Sub-typing in oncology has led to a substantial improvement in diagnosis and treatment of many forms of cancer such as breast cancer. Disease characterization in general and cancer diagnosis in particular still suffers from a sometimes-impeding classification based on body localization or mere list of symptoms. The utilization of multiomics data enables researchers to discern the underlying biology of diseases in line with the module system and allows for a more correct classification of different cancer indications based on their molecular signature.
The sub-typing on these modules and signatures not only allows to group different organ origins together (e.g. CRC and NSCLC sub-types), it plays a major role in identifying drugs that target specifically the inherent mechanisms. Altogether, the utilization of a small number of highly specific biomarkers enables the identification of patient groups that highly benefits from certain drugs. Development of new drugs for such molecular modules and signatures is only partially necessary as already approved drugs might potentially target exactly those mechanisms and protein structures.
Although sub-typing in cancer research holds great promise, it still has a long way to go before becoming routine practice. Examples from classically repurposed drugs (such as simvastatin and metformin) as well as lesser-known candidates (such as captopril, pioglitazone and isotretionin) will be given to illustrate the vast potential of this approach.