Novel Immune Infiltrating Cell Signature Based on Cell Pair Algorithm Is a Prognostic Marker in Cancer

Comprehensive pan‑cancer analysis of MTDH for human tumor prognosis and as an immunological biomarker including breast and kidney cancer

Metadherin (MTDH), initially discovered in primary astrocytes of the human fetus through rapid subtraction hybridization and labeled as astrocyte elevated gene-1, represents a widely recognized oncogene present in multiple types of cancers. However, the role of MTDH in different types of cancer remains unclear. To address this, a comprehensive analysis of MTDH across various types of cancers was conducted by utilizing multiple databases such as The Cancer Genome Atlas. The present analysis discovered that MTDH exhibits differential expression in different types of cancer and is associated with important factors including tumor mutational burden and microsatellite instability. These findings highlighted the significance of MTDH in the tumor microenvironment and its involvement in the development of immune cells in specific cancers. Furthermore, the results of the present study indicated that the expression of MTDH is strongly correlated with clinical prognosis, mutations and immune cell infiltration. MTDH could serve as a potential indicator of patient prognosis and potentially play a role in modulating the immune system. Given its potential as a novel immunological checkpoint, MTDH may be a viable target for tumor immunotherapy.

The prognostic and immunological role of MCM3 in pan-cancer and validation of prognosis in a clinical lower-grade glioma cohort

Background: Previous studies have shown that MCM3 plays a key role in initiating DNA replication. However, the mechanism of MCM3 function in most cancers is still unknown. The aim of our study was to explore the expression, prognostic role, and immunological characteristics of MCM3 across cancers. Methods: We explored the expression pattern of MCM3 across cancers. We subsequently explored the prognostic value of MCM3 expression by using univariate Cox regression analysis. Spearman correlation analysis was performed to determine the correlations between MCM3 and immune-related characteristics, mismatching repair (MMR) signatures, RNA modulator genes, cancer stemness, programmed cell death (PCD) gene expression, tumour mutation burden (TMB), microsatellite instability (MSI), and neoantigen levels. The role of MCM3 in predicting the response to immune checkpoint blockade (ICB) therapy was further evaluated in four immunotherapy cohorts. Single-cell data from CancerSEA were analysed to assess the biological functions associated with MCM3 in 14 cancers. The clinical correlation and independent prognostic significance of MCM3 were further analysed in the TCGA and CGGA lower-grade glioma (LGG) cohorts, and a prognostic nomogram was constructed. Immunohistochemistry in a clinical cohort was utilized to validate the prognostic utility of MCM3 expression in LGG. Results: MCM3 expression was upregulated in most tumours and strongly associated with patient outcomes in many cancers. Correlation analyses demonstrated that MCM3 expression was closely linked to immune cell infiltration, immune checkpoints, MMR genes, RNA modulator genes, cancer stemness, PCD genes and the TMB in most tumours. There was an obvious difference in outcomes between patients with high MCM3 expression and those with low MCM3 expression in the 4 ICB treatment cohorts. Single-cell analysis indicated that MCM3 was mainly linked to the cell cycle, DNA damage and DNA repair. The expression of MCM3 was associated with the clinical features of LGG patients and was an independent prognostic indicator. Finally, the prognostic significance of MCM3 in LGG was validated in a clinical cohort. Conclusion: Our study suggested that MCM3 can be used as a potential prognostic marker for cancers and may be associated with tumour immunity. In addition, MCM3 is a promising predictor of immunotherapy responses.

A novel immune cell signature for predicting glioblastoma after radiotherapy prognosis and guiding therapy

