An epigenetic signature of adhesion molecules predicts poor prognosis of ovarian cancer patients

Integrating Tumor and Organoid DNA Methylation Profiles Reveals Robust Predictors of Chemotherapy Response in Rectal Cancer

Rectal cancer patients display heterogeneous responses to neoadjuvant treatment-including the intensive total neoadjuvant therapy (TNT)-and reliable biomarkers are lacking to guide which tumors will benefit most from these regimens. Here, we profiled DNA methylation in tumor tissue and matched patient-derived organoids (PDOs) from 18 rectal cancer cases (50 total samples), leveraging the Illumina MethylationEPIC array and quality control filters that retained 771,964 CpG sites. Analyses used linear models (for tissue-only or PDO-only) and a joint linear mixed-effects approach (accounting for patient-level random effects) to identify significant CpGs associated with log-transformed FOLFOX IC50. We found that PDOs faithfully recapitulate patient-tumor methylation patterns (Spearman's correlation >0.95 among replicate organoids), and the joint model uncovered 745 CpGs tied to FOLFOX sensitivity, many of which were missed in tissue-only analyses. Differentially methylated regions reinforced that broader epigenetic blocks near TSS or enhancer regions may modulate chemo-resistance, while pathway enrichment pinpointed focal adhesion, ECM-receptor interaction, calcium signaling, and folate metabolism as key processes. A methylation risk score derived from these CpGs significantly predicted progression-free survival in an independent colorectal cancer cohort (p=0.019), outperforming single-sample-based signatures. These findings suggest that combining methylation profiles from both tumors and PDOs can expose robust epigenetic drivers of therapy response, aiding the development of clinically actionable biomarkers for rectal cancer TNT.

TP53 mutations and the association with platinum resistance in high grade serous ovarian carcinoma

OBJECTIVES

Alterations in the tumor suppressor TP53 gene are the most common mutations in high grade serous ovarian carcinoma. The impact of TP53 mutations on clinical outcomes and platinum resistance is controversial. We sought to evaluate the genomic profile of high grade serous ovarian carcinoma and explore the association of TP53 mutations with platinum resistance.

METHODS

Next generation sequencing data was obtained from our institutional database for patients with high grade serous ovarian carcinoma undergoing primary treatment. Sequencing data, demographic, and clinical information was reviewed. The primary outcome analyzed was time to recurrence or refractory diagnosis. Associations between the primary outcome and different classification schemes for TP53 mutations (structural, functional, hot spot, pathogenicity scores, immunohistochemical staining patterns) were performed.

RESULTS

209 patients met inclusion criteria. TP53 mutations were the most common mutation. There were no differences in platinum response with TP53 hotspot mutations or high pathogenicity scores. Presence of TP53 gain-of-function mutations or measure of TP53 gain-of function activity were not associated with platinum resistance. Immunohistochemical staining patterns correlated with expected TP53 protein function and were not associated with platinum resistance.

CONCLUSIONS

TP53 hotspot mutations or high pathogenicity scores were not associated with platinum resistance or refractory disease. Contrary to prior studies, TP53 gain-of-function mutations were not associated with platinum resistance. Estimation of TP53 gain-of-function effect using missense mutation phenotype scores was not associated with platinum resistance. The polymorphic nature of TP53 mutations may be too complex to demonstrate effect using simple models, or response to platinum therapy may be independent of initiating TP53 mutation.

A Bayesian framework for pathway-guided identification of cancer subgroups by integrating multiple types of genomic data

In recent years, comprehensive cancer genomics platforms, such as The Cancer Genome Atlas (TCGA), provide access to an enormous amount of high throughput genomic datasets for each patient, including gene expression, DNA copy number alterations, DNA methylation, and somatic mutation. While the integration of these multi-omics datasets has the potential to provide novel insights that can lead to personalized medicine, most existing approaches only focus on gene-level analysis and lack the ability to facilitate biological findings at the pathway-level. In this article, we propose Bayes-InGRiD (Bayesian Integrative Genomics Robust iDentification of cancer subgroups), a novel pathway-guided Bayesian sparse latent factor model for the simultaneous identification of cancer patient subgroups (clustering) and key molecular features (variable selection) within a unified framework, based on the joint analysis of continuous, binary, and count data. By utilizing pathway (gene set) information, Bayes-InGRiD does not only enhance the accuracy and robustness of cancer patient subgroup and key molecular feature identification, but also promotes biological understanding and interpretation. Finally, to facilitate an efficient posterior sampling, an alternative Gibbs sampler for logistic and negative binomial models is proposed using Pólya-Gamma mixtures of normal to represent latent variables for binary and count data, which yields a conditionally Gaussian representation of the posterior. The R package "INGRID" implementing the proposed approach is currently available in our research group GitHub webpage (https://dongjunchung.github.io/INGRID/).

The Role of CTNNA1 in Malignancies: An Updated Review

Catenin alpha 1 (CTNNA1), encoding α-catenin, is involved in several physiological activities, such as adherens junction synthesis and signal transduction. Recent studies have suggested additional functions for CTNNA1 malignancies. This review systematically summarizes the varying functions of CTNNA1 in different tumors and briefly describes the diverse pathways and mechanisms involved in different types of tumors. CTNNA1 is abnormally expressed in leukemia and solid tumor such as cancers of digestive system, genitourinary system and breast, and it's related to the occurrence, development, and prognosis of tumors. In addition, the possible physiological processes involving CTNNA1, such as methylation, miRNA interference, or regulatory axes, similar to those of CDH1, SETD2, and hsa-miR-30d-5p/GJA1 are also summarized here. The precise mechanism of CTNNA1 in most cancers remains uncertain; hence, additional pre-clinical studies of CTNNA1 are warranted for potential early tumor diagnosis, prognosis, and treatment.

Single-cell and bulk RNA sequencing reveal ligands and receptors associated with worse overall survival in serous ovarian cancer

Background

Serous ovarian carcinoma is the most frequent histological subgroup of ovarian cancer and the leading cause of death among gynecologic tumors. The tumor microenvironment and cancer-associated fibroblasts (CAFs) have a critical role in the origin and progression of cancer. We comprehensively characterized the crosstalk between CAFs and ovarian cancer cells from malignant fluids to identify specific ligands and receptors mediating intercellular communications and disrupted pathways related to prognosis and therapy response.

Methods

Malignant fluids of serous ovarian cancer, including tumor-derived organoids, CAFs-enriched (eCAFs), and malignant effusion cells (no cultured) paired with normal ovarian tissues, were explored by RNA-sequencing. These data were integrated with single-cell RNA-sequencing data of ascites from ovarian cancer patients. The most relevant ligand and receptor interactions were used to identify differentially expressed genes with prognostic values in ovarian cancer.

Results

CAF ligands and epithelial cancer cell receptors were enriched for PI3K-AKT, focal adhesion, and epithelial-mesenchymal transition signaling pathways. Collagens, MIF, MDK, APP, and laminin were detected as the most significant signaling, and the top ligand-receptor interactions THBS2/THBS3 (CAFs)—CD47 (cancer cells), MDK (CAFs)—NCL/SDC2/SDC4 (cancer cells) as potential therapeutic targets. Interestingly, 34 genes encoding receptors and ligands of the PI3K pathway were associated with the outcome, response to treatment, and overall survival in ovarian cancer. Up-regulated genes from this list consistently predicted a worse overall survival (hazard ratio > 1.0 and log-rank P < 0.05) in two independent validation cohorts.

Conclusions

This study describes critical signaling pathways, ligands, and receptors involved in the communication between CAFs and cancer cells that have prognostic and therapeutic significance in ovarian cancer.

MFAP4-Mediated Effects in Elastic Fiber Homeostasis, Integrin Signaling and Cancer, and Its Role in Teleost Fish

Microfibrillar-associated protein 4 (MFAP4) is an extracellular matrix (ECM) protein belonging to the fibrinogen-related domain superfamily. MFAP4 is highly expressed in elastin-rich tissues such as lung, blood vessels and skin. MFAP4 is involved in organization of the ECM, regulating proper elastic fiber assembly. On the other hand, during pathology MFAP4 actively contributes to disease development and progression due to its interactions with RGD-dependent integrin receptors. Both tissue expression and circulating MFAP4 levels are associated with various disorders, including liver fibrosis and cancer. In other experimental models, such as teleost fish, MFAP4 appears to participate in host defense as a macrophage-specific innate immune molecule. The aim of this review is to summarize the accumulating evidence that indicates the importance of MFAP4 in homeostasis as well as pathological conditions, discuss its known biological functions with special focus on elastic fiber assembly, integrin signaling and cancer, as well as describe the reported functions of non-mammalian MFAP4 in fish. Overall, our work provides a comprehensive overview on the role of MFAP4 in health and disease.

