Tumor Immune Estimation Resource Database Research Articles

Study on the expression and prognostic relationship of MYL6B in liver cancer based on bioinformatics.

Primary liver cancer is a prevalent and deadly cancer type. Despite treatment advances, prognosis remains poor, with high recurrence rates. Early detection is crucial but challenging due to the disease's insidious nature. Myosin proteins play significant roles in cancer development, influencing cell migration, invasion, and tumor suppression. MYL6B, a myosin light chain, is involved in various cellular processes and has been associated with poor prognosis in colorectal adenocarcinoma and potential as a biomarker in breast cancer. To investigate the expression of MYL6B in liver hepatocellular carcinoma (LIHC) and its impact on prognosis and potential mechanisms of action using bioinformatics methods. The expression of MYL6B in pan-cancer and normal tissues was analyzed using the gene expression profiling interactive analysis 2 and tumor immune estimation resource databases. The expression level of MYL6B in LIHC tissues and its relationship with prognosis were analyzed, immunohistochemical analysis of MYL6B and its effect on immune cell infiltration, and the protein network were further studied. MYL6B was highly expressed in diffuse large b-cell lymphoma, LIHC, pancreatic adenocarcinoma, skin cutaneous melanoma, thymoma, uterine corpus endometrial carcinoma, uterine carcinosarcoma, and lowly expressed in kidney chromophobe, acute myeloid leukemia, testicular germ cell tumors. The expression level of MYL6B was significantly different between cancer and normal tissues. It had a significant impact on both overall survival and disease-free survival. MYL6B is highly expressed in hepatocellular carcinoma and its expression level increases with cancer progression. High MYL6B expression is associated with poor prognosis in terms of overall survival and recurrence-free survival. The immunohistochemical level of MYL6B is high in hepatocellular carcinoma tissues, and MYL6B has a high level of immune infiltration inflammation. In protein network analysis, MYL6B is correlated with MYL2, MYL6, MYL9, MYLK4, MYLK2, MYL12A, MYL12B, MYH11, MYH9 and MYH10. The expression level of MYL6B in LIHC was significantly higher than in normal liver tissues, and it was correlated with the degree of differentiation survival rate, and immune infiltration. MYL6B is a potential target for LIHC treatment.

PLXDC1 serves as a potential prognostic marker and involves in malignant progression and macrophage polarization in colon cancer.

The malignant behavior and immune escape ability of cancer cells lead to therapeutic failure and poor prognosis for patients with various cancers, including colon cancer. Plexin domain containing 1 (PLXDC1) was initially identified to exert key roles in tumor by regulating angiogenesis and has recently proved to be involved in cell proliferation and migration of glioblastoma and gastric cancer cells. However, its roles in colon cancer remain unclear. In this study, the online bioinformatics databases confirmed high expression of PLXDC1 in colon cancer specimens, which was associated with cancer stages and nodal metastasis. Similarly, the increased expression of PLXDC1 was also validated in our collected samples and colon cancer cells. Moreover, patients with high expression of PLXDC1 had shorter survival, indicating that PLXDC1 might be a potential prognostic predictor for colon cancer patients. Notably, targeting PLXDC1 inhibited cancer cell viability and invasion, and enhanced cell apoptosis. Intriguingly, Tumor Immune Estimation Resource database confirmed that PLXDC1 expression was related to various tumor-infiltrating immune cells in colon adenocarcinoma including macrophages, and its expression was also correlated with M2-like macrophage markers. In vitro, colon cancer cells with PLXDC1 downregulation had a reduced ability to recruit and polarize macrophage towards M2 phenotype by decreasing the percentage of CD206+ cells and M2-like markers (CD206, CD163, arginase1, and interleukin 10 [IL-10]). Moreover, PLXDC1 knockdown attenuated M2 macrophage-mediated promotion in cancer cell viability and invasion. Mechanically, inhibition of PLXDC1 suppressed activation of the IL-6/Signal transducer and activator of transcription 3 (STAT3) signaling. Reactivating the above pathway by transfection with IL-6 plasmids reversed the suppressive effects of PLXDC1 knockdown on cancer cell malignant behaviors, macrophage recruitment and M2-like polarization. Thus, PLXDC1 downregulation may inhibit the malignancy of colon cancer cells and their ability to recruit and polarize macrophages towards M2 phenotype by blocking the IL-6/STAT3 pathway. Together, targeting PLXDC1 may attenuate the progression of colon cancer by direct roles in cancer cells and indirect roles in macrophage polarization, representing a promising therapeutic target for colon cancer patients.

Bioinformatic prediction of miR-320a as a potential negative regulator of CDGSH iron-sulfur domain 2 (CISD2), involved in lung adenocarcinoma bone metastasis via MYC activation, and associated with tumor immune infiltration.

Ferroptosis, a form of regulated cell death associated with iron-dependent lipid peroxidation, plays a role in cancer progression. However, the specific mechanisms of ferroptosis in lung adenocarcinoma (LUAD) bone metastasis (BM) remain unclear. Using bioinformatics analysis, this study sought to identify the ferroptosis-associated genes involved in BM in LUAD, thus providing potential novel targets for the treatment of BM in LUAD. The RNA expression dataset GSE10799 was acquired from the Gene Expression Omnibus (GEO) database, and intersected with the ferroptosis dataset to identify ferroptosis-related differentially expressed genes (DEGs). The expression of candidate genes and their correlation with the prognosis of LUAD patients were validated in The Cancer Genome Atlas (TCGA) database. A protein gene interaction network was constructed using GeneMania and Retrieval of Interacting Genes/Proteins (STRING) databases. The association between the candidate genes and immune cells was assessed via TCGA and Tumor IMmune Estimation Resource (TIMER) databases. The potential mechanisms were elucidated by a gene set enrichment analysis (GSEA). The relevant microRNAs (miRNAs or miRs) that bind to the 3'untranslated region (3'UTR) end of candidate genes' mRNA was explored using the TargetScan database. The expression of these candidate miRNAs in LUAD was validated and the correlation between candidate miRNAs and candidate mRNAs was tested using the TCGA database. Finally, the clinical data of 40 LUAD patients were retrospectively analyzed to evaluate the clinical value of candidate gene expression for LUAD BM patients. In this research, 15 ferroptosis-related DEGs in LUAD BM were identified. TCGA database analysis indicated that patients with low levels of CDGSH iron-sulfur domain 2 (CISD2) in LUAD had better disease-specific survival (DSS), overall survival (OS), and a better progression-free interval (PFI) than those with high levels of CISD2. The TIMER database results show that the expression of CISD2 is correlated with the infiltration levels of various immune cells. The GSEA indicated that CISD2 might influence biological activity in LUAD by participating in cell-cycle regulation, mitochondrial translation, DNA damage repair, c-Myc (MYC) activation, and the P53 signaling pathway. Through the combined analysis of the TargetScan and TCGA databases, hsa-miR-320a was identified as the optimal upstream regulatory miRNA. The immunohistochemistry data indicated that the positive CISD2 expression rates and immunohistochemistry scores of the patients with BM were significantly higher than those of the patients without BM (P<0.05). The high expression of CISD2 is a significant risk factor for BM in LUAD. The downregulation of CISD2 expression may extend DSS, OS, and the PFI of LUAD patients. Thus, CISD2 could serve as a novel predictive biomarker for LUAD patients. Further, miR-320a might negatively regulate CISD2 and participate in LUAD BM by activating MYC. These data provide a potential perspective for developing anticancer therapies for LUAD-BM patients.

NFKBIE is a predictive factor of survival and is correlated with immune infiltration and antigen processing and presentation in hepatocellular carcinoma.

The important role of the nuclear factor κB (NFκB) pathway in tumour development has long been recognized; however, the role of the NFκB inhibitor family in liver cancer has not been elucidated. Hepatocellular carcinoma (HCC) is a serious public health burden with a high incidence, poor prognosis, and early detection, especially in Asia, where hepatitis is prevalent. In the present study, the mRNA expression level of the NFκB inhibitor family was assessed in HCC and normal tissues using the Metabolic Gene Rapid Visualizer, University of Alabama at Birmingham Cancer Data Analysis Portal, and the Tumor Immune Estimation Resource database (TIMER). Survival curves of nuclear factor of κ light polypeptide gene enhancer in B-cells inhibitor (NFKBI)E were obtained using the Kaplan-Meier method. Genes co-expressed with NFKBIE in HCC samples were studied using data from the LinkedOmics and the Hepatocellular Carcinoma Databases. Protein-protein interaction networks, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment pathway analyses were used to assess the NFKBIE mechanism in HCC. Using the TIMER database, the association between immune infiltration and NFKBIE was determined. RNA-sequencing (RNA-seq) was used to evaluate the function of NFKBIE in HCC and its impact on proliferation and migration. Western blotting was used to confirm the expression of NFKBIE in HCC cell lines. In addition, NFKBIE overexpression in HCC was demonstrated using tissue microarrays encompassing 80 pairs of HCC and normal liver tissues. NFKBIE was the only NFκB inhibitor with high expression and an improved prognosis in HCC compared with other NFκB inhibitors. NFKBIE was correlated with clinical characteristics, such as tumour grade, tumour protein P53 mutation status and tumour stage. Data obtained from Gene Set Cancer Analysis suggested that NFKBIE may inhibit the PI3K/AKT, RAS/MAPK, RTK and TSC/mTOR pathways. In addition, NFKBIE was significantly associated with B-cell immune infiltration and the RNA-seq data demonstrated that knockdown of NFKBIE significantly affected 'Antigen processing and presentation' and 'hepatocellular carcinoma' pathways. Immunohistochemistry of microarrays of tissue samples revealed that NFKBIE was overexpressed in several stages of HCC. Finally, inhibition of NFKBIE decreased the proliferation and migration of HCC cells. In conclusion, due to its prognostic value and overexpression in HCC, NFKBIE distinguished itself from other NFκB inhibitors. As such, it may provide a novel prognostic indicator and immunotherapeutic target for HCC.

Identification and expression of prognostic-related genes in kidney renal clear cell carcinoma and their possible regulatory mechanisms.

Many factors affect the prognosis of kidney renal clear cell carcinoma (KIRC). Early diagnosis can significantly improve the prognosis of KIRC patients. Therefore, a method needs to be developed to diagnose KIRC early, predict patient prognosis, and improve personalized treatments. The objective of this study is to utilize bioinformatics tools and public database resources to identify differentially expressed genes (DEGs) between renal cancer tissues and adjacent normal tissues, and to further screen for prognostic-related genes (PRGs) of KIRC. KIRC was studied using R language and FunRich software and several databases, including the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham cancer data analysis Portal (UALCAN), and Tumor Immune Estimation Resource (TIMER) databases. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the expression of multiple genes in KIRC and adjacent normal tissues. There were substantial differences in immune cell infiltration between the KIRC and adjacent normal tissues in the GSE40435 and GSE46699 datasets. In addition, we screened multiple PRGs of KIRC by combining the GEO and TCGA data. The UALCAN database verified that some representative PRGs were differently expressed depending on the lymph node metastasis status, grade, and stage of KIRC. The qRT-PCR results confirmed the expression of the PRGs in KIRC and adjacent normal tissues. Through the GO and KEGG analyses, interaction analysis, and TIMER database, we found that the prognosis of KIRC was closely related to immune microenvironment and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) signaling. Our findings could contribute to the prognosis prediction of KIRC, the selection of personalized treatments, and the early diagnosis of KIRC.

Comprehensive Analysis Reveals Epithelial Growth Factor Receptor as a Potential Diagnostic Biomarker in Glioblastoma Multiforme.

Glioblastoma multiforme (GBM), a highly aggressive tumor of the central nervous system, is the most common malignant brain tumor and poses a significant risk to life. GBM patients have a low survival rate owing to their aggressive nature, poor prognosis, genomic variations among patients, and histopathological differences. In this study, we used several bioinformatics platforms, namely Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) databases, Kaplan-Meier plotter, and cBioPortal, to conduct a comprehensive analysis to highlight the expression of epithelial growth factor receptor (EGFR) in patients with GBM. Our study highlights EGFR as a potential diagnostic and prognostic marker. According to the TIMER database, EGFR was upregulated in five cancers, including GBM, head and neck squamous cell carcinoma, kidney renal cell carcinoma, kidney renal cell papillary cell carcinoma, and lung squamous cell carcinoma, whereas it was downregulated in breast invasive carcinoma, colon adenocarcinoma, pheochromocytoma and paraganglioma, prostate adenocarcinoma, rectum adenocarcinoma, and uterine corpus endometrial carcinoma. Our investigation highlighted the expression of EGFR in various clinicopathological parameters, which include age, sex, gender, and TP53 mutation status in patients with GBM. We found that EGFR was upregulated in middle-aged and older adults compared to normal tissues, while it was not significantly downregulated in young adults and older adults. EGFR was upregulated in Caucasians compared to normal tissue, whereas it was downregulated in Asian and African American populations, but this was not statistically significant. In terms of gender, EGFR was upregulated in the male population compared to the female population. Furthermore, EGFR was upregulated in patients with TP53 mutations compared to normal tissues. We also examined the correlation between EGFR gene expression and immune cell infiltration in GBM patients and the impact of EGFR mutations on patient prognosis. Our results revealed a significant positive correlation between EGFR, B cells, and macrophages, but this was not significant for other cell types. This study signified that upregulation of EGFR was associated with a poor prognosis in patients with GBM validated by the GEPIA and UALCAN databases.

Pan-cancer analysis of the prognostic and immunological role of RPL4

Ribosomal proteins (RPs) play an important role in the overall stability, function, and integrity of ribosomes. Ribosomal protein L4 (RPL4), which is encoded by RPL4, is assumed to play different roles in different cancers due to the strong correlation between them. However, research based on the underlying mechanisms of this correlations is limited. Therefore, this study investigated the biological role of RPL4 in various cancers. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to compare the differential expression of RPL4 in tumor and normal tissues. The Sangerbox database and Kaplan–Meier method were employed to assess RPL4's impact on the prognosis of pan-cancer. Analyses using the cBioPortal tool, Shiny Methylation Analysis Resource Tool (SMART), and MethSurv provided insights into the methylation and epigenetic alterations of RPL4. Gene enrichment analysis revealed that RPL4 is involved in ribosome biogenesis through multiple pathways, and its enrichment in signaling pathways directly or indirectly influence tumor development. Tumor Immune Single-cell Hub (TISCH) was used to analyze RPL4 expression levels and cellular functions in the tumor microenvironment. Tumor Immune Estimation Resource Database 2.0 (TIMER2.0) and Tumor-Immune System Interactions Database (TISIDB) tools revealed that RPL4 affected the immune infiltration potential of tumors. Furthermore, the application of the ROC mapper and CellMiner databases indicated an association between RPL4 and sensitivity to multiple antitumor drugs. Additionally, RPL4 was found to remodel the tumor immune microenvironment, leading to the development of chemoresistance. In conclusion, the findings suggest that RPL4 can be used as a potential tumor biomarker and may serve as a target for immunotherapy in various cancers. Genetic testing of RPL4 provides a foundation for the diagnosis, prognosis, and treatment of clinical tumors.

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.