CircNUP50 is a novel therapeutic target that promotes cisplatin resistance in ovarian cancer by modulating p53 ubiquitination.

BACKGROUND: Most patients with ovarian cancer (OC) treated with platinum-based chemotherapy have a dismal prognosis owing to drug resistance. However, the regulatory mechanisms of circular RNA (circRNA) and p53 ubiquitination are unknown in platinum-resistant OC. We aimed to identify circRNAs associated with platinum-resistant OC to develop a novel treatment strategy. METHODS: Platinum-resistant circRNAs were screened through circRNA sequencing and validated using quantitative reverse-transcription PCR in OC cells and tissues. The characteristics of circNUP50 were analysed using Sanger sequencing, oligo (dT) primers, ribonuclease R and fluorescence in situ hybridisation assays. Functional experimental studies were performed in vitro and in vivo. The mechanism underlying circNUP50-mediated P53 ubiquitination was investigated through circRNA pull-down analysis and mass spectrometry, luciferase reporters, RNA binding protein immunoprecipitation, immunofluorescence assays, cycloheximide chase assays, and ubiquitination experiments. Finally, a platinum and si-circNUP50 co-delivery nanosystem (Psc@DPP) was constructed to treat platinum-resistant OC in an orthotopic animal model. RESULTS: We found that circNUP50 contributes to platinum-resistant conditions in OC by promoting cell proliferation, affecting the cell cycle, and reducing apoptosis. The si-circNUP50 mRNA sequencing and circRNA pull-down analysis showed that circNUP50 mediates platinum resistance in OC by binding p53 and UBE2T, accelerating p53 ubiquitination. By contrast, miRNA sequencing and circRNA pull-down experiments indicated that circNUP50 could serve as a sponge for miR-197-3p, thereby upregulating G3BP1 to mediate p53 ubiquitination, promoting OC platinum resistance. Psc@DPP effectively overcame platinum resistance in an OC tumour model and provided a novel idea for treating platinum-resistant OC using si-circNUP50. CONCLUSIONS: This study reveals a novel molecular mechanism by which circNUP50 mediates platinum resistance in OC by modulating p53 ubiquitination and provides new insights for developing effective therapeutic strategies for platinum resistance in OC.

Establishing Molecular Subgroups of CD8+ T Cell-Associated Genes in the Ovarian Cancer Tumour Microenvironment and Predicting the Immunotherapy Response.

BACKGROUND: The mechanism by which infiltrating CD8+ T lymphocytes in the tumour microenvironment influence the survival of patients with ovarian cancer (OC) remains unclear. METHODS: To identify biomarkers to optimise OC treatment, 13 immune-cell-line-associated datasets, RNA sequencing data, and clinical data from the GEO, TCGA, and the ICGC were collected. Gene expression in OC was assessed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) staining. RESULTS: We identified 520 genes and three immunological clusters (IC1, IC2, and IC3) associated with CD8+ T cells. Higher IFN scores, immune T cell lytic activity, and immune cell infiltration and upregulated expression of immune-checkpoint-related genes indicated that IC3 is more responsive to immunotherapy, whereas IC1 and IC2 have a poorer prognosis. A 10-gene signature, including SEMA4F, CX3CR1, STX7, PASK, AKIRIN2, HEMGN, GBP5, NSG1, and CXorf65, was constructed, and a multivariate Cox regression analysis revealed a significant association between the 10-gene signature-based risk model and overall survival (p < 0.001). A nomogram was constructed with age and the 10-gene signature. Consistent with the bioinformatics analysis, IHC and qRT-PCR confirmed the accuracy of the signatures in OC tissue samples. The predictive ability of the risk model was demonstrated using the Imvigor210 immunotherapy dataset. CONCLUSIONS: The development of a novel gene signature associated with CD8+ T cells could facilitate more accurate prognostics and prediction of the immunotherapeutic response of patients with OC.

Narciclasine, a novel topoisomerase I inhibitor, exhibited potent anti-cancer activity against cancer cells.

DNA topoisomerases are essential nuclear enzymes in correcting topological DNA errors and maintaining DNA integrity. Topoisomerase inhibitors are a significant class of cancer chemotherapeutics with a definite curative effect. Natural products are a rich source of lead compounds for drug discovery, including anti-tumor drugs. In this study, we found that narciclasine (NCS), an amaryllidaceae alkaloid, is a novel inhibitor of topoisomerase I (topo I). Our data demonstrated that NCS inhibited topo I activity and reversed its unwinding effect on p-HOT DNA substrate. However, it had no obvious effect on topo II activity. The molecular mechanism of NCS inhibited topo I showed that NCS did not stabilize topo-DNA covalent complexes in cells, indicating that NCS is not a topo I poison. A blind docking result showed that NCS could bind to topo I, suggesting that NCS might be a topo I suppressor. Additionally, NCS exhibited a potent anti-proliferation effect in various cancer cells. NCS arrested the cell cycle at G2/M phase and induced cell apoptosis. Our study reveals the antitumor mechanisms of NCS and provides a good foundation for the development of anti-cancer drugs based on topo I inhibition.

Clinical analysis of 312 patients with stage IB1-IIA2 cervical squamous cell carcinoma and research on the influencing factors of postoperative recurrence.

OBJECTIVE: To investigate the influencing factors of the recurrence of IB1-IIA2 cervical squamous cell carcinoma after surgical treatment, and to explore the relationship between high-risk human papillomavirus (HR-HPV) infection and postoperative cervical squamous cell carcinoma recurrence. METHODS: Patients (n = 312) diagnosed with stage IB1-IIA2 cervical cancer and treated by radical hysterectomy and lymphadenectomy at this hospital were accrued between January 2014 and December 2016. The clinical data of these patients were analysed, and the association among clinicopathological factors, the association among clinicopathological factors, HPV infection and recurrences was investigated through Cox regression. RESULTS: The median follow-up time was 59.2 months (with a range of 14-77.9 months). The pre-operative HPV infection rate was 85.3% (266/312), and 74 patients had a high level of HPV-DNA (> 5 × 106 copy number / 104 cells). Twenty-nine patients had a postoperative persistent high level of HPV-DNA (9.3%). On multivariate analysis, deep 1/3 stromal invasion (hazard ratio [HR] 114.79, 95% confidence interval [CI] 2.821-4670.111, p = 0.012*) and postoperative persistence of high HPV-DNA levels within 12 months (HR 269.044, 95% CI 14.437-5013.754, p < 0.001*) and 24 months (HR 31.299, 95% CI 1.191-822.215, p = 0.039*) were associated with a higher local recurrence rate. CONCLUSION: Continuous high HPV-DNA levels within 24 months of an operation and deep 1/3 interstitial infiltration were independent risk factors for local recurrences of cervical cancer.

Development of the expression and prognostic significance of m5 C-related LncRNAs in breast cancer.

BACKGROUND: 5-Methylcytosine (m5C) methylation is a major epigenetic RNA modification and is closely related to tumorigenesis in various cancers. This study aimed to explore the prognostic value of m5C-related lncRNAs in breast cancer. METHODS: Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. First, we performed differentially expressed gene (DEG) analysis and constructed a PPI network for the 12 m5C regulators. Then, we identified the m5C-related LncRNAs by the "cor. test." An m5C-related lncRNA prognostic risk signature was developed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was determined using Kaplan-Meier (KM) survival analysis and ROC curves. Finally, a nomogram was constructed for clinical application in evaluating patients with BRCA. We also researched the drug sensitivity of signature lncRNAs and immune cell infiltration. Finally, we validated the expression of the signature lncRNAs through qRT-PCR in a breast cancer cell line and a breast epithelial cell line. RESULTS: Overall, we constructed an 11-lncRNA risk score signature based on the lncRNAs associated with m5C regulators. According to the median risk score, we divided BRCA patients into high- and low-risk groups. The prognostic risk signature displayed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of immune cell subtypes. Drug sensitivity proved that our prognostic risk signature potentially has therapeutic value. CONCLUSIONS: The m5C-related lncRNA signature reliably predicted the prognosis of breast cancer patients and may provide new insight into the breast cancer tumor immune microenvironment.

Total Synthesis of (+)-Pancratistatin and Its Potent Topo I Inhibition Activity Studies.

As a preeminent anticancer natural product, (+)-pancratistatin has always been a privileged synthetic target. Herein, the total synthesis of (+)-pancratistatin is reported in 10 linear steps by utilizing a known aldehyde as chiral source. This synthetic route features a highly stereoselective intermolecular Michael addition and intramolecular Henry reaction to construct a cyclohexane ring bearing 6 successive stereocenters. Moreover, all of the synthetic steps are reliable and efficient and can be easily scaled up, which facilitated anticancer pharmacological tests of (+)-pancratistatin. Importantly, a new pharmacological mechanism of action was discovered for the first time where (+)-pancratistatin is able to inhibit the activity of topoisomerase I, which would pave the way for the development of new-type Topo I inhibitors.

Immune Subtypes and Immune Landscape Analysis of Endometrial Carcinoma.

