Metabolic reprogramming-driven homologous recombination and TCA cycle dysregulation contribute to poor prognoses in lung adenocarcinoma.

Increasing evidence has shown that homologous recombination (HR) and metabolic reprogramming are essential for cellular homeostasis. These two processes are independent as well as closely intertwined. Nevertheless, they have rarely been reported in lung adenocarcinoma (LUAD). We analysed the genomic, immune microenvironment and metabolic microenvironment features under different HR activity states. Using cell cycle, EDU and cell invasion assays, we determined the impacts of si-SHFM1 on the LUAD cell cycle, proliferation and invasion. The levels of isocitrate dehydrogenase (IDH) and α-ketoglutarate dehydrogenase (α-KGDH) were determined by ELISA in the NC and si-SHFM1 groups of A549 cells. Finally, cell samples were used to extract metabolites for HPIC-MS/MS to analyse central carbon metabolism. We found that high HR activity was associated with a poor prognosis in LUAD, and HR was an independent prognostic factor for TCGA-LUAD patients. Moreover, LUAD samples with a high HR activity presented low immune infiltration levels, a high degree of genomic instability, a good response status to immune checkpoint blockade therapy and a high degree of drug sensitivity. The si-SHFM1 group presented a significantly higher proportion of cells in the G0/G1 phase, lower levels of DNA replication, and significantly lower levels of cell migration and both TCA enzymes. Our current results indicated that there is a strong correlation between HR and the TCA cycle in LUAD. The TCA cycle can promote SHFM1-mediated HR in LUAD, raising their activities, which can finally result in a poor prognosis and impair immunotherapeutic efficacy.

The multifaceted roles of COL4A4 in lung adenocarcinoma: An integrated bioinformatics and experimental study.

BACKGROUND: Abnormal expression of collagen IV subunits has been reported in cancers, but the significance is not clear. No study has reported the significance of COL4A4 in lung adenocarcinoma (LUAD). METHODS: COL4A4 expression data, single-cell sequencing data and clinical data were downloaded from public databases. A range of bioinformatics and experimental methods were adopted to analyze the association of COL4A4 expression with clinical parameters, tumor microenvironment (TME), drug resistance and immunotherapy response, and to investigate the roles and underlying mechanism of COL4A4 in LUAD. RESULTS: COL4A4 is differentially expressed in most of cancers analyzed, being associated with prognosis, tumor stemness, immune checkpoint gene expression and TME parameters. In LUAD, COL4A4 expression is down-regulated and associated with various TME parameters, response to immunotherapy and drug resistance. LUAD patients with lower COL4A4 have worse prognosis. Knockdown of COL4A4 significantly inhibited the expression of cell-cycle associated genes, and the expression and activation of signaling pathways including JAK/STAT3, p38, and ERK pathways, and induced quiescence in LUAD cells. Besides, it significantly induced the expression of a range of bioactive molecule genes that have been shown to have critical roles in TME remodeling and immune regulation. CONCLUSIONS: COL4A4 is implicated in the pathogenesis of cancers including LUAD. Its function may be multifaceted. It can modulate the activity of LUAD cells, TME remodeling and tumor stemness, thus affecting the pathological process of LUAD. COL4A4 may be a prognostic molecular marker and a potential therapeutic target.

Construction of 11 metabolic-related lncRNAs to predict the prognosis in lung adenocarcinoma.

OBJECTIVE: To explore the metabolism-related lncRNAs in the tumorigenesis of lung adenocarcinoma. METHODS: The transcriptome data and clinical information about lung adenocarcinoma patients were acquired in TCGA (The Cancer Genome Atlas). Metabolism-related genes were from the GSEA (Gene Set Enrichment Analysis) database. Through differential expression analysis and Pearson correlation analysis, lncRNAs about lung adenocarcinoma metabolism were identified. The samples were separated into the training and validation sets in the proportion of 2:1. The prognostic lncRNAs were determined by univariate Cox regression analysis and LASSO (Least absolute shrinkage and selection operator) regression. A risk model was built using Multivariate Cox regression analysis, evaluated by the internal validation data. The model prediction ability was assessed by subgroup analysis. The Nomogram was constructed by combining clinical indicators with independent prognostic significance and risk scores. C-index, calibration curve, DCA (Decision Curve Analysis) clinical decision and ROC (Receiver Operating Characteristic Curve) curves were obtained to assess the prediction ability of the model. Based on the CIBERSORT analysis, the correlation between lncRNAs and tumor infiltrating lymphocytes was obtained. RESULTS: From 497 lung adenocarcinoma and 54 paracancerous samples, 233 metabolic-related and 11 prognostic-related lncRNAs were further screened. According to the findings of the survival study, the low-risk group had a greater OS (Overall survival) than the high-risk group. ROC analysis indicated AUC (Area Under Curve) value was 0.726. Then, a nomogram with T, N stage and risk ratings was developed according to COX regression analysis. The C-index was 0.743, and the AUC values of 3- and 5-year survival were 0.741 and 0.775, respectively. The above results suggested the nomogram had a good prediction ability. The results based on the CIBERSORT algorithm demonstrated the lncRNAs used to construct the model had a strong correlation with the polarization of immune cells. CONCLUSIONS: The study identified 11 metabolic-related lncRNAs for lung adenocarcinoma prognosis, on which basis a prognostic risk scoring model was created. This model may have a good predictive potential for lung adenocarcinoma.

