Ontology highlight
ABSTRACT:
PROVIDER: PRJNA482683 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7589070.fastq.gz | Fastqsanger.gz | |||
| SRR7589080.fastq.gz | Fastqsanger.gz | |||
| SRR7589071.fastq.gz | Fastqsanger.gz | |||
| SRR7589081.fastq.gz | Fastqsanger.gz | |||
| SRR7589072.fastq.gz | Fastqsanger.gz |
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Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients.
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Project description:Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients. Whole genome expression profiling of breast cancers from 185 patients in Taiwan from 1995 to 2008 was performed, and the results were compared to the previously published literature to detect differences between Asian and Western patients. Pathway analysis and Cox proportional hazard models were applied to construct a prediction model for the recurrence of triple negative breast cancer. Most expression data of samples (181/185) were reanalyzed from previous studies already uploaded to GEO (see "reanalysis of" links below). Four additional gene expression profiling data of triple negative breast cancer sample were added to this study.
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Project description:DNA methylation biomarkers for non-invasive detection of triple negative breast cancer using liquid biopsy
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Project description:An iTRQA-based quantitative proteome analysis using liquid chromatography–coupled tandem mass spectrometry was performed to acquire proteome-wide expression data on Triple-negative Breast Cancer (TNBC) cells treated with Rocaglamide A for 24 hours.
2024-12-08 | PXD047648 | JPOST Repository
Project description:Triple-negative breast cancer represents approximately 15–20% of all reported breast cancer cases, and is characterized by a shorter survival time and higher mortality rates compared to other breast cancer sub-types. Tumor microenvironment (TME) refers to the internal and external environment of tumor tissue. Increasing evidence indicates that a tumor’s microenvironment is tightly associated with the immunological surveillance and defense during the development of breast cancer. Although oncology studies employing digital dissection methodologies have provided some insight on the biological features of TME, the development of methods to investigate the cellular composition of the tumor microenvironment remain an important research priority. In this study, we extracted whole transcriptome from 30 Triple-negative breast cancer (TNBC) patients and then used bioinformatics approaches to characterize cell type content in tumor tissue compared with para-cancerous tissue. We identified 4 types of enriched immune cells and 6 types of downregulated immune cells in the tumor tissue samples. After comprehensive bioinformatics analyses, we developed an ‘immune infiltration score’ (IIS) to quantitatively model immune cell infiltration in TNBC. To demonstrate the utility of the IIS, we used 2 independent datasets for validation. We found that patients with a higher IIS showing a longer progression-free survival time and significantly better prognosis than those with a lower IIS value. In sum, we explored the immune infiltration landscape in 30 TNBC patients and provided a novel and reliable biomarker IIS to evaluate the progression-free survival and prognosis in the TNBC patients.
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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.
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Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
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Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
2018-08-31 | GSE86945 | GEO