Background: Glioblastoma, a highly aggressive brain tumor, poses a significant clinical challenge, particularly in the context of radiotherapy. In this study, we aimed to explore infiltrating immune cells and identify immune-related genes associated with glioblastoma radiotherapy prognosis. Subsequently, we constructed a signature based on these genes to discern differences in molecular and tumor microenvironment immune characteristics, ultimately informing potential therapeutic strategies for patients with varying risk profiles. Methods: We leveraged UCSC Xena and CGGA gene expression profiles from post-radiotherapy glioblastoma as verification cohorts. Infiltration ratios were stratified into high and low groups based on the median value. Differential gene expression was determined through Limma differential analysis. A signature comprising four genes was constructed, guided by Gene Ontology (GO) functional enrichment results and Kaplan-Meier survival analysis. We evaluated differences in cell infiltration levels, Immune Score, Stromal Score, and ESTIMATE Score and their Pearson correlations with the signature. Spearman's correlation was computed between the signature and patient drug sensitivity (IC50), predicted using Genomics of Drug Sensitivity in Cancer (GDSC) and CCLE databases. Results: Notably, the infiltration of central memory CD8+T cells exhibited a significant correlation with glioblastoma radiotherapy prognosis. Samples were dichotomized into high- and low-risk groups based on the optimal signature threshold (2.466642). Kaplan-Meier (K-M) survival analysis revealed that the high-risk group experienced a significantly poorer prognosis (p = .0068), with AUC values exceeding 0.82 at 1, 3, and 5 years, underscoring the robust predictive potential of the signature scoring system. Independent validation sets substantiated the validity of the signature. Statistically significant differences in tumor microenvironments (p < .05) were observed between high- and low-risk groups, and these differences were significantly correlated with the signature (p < .05). Furthermore, there were significant correlations between high and low-risk groups regarding immune checkpoint expressions, Immune Prognostic Score (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores. Conclusion: The immune cell signature, comprising SDC-1, PLAUR, FN1, and CXCL13, holds promise as a predictive tool for assessing glioblastoma prognosis following radiotherapy. This signature also offers valuable guidance for tailoring treatment strategies, emphasizing its potential clinical relevance in improving patient outcomes.

Pan-cancer and single-cell analysis reveal the prognostic value and immune response of NQO1

Background: Overexpression of the NAD(P)H: Quinone Oxidoreductase 1 (NQOI) gene has been linked with tumor progression, aggressiveness, drug resistance, and poor patient prognosis. Most research has described the biological function of the NQO1 in certain types and limited samples, but a comprehensive understanding of the NQO1's function and clinical importance at the pan-cancer level is scarce. More research is needed to understand the role of NQO1 in tumor infiltration, and immune checkpoint inhibitors in various cancers are needed. Methods: The NQO1 expression data for 33 types of pan-cancer and their association with the prognosis, pathologic stage, gender, immune cell infiltration, the tumor mutation burden, microsatellite instability, immune checkpoints, enrichment pathways, and the half-maximal inhibitory concentration (IC50) were downloaded from public databases. Results: Our findings indicate that the NQO1 gene was significantly upregulated in most cancer types. The Cox regression analysis showed that overexpression of the NQO1 gene was related to poor OS in Glioma, uveal melanoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma, and adrenocortical carcinoma. NQO1 mRNA expression positively correlated with infiltrating immune cells and checkpoint molecule levels. The single-cell analysis revealed a potential relationship between the NQO1 mRNA expression levels and the infiltration of immune cells and stromal cells in bladder urothelial carcinoma, invasive breast carcinoma, and colorectal cancer. Conversely, a negative association was noted between various drugs (17-AAG, Lapatinib, Trametinib, PD-0325901) and the NQO1 mRNA expression levels. Conclusion: NQO1 expression was significantly associated with prognosis, immune infiltrates, and drug resistance in multiple cancer types. The inhibition of the NQO1-dependent signaling pathways may provide a promising strategy for developing new cancer-targeted therapies.

Pan-cancer analysis of the immune aspects and prognostic value of NCAPG2

NCAPG2 has been reported to be associated with tumorigenesis in various types of cancer. However, data on the pathological mechanisms of NCAPG2 in pan-cancers remain lacking. Therefore, the study aimed to comprehensively elucidate the immune characteristics and prognostic of NCAPG2 in tumor microenvironments (TMEs). NCAPG2 was overexpressed in many tumor types, and this overexpression is related to poor clinical stages and prognosis. Furthermore, elevated NCAPG2 expression was strongly associated with TMEs. Moreover, gene set enrichment analysis was performed to investigate the pathways associated with NCAPG2, revealing its involvement in several immune-related pathways. Finally, we predicted the immunotherapeutic value and sensitivity to drugs based on NCAPG2 expression. Our study revealed that NCAPG2 could be utilized as an immune-related biomarker for both diagnosing and predicting the prognosis of multiple cancer types. Therefore, our findings suggest that targeting NCAPG2 in TMEs could be a promising therapeutic strategy.

