Identification of a novel cell cycle-related gene signature predicting survival in patients with gastric cancer

Gastric cancer (GC) is one of the most fatal cancers in the world. Thousands of biomarkers have been explored that might be related to survival and prognosis via database mining. However, the prediction effect of single gene biomarkers is not specific enough. Increasing evidence suggests that gene signatures are emerging as a possible better alternative. We aimed to develop a novel gene signature to improve the prognosis prediction of GC. Using the messenger RNA (mRNA)-mining approach, we performed mRNA expression profiling in a large GC cohort (n = 375) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and we recovered genes related to the G2/M checkpoint, which we identified with a Cox proportional regression model. We identified a set of five genes (MARCKS, CCNF, MAPK14, INCENP, and CHAF1A), which were significantly associated with overall survival (OS) in the test series. Based on this five-gene signature, the test series patients could be classified into high-risk or low-risk subgroups. Multivariate Cox regression analysis indicated that the prognostic power of this five-gene signature was independent of clinical features. In conclusion, we developed a five-gene signature related to the cell cycle that can predict survival for GC. Our findings provide novel insight that is useful for understanding cell cycle mechanisms and for identifying patients with GC with poor prognoses.     

Identification of a five-gene signature with prognostic value in colorectal cancer

Colorectal cancer (CRC) ranks as one of the most commonly diagnosed malignancies worldwide. Although mortality rates have been decreasing, the prognosis of CRC patients is still highly dependent on the individual. Therefore, identifying and understanding novel biomarkers for CRC prognosis remains crucial. The gene expression profiles of five-gene expression omnibus (GEO) data sets of CRC were first downloaded. A total of 352 consistent differentially expressed genes (DEGs) were identified for CRC and paired with normal tissues. Functional analysis including gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment revealed that these DEGs were related to metabolic pathways, tight junctions, and the cell cycle. Ten hub DEGs were identified based on the search tool for the retrieval of interacting genes database and protein–protein interaction networks. By using univariate Cox proportional hazard regression analysis, we found 11 survival-related genes among these DEGs. We finally established a five-gene signature (kinesin family member 15, N-acetyltransferase 2, glutathione peroxidase 3, secretogranin II, and chloride channel accessory 1) with prognostic value in CRC by step multivariate Cox regression analysis. Based on this risk scoring system, patients in the high-risk group had significantly poorer survival results compared with those in the low-risk group (log-rank test, p < 0.0001). Finally, we validated our gene signature scoring system in two independent GEO cohorts (GSE17536 and GSE33113). We found all five of the signature genes to be DEGs in The Cancer Genome Atlas database. In conclusion, our findings suggest that our five DEG-based signature can provide a novel biomarker with useful applications in CRC prognosis.     

YAP Promotes Ovarian Cancer Cell Tumorigenesis and Is Indicative of a Poor Prognosis for Ovarian Cancer Patients

YAP is a key component of the Hippo signaling pathway and plays a critical role in the development and progression of multiple cancer types, including ovarian cancer. However, the effects of YAP on ovarian cancer development in vivo and its downstream effectors remain uncertain. In this study we found that strong YAP expression was associated with poor ovarian cancer patient survival. Specifically, we showed for the first time that high YAP expression levels were positively correlated with TEAD4 gene expression, and their co-expression was a prognostic marker for poor ovarian cancer survival. Hyperactivation of YAP by mutating its five inhibitory phosphorylation sites (YAP-5SA) increased ovarian cancer cell proliferation, resistance to chemotherapeutic drugs, cell migration, and anchorage-independent growth. In contrast, expression of a dominant negative YAP mutant reversed these phenotypes in ovarian cancer cells both in vitro and in vivo. Our results suggested that YAP caused these effects by promoting an epithelial-to-mesenchymal transition. Thus, YAP promotes ovarian cancer cell growth and tumorigenesis both in vitro and in vivo. Further, high YAP and TEAD4 expression is a prognostic marker for ovarian cancer progression and a potential target for ovarian cancer treatment.     

A new m6A methylation-related gene signature for prognostic value in patient with urothelial carcinoma of the bladder

Background: Bladder cancer (BC) is one of the most common malignant urological cancer in the world. Because of its characteristic of easy-recurrence and muscle-invasive, advances in our genetic understanding of bladder cancer should be translated into prognostic indicators.Methods: We investigated 16 m⁶A RNA methylation regulators from The Cancer Genome Atlas (TCGA) database and The Human Protein Atlas (HPA) database. The expression profile, clinical application as well as prognostic value of these genes in UC were investigated. Moreover, we further explored the correlation between RNA methylation genes and biological functions, pathways and immune status.Results: Five m⁶A-related genes (HNRNPC, YTHDF2, YTHDF1, HNRNPA2B1, METTL3) up-regulated in UC tissues, while three regulators (ZC3H13, METTL16, FTO) down-regulated in UC. FTO and YTHDF2 show biomarker potential for the prognosis of UC patients. In addition, these identified genes may related with essential functions and core molecular pathways.Conclusions: Our research shows that two m⁶A RNA methylation regulators can serve as reliable prognostic biomarkers of UC, which might be exerted as potential targets of therapeutic strategies.     

A Comprehensive Analysis of CXCL12 Isoforms in Breast Cancer1,2

CXCL12-CXCR4-CXCR7 signaling promotes tumor growth and metastasis in breast cancer. Alternative splicing of CXCL12 produces isoforms with distinct structural and biochemical properties, but little is known about isoform-specific differences in breast cancer subtypes and patient outcomes. We investigated global expression profiles of the six CXCL12 isoforms, CXCR4, and CXCR7 in The Cancer Genome Atlas breast cancer cohort using next-generation RNA sequencing in 948 breast cancer and benign samples and seven breast cancer cell lines. We compared expression levels with several clinical parameters, as well as metastasis, recurrence, and overall survival (OS). CXCL12-α, -β, and -γ are highly co-expressed, with low expression correlating with more aggressive subtypes, higher stage disease, and worse clinical outcomes. CXCL12-δ did not correlate with other isoforms but was prognostic for OS and showed the same trend for metastasis and recurrence-free survival. Effects of CXCL12-δ remained independently prognostic when taking into account expression of CXCL12, CXCR4, and CXCR7. These results were also reflected when comparing CXCL12-α, -β, and -γ in breast cancer cell lines. We summarized expression of all CXCL12 isoforms in an important chemokine signaling pathway in breast cancer in a large clinical cohort and common breast cancer cell lines, establishing differences among isoforms in multiple clinical, pathologic, and molecular subgroups. We identified for the first time the clinical importance of a previously unstudied isoform, CXCL12-δ.     

Construction of a five-gene prognostic model based on immune-related genes for the prediction of survival in pancreatic cancer

Purpose: To identify differentially expressed immune-related genes (DEIRGs) and construct a model with survival-related DEIRGs for evaluating the prognosis of patients with pancreatic cancer (PC).Methods: Six microarray gene expression datasets of PC from the Gene Expression Omnibus (GEO) and Immunology Database and Analysis Portal (ImmPort) were used to identify DEIRGs. RNA sequencing and clinical data from The Cancer Genome Atlas Program-Pancreatic Adenocarcinoma (TCGA-PAAD) database were used to establish the prognostic model. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to determine the final variables of the prognostic model. The median risk score was used as the cut-off value to classify samples into low- and high-risk groups. The prognostic model was further validated using an internal validation set of TCGA and an external validation set of {"type":"entrez-geo","attrs":{"text":"GSE62452","term_id":"62452"}}GSE62452.Results: In total, 142 DEIRGs were identified from six GEO datasets, 47 were survival-related DEIRGs. A prognostic model comprising five genes (i.e., ERAP2, CXCL9, AREG, DKK1, and IL20RB) was established. High-risk patients had poor survival compared with low-risk patients. The 1-, 2-, 3-year area under the receiver operating characteristic (ROC) curve of the model reached 0.85, 0.87, and 0.93, respectively. Additionally, the prognostic model reflected the infiltration of neutrophils and dendritic cells. The expression of most characteristic immune checkpoints was significantly higher in the high-risk group versus the low-risk group.Conclusions: The five-gene prognostic model showed reliably predictive accuracy. This model may provide useful information for immunotherapy and facilitate personalized monitoring for patients with PC.     

