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Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators
BACKGROUND: Somatic 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 r...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885701/ https://www.ncbi.nlm.nih.gov/pubmed/36717859 http://dx.doi.org/10.1186/s12967-023-03907-z |
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author | Simeone, Ines Ceccarelli, Michele |
author_facet | Simeone, Ines Ceccarelli, Michele |
author_sort | Simeone, Ines |
collection | PubMed |
description | BACKGROUND: Somatic 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. METHODS: Here, 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. RESULTS: We 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. CONCLUSIONS: These 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03907-z. |
format | Online Article Text |
id | pubmed-9885701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98857012023-01-31 Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators Simeone, Ines Ceccarelli, Michele J Transl Med Research BACKGROUND: Somatic 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. METHODS: Here, 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. RESULTS: We 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. CONCLUSIONS: These 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-023-03907-z. BioMed Central 2023-01-30 /pmc/articles/PMC9885701/ /pubmed/36717859 http://dx.doi.org/10.1186/s12967-023-03907-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Simeone, Ines Ceccarelli, Michele Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title | Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title_full | Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title_fullStr | Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title_full_unstemmed | Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title_short | Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
title_sort | pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885701/ https://www.ncbi.nlm.nih.gov/pubmed/36717859 http://dx.doi.org/10.1186/s12967-023-03907-z |
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