한빛사논문
- 조회386
Chansub Lee1,2†, Sungyoung Lee3,4†, Eunchae Park1,2, Junshik Hong1,2,5, Dong‑Yeop Shin1,2,5, Ja Min Byun1,2,5, Hongseok Yun3,4*, Youngil Koh1,2,5* and Sung‑Soo Yoon1,2,5*
1Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea. 2Center for Medical Innovation, Seoul National Uni‑versity Hospital, Seoul, Republic of Korea. 3Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea. 4Center for Preci‑sion Medicine, Seoul National University Hospital, Seoul, Republic of Korea. 5Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
†Chansub Lee and Sungyoung Lee contributed equally to this work.
*Correspondence
Abstract
Background
Although anti-apoptotic proteins of the B-cell lymphoma-2 (BCL2) family have been utilized as therapeutic targets in acute myeloid leukaemia (AML), their complicated regulatory networks make individualized therapy difficult. This study aimed to discover the transcriptional signatures of BCL2 family genes that reflect regulatory dynamics, which can guide individualized therapeutic strategies.
Methods
From three AML RNA-seq cohorts (BeatAML, LeuceGene, and TCGA; n = 451, 437, and 179, respectively), we constructed the BCL2 family signatures (BFSigs) by applying an innovative gene-set selection method reflecting biological knowledge followed by non-negative matrix factorization (NMF). To demonstrate the significance of the BFSigs, we conducted modelling to predict response to BCL2 family inhibitors, clustering, and functional enrichment analysis. Cross-platform validity of BFSigs was also confirmed using NanoString technology in a separate cohort of 47 patients.
Results
We established BFSigs labeled as the BCL2, MCL1/BCL2, and BFL1/MCL1 signatures that identify key anti-apoptotic proteins. Unsupervised clustering based on BFSig information consistently classified AML patients into three robust subtypes across different AML cohorts, implying the existence of biological entities revealed by the BFSig approach. Interestingly, each subtype has distinct enrichment patterns of major cancer pathways, including MAPK and mTORC1, which propose subtype-specific combination treatment with apoptosis modulating drugs. The BFSig-based classifier also predicted response to venetoclax with remarkable performance (area under the ROC curve, AUROC = 0.874), which was well-validated in an independent cohort (AUROC = 0.950). Lastly, we successfully confirmed the validity of BFSigs using NanoString technology.
Conclusions
This study proposes BFSigs as a biomarker for the effective selection of apoptosis targeting treatments and cancer pathways to co-target in AML.
논문정보
- Research article
- 2022년 09월 (BRIC 등록일 2022-10-11)
- 국내 연구진
- 의약학 > 유전 및 유전체의학
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