POSTN/TGFBI-associated stromal signature predicts poor prognosis in serous epithelial ovarian cancer

Improving the Lives of Women With Ovarian Cancer

Being a gynecologic oncologist is a privilege. Women with cancer address their challenges with grit and resilience. Their most basic questions motivated my career-long search for scientific answers hidden in genetics, novel therapeutics, and cancer prevention. But medicine is a team sport. Working alongside gifted colleagues and mentoring trainees to assume starring roles on the team has sustained and enriched my career. Advocating for patients and the specialty of gynecologic oncology provided another means to advance research and cancer awareness to improve patient outcomes. The author believe the most exciting times are yet to come.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

PTX3 activates POSTN and promotes the progression of glioblastoma via the MAPK/ERK signalling axis

BACKGROUND

Intrinsic brain tumours such as glioblastoma (GBM) are believed to develop from neuroglial stem or progenitor cells. GBM accounts for approximately half of gliomas. GBM has a poor prognosis and a low 5-year survival rate. Pentraxin 3 (PTX3) is overexpressed in GBM, but the potential mechanism is unclear.

METHODS

Glioblastoma data from the TCGA and CGGA databases were used to analyse PTX3 expression. Subsequently, in vivo and in vitro experiments were conducted to verify the effect of PTX3 silencing in glioma cells on EMT like process and GSC maintenance. The JASPAR database was used to predict the downstream genes of PTX3. POSTN is a novel target gene of PTX3 in gliomas, and this finding was validated using a luciferase reporter gene assay. Western blotting and KEGG enrichment analysis were used to predict the downstream pathway of POSTN, and it was found that the MAPK/ERK pathway might be related to the function of POSTN.

RESULTS

GBM tissues have higher levels of PTX3 expression than normal brain tissues (NBTs). In functional tests, PTX3 promoted the EMT like process of GBM cells while maintaining the stem cell characteristics of GBM stem cells and enhancing their self-renewal. Moreover, we performed a dual luciferase reporter experiment to confirm that PTX3 binds to the POSTN promoter region. In addition, the expression of key proteins in the MAPK/ERK signalling pathway was increased after PTX3 overexpression.

CONCLUSION

POSTN is a direct target of PTX3 that promotes GBM growth via the MAPK/ERK signalling pathway.

Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning-derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine-learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in-house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.

Periostin facilitates ovarian cancer recurrence by enhancing cancer stemness

The lethality of epithelial ovarian cancer (OC) is largely due to a high rate of recurrence and development of chemoresistance, which requires synergy between cancer cells and the tumor microenvironment (TME) and is thought to involve cancer stem cells. Our analysis of gene expression microarray data from paired primary and recurrent OC tissues revealed significantly elevated expression of the gene encoding periostin (POSTN) in recurrent OC compared to matched primary tumors (p = 0.015). Secreted POSTN plays a role in the extracellular matrix, facilitating epithelial cell migration and tissue regeneration. We therefore examined how elevated extracellular POSTN, as we found is present in recurrent OC, impacts OC cell functions and phenotypes, including stemness. OC cells cultured with conditioned media with high levels of periostin (CMPOSTNhigh) exhibited faster migration (p = 0.0044), enhanced invasiveness (p = 0.006), increased chemoresistance (p < 0.05), and decreased apoptosis as compared to the same cells cultured with control medium (CMCTL). Further, CMPOSTNhigh-cultured OC cells exhibited an elevated stem cell side population (p = 0.027) along with increased expression of cancer stem cell marker CD133 relative to CMCTL-cultured cells. POSTN-transfected 3T3-L1 cells that were used to generate CMPOSTNhigh had visibly enhanced intracellular and extracellular lipids, which was also linked to increased OC cell expression of fatty acid synthetase (FASN) that functions as a central regulator of lipid metabolism and plays a critical role in the growth and survival of tumors. Additionally, POSTN functions in the TME were linked to AKT pathway activities. The mean tumor volume in mice injected with CMPOSTNhigh-cultured OC cells was larger than that in mice injected with CMCTL-cultured OC cells (p = 0.0023). Taken together, these results show that elevated POSTN in the extracellular environment leads to more aggressive OC cell behavior and an increase in cancer stemness, suggesting that increased levels of stromal POSTN during OC recurrence contribute to more rapid disease progression and may be a novel therapeutic target. Furthermore, they also demonstrate the utility of having matched primary-recurrent OC tissues for analysis and support the need for better understanding of the molecular changes that occur with OC recurrence to develop ways to undermine those processes.

A novel role of TGFBI in macrophage polarization and macrophage-induced pancreatic cancer growth and therapeutic resistance

Tumor-associated macrophages (TAMs), as a major and essential component of tumor microenvironment (TME), play a critical role in orchestrating pancreatic cancer (PaC) tumorigenesis from initiation to angiogenesis, growth, and systemic dissemination, as well as immunosuppression and resistance to chemotherapy and immunotherapy; however, the critical intrinsic factors responsible for TAMs reprograming and function remain to be identified. By performing single-cell RNA sequencing, transforming growth factor-beta-induced protein (TGFBI) was identified as TAM-producing factor in murine PaC tumors. TAMs express TGFBI in human PaC and TGFBI expression is positively related with human PaC growth. By inducing TGFBI loss-of-function in macrophage (MΦs) in vitro with siRNA and in vivo with Cre-Lox strategy in our developed TGFBI-floxed mice, we demonstrated disruption of TGFBI not only inhibited MΦ polarization to M2 phenotype and MΦ-mediated stimulation on PaC growth, but also significantly improved anti-tumor immunity, sensitizing PaC to chemotherapy in association with regulation of fibronectin 1, Cxcl10, and Ccl5. Our studies suggest that targeting TGFBI in MΦ can develop an effective therapeutic intervention for highly lethal PaC.

The TGFBI gene and protein expression in topotecan resistant ovarian cancer cell lines

PURPOSE

The primary limiting factor in achieving cures for patients with cancer, particularly ovarian cancer, is drug resistance. The mechanisms of drug resistance of cancer cells during chemotherapy may include compounds of the extracellular matrix, such as the transforming growth factor-beta-induced protein (TGFBI). In this study, we aimed to analyze the TGFBI gene and protein expression in different sensitive and drug-resistant ovarian cancer cell lines, as well as test if TGFBI can be involved in the response to topotecan (TOP) at the very early stages of treatment.

MATERIALS AND METHODS

In this study, we conducted a detailed analysis of TGFBI expression in different ovarian cancer cell lines (A2780, A2780TR1, A2780TR2, W1, W1TR, SKOV-3, PEA1, PEA2 and PEO23). The level of TGFBI mRNA (QPCR), intracellular and extracellular protein (Western blot analysis) were assessed in this study.

RESULTS

We observed upregulation of TGFBI mRNA in drug-resistant cell lines and estrogen-receptor positive cell lines, which was supported by overexpression of both intracellular and extracellular TGFBI protein. We also showed the TGFBI expression after a short period of treatment of sensitive ovarian cancer cell lines with TOP.

CONCLUSION

The expression of TGFBI in ovarian cancer cell lines suggests its role in the development of drug resistance.

The response and resistance to drugs in ovarian cancer cell lines in 2D monolayers and 3D spheroids

Ovarian cancer is the most common type of gynecologic cancer. One of the leading causes of high mortality is chemoresistance, developed primarily or during treatment. Different mechanisms of drug resistance appear at the cellular and cancer tissue organization levels. We examined the differences in response to the cytotoxic drugs CIS, MTX, DOX, VIN, PAC, and TOP using 2D (two-dimensional) and 3D (three-dimensional) culture methods. We tested the drug-sensitive ovarian cancer cell line W1 and established resistant cell lines to appropriate cytotoxic drugs. The following qualitative and quantitative methods were used to assess: 1) morphology - inverted microscope and hematoxylin & eosin staining; 2) viability - MTT assay; 3) gene expression - a quantitative polymerase chain reaction; 4) identification of proteins - immunohistochemistry, and immunofluorescence. Our results indicate that the drug-sensitive and drug-resistant cells cultured in 3D conditions exhibit stronger resistance than the cells cultured in 2D conditions. A traditional 2D model shows that drug resistance of cancer cells is caused mainly by changes in the expression of genes encoding ATP-binding cassette transporter proteins, components of the extracellular matrix, "new" established genes related to drug resistance in ovarian cancer cell lines, and universal marker of cancer stem cells. Whereas in a 3D model, the drug resistance in spheroids can be related to other mechanisms such as the structure of the spheroid (dense or loose), the cell type (necrotic, quiescent, proliferating cells), drug concentrations or drug diffusion into the dense cellular/ECM structure.

Secretome of Stromal Cancer-Associated Fibroblasts (CAFs): Relevance in Cancer

The cancer secretome reflects the assortment of proteins released by cancer cells. Investigating cell secretomes not only provides a deeper knowledge of the healthy and transformed state but also helps in the discovery of novel biomarkers. Secretomes of cancer cells have been studied in the past, however, the secretome contribution of stromal cells needs to be studied. Cancer-associated fibroblasts (CAFs) are one of the predominantly present cell populations in the tumor microenvironment (TME). CAFs play key role in functions associated with matrix deposition and remodeling, reciprocal exchange of nutrients, and molecular interactions and signaling with neighboring cells in the TME. Investigating CAFs secretomes or CAFs-secreted factors would help in identifying novel CAF-specific biomarkers, unique druggable targets, and an improved understanding for personalized cancer diagnosis and prognosis. In this review, we have tried to include all studies available in PubMed with the keywords "CAFs Secretome". We aim to provide a comprehensive summary of the studies investigating role of the CAF secretome on cancer development, progression, and therapeutic outcome. However, challenges associated with this process have also been addressed in the later sections. We have highlighted the functions and clinical relevance of secretome analysis in stromal CAF-rich cancer types. This review specifically discusses the secretome of stromal CAFs in cancers. A deeper understanding of the components of the CAF secretome and their interactions with cancer cells will help in the identification of personalized biomarkers and a more precise treatment plan.

Genetic Influences in Cancer-Associated Myositis

Idiopathic inflammatory myopathies (IIMs) comprise a heterogeneous group of rare immune-mediated disorders that primarily affect muscles but also lead to dysfunction in other organs. Five different clinical subphenotypes of IIM have been distinguished: dermatomyositis, polymyositis, inclusion body myositis, antisynthetase syndrome, and immune-mediated necrotizing myopathy. Excess mortality and morbidity associated with IIM are largely attributed to comorbidities, particularly cancer. The risk of malignancy is not equally distributed among IIM groups and is particularly high among patients with dermatomyositis. The cancer risk peaks around 3 years on either side of the IIM diagnosis and remains elevated even 10 years after the onset of the disease. Lung, colorectal, and ovarian neoplasms typically arise before the onset of IIM, whereas melanoma, cervical, oropharyngeal, and nonmelanoma skin cancers usually develop after IIM diagnosis. Given the close temporal proximity between IIM diagnosis and the emergence of malignancy, it has been proposed that IIM could be a consequence rather than a cause of cancer, a process known as a paramalignant phenomenon. Thus, a separate group of IIMs related to paramalignant phenomenon has been distinguished, known as cancer-associated myositis (CAM). Although the relationship between IIM and cancer is widely recognized, the pathophysiology of CAM remains elusive. Given that genetic factors play a role in the development of IIM, dissection of the molecular mechanisms shared between IIM and cancer presents an opportunity to examine the role of autoimmunity in cancer development and progression. In this review, the evidence supporting the contribution of genetics to CAM will be discussed.

