Utilizing the molecular gateway: the path to personalized cancer management

Abstract

Background: Personalized medicine is the provision of focused prevention, detection, prognostic, and therapeutic efforts according to an individual's genetic composition. The actualization of personalized medicine will require combining a patient's conventional clinical data with bioinformatics-based molecular-assessment profiles. This synergistic approach offers tangible benefits, such as heightened specificity in the molecular classification of cancer subtypes, improved prognostic accuracy, targeted development of new therapies, novel applications for old therapies, and tailored selection and delivery of chemotherapeutics.

Content: Our ability to personalize cancer management is rapidly expanding through biotechnological advances in the postgenomic era. The platforms of genomics, proteomics, single-nucleotide polymorphism profiling and haplotype mapping, high-throughput genomic sequencing, and pharmacogenomics constitute the mechanisms for the molecular assessment of a patient's tumor. The complementary data derived during these assessments is processed through bioinformatics analysis to offer unique insights for linking expression profiles to disease detection, tumor response to chemotherapy, and patient survival. Together, these approaches permit improved physician capacity to assess risk, target therapies, and tailor a chemotherapeutic treatment course.

Summary: Personalized medicine is poised for rapid growth as the insights provided by new bioinformatics models are integrated with current procedures for assessing and treating cancer patients. Integration of these biological platforms will require refinement of tissue-processing and analysis techniques, particularly in clinical pathology, to overcome obstacles in customizing our ability to treat cancer.

Fig. 1. Pathways in personalized cancer management

Cancer management is personalized by integrating synergistic molecular-assessment methods with conventional methods of clinical practice. In a prediagnostic setting, combining current knowledge of environmental factors with available screens for heritable cancer-inducing genetic mutations allows physicians an opportunity to modify preventive and monitoring guidelines. The onset of malignant transformation signals a transition from passive to active treatment in order to curtail an increase in disease burden. After diagnosis, the patient’s clinical data are combined with molecular-expression profile data for the tumor, and the data are analyzed with bioinformatics methods that draw upon archival expression data from external databases. This collaborative effort tailors cancer treatment by means of increased accuracy of risk assessment and improved methods so that therapies targeted to specific molecular dysregulations can be selected. Most importantly, the iterative nature of this approach to therapeutic assessment offers a continuous opportunity for physicians to reanalyze risk and select additional therapies to adapt to a patient’s changing molecular profile.