DNMT3A promotes glioma growth and malignancy via TNF-α/NF-κB signaling pathway.

Background: DNMT3A is the main molecule responsible for DNA methylation in cells. DNMT3A affects the progression of inflammation, degenerative diseases, and malignant tumors, and exhibits significant aberrantly expression in tumor tissues. Methods: Transcriptome data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) datasets. Differential expression analysis and prognostic analysis were conducted based on above statistics. We constructed a clinical prognostic model and identified DNMT3A as an independent prognostic factor to accurately predict patient prognosis. Differential gene enrichment analysis revealed that DNMT3A affects the progression of glioma through multiple pathways, among which the tumor necrosis factor-α (TNF-α)/nuclear factor-kappa B (NF-κB) pathway shows a strong correlation. Immunological analysis also revealed a certain correlation between DNMT3A and tumor immunity. We demonstrated through gene editing that DNMT3A can affect the release of TNF-α in cells, thereby affecting the progression of glioma. Functional experiments have also demonstrated that DNMT3A plays a crucial role in tumors. Results: RNA-sequencing and survival analyses of lower-grade glioma (LGG) patients in TCGA, CGGA, and GEO cohorts showed that high DNMT3A expression correlated with poor prognosis of LGG patients. Univariate and multivariate Cox regression analyses showed that DNMT3A expression was an independent prognostic indicator in LGG. The prognosis prediction nomogram with age, World Health Organization (WHO) grading, and DNMT3A expression showed reliable performance in predicting the 1-, 3-, and 5-year overall survival (OS) of LGG patients. Functional enrichment analysis, gene set enrichment analysis (GSEA), and ESTIMATE algorithm analyses showed that DNMT3A expression was associated with the tumor infiltration of immune cells and predicted response to immunotherapy in two immunotherapy cohorts of pan-cancer patients. Furthermore, short hairpin RNA (shRNA)-mediated knockdown of DNMT3A in the LGG cell lines suppressed proliferation, migration, and invasion of LGG cells by downregulating the TNF-α/NF-κB signaling pathway. Conclusions: Our data showed that DNMT3A was a potential prognostic biomarker in glioma. DNMT3A promoted proliferation and malignancy of LGG cells through the TNF-α/NF-κB signaling pathway. DNMT3A is a promising therapeutic target for treating patients with LGG.

Aberrant RBMX expression is relevant for cancer prognosis and immunotherapy response.

Cancer accounts for the highest rates of morbidity and mortality worldwide. RNA binding motif protein X-linked (RBMX) is a nuclear RNA-binding protein, associated with certain types of cancer by participating in the integration of sister chromatids and a combination of ribonucleoprotein complexes. However, the specific role of RBMX in cancer immunity remains unknown. This study presents the aberrant expression levels, single-cell distributions, effective prognostic roles, immune cell infiltration associations, and immunotherapy responses of RBMX as a biomarker in various types of cancer. Moreover, it validates the aberrant expression of RBMX in clinical cancer samples. Furthermore, we also evaluated the relationships between RBMX expression and myeloid-derived suppressor cells in clinical samples by immunofluorescent staining. The results showed that knockdown of RBMX can impair the proliferation, migration, and invasion of liver cancer cells. Finally, we indicated that RBMX may play an immunoregulatory role in cancer progression, affecting the therapeutic effects of immune checkpoint inhibitors in patients with cancer.

Predictive role of E2F6 in cancer prognosis and responses of immunotherapy.

