Cancer Immunomics in the Age of Information: Role in Diagnostics and Beyond

Abstract

Cancer genome sequencing is useful for diagnosis and personalized treatment. Analysis of the sequencing data involves integration of computation, statistics and system biology methods. The amalgam of such methods which help study interaction of cancer cells with immune system, harnessing immune system for cancer therapy or its prevention through vaccines has led to the foundation of cancer immunomics. It is, therefore, a combinatorial science which merges diverse techniques from genomics and proteomics for diagnosis and drug design/treatment. There has been a gradual increase in establishment of cancer immune focused start-ups, research facilities and pharma giants working on state-of-the-art methods for improving diagnostics, treatment and prevention or minimizing side effects, applying immunomics. However, we are still far away from making precise, quick and reliable diagnostic and treatment predictions. We need decision support systems to facilitate diagnosis, tumor evaluation prediction and assessment of individual profile for making personalized therapy a reality. The future is centered not only on data management but wise decision aided by artificially intelligent algorithms. In this review, we provide an overall picture and focus on immune biomarkers and relevant softwares that aid in diagnostics and analysis of cancer.