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Cancer Drug Resistance: Targets and Therapies


  1. Barbara Zdrazil,
  2. Gerhard F. Ecker

Published Online: 15 SEP 2010

DOI: 10.1002/0471266949.bmc215

Burger's Medicinal Chemistry and Drug Discovery

Burger's Medicinal Chemistry and Drug Discovery

How to Cite

Zdrazil, B. and Ecker, G. F. 2010. Cancer Drug Resistance: Targets and Therapies. Burger's Medicinal Chemistry and Drug Discovery. 361–382.

Author Information

  1. University of Vienna, Department of Medicinal Chemistry, Vienna, Austria

Publication History

  1. Published Online: 15 SEP 2010

1 Introduction

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

Hundred years ago, Paul Ehrlich, the founder of chemotherapy, received the Nobel Price for Physiology or Medicine for his landmark immunological insights. Ehrlich postulated the existence of specific receptors (either associated with cells or distributed in the blood stream), which may be regarded as side chains that bind antigens (“side-chain theory of immunity, ” see timeline in Fig. 1) (1). According to him, each type of receptors is attuned to one special group of drugs (2). He declared “wir müssen zielen lernen, chemisch zielen lernen” (“we have to learn how to target chemically”)—Ehrlich already suspected that the key for synthetic chemistry was to modify some starting material in various ways. After the discovery of the antisyphilitic activity of Salvarsan—an organic arsenic compound—in 1908 in Paul Ehrlich's laboratory, lead optimization led to the improved derivative Neosalvarsan in 1912. Biological activity of a lead compound for the first time was optimized through systematic modifications. This was the real beginning of chemotherapy (3, 4).

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Figure 1. Timeline taken from Ref. 4.

It took some time—until the end of the World War II—that chemotherapy was introduced in clinical practice for cancer treatment. Gilman and coworkers treated a patient with non-Hodgkin lymphoma with nitrogen mustard, a chemical warfare agent that accidentally had caused lymphoid and myeloid suppression in humans during World War II. The therapy initially caused a dramatic antitumor effect, but by the time the third treatment was given, the tumor no longer responded to the chemotherapeutic treatment (4, 5).

Since these early days of cancer chemotherapy, the increased knowledge of the cancer genome and the development of new drug discovery technologies, such as quantitative structure–activity relationships (QSAR), high-throughput screening (HTS), nuclear magnetic resonance (NMR), X-ray diffraction, and protein–ligand cocrystallography, have paved the way for targeted and multitargeted cancer therapeutics. Nevertheless, classical (unspecific cytotoxic) as well as targeted chemotherapy are often faced with one major obstacle that limits its success: drug resistance (tolerance).

2 Overview of Drug Resistance Mechanisms

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

By elucidation of the diverse resistance mechanisms to antineoplastic therapy, putative future drug targets can be studied. Some of the mechanisms may have the potential to be targeted, and to maintain or even improve selectivity of antitumor action (6). Mechanisms of drug resistance that are associated with small molecules are illustrated in Fig. 2.

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Figure 2. Different drug-resistance mechanisms. Taken from Ref. 7.

Those resistance mechanisms essentially include the following:

  • Decreased intracellular concentration of the drug (e.g., ABC transporters)

  • Alterations of the drug target (e.g., point mutations, overexpression of the target)

  • Increased detoxification of the drug (e.g., glutathione conjugation)

  • Decreased metabolic activation of the (pro)drug

  • Decreased active uptake of the drug

  • Activation of DNA repair systems

  • Alterations in the cell-cycle checkpoint (e.g., p21)

  • Changes in the ratio of pro- and antiapoptotic proteins

Besides, we should distinguish between two basic types of antineoplastic drug tolerance mechanisms: Intrinsic resistance, which already exists at the time of the diagnosis prior to drug therapy, and acquired (adaptive) drug resistance, which appears later in the treatment. The latter is attributed to spontaneous genetic mutations and “negative” selection by cytotoxic chemotherapy—a phenomenon that leads to selective deletion of the most responsive tumor cells but simultaneous survival of the least sensitive cells (6, 8). Since the tissues that are highly susceptible to chemotherapy include bone marrow and mucosal surfaces (e.g., of the gastrointestinal tract), their depletion actually limits treatment options (9). Nevertheless, by trying to find a classification scheme for different drug resistance mechanisms, one should not lose sight of one attribute they all have in common: Resistance to cancer treatment should ultimately be regarded as a consequence to somatic mutations and genomic plasticity associated with cancer.

With respect to overcoming drug resistance, there are also two completely different cases. If the resistance observed is limited to the actual compound class used and, for example, is caused by a single point mutation of the target or of an enzyme involved in metabolic activation, then classical drug design approaches leading to distinctly modified compounds are the strategy of choice. On the other hand, there are mechanisms leading to multiple drug resistance. These include mainly the inability to enter apoptosis and the overexpression of drug efflux pumps, such as P-glycoprotein. For the latter, coadministration of respective inhibitors has been proposed and several compounds were tested in clinical trials. Interestingly, none of them has been marketed till now. Both principal approaches will be discussed in detail in this chapter, whereby we will restrict ourselves to more recent concepts.

3 Targeted Chemotherapy and Resistance

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

Targeted chemotherapy includes the use of either monoclonal antibodies (MAbs) or small-molecule drugs, both of which interfere with tumor-specific (or tumor–associated) proteins to alter their signaling. The use of ‘targeted small-molecule therapeutics’ is a consequence of the manifold new insights into the molecular/somatic alterations that are present in tumors. It has initiated a second wave of anticancer drug development that is characterized by rational design of low molecular weight compounds that should specifically target crucial effectors involved in cell proliferation, invasion and metastasis, angiogenesis, and apoptosis (4).