Periostin: an emerging activator of multiple signaling pathways

Matricellular proteins are responsible for regulating the microenvironment, the behaviors of surrounding cells, and the homeostasis of tissues. Periostin (POSTN), a non-structural matricellular protein, can bind to many extracellular matrix proteins through its different domains. POSTN usually presents at low levels in most adult tissues but is highly expressed in pathological sites such as in tumors and inflamed organs. POSTN can bind to diverse integrins to interact with multiple signaling pathways within cells, which is one of its core biological functions. Increasing evidence shows that POSTN can activate the TGF-β, the PI3K/Akt, the Wnt, the RhoA/ROCK, the NF-κB, the MAPK and the JAK pathways to promote the occurrence and development of many diseases, especially cancer and inflammatory diseases. Furthermore, POSTN can interact with some pathways in an upstream and downstream relationship, forming complicated crosstalk. This article focuses on the interactions between POSTN and different signaling pathways in diverse diseases, attempting to explain the mechanisms of interaction and provide novel guidelines for the development of targeted therapies.

Exploration of the underlying biological differences and targets in ovarian cancer patients with diverse immunotherapy response

Background

Preclinical trials of immunotherapy in ovarian cancer (OC) have shown promising results. This makes it meaningful to prospectively examine the biological mechanisms explaining the differences in response performances to immunotherapy among OC patients.

Methods

Open-accessed data was obtained from the Cancer Genome Atlas and Gene Expression Omnibus database. All the analysis was conducted using the R software.

Results

We firstly performed the TIDE analysis to evaluate the immunotherapy response rate of OC patients. The machine learning algorithm LASSO logistic regression and SVM-RFE were used to identify the characteristic genes. The genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were selected for molecular typing. Our result showed that the patients in Cluster1 might have a better prognosis and might be more sensitive to immunotherapy, including PD-1 and CTLA4 therapy options. Pathway enrichment analysis showed that in Cluster2, the pathway of EMT, TNFα/NF-kB signaling, IL2/STAT5 signaling, inflammatory response, KRAS signaling, apical junction, complement, interferon-gamma response and allograft rejection were significantly activated. Also, genomic instability analysis was performed to identify the underlying genomic difference between the different Cluster patients. Single-cell analysis showed that the DPT, COL6A6, LSAMP and RUNX1T1 were mainly expressed in the fibroblasts. We then quantified the CAFs infiltration in the OC samples. The result showed that patients with low CAFs infiltration might have a lower TIDE score and a higher proportion of immunotherapy responders. Also, we found all the characteristic genes DPT, RUNX1T1, PTPRN, LSAMP, FDCSP and COL6A6 were upregulated in the patients with high CAFs infiltration. Immune infiltration analysis showed that the patients in Cluster2 might have a higher infiltration of naive B cells, activated NK cells and resting Dendritic cells.

Conclusions

In summary, our study provides new insights into ovarian cancer immunotherapy. Meanwhile, specific targets DPT, RUNX1T1, PTPRN, LSAMP, FDCSP, COL6A6 and CAFs were identified for OC immunotherapy.

Integrating cell cycle score for precise risk stratification in ovarian cancer

Background: Ovarian cancer (OC) is a highly heterogeneous disease, of which the mesenchymal subtype has the worst prognosis, is the most aggressive, and has the highest drug resistance. The cell cycle pathway plays a vital role in ovarian cancer development and progression. We aimed to screen the key cell cycle genes that regulated the mesenchymal subtype and construct a robust signature for ovarian cancer risk stratification.

Methods: Network inference was conducted by integrating the differentially expressed cell cycle signature genes and target genes between the mesenchymal and non-mesenchymal subtypes of ovarian cancer and identifying the dominant cell cycle signature genes.

Results: Network analysis revealed that two cell cycle signature genes (POLA2 and KIF20B) predominantly regulated the mesenchymal modalities of OC and used to construct a prognostic model, termed the Cell Cycle Prognostic Signature of Ovarian Cancer (CCPOC). The CCPOC-high patients showed an unfavorable prognosis in the GSE26712 cohort, consistent with the results in the seven public validation cohorts and one independent internal cohort (BL-OC cohort, qRT-PCR, n = 51). Functional analysis, drug-sensitive analysis, and survival analysis showed that CCPOC-low patients were related to strengthened tumor immunogenicity and sensitive to the anti-PD-1/PD-L1 response rate in pan-cancer (r = −0.47, OC excluded), which indicated that CCPOC-low patients may be more sensitive to anti-PD-1/PD-L1.

Conclusion: We constructed and validated a subtype-specific, cell cycle-based prognostic signature for ovarian cancer, which has great potential for predicting the response of anti-PD-1/PD-L1.

Computational pathology in ovarian cancer

Histopathologic evaluations of tissue sections are key to diagnosing and managing ovarian cancer. Pathologists empirically assess and integrate visual information, such as cellular density, nuclear atypia, mitotic figures, architectural growth patterns, and higher-order patterns, to determine the tumor type and grade, which guides oncologists in selecting appropriate treatment options. Latent data embedded in pathology slides can be extracted using computational imaging. Computers can analyze digital slide images to simultaneously quantify thousands of features, some of which are visible with a manual microscope, such as nuclear size and shape, while others, such as entropy, eccentricity, and fractal dimensions, are quantitatively beyond the grasp of the human mind. Applications of artificial intelligence and machine learning tools to interpret digital image data provide new opportunities to explore and quantify the spatial organization of tissues, cells, and subcellular structures. In comparison to genomic, epigenomic, transcriptomic, and proteomic patterns, morphologic and spatial patterns are expected to be more informative as quantitative biomarkers of complex and dynamic tumor biology. As computational pathology is not limited to visual data, nuanced subvisual alterations that occur in the seemingly “normal” pre-cancer microenvironment could facilitate research in early cancer detection and prevention. Currently, efforts to maximize the utility of computational pathology are focused on integrating image data with other -omics platforms that lack spatial information, thereby providing a new way to relate the molecular, spatial, and microenvironmental characteristics of cancer. Despite a dire need for improvements in ovarian cancer prevention, early detection, and treatment, the ovarian cancer field has lagged behind other cancers in the application of computational pathology. The intent of this review is to encourage ovarian cancer research teams to apply existing and/or develop additional tools in computational pathology for ovarian cancer and actively contribute to advancing this important field.

