Irina Ostrovnaya

The paper proposes a weighted estimation method to correct for imperfect mutation detection in tumor sequencing due to intra-tumor heterogeneity, reducing bias and type I error.

The paper develops and validates a clinicogenomic risk model to predict second primary cancers in cancer survivors using genetic, clinical, and lifestyle factors.

This study identifies BET inhibitors as effective against GI transcriptome-positive CRPC by targeting HNF1A and HNF4G, improving outcomes in preclinical models.

This paper introduces a pooled sequencing strategy to address intratumoral genetic heterogeneity in cancer, showing it improves mutation detection and risk stratification while reducing costs.

The paper identifies clear cell renal cell carcinoma as highly infiltrated by T-cells and finds three clinically relevant clusters associated with survival outcomes.