Genetic analysis of potential biomarkers and therapeutic targets in ferroptosis from coronary artery disease

Ferroptosis plays a key role in the death of cells including cardiomyocytes, and it is related to a variety of cardiac diseases. However, the role of ferroptosis‐related genes (FRGs) in coronary artery disease (CAD) is not well characterized. We downloaded CAD‐related information and FRGs from the gene expression omnibus (GEO) database and Ferroptosis Database (FerrDb) respectively. A total of 10 CAD‐related DE‐FRGs were obtained, which were closely linked to autophagy regulation and immune response. Subsequently, CA9, CBS, CEBPG, HSPB1, SLC1A4, STMN1 and TRIB3 among the 10 DE‐FRGs were identified as marker genes by LASSO and SVM‐RFE algorithms, which had tolerable diagnostic capabilities. Subsequent functional enrichment analysis showed that these marker genes may play a corresponding role in CAD by participating in the regulation of immune response, amino acid metabolism, cell cycle and multiple pathways related to the pathogenesis of CAD. Furthermore, a total of 58 drugs targeting 7 marker genes had been obtained. On the contrary, the ceRNA network revealed a complex regulatory relationship based on the marker genes. Also, CIBERSORT analysis showed that the changes in the immune microenvironment of CAD patients may be related to CBS, HSPB1 and CEBPG. We developed a diagnostic potency and provided an insight for exploring the mechanism for CAD. Before clinical application, further research is needed to test its diagnostic value for CAD.     

M2‐phenotype tumour‐associated macrophages upregulate the expression of prognostic predictors MMP14 and INHBA in pancreatic cancer

Pancreatic cancer is one of the most lethal gastrointestinal tumours, the most common pathological type is pancreatic adenocarcinoma (PAAD). In recent year, immune imbalanced in tumour microenvironment has been shown to play an important role in the evolution of tumours progression, and the efficacy of immunotherapy has been gradually demonstrated in clinical practice. In this study, we propose to construct an immune‐related prognostic risk model based on immune‐related genes MMP14 and INHBA expression that can assess the prognosis of pancreatic cancer patients and identify potential therapeutic targets for pancreatic cancer, to provide new ideas for the treatment of pancreatic cancer. We also investigate the correlation between macrophage infiltration and MMP14 and INHBA expression. First, the gene expression data of pancreatic cancer and normal pancreatic tissue were obtained from The Cancer Genome Atlas Program (TCGA) and The Genotype‐Tissue Expression public database (GTEx). The differentially expressed immune‐related genes between pancreatic cancer samples and normal sample were screened by R software. Secondly, univariate Cox regression analysis were used to evaluate the relationship between immune‐related genes and the prognosis of pancreatic cancer patients. A polygenic risk score model was constructed by Cox regression analysis. The prognostic nomogram was constructed, and its performance was evaluated comprehensively by internal calibration curve and C‐index. Using the risk model, each patient gets a risk score, and was divided into high‐ or low‐ risk groups. The proportion of 22 types of immune cells infiltration in pancreatic cancer samples was inferred by CIBERSOFT algorithm, correlation analysis (Pearson method) was used to analyse the correlation between the immune‐related genes and immunes cells. Then, we applied macrophage conditioned medium to culture pancreatic cancer cell line PANC1, detected the expression of MMP14 and INHBA by qRT‐PCR and Western blot methods. Knock‐down MMP14 and INHBA in PANC1 cells by transfected with shRNA lentiviruses. Detection of migration ability of pancreatic cells was done by trans‐well cell migration assay. A subcutaneous xenograft tumour model of human pancreatic cancer in nude mice was constructed. In conclusion, an immune‐related gene prognostic model was constructed, patients with high‐risk scores have poorer survival status, M2‐phenotype tumour‐associated macrophages (TAMs) up‐regulate two immune‐related genes, MMP14 and INHBA, which were used to establish the prognostic model. Knock‐down of MMP14 and INHBA inhibited invasion of pancreatic cancer.     

Pyroptosis‐related molecular classification and immune microenvironment infiltration in breast cancer: A novel therapeutic target

The underlying role of pyroptosis in breast cancer (BC) remains unknown. Herein, we investigated the correlations of 33 pyroptosis‐related genes (PRGs) with immune checkpoints and immune cell infiltrations in BC patients based on The Cancer Genome Atlas cohort (n = 996) and Gene Expression Omnibus cohort (n = 3,262). Enrichment analysis revealed that these PRGs mainly functioned in pyroptosis, inflammasomes and regulation of autophagy pathway. Four prognostic independent PRGs (CASP9, TIRAP, GSDMC and IL18) were identified. Then, cluster 1/2 was recognized using consensus clustering for these four PRGs. Patients from cluster 1 had a favourable prognosis and diverse immune cell infiltrations. A nomogram was developed based on age, TNM stage, tumour subtype and pyroptosis score. Patients with the high‐risk group exhibited worse 5‐year OS, and the result was consistent in the external cohort. Additionally, high‐risk group patients were associated with downregulated immune checkpoint expression. Further analysis suggested that the high‐risk group patients were associated with a higher IC50 of paclitaxel, doxorubicin, cisplatin, methotrexate and vinorelbine. In summarizing, the pyroptosis score‐based nomogram might serve as an independent prognostic predictor and could guide medication for chemotherapy. Additionally, it may bring novel insight into the regulation of tumour immune microenvironment in BC and help to achieve precision immunotherapy.     

Pyroptosis in glioblastoma: A crucial regulator of the tumour immune microenvironment and a predictor of prognosis

Recent studies have shown that pyroptosis, an inflammatory form of cell death, has a dual role in tumorigenesis and tumour progression and affects the prognosis of patients; however, the role of pyroptosis in glioblastoma (GBM) is still unclear. In this study, based on GBM patients'' data from two independent cohorts, we performed a comprehensive analysis of the expression and prognostic value of 33 pyroptosis‐associated genes (PAGs) in GBM, as well as their role in the tumour immune microenvironment (TIME) of GBM. We identified 29 PAGs that were differentially expressed between GBM and normal brain tissue, 18 of which were upregulated in GBM tissue. Most of the 33 PAGs were strongly correlated with the levels of immune cell infiltration. Based on the 33 PAGs, the GBM samples can be divided into two clusters (C1‐C2), with C1 having a ‘hot’ but immunosuppressive TIME and C2 having a ‘cold’ TIME, suggesting different immunotherapeutic responses in the two clusters. In addition, we identified four PAGs that were strongly associated with GBM prognosis and constructed a risk model based on these four PAGs. This risk model is an independent prognostic factor for GBM patients, and there is a different immune status between high‐ and low‐risk groups. In conclusion, this study demonstrates that pyroptosis is closely associated with the prognosis and TIME of GBM and provides an important basis for further studies on the relationship between pyroptosis and GBM.     

Single‐cell sequencing reveals the heterogeneity and intratumoral crosstalk in human endometrial cancer

BackgroundEndometrial cancer (EC) is one of the most common gynecologic malignancies with increasing morbidity. Cell–cell and cell‐matrix interactions within the tumour microenvironment (TME) exert a powerful influence over the progression of EC. Therefore, a comprehensive exploration of heterogeneity and intratumoral crosstalk is essential to elucidate the mechanisms driving EC progression and develop novel therapeutic approaches.Methods4 EC and 2 normal endometrium samples were applied for single‐cell RNA sequencing (scRNA‐seq) analysis. In addition, we also included the public database to explore the clinical benefits of the single cell analysis.Results9 types of cells were identified with specific expression of maker genes. Both the malignant epithelial cells and cells comprising the immune microenvironment displayed a high degree of intertumoral heterogeneity. Notably, the proliferation T cells also showed an exhausted feature. Moreover, the malignant cells may induce an immunosuppressive microenvironment through TNF‐ICOS pair. Cancer‐associated fibroblasts (CAFs) were divided into four subsets with distinct characteristics and they maintained frequent communications with malignant cells which facilitating the progression of EC. We also found that the existence of vascular CAF (vCAF) may indicate a worse prognosis for EC patients through integrating TCGA database.ConclusionThe TME of human EC remains highly heterogeneous. Out finding that malignant cells interact closely with immune cells and vCAFs identifies potential therapeutic targets.

In order to comprehensively explore the heterogeneity and intra‐tumoral crosstalk of human endometrial cancer, we profiled 41,358 single cells of human endometrial cancer and normal endometrial tissues. The results showed that the tumour microenvironment of human ECs remains highly heterogeneity. Malignant cells interact closely with immune cells and vCAFs which may indicate potential therapeutic targets.     

Predicting the prognosis of glioma by pyroptosis‐related signature

Glioma is the most common malignant primary brain tumour. It is of great significance for the prognosis and personalized treatment of glioma patients to accurate identification of glioma based on biomarkers. Pyroptosis, a kind of programmed cell death, is closely related to tumour progression and tumour immune microenvironment. However, the role of pyroptosis in glioma remained unclear. Herein, we used glioma clinical and expression data from TCGA and CGGA to explore the relationship between pyroptosis and glioma. We first summarized the incidence of copy number variations and somatic mutations of 33 pyroptosis‐related genes and explored prognostic correlation of these genes. Based on pyroptosis‐related genes, three molecular subgroups of glioma related to prognosis were identified. We also found that each subgroup has unique immune and biological behaviours characteristics. Finally, based on 7 pyroptosis‐related genes (CASP3, CASP4, CASP6, CASP8, CASP9, PRKACA and ELANE), we constructed a prognosis model by Lasso and Cox regression, which had a strong predictive power for the overall survival in CGGA test cohort (p < 0.05). In summary, we explored the role of pyroptosis‐related genes in gliomas and the association of these genes with tumour immunity. We found the biomarkers valuable to diagnosis and prognosis, hence, provide reference to the development and treatment of tumorigenesis in glioma.     

Identification of immune microenvironment subtypes that predicted the prognosis of patients with ovarian cancer

Ovarian cancer (OC) is associated with high mortality rate. However, the correlation between immune microenvironment and prognosis of OC remains unclear. This study aimed to explore prognostic significance of OC tumour microenvironment. The OC data set was selected from the cancer genome atlas (TCGA), and 307 samples were collected. Hierarchical clustering was performed according to the expression of 756 genes. The immune and matrix scores of all immune subtypes were determined, and Kruskal-Wallis test was used to analyse the differences in the immune and matrix scores between OC samples with different immune subtypes. The model for predicting prognosis was constructed based on the expression of immune-related genes. TIDE platform was applied to predict the effect of immunotherapy on patients with OC of different immune subtypes. The 307 OC samples were classified into three immune subtypes A-C. Patients in subtype B had poorer prognosis and lower survival rate. The infiltration of helper T cells and macrophages in microenvironment indicated significant differences between immune subtypes. Enrichment analyses of immune cell molecular pathways showed that JAK–STAT3 pathway changed significantly in subtype B. Furthermore, predictive response to immunotherapy in subtype B was significantly higher than that in subtype A and C. Immune subtyping can be used as an independent predictor of the prognosis of OC patients, which may be related to the infiltration patterns of immune cells in tumour microenvironment. In addition, patients in immune subtype B have superior response to immunotherapy, suggesting that patients in subtype B are suitable for immunotherapy.     

Expression of PD‐L1 on regulatory B cells in patients with acute myeloid leukaemia and its effect on prognosis

Programmed death‐ligand 1 (PD‐L1) is involved in immunosuppression in variety of tumours. Regulatory B cells (Bregs) are critical immune regulatory cells, and it has been demonstrated that the number of regulatory B cells in patients with acute myeloid leukaemia (AML) is much higher than that in healthy donors (HDs), which is linked to a poor prognosis. This study aimed to determine whether increased expression of PD‐L1, including in Bregs, is associated with a worse prognosis in individuals with AML. The proportion of Bregs, PD‐L1 expression in Bregs and PD‐1 expression in T cells were determined using flow cytometry using patient samples from 21 newly diagnosed AML patients at different stages of treatment and 25 HDs. We confirmed PD‐L1 expression in Bregs, and PD‐1 expression in CD3⁺CD4⁺T cells in bone marrow and peripheral blood samples from AML patients was higher than that in samples from HDs. The complete remission (CR) and progression‐free survival (PFS) of Bregs with high PD‐L1 expression were significantly decreased following induction chemotherapy. PD‐L1 expression is indeed increased in Bregs from individuals with AML, and high PD‐L1 expression is related to a poor prognosis.     

Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer

Cancer immune plays a critical role in cancer progression. Tumour immunology and immunotherapy are one of the exciting areas in bladder cancer research. In this study, we aimed to develop an immune‐related gene signature to improve the prognostic prediction of bladder cancer. Firstly, we identified 392 differentially expressed immune‐related genes (IRGs) based on TCGA and ImmPort databases. Functional enrichment analysis revealed that these genes were enriched in inflammatory and immune‐related pathways, including in ‘regulation of signaling receptor activity’, ‘cytokine‐cytokine receptor interaction’ and ‘GPCR ligand binding’. Then, we separated all samples in TCGA data set into the training cohort and the testing cohort in a ratio of 3:1 randomly. Data set {"type":"entrez-geo","attrs":{"text":"GSE13507","term_id":"13507"}}GSE13507 was set as the validation cohort. We constructed a prognostic six‐IRG signature with LASSO Cox regression in the training cohort, including AHNAK, OAS1, APOBEC3H, SCG2, CTSE and KIR2DS4. Six IRGs reflected the microenvironment of bladder cancer, especially immune cell infiltration. The prognostic value of six‐IRG signature was further validated in the testing cohort and the validation cohort. The results of multivariable Cox regression and subgroup analysis revealed that six‐IRG signature was a clinically independent prognostic factor for bladder cancer patients. Further, we constructed a nomogram based on six‐IRG signature and other clinicopathological risk factors, and it performed well in predict patients'' survival. Finally, we found six‐IRG signature showed significant difference in different molecular subtypes of bladder cancer. In conclusions, our research provided a novel immune‐related gene signature to estimate prognosis for patients'' survival with bladder cancer.     

FGF21 alleviates acute liver injury by inducing the SIRT1‐autophagy signalling pathway

Liver injury can lead to different hepatic diseases, which are the mainly causes of high global mortality and morbidity. Autophagy and Sirtuin type 1 (SIRT1) have been shown protective effects in response to liver injury. Previous studies have showed that Fibroblast growth factor 21 (FGF21) could alleviate acute liver injury (ALI), but the mechanism remains unclear. Here, we verified the relationship among FGF21, autophagy and SIRT1 in carbon tetrachloride (CCl₄)‐induced ALI. We established CCl₄‐induced ALI models in C57BL/6 mice and the L02 cell line. The results showed that FGF21 was robustly induced in response to stress during the development of ALI. After exogenous FGF21 treatment in ALI models, liver damage in ALI mice was significantly reduced, as well as serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels. Consistently, FGF21 also greatly reduced the levels of ALT, AST, pro‐inflammatory cytokines interleukin 6 (IL6) and tumour necrosis factor‐alpha (TNFα) in ALI cell lines. Mechanistically, exogenous FGF21 treatment efficiently upregulated the expression of autophagy marker microtubule‐associated protein light chain‐3 beta (LC3 II) and autophagy key molecule coiled‐coil myosin‐like BCL2‐interacting protein (Beclin1), which was accompanied by alleviating hepatotoxicity in CCl₄‐treated wild‐type mice. Then, we examined how FGF21 induced autophagy expression and found that SIRT1 was also upregulated by FGF21 treatment. To further verify our results, we constructed an anti‐SIRT1 lentit‐RNAi to inhibit SIRT1 expression in mice and L02 cells, which reversed the protective effect of FGF21 on ALI. In summary, these results indicate that FGF21 alleviates ALI by enhancing SIRT1‐mediated autophagy.     

Characterizing heterogeneity of non‐small cell lung tumour microenvironment to identify signature prognostic genes

Growing evidence has highlighted the immune response as an important feature of carcinogenesis and therapeutic efficacy in non‐small cell lung cancer (NSCLC). This study focused on the characterization of immune infiltration profiling in patients with NSCLC and its correlation with survival outcome. All TCGA samples were divided into three heterogeneous clusters based on immune cell profiles: cluster 1 (''low infiltration'' cluster), cluster 2 (''heterogeneous infiltration'' cluster) and cluster 3 (''high infiltration'' cluster). The immune cells were responsible for a significantly favourable prognosis for the ''high infiltration'' community. Cluster 1 had the lowest cytotoxic activity, tumour‐infiltrating lymphocytes and interferon‐gamma (IFN‐γ), as well as immune checkpoint molecules expressions. In addition, MHC‐I and immune co‐stimulator were also found to have lower cluster 1 expressions, indicating a possible immune escape mechanism. A total of 43 differentially expressed genes (DEGs) that overlapped among the groups were determined based on three clusters. Finally, based on a univariate Cox regression model, prognostic immune‐related genes were identified and combined to construct a risk score model able to predict overall survival (OS) rates in the validation datasets.