Epigenomic Profiling of Epithelial Ovarian Cancer Stem-Cell Differentiation Reveals GPD1 Associated Immune Suppressive Microenvironment and Poor Prognosis

Intraperitoneal metastasis is a challenging clinical scenario in epithelial ovarian cancer (EOC). As they are distinct from hematogenous metastasizing tumors, epithelial ovarian cancer cells primarily disseminate within the peritoneal cavity to form superficially invasive carcinomas. Unfavorable pharmacokinetics for peritoneal tumors and gut toxicity collectively lead to a narrow therapeutic window and therefore limit the opportunities for a favorable clinical outcome. New insights into tumor metastasis in the peritoneal microenvironment are keenly awaited to develop new therapeutic strategies. Epithelial ovarian cancer stem cell (OCSC) seeding is considered to be a critical component of the peritoneal spread. Using a unique and stepwise process of the OCSC differentiation model may provide insight into the intraperitoneal metastasis. The transcriptome and epigenome of OCSC differentiation were characterized by expression array and MethylCap-Seq. The TCGA, AOCS, and KM-Plotter databases were used to evaluate the association between survival outcomes and the methylation/expression levels of candidate genes in the EOC datasets. The STRING database was used to investigate the protein–protein interaction (PPI) for candidates and their associated genes. The infiltration level of immune cells in EOC patients and the association between clinical outcome and OCSCs differentiation genes were estimated using the TIDE and TIME2.0 algorithms. We established an EOC differentiation model using OCSCs. After an integrated transcriptomics and methylomics analysis of OCSCs differentiation, we revealed that the genes associated with earlier OCSC differentiation were better able to reflect the patient’s outcome. The OCSC differentiation genes were involved in regulating metabolism shift and the suppressive immune microenvironment. High GPD1 expression with high pro-tumorigenic immune cells (M2 macrophage, and cancer associated fibroblast) had worst survival. Moreover, we developed a methylation signature, constituted by GNPDA1, GPD1, GRASP, HOXC11, and MSLN, that may be useful for prognostic prediction in EOC. Our results revealed a novel role of epigenetic plasticity OCSC differentiation and suggested metabolic and immune intervention as a new therapeutic strategy.

To Detach, Migrate, Adhere, and Metastasize: CD97/ADGRE5 in Cancer

Tumorigenesis is a multistep process, during which cells acquire a series of mutations that lead to unrestrained cell growth and proliferation, inhibition of cell differentiation, and evasion of cell death. Growing tumors stimulate angiogenesis, providing them with nutrients and oxygen. Ultimately, tumor cells invade the surrounding tissue and metastasize; a process responsible for about 90% of cancer-related deaths. Adhesion G protein-coupled receptors (aGPCRs) modulate the cellular processes closely related to tumor cell biology, such as adhesion and detachment, migration, polarity, and guidance. Soon after first being described, individual human aGPCRs were found to be involved in tumorigenesis. Twenty-five years ago, CD97/ADGRE5 was discovered to be induced in one of the most severe tumors, dedifferentiated anaplastic thyroid carcinoma. After decades of research, the time has come to review our knowledge of the presence and function of CD97 in cancer. In summary, CD97 is obviously induced or altered in many tumor entities; this has been shown consistently in nearly one hundred published studies. However, its high expression at circulating and tumor-infiltrating immune cells renders the systemic targeting of CD97 in tumors difficult.

