Preoperative walking exercise to improve prognosis in patients with supratentorial brain tumours after craniotomy: protocol for a randomised controlled trial.

INTRODUCTION: Cardiopulmonary complications and cognitive impairment following craniotomy have a significantly impact on the general health of individuals with brain tumours. Observational research indicates that engaging in walking is linked to better prognosis in patient after surgery. This trial aims to explore whether walking exercise prior to craniotomy in brain tumour patients can reduce the incidence of cardiopulmonary complications and preserve patients' cognitive function. METHODS AND ANALYSIS: In this randomised controlled trial, 160 participants with supratentorial brain tumours aged 18-65 years, with a preoperative waiting time of more than 3-4 weeks and without conditions that would interfere with the trial such as cognitive impairment, will be randomly assigned in a ratio of 1:1 to either receive traditional treatment or additional combined with a period of 3-4 weeks of walking exercise of 10 000-15 000 steps per day. Wearable pedometer devices will be used to record step counts. The researchers will evaluate participants at enrolment, baseline, 14 days preoperatively, 3 days prior to surgery and 1 week after surgery or discharge (select which occurs first). The primary outcomes include the incidence of postoperative cardiopulmonary complications and changes in cognitive function (gauged by the Montreal Cognitive Assessment test). Secondary outcomes include the average length of hospital stay, postoperative pain, participant contentment, healthcare-associated costs and incidence of other postoperative surgery-related complications. We anticipate that short-term preoperative walking exercises will reduce the incidence of surgery-related complications in the short term after craniotomy, protect patients' cognitive function, aid patients' postoperative recovery and reduce the financial cost of treatment. ETHICS AND DISSEMINATION: The study protocol has been approved by Ethics Committee of Xiangya Hospital of Central South University (approval number: 202305117). The findings of the research will be shared via publications that have been reviewed by experts in the field and through presentations at conferences. TRIAL REGISTRATION NUMBER: NCT05930288.

Modifiable lifestyle factors influencing psychiatric disorders mediated by plasma proteins: A systemic Mendelian randomization study.

BACKGROUND: Psychiatric disorders are emerging as a serious public health hazard, influencing an increasing number of individuals worldwide. However, the effect of modifiable lifestyle factors on psychiatric disorders remains unclear. METHODS: Genome-wide association studies (GWAS) summary statistics were obtained mainly from Psychiatric Genomics Consortium and UK Biobank, with sample sizes varying between 10,000 and 1,200,000. The two-sample Mendelian randomization (MR) method was applied to investigate the causal associations between 45 lifestyle factors and 13 psychiatric disorders, and screen potential mediator proteins from 2992 candidate plasma proteins. We implemented a four-step framework with step-by-step screening incorporating two-step, univariable, and multivariable MR. RESULTS: We found causal effects of strenuous sports or other exercise on Tourette's syndrome (OR [95%CI]: 0.0047 [5.24E-04-0.042]); lifelong smoking index on attention-deficit hyperactivity disorder (10.53 [6.96-15.93]), anxiety disorders (3.44 [1.95-6.05]), bipolar disorder (BD) (2.25 [1.64-3.09]), BD II (2.89 [1.81-4.62]), and major depressive disorder (MDD) (2.47 [1.90-3.20]); and educational years on anorexia nervosa (AN) (1.47 [1.22-1.76]), and MDD (0.74 [0.66-0.83]). Five proteins were found to have causal associations with psychiatric disorders, namely ADH1B, GHDC, STOM, CD226, and TP63. STOM, a membrane protein deficient in the erythrocytes of hereditary stomatocytosis patients, may mediate the effect of educational attainment on AN. LIMITATIONS: The mechanisms underlying the effects of lifestyle factors on psychiatric disorders require further investigation. CONCLUSIONS: These findings could help assess the risk of psychiatric disorders based on lifestyle factors and also support lifestyle interventions as a prevention strategy for mental illness.