BACKGROUND: E2F6 is a member of the E2F transcription factor family. Numerous studies have demonstrated that E2F6 is critical to cancer development and progression, but its role in cancer immunotherapy remains unclear. METHODS: Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases were used to obtain RNA-seq data for cancer and normal tissues, and we utilized the cBioPortal to analyze E2F6 genomic alterations in pan-cancer. The protein localization of E2F6 was obtained using the Human Protein Atlas (HPA), and the upregulation of E2F6 expression in clinical glioblastoma multiforme (GBM) tissues was detected by Western blot analysis. The ComPPI website was used to analyze the protein interaction information of E2F6. To evaluate the role of E2F6 in pan-cancer prognosis, we used univariate Cox regression and Kaplan-Meier methods, and gene set enrichment analysis (GSEA) was utilized to identify markers associated with E2F6 expression in tumors. TIMER 2.0 was used to study E2F6-related immune cell infiltration in tumor tissues, and the correlation of E2F6 with immunotherapy biomarkers was investigated using Spearman correlation analysis. The role of E2F6 in the cell cycle was analyzed by flow cytometry, and the Cell Counting Kit-8 (CCK-8) and colony formation assays were utilized to determine the proliferative ability of cells. RESULTS: In most tumor types, E2F6 was highly expressed and was a good predictor of prognosis. E2F6 was significantly related to markers of immune activation, tumor immune cell infiltration, and immune regulators. Furthermore, E2F6 knockdown significantly attenuated the proliferative ability of glioma cells. Finally, E2F6 effectively predicted anti-programmed cell death 1 (PD1) treatment response. CONCLUSION: E2F6 is an effective biomarker that predicts the prognosis of cancer patients treated with anti-immune checkpoint therapy.

The role of lysosomal peptidases in glioma immune escape: underlying mechanisms and therapeutic strategies.

Glioblastoma is the most common primary malignant tumor of the central nervous system, which has the characteristics of strong invasion, frequent recurrence, and rapid progression. These characteristics are inseparable from the evasion of glioma cells from immune killing, which makes immune escape a great obstacle to the treatment of glioma, and studies have confirmed that glioma patients with immune escape tend to have poor prognosis. The lysosomal peptidase lysosome family plays an important role in the immune escape process of glioma, which mainly includes aspartic acid cathepsin, serine cathepsin, asparagine endopeptidases, and cysteine cathepsins. Among them, the cysteine cathepsin family plays a prominent role in the immune escape of glioma. Numerous studies have confirmed that glioma immune escape mediated by lysosomal peptidases has something to do with autophagy, cell signaling pathways, immune cells, cytokines, and other mechanisms, especially lysosome organization. The relationship between protease and autophagy is more complicated, and the current research is neither complete nor in-depth. Therefore, this article reviews how lysosomal peptidases mediate the immune escape of glioma through the above mechanisms and explores the possibility of lysosomal peptidases as a target of glioma immunotherapy.

The cell senescence regulator p16 is a promising cancer prognostic and immune check-point inhibitor (ICI) therapy biomarker.

Cyclin-dependent kinase inhibitor 2A (CDKN2A) encodes the cell senescence regulator protein p16. The expression of p16 raises in cell senescence and has a nuclear regulation in cell aging. Meanwhile, it's also reported to inhibit the aggression of several cancers. But its clinical application and role in cancer immunotherapy needs further investigation. We collected the transcriptional data of pan-cancer and normal human tissues from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. CBioPortal webtool was employed to mine the genomic alteration status of CDKN2A across cancers. Kaplan-Meier method and univariate Cox regression were performed for prognostic assessments across cancers, respectively. Gene Set Enrichment Analysis is the main method used to search the associated cancer hallmarks associated with CDKN2A. TIMER2.0 was used to analyze the immune cell infiltration relevance with CDKN2A in pan-cancer. The associations between CDKN2A and immunotherapy biomarkers or regulators were performed by spearman correlation analysis. We found CDKN2A is overexpressed in most cancers and exhibits prognosis predictive ability in various cancers. In addition, it is significantly correlated with immune-activated hallmarks, cancer immune cell infiltrations and immunoregulators. The most interesting finding is that CDKN2A can significantly predict anti-PDL1 therapy response. Finally, specific inhibitors which correlated with CDKN2A expression in different cancer types were also screened by using Connectivity Map (CMap) tool. The results revealed that CDKN2A acts as a robust cancer prognostic and immunotherapy biomarker. Its function in the regulation of cancer cell senescence might shape the tumor microenvironment and contribute to its predictive ability of immunotherapy.

Protein disulfide-isomerase A4 confers glioblastoma angiogenesis promotion capacity and resistance to anti-angiogenic therapy.

