Dataset Information

EPHA5 mutations predict survival after immunotherapy in lung adenocarcinoma.

ABSTRACT: Eph receptors constitute the largest family of RTKs, and their associations with antitumor immunity and immunotherapy are largely unknown. By integrating genomic, transcriptomic and clinical data from cohorts in public databases, we identified EPHA5 as the most common mutated gene of Eph receptors in lung adenocarcinoma (LUAD). Moreover, compared with EPHA5 wild-type (WT) patients, EPHA5-mutant (Mut) patients exhibited significantly enhanced infiltration of CD8⁺ T cells and M1 macrophages, reduced recruitment of immunosuppressive regulatory T cells (Tregs) into the tumor site, as well as the increased level of chemokine, interferon-gamma, inhibitory immune checkpoint signatures, tumor mutation burden (TMB) and tumor neoantigen burden (TNB). Additionally, EPHA5 mutation cooccurred with homologous recombination (HR) or mismatch repair (MMR) gene mutations. These data were validated in the LUAD cell line H1299 and a Chinese LUAD cohort. Most importantly, clinical analysis of a Memorial Sloan Kettering Cancer Center (MSKCC) immunotherapy cohort indicated that LUAD patients with EPHA5 mutations who were treated with immunotherapy had markedly prolonged survival times. Our results revealed the correlation of EPHA5 mutations with tumor immune microenvironment and predictive factors for immunotherapy, implying the potential of EPHA5 mutations as a prognostic marker for the prognosis of LUAD patients to immune checkpoint blockade therapy.

SUBMITTER: Chen Z

PROVIDER: S-EPMC7834994 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

EPHA5 mutations predict survival after immunotherapy in lung adenocarcinoma.

Chen Zhiming Z Chen Ji J Ren Dandan D Zhang Jiao J Yang Ying Y Zhang Henghui H Mao Beibei B Ma Haitao H

Aging 20201203 1

Eph receptors constitute the largest family of RTKs, and their associations with antitumor immunity and immunotherapy are largely unknown. By integrating genomic, transcriptomic and clinical data from cohorts in public databases, we identified EPHA5 as the most common mutated gene of Eph receptors in lung adenocarcinoma (LUAD). Moreover, compared with EPHA5 wild-type (WT) patients, EPHA5-mutant (Mut) patients exhibited significantly enhanced infiltration of CD8<sup>+</sup> T cells and M1 macroph ...[more]

PMID: 33288738

Similar Datasets

Project description:Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and has a poor prognosis. Disulfidptosis is a novel regulated cell death form characterized by aberrant disulfide stress and actin network collapse. This study aimed to identify disulfidptosis-related lncRNAs, and predict LUAD patients' prognosis and response to antitumor therapies by establishing a disulfidptosis-related lncRNA model. Methods: Transcriptome and clinical data of LUAD patients were obtained from the TCGA database. Pearson correlation and Cox regression analysis was used to identify disulfidptosis-related lncRNAs associated with overall survival. LASSO regression analysis was adopted to construct the prognostic model. GO, KEGG and GSEA analysis was used to identify cellular pathways related to this model. Immune cell infiltration was investigated by ESTIMATE and CIBERSORT algorithms. Tumor mutational burden (TMB) and its association with model-derived risk score were analyzed using simple nucleotide variation data. Patients' response to immunotherapy and other antineoplastic drugs was predicted by the TIDE algorithm and GDSC tool, respectively. Results: We identified 127 disulfidptosis-related lncRNAs, and a prognostic model that consists eight of them (KTN1-AS1, AL365181.3, MANCR, LINC01352, AC090559.1, AC093673.1, AP001094.3, and MHENCR) was established and verified. The prognostic model could stratify LUAD patients into two distinct risk-score groups. A high risk score was an independent prognosis factor indicating poor overall survival, and correlated with reduced immune cell infiltration, high TMB, and lower activity of tumor immune response. Immune checkpoint blockade might bring more survival benefits to the high-risk LUAD patients, whereas low-risk patients might be more responsive to targeted therapy and diverse kinase inhibitors. Conclusion: We established a disulfidptosis-related lncRNA model that can be exploited to predict the prognosis, tumor mutational burden, immune cell infiltration landscape, and response to immunotherapy and targeted therapy in LUAD patients.

