maximum in mitosis (74). The cell cycle-dependent repression of Plk1 is mediated by Rb pathway. During DNA damage-mediated checkpoint activation, tumor suppressors like p53 and BRCA1 are found to influence levels of Plk1 (74, 75). Correlated with the loss of functional tumor suppressors, transcriptional deregulation of Plk1 is reported in various cancers and associated with CIN and oncogenic transformation (76). Furthermore, tumor suppressors like BRCA1 and Rb are reported to regulate the levels of another mitotic kinase Nek2. In co-ordination with the loss-of-function of tumor suppressors, the overexpression of this protein is associated with CIN and cancer (77–80). Cell cycle specific expression of mitotic Aurora kinases (Aurora kinase A and Aurora kinase B) are CDE-CHR element regulated (81, 82). Oncoproteins like EWS-Fli1 and Myc upregulate expression of aurora family proteins through binding on promoter response elements. On the other hand, tumor suppressors like p53, Brd4 also influence expression of Aurora kinases (83–86). In fact, the altered expression of Aurora kinases are potential markers of cancer progression (87). Regulated expression of kinetochore protein Hec1 is directly related to phosphorylation-mediated inactivation of Rb during the course of cell cycle. Beside this, the CREB family of oncoprotein transcription factors has been shown to upregulate the levels of kinetochore protein Hec1 (88). Disrupted pRb function is associated with transcriptional upregulation of Hec1, which may cause aneuploidy and tumor formation (89, 90).

The initial events of mitosis are followed by chromosomal alignment at the equatorial plane of the cell during metaphase. The amphitelic metaphase alignment precedes SAC release, chromosomal segregation, and entry into anaphase. Consistent with their mitotic roles, a number of core SAC and SAC-associated proteins (Mad1, Mad2, Bub1, Cdc20, UbcH10 to name a few) accumulate gradually through the G2 phase with peak levels at mitosis (13, 68, 91, 92). Different transcription factors and chromatin modifiers regulate cell cycle specific promoter activities of these genes (68, 92, 93). The well-known tumor suppressor p53 is reported to control the transcription of *CDC20* and *BUB1B* (46, 47, 94). Upon genotoxic stress, Cdc20 expression is indirectly suppressed by p53 through p21-dependent mechanism (46). On the other hand, a direct p53 binding element has been identified on the *CDC20* promoter and shown to bring about repression of transcription through chromatin remodeling (47).

Similarly, direct recruitment of p53 on the promoter consensus element brings about chromatin remodeling and the repression of Mad1 expression (95). Expression of Mad2 is regulated by E2F in a cell cycle-dependent manner. Rb inactivation leads to aberrant Mad2 expression by deregulating E2F activity and contributes to mitotic defects and aneuploidy (58). The tumor suppressor BRCA1 was also reported to regulate Mad2 expression (96). Cancer-associated defects in these tumor suppressors contribute to the abnormal expression of these proteins and a flawed SAC. Indeed, transcriptional abnormalities including differential promoter methylation of these SAC proteins are potential markers of cancers of various origins (97, 98). Their deregulated expressions are associated with CIN phenotype and incidence of cancer (6).

The final stages of mitosis involve cytokinesis and mitotic exit. Along with mitotic kinases like Aurora, Polo, and related families, some other molecular components also regulate this stage of the

### **References**

1. Jallepalli PV, Lengauer C. Chromosome segregation and cancer: cutting xthrough the mystery. *Nat Rev Cancer* (2001) **1**:109–17. doi:10.1038/ 35101065

cell cycle. Protein regulator of cytokinesis 1 (PRC1) and the guanine nucleotide exchange factor, Ect2, the two major molecules of cytokinesis have been related with cancer-associated altered expressions and CIN (6). In conclusion, we have summarized a number of reports from the ever-growing lists of proto-onco gene as well as tumor suppressor trans-factors in regulation of mitosis and their deregulation in tumor background (**Table 1**).

### **Conclusion**

The role of transcriptional regulatory pathways behind the incidence of tumorigenesis remains an enigma. For a number of key cell cycle regulators, the transcriptional control represents an evolutionarily conserved mechanism to precisely maintain their abundance, working in conjunction with miRNA mediated silencing, translational control, and ubiquitin-mediated degradation (23, 26, 114, 115). Among these cell cycle regulators, a defined set of factors stringently control mitotic entry, progression, and exit. The interplay among these factors is naturally adjusted by their abundance. Abnormality in this abundance is associated with the occurrence of aneuploidy, a hallmark of cancer (2, 8, 116). In this review, we have discussed the maintenance of protein levels of the mitotic players whose transcription is regulated in a cell cycle specific manner. We further discussed the deregulation of their transcriptional control, working in concert with cancer onset. In this regard, mutations in various tumor suppressors and proto-oncogenes acting as co-factors of transcription are found to disharmonize the relative protein levels, rather than mutations in the mitotic genes themselves. Besides this, a few mitotic genes are reported to participate in transcriptional control. Furthermore, the list of transcripts whose transcription is affected by certain cell cycle or developmental transitions is being expanded owing to new genome-wide approaches. Answer to many open questions regarding the interplay between transcriptional regulation and mitotic progression will make an important contribution to the understanding of cell cycle control. This, in turn, will help to dissect the involvement of cell cycle progression in the onset of tumorigenesis.

### **Acknowledgments**

This work is supported by CSIR-Mayo Clinic collaboration for Innovation and Translational Research Grant CMPP-08 and CSIR-NMITLI project TLP 0007 to Dr. SR. Pre-doctoral fellowship to SN and DG is supported by CSIR.

### **Supplementary Material**

The Supplementary Material for this article can be found online at http://journal.frontiersin.org/article/10.3389/fendo. 2015.00060

gene MAD1 and modulating mitotic progression. *Cell Death Differ* (2013) **20**:430–42. doi:10.1038/cdd.2012.135

an aberrant transcriptional mechanism of cell cycle regulation. *Cancer Cell* (2006) **10**:191–202. doi:10.1016/j.ccr.2006.08.013

**Conflict of Interest Statement:** 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 © 2015 Nath, Ghatak, Das and Roychoudhury. 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) or licensor 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 tumor cytosol miRNAs, fluid miRNAs, and exosome miRNAs in lung cancer

#### **Xin Qin1,2,3† , Haisheng Xu2† ,Wenrong Gong1 andWenbin Deng1,3\***

1 Medical College, Hubei University of Arts and Science, Xiangyang, China

2 Department of Oncology, Xiangyang Central Hospital, Xiangyang, China

3 Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, Sacramento, CA, USA

#### **Edited by:**

Wen Zhou, Columbia University, USA

#### **Reviewed by:**

Lakshmi Kiran Chelluri, Global Hospitals, India Xiaoxu Zheng, University of Maryland Baltimore, USA Fan Lai, University of Miami, USA

#### **\*Correspondence:**

Wenbin Deng, Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, 2425 Stockton Boulevard, Sacramento, CA 95817, USA e-mail<EMAIL_ADDRESS>
†Xin Qin and Haisheng Xu have contributed equally to this work. The focus of this review is to provide an update on the progress of microRNAs (miRNAs) as potential biomarkers for lung cancer. miRNAs are single-stranded, small non-coding RNAs that regulate gene expression and show tissue-specific signatures. Accumulating evidence indicates that miRNA expression patterns represent the in vivo status in physiology and disease. Moreover, miRNAs are stable in serum and other clinically convenient and available tissue sources, so they are being developed as biomarkers for cancer and other diseases. Cancer is currently the primary driver of the field, but miRNA biomarkers are being developed for many other diseases such as cardiovascular and central nervous system diseases. Here, we examine the framework and scope of the miRNA landscape as it specifically relates to the translation of miRNA expression patterns/signatures into biomarkers for developing diagnostics for lung cancer. We focus on examining tumor cytosol miRNAs, fluid miRNAs, and exosome miRNAs in lung cancer, the connections among these miRNAs, and the potential of miRNA biomarkers for the development of diagnostics. In lung cancer, miRNAs have been studied in both cell populations and in the circulation. However, a major challenge is to develop biomarkers to monitor cancer development and to identify circulating miRNAs that are linked to cancer stage. Importantly, the fact that miRNAs can be successfully harvested from biological fluids allows for the development of biofluid biopsies, in which miRNAs as circulating biomarkers can be captured and analyzed ex vivo. Our hope is that these minimally invasive entities provide a window to the in vivo milieu of the patients without the need for costly, complex invasive procedures, rapidly moving miRNAs from research to the clinic.

