Sex-specific differences in ICOS+ T helper cell differentiation in systemic lupus erythematosus patients with low disease activity.

Systemic lupus erythematosus (SLE) is a sex biased chronic autoimmune disease affecting predominantly females during reproductive ages. Changes in the ratio of inducible costimulatory molecule (ICOS)+ regulatory (Treg) and non-regulatory responder (Tresp) CD4+ T cells proved to be crucial for the occurrence of high disease activity. Here, we investigated how the differentiation of ICOS+CD45RA+CD31+ recent thymic emigrant (RTE) Tresps into CD45RA-CD31- memory Tresps affects the percentages of ICOS+ Tresps within total CD4+ T cells. Three different pathways (pathway 1 via CD45RA-CD31+ memory Tresps, pathway 2 via direct proliferation and pathway 3 via resting mature naïve CD45RA+CD31- (MN) cells) were examined in healthy controls and SLE remission patients separated by sex. In female SLE remission patients, immunosuppressive therapy inhibited the ICOS+ RTE differentiation via CD45RA-CD31+ memory Tresps and direct proliferation, leaving an age-independently increased differentiation into CD45RA-CD31- memory Tresps by conversion of resting MN Tresps compared with healthy controls. Due to exhaustion of this pathway with age, no age-dependent change in the percentages of ICOS+ Tresps within total CD4+ T cells could be found. In contrast, no age-independently increased differentiation could be detected in men due to sufficient immunosuppression of all three pathways. This allowed an age-dependent differentiation of ICOS+ RTE Tresps into CD45RA-CD31- memory Tresps by conversion of resting MN Tresps, resulting in age-dependently increasing percentages of ICOS+ Tresps within total CD4+ T cells. We hypothesize that the sex-specific differential effect of immunosuppression on the differentiation of ICOS+ Tresps may explain the sex- and age-dependent occurrence of high disease activity.

MARCH-I: A negative regulator of dendritic cell maturation.

The expression of costimulatory molecules such as MHC-II, CD86 and CD83 on dendritic cells (DCs) are strongly regulated during cellular activation. Ubiquitination of some of these markers by the E3 ubiquitin ligase MARCH-I affects the maturation state of DCs and subsequently modulates immune responses. The effects of MARCH-I gene overexpression on the functional activity of human DCs is not well understood. Here, we investigate how MARCH-I, regulates maturation of DCs. We now provide evidence that MARCH-I transduced DCs secrete high levels of IL10 despite low secretion of IL 6 and IL 12 in response to LPS stimulation. They are weak stimulators of T lymphocyte cells but skewed T cell polarization toward T regulatory subset. These results exhibit that reduced expression of surface costimulatory molecules suppresses DC activation. It can be concluded that overexpression of MARCH-I gene in DCs leads to the production of tolerogenic DC.

Differential expression of immune checkpoints (OX40/OX40L and PD-1/PD-L1) in decidua of unexplained recurrent spontaneous abortion women.

In this study, we aimed to investigate the expression of OX40, OX40L, PD-1 and PD-L1 in patients with unexplained recurrent spontaneous abortion (URSA) compared to normal pregnancies (NP). A total of 50 patients who were diagnosed with URSA and 41 NP were recruited to this study. Real-time polymerase chain reaction (RT-PCR) was used to determine the expression of OX40, OX40L, PD-1 and PD-L1 in decidual tissues; Immunohistochemistry (IHC) was conducted to characterize the distribution of the involved genes in decidual tissues; Double immunofluorescence staining was used to prove the localization of the involved genes in decidual tissues. The concentrations of OX40L and PD-L1 in plasma were measured with enzyme-linked immunosorbent assay (ELISA). The expression of OX40L in the decidua of URSA patients was significantly increased compared to that in the NP group, while the expression of PD-L1 in the URSA group was decreased compared to that in the NP group. Both proteins are localized in the decidual stroma as analyzed by double immunofluorescence staining. The staining results were confirmed at the mRNA level of decidual tissues, while the mRNA level of peripheral blood showed no significant difference. In conclusion, the results suggest that decidual stromal cells may promote the interaction with OX40 on T cells by upregulating the expression of OX40L and reduce the interaction with PD-1 on T cells by downregulating the expression of PD-L1 in URSA patients, which may interfere with the immune tolerance of the maternal-fetal interface, leading to poor pregnancy outcomes.

