Predictive Immunological Markers in Oncology

Most treatment decisions in oncology are still based on histomorphological criteria, criteria that are incorporated in actual staging systems. With just a few exceptions (i.e., leukemias, some lymphomas, GIST, NSCLC, etc.) molecular and immunological characteristics of individual tumors do not contribute to this process. The basis for clinical considerations and treatment indications are clinical trials. In these clinical trials, a specific treatment is associated with a statistical outcome for the entire patient population treated in this trial. Not surprisingly, a subgroup of patients does not benefit from the administered treatment and no biomarker to identify these patient subpopulations have been found. So treatment recommendations are typically given as recommendations for all patients with comparable disease situations. As an example, we treat patients with adjuvant chemotherapy knowing that a small minority, far less than 20% of all treated patients, benefits from such adjuvant treatments. The vast majority experiences only treatment related side effects. In parallel, this approach produces enormous costs for our health care system. In advanced disease situations, treatments leading to objective response rates of 30% and higher are considered to be effective treatments. Still, the majority of patients does not benefit and experiences treatment related side effects compromising their quality of life.