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Cao, X.* ; Huber, S.* ; Ahari, A.J.* ; Traube, F.R.* ; Seifert, M.* ; Oakes, C.C.* ; Secheyko, P.* ; Vilov, S. ; Scheller, I.F. ; Wagner, N.* ; Yépez, V.A.* ; Blombery, P.* ; Haferlach, T.* ; Heinig, M. ; Wachutka, L.* ; Hutter, S.* ; Gagneur, J.

Analysis of 3760 hematologic malignancies reveals rare transcriptomic aberrations of driver genes.

Genome Med. 16:70 (2024)
Postprint DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
BACKGROUND: Rare oncogenic driver events, particularly affecting the expression or splicing of driver genes, are suspected to substantially contribute to the large heterogeneity of hematologic malignancies. However, their identification remains challenging. METHODS: To address this issue, we generated the largest dataset to date of matched whole genome sequencing and total RNA sequencing of hematologic malignancies from 3760 patients spanning 24 disease entities. Taking advantage of our dataset size, we focused on discovering rare regulatory aberrations. Therefore, we called expression and splicing outliers using an extension of the workflow DROP (Detection of RNA Outliers Pipeline) and AbSplice, a variant effect predictor that identifies genetic variants causing aberrant splicing. We next trained a machine learning model integrating these results to prioritize new candidate disease-specific driver genes. RESULTS: We found a median of seven expression outlier genes, two splicing outlier genes, and two rare splice-affecting variants per sample. Each category showed significant enrichment for already well-characterized driver genes, with odds ratios exceeding three among genes called in more than five samples. On held-out data, our integrative modeling significantly outperformed modeling based solely on genomic data and revealed promising novel candidate driver genes. Remarkably, we found a truncated form of the low density lipoprotein receptor LRP1B transcript to be aberrantly overexpressed in about half of hairy cell leukemia variant (HCL-V) samples and, to a lesser extent, in closely related B-cell neoplasms. This observation, which was confirmed in an independent cohort, suggests LRP1B as a novel marker for a HCL-V subclass and a yet unreported functional role of LRP1B within these rare entities. CONCLUSIONS: Altogether, our census of expression and splicing outliers for 24 hematologic malignancy entities and the companion computational workflow constitute unique resources to deepen our understanding of rare oncogenic events in hematologic cancers.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Lrp1b ; Aberrant Expression ; Aberrant Splicing ; Driver Gene Prediction ; Hairy Cell Leukemia Variant (hcl-v); Health-organization Classification; Myeloid-leukemia Aml; 5th Edition; Cancer; Expression; Mutations; Chemotherapy; Selection; Patterns; Search
ISSN (print) / ISBN 1756-994X
e-ISSN 1756-994X
Journal Genome Medicine
Quellenangaben Volume: 16, Issue: 1, Pages: , Article Number: 70 Supplement: ,
Publisher BioMed Central
Publishing Place Campus, 4 Crinan St, London N1 9xw, England
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Grants Bundesministerium fr Bildung und Forschung