Predicting biomarkers for ovarian cancer using gene-expression microarrays

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

A bespoke target selection tool to guide biomarker discovery in tubo-ovarian cancer

Introduction

Cancers presenting at advanced stages inherently have poor prognosis. High grade serous carcinoma (HGSC) is the most common and aggressive form of tubo-ovarian cancer. Clinical tests to accurately diagnose and monitor this condition are lacking. Hence, development of disease-specific tests are urgently required.

Methods

The molecular profile of HGSC during disease progression was investigated in a unique patient cohort. A bespoke data browser was developed to analyse gene expression and DNA methylation datasets for biomarker discovery. The Ovarian Cancer Data Browser (OCDB) is built in C# with a.NET framework using an integrated development environment of Microsoft Visual Studio and fast access files (.faf). The graphical user interface is easy to navigate between four analytical modes (gene expression; methylation; combined gene expression and methylation data; methylation clusters), with a rapid query response time. A user should first define a disease progression trend for prioritising results. Single or multiomics data are then mined to identify probes, genes and methylation clusters that exhibit the desired trend. A unique scoring system based on the percentage change in expression/methylation between disease stages is used. Results are filtered and ranked using weighting and penalties.

Results

The OCDB’s utility for biomarker discovery is demonstrated with the identified target OSR2. Trends in OSR2 repression and hypermethylation with HGSC disease progression were confirmed in the browser samples and an independent cohort using bioassays. The OSR2 methylation biomarker could discriminate HGSC with high specificity (95%) and sensitivity (93.18%).

Conclusions

The OCDB has been refined and validated to be an integral part of a unique biomarker discovery pipeline. It may also be used independently to aid identification of novel targets. It carries the potential to identify further biomarker assays that can reduce type I and II errors within clinical diagnostics.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

Differential gene expression and network analysis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy with a poor prognosis, whose biomarkers have not been studied in great detail. We have collected genomic data of HNSCC patients from The Cancer Genome Atlas (TCGA) and analyzed them to get deeper insights into the gene expression pattern. Initially, 793 differentially expressed genes (DEGs) were categorized, and their enrichment analysis was performed. Later, a protein-protein interaction network for the DEGs was constructed using the STRING plugin in Cytoscape to study their interactions. A set of 10 hub genes was selected based on Maximal Clique Centrality score, and later their survival analysis was studied. The elucidated set of 10 genes, i.e., PRAME, MAGEC2, MAGEA12, LHX1, MAGEA3, CSAG1, MAGEA6, LCE6A, LCE2D, LCE2C, referred to as potential candidates to be explored as HNSCC biomarkers. The Kaplan-Meier overall survival of the selected genes suggested that the alterations in the candidate genes were linked to the decreased survival of the HNSCC patients. Altogether, the results of this study signify that the genomic alterations and differential expression of the selected genes can be explored in therapeutic interpolations of HNSCC, exploiting early diagnosis and target-propelled therapy.

Human iPSC-derived fallopian tube organoids with BRCA1 mutation recapitulate early-stage carcinogenesis

Germline pathogenic mutations in BReast CAncer (BRCA1) genes are thought to drive normal fallopian tube epithelial (FTE) cell transformation to high-grade serous ovarian cancer. No human models capture the sequence of events for disease initiation and progression. Here, we generate induced pluripotent stem cells (iPSCs) from healthy individuals and young ovarian cancer patients with germline pathogenic BRCA1 mutations (BRCA1^mut). Following differentiation into FTE organoids, BRCA1^mut lines exhibit cellular abnormalities consistent with neoplastic transformation compared to controls. BRCA1^mut organoids show an increased production of cancer-specific proteins and survival following transplantation into mice. Organoids from women with the most aggressive ovarian cancer show the greatest pathology, indicating the potential value to predict clinical severity prior to disease onset. These human FTE organoids from BRCA1^mut carriers provide a faithful physiological in vitro model of FTE lesion generation and early carcinogenesis. This platform can be used for personalized mechanistic and drug screening studies.

Yucer et al. generate a human BRCA1 mutant iPSC-derived fallopian tube organoid model, which recapitulates BRCA1 mutant ovarian carcinogenesis in vitro and shows tumors in vivo. This model provides a biologically relevant platform to validate drugs and a basis for personalized early detection and preventative strategies for women carrying BRCA1 mutations.

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.

Screening of CXC chemokines in the microenvironment of ovarian cancer and the biological function of CXCL10

BACKGROUND

This study aims to screen and identify the biological functions and prognostic value of CXC chemokines in ovarian cancer (OC) through bioinformatics and molecular biology methods, and to provide data support for the selection of biomarkers and prognostic analysis of OC.

METHODS

In this study, GEO, ONCOMINE, GEPIA, cBioPortal, GeneMANIA, Metascape, STRING, TRRUST, and TIMER databases were used to study CXC chemokines. Angiogenesis and T cell killing assay were used to detect the effect of CXCL10 on tumor cell immunity and angiogenesis. Real-time quantitative PCR (qRT-PCR), immunoblotting, and ectopic tumor formation experiments were used to verify the effect of CXCL10 on ovarian cancer tumors.

RESULTS

We found that CXCL1, CXCL10, CXCL11, CXCL13, and CXCL14 were significantly upregulated in OC samples compared with normal tissues. Our data showed that there was a relationship between the expression of CXC chemokines and the infiltration of six types of immune cells significant correlation. In vitro assay confirmed that overexpression of CXCL10 could enhance the killing effect of T cells and inhibit angiogenesis. Further in vivo assay had shown that CXCL10 could affect the progression of ovarian cancer by increasing the expression of cytotoxic T cells and inhibiting angiogenesis.

CONCLUSION

In conclusion, we hope that our data will provide new insights into the development of immunotherapy and the selection of prognostic markers for patients with OC.

Knockdown of DLGAP5 suppresses cell proliferation, induces G2/M phase arrest and apoptosis in ovarian cancer

Discs large-associated protein 5 (DLGAP5) is a microtubule-associated protein and is reported to exert oncogenic role in tumorigenesis, including lung cancer and hepatocellular carcinoma. However, the prognostic value and biological function of DLGAP5 in ovarian cancer (OC) still remain unclear. The present study investigated the expression pattern of DLGAP5 by searching the Oncomine microarray database. The correlation between DLGAP5 and survival prognosis of OC patients was analyzed by the online tool KM-plotter. Knockdown of DLGAP5 was achieved by transfection with small interfering RNA targeting DLGAP5 in two OC cell lines (SKOV3 and CAOV3). Cell proliferation was assessed by Cell Counting Kit-8 assay and colony-formation assay. Flow cytometry was utilized to determine the effects of DLGAP5 on cell cycle distribution and apoptosis. The present study data showed that DLGAP5 was significantly upregulated in OC and its higher expression was associated with poor survival prognosis. Knockdown of DLGAP5 significantly suppressed cell proliferation, induced cell cycle G₂/M phase arrest and apoptosis. Western blot analysis further demonstrated that DLGAP5 knockdown downregulated the expression of CDK1, Cyclin B1 and Bcl-2, but upregulated Bax expression. Collectively, these data demonstrate that DLGAP5 might be a promising prognostic therapeutic target for OC treatment.

