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A Personalized Approach to Cancer Treatment: How Biomarkers Can Help

¹ Department of Pathology and Laboratory Medicine and ² Department of Medical Oncology, St Vincent’s University Hospital, Dublin; ³ UCD School of Medicine and Medical Science, Conway Institute of Biomolecular and Biomedical Research, University College Dublin and Dublin Molecular Medicine Institute, Dublin, Ireland.

^aAddress correspondence to this author at: Department of Nuclear Medicine, St Vincent’s University Hospital, Elm Park, Dublin 4, Ireland. Fax 353–1-2696018; e-mail Michael.J.Duffy{at}ucd.ie.

Background: The present approach to cancer treatment is often referred to as "trial and error" or "one size fits all." This practice is inefficient and frequently results in inappropriate therapy and treatment-related toxicity. In contrast, personalized treatment has the potential to increase efficacy and decrease toxicity.

Content: We reviewed the literature relevant to prognostic, predictive, and toxicity-related markers in cancer, with particular attention to systematic reviews, prospective randomized trials, and guidelines issued by expert panels. To achieve personalized treatment for cancer, we need markers for determining prognosis, predicting response to therapy, and predicting severe toxicity related to treatment. Among the best-validated prognostic markers currently available are serum concentrations of -fetoprotein (AFP), human chorionic gonadotropin (hCG), and lactate dehydrogenase (LDH) for patients with nonseminoma germ cell tumors and tissue concentrations of both urokinase plasminogen activator and plasminogen activator inhibitor 1 (PAI-1) for breast cancer patients. Clinically useful therapy predictive markers are estrogen and progesterone receptors to select patients with breast cancer for treatment with endocrine therapy and human epidermal growth factor receptor 2 (HER-2) to select breast cancer patients for treatment with trastuzumab (Herceptin). Markers available for identifying drug-induced adverse reactions include thiopurine methyltransferase (TPMT) to predict toxicity from thiopurines in the treatment of acute lymphoblastic leukemia and uridine diphosphate glucuronyltransferase to predict toxicity from irinotecan in the treatment of colorectal cancer.

Conclusions: Validated prognostic, predictive, and toxicity markers should help cancer treatment move from the current trial-and-error approach to more personalized treatment.

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