Translational pathology of neoplasia.

With the increasing use of individualized medical care (personalized medicine) in treating and managing patients with cancer, the utilization of biomarkers in selecting and tailoring such medical approaches also is increasing and becoming more important. Specifically, many therapies are effective against only a subgroup of a specific type of tumors and exposing patients with different non-responsive subgroups of the same tumor to ineffective therapies, not only exposes these patients needlessly to acute and chronic side effects of the therapy, but also adds to the costs of medical care. For example, the Oncotype Dx test for estrogen receptor positive tumors that are node negative has been used to identify low risk tumors for which surgery alone is an adequate therapy. Biomarkers may be used to aid in multiple aspects of medical care related to cancer, including early detection, diagnosis, risk assessment, as well as in predicting the aggressiveness of cancers (i.e., prognosis) and predicting the therapeutic efficacy of treatments (i.e., prediction). Biomarkers may be also used as surrogate endpoints to aid in evaluating therapies and preventive approaches. Types of biomarkers vary greatly and include histopathologic appearance, stage of the lesion, quantitative morphologic features, size of the lesion, metastatic pattern and extent of metastasis, as well as imaging and molecular features. The types of measurements of biomarkers also vary; for example, molecular features can be measured at the DNA, mRNA or protein levels as well as at regulatory levels (e.g., microRNA). The usefulness of each biomarker is limited by its sensitivity and specificity in fulfilling its role (e.g., in early detection) and the requirements of sensitivity and specificity to accomplish specific tasks are affected by multiple variables. For example, both very high specificity and sensitivity of a test are required to screen a population with a low prevalence of a specific tumor. The goal of this manuscript is to introduce the reader to how biomarkers may be used and the limitations on the uses of biomarkers in translational research.