Cancer is now one of the leading causes of death in modern industrial nations and is the focus of various applied as well as academic research activities. Any type of cancer is characterized by uncontrolled cellular growth. Aside from a few commonalities, cancer types differ depending on their origin, e.g., liver, brain, or blood. These differences manifest themselves in the form of changes in the coding (= sequence) of the genetic material, also called DNA. Differences in the makeup of the genetic material result eventually in a different set of proteins (and RNA) regulating all kinds of cellular activities. Therefore cells of a certain cancer type are not only different from their normal, healthy counterparts but can also differ slightly but in important ways with respect to successful treatment from one individual cancer to the next of the same cell type. Today cancer researchers focus on understanding the molecular differences among patients as an important first step to guide therapy more effectively to individual patients and to understand why certain patients with the same cancer type respond to a given treatment and others do not.
With new technologies available and together with modern IT-capacities, it has become possible to analyze the genetic material of a large number of individual tumor samples. In the long run, the identification of specific changes in the genetic makeup of an individual patient should allow for the development and application of new treatment therapies.
Major challenges for achieving this goal are to produce reliable molecular data and to combine those with the patients’ individual clinical background. Cancer tissues that provide the basis for molecular analysis are highly sensitive to external factors such as drugs or the collection procedures during and after surgical tumor removal. INDIVUMED’s mission is the build-up of a tumor tissue bank by using standardized protocols for the collection and processing of the tumor material donated by an individual cancer patient, so that such factors can be reduced and so that the tissues and samples come as close as possible to reflecting molecular reality.