PD-L1-related IncRNAs are associated with malignant characteristics and immune microenvironment in glioma.

BACKGROUND: The expression of long non-coding RNA (lncRNA) can function as diagnostic and therapeutic biomarker for tumors. This research explores the role of PD-L1-related lncRNAs in affecting malignant characteristics and the immune microenvironment of glioma. METHODS: Downloading gene expression profiles and clinicopathological information of glioma from TCGA and CGGA databases, 6 PD-L1-related lncRNAs were identified through correlation analysis, Cox and LASSO regression analysis, establishing the risk score model based on them. Bioinformatics analysis and cell experiments in vitro were adopted to verify the effects of LINC01271 on glioma. RESULTS: Risk scores based on 6 PD-L1-related lncRNAs (AL355974.3, LINC01271, AC011899.3, MIR4500HG, LINC02594, AL357055.3) can reflect malignant characteristics and immunotherapy response of glioma. Patients with high LINC01271 expression had a worse prognosis, a higher abundance of M1 subtype macrophages in the immune microenvironment, and a higher degree of tumor malignancy. Experiments in vitro confirmed its positive regulatory effect on the proliferation and migration of glioma cells. CONCLUSIONS: The risk score model based on 6 PD-L1-related lncRNAs can reflect the malignant characteristics and prognosis of glioma. LINC01271 can independently be used as a new target for prognosis evaluation and therapy.

Application of Organoids in Regenerative Medicine.

Regenerative medicine mainly relies on heterologous transplantation, often hindered by sample availability and ethical issues. Furthermore, patients are required to take immunosuppressive medications to prevent adverse side effects. Stem cell-derived 3D-organoid culture has provided new alternatives for transplantation and regenerative medicine. Scholars have combined organoids with tissue engineering technology to improve reproducibility, the accuracy of constitution and throughput, and genetic correction to achieve a more personalized therapy. Here, we review the available applications of organoids in regenerative medicine and the current challenges concerning this field.

Applications of organoid technology to brain tumors.

Lacking appropriate model impedes basic and preclinical researches of brain tumors. Organoids technology applying on brain tumors enables great recapitulation of the original tumors. Here, we compared brain tumor organoids (BTOs) with common models including cell lines, tumor spheroids, and patient-derived xenografts. Different BTOs can be customized to research objectives and particular brain tumor features. We systematically introduce the establishments and strengths of four different BTOs. BTOs derived from patient somatic cells are suitable for mimicking brain tumors caused by germline mutations and abnormal neurodevelopment, such as the tuberous sclerosis complex. BTOs derived from human pluripotent stem cells with genetic manipulations endow for identifying and understanding the roles of oncogenes and processes of oncogenesis. Brain tumoroids are the most clinically applicable BTOs, which could be generated within clinically relevant timescale and applied for drug screening, immunotherapy testing, biobanking, and investigating brain tumor mechanisms, such as cancer stem cells and therapy resistance. Brain organoids co-cultured with brain tumors (BO-BTs) own the greatest recapitulation of brain tumors. Tumor invasion and interactions between tumor cells and brain components could be greatly explored in this model. BO-BTs also offer a humanized platform for testing the therapeutic efficacy and side effects on neurons in preclinical trials. We also introduce the BTOs establishment fused with other advanced techniques, such as 3D bioprinting. So far, over 11 brain tumor types of BTOs have been established, especially for glioblastoma. We conclude BTOs could be a reliable model to understand brain tumors and develop targeted therapies.

Tumor buster - where will the CAR-T cell therapy 'missile' go?

Chimeric antigen receptor (CAR) T cell (CAR-T cell) therapy based on gene editing technology represents a significant breakthrough in personalized immunotherapy for human cancer. This strategy uses genetic modification to enable T cells to target tumor-specific antigens, attack specific cancer cells, and bypass tumor cell apoptosis avoidance mechanisms to some extent. This method has been extensively used to treat hematologic diseases, but the therapeutic effect in solid tumors is not ideal. Tumor antigen escape, treatment-related toxicity, and the immunosuppressive tumor microenvironment (TME) limit their use of it. Target selection is the most critical aspect in determining the prognosis of patients receiving this treatment. This review provides a comprehensive summary of all therapeutic targets used in the clinic or shown promising potential. We summarize CAR-T cell therapies' clinical trials, applications, research frontiers, and limitations in treating different cancers. We also explore coping strategies when encountering sub-optimal tumor-associated antigens (TAA) or TAA loss. Moreover, the importance of CAR-T cell therapy in cancer immunotherapy is emphasized.

Efficacy of metformin therapy in patients with cancer: a meta-analysis of 22 randomised controlled trials.

BACKGROUND: To investigate whether metformin monotherapy or adjunctive therapy improves the prognosis in patients with any type of cancer compared to non-metformin users (age ≥18). METHODS: Databases (Medline, Embase, and the Cochrane Central Register of Controlled Trials) and clinical trial registries ( ClinicalTrials.gov ; the World Health Organization International Clinical Trials Registry Platform) were screened for randomized, controlled trials (RCT) reporting at least progression-free survival (PFS) and/or overall survival (OS). Main outcome measures included hazard ratios (HR), and combined HRs and 95% confidence intervals (CI) were calculated using random-effects models. RESULTS: Of the 8419 records screened, 22 RCTs comprising 5943 participants were included. Pooled HRs were not statistically significant in both PFS (HR 0.97, 95% CI 0.82-1.15, I2 = 50%) and OS (HR 0.98, 95% CI 0.86-1.13, I2 = 33%) for patients with cancer between the metformin and control groups. Subgroup analyses demonstrated that metformin treatment was associated with a marginally significant improvement in PFS in reproductive system cancers (HR 0.86, 95% CI 0.74-1.00) and a significantly worse PFS in digestive system cancers (HR 1.45, 95% CI 1.03-2.04). The PFS or OS was observed consistently across maintenance dose, diabetes exclusion, median follow-up, risk of bias, and combined antitumoral therapies. CONCLUSION: Metformin treatment was not associated with cancer-related mortality in adults compared with placebo or no treatment. However, metformin implied beneficial effects in the PFS of the patients with reproductive system cancers but was related to a worse PFS in digestive system cancers. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number CRD42022324672.

HOXA5: A crucial transcriptional factor in cancer and a potential therapeutic target.

HOX genes occupy a significant role in embryogenesis, hematopoiesis, and oncogenesis. HOXA5, a member of the A cluster of HOX genes, is essential for establishing the skeleton and normal organogenesis. As previously reported, aberrant HOXA5 expression contributes to anomalies and dysfunction of various organs, as well as affecting proliferation, differentiation, invasion, apoptosis, and other biological processes of tumor cells. Different cancers showed both downregulated and upregulated HOXA5 expression. The most common strategy for controlling HOXA5 downregulated expression may be CpG island hypermethylation. Additionally, current research demonstrated the regulatory network of HOXA5 and its connection with cancer stem cell progression and the immune microenvironment. Epigenetic modulators and upstream regulators, such as DNMTi and retinoic acid, may be beneficial for anti-tumor effects targeting HOXA5. Here, we summarize current knowledge about the HOXA5 gene, its role in various cancers, and its potential therapeutic value.

Machine learning-based identification of tumor-infiltrating immune cell-associated lncRNAs for improving outcomes and immunotherapy responses in patients with low-grade glioma.