Glucocorticoid-induced TNF receptor family-related protein functions as a costimulatory molecule for murine eosinophils.

Eosinophils are typical effector cells associated with type 2 immune responses and play key roles in the pathogenesis of allergic diseases. These cells are activated by various stimuli, such as cytokines, chemokines, and growth factors, but the regulatory mechanisms of eosinophil effector functions remain unclear. Glucocorticoid-induced tumor necrosis factor receptor family-related protein (GITR), a transmembrane protein belonging to the tumor necrosis factor (TNF) receptor superfamily, is a well-known regulatory molecule for T cell activation. Here, we show that GITR is also constitutively expressed on eosinophils and functions as a costimulatory molecule for these cells. Although degranulation was unaffected by GITR engagement of murine bone marrow-derived eosinophils, secretion of inflammatory cytokines such as interleukin (IL)-4, IL-6, and IL-13 from IL-33-activated bone marrow-derived eosinophils was augmented by anti-mouse GITR agonistic antibody (DTA-1). In conclusion, our results provide a new regulatory pathway of cytokine secretion from eosinophils in which GITR functions as a costimulatory molecule.

Identification of Key Prognostic Alternative Splicing Events of Costimulatory Molecule-Related Genes in Colon Cancer.

OBJECTIVE: This study aimed to explore the key alternative splicing events in costimulatory molecule-related genes in colon cancer and to determine their correlation with prognosis. METHODS: Gene expression RNA-sequencing data, clinical data, and SpliceSeq data of colon cancer were obtained from The Cancer Genome Atlas. Differentially expressed alternative splicing events in genes were identified, Followed by correlation analysis of genes corresponding to differentially expressed alternative splicing events with costimulatory molecule-related genes. Survival analysis was conducted using differentially expressed alternative splicing events in these genes and a prognostic model was constructed. Functional enrichment, proteinprotein interaction network, and splicing factor analyses were performed. RESULTS: In total, 6504 differentially expressed alternative splicing events in 3949 genes were identified between tumor and normal tissues. Correlation analysis revealed 3499 differentially expressed alternative splicing events in 2168 costimulatory molecule-related genes. Moreover, 328 differentially expressed alternative splicing events in 288 costimulatory molecule-related genes were associated with overall survival. The prognostic models constructed using these showed considerable power in predicting survival. The ubiquitin A-52 residue ribosomal protein fusion product 1 and ribosomal protein S9 were the hub nodes in the protein-protein interaction network. Furthermore, one splicing factor, splicing factor proline and glutamine-rich, was significantly associated with patient prognosis. Four splicing factor-alternative splicing pairs were obtained from four alternative splicing events in three genes: TBC1 domain family member 8 B, complement factor H, and mitochondrial fission 1. CONCLUSION: The identified differentially expressed alternative splicing events of costimulatory molecule-related genes may be used to predict patient prognosis and immunotherapy responses in colon cancer.

Reciprocal costimulatory molecules control the activation of mucosal type 3 innate lymphoid cells during engagement with B cells.

Innate lymphoid cells (ILCs) are the counterpart of T helper cells in the innate immune system and share multiple phenotypes with T helper cells. Inducible T-cell costimulator (ICOS) is recognized on T cells and participates in T-cell activation and T and B-cell engagement in lymphoid tissues. However, the role of ICOS in ILC3s and ILC3-involved interactions with the immune microenvironment remains unclear. Here, we found that ICOS expression on human ILC3s was correlated with the activated state of ILC3s. ICOS costimulation enhanced the survival, proliferation, and capacity of ILC3s to produce cytokines (IL-22, IL-17A, IFN-γ, TNF, and GM-CSF). Via synergistic effects of ICOS and CD40 signaling, B cells promoted ILC3 functions, and ILC3-induced T-cell-independent B-cell IgA and IgM secretion primarily required CD40 signaling. Hence, ICOS is essential for the nonredundant role of ILC3s and their interaction with adjacent B cells.

Integrated multiomics analyses unveil the implication of a costimulatory molecule score on tumor aggressiveness and immune evasion in breast cancer: A large-scale study through over 8,000 patients.

BACKGROUND: Although immunotherapy has revolutionised cancer management, reliable genomic biomarkers for identifying eligible patient subpopulations are lacking. Costimulatory molecules play a crucial role in mounting anti-tumour responses, and clinical trials targeting these novel biomarkers are underway. However, whether these molecules can determine tumour aggressiveness and the risk of tumour evasion in breast cancer (BC) remains largely unknown. METHODS: The whole-tissue transcriptomic data of 8236 patients with BC from 15 independent cohorts were extracted. An integrated scoring system named 'costimulatory molecule score' (CMS) was constructed and sufficient validated using least absolute shrinkage and selection operator regression (1000 iterations) and the random survival forest algorithm (1000 trees). The correlation among CMSs, cancer genotypes and clinicopathological characteristics was examined. Extensive multiomics and immunogenomic analyses were performed to investigate and verify the association among CMSs, enriched pathways, potential intrinsic and extrinsic immune escape mechanisms, immunotherapy response and therapeutic options. RESULTS: The predictive role of CMS model that relies on expression pattern of merely 5 costimulatory genes for prognosis is almost universally applicable to BC patients in a platform-independent manner. Through internal and external in silico validation, high CMS was characterized by favorable genotypes but decreased tumor immunogenicity, activation of stroma, immune-suppressive states and potential immunotherapeutic resistance. Similar results were observed in a real-world immunotherapy cohort and Pan-Cancer analysis. CONCLUSION: This comprehensive characterization indicates CMS model may be complemented for predicting tumor aggressiveness and immune evasion in BC patients, underlining the future clinical potential for further exploration of resistance mechanisms and optimization of immunotherapeutic strategies.

LINC00941 Promotes Cell Malignant Behavior and Is One of Five Costimulatory Molecule-Related lncRNAs That Predict Prognosis in Renal Clear Cell Carcinoma.

Background and Objectives: A significant role was played by costimulatory molecules in renal cancer. However, the lncRNAs regulating costimulatory molecules have not been fully investigated. Materials and Methods: Data from the next-sequence file and clinical data were downloaded from the Cancer Genome Atlas (TCGA) database. All analyses were conducted using the R and GraphPad Prism software. Results: A total of 1736 costimulatory molecule-related lncRNAs were determined under the threshold of |Cor| > 0.5 and p-value < 0.001. Furthermore, a prognosis prediction signature consisting of five lncRNAs: LINC00941, AC016773.1, AL162171.1, HOTAIRM1, and AL109741.1 was established with great prediction ability. By combining risk score and clinical parameters, a nomogram plot was constructed for better clinical practice. A biological enrichment analysis indicated that E2F targets, coagulation, IL6/JAK/STAT3 signaling, G2/M checkpoint, and allograft rejection pathways were activated in high-risk patients. Furthermore, a higher infiltration level of resting CD4+ T cell, M2 macrophage, and resting mast cells, while a lower CD8+ T cell infiltration was observed in high-risk patients. It is worthy of note that, low-risk patients might respond better to PD-1 checkpoint therapy. A correlation analysis of LINC00941 revealed that it was positively correlated with Th2 cells, Th1 cells, macrophages, and Treg cells, but negatively correlated with Th17 cells. A pathway enrichment analysis indicated that the pathways of the inflammatory response, G2M checkpoint, and IL6/JAK/STAT3 signaling were significantly activated in patients with high LINC00941 expression. In vitro experiments indicated that LINC00941 can enhance the malignant biological behaviors of renal cancer cells. Conclusions: Our study established a costimulatory molecule-related lncRNAs-based prognosis model with a great prediction prognosis. In addition, LINC00941 could enhance the malignant biological behaviors of renal cancer cells.

