Signature-based Chemogram

Gene expression signatures predictive of chemotherapeutic response have the potential to greatly extend the reach of precision medicine by allowing medical providers to plan treatment regimens on an individual basis. Most published gene signatures are only capable of predicting response for individual drugs, but currently, a majority of chemotherapy regimens utilize combinations of different agents. Further, cancer patients with advanced disease may not always have clearly defined or reliably effective chemotherapy regimens. We propose a unified framework, called the chemogram (named for its similarity in approach to antibiograms), that uses predictive gene signatures (see signature extraction paper linked above) to rank the predicted sensitivity of different drugs in any given individual. Using this approach, providers could efficiently screen against many therapeutics to identify the drugs that would fit best into a patient’s treatment plan at any given time. This can be easily reassessed at any point in time if treatment efficacy begins to decline due to therapeutic resistance.