EIF3D promotes the progression of preeclampsia by inhibiting of MAPK/ERK1/2 pathway

Preeclampsia (PE) has been recognized as one of the main reasons for neonatal and maternal mortality and morbidity. This study intended to identify certain genes that correlated with the pathogenesis of PE, and disclose the underlying mechanisms. The GSE14776 and GSE65271 datasets were obtained from the Gene Expression Omnibus database. Venn diagram analysis was performed to identify the differently expressed genes. The potential pathways were analyzed by Gene set enrichment analysis software. The expression of eukaryotic translation initiation factor 3 subunit D (EIF3D) in tissues and cells was respectively tested by immunohistochemistry and the quantitative real-time PCR. Cell transfection was utilized to alter the expression of EIF3D. Cell proliferation, invasion and migration were respectively tested by MTT, EdU, transwell and wound healing assays. Tube formation assay was utilized to determine the tube formation capacity of HTR-8/SVneo cells. ELISA was employed for determination of the concentration of Angiotensin (ANG)-1. Moreover, the expression of EIF3D, proliferation-, metastasis-, tube formation- and MAPK/ERK1/2 pathway-related proteins were measured utilizing western blot. EIF3D was selected in this study. EIF3D was upregulated in placentas tissues collected from patients with PE. EIF3D upregulation observably repressed the proliferation, invasion, migration, wound healing and tube formation of HTR-8/SVneo cells, and the expression of their associated proteins. Besides, the concentration of ANG-1, and the ratios of phosphorylated-ERK1/2 and phosphorylated-MEK1/MEK1 were also markedly lowered by EIF3D upregulation. Whereas, EIF3D knockdown exerted the opposite effects, and these effects were distinctly counteracted by ERK1/2 inhibitor SC-221593 treatment. In conclusion, these observations manifested that EIF3D upregulation might have repressed the progression of PE through modulation of MAPK/ERK1/2 pathway.

m6A Pathway Regulators Are Frequently Mutated in Breast Invasive Carcinoma and May Play an Important Role in Disease Pathogenesis

Breast invasive carcinoma (BIC) is one of the most commonly observed and the deadliest cancer among women. Studies examining the role of epigenetics and regulation of gene expression stand to make important strides in clinical management of BIC. In this context, messenger-RNA (mRNA) modification by regulatory proteins is noteworthy. Methylation of the adenosine base on the sixth nitrogen position is termed as N6-methyladenosine (m⁶A) modification, and this is the most abundant mRNA modification in mammals. Using several publicly available datasets, we report, in this study, comprehensive analyses and new findings on the impact of epitranscriptome regulatory factors and genetic alterations in m⁶A pathway genes on BIC. Accordingly, mutation frequency, type, and expression levels were determined. Importantly, we found that VIRMA, METTL14, RBM15B, EIF3B, YTHDF1, and YTHDF3 genes hold potential significance as prognostic biomarker candidates as evidenced in particular by the overall survival analysis. Enrichment of gene ontology (GO) terms and KEGG pathways for the tumor samples with genetic alterations in the epitranscriptome regulatory pathways were investigated. Dysregulation of regulatory factors in breast cancer was associated with cell division, and survival-related pathways such as "nuclear division," and "chromosome segregation." Hence, the gained overactivity of these pathways may account for BIC's poor prognosis. In conclusion, these data underscore that m⁶A pathway regulators are frequently mutated in BIC and likely play a significant role in disease pathogenesis. Epitranscriptome pathway genes warrant further research attention as regulators of cancer growth and biological targets in BIC, and with an eye to personalized medicine in clinical oncology.

Prolyl-4-Hydroxylase α Subunit 2 as a Novel Potential Biomarker for Predicting the Prognosis of Epithelial Ovarian Carcinoma

Objective

Epithelial ovarian cancer (EOC) is one of the leading causes of death worldwide. The aim of this study was to explore the prognostic significance of prolyl-4-hydroxylase α subunit 2 (P4HA2) in patients with EOC.

Patients and Methods

A total of 217 clinical samples (EOC tissues, 167 cases; normal ovarian, 50 cases) were collected and pathologically confirmed using hematoxylin and eosin (H&E) staining. P4HA2 expression in clinical samples was stained by immunohistochemistry (IHC). Relationship between P4HA2 expression and clinicopathological characteristics of EOC patients were analyzed using chi-square test. The differential expression of targets was analyzed in Oncomine database. The prognostic value of P4HA2 was investigated in clinical EOC patients and Kaplan–Meier (KM) Plotter database.

Results

IHC staining showed that P4HA2 was significantly up-regulated in EOC tissues, compared to the normal tissues. Two databases retrieved from Oncomine database further confirmed the up-regulation P4HA2 in EOC. Chi-square test demonstrated that P4HA2 expression was associated with clinical stage (p=0.036), tumor grade (p<0.001), and residual disease (p=0.022). Both in clinical samples and KM Plotter database, high P4HA2 expression was significantly associated with worse progression-free survival (PFS) and overall survival (OS). Cox’s proportional hazards regression analysis suggested that high P4HA2 expression were independent risk factors for the survival of EOC patients. Besides, we confirmed the positive correlation between P4HA2 and COL1A1 expression. Moreover, COL1A1 was found to be up-regulated in EOC and also associated with short PFS and OS.

Conclusion

The present study preliminarily proved that P4HA2 expression was associated with clinical outcome in EOC patients. P4HA2 might be a prognostic factor for EOC progression, and has the potential to be a valuable therapeutic target for EOC.

Determination of Potential Therapeutic Targets and Prognostic Markers of Ovarian Cancer by Bioinformatics Analysis

This study is to study the expression of CXCRs in ovarian cancer tissues and their value in prognosis. The expressions of CXCR1-CXCR7 mRNA between ovarian tumor tissues and normal tissues and in different pathological types of ovarian tumor tissues were compared by ONCOMINE online tool. The relationship between the expression of CXCRs and clinical pathological staging was studied by GEPIA. Kaplan-Meier plotter online tool was used to analyze prognosis. Finally, GO and KEGG analyses and protein interaction network analysis were performed for CXCRs by the DAVID software to predict their function, and cBioPortal was used to identify the key functional genes. The expression of CXCR3/4/7 mRNA in ovarian cancer tissues was higher than that in normal ovarian tissues, and the expression of CXCR4 was the highest (fold change = 306.413, P < 0.05). The expression of CXCR1/2/3/4/7 mRNA in different pathological types of ovarian tumors was significantly different (P < 0.05). Only CXCR5 expression level was associated with tumor staging. Survival analysis showed that high CXCR7 mRNA expression and low CXCR5/6 expression were associated with the shortening of overall survival. High CXCR4/7 expression and low CXCR5/6 expression were associated with the shortening of progression-free survival. High CXCR2/4 expression and low CXCR5/6 expression were closely related to the shortening of postprogressing survival. Protein interaction network analysis showed that GNB1, PTK2, MAPK1, PIK3CA, GNB4, GNA11, KNG1, and ARNT proteins were closely related to the CXC receptor family. CXCR3/4/7 are potential therapeutic targets, and CXCR2/4/5/6/7 are new markers for the prognosis of ovarian cancer.

Identification and Analysis of An Epigenetically Regulated Five-lncRNA Signature Associated With Outcome and Chemotherapy Response in Ovarian Cancer

The deregulation of long non-coding RNAs (lncRNAs) by epigenetic alterations has been implicated in cancer initiation and progression. However, the epigenetically regulated lncRNAs and their association with clinical outcome and therapeutic response in ovarian cancer (OV) remain poorly investigated. This study performed an integrative analysis of DNA methylation data and transcriptome data and identified 419 lncRNAs as potential epigenetically regulated lncRNAs. Using machine-learning and multivariate Cox regression analysis methods, we identified and developed an epigenetically regulated lncRNA expression signature (EpiLncRNASig) consisting of five lncRNAs from the list of 17 epigenetically regulated lncRNAs significantly associated with outcome. The EpiLncRNASig could stratify patients into high-risk groups and low-risk groups with significantly different survival and chemotherapy response in different patient cohorts. Multivariate Cox regression analyses, after adjusted by other clinical features and treatment response, demonstrated the independence of the DEpiLncSig in predicting survival. Functional analysis for relevant protein-coding genes of the DEpiLncSig indicated enrichment of known immune-related or cancer-related biological pathways. Taken together, our study not only provides a promising prognostic biomarker for predicting outcome and chemotherapy response but also will improve our understanding of lncRNA epigenetic regulation mechanisms in OV.