Exploring Mast Cell-CD8 T Cell Interactions in Inflammatory Skin Diseases.

The skin is exposed to environmental challenges and contains skin-resident immune cells, including mast cells (MCs) and CD8 T cells that act as sentinels for pathogens and environmental antigens. Human skin MCs and their mediators participate in the maintenance of tissue homeostasis and regulate the recruitment and activity of immune cells involved in the pathogenesis of skin diseases. The cutaneous CD8 T cell compartment is comprised of long-persisting resident memory T cells (TRM) and migratory or recirculating cells; both populations provide durable site immune surveillance. Several lines of evidence indicate that MC-derived products, such as CCL5 and TNF-α, modulate the migration and function of CD8 T cells. Conversely, activated CD8 T cells induce the upregulation of MC costimulatory molecules. Moreover, the close apposition of MCs and CD8 T cells has been recently identified in the skin of several dermatoses, such as alopecia areata. This review outlines the current knowledge about bidirectional interactions between human MCs and CD8 T cells, analyses the alteration of their communication in the context of three common skin disorders in which these cells have been found altered in number or function-psoriasis, atopic dermatitis, and vitiligo-and discusses the current unanswered questions.

Costimulatory molecule-related lncRNA model as a potential prognostic biomarker in non-small cell lung cancer.

OBJECTIVE: Costimulatory molecules have been demonstrated to exert essential roles in multiple cancers. However, their role in lung cancer remains elusive. Here, we sought to identify costimulatory molecule-related lncRNAs in non-small cell lung cancer (NSCLC) and establish a prognostic signature to predict the prognosis of patients with NSCLC. METHODS: A total of 535 lung adenocarcinoma (LUAD) and 502 lung squamous cell carcinoma (LUSC) patients from the cancer genome atlas (TCGA) database were recruited. A novel costimulatory molecule-based lncRNA prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival. The Homo_sapiens.GRCh38 data set was set as a reference file for probe annotation. RESULTS: A total of 593 costimulatory molecule-related lncRNAs were extracted. After analysis, six costimulatory molecule-related lncRNAs (AC084859.1, AC079949.2, HSPC324, LINC01150, LINC01150, and AC090617.5) were screened. A prognostic model based on the six lncRNAs was established using systematic bioinformatics analyses. The prognostic model had a prognostic value in NSCLC patients. Furthermore, a prognostic nomogram was established based on clinical parameters and a risk-score model. Patients with different risk scores had considerably different tumor-infiltrating immune cells, somatic mutational loading, clinical outcomes, signaling pathways, and immunotherapy efficacy. In addition, LINC01137 was associated with unfavorable disease outcomes and fueled tumor progression in NSCLC. CONCLUSION: Taken together, our study demonstrated that a costimulatory molecule-related lncRNA model could be a potential prognostic biomarker in NSCLC. Moreover, LINC01137 could facilitate the proliferation and invasion of lung cancer.

Costimulatory molecule expression profile as a biomarker to predict prognosis and chemotherapy response for patients with small cell lung cancer.

Owing to the paucity of specimens, progress in identifying prognostic and therapeutic biomarkers for small cell lung cancer (SCLC) has been stagnant for decades. Considering that the costimulatory molecules are essential elements in modulating immune responses and determining therapeutic response, we systematically revealed the expression landscape and identified a costimulatory molecule-based signature (CMS) to predict prognosis and chemotherapy response for SCLCs for the first time. We found T cell activation was restrained in SCLCs, and costimulatory molecules exhibited widespread abnormal genetic alterations and expression. Using a LASSO Cox regression model, the CMS was built with a training cohort of 77 cases, which successfully divided patients into high- or low-risk groups with significantly different prognosis and chemotherapy benefit (both P < 0.001). The CMS was well validated in an independent cohort containing 131 samples with qPCR data. ROC and C-index analysis confirmed the superior predictive performance of the CMS in comparison with other clinicopathological parameters from different cohorts. Importantly, the CMS was confirmed as a significantly independent prognosticator for clinical outcomes and chemotherapy response in SCLCs through multivariate Cox analysis. Further analysis revealed that low-risk patients were characteristic by an activated immune phenotype with distinct expression of immune checkpoints. In summary, we firstly uncovered the expression heterogeneity of costimulatory molecules in SCLC and successfully constructed a novel predictive CMS. The identified signature contributed to more accurate patient stratification and provided robust prognostic value in estimating survival and the clinical response to chemotherapy, allowing optimization of treatment and prognosis management for patients with SCLC.

