Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA102281 | ENA |
REPOSITORIES: ENA
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Project description:Background: One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results: The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions: Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Keywords: Recurrence Free Survival Analysis
2007-11-20 | GSE8894 | GEO
Project description:Background:; One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results:; The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions:; Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Experiment Overall Design: Methods: Experiment Overall Design: At first, we selected the statistically significant genes from the analysis of time-to-recurrence and censoring information from 138 whole-genome wide microarray data. Then, we further reduced the number of genes which could be reliably reproducible by RTQ-PCR. With these assayable genes and clinical parameters, construction of recurrence prediction model by Cox proportional hazard regression was done. After validation into two independent cohorts (n=59 and n=56), the model was transformed into recurrence prediction for the each patient.
2008-06-17 | E-GEOD-8894 | biostudies-arrayexpress
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.
2010-05-23 | E-GEOD-15081 | biostudies-arrayexpress
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis with peritoneal relapse free survival showed a significant difference between ‘good signature group’ and ‘poor signature group’ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers.
2009-03-04 | GSE15081 | GEO
Project description:Understanding the molecular events in non-small cell lung cancer (NSCLC) is essential to improve early diagnosis and treatment for this disease. We examined the effect of chromosomal copy number changes on gene expression in resected NSCLC patients. We identified a deletion on 14q32.2-33 as a common alteration in NSCLC (44%), which significantly influenced gene expression for HSP90AA1, residing on 14q32. This deletion was correlated with better overall and recurrence free survival (P=0.008 and P=0.004, respectively) and survival was also longer in patients whose tumors had low expression levels of HSP90AA1. We extended the analysis to an independent validation set of 140 resected NSCLC patients, and confirmed low HSP90AA1 expression to be significantly related with overall survival and recurrence free survival (P=0.003 and P=0.007, respectively). In vitro treatment with an HSP90 inhibitor had potent antiproliferative activity in NSCLC cell lines. We suggest that targeting HSP90 will have clinical impact for NSCLC patients. Keywords: Array CGH gene expression integration
2007-08-01 | GSE7878 | GEO
Project description:Background: Circular RNAs (circRNAs) have attracted increasing attention in recent years for their potential application as disease biomarkers due to their high abundance and stability. In this study, we attempted to screen circRNAs that can be used to predict postoperative recurrence and survival in patients with gastric cancer (GC). Methods: High-throughput RNA sequencing was used to identify differentially expressed circRNAs in GC patients with different prognoses. The expression level of circRNAs in the training set (n=136) and validation set (n=167) was detected by quantitative real-time PCR (qRT-PCR). Kaplan–Meier estimator, receiver operating characteristic (ROC) curve and cox regression analysis were used to evaluate the prognostic value of circRNAs on recurrence-free survival (RFS) and overall survival (OS) in GC patients. CeRNA network prediction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for the circRNAs with prognostic significance. Results: A total of 259 differentially expressed circRNAs were identified in GC patients with different RFS. We found two circRNAs (hsa_circ_0005092 and hsa_circ_0002647) that highly expressed in GC patients with good prognoses, and subsequently established a predictive model for postoperative recurrence and prognosis evaluation, named circPanel. Patients with circPanellow might have shorter recurrence-free survival (RFS) and overall survival (OS). We also performed circRNA-miRNA-mRNA network prediction and functional analysis for hsa_circ_0005092 and hsa_circ_0002647. Conclusions: CircPanel has the potential to be a prognostic biomarker in GC patients with greater accuracy than a single circRNA and certain traditional tumor markers (e.g., CEA, CA19-9 and CA724).
2021-08-12 | GSE181769 | GEO
Project description:Postoperative recurrence is the main cause of poor prognosis in early stage lung adenocarcinoma (LUAD). Factors that can predict recurrence risk are critically needed.we designed a screening procedure based on gene profile data.The differentially expressed genes (DEGs) between patients with recurrence-free survival (RFS)<1 year and RFS>3 years were found.Cox proportional hazards model, IHC and Kaplan-Meier survival analysis were preformed to validate these biomarkers in TCGA and Daping validation sets.