Bioinformatics Analysis of Potential Therapeutic Targets and Prognostic Biomarkers amid CXC Chemokines in Ovarian Carcinoma Microenvironment

Background

Ovarian cancer (OC) is one of the leading lethal gynecologic cancers of women around the world. More than 70% of patients are diagnosed with stage III or IV with poor outcome. This is partly because of lacking early effective screening techniques and potential biomarkers of OC. CXC chemokines in tumor microenvironment (TME) and their interaction with relative receptors can excite the downstream signaling pathways to influence tumor progression. However, the role of CXC chemokines in OC has not been identified.

Methods

ONCOMINE, GEPIA, Kaplan–Meier plotter, cBioPortal, TIMER, Metascape, and LinkedOmics were applied in our study.

Results

The transcriptional levels of CXCL1/8/9/10/11/12/13/14/16/17 were significantly elevated while CXCL3 was obviously reduced in OC vs normal ovarian tissue. CXCL8/9/11/13 were correlated with clinic pathological stage. Patients with low expression of CXCL8/9/11/13 were associated with better prognosis. We also found that CXCL3 and CXC12 could be used as potential prognostic markers of OC through Kaplan–Meier plotter. Patients with high expression of CXCL3/12 had a significantly better prognosis. Their functions focus on locomotion, signaling, response to stimulus, undergoing the process of multiorganism, immune system, biological regulation, etc. The differentiated CXC chemokines mainly participate in cytokine-cytokine receptor interaction, chemokine signaling pathway, IL-17 signaling pathway, and toll-like receptor signaling pathway. Our results showed that CXC chemokines were highly correlated with infiltration of immune cells. The kinase targets of differentially expressed CXC chemokines are mainly in ATM, LYN, LCK, PLK1, FYN, CDK2, and ATR.

Conclusions

Our results may provide a new insight for selecting precision biomarkers of targeted therapy of OC.

Structure-activity relationship studies of dipeptide-based hepsin inhibitors with Arg bioisosteres

Hepsin is a type II transmembrane serine protease (TTSP) associated with cell proliferation and overexpressed in several types of cancer including prostate cancer (PCa). Because of its significant role in cancer progression and metastasis, hepsin is an attractive protein as a potential therapeutic and diagnostic biomarker for PCa. Based on the reported Leu-Arg dipeptide-based hepsin inhibitors, we performed structural modification and determined in vitro hepsin- and matriptase-inhibitory activities. Comprehensive structure-activity relationship studies identified that the p-guanidinophenylalanine-based dipeptide analog 22a exhibited a strong hepsin-inhibitory activity (K_i = 50.5 nM) and 22-fold hepsin selectivity over matriptase. Compound 22a could be a prototype molecule for structural optimization of dipeptide-based hepsin inhibitors.

Increased Expression of UBE2T Predicting Poor Survival of Epithelial Ovarian Cancer: Based on Comprehensive Analysis of UBE2s, Clinical Samples, and the GEO Database

Ubiquitin-conjugating enzymes E2 (UBE2) have been reported in the microenvironment of various malignant tumors, but their correlation with ovarian cancer (OC) remains elusive. This study aimed to systematically analyze the expression patterns, prognostic value, genetic variation, and biological functions of 12 members of the UBE2 gene family in OC through the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier plotter, cBioPortal, and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) databases, respectively. We found that the mRNA levels of UBE2C, UBE2N, UBE2S, and UBE2T were significantly upregulated in OC compared with those in normal ovarian tissue. In patients with serous ovarian cancer (SOC), UBE2A, UBE2B, UBE2C, UBE2G, UBE2R2, and UBE2T upregulation were associated with poor overall survival. Moreover, UBE2A, UBE2N, UBE2R2, and UBE2T upregulation and UBE2G downregulation were associated with poor progression-free survival. UBE2T exhibited a strong correlation with OC and was thus further examined. We found that UBE2T has a high diagnostic accuracy (area under the receiver operating characteristic curve = 0.969) in epithelial ovarian cancer (EOC). Immunohistochemical assays and the Gene Expression Omnibus (GEO) database revealed that UBE2T was significantly upregulated in EOC compared with that in borderline tumors, benign tumors, and normal ovarian tissues, and its high expression was associated with poor prognosis. The Cox model showed that UBE2T upregulation was an independent risk factor affecting the prognosis of EOC and SOC. Furthermore, UBE2T was associated with specific immune cells and was mainly involved in cell cycle-related events. Genomic analysis showed that TP53 and TTN mutations were associated with UBE2T expression. Gene copy number amplification and hypomethylation may be responsible for UBE2T upregulation in OC. In conclusion, UBE2 family members may play a role in the development of OC. Specifically, UBE2T could serve as a new prognostic marker and therapeutic target for this disease. (IRB Approval No. 2020PS533K).

The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum‐based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene‐gene network, including protein‐protein interaction and co‐expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum‐resistant and platinum‐sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum‐treated patients was performed in the current study. Finally, the RT‐qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.

Brain Metastases from Ovarian Cancer: Current Evidence in Diagnosis, Treatment, and Prognosis

With this review, we provide the state of the art concerning brain metastases (BMs) from ovarian cancer (OC), a rare condition. Clinical, pathological, and molecular features, treatment options, and future perspectives are comprehensively discussed. Overall, a diagnosis of high-grade serous OC and an advanced disease stage are common features among patients who develop brain metastases. BRCA1 and BRCA2 gene mutations, as well as the expression of androgen receptors in the primary tumor, are emerging risk and prognostic factors which could allow one to identify categories of patients at greater risk of BMs, who could benefit from a tailored follow-up. Based on present data, a multidisciplinary approach combining surgery, radiotherapy, and chemotherapy seem to be the best approach for patients with good performance status, although the median overall survival (<1 year) remains largely disappointing. Hopefully, novel therapeutic avenues are being explored, like PARP inhibitors and immunotherapy, based on our improved knowledge regarding tumor biology, but further investigation is warranted.

Integrated Analysis of Prognostic and Immune Associated Integrin Family in Ovarian Cancer

Human integrin receptors are important for cell-cell and cell-matrix adhesion in normal epithelial cells. Emerging evidences have indicated integrin members are involved in cancer development and progression as well. However, the expression patterns and clinical significance of the whole integrin family in ovarian cancer (OC) have not yet been well understood. In the present study, we utilized the public datasets including GEPIA, GEO, ONCOMINE, cBioPortal, Kaplan-Meier Plotter, TIMER databases, to analyze the expression and prognostic value of integrin members in OC. We found ITGA3/B4/B6/B7/B8 were abnormally overexpressed in OC; ITGA6 was good prognosis predictor in OC; ITGA3/ B4/B8 were poor prognosis predictor specially in advanced OC patients; elevated ITGA3/B4 might promote metastasis and elevated ITGA3/B8 might promote platinum resistance of OC; ITGA3 and ITGB4 might synergistically or independently regulate cell adhesion and proliferation; ITGA4/AL/AM/AX/B2/B7 showed strong correlations with various tumor immune infiltrates (TILs), especially with pro-tumor immunes cell types like monocyte, M2 macrophage and exhaustion T cells infiltration; ITGAL/AM/B2/B7 and residing memory CD8+ T cells marker ITGAE were specially associated with early OC patients outcome. Our results implied that ITGA3/B4 were important prognostic markers of advanced OC, ITGAL/AM/ B2/B7 were immune associated prognosis markers of early OC, together they might render important therapeutic targets for OC.