During the early days of targeted cancer chemotherapy, the novel compounds were designed to target one single crucial oncoprotein in a highly specific fashion. Nowadays, cancer has been recognized as a multifactorial disease where there is multilevel cross-stimulation among the targets along several pathways of signal transduction that finally led to neoplasia. Thus, by blocking only one of these pathways, the other pathways involved in the manifestation of cancer (which are not blocked) could act as salvage mechanism for the cancer cell. Thus, a second generation of so-called “multitargeted” chemotherapeutics aims at the interference of a multitude of these pathways/oncoproteins that is expected to result in a broader antitumor effect.

3.1 Resistance to Tyrosine Kinase Inhibitors (TKIs)

More than 25 years ago, tyrosine kinases (TKs) have been found to be involved in tumor development and progression. Approximately 90 TKs are encoded by the human genome, and their overexpression or abnormal activation—caused by somatic mutation(s) of these genes—is generally accepted to be a characteristic feature of many cancers. Most of the known existing TKs (approximately 60) are receptor TKs (RTKs), consisting of an extracellular, a transmembrane, and an intracellular domain. The remaining ones (approximately 30) target nonreceptor TKs, which are located in the cytoplasm of the cell (e.g., the SRC-, and the ABL-family of nonreceptor TK).

Currently, TK inhibitors (TKIs) have become part of standard chemotherapy for specific tumors (in combination with conventional chemotherapy and radiotherapy) due to a number of good qualities: their capability to stabilize tumor progression and their minimal side effects. Classical RTKIs are small molecular weight molecules that bind intracellular and competitively to the ATP-binding catalytic site of RTKs. In contrast, antibody-based drugs compete with the endogenous ligand for binding to the extracellular domain (10-13).

However, after initial remission, most of the patients quickly develop drug resistance against TKIs. In principle, mechanisms that contribute to the progression of the disease may be primary (intrinsic)—such as in some cases of imatinib resistance (see below)—or acquired. In particular, they include secondary mutations and/or overexpression of the targeted kinase by gene amplification, increased drug efflux, altered drug metabolism, and activation of downstream salvage pathways (13, 14). Since in a high fraction of patients with resistance to TKI the acquired mutations of the TK-encoding genes is determined as the predominant hindrance for successful therapy, a second generation of TKI was designed to be active against these new mutations (12).

3.1.1 Small-Molecule TKIs Resistance to Imatinib Mesylate (GLEEVEC, Novartis)

The discovery of the Philadelphia chromosome in 1960—a chromosomal abnormality that results from a reciprocal translocation that juxtaposes the BCR gene (on chromosome 22) with the ABL gene (on chromosome 9)—was considered as a major milestone in the treatment of chronic myelogenous leukemia (CML) (15). In patients with CML the generated fusion gene BCR-ABL encodes an oncoprotein (a cytoplasmatic TK) with deregulated (constitutively active) TK activity. Imatinib is a promiscuous (but selective) small-molecule inhibitor of the BCR-ABL kinase used in the therapy of CML, gastrointestinal stromal tumors (GISTs), and hypereosiophilic syndrome (13). Its poly-specificity is oriented toward the inhibition of additional TKs, including the platelet-derived growth factor receptor (PDGFR) and the stem cell factor receptor (c-KIT) (12).

CML patients who are treated with imatinib in some cases retain the Philadelphia chromosome in most of their bone marrow cells, showing a form of intrinsic drug resistance (14). Others first respond, but secondary acquire point-mutations in BCR-ABL (approximately 50% of acquired imatinib-resistant patients). These mutations frequently occur within amino acid sequences that encode important structural features of the TK, such as the “gatekeeper” residue, the p-loop and the activation loop. Figure 3 illustrates the location of these mutational hotspots within the Abl kinase domain (16).

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Figure 3. Structure of the Abl kinase domain in complex with imatinib (green): hotspots of frequent amino acid mutations are colored red (T315), yellow (p-loop, Y253, and E255), orange (activation loop, and H396), and pink (M351). Taken from Ref. 16.

To a lesser extend gene amplification, overexpression at the mRNA or protein levels, drug efflux by ABC transporters, reduced drug-uptake by plasma sequestration, and activation of alternative pathways may play a role in the generation of imatinib resistance (17).

Thus, the development of so-called “second-generation” inhibitors (e.g., dasatinib (18), nilotinib, and bosutinib (Fig. 4)) yielded in effective inhibition of kinases, which harbor secondary mutations. Nilotinib binds—like imatinib—to the closed, inactive form of BCR-ABL but exhibits a 30-fold increased activity. In contrast, dasatinib binds to the catalytic domain in the biologically active conformation. As the mutations, which confer imatinib resistance, include those that lead to loss of the enzymes' ability to convert into the inactive form to allow imatinib binding, dasatinib is able to bind to the imatinib-resistant mutant enzyme. It has 300-fold increased activity (compared to imatinib) and a broad spectrum of activity against BCR-ABL, SRC kinases, c-KIT, and PDGFR (18).

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Figure 4. Chemical structures of selected tyrosine kinase inhibitors.

