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Objective: To explore the lactate-related genes (LRGs) in lung adenocarcinoma (LUAD) by various methods, construct a prognostic model, and explore the relationship between lactate subtypes and the immune tumor microenvironment (TME). Methods: 24 LRGs were collected. The mutation landscape and the prognosis value of LRGs were explored by using The Cancer Genome Atlas (TCGA) data. Consensus clustering analysis was used for different lactate subtype identification. Based on the lactate subtypes, we explore the landscape of TME cell infiltration. A risk-score was calculated by using the LASSO-Cox analysis. A quantitative real-time PCR assay was utilized to validate the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients. Results: Comparing the normal samples, 18 LRGs were differentially expressed in tumor samples, which revealed that the differential expression of LRGs may be related to Copy Number Variation (CNV) alterations. The two distinct lactate subtypes were defined. Compared to patients in the LRGcluster A group, LUAD patients in the LRGcluster B group achieved better survival. The prognostic model was constructed based on differentially expressed genes (DEGs) via the LASSO-Cox analysis, which showed the accuracy of predicting the prognosis of LUAD patients using the ROC curve. A high-risk score was related to a high immune score, stromal score, and tumor mutation burden (TMB). Patients had better OS with low risk compared with those with high risk. The sensitivities of different risk groups to chemotherapeutic drugs were explored. Finally, the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients was verified via qRT-PCR. Conclusions: The lactate subtypes were independent prognostic biomarkers in LUAD. Additionally, the difference in the lactate subtypes was an indispensable feature for the individual TME. The comprehensive evaluation of the lactate subtypes in the single tumor would help us to understand the infiltration characteristics of TME and guide immunotherapy strategies. [ABSTRACT FROM AUTHOR]

The existence of tumor heterogeneity and complex carcinogenic mechanisms in lung adenocarcinoma (LUAD) make the most commonly used TNM staging system unable to well-interpret the prognosis of patients. Using transcriptome profiling and clinical data from The Cancer Genome Atlas (TCGA) database, we constructed an immune signature based on a multivariate Cox analysis (stepwise model). We estimated the half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs in patients according to the pRRophetic algorithm. Gene-set variation analysis (GSVA) was used to reveal pathway enrichment between groups. Moreover, immune microenvironment landscape was described by single-sample gene-set enrichment analysis (ssGSEA) and CIBERSORT and systematically correlated with genomic of these patients. A prognostic nomogram combining the immune signature and TNM stage to predict the prognosis was developed by multivariate Cox regression. The novel signature with four immune-related genes (MAL, MS4A1, OAS1, and WFDC2) had good robustness, which can accurately distinguish between high- and low-risk patients. Compared with low-risk patients, high-risk patients with a worse prognosis (5-year OS: 46.5 vs. 59.4%, p = 0.002) could benefit more from immunotherapy and the application of common chemotherapeutic agents such as cisplatin and paclitaxel (Wilcoxon test, all p < 0.05). There were significant differences in tumor immune microenvironment and metabolic pathways between the two groups. Additionally, the constructed nomogram had reliable predictive performance with the C-index of 0.725 (95% CI = 0.668–0.781) in the development set (n = 500), 0.793 (95% CI = 0.728–0.858) in the internal validation set (n = 250) and 0.679 (95% CI = 0.644–0.714) in the external validation set (n = 442). The corresponding calibration curves also showed good consistency. To sum up, we developed an immune-related gene signature and comprehensively evaluated LUAD immune landscape and metabolic pathways. Effective differentiation of high- and low-risk patients and accurate construction of nomogram would be helpful to the development of individualized treatment strategies. [ABSTRACT FROM AUTHOR]

Objective: To explore the expression of secreted phosphoprotein 1 (SPP1) in lung adenocarcinoma (LUAD), and evaluate its relationship with clinicopathological characteristics and prognosis of LUAD, and analyze the advantages of SPP1 as a potential prognostic marker in LUAD. Methods: The expression of SPP1 in normal lung tissue and LUAD was analyzed from the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases. GSE68465 was used to explore the relationship between the SPP1 expression and clinicopathological characteristics and the prognosis of LUAD patients. The relationship between SPP1 and immune infiltration in LUAD was analyzed by the Tumor Immune Estimation Resource (TIMER) database. Gene enrichment analysis was performed in GSEA. The Cancer Genome Atlas (TCGA)-LUAD data was used to verify the results. Results: In the cell line level, non-small cell lung cancer ranked ninth among cancer cell lines based on SPP1 expression. In the messenger RNA (mRNA) and protein levels, SPP1 expression was higher in LUAD tissues than that in normal control. SPP1 expression was related to gender, N stage, histological grade, and progression or relapse. In men, SPP1 expression were higher compared to that in women. The higher the N stage, the higher the SPP1 expression level. As LUAD progresses or relapses, SPP1 expression could increase. In the pathological grade, the SPP1 expression was higher in LUAD samples with moderate differentiation. In addition, the overall 5-year survival rates of the SPP1 high and low expression groups were 50.574 and 59.181% [ P = 0.008; hazard ratio (HR) = 0.7057; 95% CI, 0.5467–0.9109], indicating that SPP1 had an impact on overall survival for LUAD patients. The relationship between SPP1 expression and CD4+ T cell, macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. SPP1 could be considered as an independent prognostic marker in LUAD (P = 0.003; HR = 1.150; 95% CI, 1.048–1.261) by multivariate Cox regression analysis. The results of GSEA indicated that samples with high SPP1 expression were enriched in protein secretion, mTORC1 signaling, angiogenesis, and glycolysis pathway. The analysis results obtained by TCGA-LUAD data were basically consistent with the results obtained by GSE68465. Conclusions: SPP1 can not only affect the occurrence and development of LUAD but also may be an independent prognostic marker of LUAD. SPP1 is expected to be a new target for molecular targeted therapy. [ABSTRACT FROM AUTHOR]