Rationale: Accumulating evidence demonstrated that long noncoding RNAs (lncRNAs) involved in the regulation of the immune system and displayed a cell-type-specific pattern in immune cell subsets. Given the vital role of tumor-infiltrating lymphocytes in effective immunotherapy, we explored the tumor-infiltrating immune cell-associated lncRNA (TIIClncRNA) in low-grade glioma (LGG), which has never been uncovered yet. Methods: This study utilized a novel computational framework and 10 machine learning algorithms (101 combinations) to screen out TIIClncRNAs by integratively analyzing the sequencing data of purified immune cells, LGG cell lines, and bulk LGG tissues. Results: The established TIIClnc signature based on the 16 most potent TIIClncRNAs could predict outcomes in public datasets and the Xiangya in-house dataset with decent efficiency and showed better performance when compared with 95 published signatures. The TIIClnc signature was strongly correlated to immune characteristics, including microsatellite instability, tumor mutation burden, and interferon γ, and exhibited a more active immunologic process. Furthermore, the TIIClnc signature predicted superior immunotherapy response in multiple datasets across cancer types. Notably, the positive correlation between the TIIClnc signature and CD8, PD-1, and PD-L1 was verified in the Xiangya in-house dataset. Conclusions: The TIIClnc signature enabled a more precise selection of the LGG population who were potential beneficiaries of immunotherapy.

Role of CD47 in tumor immunity: a potential target for combination therapy.

CD47 performs a vital function in cancer therapy by binding to different SIRPα, thrombospondin 1, and integrin. However, its role in tumor immunity and its correlation with prognosis among many cancer types remain unknown. The raw mRNA expression data of CD47 in cancer patients was downloaded from TCGA and GTEx datasets. The protein expression of CD47 was detected using a microarray. Kaplan Meier analysis and forest plot were performed to compare the effects of high and low expression of CD47 on overall survival in different cancers. In addition, the correlations between CD47 expression and immune cell infiltration, stromal components, immune checkpoint genes, tumor mutational burden (TMB), and microsatellite instability (MSI) were analyzed from the public database. The gene function was determined by Gene Set Enrichment Analysis (GSEA). The expressions of CD47 in CHOL, COAD, ESCA, HNSC, KIRC, STAD, and THCA were higher compared with normal tissues. Elevated expression of CD47 predicted poor prognosis in ACC, KICH, KIRP, LGG, PAAD and UCEC. CD47 expression was strongly associated with immune infiltrating cells among KICH, KIRP, LGG, and PAAD. In addition, significant positive correlations with most immune checkpoint genes including PDCD 1 (PD-1), CD274 (PD-L1), CTLA4 in BLCA, DLBC, KICH, KIRC, LUAD, LUSC, PAAD, PCPG, SKCM, STAD, UCEC, and UVM was noted for the expression of CD47. GSEA analysis demonstrated that CD47 was a key regulator in metabolism-related pathways. These findings provide novel evidence that CD47 could be utilized as a promising prognostic biomarker and combination treatment target in various cancers.

Role of CD68 in tumor immunity and prognosis prediction in pan-cancer.

CD68 plays a critical role in promoting phagocytosis; however, the function of CD68 in tumor immunity and prognosis remains unknown. We analyzed CD68 expression among 33 tumor and normal tissues from The Cancer Genome Atlas and Genotype-Tissue Expression datasets. The relationship between CD68 expression and cancer prognosis, immune infiltration, checkpoint markers, and drug response was explored. Upregulated CD68 levels were observed in various cancer types, which were verified through tumor tissue chips using immunohistochemistry. High levels of CD68 in tumor samples correlated with an adverse prognosis in glioblastoma, kidney renal clear cell carcinoma, lower-grade glioma, liver hepatocellular carcinoma, lung squamous cell carcinoma, thyroid carcinoma, and thymoma and a favorable prognosis in kidney chromophobe. The top three negatively enriched Kyoto Encyclopedia of Genes and Genomes terms in the high CD68 subgroup were chemokine signaling pathway, cytokine-cytokine receptor interaction, and cell adhesion molecule cams. The top negatively enriched HALLMARK terms included complement, allograft rejection, and inflammatory response. A series of targeted drugs and small-molecule drugs with promising therapeutic effects were predicted. The clinical prognosis and immune infiltration of high expression levels of CD68 differ across tumor types. Inhibiting CD68-dependent signaling could be a promising therapeutic strategy for immunotherapy in many tumor types.

