The effective use of cancer chemotherapy requires a thorough understanding of the principles of neoplastic cell growth kinetics, basic pharmacologic mechanisms of drug action, pharmacokinetic and pharmacodynamic variability, and mechanisms of drug resistance. Recent scientific advances in the field of molecular oncology have led to the identification of large numbers of potential targets for novel anticancer therapies. This has resulted in a tremendous expansion of the drug development pipeline, and in the present era, the diversity of clinically useful novel anticancer therapeutic agents is growing at an unprecedented rate. However, the great enthusiasm that surrounds these new agents must be tempered by the challenges they present in optimizing their clinical use and in rationally integrating them with existing anticancer therapies. This discussion focuses on the basic principles underlying the development of modern combination chemotherapy, and it is followed by a description of the major classes of chemotherapeutic drugs and their mechanisms of action.
The cell cycle and tumor growth pattern
The growth pattern of individual neoplastic cells may greatly affect the overall biologic behavior of human tumors and their responses to specific types of cancer therapy. Tumor cells can be subdivided into three general populations: (1) cells that are not dividing and are terminally differentiated; (2) cells that continue to proliferate; and (3) nondividing cells that are currently quiescent but may be recruited into the cell cycle. The kinetic behavior of dividing cells is best described by the concept of the cell cycle.
The cell cycle is composed of four distinct phases during which the cell prepares for and undergoes mitosis. The G1 phase consists of cells that have recently completed division and are committed to continued proliferation. After a variable period, these cells begin to synthesize DNA, marking the beginning of the S phase. After DNA synthesis is complete, the end of the S phase is followed by the premitotic rest interval called the G2 phase. Finally, chromosome condensation occurs and the cells divide during the mitotic M phase. Resting diploid cells that are not actively dividing are described as being in the G0 phase. The transition between cell-cycle phases is strictly regulated by specific signaling proteins; however, these cell-cycle checkpoints may become aberrant in some tumor types.
Some anticancer agents induce their cytotoxic effects during specific phases of the cell cycle. Antimetabolites, such as fluorouracil (5-FU) and methotrexate, are more active against S-phase cells, whereas the vinca alkaloids, epipodophyllotoxins, and taxanes are relatively more M-phase specific. These kinetic properties may have clinically important consequences for cancer chemotherapy. For example, cell-cycle–nonspecific agents, such as the alkylating agents and platinum derivatives, generally have linear dose-response curves (ie, increasing the dose increases cytotoxicity). In contrast, cell-cycle–specific agents will often plateau in their concentration-dependent effects because only a subset of proliferating cells remain fully sensitive to drug-induced cytotoxicity. These cell-cycle–specific agents tend to be schedule dependent, because the only way to increase the total cell kill is by extending the duration of exposure, not by increasing the dose.
In clinical practice, solid tumors typically have low growth fractions and heterogeneous doubling times; as they increase in size, tumors may outgrow their blood and nutrient supply, leading to slower growth rates. In real life, most tumors display a sigmoid-shaped Gompertzian growth pattern in which growth rates decline as tumors expand. The most rapid growth occurs at small tumor volumes, whereas larger tumors may harbor higher numbers of nonproliferating cells, potentially making them less sensitive to agents that selectively target dividing cells. This understanding of tumor growth kinetics has been used to support the development of novel clinical strategies for optimizing cancer chemotherapy. This includes the use of adjuvant chemotherapy to treat small volumes of tumor cells during times of high growth rates and the sequential administration of non–cross-resistant drug combinations.
Principles of combination chemotherapy
Based upon cell kinetic and pharmacologic principles, a set of guidelines for designing modern combination chemotherapy regimens has been derived. Multiagent therapy has three important theoretical advantages over single-agent therapy. First, it can maximize cell kill while minimizing host toxicities by using agents with nonoverlapping dose-limiting toxicities. Second, it may increase the range of drug activity against tumor cells with endogenous resistance to specific types of therapy. Finally, it may also prevent or slow the development of newly resistant tumor cells. Specific principles for selecting agents for use in combination chemotherapy regimens are listed in Table 1.
