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.     

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.     

Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in “iClusterPlus” R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time (P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.     

Identification of pathological grade and prognosis-associated lncRNA for ovarian cancer

Ovarian carcinoma (OC) is one of the most common malignant tumors in female genitals. In recent years, the therapeutic effect of OC has been significantly improved through the application of effective chemotherapy regimen. However, the 5-year survival rate is also lower than 30% due to high rate of relapse. So, it is needed to screen reliable predictive and prognostic markers of OC. Ovarian cancer gene expression data and corresponding clinical data used were downloaded from Gene Expression Omnibus database. Weighted gene expression network analysis (WGCNA) and Cox proportional hazards regression (PHR) were used to screen Pathological Grade and Prognosis-associated long noncoding RNA (lncRNA). Kaplan-Meier analysis and receiver operating characteristic curves analysis were performed to evaluate the predictive ability of the selected lncRNA. Gene Ontology (GO) enrichment and Gene Set Enrichment Analysis (GSEA) enrichment analysis methods were used to explore the possible mechanisms of the selected lncRNA affecting the development of OC. Five reliably lncRNAs (LINC00664, LINC00667, LINC01139, LINC01419, and LOC286437) was identified through a series of bioinformatics methods. In testing cohorts, we found that the five lncRNAs in predicting the risk of OC recurrence is robustness, and multivariate Cox PHR analysis indicate that the five lncRNAs is an independent risk factor for OC recurrence. Moreover, GO and GSEA enrichment analysis showed that the five lncRNAs are involved in multiple ovarian cancer occurrence mechanism. In summary, all these findings indicated that the five lncRNAs can effectively predict the risk of recurrence of ovarian cancer.     

Low expression of ENC1 predicts a favorable prognosis in patients with ovarian cancer

Ectodermal-neural cortex 1 (ENC1) belongs to a member of the kelch family of genes. It is an actin-binding protein and plays a pivotal role in neuronal and adipocyte differentiation. Here, we found that lower expression of ENC1 in the ovarian cancer patients was associated with favorable prognosis. In addition, ENC1 was heterogeneously expressed in various ovarian cancer cells. The messenger RNA and protein expression levels of ENC1 in HO-8910PM and NIH:OVCAR-3 cells were obviously higher than that in the other types of ovarian cancer cells. Knockdown of ENC1 in HO-8910PM or NIH:OVCAR-3 cells could significantly increase the reactive oxygen species levels, resulting in inhibition of in vitro proliferation, migration, and invasion. Our findings suggest that decreasing expression of ENC1 may be a new approach that can be used for ovarian cancer treatment.     

Tumour microenvironment‐based molecular profiling reveals ideal candidates for high‐grade serous ovarian cancer immunotherapy

ObjectiveDue to limited immunological profiles of high‐grade serous ovarian cancer (HGSOC), we aimed to characterize its molecular features to determine whether a specific subset that can respond to immunotherapy exists.Materials and MethodsA training cohort of 418 HGSOC samples from TCGA was analysed by consensus non‐negative matrix factorization. We correlated the expression patterns with the presence of immune cell infiltrates, immune regulatory molecules and other genomic or epigenetic features. Two independent cohorts containing 482 HGSOCs and in vitro experiments were used for validation.ResultsWe identified immune and non‐immune groups where the former was enriched in signatures that reflect immune cells, infiltration and PD‐1 signalling (all, P < 0.001), and presented with a lower chromosomal aberrations but increased neoantigens, tumour mutation burden, and microsatellite instability (all, P < 0.05); this group was further refined into two microenvironment‐based subtypes characterized by either immunoactivation or carcinoma‐associated fibroblasts (CAFs) and distinct prognosis. CAFs‐immune subtype was enriched for factors that mediate immunosuppression and promote tumour progression, including highly expressed stromal signature, TGF‐β signalling, epithelial‐mesenchymal transition and tumour‐associated M2‐polarized macrophages (all, P < 0.001). Robustness of these immune‐specific subtypes was verified in validation cohorts, and in vitro experiments indicated that activated‐immune subtype may benefit from anti‐PD1 antibody therapy (P < 0.05).ConclusionOur findings revealed two immune subtypes with different responses to immunotherapy and indicated that some HGSOCs may be susceptible to immunotherapies or combination therapies.     

浆液性卵巢癌铁死亡关键基因的筛选及[]生物信息学分析

利用生物信息学方法筛选浆液性卵巢癌相关铁死亡关键基因,并预测其生物学功能。从GEO数据库中获得有关浆液性卵巢癌的数据集GSE54388和GSE12470,采用R语言中的“Limma”包分析挑选浆液性卵巢癌上皮组织与正常卵巢上皮组织中差异表达基因,绘制火山图、热图。利用Venn软件在线工具绘制GSE54388,GSE12470,FerrDb三个数据集韦恩图。对相关基因进行功能富集分析、蛋白互作分析、生存分析,对关键基因绘制ROC曲线进行诊断分析。采用GEPIA2 数据库对筛选基因进行验证,并进行免疫浸润分析。结果发现:从GSE54388中筛选出2458个差异基因,其中上调1309个,下调1149个。从GSE12470中筛选出3534个差异基因,其中上调1 837个,下调1 697个。与铁死亡基因数据集取交集,共得到16个差异基因,蛋白互作网络筛选出7个基因构建的关键模块,绘制生存曲线发现浆液性卵巢癌患者中5个基因与患者总生存率不良相关,其中NRAS,PSAT1,CDKN2A,GDF15这4个基因高表达,CAV1低表达。ROC曲线显示这5个基因中CAV1,NRAS,PSAT1的AUC诊断曲线面积大于0.95,有较高的诊断价值。GEPIA2 数据库验证发现5个基因的表达情况与预测相符,仅NRAS基因表达在浆液性卵巢癌患者Ⅱ期、Ⅲ期、Ⅳ期有显著差异(P<0.05)。免疫浸润分析发现CDKN2A表达与aDC细胞浸润水平呈正相关(P<0.05,spearman相关系数0.353);CAV1表达与Mast细胞浸润正向关(P<0.05,spearman相关系数0.327);NRAS与T helper细胞浸呈正向关(P<0.05,spearman相关系数0.362)。通过生物信息学方法筛选出与浆液性卵巢癌铁死亡相关的5个基因CAV1,NRAS,PSAT1,CDKN2A,GDF15,可能在浆液性卵巢癌的发生发展中起重要作用,有望成为该病诊断、治疗和预后的潜在分子生物标志物。     

Interactions between immunity,proliferation and molecular subtype in breast cancer prognosis

Background

Gene expression signatures indicative of tumor proliferative capacity and tumor-immune cell interactions have emerged as principal biology-driven predictors of breast cancer outcomes. How these signatures relate to one another in biological and prognostic contexts remains to be clarified.

Results

To investigate the relationship between proliferation and immune gene signatures, we analyzed an integrated dataset of 1,954 clinically annotated breast tumor expression profiles randomized into training and test sets to allow two-way discovery and validation of gene-survival associations. Hierarchical clustering revealed a large cluster of distant metastasis-free survival-associated genes with known immunological functions that further partitioned into three distinct immune metagenes likely reflecting B cells and/or plasma cells; T cells and natural killer cells; and monocytes and/or dendritic cells. A proliferation metagene allowed stratification of cases into proliferation tertiles. The prognostic strength of these metagenes was largely restricted to tumors within the highest proliferation tertile, though intrinsic subtype-specific differences were observed in the intermediate and low proliferation tertiles. In highly proliferative tumors, high tertile immune metagene expression equated with markedly reduced risk of metastasis whereas tumors with low tertile expression of any one of the three immune metagenes were associated with poor outcome despite higher expression of the other two metagenes.

Conclusions

These findings suggest that a productive interplay among multiple immune cell types at the tumor site promotes long-term anti-metastatic immunity in a proliferation-dependent manner. The emergence of a subset of effective immune responders among highly proliferative tumors has novel prognostic ramifications.     

Overview of CD24 as a new molecular marker in ovarian cancer

Ovarian cancer (OC) is the fifth leading cause of cancer-related death among women. The high mortality rate is due to lack of early symptoms, late diagnosis, limited treatment options, and also emerging of drug resistance. Todays, molecular markers have become promising in tumor-targeted therapy. Several molecular markers have been known in OC immunotherapy. Identification of the specific molecular markers with prognostic significance is interested. CD24 is a small sialoglycoprotein which is localized in lipid rafts through its glycosylphosphatidylinositol (GPI) anchor. It has been reported that CD24 is overexpressed in many cancers including OC. Also, CD24 is identified as a cancer stem cell marker in OC. The CD24 expression is associated with the development, invasion, and metastasis of cancer cells. The exact role of CD24 in cancer cells is not clearly understood. Recently, CD24 has been identified as an independent prognostic marker of survival in patients with OC. In this study, we reviewed the molecular targets in OC immune-targeted therapy and also presented an overview of the new molecular marker CD24 and its association with the OC by reviewing the recent literature.     