Some patients with endometrial cancer (EC) suffer from limited survival benefits after immunotherapy, suggesting that there may be a specific pattern associated with immunotherapy. Immune-related genes were extracted from The Cancer Genome Atlas databases. We analyzed the differences among immune subtypes (ISs) in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, immune checkpoint-related genes, immunotherapy, and chemotherapy. We applied dimensionality reduction and defined the immune landscape of EC. Then, we used the Weighted Gene Co-Expression Network Analysis package to identify the coexpression modules of these immune genes. Finally, hub genes were selected and detected by quantitative PCR and immunohistochemistry. We obtained three ISs. There were differences in the distribution of the tumor mutational burden, chemotherapy-induced immune response markers, and immune checkpoint-related genes among the ISs. Regarding immunotherapy and chemotherapy, the IS2 subtypes were more sensitive to programmed cell death protein 1 inhibitors. In addition, different positions in the immune landscape map exhibited different prognostic characteristics, providing further evidence of the ISs. The IS2 subtypes were significantly positively correlated with yellow module gene list, indicating a good prognosis with high score. SIRPG and SLAMF1 were identified as the final characteristic genes. The quantitative PCR and immunohistochemistry results showed that the expression levels of SIRPG and SLAMF1 were low in human EC tissue. In this study, we identified three reproducible ISs of EC. The immune landscape analysis further revealed the intraclass heterogeneity of the ISs. SIRPG and SLAMF1 were identified to be associated with progression, suggesting that they may be novel immune-related biomarkers of EC.

Single-cell RNA sequencing analysis to explore immune cell heterogeneity and novel biomarkers for the prognosis of lung adenocarcinoma.

Background: Single-cell RNA sequencing is necessary to understand tumor heterogeneity, and the cell type heterogeneity of lung adenocarcinoma (LUAD) has not been fully studied. Method: We first reduced the dimensionality of the GSE149655 single-cell data. Then, we statistically analysed the subpopulations obtained by cell annotation to find the subpopulations highly enriched in tumor tissues. Monocle was used to predict the development trajectory of five subpopulations; beam was used to find the regulatory genes of five branches; qval was used to screen the key genes; and cellchart was used to analyse cell communication. Next, we used the differentially expressed genes of TCGA-LUAD to screen for overlapping genes and established a prognostic risk model through univariate and multivariate analyses. To identify the independence of the model in clinical application, univariate and multivariate Cox regression were used to analyse the relevant HR, 95% CI of HR and p value. Finally, the novel biomarker genes were verified by qPCR and immunohistochemistry. Results: The single-cell dataset GSE149655 was subjected to quality control, filtration and dimensionality reduction. Finally, 23 subpopulations were screened, and 11-cell subgroups were annotated in 23 subpopulations. Through the statistical analysis of 11 subgroups, five important subgroups were selected, including lung epithelial cells, macrophages, neuroendocrine cells, secret cells and T cells. From the analysis of cell trajectory and cell communication, it is found that the interaction of five subpopulations is very complex and that the communication between them is dense. We believe that these five subpopulations play a very important role in the occurrence and development of LUAD. Downloading the TCGA data, we screened the marker genes of these five subpopulations, which are also the differentially expressed genes in tumorigenesis, with a total of 462 genes, and constructed 10 gene prognostic risk models based on related genes. The 10-gene signature has strong robustness and can achieve stable prediction efficiency in datasets from different platforms. Two new molecular markers related to LUAD, HLA-DRB5 and CCDC50, were verified by qPCR and immunohistochemistry. The results showed that HLA-DRB5 expression was negatively correlated with the risk of LUAD, and CCDC50 expression was positively correlated with the risk of LUAD. Conclusion: Therefore, we identified a prognostic risk model including CCL20, CP, HLA-DRB5, RHOV, CYP4B1, BASP1, ACSL4, GNG7, CCDC50 and SPATS2 as risk biomarkers and verified their predictive value for the prognosis of LUAD, which could serve as a new therapeutic target.

Single-cell and WGCNA uncover a prognostic model and potential oncogenes in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. Single-cell transcriptome sequencing (scRNA-seq) can provide accurate gene expression data for individual cells. In this study, a new prognostic model was constructed by scRNA-seq and bulk transcriptome sequencing (bulk RNA-seq) data of CRC samples to develop a new understanding of CRC. METHODS: CRC scRNA-seq data were downloaded from the GSE161277 database, and CRC bulk RNA-seq data were downloaded from the TCGA and GSE17537 databases. The cells were clustered by the FindNeighbors and FindClusters functions in scRNA-seq data. CIBERSORTx was applied to detect the abundance of cell clusters in the bulk RNA-seq expression matrix. WGCNA was performed with the expression profiles to construct the gene coexpression networks of TCGA-CRC. Next, we used a tenfold cross test to construct the model and a nomogram to assess the independence of the model for clinical application. Finally, we examined the expression of the unreported model genes by qPCR and immunohistochemistry. A clone formation assay and orthotopic colorectal tumour model were applied to detect the regulatory roles of unreported model genes. RESULTS: A total of 43,851 cells were included after quality control, and 20 cell clusters were classified by the FindCluster () function. We found that the abundances of C1, C2, C4, C5, C15, C16 and C19 were high and the abundances of C7, C10, C11, C13, C14 and C17 were low in CRC tumour tissues. Meanwhile, the results of survival analysis showed that high abundances of C4, C11 and C13 and low abundances of C5 and C14 were associated with better survival. The WGCNA results showed that the red module was most related to the tumour and the C14 cluster, which contains 615 genes. Lasso Cox regression analysis revealed 8 genes (PBXIP1, MPMZ, SCARA3, INA, ILK, MPP2, L1CAM and FLNA), which were chosen to construct a risk model. In the model, the risk score features had the greatest impact on survival prediction, indicating that the 8-gene risk model can better predict prognosis. qPCR and immunohistochemistry analysis showed that the expression levels of MPZ, SCARA3, MPP2 and PBXIP1 were high in CRC tissues. The functional experiment results indicated that MPZ, SCARA3, MPP2 and PBXIP1 could promote the colony formation ability of CRC cells in vitro and tumorigenicity in vivo. CONCLUSIONS: We constructed a risk model to predict the prognosis of CRC patients based on scRNA-seq and bulk RNA-seq data, which could be used for clinical application. We also identified 4 previously unreported model genes (MPZ, SCARA3, MPP2 and PBXIP1) as novel oncogenes in CRC. These results suggest that this model could potentially be used to evaluate the prognostic risk and provide potential therapeutic targets for CRC patients.

ALKBH5-mediated m6A modification of circCCDC134 facilitates cervical cancer metastasis by enhancing HIF1A transcription.

BACKGROUND: Metastasis is the main cause of mortality in cervical cancer (CC). Circular RNAs (circRNAs) have been demonstrated to play a crucial role in carcinoma biology. However, the expression and function of circRNAs in cervical cancer metastasis are still unclear. METHODS: In the present study, we identified a circRNA with an N6-methyladenosine (m6A) modification, circCCDC134, whose expression was increased in CC tissues by circRNA-Seq and qPCR. CircCCDC134 upregulation in CC was fine-tuned by ALKBH5-mediated m6A modification, which enhanced its stability in a YTHDF2-dependent manner. The functional experiments illustrated that circCCDC134 enhanced tumour proliferation and metastasis in vitro and in vivo. For the comprehensive identification of RNA-binding proteins, circRNA pull-down and mass spectrometry (ChIRP-MS), chromatin immunoprecipitation-seq (Chip-seq), RNA binding protein immunoprecipitation (RIP) and luciferase reporter assays were used to perform mechanistic investigations. RESULTS: The results revealed that circCCDC134 recruited p65 in the nucleus and acted as a miR-503-5p sponge to regulate the expression of MYB in the cytoplasm, ultimately stimulating HIF1A transcription and facilitating CC growth and metastasis. CONCLUSION: These findings indicate that circCCDC134 is an important therapeutic target and provide new regulatory model insights for exploring the carcinogenic mechanism of circCCDC134 in CC.

Plasma cfDNA methylation markers for the detection and prognosis of ovarian cancer.

