University of Oulu

Mäkinen V-P, Rehn J, Breen J, Yeung D, White DL. Multi-Cohort Transcriptomic Subtyping of B-Cell Acute Lymphoblastic Leukemia. International Journal of Molecular Sciences. 2022; 23(9):4574. https://doi.org/10.3390/ijms23094574

Multi-cohort transcriptomic subtyping of B-cell acute lymphoblastic leukemia

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Author: Mäkinen, Ville-Petteri1,2,3,4; Rehn, Jacqueline5,6; Breen, James6,7,8;
Organizations: 1Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
2Australian Centre for Precision Health, UniSA Clinical & Health Sciences, University of South Australia, Adelaide, SA 5000, Australia
3Computational Medicine, Faculty of Medicine, University of Oulu, FI-90014 Oulu, Finland
4Center for Life Course Health Research, Faculty of Medicine, University of Oulu, FI-90014 Oulu, Finland
5Blood Cancer Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
6Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA 5005, Australia
7South Australian Genomics Centre, South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
8Robinson Research Institute, University of Adelaide, Adelaide, SA 5005, Australia
9Australian and New Zealand Children’s Oncology Group, Clayton, VIC 3168, Australia
10Department of Haematology, Royal Adelaide Hospital and SA Pathology, Adelaide, SA 5000, Australia
11Faculty of Sciences, University of Adelaide, Adelaide, SA 5005, Australia
12Australian Genomics Health Alliance, Parkville, VIC 3052, Australia
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022090757752
Language: English
Published: Multidisciplinary Digital Publishing Institute, 2022
Publish Date: 2022-09-07
Description:

Abstract

RNA sequencing provides a snapshot of the functional consequences of genomic lesions that drive acute lymphoblastic leukemia (ALL). The aims of this study were to elucidate diagnostic associations (via machine learning) between mRNA-seq profiles, independently verify ALL lesions and develop easy-to-interpret transcriptome-wide biomarkers for ALL subtyping in the clinical setting. A training dataset of 1279 ALL patients from six North American cohorts was used for developing machine learning models. Results were validated in 767 patients from Australia with a quality control dataset across 31 tissues from 1160 non-ALL donors. A novel batch correction method was introduced and applied to adjust for cohort differences. Out of 18,503 genes with usable expression, 11,830 (64%) were confounded by cohort effects and excluded. Six ALL subtypes (ETV6::RUNX1, KMT2A, DUX4, PAX5 P80R, TCF3::PBX1, ZNF384) that covered 32% of patients were robustly detected by mRNA-seq (positive predictive value ≥ 87%). Five other frequent subtypes (CRLF2, hypodiploid, hyperdiploid, PAX5 alterations and Ph-positive) were distinguishable in 40% of patients at lower accuracy (52% ≤ positive predictive value ≤ 73%). Based on these findings, we introduce the Allspice R package to predict ALL subtypes and driver genes from unadjusted mRNA-seq read counts as encountered in real-world settings. Two examples of Allspice applied to previously unseen ALL patient samples with atypical lesions are included.

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Series: International journal of molecular sciences
ISSN: 1661-6596
ISSN-E: 1422-0067
ISSN-L: 1661-6596
Volume: 23
Issue: 9
Article number: 4574
DOI: 10.3390/ijms23094574
OADOI: https://oadoi.org/10.3390/ijms23094574
Type of Publication: A1 Journal article – refereed
Field of Science: 3111 Biomedicine
3122 Cancers
Subjects:
Funding: D.L.W. was funded by the National Health and Medical Research Council of Australia Target Call for Research (APP1160833) and by Cancer Council SA Beat Cancer Project Principal Cancer Research Fellowship (PRF1618). The work was also supported by the Australasian Leukaemia and Lymphoma Group and Australian and New Zealand Children’s Haematology/Oncology Group.
Copyright information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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