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Background  Precision oncology seeks to integrate multiple layers of data from a patient’s cancer to effectively tailor therapy. Conventional chemotherapies are sometimes effective but accompanied by adverse events, warranting the identification of a biomarker of chemosensitivity.    Objective  Identify an mRNA biomarker that predicts chemosensitivity across solid tumor subtypes.    Methods  We performed a pan-solid tumor analysis integrating gene expression and drug sensitivity profiles from 3 cancer cell line datasets to identify transcripts correlated with sensitivity to a panel of chemotherapeutics. We then tested the ability of an mRNA biomarker to predictive clinical outcomes in cohorts of patients with breast, lung, or ovarian cancer.    Results  Expression levels of several mRNA transcripts were significantly correlated with sensitivity or resistance chemotherapeutics in cancer cell line datasets. The only mRNA transcript significantly correlated with sensitization to multiple classes of DNA-damaging chemotherapeutics in all 3 cell line datasets was encoded by  Schlafen Family Member 11  ( SLFN11 ). Analyses of multiple breast, lung, and ovarian cancer patient cohorts treated with chemotherapy confirmed  SLFN11  mRNA expression as a predictive biomarker of longer overall survival and improved tumor response.    Conclusions  Tumor  SLFN11  mRNA expression is a biomarker of sensitivity to an array of DNA-damaging chemotherapeutics across solid tumor subtypes.

plos one

Integrated pan-cancer gene expression and drug sensitivity analysis reveals SLFN11 mRNA as a solid tumor biomarker predictive of sensitivity to DNA-damaging chemotherapy