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Clonal gene signatures predict prognosis in mesothelioma and lung adenocarcinoma

Authors :
Yupei Lin
Bryan M. Burt
Hyun-Sung Lee
Thinh T. Nguyen
Hee-Jin Jang
Claire Lee
Wei Hong
Robert Taylor Ripley
Christopher I. Amos
Chao Cheng
Source :
npj Precision Oncology, Vol 8, Iss 1, Pp 1-10 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract Malignant pleural mesothelioma (MPM) is a rare but lethal pleural cancer with high intratumor heterogeneity (ITH). A recent study in lung adenocarcinoma has developed a clonal gene signature (ORACLE) from multiregional transcriptomic data and demonstrated high prognostic values and reproducibility. However, such a strategy has not been tested in other types of cancer with high ITH. We aimed to identify biomarkers from multi-regional data to prognostically stratify MPM patients. We generated a multiregional RNA-seq dataset for 78 tumor samples obtained from 26 MPM patients, each with one sample collected from a superior, lateral, and inferior region of the tumor. By integrating this dataset with the Cancer Genome Atlas MPM RNA-seq data, we selected 29 prognostic genes displaying high variability across different tumors but low ITH, which named PRACME (Prognostic Risk Associated Clonal Mesothelioma Expression). We evaluated PRACME in two independent MPM datasets and demonstrated its prognostic values. Patients with high signature scores are associated with poor prognosis after adjusting established clinical factors. Interestingly, the PRACME and the ORACLE signatures defined respectively from MPM and lung adenocarcinoma cross-predict prognosis between the two cancer types. Further investigation indicated that the cross-prediction ability might be explained by the high similarity between the two cancer types in their genomic regions with copy number variation, which host many clonal genes. Overall, our clonal signature PRACME provided prognostic stratification in MPM and this study emphasized the importance of multi-regional transcriptomic data for prognostic stratification based on clonal genes.

Details

Language :
English
ISSN :
2397768X
Volume :
8
Issue :
1
Database :
Directory of Open Access Journals
Journal :
npj Precision Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.858d5c3a45d04e258ecdd6f6c25f8572
Document Type :
article
Full Text :
https://doi.org/10.1038/s41698-024-00531-y