Epithelial to Mesenchymal Transition: the Key to Cancer Metastasis

We have all seen science fiction movies where alien invaders, in search of a fertile planet like earth, start a full scale war against humanity. A common theme in many of these stories, but often overlooked, is the role of the scout. Before any invasion, a solitary member of the invaders, fortified for the harsh journey, is sent on a quest to scout out the new land. As soon as this scout finds a promised land, the colony is formed and the invasion begins. This concept of invasion is seen in nature with viral and bacterial infections, where fortified virus or sporulated bacteria are able to survive harsh conditions and then proliferate in their host system upon arrival. In an ironic display, cancer metastasis follows a similar system; cancer cells are able to leave the primary tumor, travel long distances in harsh conditions, and form colonies in other tissues within an organism. These metastases have grave consequences. In fact in certain cancers, such as melanoma, it is metastasis to vital areas like the brain that makes it life-threatening. One of the biggest areas in cancer biology research is elucidating the mechanisms involved in cancer metastasis, which includes the concept of the epithelial to mesenchymal transition (EMT). It is this process that gives the cancer “scouts” the means to invade vasculature, fortify themselves for a journey to the metastatic site, and resist most therapies at all locations in the tumor-bearing patient. In normal development, the epithelial to mesenchymal transition is a reversible system that is involved in embryonic gastrulation1 and cardiac development1,2. In adulthood, EMT is involved in wound healing3. Unfortunately, EMT is also involved in pathological events such as fibrosis of injured tissue1 and cancer development and progression1-4. Here, we focus on EMT’s role in tumorigenesis, cancer proliferation, treatment resistance, and metastasis.

The epithelial to mesenchymal transition occurs in many different solid tumors of epithelial origin. Many tumors are carcinoma based, which implies that they are usually confined from motility by the basement membrane1 but the process of converting toward a cancer cell that has mesenchymal characteristics allows cancer cells to infiltrate the circulatory and lymphatic systems, causing motility that will later lead to metastasis1,5. As a cancer progresses, epithelial features, such as cellular adhesion marker  E-cadherin3 and intracellular adhesion components such as tight junctions, cytokeratins, and desmosomes, are downregulated5. Coordinating with this downregulation is an upregulation of mesenchymal markers such as N-Cadherin, Vimentin, and Fibronectin3. This phenotypic shift is orchestrated by a coordination of many different mechanisms: epigenetic changes, post-translational modifications of proteins, transcriptional silencing by noncoding-RNAs (ncRNAs), and activation of epithelial to mesenchymal transcription factors (EMT-TFs)3. However, while all mechanisms of EMT development are important, this article will focus on the main orchestrators of EMT: the EMT-TFs.

EMT-TFs are many, but the main transcription factors fall into three families: SNAIL, ZEB, and TWIST. SNAIL has three main transcription factors: SNAIL (Snail1), SLUG (Snail2), and SMUC (Snail3)5. These proteins are zinc finger nucleases that are at the crux of EMT phenotype. In fact, it has been noted that SNAIL, and possibly SLUG, directly repress the expression of E-cadherin by binding to its promoter, CDH13. Furthermore, the SNAIL family has been shown to repress desmoplakin, adherens junctions, occulidins, and cytokeratin upon activation5. While not much is known about SMUC’s role in normal or pathological development, SNAIL, unlike SLUG, is so crucial to cancer metastasis that has been implicated in being an independent prognostic factor in the metastatic potential and severity of cancers5. Interestingly, not only does the SNAIL family propagate the characteristics of EMT transition, they also upregulate other EMT-TFs, such as ZEB1 and ZEB2, to further propagate the mechanism of EMT 5.

The Zinc-finger E-box-binding homeobox (ZEB) family are also a family of transcription factors with zinc-finger nuclease properties3. Like SNAIL, ZEB1 and ZEB2 bind to the E-cadherin promoter5. Moreover, ZEB1 and ZEB2 also downregulate tight/gap junctions, desmosomes and markers of polarity5. In addition, the ZEB family has been implicated in repressing P- and R-cadherins, other markers that inhibit the motility of epithelial cells5. ZEB1 is usually not found on non-cancerous cells but is found highly expressed on many cancer types5. In contrast, ZEB2 is expressed on normal epithelial cells, but is vastly upregulated in cancerous cells5.

describe the imageThe final group is the TWIST family, a basic helix-loop-helix transcription factor involved in different steps in embryonic development1. Interestingly, while TWISTs are vital to embryogenesis, they are absent in normal adult epithelium5. As a cancerous cell progresses , TWIST1 and TWIST2 appear and their reactivity increases in correlation with the tumorigenic progress5. Interestingly, while TWIST1 is involved  in regulating some of SLUG’s EMT effects, and directly drives expression of N-cadherin, it is not directly associated with the downregulation of E-cadherin5.

It is through these EMT-TFs that EMT is involved in tumorigenesis and tumor progression. EMT-TFs are involved in suppressing senescence and increasing cell cycle proliferation5. However, EMT-TFs are not enough to push tumorigenesis on their own, but require another event of tumorigenesis3. Therefore, EMT-TFs may act as a facilitator of tumorigenesis, but not be tumorigenic factors by themselves. EMT is also crucial for tumor invasiveness and metastasis. Besides the aforementioned changes in cellular adhesion molecules, activation of the EMT-TFs causes upregulation of matrix-metalloproteinases (MMP), enzymes involved in degradation of the extracellular matrix and invasion of cancer cells3. It has been demonstrated that the SNAIL family activates the expression of MMP1, MMP2, MMP7, and MT1-MP 5. Furthermore, the upregulation of MMPs additionally activates EMT-TFs, thus forming a feed-forward loop3. EMT events may also go beyond extracellular degradation; TWIST1 is known to be involved in the formation of invadopodia which has been correlated with invasiveness3.

