Tumor Immune Estimation Resource Database Research Articles

Diagnostic Value of GDF10 for the Tumorigenesis and Immune Infiltration in Lung Squamous Cell Carcinoma.

Lung squamous cell carcinoma (LUSC) is associated with a low survival rate. Evidence suggests that bone morphogenetic proteins (BMPs) and their receptors (BMPRs) play crucial roles in tumorigenesis and progression. However, a comprehensive analysis of their role in LUSC is lacking. Our study aimed to explore the relationship between BMPs/BMPRs expression levels and the tumorigenesis and prognosis of LUSC. The "R/Limma" package was utilized to analyze the differential expression characteristics of BMPs/BMPRs in LUSC, using data from TCGA, GTEx, and GEO databases. Concurrently, the "survminer" packages were employed to investigate their prognostic value and correlation with clinical features in LUSC. The core gene associated with LUSC progression was further explored through weighted gene correlation network analysis (WGCNA). LASSO analysis was conducted to construct a prognostic risk model for LUSC. Clinical specimens were examined by immunohistochemical analysis to confirm the diagnostic value in LUSC. Furthermore, based on the tumor immune estimation resource database and tumor-immune system interaction database, the role of the core gene in the tumor microenvironment of LUSC was explored. GDF10 had a significant correlation only with the pathological T stage of LUSC, and the protein expression level of GDF10 decreased with the tumorigenesis of LUSC. A prognostic risk model was constructed with GDF10 as the core gene and 5 hub genes (HRASLS, HIST1H2BH, FLRT3, CHEK2, and ALPL) for LUSC. GDF10 showed a significant positive correlation with immune cell infiltration and immune checkpoint expression. GDF10 might serve as a diagnostic biomarker reflecting the tumorigenesis of LUSC and regulating the tumor immune microenvironment to guide more effective treatment for LUSC.

Exploring the molecular mechanisms network of breast cancer by multi-omics analysis.

Breast cancer (BC), the most prevalent malignancy in women globally, still lacks comprehensive research on its molecular targets and necessitates further investigation into the underlying molecular mechanisms driving its initiation and progression. The GSE20685 Series Matrix File downloaded from the Gene Expression Omnibus database was divided into a high-risk group (n=49) and a low-risk group (n=278) to construct the co-expression network. Four hub genes were identified based on the Weighted Gene Co-expression Network Analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses were performed. Hub gene immune infiltration was investigated using the Tumor Immune Estimation Resource database, and CD4+ T cell expression levels were substantially correlated with hub gene expression. Based on the CancerRxGene database (Genomics of Drug Sensitivity in Cancer database), it was found that the hub genes were highly sensitive to common chemotherapy drugs such as AKT inhibitor VIII and Erlotinib. The expression of Secreted Frizzled-Related Protein 1, melanoma-inhibiting activity (MIA), and Keratin 14 was related to tumor mutation burden, and the expression of MIA also affected the microsatellite instability of the tumor. This study employs multi-omics analysis to investigate the molecular network associated with the prognosis of BC, highlighting its intricate connection with the immune microenvironment. These findings pinpoint four crucial genes in BC progression, offering targets for further research and therapy. Their connections to immune infiltration and chemotherapy sensitivity underscore complex interactions in the tumor microenvironment.

WSCD2 Expression: Its Relevance to Tumor-Infiltrating Immune Cells and Glioma Prognosis.

Patients with glioma have limited treatment options and experience poor prognoses. Therefore, it is urgently needed to explore new diagnostic and therapeutic targets. This study aimed to investigate the relevance of WSC domain-containing 2 (WSCD2) expression to glioma, clinicopathological characteristics, tumor-infiltrating immune cells (TILs), and patient prognosis. We analyzed WSCD2 mRNA expression in glioma tissues and patient survival using the Gene Expression Profiling Interactive Analysis database. Furthermore, the relationship between the expressions of WSCD2 mRNA and TILs in gliomas was evaluated utilizing the Tumor Immune Estimation Resource database. Lastly, we employed multiplex immunohistochemistry to detect the protein expressions of WSCD2 and TILs in glioma tissues. WSCD2 mRNA expression in glioma tissues was lower than that in tissues of benign brain disease. High WSCD2 mRNA expression was also significantly associated with a favorable outcome. Additionally, WSCD2 mRNA expression was correlated with TIL expression in glioma; however, no such relationship was detected between the protein expressions of WSCD2 and TILs in glioma tissues. Cox regression multivariate analysis and Kaplan-Meier survival analysis showed that WSCD2 expression in glioma tissues could be an independent prognostic factor. This study highlights the correlation between WSCD2 expression and TILs and demonstrates the prognostic significance of WSCD2 in glioma. Furthermore, our results suggest that WSCD2 may be a potential immunotherapy target in glioma.

