Genomics

Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration

This study aims to develop an immune-related genes (IRGs) prognostic signature to stratify the epithelial ovarian cancer (EOC) patients. We identified 332 up- and 154 down-regulated EOC-specific IRGs. As a result, candidate IRGs were idendified to construct prognostic models respectivy for overall survial and progression-free survival. The risk score was validated as a risk factor for prognosis and was used to built a combined nomogram. According to the IRG-related prognostic model, EOC patients were divided into high- and low- risk group and were further explored their association with tumor immune microenvironment (TME). CIBERSORT algorithm showed higher macrophages M1 cell, T cells follicular helper cell and plasma cells infiltrating levels in the low-risk group. In addition, the low-risk group was found with higher immunophenoscore and distinct mutation signatures compared with the high-risk group. These findings may shed light on the development of novel immune biomarkers and target therapy of EOC.

Tissue-based long non-coding RNAs “PVT1, TUG1 and MEG3” signature predicts Cisplatin resistance in ovarian Cancer

The current study aimed to investigate the potentiality of three lncRNAs "Plasmacytoma variant translocation 1(lnc-PVT1), Taurine upregulated gene type 1(lnc-TUG1) and Maternally expressed gene 3 (lnc-MEG-3)", to predict Cisplatin resistance in ovarian cancer (OC), in addition, to access their prognostic significance. The expression level of lncRNAs were measured in 100 formalin-fixed paraffin-embedded tissue (FFET) samples of OC patients who were treated by Cisplatin-based chemotherapy using qPCR. The results showed that lnc_PVT1 was significantly upregulated by 2.3 folds in Cisplatin resistant tissues, while, lnc-TUG1 and lnc-MEG3 were downregulated by 1.2 and 3 folds, respectively. In addition, the three lncRNAs exhibited high sensitivity and specificity in predicting chemo-resistance and they were negatively associated with OS and progression-free survival (p < 0.001). The lnc-PVT1, lnc-TUG1, and lnc-MEG3 transcriptome signatures could be used for predicting resistance to Cisplatin in OC patients.

Profiling and integrated analysis of differentially expressed circRNAs in cervical cancer

Circular RNAs (circRNAs) are a new type of regulatory RNAs, which have been identified to play critical role in various tumors. However, the profiles and roles of circRNAs in cervical cancer (CCa) have not been fully understood and need to be further explored. In the present study, we performed circRNA array and mRNA-sequencing (mRNA-Seq) to profile the differentially expressed circRNAs and mRNAs in CCa tissues. A total of 397 differentially expressed circRNAs and 2138 differentially expressed mRNAs were detected, respectively. Subsequently, a circRNA-miRNA-mRNA regulatory network was constructed and indicated that hsa_circ_0026377 was downregulated in CCa. Overexpression of hsa_circ_0026377 inhibited HeLa and SiHa cells proliferation, migration and invasion. Collectively, this study provided new insights into the circRNA profiles in CCa and suggested that hsa_circ_0026377 might play important roles in CCa development.

Integrative analysis of the expression and prognosis for CENPs in ovarian cancer

Centromere proteins (CENPs) are nuclear proteins that are involved in centromere formation and chromosome segregation during mitosis. Some members of CENPs have been extensively studied in the initiation and development of cancers. However, the expression patterns and exact roles of CENPs in ovarian cancer (OC) have not been fully elucidated. In this study, we comprehensively assessed the genetic variation, expression patterns and prognostic value of CENPs in OC by several databases. The mRNA expression levels of CENPA/F/H/L/N/U/W were found to be significantly upregulated in OC and related to worse prognosis. Additionally, function enrichment analysis showed that CENPs were involved in DNA repair and cell division. Meanwhile, immune infiltration analysis elucidated that CENPs were associated with myeloid-derived suppressor cells (MDSCs) and major histocompatibility complex (MHC). These results suggested that CENPs might serve as potential diagnostic and prognostic markers and provide new insights for the development of CENPs-targeted therapeutics for ovarian cancer.