Definition of response
In clinical studies, formal response criteria have been developed and have gained wide acceptance. The National Cancer Institute (NCI) has proposed and implemented newer standard response criteria called Response Evaluation Criteria in Solid Tumors (RECIST). In contrast, the World Health Organization (WHO) has a different standard for assessing response. Major differences between these guidelines are outlined in Appendix 1.
Drug resistance
Drug resistance to chemotherapy may arise from a variety of different mechanisms, including anatomic, pharmacologic, and genetic processes. Some of the common factors that may broadly affect tumor cell sensitivity to different classes of agents include the failure of drugs to penetrate into specific sanctuary sites, such as the brain and testes, or the development of mutations in the target proteins that render them less sensitive to specific molecular inhibitors. Another factor may be decreased drug accumulation resulting from the increased expression of drug efflux pumps in the cell membrane, such as p-glycoprotein, which is encoded for by the multidrug resistance (MDR-1) gene. This 170-kDa glycoprotein normally removes toxins or xenobiotic metabolites from cells via an energy-dependent process. High levels of MDR-1 expression in tumor cells correlate with resistance to a wide range of cytotoxic agents. Other drug efflux pumps that have been implicated in the development of broad resistance to cancer chemotherapy include the MDR-associated protein (MRP) and breast cancer resistance protein (BCRP).
Pharmacokinetic and pharmacodynamic variability
Variability in clearance
The rational clinical use of cancer chemotherapy requires a thorough understanding of the variability in human response to drug therapy. One of the major goals of the field of clinical pharmacology is to precisely define the processes responsible for this variability in drug action. Pharmacokinetic variability can arise from interindividual differences in drug adsorption, distribution, metabolism, and excretion. All of these processes result in differences in drug delivery to its ultimate site of action. In contrast, pharmacodynamic variability arises from inherent differences in the sensitivity of target tissues to drug effects. Both kinetic and dynamic factors can complicate the treatment of individual cancer patients and must be addressed by the practicing oncologist on a daily basis. Although a formal review of drug pharmacokinetics and pharmacodynamics is not possible here, a brief discussion of the most clinically relevant points is warranted.
The most clinically useful parameter in drug therapy is clearance, because clearance reflects all the processes in the body that contribute to drug elimination. In oncology, the importance of clearance is enhanced because clearance is the only parameter that relates dose to the measured area under the concentration vs time curve (AUC), which is a useful measure of systemic drug exposure. Mathematically, clearance is defined as dose/AUC. Clearance is not a rate of drug elimination; instead it is defined as a volume of drug cleared per unit of time.
Overcoming interindividual variation in clearance is a fundamental goal of pharmacokinetic analyses. Because they tend to be highly toxic with low efficacy, anticancer drugs may have the narrowest therapeutic index of any class of agents used in clinical medicine. Thus, the ability to administer an individualized dose of drug to achieve a uniform target AUC and a uniform clinical result is often a high priority for cancer therapeutics. Because clearance defines the relationship between dose and AUC, estimating clearance prior to anticancer drug administration is extremely important. A common attempt to individualize cancer chemotherapy is to dose a drug based upon the body surface area (BSA) expressed in mg/m2 to achieve a uniform AUC in patients with different body sizes. Inherent in this approach is the fundamental assumption that clearance is strongly correlated with BSA. However, when studied formally, the relationship between clearance and BSA is often weak and does not consistently justify the routine use of this dosing approach. Nonetheless, although the application of BSA-based dosing has been widely criticized, it still remains a common practice.
Recognizing clinical situations in which drug clearance is commonly altered, such as in patients with hepatic or renal dysfunction, is important for agents that are eliminated by these routes. For example, carboplatin is extensively cleared by glomerular filtration, and its systemic AUC in plasma ultrafiltrates is strongly correlated with pharmacodynamic effects, such as thrombocytopenia. Thus, dosing strategies that estimate the glomerular filtration rate (GFR) to achieve a targeted AUC and thereby minimize excessive toxicity in individual patients have gained wide clinical acceptance. Likewise, for hepatically metabolized drugs, doses must be adjusted in patients with liver dysfunction. However, accurately assessing hepatic drug-metabolizing capacity is more difficult than estimating the GFR. Nonetheless, guidelines for dose-adjusting agents metabolized in the liver, such as doxorubicin, have been established.