Natural killer cell-related gene signature predicts malignancy of glioma and the survival of patients.

BACKGROUND: Natural killer (NK) cells-based therapies are one of the most promising strategies against cancer. The aim of this study is to investigate the natural killer cell related genes and its prognostic value in glioma. METHODS: The Chinese Glioma Genome Atlas (CGGA) was used to develop the natural killer cell-related signature. Risk score was built by multivariate Cox proportional hazards model. A cohort of 326 glioma samples with whole transcriptome expression data from the CGGA database was included for discovery. The Cancer Genome Atlas (TCGA) datasets was used for validation. GO and KEGG were used to reveal the biological process and function associated with the natural killer cell-related signature. We also collected the clinical pathological features of patients with gliomas to analyze the association with tumor malignancy and patients' survival. RESULTS: We screened for NK-related genes to build a prognostic signature, and identified the risk score based on the signature. We found that NK-related risk score was independent of various clinical factors. Nature-killer cell gene expression is correlated with clinicopathological features of gliomas. Innovatively, we demonstrated the tight relation between the risk score and immune checkpoints, and found NK-related risk score combined with PD1/PDL1 patients could predict the patient outcome. CONCLUSION: Natural killer cell-related gene signature can predict malignancy of glioma and the survival of patients, these results might provide new view for the research of glioma malignancy and individual immunotherapy.

CMTM Family Genes Affect Prognosis and Modulate Immunocytes Infiltration in Grade II/III Glioma Patients by Influencing the Tumor Immune Landscape and Activating Associated Immunosuppressing Pathways.

Lower-grade glioma (LGG) is one of the most common primary tumor types in adults. The chemokine-like factor (CKLF)-like Marvel transmembrane domain-containing (CMTM) family is widely expressed in the immune system and can modulate tumor progression. However, the role of the CMTM family in LGG remains unknown. A total of 508 LGG patients from The Cancer Genome Atlas (TCGA) database were used as a training cohort, and 155 LGG patients from the Chinese Glioma Genome Atlas (CGGA) array database, 142 LGG patients from the CGGA RNA-sequencing database, and 168 LGG patients from the GSE108474 database were used as the validation cohorts. Patients were subdivided into two groups using consensus clustering. The ENET algorithm was applied to build a scoring model based on the cluster model. Finally, ESTIMATE, CIBERSORT, and xCell algorithms were performed to define the tumor immune landscape. The expression levels of the CMTM family genes were associated with glioma grades and isocitrate dehydrogenase (IDH) status. Patients in cluster 2 and the high-risk score group exhibited a poor prognosis and were enriched with higher grade, wild-type IDH (IDH-WT), 1p19q non-codeletion, MGMT promoter unmethylation, and IDH-WT subtype. Patients in cluster 1 and low-risk score group were associated with high tumor purity and reduced immune cell infiltration. Enrichment pathways analysis indicated that several essential pathways involved in tumor progression were associated with the expression of CMTM family genes. Importantly, PD-1, PD-L1, and PD-L2 expression levels were increased in cluster 2 and high-risk groups. Therefore, the CMTM family contributes to LGG progression through modulating tumor immune landscape.

Heme Oxygenase-1 Predicts Risk Stratification and Immunotherapy Efficacy in Lower Grade Gliomas.

Background: Gliomas are the most common tumors in human brains with unpleasing outcomes. Heme oxygenase-1 (HMOX1, HO-1) was a potential target for human cancers. However, their relationship remains incompletely discussed. Methods: We employed a total of 952 lower grade glioma (LGG) patients from TCGA and CGGA databases, and 29 samples in our hospital for subsequent analyses. Expression, mutational, survival, and immune profiles of HMOX1 were comprehensively evaluated. We constructed a risk signature using the LASSO Cox regression model, and further generated a nomogram model to predict survival of LGG patients. Single-cell transcriptomic sequencing data were also employed to investigated the role of HMOX1 in cancer cells. Results: We found that HMOX1 was overexpressed and was related to poorer survival in gliomas. HMOX1-related genes (HRGs) were involved in immune-related pathways. Patients in the high-risk group exhibited significantly poorer overall survival. The risk score was positively correlated with the abundance of resting memory CD4+ T cells, M1, M2 macrophages, and activated dendritic cells. Additionally, immunotherapy showed potent efficacy in low-risk group. And patients with lower HMOX1 expression were predicted to have better response to immunotherapies, suggesting that immunotherapies combined with HMOX1 inhibition may execute good responses. Moreover, significant correlations were found between HMOX1 expression and single-cell functional states including angiogenesis, hypoxia, and metastasis. Finally, we constructed a nomogram which could predict 1-, 3-, and 5-year survival in LGG patients. Conclusion: HMOX1 is involved in immune infiltration and predicts poor survival in patients with lower grade glioma. Importantly, HMOX1 were related to oncological functional states including angiogenesis, hypoxia, and metastasis. A nomogram integrated with the risk signature was obtained to robustly predict glioma patient outcomes, with the potential to guide clinical decision-making.

A pan-cancer analysis revealing the role of TIGIT in tumor microenvironment.

T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT), an immune checkpoint, plays a pivotal role in immune suppression. However its role in tumor immunity and correlation with the genetic and epigenetic alterations remains unknown. Here, we comprehensively analyzed the expression patterns of the TIGIT and its value of prognostic prediction among 33 types of cancers based on the data collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression projects (GTEx). Furthermore, the correlations of TIGIT with pathological stages, tumor-infiltrating immune cells (TIICs), signatures of T cells subtypes, immune checkpoint genes, the degree of Estimation of STromal and Immune cells in MAlignant Tumor tissues using the Expression data (ESTIMATE), tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, and DNA methyltransferases (DNMTs) were also explored. Gene functional enrichment was conducted by Gene Set Enrichment Analysis (GSEA). Our results showed that the expression of TIGIT was upregulated in most of the cancer types. Cox regression model showed that high expression of TIGIT in tumor samples correlates with poor prognosis in KIRC, KIRP, LGG, UVM, and with favorable prognosis in BRCA, CECS, HNSC, SKCM. TIGIT expression positively correlated with advanced stages, TIICs, the signatures of effector T cells, exhausted T cells, effector Tregs and the degree of ESTIMATE in KIRC, KIRP and UVM. TIGIT expression also positively correlated with CTLA4, PDCD1 (PD-1), CD274 (PD-L1), ICOS in most of the cancer types. Furthermore, the expression of TIGIT was correlated with TMB, MSI, MMR genes and DNMTs in different types of cancers. GSEA analysis showed that the expression of TIGIT was related to cytokine-cytokine receptor interaction, allograft rejection, oxidative phosphorylation. These findings suggested that TIGIT could serve as a potential biomarker for prognosis and a novel target for immunotherapies in cancers.

Immune Infiltration-Related Signature Predicts Risk Stratification and Immunotherapy Efficacy in Grade II and III Gliomas.

Background: Tumor microenvironment, especially infiltrating immune cell, is crucial for solid tumors including glioma. However, the hub genes as well as their effects on patient prognosis and immunotherapy efficacy remain obscure. Methods: We employed a total of 952 lower grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases, and 24 samples in our hospital for subsequent analyses. Abundances of immune infiltrates were evaluated using CIBERSORT and ImmuCellAI. Their correlations with prognosis were assessed by log-rank test. Immune infiltration-related hub genes were obtained from overlapped differential expressed genes (DEGs) in various subsets of survival-related immune cell types. The risk signature was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. The functional analyses were estimated by GVSA and Gene Set Enrichment Analysis (GSEA) algorithms. And protein-protein interaction enrichment analysis was carried out with the Metascape database integrating STRING, BioGrid, OmniPath, and InWeb_IM. Results: Among the 21 infiltrates, the abundances of five immune infiltrates were correlated with overall survival (OS) in LGG patients. Higher abundances of naïve CD4+ T cells (p = 0.002), activated mast cells (p = 0.015), and monocytes (p = 0.014) were correlated with better prognosis, while higher abundances of resting memory CD4+ T cells (p = 0.015) and M1 macrophages (p = 0.020) correlated with poorer OS. We finally obtained 44 hub genes and constructed an immune infiltration-related signature (IIRS). The IIRS correlates with clinicopathological characteristics and exhibited potential power in predicting the immunotherapy efficacy. The IRRS correlates with cancer related pathways, especially "epithelial-mesenchymal transition (EMT)," and cytotoxic T lymphocytes. Conclusion: Our study constructed and validated a novel signature for risk stratification and prediction of immunotherapy response in grade II and III gliomas, which was closely associated with glioma immune microenvironment and could serve as a promising prognostic biomarker for glioma patients.

CD161, a promising Immune Checkpoint, correlates with Patient Prognosis: A Pan-cancer Analysis.

Background: CD161 is a promising immune checkpoint mainly expressed on natural killer (NK) cells and is essential for immunoregulatory functions. However, it remains obscure how CD161 correlates with immune infiltration and patient prognosis in pan-cancer. Methods: We employed HPA, TCGA, GTEx, TIMER2.0, and GEPIA2 databases as well as R language to analyze and visualize CD161 in cancers. Our twenty-four glioma samples were sequenced for validation. Results: Overall, CD161 was differentially expressed between most paired cancer and normal controls. Higher CD161 expression was associated with poorer overall survival (OS) in the TCGA LGG (HR = 2.18, 95%CI = 1.79-2.66, P < 0.001) and UVM (HR = 1.32, 95%CI = 1.05-1.65, P = 0.016) cohorts. In these two cancer types, CD161 was significantly correlated with expression levels of recognized immune checkpoints and the abundance of markers of specific immune subsets, including CD8+ T cells, dendric cells (DCs), M2 macrophages, and exhausted T cells (Texs). In addition, CD161 was involved in several immune pathways in LGG and UVM, highlighting its role in regulating immune processes in the context of oncology. Conclusions: CD161 is a potential prognostic biomarker and immunotherapy target in human cancers, especially brain lower grade gliomas.

CD96 Correlates With Immune Infiltration and Impacts Patient Prognosis: A Pan-Cancer Analysis.

BACKGROUND: Immunotherapy has significantly improved patient outcomes, but encountered obstacles recently. CD96, a novel immune checkpoint expressed on T cells and natural killer (NK) cells, is essential for regulating immune functions. However, how CD96 correlating with immune infiltration and patient prognosis in pan-cancer remains unclear. METHODS: HPA, TCGA, GEO, GTEx, Oncomine, TIMER2.0, PrognoScan, Linkedomics, Metascape, and GEPIA2 databases were used to analyze CD96 in cancers. Visualization of data was mostly achieved by R language, version 4.0.2. RESULTS: In general, CD96 was differentially expressed between most cancer and adjacent normal tissues. CD96 significantly impacted the prognosis of diverse cancers. Especially, high CD96 expression was associated with poorer overall survival (OS) and disease-specific survival (DSS) in the TCGA lower grade glioma (LGG) cohort (OS, HR = 2.18, 95% CI = 1.79-2.66, P < 0.001). The opposite association was significantly observed in skin cutaneous melanoma (SKCM) cohort (OS, HR = 0.96, 95% CI = 0.94-0.98, P < 0.001). Notably, SKCM samples demonstrated the highest CD96 mutation frequency among all cancer types. Furthermore, in most cancers, CD96 expression level was significantly correlated with expression levels of recognized immune checkpoints and abundance of multiple immune infiltrates including CD8+ T cells, dendric cells (DCs), macrophages, monocytes, NK cells, neutrophils, regulatory T cells (Tregs), and follicular helper T cells (Tfh). CD96 was identified as a risk factor, protective factor, and irrelevant variable in LGG, SKCM and adrenocortical carcinoma (ACC), respectively. CD96 related genes were involved in negative regulation of leukocyte in LGG, however, involved in multiple positive immune processes in SKCM. Furthermore, CD96 was significantly associated with particular immune marker subsets. Importantly, it strongly correlated with markers of type 1 helper T cell (Th1) in SKCM, but not in LGG or ACC either. CONCLUSIONS: CD96 participates in diverse immune responses, governs immune cell infiltration, and impacts malignant properties of various cancer types, thus standing as a potential biomarker for determining patient prognosis and immune infiltration in multiple cancers, especially in glioma and melanoma.