Comprehensive analysis of the protein phosphatase 2A regulatory subunit B56ε in pan-cancer and its role and mechanism in hepatocellular carcinoma.

B56ε is a regulatory subunit of the serine/threonine protein phosphatase 2A, which is abnormally expressed in tumors and regulates various tumor cell functions. At present, the application of B56ε in pan-cancer lacks a comprehensive analysis, and its role and mechanism in hepatocellular carcinoma (HCC) are still unclear. To analyze B56ε in pan-cancer, and explore its role and mechanism in HCC. The Cancer Genome Atlas, Genotype-Tissue Expression, Gene Expression Profiling Interactive Analysis, and Tumor Immune Estimation Resource databases were used to analyze B56ε expression, prognostic mutations, somatic copy number alterations, and tumor immune characteristics in 33 tumors. The relationships between B56ε expression levels and drug sensitivity, immunotherapy, immune checkpoints, and human leukocyte antigen (HLA)-related genes were further analyzed. Gene Set Enrichment Analysis (GSEA) was performed to reveal the role of B56ε in HCC. The Cell Counting Kit-8, plate cloning, wound healing, and transwell assays were conducted to assess the effects of B56ε interference on the malignant behavior of HCC cells. In most tumors, B56ε expression was upregulated, and high B56ε expression was a risk factor for adrenocortical cancer, HCC, pancreatic adenocarcinoma, and pheochromocytoma and paraganglioma (all P < 0.05). B56ε expression levels were correlated with a variety of immune cells, such as T helper 17 cells, B cells, and macrophages. There was a positive correlation between B56ε expression levels with immune checkpoint genes and HLA-related genes (all P < 0.05). The expression of B56ε was negatively correlated with the sensitivity of most chemotherapy drugs, but a small number showed a positive correlation (all P < 0.05). GSEA analysis showed that B56ε expression was related to the cancer pathway, p53 downstream pathway, and interleukin-mediated signaling in HCC. Knockdown of B56ε expression in HCC cells inhibited the proliferation, migration, and invasion capacity of tumor cells. B56ε is associated with the microenvironment, immune evasion, and immune cell infiltration of multiple tumors. B56ε plays an important role in HCC progression, supporting it as a prognostic marker and potential therapeutic target for HCC.

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma.

Tumor mutational burden (TMB) is a valuable prognostic biomarker. This study explored the predictive value of TMB and the potential association between TMB and immune infiltration in diffuse large B-cell lymphoma (DLBCL). We downloaded the gene expression profile, somatic mutation, and clinical data of DLBCL patients from The Cancer Genome Atlas (TCGA) database. We classified the samples into high-and low-TMB groups to identify differentially expressed genes (DEGs). Functional enrichment analyses were performed to determine the biological functions of the DEGs. We utilized the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to estimate the abundance of 22 immune cells, and the significant difference was determined by the Wilcoxon rank-sum test between the high- and low-TMB group. Hub gene had been screened as the prognostic TMB-related immune biomarker by the combination of the Immunology Database and Analysis Portal (ImmPort) database and the univariate Cox analysis from the Gene Expression Omnibus (GEO) database including six DLBCL datasets. Various database applications such as Tumor Immune Estimation Resource (TIMER), CellMiner, konckTF, and Genotype-Tissue Expression (GTEx) verified the functions of the target gene. Wet assay confirmed the target gene expression at RNA and protein levels in DLBCL tissue and cell samples. Single nucleotide polymorphism (SNP) occurred more frequently than insertion and deletion, and C > T was the most common single nucleotide variant (SNV) in DLBCL. Survival analysis showed that the high-TMB group conferred poor survival outcomes. A total of 62 DEGs were obtained, and 13 TMB-related immune genes were identified. Univariate Cox analysis results illustrated that CD1c mutation was associated with lower TMB and manifested a satisfactory clinical prognosis by analysis of large samples from the GEO database. In addition, infiltration levels of immune cells in the high-TMB group were lower. Using the TIMER database, we systematically analyzed that the expression of CD1c was positively correlated with B cells, neutrophils, and dendritic cells and negatively correlated with CD8+ T cells, CD4+ T cells, and macrophages. Drug sensitivity showed a significant positive correlation between CD1c expression level and clinical drug sensitivity from the CellMiner database. CREB1, AHR, and TOX were used to comprehensively explore the regulation of CD1c-related transcription factors and signaling pathways by the KnockTF database. We searched the GETx database to compare the mRNA expression levels of CD1c between DLBCL and normal tissues, and the results suggested a significant difference between them. Moreover, wet experiments were conducted to verify the high expression of CD1c in DLBCL at the RNA and protein levels. Higher TMB correlated with poor survival outcomes and inhibited the immune infiltrates in DLBCL. Our results suggest that CD1c is a TMB-related prognostic biomarker.

Circulating small extracellular vesicle-derived splicing factor 3b subunit 4 as a non-invasive diagnostic biomarker of early hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) accounts for a majority of primary liver cancer cases and related deaths. The purpose of this study was to assess the diagnostic value of splicing factor 3b subunit 4 (SF3B4) as a novel non-invasive biomarker for HCC and determine the association between SF3B4 expression and immune cell infiltration.MethodsAn enzyme-linked immunosorbent assay (ELISA) was used to detect SF3B4 levels in plasma samples obtained from healthy controls (HCs) and patients with chronic hepatitis, liver cirrhosis, and HCC. The expression levels of autoantibodies that detect SF3B4 in the plasma samples of each group of patients were measured. Small extracellular vesicles (EVs) were isolated from patient sera, and the expression levels of EV-SF3B4 were measured using quantitative reverse transcription PCR.ResultsELISA results confirmed that the expression levels of SF3B4 proteins and autoantibodies in the plasma of patients with HCC were higher than those in HCs. However, their diagnostic performance was not better than that of alpha-fetoprotein (AFP). The mRNA expression of SF3B4 in serum EV increased but not in the buffy coat or serum of patients with HCC. Serum EV-SF3B4 displayed better diagnostic power than AFP for all stages of HCC (AUC = 0.968 vs. 0.816), including early-stage HCC (AUC = 0.960 vs. 0.842), and this was consistent in the external cohort. Single-cell RNA sequencing indicated that SF3B4 expression was correlated with myeloid-derived suppressor cells. The Tumor Immune Estimation Resource database reconfirmed the correlation between SF3B4 expression and immune cell infiltration in HCC.ConclusionsSF3B4 may be associated with tumor immune infiltration in HCC, and EV-SF3B4 shows potential as a novel non-invasive diagnostic biomarker of HCC.

Comprehensive analysis of the expression, prognosis and biological significance of FSCN family in clear cell renal cell carcinoma.

Fascin (FSCN) is an actin-binding protein that serves a critical role in cell migration and invasion, contributing to tumor metastasis. However, there is little known about the function of FSCN family in kidney renal clear cell carcinoma (KIRC). The present study used the UALCAN, gene expression profiling interactive analysis, The Cancer Genome Atlas, cBioPortal, STRING and The Tumor Immune Estimation Resource databases to investigate the transcription level, genetic alteration and biological function of FSCNs in KIRC and their association with the prognosis value and immune cell infiltration in patients with KIRC. Results showed that the expression of FSCN1 and FSCN3 was markedly upregulated in patients with KIRC, while the expression of FSCN2 showed an opposite trend, which was the same as the experiments. Furthermore, the expression levels of FSCNs were associated with pathological stage, molecular subtypes and tumor grade. The expression levels of FSCNs were statistically correlated with the immune cell infiltration in KIRC. Higher expression levels of FSCN1 and FSCN3 were associated with worse overall survival (OS) and progression-free interval of patients bearing KIRC. Univariate and multivariate analysis demonstrated that FSCN2 was an independent risk factor for OS time in KIRC. Furthermore, mutations in FSCNs were significantly associated with poor OS and progression-free survival in patients with KIRC. The FSCNs were involved in pathways including focal adhesion, endocytosis, hypertrophic cardiomyopathy, regulation of actin cytoskeleton. The results indicated that FSCN2 might serve as an independent prognostic factor for OS of KIRC and that FSCN1 and FSCN3 can be used as favorable biomarkers for predicting clinical outcomes in KIRC.

High SNRPA1 expression leads to poor prognosis in patients with lung adenocarcinoma.

SNRPA1, a subunit of spliceosome complex, has been implicated in diverse cancers, while its biological effect in LUAD remains elusive. Therefore, we sought to decipher the relationship between SNRPA1 expression and the prognosis of patients with LUAD and reveal the underlying molecular mechanism. Based on the clinical data from TCGA databases, the multivariate Cox model was constructed to screen the prognostic value of SNRPA1. qRT-PCR and immunohistochemical staining were used to examine SNRPA1 mRNA and protein expression in LUAD. The effect of SNRPA1 on LUAD cell proliferation, migration, and epithelial mesenchymal transformation were examined using colony formation assays, wound healing, and western blot assays, respectively. Finally, the influence of SNRPA1 on LUAD immune microenvironment were validated from the Tumor Immune Estimation Resource database. SNRPA1 was significantly upregulated in both LUAD tissues and cell lines, and highly expressed SNRPA1 contributed to poor prognosis of LUAD patients. In vitro, SNRPA1 knockdown inhibited the proliferation and migration, as well as delayed the EMT differentiation of LUAD cells. Lastly, SNRPA1 was found to be positively associated with immune infiltration and some immune-check-point markers. Our findings indicate that SNRPA1 may be a new biomarker for prognostic prediction and a potential therapeutic target in the treatment of LUAD.

Effect of urokinase-type plasminogen activator combined with clinical stage and Barcelona Clinic Liver Cancer stage on the prognosis of patients with hepatocellular carcinoma.

The aim of this investigation is to evaluate the association and potential mechanism between plasminogen activator urokinase (PLAU) and the prognosis of patients with liver hepatocellular carcinoma (LIHC). We verified PLAU expression and its correlation with LIHC patients' prognosis in The Cancer Genome Atlas (TCGA) database. The interaction network for protein-gene was established in the GeneMania database and the STRING database, and the association between PLAU and immune cells was assessed in Tumor Immune Estimation Resource (TIMER) and TCGA databases. The potential physiological mechanism was elucidated by the Gene Set Enrichment Analysis (GSEA) enrichment assessment. Finally, the individual clinical data of 100 LIHC patients were retrospectively evaluated to further analyze the clinical value of PLAU. The PLAU expression in LIHC tissues was greater than in paracancerous tissues, and LIHC patients with low PLAU expression had better disease-specific survival (DSS), overall survival (OS), and progression free interval (PFI) than those with high PLAU expression. In the TIMER database, the PLAU expression was positively associated with six kinds of infiltrating immune cells: CD4+ T, neutrophils, CD8+ T, macrophages, B, and dendritic cells, while GSEA enrichment analysis indicated PLAU may impact the biological activities of LIHC by taking part in MAPK and JAK_STAT signaling pathways, angiogenesis, and P53. There were statistically significant differences in T-stage and Edmondson grading between the two groups of patients with high and low expression of PLAU (P<0.05). The tumor progression rates were 88% (44/50) and 92% (46/50) respectively in the low and high PLAU groups, with early recurrence rates of 60% (30/50) and 72% (36/50), and median PFS of 29.5 and 23 months, respectively. The COX regression analysis showed PLAU expression and CS and Barcelona Clinic Liver Cancer (BCLC) stages were independent prognostic factors affecting tumor progression in LIHC patients. The decreased expression of PLAU can prolong the DSS, OS, and PFI in LIHC patients, and can be utilized as a novel predictive index. PLAU combined with CS staging and BCLC staging has good clinical value in the early screening and prognosis of LIHC. These results reveal an efficient approach for developing anticancer strategies against LIHC.

Fibroblast Growth Factor 11 Enables Tumor Cell Immune Escape by Promoting T Cell Exhaustion and Predicts Poor Prognosis in Patients with Lung Adenocarcinoma.

Fibroblast growth factor 11 (FGF11) accelerates tumor proliferation in a variety of cancer types. This study aimed to examine the link between FGF11 and the prognosis of lung adenocarcinoma. FGF11 was searched in the Tumor Cancer Genome Atlas (TCGA) and ImmProt databases. The link between FGF11 and lung cancer clinical data was investigated using TCGA and Kaplan-Meier (KM)-plotter databases, and we developed a prediction model. Putative mechanisms of action were investigated using Gene Ontology (GO) and KEGG enrichment analyses. The GeneMANIA and STRING databases were used to search for genes that interact with FGF11, and the Tumor Immune Estimation Resource (TIMER) database was used to discover connections between FGF11 and immune cells, as well as any correlations with immune-related genes. We found that FGF11 expression was higher in the lung adenocarcinoma tissue than in the paracancerous tissue, and patients with high FGF11 expression had a lower overall survival, progression-free survival, and disease specific survival rate than those with low FGF11 expression. The expression of FGF11 was inversely linked to six types of infiltrating immune cells in the TIMER database and was associated with EGFR, VEGFA, BRAF, and MET expressions. The FGF11 gene is negatively correlated with the expression of most immune cells, mainly with various functional T cells including Th1, Th1-like, Treg, and Resting Treg characterization genes. These results indicate that FGF11 has the potential to be a new lung adenocarcinoma biomarker. It increases tumor cell immune escape by boosting T cell exhaustion in the tumor microenvironment, contributing to the poor prognosis of the patients with lung adenocarcinoma. These results provide incentive to further research FGF11 as a possible biomarker and drug target for patients with lung adenocarcinoma.

RGN as a prognostic biomarker with immune infiltration and ceRNA in lung squamous cell carcinoma

Regucalcin (RGN) is a potent inhibitory protein of calcium signaling and expresses in various tissues. However, the role of RGN in the tumor immunological microenvironment in lung squamous cell carcinoma (LUSC) remains unclear. This study identified the expression of RGN from public databases and immunohistochemistry with clinical specimen. The association between RGN and the tumor immune microenvironment (TIME) was investigated in LUSC by ESTIMATE and CIBERSORT algorithms. Similarly, the Tumor IMmune Estimation Resource (TIMER) database was used to identify the correlation between RGN and immune cells. The ceRNA network was established based on the data obtained from public databases. Finally, prediction of drug response to chemotherapy and immunotherapy was performed to evaluate clinical significance. This study found that RGN expression was significantly downregulated in tumor tissues and closely related to clinical factors and prognosis of LUSC patients. Differentially expressed genes (DEGs) grouped by the expression of RGN were mostly involved in immunobiological processes such as humoral immune response and leukocyte mediated immunity. RGN and its related miRNA (has-miR-203a-3p) and lncRNAs (ZNF876P and PSMG3-AS1) constructed the novel prognosis-related ceRNA network. Plasma cells, T cells CD4 memory resting, Macrophages M0, Macrophages M1, Mast cells resting, Mast cells activated and Neutrophils showed significantly different levels of infiltration between high and low RGN expression groups. The TIMER database showed that RGN expression was positively correlated with certain immune infiltrating cells. High RGN expression group showed a higher TIDE score, a higher dysfunction score and a lower MSI score, presenting a possible lower efficacy after accepting the immunotherapy than low RGN expression group. RGN expression was closely associated with prognosis of LUSC patients and played an important role in tumor microenvironment. This suggests that RGN could be a promising biomarker for assessing immunotherapy efficacy and prognosis.

Pan-Cancer Analysis Reveals PPRC1 as a Novel Prognostic Biomarker in Ovarian Cancer and Hepatocellular Carcinoma.

Background and Objectives: As is well understood, peroxisome proliferator-activated receptor gamma cofactor-related 1 (PPRC1) plays a central role in the transcriptional control of the mitochondrial biogenesis and oxidative phosphorylation (OXPHOS) process, yet its critical role in pan-cancer remains unclear. Materials and Methods: In this paper, the expression levels of PPRC1 in different tumor tissues and corresponding adjacent normal tissues were analyzed based on four databases: The Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), and Tumor Immune Estimation Resource (TIMER). Meanwhile, the prognostic value of PPRC1 was inferred using Kaplan-Meier plotter and forest-plot studies. In addition, the correlation between PPRC1 expression and tumor immune cell infiltration, immune checkpoints, and the tumor-stemness index was analyzed using TCGA and TIMER databases. Results: According to our findings, the expression level of PPRC1 was found to be different in different cancer types and there was a positive correlation between PPRC1 expression and prognosis in several tumor types. In addition, PPRC1 expression was found to be significantly correlated with immune cell infiltration, immune checkpoints, and the tumor-stemness index in both ovarian and hepatocellular carcinoma. Conclusions: PPRC1 demonstrated promising potential as a novel biomarker in pan-cancer due to its potential association with immune cell infiltration, expression of immune checkpoints, and the tumor-stemness index.

Aquaporin-4 as a New Potential Molecular Biomarker for Prognosis of Low-Grade Glioma: Comprehensive Analysis Based on Online Platforms

Aquaporin-4 (AQP4) is a significant factor in transcellular and transepithelial water movement, and abnormal expression of AQP4 has been detected in many types of tumors. The purpose of this study was to explore its role in low-grade gliomas (LGG) using freely available online bioinformatics tools. OncoLnc database was used to analyze Cox coefficients and compare AQP4 expression between various types of tumors; Tumor Immune Estimation Resource database and Gene Expression Profiling Interactive Analysis were used to compare gene expression between LGG and normal tissues; University of California Santa Cruz Xena browser generated Kaplan-Meier survival curves in the LGG cohort in The Cancer Genome Atlas and subgroups; LinkedOmics database screened the most relevant genes based on Pearson correlation coefficient; Gene Ontology Biological Process and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed through gene set enrichment analysis to explore possible molecular mechanisms. LGG had higher AQP4 expression compared with normal tissues and ranked first among 21 different types of cancer (P < 0.05). The oligodendroglioma group had the lowest AQP4 expression and the longest overall survival (OS) (P < 0.05). LGG with astrocytoma, isocitrate dehydrogenase mutation, or 1p/19q codeletion had lower AQP4 expression and longer OS (P < 0.001). LGG with lower AQP4 expression, without 1p/19q codeletion, without chemotherapy, and with or without radiation therapy had longer OS (P < 0.05). AQP4 and coexpressed genes were involved in complex biological processes in LGG, including regulation of neurotransmitter level, peroxisome proliferator-activated receptor signaling pathway, cell adhesion molecules, and others. AQP4 is a prognostic marker in LGG and its subgroups. Patients with lower AQP4 expression may have longer OS.

