Integrative computational immunogenomic profiling of cortisol-secreting adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare but highly aggressive malignancy. Nearly half of ACC tumours overproduce and secrete adrenal steroids. Excess cortisol secretion, in particular, has been associated with poor prognosis among ACC patients. Furthermore, recent immunotherapy clinical trials have demonstrated significant immunoresistance among cortisol-secreting ACC (CS-ACC) patients when compared to their non-cortisol-secreting (nonCS-ACC) counterparts. The immunosuppressive role of excess glucocorticoid therapies and hypersecretion is known; however, the impact of the cortisol hypersecretion on ACC tumour microenvironment (TME), immune expression profiles and immune cell responses remain largely undefined. In this study, we characterized the TME of ACC patients and compared the immunogenomic profiles of nonCS-ACC and CS-ACC tumours to assess the impact of differentially expressed genes (DEGs) by utilizing The Cancer Genome Atlas (TCGA) database. Immunogenomic comparison (CS- vs. nonCS-ACC tumour TMEs) demonstrated an immunosuppressive expression profile with a direct impact on patient survival. We identified several primary prognostic indicators and potential targets within ACC tumour immune landscape. Differentially expressed immune genes with prognostic significance provide additional insight into the understanding of potential contributory mechanisms underlying failure of initial immunotherapeutic trials and poor prognosis of patients with CS-ACC.     

Investigation of fatty acid metabolism-related genes in breast cancer: Implications for Immunotherapy and clinical significance

Breast cancer (BRCA) is a major global health issue, characterized by high mortality and low early diagnosis rates. The tumor immune microenvironment (TME) of BRCA is closely linked to fatty acid metabolism (FAM). This study aimed to identify FAM-related subtypes in BRCA based on gene expression and clinical data from the Cancer Genome Atlas (TCGA) database. The study found two distinct FAM-related subtypes, each with unique immune characteristics and prognostic implications. A FAM-related risk score prognostic model was developed and validated using TCGA and International Cancer Genome Consortium (GEO) cohorts, showing potential clinical applications for chemotherapy and immunotherapy. Additionally, a nomogram was established to facilitate clinical use of the risk score. These results highlight the significant correlation between FAM genes and TME in BRCA, and demonstrate the potential clinical utility of the FAM-related risk score in informing treatment decisions for BRCA patients.     

Exploration of a novel prognostic risk signatures and immune checkpoint molecules in endometrial carcinoma microenvironment

In this study, we devoted to investigate immune-related genes and tumor microenvironment (TME) in EC based on The Cancer Genome Atlas (TCGA) database. In total 799 up-regulated and 139 down-regulated immune-related and differentially expressed genes in EC were investigated for functional annotations and prognosis. By a conjoint Cox regression analysis, we built two risk models for OS and DFS, as well as the consistent nomograms. Immune-related pathways were revealed mostly enriched in the low-risk group. By further analyzing TME based on the risk signatures, the higher immune cell infiltration and activation, lower tumor purity and higher tumor mutational burden were found in low-risk group, which presented a better prognosis. Both the expression and immunophenoscore of immune checkpoints PD-1, CTLA4, PD-L1 and PD-L2 increased significantly in low-risk group. These findings may provide new ideas for novel biomarkers and immunotherapy targets in EC.     

Prognostic value and immune cell infiltration of hypoxic phenotype‐related gene signatures in glioblastoma microenvironment

Glioblastoma (GBM) is a malignant intracranial tumour with the highest proportion and lethality. It is characterized by invasiveness and heterogeneity. However, the currently available therapies are not curative. As an essential environmental cue that maintains glioma stem cells, hypoxia is considered the cause of tumour resistance to chemotherapy and radiation. Growing evidence shows that immunotherapy focusing on the tumour microenvironment is an effective treatment for GBM; however, the current clinicopathological features cannot predict the response to immunotherapy and provide accurate guidance for immunotherapy. Based on the ESTIMATE algorithm, GBM cases of The Cancer Genome Atlas (TCGA) data set were classified into high‐ and low‐immune/stromal score groups, and a four‐gene tumour environment‐related model was constructed. This model exhibited good efficiency at forecasting short‐ and long‐term prognosis and could also act as an independent prognostic biomarker. Additionally, this model and four of its genes (CLECL5A, SERPING1, CHI3L1 and C1R) were found to be associated with immune cell infiltration, and further study demonstrated that these four genes might drive the hypoxic phenotype of perinecrotic GBM, which affects hypoxia‐induced glioma stemness. Therefore, these might be important candidates for immunotherapy of GBM and deserve further exploration.     

自噬基因CTSL表达与胶质母细胞瘤患者预后相关

本研究旨在探讨自噬基因CTSL对胶质母细胞瘤(GBM)患者的预后影响。利用癌症基因组图谱(TCGA)、人类自噬数据库(HADB)、中国脑胶质瘤基因组图谱(CGGA)数据库、基因表达谱分析(GEPIA)获取数据信息,通过筛选差异表达基因及单因素和多因素COX分析确定GBM的独立预后危险因素,同时通过基因本体论(GO)、基因组百科全书途径(KEGG)、临床病理相关性、基因集富集分析(GSEA)、自噬基因网络分析CTSL的相关作用机制。结果显示:(1)富集分析显示胶质母细胞瘤中差异自噬基因(ARG)与自噬体的形成、细胞凋亡、血管生成、细胞化疗等相关;(2)GBM中CTSL的mRNA水平明显高于正常组织样本;(3)多因素COX回归分析显示自噬基因CTSL的高表达为GBM预后的独立危险因素,STUPP治疗(术后替莫唑胺[Tmz]同步放化疗+Tmz辅助化疗)为独立保护因素;(4)自噬基因CTSL在非GCIMP(CpG岛甲基化)型、间质型、IDH野生型、1p/19q无缺失型胶质母细胞瘤及化疗后表达量更高。综上所述,本研究分析了自噬基因在GBM中的作用,并表明自噬基因CTSL的过表达预示胶质母细胞瘤患者不良预后,显示自噬基因CTSL有作为有效靶标的潜质。     

Prognostic significance of immune landscape in tumour microenvironment of endometrial cancer

Tumour microenvironment (TME) is crucial to tumorigenesis. This study aimed to uncover the differences in immune phenotypes of TME in endometrial cancer (EC) using Uterine Corpus Endometrial Carcinoma (UCEC) cohort and explore the prognostic significance. We employed GVSA enrichment analysis to cluster The Cancer Genome Atlas (TCGA) EC samples into immune signature cluster modelling, evaluated immune cell profiling in UCEC cohort (n = 538) and defined four immune subtypes of EC. Next, we analysed the correlation between immune subtypes and clinical data including patient prognosis. Furthermore, we analysed the expression of immunomodulators and DNA methylation modification. The profiles of immune infiltration in TCGA UCEC cohort showed significant difference among four immune subtypes of EC. Among each immune subtype, natural killer T cells (NKT), dendritic cells (DCs) and CD8⁺T cells were significantly associated with EC patients survival. Each immune subtype exhibited specific molecular classification, immune cell characterization and immunomodulators expression. Moreover, the expression immunomodulators were significantly related to DNA methylation level. In conclusion, the identification of immune subtypes in EC tissues could reveal unique immune microenvironments in EC and predict the prognosis of EC patients.     

IKBIP,a novel glioblastoma biomarker,maintains abnormal proliferation of tumor cells by inhibiting the ubiquitination and degradation of CDK4

Sustained proliferative signaling is a crucial hallmark and therapeutic target in glioblastoma (GBM); however, new intrinsic regulators and their underlying mechanisms remain to be elucidated. In this study, I kappa B kinase interacting protein (IKBIP) was identified to be correlated with the progression of GBM by analysis of The Cancer Genome Atlas (TCGA) data. TCGA database analysis indicated that higher IKBIP expression was associated with high tumor grade and poor prognosis in GBM patients, and these correlations were subsequently validated in clinical samples. IKBIP knockdown induced G1/S arrest by blocking the Cyclin D1/CDK4/CDK6/CDK2 pathway. Our results showed that IKBIP may bind directly to CDK4, a key cell cycle checkpoint protein, and prevent its ubiquitination-mediated degradation in GBM cells. An in vivo study confirmed that IKBIP knockdown strongly suppressed cell proliferation and tumor growth and prolonged survival in a mouse xenograft model established with human GBM cells. In conclusion, IKBIP functions as a novel driver of GBM by binding and stabilizing the CDK4 protein. IKBIP could be a potential therapeutic target in GBM.     

Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Gene expression profiling of GBM has revealed clinically relevant tumor subtypes, and this provides exciting opportunities to better understand disease pathogenesis. Results from an increasing number of studies demonstrate a role for the immune response in cancer progression, yet it is unclear how the immune response differs across tumor subtypes and how it affects outcome. Utilizing gene expression data from The Cancer Genome Atlas Project and the Gene Expression Omnibus database, we demonstrate an enrichment of immune response-related gene expression in the mesenchymal subtype of adult GBM (n = 173) and pediatric high-grade gliomas (n = 53). In an independent cohort of pediatric astrocytomas (n = 24) from UCSF, we stratified tumors into subtypes and confirmed these findings. Using novel immune cell-specific gene signatures we demonstrate selective enrichment of microglia/macrophage-related genes in adult and pediatric GBM tumors of the mesenchymal subtype. Furthermore, immunostaining of adult GBM tumors showed significantly higher cell numbers of microglia/macrophages in mesenchymal versus non-mesenchymal tumors (p = 0.04). Interestingly, adult GBM tumors with the shortest survival had significant enrichment of microglia/macrophage-related genes but this was not true for pediatric GBMs. Consistent with an association with poor outcome, immune response-related genes were highly represented in an adult poor prognosis gene signature, with the expression of genes related to macrophage recruitment and activation being most strongly associated with survival (p<0.05) using CoxBoost multivariate modeling. Using a microglia/macrophage high gene signature derived from quantification of tumor-infiltrating cells in adult GBM, we identified enrichment of genes characteristic of CD4 T cells, granulocytes, and microglia/macrophages (n = 573). These studies support a role for the immune response, particularly the microglia/macrophage response, in the biology of an important subset of GBM. Identification of this subset may be important for future therapeutic stratification.     

Identification of a novel tumour microenvironment-based prognostic biomarker in skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)-based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype-Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16-15, PRSS35, SLC7A10, IGHV1-69D and IGHV2-26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME-based prognostic biomarker in SKCM, and functional analysis enriched immune-related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.     

Metabolic reprogramming-associated genes predict overall survival for rectal cancer

Metabolic reprogramming has become a hot topic recently in the regulation of tumour biology. Although hundreds of altered metabolic genes have been reported to be associated with tumour development and progression, the important prognostic role of these metabolic genes remains unknown. We downloaded messenger RNA expression profiles and clinicopathological data from The Cancer Genome Atlas and the Gene Expression Omnibus database to uncover the prognostic role of these metabolic genes. Univariate Cox regression analysis and lasso Cox regression model were utilized in this study to screen prognostic associated metabolic genes. Patients with high-risk demonstrated significantly poorer survival outcomes than patients with low-risk in the TCGA database. Also, patients with high-risk still showed significantly poorer survival outcomes than patients with low-risk in the GEO database. What is more, gene set enrichment analyses were performed in this study to uncover significantly enriched GO terms and pathways in order to help identify potential underlying mechanisms. Our study identified some survival-related metabolic genes for rectal cancer prognosis prediction. These genes might play essential roles in the regulation of metabolic microenvironment and in providing significant potential biomarkers in metabolic treatment.     

Identification of microenvironment-related genes with prognostic value in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor. Previous studies have shown that the interaction between tumor cells and microenvironment has an important impact on prognosis. Immune and stromal cells are two vital components of the tumor microenvironment. Our study aimed to better understand and explore the genes involved in immune/stromal cells on prognosis. We used the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm to calculate immune/stromal scores. According to the scores, we divided ccRCC patients from The Cancer Genome Atlas database into low and high groups and identified the genes which were differentially expressed and significantly associated with prognosis. The result of functional enrichment analysis and protein-protein interaction networks indicated that these genes mainly were involved in extracellular matrix and regulation of cellular activities. Then another independent cohort from the International Cancer Genome Consortium database was used to validate these genes. Finally, we acquired a list of microenvironment-related genes that can predict prognosis for ccRCC patients.     

Profiles of immune-related genes and immune cell infiltration in the tumor microenvironment of diffuse lower-grade gliomas

The tumor microenvironment is highly correlated with tumor occurrence, progress, and prognosis. We aimed to investigate the immune-related gene (IRG) expression and immune infiltration pattern in the tumor microenvironment of lower-grade glioma (LGG). We employed the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm to calculate immune and stromal scores and identify prognostic IRG based on The Cancer Genome Atlas data set. The potential molecular functions of these genes were explored with the help of functional enrichment analysis and the protein–protein interaction network. Remarkably, three cohorts that were downloaded from the Chinese Glioma Genome Atlas database were analyzed to further verify the prognostic values of these genes. Moreover, the Tumor IMmune Estimation Resource (TIMER) algorithm was used to estimate the abundance of infiltrating immune cells and explore the immune infiltration pattern in LGG. And unsupervised cluster analysis determined three clusters of the immune infiltration pattern and indicated that CD8⁺ T cells and macrophages were significantly associated with LGG outcomes. Altogether, our study identified a list of prognostic IRGs and provided a perspective to explore the immune infiltration pattern in LGG.     

Prognostic value of tumour microenvironment-related genes by TCGA database in rectal cancer

Rectal cancer is a common malignant tumour and the progression is highly affected by the tumour microenvironment (TME). This study intended to assess the relationship between TME and prognosis, and explore prognostic genes of rectal cancer. The gene expression profile of rectal cancer was obtained from TCGA and immune/stromal scores were calculated by Estimation of Stromal and Immune cells in Malignant Tumors using Expression data (ESTIMATE) algorithm. The correlation between immune/stromal scores and survival time as well as clinical characteristics were evaluated. Differentially expressed genes (DEGs) were identified according to the stromal/immune scores, and the functional enrichment analyses were conducted to explore functions and pathways of DEGs. The survival analyses were conducted to clarify the DEGs with prognostic value, and the protein-protein interaction (PPI) network was performed to explore the interrelation of prognostic DEGs. Finally, we validated prognostic DEGs using data from the Gene Expression Omnibus (GEO) database by PrognoScan, and we verified these genes at the protein levels using the Human Protein Atlas (HPA) databases. We downloaded gene expression profiles of 83 rectal cancer patients from The Cancer Genome Atlas (TCGA) database. The Kaplan-Meier plot demonstrated that low-immune score was associated with worse clinical outcome (P = .034), metastasis (M1 vs. M0, P = .031) and lymphatic invasion (+ vs. -, P < .001). A total of 540 genes were screened as DEGs with 539 up-regulated genes and 1 down-regulated gene. In addition, 60 DEGs were identified associated with overall survival. Functional enrichment analyses and PPI networks showed that the DEGs are mainly participated in immune process, and cytokine-cytokine receptor interaction. Finally, 19 prognostic genes were verified by GSE17536 and GSE17537 from GEO, and five genes (ADAM23, ARHGAP20, ICOS, IRF4, MMRN1) were significantly different in tumour tissues compared with normal tissues at the protein level. In summary, our study demonstrated the associations between TME and prognosis as well as clinical characteristics of rectal cancer. Moreover, we explored and verified microenvironment-related genes, which may be the potential key prognostic genes of rectal cancer. Further clinical samples and functional studies are needed to validate this finding.     

Temozolomide resistance in glioblastoma cells occurs partly through epidermal growth factor receptor-mediated induction of connexin 43

Glioblastoma Multiforme (GBM) is an aggressive adult primary brain tumor with poor prognosis. GBM patients develop resistance to the frontline chemotherapy, temozolomide (TMZ). As the connexins (Cx) have been shown to have a complex role in GBM, we investigated the role of Cx43 in TMZ resistance. Cx43 was increased in the TMZ-resistant low passage and cell lines. This correlated with the data in The Cancer Genome Atlas. Cx43 knockdown, reporter gene assays, chromatin immunoprecipitation assay, real-time PCR and western blots verified a role for Cx43 in TMZ resistance. This occurred by TMZ-resistant GBM cells being able to activate epidermal growth factor receptor (EGFR). In turn, EGFR activated the JNK-ERK1/2-AP-1 axis to induce Cx43. The increased Cx43 was functional as indicated by gap junctional intercellular communication among the resistant GBM cells. Cell therapy could be a potential method to deliver drugs, such as anti-EGF to tumor cells. Similar strategies could be used to reverse the expression of Cx43 to sensitize GBM cells to TMZ. The studies showed the potential for targeting EGF in immune therapy. These agents can be used in conjunction with stem cell therapy to treat GBM.     

Identification of immunogenic cell death-associated subtypes and characterization of the tumor microenvironment in endometrial cancer

Immunogenic cell death (ICD) is one of the mechanisms regulating cell death, which activates adaptive immunity in immunocompetent hosts and is associated with tumor progression, prognosis and therapeutic response. Endometrial cancer (EC) is one of the most common malignancies of the female genital tract, and the potential role of immunogenic cell death-related genes (IRGs) in the tumor microenvironment (TME) remains unclear. We describe the variation of IRGs and assess the expression patterns in EC samples from The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Based on the expression of 34 IRGs, we identified two different ICD-related clusters and subsequently differentially expressed genes between the two ICD-related clusters were used for the identification of two ICD gene clusters. We identified the clusters and found that alterations in the multilayer IRG were associated with patient prognosis and TME cell infiltration characteristics. On this basis, ICD score risk scores were calculated, and ICD signatures were constructed and validated for their predictive power in EC patients. To help clinicians better apply the ICD signature, an accurate nomogram was constructed. The low ICD risk group was characterized by high microsatellite instability, high tumor mutational load, high IPS score and stronger immune activation. Our comprehensive analysis of IRGs in EC patients suggested a potential role in the tumor immune interstitial microenvironment, clinicopathological features and prognosis. These findings may improve our understanding of the role of ICDs, and provide a new basis for assessing prognosis and developing more effective immunotherapeutic strategies in EC.     