**Keywords: microRNA, biomarker, lung cancer**

#### **INTRODUCTION**

Lung cancer is the most common type of cancer worldwide. It is estimated that there are 430,090 men and women living in the United States with a history of lung cancer, and that an additional 224,210 cases will be diagnosed in 2014 (1). Lung cancer is also the leading cause of cancer-related death (2). Because of the lack of validated population-based screening procedures, most patients with lung cancer are diagnosed at an advanced stage. Consequently, the overall 5-year survival rate is only 15% (3). Therefore, there is an urgent need to identify reliable biomarkers of lung cancer, which can then be used for improving accuracy of diagnosis, predicting prognosis, and monitoring disease progression and response to therapy.

MicroRNAs (miRNAs) are small, non-coding RNAs, 19–24 nucleotides in length. They negatively regulate the expression of multiple genes either by inducing translational silencing or by causing the degradation of messenger RNAs (mRNAs) of the targeted gene, both via incomplete base-pairing to a complementary sequence in the 30 -untranslated region (UTR) (4). Since the discovery of the first miRNA, lin-4, in *Caenorhabditis elegans* (5), more than 1,800 human precursor miRNAs have been characterized (6). The accumulating data indicate that miRNAs play important roles in tumorigenesis, metastasis, and drug responsiveness in lung cancer, and can be potential biomarkers for lung cancer (7, 8). Current research has found that the miRNAs can not only be detected in tumor tissues but also in body fluids and even in some extracellular organelles, such as exosomes, all of which have the potential to serve as biomarkers for lung cancer. In this article, we summarize the progress on miR-NAs originating from three different sources (tumor tissues, body fluids, and exosomes) as biomarkers for lung cancer.

### **THE TUMOR CYTOSOL miRNAs, FLUID miRNAs, AND EXOSOME miRNAs IN LUNG CANCER**

#### **THE TUMOR CYTOSOL miRNAs IN LUNG CANCER**

Many factors, including variations of chromatin, epigenetic factors, hypoxia, and changes in hormone levels, can affect the expression profiles of tumor cytosolic miRNAs. Differences between miRNAs in tumor tissues and normal tissues have been studied extensively and profoundly, and data collected from these studies indicate that miRNAs are involved in several critical processes of lung cancer including the initiation, metastasis, and drug response.

In 2004, Takamizawa et al. (9) identified the first miRNA family, let-7, which was associated with the tumorigenesis of lung cancer.

In their study, they found that introduction of let-7a and let-7f isoforms into A549 cells, a lung adenocarcinoma cell line with low baseline levels of let-7 expression, significantly inhibited the growth of A549 cells. This was further validated clinically, where significantly shorter patient survival after diagnosis was associated with reduced *let-7* expression. Subsequently, many targets of let-7 have been identified, including the RAS family (10), HMGA2 (10–12), c-Myc (13, 14), CDC25A, CDK6, and Cyclin D2 (15), which elucidated the mechanisms by which let-7 exerts its function in tumorigenesis. Since then, many miRNAs were identified as oncogenes or tumor suppressor genes, such as miR-17–92 (16, 17), miR-218 (18), miR-21 (19), and miR-34 family (miR-34a and miR-34b/c) (20–24).

MicroRNAs not only play pivotal role in tumorigenesis of lung cancer but also are involved in tumor metastasis. Several miRNAs including miR-17–92 (25–28), miR-200 family of miR-NAs (miR-200a, miR-200b, miR-200c, miR-141, and miR-429) (29), miR-125a-3p/5p (30), miR-21 (31), and miR-106b-25 cluster (miR-106b and miR-93) (32) are reported to be related to the metastasis of lung cancer.

MicroRNAs are also involved in the drug responsiveness of lung cancer cells. It was reported that overexpression of miR-181b could sensitize A549/Cisplatin (CDDP) cells to CDDP-induced apoptosis by decreasing the levels of the anti-apoptotic protein BCL2 (33). Additionally, miR-181a and miR-630 were reported to be modulators of CDDP response in non-small-cell lung cancer (NSCLC) A549 cells (34). In contrast, down-regulation of miR-17-5p expression was associated with paclitaxel resistance by up-regulation of the autophagic protein Beclin 1 (BECN1) expression in NSCLC (35). Similarly, let-7a, miR-126, and miR-145 could sensitize the responsiveness of the large-cell cancer cell line H460 and A549 cells to Gefitinib (36).

#### **BODY FLUID miRNAs IN LUNG CANCER**

In addition to tumor tissues, miRNAs are also found in body fluids such as blood, serum, plasma, urine, and cerebrospinal fluid (CSF), as well as in sputum, saliva, and bronchoalveolar lavage (BAL) (37, 38). Several studies indicate that body fluid miRNAs are stable even under extreme conditions, such as repeated freeze-thaw cycles and extreme pHs (e.g., pH = 1 or pH = 13). This feature makes body fluid miRNAs suitable biomarkers for clinical detection (39).

Chen et al. showed that there is a distinct difference between the profile of miRNAs found in sera of healthy individuals and NSCLC patients. Compared to healthy sera, the expressions of 28 different miRNAs were down-regulated and 63 different miRNAs were up-regulated in lung cancer patients. The expression levels of miRNA-25 and miRNA-223, which exhibited the most robust difference in the profile, were further studied in the sera from 152 lung cancer patients and 75 healthy subjects, showing that both of the miRNAs were indeed highly expressed in cancer patient sera. These results indicated that miRNA-25 and miRNA-223 could be used as potential diagnosis biomarkers for NSCLC (40).

Several other miRNAs, including miR-141, miR-155, miR-1254, and miR-574-5p, were identified as potential early diagnostic biomarkers (41, 42). A recent meta-analysis indicated that the early diagnostic value of circulating miR-21 is much better than the plasma miR-21 (43). Roth et al. found that circulating levels of

miR-361-3p and miR-625\* could be used as blood-based markers for differentiating malignant lung tumors from benign lung tumors (44).

Body fluid miRNAs, especially the circulating miRNAs, can also be promising biomarkers for metastasis and survival time indication. Roth et al. found that high expression levels of miRNA-10b were highly associated with positive lymph node metastasis in lung cancer (41). Hu et al. investigated the circulating miRNA in 303 lung cancer patients and found that the concentrations of 11 miR-NAs were elevated more than fivefolds in patients with shorter survival times compared to those whom survived significantly longer. In addition, miR-486, miR-30d, miR-1, and miR-499 were identified as disease fingerprints to predict overall survival in those patients (45). Boeri et al. showed that plasma levels of miR-155, miR-197, and miR-182 could serve as non-invasive biomarkers for early detection and diagnosis of lung cancer. These miRNAs were shown to be significantly elevated in the plasma of the lung cancer patients compared to the cancer free control subjects by greater than 10-folds, and could help discriminate the two groups (46).

#### **EXOSOMAL miRNAs AND LUNG CANCER**

Exosomal miRNAs, strictly speaking, are also body fluid miRNAs. However, in contrast to the miRNAs circulating freely in the body fluid, exosomal miRNAs are encapsulated in the cell organelles called the exosomes, which are small (30–90 nm) extracellular vesicles derived from the multivesicular body (MVB) sorting pathway (47). Numerous studies indicate that the expression of miRNAs in exosomes is different in the normal condition and in pathological conditions such as tumor.

Riccardo and colleagues screened 742 miRNAs in circulating exosomes and selected 4 miRNAs (miR-378a, miR-379, miR-139- 5p, and miR-200b-5p) as screening markers for segregating lung adenocarcinoma and carcinomas patients from healthy former smokers. They also identified six miRNAs (miR-151a-5p, miR-30a-3p, miR-200b-5p, miR-629, miR-100, and miR-154-3p) for segregating lung adenocarcinoma patients and lung granuloma patients (48).

Guilherme et al. compare 12 specific miRNAs (miR-17-3p, miR-21, miR-106a, miR-146, miR-155, miR-191, miR-192, miR-203, miR-205, miR-210, miR-212, and miR-214) in peripheral circulation exosome-derived miRNAs and tumor-derived miRNAs in lung cancer patients and healthy people. The results showed that there was no significant difference between peripheral circulation miRNA-derived exosomes and miRNA-derived tumors, and thus the exosome-derived miRNAs can be used as biomarkers for lung cancer (49).

Clearly, a number of specific miRNAs or their families show clinical associations in lung cancer and potential values in cancer stages in clinic (**Table 1**).

