American Association for Cancer Research
00085472can182970-sup-209119_2_supp_5410150_psmk9h.xlsx (38.86 kB)

Table S2 from Hemap: An Interactive Online Resource for Characterizing Molecular Phenotypes across Hematologic Malignancies

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posted on 2023-03-31, 01:43 authored by Petri Pölönen, Juha Mehtonen, Jake Lin, Thomas Liuksiala, Sergei Häyrynen, Susanna Teppo, Artturi Mäkinen, Ashwini Kumar, Disha Malani, Virva Pohjolainen, Kimmo Porkka, Caroline A. Heckman, Patrick May, Ville Hautamäki, Kirsi J. Granberg, Olli Lohi, Matti Nykter, Merja Heinäniemi

Summary of data


Academy of Finland

Finnish Cultural Foundation

Sigrid Juselius Foundation

Cancer Society of Finland

Paulo Foundation

Foundation for Pediatric Research

Jane and Aatos Erkko Foundation

Nokia Foundation

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 chronic lymphocytic leukemia, and supported CDK6 as a disease-specific target in acute myeloid leukemia. 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. This study describes a data resource for researching derailed cellular pathways and candidate drug targets across hematologic malignancies.

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