Transcriptome of human NSCLC tissues
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE74706 | GEO | 2016/05/18
SECONDARY ACCESSION(S): PRJNA301214
REPOSITORIES: GEO
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Project description:Eighty-four completely resected stage I/II non-small cell lung cancer (NSCLC) without adjuvant therapy were profiled using whole genome expression microarrys in order to identify novel classifications associated with RFS. Association with relapse-free survival (RFS) and clinicopathological parameters was assessed. An external cohort of 162 tumors was used to validate results.
2014-07-29 | E-MTAB-1790 | biostudies-arrayexpress
Project description:NSCLC remains to be the leading cause of cancer incidence and mortality in the Philippines. Early diagnosis, better understanding on the mechanisms of drug resistance, and proper treatment monitoring is necessary to lower the incidence and mortality rate of NSCLC. This study was able to provide initial insights on the proteomic profile of Filipino NSCLC by quantitative proteomic analysis and identification of aberrant expressions in the tumor tissue relative to the adjacent normal tissue specimen. A total of 4518 proteins were identified and from this, 1855 proteins were found to be significantly upregulated and downregulated. Functional and pathway analysis was done to the upregulated and downregulated proteins with at least 4-fold expression change. Pathway analysis revealed the possible activation of the upregulated protein, MUC1, which is a known oncogenic driver involved in the stimulation of pathways that promote angiogenesis in NSCLC tumor, and prevention of apoptosis. STAT1 and STAT3, also found upregulated in the tumor specimen, were known to have interactions with MUC1 which results to expression of proteins for cell proliferation. The analysis also suggests the stabilization of HIF which allows cell growth in the hypoxic tumor environment, and the activation of EIF signaling correlated with low survival rate of NSCLC patients. Our data demonstrate the rich proteomic information that can be obtained from comprehensive profiling of the NSCLC proteome and applications for better understanding of NSCLC tumorigenicity.
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Project description:Purpose: Generate genome-wide methylation profiles of non-small cell lung carcinomas (NSCLC) and their matching lung tissues for detection of hypermethylated and hypomethylated regions present in the tumors. Methods: MethylCapture followed by next-generation sequencing (Illumina GAIIx) of 7 nsclc tumor samples and paired lung tissues in replicated, plus one cell line, 2 fully artificially methylated and 2 fully artificially unmethylated controls. Normalization of methylation reads based on CpG coupling factor–method. Relative methylation scores (rms) in 500bp non-overlapping windows. 90th percentile of rpm (reads per million) values for all 500bp genome-wide windows, with rpm <1.33 were considered. Distributions of 10bp bins rms values within each 500bp genomic region were compared using both one-sided Student’s t-test and one-sided Wilcoxon rank-sum test. Testing was done separately for hypo- and hypermethylation and p-value threshold of 10-18. Results: MethylCap-seq data revealed strong positive correlation between replicate experiments and between paired tumor/lung samples. 14472 differentially methylated regions (DMR) with non-overlapping 500 bp windows were found. 57 DMRs were present in all NSCLC tumors. 287 were unique for squamous-cell carcinomas and 26 unique for adenocarcinomas. While hypomethylated DMRs did not correlate to any particular functional category of genes, the hypermethylated DMRs were strongly associated with genes encoding transcriptional regulators. Furthermore, subtelomeric regions and satellite repeats were hypomethylated in the NSCLC samples. Conclusion: We provide a resource containing genome-wide DNA methylation maps of NSCLC and their paired lung tissues, and comprehensive lists of known and novel DMRs and associated genes in NSCLC. The DMRs can be in further studies to develop sensitive biological markers for NSCLC, which may enable non-invasive diagnosis and early detection of the disease, and potentially allow histological classification. MethylCap-seq of 7 nsclc tumor samples and paired lung tissues, plus 2 fully methylated and 2 fully unmethylated controls.
2012-10-05 | E-GEOD-41343 | biostudies-arrayexpress
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. Currently, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack of neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples. In this study, a set of 31 pairs and one non-paired sample of macroscopic tumor and non-tumor samples (10 pairs and 1 non-paired sample squamous-cell carcinoma, 19 pairs and one non-paired samples adenocarcinoma, 2 pairs adeno-squamous-cell carcinoma) was selected for bulk/macro sampling. Of these 31 pairs and 2 non-paired samples, 16 pairs plus 15 non paired samples were reanalyzed using laser capture microdissection (LCM) for sampling the cells (7 pairs and 3 non-paired samples squamous-cell carcinoma, 8 pairs and 11 non-paired samples adeno carcinomas, 1 pair and 1 non paired sample Adeno-squamous-cell carcinoma). For macroscopic samples, 50 to 80 µg of tissue was used to isolate total RNA. Gene expression profile was determined using Affymetrix Human Genome Gene 1.0 ST genechip. For the LCM samples, from representative slides histologically confirmed and mapped by a pathologist, approximately 1000 cells/sample were collected by LCM;. cDNA was amplified using Nugen WT-Ovation One-Direct amplification system. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples.