Project description:BackgroundThe role of tumor-infiltrating B-cells (TIBs) and intratumorally-produced antibodies in cancer-immunity interactions essentially remains terra incognita. In particular, it remains unexplored how driver mutations could be associated with distinct TIBs signatures and their role in tumor microenvironment.MethodsHere we analyzed associations of immunoglobulin isotypes and clonality with survival in TCGA RNA-Seq data for lung adenocarcinoma (LUAD), stratifying patients into 12 driver mutation and phenotypic tumor subgroups.ResultsWe revealed several unexpected associations between TIBs behavior and prognosis. Abundance and high proportion of IgG1 isotype, and low proportion of IgA among all intratumorally produced immunoglobulins were specifically associated with improved overall survival for KRASmut but not KRASwt LUAD, revealing the first link between a driver mutation and B-cell response. We found specific IgG1 signature associated with long survival, which suggests that particular specificities of IgG1+ TIBs could be beneficial in KRASmut LUAD. In contrast to our previous observations for melanoma, highly clonal IgG1 production by plasma cells had no meaningful effect on prognosis, suggesting that IgG1+ TIBs may exert a beneficial effect in KRASmut cases in an alternative way, such as efficient presentation of cognate antigens or direct B cell attack on tumor cells. Notably, a high proportion of the IgG1 isotype is positively correlated with the non-silent mutation burden both in the general LUAD cohort and in most patient subgroups, supporting a role for IgG1+ TIBs in antigen presentation. Complementing the recent finding that the presence of stromal IgG4-producing cells is associated with a favorable prognosis for patients with stage I squamous cell carcinoma, we show that the abundance of IgG4-producing TIBs likewise has a strong positive effect on overall survival in STK11mut and proximal proliferative subgroups of LUAD patients. We hypothesize that the positive role of IgG4 antibodies in some of the lung cancer subtypes could be associated with reported inability of IgG4 isotype to form immune complexes, thus preventing immunosuppression via activation of the myeloid-derived suppressor cell (MDSC) phenotype.ConclusionsWe discover prominent and distinct associations between TIBs antibody isotypes and survival in lung adenocarcinoma carrying specific driver mutations. These findings indicate that particular types of tumor-immunity relations could be beneficial in particular driver mutation context, which should be taken into account in developing strategies of cancer immunotherapy and combination therapies. Specificity of protective B cell populations in specific cancer subgroups could become a clue to efficient targeted immunotherapies for appropriate cohorts of patients.

Project description:BackgroundLung adenocarcinoma (LUAD) is the most common histological type of lung cancers, which is the primary cause of cancer-related mortality worldwide. Growing evidence has suggested that tumor microenvironment (TME) plays a pivotal role in tumorigenesis and progression. Hence, we investigate the correlation of TME related genes with LUAD prognosis.MethodThe information of LUAD gene expression data was obtained from The Cancer Genome Atlas (TCGA). According to their immune/stromal scores calculated by the ESTIMATE algorithm, differentially expressed genes (DEGs) were identified. Then, we performed univariate Cox regression analysis on DEGs to obtain genes that are apparently bound up with LUAD survival (SurGenes). Functional annotation and protein-protein interaction (PPI) was also conducted on SurGenes. By validating the SurGenes with data sets of lung cancer from the Gene Expression Omnibus (GEO), 106 TME related SurGenes were generated. Further, intersection analysis was executed between the 106 TME related SurGenes and hub genes from PPI network, PTPRC and CD19 were obtained. Gene Set Enrichment Analysis and CIBERSORT analysis were performed on PTPRC and CD19. Based on the TCGA LUAD dataset, we conducted factor analysis and Step-wise multivariate Cox regression analysis for 106 TME related SurGenes to construct the prognostic model for LUAD survival prediction. The LUAD dataset in GEO (GSE68465) was used as the testing dataset to confirm the prognostic model. Multivariate Cox regression analysis was used between risk score from the prognostic model and clinical parameters.ResultA total of 106 TME related genes were collected in our research totally, which were markedly correlated with the overall survival (OS) of LUAD patient. Bioinformatics analysis suggest them mainly concentrated on immune response, cell adhesion, and extracellular matrix. More importantly, among 106 TME related SurGenes, PTPRC and CD19 were highly interconnected nodes among PPI network and correlated with immune activity, exhibiting significant prognostic potential. The prognostic model was a weighted linear combination of the 106 genes, by which the low-OS LUAD samples could be separated from the high-OS samples with success. This model was also able to rebustly predict the situation of survival (training set: p-value < 0.0001, area under the curve (AUC) = 0.649; testing set: p-value = 0.0009, AUC = 0.617). By combining with clinical parameters, the prognostic model was optimized. The AUC achieved 0.716 for 3 year and 0.699 for 5 year.ConclusionA series of TME-related prognostic genes were acquired in this research, which could reflect immune disorders within TME, and PTPRC and CD19 show the potential to be an indicator for LUAD prognosis and tumor microenvironment modulation. The prognostic model constructed base on those prognostic genes presented a high predictive ability, and may have clinical implications in the overall survival prediction of LUAD.

Dataset Information

EPHA5 mutations predict survival after immunotherapy in lung adenocarcinoma.

Publications

EPHA5 mutations predict survival after immunotherapy in lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets