Overcoming treatment resistance in cancer: Current understanding and tactics

ARTICLE IN PRESS Cancer Letters ■■ (2016) ■■–■■

Contents lists available at ScienceDirect

Cancer Letters j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / c a n l e t

Mini-review

Overcoming treatment resistance in cancer: Current understanding and tactics Guang Wu a, George Wilson a, Jacob George a, Christopher Liddle a, Lionel Hebbard a,b,*, Liang Qiao a,** a b

Storr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW 2145, Australia Department of Molecular and Cell Biology, James Cook University, Townsville, QLD, Australia

A R T I C L E

I N F O

Keywords: Treatment resistance Cancer stem cells Cancer progression Mutation EMT EMT transition

A B S T R A C T

Chemotherapy is the standard treatment for many, if not all, metastatic cancers. While chemotherapy is often capable of inducing cell death in tumors leading to shrinkage of the tumor bulk, many patients suffer from recurrence and ultimately death due to resistance. During the last decade, treatment resistance has attracted great attention followed by some seminal discoveries, including sequential mutations, cancer stem cells, and bidirectional inter-conversion of stem and non-stem cancer cell populations. Nevertheless, the successful treatment of cancer will require a considerable refinement of our knowledge concerning treatment resistance. In doing so, we expect that a more informed and refined approach to treat cancer will be developed and this may improve prognosis of cancer patients. In this review, we will discuss the current knowledge concerning the failure of cancer treatments and the potential approaches to overcome therapeutic resistance. © 2016 Published by Elsevier Ireland Ltd.

Introduction Due to advances in oncology research our understanding of cancer has changed dramatically over last decade. The tumor itself is not only recognized as an aggregation of excessive, uncontrolled abnormal cells but is also characterized by dynamic changes in the genome

Abbreviations: ABCB1, ATP-binding cassette, Sub-family B, Member 1; ABCG2, ATP-binding cassette, Sub-family G, Member 2; AKT, V-Akt murine thymoma viral oncogene; APC, adenomatous polyposis coli; AQ4N, di-N-oxide aliphatic amino anthracenedione; BRAF, b-Raf proto-oncogene; BRCA, breast cancer gene; CDK2N, cyclin-dependent kinase 2; CSCs, cancer stem cells; EGFR, epidermal growth factor receptor; EMT, epithelial to mesenchymal transition; ER, estrogen receptors; FBXW7, f-box and WD repeat domain containing 7; HCC, hepatocellular carcinoma; HDAC, histone deacetylase; HIF, hypoxia inducible factor; KRAS, the human homolog of the Kirsten rat sarcoma-2 virus oncogene; MAPK, mitogen-activated protein kinase; MEK, mitogen-activated protein kinase; MMPs, matrix metalloproteinase; NF, nuclear factor; NRAS, neuroblastome RAS viral oncogene:; NSCLC, non-small cell lung carcinoma; PIK3CA, phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha; PTEN, phosphatase and tensin homolog; siRNA, small interfering RNA; SAHA, suberoylanilide hydroxamic acid; SMAD4, SMAD family member 4; SP, side population; TERT, telomerase reverse transcriptase; TGF-β1, transforming growth factor, beta 1; TIMP2, tissue inhibitor of matrix metalloproteinase-2; TMZ, Temozolomide; TP53, tumor protein 53; ZEB1, zinc finger E-box binding homebox 1. * Corresponding author. Tel.: +617 4781 5684. E-mail address: [email protected] (L. Hebbard). ** Corresponding author. Tel.: +612 86273534; fax: +612 86273099. E-mail address: [email protected] (L. Qiao).

leading to the initiation and progression of cancer [1]. In addition, the long-held hypothesis, in which every single cell has the same capacity in terms of invading and colonizing other parts of the body, has been challenged by heterogeneous cancer stem cells (CSCs) models [2]. Moreover, a new model of “plastic cancer stem cells”, in which non-CSCs can be trans-differentiated into CSCs in response to certain stimuli, has further broadened our view of cancer [3]. These discoveries have provoked a rapid development of treatment options for cancer therapy, including surgery, radiation, cytotoxic chemotherapy and more selective treatments derived from the increased understanding of biological features of distinct tumor subtypes [4]. Chemotherapy has long been the approach of choice for the treatment of tumors that are not suitable for radical resection because of advanced stage. However, these tumors possess the uncanny ability to resist the effects of cancer chemotherapeutic agents, and after an initial robust response, the tumors reappear. In this light near 90% of the drug failures in metastatic cancers can be attributed to resistance [5]. Resistance to chemotherapeutics can be divided into two categories: intrinsic and acquired [6]. The former indicates the presence of pre-existing mediators leading to inefficacy towards a given treatment, while the later represents the emerging resistance against an initially effective therapeutic regime. In as much, numerous studies focusing on treatment resistance are being published. Therefore, we will now review the current understanding of cancer treatment failure and consider approaches that can better treat these malignancies.

http://dx.doi.org/10.1016/j.canlet.2016.04.018 0304-3835/© 2016 Published by Elsevier Ireland Ltd.

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A. Breakthrough phase

B. Expansion phase

C. Invasive phase

Fig. 1. Sequential mutations and treatment resistance. A. At breakthrough phase, one cell starts proliferating abnormally upon acquiring the mutation. B. Cells with the first mutation attain the second one in the expansion phase leading to fast expansion of malignant cells. C. In the invasive phase, cells develop another mutation, enabling them to metastasize into surrounding tissues.

Sequential mutations and treatment resistance One model to explain the emergence of cancer drug resistance is based on the accumulation of mutations throughout the progression of a tumor. The evolution of a tumor can be artificially divided into three phases: breakthrough phase, expansion phase and invasive phase [1] [Fig. 1]. In the breakthrough phase, a tumor cell begins to grow abnormally due to the acquisition of specific gene mutations. These mutated cells then attain a second mutation in the expansion phase, where they can then thrive in an ill-disposed microenvironment, such as low oxygen tension, nutrient-deprived or over-crowding. Following the invasive phase further mutations are acquired to promote tumor cell invasion and metastasis, the hallmarks of end stage malignancy. Evidence of the accumulated mutation model in human tumors has been published and some of these we will now discuss. The dominant mutation for the breakthrough phase of pancreatic ductal adenocarcinoma is KRAS (the human homolog of the Kirsten rat sarcoma-2 virus oncogene) followed by CDKN2A (cyclin-dependent kinase 2) mutations, occurring at a rate greater than 50%, which promotes the expansion of transformed cells. For the invasive phase, SMAD4 (SMAD family member 4) and TP53 (tumor protein 53) mutations have been identified [7,8]. Due to the distinct driver mutations at different stages of pancreatic cancer, it is not surprising that current therapeutic strategies, using a non-specific approach to patient recruitment, have kept the median survival of pancreatic cancer patients at 6 months and a 5-year survival rate of below 5% [9]. One way to improve therapeutic efficacy is obviously to develop personalized treatment based on disease genotype. For instance, gemcitabine-based chemotherapy is the first-line treatment option for advanced pancreatic adenocarcinoma. However, patients with KRAS mutations (71 out of 136 patients) showed worse response than those with wild-type KRAS [10]. In order to overcome gemcitabine resistance in advanced pancreatic carcinoma, Maria et al [11] generated personalized xenograft mice model using gemcitabine-resistant human pancreatic tumors and demonstrated that additional administration of mitomycin C (MMC), a DNA damaging agent resulting in long-lasting (>36 months) tumor response. Mechanistic studies revealed that mutation of PALB2 (Parter and Localizer of BRCA2) is a key determinant of response to MMC. In addition, a recent sequencing study of pancreatic cancer has shown structural variation (the variation in structure of the tumor cell chromosome) as an important mutational mechanism in pancreatic carcinogenesis. This finding led the authors to further subdivide pancreatic cancer into four groups based on the frequency and distribution of structural rearrangements: (i) stable, (ii) locally rearranged, (iii) scattered, and (iv) unstable subtype. Clinical and animal studies have revealed that unstable genome and a high BRCA mutational signature burden were associated with poorer response to platinum-based therapy [8]. Although these studies have potential implications for selecting the appropriate therapeutic options

for pancreatic cancer, the putative biomarkers defined by these data need further testing in a large clinical trials, In colon cancer, APC (adenomatous polyposis coli) mutations initiate the neoplastic process, and the expansion phase is driven by KRAS mutations, leading to the progression from colorectal adenoma to carcinoma. Further mutations of TP53, SMAD4, PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha) or FBXW7 (F-box and WD repeat domain containing 7) can promote invasion into the surrounding tissues. Independent studies have also shown the importance of KRAS mutations as they were detected in over one-third of the colorectal cancer (CRC) tissues [12]. Cetuximab, a monoclonal antibody that binds the extracellular domain of epidermal growth factor receptor (EGFR), has been shown to be effective against a subset of KRAS wild-type metastatic CRC cases. However, a majority of patients develop resistance after an initial response and further analysis of the resistant tumors confirmed the acquisition of secondary KRAS mutations in 60% of them, indicating that KRAS mutations are frequent drivers of acquired resistance to EGFR inhibition [13]. Melanomas often arise from distinctive precursor lesions such as melanocytic nevi, intermediate lesions, or melanoma in situ. By DNA sequencing and functional experiments, it has been found that precursor lesions are initiated by mutations of genes capable of activating the mitogen-activated protein kinase (MAPK) pathway [14]. However, only benign lesions harbor BRAF (B-Raf proto-oncogene) V600E mutations and intermediate lesions are enriched for mutations of NRAS (neuroblastoma RAS viral oncogene) and additional driver genes, such as BRAF V600K or BRAF K601E. TERT (telomerase reverse transcriptase) promoter mutations were found in 77% of the areas of intermediate lesions and melanomas in situ. In contrast, biallelic inactivation of CDKN2A is exclusively associated with invasive melanomas, while PTEN (phosphatase and tensin homolog) and TP53 mutations were found mainly in advanced primary melanomas. These studies might help explain why chemotherapy may work at the early phase of treatment but not as effective as a targeted therapy in melanoma [15]. Dacarbazine, the most effective systemic chemotherapeutic agent approved by FDA for advanced melanoma, only has a response rate of 10–20% with complete remission in only 5% of patients [16]. Increased expression of BCL-2 in tumor tissues and associated resistance to apoptosis is one of the mechanisms responsible for treatment resistance in patients with KRAS mutations [17,18]. Studies from multiple centers have shown that combination of oblimersen (a BCL-2 antisense oligonucleotide) with dacarbazine significantly improved clinical outcomes of patients with advanced melanoma [19]. This funding prompted further clinical trials on whether the addition of oblimersen should be suggested as the first line treatment for patients with melanoma harboring NRAS mutation. As BRAF mutation exist in the vast majority of melanoma cases, FDA has approved two BRAF inhibitors vemurafenib and dabrafenib for the treatment of unresectable or metastatic melanoma [20]. However, resistance to these agents

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develops in majority of patients, resulting in a median progressionfree survival of 6 to 7 months [21]. One of the most important mechanisms is reactivation of the MAPK pathway, which may stimulate the growth of the tumors harboring RAS mutation [22,23]. In 2014, FDA approved trametinib, a MEK inhibitor, in combination with dabrafenib to treat advanced melanoma with BRAF mutation, and this treatment resulted in greater efficacy than BRAF inhibitor alone [24,25]. These results also point to the value of repeat tumor biopsies throughout the disease course to determine the best treatment regimen. However, invasive biopsies could have a detrimental impact on tumor progression as the wound-induced infiltration of inflammatory cells may promote proliferation of transformed cells [26]. Recent advances in blood-based liquid biopsy have established a new platform for tracking accumulated mutations in cancer. For example, molecular analysis of circulating tumor cells from the blood of patients with lung cancer has provided a practically useful tool to monitor changes in epithelial tumor genotypes during the course of treatment [27]. In breast cancer patients with multiple or inaccessible metastases, direct sequencing of plasma DNA could be used to mirror the tumor genotype [28,29]. Analysis of circulating DNA from metastatic CRC has also been demonstrated being a viable noninvasive approach for the evaluation of tumor genotype. This approach enables the identification of clinically relevant mutations including the mutations that were undetected in archived tissues [30]. Furthermore, mRNA sequencing of tumor-educated blood platelets has identified genetic alterations in tumors of lung, colon, brain, liver and pancreas [31]. Other blood tests such as neutrophil-to-lymphocyte ratio has also been shown to predict patient outcome and can be used to measure response to treatment, where patients with a high neutrophil-to-lymphocyte ratio are unlikely responsive to treatment and therefore show a poor