INTRODUCTION: Increasing evidence has revealed the key activity of protein disulfide isomerase A4 (PDIA4) in the endoplasmic reticulum stress (ERS) response. However, the role of PDIA4 in regulating glioblastoma (GBM)-specific pro-angiogenesis is still unknown. METHODS: The expression and prognostic role of PDIA4 were analyzed using a bioinformatics approach and were validated in 32 clinical samples and follow-up data. RNA-sequencing was used to search for PDIA4-associated biological processes in GBM cells, and proteomic mass spectrum (MS) analysis was used to screen for potential PDIA4 substrates. Western blotting, real-time quantitative polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assays (ELISA) were used to measure the levels of the involved factors. Cell migration and tube formation assays determined the pro-angiogenesis activity of PDIA4 in vitro. An intracranial U87 xenograft GBM animal model was constructed to evaluate the pro-angiogenesis role of PDIA4 in vivo. RESULTS: Aberrant overexpression of PDIA4 was associated with a poor prognosis in patients with GBM, although PDIA4 could also functionally regulate intrinsic GBM secretion of vascular endothelial growth factor-A (VEGF-A) through its active domains of Cys-X-X-Cys (CXXC) oxidoreductase. Functionally, PDIA4 exhibits pro-angiogenesis activity both in vitro and in vivo, and can be upregulated by ERS through transcriptional regulation of X-box binding protein 1 (XBP1). The XBP1/PDIA4/VEGFA axis partially supports the mechanism underlying GBM cell survival under ER stress. Further, GBM cells with higher expression of PDIA4 showed resistance to antiangiogenic therapy in vivo. CONCLUSIONS: Our findings revealed the pro-angiogenesis role of PDIA4 in GBM progression and its potential impact on GBM survival under a harsh microenvironment. Targeting PDIA4 might help to improve the efficacy of antiangiogenic therapy in patients with GBM.

Pan-cancer analysis: predictive role of TAP1 in cancer prognosis and response to immunotherapy.

BACKGROUND: Transporter associated with antigen processing 1 (TAP1) is a molecule involved in processing and presentation of major histocompatibility complex class I restricted antigens, including tumor-associated antigens. TAP1 participates in tumor immunity, and is aberrantly expressed in multiple cancer types; METHODS: Transcriptome profiles were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Genetic alterations, protein distribution, and interaction information for TAP1 were downloaded from cBioPortal, Human Protein Atlas and Compartmentalized Protein-Protein Interaction, respectively. Single-cell analyses of TAP1 across cancers were conducted via the Tumor Immune Single-cell Hub website. Gene set enrichment analysis was employed to investigate TAP1-associated functional mechanisms and processes. Immune cell infiltration was explored using Tumor Immune Estimation Resource 2.0. Pan-cancer correlations between TAP1 expression and immunotherapy biomarkers were explored using the Spearman's correlation test. Associations with immunotherapy responses were also investigated using clinicopathological and prognostic information from cohorts of patients with cancer receiving immune checkpoint inhibitors. RESULTS: TAP1 expression was elevated in most cancer types and exhibited distinct prognostic value. Immune cells expressed more TAP1 than malignant cells within most tumors. TAP1 expression was significantly correlated with immune-related pathways, T-lymphocyte infiltration, and immunotherapeutic biomarkers. Clinical cohort validation revealed a significant correlation with immune therapeutic effects and verified the prognostic role of TAP1 in immunotherapy. Western blot assay indicated that TAP1 is upregulated in glioblastoma compared with adjacent normal brain tissues. CONCLUSION: TAP1 is a robust tumor prognostic biomarker and a novel predictor of clinical prognosis and immunotherapeutic responses in various cancer types.

Identification of a robust scoring system based on metabolic genes followed by in-depth validation of ATP1A3 in glioma.

AIMS: In the past few decades, the prognosis of glioma patients has not significantly improved. Therefore, to provide more precise medical services for glioma patients, it is urgent to identify more clinically meaningful subtypes, establish more robust clinical prediction models, and find more effective therapeutic targets. MATERIALS AND METHODS: Four distinct metabolic-associated subtypes were identified by the NMF algorithm based on metabolic genes (MEGs). A robust scoring system was constructed based on the differentially expressed genes (DEGs) screened from the four metabolic-associated subtypes with the LASSO regression algorithm and multivariate Cox regression analysis. Further analysis of scoring systems was done by different R packages. In addition, the ATP1A3 gene was screened and bioinformatics analysis of it was conducted on several public websites. GSEA software was utilized to search hallmark signaling pathways closely related to ATP1A3. Cytological experiments were used to investigate the role of ATP1A3 in the malignant progression of glioblastoma (GBM) cells. KEY FINDINGS: Four metabolic-associated subtypes with significantly different clinicopathological characteristics were identified, and a robust scoring system with outstanding clinical application value was established. In addition, a tumor suppressor gene ATP1A3 was found, which is expected to be a potential therapeutic target for glioma. SIGNIFICANCE: This study is of great significance in the diagnosis, prognosis, and prediction of the response to immune checkpoint blockers (ICBs) for glioma patients. More importantly, this study found a potential therapeutic target for glioma.

Development and validation of a leukocyte-associated immunoglobulin-like receptor-1 prognostic signature for lower-grade gliomas.

OBJECTIVE: Leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1), is an immunosuppressive receptor, widely expressed by immune cells, but the part of LAIR-1 in glioma progression remains unclear. The purpose of this study was to explore the relationship between LAIR-1 expression and the development of lower-grade glioma (LGG) using publicly available data sets. METHODS: We took advantage of The Cancer Genome Atlas (TCGA) to analyze the expression of LAIR-1 in patients with LGG. Second, Kaplan-Meier methods and univariate and multivariate Cox regression analyses were used to examine the clinical significance of LAIR-1 expression in combination with CGGA databases, and then receiver operating characteristic curve analysis was used to verify the prognostic utility of LAIR-1. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore the function of LAIR-1. Analysis of the correlation with immune infiltration was conducted using the ESTIMATE algorithm and single sample gene set enrichment analysis. RESULTS: Our results showed that LAIR-1 expression to be positively correlated with malignant clinicopathologic features of LGG. Univariate analysis and multivariate analysis revealed that overexpression of LAIR-1 was correlated with a worse prognosis in patients. A nomogram model combining LAIR-1 was more useful in guiding clinical diagnosis, and functional enrichment analysis showed that malignant development of glioma was closely affiliated with the tumor immune microenvironment. CONCLUSION: These results indicate that LAIR 1 is a latent marker for determining the prognosis of LGG patients. LAIR 1 may also participate a critical part in TIME of LGG by regulating the infiltration of immune cells, suggesting that LAIR 1 might be used as a therapeutic target to regulate the antitumor immune response.

Ferroptosis in tumor immunity and therapy.

Ferroptosis is a type of regulated cell death (RCD), and it plays an important role in the occurrence of diseases, especially the development of tumors. Ferroptosis of tumor cells affects the antitumor immunity and the immune response to treatment to varying degrees. Ferroptosis also plays a key role in immune cells. This review outlines the mechanism of the immune-related effects of ferroptosis pathways in tumor progression and treatment, and it discusses potential methods for improving antitumor immunity and enhancing the efficacy of current cancer treatments by targeting ferroptosis.

Intrinsic immune evasion patterns predict temozolomide sensitivity and immunotherapy response in lower-grade gliomas.

BACKGROUND: Although intrinsic immune-evasion is important in cancer proliferation, metastasis and response to treatment, it is unclear whether intrinsic immune-evasion patterns of gliomas can aid in predicting clinical prognosis and determining treatment. METHODS: A total of 182 immune-evasion genes intrinsic to cancer were subjected to consensus clustering to identify immune-evasion patterns in 1421 patients with lower-grade glioma (LGG). The levels of each cancer hallmark were determined by the Gene Set Variant Analysis (GSVA) method, and immune cell infiltrations were quantified using two algorithms, the single-sample Gene Set Enrichment Analysis (ssGSEA) and the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) methods. IEVscore was determined by a method that combined univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression and principal component analysis (PCA). RESULTS: Transcriptional and genomic analysis showed that most immune evasion genes (IEVGs) were upregulated in LGGs, with aberrant expression driven by alterations in copy number variants (CNV). Based on the mRNA expression profiles of cancer-intrinsic IEVGs could be divided into three LGG subgroups with distinct prognosis, clinicopathological features and immune infiltrations. A combined scoring scheme designed to assess the immune-evasion levels of LGGs divided these 1421 patients into two subgroups that differed in IEVscores. LGG patients with low-IEVscore had a better prognosis, would be more likely to benefit from immune check-point inhibitors and would be more susceptible to temozolomide (TMZ) chemotherapy. CONCLUSION: Intrinsic immune evasion in the tumor microenvironment (TME) has a crucial effect on glioma formation. Quantitatively assessing the IEV scores of individual LGG patients could enhance knowledge about the intra-glioma microenvironment and lead to the development of individualized therapeutic strategies for patients with LGG.

Comprehensive analysis of the prognostic implications and functional exploration of PAK gene family in human cancer.

BACKGROUND: The p21-activated kinase (PAK) family (PAKs) plays a key role in the formation and development of human tumors. However, a systematic analysis of PAKs in human cancers is lacking and the potential role of PAKs in cancer immunity has not been explored. METHODS: We used datasets from in The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression database (GTEx). RESULTS: Based on TCGA datasets most PAKs show noteworthy differences in expression between tumors and corresponding normal tissues or across different tumor tissues. Patients with high expression of PAKs often show a worse prognosis. However, copy number variation, mutation, and DNA methylation of PAKs have limited impact on tumor development. Further analysis showed that the impact of PAKs on immunity varies with the type of tumor and the respective tumor microenvironment. PAK1 and PAK4 may be stronger predictors of immune characteristics, and are more suitable as drugs and molecular therapeutic targets. Furthermore, Cox regression analysis revealed that a PAK gene signature could be used as an independent prognostic factor for lower grade glioma (LGG) and glioblastoma (GBM). Gene set enrichment analysis (GSEA) analysis indicated that PAK genes may affect the occurrence and development of GBM through the PI3K signaling pathway. Further experiments verified that PAK1 and AKT1 have a significant interaction in GBM cells, and inhibiting the overactivation of PAK1 can significantly inhibit the proliferation of GBM cells. CONCLUSIONS: Our study provides a rationale for further research on the prognostic and therapeutic potential of PAKs in human tumors.

Sperm Autoantigenic Protein 17 Predicts the Prognosis and the Immunotherapy Response of Cancers: A Pan-Cancer Analysis.

Background: Sperm autoantigen protein 17 (SPA17) is a highly conserved mammalian protein that participates in the acrosome reaction during fertilization and is a recently reported member of the cancer-testicular antigen (CTA) family. It has been reported that the SPA17 expression is limited in adult somatic tissues and re-expressed in tumor tissues. Recently, studies have found that SPA17 regulates the progression of various cancers, but its role in cancer immunotherapy is not clear. Methods: The pan-cancer and normal tissue transcriptional data were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. We explored the SPA17 pan-cancer genomic alteration analysis in the cBioPortal webtool. The Human Protein Atlas (HPA) and ComPPI websites were used to mine the SPA17 protein information. We performed a western blotting assay to validate the upregulated SPA17 expression in clinical glioblastoma (GBM) samples. The univariate Cox regression and Kaplan-Meier method were used to assess the prognostic role of SPA17 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was used to search the associated cancer hallmarks with SPA17 expression in each cancer type. TIMER2.0 was the main platform to investigate the immune cell infiltrations related to SPA17 in pan-cancer. The associations between SPA17 and immunotherapy biomarkers were performed by Spearman correlation analysis. The drug sensitivity information from the Connectivity Map (CMap) dataset was downloaded to perform SAP17-specific inhibitor sensitivity analysis. Findings: SPA17 was aberrantly expressed in most cancer types and exhibited prognosis predictive ability in various cancers. In addition, our results also show that SPA17 was significantly correlated with immune-activated hallmarks (including pathways and biological processes), immune cell infiltrations, and immunoregulator expressions. The most exciting finding was that SPA17 could significantly predict anti-PDL1 and anti-PD1 therapy responses in cancer patients. Finally, specific inhibitors, like irinotecan and puromycin, which correlate with SPA17 expression in different cancer types, were also screened using Connectivity Map (CMap). Conclusions: Our results reveal that SPA17 was abnormally expressed in cancer tissues, and this expression pattern could be associated with immune cell infiltrations in tumor microenvironments. Clinically, SPA17 not only acted as a potent prognostic factor to predict the clinical outcomes of cancer patients but was also a promising immunotherapy predictive biomarker for cancer patients treated with immune-checkpoint inhibitors (ICIs).