LncRNA FIRRE regulated endometrial cancer radiotherapy sensitivity via the miR-199b-5p/SIRT1/BECN1 axis-mediated autophagy

Endometrial cancer (EC) poses a serious threat to women's health. Radiotherapy has been widely used for EC treatment. However, the mechanism of FIRRE in EC development and radioresistance remains unknown. MTT and colony formation assays determined cell proliferation. The degree of autophagy was tested by the measurement of autophagy-related genes and immunofluorescence staining of LC3. Molecular interactions were demonstrated via luciferase reporter assay, RIP, and Co-IP. The FIRRE role's was analyzed by in vivo xenograft tumor model. FIRRE and SIRT1 were upregulated in EC tumor tissues, whereas miR-199b-5p was reduced. FIRRE knockdown increased EC cell radiotherapy sensitivity by sponging miR-199b-5p and inhibiting autophagy. SIRT1 was targeted and negatively regulated by miR-199b-5p. SIRT1 could otherwise deacetylate BECN1 protein and participate in FIRRE-mediated autophagy. Silencing FIRRE increased sensitivity of EC radiotherapy in vivo. FIRRE reduced EC cell radiotherapy sensitivity by stimulating autophagy via miR-199b-5p/SIRT1/BECN1 axis.

Differentially expressed circular RNA profiles and comprehensive analysis of circRNA-miRNA-mRNA regulatory network in microsatellite instability-high endometrial cancer

The clinical benefit of anti-programmed cell death protein 1 (PD-1)-based immunotherapy among patients with microsatellite instable (MSI) endometrial cancer (EC) precedes that of microsatellite stable (MSS) EC, the mechanisms of which have not been fully understood. Circular RNAs (circRNAs) were reported to modulate immune evasion in several types of malignancies, while their roles in the immune regulation in EC remain largely unknown. Here, we conducted circRNA array analysis and mRNA-Sequencing of 10 MSI EC samples and 10 MSS EC samples and identified 1083 differentially expressed circRNAs (DE-circRNAs) and 864 differentially expressed mRNAs, based on which we constructed a circRNA-miRNA-mRNA comprehensive network consisting of 35 DE-circRNAs, 56 predicted miRNAs and 24 differentially expressed mRNAs. Finally, we confirmed hsa_circ_0058230 being positively correlated with CD8+ T cells infiltration, suggesting that it might take a part in anti-tumor immunity in EC.

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

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

Exosomes derived from ovarian cancer cells regulate proliferation and migration of cancer-associated fibroblasts

Cancer-associated fibroblast (CAF) is an essential risk factor for ovarian cancer. Exosomes can mediate cellular communication in the tumour microenvironment, but the interaction of tumour cell exosomes with CAF is less studied in Ovarian cancer. This study identified H19/miR-29c-3p/LOXL2-COL1A1 as a ceRNA regulatory network involved in regulating tumour matrix-associated signaling pathways associated with CAF. Cellular assays demonstrated that exosomes from ovarian cancer cell line SKOV3 significantly promoted the proliferation and migration of CAF. The results of mixed transplantation tumour experiments in nude mice showed that exosomes of SKOV3 significantly promoted tumour growth. Ovarian cancer tumour-derived exosomes can regulate CAF proliferation and migration through H19/miR-29c-3p/LOXL2-COL1A1. This study reveals the regulatory role of tumour exosomes on CAF, which may provide a theoretical basis for the development of therapeutic regimens targeting fibroblasts in ovarian cancer.

Determining the effect of long non-coding RNA maternally expressed gene 3 (lncRNA MEG3) on the transcriptome profile in cervical cancer cell lines

This study investigates the role of the long non-coding RNA Maternally Expressed Gene3 (lncRNA MEG3) gene in cervical cancer, as evidenced by its downregulation in cancerous cell lines. The study demonstrates the effects of the overexpression of lncRNA MEG3 in cervical cancer cell lines, particularly in C33A and CaSki. Through comprehensive analyses, including Next-Generation Sequencing (NGS), alterations in global mRNA expression were analyzed. In C33A cells, 67 genes were upregulated, while 303 genes were downregulated. Similarly, in CaSki cells, 221 genes showed upregulation and 248 genes displayed downregulation. Gene ontology and KEGG pathway analyses were conducted to gain insight into potential mechanisms. Furthermore, the study delves into gene regulatory networks, uncovering intricate interactions among genes. The RNA sequencing data were confirmed for eight genes: PAX3, EGR2, ROR1, NRP1, OAS2, STRA6, CA9, and EDN2 by Real-time PCR. The findings illuminate the complex landscape of gene expression alterations and pathways impacted by the overexpression of lncRNA MEG3. The impact of MEG3 on the overall cervical cancer cells' mRNA profile is reported for the first time. New biomarkers for the prognosis of cervical cancer are also reported in this study. Moreover, identifying specific genes within the regulatory networks provides valuable insights into potential therapeutic targets for managing cervical cancer.

Deficiency of ligase IV leads to reduced NHEJ, accumulation of DNA damage, and can sensitize cells to cancer therapeutics

Ligase IV is a key enzyme involved during DNA double-strand breaks (DSBs) repair through nonhomologous end joining (NHEJ). However, in contrast to Ligase IV deficient mouse cells, which are embryonic lethal, Ligase IV deficient human cells, including pre-B cells, are viable. Using CRISPR-Cas9 mediated genome editing, we have generated six different LIG4 mutants in cervical cancer and normal kidney epithelial cell lines. While the LIG4 mutant cells showed a significant reduction in NHEJ, joining mediated through microhomology-mediated end joining (MMEJ) and homologous recombination (HR) were significantly high. The reduced NHEJ joining activity was restored by adding purified Ligase IV/XRCC4. Accumulation of DSBs and reduced cell viability were observed in LIG4 mutant cells. LIG4 mutant cells exhibited enhanced sensitivity towards DSB-inducing agents such as ionizing radiation (IR) and etoposide. More importantly, the LIG4 mutant of cervical cancer cells showed increased sensitivity towards FDA approved drugs such as Carboplatin, Cisplatin, Paclitaxel, Doxorubicin, and Bleomycin used for cervical cancer treatment. These drugs, in combination with IR showed enhanced cancer cell death in the background of LIG4 gene mutation. Thus, our study reveals that mutation in LIG4 results in compromised NHEJ, leading to sensitization of cervical cancer cells towards currently used cancer therapeutics.

Pancancer analysis of SKA1 mutation and its association with the diagnosis and prognosis of human cancers

This study aims to explore the role of SKA1 in cancer diagnosis and prognosis and to investigate the mechanism by which SKA1 affects the malignant behaviors of ovarian cancer. Herein, we analyzed the oncogenic role of SKA1 at pan-cancer level by multiple informatics databases and verified the analysis by in vitro experiments. As a result, SKA1 was upregulated across cancers and was related to poor clinical outcome and immune infiltration. Specifically, the constructed nomogram showed superior performance in predicting the prognosis of epithelial ovarian cancer patients. Furthermore, the in vitro experiments revealed that silencing SKA1 significantly inhibited the proliferation, migratory ability and enhanced the cisplatin sensitivity of ovarian cancer cells. Therefore, we explored the oncogenic and potential therapeutic role of SKA1 across cancers through multiple bioinformatic analysis and revealed that SKA1 may promote ovarian cancer progression and chemoresistance to cisplatin by activating the AKT-FOXO3a signaling pathway.

Integrative, genome-wide association study identifies chemicals associated with common women's malignancies

Breast cancer, cervical cancer, and ovarian cancer are three of the most commonly diagnosed malignancies in women, and more cancer prevention research is urgently needed. Summary data of a large genome-wide association study of female cancers were derived from the UK biobank. We performed a transcriptome-wide association study and a gene set enrichment analysis to identify correlations between chemical exposure and aberrant expression, repression, or mutation of genes related to cancer using the Comparative Toxicogenomics Database. We identified five chemicals (NSC668394, glafenine, methylnitronitrosoguanidine, fenofibrate, and methylparaben) that were associated with the incidence of both breast cancer and cervical cancer. Using a transcriptome-wide association study and gene set enrichment analysis we identified environmental chemicals that are associated with an increased risk of breast cancer, cervical cancer, and ovarian cancer.

Correlation between polymorphisms in IGF2/H19 gene locus and epithelial ovarian cancer risk in Chinese population

To investigate the association between SNPs in human IGF2/H19 gene locus and epithelial ovarian cancer (EOC) risk, we performed a case-control study in 422 individuals (219 EOC patients and 203 cancer-free controls). Four SNPs (rs2525885, rs2839698, rs3741206, rs3741219) were found to be related with EOC risk. Specifically, the minor allele C of rs2525885 and allele A of rs2839698 was associated with elevated EOC genetic susceptibility under both dominant and recessive models (TC + CC vs TT: adjusted OR: 1.61, P = .031; CC vs TT + TC: adjusted OR: 4.87, P = .014; GA + AA vs GG: adjusted OR: 1.63, P = .023; AA vs GG + GA: adjusted OR: 2.43, P = .007). For rs3741206, the genotype TC + CC was associated with a significant decrease in EOC risk with the TT genotype as reference in a dominant genetic model (adjusted OR: 0.44, P = .003), while for rs3741219, genotype AA was associated with a 59% decrease in EOC risk only in the recessive model (adjusted OR: 0.41, P = .038). In the stratified analysis, an increased risk associated with the variant genotypes was observed in only subjects aged >47 years for rs2525885 (adjusted OR = 2.04, P = .024), rs2839698 (adjusted OR = 2.50, P = .047) and rs3741206 (adjusted OR = 0.37, P = .009), respectively. What's more, the TC + CC genotype of rs2525885 was significantly associated with advanced FIGO stage (III vs II, adjusted OR = 2.73, P = .040).