Cuproptosis-related classification and personalized treatment in lower-grade gliomas to prompt precise oncology

BACKGROUND

Cuproptosis is implicated in regulating tricarboxylic acid cycle and associated with tumor therapeutic sensitivity, patient outcomes and tumorigenesis. However, the classification and prognostic effect of cuproptosis-associated genes (CAGs), the relationship between cuproptosis and tumor microenvironment (TME) and the treatment of lower-grade glioma (LrGG) remain enigmatic.

METHODS

The genetic and transcriptional alterations, prognostic value and classification related to cuproptosis were systematically analyzed. Subtypes of cuproptosis and cuproptosis score (Cuscore) were constructed and further confirmed by two external cohorts. The relationships between cuproptosis and TME, prognosis, and treatment response were also evaluated.

RESULTS

Four clusters were identified based on cuproptosis-associated genes. The associations between cuproptosis-associated clusters and clinical features, prognosis, immune cell infiltration, and chemotherapy sensitivity were observed. The Cuscore is an independent prognostic indicator in LrGG patients. The nomogram is constructed according to Cuscore and clinical characteristics, and has good predictive ability and calibration. Patients with high Cuscore had a worse prognosis and advanced performance. A higher Cuscore also indicated a higher stromal score, abundant immune infiltration, and increased tumor mutation burden. A high Cuscore was remarkably related to immune checkpoint inhibitors, immunotherapy response and immune phenotype.

CONCLUSIONS

This study demonstrates the clinical effect of CAGs, and suggests that cuproptosis could be a potential therapeutic target in LrGG.

Pancancer Analysis Revealed the Value of RAC2 in Immunotherapy and Cancer Stem Cell

Objective

To investigate the oncogenic effect and clinical significance of RAC2 in pancarcinoma from the perspective of tumor immunity and cancer stem cell.

Methods

After in-depth mining of TCGA, GEO, UCSC, and other databases, basic information of the RAC2 gene and its expression in tumor tissues as well as the relationship between RAC2 and tumor were analyzed based on survival, mutation, immune microenvironment, tumor stemness, and enrichment analysis on related pathways.

Results

RAC2 mRNA expression was increased in most tumor tissues and was associated with their prognosis. Compared to normal tissues, the RAC2 mutation rate was higher in patients with skin melanoma, uterine sarcoma, and endometrial cancer. RAC2 had a strong relation with immune cell infiltration, immunomodulators, immunotherapy markers, cancer stem cell of THYM, and immune-related pathways.

Conclusions

This study explored the potential importance of RAC2 in the prognosis, immunotherapy, and cancer stem cell of 33 cancers, laying the foundation for mechanistic experiments and its future application in clinical practice. However, the results using bioinformatics methods could be affected by the differences in patients across databases. Thus, the present results were preliminary and required further experimental validation.

Tumor-secreted lactate contributes to an immunosuppressive microenvironment and affects CD8 T-cell infiltration in glioblastoma

Introduction

Glioblastoma is a malignant brain tumor with poor prognosis. Lactate is the main product of tumor cells, and its secretion may relate to immunocytes' activation. However, its role in glioblastoma is poorly understood.

Methods

This work performed bulk RNA-seq analysis and single cell RNA-seq analysis to explore the role of lactate in glioblastoma progression. Over 1400 glioblastoma samples were grouped into different clusters according to their expression and the results were validated with our own data, the xiangya cohort. Immunocytes infiltration analysis, immunogram and the map of immune checkpoint genes' expression were applied to analyze the potential connection between the lactate level with tumor immune microenvironment. Furthermore, machine learning algorithms and cell-cell interaction algorithm were introduced to reveal the connection of tumor cells with immunocytes. By co-culturing CD8 T cells with tumor cells, and performing immunohistochemistry on Xiangya cohort samples further validated results from previous analysis.

Discussion

In this work, lactate is proved that contributes to glioblastoma immune suppressive microenvironment. High level of lactate in tumor microenvironment can affect CD8 T cells' migration and infiltration ratio in glioblastoma. To step further, potential compounds that targets to samples from different groups were also predicted for future exploration.

Single-Cell Sequencing Reveals Necroptosis-Related Prognostic Genes of Glioblastoma

Background

Glioblastoma (GBM) is one of the most malignant forms of brain cancer, with the extremely lower survival rate. Necroptosis (NCPS) is also one of the most wide types of cell death, and its clinical importance in GBM is not clear.