Also for GIST, imatinib has become the standard therapy. Here, primarily activating mutations of the KIT and/or PDGF kinase domain(s) cause resistance and thus present limiting treatment obstacles. In such cases, a second-generation TKI approved for imatinib-refractory GIST, sunitinib is active against some of the KIT mutant cancer forms. Other forms of resistance that may affect (with a minor prevalence) the successful outcome of GIST treatment by imatinib are the same as being described for CML treatment.

However, the most frequent resistance mutation—the T315I mutation—is refractory against all clinically available TKIs. Recently, the Aurora kinase inhibitor VX-680 (Merck) and the MAP kinase p38 inhibitor BIRB-796 (Fig. 5) (Boehringer Ingelheim) have demonstrated inhibition of T315I mutants (19). While BIRB-796 has been discontinued from development, more recent p38 inhibitors, such as VX-702 and SB-681323, are still under active development.

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Figure 5. Chemical structures of kinase inhibitors.

Alternatively, targeting the molecular chaperone heat shock protein 90 (HSP-90) or histone deacetylases (HDAC), or a combination of both could be effective in BCR-ABL mediated imatinib resistance. The geldanamycin derivative 17-allylamino-17-demethoxygeldanamycin (17-AAG, National Cancer Institute), a HSP90 inhibitor, recently demonstrated good toxicity profile in phase I clinical trials (20, 21). LAQ824 (Novartis), a cinnamyl hydroxamic acid analog inhibitor of HDAC, led to a decrease in BCR-ABL expression on the mRNA and protein level in patients with CML blast crisis. In addition, this HDAC inhibitor also diminished the association of HSP90 with BCR-ABL (22). Moreover, in a recent study the combination of HDAC inhibitors with the Hsp90 antagonist 17-AAG shows synergistic effects and therefore may represent a novel strategy against Bcr-Abl+ leukemias, including those resistant to imatinib (23).

Finally, there are efforts to target downstream signaling pathways of BCR-ABL (Ras/MAPK, Raf-1 and Mek, and the PI3K/Akt pathway). All these strategies and their promising drug candidates eventually alone—but most probably in combination with each other and with conventional chemotherapeutics—may postpone the apparently inalterable emergence of drug resistance and in that way optimize treatment outcome. Resistance to EGFR Kinase Inhibitors

Anti-EGFR drugs include small-molecule adenosine triphosphate-competitive inhibitors, as well as MAbs directed against the extracellular domain of the EGFR (see Section 3.1.2), which do not completely overlap regarding their mechanisms of action and their antitumor activity (12).

Small-molecule RTKI targeting EGFR (such as erlotinib and gefitinib) have proven to be effective in the therapy of nonsmall-cell lung cancer (NSCLC), and has resulted in cellular responses in patients with advanced pancreatic cancer (24), glioblastoma (25), colorectal carcinoma, head-and-neck cancer, and renal cell carcinoma (26). Sensitivity to erlotinib or gefitinib can especially be expected in cases where activating mutations of the EGFR domain have driven the cancer development (27, 28). The most common mutation (ore than 40% of EGFR mutations in NSCLC), associated with responsiveness to erlotinib and gefitinib, is the L858R mutation (19).

However, an impressive initial response to the treatment with EGFR TKIs is often followed by resistance—in half of the cases, this happens due to a secondary mutation resulting in a threonine to methionine substitution at position 790 in the protein strand (T790M) (29). In addition to frequent acquired T790M mutations in lung cancers, in a small number of cases, this mutation was detected prior to exposure to EGFR inhibitors (intrinsic) (30). Interestingly, mutation of this conserved threonine residue located in the active site (also referred to as the “gatekeeper”), is also common in other structurally related kinases: BCR-ABL (T315I) and KIT (T670I) (19).

In an attempt to overcome T790M induced resistance, second-generation EGFR inhibitors (e.g., HKI-272, EKB-569; see Fig. 6) aim at irreversible blocking EGFR T790M signaling by binding to Cys773 (31). Though, recently a novel secondary mutation (D761Y), as a response to anti-EGFR therapy, has been described (32).

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Figure 6. Chemical structures of selected EGRF inhibitors.

Alternatively, to irreversible EGFR blockers there are a few strategies that may improve therapeutic efficacy by targeting other mechanisms of acquired resistance. Especially, downstream pathways of EGFR (phosphoinositol-3-kinase PI3K pathway) and amplification of the mesenchymal–epithelial transition factor (MET) have been associated with secondary resistance to anti-EGFR therapy and may be interesting points of intersection (13). Resistance to Angiogenesis Inhibitors

Nowadays, the process of angiogenesis (neovascularization) during carcinogenesis is increasingly recognized as a rate-limiting secondary event. Thus, antiangiogentic therapy has been noted as an important milestone in cancer treatment and is becoming a component of a standard-of-care chemotherapy, especially for colorectal and renal cancers (33, 34).

Above all, angiogenesis inhibitors which target the vascular endothelial growth factor (VEGF) proangiogenic signaling pathways demonstrated therapeutic efficacy. Most prominent representatives of these VEGF pathway inhibitors are bevacizumab (AVASTIN, Genentech/Roche), which is a ligand-trapping monoclonal antibody against the VEGF-RTK [see Section 3.1.2], sorafenib (NEXAVAR, Bayer/Onyx) and sunitinib malate (SUTENT, Pfizer)—two small-molecule multi-RTK inhibitors. Besides VEGFR inhibition sorafenib also interacts with the kinase activity of PDGFR, C-RAF and B-RAF, and c-KIT. In analogy, sunitinib targets additionally PDGFR, KIT, and fms-like TK3 (35). Both RTK inhibitors are FDA approved for the treatment of advanced renal cell carcinoma (RCC). Sunitinib is also approved for patients with GIST who fail, or are intolerant of, therapy with imatinib mesylate (34).

However, though therapy with VEGF pathway inhibitors in many cases show demonstrable clinical benefit, sometimes progression of the tumor after initial response to the therapy is observed (adaptive resistance). Distinct (and partly interrelated) mechanisms that confer adaptive resistance may be basically attributed to the evasion of the antiangiogenic therapy. Hanahan et al. (34) essentially proposed the following mechanisms: revascularization by upregulation of alternative proangiogenic signaling factors (e.g., fibroblast growth factor (FGF)); decreased dependence on neovascularization by protection of the existing tumor vasculature (e.g., by increased pericyte coverage); and perivascular invasion. In addition, certain tumors also show intrinsic (preexisting) resistance to angiogenesis inhibitors, meaning that the pretherapeutic conditions do not allow any beneficial effect by the therapy.

As a strategy to circumvent such resistance mechanisms, the authors propose the combination of VEGF pathway inhibitors with anti-invasive and antimetastatic drugs, such as inhibitors of the proinvasive hepatocyte growth factor (HGF)—MET pathway, and drugs targeting the insulin-like growth factor 1 (IGF 1) receptor pathway. Secondly, simultaneous interference with parallel proangiogenic signaling pathways may be a fruitful strategy to prevent the emergence of resistance to antiangiogenic therapy (34).

3.1.2 Monoclonal Antibodies Targeting TK

The first MAb that was approved by the FDA for therapeutic use was rituximab (RITUXAN, Genentech) in 1997. This chimeric MAb binds to the pan-B-cell marker CD20 and is used for the treatment of patients with relapsed or refractory low-grade or follicular, B-cell non-Hodgkin's lymphoma (NHL) (36). Shortly later, in the year 1998, the humanized MAb trastuzumab (HERCEPTIN, Genentech) followed with an FDA approval for HER2 (ErbB2) overexpressing breast cancers. Successful clinical application of these two MAbs encouraged the assessment of further drug candidates into clinical trials. After the turn of the millennium, new MAbs were introduced in the clinics: alemtuzumab (FDA approval in 2001), which is directed against CD52 in patients with chronic lymphocytic leukemia, and cetuximab (FDA approval in 2004). The latter inhibits the EGFR tyrosine kinase (ErbB1) and is indicated in cases of metastatic colorectal cancer and head-and-neck tumors (37).

All this clinically approved MAbs directly attack the tumor cells by making use of different mechanisms of action: modulation of signaling pathways, antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and immomodulation (37, 38). As a consequence, each mode of action may be responsible for one or multiple potential mechanism of resistance to antibody-based therapy. As examples, resistance mechanisms to rituximab and trastuzumab are pointed out below.

Rituximab leads to relevant clinical response to initial treatment in only approximately 50% of the patients. The manifold mechanisms that may contribute to rituximab resistance include Fc receptor polymorphism, CD20 modulation, and decreased ADCC. Consequently, potential mechanisms to overcome anti-CD20 resistance might be the use of engineered antibodies that facilitate Fc receptor binding, the use of cytokines (like interferon-α), radioimmunoconjugates and especially chemotherapy combinations (39). In the case of trastuzumab, it is only approximately one-third of women under treatment that actually respond to monotherapy with this MAb (40). Mechanisms of resistance related with failure of trastuzumab treatment are the activation of the PI3K/Akt pathway or via loss of PTEN function, a tumor surpressor and thus negative regulator of Akt. Here, the combination or sequential therapy with another chemotherapeutic drug (such as lapatinib) seem to be the most promising strategies (41).

In addition to the development of these MAbs, which all target membrane proteins in tumor cells, there has been effort to identify other targets in the microenvironment associated with the carcinogenic event. The approval of bevacizumab (AVASTIN, Genentech) in 2004 for the treatment of metastatic colorectal cancer (and later also for NSCLC and metastatic HER2-negative breast cancer) is an example for such a strategy. It is an antiangiogenic compound directed against the VEGFR. Resistance mechanisms that are associated with antiangiogenic therapy have been discussed in the Section 3.1.1 (34).

3.2 Endocrine Resistance in Breast Cancer

Approximately 70% of breast tumors express estrogen receptors (ERs), making them accessible for antiestrogens such as tamoxifen (Fig. 7). This nonsteroidal selective estrogen receptor modulator (SERM) blocks the ERs of tumor cells, but has an agonistic effect in other organs/tissues (liver, uterus, bone cells). In contrast, aromatase inhibitors (AI, estrogen synthase inhibitors) such as exemestane, anastrozole, and letrozole reduce the estrogen levels also in peripheral tissues (42). The sequential use of exemestane demonstrated to be of advantage in the cases tamoxifen resistance. Such endocrine-insensitive states usually appear after 2–3 years of treatment with tamoxifen (43). But not only partial estrogen receptor agonists but also “pure” antiestrogens (ER downregulators)—such as fulvestrant—lead to the acquisition of an endocrine-resistant state and an increase in their migratory and invasive capacity in vitro after chronic exposure (44).

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Figure 7. Chemical structures of selected ER inhibitors.

Besides initiation and regulation of breast tumor growth by steroid hormones and ERs, also peptide growth factors and growth factor receptors (EGFR, HER2) are involved in this process. This is demonstrated by the fact that up to 25% of breast cancers are HER2-positiv and thus respond to trastuzumab treatment. It is generally believed that there exist tight interactions between these two signaling pathways. Especially cross-talk between ER, HER2, p38 and ERK at the time of tamoxifen resistance indicates that there are novel potential targets to overcome this resistance (45). However, very recent investigation suggests no direct connection between ER and HER2 at a transcriptional level in the mediation of tamoxifen resistance. Instead, the authors postulate that PAX2 is a central key player in the ER-mediated repression of ErbB2. Accordingly, PAX2 mutations may be the main reason for increased ErbB2 expression and thus potentially determine response to tamoxifen. In addition, the linkage of the two breast cancer types (ER-positiv and HER2/ErbB2-positive) by the mechanism of repression of ErbB2 by ER-PAX2 suggests that evasion of this blocking could make an ER-positive tumor transform into an aggressive HER2-positive tumor (46).

To date, promising strategies to overcome resistance to endocrine therapy (besides the ones mentioned before) include the combination of trastuzumab with fulvestrant for treatment of cancers that express HER2 and ER, the simultaneous use of EGFR TKIs (like gefitinib) or other growth factor pathway inhibitors, targeting the PI3K/Akt pathway (which is often active in breast cancer), disruption of the ER function (e.g., farnesyltransferase inhibitors), and combination with angiogenesis inhibitors (42).

4 Multiple Drug Resistance

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

Based on the knowledge about the multiple mechanisms that may confer multidrug resistance to cancer chemotherapy, a multitude of strategies has been evolved to deal with this problem. In this chapter, we will review only two of the most prominent approaches: targeting apoptosis pathways and reversal of resistance that is attributed to the function of ABC transporters. Others include for instance modulation of the methylation status of crucial proteins in tumorigenesis, or depletion of intracellular glutathione levels (47).

4.1 Targeting Proteins Involved in Apoptosis

Apoptosis—or programmed cell death—is an intrinsic mechanism of cells that leads to cell attrition. A balance between apoptosis and cell proliferation is necessary to maintain the tissue homeostasis. In many cancer patients, defects in the apoptosis pathways lead to the neoplastic transformation. Thus, many chemotherapeutic anticancer agents act by inducing apoptosis. However, genetic alterations in the apoptosis pathway may also result in apoptosis resistance (33, 48).

Targeting this pathway to modulate drug resistance includes several strategies that take into account the potential different sites for therapeutic intervention. Death ligands (e.g., TRAIL) bind to death receptors on the cell surface that activate the caspase cascade and in that way initiate apoptosis (49). Another approach is aimed at the downregulation of antiapoptotic proteins, such as Bcl-2 or Bcl-XL. Here, the use of antisense oligonucleotides (ASOs) (50), small molecules, and RNA interference (51) are offering interesting possibilities.

Direct activation of caspases may be fulfilled by peptides that target the IAPs (inhibitors of apoptosis, e.g., survivin (52)). The conserved IAP protein family suppresses apoptosis by blocking caspases—proteins like Smac/DIABLO eliminate the inhibitory effect of IAPs and thus (re)activate apoptosis (53).

Finally, although controversial, there have been many efforts to restore wild-type p53 in tumor cells, a tumor surpressor gene that is often mutated in human cancer. Several small-molecule drugs have been demonstrated to restore a wild-type status to cells harboring mutant p53 and thus activate apoptosis (54).

4.2 Targeting Resistance Mediated by ABC Transporters

Regarding the different drug resistance mechanisms described in Chapter 2, the one that we most commonly are faced with in the laboratory is the enhanced extrusion of hydrophobic cytotoxic drugs by ABC transporters (55). This ATP-binding cassette superfamily is the largest transporter gene family—consisting of 48 known human ABC genes, which can be divided into seven distinct subfamilies (designated A through G). Each functional unit of an ABC transporter consists of two cytoplasmatic, nucleotide binding domains (NBDs) and two transmembrane domains (TMDs) made up of α-helices. Driven by binding and hydrolysation of ATP at the NBDs, a wide variety of substrates are translocated across plasma membranes: sugars, amino acids, metal ions, peptids/proteins, hydrophobic compounds, and metabolites (56, 57).

As these proteins are constitutively expressed in tissues that are important for absorption, metabolism and elimination (e.g., lung, GUT, liver, kidney), as well as in sanctuary site tissues (e.g., blood–brain barrier, placenta), their role as central key players in tissue defense has been increasingly recognized (58).

Besides active extrusion of xenobiotics out of normal cells, overexpression of ABC transporters in the cell membranes of multidrug-resistant tumor cells cause an active outward transport of chemotherapeutic agents. The emergence of multidrug resistance (MDR) is a major hindrance to the successful therapy of various forms of malignant and infectious diseases—not only in cancer treatment but also in other treatments. The concept of MDR describes simultaneous resistance (cross-resistance) of cancer cells toward a broad spectrum of structurally and also mechanistically unrelated cytotoxic drugs with different modes of action (59). This implicates that after initial administration of a certain drug/drug combination, resistance may arise to agents to which the patient has not been exposed previously.

4.2.1 P-Glycoprotein (ABCB1)

In 1976, the first ABC transporter was discovered by Juliano and Ling (60) and called P-glycoprotein (P-gp, MDR1), because this cell surface glycoprotein was found in mutant cells displaying altered drug permeability (P stands for permeability). It was for the first time that one single protein was linked to a huge number of structurally diverse compounds to which it conferred resistance. However, not until 1986 the human mdr1 gene was isolated and the evidence of its ability to confer alone the drug resistant phenotype was provided (61).

The broad spectrum of substances transported by P-gp contains a wide variety of natural product toxins such as vinca alkaloids, anthracyclines, epipodophyllotoxins, taxanes, and many more (55). This phenomenon (often observed in ABC transporters) of a structurally unrelated ligand recognition pattern is called promiscuity or multispecificity. We prefer the latter term, as these transporters still show specificity toward distinct structural scaffolds and it has been demonstrated that predictive in silico models may be obtained (62).

Only 5 years after the discovery of ABCB1, verapamil—a calcium channel blocker—was found to block P-gp mediated transport and thus revert vincristin resistance in tumor cells [63]. After that an intensive research in the field of potential inhibitors of P-gp followed to invert drug resistance and reestablish sensitivity to standard therapeutic regimens. “First-generation” P-gp inhibitors include compounds that were already approved for other indications: two other classes of calcium channel blockers, benzothiazepines and 1,4-dihydropyridines, phenothiazines, quinine, tamoxifen, and cyclosporine A. Due to inherent cardiac or other toxicities of these drugs in the doses required for modulation of P-gp function [64], a “second generation” of inhibitors should fulfil the need of avoiding those limiting side effects. Examples are biricodar (VX-710), a derivative of the macrocyclic antibiotic FK-506, and the cyclosporine D analog Valspodar (PSC-833), which is able to block P-gp without having immunosuppressive effects or having an effect on Ca ion channels. However, also this class of agents has not reached the market due to interference with cytochrome P450 3A4 that often leads to limited drug clearance and therefore causes toxic plasma concentrations [65]. The “third generation” of MDR modulators was designed to satisfy the need of low pharmacokinetic interaction: laniquidar, tariquidar, zosuqidar, elacridar, and ONT-093 (Fig. 8). Although, the clinical studies of the majority of these compounds are not terminated or fully analyzed to date, it seems that also this generation of MDR modulators cannot meet the expectations. After more than 20 years and numerous clinical studies, there is no definitive proof that a PGP inhibitor effectively reverses drug resistance in humans. This is mainly due to the fact that the pharmacokinetic interactions observed with these agents have made it difficult to interpret efficacy.

Nevertheless, the search for more appropriate MDR modulators is going on, but now the focus is to target multiple ABC transporters (such as P-gp and ABCG2) at once. Though, one major drawback of such an approach may be an even greater potential of treatment limiting side effects.

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Figure 8. Chemical structures of selected P-gp inhibitors.

Not only P-gp but also ABCG2 and MRP1 (multidrug resistance protein 1, ABCC1) may be determined as the most important proteins involved in the appearance of a MDR phenotype in cancer. Although, only modulators of these three ABC transporters have been evaluated in clinical trials, some emerging studies revealed the involvement of a lot more members of this superfamily: ABCA2, ABCB4 (MDR3), ABCB11 (“sister of P-gp”), ABCC2 (MRP2), ABCC3 (MRP3), ABCC6 (MRP6), and ABCC10 (MRP7) (55).

4.2.2 ABCC1 (Multidrug Resistance Protein 1)

MRP1 was the second ABC transporter that was found to be involved in MDR (66). It is highly expressed in stomach, lung, and brain and its physiological role as a high-affinity anion transporter makes it capable to translocate glutathione conjugates, such as LTC4, as well as glucuronate and sulphate conjugates (67, 68). With regard to its resistance profile, there is a substantial overlap with that of P-gp. It may be responsible for resistance to natural product drugs, such as vinca alkaloids, anthracyclines, and epipodophyllotoxines, and for mitoxantrone- and methotrexate-resistance. In contrast, high levels of resistance to taxanes or bisantrene have not been observed (69).

Like in the case of P-gp, a lot of effort has been made to find potential inhibitors of MRP1 to inverse MDR, but research is still in its infancy. Advances in the discovery of ABCC1 inhibitors have been reviewed recently (70).

4.2.3 ABCG2 (Breast Cancer Resistance Protein, MXR)

The ABCG2 gene was first isolated from a breast cancer cell line and therefore called the breast cancer resistance protein (BCRP) gene. In human, it is highly expressed in the placenta, liver, intestine, kidney, in the lactating mammary gland, at the blood–brain barrier, and in hematopoietic stem cells (71). In contrast to P-gp and the ABCC family, ABCG2 is a half-transporter forming homodimers to obtain functional units.

The range of substrate recognition of ABCG2 is almost as broad as that of P-gp. Moreover, many of the transported agents do simultaneously interact with P-gp (72). However, results obtained from pharmacophore modeling and QSAR studies for the class of propafenones indicate that ABCG2 may be more tolerant to structural modification than ABCB1 (73).