The invasion of metastasis is not just due to intrinsic changes but also to changes in the host, and target microenvironment4. For instance, TGF-β, a cytokine that normally acts as a tumor suppressor, can enhance tumor invasion in later-stage tumors2. Furthermore, TGF-β activates the SNAIL and TWIST families of the EMT-TFs2,5. TGF-β may be produced by myeloid derived suppressor cells and CD11b+/F4/80+ tumor associated macrophages (TAMs) in the primary tumor microenvironment, thus perpetuating the EMT phenotype4. TAMs also express the cytokines fibroblast growth factor (FGF), epidermal growth factor (EGF), and macrophage colony stimulating factor (CSF-1) which are involved in EMT-based invasion as well as recruitment of immune cells toward a metastatic-favored microenvironment4. Moreover, TNF-α, usually correlated with  an anti-tumor phenotype, also stabilizes SNAIL expression, thus implicating it in facilitating EMT3. Besides immune cells, other stromal cells are involved in EMT initiating and metastasis. For instance, mesenchymal stem cells (MSCs) and cancer associated fibroblasts (CAFs) are both involved in EMT initiation and propagation4.

One of the more clinically relevant aspects of EMT in cancer progression is the ability of EMT to confer therapy resistance. Resistance to doxorubicin is breast cancer correlates with higher levels of ZEB15 and both ZEB1 and ZEB2 have been shown to guard against cisplatin therapy5. TWIST1 mediates resistance to paciltaxel and TWIST1 and TWIST2 block daunorubicin by inhibiting degradation of the anti-apoptotic protein, Bcl-2, in bladder, ovarian, and prostate cancer5. Along the same lines, the EMT has been shown to confer upon cells a cancer stem cell-like phenotype2,4, a cancer phenotype also known for its therapy resistance5. TGF-β-driven EMT activates protein involved in stem cell phenotype, such as Sox2, PDGFB, and LIF 2. Furthermore, ZEB1 has been shown to be vital in the formation and maintenance of stem cell phenotype in some cancers5. However, while activation of the EMT pathway may confer a cancer stem cell-like phenotype, it is not necessary to get this phenotype3 as EMT-TFs are not necessarily involved in dedifferentiation3. In fact, some reports shine controversy on EMT-TFs’ role in stem cell development: while colorectal cancer spheroids show higher levels of SNAIL, other studies have shown that overexpression of SNAIL and SLUG in ovarian cancer drives these cancers away from a stem cell phenotype5.

cancer patientBesides the difficulty in treatment that EMT poses, one of the main obstacles that is troubling the cancer metastasis field is difficulty in identification of EMT/MET in cancer in vivo4. Because EMT is an orchestration between tumor and it’s microenvironment, researchers have been unable to definitively demonstrate the role of EMT beyond stromal epithelium4. The field needs better phenotypic markers  to identify tumor epithelial cells from normal epithelial cells as well as a way to trace lineages of human cancers in vivo 4. Another is MET, the reverse of EMT and the end result of metastasis. To date, bona fide evidence for MET is only found in vitro studies and xenograft experiments4. MET explains why the phenotype of metastatic tumors mirror the primary site, but it is not an explanation for the system4. Several methods have been proposed to more appropriately study EMT, such as intravital 2-photon microscopy4. However, the sporadic nature of the EMT event makes observation, even in this system, very difficult4. In such a case, we are left to the spontaneous tumor-forming mouse models or studying xenograft models of immortalized cancer lines that are known to be highly metastatic. In addition, since there are no anatomically distinguishable between mesenchymal and epithelial cells, people have proposed the solutions of creating tumor lines the express reporter genes linked to promoters for epithelial/mesenchymal fates4. If one were able to combine an intravital two-photon system with a xenograft of a highly metastatic cancer line transduced with mesenchymal/epithelial reporter constructs, this would be the most feasible model to study EMT in real-time. As technology advances to detect individual cell populations in real-time, the expectation to solidify the mechanism of epithelial to mesenchymal transition in metastasis will increase the reliably of current EMT findings.

 

References:

1          Lim, J. & Thiery, J. P. Epithelial-mesenchymal transitions: insights from development. Development 139, 3471-3486, doi:10.1242/dev.071209 (2012).

2          Massagué, J. TGFβ signalling in context. Nat Rev Mol Cell Biol 13, 616-630, doi:10.1038/nrm3434 (2012).

3          Craene, B. D. & Berx, G. Regulatory networks defining EMT during cancer initiation and progression. Nat Rev Cancer 13, 97-110, doi:10.1038/nrc3447 (2012).

4          Gao, D., Vahdat, L. T., Wong, S., Chang, J. C. & Mittal, V. Microenvironmental regulation of epithelial-mesenchymal transitions in cancer. Cancer Res 72, 4883-4889, doi:10.1158/0008-5472.can-12-1223 (2012).

5          Sánchez-Tilló, E. et al. EMT-activating transcription factors in cancer: beyond EMT and tumor invasiveness. Cell Mol Life Sci 69, 3429-3456, doi:10.1007/s00018-012-1122-2 (2012).

 

Multidrug-Resistance in Cancer: ABC-Transporters

Multidrug-resistance (MDR) is the chief limitation to the success of chemotherapy. According to the National Cancer Institute, multidrug-resistance is a phenomenon where cancer cells adopt to anti-tumor drugs in such a way that makes the drugs less effective. Studies have shown that 40% of all human cancers develop MDR. Deaths due to cancer occur in most of the cases when the tumor metastasizes. Chemotherapy is the only choice of treatment in metastatic cancer, and MDR limits that option.

Cancer one resized 600As shown in Figure 1, tumor cells adopt several mechanisms to evade death induced by anti-tumor agents. These include changes in apoptotic pathways and activation of cell-cycle check points to increase DNA repair. Alternatively, cancer cells develop resistance by increased expression of multidrug-resistant proteins and altered anti-tumor drug transport mechanisms. Members of the ABC transporters (ATP-binding cassette) are known to be associated with this phenomenon, as the human genome express over 48 genes in this transporter family alone. These proteins bind ATP in their ATP binding domain and use the energy to transport various molecules across the cell, thus they are known as ABC proteins. Among these proteins, P-glycoprotein (Pgp, ABCB1), multidrug resistance-associated protein (MRP1, ABCC1), and breast cancer resistance protein (BCRP, ABCG2) are chiefly responsible for drug resistance in tumor cells. Studies are warranted to determine the role of other members of ABC transporters including MRP2, MRP3, MRP4, MRP5, ABCA2 and BSEP in drug-resistance.

MDR1(Pgp)

cancerPlasma membrane glycoprotein (Pgp) was the first ABC-transporter detected in various cancers exerting resistance to a variety of chemically unrelated cytotoxic agents including anti-tumor drugs such as doxorubicin, vinblastine, ritonavir, indinavir and paclitaxel. It works as an energy-dependent efflux pump and can recognize a wide range of substrates. Even though this protein normally protects us from endogenous and exogenous toxins by transporting them out of the cells, the transporter causes a major problem in the bioavailability of anti-tumor drugs to tumor cells during chemotherapy.

Clinical Significance

Pgp plays an important role in altering the pharmacokinetics of a wide variety of drugs. This efflux pump creates a major physiological barrier in pharmacokinetics of drugs because of its localization at the site of drug absorption and elimination. Tumors with detectable levels of Pgp are 3-4 fold more susceptible to chemotherapeutic failure than Pgp negative tumors. Therefore the role of Pgp in the development of MDR is very significant: it has been used as a potential target for reversing clinical MDR. To overcome Pgp mediated drug resistance several inhibitors are developed and currently in clinical trials which include verapamil, cyclosporin A, quinine, and tamoxifen.

Multidrug Resistance Protein 1 (MRP1)

Like Pgp, MRP1 is also overexpressed in tumor cells and represents a major obstacle to drug delivery. MRP1 is ubiquitiously expressed in the lung, testis, kidney, and peripheral blood mononuclear cells in humans.

Clinical Significance

High levels of expression of MRP1 protein was observed in non-small-cell lung cancer. In breast cancer, there is also a significant expression of this protein which may increase the chance of treatment failure. Studies have also shown that over expression of MRP causes resistance to methotrexate (MTX) and antifoliates such as ZD1694 in colorectal cancer. Development of MRP1 inhibitors is in progress. In preclinical studies, effective inhibition of MRP1 was observed following treatment with MK571 and ethacrynicacid.

Breast Cancer Resistance Protein (BCRP)

BCRP belongs to a novel branch of the ABC-transporter family. The members of this subfamily are about half the size of the full-length ABC transporters, thus known as half-transporters. Overexpression of BCRP was reported in the plasma membrane of  drug-resistant ovary, breast, colon, gastric cancer, and fibrosarcoma cell lines. Even though the normal physiological function of BCRP has not been determined, it is possible that BCRP plays an important role in drug disposition. The overexpression of this protein causes reduced accumulation of chemotherapeutic agents such as mitoxantrone, irinotecan, SN-38, topotectan, and flavopiridol.

Clinical Significance

Since BCRP is expressed in the gastrointestinal tract, it is thought that this protein may affect the bioavailability of the drugs. Its overexpression in several types of cancer makes it a relevant target of strategies aimed at defeating multidrug-resistance. Some of the potent inhibitors of BCRP are Fumitremorgin C, reserpine and tryprostatin A.

Cancer defends itself against chemotherapeutic regimes by several mechanisms including MDR. Therefore, a detail understanding of ABC-transporters mediated drug resistance would help to formulate strategies to overcome this problem. Screening of novel inhibitors of ABC-transporters which are not effluxed by these transporters is currently in progress. One of these drugs, ixabepilone, has been approved in the United States for the treatment of breast cancer patients pretreated with an anti-tumor agent. Ongoing efforts to circumvent MDR also include development of potentially effective alternative strategies (e.g drug delivery using liposomes or nanoparticles, inhibition of expression of MDR associated ABC-transporters using monoclonal antibodies). Promising experimental data on these strategies suggest their potentialily to overcome important causes of MDR to significantly improve cancer treatment.

 

References:

1.         Türk D, Hall MD, Chu BF, et al. Identification of compounds selectively killing multidrug-resistant cancer cells. Cancer Res. 2009;69(21):8293-8301.

2.         Litman T, Druley TE, Stein WD, Bates SE. From MDR to MXR: new understanding of multidrug resistance systems, their properties and clinical significance. Cell Mol Life Sci. 2001;58(7):931-959.

3.         Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer. 2002;2(1):48-58.

4.         Gottesman MM, Ludwig J, Xia D, Szakács G. Defeating drug resistance in cancer. Discov Med. 2006;6(31):18-23.

5.         Nobili S, Landini I, Mazzei T, Mini E. Overcoming tumor multidrug resistance using drugs able to evade P-glycoprotein or to exploit its expression. Med Res Rev. 2012;32(6):1220-1262.

Cancer Stem Cell Hypothesis: Proceed with Caution

CSC picture

In 1937, the cancer stem cell hypothesis was proposed to explain the concept of tumor heterogeneity (Clevers, 2011). In the mid 1990s, alongside the boom of stem cell biology, the theory that subpopulations of leukemia with stem cell-like properties was reintroduced with seminal work from John Dick (Clevers, 2011). These subpopulations were named “cancer stem cells” (although many today prefer the term “tumor-initiating cells”) due to their tumorigenicity and apparent self-renewal, thus mimicking the adult stem cell properties of multipotency and self-renewal. Today, cancer stem cell populations have been identified for cancers of the brain, pancreas, ovary, colon, liver, as well as leukemia (Magee et al, 2012). However, while confirmation of tumor-initiating cells in all tumors cannot be proven (Magee et al, 2012), the study of cancer stem cells remains important due to its possible impact on current cancer therapy.

In many tumors, cancer cell subpopulations are believed by many to be resistant to chemotherapy and radiation therapy (Clevers, 2011) (Magee et al, 2012). The importance becomes clearer when one looks at the possible outcome of not taking into account targeting cancer stem cells when developing cancer therapy. Computer simulations have shown that use of therapy that only targets non-tumorigenic cancer cells would enrich for the tumorigenic tumor-initiating cells, exacerbating the malignancy of many cancers (Vermeulen et al, 2012). This would explain why many cancers are more malignant after treatment with current therapy. In addition, the current intricacy of dealing with heterogeneity of the tumor is an issue since many different cancerous cell types respond differently to current therapies (Vermeulen et al, 2012) thus making ideal therapy difficult.

The cancer stem cell hypothesis is not the only theory to be brought forth to explain tumor heterogeneity.  One belief is in the stochastic model of tumor heterogeneity, where variances in genetics and epigenetics cause the heterogeneity of tumor. Due to selection of more robust subpopulations, clonal evolution causes cell populations to proliferative non-uniformly in a tumor (Magee et al, 2012). Another proposed theory of tumor heterogeneity is the belief in the variation of extrinsic factors caused by the changes in the tumor microenvironment (Magee et al, 2012). In this model, cells that are closer to areas, such as the vasculature, form a niche that change the properties of tumor cells in a temporary, or permanent, manner (Magee et al, 2012). The cancer stem cell model states that a distinct subset of a tumor is tumorigenic and has the ability to self-renew (form more tumorigenic cells) or differentiate into the bulk of the non-tumorigenic cells of the tumor (Magee et al, 2012).  Within the tumor-initiating cell community, there has been increasing support for a non-mutually exclusive model which has a combination of the hypotheses listed above that may contribute to tumor heterogeneity (Clevers, 2011)(Magee et al, 2012). One must account for all of these factors as possibilities when studying populations that may be tumorigenic inside a tumor model. For instance, attempting to study a certain population of ovarian cancer stem cells in vitro does not recapitulate the microenvironment and may negatively affect observation outcomes.

There have been many proposed mechanisms for identifying and studying cancer stem cells. These include the isolation of specific surface marker phenotypes, the use of cultures that are thought to favor the clonogenicity of the cancer stem cell population (such as the sphere forming cultures), serial transplantations of certain populations into immunocompromised mice to check tumorigenicity, and microscopic analysis of tumor heterogeneity through markers. However, there are limitations and caveats that one must consider when using these techniques to study cancer stem cell biology. First, studies have indicated that the cancer stem cell phenotype may be a context-specific event, showing up only in certain patient samples at certain ages (Magee et al, 2012). Furthermore, it is still unknown whether non-tumorigenic cells may become (through spontaneous formation or de-differentiation) tumorigenic cancer stem cells.  This phenotypic plasticity calls into question the isolation of certain populations and the validity of ex-post facto tumor heterogeneity since confirmatory data to the initial isolation of a cancer stem cell population and subsequent studies would be lacking.

Therefore, if one were to study cancer stem cells, the key is to not rely too heavily on one assay, but to interweave all of the assays for bona fide tumor-initiating cell experimentation.  For instance, one should study different populations of brain tumors, keeping in mind the limitations of their results, and be able to recapitulate their findings in a properly formed sphere formation assay as well as in an in vivo limited dilution model of tumorgenecity.  Even to this end, the expression of cancer stem cells, both in number and property, may be extremely patient specific and rigorous testing of individual cases must be performed before any basic-science concepts are used for treatment.

Things to keep in mind when studying cancer stem cells:

  • Although controversial, Cell surface markers have been correlated with a cancer stem cell phenotype, these include:
  • Glioma: CD133, SSEA1, CD49f, Musashi-1, and Nestin
  • Breast: BMI-1, CD44, CD24, CD49f, ALDHA1, and EpCAM
  • Lung: ALDHA1, CD90, CD117, and EpCAM
  • Upregulation of certain stem cell associated genes, such as Nestin, Oct4, Sox2, Nanog, Mushashi1, Notch1, and Notch4 have also been traditionally used to identify cancer stem cell subpopulations
  • Multiple primary tumors tend to be better specimens to study compared to immortalized cancer cell lines, which have undergone many mutations through passages that may affect the representative phenotype of tumor-initiating cells.
  • Many labs studying cancer stem cells agree that lineage tracing and side-by-side fate mapping of tumor subpopulations is essential for proper tumor-initiating cell studies.
  • Single-cell, serial transplantation into immunocompromised mice, if feasible in your system, is an adequate assay to test for cancer stem cell phenotype. However, there are still possible issues of minor immunoediting in immunocompromised mice. If one is dealing with murine specimens, the use of a syngeneic mouse line may limit this issue.
  • The possibility of quiescent cancer stem cells must be taken into account
    • This can be studied looking at the cell population of interest and performing a western blot analysis on stem cell associated proteins (such as Sox2, Nestin, Oct 4, Nanog, etc.) with cell proliferation markers (increase of cell cycle regulators, such as p21, Cyclin D2, TP53 and a downregulation of cell cyclin proliferative markers such as Cyclin B1, cdc20, and Myc)(Moore and Lyle, 2011).
    • Use label-retention/chase experiments, such as tritiated thymidine (3H-TdR) or 5-bromo-2-deoxy-uridine (BrdU), on your cell of interest is also a good technique and an in vivo alternative a (Moore and Lyle, 2011).
  • Genetically engineered mouse models that spontaneously form tumors are tools that allow for the study of tumor-initiating cells while controlling for most artificial biases seen in engraftment of xenospecies cells and/or high-passage cancer cells. There is some concern whether artificial plastic culture conditions may affect the in vitro study of cell populations due to the lack of mechanical sensitivity found in the actual tumor microenvironment.  This may be controlled for by assaying clonal analysis on a 3D scaffold system that is representative of the primary location of the tumor (Pastrana et al, 2011).
    • Sphere formation assays may select against tumor initiating cells that do not form spheres (Read  and Wechsler-Reya,  2012).

Suggested Reading/ References:

The cancer stem cell: premises, promises, and challenges. Clevers H. Nature Medicine 2011 Mar 7:17(3).

Cancer Stem Cells: Impact, Heterogeneity, and Uncertainty. Magee JA, Piskounova E, Morrison SJ. Cancer Cell 2012 Mar 20:(21).

The developing cancer stem-cell model: clinical challenges and opportunities. Vermeulen L, De Sousa e Melo F, Richel DJ, Medema JP. Lancet Oncology Feb: (13):e83-89.

Quiescent, Slow –Cycling Stem Cell Populations in Cancer: A Review of Evidence and Discussion of Significance. Moore N and Lyle S. Journal of Oncology, 2011.

Spheres without Influence: Dissociationg In Vitro Self-Renewal from Tumorigenic Potential in Glioma. Read TA, Wechsler-Reya RJ. Cancer Cell, 2012 Jan 17: (21).

Eyes Wide Open: A Critical Review of Sphere-Formation as an Assay for Stem Cells. Pastrana E, Silva-Vargas V, Doetsch F. Cell Stem Cell May6:(8).

Histone Deacetylase Inhibitors: A New Treatment Option in Cancer

Even though cancer is considered as a disease of genetic defects, various studies have shown that epigenetic changes also play an important role in the onset and progression of cancer. Histone acetylation is one of the important epigenetic modifications, and is controlled by two enzymes: histone acetyltransferases (HATs) and histone deacetylases (HDACs).  HAT transfers the acetyl group from the acetyl co-enzyme A to lysine residues of the histones comprising the core. This is thought to loosen DNA resulting in greater access to DNA for transcription factors and RNA polymerase. HDAC on the other hand, removes the acetyl groups, resulting in the compaction of chromatin thus narrowing access to DNA. Aberrant acetylation of the histone tail by these enzymes is associated with carcinogenesis. Expression patterns of various genes may become changed due to the altered activities of these enzymes.

Histone Deacetylases (HDACs)

HDACs cause transcriptional repression of genes by deacetylating lysine residues on describe the imagehistone tails. HDACs also cause deacetylation of non-histone proteins thus altering the transcriptional activity of p53 (tumor suppressor gene), E2F (transcription factor), c-Myc (transcription factor), nuclear factor kB (NF-kB), hypoxia inducible factor 1α (HIF-1 α), estrogen receptor α, and androgen receptor complexes.

HDACs in Cancer

HDACs are important enzymes in regulating various cellular processes. However, over-expression and abnormal recruitment of HDACs to the promoter region of various tumor suppressor genes may cause tumor initiation and progression. A number of studies have reported a high level of expression of HDACs in various tumors compared to normal cells. Increased expression of HDAC1 was reported in gastric, prostate, colon, and breast carcinomas. Elevated expression of HDAC2 was found in colon cancer.  High levels of expression of HDAC6 were reported in breast cancer. In addition to the over-expression, aberrant recruitment of this enzyme to specific promoter regions may also promote tumor invasion and metastasis. For example, E-cadherin is a transmembrane protein that is found in epithelial cells and plays an important role in cell adhesion. Invasive carcinomas exhibit reduced expression or loss of function of E-cadherin. Recruitment of HDAC1 and HDAC2 to the promoter region of E-cadherin by transcription factor Snail caused reduced expression of E-cadherin.

In addition to histone deacetylation, HDACs also deacetylate non-histone proteins.  For example, mammalian HDAC1, 2, and 3 impair the function of tumor suppressor gene p53. HDACs also alter the transcriptional activity of transcription factor E2F, c-Myc, nuclear factor kB, and HIF-1 α. The chaperone activity of the heat shock protein Hsp90 is regulated by HDAC6. Most of the client proteins of Hsp90 are proteins kinases (c-Raf, MEK, Akt, HER-2) or transcription factors (androgen receptor, progesterone receptor, estrogen receptor) associated with cell proliferation, survival, and signaling.

Histone Deacetylase Inhibitors (HDIs)

With the increasing knowledge of the roles of the HDACs in cancer, efforts have been made to identify potent inhibitors. HDIs identified so far have been shown to induce growth arrest, differentiation, and apoptosis in tumor cells. These inhibitors were found to induce cell cycle regulatory protein p21, apoptotic proteins Bax, and PUMA. HDIs were also able to down-regulate various survival signaling pathways and were able to disrupt the cellular redox state. Therefore, in recent years HDIs have drawn interest as anti-cancer agents. Several HDIs aredescribe the image currently in clinical trials both in monotherapy and in combination therapy with other anti-tumor drugs. A review by Tan et al. (2010) reported that at least 80 clinical trials are underway, testing more than 11 different HDIs in hematologic and solid tumors, including leukemias, lymphomas, and multiple myeloma, lung, breast, pancreas, renal, and bladder cancers, melanoma, glioblastoma. To date, most of the responses using HDIs as single agents were observed in advanced hematologic tumors and few were observed in solid tumors. In 2006, HDI vorinostat (suberoylanilide hydroxamic acid, SAHA) was approved by the Food and Drug Administration (FDA, USA) for the treatment of relapsed and refractory cutaneous T-cell lymphoma CTCL. In November, 2009, the FDA also approved another HDI romidepsin (depsipeptide) for the treatment of CTCL, and in 2011 for the treatment of peripheral T-cell lymphoma patients who have already received prior therapy.

Even though HDIs have shown anti-tumor activity across a broad variety of hematologic and solid tumors in the clinical trials, only a portion of patients with a given diagnosis showed therapeutic response. Therefore, a detailed understanding of the mechanisms of action, as well as mechanisms of resistance, of HDIs would help to identify markers and formulate strategies which may enhance the efficacy of HDIs in the clinic.

Further reading:

1. Johnstone RW. Histone-deacetylase inhibitors: novel drugs for the treatment of cancer. Nat Rev Drug Discov. 2002;1(4):287-299.

2. Lane AA, Chabner BA. Histone deacetylase inhibitors in cancer therapy. J Clin Oncol. 2009;27(32):5459-5468.

3. Ropero S, Esteller M. The role of histone deacetylases (HDACs) in human cancer. Mol Oncol. 2007;1(1):19-25.

4. Shankar S, Srivastava RK. Histone deacetylase inhibitors: mechanisms and clinical significance in cancer: HDAC inhibitor-induced apoptosis. Adv Exp Med Biol. 2008;615:261-298.

5. Tan J, Cang S, Ma Y, Petrillo RL, Liu D. Novel histone deacetylase inhibitors in clinical trials as anti-cancer agents. J Hematol Oncol. 2010;3:5.

Cancer Biomarkers: How they are used for personalized medicine

As promising cancer treatments emerge the need for improved detection and characterization methods are still evident.  Identification of novel biomarkers is a promising area of cancer research and development but because of the high complexity and heterogeneity of tumors much remains to be learned.

What is a cancer biomarker? A biomarker is a biological molecule that can be found in the blood, bodily fluids or tissue of interest (i.e. tumor) that can give information about the molecular characteristics of a tumor.

Specimens for biomarker discovery

Potential biomarker biological molecules

  • DNA (copy number, methylation states, mutations)
  • RNA (mRNA, microRNA)
  • Protein (phosphorylation, post-translational modifications)
  • Metabolic products

Tools for cancer biomarker identification

Biomarkers can be used as tools for diagnosis (detect the presence of cancer), prognosis, tracking cancer progression, and assessing treatment efficacy.

