Dataset Information

MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer.

ABSTRACT: miRNAs have been linked to chemosensitivity of breast cancer cells in vitro. In patients, however, there is no clinically validated method for predicting chemotherapy response. The aim of this study was to assess whether (I) a specific pattern of miRNA expression in pretherapeutic biopsies can predict response to neoadjuvant chemotherapy, and (II) differential miRNA expression in residual tumor after completion of chemotherapy allows further prognostic stratification of non-responding patients.Sixty-four patients with newly diagnosed large (?3 cm) or locally advanced primary breast cancers who underwent neoadjuvant anthracycline/taxane-based chemotherapy were included. Relative expression of 10 miRNAs likely to be associated with chemotherapy response (miR-7,-21,-29a,-29b,-34a,-125b,-155,-200c,-340,-451) was determined by quantitative RT-PCR from pretherapeutic biopsies (n = 64) and residual invasive tumor after chemotherapy (n = 42). Pathologic complete response (pCR) defined by absence of invasive tumor served as reference standard. In addition, miRNA expression was compared with disease-free and overall survival.Nine (14%) of 64 patients achieved pCR. High expression of miR-7 and low expression of miR-340 in pretherapeutic biopsies predicted pCR with a negative predictive value of 96 and 97%, respectively (specificity 54 and 57%). The combined profile of miR-7high/miR-340low demonstrated improved specificity of 86% while maintaining a high negative predictive value (96%) to identify non-responders. Pretherapeutic expression of miR-200c and miR-155 showed prognostic information, and low expression was associated with increased overall survival (115 vs. 90 months, p ? 0.03). After chemotherapy, the overall survival of patients with residual invasive tumor was better for those demonstrating low miR-7 or high miR-125b (p = 0.01).Intratumoral expression of miR-7 and miR-340 prior to neoadjuvant chemotherapy could be used to predict pCR and a profile of miR-7low or miR-340high identified patients unlikely to achieve pCR who might benefit from alternative treatment options including earlier surgery. Our study identifies miRNAs as promising predictive biomarkers, which could aid in optimization of breast cancer management and treatment stratification.

SUBMITTER: Raychaudhuri M

PROVIDER: S-EPMC5367042 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer.

Raychaudhuri Mithu M Bronger Holger H Buchner Theresa T Kiechle Marion M Weichert Wilko W Avril Stefanie S

Breast cancer research and treatment 20170208 3

<h4>Purpose</h4>miRNAs have been linked to chemosensitivity of breast cancer cells in vitro. In patients, however, there is no clinically validated method for predicting chemotherapy response. The aim of this study was to assess whether (I) a specific pattern of miRNA expression in pretherapeutic biopsies can predict response to neoadjuvant chemotherapy, and (II) differential miRNA expression in residual tumor after completion of chemotherapy allows further prognostic stratification of non-respo ...[more]

PMID: 28181130

Similar Datasets

Project description:Background: Early prediction of response to neoadjuvant chemotherapy (NAC) is critical in choosing appropriate chemotherapeutic regimen for patients with locally advanced breast cancer. Herein, we sought to identify potential biomarkers to predict the response to neoadjuvant chemotherapy for breast cancer patients.Methods: Three genomic profiles acquired by microarray analysis from subjects with or without residual tumors after NAC downloaded from the GEO database were used to screen the differentially expressed genes (DEGs). An array of public databases, including ONCOMINE, cBioportal, Breast Cancer Gene Expression Miner v4.0, and the Kaplan Meir-plotter, etc., were used to evaluate the potential functions, related signaling pathway, as well as prognostic values of FABP7 in breast cancer. Anti-cancer drug sensitivity assay, real-time PCR, flow cytometry and western-blotting assays were used to investigate the function of FABP7 in breast cancer cells and examine the relevant mechanism.Results: Two differentially expressed genes, including FABP7 and ESR1, were identified to be potential indicators of response to anthracycline and taxanes for breast cancer. FABP7 was associated with better chemotherapeutic response, while ESR1 was associated with poorer chemotherapeutic effectiveness. Generally, the expression of FABP7 was significantly lower in breast cancer than normal tissue samples. FABP7 mainly high expressed in ER-negative breast tumor and might regulate cell cycle to enhance chemosensitivity. Moreover, elevated FABP7 expression increased the percentage of cells at both S and G2/M phase in MDA-MB-231-ADR cells, and decreased the percentage of cells at G0/G1 phase, as compared to control group. Western-blotting results showed that elevated FABP7 expression could increase Skp2 expression, while decrease Cdh1 and p27kip1 expression in MDA-MB-231-ADR cells. In addition, FABP7 was correlated to longer recurrence-free survival (RFS) in BC patients with ER-negative subtype of BC treated with chemotherapy.Conclusion: FABP7 is a potential favorable biomarker and predicts better response to NAC in breast cancer patients. Future study on the predictive value and detail molecular mechanisms of FABP7 in contribution to chemosensitivity in breast cancer is warranted.

Project description:BackgroundAccurate evaluation of the response to neoadjuvant chemotherapy (NAC) provides important information about systemic therapies for breast cancer, which implies pharmacological response, prognosis, and guide further therapy. Gene profiles overcome the shortcomings of the relatively limited detection indicators of the classical pathological evaluation criteria and the subjectivity of observation, but are complicated and expensive. Therefore, it is essential to develop a more accurate, repeatable, and economical evaluation approach for neoadjuvant chemotherapy responses.MethodsWe analyzed the transcriptional profiles of chemo-resistant breast cancer cell lines and tumors of chemo-resistant breast cancer patients in the GSE25066 dataset. We preliminarily screened out common significantly differentially expressed genes and constructed a NAC response risk model using LASSO regression and univariate and multivariate analyses. The differences in bioinformatic features of tumor cells, immune characteristics, and prognosis were compared between high and low-risk group. The potential drugs that could reverse chemotherapy resistance in breast cancer were screened by the CMap database.ResultsThirty-six genes were commonly up/down-regulated in both NAC chemo-resistant tumors and cells compared to the sensitive tumors and wild-type cells. Through LASSO regression, we obtained a risk model composed of 12 genes. The risk model divided patients into high and low-risk groups. Univariate and multivariate Cox regression analyses suggested that the risk score is an independent prognostic factor for evaluating NAC response in breast cancer. Tumors in risk groups exhibited significant differences in molecular biological characteristics, tumor-infiltrating lymphocytes, and immunosuppressive molecule expression. Our results suggested that the risk score was also a good prognostic factor for breast cancer. Finally, we screened potential drugs that could reverse chemotherapy resistance in breast cancer.ConclusionA novel 12 gene-signature could be used to predict NAC response and predict prognosis in breast cancer.

Project description:BACKGROUND:The main purpose was to investigate the correlation between magnetic resonance imaging (MRI)-based response patterns halfway through neoadjuvant chemotherapy and immunotherapy (NAC) and pathological tumor response in patients with breast cancer. Secondary purposes were to compare the predictive value of MRI-based response patterns measured halfway through NAC and after NAC and to measure interobserver variability. METHODS:All consecutive patients treated with NAC for primary invasive breast cancer from 2012 to 2015 and who underwent breast MRI before, halfway through (and after) NAC were included. All breast tumors were reassessed on MRI by two experienced breast radiologists and classified into six patterns: type 0 (complete radiologic response); type 1 (concentric shrinkage); type 2 (crumbling); type 3 (diffuse enhancement); type 4 (stable disease); type 5 (progressive disease). Percentages of tumors showing pathological complete response (pCR), > 50% tumor reduction and > 50% tumor diameter reduction per MRI-based response pattern were calculated. Correlation between MRI-based response patterns and pathological tumor reduction was studied with Pearson's correlation coefficient, and interobserver agreement was tested with Cohen's Kappa. RESULTS:Patients (n = 76; mean age 53, range 29-72 years) with 80 tumors (4 bilateral) were included. There was significant correlation between these MRI-based response patterns halfway through NAC and tumor reduction on pathology assessment (reader 1 r = 0.33; p = 0.003 and reader 2 r = 0.45; p < 0.001). Type-0, type-1 or type-2 patterns halfway through NAC showed highest tumor reduction rates on pathology assessment, with > 50% tumor reduction in 90%, 78% and 65% of cases, respectively. In 83% of tumors with type 0 halfway through NAC, pathology assessment showed pCR. There was no significant correlation between MRI-based response patterns after NAC and tumor reduction rates on pathology assessment (reader 1 r = - 0.17; p = 0.145 and reader 2 r = - 0.17; p = 0.146). In 41% of tumors with type 0 after NAC, pathology assessment showed pCR. CONCLUSION:MRI-based response patterns halfway through NAC can predict pathologic response more accurately than MRI-based response patterns after NAC. Complete radiological response halfway NAC is associated with 83% pCR, while complete radiological response after NAC seems to be correct in only 41% of cases.

Dataset Information

MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer.

Publications

MicroRNAs miR-7 and miR-340 predict response to neoadjuvant chemotherapy in breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets