Detection of pan-cancer surface protein biomarkers via a network-based approach on transcriptomics data

Autor:	Daniele Mercatelli, Chiara Cabrelle, Pierangelo Veltri, Federico M Giorgi, Pietro H Guzzi
Rok vydání:	2022
Předmět:	Biomarkers Tumor Humans Membrane Proteins Antineoplastic Agents Breast Neoplasms Female Transcriptome Molecular Biology Information Systems
Zdroj:	Briefings in bioinformatics. 23(5)
ISSN:	1477-4054
Popis:	Cell surface proteins have been used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. Many of these proteins lie at the top of signaling cascades regulating cell responses and gene expression, therefore acting as ‘signaling hubs’. It has been previously demonstrated that the integrated network analysis on transcriptomic data is able to infer cell surface protein activity in breast cancer. Such an approach has been implemented in a publicly available method called ‘SURFACER’. SURFACER implements a network-based analysis of transcriptomic data focusing on the overall activity of curated surface proteins, with the final aim to identify those proteins driving major phenotypic changes at a network level, named surface signaling hubs. Here, we show the ability of SURFACER to discover relevant knowledge within and across cancer datasets. We also show how different cancers can be stratified in surface-activity-specific groups. Our strategy may identify cancer-wide markers to design targeted therapies and biomarker-based diagnostic approaches.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a85b5f746533718ff430033c74a73e1 https://pubmed.ncbi.nlm.nih.gov/36088571 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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