Cathelicidin-3 Associated With Serum Extracellular Vesicles Enables Early Diagnosis of a Transmissible Cancer

The identification of practical early diagnostic biomarkers is a cornerstone of improved prevention and treatment of cancers. Such a case is devil facial tumor disease (DFTD), a highly lethal transmissible cancer afflicting virtually an entire species, the Tasmanian devil (Sarcophilus harrisii). Despite a latent period that can exceed one year, to date DFTD diagnosis requires visual identification of tumor lesions. To enable earlier diagnosis, which is essential for the implementation of effective conservation strategies, we analyzed the extracellular vesicle (EV) proteome of 87 Tasmanian devil serum samples using data-independent acquisition mass spectrometry approaches. The antimicrobial peptide cathelicidin-3 (CATH3), released by innate immune cells, was enriched in serum EV samples of both devils with clinical DFTD (87.9% sensitivity and 94.1% specificity) and devils with latent infection (i.e., collected while overtly healthy, but 3-6 months before subsequent DFTD diagnosis; 93.8% sensitivity and 94.1% specificity). Although high expression of antimicrobial peptides has been mostly related to inflammatory diseases, our results suggest that they can be also used as accurate cancer biomarkers, suggesting a mechanistic role in tumorous processes. This EV-based approach to biomarker discovery is directly applicable to improving understanding and diagnosis of a broad range of diseases in other species, and these findings directly enhance the capacity of conservation strategies to ensure the viability of the imperiled Tasmanian devil population.

Copy number and expression of CEP89, a protein required for ciliogenesis, are increased and predict poor prognosis in patients with ovarian cancer

CEP89 (centrosomal protein 89) is required for ciliogenesis and mitochondrial metabolism, but its role in cancer has yet to be clarified. We report that CEP89 is overexpressed in ovarian cancer (OC) compared to normal ovaries. Likewise, its expression is higher in malignant ovarian tumors than in borderline ovarian tumors with low malignant potential. More than a quarter of patients with OC have copy number gains in the CEP89 gene, and patients with high expression have more than a year shorter overall survival compared to those with low expression. Moreover, we found that CEP89 can be considered as a prognostic marker for poor overall survival in patients with OC, after adjusting for tumor stage and residual tumor. Nine out of the top 10 protein interactors of CEP89 have the highest percentage of total copy number variation (CNV) events in OC among all other cancer types. Furthermore, CEP89 messenger RNA (mRNA) levels are higher in OC patients with disease recurrence compared to those with no recurrence. We also analyzed CEP89 levels in OC cell lines in terms of CNV, mRNA, and protein levels; and observed that the FUOV-1 cell line has the highest levels among cell lines that originated from primary sites. Our study suggests that CEP89 may be a valuable prognostic predictor for the overall survival of patients with OC, and it could also be a novel therapeutic target in this malignancy.

The Transcoelomic Ecosystem and Epithelial Ovarian Cancer Dissemination

Epithelial ovarian cancer (EOC) is considered the deadliest gynecological disease and is normally diagnosed at late stages, at which point metastasis has already occurred. Throughout disease progression, EOC will encounter various ecosystems and the communication between cancer cells and these microenvironments will promote the survival and dissemination of EOC. The primary tumor is thought to develop within the ovaries or the fallopian tubes, both of which provide a microenvironment with high risk of causing DNA damage and enhanced proliferation. EOC disseminates by direct extension from the primary tumors, as single cells or multicellular aggregates. Under the influence of cellular and non-cellular factors, EOC spheroids use the natural flow of peritoneal fluid to reach distant organs within the peritoneal cavity. These cells can then implant and seed distant organs or tissues, which develop rapidly into secondary tumor nodules. The peritoneal tissue and the omentum are two common sites of EOC metastasis, providing a microenvironment that supports EOC invasion and survival. Current treatment for EOC involves debulking surgery followed by platinum-taxane combination chemotherapy; however, most patients will relapse with a chemoresistant disease with tumors developed within the peritoneum. Therefore, understanding the role of the unique microenvironments that promote EOC transcoelomic dissemination is important in improving patient outcomes from this disease. In this review article, we address the process of ovarian cancer cellular fate at the site of its origin in the secretory cells of the fallopian tube or in the ovarian surface epithelial cells, their detachment process, how the cells survive in the peritoneal fluid avoiding cell death triggers, and how cancer- associated cells help them in the process. Finally, we report the mechanisms used by the ovarian cancer cells to adhere and migrate through the mesothelial monolayer lining the peritoneum. We also discuss the involvement of the transcoelomic ecosystem on the development of chemoresistance of EOC.

OSov: An Interactive Web Server to Evaluate Prognostic Biomarkers for Ovarian Cancer

Simple Summary

The OSov web server incorporates gene expression profiles with clinical risk factors to estimate the ovarian cancers patients’ survival, and provides a tool for multiple analysis, such as forest-plot, uni/multi-variate survival analysis, Kaplan-Meier plot and nomogram construction.

Abstract

Ovarian cancer is one of the most aggressive and highly lethal gynecological cancers. The purpose of our study is to build a free prognostic web server to help researchers discover potential prognostic biomarkers by integrating gene expression profiling data and clinical follow-up information of ovarian cancer. We construct a prognostic web server OSov (Online consensus Survival analysis for Ovarian cancer) based on RNA expression profiles. OSov is a user-friendly web server which could present a Kaplan–Meier plot, forest plot, nomogram and survival summary table of queried genes in each individual cohort to evaluate the prognostic potency of each queried gene. To assess the performance of OSov web server, 163 previously published prognostic biomarkers of ovarian cancer were tested and 72% of them had their prognostic values confirmed in OSov. It is a free and valuable prognostic web server to screen and assess survival-associated biomarkers for ovarian cancer.

Construction of a Macrophage Infiltration Regulatory Network and Related Prognostic Model of High-Grade Serous Ovarian Cancer

Background

High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated.

Method

We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts.

Results

In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group.

Conclusion

We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.

TGFBI Production by Macrophages Contributes to an Immunosuppressive Microenvironment in Ovarian Cancer

The tumor microenvironment evolves during malignant progression, with major changes in nonmalignant cells, cytokine networks, and the extracellular matrix (ECM). In this study, we aimed to understand how the ECM changes during neoplastic transformation of serous tubal intraepithelial carcinoma lesions (STIC) into high-grade serous ovarian cancers (HGSOC). Analysis of the mechanical properties of human fallopian tubes (FT) and ovaries revealed that normal FT and fimbria had a lower tissue modulus, a measure of stiffness, than normal or diseased ovaries. Proteomic analysis of the matrisome fraction between FT, fimbria, and ovaries showed significant differences in the ECM protein TGF beta induced (TGFBI, also known as βig-h3). STIC lesions in the fimbria expressed high levels of TGFBI, which was predominantly produced by CD163-positive macrophages proximal to STIC epithelial cells. In vitro stimulation of macrophages with TGFβ and IL4 induced secretion of TGFBI, whereas IFNγ/LPS downregulated macrophage TGFBI expression. Immortalized FT secretory epithelial cells carrying clinically relevant TP53 mutations stimulated macrophages to secrete TGFBI and upregulated integrin αvβ3, a putative TGFBI receptor. Transcriptomic HGSOC datasets showed a significant correlation between TGFBI expression and alternatively activated macrophage signatures. Fibroblasts in HGSOC metastases expressed TGFBI and stimulated macrophage TGFBI production in vitro. Treatment of orthotopic mouse HGSOC tumors with an anti-TGFBI antibody reduced peritoneal tumor size, increased tumor monocytes, and activated β3-expressing unconventional T cells. In conclusion, TGFBI may favor an immunosuppressive microenvironment in STICs that persists in advanced HGSOC. Furthermore, TGFBI may be an effector of the tumor-promoting actions of TGFβ and a potential therapeutic target. SIGNIFICANCE: Analysis of ECM changes during neoplastic transformation reveals a role for TGFBI secreted by macrophages in immunosuppression in early ovarian cancer.

Identification of a glycolysis-related gene signature for survival prediction of ovarian cancer patients

Background

Ovarian cancer (OV) is deemed the most lethal gynecological cancer in women. The aim of this study was to construct an effective gene prognostic model for predicting overall survival (OS) in patients with OV.

Methods

The expression profiles of glycolysis‐related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed using training and test sets.

Results

A gene risk signature based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4) was identified to predict the survival outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high‐grade OV, in the TCGA dataset, with areas under the curve (AUC) of 0.709 and 0.762 for 3‐ and 5‐year survival, respectively. Similar results were found in the test sets, and the AUCs of 3‐, 5‐year OS were 0.714 and 0.772 in the combined test set. And our signature was an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was developed.

Conclusion

Our study established a nine‐GRG risk model and nomogram to better predict OS in patients with OV. The risk model represents a promising and independent prognostic predictor for patients with OV. Moreover, our study on GRGs could offer guidance for the elucidation of underlying mechanisms in future studies.

TGFBI Expression Predicts the Survival of Patients With Oropharyngeal Squamous Cell Carcinoma

BACKGROUND/AIM

This study was conducted to investigate transforming growth factor beta-induced protein (TGFBI) expression and analyze the clinical and prognostic significance of TGFBI in oropharyngeal squamous cell carcinoma (OPSCC).

PATIENTS AND METHODS

We evaluated TGFBI expression by immunohistochemistry in 94 patients with OPSCC. For comprehensive analysis, TGFBI expression was subdivided into tumor cell score (T), stroma score (S), and the sum of two scores (TS) calculated using H-score. Clinicopathological features and survival outcomes were compared between groups of high expression and low expression of TGFBI in each area.

RESULTS

Overall, 12 patients (12.8%) showed high T score, and 41 patients (43.6%) revealed high S score. Although T score showed no significant difference both in overall survival (OS) (p=0.080) and recurrence free survival (RFS) (p=0.272), high S score patients had significantly worse OS (p=0.003) and worse RFS (p=0.043). High TS score also showed significant association with worse OS (p=0.011) and worse RFS (p=0.021). High S score was an independent prognostic factor predicting shorter OS (HR=6.352, 95%CI=1.206-40.050, p=0.029) and RFS (HR=18.843, 95%CI=1.030-344.799, p=0.048) in the multivariate analysis.

CONCLUSION

High S score of TGFBI was a significant predictor of poor prognosis in OPSCC. TGFBI could be a useful new predictive and prognostic biomarker in OPSCC.

Differential Expression and Copy Number Variation of Gasdermin (GSDM) Family Members, Pore-Forming Proteins in Pyroptosis, in Normal and Malignant Serous Ovarian Tissue

Gasdermins (GSDM) are members of a family of pore-forming effector proteins which lead to membrane permeabilization and pyroptosis, a lytic cell death with pro-inflammatory characteristics. Recently, two members of the gasdermin family, gasdermin B (GSDMB) and gasdermin E (GSDME), were shown to suppress tumor growth, through the involvement of cytotoxic lymphocytes. Other studies also reported the important functions of gasdermins in various cancer types including gastric cancer, hepatocarcinoma, and cervix and breast cancer. However, gasdermins have not been previously studied in the context of serous ovarian cancer. Here, we showed that gasdermin D (GSDMD) and gasdermin C (GSDMC) expression increases in serous ovarian cancer; in contrast, the expression of GSDME and PJVK (Pejvakin, DFNB59) is downregulated, compared to healthy ovaries, in multiple independent gene expression datasets. We found that copy number gains are highly frequent (present in approximately 50% of patients) in genes encoding GSDMD and GSDMC in ovarian cancer, in line with their upregulated expression in serous ovarian cancer. Moreover, we observed that the expression of GSDMB and GSDMD, but not of GSDME, is different among several histotypes of epithelial ovarian cancer. Therefore, we propose that differential expression and copy number variations of certain gasdermins might be associated with the development of serous ovarian cancer, in which different members of the family have distinct functions; however, further research is required in in vivo models to understand how changes in gasdermin family members mechanistically contribute to serous ovarian cancer.