Systematic Analysis of the Prognostic Significance and Roles of the Integrin Alpha Family in Non-Small Cell Lung Cancers.

Lung cancer is one of the most common cancer malignancies and the principal cause of cancer-associated deaths worldwide. Non-small cell lung cancers (NSCLCs) account for more than 80% of all lung cancer cases. Recent studies showed that the genes of the integrin alpha (α) (ITGA) subfamily play a fundamental role in various cancers. However, little is known about the expression and roles of distinct ITGA proteins in NSCLCs. Gene Expression Profiling Interactive Analysis and UALCAN (University of ALabama at Birmingham CANcer) web resources and The Cancer Genome Atlas (TCGA), ONCOMINE, cBioPortal, GeneMANIA, and Tumor Immune Estimation Resource databases were used to evaluate differential expression, correlations between the expression levels of individual genes, the prognostic value of overall survival (OS) and stage, genetic alterations, protein-protein interactions, and the immune cell infiltration of ITGAs in NSCLCs. We used R (v.4.0.3) software to conduct gene correlation, gene enrichment, and clinical correlation of RNA sequencing data of 1016 NSCLCs from TCGA. To evaluate the expression of ITGA5/8/9/L at the expression and protein levels, qRT-PCR, immunohistochemistry (IHC), and hematoxylin and eosin (H&E) were performed, respectively. Upregulated levels of ITGA11 messenger RNA and downregulated levels of ITGA1/3/5/7/8/9/L/M/X were observed in the NSCLC tissues. Lower expression of ITGA5/6/8/9/10/D/L was discovered to be expressively associated with advanced tumor stage or poor patient prognosis in patients with NSCLC. A high mutation rate (44%) of the ITGA family was observed in the NSCLCs. Gene Ontology functional enrichment analyses results revealed that the differentially expressed ITGAs could be involved in roles related to extracellular matrix (ECM) organization, collagen-containing ECM cellular components, and ECM structural constituent molecular functions. The results of the Kyoto Encyclopedia of Genes and Genomes analysis revealed that ITGAs may be involved in focal adhesion, ECM-receptor interaction, and amoebiasis; the expression of ITGAs was significantly correlated with the infiltration of diverse immune cells in NSCLCs. ITGA5/8/9/L was also highly correlated with PD-L1 expression. The validation results for marker gene expression in NSCLC tissues by qRT-PCR, IHC, and H&E staining indicated that the expression of ITGA5/8/9/L decreased compared with that in normal tissues. As potential prognostic biomarkers in NSCLCs, ITGA5/8/9/L may fulfill important roles in regulating tumor progression and immune cell infiltration.

High expression of PCOLCE gene indicate poor prognosis in patients and are associated with immune infiltration in glioma

The procollagen C-protease enhancer (PCOLCE) has been identified to influence tumor growth and metastasis in multiple cancers. However, the relationship between PCOLCE activity and the progression of gliomas remains largely unknown. Glioma RNA-seq data were derived from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas databases for analysis. Kaplan–Meier survival curve, clinical characterization correlation, univariate and multivariate Cox, and receiver operating characteristic curve analyses were performed to assess the prognostic role of PCOLCE. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to determine the functions or pathways associated with PCOLCE. The ESTIMATE and CIBERSORT algorithms, Spearman’s rank correlation analysis, and Tumor Immune Estimation Resource (TIMER) databases were used to explore the relationship between PCOLCE and immune infiltration. Correlation analysis between PCOLCE, related genes, and immune cell markers was conducted using the TIMER database. Immunophenoscore assays were performed to determine differential PCOLCE expression levels in glioma. The sensitivity of multi-drugs were determined to explore potential chemotherapeutic agents in between PCOLCE. Compared to normal brain tissue, PCOLCE expression was increased in glioma and correlated with shorter overall survival (OS). Furthermore, significant differences were observed in the immune scores and immune cell infiltration levels. PCOLCE is positively associated with immune checkpoints and many immune markers. Additionally, PCOLCE expression was higher in gliomas with higher IPS Z-scores in CGGA. High expression of PCOLCE increased sensitivity to multiple chemotherapy agents in CGGA (P < 0.001), and TCGA. These results suggest that PCOLCE significantly influences the prognosis of patients with glioma, can serve as an independent prognostic factor, and is related to tumor immunity. PCOLCE may be a novel immune-related target for treating gliomas. Additionally, analysis of chemosensitivity in gliomas with high PCOLCE expression may provide a promising direction for drug development.

CTHRC1 is associated with immune cell infiltration and functions as an adverse marker for prognosis in head and neck squamous cell carcinoma.

Collagen triple helix repeat containing 1 (CTHRC1) is a secreted glycoprotein that decreases the deposition of collagen matrix and accelerates tumor metastasis. However, the relationship between CTHRC1 and the outcomes of head and neck squamous cell carcinoma (HNSCC) and tumor-infiltrating lymphocytes remains unclear. In the present study, the transcriptional level of CTHRC1 and its association with overall survival (OS) and relapse-free survival (RFS) time in diverse cancer types were evaluated using The Cancer Genome Atlas, Tumor Immune Estimation Resource (TIMER), ONCOMINE and Kaplan-Meier plotter databases. The association of CTHRC1 expression level with the clinicopathological parameters of patients with HNSCC from The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) database were also evaluated. Enrichment analysis of CTHRC1 was carried out using gene set enrichment analysis software. CIBERSORT and TIMER databases were used to evaluate the relationship between the expression level of CTHRC1 and the proportion of tumor-infiltrating immune cells (TICs) in multiple cancer types. Moreover, immunohistochemistry was used to verify the expression of CTHRC1 in clinical samples of HNSCC. CTHRC1 was upregulated in HNSCC and high expression of CTHRC1 was associated with worsening clinicopathologic parameters and shorter OS and RFS times. There were eight HALLMARK gene sets, 1,231 immune signature gene sets and 14 KEGG gene sets significantly enriched in the high CTHRC1 expression group, while no gene set was enriched in the low CTHRC1 expression group. The expression of CTHRC1 was closely correlated with the proportion of TICs, where the expression of CTHRC1 was significantly positively correlated with the amount of infiltrated M0 and M2 macrophages, and significantly negatively associated with the levels of M1 macrophages. These findings suggest that CTHRC1 is an adverse prognostic marker and is associated with immune cell infiltration in HNSCC.

A New Signature of Sarcoma Based on the Tumor Microenvironment Benefits Prognostic Prediction.

Sarcomas are a group of malignant tumors derived from mesenchymal tissues that display complex and variable pathological types. The impact of the immune properties of the tumor microenvironment (TME) on the prognosis, treatment, and management of sarcomas has attracted attention, requiring the exploration of sensitive and accurate signatures. In this study, The Cancer Genome Atlas (TCGA) database was searched to screen for an RNA sequencing dataset, retrieving 263 sarcoma and 2 normal samples with survival data. Genes associated with immune regulation in sarcomas were retrieved from the Tumor Immune Estimation Resource database to estimate tumor purity and immune cell infiltration levels. The samples were then divided into the immune-high and immune-low groups. Then, we screened for differentially expressed genes (DEGs) between the two groups. The intersection between immune-related genes and DEGs was then determined. Univariate Cox and least absolute shrinkage and selection operator analyses were used to select ideal genes for prognostic prediction and subsequent construction of a risk signature. A survival analysis was performed to reveal the dissimilarity in survival between the high- and low-score groups. Finally, a nomogram was generated to verify the accuracy and reliability of the signature. Through Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression (ESTIMATE) analysis, high ESTIMATE, and low tumor purity were significantly associated with a favorable prognosis. Moreover, a total of 5259 DEGs were retrieved, the majority of which were downregulated. In total, 590 immune-associated genes overlapped with the DEGs, among which nine hub genes were identified. Finally, two candidate genes, ACVR2B and NFYA, were identified, based on which a risk signature was constructed. The risk signature constructed in this study is accurate and reliable for the prognostic prediction and phenotyping of sarcomas.

Development of a Novel KCNN4-Related ceRNA Network and Prognostic Model for Renal Clear Cell Carcinoma