#### **THE ISOLATION AND DETECTION OF TUMOR CYTOSOL miRNAs, FLUID miRNAs, AND EXOSOME miRNAs**

Tumor cytosol miRNAs can be isolated from fresh tumor tissues or stored formalin-fixed paraffin embedded (FFPE) tissues with Trizol or the conventional phenol/chloroform extraction.

Compared to miRNAs isolated from tumor tissues, the isolation of miRNAs from body fluids requires careful handling in order to

#### **Table 1 | Selected microRNA signatures in lung cancer and their potential value in clinic**.

avoid the contaminations of proteins in the body fluids. Chen et al. used phenol/chloroform to remove the serum proteins after using the Trizol for isolating miRNAs from serum (40). Researchers have also added proteinase K to the body fluids during extraction of the miRNAs (50). There are also commercially available kits for isolation the body fluid miRNAs such as the PARIs Kit and PAXGene Blood miRNA Kit (Qiagen). The conventional detection method is also applicable for body fluid miRNAs (51).

For detection of exosomal miRNAs, exosomes have to be harvested. The commonly used methods for isolation of exosomes include ultracentrifugation (52) and polymer-based Exoquick reagent (System Bioscience, Inc.) (53). The exosomes can be identified by Western-blot analysis with the two commonly used exosomal markers, the tetraspanin molecule CD63 and tumor susceptibility gene TSG 101 (54).

The actual detection of tumor cytosol miRNAs, fluid miRNAs, and exosome miRNAs use similar strategies such as Northern blot, RT-PCR, miRNA array, or next generation sequence (NGS) (55).

Although the procedures for isolation of miRNAs from body fluids or exosomes are relatively more complex than isolation of miRNAs from tumor tissues, miRNAs from body fluids or exosomes are considered as better biomarkers for lung cancers because they involve non-invasive procedures compared biopsies for extracting tumor-derived miRNAs. Another advantage of using miRNAs from body fluids or exosomes as biomarkers in lung cancer is that once potential biomarkers are identified, methods can be optimized to detect these specific miRNAs for use in larger studies and every-day practice (**Table 2**).

### **THE CONNECTIONS AMONG TUMOR CYTOSOL miRNAs, FLUID miRNAs, AND EXOSOME miRNAs**

The maturation of miRNAs have been studied extensively and profoundly, and the well-accepted model is that the DNA coding miRNAs are transcribed into the primary miRNAs (pri-miRNAs), and then the pri-miRNAs are processed by Drosha (an RNase type III endonuclease) and specific cofactors to generate the precursor miRNAs (pre-miRNAs). Pre-miRNAs are transported from nucleus into cytoplasm where they undergo processing by Dicer and various cofactors to for mature miRNAs (56). But how the mature miRNAs enter into body fluids and what is the relationship between body fluid miRNAs and exosome miRNAs are still not clear. There are three possible ways for miRNAs to enter body

**Table 2 |The isolation and detection of tumor cytosol, body fluid and exosome miRNAs**.

FFPE, formalin-fixed paraffin embedded; CSF, cerebrospinal fluid; BAL, bronchoalveolar lavage; NGS, next generation sequence.

fluids. First, the tumor cells in the primary location "secret" miR-NAs, which combined with Ago2 and GW182 to enter body fluids (57, 58). Second, the miRNAs in the primary tumor cells are packaged into membranous vesicles (MVs) or exosomes and then enter into body fluids (59). However, it is still not clear if the incorporation of miRNAs into exosomes occurs at the pre-miRNA or mature miRNA level. Recently, Villarroya-Beltri et al. reported that exosomes contain mature miRNAs (60). Third, the tumor cells or other cells in body fluids directly release their cytosol miRNAs into body fluids after apoptosis (61) (**Figure 1**).

Currently, there is no consensus regarding the relationships between exosomal miRNAs and the body fluid miRNAs, especially the whole blood miRNAs. Several studies have indicated that the majority of miRNAs found in plasma and serum are present primarily outside the exosomes (62, 63), while other studies found that miRNAs in serum and saliva exist primarily inside the exosomes (54).

#### **CONCLUSION**

Over the last decade, great progress has been made in the research of miRNAs and lung cancer. Several miRNAs with differential expression patterns in lung cancer tissues compared to normal tissues have been identified. Furthermore, aberrant expression patterns of miRNAs in lung cancer patients can not only be detected in tumor tissues but also in body fluids and extracellular organelles such as exosomes. All these studies give weight to the conclusion that miRNAs are promising biomarkers for diagnosis and prediction, as well as targets of potential therapeutics for lung cancer. Yet, before they can be effectively integrated into the field of clinical oncology, there are several issues that need to be addressed: (1) Using miRNA array analysis, it is easy to find numerous miRNA candidates whose expressions vary in lung cancer tissue compared to the normal tissue, or whose expressions vary in lung cancer patients body fluids and exosomes compared to the healthy persons. However, there is still no gold standard to evaluate meaningful candidates. It remains a challenge to increase the accuracy of the results from miRNA array analysis and validate meaningful candidates in an efficient manner. (2) Compared to tumor cytosol miRNAs, fluid miRNAs, and exosome miRNAs have attracted more attention as potential diagnostic markers for lung cancer, but there is no standard method for isolating these two kinds of miRNAs, and no reliable endogenous control for evaluation. (3) The quality control of the normal healthy tissue and fluid sample collections is also a key issue in the field, and obtaining a near perfect control at the nano-scale currently remains a major challenge. (4) The up-surging new information in this area brings more and more potential miRNA candidates for lung cancer, but how to interpret and integrate all the information into a network of knowledge for their clinical use as diagnostic and prognostic biomarkers and as potential therapeutic targets represents another attractive area for future investigation. Overall, the study of miRNAs offers a new and exciting angle for us to understand the molecular mechanisms of lung cancer biology. Further studies could provide more accurate biomarkers for both diagnosis and prediction, as well as improved strategies for lung cancer treatment.

#### **AUTHOR CONTRIBUTIONS**

All authors participated in conceiving the concept and writing the manuscript.

#### **ACKNOWLEDGMENTS**

We thank Dr. Sangita Biswas for critical reading of the manuscript. We would like to acknowledge the support from the National Institutes of Health (R01 NS059043 and R01 ES015988), Shriners Hospitals for Children, the Natural Science Foundation of Hubei Province (2014CFC1154), and the Foundation of Medical College of Hubei University of Arts and Science (YXKY 201402).

### **REFERENCES**

detection. *Proc Natl Acad Sci U S A* (2008) **105**:10513–8. doi:10.1073/pnas.<PHONE_NUMBER>

**Conflict of Interest Statement:** 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.

*Received: 19 November 2014; paper pending published: 25 November 2014; accepted: 27 November 2014; published online: 05 January 2015.*

*Citation: Qin X, Xu H, Gong W and Deng W (2015) The tumor cytosol miR-NAs, fluid miRNAs, and exosome miRNAs in lung cancer. Front. Oncol. 4:357. doi: 10.3389/fonc.2014.00357*

*This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Oncology.*

*Copyright © 2015 Qin, Xu, Gong and Deng . 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) or licensor 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.*

# Relevance of splicing on tumor-released exosome landscape: implications in cancer therapeutics

### **Elisa Oltra\***

Facultad de Medicina, Universidad Católica de Valencia "San Vicente Mártir", Valencia, Spain \*Correspondence<EMAIL_ADDRESS>
**Edited by:** Wen Zhou, Columbia University, USA

**Reviewed by:**

Xi Zhang, University of Connecticut, USA

**Keywords: tumor-released exosomes, dexosomes, splicing, cancer therapy, phage display, SELEX**

Apart from apoptotic bodies and ectosomes, microvesicles that bud out of the plasma membrane, most types of cells release exosomes when intracellular endosomal microvesicular bodies fuse with their plasma membrane. This last type of vesicles with attributed intercellular communicating capabilities has acquired an enormous attention in the past two decades, especially for their potential as disease biomarkers and/or their use as therapeutic vehicles. The intense study of their molecular composition with special attention to miRNA has led to the development of databases like Exocarta (http://www.exocarta.org/) (1); however, the way exosomes released from tumors (Tex) that may influence cancer patient's health is not yet completely understood.

The observation that exosome production and release is notably increased with tumor progression suggests that they must play an active role in cancer (2, 3). As tumors become more aggressive, heparanase activity is enhanced at least in myeloma, lymphomas, or breast cancer, increasing both the number of exosomes released and the amount of syndecan-1, VEGF, and HGF molecules exposed on their surface (4).