Integrated analysis of virus and host transcriptomes in cervical cancer in Asian and Western populations

Race may influence vulnerability to HPV variants in viral infection and perisistence. Integrated analysis of the virus and host transcriptomes from different populations provides an unprecedented opportunity to understand these racial disparities in the prevalence of HPV and cervical cancers. We performed RNA-Seq analysis of 90 tumors and 39 adjacent normal tissues from cervical cancer patients at Zhejiang University (ZJU) in China, and conducted a comparative analysis with RNA-Seq data of 286 cervical cancers from TCGA. We found a modestly higher rate of HPV positives and HPV integrations in TCGA than in ZJU. In addition to LINC00393 and HSPB3 as new common integration hotspots in both cohorts, we found new hotspots such as SH2D3C and CASC8 in TCGA, and SCGB1A1 and ABCA1 in ZJU. We described the first, to our knowledge, virus-transcriptome-based classification of cervical cancer associated with clinical outcome. Particularly, patients with expressed E5 performed better than those without E5 expression. However, the constituents of these virus-transcriptome-based tumor subtypes differ dramatically between the two cohorts. We further characterized the immune infiltration landscapes between different HPV statuses and revealed significantly elevated levels of regulatory T cells and M0 macrophages in HPV positive tumors, which were associated with poor prognosis. These findings increase our understanding of the racial disparities in the prevalence of HPV and its associated cervical cancers between the two cohorts, and also have important implications in the classification of tumor subtypes, prognosis, and anti-cancer immunotherapy in cervical cancer.

Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data

Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were down-regulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

Identification of a five-gene signature of the RGS gene family with prognostic value in ovarian cancer

The RGS (regulator of G protein signaling) gene family, which includes negative regulators of G protein-coupled receptors, comprises important drug targets for malignant tumors. It is thus of great significance to explore the value of RGS family genes for diagnostic and prognostic prediction in ovarian cancer. The RNA-seq, immunophenotype, and stem cell index data of pan-cancer, The Cancer Genome Atlas (TCGA) data, and GTEx data of ovarian cancer were downloaded from the UCSC Xena database. In the pan-cancer database, the expression level of RGS1, RGS18, RGS19, and RGS13 was positively correlated with stromal and immune cell scores. Cancer patients with high RGS18 expression were more sensitive to cyclophosphamide and nelarabine, whereas those with high RGS19 expression were more sensitive to cladribine and nelarabine. The relationship between RGS family gene expression and overall survival (OS) and progression-free survival (PFS) of ovarian cancer patients was analyzed using the KM-plotter database, RGS17, RGS16, RGS1, and RGS8 could be used as diagnostic biomarkers of the immune subtype of ovarian cancer, and RGS10 and RGS16 could be used as biomarkers to predict the clinical stage of this disease. Further, Lasso cox analysis identified a five-gene risk score (RGS11, RGS10, RGS13, RGS4, and RGS3). Multivariate COX analysis showed that the risk score was an independent prognostic factor for patients with ovarian cancer. Immunohistochemistry and the HPA protein database confirmed that the five-gene signature is overexpressed in ovarian cancer. GSEA showed that it is mainly involved in the ECM-receptor interaction, TGF-beta signaling pathway, Wnt signaling pathway, and chemokine signaling pathway, which promote the occurrence and development of ovarian cancer. The prediction model of ovarian cancer constructed using RGS family genes is of great significance for clinical decision making and the personalized treatment of patients with ovarian cancer.