4.2.4 SAR- and QSAR Studies on Inhibitors of ABC Transporters

In lead optimization programs, numerous QSAR studies on structurally homologous series of compounds have been performed. Especially, verapamil analogs, triazines, acridonecarboxamides, phenothiazines, thioxanthenes, flavones, dihydropyridines, propafenones, and cyclosporine derivatives have been extensively studied, and the results are summarized in several excellent reviews (74, 75). These studies pinpoint the importance of H-bond acceptors and their strength, the distance between aromatic moieties and H-bond acceptors as well as the influence of global physicochemical parameters, such as lipophilicity and molar refractivity. Systematic quantitative structure–activity relationship studies have been performed mainly on phenothiazines and propafenones (76). The latter have been carried out using Hansch- and Free-Wilson analyses (77), hologram QSAR, CoMFA, and CoMSIA studies (78) as well as nonlinear methods (79) and similarity-based approaches (80). Hansch-type correlation analyses normally lead to excellent correlations between lipophilicity and pIC50 values within structurally homologous series of compounds. However, this is not surprising as the interaction of ligands with P-gp is supposed to take place in the membrane bilayer. Thus, lipophilicity of the compounds triggers their concentration at the binding site rather than being a parameter important for ligand–protein interaction. However, Pajeva and Wiese demonstrated for both a series of phenothiazines and thioxanthenes (81) and for a subset of our propafenone-based library (82) that lipophilicity should also be regarded as a space directed property.

Although, all these QSAR studies give clear individual pictures and yield predictive models, the attempt to define distinct structural features necessary for high P-gp inhibitory activity leads to rather general features. Strong inhibitors are characterized by high lipophilicity (and/or molar refractivity) and possess at least two H-bond acceptors. Other features, such as H-bond donors, may act as additional interaction points. Furthermore, some steric constraints seem to apply in the vicinity of pharmacophoric structures.

This picture has been supported by various pharmacophore modeling studies, most comprehensivly studied by the group of Ekins (83, 84). They used several different training sets, such as inhibitors of digoxin transport, inhibitors of vinblastine binding, inhibitors of vinblastine accumulation, and inhibition of calcein accumulation. Not really surprising, all four models retrieved showed differences both in the number and type of features involved and in the spacial arrangement of these features. A consensus model, which correctly ranked all four data sets, consists of one H-bond acceptor, one aromatic feature, and two hydrophobic features. This further strengthens the hypothesis that toxins might bind to P-gp at different, but overlapping sites. This was also stressed out by Garrigues et al., who calculated the intramolecular distribution of polar and hydrophobic surfaces of a set of structurally diverse P-gp ligands and used the respective fields for superposition of the molecules. This led to the identification of two different, but partially overlapping binding pharmacophores (85).

We used a CATALYST model based on propafenone-type inhibitors for an in silico approach to identify new inhibitors of P-gp. The training set comprised 27 propafenone-type inhibitors of daunorubicin efflux and the model derived included one H-bond acceptor, two aromatic features, one hydrophobic area and one positively charged group. The model was validated with an additional 81 compounds from our in-house data set and subsequently used to screen the World Drug Index. After applying an additional shape filter, 32 structurally diverse hits were retrieved. Nine out of these 32 compounds have already been described as P-gp inhibitors (86). Thus, it is rather likely that the other compounds selected also bind to P-gp.

4.2.5 Structural Aspects of ABC Transporters

ABC-transporters are membrane-spanning proteins, so for a long time there were no X-ray structures available for human transporters. Thus, the publication of the first bacterial homolog structure of a full-length ABC-transporter, the lipid A transporter MsbA from Escherichia coli representing an open conformation (87) immediately gave rise to protein homology modeling attempts. Also the subsequent appearance of MsbA from Vibrio cholerae showing the closed state (88) as well as the structure of MsbA from Salmonella typhimurium, which resembled the posthydrolytic conformation (89) seemed to provide versatile starting points for protein homology modeling of ABCB1 in various states of the catalytic cycle. However, a few years later the structures had to be withdrawn due to errors in data postprocessing (90), which also rendered the hitherto published homology models quite useless. Recently, both the corrected structures of MsbA (91) as well as two structures of a putative multidrug transporter from methicillin resistant Staphylococcus aureus (Sav1866) have been published (92, 93). Especially the structure of Sav1866, which exhibits a quite reasonable resolution (3.0 Å), has been immediately used for the generation of models of ABCB1 and ABCC5 (94-96). The homology model from Globisch et al. was subsequently used for identification of putative binding sites for ligands. The authors were able to visualize multiple binding sites, which are mostly located in the transmembrane region of the model. However, Sav1866 has been crystallized in the posthydrolytic state, which might limit the usability in structure-based drug discovery approaches. We recently presented a Sav1866-based homology model that was refined in a data-driven structural modification approach to fit a vast collection of cross-linking data (97) (Fig. 9).

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Figure 9. Protein homology model of P-glycoprotein in the energized state. (Taken from Ref. 100.)

Very recently, Becker et al. published homology models of ABCB1 in different catalytic states by additionally utilizing the updated MsbA template structures (98). They also performed docking of four different ligands into the nonenergized (nucleotide-free model) state and were able to show that all four ligands exhibit interactions with residues shown to be important. Although these first attempts on structure based modeling of ABCB1-drug interactions seem to be quite promising, it has to be kept in mind that the templates currently show only a small sequence homology in the drug-binding regions (TMDs) and the only nonenergized structure of MsbA currently available does not resemble a full atom model but only represents the Cα-trace in a resolution >5 Å.

However, very recently the group of Geoffrey Chang published the first structure of P-glycoprotein (mouse P-gp) with a resolution of 3.8 Å (99). The apo form shows an internal cavity of approximately 6000 Å3 with a 30 Å separation of the two nucleotide-binding domains. The authors also solved two additional structures with the cyclic peptide inhibitors QZ59-RRR and QZ59-SSS bound to the protein. In both cases, the compounds are sandwiched between TM helices 6 and 12, which have been demonstrated various times as being important for drug binding. Combining now all the structure-based knowledge available, the substrate transport may be modeled as given in Fig. 10. This first structure of P-glycoprotein definitely will remarkably influence the whole field and we are convinced that this will form the basis for subsequent structure-based design studies.

