Identification of SHMT2 as a Potential Prognostic Biomarker and Correlating with Immune Infiltrates in Lung Adenocarcinoma.
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ABSTRACT:
SUBMITTER: Luo L
PROVIDER: S-EPMC8049788 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundGlucose-6-phosphate isomerase (GPI) plays an important role in glycolysis and gluconeogenesis. However, the role of GPI in lung adenocarcinoma (LUAD) remains unclear.MethodsAll original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated via R 3.2.2. GPI expression was explored with TCGA, GEO, and Oncomine databases. Immunohistochemistry staining was used to analyze GPI expression in clinical specimens. The correlations between GPI and cancer immune characteristics were analyzed via the TIMER and TISIDB databases. GPI-specific siRNAs were used to verify the role of GPI expression on cell proliferation and cell cycle distribution.ResultsIn general, GPI is predominantly overexpressed and has reference value in the diagnosis and prognostic estimation of LUAD. Upregulated GPI was associated with poorer overall survival, clinical stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we identified a hub gene that included a total of 56 GPI-related genes, which were tightly associated with the cell cycle pathway in LUAD patients. Knockdown of GPI induced cell proliferation inhibition and cell cycle arrest. GPI expression was positively correlated with infiltrating levels of Th2 cells and regulatory T cells (Tregs); in contrast, GPI expression was negatively correlated with infiltrating levels of CD8+ T cells, central memory T cells, dendritic cells, macrophages, mast cells, and eosinophils. GPI was negatively correlated with the expression of immunostimulators, such as CD40L, IL6R, and TMEM173, in LUAD.ConclusionGPI may play an important role in the cell cycle and can be used as a prognostic biomarker for determining the prognosis and immune infiltration in LUAD.
| S-EPMC8666546 | biostudies-literature
Project description:Non-SMC condensin I complex subunit H (NCAPH) plays a regulatory role in various cancers. However, its role in prognosis and immune infiltrates in lung adenocarcinoma (LUAD) remains unclear. This study examined the expression of NCAPH in tumor tissues and its association with immune infiltrates and prognostic roles in LUAD patients. Patients characteristics were obtained from The Cancer Genome Atlas (TCGA). Integrated analysis of TCGA showed that NCAPH was overexpressed across cancers, including LUAD. NCAPH expression was verified by quantitative polymerase chain reaction and western blotting in 20 LUAD matched tissues. High NCAPH expression was significantly related to T, N, M, pathologic stage, primary therapy outcome and smoking status according to the Wilcoxon rank sum test. Cox and Kaplan-Meier analyses showed that the NCAPH-high group was associated with shorter OS. The PFI and DSS in the NCAPH-high group were significantly decreased. Multivariate analysis showed that NCAPH was an independent predictive factor for poor prognosis. Gene set enrichment analysis demonstrated that the G2/M checkpoint, ncRNA metabolic, memory B cells, KRAS, E2F targets and MIER1 process were significantly associated with NCAPH expression. Single-sample Gene Set Enrichment Analysis indicated that NCAPH expression was associated with levels of Th2 and mast cells. The impact of NCAPH on malignant phenotypes was evaluated by MTT, transwell, cell cycle and apoptosis assays in vitro. The malignant phenotype of LUAD cells was inhibited if NCAPH was knocked down. In conclusion, this research indicates that NCAPH could be a potential factor for predicting prognosis and a new biomarker in LUAD.
| S-EPMC9187691 | biostudies-literature
Project description:Background: Lymphoid-restricted membrane protein (LRMP) is an endoplasmic reticulum-associated protein that is expressed in a developmentally regulated manner in both B and T cell lineages. However, the role of LRMP in the growth, prognosis and immune infiltration in lung adenocarcinoma (LUAD) remains unclear. Method: The expression levels of LRMP mRNA in tumor and normal tissues were analyzed using Tumor Immune Estimation Resource 2.0 (TIMER 2.0) and Gene Expression Profiling Interactive Analysis 2 (GEPIA 2). LRMP protein expression was examined using the Human Protein Atlas. In vitro experiments, including qRT-PCR Western blot and immunohistochemistry staining were also performed to investigate LRMP expression. GEPIA2 and Kaplan-Meier plotter databases were used to analyze the clinical prognostic significance of LRMP. To further confirm the underlying function of LRMP, the data were analyzed using gene set enrichment analysis. Moreover, we also constructed plasmids to overexpress LRMP and explored the effect of LRMP in A549 cell line. Additionally, Tumor Immune single-cell Hub was used to investigate the distribution of LRMP in the LUAD immune microenvironment; TIMER and CIBERSORT were used to investigate the relationships among LRMP, LRMP co-expressed genes, and tumor-infiltrating immune cells; Finally, the correlations between LRMP and immune checkpoints were analyzed using TIMER 2.0. Results: The expression of LRMP was significantly lower in LUAD tissues and cell lines. High LRMP expression is associated with a better prognosis in patients with LUAD. In vitro experimental studies demonstrated that overexpression of LRMP could decrease the proliferation, migration and invasion in A549 cells, and downregulated multiple oncogenic signaling pathways, including p-STAT3, p-PI3K-p-AKT, p-MEK and EMT pathways. GSEA results showed that immuno-related and cell adhesion pathways were enriched in samples with high LRMP expression. LRMP and its co-expressed genes were positively correlated with various tumor-infiltrating immune cells and their markers. Additionally, LRMP positively correlated with immune checkpoints. Conclusions: Our data suggest that LRMP may act as a tumor suppressor gene and indicates a better prognosis. Moreover, LRMP is associated with immune infiltrates which may be involved in immunotherapy response in LUAD. Further studies are needed to validate these findings.
| S-EPMC8661541 | biostudies-literature
Project description:Overexpression of DARS2 may enhance the progression of hepatocellular carcinoma (HCC). However, there are few extensive reports on DARS2 function in lung adenocarcinoma (LUAD). The differential expression of DARS2 was detected by genomics and in vitro experiments, and the effect of DARS2 expression on LUAD cell activity was analyzed. Functional enrichment analysis was performed to explore possible signal pathways involved in the biological functions of DARS2 and its co-expressed genes. Utilizing TIMER and GEPIA datasets, the association between DARS2 expression and immunological infiltrating cells was analyzed. At the same time, the association between DARS2 expression pattern and LUAD m6A modification and cuproptosis was examined utilizing TCGA and GEO datasets. The level of DARS2 in LUAD increased, and inhibition of DARS2 expression could significantly inhibit the proliferation of LUAD cells. ROC curves showed that DARS2 overexpression could accurately diagnose LUAD and lead to a significant decline in the survival rates of OS, DSS, and PFI in LUAD. Enrichment analysis showed that DARS2 and its co-expressed genes were closely associated with chromosome segregation and the cell cycle. TIMER and GEPIA database analysis demonstrated that the DARS2 expression pattern was adversely correlated with the infiltration of B cells and Tfh cells. TCGA and GEO dataset examination revealed that DARS2 expression was significantly linked to four m6A-related genes and one cuproptosis-related gene. DARS2 expression is increased in LUAD patients and is closely associated with LUAD immune cell infiltration, modification of m6A, and cuproptosis. DARS2 is a potential reliable prognostic biomarker of LUAD.
| S-EPMC10077054 | biostudies-literature
Project description:Objective: Prolyl 4-hydroxylase, alpha polypeptide I (P4HA1), a key enzyme in collagen synthesis, comprises two identical alpha subunits and two beta subunits. However, the immunomodulatory role of P4HA1 in tumor immune microenvironment (TIME) remains unclear. This study aimed to evaluate the prognostic value of P4HA1 in pan-cancer and explore the relationship between P4HA1 expression and TIME. Methods: P4HA1 expression, clinical features, mutations, DNA methylation, copy number alteration, and prognostic value in pan-cancer were investigated using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data. Pathway enrichment analysis of P4HA1 was performed using R package "clusterProfiler." The correlation between immune cell infiltration level and P4HA1 expression was analyzed using three sources of immune cell infiltration data, including ImmuCellAI database, TIMER2 database, and a published work. Results: P4HA1 was substantially overexpressed in most cancer types. P4HA1 overexpression was associated with poor survival in patients. Additionally, we discovered that P4HA1 expression was positively associated with infiltration levels of immunosuppressive cells, such as tumor-associated macrophages, cancer-associated fibroblasts, nTregs, and iTregs, and negatively correlated with CD8+ T and NK cells in pan-cancer. Conclusions: Our results highlighted that P4HA1 might serve as a potential prognostic biomarker in pan-cancer. P4HA1 overexpression is indicative of an immunosuppressive microenvironment. P4HA1 may be a potential target of immunotherapy.
