Expression data from invasive breast cancer patient
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE102484 | GEO | 2017/08/11
SECONDARY ACCESSION(S): PRJNA397866
REPOSITORIES: GEO
Similar Datasets
Project description:Breast cancer (BC) adjuvant therapy after mastectomy in the setting of 1-3 positive lymph nodes has been controversial. This retrospective Translational Breast Cancer Research Consortium study evaluated molecular aberrations in primary cancers associated with locoregional recurrence (LRR) or distant metastasis (DM) compared to non-recurrent controls. We identified 115 HER2 negative, therapy naïve, T 1-3 and N 0-1 BC patients treated with mastectomy but no post-mastectomy radiotherapy. This included 32 LRR, 34 DM and 49 controls. RNAseq was performed on primary tumors in 110 patients; with no difference in RNA profiles between patients with LRR, DM or controls. DNA analysis on 57 primary tumors (17 LRR, 15 DM and 25 controls) identified significantly more NF1 mutations and mitogen activated protein kinase (MAPK) pathway gene mutations in patients with LRR (24%, 47%) and DM (27%, 40%) compared to controls (0%, 0%; p<0.0001 and p=0.0070, respectively). Three patients had matched primary vs LRR samples, one patient had a gain of a NF1 mutation in the LRR. There was no significant difference between the groups for PTEN loss or cleaved caspase 3 expression. The mean percentage Ki 67 labeling index was higher in patients with LRR (29.2%) and DM (26%) versus controls (14%,p= 0.0045). In summary, mutations in the MAPK pathway, specifically NF1, were associated with both LRR and DM, suggesting that alterations in MAPK signaling are associated with a more aggressive tumor phenotype. Validation of these associations in tissues from randomized trials may support targeted therapy to reduce breast cancer recurrence.
2018-09-14 | GSE119937 | GEO
Project description:To test the hypothesis that a genomic classifier (GC) would predict biochemical failure (BF) and distant metastasis (DM) in men receiving radiation therapy (RT) after radical prostatectomy (RP).
2016-05-09 | GSE72291 | GEO
Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment. 38 patients with papillary thyroid carcinoma from a consecutive cohort of patients, no replicates
2015-01-20 | E-GEOD-65074 | biostudies-arrayexpress
Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment.
2015-01-20 | GSE65074 | GEO
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer. 545 formalin-fixed paraffin-embedded (FFPE) tissue samples from primary prostate cancer obtained from Radical Prostatectomy.
2013-07-01 | E-GEOD-46691 | biostudies-arrayexpress
Project description:Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 that experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set. Results: Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67 - 0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression. Conclusion: A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.
2013-07-01 | GSE46691 | GEO
Project description:Molecular Determinants of Post-Mastectomy Breast Cancer Recurrence
| PRJNA490741 | ENA
Project description:Triple-negative breast cancer (TNBC) is a heterogeneous subtype with varying disease outcomes. Tumor infiltrating lymphocytes (TILs) are frequent in TNBC and have been shown to correlate with outcome, suggesting an immunogenic component in this subtype. However, other factors, intrinsic to the cancer cells, may also influence outcome. To identify proteins and molecular pathways associated with recurrence in TNBC, 34 formalin-fixed paraffin-embedded (FFPE) primary TNBC tumors were investigated by global proteomic profiling using TMT-HILIC-LC-MS/MS. Approximately half of the patients were lymph node-negative and remained free of local or distant metastasis within 10 years follow-up, while the other half developed distant metastasis. Proteomic profiling identified >4000 proteins, of which 63 exhibited altered expression in primary tumors of recurrence versus recurrence-free patients. Importantly, down-regulation of proteins in the major histocompatibility complex (MHC) class I antigen presentation pathways were enriched, including TAP1, TAP2, CALR, HLA-A, ERAP1 and TAPBP, and were associated with significantly shorter recurrence-free and overall survival. In addition, proteins involved in cancer cell proliferation and growth, including GBP1, RAD23B, WARS and STAT1, also exhibited altered expression in primary tumors of recurrence versus recurrence-free patients. The association between the antigen-presentation pathway and outcome were validated in a second sample set of 10 primary TNBC tumors and corresponding metastases using proteomics and in a large public gene expression database of 249 TNBC and 580 basal-like breast cancer cases. Our study demonstrates that down-regulation of antigen presentation is a key mechanism for TNBC cells to avoid immune surveillance, allowing continued growth and spread.
2018-10-26 | PXD005544 | Pride
Project description:We aimed at finding a gene signature able to discriminate patients who had a loco-regional recurrence either at early time after surgery or late (< 2 yrs, early; >2 and <5 yrs, intermediate; < 5 yrs, late)
2023-09-15 | GSE208101 | GEO