Identification of UGP2 as a progression marker that promotes cell growth and motility in human glioma

Glioblastoma (GBM) is one of the most common highly malignant primary brain tumor with poor prognosis. This study aimed to explore the possible mechanism by bioinformatics method and detect potential function of UGP2 of GBM. Gene expression microarray data of GSE4412 and messenger RNA-sequencing data of GBM with samples clinical information were downloaded from the Gene Expression Omnibus database and The Cancer Genome Atlas database, respectively. Differentially expressed genes (DEGs) analysis using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology based on R language. A total of 1000 common DEGs were identified in GBM samples, including 353 upregulated and 647 downregulated genes. Based on the random survival forest model, we identified UDP-glucose pyrophosphorylase 2 (UGP2) (upregulated gene) had a significant effect on GBM prognosis. Functional enrichment showed that UGP2 was enriched in the biological progresses of cell proliferation, migration, and invasion. Furthermore, UGP2 expression is aberrantly overexpressed in human glioma and positively correlated with pathologic grade. A loss-of-function study showed that knockdown of UGP2 decreases U251 cell growth, migration, and invasion in vivo and vitro. We proposed the development and progression of human glioma were associated with survival based on bioinformatics analysis. We also found that UGP2 might function as prognostic markers in the pathogenesis of GBM.     

Prognostic power of a lipid metabolism gene panel for diffuse gliomas

Lipid metabolism reprogramming plays important role in cell growth, proliferation, angiogenesis and invasion in cancers. However, the diverse lipid metabolism programmes and prognostic value during glioma progression remain unclear. Here, the lipid metabolism‐related genes were profiled using RNA sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database. Gene ontology (GO) and gene set enrichment analysis (GSEA) found that glioblastoma (GBM) mainly exhibited enrichment of glycosphingolipid metabolic progress, whereas lower grade gliomas (LGGs) showed enrichment of phosphatidylinositol metabolic progress. According to the differential genes of lipid metabolism between LGG and GBM, we developed a nine‐gene set using Cox proportional hazards model with elastic net penalty, and the CGGA cohort was used for validation data set. Survival analysis revealed that the obtained gene set could differentiate the outcome of low‐ and high‐risk patients in both cohorts. Meanwhile, multivariate Cox regression analysis indicated that this signature was a significantly independent prognostic factor in diffuse gliomas. Gene ontology and GSEA showed that high‐risk cases were associated with phenotypes of cell division and immune response. Collectively, our findings provided a new sight on lipid metabolism in diffuse gliomas.     

CXCL12 derived from CD248-expressing cancer-associated fibroblasts mediates M2-polarized macrophages to promote nonsmall cell lung cancer progression

Nonsmall cell lung cancer (NSCLC) is among the most prevalent malignant tumours threatening human health. In the tumour microenvironment (TME), cancer-associated fibroblasts (CAFs) induce M2-polarized macrophages, which strongly regulate tumour progression. However, little is known about the association between CAFs and M2 macrophages. CD248 is a transmembrane glycoprotein found in several cancer cells, tumour stromal cells, and pericytes. Here, we isolated CAFs from tumour tissues of NSCLC patients to detect the relationship between CD248 expression and patient prognosis. We knocked down the expression of CD248 on CAFs to detect CXCL12 secretion and macrophage polarization. We then examined the effects of CD248-expressing CAF-induced M2 macrophage polarization to promote NSCLC progression in vitro and in vivo. We found that CD248 is expressed mainly in NSCLC-derived CAFs and that the expression of CD248 correlates with poor patient prognosis. Blocking CXCL12 receptor (CXCR4) drastically decreased M2 macrophage chemotaxis. CD248 promotes CAFs secreting CXCL12 to mediate M2-polarized macrophages to promote NSCLC progression both in vitro and in vivo. Collectively, our data suggest that CD248-positive CAFs induce NSCLC progression by mediating M2-polarized macrophages.