Methods

We first identified necroptotic genes in GBM by single-cell RNA sequencing analysis of our surgical samples and weighted coexpression network analysis (WGNCA) from TCGA GBM data. The cox regression model with least absolute shrinkage and selection operator (LASSO) was used to construct the risk model. Then, KM plot and reactive operation curve (ROC) analysis were used to assess the prediction ability of the model. At last, the infiltrated immune cells and gene mutation profiling were investigated between the high- and low-NCPS groups as well.

Result

The risk model including ten necroptosis-related genes was identified as an independent risk factor for the outcome. In addition, we found that the risk model is correlated with the infiltrated immune cells and tumor mutation burden in GBM. NDUFB2 is identified to be a risk gene in GBM with bioinformatical analysis and in vitro experiment validation.

Conclusion

This risk model of necroptosis-related genes might provide clinical evidence for GBM interventions.

Cell Pair Algorithm-Based Immune Infiltrating Cell Signature for Improving Outcomes and Treatment Responses in Patients with Hepatocellular Carcinoma

BACKGROUND

Immune interactions play important roles in the regulation of T cells' cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. A comprehensive analysis of immune cell types in HCC and immune-cell-related signatures predicting prognosis and monitoring immunotherapy efficacy is still absent.

METHODS

More than 1,300 hepatocellular carcinomas (HCC) patients were collected from public databases and included in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 28 immunocyte subpopulations. A cell pair algorithm was applied to construct an immune-cell-related prognostic index (ICRPI). Survival analyses were performed to measure the survival difference across ICRPI risk groups. Spearman's correlation analyses were used for the relevance assessment. A Wilcoxon test was used to measure the expression level's differences.

RESULTS

In this study, 28 immune subpopulations were retrieved, and 374 immune cell pairs (ICPs) were established, 38 of which were picked out by the least absolute shrinkage and selection operator (LASSO) algorithm. By using the selected ICPs, the ICRPI was constructed and validated to play crucial roles in survival stratification and dynamic monitoring of immunotherapy effect. We also explored several candidate drugs targeting ICRPI. A composite ICRPI and clinical prognostic index (ICPI) was then constructed, which achieved a more accurate estimation of HCC's survival and is a better choice for prognosis predictions in HCC.

CONCLUSIONS

In conclusion, we constructed and validated ICRPI based on the cell pair algorithm in this study, which might provide some novel insights for increasing the survival estimation and clinical response to immune therapy for individual HCC patients and contribute to the personalized precision immunotherapy strategy of HCC.

Novel exosome-related risk signature as prognostic biomarkers in glioblastoma

Exosomes are progressively being detected as an indicator for the diagnosis and prognosis of cancer in clinical settings. Many clinical trials have confirmed the impact of exosomes on tumor growth, particularly in anti-tumor immunity and immunosuppression of exosomes. Therefore, we developed a risk score based on genes found in glioblastoma-derived exosomes. In this study, we used the TCGA dataset as the training queue and GSE13041, GSE43378, GSE4412, and CGGA datasets as the external validation queue. Based on machine algorithms and bioinformatics methods, an exosome-generalized risk score was established. We found that the risk score could independently predict the prognosis of patients with glioma, and there were significant differences in the outcomes of patients in the high- and low-risk groups. Univariate and multivariate analyses showed that risk score is a valid predictive biomarker for gliomas. Two immunotherapy datasets, IMvigor210 and GSE78220, were obtained from previous studies. A high-risk score showed a significant association with multiple immunomodulators that could act on cancer immune evasion. The exosome-related risk score could predict the effectiveness of anti-PD-1 immunotherapy. Moreover, we compared the sensitivity of patients with high- and low-risk scores to various anti-cancer drugs and found that patients with high-risk scores had better responses to a variety of anti-cancer drugs. The risk-scoring model established in this study provides a useful tool to predict the total survival time of patients with glioma and guide immunotherapy.

A pan-cancer and single-cell sequencing analysis of CD161, a promising onco-immunological biomarker in tumor microenvironment and immunotherapy

Background

CD161 has been linked to the appearance and development of various cancers.

