Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma
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ABSTRACT:
PROVIDER: PRJNA955661 | ENA |
REPOSITORIES: ENA
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Project description:Tumor-adjacent lung transcriptome as a predictor of recurrence in early-stage lung adenocarcinoma [snRNA-seq]
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Project description:Genome wide gene expression profiling of lung adenocarcinoma and non-tumor adjacent tissues. The Agilent microarray was used to obtain gene expression profiles. Samples included eight lung cancer and adjacent non-tumor tissues excised from a cohort of 8 patients with lung adenocarcinoma.
2017-03-09 | GSE85841 | GEO
Project description:Genome wide DNA methylation profiling of lung adenocarcinoma and non-tumor adjacent tissues. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles. Samples included eight lung cancer and adjacent non-tumor tissues excised from a cohort of 8 patients with lung adenocarcinoma.
2016-12-01 | GSE85845 | GEO
Project description:Genome wide lncRNA and mRNA expression profiling of lung adenocarcinoma and non-tumor adjacent tissues. The Agilent microarray was used to obtain gene expression profiles. Samples included eight lung cancer and adjacent non-tumor tissues excised from a cohort of 8 patients with lung adenocarcinoma.
2019-05-07 | GSE130779 | GEO
Project description:Background: Lung is the largest mucosal area of the human body and directly connected to the external environment, facing microbial exposure and environmental stimuli. Therefore, studying the internal microorganisms of the lung is crucial for a deeper understanding of the relationship between microorganisms and the occurrence and progression of lung cancer. Methods: Tumor and adjacent nontumor tissues were collected from 38 lung adenocarcinoma patients and used nanopore sequencing technology to sequence the 16s full-length sequence of bacteria, and combining bioinformatics methods to identify and quantitatively analyze microorganisms in tissues, as well as to enrich the metabolic pathways of microorganisms. Results: the microbial composition in lung adenocarcinoma tissues is highly similar to that in adjacent tissues, but the alpha diversity is significantly lower than that in adjacent tissues. The difference analysis results show that the bacterial communities of Streptococcaceae, Lactobacillaceae, and Neisseriales were significantly enriched in cancer tissues. The results of metabolic pathway analysis indicate that pathways related to cellular communication, transcription, and protein synthesis were significantly enriched in cancer tissue. In addition, clinical staging analysis of nicotine exposure and lung cancer found that Haemophilus, paralinfluenzae, Streptococcus gordonii were significantly enriched in the nicotine exposure group, while the microbiota of Cardiobactereae and Cardiobacterales were significantly enriched in stage II tumors. The microbiota significantly enriched in IA-II stages were Neisseriaeae, Enterobacteriales, and Cardiobacterales, respectively. Conclusion Nanopore sequencing technology was performed on the full length 16s sequence, which preliminarily depicted the microbial changes and enrichment of microbial metabolic pathways in tumor and adjacent nontumor tissues. The relationship between nicotine exposure, tumor progression, and microorganisms was explored, providing a theoretical basis for the treatment of lung cancer through microbial targets.
2024-03-25 | GSE262090 | GEO
Project description:Gene expression profiling of 60 lung adenocarcinoma tumors and their matched histologically normal adjacent lung tissue samples were analyzed using Illumina HumanWG-6 v3.0 expression beadchip. We integrated these data with DNA methylation profiles of the same samples to identify potential DNA methylation regulated genes. Lung cancer is the leading cause of cancer death worldwide and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung samples, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent downregulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and downregulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor-suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by providing new candidate DNA methylation biomarkers for early detection, identifying novel molecular alterations potentially involved in lung adenocarcinoma development/progression, and describing an epigenetic subgroup of lung adenocarcinoma associated with KRAS mutation. 58 lung adenocarcinoma and 58 adjacent non-tumor lung fresh frozen tissues were macrodissected, and total RNA was isolated to be analyzed using the Illumina HumanWG-6 v3.0 expression beadchip.
2012-03-21 | E-GEOD-32863 | biostudies-arrayexpress
Project description:Individual variations in the transcriptional profile of normal lung tissue may reflect the lung ADCA patients’ predisposition to a specific clinical stage Associations between clinical outcome of cancer patients and the gene expression signature in primary tumors at time of diagnosis have been reported. To test whether gene expression patterns in the normal tissue surrounding the cancerous tissue might correlate with clinical stage, we compared transcriptome of normal lung samples of adenocarcinoma (ADCA) smoker patients of clinical stage I versus stage >I, and identified 55 differentially expressed genes. Eight out of 10 genes validated by quantitative real-time PCR confirmed statistical association with clinical stage, with 6 genes downregulated in high clinical stage patients, including the TMEM100 gene showing the best statistical association. Five of these 6 genes were also downregulated in lung ADCA tissue as compared to normal tissue. Functional studies in vitro indicated that four of them (SLC14A1, SMAD6, TMEM100, and TXNIP) inhibited colony formation when over-expressed by transfection in lung cancer cell lines, suggesting their potential tumor-suppressor activity. Our findings indicated that individual variations in the transcriptional profile of normal lung tissue may reflect the lung ADCA patients’ predisposition to a specific clinical stage. The 120 RNA samples from normal lung were combined in 24 small pools, with 12 pools constituted by stage I patients and 12 pools by stage >I patients (5 samples per pool)
2013-01-01 | E-GEOD-31267 | biostudies-arrayexpress