2011-08-25 | E-GEOD-31552 | biostudies-arrayexpress
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. Currently, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) which account for 20% and 80% of lung carcinomas, respectively. NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack of neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples. In this study, an initial set of 30 pairs of macroscopic tumor and non-tumor samples (10 pairs squamous-cell carcinoma, 18 pairs adenocarcinoma, 2 pairs adeno-squamous carcinoma) and 2 unpaired samples was selected for bulk/macro sampling. Of these 30 pairs and 2 unpaired samples, 17 pairs and 9 unpaired samples were reanalyzed using laser capture microdissection (LCM) for sampling the cells (7 pairs squamous and 1 unpaired sample, 9 pairs adenocarcinomas and 7 unpaired samples, 1 pair adeno-squamous carcinoma and 1 unpaired sample). For macroscopic samples, 50 to 80 µg of tissue was used to isolate total RNA. Gene expression profile was determined using Affymetrix Human Genome Gene 1.0 ST genechip. For the LCM samples, from representative slides histologically confirmed and mapped by a pathologist, approximately 1000 cells/sample were collected by LCM. cDNA was amplified using Nugen WT-Ovation One-Direct amplification system. In order to validate Nugen amplification bias of WT-Ovation One-Direct amplification system, the total RNA samples of 10 pairs of macroscopic tumor and non-tumor samples were amplified with this amplification system, and their cDNA was used to microarray.
2011-08-26 | GSE31552 | GEO
Project description:Earlier studies had shown that side population cells isolated from established non-small cell lung cancer (NSCLC) cell lines exhibit cancer stem cell properties. Microarray data from side population (SP) and main population (MP) cells isolated from 4 NSCLC lines (A549, H1650, H460, H1975) were used to examine gene expression profiles associated with stemness. Total RNA extracted from SP and MP samples were used to generate cRNA targets, which were hybridized to Human Genome U133 Plus 2.0 probe arrays. Raw data was processed and the mean center expression level for each gene was determined. Four cell lines (A549, H1650, H460, H1975), each having 1 SP and 1 MP sample.
2012-06-30 | E-GEOD-36821 | biostudies-arrayexpress
Project description:<p><strong>OBJECTIVES:</strong> High activity of Indoleamine 2,3-dioxygenase1 (IDO1) in lung cancer patients converts tryptophan (Trp), which is the essential amino acid for T cell metabolism, to kynurenine (Kyn) and consequently suppresses anti-tumor immune responses. We aimed to track the dynamics of IDO1 activity in stage III non-small cell lung cancer (NSCLC) patients who received first-line radiotherapy (RT) and explore its association with survival outcomes.</p><p><strong>MATERIALS AND METHODS:</strong> Systemic IDO1 activity was calculated by Kyn:Trp ratio. Plasma levels of Kyn and Trp in 113 thoracic RT-received stage III NSCLC patients were measured by high-performance liquid chromatography before the initiation of RT. Dynamic change of IDO1 activity was followed in 24 patients by measuring Kyn:Trp ratio before, during and after RT administration.</p><p><strong>RESULTS:</strong> In 24 patients with dynamic tracking of plasma IDO1 activity, there was no significant alterations observed among the 3 time points (Friedman test, p=0.13). The changing pattern of Kyn:Trp ratio was divided into 4 groups: decreased consistently during RT, first increased then decreased, increased consistently, first decreased then increased. Patients whose Kyn:Trp ratio kept decreasing or first increased then decreased were defined as good-change group. The good-change status was identified as an independent positive factor for overall survival (OS) and progression-free survival (PFS) (p=0.04; p=0.01) in multivariate analysis among evaluated parameters. Patients with good change showed significantly superior local control than bad-change group (p=0.01, HR=0.22). In 113 stage III NSCLC patients with pre-radiation Kyn:Trp ratio, a trend that high baseline IDO1 activity was associated with short OS was observed (p=0.079).</p><p><strong>CONCLUSION: </strong>Favorable change of IDO1 activity during RT was associated with superior OS, PFS and local control. IDO1 activity is a promising biomarker for prognosis in stage III NSCLC patients.</p>
2022-08-05 | MTBLS5267 | MetaboLights
Project description:The goal of this study is to characterize immune cell populations by single cell RNA-sequencing (scRNA-seq) in tumor and uninvolved normal tissues from non-small cell lung cancer (NSCLC) patients with resectable non-small cell lung cancer and who received neoadjuvant chemoimmunotherapy. scRNA-seq was performed on seven pairs of tumor and normal tissues as well as one lymph node (LN) sample.
| EGAS00001006728 | EGA