Whole-transcript expression data for liposarcoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE30929 | GEO | 2011/09/02
SECONDARY ACCESSION(S): PRJNA146279
REPOSITORIES: GEO
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Project description:Liposarcoma is the most common soft tissue sarcoma, accounting for about 20% of cases. Liposarcoma is classified into 5 histologic subtypes that fall into 3 biological groups characterized by specific genetic alterations. To identify genes that contribute to liposarcomagenesis and to better predict outcome for patients with the disease, we undertook expression profiling of liposarcoma. U133A expression profiling was performed on 140 primary liposarcoma samples, which were randomly split into training set (n=95) and test set (n=45). A multi-gene predictor for distant recurrence-free survival (DRFS) was developed using the supervised principal component method. Expression levels of the 588 genes in the predictor were used to calculate a risk score for each patient. In validation of the predictor in the test set, patients with low risk score had a 3-year DRFS of 83% vs. 45% for high risk score patients (P=0.001). The hazard ratio for high vs. low score, adjusted for histologic subtype, was 4.42 (95% confidence interval 1.26-15.55; P=0.021). The concordance probability for risk score was 0.732. Genes related to adipogenesis, DNA replication, mitosis, and spindle assembly checkpoint control were all highly represented in the multi-gene predictor. Three genes from the predictor, TOP2A, PTK7, and CHEK1, were found to be overexpressed in liposarcoma samples of all five subtypes and in liposarcoma cell lines. Knockdown of these genes in liposarcoma cell lines reduced proliferation and invasiveness and increased apoptosis. Thus, genes identified from this predictor appear to have roles in liposarcomagenesis and have promise as therapeutic targets. In addition, the multi-gene predictor will improve risk stratification for individual patients with liposarcoma. 140 human liposarcoma specimens were profiled on Affymetrix U133A arrays per manufacturer's instructions.
2011-09-01 | E-GEOD-30929 | biostudies-arrayexpress
Project description:Purpose Survival of patients with multiple myeloma is highly heterogeneous from periods of few weeks to more than ten years. We used gene-expression profiles of myeloma cells obtained at diagnosis to identify broadly applicable prognostic markers. Methods In a training set of 182 patients, we used supervised methods to identify individual genes associated with length of survival. A survival model was built from these genes. The validity of our model was assessed in our test set of 68 patients and in three independent cohorts comprising 853 multiple myeloma patients. Results The 15 strongest genes associated with the length of survival were used to calculate a risk score and to stratify patients in low-risk and high-risk. The survival-predictor score was significantly associated with survival in both the training and test sets and in the external validation cohorts. The Kaplan Meier estimates of rates of survival at 3 years were 90.5 percent (95 percent CI, 85.6 – 95.3), and 47.4 (95 percent CI, 33.5 - 60.1) respectively in our patients having a low-risk or high-risk, independently of traditional prognostic factors. High-risk patients constituted a homogeneous biological entity characterized by the overexpression of genes involved in cell cycle progression and its surveillance, while low-risk patients were heterogeneous and displayed hyperdiploid signatures. Conclusion Gene expression-based survival prediction and molecular features associated with high-risk patients may be useful for developing prognostic markers and may provide basis to treat these patients with new targeted anti-mitotics. Keywords: Gene-expression profiling
2008-08-05 | GSE7039 | GEO
Project description:Reliable non-invasive tools to diagnose at risk metabolic dysfunction-associated steatohepatitis (MASH) are urgently needed to improve management. We developed a risk stratification score incorporating proteomics-derived serum markers with clinical variables to identify high risk MASH patients (NAFLD Activity Score (NAS) >4 and fibrosis score >2). In this three-phase proteomic study of biopsy-proven metabolic dysfunction-associated steatotic fatty liver disease (MASLD), we first developed a multi-protein predictor for discriminating NAS>4 based on SOMAscan proteomics quantifying 1,305 serum proteins from 57 US patients. Four key predictor proteins were verified by ELISA in the expanded US cohort (N=168), and enhanced by adding clinical variables to create the 9-feature MASH Dx Score which predicted MASH and also high risk MASH (F2+). The MASH Dx Score was validated in two independent, external cohorts from Germany (N=139) and Brazil (N=177). The discovery phase identified a 6-protein classifier that achieved an AUC of 0.93 for identifying MASH. Significant elevation of four proteins (THBS2, GDF15, SELE, IGFBP7) was verified by ELISA in the expanded discovery and independently in the two external cohorts. MASH Dx Score incorporated these proteins with established MASH risk factors (age, BMI, ALT, diabetes, hypertension) to achieve good discrimination between MASH and MASLD without MASH (AUC:0.87- discovery; 0.83- pooled external validation cohorts), with similar performance when evaluating high risk MASH F2-4 (vs. MASH F0-1 and MASLD without MASH). The MASH Dx Score offers the first reliable non-invasive approach combining novel, biologically plausible ELISA-based fibrosis markers and clinical parameters to detect high risk MASH in patient cohorts from the US, Brasil and Europe.
2023-12-22 | GSE251855 | GEO
Project description:The prognosis of children with metastatic stage 4 neuroblastoma (NB) has remained poor in the past decade. Using microarray analyses of 342 primary tumors, we here developed and validated an easy to use gene expression-based risk score including 18 genes, which can robustly predict the outcome of stage 4 patients. This classifier was a significant predictor of overall survival in two independent validation cohorts (cohort 1 (n=214): P=6.3x10-5; cohort 2 (n=27): P=3.1x10-2). The prognostic value of the risk score was validated by multivariate analysis including the established markers age and MYCN status (P=0.027). In the pooled validation cohorts (n=241), integration of the risk score with the age and/or MYCN status identified subgroups with significantly differing overall survival (ranging from 35% to 100%). Together, the 18-gene risk score classifier can identify patients with stage 4 NB with favorable outcome and may therefore improve risk assessment and treatment stratification of NB patients with disseminated disease. We analyzed expression profiling arrays of 27 Tumor samples from stage 4 neuroblastoma patients.
2016-04-05 | E-GEOD-79910 | biostudies-arrayexpress
Project description:The prognosis of children with metastatic stage 4 neuroblastoma (NB) has remained poor in the past decade. Using microarray analyses of 342 primary tumors, we here developed and validated an easy to use gene expression-based risk score including 18 genes, which can robustly predict the outcome of stage 4 patients. This classifier was a significant predictor of overall survival in two independent validation cohorts (cohort 1 (n=214): P=6.3x10-5; cohort 2 (n=27): P=3.1x10-2). The prognostic value of the risk score was validated by multivariate analysis including the established markers age and MYCN status (P=0.027). In the pooled validation cohorts (n=241), integration of the risk score with the age and/or MYCN status identified subgroups with significantly differing overall survival (ranging from 35% to 100%). Together, the 18-gene risk score classifier can identify patients with stage 4 NB with favorable outcome and may therefore improve risk assessment and treatment stratification of NB patients with disseminated disease.
2016-04-05 | GSE79910 | GEO
Project description:Background & Aims: The recurrence determines the postoperative prognosis of patients with hepatocellular carcinoma (HCC). It is unknown whether de novo HCCs derive from the liver with disability of an organic anion transport. This study was designed to elucidate the link between such transporters and the multicentric occurrence (MO) after radical hepatectomy. Results: SLC22A7 expression was the best predictor of metastasis-free survival (MFS) as judged by the GA (Fold, 0.726; P=0.001). High SLC22A7 gene expression in noncancerous tissue prevent HCC occurrence after hepatectomy (Odds Ratio (OR), 0.2; 95%CI, 0.1-0.6; P=0.004). Multivariate analyses of MFS revealed the independent risk factor to be SLC22A7 expression (OR, 0.3; 95%CI, 0.1-1.0, P=0.043). Low SLC22A7 expression caused MO of HCC significantly (log-rank, P=0.001). In the validation study, multivariate analyses of MFS revealed the independent risk factor to be SLC22A7 expression (OR, 0.5; 95%CI, 0.3-0.8; P=0.012). As judged by Gene set-enrichment analysis, SLC22A7 down-regulation associated with mitochondrion (P=0.008; false discovery rate (FDR)=0.199; normalized enrichment score (NES) =1.804), oxidoreductase activity (P=0.006; FDR=0.157; NES=1.854) and fatty acid metabolic process (P=0.021; FDR=0.177; NES=1.723). Sirtuin3 also determined MFS (P= 0.018). Conclusions: These pathways involving SLC22A7 dysfunction may promote the occurrence of HCC. The 49 noncancerous liver tissues of HCC patients within Milan criteria, treated at our institution between January 2004 and August 2008, were examined as a training set by genome-wide gene expression analysis (GA). Cox proportional hazards regression analyses for MO-free survival (MFS) were performed to estimate the risk factors. Using the independent two institutional cohorts of 134 patients between September 2008 and December 2009, a validation study was employed using tissue microarrays.