A comprehensive meta-analysis of non-coding polymorphisms associated with precancerous lesions and cervical cancer

To study the risk of polymorphisms present in the non-coding regions of genes related with cervical cancer. The PubMed database was extensively searched using text-mining techniques to identify literature containing the association of single nucleotide polymorphisms and cervical cancer. Case-control studies published till June 2020 were considered for the meta-analysis if they fulfilled the selection criteria. The polymorphisms within each case-control study were checked for the presence of genotype data and then divided into groups based on the precancerous and cancerous conditions of the cervix. Odds ratio and 95% confidence intervals (CI) were used to study the effects of polymorphisms with the help of different genetic models (allele, dominant, recessive, heterozygous and homozygous). Also checked heterogeneity along with publication bias and statistical significance using the p-value. 120 papers covering 48 unique non-coding SNPs having 37,123 cases and 39,641 control data was considered for the meta-analysis. The genotype data was categorised into Cancer, Precancer and "Cancer + Precancer" groups, for 43, 8 and 11 SNPs respectively. The meta-analysis identified 21 and 1 SNPs as significant in the Cancer and "Cancer + Precancer" groups. Among all the polymorphisms, rs1143627 (IL1B), rs1800795 (IL6), rs1800871 (IL10), rs568408 (IL12A), rs3312227 (IL12B), rs2275913 (IL17A), rs5742909 (CTLA4), rs1800629 (TNFα), and rs4646903 (CYP1A1) were found to increase risk of cervical cancer in at least three of the five genetic models. We identified potential non-coding SNPs corresponding to various cytokines like interleukins (ILs), tumor necrosis factor (TNF), interferon (IFN) and other immune related genes like toll like receptor (TLR), cytotoxic T-lymphocyte associated protein (CTLA) and matrix metalloproteinase (MMP), as significant with increased pooled OR in this meta-analysis pointing to risk association of the immune-related genes in cervical carcinogenesis.

Predicting DNA methylation from genetic data lacking racial diversity using shared classified random effects

Public genomic repositories are notoriously lacking in racially and ethnically diverse samples. This limits the reaches of exploration and has in fact been one of the driving factors for the initiation of the All of Us project. Our particular focus here is to provide a model-based framework for accurately predicting DNA methylation from genetic data using racially sparse public repository data. Epigenetic alterations are of great interest in cancer research but public repository data is limited in the information it provides. However, genetic data is more plentiful. Our phenotype of interest is cervical cancer in The Cancer Genome Atlas (TCGA) repository. Being able to generate such predictions would nicely complement other work that has generated gene-level predictions of gene expression for normal samples. We develop a new prediction approach which uses shared random effects from a nested error mixed effects regression model. The sharing of random effects allows borrowing of strength across racial groups greatly improving predictive accuracy. Additionally, we show how to further borrow strength by combining data from different cancers in TCGA even though the focus of our predictions is DNA methylation in cervical cancer. We compare our methodology against other popular approaches including the elastic net shrinkage estimator and random forest prediction. Results are very encouraging with the shared classified random effects approach uniformly producing more accurate predictions - overall and for each racial group.

Profiling of circular RNAs and circTPCN/miR-634/mTOR regulatory pathway in cervical cancer

Circular RNAs (circRNAs) are highly stable forms of endogenous non-coding RNA molecules with diverse biological functions. Some of them have been demonstrated to play crucial roles in the initiation or development of cancers through regulation of gene expression. However, the profiles and the roles of circRNAs in tumorigenesis of cervical cancer remain largely unknown. In the current study, we investigated the expression profiles of circRNAs and their potential oncogenic mechanisms in cervical cancer. The expression patterns, obtained using a microarray assay, revealed a total of 192 differentially expressed circRNAs, of which 106 were upregulated and 86 were downregulated, in cervical cancer samples compared with normal cervical samples. The differential expression of circRNAs was validated using quantitative real-time polymerase chain reaction. Two circRNAs (circTPCN and circFAM185A) were confirmed to be significantly upregulated in cervical cancer samples, indicating that they represent potential biomarkers of cervical cancer. The role and the potential molecular mechanism of circTPCN in cervical cancer tumorigenesis were further investigated. Knockdown of circTPCN significantly suppressed proliferation, migration, and invasion and increased apoptosis of cervical cancer cells in vitro. Molecular analysis revealed that circTPCN acted as a sponge of miR-634 to enhance mTOR expression. Thus, the circTPCN/miR-634/mTOR regulatory pathway might be involved in cervical cancer tumorigenesis, and circTPCN is a potential therapeutic target in cervical cancer.

