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Gene Expression Profiles in Peripheral Blood Mononuclear Cells Can Distinguish Patients with NonSmall Cell Lung Cancer.

ABSTRACT: We report a 29-gene diagnostic signature, which distinguishes individuals with NSCLC from controls with non-malignant lung disease with 91% Sensitivity, 79% Specificity and a ROC AUC of 92%. Accuracy on an independent set of 18 NSCLC samples from the same location was 79%. Samples from an independent location including 12 stage 1 NSCLC and 15 controls, achieved an accuracy of 74%. A study of 18 paired samples taken pre and post surgery shows that the PBMC associated “cancer” signature is significantly reduced after tumor removal, supporting the hypothesis that the signature detected in pre-surgery samples is a response to the presence of the tumor.

ORGANISM(S): Homo sapiens

PROVIDER: GSE13255 | GEO | 2009/12/01

SECONDARY ACCESSION(S): PRJNA109539

REPOSITORIES: GEO

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Gene Expression Profiles in Peripheral Blood Mononuclear Cells Can Distinguish Patients with NonSmall Cell Lung Cancer.

Project description:We report a 29-gene diagnostic signature, which distinguishes individuals with NSCLC from controls with non-malignant lung disease with 91% Sensitivity, 79% Specificity and a ROC AUC of 92%. Accuracy on an independent set of 18 NSCLC samples from the same location was 79%. Samples from an independent location including 12 stage 1 NSCLC and 15 controls, achieved an accuracy of 74%. A study of 18 paired samples taken pre and post surgery shows that the PBMC associated â??cancerâ?? signature is significantly reduced after tumor removal, supporting the hypothesis that the signature detected in pre-surgery samples is a response to the presence of the tumor. We compared microarray gene expression profiles in PBMC from patients with NSCLC and a control group with smoking-related non-malignant lung disease, a likely confounding factor. We found a distinguishing gene signature which was validated on 2 independent sets of hold-out samples one set from a different location. Gene expression changes were also compared between pre and post surgery samples from 18 patients.

2010-04-09 | E-GEOD-13255 | biostudies-arrayexpress

Copy number variations distinguish lung adenocarcinomas from squamous cell carcinomas

Project description:For a number of clinical and biological reasons, the accurate classification of non-small cell lung carcinoma (NSCLC) into adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is essential. DNA-based tests, which are not currently used, are more robust when applied to formalin-fixed paraffin-embedded tissues. To develop a molecular-based classification of NSCLC based on genome wide copy number variations (CNVs), the corresponding TCGA, SPORE and CANARY patient datasets were used as training and independent validation data. The signature genes were selected by advanced supervised classification algorithms and restricted to known important oncogenes/tumor suppressors, resulting in a final 27-gene signature that was able to classify ADC from SCC with 0.85-0.87 accuracies of SPORE validation sets and 0.96-0.98 accuracy of CANARY validation sets. Even by using the top 7 genes in this signature, the accuracies of the validation sets were still as high as 0.80 and 0.97, respectively. These signature genes also classified adenocarcinoma and squamous cell carcinomas from the non-malignant lung samples with accuracies of 91-97%.

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Expression data for early stage NSCLC

Project description:We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of NSCLC. A prognostic signature of 17 genes showed the best association with post-surgery survival time. The performance of the signatures was validated using a patient cohort of similar size

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Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer

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

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer

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.

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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

Retrospective and prospective validation of a 33-gene signature to predict recurrence of lung cancer after surgery.

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Project description:We have examined the changes that occur in microRNA (miRNA) expression levels in peripheral blood mononuclear cells (PBMC) collected from paired pre- vs. post-tumor removal samples in order to characterize the way lung tumor removal affects gene expression in peripheral immune cells. 5 miRNAs were expressed at significantly higher levels before vs. after tumor removal. Significant number of genes that were identified computationally as targets of the miRNAs and negatively correlated with the miRNA expression were transcription factors. miRNA expression changes were compared between 11 pre and post surgery NSCLC lung cancer samples.

2011-12-01 | E-GEOD-27606 | biostudies-arrayexpress

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