Transcriptional Patterns of Lower-Grade Glioma Patients with Distinct Ferroptosis Levels, Immunotherapy Response, and Temozolomide Sensitivity.

Background: Many studies have defined a critical role for ferroptosis in cancer progression and therapy, but it is unclear how ferroptosis regulates tumor immunity or tumor microenvironment (TME). Methods: In this study, 24 ferroptosis-regulators were assessed by nonnegative matrix factorization (NMF) consensus clustering to identify ferroptosis patterns in lower-grade gliomas (LGGs). Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method and single sample gene set enrichment analysis (ssGSEA) were used to quantify immune cell infiltrations. The PCA algorithm was used to develop the ferroptosis-related score (FRscore) to measure ferroptosis levels. Results: Two LGG subgroups named ferroptosis-related clusters 1 (FRC1) and 2 (FRC2), with distinct ferroptosis levels, immune infiltrations, and clinical outcomes were determined in 1,407 LGG samples. A well-designed scoring system was developed to evaluate the ferroptosis levels in LGG patients based on the FRSig gene profile and divided patients into low- and high-FRscore subgroups. Patients with low FRscores had lower ferroptosis levels and prolonged survival time and were expected to benefit from immune checkpoint blockade (ICB) therapy and showed higher sensitivity to TMZ chemotherapy. Findings also showed that the PI3K-AKT-mTOR pathway is activated by ferroptosis induction in SW1088 cells. Conclusions: This study highlights the critical role of ferroptosis in TME formation and shaping, and quantitatively assessing ferroptosis levels in individual tumors can help to define the intratumor microenvironment and formulate precise treatment strategies for LGG patients.

Protein Disulfide-Isomerase A3 Is a Robust Prognostic Biomarker for Cancers and Predicts the Immunotherapy Response Effectively.

Background: Protein disulfide isomerase A3 (PDIA3) is a member of the protein disulfide isomerase (PDI) family that participates in protein folding through its protein disulfide isomerase function. It has been reported to regulate the progression of several cancers, but its function in cancer immunotherapy is unknown. Methods: The RNA-seq data of cancer and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. The Cbioportal dataset was used to explore the genomic alteration information of PDIA3 in pan-cancer. Human Protein Atlas (HPA) and ComPPI websites were employed to mine the protein information of PDIA3, and western blot assay was performed to monitor the upregulated PDIA3 expression in clinical GBM samples. The univariate Cox regression and the Kaplan-Meier method were utilized to appraise the prognostic role of PDIA3 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was applied to search the associated cancer hallmarks with PDIA3 expression. TIMER2.0 was the main platform to investigate the immune cell infiltrations related to PDIA3 in pan-cancer. The associations between PDIA3 and immunotherapy biomarkers were performed by Spearman correlation analysis. The immunoblot was used to quantify the PDIA3 expression levels, and the proliferative and invasive ability of glioma cells was determined by colony formation and transwell assays. Findings: PDIA3 is overexpressed in most cancer types and exhibits prognosis predictive ability in various cancers, and it is especially expressed in the malignant cells and monocytes/macrophages. In addition, PDIA3 is significantly correlated with immune-activated hallmarks, cancer immune cell infiltrations, and immunoregulators, and the most interesting finding is that PDIA3 could significantly predict anti-PDL1 therapy response. Besides, specific inhibitors that correlated with PDIA3 expression in different cancer types were also screened by using Connectivity Map (CMap). Finally, knockdown of PDIA3 significantly weakened the proliferative and invasive ability of glioma cells. Interpretation: The results revealed that PDIA3 acts as a robust tumor biomarker. Its function in protein disulfide linkage regulation could influence protein synthesis, degradation, and secretion, and then shapes the tumor microenvironment, which might be further applied to develop novel anticancer inhibitors.

CLCF1 Is a Novel Potential Immune-Related Target With Predictive Value for Prognosis and Immunotherapy Response in Glioma.

Background: Cardiotrophin-like cytokine factor 1 (CLCF1) has been described as an oncogene and a potential therapeutic target in a variety of cancers, but its role in glioma remains unknown. Methods: Based on The Cancer Genome Atlas (TCGA), we conducted a bioinformatics analysis to investigate the clinical significance and biological functions of CLCF1 in glioma at the transcriptional level and predicted the response to immunotherapy of glioma patients with different CLCF1 expression levels. All the results were further verified in Chinese Glioma Genome Altas(CGGA) Data processing and figure generating were performed with R language. Results: Elevated CLCF1 expression was common in cancers and usually predicted poor prognosis, which was also consistent with gliomas. In Univariate Cox Regression analysis and Kaplan-Meier survival analysis, tumor patients with higher CLCF1 expression tended to experience a worse prognosis. In the multivariate Cox proportional hazard model, the expression of CLCF1 was an independent prognostic factor in gliomas. The biological function analysis of CLCF1 in glioma showed that CLCF1 was closely associated with immune signatures, including immune-related pathways, immune cell infiltration, and immune checkpoints. Moreover, glioma patients with low CLCF1 expression showed a greater tendency to respond to anti-PD1/PD-L1 immunotherapy, indicating CLCF1 also had potential clinical significance in guiding immunotherapy. And CLCF1 as a member of the IL6 family had a better predictive value for prognosis and immunotherapy response in glioma than that of IL6 and other IL6 family members. Conclusion: CLCF1 expression is an independent prognosticator and a promising therapeutic target correlated with immunotherapy in glioma.

Comprehensive analysis of the prognostic and role in immune cell infiltration of MSR1 expression in lower-grade gliomas.

BACKGROUND: The therapeutic effects of conventional treatment on gliomas are not promising. The tumor microenvironment (TME) has a close association with the invasiveness of multiple types of tumors, including low-grade gliomas (LGG). This study aims to validate the prognostic and immune-related role of macrophage scavenger receptor 1 (MSR1) in LGG patients. METHODS: Data in this study were obtained from public databases. The differential expression of MSR1 was analyzed in LGG patients with different clinicopathological characteristics. Kaplan-Meier survival analysis, a time-dependent receiver operating characteristic (ROC) curve, and Cox regression analysis were used to assess the prognostic value of MSR1. Differentially expressed genes (DEGs) were screened between the high and low expression groups of MSR1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to annotate the function of these DEGs. Hallmark gene sets were identified based on MSR1 by Gene Set Enrichment Analysis (GSEA). Difference analysis and correlation analysis were used to study the relationship between MSR1 and TME-related scores, tumor-infiltrating immune cells (TIICs), immune-related gene sets, and immune checkpoints (ICPs). The single-cell sequencing data were processed to identify the cell types expressing MSR1. The quantification of TIICs in TME was calculated by single-sample gene set enrichment analysis (ssGSEA). The differential expression of MSR1 in LGG and control brain tissues was verified by experiments. RESULTS: There were significant differences in the expression level of MSR1 in different types of tissues and cells. MSR1 has a high prognostic value in LGG patients and can be used as an independent prognostic factor. MSR1 is closely related to TME and may play an important role in the immunotherapy of LGG patients. CONCLUSIONS: The result of our study demonstrated that MSR1 is an independent prognostic biomarker in LGG patients and may play an important role in the TME of LGGs.

DNAJC10 correlates with tumor immune characteristics and predicts the prognosis of glioma patients.