Functions of RNF Family in the Tumor Microenvironment and Drugs Prediction in Grade II/III Gliomas.

Increasing evidence has demonstrated that RING finger (RNF) proteins played a vital role in cellular and physiological processes and various diseases. However, the function of RNF proteins in low-grade glioma (LGG) remains unknown. In this study, 138 RNF family members revealed their role in LGG. The TCGA database was used as the training cohort; two CGGA databases and GSE108474 were selected as external validation cohorts. Patients were grouped into cluster 1 and cluster 2, both in the training and validation cohorts, using consensus clustering analysis. The prognosis of patients in cluster 1 is significantly better than that in cluster 2. Meanwhile, biofunction prediction was further introduced to explore the potential mechanisms that led to differences in survival outcomes. Patients in Cluster 2 showed more complicated immunocytes infiltration and highly immunosuppressive features than cluster 1. Enrichment pathways such as negative regulation of mast cell activation, DNA replication, mismatch repair, Th17 cell differentiation, antigen processing and presentation, dendritic cell antigen processing and presentation, dendritic cell differentiation were also enriched in cluster 2 patients. For the last, the main contributors were distinguished by employing a machine learning algorithm. A lot of targeted and small molecule drugs that are sensitive to patients in cluster 2 were predicted. Importantly, we discovered TRIM8, DTX2, and TRAF5 as the most vital contributors from the RNF family, which were related to immune infiltration in LGG tumor immune landscape. In this study, we demonstrated the predicted role of RNF proteins in LGG. In addition, we found out three markers among RNF proteins that are closely related to the immune aspects of LGG, which might serve as novel therapeutic targets for immunotherapy in the future.

A novel integrated system using patient-derived glioma cerebral organoids and xenografts for disease modeling and drug screening.

A physiologically relevant glioma tumor model is important to the study of disease progression and screening drug candidates. However, current preclinical glioma models lack the brain microenvironment, and the established tumor cell lines do not represent glioma biology and cannot be used to evaluate the therapeutic effect. Here, we reported a real-time integrated system by generating 3D ex vivo cerebral organoids and in vivo xenograft tumors based on glioma patient-derived tissues and cells. Our system faithfully recapitulated the histological features, response to chemotherapy drugs, and clinical progression of their corresponding parental tumors. Additionally, our model successfully identified a case from a grade II astrocytoma patient with typical grade IV GBM features in both organoids and xenograft models, which mimicked the disease progression of this patient. Further genomic and transcriptomic characterization was associated with individual clinical features. We have demonstrated the "GBM-&Normal-like" signature to predict prognosis. In conclusion, we developed an integrated system of parallel models from patient-derived glioma cerebral organoids and xenografts for understanding the glioma biology and prediction of response to chemotherapy drugs, which might lead to a new strategy for personalized treatment for this deadly disease.