An assessment of prognostic immunity markers in breast cancer
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ABSTRACT:
PROVIDER: PRJNA454288 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We used Targeted RNA-seq to generate a gene expression data set of the 72-gene panel (TARGETSEQ) including 483 targeted RNA-seq data of 225 breast cancer FFPE samples from Shanghai and 258 breast cancer FFPE samples from UNC at Chapel Hill. The identified gene panel and risk evaluation model iRDM were developed in training data set AFFY1951 (p<0.0001, n=1951) and further validated in two other published gene expression datasets including Illumina beads array data METABRIC (p<0.0001, n=1997) and whole transcriptomic mRNA-seq data TCGA (p=0.00019, n=996) and in our own targeted RNA-seq data TARGETSEQ (p<0.0001, n=303) (of 483 RNA-seq samples, 303 with survival data). In conclusion, immunity gene expression were an important parameter for prognosis and therefore can be incorporated into current multi-gene assays to improve assessment of risk of distant metastasis in breast cancer.
2018-10-01 | GSE113863 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE22216: microRNA expression profiling of early primary breast cancer to identify prognostic markers and associated pathways GSE22219: Gene expression profiling of early primary breast cancer to identify prognostic markers and associated pathways Refer to individual Series. Supplementary file: Shows correspondence between mRNA and miRNA samples.
2011-07-08 | E-GEOD-22220 | biostudies-arrayexpress
Project description:There are no widely-accepted prognostic markers currently available to predict outcomes in patients with triple-negative breast cancer (TNBC), and no targeted therapies with confirmed benefit. We have used MALDI mass spectrometry imaging (MSI) of tryptic peptides to compare regions of cancer and benign tissue in 10 formalin-fixed, paraffin-embedded sections of TNBC tumors. Proteins were identified by reference to a peptide library constructed by LC-MALDI-MS/MS analyses of the same tissues. The prognostic significance of proteins that distinguished between cancer and benign regions was estimated by Kaplan-Meier analysis of their gene expression from public databases. Among peptides that distinguished between cancer and benign tissue in at least 3 tissues with a ROC area under the curve >0.7, 14 represented proteins identified from the reference library, including proteins not previously associated with breast cancer. Initial network analysis using the STRING database showed no obvious functional relationships except among collagen subunits COL1A1, COL1A2, and COL63A, but manual curation, including the addition of EGFR to the analysis, revealed a unique network connecting 10 of the 14 proteins. Kaplan-Meier survival analysis to examine the relationship between tumor expression of genes encoding the 14 proteins, and recurrence-free survival (RFS) in patients with basal-like TNBC showed that, compared to low expression, high expression of nine of the genes was associated with significantly worse RFS, most with hazard ratios >2. In contrast, in estrogen receptor-positive tumors, high expression of these genes showed only low, or no, association with worse RFS. These proteins are proposed as putative markers of RFS in TNBC, and some may also be considered as possible targets for future therapies.
2019-05-06 | PXD013397 | Pride
Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.
2012-09-18 | E-GEOD-40954 | biostudies-arrayexpress
Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease.
2012-09-18 | GSE40954 | GEO
Project description:Prognostication of Breast Cancer (BC) relies largely on traditional markers such as hormone or growth factors but due to their suboptimal specificities, it is challenging to identify the subset of patients who are likely to undergo recurrence and markers of higher specificity are sought to guide therapies. MicroRNAs (miRNAs) are small non-coding RNAs which function as post-transcriptional regulators of gene expression and have shown promise as potential prognostic markers in several cancer types including BC. In our study, we sequenced 104 breast tumor tissue samples and 11 apparently healthy normal breast tissues for miRNAs. Two widely used approaches were adopted to identify prognostic markers â Case-control and Case-only. For both the approaches, Cox-proportional hazards regression model and risk score analysis was performed to identify miRNA signature independent of potential confounders. Representative miRNAs were validated using qRT-PCR. Gene ontology terms were identified for miRNAs significant in survival analysis. A total of 1,423 miRNAs were captured from the tissues, of which 126 were retained with predetermined criteria for good read counts. In the case-control approach, 80 miRNAs were differentially expressed, from which four and two miRNAs were significant for OS and RFS respectively. In the case-only approach, from 147 miRNAs, 11 and four miRNAs were significant for OS and RFS respectively, in which miR-574-3p and miR-660-5p were novel and were not previously found to be associated with BC prognosis. Multivariate Cox analysis indicated that the risk scores calculated in both the approaches were potential independent prognostic factors for BC. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration. Identification of miRNAs as prognostic markers for breast cancer
2016-03-02 | E-GEOD-68085 | biostudies-arrayexpress
Project description: Not available
| S-EPMC6206135 | biostudies-literature
Project description:Retrospective series of primary breast cancer patients who received surgery between 1989 and 1992. Patients received adjuvant chemotherapy and/or adjuvant hormone therapy, or no adjuvant treatment. Tamoxifen was used as endocrine therapy for 5 years in ER+ BC patients. Patients who were <50 years of age, with lymph node positive tumors, or ER– and/or >3 cm in diameter, received adjuvant cyclophosphamide, methotrexate, and 5-fluorouracil (CMF) for six cycles, in a thrice weekly intravenous regimen. Patients >50 years of age with ER–, lymph node–positive tumors also received CMF. Retrospective clinical study to identify breast cancer prognostic markers and associated pathways. 210 early primary breast cancers were considered who had complete 10-years follow-up, clinical and demographics information. miRNA profiling data.
2011-07-08 | E-GEOD-22216 | biostudies-arrayexpress
Project description:Retrospective series of primary breast cancer patients who received surgery between 1989 and 1992. Patients received adjuvant chemotherapy and/or adjuvant hormone therapy, or no adjuvant treatment. Tamoxifen was used as endocrine therapy for 5 years in ER+ BC patients. Patients who were <50 years of age, with lymph node positive tumors, or ER– and/or >3 cm in diameter, received adjuvant cyclophosphamide, methotrexate, and 5-fluorouracil (CMF) for six cycles, in a thrice weekly intravenous regimen. Patients >50 years of age with ER–, lymph node–positive tumors also received CMF. Retrospective clinical study to identify breast cancer prognostic markers and associated pathways. 216 early primary breast cancers were considered who had complete 10-years follow-up, clinical and demographics information. mRNA profiling data.
2011-07-08 | E-GEOD-22219 | biostudies-arrayexpress
Project description:proteomics identified potential prognostic markers in early ovarian
2020-11-09 | PXD022436 | iProX