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prognosis [32]. Taken together, these reports suggest that in the era of precision medicine, the continual assessment of cancer evolution over the course of treatment by minimal invasive tests will enable the identification of optimal strategies to overcome treatment resistance. EMT and treatment resistance EMT (epithelial to mesenchymal transition) is an evolutionarily conserved developmental process that was first described in the primitive streak of chick embryos [33]. EMT is a transdifferentiation program that is required for tissue morphogenesis during embryonic development, and its process can be regulated by an array of cytokines and growth factors, such as transforming growth factor whose activities are often deregulated during carcinogenesis and tumor progression. Accumulating data have shown that the induction of EMT in cancer cells can lead to the acquisition of invasive and metastatic properties [Fig. 2]. During the acquisition of EMT, cells lose epithelial cell-cell junctions, undergo cytoskeleton reorganization and decrease the expression of proteins that would normally promote cell–cell contact such as E-cadherin and β-catenin. Meanwhile, cells that underwent EMT usually exhibit enhanced expression of mesenchymal markers such as vimentin, fibronectin, α-smooth muscle actin and N-cadherin, as well as increased activity of matrix metalloproteinase (MMPs) as indicated by increased expression of MMP-2, MMP-3 and MMP-9 that is associated with an invasive phenotype. Recent studies have also indicated that EMT of cancer cells contributes to treatment resistance [34]. By example, tamoxifen, an estrogen receptor (ER) inhibitor, has been shown to be ineffective in certain breast cancers. Tamoxifen represses ER activity by competitively inhibiting the interaction of estrogen with the ER, and is commonly used as a first-line treatment

A. Epithelial

B. Mesenchymal

Sensitive to treatment Differentiated

Resistant to treatment Undifferentiated

TGFβ

TNFα

EGF Hypoxia

SMAD

NF-κB

SNAIL SLUG

STAT3

ZEB

Notch

E-cadherin cytokeratins

WNT

HIF

Vimentin N-cadherin

Fig. 2. EMT and treatment resistance. A. Extracellular stimuli such as TGF-β, TNF-α, EGF and hypoxic condition activate intracellular signaling SMAD, NF-κB and STAT3, leading to EMT mediated by EMT related transcription factor, SNAIL, SLUG, TWIST and ZEB. B. Malignant cells underwent EMT lose the expression of E-cadherin and cytokeratin accompanied by gain of Vimentin and N-cadherin. Mesenchymal cells with stem cell feature express different CSC surface markers and higher level of ABC transporters. In addition, Notch signaling and WNT pathway are activated in this cell population to maintain the CSC phonotype.

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for ER+ breast cancer patients [35]. However, up to 50% of patients with metastatic breast cancer do not respond to tamoxifen. In addition, many initial responders experience relapse [36]. By comparing the tamoxifen-sensitive and resistant breast cancer cells, Aoife Ward et al [37] found that the tamoxifen resistant cancer cells underwent EMT leading to a more invasive phenotype. Furthermore, follow-up studies have shown that these resistant cells can be resensitized to tamoxifen through inhibition of EMT. Mechanistically, it has been observed that tamoxifen resistant breast cancer cell with mesenchymal features show increased expression of β1-integrin, which has been suggested to promote the interaction of the cancer cells with cancer-associated fibroblasts to protect tumor cells from chemotherapy-induced killing [38]. Studies in lung cancer have also illustrated that EMT is involved in the development of resistance to the EGFR inhibitors, such as erlotinib and gefinitib. These drugs have been shown to be effective in a subpopulation of non-small cell lung carcinoma (NSCLC) patients harboring mutations in the EGFR tyrosine kinase domain. However, the patients initially sensitive to these EGFR inhibitors become resistant after a median time of 12 months [39,40]. Epithelial tumor cells have been shown to be more sensitive to EGFR inhibitors than tumor cells with mesenchymal characteristics after EMT transition [41,42]. Other studies have demonstrated that cancer cells from NSCLC, head and neck cancer and bladder cancer could switch to an AKT-activated EGFR-independent state after EMT, and these cells exhibited increased proliferative ability in the presence of an EGFR inhibitor [43]. Furthermore, emerging evidence has shown that EMT can promote a cancer stem cell phenotype which is known to be linked to treatment resistance. A seminal paper by Mani et al [44] demonstrated that a breast cancer stem cell population with a CD44low/ CD24high profile could be induced from normal mammary epithelial cells on exposure to TGF-β1 (transforming growth factor, beta 1) or through the overexpression of EMT-inducing transcription factors SNAIL or TWIST. This CD44low/CD24high subpopulation of breast cancer cells is resistant to chemotherapy such as lapatinib, a dual tyrosine kinase inhibitor [45]. Apart from breast cancer, the EMTactivator ZEB1 (zinc finger E-box binding homebox 1) can induce EMT in pancreatic cancer and colon cancer leading to the enrichment of cancer stem cells with resistance to gemcitabine, a chemotherapeutic nucleoside analog that has limited success in treating pancreatic cancer. The critical role of ZEB1 in the mediation of EMT and treatment resistance was supported by the findings that ZEB1-knockdown pancreatic cancer cells became more sensitive to gemcitabine [46]. Nevertheless, the prevailing hypothesis that EMT is a key player in the metastatic process of epithelial cancers has been challenged by two recent publications [47,48]. In these studies, the inhibition of EMT through the deletion of EMT related transcription factors did not impair metastasis, but EMT inhibition was confirmed to improve chemoresistance. In this light, due to the importance of EMT in the development of cancer treatment resistance, it is not surprising that targeting EMT could be a promising option to overcome treatment resistance. Current strategies targeting EMT related treatment resistance can be classified into two groups: (i) targeting EMT induction, and (ii) inhibiting cells with mesenchymal features. Many signals, including oxygen tension, cytokines and growth factors, in the tumor microenvironment that can induce EMT in cancer [49,50]. To target an individual cell surface receptor, which is the recipient of these extracellular signals, is a potential strategy to inhibit EMT in cancer cells. By example, AG1478, an EGF receptor kinase inhibitor, reverses EGF induced EMT and treatment resistance in breast cancer [51]. In addition, TGF-β induced EMT in pancreatic cancer can be limited by using the TGF-β receptor kinase inhibitor SB431542 [52]. Furthermore, nuclear factor

(NF)-κB induced EMT in prostate cancer can be reversed by the application of NPI-0052, a proteasome inhibitor targeting NF-κB [53]. There are additional signaling pathways such as Notch and WNT that are also capable of inducing EMT and these will be discussed in the following chapter as they are more important in maintaining cancer cells in a less differentiated state. As multiple functionally redundant signaling capable of inducing EMT is present in tumor microenvironment, a possible, better way to reverse EMT is to target an additional intracellular signal transduction pathway. By example, the signal transducer and activator of transcription 3 (STAT3) has been shown to be an important mediator of interleukin 6 (IL-6) and EGF induced EMT in head and neck, pancreas and colon cancers [54]. Although transcription factors are known to be difficult to target, several STAT3 inhibitors have been developed that can reverse EMT and render the cancer cells more sensitive to other treatments. These inhibitors include Stattic, S3I2001, NSC74859, and the STAT3 decoy oligonucleotide, which is currently undertaking clinical trials [55]. In addition, metformin, a complex I inhibitor widely used as hypoglycemic drug in type 2 diabetes, has been shown to inhibit STAT3 and limit EMT in breast cancers and lung cancer [56]. Apart from targeting STAT3, other inhibitors targeting transcription factors have been utilized. The SNAIL inhibitor NPI-0052 has been shown to prevent EMT in prostate cancer [53]. siRNA (small interfering RNA) against SLUG [57,58] and nanoparticle-mediated inhibition of TWIST [59] have been shown to inhibit EMT induction and promote treatment sensitivity. ZEB1 can induce EMT in pancreatic cancer leading to resistance against gemcitabine. Mocetionstat, a class 1 HDAC (histone deacetylase) inhibitor, can interfere with ZEB1 function and induce sensitivity to chemotherapy [60]. As EMT is characterized by the acquisition of an array of mesenchymal cell markers, including Vimentin, N-cadherin, and Fibronectin [61–63], targeting these mesenchymal proteins may hold promise in overcoming treatment resistance. By example, an antitumor agent withaferin-A, a bioactive compound extracted from Withania somnifera, has been shown to degrade vimentin [64]. Similarly, a specific antibody against N-cadherin has been shown to inhibit EMT and prevent castration resistance in prostate cancer [65]. As discussed above, EMT plays a major role in conferring treatment resistance in many cancers. Consequently, an array of pharmacological approaches to target EMT in order to prevent or overcome treatment resistance has been developed. As EMT may be regulated by multiple functionally redundant signaling that are transduced through cell surface receptors, targeting individual cell surface receptor in the tumor microenvironment may not be potent enough to overcome treatment resistance. This is because if the function of one receptor is blocked, the remaining EMT signaling can lead to a mesenchymal phenotype through the rewiring of signaling pathways, as has been shown in NSCLC [66]. Furthermore, it must be noted that EMT is not a prerequisite for treatment resistance of all cancers. A recent study has shown that the number of cancer cells that undergo EMT is very rare, suggesting that other mechanisms are involved in promoting treatment resistance [47,48].

Cancer stem cells and treatment resistance Cancer is a heterogeneous disease and there is increasing evidence that intratumoral heterogeneity contributes to therapy failure and disease progression [67,68]. Indeed, a tumor is a complex ecosystem that contains tumor cells and various infiltrating endothelial, hematopoietic, immune and stromal cell types that can influence tumor growth and progression [2]. Within the tumor cells, heterogeneity exists as cancer cells bearing stem cell features have been successfully isolated from multiple human cancers, including lung, pancreatic and liver cancers [69,70]]. Moreover, recent work in

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different cancers has suggested that the CSC population is a source of treatment failure. The mechanism of CSC related treatment resistance can be classified into three groups: (i) CSCs have a slow proliferation rate; (ii) they are capable of efflux chemotherapeutic drugs; (iii) CSCs are metabolically heterogeneous. CSCs are relatively quiescent and have a slow proliferation rate, which protect them against chemotherapeutic agents. In contrast, actively dividing cancer cells are more vulnerable to chemotherapy [71]. CSCs isolated from melanomas by the marker H3K4 demethylase JARID1B have been shown to have a doubling time of four weeks longer than the rapidly proliferating cancer cells whose doubling time is only 48 hours [72]. Breast CSCs are also quiescent when compared to non-CSCs, as evidenced by the retention of BrdU and the absence of expression of the proliferative marker Ki-67 [73]. CD24+ liver CSCs are enriched in residual cisplatin resistant tumors, but have a significantly lower proliferation rate compared to CD24- cells [74]. Likewise, temozolomide (TMZ) resistant glioblastoma are enriched for relatively quiescent CSCs, and have been shown to be responsible for sustaining long-term tumor growth [75]. Accumulating data has indicated that CSCs express high levels of the ATP-binding cassette transporters (ABC transporters), which can actively regulate the flux across the plasma membrane of multiple structurally and mechanistically unrelated chemotherapeutic drugs, thus protecting CSCs from cytotoxic agents [76]. The side population (SP) of CSCs is a subpopulation of cancer cells that are able to efflux antimitotic drugs. This subpopulation can be isolated by its capacity to efflux the fluorescent dye Hoechst 33342. By example, the side population from HCC (hepatocellular carcinoma) can be enriched for liver CSCs and the expression of ABCB1 (ATP-binding cassette, sub-family B, member 1) is unregulated in the SP cells [77]. Not only in SP cells, liver CSCs isolated through the expression of an exogenous human Oct-4 promoter are resistant to sorafenib and these Oct4+ cells show overexpression of some ABC transporters [78]. The SP of glioblastoma with higher expression of ABC transporters is also resistant to temozolomide, an alkylating agent that is used to treat glioblastoma. Loss of PTEN and activation of AKT (V-Akt Murine Thymoma Viral Oncogene) pathways are important genomic alterations associated with increased SP and treatment resistance. A SP with treatment resistance has also been found in lung cancer [79]. However, a recent study found that the SP of lung cancer cells with overexpression of ABCG2 (ATP-binding cassette, Sub-family G, Member 2) and ABCB1 is sensitive to an endogenous inhibitor of angiogenesis called tissue inhibitor of matrix metalloproteinase-2 (TIMP-2) [80]. In this regard, ABC transporter inhibitors, such as zofuquidar and tariquidar, have been developed and have shown great potency and specificity in cancer therapy [81,82]. Nevertheless, disappointing results from clinical trials suggest that other mechanisms are involved in chemo-resistance of CSCs. CSCs isolated from multiple solid tumors have been shown to reside in a relative hypoxic environment. Indeed, pancreatic CSCs isolated using the surface makers CD133 and CXCR4 are highly resistant to standard chemotherapy and home to the invasive front of pancreatic tumors [83]. In parallel, EpCAM positive liver CSCs have been found in the invasive front of cancer tissues and are resistant to sorafenib [84]. The low concentration of chemotherapeutic drugs at the invasive front of the tumor tissues could be due to the increased tumor-to-blood ratio. However, how CSCs manage to thrive in such an inhospitable environment is not clearly understood. It has been proposed that CSCs may prefer glycolysis over oxidative phosphorylation for energy supply during hypoxic conditions [85–88]. However, accumulating evidence suggests that CSCs are also heterogeneous populations [89], and another subpopulation of therapy-resistant CSCs with higher dependence on oxidative phosphorylation has been identified in several cancer types including

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melanoma [90], acute myeloid leukemia [91] and pancreatic cancer [92,93]. Given the metabolic heterogeneity of CSCs, it’s reasonable to hypothesize that in addition to Metformin being able to induce metabolic stress and apoptosis in glycolysis-dependent CSCs, targeting mitochondrial respiration (OXPHOS) could also be a potential approach to overcome treatment resistance of CSCs. In addition, to favor the expansion of CSCs, hypoxic condition also activates several signaling pathways that are closely linked to cell proliferation. In this regard, it has been shown that hypoxia can activate Notch signaling and EMT, favoring the expansion of CSCs [94]. This was further demonstrated in breast cancer in that the limited efficacy of antiangiogenic agents such as sunitinib and bevacizumab was likely due to the intratumoral hypoxia that is known to promote the expansion and self-renewal ability of CSCs [95]. These studies provided a potential rationale of targeting the inherited metabolic characteristic of CSCs and hypoxic microenvironment as an approach to overcome treatment resistance. In this aspect, targeting glycolysis has been shown to activate AMPK and inhibit mTOR in beast CSCs, and may therefore hold promise for the treatment of breast cancer [96]. TH-302, a 2-nitroimidazole triggered hypoxia-activated prodrug of the cytotoxin bromoisophosphoramide mustard, has also been shown to reduce the number of breast CSCs in hypoxic regions [97]. Another drug, AQ4N (the di-N-oxide aliphatic amino anthracenedione) has been shown to specifically target CSCs at the hypoxic invasive front of pancreatic cancer [98]. As increased expression of HIF (hypoxia inducible factor) including HIF-1α and HIF-2α has been observed as a principal mediator of hypoxia-induced metabolic change in CSCs, targeting HIF has been a focus to target the hypoxic tumor microenvironment. However, the efficacy of HIF inhibitors has been disappointing [99,100]. Notch signaling is a highly conserved pathway that regulates a range of cellular functions including proliferation, apoptosis, cell fate and differentiation [101]. Notch signaling has been shown to induce EMT leading to treatment resistance in multiple solid tumors. Aberrant Notch2 signaling has been identified as an inducer of EMT in treatment-resistant pancreatic cancer cells [49,102]. Constitutive activation of Notch1 signaling in lung cancer can promote EMT and contribute to gefitinib resistance [103]. Notch signaling can regulate CSC activity. For example, hyper-activated Notch2 in liver CSCs and overexpression of Notch1 in CSCs from esophageal adenocarcinoma were found to drive the stemness features and self-renewal ability of these cells [104,105]. Currently, targeting Notch signaling is achieved by γ-secretase inhibitors in most studies. However, γ-secretase inhibitors are a group of pan Notch inhibitors and nonselective “shut down” of Notch signaling is detrimental to many organs as Notch signaling is indispensable for normal tissue homeostasis [106]. Likewise, WNT, TGF-β, Hedgehog and Hippo signaling pathways have also been shown to be essential for the maintenance of both normal adult stem cells and CSCs [107–111]; non-specific targeting of these signaling pathways as an treatment approach for cancers may not be practically feasible. Hence, intensive studies and particularly, exploration of highly specific CSCtargeting agents, are clearly warranted. The targeted and induced differentiation of CSCs is another approach to treat drug resistance in cancer. Targeted therapy would presumably act by inducing CSC differentiation, giving rise to differentiated non-CSCs, which are more susceptible to chemotherapy. In a recent study, MiR-148a was identified as an inducer of hepatocytic differentiation, and the expression of MiR-148a is downregulated in HCC [112]. Induction of CSC differentiation using a MiR148a mimetic was able to inhibit tumor growth and increase the sensitivity to chemotherapy [112]. HDAC-dependent histone deacetylation is upregulated in some cancers and is indispensible in repressing some epithelial genes such as E-cadherin. HDAC inhibitors, such as η-butyrate and suberoylanilide hydroxamic acid

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(SAHA), have been shown to induce the differentiation of many CSC types derived from the breast, lung, prostate and liver cancers [113]. A high-throughput chemical compound screening has revealed that salinomycin, an antibiotic potassium ionophore, could be an inducer of CSC differentiation in breast cancer, head and neck squamous cancer, colon cancer and lung adenocarcinoma [114]. Despite these promising studies, differentiation inducers may not be sufficient to overcome treatment resistance, as CSCs are now believed to exist in a dynamic state in that non-CSCs can dedifferentiate into CSCs under certain conditions. Therefore, any therapeutic approaches aiming at eliminating CSCs should consider multiple approaches to illicit a durable clinical response [2]. Summary and future directions Resistance to chemotherapy and/or targeted therapy represents a formidable roadblock to long-lasting clinical response. In this review, we discussed the most updated mechanisms relating to chemotherapy failure. Sequential mutations during the processing of tumors are apparently responsible for treatment failure. Thus, identifying the mutation stage of each cancer patient before and during treatment would lead to a better outcome. However, this approach is labor and time demanding. Genetic data and clinical experience suggest that the progeny of a cell that initiates the breakthrough phase can take up to three decades to progress through the other phases and acquire the necessary genetic alterations to acquire metastatic properties [115]. Thus, there is a large window of opportunity to utilize specific and sensitive early detection methods to improve prognosis of cancer patients. As EMT occurs in an array of different tumors and is one of the major contributors to cancer treatment resistance, future drug discovery efforts aiming at increasing patient survival should undoubtedly consider targeting EMT as a better therapeutic strategy. CSCs are another mechanism contributing to treatment resistance. Considerable efforts have been made in finding the most reliable approaches targeting CSCs, but the ability of non-CSCs de-differentiating into CSCs under certain stimuli hindered the translation of CSCs-targeted therapy from bench to bed. What makes this field even complex is that pre-exist drugresistant cancer cells can benefit from therapeutic targeting of surrounding drug-sensitive cells [116]. Thus, our understanding of treatment resistance in cancer is far from completed. Only a combination of drugs that can simultaneously eradicate CSCs and kill the differentiated tumor cells would lead to a better outcome for cancer patients; all these are predicated on extensive mechanistic studies. Funding sources The Robert W. Storr Bequest to the Sydney Medical Foundation, University of Sydney, National Health and Medical Research Council of Australia (NHMRC) Program grant APP1053206. NHMRC project grants (APP1047417, LQ; APP1087297, JG and LH); and the Cancer Council NSW Project Grants (APP1070076, LQ; APP1069733, LH). Conflict of interest The authors have no conflicts to declare. References [1] B. Vogelstein, K.W. Kinzler, The path to cancer – three strikes and you’re out, N. Engl. J. Med. 373 (2015) 1895–1898. [2] A. Kreso, J.E. Dick, Evolution of the cancer stem cell model, Cell Stem Cell 14 (2014) 275–291. [3] K. Polyak, R.A. Weinberg, Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits, Nat. Rev. Cancer 9 (2009) 265–273.

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Please cite this article in press as: Guang Wu, et al., Overcoming treatment resistance in cancer: Current understanding and tactics, Cancer Letters (2016), doi: 10.1016/ j.canlet.2016.04.018