| S-EPMC8710955 | biostudies-literature
Project description:BackgroundUpregulation of Stathmin 1 (STMN1), a cytoplasmic phosphoprotein that controls the dynamics of cellular microtubules, is linked to malignant behavior and poor prognosis in a range of malignancies. However, little research has been done on STMN1's potential role in HCC as a single factor in DNA methylation, m6A, or immunological modulation.ResultsSTMN1 is overexpressed in hepatocellular carcinoma, where it is related to clinicopathological parameters and affects the prognosis of HCC patients. STMN1 overexpression plays an important role in the diagnosis and prognosis of hepatocellular carcinoma. Meanwhile, methylation of 7 CpG sites of STMN1 in HCC was correlated with prognosis, and STMN1 expression was closely related to m6A modification. In addition, STMN1 expression is associated with immune cell infiltration, immune molecules, and immune checkpoints in HCC.ConclusionSTMN1 has a significant role in hepatocellular carcinoma diagnosis and prediction. STMN1 is implicated not just in the onset and course but also in the immunological modulation of the disease. DNA methylation and m6A are both linked to STMN1. Therefore, STMN1 could be used as a diagnostic and prognostic biomarker for HCC, as well as a target for immunotherapy.
| S-EPMC9487063 | biostudies-literature
Project description:Pancreatic ductal adenocarcinoma (PDAC) is an extremely malignant tumor. The immune profile of PDAC and the immunologic milieu of its tumor microenvironment (TME) are unique; however, the mechanism of how the TME engineers the carcinogenesis of PDAC is not fully understood. This study is aimed at better understanding the relationship between the immune infiltration of the TME and gene expression and identifying potential prognostic and immunotherapeutic biomarkers for PDAC. Analysis of data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases identified differentially expressed genes (DEGs), including 159 upregulated and 53 downregulated genes. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes enrichment were performed and showed that the DEGs were mainly enriched for the PI3K-Akt signaling pathway and extracellular matrix organization. We used the cytoHubba plugin of Cytoscape to screen out the most significant ten hub genes by four different models (Degree, MCC, DMNC, and MNC). The expression and clinical relevance of these ten hub genes were validated using Gene Expression Profiling Interactive Analysis (GEPIA) and the Human Protein Atlas, respectively. High expression of nine of the hub genes was positively correlated with poor prognosis. Finally, the relationship between these hub genes and tumor immunity was analyzed using the Tumor Immune Estimation Resource. We found that the expression of SPARC, COL6A3, and FBN1 correlated positively with infiltration levels of six immune cells in the tumors. In addition, these three genes had a strong coexpression relationship with the immune checkpoints. In conclusion, our results suggest that nine upregulated biomarkers are related to poor prognosis in PDAC and may serve as potential prognostic biomarkers for PDAC therapy. Furthermore, SPARC, COL6A3, and FBN1 play an important role in tumor-related immune infiltration and may be ideal targets for immune therapy against PDAC.
| S-EPMC7479484 | biostudies-literature
Project description:BackgroundLung adenocarcinoma (LUAD) with Pulmonary arterial hypertension (PAH) shows a poor prognosis. Detecting related genes is imperative for prognosis prediction.MethodsThe gene expression profiles of LUAD and PAH were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, respectively. The co-expression modules associated with LUAD and PAH were evaluated using the Weighted Gene Co-Expression Network Analysis (WGCNA). The relationship between key gene expression with immune-cell infiltration and the tumor immune microenvironment (TIME) was evaluated. We confirmed the mRNA and protein levels in vivo and vitro. G6PD knockdown was used to conduct the colony formation assay, transwell invasion assay, and scratch wound assay of A549 cells. EDU staining and CCK8 assay were performed on G6PD knockdown HPASMCs. We identified therapeutic drug molecules and performed molecular docking between the key gene and small drug molecules.ResultsThree major modules and 52 overlapped genes were recognized in LUAD and PAH. We identified the key gene G6PD, which was significantly upregulated in LUAD and PAH. In addition, we discovered a significant difference in infiltration for most immune cells between high- and low-G6PD expression groups. The mRNA and protein expressions of G6PD were significantly upregulated in LUAD and PAH. G6PD knockdown decreased proliferation, cloning, and migration of A549 cells and cell proliferation in HPASMCs. We screened five potential drug molecules against G6PD and targeted glutaraldehyde by molecular docking.ConclusionsThis study reveals that G6PD is an immune-related biomarker and a possible therapeutic target for LUAD and PAH patients.
| S-EPMC10817399 | biostudies-literature
Project description:BackgroundGlioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery.MethodsThe CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities.ResultsWe identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers.ConclusionIn light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study.
| S-EPMC10878878 | biostudies-literature
Project description: Not available
| S-EPMC11231847 | biostudies-literature