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.     

A signature of immune-related gene pairs predicts oncologic outcomes and response to immunotherapy in lung adenocarcinoma

In this study, we established the predictive model for lung adenocarcinoma (LUAD) depending on immune-related gene pairs (IRGPs) signature, which could not consider the technical bias of different platforms. Furthermore, we explored the predictive model with regard to the immune microenvironment and response to immunotherapy and identified specific drugs targeting the IRGPs model. Twenty-three IRGPs were identified and comprised the predictive model. When compared with the high-risk group, the low-risk group displayed a distinctly favorable prognosis and was characterized by increased immune score and decreased tumor purity. In addition, the low-risk group exhibited higher expression of immune checkpoint molecules, lower tumor stemness index, and was much more sensitive to immunotherapy. Lastly, candidate drugs that aimed at LUAD subtype differentiation were identified. The derived IRGPs model is an adverse independent biomarker for estimating oncologic outcomes in LUAD patients, and may be helpful to formulate personalized immunotherapy strategy.     

Identification of immune-enhanced molecular subtype associated with BRCA1 mutations,immune checkpoints and clinical outcome in ovarian carcinoma

Ovarian carcinoma has the highest mortality among the malignant tumours in gynaecology, and new treatment strategies are urgently needed to improve the clinical status of ovarian carcinoma patients. The Cancer Genome Atlas (TCGA) cohort were performed to explore the immune function of the internal environment of tumours and its clinical correlation with ovarian carcinoma. Finally, four molecular subtypes were obtained based on the global immune-related genes. The correlation analysis and clinical characteristics showed that four subtypes were all significantly related to clinical stage; the immune scoring results indicated that most immune signatures were upregulated in C3 subtype, and the majority of tumour-infiltrating immune cells were upregulated in both C3 and C4 subtypes. Compared with other subtypes, C3 subtype had a higher BRCA1 mutation, higher expression of immune checkpoints, and optimal survival prognosis. These findings of the immunological microenvironment in tumours may provide new ideas for developing immunotherapeutic strategies for ovarian carcinoma.     

Ubiquitin-proteasome system reveals clinical subtypes with distinct molecular characteristics and prognoses in gastric cancer

Modulators in ubiquitin-proteasome system (UPS) has been implicated in regulating cancer-related genes, immune responses, and oncogenesis. However, the global UPS expression pattern and its role in gastric cancer (GC) pathology remain elusive. Herein, we integrated the modulators in UPS and dissected their associations with tumor microenvironment (TME), therapeutic response and prognosis in GC. Ten eligible GC cohorts (n = 2161) were collected in this comprehensive analysis. Unsupervised clustering based on expression profile of ubiquitination regulators was performed to identify distinct expression pattern. Then, pathway activation, and TME characteristics and prognosis were explored for patients in each pattern. Finally, a UPS scoring system in GC, termed UPSGC, is developed for individualized quantification of UPS expression pattern. Two prognosis-distinctive UPS expression patterns were identified and validated. Multiple interdependent characteristics were found in each pattern. Patients in the pattern with poor prognosis were found with activation of EMT, TNFα/NF-κB and IL6/JAK/STAT3 signaling, and more infiltration of immunosuppressive M2 macrophages and Th2 cells in TME. And another pattern was characterized by upregulation of angiogenesis, Notch and Wnt-β/catenin signaling, as well as enrichment of microvessels in TME. Based on the UPSGC system, two pattern-related clinical subtypes were identified. Finally, the UPSGC subtypes were validated as robust biomarker to predict patient's therapeutic responses and survival outcomes. In conclusion, this study proposes two previously unexplored UPS expression patterns in GC, in which patients have distinct survival outcomes and molecular characteristics. The findings provide new evidences to support the clinical relevance of ubiquitination with personalized therapy.     