In cancer, a biomarker is often a protein that is mutated or is expressed at higher levels in the cancerous cells compared to the normal tissue.  There are various proteins whose mutated status is shared by multiple types of cancers these include inactivating mutations of tumor suppressor proteins such as the cell cycle regulators p53, PTEN, and retinoblastoma protein (RB) and activating mutations of proto-oncogenes such as Ras and Myc.  Another prominent cancer biomarker is the cell proliferation marker, Ki67 that can be used not only as a prognostic indicator but also to assess the efficacy of a treatment where reduction in Ki67 expression indicates reduced cellular proliferation.

Types of biomarkers and their uses

types_of_biomarkers_uses.jpg

  1. Prognostic biomarker: Knowing the key molecular changes in a patient’s cancer allows a doctor to determine whether the patient is likely to have a poor outcome and thus more aggressive treatment is necessary.
  2. Predictive biomarker: Understanding the molecular characteristics about a patients cancer can lead to tailoring of drug treatments with a higher likelihood of efficacy.  For example, patients with certain kinase domain mutations on EGFR would possibly not respond to EGFR targeted treatments such as erlotinib. Additionally this gives the added benefit reducing a patients exposure to possible toxic side effects from a drug they may not have benefited from.
  3. Pharmacodynamic biomarker: Using biomarkers drug dosing could be tailored to each patient. Dosing a drug that has a specific molecular target can be decided based on its ability to decrease the activity of its biological target. For example, if a patient shows high activity for a particular kinase a targeted drug could be dosed up for that patients specific needs.

biomarker_drug_selection

With the advent of genomic and proteomic technology and improved data mining algorithms, it is now easier and faster to identify biomarkers.  Unfortunately, a major limitation in biomarker research and discovery is the need for biopsy samples and their limited availability for research. Another issue is that most biopsy samples available are taken from a patient during the initial diagnosis. Less available are samples from patients post treatment initiation or with advanced disease where the molecular characteristics of their cancer may have very likely changed.

Luckily, there is great interest in developing and improving current technologies to utilize blood specimens for protein, metabolic products, CTCs and circulating DNA as alternative non-invasive sources to identify and screen for cancer biomarkers.

Further reading:

Mining the plasma proteome for cancer biomarkers

The cancer biomarker problem

Taming the dragon: genomic biomarkers to individualize the treatment of cancer

Proteomics for Cancer Biomarker Discovery

 

Clinical Trials: What’s New in Oncology?

Novel Immunotherapy Shows Promise for Various Types of Cancers

Since the approval of Provenge and Yervoy immunotherapies, development of anti-cancer immune therapies has gained a lot of momentum. Bristol-Myers Squibb’s and Ono Pharma’s antibodies targeted toward PD-1 and PD-L1 molecules are showing great promise for the treatment of non-small cell lung cancer, melanoma, kidney cancer and ovarian cancer. PD-1 is a molecule found on T-cells, when PD-1’s ligand PD-L1 binds to it T-cells loose activity or die. These targeted antibodies block the binding of ligand to receptor and in doing so maintain anti-tumor T-cell activity.   

Investigational Drug Trastuzamab Emtansine Delays Progression of Advanced HER2-positive Breast Cancer

Trastuzamab emtansine  (T-DM1) is a combination drug containing the trastzamag (Herceptin) antibody attached to chemotherapeutic agent DM1. DM1 is toxic when delivered alone into the bloodstream, combining it with an antibody which has specificity for a given antigen limits its potential wide range toxicity to only cells positive for Her2. Women treated with T-DM1 benefited from a 3 month progression free survival compared to patients treated with lapatinib (Her2/neu and EGFR inhibitor) and chemotherapeutic, capecitabine (DNA synthesis inhibitor) combination treatment.

The FDA is expected to decide on the approval of T-DM1 on Feb. 26, 2013.

Improved Therapy for Rare Form of Brain Cancer
Brain tumor resized 600
Clinical trials conducted on patients with anaplastic oligodendrogliomas, a rare form of brain cancer (anaplastic oligodendrogliomas account for less than 10% of brain cancers) were found to live much longer if treated with a combination of chemotherapy and radiation therapy rather than radiation alone. These findings came after a long term (10 yr) follow up in patients whose tumors had mutations or deletions in both chromosomes 1 and 19 which account for about half of all cases.  Patients who lacked those mutations did not show any benefit to the combination treatment.  This work highlights the importance of genetic screening of a patients cancer and tailoring of cancer treatments.  

Promising New Treatment for Drug-Resistant Leukemia

Chronic Myeloid Leukemia (CML) patients who have failed all therapeutic options now have a new drug option, ponatinib. This drug is efficacious at inhibiting various mutations of the BCR-ABL fusion protein known to cause CML. First and second-generation BCR-ABL inhibitors imatinib, desatinib and nilotinib are effective in the treatment of CML but eventually acquired resistance develops towards these treatments or in some cases there is no response. Resistance to these therapies is largely attributed to mutations on BCR-ABL. Ponatinib is said to overcome these limitations based on its intelligent design that renders it capable of blocking BRC-ABL’s various mutations.

The FDA approved ponatinib on Dec. 14, 2012 for the treatment of CML and Philadelphia chromosome-positive acute lymphoblastic leukemia (ALL). 

Characterization of Myeloid Suppressor Cells in the Tumor Microenvironment

Myeloid suppressor cells (MSCs) such as of macrophages and myeloid derived suppressor cells (MDSCs) are thought to be key players in cancer promotion and resistance to therapy.  MSCs originate from the myeloid lineage in the bone marrow and circulate the bloodstream. They are recruited from the peripheral blood to tissues or tumor sites by cytokines such as colony stimulating factor-1 (CSF-1) where they can differentiate into macrophages or MDSCs. Their normal role is to protect a host from possible autoimmune reactions and to subdue over active immune responses.