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Figure 10. Proposed substrate translocation pathway for P-glycoprotein. Taken from Ref. 102.

5 Cancer Stem Cells and MDR

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

The important role of “stem cell-like” cancer cells in tumors of the hematopoietic system (like acute myeloid leukemia) has been suspected since the 1950. However, their implication in the emergence of solid tumors became evident only in 2003 (100). According to the cancer stem cell (CSC) hypothesis, a small fraction of cancer cells—the so-called cancer stem cells and vast majority of the so-called “side population” (SP)—has the ability to self-renew and thus is believed to represent the pool of cells of origin that build up a tumor. However, by which factors this self-renewing capacity is determined and how cancer stem cells arise is not yet understood (59). On principle, there are two mechanisms by which pluripotent stem cells in tumors might originate: either they could arise from organ stem cells that undergo malignant transformation or a more differentiated tumor cell acquires self-renewal capacity (101).

The term “side population” refers to the cells that are detected to one side of the majority of cells on a density plot during analysis by flow cytometry. SP cells do not accumulate the fluorescent dyes Hoechst 33342 and rhodamine 123, and thus can be separated from the vast mass of nontumorigenic cancer cells. Even though in the SP compartment there are stem cells and nonstem cells, strong evidence exists that predominantly the CSCs build up the SP. Besides, the SP phenotype—and also normal stem cells—are characterized by high levels of ATP-binding cassette transporters (mainly ABCB1 and ABCG2) that are expressed at the cell surfaces and thus lead to extrusion of the fluorescent dyes mentioned above (59). It seems that none of these transporters is necessary for stem cell growth or maintenance, as knockout mice (who lack the corresponding genes) demonstrated to be viable, fertile, and have normal stem cell compartments (102). However, through the expression of several ABC transporters, CSCs are able to confer resistance to drugs. Besides, they share other properties of normal stem cells: relative quiescence, active DNA-repair capacity, and resistance to apoptosis. All these characteristics are leading to a long lifespan of these cells and they provide evidence for the possibility of a so-called “cancer stem cell model of drug resistance.” In this model, it is supposed that there exists a built-in population of drug-resistant CSCs, which (in contrast to the variably differentiated tumor cells) survive chemotherapy and repopulate the tumor. Alternatively, both compartments, CSCs and the vast mass of tumor cells, might show resistance to chemotherapy in some cases. This type of drug resistance corresponds to what we call “intrinsic resistance” (59).

Future considerations on drug resistance should take into account what we learned about CSCs within the last few years. Especially regarding the design of new drugs for its reversal/evasion, this new concept of how resistance might arise offers new therapeutic opportunities (see Chapter 6).

6 Perspectives for New Strategies to Overcome Drug Resistance

  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References

Nowadays, an ongoing effort in oncology concentrates on the development of novel drugs that target cancer cells in a new manner, and thus probably avoid the emergence of drug resistance. One task is to target key components of the cell-cycle machinery such as polo-like kinase 1 (PLK1) (103) and cyclin dependent kinases (104). An alternative strategy focuses on blocking protein–protein interactions such as the regulation of p53 expression via MDM2/MDMX binding (105). Regarding resistance mediated by P-glycoprotein, a new approach involves the interference with one of the regulatory steps in P-gp expression (ecteinascidin 743 under clinical trial) either than directly blocking the protein (106).

Additionally, it seems useful to reconsider drug application schemes. Especially combination therapies have proven to be useful in many cases. However, the question arises if the sequential application or the upfront administration of a combination of drugs (especially TKIs) under certain circumstances might be more beneficial for treatment outcome and retardation of the resistant phenotype (12).

A quantum leap still has to be surmounted in the fields of cancer diagnosis and the dedication of medical imaging technologies. New predictive biomarkers are urgently needed to classify patients correctly into responder/nonresponder to a special treatment (e.g., with trastuzumab) (107). Furthermore, a genome wide expression profiling could give insights into the regulatory networks that are involved in the acquisition of drug resistance and thus lead to novel treatment strategies (13).

In the field of molecular imaging a step forward has to be made regarding the implementation of technologies such as nuclear magnetic resonance and optical imaging technologies. Thereby, not only the localization of the tumor but also the expression and activity of specific proteins and biological processes (such as apoptosis, and angiogenesis) can be visualized. Thus, information about the tumor behavior or therapy response is obtained (108).

Since cancer stem cells can be isolated from many tissues, purified and propagated, targeted therapies have the potential to be further improved. However, new cancer models are needed where future drugs can be directly tested for their ability to kill CSCs (59). According to the stem cell hypothesis, new strategies should be focused on targeting these CSCs. Novel therapeutic opportunities include dual ABCB1/ABCG2 inhibitors (e.g., tariquidar), antibodies directed against ABC inhibitors, stem cell inhibitors like cyclopamine (targets the Hedgehog-Patched pathway), and immunotherapy (59).


  1. Top of page
  2. Introduction
  3. Overview of Drug Resistance Mechanisms
  4. Targeted Chemotherapy and Resistance
  5. Multiple Drug Resistance
  6. Cancer Stem Cells and MDR
  7. Perspectives for New Strategies to Overcome Drug Resistance
  8. Acknowledgments
  9. References
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