Gene expression profiling of Non-small cell lung cancer in Taiwan
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wei TY
PROVIDER: S-ECPF-GEOD-27262 | biostudies-other | 2012 Sep
REPOSITORIES: biostudies-other
Similar Datasets
Project description:This study focus on the expression signature between tumor and adjacent normal tissues.
2013-04-10 | GSE27262 | GEO
Project description:This study focus on the expression signature between tumor and adjacent normal tissues. Tumor(T) and adjacent normal(N) tissue pairs from 25 stage I lung adenocarcinoma patients were selected for RNA extraction and hybridization on microarrays.
2013-04-10 | E-GEOD-27262 | biostudies-arrayexpress
Project description:BackgroundRecent technological advances in atmospheric plasmas have made the creation of non-thermal atmospheric pressure plasma (NTP) possible for utilization in the medical field. Although accumulated evidence suggests that NTP induces cell death in various cancer cell types thus offering a promising alternative treatment strategy, the mechanism underlying its therapeutic effect is not fully understood.ResultsWe analyzed relevant signaling cascades associated with the tumor protein p53, in particular the cell cycle arrest, DNA damage as well as the underlying apoptosis pathways. Based on our results, the major effect from plasma exposure was found to be the activation of MAPK and p53 signaling pathways, resulting in changes in gene expression of MEKK, GADD, FOS and JUN. Finally, a significant modulation in expression of genes related to cellular proliferation and differentiation was observed.ConclusionOverall, the presented data of the tumor transcriptome helped identify the key players in modulated gene expression following exposure to plasma at the molecular level, and also helped interpret the downstream processes. The present work laid the foundation for further studies to clarify the roles of multiple pathways in plasma-induced biological processes. Further investigation of these genes in other cell lines may reveal comprehensive mechanisms of plasma induced effects.
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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
Project description:Hypoxia triggers aggressive cancer growth and contributes to chemotherapy resistance. Novel therapeutic strategies aim at targeting hypoxia activated signaling pathways. Tumor hypoxia not only affects neoplastic tumor cells but also the surrounding stroma cells. Therefore, a novel ex vivo model was established, which allows the study of hypoxia effects in fragments of non-small cell lung cancer (NSCLC) with preserved tumor microenvironment and 3D-structure. Microarray analysis identified 107 significantly regulated genes with at least two-fold expression change in hypoxic compared to normoxic fragments. However, only four genes were significantly regulated in both subtypes, adenocarcinoma and squamous cell carcinoma. The hypoxic regulation of these four genes was verified in an independent set using quantitative PCR. Non-small cell lung cancer (NSCLC) fragments were cultured ex vivo under hypoxia or normoxia for three days. cDNA microarray analysis was performed in hypoxic and normoxic lung cancer fragments from ten patients.
| S-ECPF-GEOD-30979 | biostudies-other
Project description:Human non-transformed lung epithelial cell line (BEAS-2B) was transduced with a control (BEAS-C) or PI3KCA-E545K (BEAS-PI3K-CA) expressing lentivirus. After clones selection, RNA was extracted from three different clones for each cell line. For mRNA expression profiling, 500 ng total RNA were reverse transcribed and used for synthesis of cDNA and biotinylated cRNA. Finally cRNA were hybridized for 18 hours on Illumina HumanHT-12 v3.0 BeadChips and after scanning, data analysis was performed.
| S-ECPF-TABM-1192 | biostudies-other
Project description:Genome-wide expression profiling of NSCLC patients were done using Phalanx Human OneArray chip. The surgically resected tumor tissue and corresponding normal tissue were collected from 21 patients diagnosed with primary NSCLC admitted to Taipei Veterans General Hospital, Taiwan. In this study, we used cDNA microarray to detect gene expression profiling in tumor and corresponding normal samples from 21 NSCLC patients. There were 11 AD patients and 10 SQ patients. The patients consisted of 10 early stage patients (stages I and II) and 11 late stage patients (stages III and IV). Hybridization targets were prepared from total RNA and hybridized according to standard protocol using Phalanx Human OneArray chip (32,050 total features: 30968 human genome probes and 1082 experimental control probes).
