Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC.

BACKGROUND AND AIMS: Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues. APPROACH AND RESULTS: We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC. CONCLUSIONS: Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

Single-cell analysis identified PDIA3 as regulator of malignant characteristics and macrophage function in human cancers.

Protein disulfide isomerase A3 (PDIA3) is an endoplasmic reticulum (ER) protein. It has different functions including glycoprotein folding in the ER. The unfavorable prognosis of cancer patients was related to the abnormal PDIA3 expression level. However, it is unclear how PDIA3 correlates with the malignant characteristics of different tumors and its impact on tumor immunity. Pan-cancer data were downloaded from several databases for large-scale bioinformatics analysis. The immunological functions of PDIA3 were systematically explored at the single-cell sequencing level, including cell communication, cell metabolism, cell evolution and epigenetic modification. We performed immunofluorescence staining to visualize PDIA3 expression and infiltration of macrophages in pan-cancer samples. Further, we performed a loss-of-function assay of PDIA3 in vitro. The CCK8 assay, clone formation assay, and transwell assay were performed. M2 macrophages were co-cultured with different cell lines before the transwell assay was performed. The immunofluorescence staining of pan-cancer samples presented a higher expression of PDIA3 than those of the paired normal tissues. According to single-cell sequencing analysis, expression of PDIA3 was closely associated with cell communication, cell metabolism, cell evolution and epigenetic modification. The knockdown of PDIA3 in tumor cells inhibited cell proliferation and invasion, and restrained cocultured M2 macrophage migration. Furthermore, PDIA3 displayed predictive value in immunotherapy response in human cancer cohorts, indicating a potential therapeutic target. Our study showed that PDIA3 was associated with tumor malignant characteristics and could mediate the migration of M2 macrophages in various tumor types. PDIA3 could be a promising target to achieve tumor control and improve the immune response on a pan-cancer scale.

Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma.

Long noncoding ribonucleic acids (RNAs; lncRNAs) have been associated with cancer immunity regulation. However, the roles of immune cell-specific lncRNAs in glioblastoma (GBM) remain largely unknown. In this study, a novel computational framework was constructed to screen the tumor-infiltrating immune cell-associated lncRNAs (TIIClnc) for developing TIIClnc signature by integratively analyzing the transcriptome data of purified immune cells, GBM cell lines and bulk GBM tissues using six machine learning algorithms. As a result, TIIClnc signature could distinguish survival outcomes of GBM patients across four independent datasets, including the Xiangya in-house dataset, and more importantly, showed superior performance than 95 previously established signatures in gliomas. TIIClnc signature was revealed to be an indicator of the infiltration level of immune cells and predicted the response outcomes of immunotherapy. The positive correlation between TIIClnc signature and CD8, PD-1 and PD-L1 was verified in the Xiangya in-house dataset. As a newly demonstrated predictive biomarker, the TIIClnc signature enabled a more precise selection of the GBM population who would benefit from immunotherapy and should be validated and applied in the near future.

Define cancer-associated fibroblasts (CAFs) in the tumor microenvironment: new opportunities in cancer immunotherapy and advances in clinical trials.

Despite centuries since the discovery and study of cancer, cancer is still a lethal and intractable health issue worldwide. Cancer-associated fibroblasts (CAFs) have gained much attention as a pivotal component of the tumor microenvironment. The versatility and sophisticated mechanisms of CAFs in facilitating cancer progression have been elucidated extensively, including promoting cancer angiogenesis and metastasis, inducing drug resistance, reshaping the extracellular matrix, and developing an immunosuppressive microenvironment. Owing to their robust tumor-promoting function, CAFs are considered a promising target for oncotherapy. However, CAFs are a highly heterogeneous group of cells. Some subpopulations exert an inhibitory role in tumor growth, which implies that CAF-targeting approaches must be more precise and individualized. This review comprehensively summarize the origin, phenotypical, and functional heterogeneity of CAFs. More importantly, we underscore advances in strategies and clinical trials to target CAF in various cancers, and we also summarize progressions of CAF in cancer immunotherapy.

Glioma targeted therapy: insight into future of molecular approaches.

Gliomas are the common type of brain tumors originating from glial cells. Epidemiologically, gliomas occur among all ages, more often seen in adults, which males are more susceptible than females. According to the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), standard of care and prognosis of gliomas can be dramatically different. Generally, circumscribed gliomas are usually benign and recommended to early complete resection, with chemotherapy if necessary. Diffuse gliomas and other high-grade gliomas according to their molecule subtype are slightly intractable, with necessity of chemotherapy. However, for glioblastoma, feasible resection followed by radiotherapy plus temozolomide chemotherapy define the current standard of care. Here, we discuss novel feasible or potential targets for treatment of gliomas, especially IDH-wild type glioblastoma. Classic targets such as the p53 and retinoblastoma (RB) pathway and epidermal growth factor receptor (EGFR) gene alteration have met failure due to complex regulatory network. There is ever-increasing interest in immunotherapy (immune checkpoint molecule, tumor associated macrophage, dendritic cell vaccine, CAR-T), tumor microenvironment, and combination of several efficacious methods. With many targeted therapy options emerging, biomarkers guiding the prescription of a particular targeted therapy are also attractive. More pre-clinical and clinical trials are urgently needed to explore and evaluate the feasibility of targeted therapy with the corresponding biomarkers for effective personalized treatment options.

Causal relationship and shared genes between air pollutants and amyotrophic lateral sclerosis: A large-scale genetic analysis.

OBJECTIVE: Air pollutants have been reported to have a potential relationship with amyotrophic lateral sclerosis (ALS). The causality and underlying mechanism remained unknown despite several existing observational studies. We aimed to investigate the potential causality between air pollutants (PM2.5, NOX, and NO2) and the risk of ALS and elucidate the underlying mechanisms associated with this relationship. METHODS: The data utilized in our study were obtained from publicly available genome-wide association study data sets, in which single nucleotide polymorphisms (SNPs) were employed as the instrumental variantswith three principles. Two-sample Mendelian randomization and transcriptome-wide association (TWAS) analyses were conducted to evaluate the effects of air pollutants on ALS and identify genes associated with both pollutants and ALS, followed by regulatory network prediction. RESULTS: We observed that exposure to a high level of PM2.5 (OR: 2.40 [95% CI: 1.26-4.57], p = 7.46E-3) and NOx (OR: 2.35 [95% CI: 1.32-4.17], p = 3.65E-3) genetically increased the incidence of ALS in MR analysis, while the effects of NO2 showed a similar trend but without sufficient significance. In the TWAS analysis, TMEM175 and USP35 turned out to be the genes shared between PM2.5 and ALS in the same direction. CONCLUSION: Higher exposure to PM2.5 and NOX might causally increase the risk of ALS. Avoiding exposure to air pollutants and air cleaning might be necessary for ALS prevention.

The tertiary lymphoid structure-related signature identified PTGDS in regulating PD-L1 and promoting the proliferation and migration of glioblastoma.

Background: Tertiary lymphoid structure (TLS) is a unique organ that carries out tumor cell elimination at tumor sites. It is continuously stimulated by inflammatory tumor signals and has been found to augment immunotherapy response. However, the detailed mechanisms behind it still need to be defined. Methods: To explore and grasp the whole picture of TLS from a pan-cancer view, we collected nine TLS-related genes from previous studies. We performed a comprehensive analysis of 9637 samples across 33 tumor types accessed from The Cancer Genome Atlas (TCGA) database. EdU, Transwell, and flow cytometry were performed on the feature gene PTGDS in U251 cells. The regulatory role of PTGDS on PD-L1 expression and macrophage polarization was verified. Results: Alteration analysis showed that mutations of TLS-related genes were widespread and relatively high. Clustering analysis based on the expression of these nine genes obtained two distinct clusters, with high EIF1AY and PTGDS in cluster 2 and better overall survival in cluster 1. To distinguish the two clusters, we utilized six machine learning algorithms and filtrated EIF1AY, PTGDS, SKAP1, and RBP5 as the characteristic genes, among which the former two genes were proved to be hazardous. PTGDS was found to regulate PD-L1 expression and also promoted the proliferation and migration of U251 cells. The knockdown of PTGDS could reduce the migration of macrophages and inhibit the polarization of macrophages into M2-phenotype. In addition, we established a TLS score to demonstrate patients' TLS activity. The low TLS-score group overlapped with cluster 1 and displayed a better prognosis. Besides, the low TLS-score group was related to better immunotherapy responses. The HE staining of histopathological sections confirmed that the low TLS-score group exhibited higher infiltration of immune cells. Conclusion: This study reveals broad molecular, tumorigenic, and immunogenic signatures for further functional and therapeutic studies of tertiary lymphoid structure. The TLS score we established effectively predicted immunotherapy response and patients' survival. Its future application and combination await more research.

Beyond the Gut: The intratumoral microbiome's influence on tumorigenesis and treatment response.

The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co-metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3-kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/ß-catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti-tumor immunity, pro-tumor immunity, and microbial-derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM-related mechanisms and TM-based treatment in cancer.

The causal effect of air pollution on the risk of essential hypertension: a Mendelian randomization study.

Background: Air pollution poses a major threat to human health by causing various illnesses, such as cardiovascular diseases. While plenty of research indicates a correlation between air pollution and hypertension, a definitive answer has yet to be found. Methods: Our analyses were performed using the Genome-wide association study (GWAS) of exposure to air pollutants from UKB (PM2.5, PM10, NO2, and NOX; n = 423,796 to 456,380), essential hypertension from FinnGen (42,857 cases and 162,837 controls) and from UKB (54,358 cases and 408,652 controls) as a validated cohort. Univariable and multivariable Mendelian randomization (MR) were conducted to investigate the causal relationship between air pollutants and essential hypertension. Body mass index (BMI), alcohol intake frequency, and the number of cigarettes previously smoked daily were included in multivariable MRs (MVMRs) as potential mediators/confounders. Results: Our findings suggested that higher levels of both PM2.5 (OR [95%CI] per 1 SD increase in predicted exposure = 1.24 [1.02-1.53], p = 3.46E-02 from Finn; OR [95%CI] = 1.04 [1.02-1.06], p = 7.58E-05 from UKB) and PM10 (OR [95%CI] = 1.24 [1.02-1.53], p = 3.46E-02 from Finn; OR [95%CI] = 1.04 [1.02-1.06], p = 7.58E-05 from UKB) were linked to an increased risk for essential hypertension. Even though we used MVMR to adjust for the impacts of smoking and drinking on the relationship between PM2.5 exposure and essential hypertension risks, our findings suggested that although there was a direct positive connection between them, it is not present after adjusting BMI (OR [95%CI] = 1.05 [0.87-1.27], p = 6.17E-01). Based on the study, higher exposure to PM2.5 and PM10 increases the chances of developing essential hypertension, and this influence could occur through mediation by BMI. Conclusion: Exposure to both PM2.5 and PM10 is thought to have a causal relationship with essential hypertension. Those impacted by substantial levels of air pollution require more significant consideration for their cardiovascular health.

Patient-derived xenograft models in cancer therapy: technologies and applications.

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

RUNX1/CD44 axis regulates the proliferation, migration, and immunotherapy of gliomas: A single-cell sequencing analysis.

Background: Glioma is one of the most common, primary, and lethal adult brain tumors because of its extreme aggressiveness and poor prognosis. Several recent studies relevant to the immune function of CD44, a transmembrane glycoprotein as a significant hyaluronic acid receptor, have achieved great success, revealing the critical role of CD44 in immune infiltration in gliomas. The overexpression of CD44 has been verified to correlate with cancer aggressiveness and migration, while the clinical and immune features of CD44 expression have not yet been thoroughly characterized in gliomas. Methods: Molecular and clinical data of glioma collected from publicly available genomic databases were analyzed. Results: CD44 was up-expressed in malignant gliomas, notably in the 1p/19q non-codeletion cases, isocitrate dehydrogenase (IDH) wild-type, and mesenchymal subtypes in GBM samples. CD44 expression level strongly correlates with stromal and immune cells, mainly infiltrating the glioma microenvironment by single-cell sequencing analysis. Meanwhile, CD44 can be a promising biomarker in predicting immunotherapy responses and mediating the expression of PD-L1. Finally, RUNX1/CD44 axis could promote the proliferation and migration of gliomas. Conclusions: Therefore, CD44 was responsible for glioma growth and progression. It could potentially lead to a novel target for glioma immunotherapy or a prognostic biomarker.

ROS-scavenging nanomedicine for "multiple crosstalk" modulation in non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a chronic inflammatory disease characterized by "multiple crosstalk" paths of insulin resistance, lipid metabolism, oxidative stress, etc. The combination of LY294002 and oridonin was proposed as a promising therapy by targeting insulin-PI3K/AKT signaling and NF-κB inflammatory pathway. However, due to oxidative stress, disease-associated upregulation of murine CYP3A11 activity can contribute to unexpected drug metabolism and disposition, which could seriously hinder the efficacy of LY294002 and oridonin. Nanotechnology-based effective reactive oxygen species (ROS) scavengers have emerged as a promising strategy to overcome these limitations. In this study, a rationally designed ROS-responsive liposome loaded with oridonin and LY294002 (RLLs) was developed for effective liver deposition and metabolic regulation for NAFLD treatment. First, we ascertained that the insulin resistance-induced signaling response was balanced by the combination of LY294002 and oridonin. Then, the particle size, zeta potential, ROS-responsive release behavior, and ROS-scavenging properties were investigated. Moreover, the CCl4-exposed mouse model was used to assess the biodistribution and therapeutic efficacy of RLLs on NAFLD. Finally, the "multiple crosstalk" modulation of RLLs was explored by western blotting, enzyme-linked immunosorbent assay, and polymerase chain reaction analysis. RLLs exhibited antioxidant efficacy for the safe delivery of LY294002 and oridonin with good stability and biocompatibility. The biodistribution analysis proved that the accumulation of RLLs was significantly increased due to CD44-mediated targeting. In addition, RLLs had comprehensive protective effects on the CCl4-exposed mouse model, leading to significant elimination of excessive ROS, maintenance of insulin sensitivity and CYP450 activity, and reduction of inflammatory response. In the CCl4-induced mice, RLL intervention remarkably improved metabolic profiles and reduced the fibrosis lesions. Our results provided a strategy for the amelioration of oxidative stress and CYP450 activity using ROS-responsive thioketal as an antioxidant adjuvant facilitated by nanotechnology.

A cancer-associated fibroblast subtypes-based signature enables the evaluation of immunotherapy response and prognosis in bladder cancer.

Bladder cancer (BLCA) is one of the most prevalent and heterogeneous urinary malignant tumors. Previous researches have reported a significant association between cancer-associated fibroblasts (CAFs) and poor prognosis of tumor patients. However, uncertainty surrounds the role of CAFs in the BLCA tumor microenvironment, necessitating further investigation into the CAFs-related gene signatures in BLCA. In this study, we identified three CAF subtypes in BLCA according to single-cell RNA-seq data and constructed CAFs-related risk score (CRRS) by screening 102,714 signatures. The survival analysis, ROC curves, and nomogram suggested that CRRS was a valuable predictor in 2,042 patients from 9 available public datasets and Xiangya real-world cohort. We further revealed the significant correlation between CRRS and clinicopathological characteristics, genome alterations, and epithelial-mesenchymal transition (EMT). A high CRRS indicated a non-inflamed phenotype and a lower remission rate of immunotherapy in BLCA. In conclusion, the CRRS had the potential to predict the prognosis and immunotherapy response of BLCA patients.

An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms.

The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.

Corrigendum: Antigen Presentation Machinery Signature-Derived CALR Mediates Migration, Polarization of Macrophages in Glioma and Predicts Immunotherapy Response.

[This corrects the article DOI: 10.3389/fimmu.2022.833792.].

A Novel Thrombosis-Related Signature for Predicting Survival and Drug Compounds in Glioblastoma.

Glioblastoma is the most common primary tumor in the central nervous system, and thrombosis-associated genes are related to its occurrence and progression. Univariate Cox and LASSO regression analysis were utilized to develop a new prognostic signature based on thrombosis-associated genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and HALLMARK were used for functional annotation of risk signature. ESTIMATE, MCP-counter, xCell, and TIMER algorithms were used to quantify immune infiltration in the tumor microenvironment. Genomics of Drug Sensitivity in Cancer (GDSC) was used for selecting potential drug compounds. Risk signature based on thrombosis-associated genes shows moderate performance in prognosis prediction. The functional annotation of the risk signature indicates that the signaling pathways related to the cell cycle, apoptosis, tumorigenesis, and immune suppression are rich in the high-risk group. Somatic mutation analysis shows that tumor-suppressive gene TP53 and oncogene PTEN have higher expression in low-risk and high-risk groups, respectively. Potential drug compounds are explored in risk score groups and show higher AUC values in the low-risk score group. A nomogram with valuable prognostic factors exhibits high sensitivity in predicting the survival outcome of GBM patients. Our research screens out multiple thromboses-associated genes with remarkable clinical significance in GBM and further develops a meaningful prognostic risk signature predicting drug sensitivity and survival outcome.

Antigen Presentation Machinery Signature-Derived CALR Mediates Migration, Polarization of Macrophages in Glioma and Predicts Immunotherapy Response.

Immunogenicity, influenced by tumor antigenicity and antigen presenting efficiency, critically determines the effectiveness of immune checkpoint inhibitors. The role of immunogenicity has not been fully elucidated in gliomas. In this study, a large-scale bioinformatics analysis was performed to analyze the prognostic value and predictive value of antigen presentation machinery (APM) signature in gliomas. ssGSEA algorithm was used for development of APM signature and LASSO regression analysis was used for construction of APM signature-based risk score. APM signature and risk score showed favorable performance in stratifying survival and predicting tumorigenic factors of glioma patients. APM signature and risk score were also associated with different genomic features in both training cohort TCGA and validating cohort CGGA. Furthermore, APM signature-based risk score was independently validated in three external cohorts and managed to predict immunotherapy response. A prognostic nomogram was constructed based on risk score. Risk score-derived CALR was found to mediate the invasion and polarization of macrophages based on the coculture of HMC3 and U251 cells. CALR could significantly predict immunotherapy response. In conclusion, APM signature and APM signature-based risk score could help promote the clinical management of gliomas.

Identify the immune characteristics and immunotherapy value of CD93 in the pan-cancer based on the public data sets.

CD93 is a transmembrane receptor that is mainly expressed on endothelial cells. A recent study found that upregulated CD93 in tumor vessels is essential for tumor angiogenesis in several cancers. However, the underlying mechanisms are largely unexplored. Our present research systematically analyzed the characteristics of CD93 in tumor immunotherapy among 33 cancers. CD93 levels and co-expression of CD93 on cancer and stromal cells were detected using public databases and multiple immunofluorescence staining. The Kaplan-Meier (KM) analysis identified the predictive role of CD93 in these cancer types. The survival differences between CD93 mutants and WT, CNV groups, and methylation were also investigated. The immune landscape of CD93 in the tumor microenvironment was analyzed using the SangerBox, TIMER 2.0, and single-cell sequencing. The immunotherapy value of CD93 was predicted through public databases. CD93 mRNA and protein levels differed significantly between cancer samples and adjacent control tissues in multiply cancer types. CD93 mRNA expression associated with patient prognosis in many cancers. The correlation of CD93 levels with mutational status of other gene in these cancers was also analyzed. CD93 levels significantly positively related to three scores (immune, stromal, and extimate), immune infiltrates, immune checkpoints, and neoantigen expression.. Additionally, single-cell sequencing revealed that CD93 is predominantly co-expressed on tumor and stromal cells, such as endothelial cells, cancer-associated fibroblasts (CAFs), neutrophils, T cells, macrophages, M1 and M2 macrophages. Several immune-related signaling pathways were enriched based on CD93 expression, including immune cells activation and migration, focal adhesion, leukocyte transendothelial migration, oxidative phosphorylation, and complement. Multiple immunofluorescence staining displayed the relationship between CD93 expression and CD8, CD68, and CD163 in these cancers. Finally, the treatment response of CD93 in many immunotherapy cohorts and sensitive small molecules was predicted from the public datasets. CD93 expression is closely associated with clinical prognosis and immune infiltrates in a variety of tumors. Targeting CD93-related signaling pathways in the tumor microenvironment may be a novel therapeutic strategy for tumor immunotherapy.

Identify the Prognostic and Immune Profile of VSIR in the Tumor Microenvironment: A Pan-Cancer Analysis.

VSIR is a critical immunomodulatory receptor that inhibits T cell effector function and maintains peripheral tolerance. However, the mechanism by which VSIR participates in tumor immunity in the pan-cancer tumor microenvironment remains unclear. This study systematically explored the prognostic and immune profile of VSIR in the tumor microenvironment of 33 cancers. We compared the expression patterns and molecular features of VSIR in the normal and cancer samples both from the public databases and tumor chips. VSIR level was significantly related to patients' prognosis and could be a promising predictor in many tumor types, such as GBM, KIRC, SKCM, READ, and PRAD. Elevated VSIR was closely correlated with infiltrated inflammatory cells, neoantigens expression, MSI, TMB, and classical immune checkpoints in the tumor microenvironment. Enrichment signaling pathways analysis indicated VSIR was involved in several immune-related pathways such as activation, proliferation, and migration of fibroblast, T cell, mast cell, macrophages, and foam cell. In addition, VSIR was found to widely express on cancer cells, fibroblasts, macrophages, and T cells in many tumor types based on the single-cell sequencing analysis and co-express with M2 macrophage markers CD68, CD163 based on the immunofluorescence staining. Finally, we predicted the sensitive drugs targeting VSIR and the immunotherapeutic value of VSIR. In sum, VSIR levels strongly correlated with the clinical outcome and tumor immunity in multiple cancer types. Therefore, therapeutic strategies targeting VSIR in the tumor microenvironment may be valuable tools for cancer immunotherapy.