Ethnicity-Driven Transcriptomic Biomarkers in Breast Cancer: Towards Personalized Treatment Strategies

Ethnicity-Driven Transcriptomic Biomarkers in Breast Cancer: Towards Personalized Treatment Strategies | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 21 July 2025 V1 Latest version Share on Ethnicity-Driven Transcriptomic Biomarkers in Breast Cancer: Towards Personalized Treatment Strategies Authors : Victoria Alves Porto , Carolina Bonilla , and Danilo Trabuco do Amaral 0000-0002-8940-6546 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175309460.00448153/v1 250 views 141 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Breast cancer is one of the leading causes of mortality among women worldwide and is characterized by molecular and clinical heterogeneity. Despite advances in therapeutic strategies, resistance to treatment remains a challenge, especially in diverse populations, where specific genetic factors can influence disease progression and treatment response. Ethnic variability plays a crucial role in tumor biology and resistance mechanisms, but most research has neglected global diversity. Thus, we identify differentially expressed genes in BC patients of different ethnicities, aiming to deepen the understanding of genetic variations associated with the disease in different populations. Transcriptome data were obtained from the GEO database and used for de novo transcript assembly. Abundance and differential expression gene values were applied to compare the isoforms between populations. To identify biomarkers, Principal Component Analysis and the K -Means clustering were used to group genes with similar expression patterns. Autoencoder Neural Networks were implemented to extract relevant features from the data. The analysis comparison across ethnicities revealed population-specific gene expression patterns associated with therapy resistance. We identified differentially expressed transcripts influencing key pathways like immune modulation, metabolic reprogramming, and DNA repair. ML identified ancestry-driven clustering, highlighting genes exclusive to specific populations, offering potential lineage-specific markers for targeted therapies. Supplementary Material File (ethnicity-driven transcriptomic biomarkers in breast cancer towards personalized treatment strategies.docx) Download 46.68 KB Information & Authors Information Version history V1 Version 1 21 July 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords bioinformatics biomarkers breast cancer cancer computational biology ethnic variability gene expression genetics medical applications medical biotechnology omics treatment resistance Authors Affiliations Victoria Alves Porto Universidade Federal do ABC Centro de Ciencias Naturais e Humanas View all articles by this author Carolina Bonilla Universidade de Sao Paulo Departamento de Medicina Preventiva View all articles by this author Danilo Trabuco do Amaral 0000-0002-8940-6546 [email protected] Universidade Federal do ABC Centro de Ciencias Naturais e Humanas View all articles by this author Metrics & Citations Metrics Article Usage 250 views 141 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Victoria Alves Porto, Carolina Bonilla, Danilo Trabuco do Amaral. Ethnicity-Driven Transcriptomic Biomarkers in Breast Cancer: Towards Personalized Treatment Strategies. Authorea . 21 July 2025. 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