Macrophages can exist in various activation states depending on the cues they receive from their environment. Classically activated or M1 macrophages are said to be anti-tumor and pro-inflammatory.  Signaling from cytokines such as GM-CSF, TNF, IFN-γ, or microbial stimuli such as LPS promote an M1 response. M1 macrophages are said to be cytotoxic, and secrete reactive oxygen species (ROS), and thus can damage tissue. Alternatively activated or M2 macrophages are said to be pro-tumorigenic and anti-inflammatory. Cytokines such as IL4, IL-13 and IL-10 are said to promote an M2 activation state, although the designation of IL-10 as an M2 skewing cytokines remains controversial in the field. M2 macrophages downregulate T-cell activity, secrete high levels of growth factors, angiogenenic factors and matrix remodeling enzymes. Thus, macrophages can either promote an anti-tumor inflammatory response or suppress it depending on the cytokines (signals) and they encounter.

The different activation states of macrophages can be characterized by variations in cell surface and intracellular marker expression levels.  Both M1 and M2 macrophages express myeloid markers CD11b and CD33, monocyte marker CD14 as well as macrophage marker, glycoprotein CD68. M1 macrophages express high levels of pro-inflammatory cytokines IL-12, IL-23, and low levels of the anti-inflammatory cytokine IL-10 while the reverse is true for M2 macrophages. The mannose receptor CD206 and scavenger receptor CD163 are expressed at elevated levels in M2 macrophages.  CD68, CD163 and CD206 markers are used largely for immunohistological characterization of macrophages although flow cytometry analysis with these marker is also possible.

Retrospective studies have been carried out on breast, melanoma, pancreatic, and non-small cell lung cancer specimens to name a few, assessing the phenotype of tumor associated macrophages based CD68, CD163, and CD206 expression levels.  In general, a negative or poor prognosis was associated with higher levels of M2 versus M1 macrophages.
It is important to note that variations of the M2 phenotype exist.  Additionally, these phenotypes are quite plastic and it is therefore possible for macrophages to switch between activation states.

MDSCs are a heterogeneous population of immature myeloid cells that share many functions with tumor associated macrophages. Although their most noted function is a strong ability to suppress T-cell proliferation and activity. MDSCs consist of polymorphonuclear (granulocytic) and monocytic cells (PMN and MO-MDSC). PMN-MDSCs do not express HLA-DR while MO-MDSC express low levels of HLA-DR and thus both are poor antigen presenting cells. CD14 and VEGFR1 are markers that can be used to differentiate between PMN and MO-MDSCs populations.  PMN-MDSC phenotype is VEGFR1+CD14 and MO-MDSCs are VEGFR1CD14+.

Based on the pro-tumorigenic properties of MSCs they present novel targets for anti-cancer therapies.  Pre-clinical studies in mouse models suggest blockade of MSC recruitment to tumors in combination with chemotherapies and anti-angiogenic treatments have beneficial effects in delaying the onset cancer cells resistance to therapy.

Further reading:
Transcriptional Profiling of the Human Monocyte-to-Macrophage Differentiation and Polarization: New Molecules and Patterns of Gene Expression

Myeloid Cells in the Tumor Microenvironment: Modulation of Tumor Angiogenesis and Tumor Inflammation

Tumour-associated macrophages are a distinct M2 polarised population promoting tumour progression: Potential targets of anti-cancer therapy

Spring Quarter 2013: Oncology Conferences and Events

Noncoding RNAs in Development and Cancer
January 20 – 25, 2013
Vancouver, British Columbia, Canada
IT’S NOT TOO LATE TO SUBMIT YOUR ABSTRACT. Email your formatted abstract to abstracts@keystonesymposia.org or call +1 970-262-1230/+1 800-253-0685.
Abstracts received can no longer be considered for oral short talks; poster display opportunities remain open. There will be an additional USD 50 administrative fee (USD 100 total) for abstracts received after the initial abstract deadline.

Cancer Immunology and Immunotherapy
January 27 – February 1, 2013
Vancouver, British Columbia, Canada
IT’S NOT TOO LATE TO SUBMIT YOUR ABSTRACT. Email your formatted abstract to abstracts@keystonesymposia.org or call +1 970-262-1230/+1 800-253-0685.
Abstracts received can no longer be considered for oral short talks; poster display opportunities remain open.
There will be an additional USD 50 administrative fee (USD 100 total) for abstracts received after the initial abstract deadline.

Gastrointestinal Cancers Symposium
Housing and Early Registration Deadline: December 19, 2012
Moscone West Building
San Francisco, California

Immune Responses in Tumor Microenvironment Workshop
Jan 30, 2013
San Diego, CA

Lung Development, Cancer and Disease
February 5 – 10, 2013
Taos, New Mexico, USA
IT’S NOT TOO LATE TO SUBMIT YOUR ABSTRACT. Email your formatted abstract to abstracts@keystonesymposia.org or call +1 970-262-1230/+1 800-253-0685.
Abstracts received can no longer be considered for oral short talks; poster display opportunities remain open.
There will be an additional USD 50 administrative fee (USD 100 total) for abstracts received after the initial abstract deadline.

Tumor Metabolism
February 24 – March 1, 2013
Keystone, Colorado, USA
IT’S NOT TOO LATE TO SUBMIT YOUR ABSTRACT. Email your formatted abstract to abstracts@keystonesymposia.org or call +1 970-262-1230/+1 800-253-0685.
Abstracts received can no longer be considered for oral short talks; poster display opportunities remain open.
There will be an additional USD 50 administrative fee (USD 100 total) for abstracts received after the initial abstract deadline.

4th Cancer Targets & Therapeutics Conference
25 Feb 2013 → 26 Feb 2013
Las Vegas, United States

State-of-the-Art Molecular Imaging in Cancer Biology and Therapy
An AACR-SNMMI Joint Conference
February 27-March 2, 2013
San Diego, CA
Advance registration deadline: Sunday, January 13

Epigenetic Marks and Cancer Drugs
March 20 – 25, 2013
Santa Fe, New Mexico, USA

AACR Annual Meeting 2013
Program Committee Chairperson: José Baselga
April 6-10, 2013 • Washington, DC
Abstract submission deadline: Thursday, November 15
Early registration deadline: Friday, December 21

Avon Walk for Breast Cancer
Houston
April 20-21, 2013

Making Strides Against Breast Cancer
Albuquerque NM
Sunday, April 28, 2013
7:30 AM to 10:00 AM

Making Strides Against Breast Cancer
Portland, OR
Saturday, May 11, 2013
9:00 AM to 1:00 PM

The Hippo Tumor Suppressor Network: From Organ Size Control to Stem Cells and Cancer 
May 19 – 23, 2013
Monterey, California, USA

Accelerating Anticancer Agent Development and Validation Workshop
May 8-10, 2013
Bethesda, MD

Synthetic Lethal Approaches to Cancer Vulnerabilities
May 17-20, 2013
Bellevue, WA

How immune cells can promote cancer progression

Did you know that the immune system can actually help promote cancer?

The tumor microenviroment is a complex milieu containing stromal cells (such as immune cells and fibroblasts), signaling molecules such as cytokines, and extracellular matrix. There is growing evidence that immune cells in the tumor microenvironment can be tricked by tumor cells to help the cancer grow by promoting angiogenesis (new blood vessel formation), suppressing the anti-tumor immune response, and promoting growth by secretion of growth factors. Immune cells are also thought to aid in the metastatic process as well as confer resistance to various chemotherapies.  It is therefore extremely important to further understand the interplay between cancer cells and cells in the tumor microenvironment.

Immune cells present in the tumor microenviroment include effectors of adaptive immunity (immunity guided by specific identification of pathogens) such as T-cells, dendritic cells, and to a lesser extent, B-cells. Also present are cells of the innate immune system (non-specific identification of pathogens) such as macrophages and other myeloid derived cells, leukocytes, and rarely natural killer cells.

Cytotoxic T-cells, can kill tumor cells by secreting cytotoxic substances such as perforin, granzymes, and granulysin.  Their activity can be regulated by various cytokines or signals from helper T-cells or other cells in the tumor microenviroment.

The myeloid lineage in tumors, generally termed myeloid suppressor cells (MSC), are considered key in the aberrant growth promotion of tumor cells and suppression of the anti-tumor immune response.  They are considered the major inflammatory cells of many solid tumors, including breast and prostate. MSCs in tumors include, tumor associated macrophages (TAM), polymorphonuclear and monocytic myeloid derived suppressor cells (PMN and MO-MDSC)Similar to T-cells, MSC activity can also be modulated by signaling factors from the microenvironment and can be induced to become more anti-tumor and pro-inflammatory.

MSCs share similar functions and their role in cancer promotion is said to be several fold.  First, they can suppress the adaptive immune response and thus function as regulators of anti-tumor T-cell activity. Second, they can induce angiogenesis through secretion of vascular endothelial growth factors (VEGFs) and matrix remodeling enzymes.  Additionally, they can also promote growth and proliferation by secreting growth factors such as epidermal growth factor (EGF), fibroblast growth factors (FGFs) among others.

In non-pathological conditions, myeloid derived cells play a large role in wound repair also by promoting angiogenesis, growth and proliferation. Therefore, it is easy to deduce that during chemotherapy or any type of anti-tumor treatment a dying tumor cell may appear as a wound that needs repair or healing.

Further research to better understand the interplay of tumor cells and the microenvironment as well as how to better fine-tune the tumor microenvironment against cancer is imperative for the development of better therapeutic agents.

DNA sequencing from peripheral blood test detects cancer

Aberrant alteration of chromosomal DNA drives the development and progression of cancer. There are a variety of alterations that promote tumorigenesis including aneuploidy, chromosomal translocation, gene amplification, and point mutations.

The ability to identify these abnormalities in cancer patients is central to disease diagnosis, staging, and treatment. The current methods that are used clinically to identify chromosomal changes rely on molecular analyses of tissue from tumor biopsies. While biopsy samples provide a wealth of information about the molecular abnormalities in tumors, they often require invasive procedures which may be prone to sampling error. The ability to detect chromosomal changes that cause cancer in peripheral blood samples may allow earlier and more accurate diagnosis.

In a recent study in Science Translational Medicine, researchers at Johns Hopkins University show that it is possible to get detailed information about the molecular characteristics of a tumor’s chromosomal DNA from peripheral blood samples. The authors exploit the fact that dead or dying tumor cells frequently dump their contents into the bloodstream. A major component of these intracellular contents is the chromosomal DNA that contains the deleterious alterations that drive tumor growth. The authors isolated this circulating cell-free DNA (CFDNA) from both cancer patients (colon and breast cancer, specifically) and healthy volunteers and used whole genome sequencing (WGS) to assess for chromosomal abnormalities. The authors saw chromosomal abnormalities such as, chromosomal copy number changes and genomic rearrangements, in the CFDNA specifically from cancer patients and not from healthy volunteers. Interestingly, the chromosomal abnormalities that the authors detected corresponded to common mutations seen in these types of cancers. Previous studies have shown that it is possible to observe oncogenic changes in chromosomal DNA from the peripheral blood of cancer patients. However, these methods required prior knowledge of what chromosomal changes might be present—that is, the investigators could only find the specific mutations that they were looking for. The current study demonstrates that it is possible to measure chromosomal changes in tumors using blood samples without advanced knowledge of the mutations that caused the cancer. This opens up the possibility of being able to fully characterize the unique molecular defects in a patient’s tumor and allowing for individual tailoring of therapy. The authors also compare chromosome arm alterations from colorectal cancer cell lines and xenografts to the blood from the colon cancer patients.  They found that both showed ≥5 chromosomal alterations compared to healthy volunteers (less than 2.4 alterations).

Although this technology is promising, substantial obstacles must be overcome before WGS on peripheral blood becomes a widely-used clinical technique. First, the sensitivity of WGS depends on the amount of mutant CFDNA obtained for sequencing. Chromosomal abnormalities that are present in small amounts may be missed (i.e. small tumors). Of note, the patients analyzed in this study all had advanced disease. Further investigations into whether this technique can identify chromosomal abnormalities during early stage disease or in instances of diagnostic uncertainty are warranted. Second, it is not clear to what extent the chromosomal abnormalities detected in peripheral blood represent the molecular defects in actual tumors. Are there additional mutations contained in tumor tissues that do not show up in the blood? Further study is necessary comparing peripheral blood sequencing analyses to those performed on biopsy samples obtained from the same patient. This will be especially important for applications which seek to use the information garnered from WGS of peripheral blood to guide treatment decisions. Finally, the sequencing techniques used in this study are expensive and preclude routine clinical use at this time. Although, based on the current trend of rapidly deceasing costs associated with next-generation DNA sequencing technologies it is plausible that clinical testing of this sort will become affordable in the near future.