scholarly journals Transcriptomic Analysis of Breast Cancer Patients Sensitive and Resistant to Chemotherapy: Looking for Overall Survival and Drug Resistance Biomarkers

2022 ◽  
Vol 21 ◽  
pp. 153303382110689
Author(s):  
Carlos A Barrón-Gallardo ◽  
Mariel Garcia-Chagollán ◽  
Andres J Morán-Mendoza ◽  
Raul Delgadillo-Cristerna ◽  
María G Martínez-Silva ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Immune Therapy ◽  
The Cancer Genome Atlas ◽  
Molecular Profile ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Receptor Interactions

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.

Transcriptomic analysis of breast cancer patients sensitive and resistant to chemotherapy: Looking for overall survival and drug resistance biomarkers 

2020 ◽  
Author(s):  
Carlos Barrón-Gallardo ◽  
Mariel García-Chagollán ◽  
Andrés Morán-Mendoza ◽  
Raúl Delgadillo-Cristerna ◽  
María Martínez-Silva ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Protein Interactions ◽  
Molecular Profile ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Protein Protein Interactions ◽  
Receptor Interactions

Abstract Neoadjuvant chemotherapy is one important therapeutic strategy for breast cancer with the drawback of resistance development. Chemotherapy has adverse effects that combined with resistance could contribute to lower overall survival. This work aimed to evaluate the molecular profile of patients who received neoadjuvant chemotherapy to discover differentially expressed genes (DEGs) that could be used as biomarkers of chemotherapy response and overall survival. Breast cancer patients who received neoadjuvant chemotherapy were enrolled in this study and according to their pathological response were assigned as sensitive or resistant. To evaluate DEGs, GO, KEGG, and protein-protein interactions, RNAseq 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. Seven of those DEGs correlated with overall survival, of them the sub-expression of C1QTNF3, CTF1, OLFML3, PLA2R1, PODN and the over expression of TUBB and TCP1 were found in resistant patients and related to patients with lower overall survival.

scholarly journals Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xu Yang ◽  
Geng-Xi Cai ◽  
Bo-Wei Han ◽  
Zhi-Wei Guo ◽  
Ying-Song Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cell Receptor ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Plasma Dna ◽  
Transcription Start Sites ◽  
Response To Chemotherapy

AbstractGene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

scholarly journals Relationship Between Obesity and Pathologic Response to Neoadjuvant Chemotherapy Among Women With Operable Breast Cancer

2008 ◽  
Vol 26 (25) ◽  
pp. 4072-4077 ◽  
Author(s):  
Jennifer K. Litton ◽  
Ana M. Gonzalez-Angulo ◽  
Carla L. Warneke ◽  
Aman U. Buzdar ◽  
Shu-Wan Kau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Pathologic Complete Response ◽  
Operable Breast Cancer ◽  
Obese Patients ◽  
Breast Cancer Patients ◽  
Significant Difference ◽  
Response To Neoadjuvant Chemotherapy

Purpose To understand the mechanism through which obesity in breast cancer patients is associated with poorer outcome, we evaluated body mass index (BMI) and response to neoadjuvant chemotherapy (NC) in women with operable breast cancer. Patients and Methods From May 1990 to July 2004, 1,169 patients were diagnosed with invasive breast cancer at M. D. Anderson Cancer Center and received NC before surgery. Patients were categorized as obese (BMI ≥ 30 kg/m2), overweight (BMI of 25 to < 30 kg/m2), or normal/underweight (BMI < 25 kg/m2). Logistic regression was used to examine associations between BMI and pathologic complete response (pCR). Breast cancer–specific, progression-free, and overall survival times were examined using the Kaplan-Meier method and Cox proportional hazards regression analysis. All statistical tests were two-sided. Results Median age was 50 years; 30% of patients were obese, 32% were overweight, and 38% were normal or underweight. In multivariate analysis, there was no significant difference in pCR for obese compared with normal weight patients (odds ratio [OR] = 0.78; 95% CI, 0.49 to 1.26). Overweight and the combination of overweight and obese patients were significantly less likely to have a pCR (OR = 0.59; 95% CI, 0.37 to 0.95; and OR = 0.67; 95% CI, 0.45 to 0.99, respectively). Obese patients were more likely to have hormone-negative tumors (P < .01), stage III tumors (P < .01), and worse overall survival (P = .006) at a median follow-up time of 4.1 years. Conclusion Higher BMI was associated with worse pCR to NC. In addition, its association with worse overall survival suggests that greater attention should be focused on this risk factor to optimize the care of breast cancer patients.

scholarly journals Peripheral Blood Classical Monocytes and Plasma Interleukin 10 Are Associated to Neoadjuvant Chemotherapy Response in Breast Cancer Patients

2020 ◽  
Vol 11 ◽  
Author(s):  
Javier Valdés-Ferrada ◽  
Natalia Muñoz-Durango ◽  
Alejandra Pérez-Sepulveda ◽  
Sabrina Muñiz ◽  
Irenice Coronado-Arrázola ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Peripheral Blood ◽  
Interleukin 10 ◽  
Chemotherapy Response ◽  
Breast Cancer Patients ◽  
Classical Monocytes

Tumor Response Ratio Predicts Overall Survival in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

2014 ◽  
Vol 21 (10) ◽  
pp. 3317-3323 ◽  
Author(s):  
Marian Miller ◽  
Rebecca A. Ottesen ◽  
Joyce C. Niland ◽  
Laura Kruper ◽  
Steven L. Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Tumor Response ◽  
Response Ratio ◽  
Breast Cancer Patients

scholarly journals Neoadjuvan Chemotheraphy Responses to Local Advanced Breast Cancer Patients at Dr Moh Hoesin Hospital Palembang

2020 ◽  
Vol 3 (3) ◽  
pp. 51-58
Author(s):  
Aldo Giovanno ◽  
Mgs. Irsan Saleh ◽  
Nur Qodir ◽  
Mulawan Umar
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Advanced Breast Cancer ◽  
Cancer Patients ◽  
Univariate Analysis ◽  
Locally Advanced ◽  
Radical Mastectomy ◽  
Advanced Breast ◽  
Chemotherapy Response ◽  
Breast Cancer Patients

Breast cancer is a malignancy which invaded breast tissue in the form of ductal or lobular. One most therapywhich is given is neoadjuvant chemotherapy. Neoadjuvant Chemotherapy can reduce tumor size so that surgerycan be performed with good breast removal with Modification of Radical Mastectomy (MRM) and BreastConservative Therapy (BCT). This purpose from this research is to find out neoadjuvant chemotherapy response inLocally Advanced Breast Cancer Patients which has received chemotherapy treatment in RSUP dr MohammadHoesin Palembang. This observational descriptive study was conducted at RSUP Mohammad Hoesin Palembang inthe period between October until November 2019. The sample of this study was locally advanced breast Cancerpatients who underwent chemotherapy that met the inclusion and exclusion criteria. The data were obtained byinterviews and observed medical records from the patients which were then analyzed by univariate analysis usingSPSS version 25. In this study there were 34 locally advanced breast cancer patients who fulfilled the inclusion andexclusion criteria. 24 of 34 patients (70,6%) received positive response and 10 of 34 patients (29,4%) receivednegative response.

scholarly journals Survivin Expression May Affect The Neoadjuvant Chemotherapy Response in Breast Cancer Patients

2017 ◽  
Vol 22 (4) ◽  
pp. 147-154
Author(s):  
Sinan Demircioğlu ◽  
Mehmet Artaç ◽  
Levent Korkmaz ◽  
Şeyda Gündüz ◽  
Mustafa Karaağaç ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Survivin Expression ◽  
Chemotherapy Response ◽  
Breast Cancer Patients
Sign in / Sign up

Export Citation Format

Share Document