| S-ECPF-GEOD-21933 | biostudies-other
Project description:Background:Non-small cell lung cancer (NSCLC) is the most common cause of cancer-death due to early metastatic spread, in many cases primarily to the brain. Organ-specific pattern of spread of disease might be driven by the activity of a specific signaling pathway within the primary tumors. We aimed to identify an expression signature of genes and the relevant signaling associated with the development of brain metastasis (BM) after surgical resection of NSCLC. Methods:Rapidly frozen NSCLC surgical specimens were procured from tumor banks. RNA was extracted and analyzed by RNA-sequencing (Illumina HiSeq 2500). Clinical parameters and gene expression were examined for differentiating between patients with BM, patients with metastases to sites other than brain, and patients who did not develop metastatic disease at a clinically significant follow up. Principal component analysis and pathway enrichments studies were done. Results:A total of 91 patients were included in this study, 32 of which developed BM. Stage of disease at diagnosis (P=0.004) and level of differentiation (P=0.007) were significantly different between BM and control group. We identified a set of 22 genes which correlated specifically with BM, and not with metastasis to other sites. This set achieved 93.4% accuracy (95% CI: 86.2-97.5%), 96.6% specificity and 87.5% sensitivity of correctly identifying BM patients in a leave-one-out internal validation analysis. The oxidative phosphorylation pathway was strongly correlated with BM risk. Conclusions:Expression level of a small set of genes from primary tumors was found to predict BM development, distinctly from metastasis to other organs. These genes and the correlated oxidative phosphorylation pathway require further validation as potentially clinically useful predictors of BM and possibly as novel therapeutic targets for BM prevention.
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Project description:Recent technological advances and the application of high-throughput mutation and transcriptome analyses have improved our understanding of cancer diseases, including non-small cell lung cancer. For instance, genomic profiling has allowed the identification of mutational events which can be treated with specific agents. However, detection of DNA alterations does not fully recapitulate the complexity of the disease and it does not allow selection of patients that benefit from chemo- or immunotherapy. In this context, transcriptional profiling has emerged as a promising tool for patient stratification and treatment guidance. For instance, transcriptional profiling has proven to be especially useful in the context of acquired resistance to targeted therapies and patients lacking targetable genomic alterations. Moreover, the comprehensive characterization of the expression level of the different pathways and genes involved in tumor progression is likely to better predict clinical benefit from different treatments than single biomarkers such as PD-L1 or tumor mutational burden in the case of immunotherapy. However, intrinsic technical and analytical limitations have hindered the use of these expression signatures in the clinical setting. In this review, we will focus on the data reported on molecular classification of non-small cell lung cancer and discuss the potential of transcriptional profiling as a predictor of survival and as a patient stratification tool to further personalize treatments.
| S-EPMC8507534 | biostudies-literature
Project description:Lung cancer is generally treated with conventional therapies, including chemotherapy and radiation. These methods, however, are not specific to cancer cells and instead attack every cell present, including normal cells. Personalized therapies provide more efficient treatment options as they target the individual's genetic makeup. The goal of this study was to identify the frequency of causal genetic mutations across a variety of lung cancer subtypes in the earlier stages. 833 samples of non-small cell lung cancer from 799 patients who received resection of their lung cancer, were selected for molecular analysis of six known mutations, including EGFR, KRAS, BRAF, PIK3CA, HER2 and ALK. A SNaPshot assay was used for point mutations and fragment analysis searched for insertions and deletions. ALK was evaluated by IHC +/- FISH. Statistical analysis was performed to determine correlations between molecular and clinical/pathological patient data. None of the tested variants were identified in most (66.15%) of cases. The observed frequencies among the total samples vs. only the adenocarcinoma cases were notable different, with the highest frequency being the KRAS mutation (24.49% vs. 35.55%), followed by EGFR (6.96% vs. 10.23%), PIK3CA (1.20% vs. 0.9%), BRAF (1.08% vs. 1.62%), ALK (0.12% vs. 0.18%), while the lowest was the HER2 mutation (0% for both). The statistical analysis yielded correlations between presence of a mutation with gender, cancer type, vascular invasion and smoking history. The outcome of this study will provide data that helps stratify patient prognosis and supports development of more precise treatments, resulting in improved outcomes for future lung cancer patients.
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