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Genome-wide profiles of methylation, microRNAs, and gene expression in chemoresistant breast cancer.

He DX, Gu F, Gao F, Hao JJ, Gong D, Gu XT, Mao AQ, Jin J, Fu L, Ma X - Sci Rep (2016)

Bottom Line: Cancer chemoresistance is regulated by complex genetic and epigenetic networks.In this study, the features of gene expression, methylation, and microRNA (miRNA) expression were investigated with high-throughput sequencing in human breast cancer MCF-7 cells resistant to adriamycin (MCF-7/ADM) and paclitaxel (MCF-7/PTX).In conclusion, our results have generated a new workflow for the integrated analysis of the effects of miRNAs and methylation on gene expression during the development of chemoresistance.

View Article: PubMed Central - PubMed

Affiliation: National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China.

ABSTRACT
Cancer chemoresistance is regulated by complex genetic and epigenetic networks. In this study, the features of gene expression, methylation, and microRNA (miRNA) expression were investigated with high-throughput sequencing in human breast cancer MCF-7 cells resistant to adriamycin (MCF-7/ADM) and paclitaxel (MCF-7/PTX). We found that: ① both of the chemoresistant cell lines had similar, massive changes in gene expression, methylation, and miRNA expression versus chemosensitive controls. ② Pairwise integration of the data highlighted sets of genes that were regulated by either methylation or miRNAs, and sets of miRNAs whose expression was controlled by DNA methylation in chemoresistant cells. ③ By combining the three sets of high-throughput data, we obtained a list of genes whose expression was regulated by both methylation and miRNAs in chemoresistant cells; ④ Expression of these genes was then validated in clinical breast cancer samples to generate a 17-gene signature that showed good predictive and prognostic power in triple-negative breast cancer patients receiving anthracycline-taxane-based neoadjuvant chemotherapy. In conclusion, our results have generated a new workflow for the integrated analysis of the effects of miRNAs and methylation on gene expression during the development of chemoresistance.

No MeSH data available.


Related in: MedlinePlus

Clinical validation of the signature.(a) Validation of the signature in resistant (R) and sensitive (S) TNBC patients from the training cohort with hierarchical clustering (left panel) and Bayesian binary regression (right panel). (b) Validation of the signature in TNBC patients in the GSE25055 (left panel), 25065 (middle panel), and 41998 (right panel) databases by Bayesian binary regression. (c) Effectiveness of the signature in predicting the prognosis in TNBC patients from the GSE25055 (left panel), 25065 (2nd left panel), 45725 (right panel), and 33926 (2nd right panel) databases. Patients were grouped according to their potential chemoresponse predicted by the signature. (d) Forest plots of the performance of the chemoresistance signature in predicting clinical outcomes. Odds ratios (OR) are plotted as vertical colored bars for comparison. The length of the horizontal bars and the width of the diamonds correspond to 95% confidence intervals. The diamond represents the total OR of the signature in the total cases. The weight means the size of each dataset versus the total cases.
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f5: Clinical validation of the signature.(a) Validation of the signature in resistant (R) and sensitive (S) TNBC patients from the training cohort with hierarchical clustering (left panel) and Bayesian binary regression (right panel). (b) Validation of the signature in TNBC patients in the GSE25055 (left panel), 25065 (middle panel), and 41998 (right panel) databases by Bayesian binary regression. (c) Effectiveness of the signature in predicting the prognosis in TNBC patients from the GSE25055 (left panel), 25065 (2nd left panel), 45725 (right panel), and 33926 (2nd right panel) databases. Patients were grouped according to their potential chemoresponse predicted by the signature. (d) Forest plots of the performance of the chemoresistance signature in predicting clinical outcomes. Odds ratios (OR) are plotted as vertical colored bars for comparison. The length of the horizontal bars and the width of the diamonds correspond to 95% confidence intervals. The diamond represents the total OR of the signature in the total cases. The weight means the size of each dataset versus the total cases.

Mentions: The discriminatory power of the signature was analyzed first in the training cohort formed by the TNBC samples we had collected. Hierarchical clustering25 and Bayesian binary regression26 were used as classifiers. The signature classified the chemoresistant and chemosensitive patients with an overall accuracy of 100% for hierarchical clustering and 100% for Bayesian binary regression (Fig. 5a), suggesting that the signature can discriminate between resistant and sensitive TNBC patients.


