Dataset Information

Multiplatform-based molecular subtypes of non-small-cell lung cancer.

ABSTRACT: Non-small-cell lung cancer (NSCLC) demonstrates remarkable molecular diversity. With the completion of The Cancer Genome Atlas (TCGA), there is opportunity for systematic analyses of the entire TCGA NSCLC cohort, including comparisons and contrasts between different disease subsets. On the basis of multidimensional and comprehensive molecular characterization (including DNA methylation and copy, and RNA and protein expression), 1023 NSCLC cases-519 from TCGA adenocarcinoma (AD) project and 504 from TCGA squamous cell carcinoma (SQCC) project-were classified using a 'cluster-of-clusters' analytic approach. Patterns from TCGA NSCLC subsets were examined in independent external databases, including the PROSPECT (Profiling of Resistance patterns and Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax) NSCLC data set. Nine genomic subtypes of NSCLC were identified, three within SQCC and six within AD. SQCC subtypes were associated with transcriptional targets of SOX2 or p63. One predominately AD subtype (with a large proportion of SQCC) shared molecular features with neuroendocrine tumors. Two AD subtypes manifested a CpG island methylator phenotype. Three AD subtypes showed high p38 and mTOR pathway activation. AD subtypes associated with low differentiation showed relatively worse prognosis. SQCC subtypes and two of the AD subtypes expressed cancer testis antigen genes, whereas three AD subtypes expressed several immune checkpoint genes including PDL1 and PDL2, corresponding with patterns of greater immune cell infiltration. Subtype associations for several immune-related markers-including PD1, PDL1, CD3 and CD8-were confirmed in the PROSPECT cohort using immunohistochemistry. NSCLC molecular subtypes have therapeutic implications and lend support to a personalized approach to NSCLC management based on molecular characterization.

SUBMITTER: Chen F

PROVIDER: S-EPMC5344748 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multiplatform-based molecular subtypes of non-small-cell lung cancer.

Chen F F Zhang Y Y Parra E E Rodriguez J J Behrens C C Akbani R R Lu Y Y Kurie J M JM Gibbons D L DL Mills G B GB Wistuba I I II Creighton C J CJ

Oncogene 20161024 10

Non-small-cell lung cancer (NSCLC) demonstrates remarkable molecular diversity. With the completion of The Cancer Genome Atlas (TCGA), there is opportunity for systematic analyses of the entire TCGA NSCLC cohort, including comparisons and contrasts between different disease subsets. On the basis of multidimensional and comprehensive molecular characterization (including DNA methylation and copy, and RNA and protein expression), 1023 NSCLC cases-519 from TCGA adenocarcinoma (AD) project and 504 f ...[more]

PMID: 27775076

Similar Datasets

Project description:BackgroundNon-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of these patients.MethodsGene expression profiles of 1026 NSCLC patients were collected from The Cancer Genome Atlas (TCGA) datasets with their corresponding clinical and somatic mutation data. Based on immune infiltration scores, molecular clustering classification was performed to identify immune subtypes in NSCLC. After the functional enrichment analysis of subtypes, hub genes were further screened using univariate Cox, Lasso, and multivariate Cox regression analysis, and the risk score was defined to construct the prognostic model. Other microarray data and corresponding clinical information of 603 NSCLC patients from the GEO datasets were applied to conduct random forest models for the prognosis of NSCLC with 100 runs of cross-validation. Finally, external datasets with immunotherapy and chemotherapy were further applied to explore the significance of risk-scores in clinical immunotherapy response for NSCLC patients.ResultsCompared with Subtype-B, the Subtype-A, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration scores and up-regulation of immunotherapy markers. In addition, we found and validated an eleven -gene signatures for better application of distinguishing high- and low-risk NSCLC patients and predict patients' prognosis and therapeutical response to immunotherapy. Furthermore, combined with other clinical characteristics based on multivariate Cox regression analysis, we successfully constructed and validated a nomogram to effectively predict the survival rate of NSCLC patients. External immunotherapy and chemotherapy cohorts validated the patients with higher risk-scores exhibited significant therapeutic response and clinical benefits.ConclusionThese results demonstrated the immunological and prognostic heterogeneity within NSCLC and provided a new clinical application in predicting the prognosis and benefits of immunotherapy for the disease.

Project description:Current paradigms hold that lung carcinomas arise from pleuripotent stem cells capable of differentiation into one or several histological types. These paradigms suggest lung tumor cell ontogeny is determined by consequences of gene expression that recapitulate events important in embryonic lung development. Using oligonucleotide microarrays, we acquired gene profiles from 32 microdissected non-small-cell lung tumors. We determined the 100 top-ranked marker genes for adenocarcinoma, squamous cell, large cell, and carcinoid using nearest neighbor analysis. Results were validated by immunostaining for 11 selected proteins using a tissue microarray representing 80 tumors. Gene expression data of lung development were accessed from a publicly available dataset generated with the murine Mu11k genome microarray. Self-organized mapping identified two temporally distinct clusters of murine orthologues. Supervised clustering of lung development data showed large-cell carcinoma gene orthologues were in a cluster expressed in pseudoglandular and canalicular stages whereas adenocarcinoma homologues were predominantly in a cluster expressed later in the terminal sac and alveolar stages of murine lung development. Representative large-cell genes (E2F3, MYBL2, HDAC2, CDK4, PCNA) are expressed in the nucleus and are associated with cell cycle and proliferation. In contrast, adenocarcinoma genes are associated with lung-specific transcription pathways (SFTPB, TTF-1), cell adhesion, and signal transduction. In sum, non-small-cell lung tumors histology gene profiles suggest mechanisms relevant to ontogeny and clinical course. Adenocarcinoma genes are associated with differentiation and glandular formation whereas large-cell genes are associated with proliferation and differentiation arrest. The identification of developmentally regulated pathways active in tumorigenesis provides insights into lung carcinogenesis and suggests early steps may differ according to the eventual tumor morphology.

Dataset Information

Multiplatform-based molecular subtypes of non-small-cell lung cancer.

Publications

Multiplatform-based molecular subtypes of non-small-cell lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets