Abnormal Long Non-Coding RNAs Expression Patterns Have the Potential Ability for Predicting Survival and Treatment Response in Breast Cancer

Autor: Luciana Rodrigues Carvalho Barros, Maria Aparecida Nagai, F. R. R. Mangone, Ana Carolina Pavanelli, Vera Luiza Capelozzi, Juliana Machado-Rugolo
Přispěvatelé: Universidade de São Paulo (USP), Cancer Institute of São Paulo, Universidade Estadual Paulista (UNESP)
Rok vydání: 2021
Předmět:
Zdroj: Scopus
Repositório Institucional da UNESP
Universidade Estadual Paulista (UNESP)
instacron:UNESP
Genes
Volume 12
Issue 7
Genes, Vol 12, Iss 996, p 996 (2021)
ISSN: 2073-4425
DOI: 10.3390/genes12070996
Popis: Made available in DSpace on 2022-04-29T08:45:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-07-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Abnormal long non-coding RNAs (lncRNAs) expression has been documented to have oncogene or tumor suppressor functions in the development and progression of cancer, emerging as promising independent biomarkers for molecular cancer stratification and patients’ prognosis. Examining the relationship between lncRNAs and the survival rates in malignancies creates new scenarios for precision medicine and targeted therapy. Breast cancer (BRCA) is a heterogeneous malignancy. Despite advances in its molecular classification, there are still gaps to explain in its multifaceted presentations and a substantial lack of biomarkers that can better predict patients’ prognosis in response to different therapeutic strategies. Here, we performed a re-analysis of gene expression data generated using cDNA microarrays in a previous study of our group, aiming to identify differentially expressed lncRNAs (DELncRNAs) with a potential predictive value for response to treatment with taxanes in breast cancer patients. Results revealed 157 DELncRNAs (90 up-and 67 down-regulated). We validated these new biomarkers as having prognostic and predictive value for breast cancer using in silico analysis in public databases. Data from TCGA showed that compared to normal tissue, MIAT was up-regulated, while KCNQ1OT1, LOC100270804, and FLJ10038 were down-regulated in breast tumor tissues. KCNQ1OT1, LOC100270804, and FLJ10038 median levels were found to be significantly higher in the luminal subtype. The ROC plotter platform results showed that reduced expression of these three DElncRNAs was associated with breast cancer patients who did not respond to taxane treatment. Kaplan–Meier survival analysis revealed that a lower expression of the selected lncRNAs was significantly associated with worse relapse-free survival (RFS) in breast cancer patients. Further validation of the expression of these DELncRNAs might be helpful to better tailor breast cancer prognosis and treatment. Discipline of Oncology Department of Radiology and Oncology Faculty of Medicine University of São Paulo Center for Translational Research in Oncology Cancer Institute of São Paulo Department of Pathology University of São Paulo Medical School (USP) Health Technology Assessment Center (NATS) Clinical Hospital (HCFMB) Medical School of São Paulo State University (UNESP) Health Technology Assessment Center (NATS) Clinical Hospital (HCFMB) Medical School of São Paulo State University (UNESP) FAPESP: 2013/07035-4 CNPq: 303134/2013-5
Databáze: OpenAIRE
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