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Basal epithelial subpopulations underlie and predict chemotherapy resistance in Triple-Negative Breast Cancer

ABSTRACT: Basal epithelial subpopulations underlie and predict chemotherapy resistance in Triple-Negative Breast Cancer

PROVIDER: PRJNA1059632 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR27393214.fastq.gz	Fastqsanger.gz
	SRR27393215.fastq.gz	Fastqsanger.gz
	SRR27393216.fastq.gz	Fastqsanger.gz
	SRR27393217.fastq.gz	Fastqsanger.gz
	SRR27393218.fastq.gz	Fastqsanger.gz

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Project description:A gene expression signature characterizes expression data from breast cancer samples of patients with pathological complete response (pCR) or residual disease (RD) following the neoadjuvant trial. Several gene expression profiles have been reported to predict breast cancer response to neoadjuvant chemotherapy. These studies often consider breast cancer as a homogeneous entity, although higher rates of pathologic complete response (pCR) are known to occur within the basal-like subclass. We postulated that profiles with higher predictive accuracy could be derived from a subset analysis of basal-like tumors in isolation. Using a previously described ‘‘intrinsic’’ signature to differentiate breast tumor subclasses, we identified 50 basal-like tumors from two independent clinical trials associated with gene expression profile data. 24 tumor data sets (included in this GEO submission) were derived from a 119-patient neoadjuvant trial at our institution and an additional 26 tumor data sets were identified from a published data set (Hess et al. J Clin Oncol 24:4236–4244, 2006). The combined 50 basal-like tumors were partitioned to form a 37 sample training set with 13 sequestered for validation. Clinical surveillance occurred for a mean of 26 months. We identified a 23-gene profile which predicted pCR in basal-like breast cancers with 92% predictive accuracy in the sequestered validation data set. Furthermore, distinct cluster of patients with high rates of cancer recurrence was observed based on cluster analysis with the 23-gene signature. Disease-free survival analysis of these three clusters revealed significantly reduced survival in the patients of this high recurrence cluster. We identified a 23- gene signature which predicts response of basal-like breast cancer to neoadjuvant chemotherapy as well as disease-free survival. This signature is independent of tissue collection method and chemotherapeutic regimen. Keywords: Disease state analysis

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Basal epithelial subpopulations underlie and predict chemotherapy resistance in Triple-Negative Breast Cancer

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