Transcription profiling of human lung cancer patients with sqamous cell or adenocarcinoma at different stages of disease to identify gene signatures to predict prognosis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Raponi M
PROVIDER: S-ECPF-GEOD-4573 | biostudies-other | 2006 Aug
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Gene signatures were derived to separate high risk patients from low risk ones. Experiment Overall Design: 130 samples from 129 patients
2007-11-01 | E-GEOD-4573 | biostudies-arrayexpress
Project description:Malignant pleural mesothelioma (MPM) is a rare but lethal pleural cancer with high intratumor heterogeneity (ITH). A recent study in lung adenocarcinoma has developed a clonal gene signature (ORACLE) from multiregional transcriptomic data and demonstrated high prognostic values and reproducibility. However, such a strategy has not been tested in other types of cancer with high ITH. We aimed to identify biomarkers from multi-regional data to prognostically stratify MPM patients. We generated a multiregional RNA-seq dataset for 78 tumor samples obtained from 26 MPM patients, each with one sample collected from a superior, lateral, and inferior region of the tumor. By integrating this dataset with the Cancer Genome Atlas MPM RNA-seq data, we selected 29 prognostic genes displaying high variability across different tumors but low ITH, which named PRACME (Prognostic Risk Associated Clonal Mesothelioma Expression). We evaluated PRACME in two independent MPM datasets and demonstrated its prognostic values. Patients with high signature scores are associated with poor prognosis after adjusting established clinical factors. Interestingly, the PRACME and the ORACLE signatures defined respectively from MPM and lung adenocarcinoma cross-predict prognosis between the two cancer types. Further investigation indicated that the cross-prediction ability might be explained by the high similarity between the two cancer types in their genomic regions with copy number variation, which host many clonal genes. Overall, our clonal signature PRACME provided prognostic stratification in MPM and this study emphasized the importance of multi-regional transcriptomic data for prognostic stratification based on clonal genes.
| S-EPMC10891127 | biostudies-literature
Project description:We aimed to find some specific pathways that can be used to predict the stage of lung adenocarcinoma.RNA-Seq expression profile data and clinical data of lung adenocarcinoma (stage I [37], stage II 161], stage III [75], and stage IV [45]) were obtained from the TCGA dataset. The differentially expressed genes were merged, correlation coefficient matrix between genes was constructed with correlation analysis, and unsupervised clustering was carried out with hierarchical clustering method. The specific coexpression network in every stage was constructed with cytoscape software. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed with KOBAS database and Fisher exact test. Euclidean distance algorithm was used to calculate total deviation score. The diagnostic model was constructed with SVM algorithm.Eighteen specific genes were obtained by getting intersection of 4 group differentially expressed genes. Ten significantly enriched pathways were obtained. In the distribution map of 10 pathways score in different groups, degrees that sample groups deviated from the normal level were as follows: stage I < stage II < stage III < stage IV. The pathway score of 4 stages exhibited linear change in some pathways, and the score of 1 or 2 stages were significantly different from the rest stages in some pathways. There was significant difference between dead and alive for these pathways except thyroid hormone signaling pathway.Those 10 pathways are associated with the development of lung adenocarcinoma and may be able to predict different stages of it. Furthermore, these pathways except thyroid hormone signaling pathway may be able to predict the prognosis.
| S-EPMC5413258 | biostudies-literature
Project description:Background: Lung adenocarcinoma (LUAD) possesses a poor prognosis with a low 5-year survival rate even for stages I-III resected patients, it is thus critical to understand the determinants that affect the survival and discover new potentially prognostic biomarkers. Somatic copy number alterations (CNAs) are major source of genomic variations driving tumor evolution, CNAs screening may identify prognostic biomarkers. Methods: Oncoscan MIP array was used to analyze the patterns of CNAs on formalin fixed paraffin embedded(FFPE) tumor specimens from 163 consecutive stage I-III resected LUAD patients, 145 out of which received platinum-based adjuvant chemotherapy. Results: Of the 163 patients, 91(55.8%) were recurred within 3 years after surgery. The most common aberrations in our cohort were 1q, 5p, 5q, 7p, 8q, 14p, 16p, 17q, 20q for copy number gains and 8p, 9p, 13p, 16q, 18q for losses. The GISTIC2 analysis produced 45 amplification peaks and 40 deletion peaks, involving some reported genes TERT, EGFR, MYC, CCND1, CDK4, MDM2, ERBB2, NKX2-1, CCNE1, and CDKN2A, most of which were consistent with TCGA database. The amplifications of 12p12.1 (CMAS, GOLT1B, YS2, LDHB, RECQL, ETNK1, IAPP, PYROXD1, KRAS) and KDM5A were correlated with worse prognosis in our cohort, this result was further validated in 506 LUAD patients from TCGA. In addition, 163 patients could be well-classified into five groups, and the clinical outcomes were significantly different based on threshold copy number at reoccurring alteration peaks. Among the 145 patients who received adjuvant chemotherapy, focal amplification of ERBB2 and deletion of 4q34.3 were found to be specific in relapsed patients, this result was validated in an independent group of Imielinski et al., demonstrating these two CNAs may contribute to resected LUAD recurrence after adjuvant chemotherapy. Conclusion: This study suggests that CNAs profiling may be a potential prognostic classifier in resected LAUD patients. Amplifications of 12p12.1 and KDM5A might be prognostic biomarkers for LUAD, and amplification of ERBB2 and deletion of 4q34.3 predicted early relapse after adjuvant chemotherapy. These novel findings may provide implication for better implementation of precision therapy for lung cancer patients.
| S-EPMC6691340 | biostudies-literature
Project description:Signatures of Oncogenic Pathway Deregulation in Human Cancers. The ability to define cancer subtypes, recurrence of disease, and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Such data is also of substantial importance to the analysis of cellular signaling pathways central to the oncogenic process. With this focus, we have developed a series of gene expression signatures that reliably reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumors, and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumor sub-types. Clustering tumors based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Furthermore, predictions of pathway deregulation in cancer cell lines are shown to coincide with sensitivity to therapeutic agents that target components of the pathway, underscoring the potential for such pathway prediction to guide the use of targeted therapeutics. Experiment Overall Design: RNA was extracted from frozen tissue of primary lung tumors for gene array analysis.
| S-ECPF-GEOD-3141 | biostudies-other
Project description:Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from Indian women, spanning International Federation of Gynaecology and Obstetrics (FIGO) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA-B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine-cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP1, proliferating cell nuclear antigen (PCNA), STK17A, and DUSP1 among others that were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression.
| S-EPMC3892388 | biostudies-literature
Project description: Not available
| S-ECPF-MTAB-923 | biostudies-other
Project description:BackgroundLactic acid, as a product of glycolysis, increases tumor cell migration and the invasion of tumor cells in the tumor microenvironment. Besides this, lactic acid promotes the expression of programmed death-1 expression (PD-1) in regulatory T cells, which could cause the failure of PD-1 blockade therapy. However, the implications of lactic acid in the tumor microenvironment of lung adenocarcinoma (LUAD) remain largely unclear.MethodsWe performed unsupervised consensus clustering to identify lactic-associated subtypes using expression profile of lactate regulators in LUAD. Differentially expressed genes (DEGs) associated with lactic-associated subtypes was used to construct lactate signature (LaSig) using LASSO regression algorithm. Immune infiltration analysis was conducted by ESTIMATER and drug sensitivity was estimated by R package called "pRRophetic". The difference between two groups was calculated using Wilcox rank sum test and correlation analysis was calculated using Pearson correlation coefficient.ResultsIn this study, we evaluated DNA methylation and the mutation frequency of lactate regulators and found lactate regulators showed low mutation frequency in the TCGA-LUAD cohort, except TP53. At the RNA level, the expression level of lactate regulators was significantly associated with the immune cell component. In particular, expression of LDHA was positively correlated with CD4 T cell, CD8 T cell, M1 macrophages, and the enrichment score of multiple immune pathways. Two clusters were defined using the gene expression level of lactate regulators, and LDHA was significantly upregulated in cluster 1 with poor overall survival. A lactate signature (LaSig) had a robust performance in predicting the survival rate and immunotherapy response of LUAD patients. Moreover, patients in the high LaSig group may be more likely to benefit from these drugs (Cisplatin, Erlotinib, Gemcitabine, and Vinblastine) than those in the low LaSig group.ConclusionIn summary, our study explores the role of lactate regulators in guiding the clinical treatment of lung adenocarcinoma and provides additional help to supplement traditional molecular subtypes.
| S-EPMC9732022 | biostudies-literature
Project description:Tumor microenvironment (TME) has critical impacts on the pathogenesis of lung adenocarcinoma (LUAD). However, the molecular mechanism of TME effects on the prognosis of LUAD patients remains unclear. Our study aimed to establish an immune-related gene pair (IRGP) model for prognosis prediction and internal mechanism investigation. Based on 702 TME-related differentially expressed genes (DEGs) extracted from The Cancer Genome Atlas (TCGA) training cohort using the ESTIMATE algorithm, a 10-IRGP signature was established to predict LUAD patient prognosis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that DEGs were significantly associated with tumor immune response. In both TCGA training and Gene Expression Omnibus validation datasets, the risk score was an independent prognostic factor for LUAD patients using Lasso-Cox analysis, and patients in the high-risk group had poorer prognosis than those in the low-risk one. In the high-risk group, M2 macrophage and neutrophil infiltrations were higher, while the levels of T cell follicular helpers were significantly lower. The gene set enrichment analysis results showed that DNA repair signaling pathways were involved. In summary, we established an IRGP signature as a potential biomarker to predict the prognosis of LUAD patients.
| S-EPMC7873765 | biostudies-literature
Project description:Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD. Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy. Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application.
| S-EPMC9614324 | biostudies-literature