Dataset Information

Molecular Subtyping and Prognostic Assessment Based on Tumor Mutation Burden in Patients with Lung Adenocarcinomas.

ABSTRACT: The distinct molecular subtypes of lung cancer are defined by monogenic biomarkers, such as EGFR, KRAS, and ALK rearrangement. Tumor mutation burden (TMB) is a potential biomarker for response to immunotherapy, which is one of the measures for genomic instability. The molecular subtyping based on TMB has not been well characterized in lung adenocarcinomas in the Chinese population. Here we performed molecular subtyping based on TMB with the published whole exome sequencing data of 101 lung adenocarcinomas and compared the different features of the classified subtypes, including clinical features, somatic driver genes, and mutational signatures. We found that patients with lower TMB have a longer disease-free survival, and higher TMB is associated with smoking and aging. Analysis of somatic driver genes and mutational signatures demonstrates a significant association between somatic RYR2 mutations and the subtype with higher TMB. Molecular subtyping based on TMB is a potential prognostic marker for lung adenocarcinoma. Signature 4 and the mutation of RYR2 are highlighted in the TMB-High group. The mutation of RYR2 is a significant biomarker associated with high TMB in lung adenocarcinoma.

SUBMITTER: Wang C

PROVIDER: S-EPMC6747282 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Molecular Subtyping and Prognostic Assessment Based on Tumor Mutation Burden in Patients with Lung Adenocarcinomas.

Wang Changzheng C Liang Han H Lin Cong C Li Fuqiang F Xie Guoyun G Qiao Sitan S Shi Xulian X Deng Jianlian J Zhao Xin X Wu Kui K Zhang Xiuqing X

International journal of molecular sciences 20190830 17

The distinct molecular subtypes of lung cancer are defined by monogenic biomarkers, such as EGFR, KRAS, and ALK rearrangement. Tumor mutation burden (TMB) is a potential biomarker for response to immunotherapy, which is one of the measures for genomic instability. The molecular subtyping based on TMB has not been well characterized in lung adenocarcinomas in the Chinese population. Here we performed molecular subtyping based on TMB with the published whole exome sequencing d ...[more]

PMID: 31480292

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Project description:BackgroundTransient receptor potential (TRP) channels have high permeability to Ca2+ ions because they are non-selective ion channels. TRP channels have been implicated in tumor onset and progression, proliferation, and migration in recent years. However, the prognostic value of genes related to TRP and their specific mechanism in pancreatic adenocarcinoma (PAAD) are yet to be understood.MethodsPublic databases such as TCGA and GEO were used to retrieve data on gene expression and clinical information of patients with pancreatic adenocarcinoma for our study. ConsensusClusterPlus package was used for unsupervised clustering analysis. The microenvironment cell population (MCP)-counter approach was employed to measure the immune cells infiltration status. The Pearson correlation was performed to identify TRP-associated lncRNAs.ResultsInitially, we separated PAAD patients into three clusters depending on TRP-related genes, and of the three clusters, cluster B showed the least immune cell infiltration, which was correlated with poor prognosis. Moreover, GSVA enrichment analysis further revealed that cluster A was subjected to a considerable enrichment in carcinogenic signaling pathways, whereas cluster C was enriched in immune-related pathways. Then, using TRP-associated lncRNAs as a starting point, we constructed a prognostic risk model for PAAD patients that could efficiently predict their prognosis. Further, GSEA revealed that cancer-related pathways, for instance, the cell cycle, p53 signaling pathway, etc. were considerably enriched in the high-risk group. In addition, we looked into the link between the prognostic model and the immunological microenvironment. Lower cytotoxic lymphocytes, NK cells, CD8 T cells, and endothelial cells infiltration were found to be associated with high risk using the MCP-counter algorithm. The expression of CD274, POLE2, MCM6, and LOXL2 was also found to be higher in the high-risk group. TMB was also considerably greater in high-risk individuals, indicating that immune checkpoint inhibitors (ICIs) therapy may benefit them more. Lastly, qRT-PCR further confirmed the differential expression of these prognostic TRP-associated lncRNAs, indicating that these lncRNAs play an imperative role in PAAD tumorigenesis.ConclusionTRP family genes may represent a new class of candidate molecular markers of the occurrence and progression of PAAD. Risk models based on TRP-associated lncRNAs could provide important new references for immunotargeted therapy of pancreatic adenocarcinoma.

Project description:PurposeTumor mutation burden (TMB) and tumor-infiltrating lymphocytes (TILs) have been well recognized as molecular determinants of immunotherapy responsiveness. In this study, we aimed to construct a TMB prognostic model and explore biomarkers that have predictive potential for prognosis and therapeutic effect in lung adenocarcinoma (LUAD).Patients and methodsThe TCGA, GEO and Immport databases were used to analyze the mutation profiles and immune infiltration of LUAD. TMB scores were calculated and differential analysis was conducted to identify TMB-related genes. Then, Cox regression model and survival analysis were applied to identify the prognostic genes and construct a TMB prognostic model. The expression and prognostic value of CD1B were further verified by immunohistochemistry (IHC) in 92 patient tissue samples. GSEA was performed to analyze the signaling pathways associated with CD1B expression.ResultsHigh-TMB samples exhibited higher infiltration of CD8+ T cells, CD4+ memory T cells, and M1 macrophages. A total of 397 TMB-related differentially expressed genes were identified, of which 47 were immune-related genes. Cox regression analyses determined 3 hub TMB-related immune genes (CD1B, SCGB3A1, and VEGFD) with prognostic effects, and a TMB prognostic model was constructed. The model demonstrated robust predictive ability in both the training (TCGA) and testing (GEO) datasets. Notably, CD1B was identified as an independent prognostic factor. IHC of clinical samples showed that low expression of CD1B was related to poor overall survival and advanced pathological stages. In addition, there was a strong positive correlation between CD1B and most immune checkpoint molecules, including PD-L1. CD1B expression was associated with immune cell infiltration and immune activation in LUAD.ConclusionOur study constructed a TMB prognostic model that effectively predicted the prognosis of LUAD patients. CD1B expression is correlated with better prognosis and promotes antitumor immunity in LUAD, which may serve as a potential prognostic biomarker and immune-related therapeutic target for LUAD.

Project description:Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC). Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, "CIBERSORT" package was utilized to estimate the immune infiltration. Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What's more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group. Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

Dataset Information

Molecular Subtyping and Prognostic Assessment Based on Tumor Mutation Burden in Patients with Lung Adenocarcinomas.

Publications

Molecular Subtyping and Prognostic Assessment Based on Tumor Mutation Burden in Patients with Lung Adenocarcinomas.

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