TWIST1 Gene expression as a biomarker for predicting primary doxorubicin resistance in breast cancer (original) (raw)
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Gene Expression Profile Associated with Response to Doxorubicin-Based Therapy in Breast Cancer
Clinical Cancer Research, 2005
This study was designed to identify genes that could predict response to doxorubicinbased primary chemotherapy in breast cancer patients. Experimental Design: Biopsy samples were obtained before primary treatment with doxorubicin and cyclophosphamide. RNA was extracted and amplified and gene expression was analyzed using cDNA microarrays. Results: Response to chemotherapy was evaluated in 51patients, and based on Response Evaluation Criteria in Solid Tumors guidelines, 42 patients, who presented at least a partial response (z30% reduction in tumor dimension), were classified as responsive. Gene profile of samples, divided into training set (n = 38) and independent validation set (n = 13), were at first analyzed against a cDNA microarray platform containing 692 genes. Unsupervised clustering could not separate responders from nonresponders. A classifier was identified comprising EMILIN1, FAM14B, and PBEF, which however could not correctly classify samples included in the validation set. Our next step was to analyze gene profile in a more comprehensive cDNA microarray platform, containing 4,608 open reading frame expressed sequence tags. Seven samples of the initial training set (all responder patients) could not be analyzed. Unsupervised clustering could correctly group all the resistant samples as well as at least 85% of the sensitive samples. Additionally, a classifier, including PRSS11, MTSS1, and CLPTM1, could correctly distinguish 95.4% of the 44 samples analyzed, with only two misclassifications, one sensitive sample and one resistant tumor. The robustness of this classifier is 2.5 greater than the first one. Conclusion: A trio of genes might potentially distinguish doxorubicin-responsive from nonresponsive tumors, but further validation by a larger number of samples is still needed. Primary chemotherapy in breast cancer is associated to the same survival benefit as adjuvant chemotherapy and offers the advantage of an increased likelihood of breast conservation (1, 2). Many drug regimens have been used for a varied number of cycles, and response rates from 65% to 100% have been achieved in operable breast cancer; two of the most used, doxorubicin and cyclophosphamide, when given before surgery, are associated with an 80% response rate of breast tumor size (1, 3). Contrariwise, some patients may not experience a tumor reduction with a particular drug regimen, and if identified, they could be offered other active drug regimens or be submitted, at once, to surgical intervention. Although predictive factors might help selection of the appropriate treatment for each individual patient, to date, there is no single marker with a predictive value for a patient's response to chemotherapy (4). A few studies have been looking for a gene profile that might predict response to primary chemotherapy in breast cancer (5-8). There is therefore much interest in breast cancer transcriptional profiling and its role in tailoring therapy. This study was undertaken to identify genes that could predict response to doxorubicin-based primary chemotherapy in breast cancer patients.
Journal of Experimental & Clinical Cancer Research
Background Triple negative breast cancer (TNBC) is a heterogeneous disease with aggressive behavior and an unfavorable prognosis rate. Due to the lack of surface receptors, TNBC must be intensely investigated in order to establish a suitable treatment for patients with this pathology. Chemoresistance is an important reason for therapeutic failure in TNBC. Method The aim of this study was to investigate the effect of doxorubicin in TNBC cell lines and to highlight cellular and molecular alterations after a long exposure to doxorubicin. Results The results revealed that doxorubicin significantly increased the half maximal inhibitory concentration (IC50) values at P12 and P24 compared to parenteral cells P0. Modifications in gene expression were investigated through microarray technique, and for detection of mutational pattern was used Next Generation Sequencing (NGS). 196 upregulated and 115 downregulated genes were observed as effect of multiple dose exposure, and 15 overexpressed ge...
Cancer Epidemiology, Biomarkers & Prevention, 2008
TWIST1, an antiapoptotic and prometastatic transcription factor, is overexpressed in many epithelial cancers including breast. Only little is known regarding the regulation of TWIST1 in these cancers. Recently, an increase in the TWIST1 promoter methylation has been shown in breast cancers. To correlate the percentage of TWIST1 promoter methylation to the protein levels, we analyzed simultaneously the methylation status as well as the mRNA and the percentage of cells expressing TWIST1 in normal breast tissue and 76 invasive breast cancers. We found that TWIST1 promoter methylation is significantly more prevalent in malignant compared with healthy breast tissue. Furthermore, the percentage of cells expressing TWIST1 was greater in breast malignancy compared with matched healthy tissue from the same patients. There was no correlation, however, between TWIST1 promoter methylation and TWIST1 protein or RNA expression. This indicates that although TWIST1 CpG methylation is useful as a bi...
Breast Cancer Research, 2012
High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes Abstract Introduction: The TWIST homolog 1 (TWIST1) is a transcription factor that induces epithelial to mesenchymal transition (EMT), a key process in metastasis. The purpose of this study was to investigate whether TWIST1 expression predicts disease progression in a large breast cancer cohort with long-term clinical follow-up, and to reveal the biology related to TWIST1 mediated disease progression. Methods: TWIST1 mRNA expression level was analyzed by quantitative real-time reverse polymerase chain reaction (RT-PCR) in 1,427 primary breast cancers. In uni-and multivariate analysis using Cox regression, TWIST1 mRNA expression level was associated with metastasis-free survival (MFS), disease-free survival (DFS) and overall survival (OS). Separate analyses in lymph node-negative patients (LNN, n = 778) who did not receive adjuvant systemic therapy, before and after stratification into estrogen receptor (ER)-positive (n = 552) and ER-negative (n = 226) disease, were also performed. The association of TWIST1 mRNA with survival endpoints was assessed using Kaplan-Meier analysis. Using gene expression arrays, genes showing a significant Spearman rank correlation with TWIST1 were used to identify overrepresented Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated biological pathways.
2000
Drug resistance in cancer is a major obstacle to successful chemotherapy. Cancer cells exposed to antitumor drugs may be directly induced to express a subset of genes that could confer resistance, thus allowing some cells to escape killing and form the relapsed resistant tumor. Alternatively, some cancer cells may be expressing an array of genes that could confer intrinsic resistance, and exposure to cytotoxic drugs select for the survival of these cells that form the relapsed tumor. We have used cDNA microarray to monitor the expression profiles of MCF-7 cells that are either transiently treated with doxorubicin or selected for resistance to doxorubicin. Our results showed that transient treatment with doxorubicin altered the expression of a diverse group of genes in a time-dependent manner. A subset of the induced genes was also found to be constitutively overexpressed in cells selected for resistance to doxorubicin. This distinct set of overlapping genes may represent the signature profile of doxorubicin-induced gene expression and resistance in cancer cells. Our studies demonstrate the feasibility of obtaining potential molecular profile or fingerprint of anticancer drugs in cancer cells by cDNA microarray, which might yield further insights into the mechanisms of drug resistance and suggest alternative methods of treatment.
Gene expression alterations in doxorubicin resistant MCF7 breast cancer cell line
Genomics, 2013
Many molecular mechanisms contribute to the development of doxorubicin resistance and different cancers can express wide and diverse arrays of drug-resistance genes. The aim of this study was to identify the changes in gene expression associated with the development of doxorubicin resistance in MCF7 breast cancer cell line. The doxorubicin resistant MCF7 cell line was developed by stepwise selection of MCF7 cells and was tested using the MTT assay. The alterations in gene expression were examined using the real-time based PCR array. The findings showed an up-regulation of many phase I/II metabolizing genes, specifically, the CYP1A1 and the CYP1A2 that were up-regulated by 206-and 96-fold respectively. Drug efflux pump genes were also up-regulated profoundly. TOP2A was strongly down-regulated by 202-fold. Many other changes were observed in genes crucial for cell cycle, apoptosis and DNA repair. The findings of this project imply that the development of doxorubicin resistance is a multi-factorial process.
Cancer research, 2000
Drug resistance in cancer is a major obstacle to successful chemotherapy. Cancer cells exposed to antitumor drugs may be directly induced to express a subset of genes that could confer resistance, thus allowing some cells to escape killing and form the relapsed resistant tumor. Alternatively, some cancer cells may be expressing an array of genes that could confer intrinsic resistance, and exposure to cytotoxic drugs select for the survival of these cells that form the relapsed tumor. We have used cDNA microarray to monitor the expression profiles of MCF-7 cells that are either transiently treated with doxorubicin or selected for resistance to doxorubicin. Our results showed that transient treatment with doxorubicin altered the expression of a diverse group of genes in a time-dependent manner. A subset of the induced genes was also found to be constitutively overexpressed in cells selected for resistance to doxorubicin. This distinct set of overlapping genes may represent the signatu...
Frontiers in Oncology
IntroductionThe molecular mechanism of chemotherapy resistance in breast cancer is not well understood. The identification of genes associated with chemoresistance is critical for a better understanding of the molecular processes driving resistance.MethodsThis study used a co-expression network analysis of Adriamycin (or doxorubicin)-resistant MCF-7 (MCF-7/ADR) and its parent MCF-7 cell lines to explore the mechanisms of drug resistance in breast cancer. Genes associated with doxorubicin resistance were extracted from two microarray datasets (GSE24460 and GSE76540) obtained from the Gene Expression Omnibus (GEO) database using the GEO2R web tool. The candidate differentially expressed genes (DEGs) with the highest degree and/or betweenness in the co-expression network were selected for further analysis. The expression of major DEGs was validated experimentally using qRT–PCR.ResultsWe identified twelve DEGs in MCF-7/ADR compared with its parent MCF-7 cell line, including 10 upregulat...
Brazilian Journal of Medical and Biological Research, 2010
In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1, MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1 based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.