Preferential expression of a HPV genotype in invasive cervical carcinomas infected by multiple genotypes

Multiple infections by HPV genotypes are frequently detected in HPV+ cervical lesions but the interaction between each viral genotype during carcinogenesis is poorly understood. Here we carried out a comprehensive study to characterize the multiple HPV expression and integration by RNA-seq analyses of 19 invasive cervical carcinomas coinfected by several HPV genotypes. Analysis of tumor DNA by a hybridization assay indicated multiple infections ranging from 2 to 6 different HPV genotypes. RNA-seq analysis showed that a single HPV genotype was preferentially expressed. Finally, the search for HPV/human chimeric transcripts indicated integration from preferentially expressed genotypes. In conclusion, the present study indicated that, in invasive cervical carcinomas infected by multiple HPV genotypes, one HPV was preferentially expressed, supporting the hypothesis that a single HPV genotype was associated with cancer development.

Transcriptomic analyses of gene expression by CRISPR knockout of miR-214 in cervical cancer cells

In this study, we investigate the effect of one such micro RNA, miR-214 which is frequently down-regulated in cervical cancer. In this study, we either CRISPR knocked out or overexpressed miR-214 in cervical cancer cells and analyzed the global mRNA expression by Next Generation Sequencing (NGS) It was observed that a total of 108 genes were upregulated and 178 downregulated between the samples, above and below the baseline respectively. Gene Ontology and KEGG pathway analysis reveal distinct biological processes and pathways. Analysis of gene regulatory networks also gave different network patterns in the two samples. We confirmed the RNA sequencing data for 10 genes; IFIF27, SMAD3, COX11, TP53INP1, ABL2, FGF8, TNFAIP3, NRG1, SP3 and MDM4 by Real-time PCR. This is the first report on the effect of miR-214 on global mRNA profile in cervical cancer cells. This study also reports new biomarkers for cervical cancer prognosis.

Deregulation of H19 is associated with cervical carcinoma

CACX is one of the most common cancer affecting women world-wide. Here, expression microarray analysis revealed 8 over-expressed transcribed pseudogenes (GBP1P1, HLA-DRB6, HLA-H, SLC6A10P, NAPSB, KRT16P2, PTTG3P and RNF126P1), down-regulated 7 lincRNAs (H19, MIR100HG, MEG3, DIO3OS, HOXA11-AS, CD27-AS1 and EPB41L4A-AS) and 6 snoRNAs (SNORD97, SNORD3A, SNORD3C, SNORD3D, SNORA12 and SCARNA9) as DEncGs (log2 fold-change ≥ ±1.0) in CACX. Consequently, down-regulation of lincRNA MEG3 and over-expression of pseudogenes, GBP1P1 and PTTG3P in the microarray analysis were found concordant with the real-time quantitative PCR results upon validation. Then, Ingenuity® Pathway analysis (IPA®) analysis with deregulated DEncGs identified functionally important gene, H19. Further, validation (n = 52) of expression confirmed frequent downregulation of H19 with significant association with its deletion (LOH) and promoter methylation (n = 128) in CACX. Moreover, clinicopathological analysis found Indian CACX patients (n = 26) with alterations of H19 by deletion or, promoter methylation with concomitant low expression have poor prognosis.

A ten-gene methylation signature as a novel biomarker for improving prediction of prognosis and indicating gene targets in endometrial cancer

Endometrial cancer (EC) is a common female reproductive tumor worldwide. Nonetheless, the pathogenesis of EC still remains ambiguous and associated epigenetic mechanism still to be explored. The goal of this study is to investigate whether gene methylation signature is associated with overall survival (OS) for EC patients. In this study, a 10-gene methylation risk model was built and the OS in high- and low-risk groups was significant different. The area under the ROC curve (AUC) of this model was 0.856 at 5 years survival. The nomogram could accurately predict the OS in EC patients, with concordance index and AUC at 5 year survival reached 0.796 and 0.792, respectively. Furthermore, we verified the nomogram with 24 patients in our center and the Kaplan-Meier survival curve also proved to be significantly different (p < 0.01). WGCNA revealed a key gene group for the model and further bioinformatics analysis indicated 6 genes as the hub genes in the module. Knockdown of MMP12 inhibited the proliferation, invasion and metastasis of EC cells. After all, a methylation signature and a nomogram based on this signature were constructed, and they could both predict survival in patients with EC. Moreover, WGCNA model identified MMP12 as a potential target for the treatment of EC.