Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Internal validation cohort of breast cancers for development of ClinicoMolecular Triad Classification

ABSTRACT: In our early study ([GEO Accession: GSE16987], [PMID: 21939527]), we have created a ClinicoMolecular Triad Classification (CMTC) to improve prediction and prognostication of breast cancer by using a training cohort contained 161 breast cancer patients (2003 to 2008). Here, a supplemental internal validation cohort contained 340 breast cancer patients was collected (2008 to 2010) for development of the CMTC. Total 340 fine-needle aspirates (FNA) specimens from breast tumors without replicate were collected and prepared for microarray examination. Finally, 284 invasive breast cancers were used in this study.

ORGANISM(S): Homo sapiens

SUBMITTER: Dong-Yu Wang

PROVIDER: E-GEOD-45725 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, β-Catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures. 149 invasive breast cancers from the 172 specimens contained 161 tumors were used in this study. Expression data of the 11 tumors with replicate was separately combined before analysis.

Dataset Information

Internal validation cohort of breast cancers for development of ClinicoMolecular Triad Classification

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure