Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human breast cancer and a modular analysis of reveals a novel low-grade molecular signature in estrogen receptor-positive tumors

ABSTRACT: Primary human breast tumors were obtained from the National Cancer Centre of Singapore (NCC) Tissue Repository, after appropriate approvals from the NCC Repository and Ethics Committees. Profiled samples contained at least 50% tumor content.

ORGANISM(S): Homo sapiens

SUBMITTER: Kun Yu

PROVIDER: E-GEOD-2294 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor-positive tumors.

Yu Kun K Ganesan Kumaresan K Miller Lance D LD Tan Patrick P

Clinical cancer research : an official journal of the American Association for Cancer Research 20060601 11 Pt 1

<h4>Purpose</h4>Previous reports using genome-wide gene expression data to classify breast tumors have typically used standard unsupervised or supervised techniques, both of which have known limitations. We hypothesized that novel clinically relevant information could be revealed in these data sets by an alternative analytic approach. Using a recently described algorithm, signature analysis (SA), we identified "modules," comprising groups of tightly coexpressed genes that are conditionally linke ...[more]

PMID: 16740749

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Project description:Successful carcinogenesis involves the integration of both pro- and anti-oncogenic pathways. We postulated that genes critical for balancing these opposing pathways are likely to be precisely controlled in tumors, since even subtle alterations in their activity might cause substantial alterations in tumor growth and survival. Using a novel genomic approach, we identified a 48-gene âPoised Gene Cassetteâ (PGC) showing tight regulation specifically in human cancers but not in corresponding nonmalignant tissues. We show, using a wide variety of in vitro and in vivo approaches, that small alterations in PGC expression are consistently associated with significant differences in experimental metastasis and patient survival, and we demonstrate a direct functional role for five PGC genes (p53CSV, MAP3K11, MTCH2, CPSF6 and SKIP) in cancer invasion. Our findings support the existence of a novel class of ultrasensitive genes that may regulate various cancer-associated phenotypes such as metastasis. Such precisely controlled genes could represent appealing drug targets, since even partial alterations in their activity should prove sufficient to induce potent effects on tumors. Besides cancer, our analytical approach is quite generalizable and likely to be applicable to other disease conditions. Experiment Overall Design: Primary human tumor and adjacent normal tissues were obtained from the Tissue Repository of the National Cancer Centre of Singapore (NCCS). Appropriate institutional approvals were obtained from the NCCS Tissue Repository and Ethics Committees. In the operating theater, morphologically visible tumor and adjacent matched normal tissues were removed by surgery and examined by a surgical pathologist to confirm the presence of cancer cells by cryosections. The tissue samples were divided into discrete aliquots, flash frozen and subsequently stored in liquid nitrogen. The detailed information regarding samples is available in Supplementary Information S1. The training set used in this study comprises 341 samples (270 tumors and 71 matched normals) from patients with breast, colon, liver, lung, oesophagal and thyroid cancer (Tissue Type/Tumor/Normal : Lung/18/12, Thyroid/35/16, Liver/9/8, Oesophagus/16/13, Colon/9/9, Breast/183/13.)

Dataset Information

Transcription profiling of human breast cancer and a modular analysis of reveals a novel low-grade molecular signature in estrogen receptor-positive tumors

Publications

A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor-positive tumors.

Similar Datasets

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