Background. Clear cell renal cell carcinoma (ccRCC) accounts for more than 80% of renal cell carcinomas. Yet, it has not been fully understood about the derivation and progression of the tumor, as well as the long-term benefits from multimodality therapy. Therefore, reliable and applicable molecular markers are urgently needed for the prediction of diagnosis and prognosis of ccRCC patients. Methods. Genetic and clinical information of 533 ccRCC patients from The Cancer Genome Atlas database was collected for comprehensive bioinformatic analyses. UALCAN was used to detect gene expression in paired tumor samples. Two data sets from Gene Expression Omnibus database were analyzed to identify differentially expressed genes (DEGs), and Gene Set Enrichment Analysis was applied for the functional enrichment of DEGs. Tumor Immune Single Cell Hub and Tumor IMmune Estimation Resource databases were separately used for analyses of single-immune cell and immune cell infiltration. Encyclopedia of RNA Interactomes database was explored to predict targeted microRNAs (miRNAs) and corresponding long non-coding RNAs (lncRNAs). Cox regression analysis was performed for the construction of risk signature and prognosis model. Finally, quantitative real-time polymerase chain reaction and western blot were conducted for KCNN4 expression detection in cell lines and clinical samples. Small interfering RNA was employed to knock down KCNN4, and corresponding functional experiments were conducted on ccRCC cells as well. Results. KCNN4 showed elevated expression in tumors and prominent clinical correlation in ccRCC. In total, 41 KCNN4-related genes were enriched, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed they were intimately related to immune-related signaling pathways. Spearman’s analysis revealed the significantly positive correlation of KCNN4 with immune cell infiltration. By integrating hub miRNA-let-7e-5p and four critical lncRNA, a competitive endogenous RNA network-based risk signature was constructed. The prognosis model derived from it showed considerable predictive value for survival of ccRCC patients. Finally, in vitro experiments confirmed the remarkable tumor-promoting role of KCNN4 in ccRCC cells. Conclusion. KCNN4 significantly affected the immune status of tumor microenvironment and immunotherapy elements, through which it promoted tumor progression in ccRCC, and it could be a potential biomarker for prognosis and immunotherapy effects of ccRCC patients.

Identification of gene signatures associated with ulcerative colitis and the association with immune infiltrates in colon cancer.

Inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease, are some of the most common inflammatory disorders of the gastrointestinal tract. The dysfunction of the immune system in the intestines is suggested to be the underlying cause of the pathogenesis of UC. However, the mechanisms regulating these dysfunctional immune cells and inflammatory phenotypes are still unclear. The differential expression analysis on microarray datasets were performed including GSE24287, GSE87466, GSE102133, and GSE107499, including 376 samples. "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes" pathway enrichment analyses were conducted to identify the common differentially expressed genes (DEGs) in these datasets and explore their underlying biological mechanisms. Further algorithms like "Cell-type Identification by Estimating Relative Subsets of RNA Transcripts" were used to determine the infiltration status of immune cells in patients with UC. "Cytoscape" and "Gene Set Enrichment Analysis" were used to screen for hub genes and to investigate their biological mechanisms. The Tumor Immune Estimation Resource database was used to study the correlation between hub genes and infiltrating immune cells in patients with UC. A total of three hub genes, CCL3, MMP3, and TIMP1, were identified using Cytoscape. A positive correlation was observed between these hub genes and patients with active UC. These genes served as a biomarker for active UC. Moreover, a decrease in CCL3, MMP3, and TIMP1 expression was observed in the mucosa of the intestine of patients with active UC who responded to Golimumab therapy. In addition, results show a significant positive correlation between CCL3, MMP3, and TIMP1 expression and different immune cell types including dendritic cells, macrophages, CD8+ T cells, and neutrophils in patients with colon cancer. Moreover, CCL3, MMP3, and TIMP1 expression were strongly correlated with different immune cell markers. Study results show the involvement of hub genes like CCL3, MMP3, and TIMP1 in the pathogenesis of UC. These genes could serve as a novel pharmacological regulator of UC. These could be used as a therapeutic target for treating patients with UC and may serve as biomarkers for immune cell infiltration in colon cancer.

The pan cancer analysis identified DIAPH3 as a diagnostic biomarker of clinical cancer.

This study aimed to determine prognostic biomarkers of cervical cancer by pan-cancer analysis. Common differentially expressed genes in Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) database were demonstrated using R software analysis, and these genes were enriched by the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology. Genes with prognostic value were identified by least absolute contraction and selection regression, Cox regression, and survival analysis, and pan-cancer analysis was conducted using the Tumor Immune Estimation Resource database and TCGA database. Western blot, qRT-PCR, and immunohistochemistry were used to preliminarily verify its expression in cervical cancer (S1). The prognostic marker Diaphanous Related Formin 3 (DIAPH3) was obtained from us. The enrichment analysis revealed that DIAPH3 was involved in tumor proliferation, invasion, and inflammation. The pan-cancer analysis revealed that it was highly expressed in various cancers. Immune infiltration analysis revealed that its expression was related to B cells, effector T cells, and macrophage infiltration; however, immune checkpoint correlation analysis and tumor mutation burden analysis revealed the correlation between gene expression and immunotherapy. The expression of DIAPH3 in cervical cancer was significantly different from that in normal cervical tissues. The expression of DIAPH3 in cervical cancer was significantly increased, which may be related to the proliferation, metastasis, immune invasion, and immunotherapy of cervical cancer.