Research progress on the role of costimulatory signaling pathway in xenotransplantation / 器官移植

Organ shortage is a critical factor limiting the development of organ transplantation. Xenotransplantation is expected to resolve the problem of organ shortage, which has become a new research hotspot. Study of costimulatory signaling pathway related to T cell regulation is a hot topic in terms of immunity of xenotransplantation. Since the discovery of costimulatory molecule CD28, multiple costimulatory molecules have been identified, including costimulatory and coinhibitory receptors and their related ligands. Specific T cell activation of donors is the key factor leading to acute immune rejection. The expression and induction of costimulatory molecules on T cells differ during different immune stages, and these costimulatory molecules play a key role in maintaining T cell tolerance and the balance of T cell immune response. At present, increasing attention has been diverted to the role of costimulatory signaling pathway in organ transplantation. In this article, the latest research progress in costimulatory signaling pathway related to xenotransplantation immunity was reviewed, aiming to provide reference for the optimization of xenotransplantation immunosuppression regimen.

Dual Roles of Tumor Necrosis Factor Superfamily 14 in Antiviral Immunity.

Tumor necrosis factor superfamily 14 (TNFSF14) (LIGHT) is an interesting costimulatory molecule associated with T lymphocyte activation, and it mainly exerts its biological effects by binding to its receptors herpesvirus invasion mediator (HVEM) and lymphotoxin-ß receptor. Research shows that TNFSF14 plays a critical regulatory role in immune responses to viral infection, but its role is different in different diseases. TNFSF14 can be a cytokine neutralization target during novel coronavirus infection, and anti-TNFSF14 monoclonal antibody treatment can reduce the risk of respiratory failure and mortality. When the host is infected with adenovirus, TNFSF14 can be used as an inflammatory biomarker to indicate whether there was an adenovirus infection in the host and the degree of disease caused by viral infection. When hosts suffer influenza virus infection, the TNFSF14-HVEM signaling pathway can stimulate the maturation and proliferation of memory CD8+ T cells, which helps the host immune system stimulate a second immune response against respiratory virus infection. TNFSF14 can act as an immune adjuvant and enhance the immunogenicity of the human papillomavirus (HPV) DNA vaccine when the host is infected with HPV. During hepatitis virus infection, TNFSF14 acts as a proinflammatory factor, participates in inflammation and causes tissue damage. In conclusion, TNFSF14 plays different and significant roles in diverse viral infections. This article reviews the current research on TNFSF14 in antiviral immunity.

Comprehensive characterization of costimulatory molecule gene for diagnosis, prognosis and recognition of immune microenvironment features in sepsis.

The present study, which involved 10 GEO datasets and 3 ArrayExpress datasets, comprehensively characterized the potential effects of CMGs in sepsis. Based on machine learning algorithms (Lasso, SVM and ANN), the CMG classifier was constructed by integrating 6 hub CMGs (CD28, CD40, LTB, TMIGD2, TNFRSF13C and TNFSF4). The CMG classifier exhibit excellent diagnostic values across multiple datasets and time points, and was able to distinguish sepsis from other critical diseases. The CMG classifier performed better in predicting mortality than other clinical characteristics or endotypes. More importantly, from clinical specimens, the CMG classifier showed more superior diagnostic values than PCT and CRP. Alternatively, the CMG classifier/hub CMGs is significantly correlated with immune cells infiltration (B cells, T cells, Tregs, and MDSC), pivotal immune and molecular pathways (inflammation-promoting, complement and coagulation cascades), and several cytokines. Collectively, CMG classifier was a robust tool for diagnosis, prognosis and recognition of immune microenvironment features in sepsis.