The advantages that Tex present for the delivery of tumorigenic signaling molecules in relation to passive release into the medium are clear, especially for transports across long distances in the body. Firstly, encapsulation of labile molecules such as RNAs and proteins within lipid bilayers offers them protection to degradation; secondly, the surface landscape of the vesicle allows for the possibility of tissue or cell specific targeting and thirdly they are suited for simultaneous multiple message delivery

allowing horizontal transfer of complex information from cancer to healthy cells.

In addition to attenuation of antitumor immunity, Tex stimulate angiogenesis, modulate stromal cells activity, and help on the extracellular matrix remodeling contributing to the establishment of a premetastatic niche and generating suitable microenvironments at distant metastatic sites (5). For example, Tex from glioblastoma have the ability to potentiate tumor growth (6) and Tex from melanoma can directly tune a remote lymph node into a microenvironment that facilitates melanoma growth and metastasis even in the local absence of tumor cells (7). These and other similar studies suggest that Tex activities are mediated, at least in part, through the action of particular miRNAs, which presumably down regulate their target transcripts in recipient cells (8,9). Interestingly enough, Fabbri et al. have recently showed that the Tex miR-21 and 29a molecules can bind to toll-like receptor 7 and 8 (TLR7 and 8) on immune cells and activate them, leading to TLR-mediated NFkB activation and secretion of prometastatic inflammatory cytokines (10, 11). This offers an alternative mode of action for the miR-mediated Tex paracrine effects in which miR act as aptamer-ligands. So, in addition to Tex internalization Tex protein, lipid, carbohydrate, or nucleic acid surface receptors could interact with target cell receptors to activate intracellular signaling; or, their surface proteins could be cleaved by proteases, and the corresponding soluble fragments act as soluble ligands binding to target cell surface receptors (12). In one case or another, Tex-mediated activities are a threat to patients working toward disease progression. Importantly, anti-cancer agents directed to inhibit DNA replication or microtubule dynamics will result innocuous to Tex. This is, Tex present themselves, together with cancer stem cells, as a therapeutic resistant reservoir for the advancement of the disease, and therefore effective cancer treatments must include targeted inactivation and/or removal of Tex.

On another side, however, exosomes have emerged as potent stimulators of immune responses and from this point of view as agents for cancer therapy. It has been recently showed that induction of HSPs (heat shock proteins)-loaded Tex occurred when hepatocarcinoma cells were treated with chemotherapeutics such as paclitaxel or carboplatin. These Tex released by treated cancer cells conferred superior immunogenicity in inducing HSPs-specific NK cell responses (13). Exosomes can carry a broad variety of immune-stimulatory molecules depending on the cell of origin and *in vitro* culture conditions. In particular, dendritic cell (DC)-derived exosomes (dexosomes) have been shown to carry NK cell activating ligands and can be loaded with antigens to activate invariant NKT cells to induce antigen-specific T and B cell responses. Tumor-antigen-derived dexosomes have been investigated as therapeutic agents against cancer in two phase I clinical trials, with a phase II clinical trial currently ongoing. The results show that although dexosomes were well tolerated, the therapeutic success and immune activation were limited (14, 15). Multiple factors need to be considered in order to improve exosomal immunogenicity for cancer immunotherapy. For example, Tex immunostimulatory effect has been shown to depend on host's DCs while dexosomes do not (16). Because of their abundant expression of tumor antigens, Tex can be envisaged as an acellular source of antigenic determinants to be exploited in the production of cancer-vaccines and therefore as a therapeutic cancer agent by itself or as a co-adjuvant treatment (17).

Although immune cells, and probably dexosomes, can be found in primary tumor lesions as infiltrating components playing favorable prognostic role (18), in metastatic lesions anti-cancer activities are suppressed due to Tex derived immunosuppressive effects allowing tumor progression. One of the mechanisms responsible for this undesired effect in different types of solid cancers uses endocytic FasL and also TRAIL loaded pro-apoptotic Tex to eliminate overreactive Fas-expressing T cells (19). Thus, Tex in malignant ascites effusions and other cancer patient fluids can eliminate activated T cells through a simple ligand–receptor interaction. In addition, functional CD39 and CD73 Tex are capable of dephosphorylating ATP and AMP to form adenosine to negatively regulate local immune responses (20). Tex can also inhibit DC differentiation, inhibit T-cell proliferation through TGF-β interactions, and promote tumor-immune evasion by interfering with NK cells (19) eventually hijacking the anti-cancer immune response that they might have initiated.

Reached this point, the key question for cancer therapeutics is: will patients benefit by the presence of Tex or effective removal of Tex should be recommended?

The answer does not seem to be straight forward but recent modeling for putative therapeutic implications of exosome exchange between tumor and immune cells may throw some light on it (21). The authors propose the existence of three cancer states: a low cancer load (L) with intermediate immune-level state, and intermediate cancer load (I) with high immunelevel state and a high cancer load (H) with low immune-level state. To design and assess possible therapeutic protocols, the authors built a cancer-immunity landscape that includes dynamical states of the cancer-immunity interplay allowing for the visualization of combined protocols as trajectories connecting different states. For example, when the immune recognition is low, the effect of the immune system

will not be strong enough to limit cancer progression.

An important observation that should be included in Lu et al. model is that exosome release is controlled by feedback regulatory loops that involve not only cancer cells but also exosome production by normal cells. In this sense, it has been reported that exosome release from normal human mammary epithelial cells and breast cancer cells is not only regulated by the presence of exosomes derived from their own cells but also exosomes from normal mammary epithelial cells inhibit exosome secretion by breast cancer cells in a tissue specific manner, implicating a dynamic equilibrium between exosome release of normal and tumor cells (22).

It is of relevance as well to point out that the different cancer-load-states may refer not only to quantitative traits but also to qualitative cancer-associated features. For example, cancer-specific membrane bound isoforms such as EGFRvIII, generated by defective alternative splicing mechanisms, have been detected on the surface of Tex (6). Such distinctive cancerassociated exons could be used for the design of directional therapeutics, allowing selective inactivation or sequestration of Tex with minimal interference of normal cell exosome activity, reducing possible secondary effects. In addition to antibodybased strategies, synthetic peptides and nucleic acid aptamers have proven not only to bind specifically and tightly to cancer cells but also to home to cancer cells *in vivo* (23–25). Similar approaches could be used to block or sequester Tex through their particular surface landscapes. Targeting through common receptors such as tetraspanins could interfere with normal exosome functions and therefore is not recommended.

The fact that solid tumors are heterogeneous in nature adds yet another degree of complexity to cancer therapeutics. Tumor heterogeneity will be reflected into a multivariety of Tex. Taking into account that the current methods for Tex isolation are based on vesicle size, density, and enrichment of certain common markers (tetraspanins) (26), we can conclude that Tex fractions are far from pure. A possible strategy to study more homogeneous Tex populations would be to establish cell lines from microdissected biopsies so that

enough Tex of a particular type can be produced and isolated. This should allow for a better characterization of the Tex complex landscapes, some of them dependent on cancer-associated splicing switches.

Deregulation of splicing is associated to acquisition of cancer advantages, aggressiveness of the tumor, and drug resistance events (27–29). For example, the inclusion of an exon in the pyruvate kinase transcript allows for activation of glycolytic pathway of cancer cells (Warburg's effect), and the KLF6-SV1 variant is associated with poor prognosis and tumor aggressiveness in prostate, lung, and ovarian cancers, associated to EMT (epithelial to mesenchymal transition) (30). In the context of directional targeting of Tex, it would be important to identify specific cancerassociated exons located on the external side of the vesicles. They may or may not be present in the plasmatic membrane of the tumor cell of origin. Toward this end, strategies such as screening of random libraries based on phage display and SELEX (Systematic Evolution of Ligands by EXponential enrichment) technologies allow for the identification of synthetic peptides and aptamers without previous knowledge of the altered splicing events (31, 32). Perhaps, tumor therapies suppressing the splicing machinery itself are advantageous to current systemic cancer treatments.

Tex cancer-associated exon sequences could be used for immunotherapy, to boost DC dexosome release and, at the same time, as targets for Tex inactivation and/or sequestration. If only inactivation/sequestration is applied, the patient would miss the benefit of the immune response against the tumor. On the other side, if the unloading of Tex is not prevented, their cargo will work toward advancement of the disease. This double-approach consisting on blocking Tex function while using their specific cancer-associated exon sequences to induce tumor-immune response could complement current tumor treatments to reduce relapses and to limit metastatic events in immuno-competent patients. In addition, this directional targeting strategy would leave exosome-dependent physiological functions unaffected.

In summary, the study of Tex surface landscape and the detection of cancer-specific exons on Tex derived from alternative splicing events results essential for the development of Tex targeted therapies. These qualitative switches should be considered in the context of patient immunological and cancer load states for the modeling and the development of improved, personalized cancer therapeutic programs.

#### **REFERENCES**

of a suite of tumor targeting peptides for nonsmall cell lung cancer. *Sci Rep* (2014) **4**:4480. doi:10.1038/srep04480

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

*Received: 18 October 2014; accepted: 30 October 2014; published online: 12 November 2014.*

*Citation: Oltra E (2014) Relevance of splicing on tumor-released exosome landscape: implications in cancer therapeutics. Front. Endocrinol. 5:194. doi: 10.3389/fendo.2014.00194*

*This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Endocrinology.*

*Copyright © 2014 Oltra. 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) or licensor 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.*

# Cancer cell gene expression modulated from plasma membrane integrin αvβ3 by thyroid hormone and nanoparticulate tetrac

#### **Paul J. Davis 1,2\*, Gennadi V. Glinsky 3 , Hung-Yun Lin4 , John T. Leith5 , Aleck Hercbergs 6 , Heng-Yuan Tang2 , Osnat Ashur-Fabian7,8, Sandra Incerpi 9 and Shaker A. Mousa2**

1 Department of Medicine, Albany Medical College, Albany, NY, USA

#### **Edited by:**

Wen Zhou, Columbia University, USA

#### **Reviewed by:**

Jean-Yves Scoazec, Université Lyon 1, France Yun Zhu, Medical University of South Carolina, USA

Fei Teng, University of Arizona, USA

#### **\*Correspondence:**

Paul J. Davis, Pharmaceutical Research Institute, Albany College of Pharmacy and Health Sciences, One Discovery Drive, Rensselaer, NY 12144, USA

e-mail<EMAIL_ADDRESS>
Integrin αvβ3 is generously expressed by cancer cells and rapidly dividing endothelial cells. The principal ligands of the integrin are extracellular matrix proteins, but we have described a cell surface small molecule receptor on αvβ3 that specifically binds thyroid hormone and thyroid hormone analogs. From this receptor, thyroid hormone (L-thyroxine, T4; 3,5,30 -triiodo-L-thyronine, T3) and tetraiodothyroacetic acid (tetrac) regulate expression of specific genes by a mechanism that is initiated non-genomically. At the integrin, T4 and T3 at physiological concentrations are pro-angiogenic by multiple mechanisms that include gene expression, and T4 supports tumor cell proliferation. Tetrac blocks the transcriptional activities directed by T4 and T3 at αvβ3, but, independently of T4 and T3, tetrac modulates transcription of cancer cell genes that are important to cell survival pathways, control of the cell cycle, angiogenesis, apoptosis, cell export of chemotherapeutic agents, and repair of double-strand DNA breaks. We have covalently bound tetrac to a 200 nm biodegradable nanoparticle that prohibits cell entry of tetrac and limits its action to the hormone receptor on the extracellular domain of plasma membrane αvβ3. This reformulation has greater potency than unmodified tetrac at the integrin and affects a broader range of cancerrelevant genes. In addition to these actions on intra-cellular kinase-mediated regulation of gene expression, hormone analogs at αvβ3 have additional effects on intra-cellular proteintrafficking (cytosol compartment to nucleus), nucleoprotein phosphorylation, and generation of nuclear coactivator complexes that are relevant to traditional genomic actions ofT3. Thus, previously unrecognized cell surface-initiated actions of thyroid hormone and tetrac formulations at αvβ3 offer opportunities to regulate angiogenesis and multiple aspects of cancer cell behavior.

**Keywords: integrin, thyroid hormone, tetraiodothyroacetic acid, nanoparticle, gene transcription**

### **INTRODUCTION**

Integrins are heterodimeric structural proteins of the plasma membrane and are principally involved in cell–cell relationships in tissues and cell–extracellular matrix (ECM) protein interactions (1). The extracellular domain of an integrin binds specific ECM proteins and outside-in transmission of the occurrence of liganding results in the generation of specific signals by the intracellular domain of the integrin. These signals, usually involving various kinases, may result in cellular changes in actin (2, 3) and cell motility (4), modulate endocytosis (5), and affect transcription of specific genes (6–8).

Amply expressed by and activated in cancer cells, integrin αvβ3 interacts with ECM proteins, but has recently been shown to have a panel of specific receptors for non-protein, small molecule ligands (9). Among these are sites for the binding of thyroid hormone (10, 11), dihydrotestosterone (12), and resveratrol (13). The thyroid hormone receptor (TR) on αvβ3 has been well-studied (11, 14). What is now apparent is that this receptor has more complex and coherent effects on cancer-relevant gene expression than had been apparent in analyses of the impact of large molecule (protein) interactions with the integrin. The multiple genes whose expression is modulated from the extracellular domain of αvβ3 by thyroid hormone or its derivative, tetraiodothyroacetic acid (tetrac), relate to angiogenesis, cancer cell proliferation, metastasis, and cancer cell defense pathways (15). The latter include genes relevant to anti-apoptosis, anti-angiogenesis, chemoresistance (MDR1), and repair of double-strand DNA breaks induced by radiation. Within the cell, unmodified tetrac

mimics certain actions of thyroid hormone. At the extracellular domain of αvβ3, in contrast, tetrac blocks binding of l-thyroxine (T4) and 3,5,30 -triiodo-l-thyronine (T3) – that is, it is a thyroid hormone antagonist. Covalent bonding of tetrac to a nanoparticle prevents cell entry of tetrac and, compared to unmodified tetrac, broadens the spectrum of defensive cancer cell genes whose expression can be desirably regulated from the integrin. This expanded panel includes pro-apoptotic genes and epidermal growth factor receptor (EGFR) gene (see subsequent sections). In addition, the potency of nanoparticulate tetrac as a thyroid hormone antagonist at αvβ3 is greater than that of unmodified tetrac. Thus, without entering the cancer or endothelial cell, thyroid hormone analogs non-genomically initiate important actions on tumor cell and blood vessel cell gene expression. In this review, we survey αvβ3-mediated effects of thyroid hormone and analogs on gene expression in human cancer cells, analyzed by RT-PCR. We also point out that, from its receptor on the integrin, thyroid hormone has adjunctive effects on nuclear receptors for thyroid hormone and for estrogen, regulating the state of phosphorylation or acetylation of such receptors and controlling the formation of complexes within the nucleus of coactivators and receptors.

### **EARLY EVIDENCE THAT THYROID HORMONE COULD MODULATE GENE EXPRESSION FROM THE CELL EXTERIOR: PROTOONCOGENE EXPRESSION; ANGIOGENESIS**

Prior to the discovery of the plasma membrane receptor for thyroid hormone and hormone analogs on integrin αvβ3, agarose-T4 had been shown to regulate protooncogene expression (16, 17). Agarose-T4 is a prototypic nanoparticulate formulation of l-thyroxine in which T4 is covalently bound to a linear polysaccharide polymer; the product is excluded from the cell interior. The thyroid hormone effect on gene expression in these studies was mitogen-activated protein kinase (MAPK)-dependent and was reproduced in cells that lacked the nuclear TR.

Studied in the chick chorioallantoic membrane (CAM) model and also prior to recognition of the hormone receptor on αvβ3, T4 at physiological free concentrations and T3 at concentrations that were supraphysiologic were shown to increase vascularity threefold in 72 h (18). The degree of activity was comparable to that of fibroblast growth factor 2 (FGF2; bFGF). Agarose-T4 also reproduced the pro-angiogenic effect of thyroid hormone. The effects of unmodified thyroid hormone and of agarose-T4 on angiogenesis were found to be inhibited by tetrac, the hormone analog subsequently shown to block the iodothyronine receptor site on the cell surface. Pharmacologic inhibitors of MAPK (ERK1/2) and of protein kinase C also eliminated thyroid hormone-induced angiogenesis. RT-PCR studies revealed that the hormone-induced transcription of *FGF2* within 6 h, and measurement of FGF2 protein in the medium showed increased release of the angiogenic factor. Thus, the promotion of vascular sprouting (19) and new vessel formation by thyroid hormone was attributable to initiation at the plasma membrane of a non-genomic effect culminating in expression of a specific vascular growth factor gene, manufacture of the gene product and release of the latter protein into the medium.