Current insights into the metastasis of epithelial ovarian cancer - hopes and hurdles

BACKGROUND

Ovarian cancer is the most lethal gynecologic cancer and the fifth leading cause of cancer-related mortality in women worldwide. Despite various attempts to improve the diagnosis and therapy of ovarian cancer patients, the survival rate for these patients is still dismal, mainly because most of them are diagnosed at a late stage. Up to 90% of ovarian cancers arise from neoplastic transformation of ovarian surface epithelial cells, and are usually referred to as epithelial ovarian cancer (EOC). Unlike most human cancers, which are disseminated through blood-borne metastatic routes, EOC has traditionally been thought to be disseminated through direct migration of ovarian tumor cells to the peritoneal cavity and omentum via peritoneal fluid. It has recently been shown, however, that EOC can also be disseminated through blood-borne metastatic routes, challenging previous thoughts about ovarian cancer metastasis.

CONCLUSIONS

Here, we review our current understanding of the most updated cellular and molecular mechanisms underlying EOC metastasis and discuss in more detail two main metastatic routes of EOC, i.e., transcoelomic metastasis and hematogenous metastasis. The emerging concept of blood-borne EOC metastasis has led to exploration of the significance of circulating tumor cells (CTCs) as novel and non-invasive prognostic markers in this daunting cancer. We also evaluate the role of tumor stroma, including cancer associated fibroblasts (CAFs), tumor associated macrophages (TAMs), endothelial cells, adipocytes, dendritic cells and extracellular matrix (ECM) components in EOC growth and metastasis. Lastly, we discuss therapeutic approaches for targeting EOC. Unraveling the mechanisms underlying EOC metastasis will open up avenues to the design of new therapeutic options. For instance, understanding the molecular mechanisms involved in the hematogenous metastasis of EOC, the biology of CTCs, and the detailed mechanisms through which EOC cells take advantage of stromal cells may help to find new opportunities for targeting EOC metastasis.

Identification of molecular biomarkers for ovarian cancer using computational approaches

Ovarian cancer is one of the major causes of mortality among women. This is partly because of highly asymptomatic nature, lack of reliable screening techniques and non-availability of effective biomarkers of ovarian cancer. The recent availability of high-throughput data and consequently the development of network medicine approach may play a key role in deciphering the underlying global mechanism involved in a complex disease. This novel approach in medicine will pave the way in translating the new molecular insights into an effective drug therapy applying better diagnostic, prognostic and predictive tests for a complex disease. In this study, we performed reconstruction of gene co-expression networks with a query-based method in healthy and different stages of ovarian cancer to identify new potential biomarkers from the reported biomarker genes. We proposed 17 genes as new potential biomarkers for ovarian cancer that can effectively classify a disease sample from a healthy sample. Most of the predicted genes are found to be differentially expressed between healthy and diseased states. Moreover, the survival analysis showed that these genes have a significantly higher effect on the overall survival rate of the patient than the established biomarkers. The comparative analyses of the co-expression networks across healthy and different stages of ovarian cancer have provided valuable insights into the dynamic nature of ovarian cancer.

The role of the cancer testis antigen PRAME in tumorigenesis and immunotherapy in human cancer

Preferentially expressed antigen in melanoma (PRAME), which belongs to the cancer/testis antigen (CTA) gene family, plays a pivotal role in multiple cellular processes and immunotherapy response in human cancers. PRAME is highly expressed in different types of cancers and is involved in cell proliferation, apoptosis, differentiation and metastasis as well as the outcomes of patients with cancer. In this review article, we discuss the potential roles and physiological functions of PRAME in various types of cancers. Moreover, this review highlights immunotherapeutic strategies that target PRAME in human malignancies. Therefore, the modulation of PRAME might be useful for the treatment of patients with cancer.

Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study

BACKGROUND

Clustering of gene expression data is widely used to identify novel subtypes of cancer. Plenty of clustering approaches have been proposed, but there is a lack of knowledge regarding their relative merits and how data characteristics influence the performance. We evaluate how cluster analysis choices affect the performance by studying four publicly available human cancer data sets: breast, brain, kidney and stomach cancer. In particular, we focus on how the sample size, distribution of subtypes and sample heterogeneity affect the performance.

RESULTS

In general, increasing the sample size had limited effect on the clustering performance, e.g. for the breast cancer data similar performance was obtained for n = 40 as for n = 330. The relative distribution of the subtypes had a noticeable effect on the ability to identify the disease subtypes and data with disproportionate cluster sizes turned out to be difficult to cluster. Both the choice of clustering method and selection method affected the ability to identify the subtypes, but the relative performance varied between data sets, making it difficult to rank the approaches. For some data sets, the performance was substantially higher when the clustering was based on data from only one sex compared to data from a mixed population. This suggests that homogeneous data are easier to cluster than heterogeneous data and that clustering males and females individually may be beneficial and increase the chance to detect novel subtypes. It was also observed that the performance often differed substantially between females and males.

CONCLUSIONS

The number of samples seems to have a limited effect on the performance while the heterogeneity, at least with respect to sex, is important for the performance. Hence, by analyzing the genders separately, the possible loss caused by having fewer samples could be outweighed by the benefit of a more homogeneous data.

Integrated Analysis To Identify Molecular Biomarkers Of High-Grade Serous Ovarian Cancer

Purpose

Ovarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC.

Methods

Six datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein-protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting.

Results

A total of 103 DEGs in patients with HGSOC-28 upregulated genes and 75 downregulated genes-were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally.

Conclusion

Based on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC.

Increased expression of TET3 predicts unfavorable prognosis in patients with ovarian cancer-a bioinformatics integrative analysis

Ovarian carcinoma is a lethal gynecological malignancy. Women with ovarian cancer (OC) are highly recurrent and typically diagnosed at late stage. Ten-eleven translocation protein 3 (TET3) belongs to the family of ten-eleven translocations (TETs) which induce DNA demethylation and gene regulation in epigenetic level by converting 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC). Previous studies indicated that TET3 is overexpressed in ovarian cancer tissues. However, the clinic-pathological functions and prognostic values of TET3 remain unclear. Here we performed an integrative study to identify the role of TET3 by bioinformatics analysis. The TET3 expression in ovarian cancer was assessed with Oncomine database, and validated with TCGA and GTEx database. The correlation of TET3 gene alteration and clinic-pathological functions was addressed by integrative analysis of GEO datasets. Then we showed mainly TET3 gain and diploid but less deletion in ovarian cancer by copy number alteration (CNA) or mutation analysis with cBioPortal. Furthermore, by using Kaplan-Meier plotter (K-M plotter), we evaluated that high TET3 level was associated with poor survival in ovarian cancer patients, which was validated with analysis by PrognoScan database and gene differential analyses with TCGA and GTEx. This is the first study demonstrated that elevated expression of TET3 is associated with poor clinic-pathological functions, poor prognosis, wherein TET3, which presents epigenetic changes or methylation changes, might be served as a diagnostic marker or therapeutic target for ovarian cancer.

Mining expression and prognosis of FOLR1 in ovarian cancer by using Oncomine and Kaplan-Meier plotter

Objective: To further explore folate receptor 1 (FOLR1) gene expression in ovarian cancer and its association with patients’ prognosis by deep mining the Oncomine and Kaplan-Meier plotter databases.

Methods: FOLR1 mRNA expression data of ovarian cancer were retrieved from the Oncomine database and further analyzed by comparing tumor to healthy tissue. The prognostic value of FOLR1 in ovarian cancer was analyzed by Kaplan-Meier Plotter, an online survival analysis database.

Results A total of 439 studies were included in the Oncomine database in multiple types of cancers. Of the 439 studies, there were 54 with statistical differences for the expression of FOLR1, 19 with increased expression of FOLR1 and 35 with decreased expression comparing ovarian cancer to normal ovary tissue. After searching the Oncomine database, six datasets were discovered comparing the mRNA expression in ovarian tumor to healthy tissue. FOLR1 mRNA expression in ovarian tumor was significantly higher than that of normal ovarian tissue (all p<0.05). The Kaplan-Meier Plotter database analyzed the correlation between FOLR1 expression and ovarian cancer patient’s prognosis. A significant difference of progression-free survival between FOLR1 high and low expressing groups was found in ovarian cancer patients (HR=1.14, 95%CI: 1.00-1.29, p=0.043). However, the overall survival was not statistically different between high and low FOLR1 expressing patients (HR=0.95, 95%CI: 0.84-1.09, p=0.48).

Conclusion FOLR1 mRNA was found to be highly expressed in ovarian tumor compared to normal ovarian tissue. Elevated FOLR1 mRNA expression was associated with the poor progression-free survival.

Annexin A8 can serve as potential prognostic biomarker and therapeutic target for ovarian cancer: based on the comprehensive analysis of Annexins

BACKGROUND

Annexins are involved in vesicle trafficking, cell proliferation and apoptosis, but their functional mechanisms in ovarian cancer remain unclear. In this study, we analyzed Annexins in ovarian cancer using different databases and selected Annexin A8 (ANXA8), which showed the greatest prognostic value, for subsequent validation in immunohistochemical (IHC) assays.

METHODS

The mRNA expression levels, genetic variations, prognostic values and gene-gene interaction network of Annexins in ovarian cancer were analyzed using the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, Kaplan-Meier plotter and GeneMANIA database. ANXA8 was selected for analyzing the biological functions and pathways of its co-expressed genes, and its correlation with immune system responses via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and the TISIDB database, respectively. We validated the expression of ANXA8 in ovarian cancer via IHC assays and analyzed its correlation with clinicopathological parameters and prognosis.

RESULTS

ANXA2/3/8/11 mRNA expression levels were significantly upregulated in ovarian cancer, and ANXA5/6/7 mRNA expression levels were significantly downregulated. Prognostic analysis suggested that significant correlations occurred between ANXA2/4/8/9 mRNA upregulation and poor overall survival, and between ANXA8/9/11 mRNA upregulation and poor progression-free survival in patients with ovarian serous tumors. Taken together, results suggested that ANXA8 was most closely associated with ovarian cancer tumorigenesis and progression. Further analyses indicated that ANXA8 may be involved in cell migration, cell adhesion, and vasculature development, as well as in the regulation of PI3K-Akt, focal adhesion, and proteoglycans. Additionally, ANXA8 expression was significantly correlated with lymphocytes and immunomodulators. The IHC results showed that ANXA8 expression was higher in the malignant tumor group than in the borderline and benign tumor groups and normal ovary group, and high ANXA8 expression was an independent risk factor for survival and prognosis of ovarian cancer patients (P = 0.013).

CONCLUSIONS

Members of the Annexin family display varying degrees of abnormal expressions in ovarian cancer. ANXA8 was significantly highly expressed in ovarian cancer, and high ANXA8 expression was significantly correlated with poor prognosis. Therefore, ANXA8 is a high candidate as a novel biomarker and therapeutic target for ovarian cancer.

Expression profile and prognostic value of SFN in human ovarian cancer

Ovarian cancer is a highly lethal cancer in females. Therefore, it is necessary to explore effective biomarkers for the diagnosis and prognosis of the disease. Stratifin (SFN) is a cell cycle checkpoint protein that has been reported to be involved in oncogenesis. Our studies detected the expression of SFN in ovarian cancer by Oncomine, Human Protein Atlas database and ULCAN database. Meanwhile, we found its coexpression gene by cBioPortal online tool and validated their expression in different ovarian cancer cells by western blot and reverse transcription quantitative PCR. Then, we also investigated their prognostic values via the Kaplan–Meier plotter database in different subtypes of ovarian cancer patients. The results demonstrated that SFN was found to be increased in ten various ovarian cancer datasets, compared with healthy tissues. Additionally, up-regulation of SFN expression is associated with age and cancer grades. The higher expression of SFN in all patients with ovarian cancers is significantly correlated with worse postprogression survival. In addition, high SFN expression is associated with significantly worse overall survival in patients who received chemotherapy contains gemcitabine, taxol, taxol+platin, paclitaxel and avastin. In human ovarian carcinoma SKOV3 and A2780 cells, the expression of SFN and its coexpression gene MICB were also increased at protein and mRNA levels compared with the normal ovarian epithelial cells. Based on above results, overexpression of SFN was correlated with the prognosis in ovarian cancer. The present study might be useful for better understanding the clinical significance of SFN mRNA.

Recent progress on inhibitors of the type II transmembrane serine proteases, hepsin, matriptase and matriptase-2

Members of the type II transmembrane serine proteases (TTSP) family play a vital role in cell growth and development but many are also implicated in disease. Two of the well-studied TTSPs, matriptase and hepsin proteolytically process multiple protein substrates such as the inactive single-chain zymogens pro-HGF and pro-macrophage stimulating protein into the active heterodimeric forms, HGF and macrophage stimulating protein. These two proteases also have many other substrates which are associated with cancer and tumor progression. Another related TTSP, matriptase-2 is expressed in the liver and functions by regulating iron homoeostasis through the cleavage of hemojuvelin and thus is implicated in iron overload diseases. In the present review, we will discuss inhibitor design strategy and Structure activity relationships of TTSP inhibitors, which have been reported in the literature.

Mortalin is a distinct bio-marker and prognostic factor in serous ovarian carcinoma

This study focused on mortalin expression and its relevance to the prognosis in serous ovarian carcinoma, mortalin modulated cell malignant proliferation and EMT progression via Wnt/β-Catenin signaling pathway. In this study, data obtained from Oncomine database, Cancer Cell Line Encyclopedia (CCLE) analysis and Immunohistochemical (IHC) staining was used to assess the expression of mortalin in serous ovarian carcinoma. The prognostic value of mortalin was analyzed using Meier plotter database and Kaplan-Meier. MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide) assay, immunofluorescence (IF) staining, and colony formation assay were used to detect cell reproductive capacity. SK-OV-3 cell motility and epithelial-mesenchymal transition (EMT) were measured by wound-healing, migration and western-blot assays. Data from Oncomine showed that mortalin was highly expressed in serous ovarian carcinomas compared with corresponding normal controls. Similar results were found in CCLE analysis and in clinical specimens. High mortalin expression was associated with high histological grade and worse overall survival (OS) rate. The results of MTT analyses, IF staining, and colony formation assay indicated that MKT-077 (1-Ethyl-2-[[3-ethyl-5-(3-methyl-2(3H)-benzothiazolylidene)-4-oxo-2-thiazolidinylidene] methyl]-pyridinium chloride) suppressed the viability of SK-OV-3 cells. Besides, mortalin suppression restrained cell EMT progression by Wnt/β-Catenin signaling pathway. Taken together, mortalin is over-expressed in serous ovarian carcinoma. High mortalin expression could be a candidate for the prognostic indicator and a biomarker in serous ovarian carcinoma.

Distinct expression and prognostic value of members of the epidermal growth factor receptor family in ovarian cancer

Background

Increased aberrant expression or activation of the epidermal growth factor receptor (EGFR) family members has been reported in a wide range of cancers, and the EGFR family of tyrosine kinases has emerged as an important therapeutic target in malignancies. However, the expression patterns and exact roles of each distinct EGFR family member, which contribute to tumorigenesis and progression of ovarian cancer (OC), are yet to be elucidated.

Materials and methods

In the current study, we report the distinct expression and prognostic value of EGFR family members in patients with OC by analyzing a series of databases including ONCOMINE, Gene Expression Profiling Interactive Analysis, Kaplan-Meier plotter, cBioPortal, and Database for Annotation, Visualization and Integrated Discovery .

Results

It was found that in patients with OC, mRNA expression levels of ERBB2/3/4 were significantly upregulated, whereas the transcription levels of EGFR were downregulated. Aberrant EGFR expression and ERBB2/3/4 mRNA levels were associated with OC prognosis.

Conclusion

These results suggest that EGFR and ERBB3/4 are distinct prognostic biomarkers and may be potential targets for OC. These results may be beneficial to better understand the molecular underpinning of OC and may be useful to develop tools for more accurate OC prognosis and for promoting the development of EGFR-targeted inhibitors for OC treatment.

Arginine Citrullination at the C-Terminal Domain Controls RNA Polymerase II Transcription

The post-translational modification of key residues at the C-terminal domain of RNA polymerase II (RNAP2-CTD) coordinates transcription, splicing, and RNA processing by modulating its capacity to act as a landing platform for a variety of protein complexes. Here, we identify a new modification at the CTD, the deimination of arginine and its conversion to citrulline by peptidyl arginine deiminase 2 (PADI2), an enzyme that has been associated with several diseases, including cancer. We show that, among PADI family members, only PADI2 citrullinates R1810 (Cit1810) at repeat 31 of the CTD. Depletion of PADI2 or loss of R1810 results in accumulation of RNAP2 at transcription start sites, reduced gene expression, and inhibition of cell proliferation. Cit1810 is needed for interaction with the P-TEFb (positive transcription elongation factor b) kinase complex and for its recruitment to chromatin. In this way, CTD-Cit1810 favors RNAP2 pause release and efficient transcription in breast cancer cells.

Sab concentrations indicate chemotherapeutic susceptibility in ovarian cancer cell lines

The occurrence of chemotherapy-resistant tumors makes ovarian cancer (OC) the most lethal gynecological malignancy. While many factors may contribute to chemoresistance, the mechanisms responsible for regulating tumor vulnerability are under investigation. Our analysis of gene expression data revealed that Sab, a mitochondrial outer membrane (MOM) scaffold protein, was down-regulated in OC patients. Sab-mediated signaling induces cell death, suggesting that this apoptotic pathway is diminished in OC. We examined Sab expression in a panel of OC cell lines and found that the magnitude of Sab expression correlated to chemo-responsiveness; wherein, OC cells with low Sab levels were chemoresistant. The Sab levels were reflected by a corresponding amount of stress-induced c-Jun N-terminal kinase (JNK) on the MOM. BH3 profiling and examination of Bcl-2 and BH3-only protein concentrations revealed that cells with high Sab concentrations were primed for apoptosis, as determined by the decrease in pro-survival Bcl-2 proteins and an increase in pro-apoptotic BH3-only proteins on mitochondria. Furthermore, overexpression of Sab in chemoresistant cells enhanced apoptotic priming and restored cellular vulnerability to a combination treatment of cisplatin and paclitaxel. Contrariwise, inhibiting Sab-mediated signaling or silencing Sab expression in a chemosensitive cell line resulted in decreased apoptotic priming and increased resistance. The effects of silencing on Sab on the resistance to chemotherapeutic agents were emulated by the silencing or inhibition of JNK, which could be attributed to changes in Bcl-2 protein concentrations induced by sub-chronic JNK inhibition. We propose that Sab may be a prognostic biomarker to discern personalized treatments for OC patients.

Tumor evolution and chemoresistance in ovarian cancer

Development of novel strategies to overcome chemoresistance is central goal in ovarian cancer research. Natural history of the cancer development and progression is being reconstructed by genomic datasets to understand the evolutionary pattern and direction. Recent studies suggest that intra-tumor heterogeneity (ITH) is the main cause of treatment failure by chemoresistance in many types of cancers including ovarian cancer. ITH increases the fitness of tumor to adapt to incompatible microenvironment. Understanding ITH in relation to the evolutionary pattern may result in the development of the innovative approach based on individual variability in the genetic, environment, and life style. Thus, we can reach the new big stage conquering the cancer. In this review, we will discuss the recent advances in understanding ovarian cancer biology through the use of next generation sequencing (NGS) and highlight areas of recent progress to improve precision medicine in ovarian cancer.

Curated compendium of human transcriptional biomarker data

One important use of genome-wide transcriptional profiles is to identify relationships between transcription levels and patient outcomes. These translational insights can guide the development of biomarkers for clinical application. Data from thousands of translational-biomarker studies have been deposited in public repositories, enabling reuse. However, data-reuse efforts require considerable time and expertise because transcriptional data are generated using heterogeneous profiling technologies, preprocessed using diverse normalization procedures, and annotated in non-standard ways. To address this problem, we curated 45 publicly available, translational-biomarker datasets from a variety of human diseases. To increase the data's utility, we reprocessed the raw expression data using a uniform computational pipeline, addressed quality-control problems, mapped the clinical annotations to a controlled vocabulary, and prepared consistently structured, analysis-ready data files. These data, along with scripts we used to prepare the data, are available in a public repository. We believe these data will be particularly useful to researchers seeking to perform benchmarking studies—for example, to compare and optimize machine-learning algorithms' ability to predict biomedical outcomes.

Advanced high-grade serous ovarian cancer: inverse association of KLK13 and KLK14 mRNA levels in tumor tissue and patients' prognosis

PURPOSE

Gene expression of a variety of the 15 members of the KLK serine protease family is dysregulated in ovarian cancer. We aimed at determining the clinical relevance of KLK13 and KLK14 mRNA expression in tumor tissues of a homogeneous patient cohort afflicted with advanced high-grade serous ovarian cancer (FIGO stage III/IV).

METHODS

mRNA expression levels of KLK13 and KLK14 were assessed by quantitative PCR in tumor tissue of 91 patients and related with clinical factors and patients' outcome.

RESULTS

There was no significant association of KLK13 and KLK14 mRNA expression with the clinical factors ascitic fluid volume or residual tumor mass. In univariate Cox regression analysis, elevated KLK13 mRNA levels were significantly linked with shorter progression-free (PFS; hazard ratio [HR] = 1.97, P = 0.020) and overall survival (OS; HR = 1.81, P = 0.041). High KLK14 mRNA levels were significantly associated with prolonged PFS (HR = 0.44, P = 0.017) and showed a trend towards significance for OS (HR = 0.55, P = 0.070). In multivariable analysis, including the factors age, residual tumor mass, ascitic fluid volume, KLK13, and KLK14, both KLKs, apart from residual tumor mass, remained statistically independent predictive markers: patients with high KLK13 mRNA expression levels displayed a more than twofold increase risk for shorter PFS (HR = 2.14, P = 0.020) as well as OS (HR = 2.05, P = 0.028), whereas elevated KLK14 mRNA values were found to be significant for both, prolonged PFS (HR = 0.36, P = 0.007) and OS (HR = 0.46, P = 0.037).