Typical tumor immune microenvironment status determine prognosis in lung adenocarcinoma

BackgroundImmune cells, vital components of tumor microenvironment, regulate tumor survival and progression. Lung adenocarcinoma (LUAD), the tumor with the highest mortality rate worldwide, reconstitutes tumor immune microenvironment (TIME) to avoid immune destruction. Data have shown that TIME influences LUAD prognosis and predicts immunotherapeutic efficacy. The related information about the role of TIME's characteristics in LUAD is limited.MethodsWe performed unsupervised consensus clustering via machine-learning techniques to identify TIME clusters among 1906 patients and gathered survival data. The characteristics of TIME clusters of LUAD were visualized by multi-omics analysis, pseudo-time dynamic analysis, and enrichment analysis. TIME score model was constructed by principal component analysis. Comprehensive analysis and validation were conducted to test the prognostic efficacy and immunotherapeutic response of TIME score.ResultsTIME clusters (A, B and C) were constructed and exhibited different immune infiltration states. Multi-omics analyses included significant mutated genes (SMG), copy number variation (CNV) and cancer stemness that were significantly different among the three clusters. TIME cluster A had a lower SMG, lower CNV, and lower stemness but a higher immune infiltration level compared to TIME clusters B and C. TIME score showed that patients in low TIME score group had higher overall survival rates, higher immune infiltration level and high expression of immune checkpoints. In validation cohorts, low TIME score subgroup had better drug sensitivity and favorable immunotherapeutic response.ConclusionWe constructed a stable model of LUAD immune microenvironment characteristics that may improve the prognostic accuracy of patients, provide improved explanations of LUAD responses to immunotherapy, and provide new strategies for LUAD treatment.     

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.     

Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BackgroundRecent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.MethodsTwo sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.ResultsMacrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.ConclusionThis study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.     

NOD2 deficiency confers a pro-tumorigenic macrophage phenotype to promote lung adenocarcinoma progression

Nucleotide-binding and oligomerization domain-containing protein 2 (NOD2) was a member of the NOD-like receptor family and played an important role in the innate immune response. Dysregulated NOD2 had been reported to contribute to tumorigenesis and progression. Here, we investigated that decreased NOD2 expressions could affect the phenotypic polarization of tumour-associated macrophages and thus lead to the poor prognosis of lung adenocarcinoma patients. We clustered the patients by the single-sample gene set enrichment analysis of tumour microenvironment and 13 prognostic differentially expressed immune-related genes (PDEIRGs) were obtained based on prognostic analyses. After multiple assessments on the 13 PDEIRGs, NOD2 was considered to be the central immune gene and had a strong effect on suppressing tumour progression. Decreased NOD2 expression could be induced by cancer cells and lead to the phenotypic polarization of macrophages from protective M1 phenotype to pro-tumorigenic M2 subtype which might be attributed to the down-regulating of NF-κB signalling pathway. This study draw attention to the role of inhibited innate immune function mediated by depletion of NOD2 in the TME. Our work also points to a potential strategy of NOD2-mediated TAM-targeted immunotherapy.     

Intra-tumoral infiltration of adipocyte facilitates the activation of antitumor immune response in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy that is characterized by an immunosuppressive microenvironment. The immune suppression in PDAC is largely driven by heterogeneous stromal and tumor cells. However, how adipocyte in the tumor microenvironment (TME) is related to the immune cell infiltration in PDAC has rarely been published. We identified adipocytes by performing bioinformatics analyses, and explored the clinical outcomes and TME characters in PDAC with different levels of adipocyte infiltration. Interestingly, in contrast to adiposity, high adipocyte infiltration in the TME was related to significantly increased median overall survival and a lower total tumor mutational burden. Functionally, high adipocyte infiltration was associated with the immune response, particularly with the abundant cytokine infiltration in PDAC samples. Moreover, adipocyte infiltration in the TME was positively associated with anticancer signatures in the immune microenvironment. Immunohistochemistry and RT-PCR were performed with PDAC tissue samples from our center to study the expression of adipocytes in PDAC. The mature adipocytes were strongly associated with the immune composition and prognosis of patients with PDAC. Primary adipocytes were isolated from mice to construct a PDAC transplantation tumor model. In vivo experiments showed that adipocytes elicited increased CD8+ T cell infiltration and potent antitumor activity in tumor-bearing mice. Overall, we innovatively found that adipocytes facilitated the antitumor immune response in the TME by performing mouse experiments and analyzing PDAC samples. This study provides a new perspective on the activation of the immune microenvironment in PDAC.     

Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer

Breast cancer is the most common cancer and the leading cause of cancer death among women in the world. Tumour-infiltrating lymphocytes were defined as the white blood cells left in the vasculature and localized in tumours. Recently, tumour-infiltrating lymphocytes were found to be associated with good prognosis and response to immunotherapy in tumours. In this study, to examine the influence of FLI1 in immune system in breast cancer, we interrogated the relationship between the FLI1 expression levels with infiltration levels of 28 immune cell types. By splitting the breast cancer samples into high and low expression FLI1 subtypes, we found that the high expression FLI1 subtype was enriched in many immune cell types, and the up-regulated differentially expressed genes between them were enriched in immune system processes, immune-related KEGG pathways and biological processes. In addition, many important immune-related features were found to be positively correlated with the FLI1 expression level. Furthermore, we found that the FLI1 was correlated with the immune-related genes. Our findings may provide useful help for recognizing the relationship between tumour immune microenvironment and FLI1, and may unravel clinical outcomes and immunotherapy utility for FLI1 in breast cancer.     

丝氨酸蛋白酶抑制剂(SERPIN)家族相关基因在结肠腺癌中预后模型的建立及应用

应用生物信息学方法,构建结肠腺癌(COAD)丝氨酸蛋白酶抑制剂(SERPIN)家族相关基因预后模型。从TCGA数据库和GEO数据库下载结肠腺癌(COAD)转录组和临床数据,根据数据中SERPINs家族基因的表达量对COAD患者进行一致性聚类分析;将数据随机均分为训练集(Train)组和验证集(Test)组,基于两个亚型的差异基因,利用Train组进行COX回归和Lasso回归构建预后模型,根据模型风险评分中位值将样本分为高、低风险两组,绘制高低风险组患者生存曲线;通过ROC曲线评价模型预测能力;利用Test组数据验证模型;构建列线图,评估患者生存率模型预测值与实际值的一致性;并利用利用ESTIMATE算法和CIBERSORT算法评估风险评分和肿瘤微环境(TME)以及免疫浸润的相关性。通过34个SERPIN基因确定了两个亚型,基于2个亚型筛选出了436个预后相关分型差异基因,通过Lasso回归确定出了11个预后相关基因参与风险模型的构建,根据模型评分区分的高低风险组具有明显的生存差异,列线图可以准确预测1、3和5年生存率。肿瘤微环境分析和免疫浸润分析显示高风险评分组患者免疫活性差。SERPIN家族相关基因构建的风险评分模型能够预测COAD的预后,有利于进一步指导临床对COAD的诊治,提高患者生存率。     

Intratumor IL-17-Positive Mast Cells Are the Major Source of the IL-17 That Is Predictive of Survival in Gastric Cancer Patients

Interleukin-17 (IL-17) is prevalent in tumor tissue and suppresses effective anti-tumor immune responses. However, the source of the increased tumor-infiltrating IL-17 and its contribution to tumor progression in human gastric cancer remain poorly understood. In this study, we enrolled 112 gastric cancer patients, immunofluorescence was used to evaluate the colocalization of CD3, CD4, CD56, CD20, CD68, and mast cell tryptase (MCT) with IL-17. Immunohistochemistry was used to evaluate the distribution of microvessel density (CD34), CD66b⁺, CD68⁺, and FoxP3⁺ cells in different microanatomical areas. Prognostic value was determined by Kaplan-Meier analysis and a Cox regression model. The results showed that mast cells, but not T cells or macrophages, were the predominant cell type producing IL-17 in gastric cancer. Significant positive correlations were detected between densities of mast cell-derived IL-17 and microvessels, neutrophils, and regulatory T cells (Tregs). Futhermore, we found that the majority of vascular endothelial cells expressing Interleukin-17 receptor (IL-17R). Kaplan-Meier analysis revealed that increasing intratumor infiltrated mast cells and IL-17⁺ cells, as well as MCT⁺ IL-17⁺ cells, were significantly associated with worse overall survival. These findings indicated that mast cells were the major source of IL-17 in gastric cancer, and intratumor IL-17 infiltration may have promoted tumor progression by enhancing angiogenesis in the tumor microenvironment through the axis of IL-17/IL-17R. IL-17-positive mast cells showed a prognostic factor in gastric cancer, indicating that immunotherapy targeting mast cells might be an effective strategy to control intratumor IL-17 infiltration, and consequently reverse immunosuppression in the tumor microenvironment, facilitating cancer immunotherapy.     