2013-04-01 | E-GEOD-40873 | biostudies-arrayexpress
Project description:Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Experiment Overall Design: 64 microarray experiments from primary breast tumors used as training set to identify genes differentially expressed in grade 1 and 3. Experiment Overall Design: 129 microarray experiments from primary breast tumors of untreated patients used as validation set to validate the list of genes and its correlation with survival. Experiment Overall Design: No replicate, no reference sample. **NOTE** There are some inconsistencies between the sample annotation provided by GEO for this experiment in the GSE2990_family.soft.gz file and the supplementary data file GSE2990_suppl_info.txt. ***
2008-06-13 | E-GEOD-2990 | biostudies-arrayexpress
Project description:Background: miRNAs might be potentially useful biomarkers for prediction of response to chemotherapeutic agents, radiotherapy and survival. The aim of this retrospective study was to validate miRNA response predictors in a cohort of patients with gastroesophageal cancer in order to predict overall survival (OS) and disease-specific survival (DSS). Material and methods: The study population encompassed 53 patients treated with curative intended for loco-regional gastroesophageal cancer. miRNA expression was quantified from pre-therapeutic and diagnostic, formalin-fixed, paraffin embedded tumor specimens using Affymetrix GeneChip miRNA 1.0 Array. Based on growth inhibition of the NCI60 panel in the presence of cisplatin, epirubicine and capecitabine, a miRNA based response predictor was developed. The Cox proportional hazards model was applied to assess the correlations of the response predictor with OS and DSS. Results: A univariate analysis demonstrated a statistical significant improvement of OS for patients who had undergone surgical resection with prediction scores above the median prediction score (HR: 0.41 (95% CI: 0.17-0.96). Adjusting for surgery and stage, this predictor was identified to be independently associated with both OS (HR: 0.37 (95% CI: 0.16-0.87)) and DSS (HR: 0.32 (0.12-0.87)). Conclusion: The miRNA profile predictive for sensitivity to cisplatin, epirubicine and capecitabine was shown to be independently associated with OS and DSS in patients with gastroesophageal cancer. Tumor biopsies from 53 patients with gastroesophageal cancer *** Submitter has provided limited clinical information. Thus, this submission is incomplete. ***
2016-02-18 | E-GEOD-78049 | biostudies-arrayexpress
Project description:Importance: Severe alcoholic hepatitis (AH) is a highly lethal disease with a 3-month mortality up to 50%. Corticosteroids are the current standard of care although nearly 40% of the patients do not respond and accurate pre-treatment predictors of survival are lacking. Objective: To develop a prognostic score based on molecular and clinical variables before initiation of corticosteroids. Design, Setting, and Participants: Gene expression profiling of fixed liver biopsy obtained for diagnosis of severe AH assessed in 3 independent cohorts (1 prospective cohort for prognostic gene signature and integrative score derivation, and 2 retrospective cohorts for validation). Samples were obtained from 4 European and 1 US medical centers between July 2006 and February 2015. Exposures: Biopsy proven severe AH patients treated with corticosteroids. Main Outcome Measures: Identification of a gene signature combined with a validated clinical index to develop an integrative prognostic score of survival without death or liver transplantation in a derivation cohort (n=71). Prognostic performance of the score was validated in an independent multi-center validation cohort 1 (n=48). Finally, the score was implemented in an FDA-approved clinical diagnostic platform (NanoString) and tested in another independent validation cohort 2 (n=20). Results: A prognostic score, integrating a 123-gene signature and the model for end-stage liver disease (gs-MELD score), was defined in the derivation cohort, in which poor- and good-prognosis patients were discriminated with a cut-off value of 2.66 at 3 months (event-free survival rates of 32% vs. 76%, respectively, p<.001) and 6 months (26% vs. 65%, respectively, p<.001). In the validation cohort 1, the score similarly discriminated poor- and good-prognosis patients at 3 months (43%, [95% CI, 26%-70%] vs. 96% [95% CI, 89%-100%], respectively, p<.001, c-index of 0.83 [95% CI, 0.66-0.99]) and 6 months (34% [95% CI, 18%-61%] vs 84% [95% CI, 72%-100%], respectively, p<.001, c-index of 0.80 [95% CI, 0.66-0.94]), and outperformed other existing clinical indices. The NanoString-based gs-MELD score remained predictive of 3- (p=.03) and 6-month (p=.009) even-free survival in the validation cohort 2. Conclusion and Relevance: The gs-MELD score, incorporating clinically applicable gene signature test and the MELD score, enables pre-treatment survival prediction in severe AH patients.
2018-02-18 | GSE95246 | GEO
Project description:Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. NB: The patients coming from Uppsala Hospital have been also used in other studies as in GSE3494. You can find the common set of patients in removing the abbreviation "UPP_" from the sample names and compare the results with the "INDEX (ID)" from the GSE3494 series. Keywords: disease state analysis
2006-02-16 | GSE2990 | GEO