Abstract 5896: Identification of lncRNAs associated with breast cancer prognosis from Latina America patients

Abstract Breast cancer (BC) is the most common cause of female cancer-related death worldwide and is considered a public health problem. Many functional studies have shown that long noncoding RNAs (lncRNAs) play different roles in gene expression regulation, acting as epigenetic factors. Accumulating evidence indicates that lncRNAs modulate diverse biological processes, and their altered expression is associated with the development and progression of cancer, including BC. Here, aiming to identify lncRNAs associated with breast cancer, we performed a re-analysis of the expression data from 1,071 tumors of eligible patients in the project LACRN MPBCS (Latin American Cancer Research-Network - Molecular Profile of Breast Cancer Study). Using normalized data, we compared the expression profiles of triple-negative breast cancer (TNBC; 170 cases) and non-TNBC tumors (782 cases). A total of 59 differentially expressed lncRNAs (DElncRNAs) could be identified based on the criteria of |log2FC| > 1 and FDR < 0.05, using the DESeq2 R package. In the Kaplan-Meier survival analysis, we identified DElncRNAs that affect disease-free survival and/or overall survival, with 8 in TNBC and 26 in non-TNBC patients. Further, we used multivariate Cox proportional-hazards models to evaluate independent predictors of survival. Two of those DElncRNAs, VLDLR-AS1 and PART1, were independent prognostic markers for TNBC patients, and seven, LINC00239, FAM30A, LINC00842, LINC01315, EGOT, LY6E-DT, and SLC25A21-AS1, were independent prognostic markers for non-TNBC patients. Our study identifies several lncRNAs that might participate in tumor progression and may serve as candidate biomarkers for BC. Citation Format: Xinhui Wang, Marcio L. Acencio, Flavia Rotea Mangone, Roger Chammas, Dirce Maria Carraro, Andrea S. Llera, Eliana Abdelhay, Nora Artagaveytia, Adrián Daneri-Navarro, Bettina Müller, Osvaldo L. Podhajcer, Carlos Velazquez, Maria A. Nagai. Identification of lncRNAs associated with breast cancer prognosis from Latina America patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5896.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-5896
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 5896: Identification of lncRNAs associated with breast cancer prognosis from Latina America patients

Eliana Abdelhay, Carlos Velazquez, Dirce Maria Carraro, Osvaldo L. Podhajcer et al.
Cancer Research
Cancer-related molecular mechanisms research
article

Abstract 5896: Identification of lncRNAs associated with breast cancer prognosis from Latina America patients

Eliana Abdelhay, Carlos Velazquez, Dirce Maria Carraro, Osvaldo L. Podhajcer, Andrea S. Llera, Nora Artagaveytia, Márcio Luís Acencio, Roger Chammas, Adrián Daneri-Navarro, M A Nagai, F R R Mangone, Bettina Müller, Xinhui Wang
article en

Abstract

Abstract Breast cancer (BC) is the most common cause of female cancer-related death worldwide and is considered a public health problem. Many functional studies have shown that long noncoding RNAs (lncRNAs) play different roles in gene expression regulation, acting as epigenetic factors. Accumulating evidence indicates that lncRNAs modulate diverse biological processes, and their altered expression is associated with the development and progression of cancer, including BC. Here, aiming to identify lncRNAs associated with breast cancer, we performed a re-analysis of the expression data from 1,071 tumors of eligible patients in the project LACRN MPBCS (Latin American Cancer Research-Network - Molecular Profile of Breast Cancer Study). Using normalized data, we compared the expression profiles of triple-negative breast cancer (TNBC; 170 cases) and non-TNBC tumors (782 cases). A total of 59 differentially expressed lncRNAs (DElncRNAs) could be identified based on the criteria of |log2FC| > 1 and FDR < 0.05, using the DESeq2 R package. In the Kaplan-Meier survival analysis, we identified DElncRNAs that affect disease-free survival and/or overall survival, with 8 in TNBC and 26 in non-TNBC patients. Further, we used multivariate Cox proportional-hazards models to evaluate independent predictors of survival. Two of those DElncRNAs, VLDLR-AS1 and PART1, were independent prognostic markers for TNBC patients, and seven, LINC00239, FAM30A, LINC00842, LINC01315, EGOT, LY6E-DT, and SLC25A21-AS1, were independent prognostic markers for non-TNBC patients. Our study identifies several lncRNAs that might participate in tumor progression and may serve as candidate biomarkers for BC. Citation Format: Xinhui Wang, Marcio L. Acencio, Flavia Rotea Mangone, Roger Chammas, Dirce Maria Carraro, Andrea S. Llera, Eliana Abdelhay, Nora Artagaveytia, Adrián Daneri-Navarro, Bettina Müller, Osvaldo L. Podhajcer, Carlos Velazquez, Maria A. Nagai. Identification of lncRNAs associated with breast cancer prognosis from Latina America patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5896.

Cancer ResearchVol. 86(7_Supplement)
Universidade de São Paulo (BR), Universidad de la República de Uruguay (UY), University of Luxembourg (LU), Universidad de Guadalajara (MX), Fundación Instituto Leloir (AR), AC Camargo Hospital (BR), Universidad de Sonora (MX), Universidad de Hermosillo (MX), Instituto do Câncer do Estado de São Paulo (BR), Instituto Nacional de Câncer - INCA (BR), Favaloro Foundation (AR), Universidad de Montevideo (UY)
Good health and well-being
Openalex Percentile: Top 29%
Cancer-related molecular mechanisms research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.