Epigenetic instability of imprinted genes in human cancers

Many imprinted genes are often epigenetically affected in human cancers due to their functional linkage to insulin and insulin-like growth factor signaling pathways. Thus, the current study systematically characterized the epigenetic instability of imprinted genes in multiple human cancers. First, the survey results from TCGA (The Cancer Genome Atlas) revealed that the expression levels of the majority of imprinted genes are downregulated in primary tumors compared to normal cells. These changes are also accompanied by DNA methylation level changes in several imprinted domains, such as the PEG3, MEST and GNAS domains. Second, these DNA methylation level changes were further confirmed manually using several sets of cancer DNA. According to the results, the Imprinting Control Regions of the PEG3, MEST and GNAS domains are indeed affected in breast, lung and ovarian cancers. This DNA methylation survey also revealed that evolutionarily conserved cis-regulatory elements within these imprinted domains are very variable in both normal and cancer cells. Overall, this study highlights the epigenetic instability of imprinted domains in human cancers and further suggests its potential use as cancer biomarkers.     

High density of IL-17-producing cells is associated with improved prognosis for advanced epithelial ovarian cancer

Interleukin (IL)-17 is the signature cytokine of T helper 17 cells. The role of IL-17 in the tumor microenvironment is still controversial. Few studies describing IL-17 expression in ovarian cancer have been reported. We have therefore analyzed the in situ tumor expression of IL-17 in advanced ovarian cancer and the possible correlation of IL-17 expression with tumor-associated macrophages (TAMs) and with survival in advanced ovarian cancer. Clinical data of 104 patients with stage III–IV epithelial ovarian cancer at the Sun Yat-sen University Cancer Center between 2000 and 2008 were retrospectively reviewed. Immunohistochemical staining of IL-17 and CD163 (marker for TAMs) was performed. Our data showed that levels of IL-17 were significantly increased in ovarian cancer compared with normal ovarian tissues (P<0.001). The high IL-17 expression group included more patients with grade 1 tumors than the low IL-17 expression group (P=0.042). High IL-17 expression correlated with improved progression-free survival (PFS) in advanced ovarian cancer (P<0.001). However, no significant difference was observed in overall survival between the high and low IL-17 expression groups. Multivariate analysis revealed that the density of IL-17-producing cells was a positive prognostic factor for PFS (P=0.001). Moreover, a positive correlation between the density of IL-17-producing cells and TAMs was identified (r=0.354, P<0.001). Our results indicate that the infiltration of IL-17-producing cells might contribute to improved PFS in advanced ovarian cancer. Our findings provide a new insight into the complex role of IL-17 in the tumor microenvironment of ovarian cancer.     

Bioinformatics analysis reveals disturbance mechanism of MAPK signaling pathway and cell cycle in Glioblastoma multiforme

Background & objectives

To analyze the reversal gene pairs and identify featured reversal genes related to mitogen-activated protein kinases (MAPK) signaling pathway and cell cycle in Glioblastoma multiforme (GBM) to reveal its pathogenetic mechanism.

Methods

We downloaded the gene expression profile GSE4290 from the Gene Expression Omnibus database, including 81 gene chips of GBM and 23 gene chips of controls. The t test was used to analyze the DEGs (differentially expressed genes) between 23 normal and 81 GBM samples. Then some perturbing metabolic pathways, including MAPK (mitogen-activated protein kinases) and cell cycle signaling pathway, were extracted from KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database. Cancer genes were obtained from the database of Cancer Gene Census. The reversal gene pairs between DEGs and cancer genes were further analyzed in MAPK and cell cycle signaling pathway.

Results

A total 8523 DEGs were obtained including 4090 up-regulated and 4433 down-regulated genes. Among them, ras-related protein rab-13(RAB13), neuroblastoma breakpoint family member 10 (NBPF10) and disks large homologue 4 (DLG4) were found to be involved in GBM for the first time. We obtained MAPK and cell cycle signaling pathways from KEGG database. By analyzing perturbing mechanism in these two pathways, we identified several reversal gene pairs, including NRAS (neuroblastoma RAS) and CDK2 (cyclin-dependent kinase 2), CCND1 (cyclin D1) and FGFR (fibroblast growth factor receptor). Further analysis showed that NRAS and CDK2 were positively related with GBM. However, FGFR2 and CCND1 were negatively related with GBM.

Interpretation & conclusions

These findings suggest that newly identified DEGs and featured reversal gene pairs participated in MAPK and cell cycle signaling pathway may provide a new therapeutic line of approach to GBM.     

Expression of c-Src and phospho-Src in epithelial ovarian carcinoma

Abnormal c-Src expression and activation has been observed in a number of tumors. To determine the therapeutic potential of Src inhibitors for ovarian cancer patients, this study aimed to explore the expression patterns of c-Src and phospho-Src in epithelial ovarian cancer. A total of 82 patients with epithelial ovarian cancer treated at Sun Yat-sen University Cancer Center from January 1999 to December 2005 were enrolled along with 25 patients with benign ovarian lesions; 20 normal ovarian tissues served as controls. Expression of c-Src and phospho-Src (Tyr416) was examined using immunohistochemistry. Survival analyses were performed using Kaplan–Meier curves. As compared to the control group, a significantly greater proportion of ovarian cancer tissues were positive for c-Src and phospho-Src expression (P < 0.001). c-Src expression was associated with age, while phospho-Src expression was significantly associated with age, FIGO stage, histology grade, and residual tumor size after surgery (all P < 0.05). The mean survival time was associated with phospho-Src expression, but not with c-Src expression. The mean survival times of patients with phospho-Src-positive tumors were significantly greater than those with phospho-Src-negative tumors (87.4 months, 95 % CI = 74.3–100.5 months and 91.5 months, 95 % CI = 84.7–98.2 months, respectively; P = 0.013). The increased c-Src expression and activation in epithelial ovarian cancer suggests that ovarian cancer patients may benefit from tyrosine kinase inhibitors such as Dasatinib. Activation of c-Src through phosphorylation at Tyr416 may play a role in the early stages of ovarian cancer development, and evaluation of its expression may be a useful prognostic marker of epithelial ovarian cancer.     

Cloning of a retinally abundant regulator of G-protein signaling (RGS-r/RGS16): genomic structure and chromosomal localization of the human gene

Regulators of G-protein signaling (RGS) constitute a family of GTPase-activating proteins with varying tissue-specific expression patterns and G-protein alpha subunit specificities. Here, we describe the molecular cloning of the human RGS-r/RGS16 cDNA, encoding a predicted polypeptide of 23 kDa that shows 86% identity to mouse RGS-r. Northern blot analysis shows that, like the mouse Rgs-r message, hRGS-r mRNA is abundantly expressed in retina, with lower levels of expression in most other tissues examined. Characterization of the genomic organization of the hRGS-r gene shows that it consists of five exons and four introns. We have also mapped the human RGS-r /RGS16 gene to chromosome 1q25–1q31 by fluorescence in situ hybridzation. Analysis of human ESTs reveals that at least five members of the RGS gene family map to chromosome 1q, suggesting that at least part of the RGS family arose through gene duplication. The chromosomal location, retinal abundance, and presumed function of the human RGS-r protein in desensitizing photoreceptor signaling make the RGS-r/RGS16 locus a candidate for mutations responsible for retinitis pigmentosa with para-arteriolar preservation of retinal pigment epithelium (RP-PPRE or RP12), an autosomal recessive disorder previously mapped to 1q31.     

Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening

Background

In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC’s prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA).

Results

With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data.

Conclusions

Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients’ survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These biomarkers shared a significant overlap, indicating that they were technically replicable.

     

Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) as prognostic biomarkers for colorectal cancer

Owing to the high morbidity and mortality, novel biomarkers in the occurrence and development of colorectal cancer (CRC) are needed nowadays. In this study, the CRC-related datasets were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. After screening the differentially expressed genes (DEGs) in R software, a total of 238 upregulated and 199 downregulated DEGs were revealed simultaneously. Then the Kaplan-Meier survival analysis and Cox regression analysis were used to reveal the prognostic function of these DEGs. Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) were two outstanding independent overall survival (OS) and relapse-free survival (RFS) prognostic genes of CRC in TCGA database. We next verified the expression of NXPE4 and PARM1 messenger RNA (mRNA) levels were significantly lower in CRC tumor tissue than in the adjacent noncancerous tissue in our clinical samples, and NXPE4 mRNA expression level was related to the tumor location and tumor size, while PARM1 was related to tumor location, lymph nodes metastasis, and tumor size. This study demonstrated that NXPE4 and PARM1 might be two potential novel prognostic biomarkers for CRC.     

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.     

UBE2C triggers HIF‐1α‐glycolytic flux in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the most common malignancy in Taiwan. Therefore, refining the diagnostic sensitivity of biomarkers for early‐stage tumours and identifying therapeutic targets are critical for improving the survival rate of HNSCC patients. Metabolic reprogramming contributes to cancer development and progression. Metabolic pathways, specifically, play a crucial role in these diverse biological and pathological processes, which include cell proliferation, differentiation, apoptosis and carcinogenesis. Here, we investigated the role and potential prognostic value of the ubiquitin‐conjugating enzyme E2 (UBE2) family in HNSCC. Gene expression database analysis followed by tumour comparison with non‐tumour tissue showed that UBE2C was upregulated in tumours and was associated with lymph node metastasis in HNSCC patients. Knockdown of UBE2C significantly reduced the invasion/migration abilities of SAS and CAL27 cells. UBE2C modulates glycolysis pathway activation and HIF‐1α expression in SAS and CAL27 cells. CoCl₂ (HIF‐1α inducer) treatment restored the expression of glycolytic enzymes and the migration/invasion abilities of UBE2C knockdown cells. Based on our findings, UBE2C expression mediates HIF‐1α activation, increasing glycolysis pathway activation and the invasion/migration abilities of cancer cells. UBE2C may be an independent prognostic factor and a therapeutic target in HNSCC.     

Differential expression analysis in ovarian cancer: A functional genomics and systems biology approach

BackgroundOvarian cancer is one of the rarest lethal oncologic diseases that have hardly any specific biomarkers. The availability of high-throughput genomic data and advancement in bioinformatics tools allow us to predict gene biomarkers and apply systems biology approaches to get better diagnosis, and prognosis of the disease with a tentative drug that may be repurposed.ObjectiveTo perform genome-wide association studies using microarray gene expression of ovarian cancer and identify gene biomarkers, construction and analyze networks, perform survival analysis, and drug interaction studies for better diagnosis, prognosis, and treatment of ovarian cancer.MethodThe gene expression profiles of both healthy and serous ovarian cancer epithelial samples were considered. We applied a series of bioinformatics methods and tools, including fold-change statistics for differential expression analysis, DisGeNET and NCBI-Gene databases for gene-disease association mapping, DAVID 6.8 for GO enrichment analysis, GeneMANIA for network construction, Cytoscape 3.8 with its plugins for network visualization, analysis, and module detection, the UALCAN for patient survival analysis, and PubChem, DrugBank and DGIdb for gene-drug interaction.ResultsWe identified 8 seed genes that were subjected for drug-gene interaction studies. Because of over-expression in all the four stages of ovarian cancer, we discern that genes HMGA1 and PSAT1 are potential therapeutic biomarkers for its diagnosis at an early stage (stage I). Our analysis suggests that there are 11 drugs common in the seed genes. However, hypermethylated seed genes HMGA1 and PSAT1 showcased a good interaction affinity with drugs cisplatin, cyclosporin, bisphenol A, progesterone, and sunitinib, and are crucial in the proliferation of ovarian cancer.ConclusionOur study reveals that HMGA1 and PSAT1 can be deployed for initial screening of ovarian cancer and drugs cisplatin, bisphenol A, cyclosporin, progesterone, and sunitinib are effective in curbing the epigenetic alteration.     

High expression of DLL3 is associated with a poor prognosis and immune infiltration in invasive breast cancer patients

BackgroundPrevious studies have shown the prognostic value of delta like canonical Notch ligand 3 (DLL3) in patients with different types of tumors, but the role and predictive value of DLL3 in invasive breast cancer (IBC) have not been reported. In this study, we explored the prognostic ability and potential ways of DLL3 in IBC patients.MethodsWe retrospectively enrolled 130 IBC patients from a single institution from 2004 to 2019 for bioinformatics and statistical analysis. The Cancer Genome Atlas breast invasive carcinoma (TCGA-BRCA) cohort was used for verification.ResultsHigh expression of DLL3 was associated with overall survival (OS) in IBC patients (P = 0.023). Multivariate analysis further showed that DLL3 expression was an independent prognostic factor (hazard ratio [HR]: 1.08; 95% confidence interval [CI]: 1.01–1.15; P = 0.017). Time-dependent receiver operating characteristic (ROC) with the area under the curve (0.786) demonstrated that DLL3 expression can predict the survival outcome of IBC patients. Furthermore, the expression of DLL3 was related to a variety of tumor infiltrating immune cells (TIICs), particularly T cells regulatory (Tregs). Gene set enrichment analysis (GSEA) and immunohistochemistry (IHC) results indicated that DLL3 was closely related to p53 signaling pathway.ConclusionsHigh expression of DLL3 was associated with poor prognosis and immune cell infiltration in IBC patients. Moreover, P53 signaling pathway may be the key pathway.     

DNA hypomethylation-mediated activation of Cancer/Testis Antigen 45 (CT45) genes is associated with disease progression and reduced survival in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is a highly lethal malignancy due to a lack of early detection approaches coupled with poor outcomes for patients with clinically advanced disease. Cancer-testis (CT) or cancer-germline genes encode antigens known to generate spontaneous anti-tumor immunity in cancer patients. CT45 genes are a recently discovered 6-member family of X-linked CT genes with oncogenic function. Here, we determined CT45 expression in EOC and fully defined its epigenetic regulation by DNA methylation. CT45 was silent and hypermethylated in normal control tissues, but a large subset of EOC samples showed increased CT45 expression in conjunction with promoter DNA hypomethylation. In contrast, copy number status did not correlate with CT45 expression in the TCGA database for EOC. CT45 promoter methylation inversely correlated with both CT45 mRNA and protein expression, the latter determined using IHC staining of an EOC TMA. CT45 expression was increased and CT45 promoter methylation was decreased in late-stage and high-grade EOC, and both measures were associated with poor survival. CT45 hypomethylation was directly associated with LINE-1 hypomethylation, and CT45 was frequently co-expressed with other CT antigen genes in EOC. Decitabine treatment induced CT45 mRNA and protein expression in EOC cells, and promoter transgene analyses indicated that DNA methylation directly represses CT45 promoter activity. These data verify CT45 expression and promoter hypomethylation as possible prognostic biomarkers, and suggest CT45 as an immunological or therapeutic target in EOC. Treatment with decitabine or other epigenetic modulators could provide a means for more effective immunological targeting of CT45.