CONCLUSION

These results indicate that in advanced high-grade serous ovarian cancer KLK13 may become proficient for tumor-supporting functions, whereas KLK14 may have adopted tumor-suppressing activity.

Adipocyte-induced CD36 expression drives ovarian cancer progression and metastasis

Ovarian cancer (OvCa) is characterized by widespread and rapid metastasis in the peritoneal cavity. Visceral adipocytes promote this process by providing fatty acids (FAs) for tumour growth. However, the exact mechanism of FA transfer from adipocytes to cancer cells remains unknown. This study shows that OvCa cells co-cultured with primary human omental adipocytes express high levels of the FA receptor, CD36, in the plasma membrane, thereby facilitating exogenous FA uptake. Depriving OvCa cells of adipocyte-derived FAs using CD36 inhibitors and short hairpin RNA knockdown prevented development of the adipocyte-induced malignant phenotype. Specifically, inhibition of CD36 attenuated adipocyte-induced cholesterol and lipid droplet accumulation and reduced intracellular reactive oxygen species (ROS) content. Metabolic analysis suggested that CD36 plays an essential role in the bioenergetic adaptation of OvCa cells in the adipocyte-rich microenvironment and governs their metabolic plasticity. Furthermore, the absence of CD36 affected cellular processes that play a causal role in peritoneal dissemination, including adhesion, invasion, migration and anchorage independent growth. Intraperitoneal injection of CD36-deficient cells or treatment with an anti-CD36 monoclonal antibody reduced tumour burden in mouse xenografts. Moreover, a matched cohort of primary and metastatic human ovarian tumours showed upregulation of CD36 in the metastatic tissues, a finding confirmed in three public gene expression data sets. These results suggest that omental adipocytes reprogram tumour metabolism through the upregulation of CD36 in OvCa cells. Targeting the stromal-tumour metabolic interface via CD36 inhibition may prove to be an effective treatment strategy against OvCa metastasis.

Distinct lymphocyte antigens 6 (Ly6) family members Ly6D, Ly6E, Ly6K and Ly6H drive tumorigenesis and clinical outcome

Stem cell antigen-1 (Sca-1) is used to isolate and characterize tumor initiating cell populations from tumors of various murine models [1]. Sca-1 induced disruption of TGF-β signaling is required in vivo tumorigenesis in breast cancer models [2, 3-5]. The role of human Ly6 gene family is only beginning to be appreciated in recent literature [6-9]. To study the significance of Ly6 gene family members, we have visualized one hundred thirty gene expression omnibus (GEO) dataset using Oncomine (Invitrogen) and Georgetown Database of Cancer (G-DOC). This analysis showed that four different members Ly6D, Ly6E, Ly6H or Ly6K have increased gene expressed in bladder, brain and CNS, breast, colorectal, cervical, ovarian, lung, head and neck, pancreatic and prostate cancer than their normal counter part tissues. Increased expression of Ly6D, Ly6E, Ly6H or Ly6K was observed in sub-set of cancer type. The increased expression of Ly6D, Ly6E, Ly6H and Ly6K was found to be associated with poor outcome in ovarian, colorectal, gastric, breast, lung, bladder or brain and CNS as observed by KM plotter and PROGgeneV2 platform. The remarkable findings of increased expression of Ly6 family members and its positive correlation with poor outcome on patient survival in multiple cancer type indicate that Ly6 family members Ly6D, Ly6E, Ly6K and Ly6H will be an important targets in clinical practice as marker of poor prognosis and for developing novel therapeutics in multiple cancer type.

Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data

Multiple types of high throughput genomics data create a potential opportunity to identify driver patterns in ovarian cancer, which will acquire some novel and clinical biomarkers for appropriate diagnosis and treatment to cancer patients. To identify candidate driver genes and the corresponding driving patterns for resistant and sensitive tumors from the heterogeneous data, we combined gene co-expression modules with mutation modulators and proposed the method to identify driver patterns. Firstly, co-expression network analysis is applied to explore gene modules for gene expression profiles through weighted correlation network analysis (WGCNA). Secondly, mutation matrix is generated by integrating the CNV data and somatic mutation data, and a mutation network is constructed from the mutation matrix. Thirdly, candidate modulators are selected from significant genes by clustering vertexs of the mutation network. Finally, a regression tree model is utilized for module network learning, in which the obtained gene modules and candidate modulators are trained for the driving pattern identification and modulators regulatory exploration. Many identified candidate modulators are known to be involved in biological meaningful processes associated with ovarian cancer, such as CCL11, CCL16, CCL18, CCL23, CCL8, CCL5, APOB, BRCA1, SLC18A1, FGF22, GADD45B, GNA15, GNA11, and so on.

Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data

Multiple types of high throughput genomics data create a potential opportunity to identify driver patterns in ovarian cancer, which will acquire some novel and clinical biomarkers for appropriate diagnosis and treatment to cancer patients. To identify candidate driver genes and the corresponding driving patterns for resistant and sensitive tumors from the heterogeneous data, we combined gene co-expression modules with mutation modulators and proposed the method to identify driver patterns. Firstly, co-expression network analysis is applied to explore gene modules for gene expression profiles through weighted correlation network analysis (WGCNA). Secondly, mutation matrix is generated by integrating the CNV data and somatic mutation data, and a mutation network is constructed from the mutation matrix. Thirdly, candidate modulators are selected from significant genes by clustering vertexs of the mutation network. Finally, a regression tree model is utilized for module network learning, in which the obtained gene modules and candidate modulators are trained for the driving pattern identification and modulators regulatory exploration. Many identified candidate modulators are known to be involved in biological meaningful processes associated with ovarian cancer, such as CCL11, CCL16, CCL18, CCL23, CCL8, CCL5, APOB, BRCA1, SLC18A1, FGF22, GADD45B, GNA15, GNA11, and so on.

Driver pattern identification over the gene co-expression of drug response in ovarian cancer by integrating high throughput genomics data

Multiple types of high throughput genomics data create a potential opportunity to identify driver patterns in ovarian cancer, which will acquire some novel and clinical biomarkers for appropriate diagnosis and treatment to cancer patients. To identify candidate driver genes and the corresponding driving patterns for resistant and sensitive tumors from the heterogeneous data, we combined gene co-expression modules with mutation modulators and proposed the method to identify driver patterns. Firstly, co-expression network analysis is applied to explore gene modules for gene expression profiles through weighted correlation network analysis (WGCNA). Secondly, mutation matrix is generated by integrating the CNV data and somatic mutation data, and a mutation network is constructed from the mutation matrix. Thirdly, candidate modulators are selected from significant genes by clustering vertexs of the mutation network. Finally, a regression tree model is utilized for module network learning, in which the obtained gene modules and candidate modulators are trained for the driving pattern identification and modulators regulatory exploration. Many identified candidate modulators are known to be involved in biological meaningful processes associated with ovarian cancer, such as CCL11, CCL16, CCL18, CCL23, CCL8, CCL5, APOB, BRCA1, SLC18A1, FGF22, GADD45B, GNA15, GNA11, and so on.