Immune and Inflammatory Cell Composition of Human Lung Cancer Stroma

Recent studies indicate that the abnormal microenvironment of tumors may play a critical role in carcinogenesis, including lung cancer. We comprehensively assessed the number of stromal cells, especially immune/inflammatory cells, in lung cancer and evaluated their infiltration in cancers of different stages, types and metastatic characteristics potential. Immunohistochemical analysis of lung cancer tissue arrays containing normal and lung cancer sections was performed. This analysis was combined with cyto-/histomorphological assessment and quantification of cells to classify/subclassify tumors accurately and to perform a high throughput analysis of stromal cell composition in different types of lung cancer. In human lung cancer sections we observed a significant elevation/infiltration of total-T lymphocytes (CD3⁺), cytotoxic-T cells (CD8⁺), T-helper cells (CD4⁺), B cells (CD20⁺), macrophages (CD68⁺), mast cells (CD117⁺), mononuclear cells (CD11c⁺), plasma cells, activated-T cells (MUM1⁺), B cells, myeloid cells (PD1⁺) and neutrophilic granulocytes (myeloperoxidase⁺) compared with healthy donor specimens. We observed all of these immune cell markers in different types of lung cancers including squamous cell carcinoma, adenocarcinoma, adenosquamous cell carcinoma, small cell carcinoma, papillary adenocarcinoma, metastatic adenocarcinoma, and bronchioloalveolar carcinoma. The numbers of all tumor-associated immune cells (except MUM1⁺ cells) in stage III cancer specimens was significantly greater than those in stage I samples. We observed substantial stage-dependent immune cell infiltration in human lung tumors suggesting that the tumor microenvironment plays a critical role during lung carcinogenesis. Strategies for therapeutic interference with lung cancer microenvironment should consider the complexity of its immune cell composition.     

Identification of metabolism-associated molecular subtype in ovarian cancer

Ovarian cancer (OC) is the most lethal gynaecological cancer with genomic complexity and extensive heterogeneity. This study aimed to characterize the molecular features of OC based on the gene expression profile of 2752 previously characterized metabolism-relevant genes and provide new strategies to improve the clinical status of patients with OC. Finally, three molecular subtypes (C1, C2 and C3) were identified. The C2 subtype displayed the worst prognosis, upregulated immune-cell infiltration status and expression level of immune checkpoint genes, lower burden of copy number gains and losses and suboptimal response to targeted drug bevacizumab. The C1 subtype showed downregulated immune-cell infiltration status and expression level of immune checkpoint genes, the lowest incidence of BRCA mutation and optimal response to targeted drug bevacizumab. The C3 subtype had an intermediate immune status, the highest incidence of BRCA mutation and a secondary optimal response to bevacizumab. Gene signatures of C1 and C2 subtypes with an opposite expression level were mainly enriched in proteolysis and immune-related biological process. The C3 subtype was mainly enriched in the T cell-related biological process. The prognostic and immune status of subtypes were validated in the Gene Expression Omnibus (GEO) dataset, which was predicted with a 45-gene classifier. These findings might improve the understanding of the diversity and therapeutic strategies for OC.