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Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

ABSTRACT: Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and the Cistrome Cancer database were analyzed to detect differentially expressed genes (DEGs), DEIRGs, and differentially expressed transcription factors (DETFs). Multivariate Cox regression analysis was used to obtain potential DEIRGs as independent prognostic factors. Oncomine, The Human Protein Atlas (HPA), TIMER databases were performed to validate the mRNA and protein expression level of DEIRGs. TIMER database was performed to explore the immunocytes infiltration of DEIRGs. In total, 7448 DEGs, 536 DEIRGs, 87 DETFs were identified from 1,037 NSCLC tissues and 108 normal tissues in TCGA database. Fifteen-DEIRG signatures (THBS1, S100P, S100A16, DLL4, CD70, DKK1, IL33, NRTN, PDGFB, STC2, VGF, GCGR, HTR3A, LGR4, SHC3) could be perceived as independent prognostic factors for predicting the overall survival of patients with NSCLC (P = 4.89e--09). Immune cell correlation analysis showed that neutrophils and b cells were positively and negatively correlated with the riskscore of the prediction model, respectively. Our study identified a Cox prediction model based on DEIRGs to predict the overall survival of patients with NSCLC. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the NSCLC immune microenvironment.

SUBMITTER: Li R

PROVIDER: S-EPMC7540139 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

Li Rui R Liu Xiao X Zhou Xi-Jia XJ Chen Xiao X Li Jian-Ping JP Yin Yun-Hong YH Qu Yi-Qing YQ

American journal of translational research 20200915 9

Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immun ...[more]

PMID: 33042464

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Project description:ImportancePrevious studies have suggested the importance of the baseline derived neutrophil to lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) level as prognostic markers. The lung immune prognostic index (LIPI) was shown to be associated with progression-free survival (PFS) and overall survival (OS) among patients with metastatic non-small cell lung cancer (mNSCLC) treated with immune checkpoint inhibitors (ICIs) but not cytotoxic chemotherapy (CCT).ObjectiveTo determine whether the LIPI is associated with long-term outcomes in pooled analyses of clinical studies of ICI and targeted therapy (TT) for patients with mNSCLC.Design, setting, and participantsAn exploratory pooled analysis was performed of the LIPI on data from 11 randomized clinical multinational trials evaluating ICIs and TT submitted to the US Food and Drug Administration between January 1, 2013, and December 31, 2017, for 4914 patients with mNSCLC. Lung immune prognostic index scores were calculated based on the dNLR and the LDH level per previous publications to generate good, intermediate, and poor composite scores. Multivariable Cox proportional PFS and OS hazard ratios were generated for the dNLR, the LDH level, age, smoking status, histologic characteristics, and Eastern Cooperative Oncology Group performance score.Main outcomes and measuresOverall survival and PFS and their association with good, intermediate, or poor prognostic LIPI scores.ResultsEleven mNSCLC randomized trials were analyzed, including 3987 patients with available data. In 5 ICI trials comprising 2440 patients, 1368 patients received ICIs and 1072 patients received CCT. In 6 TT trials comprising 1547 patients, 1110 patients received TT and 437 patients received CCT. A good LIPI score was associated with better OS among patients receiving ICIs (hazard ratio, 0.34; 95% CI, 0.28-0.42), TT (hazard ratio, 0.28; 95% CI, 0.21-0.37), and CCT (hazard ratio, 0.49; 95% CI, 0.40-0.60 in ICI trials; hazard ratio, 0.41; 95% CI, 0.27-0.61 in TT trials) than those with poor LIPI scores. Similar findings were observed in terms of PFS (ICIs: hazard ratio, 0.59; 95% CI, 0.48-0.72; TT: hazard ratio, 0.46; 95% CI, 0.37-0.57; and CCT: hazard ratio, 0.56; 95% CI, 0.45-0.68 in ICI trials; hazard ratio, 0.51; 95% CI, 0.38-0.69 in TT trials).Conclusions and relevanceThe baseline LDH level and dNLR are important prognostic biomarkers irrespective of treatment modality for patients with mNSCLC. As further prospective clinical trial information is collected, the role of the LIPI score can be better defined.

Project description:IntroductionCancer progression is determined not only by the malignant behavior of tumors but also by the immune microenvironment. The tumor immune microenvironment also plays a pivotal role in determining the clinical response of non-small-cell lung cancer (NSCLC) to immunotherapies. To understand the possible mechanisms and explore new targets in lung cancer immunotherapy, we characterized the immune profiles in NSCLC patients.MethodsSeventy-one NSCLC patients who underwent radical resection were selected. The immune cell composition in paired tumor and adjacent normal lung tissues was tested by flow cytometry. The associations of tumor immune microenvironment characteristics with clinicopathological factors and overall survival were analyzed. Kaplan-Meier curves and Cox proportional hazards models were used to determine differences in survival.ResultsCompared with adjacent normal lung tissues, an increased proportion of CD45+ hematopoietic-derived cells, CD4+ T cell subtypes, Tregs and B cells was observed in tumor samples with a reduced frequency of myeloid cell populations. There was no significant increase in total CD8+ T cells, but both PD1+ and CD38+ CD8+ T cells were significantly enriched in tumor samples and statistically significantly associated with tumor size. In addition, positive CD38 expression was highly correlated with PD1 positivity. A high proportion of CD8+ T cells and a low percentage of PD1+ CD8+ T cells were statistically significantly associated with better survival in stage II and III patients, whereas a low frequency of CD38+ CD8+ T cells was statistically significantly associated with better survival in all patients and identified as an independent prognostic factor (p=0.049).ConclusionWe profiled the immune cells in the tumor tissues of NSCLC patients using flow cytometry. The results revealed significant enrichment of infiltrating immune cells. A strong correlation was identified between CD38 and PD-1 expression on CD8+ T cells in tumors. CD8+ T cells and their subtypes play a critical role in the prediction of prognosis.

Project description:BackgroundWe aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.Materials and methodsPearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.ResultsFive immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.ConclusionAbove all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Project description:BackgroundMitochondrial ribosomal protein L15 (MRPL15), a member of mitochondrial ribosomal proteins whose abnormal expression is related to tumorigenesis. However, the prognostic value and regulatory mechanisms of MRPL15 in non-small-cell lung cancer (NSCLC) remain unclear.MethodsGEPIA, ONCOMINE, Gene Expression Omnibus (GEO), UALCAN, Kaplan-Meier plotter, PrognoScan, LinkedOmics and GeneMANIA database were utilized to explore the expression and prognostic value of MRPL15 in NSCLC. Additionally, immune infiltration patterns were evaluated via ESTIMATE algorithm and TISIDB database. Furthermore, the expression and prognostic value of MRPL15 in lung cancer were validated via immunohistochemistry (IHC) assays.ResultsIn NSCLC, multiple cohorts including GEPIA, ONCOMINE and 8 GEO series (GSE8569, GSE101929, GSE33532, GSE27262, GSE21933, GSE19804, GSE19188, GSE18842) described that MRPL15 was up-regulated. Moreover, MRPL15 was notably linked to gender, clinical stage, lymph node status and the TP53 mutation status. And patients with high MRPL15 expression showed poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS) and relapse-free survival (RFS) in NSCLC. Then, functional network analysis suggested that MRPL15 participated in metabolism-related pathways, DNA replication and cell cycle signaling via pathways involving several kinases, miRNAs and transcription factors. Additionally, it was found that MRPL15 expression was negatively related to immune infiltration, including immune scores, stromal scores and several tumor-infiltrating lymphocytes (TILs). Furthermore, IHC results further confirmed the high MRPL15 expression and its prognostic potential in lung cancer.ConclusionsThese findings demonstrate that high MRPL15 expression indicates poor prognosis in NSCLC and reveal potential regulatory networks as well as the negative relationship with immune infiltration. Thus, MRPL15 may be an attractive predictor and therapeutic strategy for NSCLC.

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Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

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Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer.

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