Methods

The mutation map and the variation of CNVs and SNVs of CD161 were displayed according to cBioportal and GSCALite. We also evaluated the pathway enrichment and drug sensitivity of CD161 according to GSCALite. We performed a single-cell sequencing analysis of cancer cells and T cells in melanoma. The cell communication patterns related to CD161 were further explored. Multiplex immunofluorescence staining of tissue microarrays was used to detect the association between CD161 expression and macrophages and T cells.

Results

A high CD161 level was related to neoantigens expression, pathway enrichment, and drug sensitivity. In addition, single-cell sequencing analysis showed that CD161 was mainly expressed in T cells, M1 and M2 Macrophages, neoplastic, microglial cells, neurons, and cancer cells in many tumor types. Further study on pseudotime trajectories and functional annotation of CD161 proved the critical role of CD161 in tumor progression and T cell immunity in melanoma. Multiplex immunofluorescence revealed that CD161 is closely correlated with the immune infiltration of T cells and macrophages in multiple cancers. In addition, high CD161 expression predicted a favorable immunotherapy response.

Conclusion

CD161 is involved in the immune infiltration of T cells and macrophages and might be a promising target for tumor immunotherapy.

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.

Multi-omics analysis of the oncogenic value of copper Metabolism-Related protein COMMD2 in human cancers

BACKGROUND

The copper metabolism MURR1 domain (COMMD) protein family is involved in tumorigenicity of malignant tumors. However, as the member of COMMD, the role of COMMD2 in human tumors remains unknown.

METHODS

We used The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA) database, Cancer Cell Line Encyclopedia (CCLE) platform, univariate Cox regression analysis, Kaplan-Meier curve, cBioPortal, UALCAN database, Sangerbox online platform, GSCA database gene set enrichment analysis (GSEA), and GeneMANIA to analyze the expression of COMMD2, its prognostic values, genomic alteration patterns, and the correlation with tumor stemness, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrates, drug sensitivity, and gene function enrichment in pan-cancer. qRT-PCR, CCK-8, EdU, wound healing, and transwell migration assays were performed to confirm the function of COMMD2.

RESULTS

COMMD2 was strongly expressed in most cancer types. Elevated COMMD2 expression affects the prognosis, clinicopathological stage, and molecular or immune subtypes of various tumors. Moreover, promoter hypomethylation and mutations in the COMMD2 gene may be associated with its high expression and poor survival. Additionally, we discovered that COMMD2 expression was linked to tumor stemness, TMB, MSI, immune cell infiltration, immune-checkpoint inhibitors, and drug sensitivity in pan-cancer. Furthermore, the COMMD2 gene co-expression network is constructed with GSEA analysis, displaying significant interaction of COMMD2 with E2F targets, G2-M checkpoint, and mitotic spindle in bladder cancer (BLCA). Finally, RNA interference data showed suppression of COMMD2 prevented proliferation and migration of BLCA and uterine corpus endometrial carcinoma (UCEC) cells.

CONCLUSION

Our findings shed light on the COMMD2 functions in human cancers and demonstrate that it is a promising prognostic biomarker and therapeutic target in pan-cancer.

Large-scale bulk RNA-seq analysis defines immune evasion mechanism related to mast cell in gliomas

Accumulating evidence has demonstrated that the immune cells have an emerging role in controlling anti-tumor immune responses and tumor progression. The comprehensive role of mast cell in glioma has not been illustrated yet. In this study, 1,991 diffuse glioma samples were collected from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). xCell algorithm was employed to define the mast cell-related genes. Based on mast cell-related genes, gliomas were divided into two clusters with distinct clinical and immunological characteristics. The survival probability of cluster 1 was significantly lower than that of cluster 2 in the TCGA dataset, three CGGA datasets, and the Xiangya cohort. Meanwhile, the hypoxic and metabolic pathways were active in cluster 1, which were beneficial to the proliferation of tumor cells. A potent prognostic model based on mast cell was constructed. Via machine learning, DRG2 was screened out as a characteristic gene, which was demonstrated to predict treatment response and predict survival outcome in the Xiangya cohort. In conclusion, mast cells could be used as a potential effective prognostic factor for gliomas.

Pericyte mediates the infiltration, migration, and polarization of macrophages by CD163/MCAM axis in glioblastoma

Microenvironment cells (MCs) play a critical role in tumor proliferation, progression, and metastasis. However, it has not been adequately addressed whether MCs could be used as a reliable prognostic marker in glioblastoma (GBM). In the current study, the cell pair (CP) score was constructed in 1137 GBM samples based on the cell pair algorithm and Gaussian finite mixture model (GMM) and was verified in 73 GBM samples from the Xiangya cohort. CP score predicted GBM patients’ survival and response to anti-PD-1 treatment with high sensitivity. Macrophage markers CD68 and CD163 were co-expressed with pericyte markers MCAM and MG2. Pericyte could mediate the infiltration, migration, and M2 type polarization of macrophages by MCAM. The CP score was a valuable tool for predicting survival outcomes and guiding immunotherapy for GBM patients. Cell pair pericyte/macrophage and gene pair CD163/MCAM were biologically significant in the tumor microenvironment of GBM.

•

We introduced a cell pair algorithm for developing a robust immune signature in GBM

•

The immune signature helps identify GBM patients with better immunotherapy responses

•

Macrophage/pericyte and CD163/MCAM significantly affected GBM patients’ survival

•

Pericytes mediate macrophage infiltration, migration, and M2 type polarization in GBM

Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Background

Cuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.

Methods

In this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).

Results

Two distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients' prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity-related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB.

Conclusion

Collectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients' therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

A Pan-Cancer Analysis Reveals CLEC5A as a Biomarker for Cancer Immunity and Prognosis

Background

CLEC5A is a member of the C-type lectin superfamily. It can activate macrophages and lead to a series of immune-inflammation reactions. Previous studies reveal the role of CLEC5A in infection and inflammation diseases.

Method

We acquire and analyze data from The Cancer Genome Atlas (TCGA) database, Genotype-Tissue Expression (GTEx) database, and other comprehensive databases via GSCALite, cBioPortal, and TIMER 2.0 platforms or software. Single-cell sequencing analysis was performed for quantifying the tumor microenvironment of several types of cancers.

Results

CLEC5A is differentially expressed in a few cancer types, of which overexpression accompanies low overall survival of patients. DNA methylation mainly negatively correlates with CLEC5A expression. Moreover, CLEC5A is positively related to immune infiltration, including macrophages, cancer-associated fibroblasts (CAFs), and regulatory T cells (Tregs). Immune checkpoint genes are significantly associated with CLEC5A expression in diverse cancers. In addition, CLEC5A expression correlates with mismatch repair (MMR) in several cancers. Tumor mutation burden (TMB), microsatellite instability (MSI), and neoantigens show a positive association with CLEC5A expression in several cancers. Furthermore, CLEC5A in cancer correlates with signal transduction, the immune system, EMT, and apoptosis process. The drug sensitivity analysis screens out potential therapeutic agents associated with CLEC5A expression, including FR-180204, Tivozanib, OSI-930, Linifanib, AC220, VNLG/124, Bexarotene, omacetaxine mepesuccinate, narciclasine, leptomycin B, PHA-793887, LRRK2-IN-1, and CR-1-31B.

Conclusion

CLEC5A overexpresses in multiple cancers in contrast to normal tissues, and high CLEC5A expression predicts poor prognosis of patients and immune infiltration. CLEC5A is a potential prognostic biomarker of diverse cancers and a target for anti-tumor therapy.

PTX3 mediates the infiltration, migration, and inflammation-resolving-polarization of macrophages in glioblastoma

Introduction

Pentraxin 3 (PTX3) is an essential regulator of the immune system. However, the immune‐modulatory role of PTX3 in the tumor microenvironment of glioma has not been elucidated.

Methods

The RNA seq samples were obtained from The Cancer Genome Atlas (TCGA) and the China Glioma Genome Atlas (CGGA) datasets. The single‐cell sequencing data of glioblastoma (GBM) samples were obtained from the Single Cell Portal platform (http://singlecell.broadinstitute.org). Immunohistochemistry was used to assess PTX3 expression, HAVCR2, PD‐1, PD‐L1, and CD276 in glioma sections from the Xiangya cohort (n = 60). Multiplex immunofluorescence staining of PTX3, CD68, and CD163 was performed in several solid cancer types, including GBM. HMC3 was cocultured with U251 and U87, and transwell assay and flow cytometry assay were performed to explore the migration and polarization activity of HMC3.

