Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators

Journal of Translational Medicine

Research

Michele Ceccarelli¹  Ines Simeone² 

[1] Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Via Claudio 21, 80128, Naples, Italy;BIOGEM Institute of Molecular Biology and Genetics, Via Camporeale, 83031, Ariano Irpino, Italy;Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, Via Claudio 21, 80128, Naples, Italy;Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), Via Adamello 16, 20139, Milan, Italy;

关键词: Onco-signatures;    Pan-cancer;    Breast cancer disease;    TCGA;    Gene set enrichment analysis;    Normalized enrichment score;    Luminal breast tumor subtype;    EMT;    Hsa-miR-135-5p;    TDMD;   

DOI  :  10.1186/s12967-023-03907-z

 received in 2022-11-09, accepted in 2023-01-20,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundSomatic alterations in cancer cause dysregulation of signaling pathways that control cell-cycle progression, apoptosis, and cell growth. The effect of individual alterations in these pathways differs between individual tumors and tumor types. Recognizing driver events is a complex task requiring integrating multiple molecular data, including genomics, epigenomics, and functional genomics. A common hypothesis is that these driver events share similar effects on the hallmarks of cancer. The availability of large-scale multi-omics studies allows for inferring these common effects from data. Once these effects are known, one can then deconvolve in every individual patient whether a given genomics alteration is a driver event.MethodsHere, we develop a novel data-driven approach to identify shared oncogenic expression signatures among tumors. We aim to identify gene onco-signature for classifying tumor patients in homogeneous subclasses with distinct prognoses and specific genomic alterations. We derive expression pan-cancer onco-signatures from TCGA gene expression data using a discovery set of 9107 primary pan-tumor samples together with respective matched mutational data and a list of known cancer-related genes from COSMIC database.ResultsWe use the derived ono-signatures to state their prognostic significance and apply them to the TCGA breast cancer dataset as proof of principle of our approach. We uncover a “mitochondrial” sub-group of Luminal patients characterized by its biological features and regulated by specific genetic modulators. Collectively, our results demonstrate the effectiveness of onco-signatures-based methodologies, and they also contribute to a comprehensive understanding of the metabolic heterogeneity of Luminal tumors.ConclusionsThese findings provide novel genomics evidence for developing personalized breast cancer patient treatments. The onco-signature approach, demonstrated here on breast cancer, is general and can be applied to other cancer types.

【 授权许可】

CC BY   
© The Author(s) 2023

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