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Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease.

ABSTRACT: BACKGROUND:Patients with Estrogen Receptor ?-positive (ER+) Inflammatory Breast Cancer (IBC) are less responsive to endocrine therapy compared with ER+ non-IBC (nIBC) patients. The study of ER+ IBC samples might reveal biomarkers for endocrine resistant breast cancer. MATERIALS & METHODS:Gene expression profiles of ER+ samples from 201 patients were explored for genes that discriminated between IBC and nIBC. Classifier genes were applied onto clinically annotated expression data from 947 patients with ER+ breast cancer and validated with RT-qPCR for 231 patients treated with first-line tamoxifen. Relationships with metastasis-free survival (MFS) and progression-free survival (PFS) following adjuvant and first-line endocrine treatment, respectively, were investigated using Cox regression analysis. RESULTS:A metagene of six genes including the genes encoding for 4-aminobutyrate aminotransferase (ABAT) and Stanniocalcin-2 (STC2) were identified to distinguish 22 ER+ IBC from 43 ER+ nIBC patients and remained discriminatory in an independent series of 136 patients. The metagene and two genes were not prognostic in 517 (neo)adjuvant untreated lymph node-negative ER+ nIBC breast cancer patients. Only ABAT was related to outcome in 250 patients treated with adjuvant tamoxifen. Three independent series of in total 411 patients with advanced disease showed increased metagene scores and decreased expression of ABAT and STC2 to be correlated with poor first-line endocrine therapy outcome. The biomarkers remained predictive for first-line tamoxifen treatment outcome in multivariate analysis including traditional factors or published signatures. In an exploratory analysis, ABAT and STC2 protein expression levels had no relation with PFS after first-line tamoxifen. CONCLUSIONS:This study utilized ER+ IBC to identify a metagene including ABAT and STC2 as predictive biomarkers for endocrine therapy resistance.

SUBMITTER: Jansen MP

PROVIDER: S-EPMC5528763 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease.

Jansen Maurice P H M MP Sas Leen L Sieuwerts Anieta M AM Van Cauwenberghe Caroline C Ramirez-Ardila Diana D Look Maxime M Ruigrok-Ritstier Kirsten K Finetti Pascal P Bertucci François F Timmermans Mieke M MM van Deurzen Carolien H M CH Martens John W M JW Simon Iris I Roepman Paul P Linn Sabine C SC van Dam Peter P Kok Marleen M Lardon Filip F Vermeulen Peter B PB Foekens John A JA Dirix Luc L Berns Els M J J EM Van Laere Steven S

Molecular oncology 20150304 6

<h4>Background</h4>Patients with Estrogen Receptor α-positive (ER+) Inflammatory Breast Cancer (IBC) are less responsive to endocrine therapy compared with ER+ non-IBC (nIBC) patients. The study of ER+ IBC samples might reveal biomarkers for endocrine resistant breast cancer.<h4>Materials & methods</h4>Gene expression profiles of ER+ samples from 201 patients were explored for genes that discriminated between IBC and nIBC. Classifier genes were applied onto clinically annotated expression data f ...[more]

PMID: 25771305

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Project description:Breast cancer is one of the most common malignant cancers affecting females. Estrogen receptor (ER)-positive breast cancer is responsive to endocrine therapy. Although current therapies offer favorable prospects for improving survival, the development of resistance remains a severe problem. In this study, we explored the resistance mechanisms of ER-positive breast cancer to neoadjuvant endocrine therapy. Microarray data of GSE87411 contained 109 pairs of samples from Z1031 trial, including untreated samples and post-treated samples with neoadjuvant aromatase inhibitor (AI) therapy. The differentially expressed genes (DEGs) were obtained from two different comparisons: untreated samples versus post-treated samples with AIs, and post-treated samples sensitive versus resistant to AIs. Multiple bioinformatic methods were applied to evaluate biological function, protein-protein network and potential binding between target protein and aromatase inhibitor. Then, regulation of gene expression, DNA methylation and clinicopathological factors of breast cancer were further analyzed with TCGA data. From GSE87411 dataset, 30 overlapped DEGs were identified. Cell division was found to be the main function of overlapped DEGs by functional enrichment and gene ontology (GO) analysis. RAD51 recombinase (RAD51), a key protein of homologous recombination, was detected to interact with BReast CAncer genes 2 (BRCA2). Moreover, according to the docking simulation, RAD51 might potentially bind to AIs. Overexpressed RAD51 was associated with hypermethylation of BRCA2, resistance to AIs and poor overall survival of patients with ER-positive breast cancer. Furthermore, RAD51 was found to be a better indicator than MKI67 for predicting resistance in neoadjuvant setting. The results indicated that methylation of BRCA2 led to incomplete suppression on RAD51, which caused an increased expression of RAD51, subsequently AI-resistance and poor prognosis in ER-positive breast cancer. RAD51 could be a new candidate used as a predicative marker and therapeutic target in neoadjuvant endocrine treatment.

Project description:BackgroundWhile adjuvant endocrine therapy (ET) may decrease the mortality rate of estrogen receptor-positive (ER+) breast cancer (BC), the likelihood of relapse and metastasis due to ET resistance remains high. Cuproptosis is a recently discovered regulated cell death (RCD), whose role in tumors has yet to be elucidated. Thus, there is a need to study its specific regulatory mechanism in resistance to ET in BC, to identify novel therapeutic targets.MethodsThe prognostic cuproptosis-related genes (CRGs) in ER+ BC were filtered by undergoing Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses in TCGA-BRCA, and a CRGs risk signature was constructed using the correlation coefficient. Immune infiltration analysis, immune function analysis, tumor microenvironment (TME) analysis, immune checkpoint analysis, immunotherapy response analysis, drug sensitivity analysis, and pathway activation analysis were carried out among the high- and low-risk groups in turn. The central CRG of cuproptosis in ER+ BC resistance to ET was acquired through the intersection of protein interaction network (PPI) analysis, genes differentially expressed (DEGs) between human BC cells LCC9 and MCF-7 (GSE159968), and CRGs with prognostic significance in TCGA-BRCA ER+ BC. The miRNAs upstream of the core CRGs were predicted based on the intersection of 4 databases, miRDB, RNA22, miRWalk, and RNAlnter. Candidate miRNAs consisted of the intersection of predicted miRNAs and miRNAs differentially expressed in the LCC9 and MCF-7 cell lines (GSE159979). Candidate lncRNAs were the intersection of the differential lncRNAs from the LCC9 and MCF-7 cell lines and the survival-related lncRNAs obtained from a univariate Cox regression analysis. Pearson's correlation analysis was performed between mRNA-miRNA, miRNA-lncRNA, and mRNA-lncRNA expression separately.ResultsWe constructed A risk signature of 4-CRGs to predict the prognosis of ER+ BC in TCGA-BRCA, a risk score = DLD*0.378 + DBT*0.201 + DLAT*0.380 + ATP7A*0.447 was used as the definition of the formula. There were significant differences between the high- and low-risk groups based on the risk score of 4-CRGs in aspects of immune infiltration, immune function, expression levels of immune checkpoint genes, and signaling pathways. DLD was determined to be the central CRG of cuproptosis in ER+ BC resistance to ET through the intersection of the PPI network analysis, DEGs between LCC9 and MCF-7 and 4-CRGs. Two miRNAs hsa-miR-370-3p and hsa-miR-432-5p were found taking DLD mRNA as a target, and the lncRNA C6orf99 has been hypothesized to be a competitive endogenous RNA that regulates DLD mRNA expression by sponging off hsa-miR-370-3p and hsa-miR-432-5p.ConclusionThis study built a prognostic model based on genes related to cuproptosis in ER+ BC. We considered DLD to be the core gene associated with resistance to ET in ER+ BC via copper metabolism. The search for promising therapeutic targets led to the establishment of a cuproptosis-related ceRNA network C6orf99/hsa-miR-370-3p and hsa-miR-432-5p/DLD.

Project description:BackgroundThe 21-gene recurrence score (RS) predicts risk of locoregional recurrence (LRR) in node-negative, estrogen receptor (ER)-positive breast cancer. We evaluated the association between RS and LRR in node-positive, ER-positive patients treated with adjuvant chemotherapy plus tamoxifen in National Surgical Adjuvant Breast and Bowel Project B-28.MethodsB-28 compared doxorubicin/cyclophosphamide (AC X 4) with AC X 4 followed by paclitaxel X 4. Tamoxifen was given to patients age 50 years or older and those younger than age 50 years with ER-positive and/or progesterone receptor-positive tumors. Lumpectomy patients received breast radiotherapy. Mastectomy patients received no radiotherapy. The present study includes 1065 ER-positive, tamoxifen-treated patients with RS assessment. Cumulative incidence functions and subdistribution hazard regression models were used for LRR to account for competing risks including distant recurrence, second primary cancers, and death from other causes. Median follow-up was 11.2 years. All statistical tests were one-sided.ResultsThere were 80 LRRs (7.5%) as first events (68% local/32% regional). RS was low: 36.2%; intermediate: 34.2%; and high: 29.6%. RS was a statistically significant predictor of LRR in univariate analyses (10-year cumulative incidence of LRR = 3.3%, 7.2%, and 12.2% for low, intermediate, and high RS, respectively, P < .001). In multivariable regression analysis, RS remained an independent predictor of LRR (hazard ratio [HR] = 2.59, 95% confidence interval [CI] = 1.28 to 5.26, for a 50-point difference, P = .008) along with pathologic nodal status (HR = 1.91, 95% CI = 1.20 to 3.03, for four or more vs one to three positive nodes, P = .006) and tumor size (HR = 1.28, 95% CI = 1.05 to 1.55, for a 1 cm difference, P = .02).ConclusionsRS statistically significantly predicts risk of LRR in node-positive, ER-positive breast cancer patients after adjuvant chemotherapy plus tamoxifen. These findings can help in the selection of appropriate candidates for comprehensive radiotherapy.

Dataset Information

Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease.

Publications

Decreased expression of ABAT and STC2 hallmarks ER-positive inflammatory breast cancer and endocrine therapy resistance in advanced disease.

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