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

Show simple item record

dc.contributor.author White, Brian S.
dc.contributor.author Khan, Suleiman A.
dc.contributor.author Mason, Mike J.
dc.contributor.author Ammad-ud-din, Muhammad
dc.contributor.author Potdar, Swapnil
dc.contributor.author Malani, Disha
dc.contributor.author Kuusanmäki, Heikki
dc.contributor.author Druker, Brian J.
dc.contributor.author Heckman, Caroline
dc.contributor.author Kallioniemi, Olli
dc.contributor.author Kurtz, Stephen E.
dc.contributor.author Porkka, Kimmo
dc.contributor.author Tognon, Cristina E.
dc.contributor.author Tyner, Jeffrey W.
dc.contributor.author Aittokallio, Tero
dc.contributor.author Wennerberg, Krister
dc.contributor.author Guinney, Justin
dc.date.accessioned 2021-09-16T12:39:01Z
dc.date.available 2021-09-16T12:39:01Z
dc.date.issued 2021-07-23
dc.identifier.citation White , B S , Khan , S A , Mason , M J , Ammad-ud-din , M , Potdar , S , Malani , D , Kuusanmäki , H , Druker , B J , Heckman , C , Kallioniemi , O , Kurtz , S E , Porkka , K , Tognon , C E , Tyner , J W , Aittokallio , T , Wennerberg , K & Guinney , J 2021 , ' Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia ' , npj precision oncology , vol. 5 , no. 1 , 71 . https://doi.org/10.1038/s41698-021-00209-9
dc.identifier.other PURE: 168513593
dc.identifier.other PURE UUID: db234079-9015-4e2f-81a1-e9ae43a4e5a0
dc.identifier.other WOS: 000679835700001
dc.identifier.other ORCID: /0000-0002-0886-9769/work/100083582
dc.identifier.other ORCID: /0000-0002-2778-6918/work/100085082
dc.identifier.other ORCID: /0000-0003-4112-5902/work/100085098
dc.identifier.uri http://hdl.handle.net/10138/334423
dc.description.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. en
dc.format.extent 11
dc.language.iso eng
dc.relation.ispartof npj precision oncology
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject DRUG RESPONSE CONSISTENCY
dc.subject R PACKAGE
dc.subject CANCER
dc.subject SENSITIVITY
dc.subject APOPTOSIS
dc.subject CELLS
dc.subject REGULARIZATION
dc.subject IDENTIFICATION
dc.subject INDUCTION
dc.subject MECHANISM
dc.subject 3122 Cancers
dc.title Bayesian multi-source regression and monocyte-associated gene expression predict BCL-2 inhibitor resistance in acute myeloid leukemia en
dc.type Article
dc.contributor.organization Institute for Molecular Medicine Finland
dc.contributor.organization Precision Systems Medicine
dc.contributor.organization HUS Comprehensive Cancer Center
dc.contributor.organization Department of Medicine
dc.contributor.organization Digital Precision Cancer Medicine (iCAN)
dc.contributor.organization Helsinki Institute for Information Technology
dc.contributor.organization Tero Aittokallio / Principal Investigator
dc.contributor.organization Bioinformatics
dc.contributor.organization Krister Wennerberg / Principal Investigator
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1038/s41698-021-00209-9
dc.relation.issn 2397-768X
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

Files in this item

Total number of downloads: Loading...

Files Size Format View
s41698_021_00209_9.pdf 1.926Mb PDF View/Open

This item appears in the following Collection(s)

Show simple item record