Metabolic Profiles: Novel Strategy May Reduce Risk of Chemotherapy Adverse Effects

Publication
Article
Oncology Live®October 2011
Volume 12
Issue 10

One of the more unique aspects of cancer chemotherapy is the relatively frequent development of serious, even severe, adverse effects.

Maurie Markman, MD

Maurie Markman, MD

Editor-in-Chief of OncologyLive

Senior vice president for Clinical Affairs and National Director for Medical Oncology Cancer Treatment Centers of America, Eastern Regional Medical Center

One of the more unique aspects of cancer chemotherapy, compared with all other areas of medicine where pharmaceutical agents are routinely employed, is the relatively frequent development of serious, even severe, adverse effects. While the toxicities of antineoplastics are generally manageable, administering these drugs in the population of cancer patients can result in a significant negative impact on the quality of life and, fortunately far less commonly, a fatal outcome.

A variety of strategies have been employed to predict and prevent treatment-related side effects, such as modifications of dose based on body size, weight, renal function, age, and prior exposure to chemotherapy or radiation. Unfortunately, for many anticancer agents these efforts achieve only a modest degree of success. This is especially a concern when the risk of toxicity is not highly predictably dose-related.

Particularly problematic are anticancer drugs whose risk of clinically relevant adverse events is known or suspected to be strongly influenced by a variety of host factors responsible for the agent’s metabolism. The impact of these often poorly defined factors may be substantial, and result in a major effect on both the overall efficacy of treatment and the quality of life for the patient during and following the course of therapy.

Pretreatment knowledge of an individual’s unique metabolic profile (ie, pharmacometabonomics) may permit modification of drug dosing or even suggest that a specific agent should not be utilized in this patient, a question that is particularly relevant if an alternative therapeutic option exists. While this provocative concept has been utilized to a limited extent outside the cancer arena,1 one can quite appropriately argue that conceptually this strategy should have great appeal with cytotoxic chemotherapy due to the potential for serious adverse events.

A recently reported study that examined the relationship between a pretreatment metabolic profile and the subsequent toxicity following the administration of single-agent capecitabine in a group of patients with colon cancer (locally advanced or metastatic inoperable disease) provides important support for this perspective.2 Patients included in this analysis received a fixed dose of capecitabine (2000 mg twice daily). The serum from a total of 54 individuals included in this report underwent 1H NMR spectroscopy to evaluate for a patient-specific metabolic profile (eg, lipoprotein content, polyunsaturated fatty acids, choline phospholipids).

A patient’s pretreatment metabolic profile may serve as a personalized approach to predicting toxicities in cytotoxic and, eventually, other forms of therapy.

Of considerable potential interest, the investigators found a greater risk of capecitabine-associated toxicity in the population of patients with the highest levels of low-density lipoprotein-derived lipids. Further, a specific “pharmacometabonomic lipid profile” that could predict the risk was defined.

The investigators postulated that one important feature of individual patient-based metabolic evaluations is that they should enable clinicians to examine the specific status of the host’s ability to metabolize the antineoplastic agent precisely at the time when the drug is being administered. It is likely that this measured profile will be influenced by a number of features including the functional state of the liver (with or without metastatic disease at this site), the presence and severity of cancer cachexia, and the impact of malignancy-related proinflammatory cytokines. In addition, the metabolic profile combines the effects of both intrinsic genetic and external environmental factors.

It will be important for this experience to be confirmed by other investigative groups, hopefully with larger sample sizes. But assuming future research supports these conclusions, it is reasonable to propose that at some future time the optimal utilization of capecitabine may be at least partially based on an examination of the serum metabolic profile of individual cancer patients. Further, it is reasonable to speculate that such data will be relevant for other antineoplastic agents, and particularly those whose biological/ clinical activity and toxicity are known to be related to its metabolic fate following administration.

References

  1. Winnike JH, Li Z, Wright FA, MacDonald JM, O’Connell TM, Watkins PB. Use of pharmaco-metabonomics for early prediction of acetaminophen-induced hepatotoxicity in humans. Clin Pharmacol Ther. 2010;88(1):45-51.
  2. Backshall A, Sharma R, Clarke SJ, Keun HC. Pharmacometabonomic profi ling as a predictor of toxicity in patients with inoperable colorectal cancer treated with capecitabine. Clin Cancer Res. 2011;17(9):3019-3028.

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