Tumour gene expression signature in primary melanoma predicts long-term outcomes: A prospective multicentre study
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PROVIDER: EGAS00001004664 | EGA |
REPOSITORIES: EGA
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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. Keywords: clinical outcome
2008-08-22 | GSE12417 | GEO
Project description:Purpose: The purpose of this study was to independently validate two biomarkers, a 44-gene DNA Damage Immune Response (DDIR) signature and stromal tumor-infiltrating lymphocytes (sTILs), as prognostic markers in TNBC patients treated with adjuvant doxorubicin (A) and cyclophosphamide (C) in SWOG 9313. Materials & Methods: 425 centrally determined TNBC cases from S9313 were identified. DDIR signature was performed on RNA isolated from FFPE tumor tissue (n=381), and samples were classified as DDIR-negative or positive using predefined cutoffs. Evaluation of sTILs was performed as previously described. Markers were tested for prognostic value for disease-free and overall survival (DFS, OS) using Cox regression models adjusted for treatment assignment nodal status and tumor size. Results: Among 425 TNBC patients, median age was 45 years, and 33% were node-positive. DDIR was successfully tested in 90% (381/425) of cases, of which 62% were DDIR signature-positive. DDIR signature positivity was associated with improved DFS (HR=0.67; 95% CI 0.48–0.92, P=0.014) and OS (HR=0.61; 95% CI 0.43–0.89, P=0.009). sTILs density assessment was available in 99% of patients and was associated with improved DFS (HR=0.70; 95% CI 0.51–0.96, P=0.028 for sTILs density ≥20% vs. <20%) and OS (HR=0.59; 95% CI 0.41–0.85, P=0.004 for sTILs density ≥20% vs. <20%). The DDIR signature score and sTILs density were moderately correlated (r=0.62) which precluded statistical significance for DFS in a joint model (P=0.08 for DDIR and P=0.25 for sTILs). Conclusion: The prognostic role of sTILs and DDIR in early-stage TNBC was confirmed. DDIR signature conferred improved prognosis in two-thirds of TNBC patients treated with adjuvant AC. DDIR signature has potential to stratify outcome and identify patients with less projected benefit following AC chemotherapy. Clinical trial number: Int0137 (The trial pre-dates Clinicaltrial.Gov website establishment)
2019-09-13 | GSE137356 | GEO
Project description:Background: The JBR.10 trial demonstrated significant survival benefit from adjuvant cisplatin/vinorelbine (ACT) in stage IB-II NSCLC (HR 0.69, p=0.04), but stage IB patients did not derive significant benefit (HR: 0.94, p= 0.79). We hypothesized that expression profiling could identify stage-independent subgroups of patients who might benefit from adjuvant chemotherapy. Methods: Gene expression profiling was conducted on mRNA isolated from frozen JBR.10 tumor samples (either from patients under observation [OBS], or treated with ACT). The minimum gene set that selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified and this gene signature was used to classify patients into high and low risk for death after surgery, and predict ACT effect. The prognostic gene signature was additionally tested on ACT patients and publicly available microarray datasets. Results: A 15-gene signature separated OBS patients into equal high and low risk subgroups with significantly different prognoses (HR 15.02, 95% CI 5.12-44.04, p=0.0001). The signature was prognostic in both stage IB and II. It was also predictive of improved survival following ACT treatment in high-risk patients (HR 0.33, 95% CI 0.17-0.63, p=0.0005), but not in low risk patients (HR 3.67, 95% CI 1.22-11.06, p=0.0133; interaction p=0.0001). The prognostic effect of the signature was validated in two independent gene expression datasets of 169 stage I-II adenocarcinoma and 106 squamous cell carcinoma patients. Conclusions: This microarray-based 15-gene prognostic expression signature is stage and histology independent and may select early stage NSCLC patients who are most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine. Keywords: Expression profiling by microarray; prognosis prediction 90 samples
2010-09-09 | E-GEOD-14814 | biostudies-arrayexpress
Project description:Background: Accurate survival stratification in early-stage NSCLC could inform the use of adjuvant therapy. We developed a clinically-implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables. Methods: Gene expression profiles from 1106 non-squamous NSCLCs were used for generation and internal validation of a 9-gene molecular prognostic index (MPI). Expression of the MPI genes was determined within sorted tumor cell subpopulations. A quantitative PCR (qPCR) assay was developed and validated on an independent cohort of FFPE tissues. A prognostic score using clinical variables was generated using Surveillance Epidemiology and End Results (SEER) data and combined with the MPI. Results: The MPI stratified stage I patients into prognostic categories in four independent validation datasets, including three microarray and one FFPE qPCR cohorts (HR=2.4, 95% CI, 1.8-3.3, P=7x10-9 in the largest microarray cohort; and HR=2.5, 95% CI 1.1-6.0, P=.03 in stage I patients of the qPCR validation cohort). Prognostic genes were expressed in distinct tumor cell subpopulations and expression of genes implicated in cellular proliferation and stem cells portended poor outcomes, while expression of genes involved in normal lung differentiation and immune infiltration was associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR=3.3, 95% CI 2.4-4.6; P=2x10-15 in the largest microarray cohort; and HR=3.6, 95% CI 1.5-8.8, P=.003 in stage I patients of the qPCR validation cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK. Conclusion: The MPI incorporates genes expressed in the tumor and its microenvironment, and designates risk of death for patients with early-stage non-squamous NSCLC. The MPI can be implemented clinically using qPCR assays on FFPE tissues and a composite model integrating the MPI with clinical variables provides the most accurate risk stratification.
2015-08-24 | GSE67639 | 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
Project description:Hormone-receptor negative (HR-) breast cancer accounts for approximately one third of all breast tumors and has a worse prognosis compared with hormone receptor-positive disease. Their unfavorable outcome and the lack of hormonal receptors determine the use of adjuvant chemotherapy as part of the standard treatment for these tumors. However, a significant proportion of patients relapse after receiving adjuvant chemotherapy. Classical prognostic factors such as tumor size, lymph node status and grade of differentiation do not suffice to identify patients with a higher risk of relapse. In the last decade, gene profiling has allowed the description of signatures with prognostic value in hormone receptor-positive tumors, but similar information is scarce in HR- disease. Reliable identification of poor-prognosis patients would be important to offer participation in clinical trials with new drugs and to modify follow-up schedules. In this study, we assessed gene expression with quantitative polymerase-chain reaction (RT-qPCR) in HR- early stage breast cancer. RNA was isolated from formalin-fixed paraffin-embedded (FFPE) tissue. Our purpose was to identify a gene signature related to outcome.
2016-02-01 | GSE33669 | GEO
Project description:Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to its high heterogeneity and aggressiveness. Recognizing the urgency to delineate molecular subtypes, our study focused on the emerging field of lipid metabolism remodeling in PDAC, particularly exploring the prognostic potential and molecular classification associated with fatty acid biosynthesis. Here we identified a 7-gene signature associated with fatty acid biosynthesis-related genes (FRGs), providing a robust tool for survival prediction. The high- FRGs score group displayed a poorer prognosis, lower immune infiltration abundance, and a higher tumor mutational burden. Notably, ACSL5, a key gene in 7-gene signature panel was upregulated in PDAC. The biological function of ACSL5 were validated with in vitro assay. Finally, we unveiled that ACSL5 played a crucial role in pancreatic cancer progression, promoting tumor initiation, metastasis, and immune evasion.
2024-01-16 | GSE253315 | GEO
Project description:Purpose: The JBR.10 trial demonstrated benefit from adjuvant cisplatin/vinorelbine (ACT) in early-stage non-small-cell lung cancer (NSCLC). We hypothesized that expression profiling may identify stage-independent subgroups who might benefit from ACT. Patients and Methods: Gene expression profiling was conducted on mRNA from 133 frozen JBR.10 tumor samples (62 observation [OBS], 71 ACT). The minimum gene set that was selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified. The prognostic value of this gene signature was tested in four independent published microarray data sets and by quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR). Results: A 15-gene signature separated OBS patients into high-risk and low-risk subgroups with significantly different survival (hazard ratio [HR], 15.02; 95% CI, 5.12 to 44.04; P .001; stage I HR, 13.31; P .001; stage II HR, 13.47; P .001). The prognostic effect was verified in the same 62 OBS patients where gene expression was assessed by qPCR. Furthermore, it was validated consistently in four separate microarray data sets (total 356 stage IB to II patients without adjuvant treatment) and additional JBR.10 OBS patients by qPCR (n 19). The signature was also predictive of improved survival after ACT in JBR.10 high-risk patients (HR, 0.33; 95% CI, 0.17 to 0.63; P .0005), but not in low-risk patients (HR, 3.67; 95% CI, 1.22 to 11.06; P = .0133; interaction P .001). Significant interaction between risk groups and ACT was verified by qPCR. Conclusion: This 15-gene expression signature is an independent prognostic marker in early-stage, completely resected NSCLC, and to our knowledge, is the first signature that has demonstrated the potential to select patients with stage IB to II NSCLC most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine.
2010-09-09 | GSE14814 | GEO
Project description:Background Currently, no gene-expression signature (GES) established from node-positive cohorts, able to predict breast cancer evolution after systemic adjuvant chemotherapy, exists. Methods Gene-expression profiles of 252 node-positive patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array representing 5,776 distinct genes. Findings In the training cohort, we established a 38-GES for the purpose of predicting time to distant metastasis. The 38-GES yielded unadjusted hazard ratio of 4.86 (95% CI=2.76-8.56). Even when adjusted with the two best clinicopathological prognostic scoring: NPI and Adjuvant!, 38-GES HR were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved mostly NPI and Adjuvant! intermediate-risk classified patients. NPI intermediate-risk patients (7-year MFS=87.2%) were divided into 2/3 (7-year MFS=95.5%) close to NPI low-risk group and 1/3 (7-year MFS=69.3%) close to NPI high-risk group (HR=6.97 [2.51-19.36]). Adjuvant! intermediate-risk patients (7-year MFS=88.0%) were divided into 2/3 (7-year MFS=94.8%) close to Adjuvant! low-risk group and 1/3 (7-year MFS=71.7%) close to Adjuvant! high-risk group (HR=5.31 [5.38-11.87]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n=224) generated from different microarray platforms. The 38-GES yielded unadjusted HR=2.95 (1.74-5.01). Furthermore, 38-GES showed performance in supplementary cohorts with different lymph-node status and endpoint (1,031 new patients). Interpretation The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and especially powerful to separate NPI or Adjuvant! intermediate-risk node-positive patients. Keywords: disease-state analysis
2008-11-28 | GSE11264 | GEO
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