BACKGROUND: The role of DnaJ heat shock protein family (Hsp40) member C10 (DNAJC10) in cancers has been reported but its function in glioma is not clear. We reveal the prognostic role and underlying functions of DNAJC10 in glioma in the present study. METHODS: Reverse Transcription and Quantitative Polymerase Chain Reaction (RT-qPCR) was used to quantify the relative DNAJC10 messenger RNA (mRNA) expression of clinical samples. Protein expressions of clinical samples were tested by Western blot. The overall survival (OS) of glioma patients with different DNAJC10 expression was compared by Kaplan-Meier method (two-sided log-rank test). Single-sample gene set enrichment analysis (ssGSEA) was used to estimate the immune cell infiltrations and immune-related function levels. The independent prognostic role of DNAJC10 was determined by univariate and multivariate Cox regression analyses. The DNAJC10-based nomogram model was established using multivariate Cox regression by R package 'rms'. RESULTS: Higher DNAJC10 is observed in gliomas and it is up-regulated in higher grade, isocitrate dehydrogenase (IDH)-wild, 1p/19q non-codeletion, O(6)-methylguanine-DNA methyltransferase (MGMT) unmethylated gliomas. Gliomas with higher DNAJC10 expression present poorer prognosis compared with low-DNAJC10 gliomas. The predictive accuracy of 1/3/5-OS of DNAJC10 is found to be stable and robust using time-dependent ROC model. Enrichment analysis recognized that T-cell activation and T-cell receptor signaling were enriched in higher DNAJC10 gliomas. Immune/stromal cell infiltrations, tumor mutation burden (TMB), copy number alteration (CNA) burden and immune checkpoint genes (ICPGs) were also positively correlated with DNAJC10 expression in gliomas. DNAJ10-based nomogram model was established and showed strong prognosis-predictive ability. CONCLUSION: Higher DNAJC10 expression correlates with poor prognosis of glioma and it was a potential prognostic biomarker for glioma.

Integrin Alpha-2 as a Potential Prognostic and Predictive Biomarker for Patients With Lower-Grade Glioma.

Diffuse gliomas are the most common malignant brain tumors with the highest mortality and recurrence rate in adults. Integrin alpha-2 (ITGA2) is involved in a series of biological processes, including cell adhesion, stemness regulation, angiogenesis, and immune/blood cell functions. The role of ITGA2 in lower-grade gliomas (LGGs) is not well defined. Firstly, we downloaded RNA sequencing and relevant clinical information from The Cancer Genome Atlas cohort, the Chinese Glioma Genome Atlas cohort, and related immune cohorts. Next, prognosis analysis, difference analysis, clinical model construction, enrichment analysis, and immune infiltration analysis are performed for this study. These analyses indicated that ITGA2 may have clinical application value and research value in LGG immunotherapy. We also detected the mRNA and protein expression of ITGA2 in three LGG cell lines and normal glial cells using quantitative real-time polymerase chain reaction assay and western blot assay. Our study not only offers a novel target for LGG immunotherapy but also can better comprehend the mechanism of the development and progression of patients with LGG. This study revealed that ITGA2 may be a potential prognostic and predictive biomarker for LGG, which can bring new insights into targeted immunotherapy.

Pan-cancer analysis of N4-acetylcytidine adaptor THUMPD1 as a predictor for prognosis and immunotherapy.

BACKGROUND: THUMPD1 is a specific RNA adaptor that assists acetylation of mRNA and production of N4-acetylcytidine (ac4C). However, it remains unclear whether THUMPD1 plays a part in tumorigenesis and therapeutic efficacy. Here, we analyzed the expression profiles and prognostic value of THUMPD1 in pan-cancer and gained insights into the correlation between THUMPD1 expression level and immunotherapy efficacy. METHODS: Gene expression pattern and its correlation with prognosis, immune cell infiltration in pan-cancer were obtained from Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) databases, with Kaplan-Meier method and Spearman correlation analysis used. Western blotting and immunofluorescence on clinical samples were performed to validate our database-derived results. Correlation between THUMPD1 expression level and immunotherapy responses was also explored, based on clinical cohorts receiving programmed cell death protein 1 ligand (PD-L1) antibody therapy. Finally, gene set enrichment analysis (GSEA) was performed to show the possible tumorigenic mechanism. RESULTS: THUMPD1 was highly expressed in most cancer types, and this elevated expression indicated poor or improved prognosis for different cancers. In kidney renal clear cell carcinoma (KIRC) and rectum adenocarcinoma (READ), patients with higher THUMPD1 expression exhibited a better prognosis, while liver hepatocellular carcinoma (LIHC) patients had worse prognosis. Besides, THUMPD1 was significantly associated with immune cell infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), immune checkpoints and neoantigen in many cancer types. Further, more clinical advantages and therapeutic responses were observed in patients with high THUMPD1 expression. CONCLUSIONS: THUMPD1 may serve as a novel predictor to evaluate cancer prognosis and immune therapy efficacy in diverse cancer types.