part through NRP2 and that NRP2 mRNA levels are partially regulated by GLI2 signaling in a TGFβ1-dependent manner. In contrast to cell lines J82 and HS853T, another cell line (5637) showed no changes in the expression of these genes possibly because TGFβ1 failed to induce their expression. Consequently, the relationship of NRP2 and GLI2 could not be observed in this cell line (**Supplementary Figure 14**). Because prediction of overall and disease-free survival could be improved by combining NRP2 and GLI2 gene expression in the TCGA patient cohort, these results suggest a functional interplay between NRP2 and GLI2 in regulating tumor growth, although the mechanisms of this interplay still remain elusive and merit further investigation. Notably, GLI2 knockdown also changed the ratio of isoforms NRP2a and NRP2b in favor of the latter in two BCa cell lines. It was recently described in a lung cancer model that while NRP2a is almost dispensable for tumor formation and metastasis, NRP2b severely impacted these traits (31). The authors demonstrated that TGFβ1 predominantly upregulated NRP2b and that TGFβ1-dependent stabilization was specifically dedicated to isoform NRP2b. In our model, both NRP2 isoforms were equally increased on mRNA level, but this induction might be the result of compensating for increased protein degradation following TGFβ1 treatment given that the protein level of total NRP2 was not significantly increased.

### NRP2 Positively Regulates Osteopontin Expression

The active ligand TGFβ1 is a potent inducer of EMT. For investigating how NRP2 might enhance EMT, we chose a qPCR array containing 84 genes involved in EMT signaling and checked cDNA from two NRP2 knockout cell lines and their parental wild-type cell line RT112. Using this approach, a number of genes were deregulated in both KO clones compared to the parental cell line irrespective of the housekeeping gene used. Validation of these genes in four independent biological repeats confirmed their altered expression, although the change for CALD1, CDH2, and SPARC1 was not significant. Because the expression of CDH2 mRNA was sufficient to detect this target by Western blot, we checked the expression of the corresponding protein N-Cadherin as well as its counterpart E-Cadherin as control in treated and untreated conditions. Although N-Cadherin expression doubled in KO clones without TGFβ1-treatment, only one KO clone showed a significant increase. However, when TGFβ1 treatment was applied, we detected a significant reduction in both KO clones, although the change was less dramatic than for N-Cadherin in the untreated condition. There have been numerous reports in the past stating the significance of cadherin switching in progression and malignancy of BCa pointing to the importance of elucidating the mechanism for targeted therapy (32–37). Moreover, it was already shown that NRP2 and E-Cadherin expression are connected in multiple cancer types (23, 38–41). However, unlike the positive correlation in our model system, all publications reported a negative correlation. It has previously been described for melanoma that Osteonectin (gene SPARC) can downregulate E-Cadherin (42). We could show a 4.5-fold (KO #2) to 9.8-fold (KO #1) upregulation of SPARC compared to WT when treated with TGFβ1. Although this change was not found to be significant, it was still the highest deregulated gene within the panel. Therefore, the reduced E-Cadherin (CDH1) expression might be a direct result of increased SPARC expression. Given that the authors of the cited paper only investigated E-Cadherin by Western blot but not by qPCR and the fact that the change of E-Cadherin in our model was only visible on protein level suggests that SPARC might not control E-Cadherin transcriptionally. Previous studies showed that SPARC induces β-catenin nuclear localization and binding to the transcriptional regulator lymphocyte-enhancer factor-1 (LEF-1) (43, 44), whereas E-Cadherin forms alternative complexes with β-catenin in the adherens junctions (AJ). These AJ complexes prevent β-catenin nuclear localization and transactivation as well as E-Cadherin internalization (45). We can hypothesize that SPARC can induce loss of β-Catenin in the AJ by triggering its nuclear translocation that might result in E-Cadherin endocytosis and degradation. Of note, protein levels of N-Cadherin (CDH2) after TGFβ1-treatment did not change dramatically anymore, potentially indicating that this change is independent of the ligand TGFβ1.

In order to investigate if the identified targets were specific to that cell line or if signaling pathways were deregulated for compensation of complete NRP2 loss in the knockout cells, we used siRNA-mediated depletion of NRP2 in another human cell line (J82). The results confirmed deregulation of all but one gene (STEAP1), but the direction of change was only consistent for one gene (SPP1/Osteopontin/OPN). Thus, changes in other genes are either cell line specific or long-term KO models adapt to missing NRP2 by deregulation of other EMT pathways that were initially downregulated in the short-term knockdown model (for example, CALD1, CDH2, and SPARC). But given that Osteopontin was the only target significantly downregulated in both NRP2 KO and knockdown models in different cell lines, we propose that this dependency might be a general mechanism. To our knowledge, this is the first report linking NRP2 and SPP1/OPN in any tissue or cancer entity by showing that NRP2 acts upstream of SPP1 in a TGFβ1-independent manner. This can be an explanation for the VEGF-induced OPN expression, which was demonstrated in a large number of cases (25). OPN was shown to be upregulated in multiple cancer types including breast and prostate cancer as well as glioblastoma and melanoma (46, 47). Regarding BCa, immunohistochemical staining of OPN demonstrated significant correlation with tumor stage (27). More recently, Wong and colleagues showed that OPN expression correlates with disease stage and grading and that higher OPN expression led to decreased survival in multiple patient cohorts (26). Of note, we could not see the same in our TCGA data set when applying median expression for overall and diseasefree survival (**Supplementary Figure 9**). However, combining NRP2 and OPN expression slightly improved prediction of disease-free but not overall survival (**Supplementary Figure 10**). Since OPN is a secreted soluble molecule, it may serve as an attractive non-invasive prognostic marker in serum or urine. One study investigated plasma OPN levels before and after tumor resection in 50 patients with BCa and found significantly higher preoperative OPN levels in patients with muscle invasive tumors despite the relatively low number of patients. OPN levels also increased significantly with T stage when patients had undergone radical cystectomy. The strong trend of correlation with tumor grade and predicting recurrence did not reach statistical significance, potentially indicating that patient number for this analysis was too low (48). Similar to OPN, the expression pattern of NRP2 was previously reported to be significantly associated with pathological stage and tumor grade in a BCa cohort, suggesting a prominent role of NRP2 in BCa progression (49).

Because OPN is also associated with bone matrix formation, it would be highly interesting to analyze if the connection between NRP2 and OPN is also true for cancer entities like breast and prostate cancer, where bone metastases remain a big challenge.

#### NRP2 as Target for Radiochemotherapy

Overall and disease-free survival data suggested NRP2 as prognostic indicator for a TCGA BCa cohort. Our group previously showed that expression of NRP2 as well as its ligand VEGF-C could predict treatment outcome of BCa patients following TURBT and radiochemotherapy. This clinical finding prompted us to use our NRP2 KO and WT cell lines for an in vitro assay to determine their clonogenicity after radio(chemo)therapeutic treatment. When looking at the radiotherapy group only, no significant differences between both KO and the WT cell lines were found, which confirmed the previous finding that NRP2 expression alone in the patient group receiving only local radiotherapy was not a prognostic factor (7). When the same analysis was applied to the group of patients, which received radiochemotherapy, NRP2 was highly prognostic for overall and cancer-specific survival. In accordance to this clinical observation, we revealed a radiation dose-dependent trend toward higher profit of additional chemotherapy in KO cells, suggesting that NRP2 downregulation results in BCa radiochemosensitization. The exact role of NRP2 for radiochemotherapy in BCa warrants further investigation using additional cell lines and animal models.

Taken together, our study demonstrated that mRNA expression of NRP2 and GLI2 highly correlate in BCa cell lines and the TCGA BCa cohort. They influence each other's expression depending on the presence or absence of TGFβ1, a potent inducer of EMT. Moreover, screening of 84 genes involved in EMT identified SPP1/Osteopontin as a downstream target of NRP2 in two different BCa cell lines using different model systems.

Future research is needed to evaluate the exact mechanism of how NRP2 and GLI2 communicate bidirectionally, how NRP2 modulates SPP1 transcription, and what implications this will have for development and progression of other cancer entities apart from bladder carcinoma.

### MATERIALS AND METHODS

#### Cell Lines and Cell Culture

The cell line RT112 (DSMZ) was maintained in MEM alpha medium with GlutaMAX supplemented with 10% FBS (fetal bovine serum, both Gibco, Life Technologies, Waltham, USA). The cell line and their knockout derivatives were validated to be RT112 by single nucleotide polymorphism (SNP) profiling (performed by Multiplexion GmbH, Friedrichshafen, Germany). Cell line J82 (ATCC) and HS853T (ATCC) were cultured in DMEM medium (4.5 g/L glucose) supplemented with 10% FBS (both Gibco, Life Technologies, Waltham, USA), 1% HEPES solution, and 1% MEM non-essential amino acids (both Sigma-Aldrich, St. Louis, USA). The cell line 5637 (ATCC) was cultured in RPMI supplemented with 10% FBS (both Gibco, Life Technologies, Waltham, USA). All cell lines were subject to regular testing for excluding mycoplasma contamination (last on 2nd April 2019). All cells were maintained at standard conditions in a humidified incubator with 5% CO2 at 37◦C.

### CRISPR/Cas9-Mediated Deletion of NRP2 in RT112 Cells

Plasmid-based CRISPR/Cas9 technology was used to generate RT112 cell clones deficient in NRP2 expression according to the protocol established by Ran et al. (50). In brief, DNA double stranded oligonucleotides located in the exon 3 splice acceptor region (NRP2e3gu1-top: 5′ -CACCGGATAAAGTCAT ACCTGGGTG-3′ , NRP2e3gu1-bottom: 5′ -AAACCACCCAGG TATGACTTTATCC-3′ ) and exon 3 coding region (NRP2e3gu2 top sequence: 5′ -CCACCGGGTGAACTTGATGTAGAGCA-3′ ; NRP2e3gu1-bottom sequence: 5′ -AAACTGCTCTACATCAAG TTCACCC-3′ ) of the NRP2 locus were designed using the Benchling software (San Francisco, USA) and cloned into pSpCas9 BB2A-GFP for gu1 (PX458, Addgene, LGC Standards, UK) or pSpCas9 BB-2A-Puro for gu2 (PX459v2, Addgene). RT112 cells were transfected by calcium phosphate precipitation with a 1:1 ratio of PX458-NRP2e3gu1 and PX459v2-NRP2e3 gu2 for 8 h, kept under puromycin selection (0.5µg/ml) for 24 h and then seeded at low density. One hundred clones were picked after two weeks, grown and checked for the desired 110 bp deletion in NRP2 exon 3 by PCR on isolated genomic DNA using primers 5′ -AGTGCCCTTCGCTTATCCATC-3′ and 5′ -TC TAAGACGCCCATCTCCCG-3′ . Clones that carried the deletion in the NRP2 locus were further checked for mutations within the corresponding region of the NRP1 locus (primer sequences 5 ′ -GCTGGATGATGCTGGTGTCTA-3′ and 5′ -TTCTACCGTA AGCTGTTCACTC-3′ ) and for Cas9 (primer sequences 5′ -CG ACGACAGCCTGACCTTTA-3′ and 5′ -TTGATGCCCTCTTC GATCCG-3′ ) to exclude integration of transfected plasmids. Sanger sequencing of the PCR amplification products verified the deletions. TOPO cloning of DNRP2 PCR products and subsequent Sanger sequencing of single mutated alleles yielded the sequences of individual deletion alleles for NRP2 in two individual RT112 DNRP2 cell clones. Three independent mutant alleles were identified for both RT112 DNRP2 clones, with altered exon 3 splice acceptor sequences and/or introduction of frame shifts due to nucleotide insertions or deletions:

(clone: mutant alleles; mutation; location of mutation in NRP2 exon 3)

#J9 (KO#1): J9high-3 delAG; delCT delAG (−2;−1); delCT (107; 108)

#J9 (KO#2): #J32low-1 del110 deletion: −3 to +107 #J9 (KO#1): #J32-P2 del111 deletion: −4 to +107

Both RT112 DNRP2 cell clones were checked for the absence of NRP2 expression by Western blot immunostaining using an anti-NRP2 antibody (R&D Systems, Minneapolis, USA). For reasons of simplicity, the clones are referred to as knockout (KO) #1 (clone #J9) and KO #2 (clone #J32) in this publication.

### TGFβ1-Induced EMT

RT112 WT and derived KO cell lines were seeded at 1 × 105 cells per well in a 6-well culture plate containing 2 ml of serumreduced (5 % FBS) growth medium either including or lacking 5 ng/ml TGFβ1 (Miltenyi Biotec, Bergisch Gladbach, Germany). After 48 h in the incubator, the medium was renewed and cells were incubated for another 24 h before RNA or protein isolation. In total, four independent biological repeats were performed with cells at different passages. RNA of two repeats was used for "RT2 Profiler PCR Array" for human EMT and all four repeats were used for validation of identified targets by qPCR. Protein was used for immunoblotting.

#### Transfection of Cell Lines With siRNA

Cell lines J82, HS853T, and 5637 were used for knockdown experiments. 2 × 105 (J82, HS853) or 5 × 105 (5,637) cells per well were seeded in a 6-well culture plate with 2 ml complete growth medium (10% FBS) and incubated 24 h to allow attachment. Next, medium was renewed and liposomal transfection was conducted according to the manufacturer's protocol using 12 µl of Lipofectamine RNAi MAX (Thermo Fisher Scientific, Waltham, USA) and 50 nM siRNA (SMARTpool by Dharmacon, Lafayette, USA). The catalog number of siRNA pools was D-001810-10-20 (siSCR, control), L-017721-00-0010 (siNRP2), L-0066468-00-0005 (siGLI2), and L-012558-00-0005 (SPP1). Cells were treated with TGFβ1 as described above.

#### RNA Isolation, cDNA Synthesis, and qPCR

RNA was isolated with the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany) by adding 350 µl of lysis buffer RLT Plus supplemented with 1% β-mercaptoethanol (Sigma-Aldrich, St. Louis, USA) to a well of a 6-well plate that was previously rinsed with PBS. Using a scraper, lysed cells were collected from the plate and transferred to a DNA removal column. The following steps were carried out according to the manufacturer's protocol and RNA was eluted from the column by addition of 30 µl of RNase-free water (Qiagen, Hilden, Germany). cDNA from 1,000 ng of total RNA input was synthesized by employing the PrimeScriptTM RT Reagent Kit (Takara Bio Inc., Kusatsu, Japan) according to the manufacturer's instructions. cDNA was diluted 1:5 with RNase-free water before continuing with realtime quantitative polymerase chain reaction (qPCR). qPCR was conducted using the TB GreenTM Premix Ex TaqTM II (Takara Bio Inc., Kusatsu, Japan) according to the manufacturer's protocol for a total reaction volume of 20 µl. The qPCR cycling conditions were set on a StepOnePlus system (Applied Biosystems, Waltham, USA): 94◦C for 3 min, 40 cycles: 94◦C for 15 s, 58◦C 60 s, 72◦C 60 s followed by a melt curve to 95◦C in steps of 0.3◦C. All experiments were conducted using at least two (for housekeeping genes) or three technical replicates (other targets) and most experiments included three different housekeeping genes as control: ACTB, GAPDH, and HPRT1. All primer sequences are listed in **Supplementary Table 3**. cDNA of the following BCa cell lines was used for qPCR analyses of NRP2 and GLI2: 5637 (ATCC), 639V (DSMZ), Cal29 (DSMZ), EJ28 (University Frankfurt), HS853T (ATCC), HT1376 (ATCC), J82 (ATCC), UMUC-3 (ATCC), UMUC-14 (Sigma-Aldrich), UMUC-16 (Sigma-Aldrich), VMCUB (DSMZ), KU1919 (DSMZ), RT112 (DSMZ), T24 (DSMZ), and TCC-SUP (DSMZ). HPRT1 served as housekeeping gene. 1Ct values were used to calculate correlation in SUMO software (http:// angiogenesis.dkfz.de/oncoexpress/software/sumo/).

## RT2 Profiler PCR Array for Human EMT

cDNA synthesis was performed following RNA isolation as described above (total volume: 10 µl). For each 96-well plate, a master mix was prepared composed of 1,050 µl of TB GreenTM Premix Ex TaqTM II, 42 µl of ROX dye, 1,000 µl of RNasefree water, and 10 µl of cDNA sample. From this master mix, 20 µl was added to each well. The PCR program was identical to the one described above. For the human EMT PCR array (Qiagen, Hilden, Germany), two out of four biological replicates were chosen that displayed values closest to the median. Later, all four biological replicates were evaluated for target validation. Data were extracted using the housekeeping gene HPRT1 from the EMT profiler plate.

#### Protein Isolation and Immunoblotting

Protein was isolated from 1-well of a 6-well plate by washing cells once with PBS before adding cold 200-µl RIPA buffer (Thermo Fisher Scientific, Waltham, USA) supplemented with Complete inhibitor (Roche, Basel, Switzerland), proteinase, and phosphatase inhibitor (both Thermo Fisher Scientific, Waltham, USA). Lysates were collected with cell scrapers, transferred to a 1.5-ml reaction tube and centrifuged at 10,000 rpm at 4◦C for 10 min in a 5415R cooling centrifuge (Eppendorf, Hamburg, Germany). Supernatant was transferred to a new reaction tube and protein was quantified by PierceTM BCA Protein Assay Kit (Thermo Fisher Scientific, Waltham, USA) according to the manufacturer's protocol. Thirty-five micrograms of total protein lysate was loaded into each pocket of a 12-well Bolt 4–12% Bis-Tris Plus Gel (Thermo Fisher Scientific, Waltham, USA) running in an XCell SureLockTM Electrophoresis Cell (Invitrogen, Carlsbad, USA) at 90 V for 2 h in MOPS buffer (Thermo Fisher Scientific, Waltham, USA). Wet transfer to a methanol-activated 0.2-µm AmershamTM HybondTM Low Fluorescence PVDF membrane (GE Healthcare, Chicago, USA) was achieved by applying 90 V for 4 h in a cooled Mini-PROTEAN R three transfer tank (Bio-Rad, Hercules, USA). Membranes were washed once with TBS-T before blocking the membrane for 1 h at room temperature with 2.5% ECL PrimeTM blocking agent (GE Healthcare, Chicago, USA) dissolved in TBS. Membranes were incubated at 4◦C overnight with primary antibodies (see **Supplementary Table 4** for the complete list of used antibodies) diluted in 2.5% ECL PrimeTM blocking agent solution before applying three washing steps with TBS-T. Then, membranes were incubated with the appropriate secondary antibodies diluted in 2.5% ECL PrimeTM blocking agent solution for 1 h at room temperature. Following another three washing steps with TBS-T, chemiluminescent detection was performed by first incubating the membrane with Pierce R ECL Western Blotting Substrate (Thermo Fisher Scientific, Waltham, USA) and subsequent detection of the signal in auto-rapid mode in a ChemiDocTM MP Imaging System (Bio-Rad, Hercules, USA). Colorimetric images were taken for determining the molecular weight of the signals. Calculation of optical densitometry was performed with ImageJ software.

### Colony Forming Assay Following Radiochemotherapy

For radiochemotherapy treatment, cells were seeded into a 6 well plate at a density of 4 × 105 cells per well and treated with cisplatin (TEVA GmbH, Ulm, Germany) for 24 h at concentrations of 1.52 × 10−6 M that corresponded to the IC5 value of KO #2 (**Supplementary Figure 11**). Twenty-four hours after start of the treatment, cells were trypsinized and used for radiobiological colony forming assay. Clonogenic survival was determined by seeding of 500 (ionizing radiation—IR only) or 750 (IR + cisplatin) cells in technical triplicates into 6-well plates containing 2 ml of complete growth medium. Cells were cultivated overnight and then irradiated with doses of 0, 2, 4, 6, and 8 Gy (Yxlon Y.TU 320; 200 kV X-rays, dose rate 1.3 Gy/min at 20 mA, filtered with 0.5 mm Cu). Irradiated cells were returned to the incubator for allowing recovery and growth for 6 days. Colonies were fixed by the addition of 600 µl of 37% formaldehyde solution (Merck, Darmstadt, Germany) directly to the culture medium and incubation at room temperature for 30 min. Following removal of this solution and a washing step with normal tap water, 1 ml of a 0.05% crystal violet solution (Sigma-Aldrich, St. Louis, USA) was added to each well for 30 min at room temperature for staining colonies. Crystal violet was removed, and wells were washed twice with normal tap water and dried overnight before manually counting colonies using a stereomicroscope (Zeiss, Oberkochen, Germany). Cell survival data were entered into the SPSS program for calculation of α and β values, curve fitting to the linear quadratic model, and determination of statistical significance.

### Analysis of the TCGA Patient Cohort Data

From the TCGA patient cohort data set, Pearson coefficient was determined using SUMO software and significance was calculated by two-tailed, unpaired Student's t test. For evaluation of combined NRP2/GLI2 signature expression, the data for each of these genes were normalized to median across the entire dataset and log2 transformed. Further, the mean of two genes was calculated for each patient and the subset with known survival data was extracted from complete cohort. Finally, the up- and down-regulated groups for Kaplan–Meier analysis were defined as the mean of NRP2/GLI2 expression was positive or negative value accordingly.

#### Statistical Analysis

The cell survival curves were analyzed using the Statistical Package for the Social Sciences (SPSS) v23 software as described previously (51) by linear–quadratic formula S(D)/S(0) = exp−(αD + βD2) using stratified linear regression. A p < 0.05 was considered statistically significant. Correlation of gene expression levels was evaluated by SUMO software using Pearson correlation coefficient. IC50 and IC5 values (50 and 5% inhibitory concentration) were determined by non-linear regression using GraphPad Prism software (San Diego, USA).

### DATA AVAILABILITY STATEMENT

All datasets generated for this study are included in the article/**Supplementary Material**.

### AUTHOR CONTRIBUTIONS

AS performed most experiments and wrote and edited the manuscript. IG performed revision experiments and edited the manuscript. RB helped to teach CRISPR/Cas9 technology and designed the guide RNAs. SFu and KE provided cell lines and cDNA of cell lines and edited the manuscript. SFo and KD edited the manuscript. TM generated and validated the knockout clones from cell line RT112. TM, AD and MM supervised and guided AS, edited the manuscript, and aided in scientific questions including experimental design. AD helped perform radiochemotherapy and colony forming assay.

### FUNDING

Work in AD lab was partially supported by grants from Deutsche Forschungsgemeinschaft (DFG) (273676790, 401326337, and 416001651), from Wilhelm Sander-Stiftung (2017.106.1), BMBF (Grant-No. 03Z1NN11), and DLR Project Management Agency (01DK17047). This work was in part supported by German Academic Exchange Service (DAAD) and the Federation of European Biochemical Societies (FEBS) for IG. Work in MM lab was partially supported by a grant from Deutsche Forschungsgemeinschaft (DFG) (273676790). The professorship of MM was also funded by the Rudolf Becker Foundation of Translational Prostate Cancer Research. MM was a member of the German BRIDGE consortium. This work was in part supported by the graduate academy of Technische Universität Dresden for AS.

### ACKNOWLEDGMENTS

The authors kindly want to thank Vasyl Lukiyanchuk for analysis of TCGA datasets and for help with analysis of PCR array data and SPSS statistical analysis. We thank Jakob Püschel for help with radiobiological clonogenic analysis. We also thank Dorothee Pfitzmann for technical advice and providing cisplatin. The authors thank all members of AD and MM lab for useful discussions.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc. 2019.01461/full#Supplementary-material

#### REFERENCES

migration, invasion, and resistance to paclitaxel. Cancer Res. (2007) 67:1979– 87. doi: 10.1158/0008-5472.CAN-06-1479

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Schulz, Gorodetska, Behrendt, Fuessel, Erdmann, Foerster, Datta, Mayr, Dubrovska and Muders. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# The Role of Cancer Stem Cells in Radiation Resistance

Christoph Reinhold Arnold1 \*, Julian Mangesius 1 , Ira-Ida Skvortsova1,2 and Ute Ganswindt 1

*1 Department of Therapeutic Radiology and Oncology, Medical University of Innsbruck, Innsbruck, Austria, 2 EXTRO-Lab, Tyrolean Cancer Research Institute, Innsbruck, Austria*

Cancer stem cells (CSC) are a distinct subpopulation within a tumor. They are able to self-renew and differentiate and possess a high capability to repair DNA damage, exhibit low levels of reactive oxygen species (ROS), and proliferate slowly. These features render CSC resistant to various therapies, including radiation therapy (RT). Eradication of all CSC is a requirement for an effective antineoplastic treatment and is therefore of utmost importance for the patient. This makes CSC the prime targets for any therapeutic approach. Albeit clinical data is still scarce, experimental data and first clinical trials give hope that CSC-targeted treatment has the potential to improve antineoplastic therapies, especially for tumors that are known to be treatment resistant, such as glioblastoma. In this review, we will discuss CSC in the context of RT, describe known mechanisms of resistance, examine the possibilities of CSC as biomarkers, and discuss possible new treatment approaches.

#### Edited by:

*Marco Durante, Helmholtz-Gemeinschaft Deutscher Forschungszentren (HZ), Germany*

#### Reviewed by:

*Emanuele Scifoni, National Institute of Nuclear Physics (INFN), Italy Claere Von Neubeck, University of Duisburg-Essen, Germany*

> \*Correspondence: *Christoph Reinhold Arnold<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Radiation Oncology, a section of the journal Frontiers in Oncology*

Received: *01 September 2019* Accepted: *30 January 2020* Published: *20 February 2020*

#### Citation:

*Arnold CR, Mangesius J, Skvortsova I-I and Ganswindt U (2020) The Role of Cancer Stem Cells in Radiation Resistance. Front. Oncol. 10:164. doi: 10.3389/fonc.2020.00164* Keywords: cancer stem cells, radiation resistance, radiation therapy, DNA damage repair, reactive oxygen species, stem cell niche, quiescence

## INTRODUCTION

Radiation therapy (RT) is one of the mainstays of cancer treatment. Roughly one half to two-third of all oncologic patients receive some form of RT in the course of their disease (1–5), either in a curative setting for primary treatment with or without other treatment modalities (i.e., surgery or chemotherapy, CHT) or in a palliative setting for the irradiation of symptomatic metastases. Importantly, the number of patients requiring RT is expected to increase in the foreseeable future (6). In short, RT exerts its effect by inducing DNA damage, either directly or indirectly via the production of water-derived radicals and reactive oxygen species (ROS) (7–9), which then interact with macromolecules including DNA, lipids and proteins. As a consequence, DNA damage response (DDR) is initiated and leads to the activation of the DNA damage repair machinery as well as the induction of checkpoint kinase pathways, which delay cell cycle progression in order to facilitate DNA repair (10–13). In case the DNA is damaged beyond repair, DDR signaling induces apoptosis, senescence or mitotic catastrophe, all of which imply the loss of reproductive capacity of a cell (14–16). Consequently, if successful, RT hinders cancer cells from further proliferation. In theory, every (cancerous) cell can be killed with RT given a high enough dose. However, the surrounding healthy tissue limits the applicable dose (17). RT is usually a balancing act between giving enough dose to achieve local tumor control and only as much dose as the surrounding tissue can tolerate. Despite a very high local tumor control rate, a non-negligible rate of therapy failure still constitutes one of the major limitations in radiation oncology (18, 19). Insufficient response to irradiation (i.e., radiation resistance) contributes to residual cancer mass, which is the key driver of locoregional or distant recurrence, both of which are negatively influencing the patient's prognosis as local recurrence often is associated with metastatic spread, which is almost always fatal.

In recent years evidence has accumulated showing that multiple genetically diverse clones co-exist within various kinds of tumors (20–24). Not all cells within a tumor are equally sensitive to RT. Understanding the diverse radiosensitivity of different tumor cell subpopulations is very important. It challenges the common practice of employing macroscopic bulk tumor responses (as measured with medical imaging) as the primary endpoint for determining the effectiveness of an antineoplastic treatment. While this is certainly a very practical approach, it is only then true if the bulk tumor response represents the response of all cells within the tumor, including the most resistant subpopulation within the tumor. This is most likely not the case for most tumors because not all subpopulations are equally affected by the treatment. The stem cell model of cancer development may explain genetic, functional, and phenotypical differences, such as increased therapy resistance, within a tumor, even within the same tumor clone. Cancer stem cells (CSC), albeit difficult to identify, are believed to contribute to resistance to various oncological therapies, including RT (25– 34), making them a primary target for anti-cancer therapy. Hence, a proper understanding of differential sensitivity of cancer cells, especially CSC, to irradiation is vital in order to develop new or improve existing anti-cancer therapies. Most research on CSC has been done in breast cancer and glioma (35, 36). However, as CSC differ between entities results cannot be transferred to other tumors, at least not without caution.

#### CANCER STEM CELLS

Today, there are basically two largely accepted models for the origin of cancer: the standard (hierarchical) CSC model and the clonal evolution model. In the latter, genetic mutations accumulate with time and theoretically any cell can have tumorigenic potential (37). The CSC model describes a hierarchical organization of tumors with tumorigenic CSC at the apex which divide asymmetrically to form new CSC as well as differentiated non-tumorigenic progenies (34). Adding to the complexity of the CSC theory, is the fact that differentiation may be bidirectional. In this way, differentiated non-tumorigenic tumor cells may, instructed by niche signals, re-differentiate into CSC to replace lost stem cells. Even though data supporting the CSC hypothesis with its hierarchical organization of tumors is more solid, it is feasible that both, the CSC hypothesis and the clonal evolution model are not necessarily mutually exclusive.

The generation of CSC is not conclusively clarified, and several hypotheses exist (38). CSC may originate from normal stem cells, where random mutations during DNA replication may lead to them becoming malignant (39). Additionally, aberrant stromal signaling and pro-inflammatory conditions can lead to the malignant degeneration of normal stem cell (40). Alternatively, as stated earlier, CSC can be derived from differentiated cells. This can occur via genomic instability of tumor cells, horizontal genetic transfer, or microenvironmental signals. Genetic instability describes the acquisition of additional genetic mutations that provide any given differentiated tumor cell with stem cell traits so that it becomes a CSC (41). It is, however, unclear, whether stem cell traits shift from one cell to another in a stochastic manner during tumor evolution. In horizontal gene transfer, a normal stem cell may phagocyte fragmented DNA from tumor cells leading to their reprogramming and CSC formation (42). Microenvironmental signals include proinflammatory cytokines such as interleukin-6 (IL-6), which has been shown to facilitate dedifferentiation of non-CSC into CSC, or nuclear factor-kB (NF-kB), which maintains CSC numbers (43).

The frequency of CSC within a tumor is difficult to estimate and largely depends on the type of malignancy. In solid tumors, reported CSC rates are in the range from below 1% of all tumor cells to more than 80% (44–48). Similarly, the frequency of CSC in hematologic malignancies also displays a broad spectrum and ranges from <1% in acute myeloid leukemia (AML) up to over 80% in acute lymphoblastic leukemia (ALL) (49, 50). It has been shown in glioblastoma that CSC seem to reside predominantly in niches that are hypoxic, low in nutrients and have a low pH (51).

CSC are a distinct subpopulation within the heterogenous tumor mass and share several properties with normal stem cells (SC), the most important being the ability to self-renew (i.e., the potential of unlimited cell division) and the ability to give rise to more differentiated, mature cancer cells (34). Like in healthy tissue, stem cells initiate, promote, and maintain tumor development and growth (and re-growth after treatment) (52–55). It has been shown in glioma and breast cancer that the number of CSC in a tumor at the time of treatment is inversely correlated with clinical outcome (56, 57). Furthermore, repopulation of CSC after fractionated RT is one of the most important factors that determine local tumor control (58, 59). Therefore, inactivation of all CSC within a tumor is the prerequisite for a curative cancer treatment (60).

One major challenge regarding CSC is their correct identification as there is not one specific CSC marker, not least because of the high intra- and inter-tumor heterogeneity as well as tumor plasticity and the associated changes in genotype and phenotype. However, there are some cell surface marker that seem robust enough to use them as indicators for CSC. Two of these biomarkers are CD44 (found on CSC in cancers of the colon, esophagus, stomach, pancreas, breast, brain, lung, ovaries, prostate, liver, and the head and neck region) and CD133 (found in cancers of the colon, esophagus, stomach, pancreas, brain, lung, ovaries, prostate, liver, skin, and the head and neck region) (38, 61). Naturally, there are more surface molecules and usually combinations of these markers are used to identify and isolate CSC depending on the type of tumor that is investigated. It is important to emphasize that CSC differ between tumor entities, both phenotypically and functionally, and results from one type of cancer should not be translated to other types.

#### RADIOCURABILITY AND RADIATION THERAPY RESISTANCE

Following RT-induced DNA damage the balance of pro- and antiapoptotic pathways skews toward cell death induction. However, in CSC pro-survival pathways seem to be more pronounced and protect these cells from cell death, rendering CSC radiation resistant (27). Radiation resistance of CSC may either be primary, i.e., due to the constitutive upregulation of certain molecules and pathways (see below). Alternatively, radiation resistance of CSC may be acquired. Following RT, as is the case with any other antineoplastic therapy, intratumoral heterogeneity can theoretically promote clonal evolution through Darwinian selection and lead to the development of adaptive responses with the result of more resistant, aggressive, and invasive tumors (62). CSC clones with genomic alterations that protect them against RT are selected for and continue to sustain the tumor (63). Indeed, it is known that RT preferentially kills non-CSC, thereby enriching the tumor for CSC (64). In addition, RT has been shown to induce the reprogramming of non-CSC in breast cancer as well as squamous cell carcinoma of the head and neck (HNSCC) leads to the acquisition of functional CSC traits in order to compensate for cell loss in the stem cell compartment in response to cellular injury as is the case after RT (65, 66). Finally, RT leads to the recruitment of CSC in breast cancer from a quiescent state into the cell cycle (67, 68). In this way, RT contributes to the acquired or adaptive radioresistance via selective repopulation from the surviving CSC.

The number of CSC within a tumor predicts the radiation dose needed to eradicate the tumor. Therefore, in tumors with a higher proportion of CSC a given dose of irradiation leads to a lower probability of local control as compared to tumors with fewer CSC (69–71). From a clinical point of view, this implies a dose-volume dependency, as radiocurability of tumors inversely correlates with tumor volume (72) and with intrinsic radiosensitivity in vitro (73). Furthermore, the probability of successful irradiation also correlates with the number, density, and intrinsic radiosensitivity of CSC (60, 71) and the absolute number of CSC increases with tumor volume (70–72, 74). Importantly, survival of one single CSC after RT can lead to tumor relapse. Hence, eradication of the entire CSC population is of utmost importance for the patient. Nonetheless, one must keep in mind that CSC differ between tumor types and there is no general radiation resistance of CSC, as many patients can be cured with current concepts of conventional RT.

### CELLULAR FACTORS FOR CSC RADIORESISTANCE

Several cellular features render CSC radioresistant. In the following, we will discuss the best-studied cellular factors, which include low levels of ROS, increased DNA damage repair capacity, or quiescence (**Figure 1**). These are common characteristics of healthy SC and CSC alike, presumably to protect their DNA from stress-induced damages.

ROS are involved in various physiological processes, such as proliferation, differentiation, metabolism, apoptosis, angiogenesis, wound healing, or motility (75, 76). Intracellular ROS levels are tightly and continuously regulated by ROS scavengers, which include superoxide dismutase, superoxide reductase, catalase, glutathione peroxidase, glutathione reductase, or apurinic/apyrimidinic endonuclease/redox

effector factor (Ape1/Ref-1, also known as APEX1) (77). There is a multitude of publications showing that ROS scavengers are upregulated and highly efficient in CSC of various tumors (78–83) leading to low levels of ROS and protecting CSC from RT-induced cell death, as ROS is essential for the effect of RT (84). This protective effect of upregulated ROS scavengers even outweighs the effect of oxygen, a known potent radiosensitizer (85). Along this line, it has been shown that CSC produce less ROS upon radiation compared to non-CSC (86).

Secondly, DNA damage repair capacity following RT, especially regarding DNA double strand breaks (DSB), has been shown to be higher in CSC as compared to their non-tumorigenic counterparts (25, 87–90). This has been shown in CSC of several tumors, including glioma, nasopharyngeal carcinoma, prostate, lung, and breast cancer, and is mainly attributed to the activation of checkpoint-pathways in response to RT (90– 98). The resulting delayed cell cycle progression allows for repair of the DNA damage. Interestingly, CSC have been shown to repair DNA damage preferably via homologous recombination (HR) instead of non-homologous end-joining (NHEJ), the latter being less accurate and more error-prone than HR (25, 99–101). A comprehensive review on DNA damage repair in CSC has recently been published (102).

Third, it has been shown in various studies that CSC proliferate more slowly than further differentiated cancer cells (78, 103, 104). This is of importance as RT is known to be more effective in killing rapidly proliferating tumor cells as compared to slowly dividing (i.e., quiescent or dormant) cells and quiescence is associated with relative radiation resistance (105, 106). This way, non-proliferating cells survive therapeutic irradiations and remain quiescent for a various amount of time, which can range from weeks (78, 104) to even decades (107, 108). Once they continue to proliferate, these cells can cause a recurrence.

#### TUMOR MICROENVIRONMENT

Similar to healthy stem cells, CSC reside in specific niches that provide microenvironmental factors such as autocrine signaling and signals coming from stromal fibroblasts (cancer associated fibroblasts, CAF), immune cells, endothelial cells, and extracellular matrix components (109, 110). The exact composition of the niche is not well-defined for most tumors, as are the exact supporting signals. It is known, however, that the niche supplies CSC with oxygen and nutrients, supports stem cell functions, protects from insults such as radiation, and regulates responsiveness to a therapy (111). For instance, in breast cancer it has been shown that deregulation of the stem cell niche by increased expression of bone morphogenetic protein 2 (BMP2) can initiated and promote malignant stem cell transformation (112). Furthermore, at least in glioblastoma tumor samples, there are different types of niches, such as hypoxic periarteriolar niches, peri-vascular niches, peri-hypoxic niches, periimmune niches, and extracellular niches (113). Whether other types of cancer have different types of niches, and what therapeutic implications this finding might have, still needs to be elucidated.