Results

PTX3 expression is significantly increased in GBM. PTX3 expression predicts worse survival in the Xiangya cohort. PTX3 is closely related to the expression of PD‐1, PD‐L1, CD276, and HAVCR2 in the tumor microenvironment. Additionally, PTX3 is involved in tumorigenic and immunogenic processes, especially the activity of macrophages based on various signaling pathways in cellular communications and critical transcription factors. Specifically, PTX3 actively mediates macrophages' infiltration, migration, and inflammation‐resolving‐polarization. PTX3 could also predict immunotherapy response.

Conclusion

PTX3 is critically involved in macrophage infiltration, migration, and inflammation‐resolving‐polarization and modulates an immunosuppressive microenvironment.

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.

Activation of the chemokine receptor 3 pathway leads to a better response to immune checkpoint inhibitors in patients with metastatic urothelial carcinoma

Immune checkpoint inhibitors (ICIs) have made important breakthrough in anti-tumor therapy, however, no single biomarker can accurately predict their efficacy. Studies have found that tumor microenvironment is a key factor for determining the response to ICI therapy. Cytokine receptor 3 (C-X-C Motif Chemokine Receptor 3, CXCR3) pathway has been reported to play an important role in the migration, activation, and response of immune cells. We analyzed survival data, genomics, and clinical data from patients with metastatic urothelial carcinoma (mUC) who received ICI treatment to explore the relationship between CXCR3 pathway activation and the effectiveness of ICIs. The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort and six other cohorts receiving ICI treatment were used for mechanism exploration and validation. In the ICI cohort, we performed univariate and multivariate COX analyses and discovered that patients in the CXCR3-high group were more sensitive to ICI treatment. A Kaplan–Meier analysis demonstrated that patients in the high CXCR3-high group had a better prognosis than those in the CXCR3-low group (P = 0.0001, Hazard Ratio = 0.56; 95% CI 0.42−0.75). CIBERSORT analysis found that mUC patients in the CXCR3-high group had higher levels of activated CD8+ T cells, M1 macrophages, and activated NK cells and less regulatory T cell (Treg) infiltration. Immunogenicity analysis showed the CXCR3-high group had higher tumor neoantigen burden (TNB). Our study suggests that CXCR3 pathway activation may be a novel predictive biomarker for the effectiveness of immunotherapy in mUC patients.

Large-Scale Single-Cell and Bulk Sequencing Analyses Reveal the Prognostic Value and Immune Aspects of CD147 in Pan-Cancer

CD147 plays an important role in promoting tumor proliferation and inhibiting cancer cell apoptosis in the tumor microenvironment. However, the mechanisms by which CD147 is involved in tumorigenesis remains unclear. This study systematically analyzed the prognostic value and immune characteristics of CD147 in 31 cancer types. The expression levels and mutant landscapes of CD147 in pan-cancer were explored. The Kaplan-Meier (KM) analysis was applied to analyze the prognostic value of CD147. The immune characteristics of CD147 in the tumor microenvironment were evaluated via TIMER 2.0 and R package (immunedeconv). We also explored the expression of CD147 on tumor cells and stromal cells through Gene Set Variation Analysis and single-cell sequencing analysis. The co-expression of CD147 and macrophage markers CD68 and CD163 in pan-cancer was detected using multiplex immunofluorescence staining on tissue microarrays. CD147 was found to be overexpressed in almost all cancer types, which was related to poor outcome. CD147 expression exhibited a strong association with immune infiltrates, immune checkpoint molecules, and neoantigen levels in the tumor microenvironment. In addition, CD147 was expressed on various cell types in the tumor microenvironment, including tumor cells, macrophages, T cells, monocytes, fibroblasts, etc. Furthermore, multiplex immunofluorescence revealed the co-expression pattern of CD147 and macrophage markers CD68 and CD163 in many tumor types. Finally, the immunotherapy response and sensitive small molecule drugs based on CD147 expression were predicted. In sum, CD147 has a significant relationship with the clinical outcome and immune infiltrates in multiple cancer types. Inhibiting the CD147-dependent signaling pathways might be a promising therapeutic strategy for tumor immunotherapy.

