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Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma.

ABSTRACT: Mounting evidence has found that tumor microenvironment (TME) plays an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of tumor microenvironment-related genes in immunotherapy and clinical outcomes remain unclear. In this study, 6 TME-related genes (PLK1, LDHA, FURIN, FSCN1, RAB27B, and MS4A1) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. In conclusion, the TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in LUAD patients, which provides recommendations for improving patients' response to immunotherapy and promoting personalized tumor immunotherapy in the future.

SUBMITTER: Li C

PROVIDER: S-EPMC10442419 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma.

Li Chunhong C Yuan Yixiao Y Jiang Xiulin X Wang Qiang Q

Scientific reports 20230821 1

Mounting evidence has found that tumor microenvironment (TME) plays an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of tumor microenvironment-related genes in immunotherapy and clinical outcomes remain unclear. In this study, 6 TME-related genes (PLK1, LDHA, FURIN, FSCN1, RAB27B, and MS4A1) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previo ...[more]

PMID: 37604869

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Project description:PurposeLung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients.MethodsThe study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines.ResultsA total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line.ConclusionsThe prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Project description:BackgroundPyroptosis is a newly found form of programmed cell death, accompanied by inflammatory response as well as immune response. Here, the specific function and prognosis predictive of pyroptosis-related genes (PRGs) were systematically explored in lung adenocarcinoma (LUAD).MethodsThe gene expression data and corresponding clinical information of LUAD patients were obtained from The Cancer Genome Atlas (TCGA), and the expression level of PRGs was identified between normal and tumor tissues. Furthermore, univariate Cox proportional hazards regression was conducted to filter the PRGs related to overall survival, and least absolute shrinkage and selection operator (LASSO) regression was subsequent employed to establish the PRGs risk model. Besides, the correlation of risk score with patients' clinical features, tumor mutational burden (TMB) as well as tumor microenvironment (TME) was also investigated.ResultsA total of 5 PRGs (NLRC4, NLRP1, NLRP3, NOD1, PLCG1, and BAK1) was used to establish the risk prognostic model. According the median value of risk score, all the patients were classified into low- and high-risk score group. Kaplan-Meier analysis indicted that the LUAD patients in low-risk group exhibited a better survival outcome compared the patients in high-risk group (P<0.001). After adjusting for age, gender, and clinical stage, the risk score was also considered as and independent risk factor affecting the overall survival of LUAD patients (HR =2.949, 95% CI: 1.762-4.937). Moreover, low-risk score group exhibited a higher Immune score and lower Tumor purity compared with high-risk score group. ssGSEA results proved that the enrichment scores of most immune cells and immune related signal pathway in low-risk score group was significant higher than that in high-risk score group. In addition, the PRGs risk score was also positive correlated with TMB in LUAD tissues.ConclusionsIn this study, a novel prognostic model based on PRGs was constructed and used to predict the survival outcome of LUAD patients. In addition, the PRGs risk signature was also associated with TMB and anti-tumor immune environment. The induction of pyroptosis inside tumors might be considered a potential strategy in cancer treatments.

Project description:As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

Dataset Information

Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma.

Publications

Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma.

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