Browse
Submit Data
Databases
API
Help

Dataset Information

15 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcription profiling on non-small cell lung cancer samples reveals CYP3A5 gene expression is associated with early recurrence

ABSTRACT: 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

ORGANISM(S): Homo sapiens

SUBMITTER: Potter David

PROVIDER: S-ECPF-GEOD-9971 | biostudies-other |

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Transcription profiling on non-small cell lung cancer samples reveals CYP3A5 gene expression is associated with early recurrence

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

Transcription profiling of human non-small cell lung cancer samples

Project description:Microarray gene expression analysis of genes that showed a gene copy number difference in non small cell lung cancer samples. Only data for a subset of the genes on the array chip are shown here.

| S-ECPF-TABM-270 | biostudies-other

CYP3A5 Gene Expression is Associated with Early Recurrence of Non-small Cell Lung Cancer

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. Keywords: comparison of gene expression profiles for recurrent and non-recurrent cancer

2009-12-01 | GSE9971 | GEO

Transcription profiling of human stage non-small cell lung cancer samples, metaanalysis for a predictive signature

Project description:We applied a meta-analysis of datasets from seven different microarray studies on lung cancer for differentially expressed genes related to survival time (under 2 y and over 5 y). Systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Experiment Overall Design: RNA was extracted from frozen tissue of primary stage I Non-Small Cell lung tumors for gene array analysis

| S-ECPF-GEOD-6253 | biostudies-other

Targeted next-generation sequencing reveals recurrence-associated genomic alterations in early-stage non-small cell lung cancer.

Project description:Purpose:The identification of genomic alterations related to recurrence in early-stage non-small cell lung cancer (NSCLC) patients may help better stratify high-risk individuals and guide treatment strategies. This study aimed to identify the molecular biomarkers of recurrence in early-stage NSCLC. Results:Of the 42 tumors evaluable for genomic alterations, TP53 and EGFR were the most frequent alterations with population frequency 52.4% and 50.0%, respectively. Fusion genes were detected in four patients, which had lower mutational burden and relatively better genomic stability. EGFR mutation and fusion gene were mutually exclusive in this study. CDKN2A, FAS, SUFU and SMARCA4 genomic alterations were only observed in the relapsed patients. Increased copy number alteration index was observed in early relapsed patients. Among these genomic alterations, early-stage NSCLCs harboring CDKN2A, FAS, SUFU and SMARCA4 genomic alterations were found to be significantly associated with recurrence. Some of these new findings were validated using The Cancer Genome Atlas (TCGA) dataset. Conclusions:The genomic alterations of CDKN2A, FAS, SUFU and SMARCA4 in early-stage NSCLC are found to be associated with recurrence, but confirmation in a larger independent cohort is required to define the clinical impact. Materials and Methods:Paired primary tumor and normal lung tissue samples were collected for targeted next-generation sequencing analysis. A panel targets exons for 440 genes was used to assess the mutational and copy number status of selected genes in three clinically relevant groups of stage I/II NSCLC patients: 1) Early relapse; 2) Late relapse; and 3) No relapse.

| S-EPMC6284742 | biostudies-literature

Transcription profiling of human early stage non-small cell lung carcinoma to refine prognosis for adjuvant therapy

Project description:Abstract from paper - Potti A, et al Experiment Overall Design: Retrospective analysis of approximately 200 samples obtained from Duke, ACOSOG and CALGB to develop a Lung metagene predictor that would then be used to assess risk of recurrence and thus identify high risk patients with stage Ia non-small cell carcinoma who would be candidates for adjuvant chemotherapy

| S-ECPF-GEOD-3593 | biostudies-other

Multiparametric profiling of non-small-cell lung cancers reveals distinct immunophenotypes.

Project description:BACKGROUND. Immune checkpoint blockade improves survival in a subset of patients with non-small-cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. METHODS. We performed comprehensive flow cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next-generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). RESULTS. Cytometric profiling identified an immunologically "hot" cluster with abundant CD8+ T cells expressing high levels of PD-1 and TIM-3 and an immunologically "cold" cluster with lower relative abundance of CD8+ T cells and expression of inhibitory markers. The "hot" cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the "hot" cluster. Additionally, approximately 20% of cases had high B cell infiltrates with a subset producing IL-10. CONCLUSIONS. Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. FUNDING. The Robert A. and Renée E. Belfer Family Foundation, Expect Miracles Foundation, Starr Cancer Consortium, Stand Up to Cancer Foundation, Conquer Cancer Foundation, International Association for the Study of Lung Cancer, National Cancer Institute (R01 CA205150), and the Damon Runyon Cancer Research Foundation.

| S-EPMC5033841 | biostudies-literature

Expression profiling of early-stage squamous cell non-small cell lung cancer

Project description:We are investigating the molecular development of squamous cell lung carcinoma based upon analysis of global gene expression profiles representing progressive stages of cancer development, consisting of precancerous, carcinoma-in-situ, and invasive cancer. Keywords: global gene expression analysis, lung cancer development In this study, we have generated 13 SAGE libraries, consisting of five carcinoma-in-situ libraries, six early invasive squamous cell carcinoma libraries, and two reference libraries representing precancerous squamous development.

| S-ECPF-GEOD-7898 | biostudies-other

Transcription profiling by array of human non-small cell lung cancer tissue

Project description:PURPOSE The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. The present study aims to determine whether the phenotypic heterogeneity and genetic diversity of lung cancer are correlated. PATIENTS AND METHODS In this study, microarray analysis was performed in a set of 91 non-small cell lung cancer (NSCLC) samples in order to: establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas; determine differentially expressed gene sequences at different stages of the disease; and identify sequences with biological significance for tumor progression. After microarray analysis, the expression level of 92 selected genes was validated by qPCR in an independent set of 70 samples. RESULTS Gene sequences were differentially expressed as a function of tumor type, stage, and differentiation grade. High upregulation was observed for KRT15 and PKP1, which may be good markers to distinguish squamous cell carcinoma samples. High downregulation was observed for DSG3 in stage IA adenocarcinomas. CONCLUSION Expression signatures in NSCLC distinguish tumor type, stage, and differentiation grade. Keywords: Tumor vs control comparative genomics study 91 samples studied, 46 tumors and 45 controls. All samples are paired except three.

| S-ECPF-GEOD-18842 | biostudies-other

Transcription profiling by array of human lung cancer samples

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 A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples

| S-ECPF-GEOD-19188 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data