Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Molecular characteristics and metastasis predictor genes of triple-negative breast cancer (II)

ABSTRACT: This microarray dataset contains 51 triple-negative breast cancers, 25 normal breast tissues, and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). Keywords: Expression profiling by array Specimens of breast cancer tissue were collected and snap-frozen from breast cancer patients who had surgery between 1995 and 2008 at National Taiwan University Hospital (NTUH, Taipei, Taiwan). Clinicopathological information was obtained for all breast cancer patients along with informed consent. The AJCC/UICC TNM system was used for breast cancer staging classification.

ORGANISM(S): Homo sapiens

SUBMITTER: King-Jen Chang

PROVIDER: E-GEOD-53752 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Twenty-four triple-negative breast cancer and 14 adjacent normal tissues were collected from breast cancer patients during surgeries at National Taiwan University Hospital (NTUH, Taipei, Taiwan). All triple-negative breast cancer samples were invasive ductal carcinomas (IDC) and were negative in immunohistochemical statuses of ER, PR, and HER2 receptors, as confirmed by professional pathologists. Treatment procedure of all patients followed the National Comprehensive Cancer Network (NCCN) guideline. All samples were neoadjuvant-free and were collected before systemic chemotherapy treatments. Written informed consent was obtained from all patients who participated in this study. Using human tissues for research in this study was approved by the institutional review board at NTUH. A novel set of 25-miRNA signature identified in this study was able to effectively distinguish between triple-negative breast cancer and adjacent normal tissues. Moreover, we documented the first evidence of seven polycistronic miRNA clusters preferentially harboring deregulated miRNA genes in triple-negative breast cancer. In the present study, a panel of 24 triple-negative breast cancer and 14 adjacent normal tissue samples were examined for the presence of deregulated miRNA genes using the high-throughput sequencing technology. Total RNA was extracted from the triple-negative breast cancer and adjacent normal samples for preparation of small RNA libraries. Each small RNA library was constructed from total RNA of each sample using the SOLiD Total RNA-Seq Kit (Applied Biosystems, Foster City, CA, USA). Upon completion of polymerase chain reaction (PCR) amplification, small RNA libraries were purified using the SOLiD Library Micro Column Purification Kit (Applied Biosystems) and hybridized to the template beads using the SOLiD EZ bead system (Applied Biosystems). The template beads were amplified and deposited onto subtract for ligation sequencing by SOLiD 4 System (Applied Biosystems).

Project description:Background: We have established a statistical approach on building a transcriptional regulatory network in silico at a global transcriptome scale. Here, we characterize clinical relevant gene activities regulated by a transcription factor-estrogen-related receptor gamma (ESRRG) via such approach. Methods: We measured gene expression relationship between ESRRG and its target gene via univariate coefficient of intrinsic dependence and Galton Pearson’s correlation coefficient. A few more bioinformatics tools were used for further investigation on ESRRG. Results: ESRRG is a negative determinant of lymphovascular invasion, lymph nodal category, stage, histological grade, nuclear pleomorphism and tubule formation in ER(+) infiltrating ductal carcinoma of breast. Interestingly, ESRRG was the only one in the final intersection of Venn Diagram analyses for determinants of those clinical indices. We established an ESRRG core network consisting of 118 probes. Both MYB and ARNT2 were up-regulated by ESRRG and in two ESRRG subnetworks (29 probes, 89 probes), respectively. We observed genes for tumor suppressive activities and responsiveness to anticancer treatments within ESRRG core network and a conserved protective role of ESRRG. Conclusions: ESRRG is a tumor suppressor typically for ER(+) breast cancer and up-regulates tumor suppressor genes mostly within ERα transcriptional regulatory network. An ESRRG core network reveals ESRRG to be a favorable marker and MYB to be the main partner for its cancer protective role during early tumor promotion. But, ARNT2 is an additional partner of ESRRG during early tumor progression. Impact: A core ESRRG transcriptional regulatory network indicates the major clinical impact of ESRRG. 181 surgical specimens of primary infiltrating ductal carcinoma (IDC) were obtained from patients who underwent surgery at National Taiwan University Hospital (NTUH) between 1998 and 2007. They include 90 ER(+) IDCs and 91 ER(-) IDCs. Tissue samples were excised, snap frozen in liquid nitrogen, and stored at -80℃. Breast cancer samples containing relatively pure cancer as defined by greater than 50% tumor cells per high-power field examined in an adjacent section of tumor sample were for this study (Lien HC, et al. Oncogene 2007; 26: 7859-71). Twenty five non-tumor samples were surgically taken from breast cancer patients in 181 IDC patients to generate 25 gene expression profiles as a control in this study. All patients had given informed consent according to the guidelines approved by the Institutional Review Board at NTUH. The matrix file linked to the bottom of this Series includes reanalyzed data from the 119 Samples of this Series and 87 Samples from Series GSE9309 and GSE17040.

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Molecular characteristics and metastasis predictor genes of triple-negative breast cancer (II)

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