BACKGROUND: Plasma cell-free DNA (cfDNA) methylation has shown the potential in the detection and prognostic testing in multiple cancers. Herein, we thoroughly investigate the performance of cfDNA methylation in the detection and prognosis of ovarian cancer (OC). METHODS: The OC-specific differentially methylated regions (DMRs) were identified by sequencing ovarian tissue samples from OC (n = 61), benign ovarian disease (BOD, n = 49) and healthy controls (HC, n = 37). Based on 1,272 DMRs, a cfDNA OC detection model (OC-D model) was trained and validated in plasma samples from patients of OC (n = 104), BOD (n = 56) and HC (n = 56) and a prognostic testing model (OC-P model) was developed in plasma samples in patients with high-grade serous OC (HG-SOC) in the training cohort and then tested the rationality of this model with International Cancer Genome Consortium (ICGC) tissue methylation data. Mechanisms were investigated in the TCGA-OC cohort. FINDINGS: In the validation cohort, the cfDNA OC-D model consisting of 18 DMRs achieved a sensitivity of 94.7% (95% CI: 85.4%‒98.9%) at a specificity of 88.7% (95% CI: 78.7%‒94.9%), which outperformed CA 125 (AUC: 0.967 vs 0.905, P = 0.03). Then the cfDNA OC-P model consisting of 15 DMRs was constructed and associated with a better prognosis of HG-SOC in multivariable Cox regression analysis (HR: 0.29, 95% CI, 0.11‒0.78, P = 0.01) in the training cohort, which was also observed in the ICGC cohort using tissue methylation (HR: 0.56, 95% CI, 0.32‒0.98, P = 0.04). Investigation into mechanisms revealed that the low-risk group had higher homologous recombination deficiency and immune cell infiltration (P < 0.05). INTERPRETATION: Our study demonstrated the potential utility of cfDNA methylation in the detection and prognostic testing in OC. Future studies with a larger population are warranted. FUNDING: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Identification of Prognostic DNA Methylation Signatures in Lung Adenocarcinoma.

Background: Increasing evidence exists of a link between DNA methylation and tumor immunotherapy. However, the impact of DNA methylation on the characteristics of the lung adenocarcinoma microenvironment and its effect on immunotherapy remain unclear. Method: This study collected TCGA-LUAD related data sets (LUAD) to explore the characteristics and regulation of 20 DNA methylation-related genes. We further identified two DNA methylation subtypes by analysing the expression profiles of these 20 DNA methylation-related genes. Subsequently, the differences in immune cell infiltration (ICI) and the expression of immune-related signaling factors among different DNA methylation subtypes were explored, and the differentially expressed genes (DEGs) among different LUAD DNA methylation subtypes were identified. Using univariate Cox to screen differentially expressed genes meaningful for survival, a DNA methylation score (DMS) was constructed based on the weight of the first and second dimensions after dimensionality reduction by principal component analysis (PCA). Our study found that DMS can better evaluate the prognosis of lung adenocarcinoma. Results: Based on DMS, LUAD samples were divided into two groups with high and low scores. The differences in clinical characteristics, tumor mutation load, and tumor immune cell infiltration between different DMS groups of LUAD were deeply explored, and the prediction ability of DMS for the benefit of immunotherapy was evaluated. Conclusions: DMS is a valuable tool for predicting survival, clinicopathological features, and immunotherapeutic efficacy, which may help to promote personalized LUAD immunotherapy in the future.

Exosomal circPABPC1 promotes colorectal cancer liver metastases by regulating HMGA2 in the nucleus and BMP4/ADAM19 in the cytoplasm.

Liver metastasis is the leading cause of death in colorectal carcinoma (CRC). However, little is known about the mechanisms of transferring effector messages between the primary tumor and the site of metastasis. Exosomes provide a novel transfer message method, and exosomal circular RNAs (circRNAs) play critical regulatory roles in cancer biology. In this study, the results showed that the expression of circPABPC1 was aberrantly upregulated in CRC tissues and exosomes. Exosomal circPABPC1 was considered an oncogene by functional experimental analysis in vitro and in vivo. Mechanistically, circPABPC1 recruited KDM4C to the HMGA2 promoter, reduced its H3K9me3 modification and initiated the transcription process in the nucleus. Moreover, cytoplasmic circPABPC1 promoted CRC progression by protecting ADAM19 and BMP4 from miR-874-/miR-1292-mediated degradation. Our findings indicated that exosomal circPABPC1 is an essential regulator in CRC liver metastasis progression by promoting HMGA2 and BMP4/ADAM19 expression. CircPABPC1 is expected to be a novel biomarker and antimetastatic therapeutic target in CRC.

Gene Signature and Prognostic Value of Ubiquitin-Specific Proteases Members in Hepatocellular Carcinoma and Explored the Immunological Role of USP36.

BACKGROUND: Ubiquitination is one of the most common post-translational modifications in cells and dysregulation is closely associated with the development of cancer. However, a comprehensive analysis of the role of ubiquitination in hepatocellular carcinoma (HCC) is still lacking. In this study we analyzed expression and prognostic value of Ubiquitin-Specific Proteases (USPs) in HCC, and the immunological role of USP36 in HCC. METHODS: Expression data, prognostic data, and DNA methylation data in cases of HCC were obtained from the cancer genome atlas (TCGA). Overexpression of USP36 in HCC was confirmed in the gene expression omnibus (GEO) database and verified by quantitative PCR in 10 pairs of HCC samples. ULCAN was used to analyze the correlation between USP36 and clinicopathological features. TIMER2.0 and DriverDBv3 were used to analyze the USP36 mutational profile. GSEA analysis explored the potential signaling pathways of USP36 affecting HCC. The immune and stromal scores of HCC samples were calculated using the ESTIMATE algorithm. TIMER1.0 was used to explore the correlation between USP36 and immune cell infiltration. Finally, we analyzed the correlation of USP36 expression with immune checkpoint molecules and determined the IC50 values of 6 chemotherapeutic drugs using the pRRophetic software package. RESULTS: Most USPs are abnormally expressed in HCC, among which USP36 and USP39 are most closely associated with HCC prognosis. We also found that USP36 is associated with TP53 mutational status. GSEA analysis indicated that USP36 may affect HCC progression through the dysregulation of various pathways such as ubiquitin-mediated proteolysis. USP36 expression positively correlated with both macrophage infiltration levels and multiple immune checkpoint molecules. Finally, chemosensitivity analysis indicated that chemosensitivity was lower in cells within the USP36 high expression group. CONCLUSIONS: Most USPs are abnormally expressed in HCC. Overexpression of USP36 in HCC is closely related to poor prognosis. In particular, the unique immunological role of USP36 may have potential clinical application value.

Establishment and validation of a novel invasion-related gene signature for predicting the prognosis of ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is an invasive gynaecologic cancer with a high cancer-related death rate. The purpose of this study was to establish an invasion-related multigene signature to predict the prognostic risk of OC. METHODS: We extracted 97 invasion-related genes from The Cancer Genome Atlas (TCGA) database. Then, the ConsensusClusterPlus and limma packages were used to calculate differentially expressed genes (DEGs). To calculate the immune scores of the molecular subtypes, we used ESTIMATE to evaluate the stromal score, immune score and ESTIMATE score. MCP-counter and the GSVA package ssgsea were used to evaluate the types of infiltrating immune cells. Survival and nomogram analyses were performed to explore the prognostic value of the signature. Finally, qPCR, immunohistochemistry staining and functional assays were used to evaluate the expression and biological abilities of the signature genes in OC. RESULTS: Based on the consistent clustering of invasion-related genes, cases in the OC datasets were divided into two subtypes. A significant difference was observed in prognosis between the two subtypes. Most genes were highly expressed in the C1 group. Based on the C1 group genes, we constructed an invasion-related 6-gene prognostic risk model. Furthermore, to verify the signature, we used the TCGA-test and GSE32062 and GSE17260 chip datasets for testing and finally obtained a good risk prediction effect in those datasets. Moreover, the results of the qPCR and immunohistochemistry staining assays revealed that KIF26B, VSIG4 and COL6A6 were upregulated and that FOXJ1, MXRA5 and CXCL9 were downregulated in OC tissues. The functional study showed that the expression of KIF26B, VSIG4, COL6A6, FOXJ1, MXRA5 and CXCL9 can regulate the migration and invasion abilities of OC cells. CONCLUSION: We developed a 6-gene prognostic stratification system (FOXJ1, MXRA5, KIF26B, VSIG4, CXCL9 and COL6A6) that is independent of clinical features. These results suggest that the signature could potentially be used to evaluate the prognostic risk of OC patients.

Establishment of a molecular risk model for the prognosis of cervical cancer based on microRNA expression.

Background: Globally, the incidence of cervical cancer (CC) is highest among all tumors of the female reproductive system. Numerous studies have shown that the expression level of microRNA (miRNA) is highly correlated with cancer. This study aimed to establish a molecular prognostic model of CC based on miRNAs in order to provide more individualized treatment to CC patients. Methods: Human tissues were selected from the Cancer Hospital (Chinese Academy of Medical Sciences and Peking Union Medical College) for miRNA gene sequencing. CC transcriptome expression and clinical data were downloaded from The Cancer Genome Atlas (TCGA). We distinguished between common differentially expressed miRNAs of CC miRNA-seq and TCGA-CC. To obtain a molecular prognostic model, R package was used to perform univariate Cox proportional hazard regression and least absolute shrinkage and selection operator (LASSO) Cox regression for common differentially-expressed miRNAs. Next, the model performance was evaluated by survival analysis, receiver operating characteristic (ROC) curve analysis, as well as univariate and multivariate analyses in the TCGA-CC dataset. Quantitative Real-time polymerase chain reaction (qPCR) detection was to verify the expression changes of miRNA. Transwell was used to verify the role of molecules in CC cell migration and invasion. Results: Thirty-nine miRNAs were distinguished in TCGA-CC and CC miRNA-seq, LASSO regression analysis to obtain the risk model (risk score =-0.310× expression of hsa-miR-142-3p +0.439× expression of hsa-miR-100-3p). The survival analysis, ROC curve analysis, patient risk assessment, and univariate and multivariate analyses showed that the risk score model had good predictive ability in assessing patient survival (P<0.01), risk of death, and independent prognosis (P<0.01). qPCR detection of clinical samples and cells showed that the expression of hsa-miR-142-3p and hsa-miR-100-3p was consistent with the results of the database analysis. The Transwell results indicated that miR-142-3p is an inhibiting factor and miR-100-3p serves as a promoting factor in CC cell migration and invasion. Conclusions: Twelve miRNA-seq and TCGA-CC tissues were used to build a prognostic model for CC. We have obtained a two-miRNA risk score model. Our results provide a new strategy for the individualized diagnosis and treatment of CC.

Circular RNA ACTN4 promotes intrahepatic cholangiocarcinoma progression by recruiting YBX1 to initiate FZD7 transcription.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinoma (ICC) is a primary liver cancer with high aggressiveness and extremely poor prognosis. The role of circular RNAs (circRNAs) in ICC carcinogenesis and progression remains to be determined. METHODS: CircRNA microarray was performed to screen significantly upregulated circRNAs in paired ICC and non-tumor tissues. Colony formation, transwell, and xenograft models were used to examine the role of circRNAs in ICC proliferation and metastasis. RNA pulldown, mass spectrometry, chromatin immunoprecipitation, RNA-binding protein immunoprecipitation, chromatin isolation by RNA purification, electrophoretic mobility shift assay, and luciferase reporter assays were used to explore the molecular sponge role of the circRNA (via miRNA binding), and the interaction between circRNA and RNA-binding proteins. RESULTS: Hsa_circ_0050898, which originated from exon 1 to exon 20 of the ACTN4 gene (named circACTN4), was significantly upregulated in ICC. High circACTN4 expression was associated with enhanced tumor proliferation and metastasis in vitro and in vivo, as well as a worse prognosis following ICC resection. In addition, circACTN4 upregulated Yes-associated protein 1 (YAP1) expression by sponging miR-424-5p. More importantly, circACTN4 also recruited Y-box binding protein 1 (YBX1) to stimulate Frizzled-7 (FZD7) transcription. Furthermore, circACTN4 overexpression in ICC cells enhanced the interaction between YAP1 and ß-catenin, which are the core components of the Hippo and Wnt signaling pathways, respectively. CONCLUSIONS: CircACTN4 was upregulated in ICC and promoted ICC proliferation and metastasis by acting as a molecular sponge of miR-424-5p, as well as by interacting with YBX1 to transcriptionally activate FZD7. These results suggest that circACTN4 is a potential prognostic marker and therapeutic target for ICC. LAY SUMMARY: Intrahepatic cholangiocarcinoma is a primary liver cancer associated with aggressiveness and extremely poor prognosis. It is essential for therapeutic development that we uncover relevant pathogenic pathways. Herein, we showed that a circular RNA (circACTN4) was highly expressed in intrahepatic cholangiocarcinoma and was positively associated with tumor growth and metastasis through key developmental signaling pathways. Thus, circACTN4 could be a prognostic biomarker and therapeutic target for intrahepatic cholangiocarcinoma.

Unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents.

BACKGROUND: It is well known that some lifestyle-related behaviors are related to depressive symptoms, but the unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents are still controversial. AIMS: The aims of this study were to examine the unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents, and explored the potential influences of gender difference on these associations. METHODS: We conducted a cross-sectional study among 3967 Chinese adolescents aged 11 to 19 from Jilin, China during September and October of 2018. Students reported their lifestyle factors including sleep duration, time spent on computer, time spent on television, time spent on homework, eating breakfast, smoking, drinking, physical activity, and outdoor activity. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D). RESULTS: The prevalence of depressive symptoms was 28.2% among Chinese adolescents. Multivariate logistic regression analysis revealed that sleep duration <8 hour/day, time spent on homework ⩾3 hour/day, skipping breakfast, alcohol use, physical activity <3 days/week, and outdoor activity <2 hour/day were positively associated with depressive symptoms in both girls and boys. Time spent on computer ⩾2 hour/day was an independent risk predictor for depressive symptoms in males, while smoking only showed higher risk of depressive symptoms in females. There was an additive relationship between the lifestyle risk index scores and the risk of depressive symptoms for both genders, the relationship being strongest among females. CONCLUSION: The important role of lifestyle factors should be taking into consideration when create intervention programs to prevent and reduce depressive symptoms among adolescents. In addition, preventive interventions may need to focus on gender-informed approaches when targeting multiple lifestyle factors.

Development and Validation of a Novel Gene Signature for Predicting the Prognosis by Identifying m5C Modification Subtypes of Cervical Cancer.

Background: 5-Methylcytidine (m5C) is the most common RNA modification and plays an important role in multiple tumors including cervical cancer (CC). We aimed to develop a novel gene signature by identifying m5C modification subtypes of CC to better predict the prognosis of patients. Methods: We obtained the expression of 13 m5C regulatory factors from The Cancer Genome Atlas (TCGA all set, 257 patients) to determine m5C modification subtypes by the "nonnegative matrix factorization" (NMF). Then the "limma" package was used to identify differentially expressed genes (DEGs) between different subtypes. According to these DEGs, we performed Cox regression and Kaplan-Meier (KM) survival analysis to establish a novel gene signature in TCGA training set (128 patients). We also verified the risk prediction effect of gene signature in TCGA test set (129 patients), TCGA all set (257 patients) and GSE44001 (300 patients). Furthermore, a nomogram including this gene signature and clinicopathological parameters was established to predict the individual survival rate. Finally, the expression and function of these signature genes were explored by qRT-PCR, immunohistochemistry (IHC) and proliferation, colony formation, migration and invasion assays. Results: Based on consistent clustering of 13 m5C-modified genes, CC was divided into two subtypes (C1 and C2) and the C1 subtype had a worse prognosis. The 4-gene signature comprising FNDC3A, VEGFA, OPN3 and CPE was constructed. In TCGA training set and three validation sets, we found the prognosis of patients in the low-risk group was much better than that in the high-risk group. A nomogram incorporating the gene signature and T stage was constructed, and the calibration plot suggested that it could accurately predict the survival rate. The expression levels of FNDC3A, VEGFA, OPN3 and CPE were all high in cervical cancer tissues. Downregulation of FNDC3A, VEGFA or CPE expression suppressed the proliferation, migration and invasion of SiHa cells. Conclusions: Two m5C modification subtypes of CC were identified and then a 4-gene signature was established, which provide new feasible methods for clinical risk assessment and targeted therapies for CC.

Integration of scRNA-Seq and Bulk RNA-Seq to Analyse the Heterogeneity of Ovarian Cancer Immune Cells and Establish a Molecular Risk Model.

BACKGROUND: Considerable evidence suggests that the heterogeneity of ovarian cancer (OC) is a major cause of treatment failure. Single-cell RNA sequencing (scRNA-seq) is a powerful tool to analyse the heterogeneity of the tumour at the single-cell level, leading to a better understanding of cell function at the genetic and cellular levels. METHODS: OC scRNA-seq data were extracted from the Gene Expression Omnibus (GEO) database and the FindCluster () package used for cell cluster analysis. The GSVA package was used for single-sample gene set enrichment analysis (ssGSEA) analysis to obtain a Hallmark gene set score and bulk RNA-seq data were used to analyse the key genes of OC-associated immune cell subsets. CIBERSORT was used to identify immune scores of cells and the "WGCNA" package for the weighted correlation network analysis (WGCNA). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses of subtype groups were performed by GSEA. Then, univariate Cox and lasso regression were performed to further establish a signature. Finally, qPCR and immunohistochemistry staining were used to evaluate the expression of signature genes in OC. RESULTS: Two scRNA-seq (GSE154600 and GES158937) datasets were integrated to obtain 20 cell clusters. T cells or NK cells (cluster 5, 6, 7, 11), B cells (cluster 16, 19, 20) and myeloid cells (cluster 4, 9, 10) were clustered according to immune cell markers. The ssGSEA revealed that M1- and M2-like myeloid cell-related genes were significantly upregulated in P3 and P4 patients in the GSE154600 data. Immune cell analysis in TCGA-OC showed that a high abundance of M1-like tumour-associated macrophages (TAMS) predicts better survival. WGCNA, univariate Cox and lasso Cox regression established a two-gene signature (RiskScore=-0.059*CXCL13-0.034*IL26). Next, the TCGA-test and TCGA-OC were used to test the risk prediction ability of the signature, showing a good effect in the datasets. Moreover, the qPCR and immunohistochemistry staining revealed that the expression of CXCL13 and IL26 was reduced in OC tissues. CONCLUSION: A two-gene signature prognostic stratification system (CXCL13 and IL26) was developed based on the heterogeneity of OC immune cells to accurately evaluate the prognostic risk.