The role of costimulatory molecules in glioma biology and immune microenvironment.

Background: Extensive research showed costimulatory molecules regulate tumor progression. Nevertheless, a small amount of literature has concentrated on the potential prognostic and therapeutic effects of costimulatory molecules in patients with glioma. Methods: The data were downloaded from The Cancer Genome Atlas (TCGA) database, Chinese Glioma Genome Atlas (CGGA) database, and Gene Expression Omnibus (GEO) database for bioinformatics analysis. R software was applied for statistical analysis. Using the FigureYa and Xiantao online tools (https://www.xiantao.love/) for mapping. Results: The Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were utilized to identify the signature consisting of five costimulatory molecules. Multivariate regression analysis revealed that the prognosis of glioma could be independently predicted by the riskscore. Furthermore, we explored clinical and genomic feature differences between the two groups. The level of tumor mutational burden (TMB) was higher in the high-risk group, while more mutation of IDH1 was observed in the low-risk group. Results of Tumor Immune Dysfunction and Exclusion (TIDE) analysis showed that high-risk patients were more prone to be responded to immunotherapy. In addition, subclass mapping analysis was performed to validate our findings and the results revealed that a significantly higher percentage of immunotherapy response rate was observed in the high-risk group. Conclusion: A novel signature with a good independent predictive capacity of prognosis was successfully identified. And our findings reveal that patients with high-risk scores were more likely to be responded to immunotherapy.

Identification of a prognostic model based on costimulatory molecule-related subtypes and characterization of tumor microenvironment infiltration in acute myeloid leukemia.

Costimulatory molecules have been found to play significant roles in anti-tumor immune responses, and are deemed to serve as promising targets for adjunctive cancer immunotherapies. However, the roles of costimulatory molecule-related genes (CMRGs) in the tumor microenvironment (TME) of acute myeloid leukemia (AML) remain unclear. In this study, we described the CMRG alterations in the genetic and transcriptional fields in AML samples chosen from two datasets. We next evaluated their expression and identified two distinct costimulatory molecule subtypes, which showed that the alterations of CMRGs related to clinical features, immune cell infiltration, and prognosis of patients with AML. Then, a costimulatory molecule-based signature for predicting the overall survival of AML patients was constructed, and the predictive capability of the proposed signature was validated in AML patients. Moreover, the constructed costimulatory molecule risk model was significantly associated with chemotherapeutic drug sensitivity of AML patients. In addition, the identified genes in the proposed prognostic signature might play roles in pediatric AML. CMRGs were found to be potentially important in the AML through our comprehensive analysis. These findings may contribute to improving our understanding of CMRGs in patients with AML, as well as provide new opportunities to assess prognosis and develop more effective immunotherapies.

A Signature Based on Costimulatory Molecules for the Assessment of Prognosis and Immune Characteristics in Patients With Stomach Adenocarcinoma.

Although costimulatory molecules have been shown to boost antitumor immune responses, their significance in stomach adenocarcinoma (STAD) remains unknown. The purpose of this study was to examine the gene expression patterns of costimulatory molecule genes in patients with STAD and develop a predictive signature to aid in therapy selection and outcome prediction. We used 60 costimulatory family genes from prior research to conduct the first complete costimulatory molecular analysis in patients with STAD. In the two study groups, consensus clustering analysis based on these 60 genes indicated unique distribution patterns and prognostic differences. Using the least absolute shrinkage and selection operator and Cox regression analysis, we identified nine costimulatory molecular gene pairs (CMGPs) with prognostic value. With these nine CMGPs, we were able to develop a costimulatory molecule-related prognostic signature that performed well in an external dataset. For the patients with STAD, the signature was proven to be a risk factor independent of the clinical characteristics, indicating that this signature may be employed in conjunction with clinical considerations. A further connection between the signature and immunotherapy response was discovered. The patients with high mutation rates, an abundance of infiltrating immune cells, and an immunosuppressive milieu were classified as high-risk patients. It is possible that these high-risk patients have a better prognosis for immunotherapy since they have higher cytolytic activity scores and immunophenoscores of CTLA4 and PD-L1/PD-L2 blockers. Therefore, our signature may help clinicians in assessing patient prognosis and developing treatment plans.