Eg5 high expression predicts dismal prognosis in epithelial ovarian cancer

The expression of kinesin spindle protein (Eg5) and its significance of clinical prognosis of patients with epithelial ovarian cancer (EOC) were evaluated in this study. Forty-five fresh frozen tissue samples for quantitative real-time polymerase chain reaction (qPCR) and 196 samples for immunohistochemistry (IHC) analysis with tissue microarray (TMA) were applied to characterize Eg5 mRNA and protein expressions in EOC. The correlation between clinical parameters and Eg5 protein expression was investigated using statistical analysis. The expression of Eg5 protein was significantly higher in EOC tissues compared with that in corresponding non-cancerous tissues (P < 0.05). The high Eg5 expression was significantly correlated with older age (P = 0.003), higher stage (P = 0.001), presence of metastasis (P = 0.041) and higher CA125 serum level (P = 0.013). For univariate analysis, associated prognostic markers in patients with ovarian cancer were analyzed for correlations with poor overall survival, including Eg5 (P = 0.011), age (P = 0.001), FIGO stage (P = 0.011), CA125 serum level (P = 0.001), lymph nodes (P = 0.012), and metastasis (P = 0.001). For multivariate analysis, Eg5 expression, FIGO stage and age were independent factors found contributing to a largely unfavorable prognosis in patients with ovarian cancer. In conclusion, the high expression of Eg5 is correlated with an unfavorable prognosis in EOC.     

Immunomodulatory action of the DNA methyltransferase inhibitor SGI-110 in epithelial ovarian cancer cells and xenografts

We aimed to determine the effect of SGI-110 on methylation and expression of the cancer testis antigens (CTAs) NY-ESO-1 and MAGE-A in epithelial ovarian cancer (EOC) cells in vitro and in vivo and to establish the impact of SGI-110 on expression of major histocompatibility (MHC) class I and Intracellular Adhesion Molecule 1 (ICAM-1) on EOC cells, and on recognition of EOC cells by NY-ESO-1-specific CD8+ T-cells. We also tested the impact of combined SGI-110 and NY-ESO-1-specific CD8+ T-cells on tumor growth and/or murine survival in a xenograft setting. EOC cells were treated with SGI-110 in vitro at various concentrations and as tumor xenografts with 3 distinct dose schedules. Effects on global methylation (using LINE-1), NY-ESO-1 and MAGE-A methylation, mRNA, and protein expression were determined and compared to controls. SGI-110 treated EOC cells were evaluated for expression of immune-modulatory genes using flow cytometry, and were co-cultured with NY-ESO-1 specific T-cell clones to determine immune recognition. In vivo administration of SGI-110 and CD8+ T-cells was performed to determine anti-tumor effects on EOC xenografts. SGI-110 treatment induced hypomethylation and CTA gene expression in a dose dependent manner both in vitro and in vivo, at levels generally superior to azacitidine or decitabine. SGI-110 enhanced the expression of MHC I and ICAM-1, and enhanced recognition of EOC cells by NY-ESO-1-specific CD8+ T-cells. Sequential SGI-110 and antigen-specific CD8+ cell treatment restricted EOC tumor growth and enhanced survival in a xenograft setting. SGI-110 is an effective hypomethylating agent and immune modulator and, thus, an attractive candidate for combination with CTA-directed vaccines in EOC.     

HMP19 is a new metastasis suppressor in epithelial ovarian cancer

HMP19 is a neuron-specific gene; its expression product belongs to a family of neuronal proteins which can be found in numerous kinds of human cancers. However, the clinicopathological significance of HMP19 expression in epithelial ovarian cancer (EOC) is as yet unknown. In this study, protein expression levels of HMP19 in cancerous tissues were determined by tissue microarray immunohistochemistry analysis (TMA-IHC) (n = 117). HMP19 protein levels in cancer tissues were associated with clinical characteristics and overall survival rates of patients with EOC. It was found that both mRNA and protein levels of HMP19 were significantly lower in EOC than those in normal ovary or fallopian tube tissues (P<0.05). The protein expression level of HMP19 was significantly associated with a lower FIGO stage, a lower level of CA-125 and a lower presence of metastasis. Consistent with related adverse clinical pathological features, the overall survival (OS) rate of patients with low or non HMP19-expressing tumors was inferior compared to those with high HMP19-expressing tumors. This is in accordance with further studies that found high HMP19 protein level to be an independent prognostic factor for OS in EOC. Multivariate analysis demonstrated that tumor patients with low HMP19 expression had an exceedingly poor OS. HMP19 plays a role in metastasis/tumor suppression and offers a prognostic value for EOC. HMP19, as a new inhibitor, strongly inhibits metastasis and partially attenuates tumor growth in EOC.