Clinical utility of kallikrein-related peptidases (KLK) in urogenital malignancies

Kallikrein-related peptidases (KLK), which represent a major tissue-associated proteolytic system, stand for a rich source of biomarkers that may allow molecular classification, early diagnosis and prognosis of human malignancies as well as prediction of response or failure to cancer-directed drugs. International research points to an important role of certain KLKs in female and male urogenital tract malignancies, in addition to cancers of the lung, brain, skin, head and neck, and the gastrointestinal tract. Regarding the female/male urogenital tract, remarkably, all of the KLKs are expressed in the normal prostate, testis, and kidney whereas the uterus, the ovary, and the urinary bladder are expressing a limited number of KLKs only. Most of the information regarding KLK expression in tumour-affected organs is available for ovarian cancer; all of the 12 KLKs tested so far were found to be elevated in the malignant state, depicting them as valuable biomarkers to distinguish between the normal and the cancerous phenotype. In contrast, for kidney cancer, a series of KLKs was found to be downregulated, while other KLKs were not expressed. Evidently, depending on the type of cancer or cancer stage, individual KLKs may show characteristics of a Janus-faced behaviour, by either expanding or inhibiting cancer progression and metastasis.

Dysregulation of AKT3 along with a small panel of mRNAs stratifies high-grade serous ovarian cancer from both normal epithelia and benign tumor tissues

Screening methods of High-Grade Serous Ovarian Cancer (HGSOC) lack specificity and sensitivity, partly due to benign tumors producing false-positive findings. We utilized a differential expression analysis pipeline on malignant tumor (MT) and normal epithelial (NE) samples, and also filtered the results to discriminate between MT and benign tumor (BT). We report that a panel of 26 dysregulated genes stratifies MT from both BT and NE. We further validated our findings by utilizing unsupervised clustering methods on two independent datasets. We show that the 26-genes panel completely distinguishes HGSOC from NE, and produces a more accurate classification between HGSOC and BT. Pathway analysis reveals that AKT3 is of particular significance, because of its high fold change and appearance in the majority of the dysregulated pathways. mRNA patterns of AKT3 suggest essential connections with tumor growth and metastasis, as well as a strong biomarker potential when used with 3 other genes (PTTG1, MND1, CENPF). Our results show that dysregulation of the 26-mRNA signature panel provides an evidence of malignancy and contribute to the design of a high specificity biomarker panel for detection of HGSOC, potentially in an early more curable stage.

Bilateral ovarian carcinomas differ in the expression of metastasis-related genes

The mechanisms behind bilaterality of ovarian carcinomas are not fully understood, as the two tumors could possibly represent two primary tumors, a primary tumor and a metastasis, or two metastases. The gene expression profiles from bilateral high-grade serous carcinomas (HGSCs) and clear cell carcinomas (CCCs) of the ovary were compared to study the association between the tumors of the two sides. A separate analysis of genes from chromosome 19 was also performed, since this chromosome is frequently rearranged in ovarian carcinomas. Tumors from four patients were included (three pairs of HGSC and one pair of CCC). The gene expression was analyzed at the exon level, and bilateral tumors were compared to identify within-pair differences. Gene expression data were also compared with genomic information on the same tumors. Similarities in gene expression were observed between the tumors within each pair, as expected if the two tumors were clonally related. However, certain genes exhibited differences in expression between the two sides, indicating metastasis involvement. Among the most differently expressed genes, one gene was common to all four pairs: Immunoglobulin J. In all HGSC pairs, serpin peptidase inhibitor, clade B (ovalbumin), member 2, serpin family E member 1 and phospholipase A2, group IIA (platelets, synovial fluid) were also among the differentially expressed genes. The specific analysis of chromosome 19 highlighted expression differences in the zinc finger protein 36 gene. These results indicate that bilateral ovarian tumors represent different stages during progression of a single clonal process. Several of the genes observed to be differently expressed are known to be metastasis-related, and are likely to be also involved in spreading from one side to the other in the bilateral cancer cases examined.

Activin A stimulates migration of the fallopian tube epithelium, an origin of high-grade serous ovarian cancer, through non-canonical signaling

Factors that stimulate the migration of fallopian tube epithelial (FTE)-derived high-grade serous ovarian cancer (HGSOC) to the ovary are poorly elucidated. This study characterized the effect of the ovarian hormone, activin A, on normal FTE and HGSOC. Activin A and TGFβ1 induced an epithelial-to-mesenchymal transition in murine oviductal epithelial (MOE) cells, but only activin A increased migration. The migratory effect of activin A was independent of Smad2/3 and required phospho-AKT, phospho-ERK, and Rac1. Exogenous activin A stimulated migration of the HGSOC cell line OVCAR3 through a similar mechanism. Activin A signaling inhibitors, SB431542 and follistatin, reduced migration in OVCAR4 cells, which expressed activin A subunits (encoded by INHBA). Murine superovulation increased phospho-Smad2/3 immunostaining in the FTE. In Oncomine, transcripts for the activin A receptors (ACVR1B and ACVR2A) were higher in serous tumors relative to the normal ovary, while inhibitors of activin A signaling (INHA and TGFB3) were lower. High expression of both INHBA and ACVR2A, but not TGFβ receptors or co-receptors, was associated with shorter disease-free survival in serous cancer patients. These results suggest activin A stimulates migration of FTE-derived tumors to the ovary.

Mechanisms and Targets Involved in Dissemination of Ovarian Cancer

Ovarian carcinoma is associated with the highest death rate of all gynecological tumors. On one hand, its aggressiveness is based on the rapid dissemination of ovarian cancer cells to the peritoneum, the omentum, and organs located in the peritoneal cavity, and on the other hand, on the rapid development of resistance to chemotherapeutic agents. In this review, we focus on the metastatic process of ovarian cancer, which involves dissemination of, homing to and growth of tumor cells in distant organs, and describe promising molecular targets for possible therapeutic intervention. We provide an outline of the interaction of ovarian cancer cells with the microenvironment such as mesothelial cells, adipocytes, fibroblasts, endothelial cells, and other stromal components in the context of approaches for therapeutic interference with dissemination. The targets described in this review are discussed with respect to their validity as drivers of metastasis and to the availability of suitable efficient agents for their blockage, such as small molecules, monoclonal antibodies or antibody conjugates as emerging tools to manage this disease.

Systematic review: The oncological safety of adipose fat transfer after breast cancer surgery

OBJECTIVES

Oncological concerns have risen around the safety of adipose fat transfer (AFT) after breast cancer surgery. In this article, we present the clinical and molecular evidences, and discuss the current contradiction between them.

MATERIALS AND METHODS

Every clinical trial and experimental study on AFT and its oncological influences was screened. Between September 2014 and September 2016, 856 articles from four databases were found. 105 core articles were selected.

RESULTS

A total of 18 clinical studies have been published. The loco-regional recurrence (LRR) incidence rates range between 0 and 3.90% per year. For the mastectomy and breast conservative therapy group separately, a LRR per year between 0 and 1.62% and 0-3.90 has been reported, respectively. Some studies included a matched control group and found no significant difference between cases and controls, with the exception of a subgroup of patients with intraepithelial breast carcinoma. Adipose derived mesenchymal stem cells have a potential oncogenic effect on residual cancer cells after breast cancer surgery. Numerous signalling proteins and pathways have been described that can stimulate tumour initiation and growth.

CONCLUSION

There is a contradiction between experimental and clinical findings. Numerous adipokines have been discovered that could potentially promote tumour initiation and growth, but clinical studies fail to point out a significant increase in LRR in patients who receive AFT after breast cancer surgery. More prospective studies are needed with a sufficient follow-up time and analysis of some critical factors, such as adjuvant radiotherapy and hormonal therapy, the origin and volume of the injected fat, and genetic influences.

A Five-Gene Expression Signature Predicts Clinical Outcome of Ovarian Serous Cystadenocarcinoma

Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients' survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma.