells [41,42]. Atypical

chemokine receptor-1 (ACKR1) also mediates trafficking in the inflammatory state, transporting pro-infiltrative chemokines to the luminal aspect of the BBB [43]. Interleukin (IL)-1 signaling in BBB endothelial cells is associated with upregulated expression of VCAM-1, ICAM-1, and ACKR1 and therefore may offer a potential strategy for enhancing T cell capture if delivered intra-tumorally [44]. Frewert et al. reported that intra-tumoral infusion of IL-1β or interferon-γ via convection enhanced delivery enhanced the number of CD4<sup>+</sup> and CD8<sup>+</sup> TILs in a rat glioma model [45]. This may therefore be a rational combinatorial approach alongside ICI.

It should be noted that the expression of these adhesion molecules is also influenced by perivascular stromal cells such as regional pericytes [46,47]. In health, these cells coordinate with endothelial cells to control both the development and permeability of the vasculature [48]. Pericytes also inhibit endocytosis by endothelial cells, limiting transcellular routes of migration [49,50]. Indeed, mice deficient in pericytes display significantly increased expression of VCAM-1 and ICAM-1 on the BBB endothelium, resulting in a mass influx of leukocytes [51]. In the tumor setting, overgrowth of pericytes derived from glioma stem cells (GSCs) results in the blockage of the entrance of therapeutic drugs such as temozolomide (TMZ) [52]. Pericyte coverage is inversely correlated with survival in patients with glioblastoma following chemotherapy [53]. Interestingly, selective targeting of these cells using ibrutinib was shown to enhance delivery of TMZ in orthotopic models of glioma by disrupting the blood–tumor barrier [53]. This may also have a double effect of interrupting the pericyte secretion of CCL5, which acts on CCR5 on glioblastoma cells, inducing resistance to TMZ by promoting DNA damage repair mechanisms [54]. However, pericytes can re-organize themselves to cover areas of deficient coverage and their function may be compensated for by other local cells such as astrocytes [55].

The CCL5–CCR5 axis is also associated with enhanced regulatory T cell recruitment [56]. CCR5 antagonists such as maraviroc (licensed for HIV-1) have been found to deplete regulatory T cells, which express CCR5/CXCR4 ratios differently to T effector cells [57,58]. Blockade of CCR5 has also been demonstrated to reduce the growth of orthotopically injected colon cancer cells by limiting cancer-associated fibroblast accumulation. Maraviroc has also been shown to reverse CCL5 resistance to TMZ and is also BBB penetrable with a favorable safety profile, making this an agent of significant interest as part of future combinatorial approaches [54,59,60]. CCR5 also binds CCL3 and CCL4 and the interaction between CCR5 and its ligands appears to have location-specific pro or anti-tumor effects [61]. For example, CCL4 can help to recruit cytolytic CCR5+ T cells in esophageal squamous cell carcinoma, but the CCL4–CCR5 interaction can enhance the invasion ability of glioblastoma in vitro [62,63].

To determine how best to drive T cells into the CNS, we need to identify the optimal pro-infiltrative phenotype of lymphocytes. A high expression of integrins and chemokine receptors as seen in autoimmune disease is likely beneficial for enhancing T cell chemotaxis in glioblastoma. When reviewing T cell phenotypes that predominate in autoimmune diseases, CNS-infiltrative lymphocytes are predictably dominated by effector memory T cells (CD62LLo and CCR7Lo) [64–69]. While sensitizing T cells in the periphery would be ideal, the high degree of heterogeneity in glioblastoma makes it impossible to identify a universal target [70]. A more optimal approach would be trafficking antigen-naïve T cells that can interact with antigen-presenting cells (APCs) that endogenously present tumor antigen. This strategy benefits from the fact that T cells do not require target antigen recognition before they are able to cross the BBB [71]. In glioblastoma, T cells primed in tumor-draining cervical lymph nodes strongly upregulated VLA-4, leading to preferential infiltration of the CNS [72]. Therefore, activating tumor-antigen naïve T cells to express VLA-4 will help to achieve this objective. Administration of IL-12 to mice bearing multiple tumor types appeared to enhance the induction of LFA-1 and VLA-4 and subsequently T cell migration, resulting in tumor regression [73]. However, this response differed across tumor types, with IL-12 resulting in largely CD4 migration in fibrosarcoma but pre-dominantly CD8 migration in ovarian cancer, and further work is required to determine its impact in glioblastoma [73].

While antigen specificity is not a pre-requisite of migration into the CNS, it is interesting to note that adoptively transferred tumor-naïve T cells appear to undergo a period of residence in the lungs, where their gene expression profile switches to a migratory phenotype [74]. Determining mediators of this 'licensing' process may therefore yield useful therapeutic targets of interest. Before entering the lungs, adoptively transferred T cells predominantly migrate towards homeostatic chemokines CCL19 and CCL21 (expressed in bronchus-associated lymphoid tissues). After transiting through the lungs, T cell homing shifts towards chemokine gradients associated with inflammation such as CXCL11 and CCL5 [74]. CXCL11 binds the chemokine receptor CXCR3 (expressed on effector T cells), and this binding can promote T cell infiltration into tumors [75]. Conversely, inhibition of CXCR3 binding results in reduced invasion of effector T cells [76].

CXCR3 binds three ligands: CXCL9, CXCL10, and CXCL11. While CXCL11 binds CXCR3 with higher affinity, it also can induce receptor internalization and promote a regulatory T cell lineage [75]. Instead, CXCL10 may be a more suitable therapeutic approach, as CXCL10 induces moderate receptor internalization and still enhances T cell infiltration [77]. This was demonstrated in intracranial melanoma models, where the absence of CXCL10 was associated with decreased numbers of CD8+ TILs [78]. Although glioma does express CXCL10, this is accompanied by the expression of dipeptidylpeptidase (DPP)-4, which cleaves CXCL10 [79]. DPP-4 blockade has been shown to increase the numbers of TILs, but when considering therapeutic blockade, it must be noted that DPP-4 also inhibits glioma proliferation independently of its enzymatic activity [80,81]. An alternative approach to inducing expression of CXCL10 is the use of poly-ICLC, which has been found to significantly increase the frequency of TILs when combined with peptide vaccination against glioma [82]. An overview of peripheral T cell chemotaxis and BBB penetrance is shown in Figure 1.

**Figure 1.** (**A**) The BBB consists of endothelial cells held together by tight junctions surrounded by pericytes and astrocytes. (**B**) T cell chemotaxis across the BBB is facilitated by expression of tethering molecules (P-selectin, ICAM-1, VCAM-1, etc.) on endothelial cell surfaces that bind to integrins on circulating T cells (LFA-1, α4β1, etc.) to slow and allow cells to roll across the membrane surface. (**C**) T cells can cross the endothelial cells either between cells (paracellular) through tight junctions or through individual cells (transcellular) to migrate into the brain. Produced using Biorender.

#### **3. Blood–Brain Barrier Specific Targets**

Following the shift towards a pro-infiltrative phenotype, T cells must cross the BBB. Although glioblastoma is a disease state in which the BBB is disrupted, regions of the tumor are likely surrounded by intact portions of barrier [83]. These privileged regions may act as the site of regrowth, shielded from immunotherapeutic attack [8,83]. Such privileged regions correspond with the non-contrast enhancing infiltrating edge, which can form the site of recurrence following core resection [84]. Infiltrating glioma cells at the leading edge demonstrate upregulated fibroblast growth factor-mediated signaling that promotes tumorigenesis [85]. The changes in cellular phenotype at the leading edge are driven by histone deacetylase signaling from the tumor core [86]. This results in a permanent alteration at the border to a pro-infiltrative milieu of glioma-initiating cells, which does not reverse following resection of the core [86]. Immune cell populations differ at this interface zone also. Spatial single-cell RNA-Seq analysis performed by Darmanis et al. revealed that tumor associated macrophages (TAMs) dominated the core while brain-derived microglia dominated the peritumoral zone [87]. These both have key roles in T cell activity at the tumor site. Macrophages can express the cytokine TGF-β, which enhances glioblastoma cell growth, migration, and invasion and downregulates antitumor immunity [88,89]. Microglia in the peritumoral zone show an increased expression of ligands for T cell exhaustion-associated receptors such as PD1 and CTLA4 [87]. Microglia also express CCL2 and CCL5 which, as mentioned previously, enhances regulatory T cell recruitment and myeloid-derived suppressor cells [56,90]. Notably, CCL5 also acts as an auto-stimulatory signal for GBM cells by binding to the non-conventional receptor CD44, resulting in increased cell survival, invasion, and proliferation [91]. Therefore, targeting this zone of recurrence and immune exhaustion protected by intact barrier is key to enhancing the efficacy of immunotherapy. However, achieving this requires CTLs to traffic through the BBB.

The BBB is a highly regulated physical and metabolic barrier which extends from the CNS microvasculature to the endothelial cells of postcapillary venules [92]. During neuro-inflammation the permeability of the endothelial cells changes to allow for the entrance of lymphocytes into the CNS. This is achieved by changes in BBB junctional morphology that allow lymphocytes access either by squeezing between endothelial cells (paracellular diapedesis) or crossing through pores in the endothelial cell membrane (transcellular diapedesis) [93]. Recent single-cell RNA sequencing of the neuro-vasculature also shows enhanced endothelial cell expression of MHC class II genes in the disease state. The endothelial cell signature also changes from CNS specific to mirroring the periphery, thereby promoting immune trafficking from the blood (preprint [94]). The endothelial cells of the BBB are sealed by adherens junctions, a continuous series of complex tight junctions, and recently discovered tricellular junctions [95]. In the inflammatory state, these tricellular junctions have been suggested to be the primary site of cellular migration, through the downregulation of proteins (tricellulin and angulins) which normally maintain their morphology [95,96]. Interestingly, recombinant CCL2 and CCL5 administration was demonstrated in vitro to enhance T cell diapedesis through tricellular junctions. This may therefore offer a therapeutic strategy specifically to enhance paracellular crossing at the BBB, although their effect on recruiting regulatory T cells must also be considered [95,96].

Tight junctions can also be targeted to allow for entry of therapeutic agents [97,98]. These junctions are maintained on the basolateral side by the transmembrane adhesion proteins VE-cadherin and platelet endothelial cell adhesion molecule (PECAM)-1 [99,100]. The apical side of endothelial tight junctions is secured by occludin and claudin-1/3/5/12 [101]. Together, these proteins seal the tight junctions together by binding with each other on opposite endothelial cells, reducing the intercellular distance [101]. Claudin-5 is the most commonly expressed protein in tight junctions [101], and can be targeted with recombinant protein inhibitors such as the non-toxic C-terminal domain of the *Clostridium Perfringens* enterotoxin [102]. This can reversibly open endothelial tight junctions and allow ingress of therapeutic agents. Targeting of claudin-5 in vitro results in reduced paracellular diapedesis of lymphocytes while increasing transcellular diapedesis [103]. Other studies have also shown that knockout of adhesion molecules such as PECAM-1 does not result in enhanced paracellular movement, but instead increases migration via cell membrane channels [104]. Taken together, it becomes apparent that functional tight junction regulating proteins are required for paracellular diapedesis, and that disruption of these proteins may shift trafficking towards endocytic lymphocyte migration patterns similar to those found in neuroinflammatory CNS states [93].

The process of transcellular diapedesis is mediated by endocytosis at the endothelial cell membrane. This endocytosis occurs through vesicles containing caveolin (Cav)-1, which are increased in number during disease states such as EAE [105,106]. Regions of the BBB rich in Cav1 upregulate expression of adhesion receptors such as ICAM-1, capturing T cells at regions of the BBB where endocytic vesicles are present [107]. Interestingly, in inflammatory conditions such as EAE, ICAM-1 is highly expressed on the endothelium, and this over-expression promotes transcellular diapedesis. This contrasts with the resting state where low/intermediate expression of ICAM-1 favors paracellular diapedesis [108]. Therefore, promoting the expression of LFA-1 on T cells which can bind to over-expressed ICAM-1 may enhance T cell trafficking (therapeutic approaches described in the previous section). However, whether this effect also extends to CD8<sup>+</sup> T cells in the context of glioblastoma is unclear.

Differential trafficking of T cell subsets was also demonstrated by experiments using Cav1−/<sup>−</sup> mice which induced almost total loss of Th1 transcellular migration but did not impair migration of Th17 cells [109]. In EAE, Th17 T cells have been demonstrated to use CCR6 to bind CCL20 produced by the choroid plexus epithelial cells to gain access to the ventricular CSF [110,111]. When considering the CCR6–CCL20 axis for therapeutic targeting in glioblastoma, CD8+CCR6+ T cells also migrate towards CCL20 and blockade of CCL20 or CCR6 has also been demonstrated to reduce neuroinflammation in murine models of subarachnoid hemorrhage [112,113]. However, over-expression of CCL20 by tumors also correlates with tumor progression in multiple cancer types, as well as decreased survival [114]. Importantly though, the tumor-promoting effects of CCR6 signaling appear to rely on CCR6+ stromal cells but not CCR6+ immune cells [114]. Upregulation of CCR6 on immune cells may therefore be the more prudent therapeutic approach for enhancing T cell infiltration while maintaining tumor control. Transforming growth factor (TGF)-β has been shown to promote CCR6 expression on human CD4 T cells but is also implicated in the promotion of regulatory FOXP3 expression [115]. However, TGF-β priming also generates a fractional population of CCR6+FOXP3<sup>−</sup> cells [116]. Further selection of this population would therefore be desirable to achieve a pro-infiltrative, effector T cell phenotype. Models of EAE have also found that increased expression of CCL19 and CCL21 from mononuclear inflammatory cells binds CCR7+ T cells in the CSF [117]. CCL19 has been shown to enhance the frequency of antigen responsive IFN-γ<sup>+</sup> CD8<sup>+</sup> T cells in viral infection and CCR7 chemotaxis may be stimulated in vitro using by-products of coagulation factor XIIa (high-molecular-weight kininogen domain 5) [118,119]. However, CCL19 may also promote the migration of regulatory T cells (CD4+CD25+FoxP3+) and therefore its usefulness in glioblastoma is unclear [120].

While these mechanisms are of interest therapeutically to allow T cells to cross the BBB from the periphery, this is only the initial step in accessing the parenchyma. Interaction with professional antigen-presenting cells in the perivascular spaces is a key step before penetration of the glia limitans, which lines the blood vessels and the surface of the brain [121].

#### **4. The Glia Limitans—Accessing the Parenchyma**

Between the outer BBB and the parenchyma lies the glia limitans. The glia limitans is formed by astrocyte foot processes associating with the basal lamina of the parenchyma [110]. It is divided into two membranes: the glia limitans perivascularis (surrounding blood vessels) and the glia limitans superficialis (covering the surface of the

brain) [122]. In much of the brain, these two membranes lie so closely together that they are indistinguishable, but beyond the capillaries at the venules, inflammation can cause these two membranes to separate, forming a perivascular space. This space communicates with the CSF and allows for APCs to present antigens to entering T cells [123]. This interaction is critical in allowing T cells to access the parenchyma—indeed, the effects of T cells in EAE only begin once immune cells have crossed the glia limitans [124]. The APC–T cell interaction drives the production of further pro-inflammatory cytokines which triggers the recruitment of more immune cells [111,125]. Interestingly, while the initial T cells that enter these perivascular spaces tend to have increased expression of CCR6, further recruitment occurs in a CCR6-independent manner [110,111]. This would suggest that CCR6+ T cells form part of an initial 'licensing' step and that their interaction with APCs in the perivascular spaces facilitates further entry of T cells in a non-CCR6-specific manner.

In normal physiology, T cell crossing at the glia limitans is mediated by the expression of laminins [126]. For example, the parenchymal membrane of the glia limitans contains α1 and α2 laminins [127], which CD4+ T cells are unable to bind in the non-inflammatory state. However, in EAE, CD4<sup>+</sup> T cells can bypass this control mechanism by using matrix metalloproteinases (MMPs) which disrupt the astrocytic foot processes, breaking down barrier integrity and allowing for T cell ingress [124]. While this might suggest that MMP agonism may be an attractive prospect for opening the glia limitans, MMPs are involved in the angiogenesis and invasion of glioma [128]. Inhibition of MMP was even trialed using a broad-spectrum MMP inhibitor, but this resulted in widespread reports of musculoskeletal toxicity due to on-target, off-tumor effects [129,130]. Given these experiences, it is unlikely that MMP agonism in glioblastoma will be a desirable therapeutic target.

Another mediator of T cell entry into the parenchyma is CXCL12. In murine models, T cells have been noted to be held in perivascular spaces due to expression of CXCL12 [131]. This 'hold' is released in inflammatory conditions, as increased levels of IL-17 drive the expression of CXCR7 on endothelial cells, resulting in the internalization of CXCL12 [132]. This leads to increased CXCR4 expression on T cells and subsequent T cell entry into the parenchyma [131,132]. However, when considering the downregulation of CXCL12 as a therapeutic strategy, it is worth noting that recent studies evaluating T cell responses to viral infection in vitro have found that CXCL12 at the BBB endothelium can promote CD8+ migration across the BCSF interface, suggestive of a location-dependent role [133]. A summary of these selected targets and therapeutic considerations is shown in Table 1.

**Table 1.** A summary of selected factors that may enhance trafficking and infiltration of T cells across the BBB.

**Table 1.** *Cont.*

This table only provides selected examples and is not exhaustive.

#### **5. T Cell Trafficking through the Parenchyma**

Once past the glia limitans, effector T cells must reach and infiltrate the tumor to exert their cytotoxic effect. As discussed in the introduction, glioblastoma can restrict T cell trafficking due to the downregulated expression of VEGF-C, resulting in restricted lymphangiogenesis [22]. Notably, in patients treated with neoadjuvant anti-PD-1, VEGF-C expression was highly correlated with increased infiltration of T cells [138]. Thus, restoring levels of lymphangiogenesis-promoting factors such as VEGF-C could also enhance T cell homing and infiltration to the tumor. This is supported by the findings of Song et al., who demonstrated that intra-cisterna magna injections of an adeno-associated viral vector coding for VEGF-C could remodel meningeal lymphatic vessels in murine models of glioma [22]. Further enhanced expression of VEGF-C in lymphatic endothelial cells could potentiate the effect of checkpoint blockade due to enhanced T cell infiltration [22].

T cell motility is also dependent on metabolic pathways that are often usurped by rapidly proliferating tumors. Tumor cells demonstrate increased glucose uptake and lactose production, even in the presence of oxygen and functioning mitochondria (known as the Warburg effect) [139,140]. This affords the tumor and other rapidly proliferating cells essential anabolic precursors for cell proliferation [140]. The increased glucose demand by tumor cells therefore decreases the amount available for circulating T cells to maintain effector and migratory function [141]. Aerobic glycolysis is the main source of ATP production in leukocytes, which is required for the energetic demands of migration [142,143]. Inhibition of the T cell glycolytic pathway through administration of 2-DG and rapamycin causes a decrease in naïve T cell motility, demonstrating the importance of glucose in T cell homing [144,145]. The associated build-up of lactate caused by the Warburg effect also results in decreased migration of CD4+ T cells and a loss of cytolytic function of CD8+ T cells by interfering with T cell glycolysis [145–148]. However, this effect can be reversed, as demonstrated in an animal model of peritonitis where antibody-mediated blockade of lactate transporters on T cells allowed them to maintain their migratory potential [149]. Expression of CTLA-4 decreases the expression of the glucose transporter GLUT-1 on T cells, and further decreases effector function, implying that combinatorial approaches using checkpoint blockade may aid with T cell trafficking as well as reinvigoration of function [142,150]. However, recent work suggests that exhausted human CD8+ T cells may actually become more mobile [151]. CTLA-4 signaling can lead to a RAP1-mediated increase in LFA-1 binding, which can induce migration [152]. This has potential implications for considering which form of ICI would best work with a tumor where T cell trafficking poses a significant challenge. An overview of the metabolic pathways limiting T cell efficacy in glioblastoma is shown in Figure 2.

Another mediator of T cell glycolysis is the PI3K/AKT/mTOR pathway, whose activation can also downregulate the expression of adhesion and migration molecules CD62L, CCR7, and S1P1 in CD8<sup>+</sup> T cells [142,153]. Loss of S1P1 has been shown to mediate T cell sequestration in bone marrow in glioblastoma, while S1P1+ cells are resistant to sequestration and can return into the circulation [142,154–156]. Therefore, reversing sequestration will be critical for future immunotherapy efficacy and is currently the subject of ongoing therapeutic investigation [157]. While one approach may be to inhibit the PI3K/AKT/mTOR pathway, this inhibition must be selective, as AKT possesses three isoforms which have varying pro- and anti-tumor effects. AKT signaling also plays an important role for the development of effector-like memory CD8<sup>+</sup> T cells necessary for tumor immune surveillance [158]. Interestingly, recent work has described small-molecule inhibitors that may be capable of targeting pathogenic AKT isoforms only (AKT1 and AKT2) while leaving the tumor-suppressive functionality of AKT3 intact [159,160]. Indeed, specific AKT1 and 2 inhibition has been associated with enhanced central memory CD8+ T cell proliferation with prolonged cytokine and Granzyme B production, making this a potential future therapeutic strategy [158–161].

**Figure 2.** Glioblastoma effects on T cell metabolism and motility. As a rapidly dividing tumor, glioblastoma rapidly takes up glucose and produces lactate (the Warburg effect). Lack of glucose results in decreased GLUT1 binding (also downregulated by CTLA4) and downregulates effector function and motility. Increased lactate is internalized in T cells, where it also inhibits glycolysis and interferes with cytoskeleton rearrangement, resulting in decreased T cell migration. Produced using Biorender.

#### **6. The Tumor Microenvironment**

Once T cells traffic past the BBB and through the parenchyma, they will encounter the highly immunosuppressive tumor microenvironment. This is made up of regulatory T cells (CD4+CD25+FOXP3+), tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), as well as other stromal cells such as GSC-derived pericytes [23,162]. These can all work to suppress effector T cell function. Regulatory T cells induce T cell exhaustion and apoptosis, signaling via programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), lymphocyte activation gene 3 (LAG-3), T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), and others [163,164]. They also can dampen the production of inflammatory cytokines and CTL proliferation by downregulating interleukin-2 and interferon-γ [165]. Gliomas are adept at recruiting regulatory T cells to the microenvironment by over-production of factors such as indoleamine 2,3 -dioxygenase-1 (IDO-1) [166]. As mentioned previously, GSC-derived pericytes also secrete CCL5, which can promote the recruitment of regulatory T cells to the TME [54]. Stromal cells in the microenvironment also produce highly immunosuppressive cytokines, such as transforming growth factor β (TGFβ) and interleukin-10 (IL-10) [167,168].

Despite the numerous targets for blockade, it is notable that ICI and the interruption of pro-tumor metabolic pathways have failed as a monotherapy [9,169]. Increasingly, attention is turning towards combinatorial therapies, where multiple drivers of T cell exhaustion can be blocked simultaneously [170]. This includes using bispecific antibodies against TGF-β and PD-L1 or against PD-L1 and the anti-agonist CD27 [171–173]. These approaches

are currently being evaluated in Phase I trials in advanced solid tumors (NCT04429542, NCT04440943). Cytokine modulation approaches are also a potential avenue for enhancing T cell activity in the TME, as seen in 'armored' CAR-T constructs. The addition of IL-12, IL-15, or IL-18 along with antigen specificity to T cells appears to result in greater CTL activity and anti-tumor efficacy [174–176]. A high percentage of regulatory T cells in the peripheral blood of GBM patients express CCR4 compared to controls (74 vs. 43%) [135]. CCL4 binds CCL22 (and others), which has been shown to be overexpressed in freshly resected human glioma cells, and blockade of CCR4 in vitro can significantly reduce regulatory T cell migration [135]. Targeting fibroblast activation proteins or introducing heparinase-expressing agents may also help to disrupt immunosuppressive stromal elements [146,177,178]. Intratumoral APCs are also necessary to stimulate and retain infiltrating lymphocytes at the tumor site, as well as carrying antigens to draining lymph nodes and cross priming peripheral CD8 T cells [179–181]. The administration of intratumoral FMS-like tyrosine kinase 3 ligand (Flt3L) and poly I:C has been shown to expand and mature dendritic cell precursors, resulting in greater antitumor efficacy when combined with immunotherapies such as PD-L1 blockade or oncolytic herpes simplex viruses [179,182].

Standard-of-care therapies also can help drive a more potent immune response. Temozolomide (TMZ) is an alkylating chemotherapy whose main function is to induce DNA double-stranded breaks, resulting in tumor cell death [183]. Interestingly, TMZ can also help to reduce the numbers of peripheral regulatory T cells, as well as interrupting their migration [136,184]. In disease states such as glioblastoma, tumor cells and platelet-derived growth factor receptor beta (PDGFRβ)-expressing cells of the neurovascular sub-units (such as pericytes and perivascular fibroblast-like cells) produce CCL2 to recruit regulatory T cells and dampen the effector response [185]. TMZ interrupts the CCL2–CCR4 axis, thereby reducing this effect [136,184]. Combining immunotherapy with radiotherapy also can help to polarize the T cell response to a cytotoxic phenotype by inducing greater T cell receptor diversity and expanding the numbers of tumor-infiltrating lymphocytes and effector memory T cells [186]. In pre-clinical murine models of glioma, radiotherapy combined with antibodies against markers of exhaustion such as TIM-3 and PD-1 was able to produce long-term survival [11].

#### **7. Modeling the BBB**

Animal and in vitro models have contributed greatly to our knowledge regarding the cell and protein interactions required to cross the BBB. Rudimentary animal models from the 1980s first established how BBB permeability could change in response to systemic compounds by tracking the CNS uptake of Evan's Blue dye following intravenous infusion [187–190]. These models established protocols to visualize membrane cellular components and tissue hierarchy through fluorescent microscopy and histology, allowing for the elucidation of fundamental mechanisms behind membrane permeability. Such models included mice with proteins essential for T cell chemotaxis across the BBB knocked out, including tight junction proteins claudin 5 [100] and occludin [191]. Unfortunately, full knockout of these proteins results in non-viable pups or other dysfunctional phenotypes, suggesting the importance of tight junction proteins in development. Additional knockout mice focusing on proteins involved in T cell rolling, p-selectin, and its ligand PSGL-1 [192] were developed and confirmed less BBB breakdown and leukocyte trafficking into the CNS. Similarly, the use of antibody natalizumab to block the α4 subunit on T cells has been successful in preventing BBB chemotaxis in MS [193]. Genetic models targeting pericyte and astrocyte function have also been generated to establish how these cell types support BBB formation in development and regulate tight junctions in injury and disease. The use of two-photon microscopy has allowed for imaging at depths up to 1mm, but real-time high-resolution imaging and cell tracking capabilities are limited. Animal models closely mimic BBB features by including all cell types within the vascular interface, fluid flow and biochemical concentrations. However, there are still challenges translating in vivo finding to clinical significance. Genetic, molecular, and immunological differences between

humans and rodents, as well as high cost and ethical concerns with animal testing, have generated a need for robust in vitro models.

In vitro models of the BBB range from simple endothelial cell monolayers to complex three-dimensional systems with fluid flow and ionic gradients [194,195]. These models have the advantage of using human cells as well as being cost effective and allowing for high-throughput screening of a variety of different conditions or molecules. Transwell, hydrogels, and microfluidic devices with three or four different cell types have been created in attempts to best mimic native BBB function. Simplified in vitro models allow for researchers to specifically modify or track elements of the BBB. Cell types used in these models have traditionally been primary brain endothelial cells or immortalized cell lines. Immune factors affecting BBB permeability have been most studied with BECs due to their accurate expression of chemokine and cytokine receptors. Interestingly, these models found CCL2 to cause redistribution of tight junction proteins, such as claudin-5 and occluding, under physiological and pathological conditions [196,197], which gives insight into the mechanism of increased T cell chemotaxis during inflammation and elevated CCL2. Brain-cancer-specific models have focused on integrating vasculature and tumor cells to test the toxicity of therapeutics prior to animal studies [198,199]. These models recapitulated the three-dimensional structure of a brain tumor but used lung fibroblasts, HUVECs, and gelatin, which may not accurately represent the blood–brain barrier and brain microenvironment. The development of induced pluripotent stem cells (iPSCs) has allowed for genetically identical personalized in vitro models to test drug and cell interactions with BBB of specific individuals and disease conditions [200]. Overall, both in vivo and in vitro models of the BBB have limitations but can provide valuable insight to improve T cell chemotaxis in GBM.

#### **8. Safety**

While this review has largely focused on strategies by which T cells can be recruited and restored to a cytotoxic effector status, it must be noted that rapid increases in activated T cells in the circulation can potentially lead to cytokine release syndrome (CRS), mediated by the release of pro-inflammatory cytokines such as IL-6 [201]. Therefore, when considering therapies that will increase circulating activated T cells and subsequent CNS T cell infiltration, careful consideration must be given to the safety of any such approach. Such therapies may lead to systemic and neurological complications, even when not used specifically to treat CNS malignancies.

This is demonstrated by the example of clinically used therapeutics such as ipilimumab, which re-invigorates T cells by blockade of CTLA-4 [202]. Ipilimumab has been associated with pituitary inflammation (hypophysitis), occurring in up to 17% of patients receiving ipilimumab treatment [203,204]. Similar syndromes are also observed when using anti-PD-1 and anti-PD-L1 therapies, albeit at a lower frequency compared to anti-CTLA-4 [205]. The mechanism of how ipilimumab causes hypophysitis remains unclear, but it is speculated that ipilimumab can release the brakes on T cells that target and destroy pituitary cells, or that expression of CTLA-4 on pituitary cells leads to complement fixation mediated by ipilimumab, resulting in the destruction of pituitary cells [206,207]. In rarer circumstances (less than 0.2% of patients), ICI, especially ipilimumab or combination ipilimumab/nivolumab (anti-PD-1), has caused aseptic meningitis and encephalitis [208–212]. Like with hypophysitis, the exact mechanism is unclear. However, in the case of encephalitis, there is evidence that the effect is autoimmune in origin, as some patients treated with ICI exhibit autoantibodies to the NMDA receptor, a characteristic of other autoimmune encephalopathies [213,214]. ICI has also reportedly induced new CNS demyelination and exacerbated existing CNS demyelination in MS patients [215,216]. These rare, but serious neurological deficits resulting from systemic ICI emphasize the need for careful monitoring of patients receiving therapies that enhance T cell trafficking and function.

The experience of treatments using adoptively transferred chimeric antigen receptor (CAR) T cells in extracranial and intracranial malignancies can also be illustrative for potential systemic and neurological toxicities. The most common CAR-related toxicity is cytokine release syndrome (CRS), occurring in up to 37–93% of patients with lymphoma or leukemia receiving CD19 CARs [217]. As described previously, CRS is caused by rapid activation of CAR T cells upon administration and subsequent release of pro-inflammatory cytokines, such as IL-6 [201]. High levels of serum IL-6 were found to correlate with severe CRS, which led to the FDA approval of tocilizumab, an anti-IL-6 receptor antagonist [218]. Strategies to reduce CRS include administering lower doses of CAR T cells over multiple infusions as opposed to one single bolus [219,220].

Neurological-specific toxicities after CAR administration are also possible. Immune effector cell-associated neurotoxicity syndrome (ICANS) can develop in around 50% of patients following systemic CAR infusion [221]. ICANS manifests with minor symptoms such as lethargy and confusion but can also cause seizures and coma. The pathophysiology of ICANS remains unclear, but evidence suggests that release of pro-inflammatory cytokines, such as IL-6 and IL-1β, by CAR T cells can disrupt the BBB, resulting in the accumulation of CAR T cells and pro-inflammatory cytokines in the CNS [222]. Klinger et al. recently described a mechanism whereby CD19 bi-specific T cell engagers (blinatumomab) can induce T cell adhesion to endothelial cells of the BBB followed by T cell migration into the perivascular space in a CD19-independent manner. Once past the BBB, they may encounter rare target CD19 cells in the CNS and release pro-inflammatory cytokines, triggering ICANS-like symptoms [223]. However, unlike CRS, ICANS does not respond to tocilizumab treatment, and symptoms are typically managed with corticosteroids or cessation of therapy [224]. Klinger et al. also reported that the non-specific entry of CD19 T cells into the CNS could be abrogated by the administration of anti-adhesion agents (anti-VLA4, natalizumab), offering another potential therapeutic if toxicity occurs [223]. In summary, while enhanced T cell chemotaxis and infiltration of glioblastoma are necessary for effective immune-mediated treatment of tumors, this must be carefully balanced with the risks described above.

#### **9. Conclusions**

For immunotherapy in glioblastoma to be successful, sustained recruitment of effector lymphocytes from the periphery to the tumor is necessary. However, achieving this in a unique immune environment such as the CNS must overcome both physical and chemical barriers. In this review, we have described the process by which effector T cells can be recruited from the periphery and what modifications may result in a pro-infiltrative phenotype. We have described both T cell and BBB factors that would be desirable therapeutic targets and set out strategies by which this may be achieved. Adhesional factors on the BBB endothelium such as ICAM-1, VCAM-1, or ACKR1 may be upregulated by IL-1β or IFN-γ, which can be delivered via convection-enhanced delivery (CED) directly to the tumor site. Delivery of these cytokines and other inflammatory factors can have profound effects on increasing BBB penetration and the migration potential of T cells. Induced expression of CXCL10 by using poly-ICLC can also interact with CXCR3 on effector T cells, prompting their infiltration into tumor. Co-culture with IL-12 may help drive the expression of key integrins such as LFA-1 on the surface of T cells in preparation for adoptive transfer to further enhance their adhesive capabilities. CCL2 and CCL5 may promote paracellular diapedesis through tricellular junctions in the BBB endothelium, while TGF-β priming of T cells can increase their CCR6 expression, which can promote transcellular crossing. However, CCL2 and CCL5 may also mediate regulatory T cell recruitment, perhaps necessitating co-administration with checkpoint blockade. Subsequent navigation through the glia limitans may be aided by IL-17-mediated downregulation of CXCL12, although this may be a location-specific effect. Once inside the parenchyma, lymphangiogenesispromoting factors such as VEGF-C may further enhance trafficking of T cells to the tumor. Metabolic mediators such as the PI3K/AKT/mTOR pathway may also be therapeutically

targeted using small-molecule inhibitors of the AKT1 and AKT2 isoforms. Combinatorial approaches to stimulate T cells and block checkpoint inhibition will likely be necessary to overcome the microenvironment. This may be achieved using novel bispecific constructs or co-administration with immune stimulatory cytokines such as IL-12, IL-15, or IL-18. Standard-of-care therapies such as TMZ and radiotherapy may also help to blockade regulatory T cell recruitment and drive a more diverse and potent T cell response. Importantly, however, any approach that enhances T cell infiltration into the CNS must consider safety, and although there are therapeutic options for adverse events, future trial designs using pro-infiltrative therapies should err on the side of caution. Nevertheless, enhanced T cell trafficking and infiltration of glioblastoma is essential for immunotherapeutic efficacy. While ICI seeks to 'release the brakes' on T cell activity, in the case of glioblastoma, we must first drive T cells to the tumor.

**Author Contributions:** K.S., writing—original draft preparation, review and editing, visualization, project administration, revision. K.M.H., writing—original draft preparation, review and editing, visualization, revision. K.K.P., writing—original draft preparation, D.S.W., writing—original draft preparation. A.A.M., visualization. S.L.C., writing—review and editing. J.H.S., supervision. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by grants from the National Institutes of Health (NIH) (U01NS090284 (JHS) and P50CA190991(JHS)).

**Conflicts of Interest:** K.S., K.M.H., K.K.P., D.S.W., A.A.M. and S.L.C. report no conflict of interest. J.H.S. has an equity interest in Istari Oncology, which has licensed intellectual property from Duke related to the use of poliovirus and D2C7 in the treatment of glioblastoma. J.H.S. is an inventor on patents related to the PEP-CMV DC vaccine with tetanus, as well as the poliovirus vaccine and D2C7 in the treatment of glioblastoma. J.H.S. has an equity interest in Annias Immunotherapeutics, which has licensed intellectual property from Duke related to the use of the pepCMV vaccine in the treatment of glioblastoma.

#### **References**

## *Article* **Multi-Platform Classification of IDH-Wild-Type Glioblastoma Based on ERK/MAPK Pathway: Diagnostic, Prognostic and Therapeutic Implications**

**Maria-Magdalena Georgescu**

NeuroMarkers PLLC, Houston, TX 77025, USA<EMAIL_ADDRESS>Tel.: +1-281-433-0492

**Simple Summary:** This study presents a unified classification of glioblastoma that streams multiplatform data from genomic, transcriptomic, histologic, and demographic analyses into targetable glioblastoma subgroups connected by signaling through canonical growth pathways. This structured and clear analysis addresses the current needs of neuro-oncological practice and offers practical guidelines for the diagnosis, prognosis, and therapeutic targeting of glioblastoma, being thus of great benefit to both patients and brain tumor practitioners alike.

**Abstract:** Glioblastoma is the most aggressive and frequent glioma in the adult population. Because current therapy regimens confer only minimal survival benefit, molecular subgrouping to stratify patient prognosis and therapy design is warranted. This study presents a multi-platform classification of glioblastoma by analyzing a large, ethnicity-inclusive 101-adult-patient cohort. It defines seven nonredundant IDH-wild-type glioblastoma molecular subgroups, G1–G7, corresponding to the upstream receptor tyrosine kinase (RTK) and RAS-RAF segment of the ERK/MAPK signal transduction pathway. These glioblastoma molecular subgroups are classified as G1/EGFR, G2/FGFR3, G3/NF1, G4/RAF, G5/PDGFRA, G6/Multi-RTK, and G7/Other. The comprehensive genomic analysis was refined by expression landscaping of all RTK genes, as well as of the major associated growth pathway mediators, and used to hierarchically cluster the subgroups. Parallel demographic, clinical, and histologic pattern analyses were merged with the molecular subgrouping to yield the first inclusive multi-platform classification for IDH-wild-type glioblastoma. This straightforward classification with diagnostic and prognostic significance may be readily used in neuro-oncological practice and lays the foundation for personalized targeted therapy approaches.

**Keywords:** glioblastoma molecular classification; ERK/MAPK pathway; PI3K/PTEN pathway; receptor tyrosine kinase; EGFR; PDGFRA; FGFR3; MET; EPHB2; NF1

#### **1. Introduction**

Glioblastoma is the most frequent malignant primary brain neoplasm in adults, with an incidence of 3–4 cases per 100,000 population, and 41% survival at 1 year [1]. The 2016 World Health Organization (WHO) Classification of Tumors of the Central Nervous System recognizes IDH-wild-type and IDH-mutant glioblastomas as separate molecular entities, with significant survival differences [2]. IDH-wild-type glioblastomas comprise over 90% of glioblastomas and show *TERT* promoter mutations, *CDKN2A/B* homozygous loss, *EGFR* amplification, *TP53* and *PTEN* mutations, as most frequent common and mostly concurrent alterations [2]. These mutations address basic cancer cell maintenance requirements: telomere extension by *TERT* overexpression, cell cycle progression by *CDKN2A/B* cell cycle-dependent kinase (CDK) 4/6 inhibitors loss and *TP53* alterations, the latter being also involved in gatekeeping the DNA-damage response (DDR), and cell survival by inactivation of PTEN, the main inhibitor of the phosphatidyl inositol 3-OH kinase (PI3K) proliferative and anti-apoptotic pathway [3,4]. EGFR is the most frequently altered receptor

**Citation:** Georgescu, M.-M. Multi-Platform Classification of IDH-Wild-Type Glioblastoma Based on ERK/MAPK Pathway: Diagnostic, Prognostic and Therapeutic Implications. *Cancers* **2021**, *13*, 4532. https://doi.org/10.3390/ cancers13184532

Academic Editor: Edward Pan

Received: 20 July 2021 Accepted: 7 September 2021 Published: 9 September 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

tyrosine kinase (RTK) in glioblastoma, but amplification and activating mutation or fusions have been also reported in other RTKs, such as PDGFRA, MET, FGFR, and NTRK1 [2].

The RTKs are categorized into 19 well-defined classes based on sequence and structural similarity of their ligand-binding extracellular domains [5]. The intracellular domains contain the highly homologous tyrosine kinase domain and more specific juxtamembrane and carboxyl (C)-terminal regions that contain tyrosine motifs. Upon ligand binding leading to RTK dimerization and activation, the phosphorylation of tyrosine motifs triggers the activation of downstream signaling pathways by docking SH2-domain-containing adaptor and enzymatic proteins. The extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) and PI3K/AKT/mTOR are two parallel signaling pathways controlling proliferation, survival, metabolism, and invasion of cancer cells that are commonly activated by RTKs, whereas Src, STAT, and phospholipase C-γ pathways are additional pathways activated by most RTKs.

There are four conventional MAPK families: ERK1/2, p38, JUNK, and ERK5, all phosphorylated and activated by upstream kinases or MAP2Ks, in turn, phosphorylated and activated by a third layer of upstream MAP3Ks [6]. Within the ERK1/2 MAPK cascade, RTKs activate Ras, which, in its active GTP-bound form, binds and activates Raf kinases (MAP3K), which activate MEK1/2 (MAP2K), which further activate ERK1/2 (MAPK). Phosphorylated ERKs translocate to the nucleus to activate transcription factors or remain cytoplasmic to activate substrates involved in cell growth. The pathway is negatively controlled upstream by direct inhibition through NF1, a Ras GTPase-activating protein (GAP) but also by feedback loops resulting from ERK-dependent transcription of the ERK phosphatases DUSP4/5/6 and the Sprouty family members [7–10]. In contrast, the PI3K/AKT/mTOR pathway is a heterogeneous pathway involving both protein and lipid signal transduction mediators and is directly inhibited by the PTEN tumor suppressor, acting upstream as phosphoinositide phosphatase counteracting the effect of PI3K [3].

By using an integrated approach interrogating a controlled glioblastoma patient cohort, I propose a simplified multi-platform classification of glioblastoma tailored to map the ERK/MAPK pathway activation, with important implications for precision therapy.

#### **2. Materials and Methods**

Tumor specimens, histology and, immunohistochemistry (IHC): Surgical resection, biopsy or autopsy specimens were obtained from patients with glioblastoma, as previously described, in accordance with hospital regulations [7,11,12]. With one exception, the IDH-wild-type cases illustrated in this study correspond to first-diagnosis, untreated tumors. Formalin-fixed paraffin-embedded (FFPE) sections were stained with hematoxylineosin (H&E). Images were acquired with the Nikon Eclipse Ci microscope equipped with the Nikon Digital Sight DS-Fi2 camera (Nikon Instruments Inc., Melville, NY, USA), as previously described [13]. For histologic pattern analysis, digital images were acquired from all cases at various magnifications. Representative tumor fields were chosen, aiming at the viable tumor core, away from areas of necrosis and normal brain interface. The images were processed in batch for level adjustment and displayed stacked in an extended image library for comparison. For difficult patterns, both digitalized images and slides were cross-examined. IHC was performed on selected sections, as described [11,13]. The following primary antibodies were used: histone H3-K27M (Millipore/Sigma, Burlington, MA, USA), IDH1-R132H (DIA-H09, Dianova, Hamburg, Germany), p53 (DO-7), Ki-67 (30-9) (Roche/Ventana Medical Systems Inc., Tucson, AZ, USA), GFAP (EP672Y) (Ventana/Cell Marque, Rocklin, CA, USA).

Next-generation sequencing (NGS) and copy number (CN) variation: Nucleic acids were extracted from FFPE samples, as previously described [11]. Variant analysis and interpretation following NGS using the xT 596-gene or xE whole-exome panels (Tempus Labs, Chicago, IL, USA) or the customized 295-gene panel were performed as previously described [7,11,12]. CN analysis was performed as previously described [7,14]. Gene amplification was called for CN ≥ 7, and loss of heterozygosity (LOH) for alterations with loss of one allele. The tumor mutation burden is expressed as single-nucleotide protein-altering mutations per megabase DNA. The MGMT promoter methylation assay was performed by quantitative methylation-specific PCR using DNA extracted from FFPE samples (Integrated Oncology, Phoenix, AZ, USA).

Transcriptomics: Whole transcriptome RNA sequencing with RNA fusion detection was performed at Tempus Labs for all glioblastoma samples with more than 30% tumor on FFPE sections as described [7]. The expression was analyzed by a proprietary protocol. Briefly, the threshold for total RNA counts was set at ≥500 in at least one tumor sample, and pseudogenes and Y-chromosome genes were excluded. A ≥5-fold overexpression threshold was set for the average tumor values from subgroups relative to precursor low-grade control values, as previously described [7].

Statistical analysis: Differences between groups were assessed by using unpaired two-tailed *t*-test with or without Welch's correction for variances significantly different, as described [15]. Multivariable correlation matrices and hierarchical clustering were generated for the glioblastoma subgroups by using the Pearson correlation coefficient. Kaplan–Meier survival analyses using the Log-rank (Mantel–Cox) test were performed as previously described [16,17]. Statistical significance was considered for *p* < 0.05. Confidence intervals for all tests were 95%. The graphic, statistic, and hierarchical clustering software included Microsoft Excel (Microsoft Corp., Redmond, WA, USA), GraphPad Prism (Version 8.3.0, GraphPad Software, La Jolla, CA, USA), and Instant Clue [18].

#### **3. Results**

#### *3.1. Non-Redundant Molecular Classification of Glioblastoma Based on ERK/MAPK Pathway*

The tumors from a 101-adult-patient cohort with WHO grade IV diffuse glioma were initially classified based on IHC into IDH wild-type glioblastoma (90 cases), IDH-mutant glioblastoma (eight cases), and diffuse midline glioma (DMG) with histone H3 K27M mutation (three cases) (Figure 1A). NGS genomic results were obtained for 112 tumors from 97 patients and whole transcriptomics results were obtained for 82 tumors from 70 of these patients. The integrated genomic and transcriptomic analysis of the tumors showed *EGFR*, *PDGFRA*, *FGFR3*, *NF1*, and *BRAF/RAF1* mutually exclusive alterations within the glioblastoma IDH-wild-type category (Figure 1 and Table S1). An additional subgroup, Multi-RTK, showed alterations in multiple RTKs, including *MET*. The combined NF1, RAF, and RTK alterations from EGFR, PDGFRA, FGFR3, and Multi-RTK subgroups that activate the ERK/MAPK signaling pathway (Figure 1B) accounted for 85% of the glioblastoma IDHwild-type cases. In the remaining cases, alterations targeting the ERK/MAPK pathway were not found, and this subset, labeled as Other, represented approximately 15% of IDH-wild-type glioblastoma cases (Figure 1A).

The RTK subgroups accounted for 63.2% of the glioblastoma IDH-wild-type cases, and the EGFR subgroup alone, for 41.4%, being thus the largest of all glioblastoma molecular subgroups (Figure 1A). The vast majority of the EGFR tumors from 91.7% of EGFR subgroup cases harbored *EGFR* amplification (EGFR↑), and only three cases showed *EGFR* gain-of-function mutations without amplification (EGFRm) (Table S1). Two tumors, EGFR#5 and EGFR#33, were multifocal with the main focus showing *EGFR* amplification and a secondary focus showing *EGFR* mutation without amplification. Interestingly, the majority of tumors with *EGFR* amplification also showed another *EGFR* genetic alteration, such as the splice variants vIII, vIVa, pathogenic mutations with or without amplification, C-terminal deletion, or *EGFR-SEPT14*, *EGFR-VOPP1*, *CTDSP2-EGFR*, and *SEC61G-EGFR* fusions. The next largest RTK subgroups are the PDGFRA and Multi-RTK, each accounting for 8% (Figure 1A). *PDGFRA* amplification with or without adjacent *KIT* and *KDR* amplification was the most frequent genetic alteration in the PDGFRA subgroup, and was found in 85.7% of the PDGFRA subgroup cases. As observed for *EGFR*, simultaneous *PDGFRA* amplification and missense mutations were frequently noted (Table S1). A common type of missense mutation targeted the di-sulfide bond cysteines of the extracellular domains of both EGFR and PDGFRα. The Multi-RTK subgroup is an eclectic group harboring various

combinations of RTK alterations. It included three cases with *PDGFRA* amplification without overexpression. The smallest RTK subgroup is composed of cases with FGFR3 fusions or mutations (Table S1) and it has been characterized in detail elsewhere [7].

The NF1 and RAF subgroups accounted for almost one-quarter of the glioblastoma IDH-wild-type cases, with the NF1 subgroup being the second largest after the EGFR subgroup (Figure 1A). Two of the 15 NF1 cases were syndromic, and these patients presented other neurofibromatosis type 1 manifestations in addition to brain tumors. Almost all NF1 tumors had two *NF1* hits, either by different mutations or by LOH (Table S1). Twenty distinct *NF1* alterations were detected, most resulting in protein truncation. Among these, two *NF1* frameshift fusions were noted, underscoring the importance of fusion detection for correct classification in the NF1 subgroup. All four tumors in the RAF subgroup also showed distinct gain-of-function mutations, three in *BRAF*, and one in *RAF1*, the latter accompanied by gene amplification (Table S1).

The landscape of RTK expression in the glioblastoma subgroups was compiled by examining the relative expression levels of all the members from the 19 RTK classes (Table S2 and Figure S1). In the EGFR subgroup, *EGFR* high overexpression was associated with gene amplification in all but one case, with an average of 26 ± 3.7 and a range between 4.5- and 72-fold overexpression (Figure 1C,D). Conversely, low or no *EGFR* overexpression characterized the samples displaying activating *EGFR* gain-of-function mutations in the absence of amplification, indicating a strong correlation between *EGFR* amplification and overexpression in the EGFR subgroup. Moderate levels of EGFR overexpression were present in some cases of the Multi-RTK subgroup, and only in isolated cases in other subgroups, in the absence of gene amplification. In contrast to *EGFR*, only two-thirds of the cases with *PDGFRA* amplification showed overexpression, with an average of 16.8 ± 3 and a range between 4.9- and 25.7-fold (Figure 1C,D). The remaining one-third of cases were classified in the Multi-RTK subgroup, as they showed genetic alterations and/or overexpression of other major RTKs, most commonly *MET*, but also *EGFR*, *KIT*, *FGFR2*, *NTRK1*, *EPHA3*, and *EPHB2* (Figure 1C,D and Table S1). The *KIT* and *KDR* gene loci are contiguous with the *PDGFRA* locus, and their amplifications showed generally the same expression trend as *PDGFRA*, except for the Multi-RTK#1 case that showed high *KIT* overexpression in the absence of gene amplification. *MET* amplification was detected in two cases from the Multi-RTK subgroup and correlated with over 40-fold expression levels. Relatively high *MET* overexpression levels were also noted in four additional cases, ranging from 5.4- to 28-fold, without amplification but with low CN gain on chromosome 7. In the PDGFRA#4 case, *MET* overexpression was most likely caused by the presence of a *PTPRZ1-MET* fusion, as *PTPRZ1* is among the highest expressed genes in glioma, and the fusion places *MET* under the control of the *PTPRZ1* promoter (Table S1). *FGFR2* was the only other RTK with amplification and very high overexpression in the cohort, and the IDH#1 case harboring it has been previously described [7].

**Figure 1.** Glioblastoma molecular subgroups—molecular characteristics and pathway-based clustering. (**A**) Subgrouping of the glioblastoma cohort in non-overlapping molecular alterations corresponding to ERK/MAPK signaling pathway. (**B**) Diagram of the canonical ERK/MAPK and PI3K signaling pathways. Inhibitors are indicated in purple; arrows and blunt arrows represent activation or inhibition, respectively. (**C**) RTK fold-expression in glioblastoma subgroups, as mean ± SEM values, showing RTKs with high or intermediate overexpression on the left or right *y*-axis, respectively. EGFR↑, EGFR with gene amplification; EGFRm, EGFR with mutation only; LGG CTR, low-grade glioma expression control subgroup. (**D**,**E**) Heatmaps of subgrouped individual tumors showing mutation–expression correlations for RTKs (**D**) and cell cycle G1 phase, p53, DDR and telomere elongation pathways (**E**). Colored or black squares mark presence of genomic alterations in the upper part of the heatmaps. Asterisk (\*) marks the multifocal EGFR#33 case with EGFR amplification in the main focus and EGFR mutation in the secondary focus, for which the expression profile is shown. Genes boxed in pink show expression data. MGMT promoter methylation (meth) is also shown, with positive values ≥ 5. ND, not determined. (**F**) Heatmap of % cases with indicated alterations grouped in pathways, based on the values from Table 1 for the glioblastoma subgroups. ↑, gene amplification (CN ≥ 7); ↓, homozygous loss; ChRm, chromatin remodeling. The gene composition of the DDR and ChRm pathways is described in Table 1. Mean CDK6 and proliferation markers expression values are also included. (**G**) Hierarchical clustering of glioblastoma subgroups by multivariable Pearson correlation analysis. Note two subgroup clusters #1 and #2, and individual segregation of the PDGFRA, EGFRm and IDH subgroups.

**Table 1.** Mutation percent (%) frequency in glioblastoma subgroups.

Wt, wild-type; ↑, gene amplification; ↓, homozygous CN loss; m, point mutation; path, pathway; DDR, DNA damage response; MMR, mismatch repair; ChRm, chromatin remodeling; methyl, methylation. The highest % for a certain alteration is indicated in bold. <sup>1</sup> % cases with cumulated *TERT* promoter mutation and *TERT* overexpression in the absence of mutation. The value in brackets corresponds to the total % cases with *TERT* promoter mutations only. <sup>2</sup> % cases with at least one alteration in *PTEN*, *PIK3CA*, *PIK3R1*, *TSC2*, or *MTOR*. <sup>3</sup> % cases with *CDKN2A* homozygous loss, *CDK4* amplification, or *RB1* mutation. <sup>4</sup> % cases with *TP53, MDM2*, *MDM4*, *RPL5*, and *PPM1D* alterations. <sup>5</sup> % cases with either *MSH6*, *MSH5*, *PMS2*, or *MLH3* pathogenic mutations. <sup>6</sup> % cases with at least one alteration in *ATM*, *BRCA2*, or MMR genes. <sup>7</sup> % cases with SWI/SNF complex *ARID1A*, *ARID1B*, *ARID2*, *SMARCA1*, *SMARCA4,* or *PBRM1* pathogenic mutations. <sup>8</sup> % cases with either *YEATS4* amplification or *DNM3TA*, *TET2*, *EZH2*, *SUZ12*, *ASXL1*, *ASXL2*, *KDM5C*, *KDM6A*, *KMT2C*, *KMT2D,* or *CREBBP* pathogenic mutations.

> A number of RTKs showed >5-fold overexpression in some cases in the absence of gene amplification (Figure 1C,D and Figure S1). The other three members of the EGFR RTK class appeared upregulated differentially in the various glioblastoma subgroups, with *ERBB2* mild overexpression in the EGFR subgroup, especially associated with EGFRm cases, *ERBB3* mild overexpression in PDGFRA and Other subgroups, and *ERBB4*, in the IDH subgroup. *NTRK1* was upregulated in isolated cases in almost all glioblastoma subgroups but more prominently in the two cases with RNA expression data from the RAF subgroup. *NTRK1* genetic alterations were noted in only one case, the Multi-RTK#7 that showed *LMNA-NTRK1* fusion. Two of the ephrin class RTKs, *EPHA3*, and *EPHB2*, also showed overexpression in scattered cases across the glioblastoma subgroups but more prominently in the Multi-RTK and PDGFRA subgroups, respectively. Similarly, *ALK* showed overexpression in a few isolated cases and more clustered in the NF1 subgroup. Three EGFR cases also showed *ALK* variants of unknown significance or likely pathogenic (Table S1). Interestingly, *KDR*, besides the 10-fold overexpression in the cancer cells from the PDGFRA#4 and #6 cases with gene amplification, showed mild to moderate overexpression without gene amplification, with a 7.7-fold upper range, in the majority of cases from many subgroups. Most likely, this overexpression stems from the endothelial compartment, reflecting the active vascular proliferation program in these tumors. Interestingly, the pseudokinase RTKs PTK7, ROR1, and ROR2 that activate the Wnt pathway rather than the

canonical MAPK and PI3K pathways [19] were mildly to moderately overexpressed in all glioblastoma subgroups (Figure S1).

#### *3.2. Glioblastoma Subgroup Clustering Based on Pathway Analysis*

The most frequent genetic alterations from glioblastoma were mapped to the different molecular subgroups (Table 1). *TERT* promoter mutations were the most frequent alteration, accounting for 81.2% of cases. *TERT* overexpression usually correlated with promoter mutations but also showed high values in a few cases without *TERT* promoter mutations (Figure 1E). *ATRX* mutations were rare and mostly complementary to *TERT* mutations. In general, *TERT* overexpression was the main mechanism of telomere elongation in IDH wildtype glioblastoma, except for the PDGFRA subgroup. The PI3K/mTOR canonical pathway showed genomic alterations in 76% of IDH-wild-type glioblastoma cases, mainly through *PTEN* mutations in 53% of cases (Table 1). The *PTEN* alterations peaked in the FGFR3, Multi-RTK, and Other subgroups. In contrast, *PIK3CA* mutations were rather clustered in the EGFR subgroup, and *PIK3R1* mutations, in the PDGFRA and NF1 subgroups.

Mutations in the cell cycle G1 phase genes *CDKN2A/2B*, *CDK4*, and *RB1* were mutually exclusive in this series, except for two heterozygous germline *RB1* point mutations, and were present in 79.3% of glioblastoma IDH-wild-type cases (Table 1 and Figure 1E). With one exception in the FGFR3 subgroup previously discussed [7], all *CDKN2A* homozygous losses were extended to the *CDKN2B* adjacent gene. Moreover, there was a perfect correlation between *CDKN2A/2B* homozygous loss and decreased RNA expression levels, although decreased levels were also seen in the absence of gene loss in two IDH-wildtype and one IDH-mutant glioblastoma cases. The type of mutated G1 phase gene was relatively specific in some subgroups. In particular, in the EGFR subgroup, EGFR↑ cases showed preferential *CDKN2A/2B* homozygous loss and EGFRm cases showed *RB1* inactivating mutations with LOH. The cases with *CDK4* amplification clustered in the Other subgroup that contained six of the ten total IDH-wild-type glioblastoma cases with *CDK4* amplification. This subgroup also presented cases with *RB1* mutation and only a minority with *CDKN2A/2B* loss. *CDK4* amplification correlated perfectly with overexpression. The other G1 phase kinase gene, *CDK6*, showed overexpression in the absence of genomic abnormalities especially in the PDGFRA, EGFR↑, and FGFR3 subgroups (Figure 1E,F).

The p53 cell cycle and cell proliferation gatekeeping pathway, defined here by mutations in *TP53* itself, as well as mutually exclusive mutations in *MDM2*, *MDM4*, *RPL5*, and *PPM1D*, was altered in approximately half of the IDH-wild-type and all IDH-mutant glioblastoma cases (Table 1 and Figure 1E). The *CDKN2A* gene locus also encodes p14ARF, a regulator of MDM2 that promotes its degradation and therefore stabilization of p53 [20]. With the exception of the NF1 and IDH subgroups, mutations in *TP53* tended to occur in the cases without *CDKN2A* loss, explaining the inverse relationship in mutation frequency between *TP53* and *CDKN2A* in most subgroups. Interestingly, *MDM4* mutations clustered in the EGFR subgroup and *MDM2* mutations were exclusively noted in the non-EGFR subgroups. Mutations in DDR genes *ATM* and *BRCA2* and in mismatch repair genes were clustered in the PDGFRA, IDH, and FGFR3 subgroups, respectively. In contrast, mutations of *STAG2*, encoding a subunit of the cohesin complex controlling sister chromatid separation during cell division, were scattered among almost all glioblastoma subgroups. Gene mutations in multiple chromatin remodeling mediators were present in all FGFR3 cases, and mutations especially in components of the SWI/SNF complex were noted in over half of IDH subgroup cases.

Overall, the tumor mutation burden of the subgroups was similar, with median values between 2.8 and 5.8 mutations/megabase DNA (Figure S2). Only three tumors representing 3.2% of the cohort had high tumor mutation burden values over 10 mutations/megabase DNA.

The relative specificity of mutation partition prompted the assembly of a correlation matrix for glioblastoma subgroup hierarchical clustering (Figure 1F). Besides gene mutations in the pathways discussed above, and *CDK6* average expression, two additional

parameters were included, *MGMT* promoter methylation and proliferation. As compared to roughly half of the tumors in the Multi-RTK, FGFR3, RAF, but also EGFR↑ subgroups, none of the tumors from EGFRm or PDGFRA subgroups showed *MGMT* promoter methylation (Table 1 and Figure 1E). The extent of *MGMT* promoter methylation was also variable, with some tumors displaying only marginally positive values. The proliferation was assessed for the cases with expression data as a compound parameter, including the *MKI67* expression, and showed the highest average value in the PDGFRA subgroup (Figure S3). The distribution of the individual proliferation values in some subgroups was not gaussian, and especially for the EGFR↑ subgroup, two clusters could be separated, in correlation with *EGFR* overexpression values.

Hierarchical clustering showed the IDH subgroup separated from the IDH-wild-type subgroups, as expected (Figures 2G and S4). Surprisingly, the EGFRm subgroup was also isolated from other subgroups. Another subgroup that segregated sharply from the rest was the PDGFRA subgroup. Unexpectedly, the EGFR↑ and NF1 subgroups clustered with the highest correlation coefficient, followed by the RAF subgroup. The FGFR3 subgroup more distantly clustered with the former three subgroups, whereas the Multi-RTK and Other subgroups formed a separate molecular cluster.

**Figure 2.** Demographic analysis of glioblastoma subgroups. (**A**) Mean ± SEM of individual age values excluding the outliers indicated by arrows. Statistically significant differences between IDH-wild-type subgroups are indicated by asterisks. (**B**) Sex distribution in glioblastoma subgroups. (**C**) Ethnic/race distribution in glioblastoma subgroups. (**D**) Tumor location distribution showing hemispheric and midline locations, the latter encompassing basal ganglia, pineal gland, and cerebellum. Corpus callosum (CC) symmetric or asymmetric butterfly glioblastoma is shown separately. (**E**–**G**) Kaplan–Meier survival curves for the 7 IDH-wild-type glioblastoma subgroups (**E**), separated EGFR subgroups (**F**), and molecular clusters (**G**). Median survival and statistical significance (*p*-values and asterisks) are indicated.

#### *3.3. Glioblastoma Subgroup Demographic Characterization*

The IDH-wild-type glioblastoma subgroups showed generally similar age central tendency parameters, with median and mean age values ranging from 60 to 62 and 59.3 to 63.7 years, respectively, for the most numerous subgroups, except for the Multi-RTK subgroup that showed significantly higher values, with a median of 68 and mean of 70 years (Figure 2A). The median and mean age for the IDH subgroup coincided, at 42 years, significantly lower than for the IDH-wild-type glioblastoma subgroups, aligning with other reports [2]. The male-to-female sex distribution of IDH-wild-type cases was 1.57:1, comparable with the reported ratio [2], but there was a bias towards 100% females in the IDH-mutant subgroup compared to the 0.96:1 reported ratio, probably at least partly due to the small sample (N = 8) (Figure 2B). The main deviations from the male-to-female ratio were noted in the PDGFRA and FGFR3 subgroups that showed bias towards males or females, respectively. The cohort comprised mainly Caucasian/White and African-American/Black patients, at a white-to-black ratio of 4.67:1 for IDH-wild-type glioblastoma and 1.7:1 for IDH-mutant glioblastoma (Figure 2C). Most IDH-wild-type subgroups had a similar ratio to the main group, except for the EGFRm subgroup which stood out with two African-American/Black out of three patients.

In the adult glioblastoma cohort, all except for one NF1 cerebellar tumor were supratentorial. This contrasted with the three histone H3-K27M-mutant DMG cases, of which two were spinal. The IDH-wild-type cases were evenly distributed between the frontal lobe (30%), temporal lobe (30%), and other locations, of which the parietal lobe was preponderant (17%) (Figure 2D). Midline locations comprised thalamus/internal capsule, pineal gland, and cerebellum, and were relatively rare, except in the PDGFRA subgroup that contained two tumors in the thalamus/internal capsule. Corpus callosum butterfly location was considered a separate location, as patients showing these tumors fare poorly, and isolated cases were seen in the major subgroups, with two cases clustered in the NF1 subgroup. In general, the location distribution varied among subgroups, with a preponderance of frontal cases in the PDGFRA, Multi-RTK, and IDH subgroups (Figure 2D).

The survival, as measured from the first surgery until death, in the IDH-wild-type glioblastoma cohort was 37.9% at 1 year, slightly lower than the reported one of 41% [1], and the median survival was 9.5 months. The best median survival was noted in the FGFR3 subgroup, at 20 months, followed by EGFR and PDGFRA, at 12 months (Figure 2E). The two longest-surviving patients, reaching 7 years, had tumors mapping to the FGFR3 and EGFR subgroups. The poorest median survival was observed in the RAF subgroup, at 3.5 months, followed by the NF1, Multi-RTK, and Other subgroups, at 6.7, 7.5, and 10 months, respectively. Further examination of the EGFRm subgroup showed a median survival of 6 months (Figure 2F). The molecular cluster #1 showed survival heterogeneity, with the EGFR↑ and FGFR3 subgroups showing longer median survival, compounded at 14 months, and the NF1 and RAF subgroups showing significantly shorter median survival (*p* = 0.039), compounded at 5 months (Figure 2G). The molecular cluster #2 composed of the Multi-RTK and Other subgroups showed also significantly lower survival than the EGFR↑/FGFR3 combined subgroups (*p* = 0.039), with a compound value at 8 months.

#### *3.4. Enrichment of Histologic Patterns in Molecular Glioblastoma Subgroups*

The three WHO-recognized IDH-wild-type histologic variants, giant cell, gliosarcoma, and epithelioid [2], were scattered in the cohort at relatively low frequencies of 3.6%, 4.8%, and 6%, respectively (Figure 3A). The remaining samples were classified into nine additional patterns and further categorized on glioblastoma subgroups (Figure 3A). Four subgroups—EGFR, Other, NF1, and RAF—showed significant enrichment for a more specific pattern. The most frequent histologic pattern was seen in over half of the EGFR subgroup cases and appeared to also be specific, hence called "EGFR" (Figure 3A,B). It consisted of monomorphic cells with minimally discernible cytoplasm, blending in an eosinophilic extracellular matrix (ECM), with small, round, or slightly elongated nuclei with vesicular chromatin (Figure 3B, Figures S5 and S6). The second most frequent pattern

had high-grade neuroendocrine (HGNE)/embryonal features previously described for the IDH#1 case [7], with pseudorosetting in most cases, and constituted about half of the PDGFRA and Other subgroup cases (Figure 3A,C, Figures S5 and S6). A similar pattern, called HGNE precursor (Pre-HGNE), had related cellular features to HGNE, except for a lack of nuclear molding, slightly vesicular chromatin, and lack of myxoid ECM (Figure S5). This pattern was also enriched in the PDGFRA and Other subgroups, but was also seen scattered in other subgroups. The third most common pattern was represented by cells with small, mostly round, hyperchromatic/dark nuclei with regular contours. It corresponded to all older adult RAF cases, where the nuclei were also surrounded by halos (Figure 3A,D, Figures S5 and S6). This pattern was also scattered in other subgroups and especially enriched in the EGFRm subgroup. Another histologic pattern that was almost entirely seen in the NF1 subgroup in approximately half of the cases was the fibroblastic type, with spindle cells embedded in eosinophilic or myxoid ECM (Figure 1A,D, Figures S5 and S6). The histology of the FGFR3 subgroup was described elsewhere [7] and, in the context of the entire cohort, showed overlap with EGFR, in a pattern called EGFR/FGFR, with a similar EGFR cell morphology pattern and prominent, intersecting capillary network (Figures S5 and S6). However, two FGFR3 cases constituting the FGFR small pattern appeared to show more specific nuclear characteristics, featuring small, finely stippled round or ovoid nuclei, and an ECM richer in hematoxylin-reacting components (Figures S5 and S6). As expected, the Multi-RTK subgroup showed a variation of patterns and included two of the three cases of giant cell glioblastoma from the cohort (Figures S5 and S6). These findings showed that the EGFR, PDGFRA, NF1, RAF, and Other subgroups were enriched in a defined histologic pattern, with the EGFR and fibroblastic patterns relatively specific for the EGFR↑ and NF1 subgroups, respectively.

To assess whether there were additional histologic–molecular associations, the 12 patterns were further clustered in five histologic clusters based on morphological similarities: #1/EGFR-like, #2/Small neuronal-like, #3/Anaplastic, #4/Spindle and #5/Epithelioid (Figure 3A,F). Case-by-case histologic cluster correlations with the most common mutations showed best correlations with cell cycle G1-phase mediators and *TP53* mutations. The EGFR-like histologic cluster was almost exclusively seen in the context of *CDKN2A/2B* homozygous loss and usually the absence of *TP53* mutations. *CDK4* mutations were only seen in the anaplastic cluster, usually associated with *TP53* or *MDM2* alterations. However, the anaplastic cluster was a feature of the PDGFRA subgroup, regardless of other alterations. The epithelioid cluster was associated with *TP53* mutations in 70% of cases, and with *RB1* mutations in 40% of the cases (Figure 3F).

GFAP IHC was performed for almost all cases, and showed reactivity in the majority of tumors, as expected (Figure 3F). The Multi-RTK, Other, and RAF subgroups showed lower or absent GFAP staining in 50%, 67%, and 71% of cases, respectively, suggesting lack of astrocytic differentiation in these subgroups.

**Figure 3.** Histologic patterns and clusters in IDH-wild-type glioblastoma subgroups. (**A**) Bar graph showing histologic pattern distribution in the molecular glioblastoma subgroups and the total distribution in the cohort. Reg, regular nuclear contour; irreg, irregular nuclear contour; HGNE, high-grade neuroendocrine. (**B**–**E**) Representative H&E morphological appearances of the most common histological patterns. The molecular subgroup corresponding to the case is indicated in parenthesis. IHC with GFAP and p53 antibodies is shown in insets. (**F**) Histologic–molecular correlations. Histologic cluster distribution in individual cases from the IDH-wild-type glioblastoma subgroups shown in association with cell cycle G1 phase and p53 pathway mutations. The five histologic clusters (histo) are illustrated in (**A**).

#### **4. Discussion**

The WHO 2016 molecular subgrouping into IDH-wild-type and IDH-mutant glioblastoma emphasizes a significantly longer survival for the IDH-mutant subgroup, due to a slower tumor growth rate, and is reflected in a more insidious onset [21]. IDH-mutant cases represent approximately 10% of all glioblastoma cases [2] and 8% in this study. Except for a small number of cases, now classified as DMG with histone H3-K27M mutation, representing 4% in this study, there is no comprehensive histo-molecular classification for the IDH- and H3-wild-type glioblastoma cases approximating 90% of glioblastoma. Attempts have been made to distinguish histologic variants, and there are three variants of very rare incidence recognized in the WHO 2016 classification of brain tumors: gliosarcoma, giant cell, and epithelioid glioblastoma [2]. For the latter, the molecular association with *BRAF* p.V600E mutation in 50% of cases was noted [22]. Recent histologic–molecular correlations have also focused on the phenotype associated with *FGFR3* fusions in glioblastoma [7,23,24]. The efforts for molecularly classifying glioblastoma have been recently reviewed [25] and are based on a bioinformatics study categorizing in three different clusters the tumors with

EGFR, NF1, and PDGFRA/IDH genetic alterations [26]. However, a more refined and inclusive molecular classification is warranted due to the lack of prognosis stratification for glioblastoma patients, and to the lack of efficacious specific therapies. In addition, developments in personalized medicine for other solid tumors and the availability of alternative targeted treatments for these demand a closer look at glioblastoma in order to design similar targeted therapies.

This study represents a novel, stepwise, comprehensive classification of glioblastoma and includes pertinent genomic, transcriptomic, demographic, clinical, and histologic information (Figure 4A). It assigns all the glioblastoma cases to seven molecular subgroups, G1–G7, and shows their prognostic stratification. The classification was performed on a relatively large controlled cohort compared to cohorts from other studies [25]. Importantly, the cohort is representative for a mixed demographic population, including both Caucasian/White and African-American/Black ethnicities, providing thus more inclusive information than previously analyzed cohorts. The classification is based on my observation of the presence of non-redundant genomic alterations that activate RTKs and the upper segment of the MAPK/ERK pathway, whereas genomic alterations activating the PI3K pathway coexist with RTK alterations in a relatively even distribution (Figure 4A). The RTK subgroups G1/EGFR, G2/FGFR3, G5/PDGFRA, and G6/Multi-RTK accounted for roughly two-thirds of the glioblastoma IDH-wild-type cases, indicating a major role of RTKs in the pathogenesis of glioblastoma. An additional approximately 20% of cases were due to alteration in the upper segment of the ERK signaling pathway, namely NF1 tumor suppressor, in the subgroup G3/NF1, or RAF family members, in the subgroup G4/RAF. The remaining cases formed a separate subgroup, G7/Other, in which only genomic alterations of the PI3K pathway were apparent.

Hierarchical clustering analysis based on the main molecular characteristics of the subgroups showed two clusters and three independent subgroups (Figure 4A). The independent subgroups were the IDH, PDGFRA, and EGFRm. Whereas the IDH subgroup has been singled out in many studies because of its distinct better patient survival and lower tumor proliferation rate [21], the lack of clustering of PDGFRA and especially of EGFRm with other RTK subgroups is surprising. The main features of the IDH-wild-type glioblastoma subgroups are illustrated in Figure 4A. The G5/PDGFRA was the only subgroup that showed a majority of cases without *TERT* alterations as a mechanism of telomere elongation, an observation noted first by Higa et al. [27]. It also showed relatively few PI3K pathway alterations, equally divided between *PTEN* and *PIK3R1*. The histology was aggressive but the survival was not shorter than that for the G1/EGFR subgroup. The G1/EGFRm is a novel, very small subgroup, and will need further characterization to confirm the preliminary results presented in this study. It featured a shorter survival, the only predominant inclusion of African American/Black patients, a relatively aggressive histology, and *RB1* and *TP53* mutations, in contrast to the main G1/EGFR↑ subgroup.

The two clusters contained two or more subgroups. The largest subgroup, G1/EGFR↑, clustered closely with the G3/NF1 and G4/RAF subgroups, and more distantly with the G2/FGFR3 subgroup, in the molecular cluster#1. The G1/EGFR↑ subgroup showed the second-longest survival after the G2/FGFR3 subgroup, which was the subgroup with the longest survival, in concordance with a previous report [28]. The longest survivors of the cohort belonged to these two subgroups, with two survivors reaching 7 years, representing 2.2% of the IDH-wild-type cohort. Although the G3/NF1 subgroup alone showed similar survival relative to non-NF1 cases (not shown), as previously reported for the TCGA dataset [29], the combined G3/NF1-G4/RAF subgroups showed significantly shorter survival compared to the combined G1/EGFR↑-G2/FGFR3 subgroups, indicating a worse prognosis overall for patients with mutations in the upper segment of the ERK/MAPK pathway. The G2/FGFR3 subgroup was enriched in female patients, similar to the IDH subgroup, and in contrast to all other glioblastoma subgroups. Surprisingly, the histology of this subgroup was variable, with the small neuronal-like morphology as the most frequent. In contrast, both G1/EGFR and G3/NF1 subgroups showed a quasipathognomonic morphology in half of the tumors. All four subgroups from the molecular cluster #1 showed similar activation profiles of the major pathways: high incidence of PI3K pathway mutations, represented mainly by *PTEN* but also by *PIK3CA* and *PIK3R1* mutations, high incidence of *CDKN2A* homozygous loss coupled with *CDK6* overexpression, and conversely, low incidence of *TP53* mutations.

**B**

**Figure 4.** ERK/MAPK-based glioblastoma classification. (**A**) Multi-platform characterization of the IDH-wild-type glioblastoma G1–G7 molecular subgroups showing main demographic, histologic, RTK expression, and growth pathway mutation analysis: light blue and peach shading indicate molecular cluster#1 and #2, respectively; yellow shading highlights some characteristic features of the subgroup. M, male; F, female; B, African-American/Black; W, Caucasian/White. The midline location comprises all midline structures including the corpus callosum. Histologic clusters: Neuro, Small neuronal; Ana, Anaplastic; Epith, Epithelioid. RTK overexpression (overexpr) shows the most commonly upregulated RTKs; in bold are RTKs with gene amplifications. The mutation frequency is considered: highest, 100% cases; very high, >90% cases; high, ≥66.7% cases; moderate, between 33.3% and 66.7% cases; low, ≤33.3% cases. Asterisks (\*) mark the presence of other minor components within the subgroup when only one parameter is shown. (**B**) Implementation of the glioblastoma classification in clinical practice and discovery. Schematic flowchart shows the management of the glioblastoma patient by the brain tumor team. An example of pathology report is shown, with incorporation of the glioblastoma molecular subgroup and histologic pattern and cluster.

> The molecular cluster#2 comprised cases with similar demographic and histologic characteristics, including relatively poor survival, classified separately into the G6/Multi

RTK and G7/Other subgroups. The molecular signature was also similar for the PI3K and p53 pathways, with a high incidence of *PTEN* and *TP53* mutations, but showed clustering of *CDK4* amplification in the G7/Other subgroup. Although the G6/Multi-RTK subgroup appeared heterogeneous, with concurrent genomic alterations and overexpression of a wide range of RTKs, it may represent a good target for the multi-RTK therapy that has shown some success in recurrent glioblastoma [30].

This classification required both genomic and transcriptomic information. The transcriptomic analysis uncovered pathogenic fusions with subgrouping relevance, and examined the translation of CN alterations into gene expression levels, as we have previously shown that gene amplification does not always result in mRNA overexpression [7]. The landscaping of RTK expression and correlation with genomic alterations has not been performed previously in glioblastoma. Its major findings are (1) lack of overlap between *EGFR*, *PDGFRA*, and *FGFR3* alterations, including overexpression; (2) good correlation between *EGFR* amplification and high overexpression in the vast majority of cases; a similar correlation for *MET* and *FGFR2*-amplified cases was also found; (3) presence of a small subgroup characterized by *EGFR* activating mutations without gene amplification or high overexpression; (4) lack of correlation between *PDGFRA* locus amplification, including *KIT* and *KDR*, and overexpression, requiring correct assignment of cases with high *PDGF*

*RA* overexpression in the G5/PDGFRA subgroup and of the *PDGFRA*-amplified non-overexpressing cases in the G6/Multi-RTK subgroup; (5) *KDR* overexpression in the majority of cases and at higher levels in the molecular cluster#1, most likely in the vascular compartment; (6) overexpression without amplification of additional RTKs in many cases, such as *NTRK1*, *ERBB2*/*ERBB3*, *EPHA3*/*EPHB2* and *ALK*, some showing subgroup specificity (Figure 4A).

The RTK landscaping, pathway associations, and subgrouping efforts presented here also carry a major impact for the clinical management of glioblastoma, including diagnosis, prognosis, and therapy (Figure 4B). Although many clinical trials targeting a plethora of pathways are ongoing in glioblastoma [31] and aim at the major pathways presented here, correct patient inclusion is crucial for regimen success. For example, the G1/EGFRm subgroup may represent a more promising target to EGFR inhibitors than the larger G1/EGFR↑ subgroup, similarly to non-small cell lung carcinomas with *EGFR* mutations. Likewise, PDGFRα inhibitors may not work for tumors with *PDGFRA* amplification without overexpression. Specific RTK inhibitors are available not only for the RTKs with genomic alterations for which drug trials are usually designed, such as EGFR, PDGFRα, FGFR2 and FGFR3, NTRK1, and MET, but also for RTKs with overexpression with or without mutations of unknown significance, such as ALK, ERBB2 (Her2/Neu), and EPHA3 [32]. Together with new targets revealed in this study, such as EPHB2, these RTKs also warrant consideration for glioblastoma therapy. Moreover, efforts should include RTK family or multi-RTK strategies to cover convergent growth signaling from multiple RTKs, and testing for RTK reprogramming leading to drug resistance [14,33]. Open questions remain, such as the use of combination therapy for targeting downstream or parallel growth pathways. Of these, the PI3K pathway may represent a selective target for the tumors composing the G7/Other subgroup that apparently rely predominantly on this canonical growth pathway.

#### **5. Conclusions**

In conclusion, I presented here a comprehensive multi-platform glioblastoma classification with large patient inclusion and immediate field applicability for diagnosis and prognosis (Figure 4). The incorporation of this novel classification in the pathology report will foster discovery by immediate molecular subgroup stratification, data sorting, and personalized follow-up of patients. This classification complements and expands the previous efforts for a better understanding of this deadly disease, and lays the foundation for precision therapy design.