Like the tumor itself, the tumor microenvironment also responds to RT (114) (**Figure 1**). For instance, it has been shown that CAFs acquire a pro-malignant phenotype after RT of in colorectal cancer samples (115–117). Furthermore, CAFs induce autophagy following irradiation of lung cancer and melanoma cell lines leading to enhanced cancer cell recovery and tumor re-growth (118).

Additionally, RT induces pro-inflammatory cytokines in the tumor microenvironment (119, 120), including platelet-derived growth factor (PDGF), interleukin 1β (IL1β), tumor necrosis factor α (TNFα), transforming growth factor β (TGFβ), C-X-C motif chemokine 12 (CXCL12), and matrix metalloproteinases (MMP), and interleukin-6 (IL6). This leads to the upregulation of ROS scavengers in CSC (7) and activation of downstream STAT3 signaling, a cascade known to promote self-renewal in embryonic stem cells neu (121). Furthermore, this promotes survival of tumor cells, facilitates tumor regrowth and leads to the development of highly invasive CSC phenotypes (122, 123).

Another mechanism by which the niche protects CSC is hypoxia. Oxygen is a potent radiosensitizer and is needed for radiation-induced ROS production and in further consequence for cell death. Lack of oxygen is known to increase radiation resistance (124–126) and has been associated with early relapse after RT. Consequently, increasing tumor oxygenation improves the response to RT (127–129). In addition to the absolute lack of oxygen and the resulting low ROS levels, CSC in hypoxic niches upregulate ROS scanvengers (7, 130, 131), thereby further lowering ROS levels compared to normoxic CSC. This in turn leads to the activation of the hypoxia-inducible factor (HIF) signaling route (132–134). Interestingly, HIF1α and the respective regulated cytokines have also been shown to be increased following RT (135). HIF are important master regulators of transcription of hypoxia response elements, which activates pro-survival pathways such as the Notch, wingless and INT-1 (WNT) and Hedgehog pathway (136–138). These pathways have been shown to be important for CSC maintenance and can lead to radioresistance and accelerated repopulation of CSC during or after treatment, as has been shown in glioma, breast cancer, and prostate cancer (97, 139–142).

### CSC AS BIOMARKER

There is accumulating evidence that CSC could be used as biomarkers to predict treatment response and estimate the likelihood of tumor relapse in cancer patients.  However, it has been shown in ovarian cancer that the prognostic value of CD44 may depend on its isoform, with the transmembrane form indicating a better prognosis, while the presence of the soluble extracellular domain was associated with a worse prognosis (166). In a recent meta-analysis, overall CD44 expression in ovarian cancer was associated with a high TNM stage and a poor 5 year overall survival (167). Along this line, low expression of CD44 was shown to be an independent factor of poor prognosis in ovarian mucinous carcinoma (168). Interestingly, in breast cancer, it has been shown that CD44 was associated with longer diseasefree-survival (DFS) in estrogen-receptor (ER) positive women, while CD44 positive tumors were associated with poor outcome in ER-negative patients (169). In a recent meta-analysis, Han and colleagues tried to generalize the prognostic significance of CD44 and its variant isoforms in advanced cancer patients. In this analysis of 15 articles with more than 1,200 patients, CD44 was slightly linked to a worse overall survival, but there was no correlation between CD44 expression and DFS, recurrence-free survival (RFS), or progression-free survival (PFS) (170).

Two studies from the German Cancer Consortium Radiation Oncology Group (DKTK-ROG) have shown that CSC marker expression is a potential biomarker for favorable prognosis in patients with locally advanced HNSCC, both after primary chemoradiotherapy (171) as well as following post-operative chemoradiotherapy (172). In a recent validation study from the same group, the addition of CD44 could further improve the prognostic performance of models using tumor volume, p16 status, and N stage (173).

Activity of the 26S proteasome, a protease complex with regulatory functions in cell cycle, DNA repair, and cell survival, is another CSC marker (131, 174–177). In this regard, low 26S proteasome activity correlated with high self-renewal capacity and high tumorigenicity in HNSCC cell lines (178). A high 26S proteasome activity correlated with a longer survival and higher local control rates in patients who underwent chemoradiotherapy for HNSCC (95).

Another potential biomarker, especially for glioma, might be the stem cell marker CD133. In a recent meta-analysis including 21 articles with more than 1,550 patients, CD133 expression correlated with higher grade of gliomas and worse prognosis in glioma patients (179). Interestingly, in a recent in vitro analysis in glioma cell lines, CD133 expression could be downregulated by vincristine, a common chemotherapeutic drug (180). In a study by Wu and colleagues, CD133 promotor methylation was a significant prognostic factor for adverse PFS and overall survival, while there was no correlation between CD133 protein expression and survival (181). Additionally, there are other publications that showed no association of CD133 protein expression with survival (182, 183).

#### NOVEL TREATMENT APPROACHES

Increased understanding of CSC has led to new ideas for improving cancer therapy. It certainly seems feasible to combine conventional anti-neoplastic therapy (e.g., RT or CHT) to target the tumor bulk with CSC specific treatment in order to improve outcome as compared to monotherapies (184, 185). Inactivation of even only limited numbers of CSC might significantly improve local tumor control probability (70). However, the assumed plasticity of the CSC and non-CSC compartments, especially the possible shift of stem cell traits, increases the complexity of treatment responses of tumors. In an ideal situation where the CSC population is strictly static, drugs that specifically target CSC would lead to a massively improved treatment outcome, possibly even without the need of additional treatment modalities (e.g., RT or CHT). However, CSC plasticity render a CSC-targeting monotherapy virtually impossible, since after treatment, non-CSC may gain CSC traits and repopulate the tumor. Additionally, regarding the current CSC marker and their uncertainty in robustly identifying CSC, and to sufficiently distinguish them from healthy SC, a strictly CSC-based therapy seems to be still a long way off.

One conceivable possibility to eliminate CSC with RT more efficiently is to increase the applied dose. This is usually not feasible for the whole tumor due to dose constraints of the surrounding healthy tissue. Therefore, visualization of CSC could allow for larger doses of radiation in CSC rich regions while still respecting the dose constraints. Indeed, there are first studies in mice, where CD133+ glioblastoma cells could be detected non-invasively by PET and near-infrared fluorescence molecular tomography using antibody-labeled tracer (186). Subsequently, the same group showed that near-infrared photoimmunotherapy using phototoxic antibody conjugates was efficient not only in rendering CD133+ glioblastoma cells visible but also in inducing cell death (187).

Another means by which RT can be utilized to eliminate CSC more efficiently is the use of types of irradiation other than commonly used photon beams (188, 189). Particle beams of protons and carbon ions are being increasingly used due to their advantageous depth-dose curve and their higher cellkilling efficiency compared with photons (190). Preclinical studies deliver promising results when using proton irradiation. For instance, in CSC-like cells from two human NSCLC cell lines, irradiation with protons was more efficient than photon treatment in reducing cell viability. clonogenic survival, cell migration, and invasiveness, while increasing apoptosis and ROS levels (191). Furthermore, proton irradiation has been shown to be more cytotoxic, induce higher and longer cell cycle arrest, reduce cell adhesion and migration ability, and reduce the overall population of CSC in NSCLC cell lines compared to photon irradiation (192). Finally, in glioma stem cells from glioblastoma patients, similar results have been achieved (193). In this study, particle irradiation with protons and carbon ions has been shown to be more effective in cell killing compared to photons, likely because of the different quality of the induced DNA damage. Indeed, compared to photons, proton beam irradiation has been shown to increase ROS levels, induce more single and double strand DNA breaks, less DNA damage repair (as measured by H2AX phosphorylation), and decreased cell cycle recovery which led to increased apoptosis (194). Interestingly, primary human glioma stem cells that were resistant to photon treatment could be rendered sensitive with carbon ion irradiation via impaired capacity to repair carbon ion induced DNA double strand breaks (195). Importantly, this study also showed an individual heterogeneity in the amount and radiosensitivity of glioma stem cells from different patients, further complicating a one size fits all treatment. In the recent years, immune checkpoint inhibitors have greatly improved treatment outcomes for many cancers. In this regard, it has been shown that proton irradiation increased sensitivity of CSC from different cell lines, such as breast or prostate cancer, to cytotoxic T-cell killing (196). These findings offer a rationale for the combined use of proton irradiation with immunotherapy. Another important aspect of particle irradiation is the reduced dependence from tissue oxygenation. While photon irradiation is always strongly affected by the presence of oxygen in the induction and maintenance of DNA damage, high LET particle beams can be much less hindered by hypoxic conditions, which are often found in solid tumors. For example, Tinganelli et al. (197) showed the survival of mammalian cells exposed to different types of particle radiation in various oxygen concentrations, leading to a hypoxia-adapted irradiation plan. Hence, it seems feasible and promising to use particle irradiation in order to counteract tumor hypoxia. Taken together, these results suggest a potential advantage of particle beam irradiations in CSC eradication, eventually in combination with conventional photon irradiation: photon beam irradiation to the whole tumor and a boost of particle beams to hypoxic areas within the tumor. Alternatively, one can ideally use a properly optimized plan of carbon or oxygen beam, or, considering the potential of the most advanced particle centers, a multiple-ion irradiation (198). Another new strategy in combating glioblastoma is the interference with metabolic pathways. It has been shown that dichloroacetate (DCA), an orphan drug, has been shown to switch the metabolism in freshly isolated glioma stem cells from mitochondrial oxidative phosphorylation to cytoplasmic glycolysis, which in turn increased mitochondrial ROS and induced apoptosis (199). In the same study, glioblastoma patients treated with the standard of care (i.e., radiation therapy and temozolomide) received oral DCA for up to 15 months. The drug was well-tolerated, and some patients showed prolonged radiologic stabilization and decelerated tumor progression. Additionally, DCA, in combination with PENAO [4-(N-(Spenicillaminylacetyl)amino) phenylarsonous acid] has been shown to increase radiosensitivity of glioma cells by inducing a cell cycle arrest, elevating ROS production, depolarizing mitochondrial membrane potential, increasing DNA damage, and inducing apoptosis (200).

Early experiments with CSC-directed antibodies have shown promising results. Gurtner et al. (201) used antibodies directed against CD44 that were loaded with highly cytotoxic drugs. In this experimental setting, these antibodies, combined with irradiation, led to an improved local tumor control. Considering the high expression of ROS scavengers in CSC, it may be reasonable to target these ROS scavengers. Pharmacological depletion of ROS scavengers (e.g., by treatment with buthionine sulfoximine (BSO), has been shown to reduce radiation resistance as well as clonogenic properties of CSC in breast cancer and HNSCC (202, 203). Additionally, the use of antioxidants during RT, which reduce ROS levels, might prove nonsensical, as high ROS levels are needed, especially in CSC, in order to facilitate RT-induced cell death.

Checkpoint pathways can be inhibited pharmacologically to prevent delayed cell cycle progression and hamper DNA damage repair in CSC as has been shown in glioma and prostate cancer (98, 204). Additionally, direct inhibition of DNA damage repair signaling has been shown to reduce radiation resistance in breast cancer CSC (92). Chemical inhibition of Notch signaling, a developmental pathway that is known to be essential for tissue homeostasis (205) has been shown to increase radiosensitivity in glioma CSC (206). However, most clinical studies regarding these signaling pathways focus on chemotherapy (207). There is preclinical data in mice with glioblastoma multiforme that were treated with RT and temozolomide combined with a Notch inhibitor. In this study, Notch inhibition had an antiglioma stem cell effect which provided a survival benefit (208). Regarding clinical data, there is an ongoing trial testing a Notch inhibitor combined with whole-brain RT or stereotactic cranial RT [NCT01217411], but so far there are no results of this study available.

Overcoming tumor hypoxia is another method to improve cancer therapy. Nitroimidazole derivates can mimic the effect of oxygen and can produce reactive species in hypoxic cells. There have already been clinical trials with a clinically relevant

#### REFERENCES

sensitization and low toxicity (209, 210). Nitric oxide (NO) is also able to mimic oxygen and thereby to increase radiosensitivity in hypoxic tissue. In a first clinical trial, the NO donor glyceryltrinitrate (GTN) has been shown to reduce hypoxia-induced progression of prostate cancer (211). Taken together, targeting the hypoxic niche of CSC might eventually improve treatment outcome following RT. An important task in this regard will be the correct identification of CSC for a given tumor, since CSC can differ between tumors both functionally/metabolically as well as phenotypically. Additionally, CSC share many properties and surface molecules with normal stem cells, making a clear distinction difficult and increasing the risk of unwanted side effects. Finally, it seems conceivable that drugs that interfere with spontaneous as well as RT-induced reprogramming of non-CSC into CSC could also be of value for cancer treatment. However, it needs to be investigated if these mechanisms are the same in normal steam cells and CSC before such drugs can be developed.

Another interesting approach to amplify the effect of radiation therapy, particularly on CSC, is the use of nanostructures that, after being endocytosed by cancer cells and following irradiation, release secondary electrons and large amounts of ROS (212). This could be especially effective in CSC, where ROS levels are generally lower. In this study, a significant tumor growth suppression and overall improvement in survival rate has been demonstrated in an in vitro and in vivo model of triple negative breast cancer.

#### CONCLUSION

There is growing evidence of a radiation resistance tumor subpopulation with increased DNA damage repair, increased survival signaling, and decreased ROS, that is furthermore protected by its environment. With refined understanding of these cells and their role in development and progression of cancer come new possibilities to improve cancer therapy. Targeting CSC, based on phenotype or function, seems promising. Nonetheless, we are just at the beginning and clinical data is still scarce. Major issues concern their correct identification and reliable distinction from healthy cells and the plasticity of the CSC department. It will be exciting to see which position CSC-specific therapies will occupy within the row of current anti-neoplastic therapies.

#### AUTHOR CONTRIBUTIONS

CA and JM performed the literature research. CA wrote the manuscript. I-IS and UG supervised the project.

breast, and lung cancers: verification of model estimates of need with radiotherapy utilization data from British Columbia. Int J Radiat Oncol Biol Phys. (2011) 79:1507–15. doi: 10.1016/j.ijrobp.2009. 12.070

3. Zhang-Salomons J, Mackillop WJ. Estimating the lifetime utilization rate of radiotherapy in cancer patients: the multicohort current utilization table (MCUT) method. Comp Methods Programs Biomed. (2008) 92:99–108. doi: 10.1016/j.cmpb.2008.06.011

combined treatments. Adv Drug Deliv Rev. (2017) 109:63–73. doi: 10.1016/ j.addr.2016.02.002

with clinical outcomes of gastric cancer patients. Asian Pac J Cancer Prev. (2018) 19:1313–8. doi: 10.22034/APJCP.2<IP_ADDRESS>3

CD133+ tumor stem cells. Proc Natl Acad Sci USA. (2014) 111:E692–701. doi: 10.1073/pnas.1314189111

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2020 Arnold, Mangesius, Skvortsova and Ganswindt. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Novel Therapeutic Strategies for Ovarian Cancer Stem Cells

Nastassja Terraneo1 , Francis Jacob2 , Anna Dubrovska3,4,5,6 and Jürgen Grünberg1 \*

1 Center for Radiopharmaceutical Sciences ETH-PSI-USZ, Paul Scherrer Institute, Villigen, Switzerland, 2 Ovarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland, 3 OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, 4 German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany, 5 German Cancer Research Center (DKFZ), Heidelberg, Germany, 6 Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany

Ovarian cancer (OC) is one of the most lethal gynecologic malignancies. Due to the lack of specific symptoms and screening methods, this disease is usually diagnosed only at an advanced and metastatic stage. The gold-standard treatment for OC patients consists of debulking surgery followed by taxane combined with platinum-based chemotherapy. Most patients show complete clinical remission after first-line therapy, but the majority of them ultimately relapse, developing radio- and chemoresistant tumors. It is now proposed that the cause of recurrence and reduced therapy efficacy is the presence of small populations of cancer stem cells (CSCs). These cells are usually resistant against conventional cancer therapies and for this reason, effective targeted therapies for the complete eradication of CSCs are urgently needed. In this review article, we highlight the mechanisms of CSC therapy resistance, epithelial-to-mesenchymal transition, stemness, and novel therapeutic strategies for ovarian CSCs.

#### Edited by:

Paul N. Span, Radboud University Nijmegen Medical Centre, Netherlands

#### Reviewed by:

Yoshihiko Hirohashi, Sapporo Medical University, Japan Janneke Hoogstad-van Evert, Radboud University Nijmegen Medical Centre, Netherlands

\*Correspondence:

Jürgen Grünberg<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Radiation Oncology, a section of the journal Frontiers in Oncology

Received: 30 September 2019 Accepted: 21 February 2020 Published: 17 March 2020

#### Citation:

Terraneo N, Jacob F, Dubrovska A and Grünberg J (2020) Novel Therapeutic Strategies for Ovarian Cancer Stem Cells. Front. Oncol. 10:319. doi: 10.3389/fonc.2020.00319 Keywords: ovarian cancer, cancer stem cells, epithelial-to-mesenchymal transition, L1CAM, radioimmunotherapy, Auger electron and alpha particle emitters, therapeutic strategies

## INTRODUCTION

#### Ovarian Cancer

Ovarian cancer (OC), which is a generic term for several different malignant tumors, is one of the most frequent cancer types in females (1). OC is the leading cause of cancer death among gynecological malignancies, and according to estimates, in 2019 ∼22,530 new cases of OC will be diagnosed and 13,980 OC-related deaths will occur in the U.S. (2). About 75% of all ovarian tumors and 90–95% of ovarian malignancies are epithelial ovarian cancer (EOC) (3) of different origin (4). The 5-year survival rate of OC varies from 30 to 92%, depending on the dissemination of the disease at the time of diagnosis (5). This type of cancer usually shows non-specific symptoms during the early development (e.g., abdominal distension and pain, loss of appetite, or increased urinary frequency) and currently there are still no reliable early screening strategies available (6). The most common sign of advanced disease is abdominal swelling due to ascitic fluids accumulation (7). OC is consisting of different histological subtypes with distinctive molecular genetic features, clinical presentations, and prognostic outcomes. In 2014, the new WHO criteria recognized five principal epithelial OC histotypes: high-grade serous (HGSC), low-grade serous (LGSC), endometrioid, clear cell, and mucinous carcinoma (8). Among them, HGSC is the most common histologic subtype of OC, with a poor 5-year survival rate of 35–40% and accounting for 70–80% of OC deaths (5, 9). Because of the lack of diagnostic methods, ∼75% of patients show the metastatic spread in the

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peritoneal cavity and adjacent organs at diagnosis, which corresponds to FIGO stages (International Federation of Gynecology and Obstetrics stages) III and IV (10). The FIGO OC staging system was first published in 1973 and revised in 2014 (11, 12). Stage I EOC (disease is confined to one or both ovaries) is usually associated with good survival rates and surgery alone is sufficient as a therapeutic approach; unfortunately, it is quite rare since most of the patients are diagnosed only at stages III and IV (13). At stage II, tumor includes either one or both ovaries with pelvic dissemination and spread into the uterus and/or fallopian tubes. This group makes up <10% and it is considered curable, usually with chemotherapy (12). Stage III EOC tumor implicates one or both ovaries with spread to the peritoneum, lymph nodes and/or other sites outside the pelvis. The majority of OC are HGSCs and patients are diagnosed at stage III (14). Stage IV is characterized by distant metastases affecting the liver, spleen and lymph nodes and/or to other organs or tissues outside the peritoneal cavity such as the lungs and bones.

### Ovarian Cancer Treatments

Current first-line treatment regimen for OC patients comprises complete debulking surgery. The reductive tumor procedure includes hysterectomy, omentectomy, and other affected tissues possible to remove. The goal of surgery is to reduce tumor burden and minimize residual disease, which is inversely proportional to survival (15). Indeed, residual lesions smaller than 2 cm have been associated with better survival than bigger ones (16). At the same time, debulking surgery allows to precisely establish the histologic subtype of the disease and, therefore, it is very important for diagnosis. Even though surgery is the basis for OC treatment, it is rarely curative alone for patients with advanced disease and it needs to be combined with chemotherapy.

In late 1990s, two phase III clinical trials combined cisplatin (CDDP) with paclitaxel (PTX) as adjuvant treatment for advanced stage OC (17). Ever since, the combination of taxane and platinum derivatives, like CDDP and carboplatin (CBT), has been used as a standard therapeutic approach for OC patients, leading to response rate, and complete clinical remission of 60–80% (18). Nevertheless, the majority of these patients will ultimately relapse with a median progression-free survival of 18 months (19). Usually, response rates to second-line chemotherapy are proportional to treatment-free interval (20). Different combinations of chemotherapeutics have been tested to overcome chemoresistance following first-line paclitaxelplatinum treatment, but clinical responses are short-lived and led to only minor survival improvements for patients with chemoresistant tumors (21). So far, radiation therapy (RT) has played a minor role in ovarian cancer. Abdominopelvic RT was associated with serious side effects and poor therapeutic efficacy for most of the patients (22, 23). Acute toxicity was most commonly due to cramps, diarrhea, nausea, vomiting and more severe myelosuppression, whereas long-term toxicity was associated with bowel obstruction (23, 24). The poor therapeutic effect was due to the limitation of dosage that causes toxicity to radiosensitive organs such as blood building system or kidney. Maybe new approaches in radiotherapy could lead to wider use of RT in OC [reviewed in Fields et al. (25) and Iorio et al. (26)]. Likewise, the use of radiolabeled antibodies for the management of advanced ovarian cancer after cytoreductive surgery and chemotherapy is limited and of no success so far. Antibodies directed to CA-125 (mAb OC-125) and MUC1 (mAb HMFG1) antigens labeled with iodine-131 or yttrium-90, respectively showed little or no therapeutic benefit in ovarian cancer patients (27, 28). Different reasons for the treatment failure were discussed. The dose of radiation may have been too low because of insufficient binding of the antibody or the lack of antigen expression in residual micrometastases. Furthermore, yttrium-90 is not the ideal isotope for irradiation of small tumor nodules. No pharmacokinetics was performed, and it is possible that there was limited systemic exposure to the intact radioimmunoconjugate. In addition, the anti-MUC1 antibody HMFG1 is not actively internalized into target tumor cells. In contrast to RT, radioimmunotherapy (RIT) is a targeted therapy were the antibody brings the radiation to the tumor site also to disseminated metastases. Non-specific irradiation of healthy tissue is normally low due to the clearing of the mAb from the blood. The dose-limiting organ is the bone marrow [reviewed in Larson et al. (29)]. New promising RIT approaches for the treatment of OC will be discussed during this report.

The better understanding of tumor biology and chemoresistance over the past years supported the development of molecular targeted therapies, improving survival and increasing the quality of life in OC patients. Many different inhibitors, such as tyrosine kinase inhibitors (30) and monoclonal antibodies (mAbs) targeting multiple crucial cancer pathways, including angiogenesis, cell survival, cell growth, metastasis formation and DNA repair, are currently tested in clinical trials (31). The most promising investigational agents include vascular endothelial growth factor (VEGF)-specific inhibitors and poly (ADP-ribose) polymerase inhibitors (PARPi). Bevacizumab (Avastin R , Genentech, Inc.), a recombinant humanized mAb against VEGF, blocks angiogenesis, enhancing the efficacy of standard therapy. In 2004, Bevacizumab has been clinically approved in the U.S. as the first angiogenesis inhibitor for colon cancer (32). In 2018, based on phase III GOG-0218 clinical study (NCT00262847), the FDA approved its use in combination with CBT and PTX, followed by single-agent bevacizumab for the treatment of patients with advanced (stage III or IV) ovarian epithelial, primary peritoneal or fallopian tube cancer after initial surgery (33). PARP enzymes are involved in different cellular functions, including DNA single-strand break (SSB) repair through base-excision repair by PARP1 (34). The first PARPi approved in the clinic was Olaparib (AZD2281, Ku-0059436 trade name Lynparza), an orally administered drug (35). In 2014, based on phase III SOLO-2 (NCT01874353) and phase II Study 19 (NCT00753545) clinical trials, Olaparib obtained an accelerated FDA approval as maintenance treatment for patients with a recurrent ovarian epithelial, fallopian tube or primary peritoneal cancer, who are in complete or partial response to platinum-based chemotherapy (35–38). In the same year, based on phase II Study 19 and phase II Study 42 (NCT01078662), the EMA authorized Olaparib as maintenance treatment for patients with platinum-sensitive, relapsed BRCA-mutated (germline or somatic) HGSC, who responded to the last platinum-based chemotherapy (38, 39). Other types of tumorigenic pathway inhibitors targeting PI3K/AKT, mTOR, Src, and FRα are still in the early phase of development (38). To date, no effective cure for OC has been found. Considering the heterogeneous nature of OC and the lack of a common deregulated pathway in most patients, individualized therapy seems to be essential to improve survival.

### TUMOR HETEROGENEITY

Two main models have been used to explain histological and molecular heterogeneity, a common feature of most solid tumors: the clonal evolution (CE) or stochastic model and the cancer stem cell (CSC) or hierarchical model. In recent times a third model, called the plasticity model, linking CE, and CSC models has been postulated (**Figure 1**).

#### The Clonal Evolution or Stochastic Model

In the 1970s, with the discovery that mutations in oncogenes and tumor suppressor genes trigger most human cancers, Nowell introduced the clonal evolution (CE) concept (40). The CE model assumes that every tumor cell is biologically equivalent and potentially able to drive tumor progression (41). The majority of cancer cells have only restricted proliferative potential and tumor progression is driven by the acquisition of gene mutations and epigenetic alterations in the original clone (42, 43). The progress from early to invasive carcinoma implicates the stepwise acquisition of random mutations in specific cancer genes, leading to uncontrolled proliferation and high tumor heterogeneity (44).

