Dataset Information

Intratumor Heterogeneity in Early Lung Adenocarcinoma.

ABSTRACT: Lung cancer is one of the deadliest diseases in the world and is the leading cause of cancer-related deaths. Among the histological types, adenocarcinoma is the most common, and it is characterized by a high degree of heterogeneity at many levels including clinical, behavioral, cellular and molecular. While most lung cancers are known for their aggressive behavior, up to 18.5% of lung cancers detected by CT screening are indolent and put patients at risk for overdiagnosis and overtreatment. The cellular and molecular underpinnings of tumor behavior remain largely unknown. In the recent years, the study of intratumor heterogeneity has become an attractive strategy to understand tumor progression. This review will summarize some of the current known determinants of lung adenocarcinoma behavior and discuss recent efforts to dissect its intratumor heterogeneity.

SUBMITTER: Senosain MF

PROVIDER: S-EPMC7090158 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Intratumor Heterogeneity in Early Lung Adenocarcinoma.

Senosain Maria-Fernanda MF Massion Pierre P PP

Frontiers in oncology 20200317

Lung cancer is one of the deadliest diseases in the world and is the leading cause of cancer-related deaths. Among the histological types, adenocarcinoma is the most common, and it is characterized by a high degree of heterogeneity at many levels including clinical, behavioral, cellular and molecular. While most lung cancers are known for their aggressive behavior, up to 18.5% of lung cancers detected by CT screening are indolent and put patients at risk for overdiagnosis and overtreatment. The ...[more]

PMID: 32257951

Similar Datasets

Project description:IntroductionMicrobiome plays roles in lung adenocarcinoma (LUAD) development and anti-tumor treatment efficacy. Aberrant glycolysis in tumor might promote lactate production that alter tumor microenvironment, affecting microbiome, cancer cells and immune cells. We aimed to construct intratumor microbiome score to predict prognosis of LUAD patients and thoroughly investigate glycolysis and lactate signature's association with LUAD immune cell infiltration.MethodsThe Cancer Genome Atlas-LUAD (TCGA-LUAD) microbiome data was downloaded from cBioPortal and analyzed to examine its association with overall survival to create a prognostic scoring model. Gene Set Enrichment Analysis (GSEA) was used to find each group's major mechanisms involved. Our study then investigated the glycolysis and lactate pattern in LUAD patients based on 19 genes, which were correlated with the tumor microenvironment (TME) phenotypes and immunotherapy outcomes. We developed a glycolysis-lactate risk score and signature to accurately predict TME phenotypes, prognosis, and response to immunotherapy.ResultsUsing the univariate Cox regression analysis, the abundance of 38 genera were identified with prognostic values and a lung-resident microbial score (LMS) was then developed from the TCGA-LUAD-microbiome dataset. Glycolysis hallmark pathway was significantly enriched in high-LMS group and three distinct glycolysis-lactate patterns were generated. Patients in Cluster1 exhibited unfavorable outcomes and might be insensitive to immunotherapy. Glycolysis-lactate score was constructed for predicting prognosis with high accuracy and validated in external cohorts. Gene signature was developed and this signature was elevated in epithelial cells especially in tumor mass on single-cell level. Finally, we found that the glycolysis-lactate signature levels were consistent with the malignancy of histological subtypes.DiscussionOur study demonstrated that an 18-microbe prognostic score and a 19-gene glycolysis-lactate signature for predicting prognosis of LUAD patients. Our LMS, glycolysis-lactate score and glycolysis-lactate signature have potential roles in precision therapy of LUAD patients.

Dataset Information

Intratumor Heterogeneity in Early Lung Adenocarcinoma.

Publications

Intratumor Heterogeneity in Early Lung Adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets