EAC Genomic data
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PROVIDER: EGAS00001004887 | EGA |
REPOSITORIES: EGA
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Project description:Diffuse large B-cell lymphoma (DLBCL) exhibits heterogeneous clinical outcomes even in tumors of the same stage and with similar pathological characteristics. A substantial number of patients with DLBCL still fail to be cured despite recent improvements in therapy. In this study, we used formalin fixed paraffin embedded (FFPE) tumor samples for microarray gene expression profiling to develop robust prognostic profiles for DLBCL. We performed a retrospective microarray gene expression profiling study of FFPE from a cohort of DLBCL patients using the whole genome cDNA mediated Annealing, Selection and Ligation (WG-DASL) assay. After removing poor-quality samples, data from 164 patients were used for statistical analyses to develop and validate a prognostic gene expression signature using a gradient lasso and leave-one-out cross-validation process.
2012-05-24 | E-GEOD-38202 | biostudies-arrayexpress
Project description:Background: Robust prognostic stratification of patients with oropharyngeal squamous cell carcinoma (OPSCC) is important for developing individualized treatment plans. This study was conducted to develop and validate a clinically feasible prognostic classifier based on transcriptome-wide gene expression profiles. Methods: Tumor tissues were collected from 208 OPSCC patients treated at Washington University in St. Louis and 115 OPSCC patients treated at Vanderbilt University, used for model training and validation, respectively. OPSCC patients (n = 70) from the TCGA cohort were also included for independent validation. Based on RNA-seq profiling data, Cox proportional hazards regression analysis was performed to identify genes associated with disease outcomes. Then, Lasso-penalized multivariate survival models were constructed to identify biomarker genes for developing a prognostic gene signature. Findings: A 60-gene signature was identified by RNA-seq profiling analysis. Computed risk score of the gene signature was significantly predictive of 5-year overall survival of the training cohort (Hazard ratio (HR) 28.32, P = 4.3E-41). Subgroup analysis stratified by HPV status revealed that the signature was prognostic in HPV-positive OPSCC patients (HR 30.55, P = 7.0E-37) and was independent of clinical features. Importantly, the gene signature was validated in two independent patient cohorts, including the TCGA cohort (HR 3.94, P = 0.0018) and the Vanderbilt cohort (HR 8.50, P = 5.7E-09) for overall survival. Conclusions: The prognostic gene signature is a robust tool for risk stratification of OPSCC patients. The signature remains prognostic among HPV-positive OPSCC patients.
2021-04-13 | GSE171898 | GEO
Project description:Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin, genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using highly-sensitive transcriptome profiling of untreated DLBCL tissues, we here assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells, in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.
2021-06-18 | GSE178394 | GEO
Project description:Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin, genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using highly-sensitive transcriptome profiling of untreated DLBCL tissues, we here assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells, in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.
2021-09-01 | GSE178965 | GEO
Project description:Diffuse large B-cell lymphoma (DLBCL) exhibits heterogeneous clinical outcomes even in tumors of the same stage and with similar pathological characteristics. A substantial number of patients with DLBCL still fail to be cured despite recent improvements in therapy. In this study, we used formalin fixed paraffin embedded (FFPE) tumor samples for microarray gene expression profiling to develop robust prognostic profiles for DLBCL.
2012-05-25 | GSE38202 | GEO
Project description:Radiation dermatitis (RD) is a common adverse reaction to radiation therapy (RT), affecting up to 95% of cancer patients. Despite its prevalence, RD’s pathophysiology is complex and remains poorly understood. Without a better molecular understanding of this condition, targeted treatments are difficult to develop and integrate into clinical practice. Prior animal model studies of RD are scarce, variable in methodology, and limited to outcomes such as clinical grading and histology. To address this gap, we aimed to develop a temporal murine model of RD using clinical grading, objective skin parameters, histopathology, and gene expression analysis of inflammatory markers.
2025-08-25 | GSE300340 | GEO
Project description:Background. Current clinicopathological factors are not accurate enough to predict tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC). Objective: To develop a prognostic classifier for intermediate/high-risk ccRCC based on gene expression and histopathological prognostic factors. Design, setting and participants: Retrospective, multicenter study including 84 intermediate/high-risk ccRCC patients who underwent surgery. Global gene expression patterns were analyzed in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 2000 kit. Expression levels of 22 selected genes were assessed by nCounter Analysis in an independent series of 71 ccRCC. A combined genetic-clinicopathological classifier for predicting tumor progression was developed. Outcomes measurements and statistical analysis: Logistic regression analysis was used to identify independent prognostic factors. Results and Limitations: A total of 1202 genes were found differentially expressed between progressive and non-progressive intermediate/high-risk ccRCC. In the independent cohort, 7 genes remained significant differentially expressed between the groups. Expression of HS6ST2, pT stage, tumor size and ISUP grade were found independent prognostic factors for tumor progression (p<0.05). A risk score generated using these variables was able to distinguish a subset of patients at higher-risk of progression (HR 7,27; p<0,001), improving the individual discriminative performance of each of these variables on their own. Conclusions: A novel prognostic algorithm based on genetic and clinicopathological factors was successfully developed. This model may aid physicians to select high-risk patients for further adjuvant target therapy or immune therapy.
2021-12-29 | GSE175648 | GEO
Project description:Radical prostatectomy remains one of the more widely-used treatment options for men with prostate cancer. However, few molecular biomarkers have been established to predict patients who are at high risk of biochemical failure. To our knowledge, this is the first such report on miRNA profiling in radical prostatectomy tissue using Nanostring. In addition, this is the first report to look at the prognostic value of miRNAs in the setting of biochemical failure and salvage radiation therapy post-radical prostatectomy. RNA was extracted from tumor-enriched 1mm cores from 43 radical prostatectomy paraffin tissue blocks. 800 miRNAs were profiled using the NanoString nCounter human miRNA assay. mirNAs were then correlated to clinical outcomes.
2015-01-23 | E-GEOD-65061 | biostudies-arrayexpress
Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis
2009-12-01 | GSE11901 | GEO
Project description:Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes) which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P=0.002), EFS (HR, 1.73; P=0.001), and RFS (HR, 1.76; P=0.025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR, 4.11; P<0.001), EFS (HR, 2.90; P<0.001), and RFS (HR, 3.14, P<0.001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene expression signature that offers additional prognostic information for patients with CN-AML. Experiment Overall Design: Analysis of 163 samples of bone morrow or peripheral blood mononuclear cells from adult patients with untreated acute myeloid leukemia
2008-10-26 | E-GEOD-12417 | biostudies-arrayexpress