A1 Journal article – refereed

Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia




List of Authors: White BS, Khan SA, Mason MJ, Ammad-ud-din M, Potdar S, Malani D, Kuusanmäki H, Druker BJ, Heckman C, Kallioniemi O, Kurtz SE, Porkka K, Tognon CE, Tyner JW, Aittokallio T, Wennerberg K, Guinney J

Publisher: NATURE RESEARCH

Publication year: 2021

Journal: npj Precision Oncology

Journal name in source: NPJ PRECISION ONCOLOGY

Journal acronym: NPJ PRECIS ONCOL

Volume number: 5

Number of pages: 11

eISSN: 2397-768X

DOI: http://dx.doi.org/10.1038/s41698-021-00209-9


Abstract
The FDA recently approved eight targeted therapies for acute myeloid leukemia (AML), including the BCL-2 inhibitor venetoclax. Maximizing efficacy of these treatments requires refining patient selection. To this end, we analyzed two recent AML studies profiling the gene expression and ex vivo drug response of primary patient samples. We find that ex vivo samples often exhibit a general sensitivity to (any) drug exposure, independent of drug target. We observe that this "general response across drugs" (GRD) is associated with FLT3-ITD mutations, clinical response to standard induction chemotherapy, and overall survival. Further, incorporating GRD into expression-based regression models trained on one of the studies improved their performance in predicting ex vivo response in the second study, thus signifying its relevance to precision oncology efforts. We find that venetoclax response is independent of GRD but instead show that it is linked to expression of monocyte-associated genes by developing and applying a multi-source Bayesian regression approach. The method shares information across studies to robustly identify biomarkers of drug response and is broadly applicable in integrative analyses.

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Last updated on 2021-16-09 at 09:27