Pan-Cancer Analysis Shows That ALKBH5 Is a Potential Prognostic and Immunotherapeutic Biomarker for Multiple Cancer Types Including Gliomas

Background

AlkB homolog 5 (ALKBH5) is a N⁶-methyladenosine (m⁶A) demethylase associated with the development, growth, and progression of multiple cancer types. However, the biological role of ALKBH5 has not been investigated in pan-cancer datasets. Therefore, in this study, comprehensive bioinformatics analysis of pan-cancer datasets was performed to determine the mechanisms through which ALKBH5 regulates tumorigenesis.

Methods

Online websites and databases such as NCBI, UCSC, CCLE, HPA, TIMER2, GEPIA2, cBioPortal, UALCAN, STRING, SangerBox, ImmuCellAl, xCell, and GenePattern were used to extract data of ALKBH5 in multiple cancers. The pan-cancer patient datasets were analyzed to determine the relationship between ALKBH5 expression, genetic alterations, methylation status, and tumor immunity. Targetscan, miRWalk, miRDB, miRabel, LncBase databases and Cytoscape tool were used to identify microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that regulate expression of ALKBH5 and construct the lncRNA-miRNA-ALKBH5 network. In vitro CCK-8, wound healing, Transwell and M2 macrophage infiltration assays as well as in vivo xenograft animal experiments were performed to determine the biological functions of ALKBH5 in glioma cells.

Results

The pan-cancer analysis showed that ALKBH5 was upregulated in several solid tumors. ALKBH5 expression significantly correlated with the prognosis of cancer patients. Genetic alterations including duplications and deep mutations of the ALKBH5 gene were identified in several cancer types. Alterations in the ALKBH5 gene correlated with tumor prognosis. GO and KEGG enrichment analyses showed that ALKBH5-related genes were enriched in the inflammatory, metabolic, and immune signaling pathways in glioma. ALKBH5 expression correlated with the expression of immune checkpoint (ICP) genes, and influenced sensitivity to immunotherapy. We constructed a lncRNA-miRNA network that regulates ALKBH5 expression in tumor development and progression. In vitro and in vivo experiments showed that ALKBH5 promoted proliferation, migration, and invasion of glioma cells and recruited the M2 macrophage to glioma cells.

Conclusions

ALKBH5 was overexpressed in multiple cancer types and promoted the development and progression of cancers through several mechanisms including regulation of the tumor-infiltration of immune cells. Our study shows that ALKBH5 is a promising prognostic and immunotherapeutic biomarker in some malignant tumors.

Targeting the gut and tumor microbiota in cancer

Microorganisms within the gut and other niches may contribute to carcinogenesis, as well as shaping cancer immunosurveillance and response to immunotherapy. Our understanding of the complex relationship between different host-intrinsic microorganisms, as well as the multifaceted mechanisms by which they influence health and disease, has grown tremendously-hastening development of novel therapeutic strategies that target the microbiota to improve treatment outcomes in cancer. Accordingly, the evaluation of a patient's microbial composition and function and its subsequent targeted modulation represent key elements of future multidisciplinary and precision-medicine approaches. In this Review, we outline the current state of research toward harnessing the microbiome to better prevent and treat cancer.

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.

Immune Characteristics of LYN in Tumor Microenvironment of Gliomas

The prognosis of gliomas is poor and there are limited therapeutic approaches. Immunotherapy has become a promising treatment for gliomas. Here, we explored the expression pattern of Lck/yes-related protein tyrosine kinase (LYN) in gliomas and assessed its value as an immunotherapy biomarker. Transcriptional data was mined from two publicly available datasets, TCGA and CGGA, and used to investigate the correlation between LYN and clinical characteristics including patient prognosis, somatic mutation, and immune infiltrating features in gliomas. Besides, the correlation between LYN and classical immune checkpoint molecules was explored. Glioma samples obtained from the Xiangya Hospital cohort were used for immunohistochemistry staining. High expression level of LYN was observed in advanced gliomas and other cancer types, which predicted a worse prognosis. LYN stratified patients’ survival in the Xiangya cohort and was also significantly associated with infiltrating immune cell types and inflammatory activities in the tumor microenvironment. LYN was involved in tumor mutation, correlated with the regulation of oncogenic genes, and also showed a significant positive correlation with PD-L1. LYN can be a potential diagnostic marker and immunotherapy marker in gliomas.