2018-10-27 | GSE121841 | GEO
Project description:We developed a 33-gene signature that is strongly correlated to the time to recurrence in non-small cell lung cancer (NSCLC). The signature was validated retrospectively in 5 cohorts of 972 NSCLC patients and in one prospective study of 111 NSCLC Stage IA patients. In all cohorts, and all stages of the disease, the signature identified a rare, aggressive tumor type that had a high proportion of recurrence after surgery and a median survival of 35 months (95% C.I.: 19-58). This tumor type forms a separate cluster in an analysis of the expression of the 33 genes in patient tumors. The signature is associated with cellular processes required by rapidly growing and spreading tumors: cell migration and invasion, vascularization, and response to hypoxia. The signature also identifies patients with good prognosis (median survival 114 months, (95% C.I.: 85-160), and intermediate prognosis (median survival 61 months (95% C. I.: 50-73). The signature is quite robust and works on tumor samples archived in RNAlater, Tissue-Tek, or formalin-fixed and paraffin embedded. 156 samples -------------------------------- *** Submitter has not provided information such as time to recurrence. Thus, the data is incomplete.
2016-02-11 | E-GEOD-77803 | biostudies-arrayexpress
Project description:Study to identify genes associated with NSCLC recurrence in patients not receiving adjuvant chemotherapy. Purpose: Recent clinical trials suggest improvement in survival with adjuvant chemotherapy in non-small cell lung cancer (NSCLC). This study's aim is to identify genes associated with NSCLC recurrence in patients not receiving adjuvant chemotherapy. Experimental design: Banked NSCLC tumors of patients who underwent resection of stage Ia-IIIb disease were identified. Patients were stratified into two groups: recurrent (R, n=11) or non-recurrent (NR, n=16) 2 years after surgery. Microarray profiling and Cox multivariate analysis were performed. Conclusion: Increased CYP3A5 gene expression correlates with NSCLC recurrence and promotes proliferation through mechanisms that may involve, in part, CYP3A5 epoxygenase activity. Experiment Overall Design: comparison of gene expression profiles for recurrent and non-recurrent cancer
2009-12-14 | E-GEOD-9971 | biostudies-arrayexpress
Project description:Background and aims: Liver transplantation (LT) is the most radical treatment for hepatocellular carcinoma (HCC) with high rates of long-term survival, but tumor recurrence after LT is an unresolved problem. The aim of our study was to identify predictive markers for tumor recurrence after liver transplantation. Methods: In a retrospective single-center study, we included all patients with LT for HCC in our institution (01/2007-12/2012). Beside demographic data, we analyzed course, bridging therapies, Serum-AFP, time point of tumor recurrence, as well as the correlation of imaging and histopathology of our recipients. Additionally, we performed a microarray analysis to identify different miRNA profiles of patients with and without HCC recurrence after LT. Single assay stem-loop real-time PCR (Q-RT-PCR) was used for validation of the results. Results: During the study period, we performed 92 LT in patients with HCC (22 women, 70 men). Twenty-two (23.9%) patients developed a recurrent HCC after LT. Our subgroup with tumor recurrence after LT, presented with a mean disease-free survival of 10 months (3-55 months) and an overall survival of 25.5 months (4-77 months). Milan criteria, AFP levels and pathologic grading had an influence on the tumor recurrence. Performing miRNA analysis, we could identify significant upregulation of 8 miRNAs and downregulation of another 5 miRNAs in patients with tumor recurrence. Consecutively, array data were successfully validated using Q-RT-PCR. Multivariate Cox regression, ROC analysis and Kaplan-Meier showed that a score consisting of two miRNAs and Milan criteria are an independent predictor for tumor recurrence-free survival. Conclusions: Despite careful selection of patients, an early recurrence of HCC after LT cannot be avoided completely. Reliable prognostic markers related to tumor biology are still missing. Analysis and validation of specific miRNAs combined with radiological parameters might lead to a promising strategy for the prediction of tumor recurrence, but prospective studies have to follow. 8 macrodissected hepatocellular carcinoma (recurrent HCC) and 10 macrodissected hepatocellular carcinoma (non-recurrent HCC).
2016-03-01 | E-GEOD-64989 | biostudies-arrayexpress