ONCAlert | Upfront Therapy for mRCC

Overcoming Resistance to Targeted Cancer Therapy

Jane de Lartigue, PhD
Published Online: Sep 11,2013
Charles Sawyer, MD

Charles Sawyer, MD

Over the past two decades, there has been a shift away from indiscriminate cell-killing by anticancer agents toward the development of more specific drugs that target key aspects of cancer cell biology— an approach that promised to offer a “magic bullet” cure for cancer. However, although there have been some astounding clinical successes, patients almost invariably, and often quickly, relapse.

As highlighted at the 2013 American Society of Clinical Oncology (ASCO) Annual Meeting in a plenary lecture by Charles Sawyer, MD, president of the American Association for Cancer Research (AACR), cancer is an adaptable enemy, and a significant challenge to the development of successful targeted therapies is the “universal, but not futile” problem of resistance.

Universal Problem With Diverse Mechanisms

Unlike traditional anticancer therapies (eg, chemotherapy) that indiscriminately kill rapidly dividing cells, targeted therapies are designed to affect cancer cell-specific processes. Yet a common feature of both traditional and targeted therapies is that a subset of patients fail to respond, and even those who initially respond almost invariably experience relapse, in large part due to the development of drug resistance.1,2 Given that significant responses are often observed with targeted therapy prior to the development of resistance, clinicians and basic researchers alike are trying to gain a better understanding of the mechanisms through which cancer cells lose their ability to respond to these drugs.

Resistance can be intrinsic to a cancer cell (already in place prior to treatment) or acquired after prolonged exposure to a drug. A multitude of resistance mechanisms have been uncovered, many specific to the particular drug being used. They can vary widely, even among patients receiving the same drug for the same type of cancer, due to the heterogeneous nature of tumors as a whole.3 However, they can very broadly be divided into two groups: genetic and nongenetic.4

Genetic Mechanisms

The inherent mutability of cancer cells (referred to as genomic instability) forms the foundation for a significant amount of resistance to therapy, as it means that cancer cells readily develop secondary mutations in their genome that can confer resistance. Cancer cells are thought to evolve, at least in part, by a process called clonal expansion; they spontaneously develop mutations as a result of their genomic instability and, when a mutation confers a growth advantage (such as drug resistance), cells with that mutation are able to reproduce and generate a population of clones with the same mutation. Regardless of whether a resistance- driving trait is present prior to or acquired during treatment, exposure to the drug provides the selective pressure to drive the development of resistance.5

Genetic alterations (see Table for common types) drive drug resistance in three main ways:
  • Secondary alterations to the drug target: The drug target can be altered, rendering the drug less effective or reducing its binding ability
  • Activation or loss of downstream signaling components: Significant amounts of cross-talk between proteins, negative feedback loops, and other phenomena that regulate signaling on multiple different levels create complex signaling “networks.” The effects of a drug can be bypassed by activation of downstream components of the same signaling pathway or via loss of negative feedback loops.
  • Activation of alternate signaling pathways: The inhibitory effects of a targeted drug on a specific cell signaling pathway can be bypassed if alternate signaling pathways with shared downstream effectors are activated.3, 6-9

Nongenetic Mechanisms

There also are numerous nongenetic mechanisms of resistance (Table). Among the most significant are the contribution of the tumor microenvironment and the role of cancer stem cells. In recent years it has become clear that the tumor interacts with the noncancerous tissue surrounding it (the tumor “microenvironment”) and creates a supportive stroma for itself that further promotes tumor progression and drug resistance. The tumor microenvironment may create a pro-survival niche for the tumor in the presence of anticancer agents by, for example, repopulating it with cells that are intrinsically drug-resistant, and supplying the tumor with a host of signaling molecules that promote survival.3,10

An alternative to the clonal expansion theory of cancer cell evolution is the cancer stem cell (CSC) hypothesis, which postulates that CSCs are the progenitor cells from which all other cancer cells arise. CSCs have the capacity for self-renewal and to differentiate into any kind of mature cell. These properties and others are believed to render them resistant to cancer therapy, and, in fact, some researchers believe that they may be the most important component—or even the origin of drug resistance.3,10

Fighting Back

Researchers are working to unveil the mechanisms of drug resistance via two basic mechanisms: cell line modeling (using preclinical cell lines to compare pretreatment drug-sensitive cells to posttreatment drug-resistant ones) and analysis of clinical specimens (comparing progression in tumor biopsies collected pre- and posttreatment). This knowledge is then applied to carefully designed clinical trials to demonstrate whether strategies for preventing these mechanisms of resistance translate into improved outcomes for patients.11

TABLE. Genetic Mechanisms of Resistance1-4

Genetic Alteration Description Example
Point mutations Most common mechanism of resistance to tyrosine kinase inhibitors; commonly reduce the affinity of the drug for its target Approximately 50% of patients treated with EGFR inhibitors erlotinib and gefitinib develop a point mutation in their kinase domain (T790M) that reduces the binding affinity of these drugs.5,6
Gene amplification Further amplification of already amplified target gene or amplification of other genes downstream of the target or in alternate signaling pathways Patients with non-small cell lung carcinoma who have developed resistance to the EGFR inhibitor gefitinib frequently display MET gene amplification.7
Deletions Loss of proteins involved in negative feedback mechanisms, which regulate alternate or downstream signaling pathways The phosphatase PTEN is lost in ~40% of breast cancers, and these tumors respond poorly to HER2- targeted agents. PTEN is a negative regulator of PI3K, which acts downstream of HER2.8
Altered protein expression Primary mechanism of resistance to monoclonal antibody therapy, which commonly targets cell surface receptors that are overexpressed in cancer; overexpression of alternative receptors or expression of receptor variants Trastuzumab resistance is commonly mediated by overexpression of the MET or IGF-1 receptors.9 A common mechanism of resistance in head and neck squamous cell carcinoma is the expression of an EGFR variant, EGFRvIII, which lacks a ligand-binding domain.10

Nongenetic Mechanisms of Resistance1,11

Mechanism Description Example
Epigenetic regulation Regulation of gene expression that does not involve changes to the DNA sequence; includes DNA methylation and histone acetylation and microRNA expression microRNAs regulate gene expression by binding to mRNA sequences. Evidence shows that certain microRNAs correlate with drug sensitivity.12
Tumor microenvironment Adaptations to the stroma surrounding tumor, which allow circumvention of drug effects Fibroblasts emerging as key players in promoting tumor progression and drug resistance, while mesenchymal cells are intrinsically drug-resistant. These cells may be selected for when the tumor cell population is eradicated following treatment.2
Cancer stem cells Cells from which a tumor arises; thought to be resistant to drug therapy and able to repopulate a tumor after treatmen Stem cell markers have been observed on subpopulations of cells that survive drug treatment.1
Alternative RNA splicing Most genes undergo splicing, whereby several different, functionally distinct forms of the same protein can be generated from a single gene; cancer-associated misregulation of splicing could generate protein isoforms that drive resistance Alternative splicing of the BCR-ABL gene has been linked to resistance to the EGFR inhibitor imatinib in patients with CML.13
Metabolic changes Rewiring of cellular metabolism to bypass growth factor signaling Lapatinib-resistant breast cancer cells have altered metabolism--more sensitive to glucose deprivation and have enhanced rates of glucose processing.14
Changes in the active concentration of the drug Often referred to as multidrug resistance since it does not discriminate based on a drug’s mechanism of action; cancer cells develop mechanisms to prevent drugs from entering, to actively pump them out of cells once they have entered, or to enzymatically inactivate the drug Imatinib-resistant cell lines overexpress the P-glycoprotein pump (also known as multidrug resistance protein 1), which transports a variety of molecules across intracellular membranes.15


Unlike resistance to traditional anticancer agents, the mechanisms of resistance to targeted therapies observed in vitro are generally found to correspond to those observed in vivo, which has allowed researchers to study the mechanisms closely and to begin to develop newer agents to “outsmart” cancer.12 Among the first agents developed were those designed to address secondary mutations in receptor tyrosine kinase targets that affect the binding of small-molecule inhibitors. For example, nilotinib (Tasigna) was approved by the FDA in 2007 for the treatment of imatinib-resistant patients with chronic myelogenous leukemia; it is designed to bind alternate conformations of the breakpoint cluster region; abelson murine leukemia viral oncogene homolog 1 (BCR-ABL) fusion protein that are resistant to imatinib.13 Despite initial success, patients often develop resistance to these new agents.9

Combination Therapy

Combination therapy is now widely seen as a potential strategy for overcoming resistance more permanently. As such, a significant amount of research is currently focused on identifying and testing rational combinations of agents. A variety of different strategies are being employed including combinations of the following9,11:
  • The same type of agent (eg, monoclonal antibody mixtures, bispecific and trifunctional antibodies with multiple targets, and multitargeted tyrosine kinase inhibitors [TKIs])
  • Different types of agents (eg, the monoclonal antibody trastuzumab and the TKI lapatinib in breast cancer)
  • Two agents against the same target (eg, trastuzumab and pertuzumab against HER2 in breast cancer)
  • Agents targeting parallel pathways in a signaling network (eg, combining inhibitors of PI3K/ Akt and MEK)
  • Agents targeting oncogenic signals and negative feedback signals (eg, combining inhibitors of PI3K/Akt and mTOR)6,9,11
Despite extensive research efforts, only a handful of combination strategies have been successfully implemented to date, and there are a number of serious issues that need to be addressed before this type of therapy can reach its full potential. Among them is the cost; dealing with multiple agents means a multiplication of the costs associated with both clinical testing and with implementation of approved therapy. It is therefore essential to be able to identify likely responders to therapy. However, a lack of predictive biomarkers is a significant hindrance in this respect.9,14

Another issue is the additional toxicity that may be expected with combination therapy. Pulse dosing could offer a potential solution, alternating between single agents and combinations over the course of treatment, but it is of vital importance to effectively assess safety in clinical trials. To this end, the FDA has released draft guidance on the development of investigational drug combinations, providing strict criteria on the selection and testing of drugs.15,16

Staying One Step Ahead

We are just beginning to fully appreciate the complexity and multidimensional nature of drug resistance, and the need for a thorough understanding of the underlying biology of individual tumors. Effectively tackling the challenge of resistance will require a systems biology approach integrating knowledge of the tumor (stage, histopathology), protein interaction networks, genomic profiling, epigenetic factors, feedback mechanisms, and the pharmacology of combined drugs. Recent research suggests that a better understanding of cancer stem cells and the tumor microenvironment will also help to provide novel strategies for tackling drug resistance.11

Technological advances are aiding in the future fight against resistance. High throughput screens allow researchers to assess thousands of drug combinations simultaneously, to identify rational combinations most likely to succeed in clinical trials, and thereby help to reduce the associated costs. Evolutionary modeling enables them to determine the pattern of mutations that has developed in a cancer cell over its lifetime. This could allow us to predict drug resistance pathways and prevent resistance before it happens—to stay one step ahead of cancer.17

Table References

  1. Lackner MR, Wilson TR, Settleman J. Mechanisms of acquired resistance to targeted cancer therapies. Future Oncol. 2012;8(8):999- 1014.
  2. Tan DS, Gerlinger M, Teh BT, Swanton C. Anti-cancer drug resistance: understanding the mechanisms through the use of integrative genomics and functional RNA interference. Eur J Cancer. 2010;46(12):2166-2177.
  3. Sierra JR, Cepero V, Giordano S. Molecular mechanisms of acquired resistance to tyrosine kinase targeted therapy. Mol Cancer. 2010;9:75-87.
  4. Yap TA, Omlin A, de Bono JS. Development of therapeutic combinations targeting major cancer signaling pathways. J Clin Oncol. 2013;31(12):1592-1605.
  5. Pao W, Miller VA, Politi KA, et al. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med. 2005;2(3):e73.
  6. Kobayashi S, Boggon TJ, Dayaram T, et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N Engl J Med. 2005;352(8):786-792.
  7. Cappuzzo F, Janne PA, Skokan M, et al. MET increased gene copy number and primary resistance to gefitinib therapy in non-small-cell lung cancer patients. Ann Oncol. 2009;20(2):298-304.
  8. Pandolfi PP. Breast cancer - loss of PTEN predicts resistance to treatment. N Engl J Med. 2004;351(22):2337-2338.
  9. Fiszman GL, Jasnis MA. Molecular mechanisms of trastuzumab resistance in HER2 overexpressing breast cancer. Int J Breast Cancer. 2011;2011:1-11.
  10. Sok JC, Coppelli FM, Thomas SM, et al. Mutant epidermal growth factor receptor (EGFRvIII) contributes to head and neck cancer growth and resistance to EGFR targeting. Clin Cancer Res. 2006;12:5064-5073.
  11. Gottschling S, Schabnel PA, Herth FJF, Herpel E. Are we missing the target? - cancer stem cells and drug resistance in non-small cell lung cancer. Cancer Genomics Proteomics. 2012;9:275-286.
  12. Maftouh M, Avan A, Galvani E, et al. Molecular mechanisms underlying the role of microRNAs in resistance to epidermal growth factor receptor-targeted agents and novel therapeutic strategies for treatment of non-small-cell lung cancer. Crit Rev Oncog. 2013;18(4):317-326.
  13. Lee TS, Ma W, Zhang X, et al. BCR-ABL alternative splicing as a common mechanism for imatinib resistance: evidence from molecular dynamics simulations. Mol Cancer Ther. 2008;7(12):3834- 3841.
  14. Locasale JW. Metabolic rewiring drives resistance to targeted cancer therapy. Mol Syst Biol. 2012;8:597-598.
  15. Mahon FX, Belloc F, Lagarde V, et al. MDR1 gene overexpression confers resistance to imatinib mesylate in leukemia cell line models. Blood. 2003;101(6):2368-2373.

References

  1. Rubin B, Duensing A. Mechanisms of resistance to small molecule kinase inhibition in the treatment of solid tumors. Lab Invest. 2006;86:981-986.
  2. Raguz S, Yagüe E. Resistance to chemotherapy: new treatments and novel insights into an old problem. Br J Cancer. 2008;99:387-391.
  3. Tan DS, Gerlinger M, Teh BT, Swanton C. Anti-cancer drug resistance: understanding the mechanisms through the use of integrative genomics and functional RNA interference. Eur J Cancer. 2010;46(12):2166-2177.
  4. Lackner MR, Wilson TR, Settleman J. Mechanisms of acquired resistance to targeted cancer therapies. Future Oncol. 2012;8(8):999- 1014.
  5. Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481 (7381):306-313.
  6. Chandarlapaty S. Negative feedback and adaptive resistance to the targeted therapy of cancer. Cancer Discov. 2012;2(4):311-319.
  7. Kruh GD. Introduction to resistance to anticancer agents. Oncogene. 2003;22(47):7262-7264.
  8. Locasale JW. Metabolic rewiring drives resistance to targeted cancer therapy. Mol Syst Biol. 2012;8:597-598.
  9. Sierra JR, Cepero V, Giordano S. Molecular mechanisms of acquired resistance to tyrosine kinase targeted therapy. Mol Cancer. 2010;9:75-87.
  10. Gottschling S, Schabnel PA, Herth FJF, Herpel E. Are we missing the target? - cancer stem cells and drug resistance in non-small cell lung vancer. Cancer Genomics Proteomics. 2012;9:275-286.
  11. Yap TA, Omlin A, de Bono JS. Development of therapeutic combinations targeting major cancer signaling pathways. J Clin Oncol. 2013;31(12):1592-1605.
  12. Azam M, Latek RR, Daley GQ. Mechanisms of autoinhibition and STI- 571/imatinib resistance revealed by mutagenesis of BCR-ABL. Cell. 2003;112(6):831-843.
  13. Tasigna (nibotinib) [prescribing information]. 2013. East Hanover, NJ, Novartis Pharmaceuticals Corporation.
  14. Bernards R. Finding biomarkers of resistance to targeted cancer therapies. EJC Supplements. 2007;5(5):109-114.
  15. U.S. Department of Health and Human Services. Food and Drug Administration. Guidance for Industry: Codevelopment of Two or More New Investigational Drugs for Use in Combination. June 2013. Available at: http://www.fda.gov/downloads/Drugs/ GuidanceComplianceRegulatoryInformation/Guidances/ UCM236669.pdf. Accessed July 30, 2013.
  16. Kwak EL, Clark JW, Chabner B. Targeted agents: the rules of combination. Clin Cancer Res. 2007;13(18 Pt 1):5232-5237.
  17. Al-Lazikani B, Banerji U, Workman P. Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol. 2012;30(7):679-692.



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Overcoming Resistance to Targeted Cancer Therapy
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