Identification of Costimulatory Molecule-Related lncRNAs Associated With Gastric Carcinoma Progression: Evidence From Bioinformatics Analysis and Cell Experiments.

Costimulatory molecules (CMGs) play essential roles in multiple cancers. However, lncRNAs regulating costimulatory molecules have not been fully explored in gastric cancer (GC). Public data of GC patients were obtained from The Cancer Genome Atlas database. R software v4.1.1, SPSS v13.0, and GraphPad Prism 8 were used to perform all the analyses. The Limma package was used for differential expression analysis. The survival package was used for patient prognosis analysis. The gene set enrichment analysis (GSEA), gene ontology (GO), and the Kyoto encyclopedia of genes and genomes (KEGG) analysis were used for pathway enrichment analysis. qRT-PCR was used to detect the RNA level of target lncRNA. CCK-8 and colony formation assay were used to assess the proliferation ability of GC cells. The transwell assay was used to evaluate the invasion and migration ability of GC cells. We first identified CMG-related lncRNAs (CMLs) through co-expression analysis. Then, an eight-CML-based signature was constructed to predict patient overall survival (OS), which showed satisfactory predictive efficiency (the training cohort: 1-year AUC = 0.764, 3-year AUC = 0.810, 5-year AUC = 0.840; the validation cohort: 1-year AUC = 0.661, 3-year AUC = 0.718, 5-year AUC = 0.822). The patients in the high-risk group tend to have a worse prognosis. GSEA showed that epithelial-mesenchymal transition, KRAS signaling, and angiogenesis were aberrantly activated in high-risk patients. GO and KEGG analyses indicated that the biological difference between high- and low-risk patients was mainly enriched in the extracellular matrix. Immune infiltration analysis showed that macrophages (M1 and M2), dendritic cells, monocytes, Tregs, and T regulatory cells were positively correlated with the risk scores, partly responsible for the worsening OS of high-risk patients. Finally, lncRNA AP000695.2 was selected for further experiments. The result showed that AP000695.2 was upregulated in GC cell lines and could facilitate the proliferation, invasion, and migration of GC cells. In summary, this study established an effective prognosis model based on eight CMLs, which would be helpful for further therapy options for cancer. Also, we found that AP000695.2 could promote GC cell malignant phenotype, making it an underlying therapy target in GC.

Prognostic implication and immunotherapy response prediction of a costimulatory molecule signature in kidney renal clear cell carcinoma.

Costimulatory molecules were considered to be promising and important targets in immunotherapy for various cancers. The present study was intended for generating a costimulatory molecule signature in kidney renal clear cell carcinoma (KIRC), to investigate prognostic implication, elucidate immune atlas, and predict immunotherapy response. All the KIRC samples from the TCGA were randomly divided into the training dataset and the testing dataset in the ratio of 7:3. The Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify 7 key costimulatory molecules which were associated with prognosis and construct a costimulatory molecule prognostic index (CMsPI), which was validated by internal and external datasets and an independent cohort. Patients in the high-CMsPI group had high mortality. Mutation analysis showed the most common mutational genes and variant types. Immune analysis demonstrated CD8+ T cells were infiltrated at a high level in the high-CMsPI group. In combination of analysis of the immune relevant gene signature and the biomarkers of immunotherapy, we may infer there were more dysfunctional CD8+ T cells in the high-CMsPI group, and the patients of this group were less sensitive to immunotherapy. A nomogram was constructed, and the concordance index was 0.77 (95% CI: 0.74-0.79). Three key signaling pathways were identified to facilitate tumor progression. The CMsPI can be regarded as a promising biomarker for predicting individual prognosis and assessing immunotherapy response in KIRC patients.

Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients. METHODS: Based on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan-Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated based on qRT-PCR and Human Protein Atlas (HPA) databases. RESULTS: All HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR and immunohistochemical results indicated six CMGs with differential expression in HCC tissues and normal tissues. CONCLUSION: In conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.