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Cancer Res. 2019 Apr 2. pii: canres.2970.2018. doi: 10.1158/0008-5472.CAN-18-2970. [Epub ahead of print]

Hemap: An interactive online resource for characterizing molecular phenotypes across hematologic malignancies.

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The Institute of Biomedicine, University of Eastern Finland.
Institute of Biomedicine, University of Eastern Finland.
Faculty of Medicine and Health Technology, Tampere University.
Pathology, Fimlab Laboratories, Tampere University Hospital.
Institute for Molecular Medicine Finland FIMM, University of Helsinki.
Faculty of Medicine, Institute for Molecular Medicine Finland.
Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Central Hospital Cancer Center.
LCSB, University of Luxembourg.
University of Eastern Finland.
Faculty of Medicine and Medical Technology, Tampere University.
Faculty of Medicine and Health Technology, Tampere University
Institute of Biomedicine, School of Medicine, University of Eastern Finland.


Large collections of genome-wide data can facilitate the characterization of disease states and subtypes, permitting pan-cancer analysis of molecular phenotypes and evaluation of disease context for new therapeutic approaches. We analyzed 9,544 transcriptomes from more than 30 hematologic malignancies, normal blood cell types, and cell lines, and showed that disease types could be stratified in a data-driven manner. We then identified cluster-specific pathway activity, new biomarkers and in silico drug target prioritization through interrogation of drug target databases. Using known vulnerabilities and available drug screens, we highlighted the importance of integrating molecular phenotype with drug target expression for in silico prediction of drug responsiveness. Our analysis implicated BCL2 expression level as an important indicator of venetoclax responsiveness and provided a rationale for its targeting in specific leukemia subtypes and multiple myeloma, linked several polycomb group proteins that could be targeted by small molecules (SFMBT1, CBX7 and EZH1) with CLL, and supported CDK6 as a disease-specific target in AML. Through integration with proteomics data, we characterized target protein expression for pre-B leukemia immunotherapy candidates, including DPEP1. These molecular data can be explored using our publicly available interactive resource, Hemap, for expediting therapeutic innovations in hematologic malignancies.

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