TAGAP expression influences CD4+ T cell differentiation, immune infiltration, and cytotoxicity in LUAD through the STAT pathway: implications for immunotherapy.

Background: T-cell Activation GTPase Activating Protein (TAGAP) plays a role in immune cell regulation. This study aimed to investigate TAGAP's expression and its potential impact on CD4+ T cell function and prognosis in lung adenocarcinoma (LUAD). Methods: We analyzed TAGAP expression and its correlation with immune infiltration and clinical data in LUAD patients using multiple datasets, including The Cancer Genome Atlas (TCGA-LUAD), Gene Expression Omnibus (GEO), and scRNA-seq datasets. In vitro and in vivo experiments were conducted to explore the role of TAGAP in CD4+ T cell function, chemotaxis, and cytotoxicity. Results: TAGAP expression was significantly lower in LUAD tissues compared to normal tissues, and high TAGAP expression correlated with better prognosis in LUAD patients. TAGAP was positively correlated with immune/stromal/ESTIMATE scores and immune cell infiltration in LUAD. Single-cell RNA sequencing revealed that TAGAP was primarily distributed in CD4+/CD8+ T cells. In vitro experiments showed that TAGAP overexpression enhanced CD4+ T cell cytotoxicity, proliferation, and chemotaxis. Gene Set Enrichment Analysis (GSEA) indicated that TAGAP was enriched in the JAK-STAT signaling pathway. In vivo experiments in a xenograft tumor model demonstrated that TAGAP overexpression suppressed tumor growth and promoted CD4+ T cell cytotoxicity. Conclusions: TAGAP influences CD4+ T cell differentiation and function in LUAD through the STAT pathway, promoting immune infiltration and cytotoxicity. This study provides a scientific basis for developing novel LUAD immunotherapy strategies and exploring new therapeutic targets.

The pathological significance and potential mechanism of ARHGEF6 in lung adenocarcinoma.

BACKGROUND: Emerging evidences suggest that ARHGEF6 is involved in cancers but the exact significance and underlying mechanism are unclear. This study aimed to elucidate the pathological significance and potential mechanism of ARHGEF6 in lung adenocarcinoma (LUAD). METHODS: Bioinformatics and experimental methods were used to analyze the expression, the clinical significance, the cellular function and potential mechanisms of ARHGEF6 in LUAD. RESULTS: ARHGEF6 was downregulated in LUAD tumor tissues and correlated negatively with poor prognosis and tumor stemness, positively with the Stromal score, the Immune score and the ESTIMATE score. The expression level of ARHGEF6 was also associated with drug sensitivity, the abundance of immune cells, the expression levels of Immune checkpoint genes and immunotherapy response. Mast cells, T cells and NK cells were the first three cells with the highest expression of ARHGEF6 in LUAD tissues. Overexpression of ARHGEF6 reduced proliferation and migration of LUAD cells and the growth of xenografted tumors, which could be reversed by re-knockdown of ARHGEF6. Results of RNA sequencing revealed that ARHGEF6 overexpression induced significant changes in the expression profile of LUAD cells, and genes encoding uridine 5'-diphosphate-glucuronic acid transferases (UGTs) and extracellular matrix (ECM) components were downregulated. CONCLUSIONS: ARHGEF6 functions as a tumor suppressor in LUAD and may serve as a new prognostic marker and potential therapeutic target. Regulating tumor microenvironment and immunity, inhibiting the expression of UGTs and ECM components in the cancer cells, and decreasing the stemness of the tumors may among the mechanisms underlying the function of ARHGEF6 in LUAD.

A novel gene signature derived from the CXC subfamily of chemokine receptors predicts the prognosis and immune infiltration of patients with lung adenocarcinoma.

The highly malignant nature of lung adenocarcinoma (LUAD) makes its early diagnosis and prognostic assessment particularly important. However, whether the CXC subfamily of chemokine receptors (CXCR) is involved in the development and prognosis of LUAD remains unclear. Here, differentially expressed genes (DEGs) associated with overall survival (OS) were selected from the cancer genome atlas (TCGA) dataset using univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Then, a prognostic gene signature was constructed, which was evaluated using Kaplan-Meier curves, receiver operating characteristics curves, nomogram curves, and an external gene expression omnibus (GEO) dataset. Finally, we verified the functions of the genes comprising the signature using the gene expression profiling interactive analysis (GEPIA) and the immune system interaction database (TISIDB) web portals. We constructed a 7-gene signature (SHC1, PRKCD, VEGFC, RPS6KA1, CAT, CDC25C, and GPI) that stratified patients into high- and low-risk categories. Notably, the risk score of the signature was a separate and effective predictor for OS (P < .001). Patients in the low-risk category had a better prognosis than those in the high-risk category. The receiver operating characteristics and nomogram curves verified the predictive power of the signature. Moreover, in both categories, biological processes and pathways associated with cell migration were enriched. Immune infiltration statuses differed between the 2 risk categories. Critically, the results from the GEPIA and TISIDB web portals indicated that the expression of the 7-gene signature was associated with survival, clinical stage, and immune subtypes of LUAD patients. We identified a CXCR-related gene signature that could assess prognosis and provide a reference for the diagnosis and treatment of LUAD.

Comprehensive analysis of angiogenesis subtype of squamous cell carcinoma.

BACKGROUND: Squamous cell carcinoma (SCC) is a disease with distinct management complexities as it displays a remarkably heterogeneous molecular subtype. However, the landscape of angiogenesis for SCC is not fully investigated. METHOD AND MATERIALS: The angiogenesis-related subtypes of SCC were established by using the ConsensusClusterPlus package based on angiogenesis-related genes and TCGA data. We analyzed the alteration of genes and miRNAs as well as pathways associated with angiogenesis subtypes. Next, the regulation network, the correlation with genomic characteristics, immune microenvironment, and clinical features of the angiogenesis subtypes were further investigated. Finally, the prognostic impact of the angiogenesis-related subtypes for SCC was also analyzed. RESULTS: A total of 1368 SCC samples were included in this study. Two angiogenesis subtypes were then identified based on the one hundred and sixty-three angiogenesis-related genes with subtype1 (angiogenesis subtype) of 951 SCC patients and subtype2 (non-angiogenesis subtype) of 417 SCC. GSEA revealed that angiogenesis and epithelial-mesenchymal transition, inflammatory response, and hypoxia were enriched in the angiogenesis subtype. Eight of the 15 immune checkpoints (ADORA2A, BTLA, CD276, CYBB, HAVCR2, SIGLEC7, SIGLEC9, and VTCN1) were significantly upregulated while C10orf54 were significantly downregulated in the angiogenesis subtype. The survival analysis revealed that the patients in the angiogenesis subtype have poorer survival outcomes than those in the non-angiogenesis subtype (P = 0.017 for disease-free interval and P = 0.00013 for overall survival). CONCLUSION: Our analysis revealed a novel angiogenesis subtype classification in SCC and provides new insights into a hallmark of SCC progression.

EGFR DNA Methylation Correlates With EGFR Expression, Immune Cell Infiltration, and Overall Survival in Lung Adenocarcinoma.

BACKGROUND: The epidermal growth factor receptor (EGFR) is a primary target of molecular targeted therapy for lung adenocarcinoma (LUAD). The mechanisms that lead to epigenetic abnormalities of EGFR in LUAD are still unclear. The purpose of our study was to evaluate the abnormal methylation of EGFR CpG sites as potential biomarkers for LUAD. METHODS: To assess the differentially methylation CpG sites of EGFR in LUAD, we used an integrative study of Illumina HumanMethylation450K and RNA-seq data from The Cancer Genome Atlas (TCGA). We evaluated and compared EGFR multiple-omics data to explore the role of CpG sites located in EGFR promoter regions and gene body regions and the association with transcripts, protein expression levels, mutations, and somatic copy number variation. We calculated the correlation coefficients between CpG sites of EGFR and immune infiltration fraction (by MCPcounter and ESTIMATE) and immune-related pathways in LUAD. Finally, we validated the differential methylation of clinically and prognostically relevant CpG sites using quantitative methylation-specific PCR (qMSP). RESULTS: We found that the methylation level of many EGFR CpGs in the promoter region was negatively correlated with the transcription level, protein expression, and SCNV, while the methylation at the gene body region was positively correlated with these features. The methylation level of EGFR CpGs in the promoter region was positively correlated with the level of immune infiltration and IFN-γ signature, while the opposite was found for methylation of the gene body region. The qMSP results showed that cg02316066 had a high methylation level, while cg02166842 had a low methylation level in LUAD. There was a high degree of co-methylation between cg02316066 and cg03046247. CONCLUSION: Our data indicate that EGFR is an epigenetic regulator in LUAD acting through DNA methylation. Our research provides a theoretical basis for the further detection of EGFR DNA methylation as a predictive biomarker for LUAD survival and immunotherapy.

Development of a gene signature associated with iron metabolism in lung adenocarcinoma.

There are few studies on the role of iron metabolism genes in predicting the prognosis of lung adenocarcinoma (LUAD). Therefore, our research aims to screen key genes and to establish a prognostic signature that can predict the overall survival rate of lung adenocarcinoma patients. RNA-Seq data and corresponding clinical materials of 594 adenocarcinoma patients from The Cancer Genome Atlas(TCGA) were downloaded. GSE42127 of Gene Expression Omnibus (GEO) database was further verified. The multi-gene prognostic signature was constructed by the Cox regression model of the Least Absolute Shrinkage and Selection Operator (LASSO). We constructed a prediction signature with 12 genes (HAVCR1, SPN, GAPDH, ANGPTL4, PRSS3, KRT8, LDHA, HMMR, SLC2A1, CYP24A1, LOXL2, TIMP1), and patients were split into high and low-risk groups. The survival graph results revealed that the survival prognosis between the high and low-risk groups was significantly different (TCGA: P < 0.001, GEO: P = 0.001). Univariate and multivariate Cox regression analysis confirmed that the risk value is a predictor of patient OS (P < 0.001). The area under the time-dependent ROC curve (AUC) indicated that our signature had a relatively high true positive rate when predicting the 1-year, 3-year, and 5-year OS of the TCGA cohort, which was 0.735, 0.711, and 0.601, respectively. In addition, immune-related pathways were highlighted in the functional enrichment analysis. In conclusion, we developed and verified a 12-gene prognostic signature, which may be help predict the prognosis of lung adenocarcinoma and offer a variety of targeted options for the precise treatment of lung cancer.

Comprehensive analysis of DNA damage repair in squamous cell carcinoma subtypes.

AIMS: Defective components resulting from DNA damage and repair mechanisms have been found to be underlying causes that affect the development and progression of different types of cancers, including squamous cell carcinoma (SCC). A more detailed classification of SCC is necessary for better application of DNA damage repair therapies. MATERIALS AND METHODS: We aimed to characterize the molecular profile of SCC by developing a classification system based on DNA damage repair gene expression profiles. An integrative analysis was performed using a metadata set of 1374 SCC human samples from the UCSC Genome Browser. We then analyzed genomic alterations and mutations, and genes-TF-microRNA regulatory relationships and conducted enrichment, survival, and immune infiltration analyses. KEY FINDINGS: This study was conducted on a total of 1374 SCC patients and 402 DNA damage repair genes. Two subtypes were established using consensus clustering, with 1143 patients being of the Non DDR subtype and 231 patients being of the DDR subtype. MATH, mutation burden, and heterogeneity were significantly higher in Non-DDR subtype than in DDR subtype. Next, a total of 1081 differentially expressed genes and 21 microRNAs were identified between the two subtypes and a genes-TF-microRNA regulatory network was constructed. In addition, stromal score, immune score and ESTIMATE score were significantly lower for the Non-DDR subtype, while tumor purity was significantly lower for the DDR subtype. In addition, five pathways associated with DNA damage repair were all enriched in the DDR subtype. SIGNIFICANCE: Our study established two subtypes of SCC based on DNA damage repair, which may help to predict prognosis and determine the most suitable treatment for SCC patients.

Hypoxia-associated alternative splicing signature in lung adenocarcinoma.

Aim: To establish a signature based on hypoxia-related alternative splicing (AS) events for lung adenocarcinoma. Materials & methods: The least absolute shrinkage and selection operator Cox approach was used to construct a prognostic model. A nomogram that integrates the final AS predictor and stage was created. The network of the key AS events and splicing factors was created. Results: We created a prognostic signature of 11 AS events. Moreover, a nomogram that constitutes the pathological stage and risk was exhibited to be greatly effective in estimating the survival likelihood of lung adenocarcinoma patients. Conclusion: Herein we developed the first-ever signature based on hypoxia-related AS events with both prognostic predictive power and diagnostic efficacy.