### The Cancer Stem Cell or Hierarchical Model

In the early 1990s, with the introduction of new technologies such as fluorescence-activated cell sorting (FACS) and mouse xenografts assays for hematopoietic stem cells, Dick and colleagues found that tumor engraftment in acute myelogenous leukemia (AML) could only be initiated by CD34+/CD38- cell population (45). In 2003, Clarke et al. applied for the first time the same experimental approach to solid breast cancer (46). Using xenograft assay, they showed that as few as 100 CD44+/CD24−/low breast cancer cells were sufficient to induce tumors, in contrast to thousands of cells expressing different markers (46). Moreover, this tumorigenic population has been passaged several times and these cells were always able to induce tumors recapitulating the original tumor composition, forming both CD44+/CD24−/low tumorigenic and non-tumorigenic cells. Afterwards, similar studies on other solid tumors, such as brain, breast, prostate and colon cancer, were published (47, 48). Most studies on CSCs have been performed in a similar way. Generally, small populations of cells defined by a specific marker or marker panel and expressed in a heterogeneous way in a particular type of tumor, are isolated from cell lines or primary tumors. When transplanted into immunodeficient mice, these cells can induce tumor growth over weeks or months and to reproduce the heterogeneity of the initial tumor (49). A frequency of CSCs present in a given tumor population can be analyzed in limiting dilution assay (LDA) by transplanting increasing dilutions of single tumor cell suspensions. LDA analysis in vivo is the gold standard to determine the CSC frequency in a given tumor cell population (50, 51). In addition to LDA, subsequent transplantation assays provide an important information about

FIGURE 1 | Models of tumor development and heterogeneity. (A) The cancer stem cell (CSC) model of tumor development. Genetic or epigenetic mutations activate stem-like programs in a single cell, generating a CSC. This CSC is able to indefinite self-renewal and/or differentiation and all derived tumor cells have a hierarchical inheritance pattern. (B) The clonal evolution (CE) model of tumor development. Due to the acquisition of epigenetic and genetic mutations through time, any cell might have tumorigenic potential. Tumor heterogeneity is due to the propagation of cells carrying genetic mutations. (C) The plasticity model highlights the plastic state of cancer stemness. Based on the model, differentiated non-tumorigenic cancer cells can potentially revert back to CSCs.

the long-term self-renewal and tumor regeneration capacity of the tentative CSC populations (52). An emerging gene engineering technologies including applications of CRISPR-Cas9 system for target genome editing substantially simplified generation of knockin or knockout cell and mice models. The genetically modified patient-derived organoid and mice models where a given cell population can be traced in vivo is an important tool to identify tumor cell of origin (53, 54). Nevertheless, because of technical issues, many theoretical and experimental details about the CSC model have remained unexplored and the frequency of CSCs in solid tumors is highly variable. Technical issues include inconstant purity of tumor cell isolation, the necessity of more solid and reliable markers and the challenges related to xenotransplant assays that offer a different environment than the original tumor niche (55).

The CSC model suggests that the origin and the progression of many cancers are driven by small subpopulations of cells with stem-like properties; however, this model does not address the question of whether tumors arise from normal stem cells. Instead, it suggests that, regardless of the cell-of-origin, many cancers are hierarchically organized in the same manner as normal tissues and CSCs share similar molecular properties to normal stem cells. In accord with this model, tumors have a hierarchical structure, with tumorigenic CSCs at the top that generate both intermediate progenitors (also called transitamplifying cells) and terminally differentiated cells. Considering that the same CSC populations can originate from different cancer subtypes, the frequency of CSCs can highly vary among tumor types and also within the same tumor, leading to tumor heterogeneity (56). CSCs, like non-neoplastic stem cells, have extensive proliferative potential and generate the differentiated progeny that form most of the tumor mass and it is highly sensitive to cancer therapies. Additionally, these cells can remain quiescent for prolonged periods of time, which renders them unresponsive toward radiation and chemical insults, including cytotoxic drugs designed to target fast-proliferating tumor cells (57). Interestingly, recent studies have highlighted some common features (58, 59) but also many differences in stem cell programs operating in CSCs and non-neoplastic stem cells (60).

### The Plasticity Model

It is now evident that one model does not exclude the other and both might contribute to cancer development, depending on tumor type and stage (61).

In recent years, an alternative model based on cellular plasticity, which links the CE and the CSC models, has emerged (61–63). The plasticity model proposes that cancer cells in different types of tumors including OC can switch between stem cell-like and differentiated states so that some differentiated non-tumorigenic cancer cells can de-differentiate to become CSCs (64). Therefore, CSC-like phenotype is flexible and dynamic, instead of being a fixed property of tumor cells. Signaling within the tumor microenvironment (tumor niche), including oxygenation, cell-to-cell contact and secreted factors, could induce differentiated tumor cells to re-acquire stem celllike properties (62). Additionally, radio- and chemotherapy treatments have been shown to enrich CSC subpopulations in residual tumors because of selective pressure on drug-resistant cells (65–67) and due to tumor cell plasticity (64). Even though the CSC state has high plasticity, it is of high clinical importance as a potential marker for clinical outcome and target for anticancer treatment (68, 69).

### OVARIAN CANCER STEM CELLS

Regardless of the high response rate to standard therapy, most OC patients develop recurrent chemoresistant disease (70). Recurrence is believed to be caused by the presence of residual tumor-propagating cells that cannot be completely eradicated by surgical and/or pharmacological regimens (9). Accumulating evidence suggests that among these residual cancer cells some have the key stem cell-like properties such as self-renewal and differentiation (71, 72). This small population of cells appears to form and to sustain the tumor bulk population, being responsible for disease recurrence after the first-line treatment (73). In some studies, these cells have been isolated by flow cytometry and were discovered to be enriched in a side population (SP) able to efflux the Hoechst33342 dye by cell transporters using the same mechanism with which normal cells efflux toxic drugs (74, 75). Further investigations revealed that these cells have several characteristics in common with normal tissue stem cells. In 2005, Bapat et al. were one of the first groups that characterized the presence of ovarian CSCs from patient ascites, showing tumorigenic properties of these cells (71). In addition to selfrenewal and the ability to give rise to more differentiated progeny, CSCs are highly tumorigenic and display increased resistance against conventional cancer therapies (76–78). As of today, there are still considerable controversies on the OC CSCs due to the heterogeneity of CSC phenotypes, plasticity of CSC states as well as limitations of the current research methodology for CSC characterization. Nevertheless, reliable markers of OC CSCs have been successfully validated by xenograft transplantations of the serial tumor cell dilutions (limiting dilution assay) along with serial tumor transplantation and lineage-tracing assays (79–82). These analyses are currently "gold standard" assays to measure key CSC properties such as self-renewal and multipotency (52). In support of these preclinical findings, clinical significance of CSCs was recently confirmed by a number of studies demonstrated the association of CSC markers with clinicopathological parameters and clinical outcomes of OC patients (69).

#### Ovarian Cancer Stem Cell Markers

The proportion of CSCs can vary depending on tumor type and in the context of OC, CSC frequency shows high interpatient variability (83). Considering CSCs resistance against conventional cancer treatments, the development of more efficient tumor therapies requires effective identification and functional characterization of these cell populations. The expression of several individuals or combined cell surface markers has been associated with CSCs (**Table 1**). The multiplicity of CSC markers, along with their plasticity, might pose a challenge to detect successful CSC-targeting therapeutic strategies. For this reason, it is important to select

#### TABLE 1 | List of some putative CSC markers.

reliable molecular markers that could be used to develop new therapies.

One of the best-characterized CSC surface markers is the transmembrane glycoprotein CD133 (also known as AC133 and Prominin-1), initially identified as hematopoietic stem cell marker supporting stem cell maintenance and expansion (85, 86). CD133 localizes to plasma membrane protrusions and microvilli, indicating its role in membrane organization (86). Several recent studies revealed the role of CD133 as a positive regulator of Wnt, PI3K and EGFR signaling pathways (87, 88). However, the exact physiological function of CD133 in normal and cancer cells is still elusive. CD133 was first characterized as CSC marker in glioblastoma (89) and later it was found to be widely expressed in tumor-initiating cells of different tumors (e.g., ovarian, liver, lung, pancreatic and prostate cancer) (90). Several groups have identified the expression of CD133 in OC cells, which is connected with tumor initiation, selfrenewal and chemoresistance (91, 92). Some published studies indicated the phenotypic heterogeneity and plasticity of CD133 expression (80). This finding might explain why some data did not support the link between CD133 and ovarian CSCs, showing inconsistent expression and no increased spherogenic or tumorigenic properties of CD133+ in comparison to the CD133− counterpart (93, 94). Inconsistent CD133 detection because of different immunoreactivity of primary anti-CD133 antibody clones might also account for discrepancies in the identification of CSCs (95).

The human genome encodes 19 aldehyde dehydrogenase (ALDH) enzymes implicated in detoxification of endogenous and exogenous aldehydes via NAD(P)+-dependent oxidation (96, 97). Upon chemotherapy and irradiation, these enzymes catalyze the oxidation of aldehydes (oxygen, carbon, and hydrogen) to carboxylic acids to prevent DNA damage. ALDH modulates the expression of drug transporters to efflux chemotherapeutic agents, contributing to cell-acquired drug resistance against conventional cancer therapies (98). Additionally, the ALDH protein family catalyzes the oxidation of retinoic acid, which regulates the differentiation of normal stem cells and CSCs (99). The ALDH1 subgroup is highly expressed in normal and CSCs. Among ALDH1 isozymes, ALDH1A1 is more widely expressed in CSCs of different cancer types than ALDH1A2 and ALDH1A3 (100). The study of the ALDH1 expression in 24 types of normal and six types of epithelial tumor tissues revealed that increased expression of ALDH1 was significantly associated with poor outcomes for 439 patients with serous OC (68). Furthermore, ALDH expression in combination with CD133 correlates with poor patient prognosis and characterizes an ovarian CSC population (76, 101). However, recent research suggested that ALDH is a better marker to identify ovarian CSCs than CD133, as ALDH correlates with tumorigenicity and spheroid formation (102). It is now well-known that only cancer progenitor cells have the ability to proliferate under nondifferentiating and non-adherent conditions, forming 3D tumor spheres (103). These spheres are enriched by cells displaying stem cell-like properties, including the upregulation of some stem cellspecific genes, high ALDH activity, self-renewal ability along with high proliferative and differentiation properties (102, 104, 105). Consequently, sphere-forming cells display aggressive growth, migration, invasion, clonogenic survival, anchorage-independent growth, and reduced drug responsiveness in vitro (105).

CD44 cell transmembrane glycoprotein has been associated with several signal transduction pathways, including NANOG and EGFR-Ras-ERK (106). The main CD44 ligand is hyaluronic acid, a component of the extracellular matrix, which is positively associated with OC migration and metastatic spread (107, 108). CD44 is expressed in both normal and ovarian CSCs and it is associated with sphere-forming ability, self-renewal, chemoresistance, tumorigenicity, proliferation and invasiveness (109). Additionally, high expression of CD44 correlates with epithelial-to-mesenchymal transition (110) and with stem celllike properties, contributing to tumor invasion, metastasis, disease recurrence and chemoresistance (111). The co-expression of CD44 with the c-Kit receptor CD117 was shown to define an ovarian subpopulation with tumor-initiating capacity (72). C-kit regulates survival, proliferation and chemoresistance of ovarian CSCs through PI3K/AKT and Wnt/β-catenin-ATPbinding cassette G2 signaling (112).

CD24 is a glycosylphosphatidylinositol-anchored membrane glycoprotein recognized as a positive or negative marker for CSCs in numerous cancer types. The low expression of CD24 combined with high CD44 (CD44+/CD24−/low) is used to identify breast CSCs (46). On the contrary, several data indicated CD24 as a positive marker for ovarian CSCs. A population of CD24+ cells isolated from OC samples and cell lines was shown to display high expression of stemness-related genes, high tumor initiation and fast tumor growth along with increased sphereforming ability (113, 114). Besides, Davidson and colleagues demonstrated that tumor cells collected from OC peritoneal fluids exhibited higher levels of CD24 than solid tumors, suggesting an enrichment of CSCs (115).

Epithelial cell adhesion molecule (EpCAM), also called CD326, is a transmembrane glycoprotein overexpressed in many carcinomas (116). Several studies described a controversial role of EpCAM in carcinogenesis. Being an adhesion molecule, EpCAM regulates homophilic adhesion interactions, which might inhibit metastatic invasion (116). However, depending on the microenvironment, EpCAM is also able to suppress E-cadherin adhesions, supporting metastasis formation. EpCAM has been recognized as an additional marker for CSCs in different tumor types (55). High expression of EpCAM in OC is associated with tumor recurrence, chemoresistance and poor patient prognosis (117). Cells co-expressing CD24, CD44, and EpCAM showed stem cell-like characteristics, high tumorigenicity in vivo as well as enhanced migration, invasion and colony-formation in vitro and this population could be enriched by chemotherapy (50, 118).

There are also several stem cell-associated genes that play a role in the maintenance and development of ovarian CSCs. LIN28, OCT4, SOX2, and NANOG transcription factors (TFs) regulate and maintain pluripotency in embryonic stem cells (119). The co-expression of LIN28 and OCT4 identifies a population of ovarian CSCs and correlates with advanced tumor grade (120). NANOG is closely associated with HGSC, high chemoresistance and poor overall patient survival (121). SOX2 is required to maintain ovarian CSCs and its expression correlates with chemoresistance and poor prognosis (122).

### Mechanisms of Cancer Stem Cell Therapy Resistance

Conventional therapies are often not sufficient to eliminate CSC populations because of intrinsic resistance mechanisms and epigenetic plasticity of the cells (123, 124). This means in many cases, tumor relapse is caused by the incomplete elimination of all CSCs, since a single CSC seems to be sufficient to regrow a tumor [**Figure 2**; (125)].

Several molecular mechanisms, such as enhancement of DNA repair and DNA damage response (DDR), increased drug efflux, efficient scavenging of reactive oxygen species (ROS) and signals from the microenvironment, support the resistance of CSCs toward conventional cancer therapies [**Figure 3**; (126)].

#### Increased DNA Pepaire Capacity

Radiation and many chemotherapeutic drugs (e.g., DNA crosslinkers, DNA synthesis, and topoisomerase inhibitors) induce DNA damage, which, if not repaired, can lead to cell death (127). Among different types of DNA damages caused by radiation and chemotherapy, DSBs are the most lethal lesions if not repaired (128). DSBs are usually repaired by error-free homologous recombination (HR) or error-prone non-homologous end joining (NHEJ) mechanisms (129). In response to radiation, DNA repair is initiated and controlled by the DNA damage response (DDR). For the purpose of stalling cell cycle progression and give time to the cells to repair DNA damage, DDR triggers the activation of checkpoint kinase signaling pathways such as ataxia telangiectasia mutated (ATM)-checkpoint kinase 2 (Chk2) and ATM-Rad3-related (ATR)-checkpoint kinase (Chk1) (130, 131). CSC populations of glioblastoma, prostate, lung, breast cancer and many others, have been shown to possess high DNA repair capacity, mainly due to increased activation of ATR-Chk1 and ATM-Chk2 pathways (130). Recent reports demonstrated increased HR-dependent DNA repair proficiency of CSCs in OC that makes them more resistant to PARP inhibition (132). Different populations of OC CSCs have a high resistance to the platinum agents due to the altered regulation of cell cycle checkpoint, upregulation of the Fanconi Anemia DNA repair proteins (FANCD2, FANCJ) (133), MLH1, and BRCA1 (134) and increased expression of DNA polymerase eta (135).

### ROS Scavenging

Radiation-induced damages include the formation of ROS, which are chemically reactive free radicals produced by oxygen metabolism. ROS are involved in many physiological signaling pathways regulating metabolism, cell proliferation, migration, angiogenesis and wound healing (136). However, in high amounts, ROS can produce oxidative DNA damage, alter proteins and cell membrane lipid bilayer, leading to cell arrest and cell death (137). The cells control ROS levels through ROS scavenging molecules (e.g., glutathione peroxidase, superoxide dismutase, and catalase), which balance the production and the elimination of these products (137). CSCs isolated from different tumors exhibit more efficient ROS scavenging systems and a lower level of ROS production compared to non-CSC

populations (138, 139). ALDH positive population in OC has an upregulation of NRF2 (Nuclear factor erythroid 2-like) signaling driving the cytoprotective response to the oxidative stress (140).

### Enhanced Drug Efflux by ABC Transporters

Another important mechanism for CSC drug resistance is the high expression of ATP-binding cassette (ABC) transporters. The human genome encodes 49 ABC genes and these proteins are essential to maintain homeostasis and to protect the cells against environmental insults in many normal tissues (e.g., liver, intestine, blood-brain barrier, placenta, kidney, and normal stem cells) (141). Three ABC transporter proteins, P-glycoprotein (Pgp, MDR1, ABCB1), multidrug resistance protein 1 (MRP1, ABCC1), and breast cancer resistance protein (BCRP, ABCG2), have been shown to play a role in multidrug resistance of various types of cancers like OC, breast, lung, colon and others (142). Due to broad substrate spectrum specificity, their expression provides tumor resistance toward the major classes of chemotherapeutic drugs (126). CSC populations of different tumors, including breast cancer, lung cancer, retinoblastoma, neuroblastoma, and glioblastoma, have been demonstrated to overexpress ABC transporters, which correlates with high drug resistance (143).

### Aldehyde Dehydrogenase Activity and Activation of Developmental Pathways

Supplementary intrinsic mechanisms underlying CSC therapy resistance are mediated by high ALDH activity and activation of developmental pathways essential for embryonic development and tissue homeostasis like the canonical Wnt/β-catenin, Notch and Hedgehog pathways (126). Notch signaling contributes to survival and platinum resistance of ovarian CSCs and it has been determined that Notch 3 expression is associated with poor prognosis for OC patients (144). Hedgehog signaling is aberrantly activated in OC and this pathway affects cell growth, motility, invasion, and tumorigenesis (145). Wnt/β-catenin is involved in stem cell proliferation and differentiation. CSCs of many tumors were found to overexpress β-catenin, which promotes stemness (146). In OC, genetic mutations in the Wnt pathway are rare, but recent data demonstrated that the activation of Wnt signaling could be regulated by the tumor microenvironment, contributing to ovarian tumorigenesis (147).

### Cancer Stem Cell Niche and Their Microenvironment

Growing bodies of evidence showed that microenvironmental stimuli coming from the specific niche in which CSCs reside could influence and regulate treatment responsiveness (**Figure 4**). Additionally, autocrine signaling and stimuli coming from stromal fibroblasts, immune cells and extracellular matrix (ECM) as well as oxygen, nutrient supply and tissue pH, might affect CSC properties and metastatic dissemination (136).

Matrix metalloproteinases (MMPs) are extracellular proteases able to degrade and cleave ECM molecules, remodeling CSC niche and releasing growth factors and cytokines, thus, being suggested to regulate signaling pathways that control proliferation, differentiation and tumor invasion (148).

Tumor and stroma-derived growth factors and cytokine regulating stemness and resistance comprise interleukin-6 (IL-6), interleukin-8 (IL-8), chemokine (C-X-C motif) ligand 12 (CXCL12), chemokine (C-X-C motif) receptor type 4 (CXCR4), chemokine (C-C motif) ligand 2 (CCL2), platelet-derived growth factor (PDGF), transforming growth factor-beta 1 (TGF-β1), tumor necrosis factor-alpha (TNFα), epidermal growth factor (EGF), VEGF and fibroblast growth factor (FGF) (62, 126). IL-6, which is secreted by tumor-associated stroma has been shown to play an important role in the enrichment of OC stem cells after treatment with platinum agents (149). Dual expression of CXCR4 and CD133 has been used to identify an OC population with stem cell-like properties that regulate tumor development and chemoresistance (92). The formation of new vessels, also known as angiogenesis, supports tumor growth and it is tightly regulated by angiogenic activators including VEGF, FGF, PDGF, and EGF (150). Bao et al. determined that glioblastoma CD133+ CSCs highly express VEGFA, which contributes to the angiogenic process by interacting with the microenvironment (151). A recent study revealed that VEGFA stimulates OC stem cells by activation of the epigenetic mechanisms inducing loss of miR128- 2 and upregulation of Bmi1 (152).

The association between inflammation and cancer development has been suggested for numerous types of tumors (153). The accumulation of proliferating tumor cells mimics a chronic inflammation and the activated stroma cells produce a number of cytokines, angiogenic factors and chemokines, which in turn recruit more immune cells including monocytes and macrophages. The most common inflammatory molecules released in the microenvironment by tumor-associated macrophages (TAMs) are the EMT-inducers TGF-β1 and TNFα (154). EMT confers stem cell-like phenotype to cancer cells, enhancing motility and drug resistance.

In addition, tissue oxygenation influence CSC properties, maintaining cells in a quiescent (hypoxia) or activated (normoxia) state. For example, hypoxia is a major stimulant of CXCL12, which is secreted by tumor stroma fibroblasts and is involved in the early stage of malignant transformation of OC (139). Hypoxia makes CSCs more resistant to various environmental insults and it is the major stimulant of angiogenesis. Hypoxia-inducible factor (HIF) target genes, such as GLUT-1, VEGF, OCT4 and Notch, are crucial regulating proliferation, tumorigenicity and self-renewal in different cancers (155). HIF induces stem cell properties in OC cells (156) and promotes OC stem cells adaptive stress response (157) and resistance to therapy (158). Hypoxia has been demonstrated to promote the acquisition of stem cell-like state through the increased expression of CSC markers like CD133 and CD44, along with CSC-related genes such as SOX2 (155). Moreover, hypoxia is also tightly associated with chemoand radioresistance. Low oxygen conditions maintain CSCs in a quiescent state with a low proliferation rate and since most conventional cytotoxic drugs target proliferating cells, CSCs cannot be destroyed. It is also recognized that the local concentration of oxygen improves radiotherapy efficacy since DNA lesions caused by ROS react with oxygen-generating stable DNA peroxides (159). Tumor oxygenation and oxygen therapeutics have been utilized as radiosensitizers to improve patients' response to radiotherapy (160).

### Epithelial-To-Mesenchymal Transition and Stemness

In recent years, high plasticity of CSCs and stemness have been increasingly linked to EMT. EMT is an essential cellular process usually involved in embryogenesis, wound healing and tumorigenesis. During tumor progression, neoplastic cells switch from an epithelial-like state to gain mesenchymal properties. Therefore, EMT allows cancer cells to become migratory and invasive, acquiring multiple properties associated with highgrade malignancies (161). EMT is suggested to be a reversible process where mesenchymal-like cells might transition back into an epithelial state, a process called mesenchymal-to-epithelial transition (MET). A number of TFs, referred as EMT-TFs, are associated with EMT and can be classified into three main protein families: Snail (Snail and Slug), ZEB (ZEB1 and ZEB2), and basic helix-loop-helix (TWIST1, TWIST2, and TCF3) families (162). These TFs coordinate changes in gene expression resulting in suppression of genes associated with the epithelial state, like E-cadherin, and in upregulation of genes correlated with the mesenchymal state, including N-cadherin and vimentin (162). The activation of some of these TFs, including Slug, ZEB1, ZEB2, TWIST1, and Snail1, has been linked to the expression of stem cell-related genes and self-renewal in various tumor types (163). The EMT process is controlled by a variety of cytokines and growth factors and among them TGF-β signaling plays a fundamental role. TGF-β signaling regulates ovarian CSCs through the modulation of tissue transglutaminase 2 (TGM2), which promotes EMT, metastasis and stem celllike phenotype (164, 165). Hypoxia, through the expression

of HIF-1α and HIF-2α, regulates CSC-associated genes and induces EMT via the TGF-β signaling pathway, which in turn contributes to stemness (166). Cancer cells with an intermediate EMT phenotype display stem cell-like properties accompanied by enhanced resistance to several anti-cancer drugs [**Figure 5**; (124)]. In 2011, Strauss and colleagues identified a minor population of OC cells in a transitory epithelial/mesenchymal hybrid stage (i.e., partial or intermediate EMT), which means that these cells expressed at the same time epithelial and mesenchymal markers, respectively linked to adhesion and migration (167). The observation that these cells drive tumor growth in vivo and have the capacity of self-renewal provided a link between stemness and phenotypic plasticity. Many other studies have highlighted a connection between partial EMT, drug resistance and tumor-initiating ability, showing that this phenotype enables the formation of highly metastatic circulating-tumor cells clusters (168). Therefore, EMT gives a hint about the plasticity model, showing that plasticity enhances invasion potential and tumorinitiating properties of cells that arrive at the metastatic site (169). Stemness is therefore not a fixed and inherent property but instead, CSCs and non-CSCs can bidirectionally interconvert between these two states (168).

### NOVEL THERAPEUTIC STRATEGIES FOR OVARIAN CANCER

High-throughput approaches have identified numerous potential therapeutic targets to treat cancer cells specifically. The current focus of anti-cancer drug discovery is the development of molecular targeted therapies rather than conventional cytotoxic drugs. A major challenge remains to find agents and strategies that select and eliminate the source of tumor recurrence after

Clinical trial information accessed via https://clinicaltrials.gov with National Clinical Trial Number (NCT Number).

therapy, along with bulk tumor cells. It became increasingly evident that CSCs are crucial for disease recurrence and chemoresistance, thus targeting these cells seems a promising way to reach complete tumor eradication.

#### Inhibition of Cancer Stem Cell-Associated Pathways

Novel therapies have been employed to target CSC-specific markers or pathways critical for regulation and maintenance of stem cell-like properties (**Table 2**).

Metformin hydrochloride is clinically used as an anti-diabetic drug for type 2 diabetes. Recent studies have reported its ability to enhance chemotherapy efficacy in different cancer types by targeting CSCs. Metformin showed a synergic effect with standard chemotherapeutic agents, reducing tumor relapse rate (170). Shank and colleagues elucidated a potential mechanism behind this effect, demonstrating that the treatment with metformin reduced ALDH+ ovarian CSCs, proliferation and angiogenesis in vitro and in vivo. This effect was additive in combination with CDDP (171). The outcomes of combinational treatment with metformin and chemotherapy in patients with stage III and IV OC are currently investigated in phase II clinical trial (NCT02122185) (172). Treatment of OC cell lines with the FDA approved PARPi olaparib and rucaparib enriched cells with highly efficient DNA repair mechanisms. These cells expressed the CSC markers CD133 and CD117 (132). This might explain why patients who received PARPi treatment develop resistance in spite of a good initial therapy response. Several developmental pathways, including Notch, Wnt and Hedgehog, are crucial for self-renewal and regulation of CSCs (173). The inhibition of these pathways in combination with traditional chemotherapy has been proposed as a promising therapeutic strategy for recurrent diseases.

Sonidegib is an FDA approved Hedgehog inhibitor for basal cell carcinoma. Sonidegib was tested in phase I clinical trial in combination with PTX (NCT01954355) as a treatment for patients with advanced OC, demonstrating anti-tumoral activity. Based on this study, a recommended dose for phase II trial has been identified (174). The second Hedgehog inhibitor, Vismodegib, was used in phase II clinical trial as maintenance therapy for patients diagnosed with OC in second or third complete remission (NCT00739661) (175). However, no significant survival benefit was observed (5.8 months for placebo vs. 7.5 months for the treatment group), implying that the blockage of the Hedgehog pathway alone is probably not enough to destroy recurrent disease (175). The Wnt inhibitor Ipafricept reduces CSC frequency, promotes cell differentiation in patient-derived OC xenografts and in phase I clinical trial in association with carboplatin and PTX for recurrent platinumsensitive OC (NCT02092363), 82% of patients achieved a partial or complete response (176). Focal adhesion kinase (FAK) is a cytoplasmic protein overexpressed in CSCs of different tumors and it maintains interaction with stromal cells to activate intracellular signaling cascades (62). Defactinib, an oral inhibitor of FAK, exhibited modest activity in phase I clinical trial in combination with PTX for advanced OC (NCT01778803), suggesting that targeting the CSC niche might offer a suitable therapy strategy (177).

#### New Radioimmunotherapy Approaches

At the Center for Radiopharmaceutical Sciences of the Paul Scherrer Institute we developed the anti-L1 cell adhesion molecule (L1CAM) chimeric monoclonal antibody chCE7 for radioimmunotherapeutic (RIT) approaches to cancer. The L1CAM is a 200–220 kDa type I membrane glycoprotein of the immunoglobulin superfamily, containing six immunoglobulinlike domains and five fibronectin type III repeats followed by a transmembrane region and a highly conserved cytoplasmic tail (178–180). Firstly, L1CAM was identified as a protein of the nervous system and during brain development it was shown to play an important role in morphogenic events like neurite outgrowth, fasciculation, adhesion and neuronal cell migration (181). L1CAM is expressed in human peripheral nerve bundles and human kidneys, while it is absent in other human tissues comprising heart, lung, colon, liver, thymus or testis (181, 182). Low levels of L1CAM are also detectable in hematopoietic cells (181). L1CAM is overexpressed in various types of human cancers, including ovarian and endometrial carcinoma, colon cancer, melanoma and glioblastoma, and it usually correlates with advanced tumor stage and poor prognosis (179, 180). L1CAM expression in cancer supports motility and invasion, promoting aggressive tumor growth and metastasis formation (180). Additionally, L1CAM in combination with CD133 characterized a new ovarian CSC population (82). This protein exhibits static and motility-promoting functions, eliciting different signaling pathways depending on the binding partners; L1CAM homophilic interactions support static cell-cell binding while binding of L1CAM to integrin induces motility and invasiveness (180).

Indeed, the restricted expression of L1CAM allowed the use of anti-L1CAM mAbs for OC targeted therapies (183). Previous work revealed that chCE7 binds near the RGD sequence in the sixth Ig-like domain of human L1CAM, preventing its binding with integrin (184). RIT using copper-67 and the radiolanthanides lutetium-177 (177Lu) and terbium-161 (161Tb) was demonstrated to increase the efficiency of antibody-based L1CAM therapy in preclinical OC models (183, 185, 186). The antigen-antibody complex usually internalizes by endocytosis and the coupled metallic radionuclides are trapped in the cell (187). Therapeutic results for RIT in solid tumors (as adjuvant therapy after primary surgery and/or chemotherapy) have been modest during recent years and the main obstacles include low radiosensitivity, poor lymphatic drainage, limited diffusion of the antibody through tumor mass, poor vascularization and lack of homogeneous targeting (188). To overcome these limitations, several new strategies, including bioengineering development of different antibody formats to improve tumor penetration, pretargeting approaches, the use of alpha particle or Auger electron emitters, as well as dose fractionation, have been developed over the past years (188). Furthermore, RIT has been combined with other chemotherapeutics, including DNA-damaging agents (e.g., CDDP), microtubules-stabilizing agents (e.g., PTX) and protein kinase inhibitors (PKIs) providing cellular radiosensitization effects (189, 190). PTX enhances anti-L1CAM RIT effectiveness, blocking cancer cells in the radiosensitive G2/M cell cycle phase. Our group could recently demonstrate that in vivo combination therapy with 177Lu-DOTA-chCE7 [177Lu was coupled to the mAb via the chelator 1,4,7,10-tetraazacyclododecane-N-N'-N"-N"' tetraacetic acid (DOTA)] and PTX significantly extended overall survival of ovarian tumor-bearing mice (55 days RIT+PTX vs. 18 days PTX and 29 days RIT) (189).

Different properties of alpha-particles and Auger electrons, including short path length and high density of released energy in tissue, make them appropriate for targeted therapies against small volume diseases like metastases (<1 cm diameter) and for eradicating radioresistant CSCs (191).

The low-linear energy transfer (LET) refers to the energy released over the track length of the radiation in biological tissues. At equal absorbed dose, high-LET particles result in relatively high deposition of energy in tumor cells, which renders these forms of radiation more cytotoxic than low-LET radiations (**Figure 6**).

Most beta-particles emit low-LET radiations of 0.1–1 keV/µm, while alpha-particles have high-LET values of 50– 230 keV/µm and Auger electrons intermediate-LET of 4 to 26 keV/µm (192). Low-LET of beta-particle emitters is due to intermediate energy (0.5–2.3 MeV) and long-range in biological tissues (0.5–12 mm), producing easily reparable sparse DNA lesions (193).  Because of heterogeneous antigen expression among tumor cells, cross-fire irradiation is suitable when not all tumor cells can be specifically targeted by radiolabeled antibodies. However, the long path of these particles can also induce bone marrow toxicity. In contrast, alpha-particles have high energy (5–9 MeV) and intermediate path length (50– 100µm), which restricts their effect to 5–10 cell diameters (193). Auger electrons have low energy (0.001–1 KeV) and subcellular nanometer range (<1µm) (193). These characteristics minimize the non-specific irradiation of non-targeted surrounding healthy tissues. Most importantly, it makes it possible to locally deliver high-absorbed doses and lethally damage tumor cells, inducing densely localized DNA DSBs. Besides DNA damage,

these short-range electrons damage the cell membrane and elicit radiation-induced bystander effect (194). For this reason, alpha-particle and Auger electron-emitting nuclides are very attractive for RIT against therapy-resistant CSCs. Our group could recently demonstrate that L1CAM, combined with CD133, defines a new ovarian CSC population and L1CAM is responsible for the radioresistance of these cells (82). This cell population showed high spherogenic and clonogenic capabilities and highly expressed some CSC- and EMT-related genes. Additionally, these cells demonstrated high tumorigenicity, fast-tumor growth and self-renewal when transplanted in nude mice. CRISPR-Cas9 deletion of L1CAM demonstrated that L1CAM expression correlates with EMT phenotype. Since L1CAM is not expressed in normal stem cells and it is present in the bulk population of cancer cells, anti-L1CAM RIT using Auger electrons and alphaparticle emitters would be a promising new option for ovarian CSCs therapy. In this context, we could clearly demonstrate in a comparative anti-L1CAM RIT study using 177Lu- and161Tblabeled mAb chCE7 that 161Tb was better by 82.6% compared to 177Lu under equitoxic conditions in a preclinical OC xenograft model (186). 161Tb emits 16 times more Auger and conversion electrons per decay (3–50 keV) than 177Lu. Both radiolanthanides have similar ß–energy of 134 keV (177Lu; mean) or 154 keV ( 161Tb; mean). Data were taken from "National Nuclear Data Centre Brookhaven National Laboratory."

Some RIT approaches for OC using alpha-particle emitters showed their great potential to treat microresidual diseases in preclinical models (194, 195). In 2017, Kasten et al. used the mAb 376.96, which recognizes the B7-H3 epitope expressed on ovarian CSCs and on the bulk population, radiolabeled with lead-212 (212Pb) to treat tumor-bearing mice. Mice treated with 212Pb-376.96, alone or combined with carboplatin, showed two to three times longer survival than control groups (195). Recent outcomes from a phase I clinical study indicated minimal toxicity of intraperitoneal (i.p) administration of 212Pb-TCMCtrastuzumab in patients with advanced OC (196).

### CONCLUSIONS

The CSC heterogeneity and plasticity of CSC state is currently the largest obstacle to move CSC research toward clinical translation. Nevertheless, although the cancer stemness is now considered as a dynamic state rather than an entity, CSCrelated biomarkers might be a powerful tool for prediction of patients' clinical outcomes, and targeting of CSC OC population might prove beneficial for the treatment of this deadly disease. Common knowledge about ovarian CSCs has made remarkable progress over the last years; still, there are many limitations and challenges related to disease complexity and current experimental techniques. Future studies are expected to employ clinically relevant models such as patient-derived

#### REFERENCES

xenografts, orthotopic mice models, and organoid cultures. Genetically engineered mice models provide opportunity to trace and validate potential CSC populations in the context of a fully functional immune system and tumor stroma. The inherent heterogeneity of OC provides therapeutic challenges and it is further complicated by the acquired heterogeneity driven by microenvironmental and therapeutic pressure. Clinical trials should consider the high heterogeneity regarding CSC markers to select the proper patient cohort. CSC frequency and content should be monitored during clinical trials to assess therapy response. Considering the possibility of bulk tumor cell reprogramming, an optimal therapeutic regimen should combine therapeutic drugs showing wide cytotoxic effects on non-CSCs in combination and/or followed by a therapy targeting resistant CSCs (**Figure 7**) (197). To reach this goal, research needs to focus on the identification of new and reliable signaling pathways that influence CSC maintenance, differentiation, drug resistance, DNA damage repair, and their plasticity. In addition, it would be helpful to identify new CSC cell surface markers that are not expressed in normal stem cells but are also present in the bulk population of tumor cells, like L1CAM in ovarian CSCs. In recent years, there has been a veritable renaissance of radiotherapeutic approaches and new promising radioisotopes were introduced in pre- and clinical trials. Especially alpha- and Auger-emitters allow the sterilization of radioresistant cells such as cancer stem cells due to their high-LET.

### AUTHOR CONTRIBUTIONS

NT and JG designed the manuscript. NT wrote the first draft and illustrated the manuscript. NT, JG, FJ, and AD edited and reviewed the manuscript.

### FUNDING

This work was supported by the Swiss Cancer Research Foundation (KFS 3585-02-2015) to JG.

### ACKNOWLEDGMENTS

We would like to thank Prof. Dr. Roger Schibli, Prof. Dr. med. Viola Heinzelmann-Schwarz, and Dr. Martin Béhé for their support and useful scientific discussions.

signaling in hepatocellular carcinoma. Cancer Lett. (2017) 389:1–10. doi: 10.1016/j.canlet.2016.12.023

and induces Rac1 and Ras signaling during ovarian tumor cell migration and growth. J Biol Chem. (2001) 276:48679–92. doi: 10.1074/jbc.M106759200

generates residual cells with mesenchymal stem cell-like profile. J Cell Biochem. (2011) 112:2850–64. doi: 10.1002/jcb.23199

**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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