Circulating tumor DNA: a noninvasive biomarker for tracking ovarian cancer

Ovarian cancer is the fifth leading cause of cancer-related mortality in women worldwide. Despite the development of technologies over decades to improve the diagnosis and treatment of patients with ovarian cancer, the survival rate remains dismal, mainly because most patients are diagnosed at a late stage. Traditional treatment methods and biomarkers such as cancer antigen-125 as a cancer screening tool lack specificity and cannot offer personalized combinatorial therapy schemes. Circulating tumor DNA (ctDNA) is a promising biomarker for ovarian cancer and can be detected using a noninvasive liquid biopsy. A wide variety of ctDNA applications are being elucidated in multiple studies for tracking ovarian carcinoma during diagnostic and prognostic evaluations of patients and are being integrated into clinical trials to evaluate the disease. Furthermore, ctDNA analysis may be used in combination with multiple "omic" techniques to analyze proteins, epigenetics, RNA, nucleosomes, exosomes, and associated immune markers to promote early detection. However, several technical and biological hurdles impede the application of ctDNA analysis. Certain intrinsic features of ctDNA that may enhance its utility as a biomarker are problematic for its detection, including ctDNA lengths, copy number variations, and methylation. Before the development of ctDNA assays for integration in the clinic, such issues are required to be resolved since these assays have substantial potential as a test for cancer screening. This review focuses on studies concerning the potential clinical applications of ctDNA in ovarian cancer diagnosis and discusses our perspective on the clinical research aimed to treat this daunting form of cancer.

Impact of residual disease at interval debulking surgery on platinum resistance and patterns of recurrence for advanced-stage ovarian cancer

OBJECTIVE

To evaluate the impact of size and distribution of residual disease after interval debulking surgery on the timing and patterns of recurrence for patients with advanced-stage epithelial ovarian cancer.

METHODS

Patient demographics and data on disease treatment/recurrence were collected from medical records of patients with stage IIIC/IV epithelial ovarian cancer who were managed with neoadjuvant chemotherapy/interval debulking surgery between January 2010 and December 2014. Among patients without complete surgical resection but with ≤1 cm of residual disease, the number of anatomic sites (<1 cm single anatomic location vs <1 cm multiple anatomic locations) was used to describe the size and distribution of residual disease.  RESULTS: A total of 224 patients were included. Of these, 70.5% (n=158) had a complete surgical resection, 12.5% (n=28) had <1 cm single anatomic location, and 17.0% (n=38) had <1 cm multiple anatomic locations. Two-year progression-free survival for complete surgical resection, <1 cm single anatomic location, and <1 cm multiple anatomic locations was 22.2%, 17.9% and 7%, respectively (p=0.007). Size and distribution of residual disease after interval debulking surgery did not affect location of recurrence and most patients had recurrence at multiple sites (complete surgical resection: 64.7%, <1 cm single anatomic location: 55.6%, and <1 cm multiple anatomic locations: 71.4%). Controlling for additional factors that may influence platinum resistance and surgical complexity, the rate of platinum-resistant recurrence was similar for patients with complete surgical resection and <1 cm single anatomic location (OR=1.07, 95% CI 0.40 to 2.86; p=0.888), but women with <1 cm multiple anatomic locations had an increased risk of platinum resistance (OR=3.09, 95% CI 1.41 to 6.78 p=0.005).

CONCLUSIONS

Despite current classification as 'optimal,' <1 cm multiple anatomic location at the time of interval debulking surgery is associated with a shorter progression-free survival and increased risk of platinum resistance.

Chemotherapy resistance in epithelial ovarian cancer: Mechanisms and emerging treatments

Ovarian cancer (OC) remains a fatal malignancy because most patients experience recurrent disease, which is resistant to chemotherapy. The outcomes for patients with platinum-resistant OC are poor, response rates to further chemotherapy are low and median survival is lower than 12 months. The complexity of platinum-resistant OC, which comprises a heterogeneous spectrum of diseases, is indeed far from being completely understood. Therefore, comprehending tumors' biological behaviour to identify reliable biomarkers, which may predict responses to therapies, is a demanding challenge to improve OC management. In the age of precision medicine, efforts to overcome platinum resistance in OC represent a dynamic and vast field in which innovative drugs and clinical trials rapidly develop. This review will present the exceptional biochemical environment implicated in OC and highlights mechanisms of chemoresistance. Furthermore, innovative molecules and new therapeutic opportunities are presented, along with currently available therapies and ongoing clinical trials.

Effect of LAMA4 on Prognosis and Its Correlation with Immune Infiltration in Gastric Cancer

Background

Laminin alpha 4 (LAMA4) is widely distributed in the basement membranes of various tissues. It can regulate cancer cell proliferation and migration. We investigated the effects of LAMA4 in gastric cancer (GC).

Methods

LAMA4 expression patterns were analyzed in GC using the Gene Expression Omnibus (GEO), Gene Expression Profiling Interactive Analysis (GEPIA), and UALCAN. Correlations between LAMA4 expression and clinicopathological characteristics were evaluated using data from The Cancer Genome Atlas (TCGA). The survival analysis was examined using the Kaplan-Meier plotter and GEPIA and ascertained by multivariate Cox analysis. Genetic alterations and DNA methylation of LAMA4 were analyzed using cBioPortal and MethSurv. LinkedOmics was applied to identify coexpressed genes of LAMA4. The association between LAMA4 and infiltration of immune cells was explored using Tumor Immune Estimation Resource (TIMER) and GEPIA.

Results

LAMA4 was highly expressed in GC, and its upregulation significantly correlated with T classification (P = 0.040). LAMA4 expression was an independent risk factor for overall survival (OS, P = 0.033). Patients with genetic alterations of LAMA4 showed a significantly better disease-free survival (DFS, P = 0.022). Ten CpG sites of LAMA4 were significantly associated with prognosis in GC. The functions of LAMA4 and coexpression genes were mainly involved in extracellular matrix (ECM) receptor interaction. LAMA4 expression significantly correlated with infiltration of macrophages (P < 0.001), CD4+ T cells (P < 0.001), and dendritic cells (P < 0.001). Furthermore, LAMA4 expression was significantly associated with markers of M2 and tumor-associated macrophages (TAMs).

Conclusion

LAMA4 expression was linked to GC prognosis and immune cell infiltration, indicating its potential use as a prognostic biomarker and therapeutic target.

DNA Methylation in Solid Tumors: Functions and Methods of Detection

DNA methylation, i.e., addition of methyl group to 5′-carbon of cytosine residues in CpG dinucleotides, is an important epigenetic modification regulating gene expression, and thus implied in many cellular processes. Deregulation of DNA methylation is strongly associated with onset of various diseases, including cancer. Here, we review how DNA methylation affects carcinogenesis process and give examples of solid tumors where aberrant DNA methylation is often present. We explain principles of methods developed for DNA methylation analysis at both single gene and whole genome level, based on (i) sodium bisulfite conversion, (ii) methylation-sensitive restriction enzymes, and (iii) interactions of 5-methylcytosine (5mC) with methyl-binding proteins or antibodies against 5mC. In addition to standard methods, we describe recent advances in next generation sequencing technologies applied to DNA methylation analysis, as well as in development of biosensors that represent their cheaper and faster alternatives. Most importantly, we highlight not only advantages, but also disadvantages and challenges of each method.

Tumor suppressor gene DLC1: Its modifications, interactive molecules, and potential prospects for clinical cancer application

Deleted in liver cancer 1 (DLC1) is a recognized tumor suppressor gene that negatively regulates Rho family proteins by hydrolyzing the active GTP-bound state to its inactive GDP-bound state. Active Rho proteins play a positive role in tumorigenesis. Numerous in vitro and in vivo experiments have shown that DLC1 is downregulated or inactivated in various solid tumors, which may be due to the following five reasons: genomic deletion, epigenetic modification and ubiquitin-dependent proteasomal degradation may cause DLC1 underexpression; phosphorylation at the post-translation level may cause DLC1 inactivation; and failure to localize at focal adhesions (FAs) may prevent DLC1 from exerting full activity. All of the causes could be attributed to molecular binding. Experimental evidence suggests that direct or indirect targeting of DLC1 is feasible for cancer treatment. Therefore, elucidating the interaction of DLC1 with its binding partners might provide novel targeted therapies for cancer. In this review, we summarized the binding partners of DLC1 at both the gene and protein levels and expounded a variety of anticancer drugs targeting DLC1 to provide information about DLC1 as a cancer diagnostic indicator or therapeutic target.

Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer

The role of an extracellular matrix- (ECM-) receptor interaction signature has not been fully clarified in gastric cancer. This study performed comprehensive analyses on the differentially expressed ECM-related genes, clinicopathologic features, and prognostic application in gastric cancer. The differentially expressed genes between tumorous and matched normal tissues in The Cancer Genome Atlas (TCGA) and validation cohorts were identified by a paired t-test. Consensus clusters were built to find the correlation between clinicopathologic features and subclusters. Then, the least absolute shrinkage and selection operator (lasso) method was used to construct a risk score model. Correlation analyses were made to reveal the relation between risk score-stratified subgroups and clinicopathologic features or significant signatures. In TCGA (26 pairs) and validation cohort (134 pairs), 25 ECM-related genes were significantly highly expressed and 11 genes were downexpressed in gastric cancer. ECM-based subclusters were slightly related to clinicopathologic features. We constructed a risk score model = 0.081∗log₂ (CD36) + 0.043∗log₂ (COL5A2) + 0.001∗log₂ (ITGB5) + 0.039∗log₂ (SDC2) + 0.135∗log₂ (SV2B) + 0.012∗log₂ (THBS1) + 0.068∗log₂ (VTN) + 0.023∗log₂ (VWF). The risk score model could well predict the outcome of patients with gastric cancer in both training (n = 351, HR: 1.807, 95% CI: 1.292-2.528, P = 0.00046) and validation (n = 300, HR: 1.866, 95% CI: 1.347-2.584, P = 0.00014) cohorts. Besides, risk score-based subgroups were associated with angiogenesis, cell adhesion molecules, complement and coagulation cascades, TGF-beta signaling, and mismatch repair-relevant signatures (P < 0.0001). By univariate (1.845, 95% CI: 1.382-2.462, P < 0.001) and multivariate (1.756, 95% CI: 1.284-2.402, P < 0.001) analyses, we regarded the risk score as an independent risk factor in gastric cancer. Our findings revealed that ECM compositions became accomplices in the tumorigenesis, progression, and poor survival of gastric cancer.

Prediction of the treatment response in ovarian cancer: a ctDNA approach

Ovarian cancer is the eighth most commonly occurring cancer in women. Clinically, the limitation of conventional screening and monitoring approaches inhibits high throughput analysis of the tumor molecular markers toward prediction of treatment response. Recently, analysis of liquid biopsies including circulating tumor DNA (ctDNA) open new way toward cancer diagnosis and treatment in a personalized manner in various types of solid tumors. In the case of ovarian carcinoma, growing pre-clinical and clinical studies underscored promising application of ctDNA in diagnosis, prognosis, and prediction of treatment response. In this review, we accumulate and highlight recent molecular findings of ctDNA analysis and its associations with treatment response and patient outcome. Additionally, we discussed the potential application of ctDNA in the personalized treatment of ovarian carcinoma. ctDNA-monitoring usage during the ovarian cancer treatments procedures.

Microfibril-associated glycoprotein 4 (Mfap4) regulates haematopoiesis in zebrafish

Microfibril-associated glycoprotein 4 (MFAP4) is an extracellular matrix protein belonging to the fibrinogen-related protein superfamily. MFAP4 is produced by vascular smooth muscle cells and is highly enriched in the blood vessels of the heart and lung, where it is thought to contribute to the structure and function of elastic fibers. Genetic studies in humans have implicated MFAP4 in the pathogenesis of Smith-Magenis syndrome, in which patients present with multiple congenital abnormalities and mental retardation, as well as in the severe cardiac malformation left-sided congenital heart disease. Comprehensive genetic analysis of the role of MFAP4 orthologues in model organisms during development and tissue homeostasis is however lacking. Here, we demonstrate that zebrafish mfap4 transcripts are detected embryonically, resolving to the macrophage lineage by 24 h post fertilization. mfap4 null mutant zebrafish are unexpectedly viable and fertile, without ostensible phenotypes. However, tail fin amputation assays reveal that mfap4 mutants have reduced numbers of macrophages, with a concomitant increase in neutrophilic granulocytes, although recruitment of both cell types to the site of injury was unaffected. Molecular analyses suggest that loss of Mfap4 alters the balance between myeloid and lymphoid lineages during both primitive and definitive haematopoiesis, which could significantly impact the downstream function of the immune system.

A Comprehensive Risk Assessment Model for Ovarian Cancer Patients with Phospho-STAT3 and IL-31 as Immune Infiltration Relevant Genes

Introduction

Ovarian carcinoma is a malignant tumor with a high mortality rate and a lack of effective treatment options for patients at advanced stages. For improving outcomes and helping patients with poor prognosis, choose a suitable therapy and an excellent risk assessment model and new treatment options are needed.

Materials and Methods

Ovarian cancer gene expression profile of GSE32062 was downloaded from the NCBI GEO database for screening differentially expressed genes (DEGs) between well and poor prognosis groups using limma package in R (version 3.4.1). Prognosis-related genes and clinical prognostic factors were obtained from univariate and multivariate Cox regression analyses, and a comprehensive risk assessment model was constructed using a Pathway Dysregulation Score (PDS) matrix, Cox-Proportional Hazards (Cox-PH) regression, as well as L1-least absolute shrinkage and selection operator (L1-LASSO) penalization. Then, significant DEGs were converted to pathways and optimal prognosis-related pathways were screened. Finally, risk prediction models based on pathways, genes involved in pathways, and comprehensive clinical risk factors with pathways were built. Their prognostic functions were assessed in verification sets. Besides, genes involved in immune-pathways were checked for immune infiltration using immunohistochemistry.

Results

A superior risk assessment model involving 9 optimal combinations of pathways and one clinical factor was constructed. The pathway-based model was found to be superior to the gene-based model. Phospho-STAT3 (from JAK-STAT signaling pathway) and IL-31 (from DEGs) were found to be related to immune infiltration.

Conclusion

We have generated a comprehensive risk assessment model consisting of a clinical risk factor and pathways that showed a possible bright foreground. The set of significant pathways might play as a better prognosis model which is more accurate and applicable than the DEG set. Besides, p-STAT3 and IL-31 showing correlation to immune infiltration of ovarian cancer tissues may be potential therapeutic targets for treating ovarian cancers.

The epigenetic factor BORIS (CTCFL) controls the androgen receptor regulatory network in ovarian cancer

The identification of prognostic biomarkers is a priority for patients suffering from high-grade serous ovarian cancer (SOC), which accounts for >70% of ovarian cancer (OC) deaths. Meanwhile, borderline ovarian cancer (BOC) is a low malignancy tumor and usually patients undergo surgery with low probabilities of recurrence. However, SOC remains the most lethal neoplasm due to the lack of biomarkers for early diagnosis and prognosis. In this regard, BORIS (CTCFL), a CTCF paralog, is a promising cancer biomarker that is overexpressed and controls transcription in several cancer types, mainly in OC. Studies suggest that BORIS has an important function in OC by altering gene expression, but the effect and extent to which BORIS influences transcription in OC from a genome-wide perspective is unclear. Here, we sought to identify BORIS target genes in an OC cell line (OVCAR3) with potential biomarker use in OC tumor samples. To achieve this, we performed in vitro knockout and knockdown experiments of BORIS in OVCAR3 cell line followed by expression microarrays and bioinformatics network enrichment analysis to identify relevant BORIS target genes. In addition, ex vivo expression data analysis of 373 ovarian cancer patients were evaluated to identify the expression patterns of BORIS target genes. In vitro, we uncovered 130 differentially expressed genes and obtained the BORIS-associated regulatory network, in which the androgen receptor (AR) acts as a major transcription factor. Also, FN1, FAM129A, and CD97 genes, which are related to chemoresistance and metastases in OC, were identified. In SOC patients, we observed that malignancy is associated with high levels of BORIS expression while BOC patients show lower levels. Our study suggests that BORIS acts as a main regulator, and has the potential to be used as a prognostic biomarker and to yield novel drug targets among the genes BORIS controls in SOC patients.

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450 K BeadChip (Illumina 450 K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450 K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression, and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones, such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, and TRIM59 showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

MicroRNA-503-5p Inhibits the CD97-Mediated JAK2/STAT3 Pathway in Metastatic or Paclitaxel-Resistant Ovarian Cancer Cells