The cell surface receptor for thyroid hormone and tetrac was shortly thereafter defined on the extracellular domain of integrin αvβ3 and functionally described in the context of angiogenesis (10). Other thyroid hormone agonist analogs, such as GC-1 (20) and diiodothyropropionic acid (DITPA) (21) were also shown to be pro-angiogenic, and tetrac blocked the activity of these analogs at the integrin. However, the anti-angiogenic properties of tetrac expressed at the integrin extend beyond the blockade of binding of T4 and T3 to αvβ3. As discussed in the next section, tetrac or its reformulation as a nanoparticulate may affect expression of blood vessel-relevant genes beyond *FGF2* independently of T4 and T3. Tetrac and Nanotetrac may also disrupt crosstalk between αvβ3 and adjacent receptors for other vascular growth factors, such as vascular endothelial growth factor (VEGF) and FGF2 (22), and platelet-derived growth factor (PDGF) (Shaker A. Mousa, unpublished observations). However, these effects on crosstalk are unrelated to gene transcription.

### **TETRAC, NANOTETRAC, AND GENE AND microRNA EXPRESSION THAT IS RELEVANT TO ANGIOGENESIS**

As indicated above, unmodified tetrac is taken up by cells and expresses low-grade T4-like activity and may be converted to triiodothyroacetic acid (triac), which is also thyromimetic (23, 24). To limit the action of tetrac exclusively to integrin αvβ3, we covalently bonded tetrac to a nanoparticle of sufficient size (~200 nm) to preclude cell uptake of the complex (25), thus mimicking agarose-T4. The polymer we used was biodegradable poly(lacticco-glycolic acid), in contrast to the physiologically inert agarose. The nanoparticulate formulation involved a stable ether bond of the outer ring hydroxyl group of tetrac to a 6-carbon linker and amide-bonding of the latter to PLGA (25). The amide bond was imbedded in the nanoparticle and thus not readily accessible to circulating or tissue peptidases. The resulting Nanotetrac indeed was restricted to the extracellular space and preserved the previously known actions of tetrac, but it was also found to have desirable additional biologic activities not previously obtained with tetrac.

Microarray studies of two human cancer cell lines showed that tetrac and Nanotetrac downregulated expression of *VEGFA* (26), the gene product of which is a principal inducer of the porous blood vessels associated with cancers (27). These effects are initiated at plasma membrane αvβ3. Tetrac and Nanotetrac also increased transcription of thrombospondin 1 (*THBS1*, *TSP1*). TSP1 protein is an endogenous suppressor of angiogenesis and is invariably suppressed in cancer cells. Nanotetrac also decreased expression of *EGFR*, the gene product of which mediates actions of EGF on angiogenesis. Tetrac lacked this action. Nanotetrac, but not tetrac, downregulates expression of *NF*κ*B* via the integrin and NFκB de-activation is an anti-angiogenic target (28, 29). Finally, thyroid hormone may regulate transcription of the monomeric α*v* gene (30), but it is not known whether this action is initiated at the αvβ3 protein or requires the nuclear TR.

In recent studies of microRNA (miR), we have shown that Nanotetrac increases cellular abundance of miR-15A in breast cancer cells by 10-fold (31) and decreases miR-21 by 50%. miR-21 is pro-angiogenic in certain tumor cells (32) and miR-15A decreases angiogenesis by a VEGF-dependent mechanism (33).

Transcriptional mechanisms involved in the anti-angiogenic activity of Nanotetrac at αvβ3 are summarized in **Table 1**.

#### **Table 1 | Transcriptional mechanisms by which Nanotetrac/tetrac is anti-angiogenic**.

Measurements of gene transcription were made in breast cancer (34) and medullary thyroid carcinoma cells (26). Protein abundance decreases are presumed to reflect decreased expression of specific genes. The pro-angiogenic activity of thyroid hormone involves non-transcriptional mechanisms as well as actions on specific gene expression shown in this table. Mechanisms that appear to be non-transcriptional are crosstalk between integrin αvβ3 and adjacent vascular growth factor receptors on the cell surface, cell release mechanisms for newly synthesized growth factors and regulation of endothelial cell motility (11, 18, 36).

### **THYROID HORMONE SUPPORTS CANCER CELL PROLIFERATION AND IS ANTI-APOPTOTIC; TETRAC–NANOTETRAC TRANSCRIPTIONALLY INHIBITS CANCER CELL PROLIFERATION, IS PRO-APOPTOTIC AND DISRUPTS CELL DEFENSE PATHWAY GENE EXPRESSION**

A number of laboratories have described the stimulatory effect of thyroid hormone on tumor cells (37–43) and clinical studies have defined thyroid hormone dependence of cancers, in that spontaneous or medically induced hypothyroidism has improved outcomes (44–49). Trophic actions of thyroid hormone on tumor cells were presumed to require a TR isoform and to be genomic in mechanism – that is, to require physical interaction of a TR protein and T3 – until recognition of the existence in 2005 (10) of the cell surface receptor for thyroid hormone and tetrac on αvβ3, described above (11, 50). Existence of this receptor offered a discrete, non-genomic mechanism for initiation of tumor cell proliferation. TRβ may be involved in certain cancer cell proliferative responses to thyroid hormone (51, 52), but work by Cheng and co-workers indicates that TRβ is a tumor suppressor that, when mutated in the thyroid gland, may be oncogenic (53).

The demonstration that T4 – including the agarose-T4 formulation – was a proliferative factor for certain human tumor (breast, thyroid cancer) (42, 54) and animal cells (C6, F98, GL261 glioma cell lines) (43) was accompanied by evidence that unmodified tetrac inhibited the T4 effect. We had shown that unmodified tetrac blocked non-genomic actions of thyroid hormone on plasma membrane functions (11, 14, 55). The proliferative effect was MAPK-dependent. Interestingly,in human breast cancer (MCF-7) cells, tetrac-inhibitable enhancement of proliferation by thyroid hormone involved Ser-118 phosphorylation of nuclear estrogen receptor-α (ERα); this pathway is identical to that by which estrogen stimulates MCF-7 cell proliferation (54).

In a model of resveratrol-induced apoptosis that involved MAPK phosphorylation of p53 at Ser-15, we showed that T4 was anti-apoptotic. The hormone prevented the p53 phosphorylation step in several tumor cell lines (42, 56). Tetrac blocked this antiapoptotic activity of T4. Additional evidence of the anti-apoptotic activity of T4 included inhibition of nucleosome liberation by resveratrol, as well as cellular accumulation of the pro-apoptotic BcLxs protein (56, 57). The hormone did not, however, affect cell accumulation of survival protein BcLxl . The action of thyroid hormone on nucleosome liberation and BcLxs in tumor cells was prevented by tetrac (58).

Subsequent microarray studies conducted with Nanotetrac in human breast cancer (MDA-MB-231) cells revealed a coherent pro-apoptosis pattern of gene expression. That is, transcription of the X-linked inhibitor of apoptosis (*XIAP*) gene was downregulated and transcription of a set of pro-apoptotic genes – *CASP2*, *CAP8AP2*, *DFFA*, and *BCL2L14* – was stimulated (11, 34).

We would also note that Nanotetrac downregulates expression of 8 of 9 cyclin genes and 1 cyclin-dependent kinase gene (34) and more than 20 oncogenes.

### **TETRAC–NANOTETRAC ACTIONS ON EXPRESSION OF GENES RELEVANT TO TUMOR INVASIVENESS**

Catenins are proteins involved in cell–cell adhesion. β-catenin also has transcriptional functions in the nucleus. Mutation and overexpression of the β-catenin gene occurs in a variety of cancers, including colorectal carcinoma, breast, and ovarian cancer (59, 60). Nanotetrac increases transcription of the *CBY1* gene (34), the gene product of which is an inhibitor of nuclear functions of β-catenins. This is a desirable action of Nanotetrac at αvβ3 in cancer cells. The action would be deleterious in non-cancer cells, but the latter when not undergoing cell division express little αvβ3. Like β-catenins, integrin αvβ3 participates in cellular adhesion complexes.

Nanotetrac also affects α-catenins, downregulating expression of the *CTNNA1* and *CTNNA2* genes. Mutation of *CTNNA2* is associated with tumor invasiveness and thus inhibition of transcription of the gene is desirable, as is downregulation of the non-mutated gene in cancers. The non-mutated gene product of *CTNNA1* can function as a tumor invasion suppressor (61), but mutation is associated with gastrointestinal tract and other cancers (62).

As mentioned above, *MMP-9* expression is induced by thyroid hormone (35). The observations were recently made in myeloma cells and were inhibited by tetrac, thus implicating αvβ3 in this action of T4. This action of the hormone may contribute to local extension of myeloma in bone and, if documented to be present in solid tumor cells, may presage metastasis. *MMP-2* transcription may also be subject to control by thyroid hormone (63, 64). Several mechanisms may be involved in the hormonal action on *MMP-2*, and it is not yet known whether this effect of the hormone is initiated at integrin αvβ3. The importance of this is that an intact metalloproteinase axis interferes with cell–cell interaction, resulting in tissue destabilization and support of cancer cell invasiveness and metastasis (65).

#### **OVERVIEW OF ANTI-CANCER PROPERTIES OF NANOTETRAC, ACTING AS A SINGLE MODALITY**

The anti-cancer actions of Nanotetrac are broadly based in terms of mechanisms, despite initiation at a single target receptor on integrin αvβ3, and in this regard resemble the pluralistic antiangiogenic actions of the drug. As noted above, the coherence of the effects of the agent on expression of differentially regulated cancer cell genes is remarkable. It is possible that there are effects of Nanotetrac at αvβ3 that may involve integrity of the actin cytoskeleton in cancer cells, and that the drug may influence interactions of the integrin with ECM proteins that may disorient tumor cell movement or interfere with defensive responses (see Conjunctive Radiation and Tetrac/Nanotetrac Treatment of Cancer Cells: Radiosensitization below). However, these possibilities have not yet been examined.

Nanotetrac promotes apoptosis, antagonizes anti-apoptotic (survival) defenses, disrupts control of the cell cycle, and interferes with function of the frequently mutated catenins (11, 26, 34). As noted above in the review of angiogenesis, thyroid hormone and tetrac or its Nanotetrac formulation affect matrix metalloproteinase gene expression. We would also note that thyroid hormone (T4) has protein-trafficking action on integrin αvβ3, directing internalization of the membrane protein – without the hormone ligand – and nuclear uptake of the αv monomer, but not of β3. In the nuclear compartment, αv is a coactivator (66) involved in transcription of a number of important cancer-relevant genes (see below, Adjunctive Modifications of Nuclear Hormone Receptors that Originate at the Hormone Receptor on αvβ3; Nuclear Uptake of αv Monomer).

Some of these actions of Nanotetrac/tetrac are summarized in **Table 2**.

#### **CHEMOSENSITIZATION BY TETRAC OF CANCER CELLS RESISTANT TO OTHER CANCER CHEMOTHERAPEUTIC AGENTS**

P-glycoprotein (P-gp; MDR1; ABCB1) is a plasma membrane efflux pump whose ligands include a number of cancer chemotherapeutic agents (72). The pump is a principal component of cancer cell chemoresistance. Thyroid hormone causes transcription of *MDR1* (73–75) and increases function of the P-gp protein (75). Thus, ambient thyroid hormone may be viewed as a support mechanism for chemoresistance (76). It is not known what the molecular basis is for regulation by iodothyronines of Pgp function or *MDR1* gene expression, i.e., microarray studies have not been conducted to establish whether the induction of *MDR1* gene expression is dependent upon the hormone receptor on integrin αvβ3. However, tetrac increases the intra-cellular retention time of doxorubicin by doxorubicin-resistant breast cancer cells (67), an effect attributed to action of tetrac–Nanotetrac on pump function of P-gp or on gene expression (76).

### **CONJUNCTIVE RADIATION AND TETRAC/NANOTETRAC TREATMENT OF CANCER CELLS: RADIOSENSITIZATION**

Hercbergs and co-workers have defined the potentiation of radiation exposure by tetrac in animal glioma (C6) cells (68) and human glioblastoma (U87MG) cells (69), and Nanotetrac in human prostate cancer (PC3, LNCaP) cells (70). *In vitro* studies revealed that at a 4 Gy x-radiation dose 1 h after exposure to tetrac, there is a 60% reduction in cell survival, compared to control (68). The mechanism of action of tetrac and Nanotetrac is interference with cancer cell repair of double-strand DNA breaks (neutral comet assay/mean tail moment) (69). What components of the DNA break repair process – and, specifically, transcription of what specific genes – are affected by tetrac/Nanotetrac is not yet known.

### **ADJUNCTIVE MODIFICATIONS OF NUCLEAR HORMONE RECEPTORS THAT ORIGINATE AT THE HORMONE RECEPTOR ON** α**V**β**3; NUCLEAR UPTAKE OF** α**V MONOMER**

The above discussion relates to regulation of transcription of specific cancer cell genes by thyroid hormone analogs that act at the cell surface via integrin αvβ3. Relevant additionally to the end result of modulation of transcription of specific genes from integrin αvβ3 is the adjunctive input from the integrin to the state of

nuclear TRs. We have recently reviewed this subject (77). In brief, trafficking of cytoplasmic TRβ1 to the cell nucleus is directed by T4 at the integrin via MAPK, and the importing by the nucleus of TRα1 is promoted by T3 via activation of phosphatidylinositol 3-kinase (78). Two discrete binding domains exist at the TR site on αvβ3: the S1 site binds T3 exclusively and S2 binds both T4 and T3. Tetrac–Nanotetrac interferes with hormone binding at both domains. In the case of TRβ1 trafficking, translocation of the receptor into the nucleus occurs as a complex with activated MAPK; specific phosphorylation of the receptor (activation) is a consequence (79, 80). An example of specific gene transcription that occurs as a result of this trafficking/phosphorylation is expression of hypoxia-inducible factor-1α (*HIF1*α) in response to T3 at the S1 site (78). The complex process of stimulating cancer cell or endothelial cell proliferation occurs via the S2 domain.

Integrin αvβ3 may be internalized by cells as a result of the protein's liganding of T4 (13). The αv monomer is imported by the nucleus as a result of this process and has been shown to be a coactivator protein that binds to the promoter region of a number of genes, including *ER*α, *HIF-1*α, cyclooxygenase-2 (*COX-2*), and *TR*β1. ERα protein is important to breast, ovarian, and certain lung cancers. We have implicated nuclear COX-2 protein in the pharmacologic induction of apoptosis (58). HIF-1α protein is a cell survival factor that triggers angiogenesis and cellular conversion to anaerobic metabolism (81). The αv monomer does not import thyroid hormone and the β3 monomer is not taken up by the nucleus. This remarkable process was an unexpected consequence of studies of small molecule actions at the integrin and offers a novel mechanism for regulation of gene expression from the cell surface and integrin.

### **CONCLUSION**

Integrin αvβ3 controls a variety of intra-cellular and transcellular functions. It is a transmembrane structural protein that is differentially expressed/activated in tumor cells and dividing blood vessel cells. The definition of the specific thyroid hormone-tetrac receptor site on αvβ3 (10, 11, 14) enabled recognition of the existence of control from a single locus of expression of differentially regulated, angiogenesis-relevant genes as well as modulation of function of adjacent vascular growth factor receptors. Nanotetrac is a prototypic anti-angiogenic and anti-cancer agent focused on a single, specific small molecule receptor site on the extracellular domain of αvβ3. From this site,Nanotetrac blocks actions of VEGF, FGF2, and PDGF at their plasma membrane receptors, inhibits expression of *VEGFA* and *EGFR*, stimulates transcription of *TSP1*, decreases endothelial cell abundance of Ang-2 without affecting Ang-1, selectively regulates miRNAs that control angiogenesis and decreases endothelial cell motility (**Table 1**).

From the standpoint of anti-cancer activity, Nanotetrac desirably disrupts gene expression critical to cell cycling in αvβ3 bearing tumor cells and dividing endothelial cells and interferes with a substantial group of cell survival pathways so that apoptosis is advanced, and defensive anti-apoptosis pathways are disordered (**Table 2**). Nanotetrac reverses chemoresistance and confers radiosensitivity. This novel and extensive spectrum of actions makes Nanotetrac an attractive anti-angiogenic and anti-cancer agent for further development. The agent has been shown to be an effective anti-proliferative, pro-apoptotic agent in a variety of human cancer cell lines (25, 31, 40–43, 71), to be effective against human cancer xenografts (26, 57, 70, 82–84) and to include important downregulation of tumor-associated angiogenesis (22, 26, 36, 57, 82, 84).

In the absence of an agent such as Nanotetrac with anti-thyroid hormone activity at integrin αvβ3, a reduction in circulating thyroid hormone, notably T4, that is either spontaneous or medically induced appears to be effective in slowing clinical growth of certain solid tumors. These include breast (45), glioblastoma multiforme (44), head-and-neck cancers (47), and renal cell carcinoma (46). We can postulate that such reductions in systemic levels of T4 largely affect tumors via the examples of gene expression reviewed above. Several of the current authors have recently confirmed clinically that systematic reduction in circulating T4 (euthyroid hypothyroxinemia) may arrest growth of certain cancers (85).

### **REFERENCES**

for gene expression. *Arch Biochem Biophys* (2008) **474**:82–90. doi:10.1016/j.abb. 2008.03.020

**Conflict of Interest Statement:** Paul J. Davis and Shaker A. Mousa are co-inventors of Nanotetrac. The issued and pending patents for Nanotetrac are held by NanoPharmaceuticals LLC, a company from which the inventors receive no reimbursement. The other co-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.

*Received: 10 November 2014; paper pending published: 25 November 2014; accepted: 19 December 2014; published online: 12 January 2015.*

*Citation: Davis PJ, Glinsky GV, Lin H-Y, Leith JT, Hercbergs A, Tang H-Y, Ashur-Fabian O, Incerpi S and Mousa SA (2015) Cancer cell gene expression modulated from plasma membrane integrin* α*v*β*3 by thyroid hormone and nanoparticulate tetrac. Front. Endocrinol. 5:240. doi: 10.3389/fendo.2014.00240*

*This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Endocrinology.*

*Copyright © 2015 Davis, Glinsky, Lin, Leith, Hercbergs, Tang , Ashur-Fabian, Incerpi and Mousa. 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) or licensor 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.*

# **Corrigendum: "Cancer cell gene expression modulated from plasma membrane integrin αvβ3 by thyroid hormone and nanoparticulate tetrac"**

*Paul J. Davis 1,2 \*, Gennadi V. Glinsky 3 , Hung-Yun Lin4 , John T. Leith5 , Aleck Hercbergs 6 , Heng-Yuan Tang2 , Osnat Ashur-Fabian7,8, Sandra Incerpi 9 and Shaker A. Mousa2*

*1 Department of Medicine, Albany Medical College, Albany, NY, USA, 2 Pharmaceutical Research Institute, Albany College of Pharmacy and Health Sciences, Rensselaer, NY, USA, 3 Stanford University, Palo Alto, CA, USA, 4 Taipei Medical University, Taipei, Taiwan, 5 Rhode Island Nuclear Science Center, Narragansett, RI, USA, 6 Cleveland Clinic, Cleveland, OH, USA, 7 Hematology Institute and Blood Bank, Meir Medical Center, Kfar-Saba, Israel, 8 Department of Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel, 9 Department of Sciences, University Roma Tre, Rome, Italy*

**Keywords: integrin, thyroid hormone, tetraiodothyroacetic acid (tetrac), nano particle, gene expression, corrigendum**

#### **A corrigendum on**

*Edited by: Wen Zhou, Columbia University, USA*

#### *Reviewed by: Jean-Yves Scoazec, Université Lyon 1, France*

*\*Correspondence:*

*Paul J. Davis<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Endocrinology*

> *Received: 27 May 2015 Accepted: 27 May 2015 Published: 09 June 2015*

#### *Citation:*

*Davis PJ, Glinsky GV, Lin H-Y, Leith JT, Hercbergs A, Tang H-Y, Ashur-Fabian O, Incerpi S and Mousa SA (2015) Corrigendum: "Cancer cell gene expression modulated from plasma membrane integrin αvβ3 by thyroid hormone and nanoparticulate tetrac". Front. Endocrinol. 6:98. doi: 10.3389/fendo.2015.00098* **Cancer cell gene expression modulated from plasma membrane integrin αvβ3 by thyroid hormone and nanoparticulate tetrac**

*by Davis PJ, Glinsky GV, Lin H-Y, Leith JT, Hercbergs A, Tang H-Y, et al. Front Endocrinol (2015) 5:240. doi: 10.3389/fendo.2014.00240*

In Table 2, the section designated "Disabling of cell survival pathway gene expression," line 5 incorrectly states "*. . .*pro-apoptotic miR-21"; the correct statement is "*. . .*pro-apoptotic miR-15A." The issue is correctly discussed in the body of the published text, p. 2, right column, paragraph 4.

**Conflict of Interest Statement:** 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 © 2015 Davis, Glinsky, Lin, Leith, Hercbergs, Tang, Ashur-Fabian, Incerpi and Mousa. 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) or licensor 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.*

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**2.3 System boundaries and assumptions**

The system boundaries for the baseline WRM operation scenario where the WRM agency does not use Road-Weather Information System are shown in **Figure 1**. The WRM vehicle has to pass the road section four times during a snowstorm event. The length of the road section is 10.4 km; therefore the vehicle travels 41.6 km. The WRM vehicle conducts gritting and plowing simultaneously. The salt consumption is 40% higher than in the preventive WRM operation scenario, reaching 10 tons (**Table 1**). Because of the plowing, the fuel consumption of the WRM vehicle increases to around 50 L per 100 km (**Table 1**). Other vehicles passing the road section during snowstorm event must adapt their driving to the snow conditions on the road. We assumed fuel consumption to be 10 or even 20% higher in

### **Figure 1.**

*System boundaries for the baseline WRM operation scenario.*

case of driving on a road with snow bonding compared to driving on snow-free road (**Table 1**).

The system boundaries for the preventive WRM operation scenario, where the WRM agency uses Road-Weather Information System are shown in **Figure 2**. In this scenario, the WRM vehicle drives at normal speed (30 km/h), consuming around 40 L of diesel fuel per 100 km (**Table 2**). The WRM vehicle conducts a preventive gritting before the beginning of the snowfall and two more gritting operations during the snowfall event lasting for 10 hours. The 6 tons of road salt are required for such an operation, taking into account the length of the road section (10.4 km) and the fact that the WRM vehicle passes the road section three times. No plowing is required. All other vehicles passing the road section during a snowstorm event are assumed to be able to drive at normal speed. The fuel consumption of vehicles was accounted accordingly (see **Table 2**).

The data on the number of vehicles passing the particular road section considered in this study are from the year 2020. Data were obtained from the two traffic counting points located along the road section. It was assumed that the daily traffic in the

#### **Table 1.**

*Input data for baseline WRM operation scenario without application of road-weather information system. Winter road maintenance operation and road traffic mobility during snowstorm events are adapted to conditions with snow accumulating on the road surface.*

*Pathway toward Sustainable Winter Road Maintenance (Case Study) DOI: http://dx.doi.org/10.5772/intechopen.110764*

#### **Figure 2.**

*System boundaries for the preventive WRM operation scenario.*

studied section is the average number from the two counting points. Based on these data, it was assumed that during a 10-hour weather event, the road section is passed by 1500 passenger cars, 100 light-duty trucks, and 50 heavy-duty trucks. For passenger cars, we assumed that 40% of them are diesel cars and 60% are petrol cars, which is realistic information for Slovenian conditions, to which the case study refers.

### **2.4 Life cycle inventory analysis**

GaBi professional software (version 10.6) was used to conduct a comparative LCA analysis. Data related with the use stage of vehicles, data for the production of fuels required for vehicles and data for deicer were gathered from the Professional database, which is integrated into GaBi software. Inventory data applied in two scenarios are indicated in **Table 1** (baseline WRM operation scenario without application of Road-Weather Information System) and **Table 2** (preventive WRM operation scenario with the application of Road-Weather Information System).

#### **2.5 Impact assessment**

ReCiPe 2016 version 1.1 Life Cycle Assessment Impact method was used to evaluate the environmental impacts of two scenarios. The ReCiPe method was developed in 2008 to harmonize the results of two other methods, CML 2001 (midpoint-oriented) and Eco-indicator 99 (endpoint-oriented). ReCiPe is one of the most commonly used methods for the calculation of environmental impacts [15]. The main principles of the ReCiPe 2016 method are based on the ISO 14040 and 14044 standards. The characterization factors are continuously updated according

#### **Table 2.**

*Input data for preventive WRM operation scenario: Winter road maintenance operation and road traffic mobility in case of application of road-weather information system take place on road, which is snow- and ice-free.*

to new knowledge [16, 17]. The ReCiPe 2016 method allows the calculation of impact categories according to three-time perspectives (Individualist, Hierarchist, and Egalitarian). The Hierarchist perspective, which considers the most acceptable time period, is used in this study. The LCA results at the midpoint levels are presented by 19 impact categories (**Table 3**).


# **Urban Agriculture, Forestry and Green-Blue Infrastructure as "Re-discovered Commons" Bridging Urban-Rural Interface**

Edited by Ryo Kohsaka and Yuta Uchiyama Printed Edition of the Special Issue Published in *Sustainability*

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