Gene expression profiles of NSCLC tumors
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Raj Chari
PROVIDER: E-GEOD-31799 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Whole genome tiling path array CGH was used to measure the copy number profiles of 271 NSCLC tumors 271 microdissected NSCLC tumors
2011-09-11 | E-GEOD-31798 | biostudies-arrayexpress
Project description:Whole genome tiling path array CGH was used to measure the copy number profiles of 271 NSCLC tumors
2011-09-12 | GSE31798 | GEO
Project description:A custom microarray was used to measure the gene expression of NSCLC tumors. This represents a subset of samples which also have matched DNA copy number profiles from array CGH experiments
2011-09-12 | GSE31799 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE31798: DNA copy number profiles of NSCLC tumors GSE31799: Gene expression profiles of NSCLC tumors Refer to individual Series
2011-09-11 | E-GEOD-31800 | biostudies-arrayexpress
Project description:A data set of normal epithelium, serous ovarian surface epithelial-stromal tumors (benign and type II malignancies), stroma distal to tumor, and stroma adjacent to tumor (50 samples total). Additional cel files are included which represent replicate sampling from patients, and cel files that failed quality control but may be bioinformatically interesting. Additional replicate or failed cel files were not included in the final analysis (and so these samples were not included in the matrix). Background: Ovarian cancer is the most lethal gynecologic cancer in the United States. If caught in early stages, patient survival rate can reach 94%, when diagnosed at late stages survival rates drop to 28%. Correct diagnosis depends on the presence of definite symptoms: while ~90% of diagnosed ovarian cancers have symptoms, they tend to be unfocused and subacute. A definitive and early molecular signature of disease is thus desired. To further progress towards this goal, we present an Affymetrix™ human exon array data set measuring ovarian tumor expression, assembled using best practices. Method: Samples were collected from patients with benign and malignant (type II) serous ovarian surface epithelial-stromal tumors. Normal epithelium, tumor, stroma adjacent to tumor, and distal stroma were selected based on histopathology, and isolated using laser capture microdissection. Nugen products were used to perform random-primed mRNA amplification procedures (for full transcript capture) before hybridization to Affymetrix exon chips. Tumor expression and paracrine signaling was assessed using GC-RMA and a two-way Model I ANOVA. Single enrichment ontological analysis and gene network construction were performed to guide inferences about biological context. Results: In total, across 50 microarrays, ~270 million measurements were obtained. Based on comparisons to known ovarian cancer properties as established in molecular genetics literature, the initial analysis presented emphasizes data quality. Major trends between sample classes included: apical surface and tight junction activity, mitotic activity, benign tumor suppression, epithelial-mesenchymal transitioning, tumor oncogene activity, and paracrine signaling. A list of differentially expressed transcripts has been produced to enable rapid comparisons with published biomarker lists, but it is expected that detailed alternative transcript analysis will refine these predictions. Conclusions: A data set of 50 arrays, from carefully dissected serous ovarian surface epithelial-stromal tumors, has been produced, from which high quality measurements were obtained. While relatively small in number, this represents an important addition to the community pool of ovarian tumor samples, and the chosen platform enables bridging between 3' expression and exome sequencing data sets. This represents a significant contribution to the ovarian cancer genetics community. A total of 50 human ovary samples were used in analysis: 23 tissue samples laser capture microdissected from an ovary with a benign serous tumor (specifically 4 normal epithelium samples, 5 tumor samples, 6 stroma samples adjacent to the tumor, and 8 stroma samples distal of the tumor), and 27 tissue samples laser capture microdissected from an ovary with a malignant serous tumor (specifically 5 normal epithelium samples, 8 tumor samples, 7 stroma samples adjacent to the tumor, and 7 stroma samples distal of the tumor). Additional cel files were provided which, although were used in the quality control of the data set, were not used in the final experimental analysis. 8 replicates are included as cel files (1 from each cohort previously listed). 14 cel files were also included which failed quality control. Although the replicate and failed cel files were not used in the final analysis, they may still be interesting in other research.
2011-05-11 | E-GEOD-29156 | 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:The delicate interaction between cancer cells and the surrounding stroma plays an essential role in all stages of tumourigenesis. Despite the significance of this interplay, alterations in protein composition underlying tumour-stroma interactions are largely unknown. The aim of this study was to identify stromal proteins with clinical relevance in non-small cell lung cancer. A list encompassing 203 stromal candidate genes was compiled based on gene expression array data and available literature. The protein expression of these genes in human NSCLC was screened utilising the Human Protein Atlas. Twelve proteins were selected that showed a differential stromal staining pattern. The corresponding antibodies were applied on a tissue microarray, including 190 NSCLC samples, and stromal staining was correlated with clinical parameters. Higher stromal expression of CD99was associated with good prognosis in the univariate (p=0.037) and multivariate (p=0.039) analyses. The association was independent from the total proportion of tumour stroma, the fraction of inflammatory cells, and clinical and pathological parameters like stage, performance status and tumour histology. The prognostic impact of stromal CD99 protein expression was confirmed in an independent cohort of 240 NSCLC patients (p=0.008). Furthermore, double-staining confocal fluorescence microscopy showed that CD99 was expressed in stromal lymphocytes as well as in cancer associated fibroblasts. Based on a comprehensive screening strategy the membrane protein CD99 was identified as a novel stromal factor with clinical relevance. The result supports the concept that stromal properties have a significant impact on tumourigenesis. Tissue from five tumors were compared to corressponding microdissected tissue from the same tissue sample
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Project description:Non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations do not respond to anti-PD-1 (L1) as well as tumors without an EGFR mutation. We showed in a xenograft mouse model of EGFR-mutated NSCLC that, neither durvalumab nor oleclumab alone inhibited tumor growth compared to the isotype control. In contrast, the combination of both antibodies significantly inhibited tumor growth and increased gene expressions that corresponded to inflammation and T cell function in tumors treated. We used microarrays to study gene expressions that corresponded to enhanced immune response in antibody-treated mice.
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Project description:Gene expression profiling of NSCLC tumors with distinct PAEP expression suggested several pathways, which might be involved in the regulation of PAEP/glycodelin expression.
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Project description:Genomic profile of 47 tumors from hereditary breast cancer cases by Array CGH, 7 of which were BRCA mutation carriers (4 in BRCA2 and 3 in BRCA1), previously analyzed for BRCA1 expression by immunohistochemistry. Our goal was to identify specific alterations for BRCA1 not expressing tumors DNA from 47 Tumors versus DNA pool from normal tissue. BRCA1 expression, Hierarchical clustering and overall survival analyses.
2015-07-07 | E-GEOD-70541 | biostudies-arrayexpress