Transcriptomic Analysis of Breast Cancer Patients Sensitive and Resistant to Chemotherapy: Looking for Overall Survival and Drug Resistance Biomarkers
| Autor: | Carlos A Barrón-Gallardo PhD, Mariel Garcia-Chagollán PhD, Andres J Morán-Mendoza MD, Raul Delgadillo-Cristerna MD, María G Martínez-Silva MD, Adriana Aguilar-Lemarroy PhD, Luis F Jave-Suárez PhD |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Technology in Cancer Research & Treatment, Vol 21 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1533-0338 15330338 |
| DOI: | 10.1177/15330338211068965 |
| Popis: | Worldwide breast cancer ranks first in mortality and incidence rates in women over 20 years old. Rather than one disease, breast cancer is a heterogeneous group of diseases that express distinct molecular profiles. Neoadjuvant chemotherapy is an important therapeutic strategy for breast cancer patients independently of their molecular subtype, with the drawback of resistance development. In addition, chemotherapy has adverse effects that combined with resistance could contribute to lower overall survival. Although great efforts have been made to find diagnostic and prognostic biomarkers for breast cancer and for response to targeted and immune therapy for this pathology, little has been explored regarding biomarkers of response to anthracyclines and taxanes based neoadjuvant chemotherapy. This work aimed to evaluate the molecular profile of patients who received neoadjuvant chemotherapy to identify differentially expressed genes (DEGs) that could be used as biomarkers of chemotherapy response and overall survival. Breast cancer patients who were candidates for neoadjuvant chemotherapy were enrolled in this study. After treatment and according to their pathological response, they were assigned as sensitive or resistant. To evaluate DEGs, Gene Ontology, Kyoto Encyclopedia Gene and Genome (KEGG), and protein–protein interactions, RNA-seq information from all patients was obtained by next-generation sequencing. A total of 1985 DEGs were found, and KEGG analysis indicated a great number of DEGs in metabolic pathways, pathways in cancer, cytokine–cytokine receptor interactions, and neuroactive ligand-receptor interactions. A selection of 73 DEGs was used further for an analysis of overall survival using the METABRIC study and the ductal carcinoma dataset of The Cancer Genome Atlas (TCGA) database. Nine DEGs correlated with overall survival, of which the subexpression of C1QTNF3, CTF1, OLFML3, PLA2R1, PODN, KRT15, HLA-A, and the overexpression of TUBB and TCP1 were found in resistant patients and related to patients with lower overall survival. |
| Databáze: | Directory of Open Access Journals |
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