CD97 shows a strong relationship with metastasis and poor clinical outcome in various tumors, including ovarian cancer. The expression of CD97 in metastatic ovarian cancer cells was higher than that in primary ovarian cancer cells. Mature miRNAs are frequently de-regulated in cancer and incorporated into a specific mRNA, leading to post-transcriptional silencing. In this study, we investigated whether the miR-503-5p targeting of the CD97 3′-untranslated region (3′-UTR) contributes to ovarian cancer metastasis as well as the underlying mechanism regulating cancer progression. In LPS-stimulated or paclitaxel-resistant ovarian cancer cells, stimulation with recombinant human CD55 (rhCD55) of CD97 in ovarian cancer cells activated NF-κB-dependent miR-503-5p down-regulation and the JAK2/STAT3 pathway, consequently promoting the migratory and invasive capacity. Furthermore, restoration of miR-503-5p by transfection with mimics or NF-κB inhibitor efficiently blocked CD97 expression and the downstream JAK2/STAT3 signaling pathway. Target inhibition of JAK with siRNA also impaired colony formation and metastasis of LPS-stimulated and paclitaxel-resistant ovarian cancer cells. Taken together, these results suggest that high CD97 expression, which is controlled through the NF-κB/miR-503-5p signaling pathway, plays an important role in the invasive activity of metastatic and drug-resistant ovarian cancer cells by activating the JAK2/STAT3 pathway.

Epigenetic loss of heparan sulfate 3-O-sulfation sensitizes ovarian carcinoma to oncogenic signals and predicts prognosis

Precision medicine requires markers for therapeutic guidance. The purpose of this study was to determine whether epithelial ovarian cancer (EOC) epigenetics can lead to the identification of biomarkers for precision medicine. Through integrative methylomics, we discovered and validated the epigenetic signature of NEFH and HS3ST2 as an independent prognostic factor for type II EOC in our dataset (n = 84), and two independent methylomics datasets (total n = 467). Integrated transcriptomics dataset (n = 1147) and tissue microarrays (n = 54) of HS3ST2 also related to high-methylation statuses and the EOC prognosis. Mechanistic explorations of HS3ST2 have assessed responses to oncogenic stimulations such as IL-6, EGF, and FGF2 in cancer cells. The combination of HS3ST2 and various oncogenic ligands also confers the worse outcome. 3-O-sulfation of heparan sulfate by HS3ST2 makes ovarian cancer cells intrinsically sensitive to oncogenic signals, which sheds new light on the application of HS3ST2 as a companion diagnostic for targeted therapy using kinase inhibitors or therapeutic antibodies.

Distinct DNA Methylation Profiles in Ovarian Tumors: Opportunities for Novel Biomarkers

Aberrant methylation of multiple promoter CpG islands could be related to the biology of ovarian tumors and its determination could help to improve treatment strategies. DNA methylation profiling was performed using the Methylation Ligation-dependent Macroarray (MLM), an array-based analysis. Promoter regions of 41 genes were analyzed in 102 ovarian tumors and 17 normal ovarian samples. An average of 29% of hypermethylated promoter genes was observed in normal ovarian tissues. This percentage increased slightly in serous, endometrioid, and mucinous carcinomas (32%, 34%, and 45%, respectively), but decreased in germ cell tumors (20%). Ovarian tumors had methylation profiles that were more heterogeneous than other epithelial cancers. Unsupervised hierarchical clustering identified four groups that are very close to the histological subtypes of ovarian tumors. Aberrant methylation of three genes (BRCA1, MGMT, and MLH1), playing important roles in the different DNA repair mechanisms, were dependent on the tumor subtype and represent powerful biomarkers for precision therapy. Furthermore, a promising relationship between hypermethylation of MGMT, OSMR, ESR1, and FOXL2 and overall survival was observed. Our study of DNA methylation profiling indicates that the different histotypes of ovarian cancer should be treated as separate diseases both clinically and in research for the development of targeted therapies.

Biomarkers of platinum resistance in ovarian cancer: what can we use to improve treatment

Ovarian cancer has poor survival rates due to a combination of diagnosis at advanced disease stages and disease recurrence as a result of platinum chemotherapy resistance. High-grade serous ovarian cancer (HGSOC), the most common ovarian cancer subtype, is conventionally treated with surgery and paclitaxel/carboplatin combination chemotherapy. Initial response rates are 60-80%, but eventually the majority of patients become platinum-resistant with subsequent relapses. Extensive research on individual biomarkers of platinum resistance has revealed many potential targets for the development new treatments. While this is ongoing, there are also epigenetic, DNA repair, genome and immune changes characterised in platinum-resistant HGSOC that can be targeted with current therapies. This review discusses biomarkers of platinum chemotherapy resistance in ovarian cancer with a focus on biomarkers that are targetable with alternative treatment combinations to those currently used. After decades of research focused on elucidating the biological cause of platinum resistance, future research needs to focus on using this knowledge to overcome resistance for patients with ovarian cancer.