Genome-wide profiles of methylation, microRNAs, and gene expression in chemoresistant breast cancer.

He DX, Gu F, Gao F, Hao JJ, Gong D, Gu XT, Mao AQ, Jin J, Fu L, Ma X - Sci Rep (2016)

Clinical validation of the signature.(a) Validation of the signature in resistant (R) and sensitive (S) TNBC patients from the training cohort with hierarchical clustering (left panel) and Bayesian binary regression (right panel). (b) Validation of the signature in TNBC patients in the GSE25055 (left panel), 25065 (middle panel), and 41998 (right panel) databases by Bayesian binary regression. (c) Effectiveness of the signature in predicting the prognosis in TNBC patients from the GSE25055 (left panel), 25065 (2nd left panel), 45725 (right panel), and 33926 (2nd right panel) databases. Patients were grouped according to their potential chemoresponse predicted by the signature. (d) Forest plots of the performance of the chemoresistance signature in predicting clinical outcomes. Odds ratios (OR) are plotted as vertical colored bars for comparison. The length of the horizontal bars and the width of the diamonds correspond to 95% confidence intervals. The diamond represents the total OR of the signature in the total cases. The weight means the size of each dataset versus the total cases.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4837395&req=5

f5: Clinical validation of the signature.(a) Validation of the signature in resistant (R) and sensitive (S) TNBC patients from the training cohort with hierarchical clustering (left panel) and Bayesian binary regression (right panel). (b) Validation of the signature in TNBC patients in the GSE25055 (left panel), 25065 (middle panel), and 41998 (right panel) databases by Bayesian binary regression. (c) Effectiveness of the signature in predicting the prognosis in TNBC patients from the GSE25055 (left panel), 25065 (2nd left panel), 45725 (right panel), and 33926 (2nd right panel) databases. Patients were grouped according to their potential chemoresponse predicted by the signature. (d) Forest plots of the performance of the chemoresistance signature in predicting clinical outcomes. Odds ratios (OR) are plotted as vertical colored bars for comparison. The length of the horizontal bars and the width of the diamonds correspond to 95% confidence intervals. The diamond represents the total OR of the signature in the total cases. The weight means the size of each dataset versus the total cases.
Mentions: The discriminatory power of the signature was analyzed first in the training cohort formed by the TNBC samples we had collected. Hierarchical clustering25 and Bayesian binary regression26 were used as classifiers. The signature classified the chemoresistant and chemosensitive patients with an overall accuracy of 100% for hierarchical clustering and 100% for Bayesian binary regression (Fig. 5a), suggesting that the signature can discriminate between resistant and sensitive TNBC patients.

Bottom Line: Cancer chemoresistance is regulated by complex genetic and epigenetic networks.In this study, the features of gene expression, methylation, and microRNA (miRNA) expression were investigated with high-throughput sequencing in human breast cancer MCF-7 cells resistant to adriamycin (MCF-7/ADM) and paclitaxel (MCF-7/PTX).In conclusion, our results have generated a new workflow for the integrated analysis of the effects of miRNAs and methylation on gene expression during the development of chemoresistance.

View Article: PubMed Central - PubMed

Affiliation: National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China.

ABSTRACT
Cancer chemoresistance is regulated by complex genetic and epigenetic networks. In this study, the features of gene expression, methylation, and microRNA (miRNA) expression were investigated with high-throughput sequencing in human breast cancer MCF-7 cells resistant to adriamycin (MCF-7/ADM) and paclitaxel (MCF-7/PTX). We found that: ① both of the chemoresistant cell lines had similar, massive changes in gene expression, methylation, and miRNA expression versus chemosensitive controls. ② Pairwise integration of the data highlighted sets of genes that were regulated by either methylation or miRNAs, and sets of miRNAs whose expression was controlled by DNA methylation in chemoresistant cells. ③ By combining the three sets of high-throughput data, we obtained a list of genes whose expression was regulated by both methylation and miRNAs in chemoresistant cells; ④ Expression of these genes was then validated in clinical breast cancer samples to generate a 17-gene signature that showed good predictive and prognostic power in triple-negative breast cancer patients receiving anthracycline-taxane-based neoadjuvant chemotherapy. In conclusion, our results have generated a new workflow for the integrated analysis of the effects of miRNAs and methylation on gene expression during the development of chemoresistance.

No MeSH data available.


Related in: MedlinePlus