The Long-Term Prognostic Significance of Circulating Tumor Cells in Ovarian Cancer-A Study of the OVCAD Consortium

INTRODUCTION

We previously reported the prognostic impact of circulating tumor cells (CTCs) in a multicenter study on minimal residual disease in primary ovarian cancer. With additional follow-up data, we evaluated the combined CTC approach (CTCs^combo), in particular for the patients who had survived more than five years.

MATERIAL AND METHODS

Blood samples taken at baseline and six months after adjuvant treatment (follow-up) were assessed by quantitative PCR (qPCR) measuring PPIC transcripts and immunofluorescent staining (IF). A positive result with either IF or qPCR was classified as CTC^combo-positive. Further, PPIC was assessed in the primary tumor tissue.

RESULTS

The concordance of IF and qPCR was 65% at baseline and 83% after treatment. Results showed that 50.5% of the baseline and 29.5% of the follow-up samples were CTC^combo-positive. CTCs^combo after treatment were associated with increased mortality after adjusting for FIGO stage (HR 2.574, 95% CI: 1.227-5.398, p = 0.012), a higher risk of recurrence after adjusting for peritoneal carcinosis (HR 4.068, 95% CI: 1.948-8.498, p < 0.001), and increased mortality after five survived years.

DISCUSSION

The two-sided analytical approach revealed CTC subpopulations associated with ovarian cancer progression and may illuminate a potential treatment-related shift in molecular phenotypes. That approach can identify patients who have elevated risk of recurrence and death due to ovarian cancer and who may require risk-adapted treatment strategies.

MRPL15 is a novel prognostic biomarker and therapeutic target for epithelial ovarian cancer

PURPOSE

To analyze the role of six human epididymis protein 4 (HE4)-related mitochondrial ribosomal proteins (MRPs) in ovarian cancer and selected MRPL15, which is most closely related to the tumorigenesis and prognosis of ovarian cancer, for further analyses.

METHODS

Using STRING database and MCODE plugin in Cytoscape, six MRPs were identified among genes that are upregulated in response to HE4 overexpression in epithelial ovarian cancer cells. The Cancer Genome Atlas (TCGA) ovarian cancer, GTEX, Oncomine, and TISIDB were used to analyze the expression of the six MRPs. The prognostic impact and genetic variation of these six MRPs in ovarian cancer were evaluated using Kaplan-Meier Plotter and cBioPortal, respectively. MRPL15 was selected for immunohistochemistry and GEO verification. TCGA ovarian cancer data, gene set enrichment analysis, and Enrichr were used to explore the mechanism of MRPL15 in ovarian cancer. Finally, the relationship between MRPL15 expression and immune subtype, tumor-infiltrating lymphocytes, and immune regulatory factors was analyzed using TCGA ovarian cancer data and TISIDB.

RESULTS

Six MRPs (MRPL10, MRPL15, MRPL36, MRPL39, MRPS16, and MRPS31) related to HE4 in ovarian cancer were selected. MRPL15 was highly expressed and amplified in ovarian cancer and was related to the poor prognosis of patients. Mechanism analysis indicated that MRPL15 plays a role in ovarian cancer through pathways such as the cell cycle, DNA repair, and mTOR 1 signaling. High expression of MRPL15 in ovarian cancer may be associated with its amplification and hypomethylation. Additionally, MRPL15 showed the lowest expression in C3 ovarian cancer and was correlated with proliferation of CD8⁺ T cells and dendritic cells as well as TGFβR1 and IDO1 expression.

CONCLUSION

MRPL15 may be a prognostic indicator and therapeutic target for ovarian cancer. Because of its close correlation with HE4, this study provides insights into the mechanism of HE4 in ovarian cancer.

The role of the extracellular matrix protein TGFBI in cancer

The secreted extracellular protein, transforming growth factor beta induced (TGFBI or βIGH3), has roles in regulating numerous biological functions, including cell adhesion and bone formation, both during embryonic development and during the pathogenesis of human disease. TGFBI has been most studied in the context of hereditary corneal dystrophies, where mutations in TGFBI result in accumulation of TGFBI in the cornea. In cancer, early studies focused on TGFBI as a tumor suppressor, in part by promoting chemotherapy sensitivity. However, in established tumors, TGFBI largely has a role in promoting tumor progression, with elevated levels correlating to poorer clinical outcomes. As an important regulator of cancer progression, TGFBI expression and function is tightly regulated by numerous mechanisms including epigenetic silencing through promoter methylation and microRNAs. Mechanisms to target TGFBI have potential clinical utility in treating advanced cancers, while assessing TGFBI levels could be a biomarker for chemotherapy resistance and tumor progression.

Piperine Targets Different Drug Resistance Mechanisms in Human Ovarian Cancer Cell Lines Leading to Increased Sensitivity to Cytotoxic Drugs

Our goal was to examine the anticancer effects of piperine against the resistant human ovarian cancer cells and to explore the molecular mechanisms responsible for its anticancer effects. Our study used drug-sensitive ovarian cancer cell line W1 and its sublines resistant to paclitaxel (PAC) and topotecan (TOP). We analyzed the cytotoxic effect of piperine and cytostatic drugs using an MTT assay. The impact of piperine on protein expression was determined by immunofluorescence and Western blot. We also examined its effect on cell proliferation and migration. We noticed a different level of piperine resistance between cell lines. Piperine increases the cytotoxic effect of PAC and TOP in drug-resistant cells. We observed an increase in PTPRK expression correlated with decreased pTYR level after piperine treatment and downregulation of P-gp and BCRP expression. We also noted a decrease in COL3A1 and TGFBI expression in investigated cell lines and increased COL3A1 expression in media from W1PR2 cells. The expression of Ki67 protein and cell proliferation rate decreased after piperine treatment. Piperine markedly inhibited W1TR cell migration. Piperine can be considered a potential anticancer agent that can increase chemotherapy effectiveness in cancer patients.

Epigenetic Mechanisms beyond Tumour-Stroma Crosstalk

Despite cancer having been usually considered the result of genetic mutations, it is now well established that epigenetic dysregulations play pivotal roles in cancer onset and progression. Hence, inactivation of tumour suppressor genes can be gained not only by genetic mutations, but also by epigenetic mechanisms such as DNA methylation and histone modifications. To occur, epigenetic events need to be triggered by genetic alterations of the epigenetic regulators, or they can be mediated by intracellular and extracellular stimuli. In this last setting, the tumour microenvironment (TME) plays a fundamental role. Therefore, to decipher how epigenetic changes are associated with TME is a challenge still open. The complex signalling between tumour cells and stroma is currently under intensive investigation, and most of the molecules and pathways involved still need to be identified. Neoplastic initiation and development are likely to involve a back-and-forth crosstalk among cancer and stroma cells. An increasing number of studies have highlighted that the cancer epigenome can be influenced by tumour microenvironment and vice versa. Here, we discuss about the recent literature on tumour-stroma interactions that focus on epigenetic mechanisms and the reciprocal regulation between cancer and TME cells.

Determinants and Functions of CAFs Secretome During Cancer Progression and Therapy

Multiple lines of evidence are indicating that cancer development and malignant progression are not exclusively epithelial cancer cell-autonomous processes but may also depend on crosstalk with the surrounding tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are abundantly represented in the TME and are continuously interacting with cancer cells. CAFs are regulating key mechanisms during progression to metastasis and response to treatment by enhancing cancer cells survival and aggressiveness. The latest advances in CAFs biology are pointing to CAFs-secreted factors as druggable targets and companion tools for cancer diagnosis and prognosis. Especially, extensive research conducted in the recent years has underscored the potential of several cytokines as actionable biomarkers that are currently evaluated in the clinical setting. In this review, we explore the current understanding of CAFs secretome determinants and functions to discuss their clinical implication in oncology.

Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

BACKGROUND

The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC.

METHODS

The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis.

RESULTS

8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK.

CONCLUSION

The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.

A broad analysis in clinical and in vitro models on regulator of G-protein signalling 10 regulation that is associated with ovarian cancer progression and chemoresistance

Ovarian cancer is one of the deadliest types of gynaecological cancers and more than half of the patients die within 5 years after diagnosis. Recurrence in advanced staged patients after chemotherapy is associated with increased chemoresistance, which results in poor prognosis. Regulator of G-protein signalling 10 (RGS10) negatively regulates cell proliferation, migration and survival by attenuating G-protein coupled-receptors mediated signalling pathways. Recent studies have shown that loss of RGS10 expression is significantly associated with proliferation and cisplatin resistance in ovarian cancer cells. SIGNIFICANCE OF THE STUDY: In this study, we analysed differential RGS10 expression levels using public microarray datasets from clinical and in vitro ovarian cancer samples. We validated that cancer progression and chemotherapy exposure change RGS10 expression. We enriched our study to evaluate the relationship between chemoresistance and differential RGS10 expression against ovarian cancer potential chemotherapeutic agent, palbociclib. Results showed that palbociclib treatment reduced cell viability, despite significantly decreased RGS10 expression in chemoresistant cells. Overall, the results confirmed that cancer progression and chemoresistance are significantly associated with the down-regulation of RGS10 while some chemotherapeutics seem to be beneficial in decreasing chemoresistance in ovarian cancer.

Stromal POSTN induced by TGF-β1 facilitates the migration and invasion of ovarian cancer

OBJECTIVE

Periostin (POSTN) overexpression observed in various cancer types is correlated with metastasis and tumor progression. However, its effect on the crosstalk between ovarian cancer cells and cancer-associated fibroblasts (CAFs) remains elusive. This study aims to ascertain the role of CAF-derived POSTN in the ovarian cancer microenvironment.

METHODS

POSTN expression in high-grade serous ovarian cancer (HGSC) was detected through immunochemistry. Transwell assay was conducted to determine cell migration and invasion. POSTN was knocked down or overexpressed using lentiviral vectors. The potential downstream effects of POSTN were explored and verified by RNA sequencing and western blotting, respectively. In vitro metastatic capability of ovarian cancer cells regulated by POSTN was determined by indirect co-culture.

RESULTS

POSTN was highly enriched in HGSC stromal components, particularly in fibroblasts, while its overexpression was correlated with reduced overall survival (OS). CAF-derived POSTN functioned as a ligand for integrin αvβ3, fueling the migration and invasion of ovarian cancer cells by activating the PI3K/Akt pathway and inducing the epithelial-mesenchymal transition (EMT). Additionally, the pro-metastatic properties and the activation of fibroblasts induced by TGF-β1 partly relied on POSTN.

CONCLUSIONS

Stromal-derived POSTN drives the remodeling of the pro-metastatic microenvironment, which might be as a potential therapeutic target in patients with ovarian cancer.

Periostin Secreted by Carcinoma-Associated Fibroblasts Promotes Ovarian Cancer Cell Platinum Resistance Through the PI3K/Akt Signaling Pathway

Periostin (POSTN) is a protein secreted by mesenchymal cells. Periostin is upregulated in several cancer types and overexpression is associated with poor prognosis. However, the functional role and molecular underpinnings of periostin in epithelial ovarian cancer (EOC) is unknown. In the present study, periostin was found to be significantly upregulated in EOC stroma. Functional studies revealed that periostin could decrease cisplatin (DDP)-induced apoptosis in EOC. Periostin led to DDP resistance in EOC cells, potentially through the PI3K/Akt signaling pathway. We generated periostin-overexpressing fibroblasts and found that EOC cells were resistant to DDP when co-cultured with periostin-overexpressing fibroblasts. The findings of the present study indicated that periostin secreted by cancer-associated stromal cells may be a potential therapeutic target for EOC.

Epigenomic Reprogramming toward Mesenchymal-Epithelial Transition in Ovarian-Cancer-Associated Mesenchymal Stem Cells Drives Metastasis

A role for cancer cell epithelial-to-mesenchymal transition (EMT) in cancer is well established. Here, we show that, in addition to cancer cell EMT, ovarian cancer cell metastasis relies on an epigenomic mesenchymal-to-epithelial transition (MET) in host mesenchymal stem cells (MSCs). These reprogrammed MSCs, termed carcinoma-associated MSCs (CA-MSCs), acquire pro-tumorigenic functions and directly bind cancer cells to serve as a metastatic driver/chaperone. Cancer cells induce this epigenomic MET characterized by enhancer-enriched DNA hypermethylation, altered chromatin accessibility, and differential histone modifications. This phenomenon appears clinically relevant, as CA-MSC MET is highly correlated with patient survival. Mechanistically, mirroring MET observed in development, MET in CA-MSCs is mediated by WT1 and EZH2. Importantly, EZH2 inhibitors, which are clinically available, significantly inhibited CA-MSC-mediated metastasis in mouse models of ovarian cancer.

Analysis in epithelial ovarian cancer identifies KANSL1 as a biomarker and target gene for immune response and HDAC inhibition

OBJECTIVE

There is an immunoreactive subtype of ovarian cancer with a favorable prognosis, but the majority of ovarian cancers have limited immune reactivity. The reason for this is poorly understood. This study aimed to approach this question by identifying prognostically relevant genes whose prognostic mRNA expression levels correlated with a genomic event.

METHODS

Expression microarray and 5-year survival data on 170 ovarian tumors and aCGH data on 45 ovarian cancer cell lines were used to identify amplified/deleted genes associated with prognosis. Three immune-response genes were identified mapping to epigenetically modified chromosome 6p21.3. Genes were searched for roles in epigenetic modification, identifying KANSL1. Genome-wide association studies were searched to identify genetic variants in KANSL1 associated with altered immune profile. Sensitivity to HDAC inhibition in cell lines with KANSL1 amplification/rearrangement was studied.

RESULTS

Expression of 196 genes was statistically significantly associated with survival, and expression levels correlated with copy number variations for 82 of them. Among these, 3 immune-response genes (HCP5, PSMB8, PSMB9) clustered together at epigenetically modified chromosome 6p21.3 and their expression was inversely correlated to epigenetic modification gene KANSL1. KANSL1 is amplified/rearranged in ovarian cancer, associated with lymphocyte profile, a biomarker for response to HDAC inhibition, and may drive expression of immune-response genes.

CONCLUSION

This study identifies 82 genes with prognostic relevance and genomic alteration in ovarian cancer. Among these, immune-response genes have correlated expression which is associated with 5-year survival. KANSL1 may be a master gene altering immune-response gene expression at 6p21.3 and drive response to HDAC inhibitors. Future research should investigate KANSL1 and determine whether targeting it alters the immune profile of ovarian cancer and improves survival, HDAC inhibition, and/or immunotherapy response.

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).

Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

Transcription factors (TFs) are major contributors to cancer risk and somatic development. In preclinical and clinical studies, direct or indirect inhibition of TF-mediated oncogenic gene expression profiles have proven to be effective in many tumor types, highlighting this group of proteins as valuable therapeutic targets. In spite of this, our understanding of TFs in epithelial ovarian cancer (EOC) is relatively limited. EOC is a heterogeneous disease composed of five major histologic subtypes; high-grade serous, low-grade serous, endometrioid, clear cell and mucinous. Each histology is associated with unique clinical etiologies, sensitivity to therapies, and molecular signatures - including diverse transcriptional regulatory programs. While some TFs are shared across EOC subtypes, a set of TFs are expressed in a histotype-specific manner and likely explain part of the histologic diversity of EOC subtypes. Targeting TFs present with unique opportunities for development of novel precision medicine strategies for ovarian cancer. This article reviews the critical TFs in EOC subtypes and highlights the potential of exploiting TFs as biomarkers and therapeutic targets.

Integrative network analysis identifies an immune-based prognostic signature as the determinant for the mesenchymal subtype in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) has been classified into four molecular subtypes, of which the mesenchymal subtype has the poorest survival. Our goal is to develop an immune-based prognostic signature by incorporating molecular subtypes for EOC patients.

METHODS

The gene expression profiles of EOC samples were collected from seven public datasets as well as an internal retrospective validation cohort, containing 1192 EOC patients. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for EOC (IPSEOC). The signature was trained and validated in eight independent datasets.

RESULTS

Seven immune genes were identified as key regulators of the mesenchymal subtype and were used to construct the IPSEOC. The IPSEOC significantly divided patients into high- and low-risk groups in discovery (OS: P < .0001), 6 independent public validation sets (OS: P = .04 to P = .002), and an internal retrospective validation cohort (OS: P = .025). Furthermore, pathway analysis revealed that differences between risk groups were mainly activation of mesenchymal-related signalling. Moreover, a significant correlation existed between the IPSEOC values versus clinical phenotypes including late tumor stages, drug resistance.

CONCLUSION

We propose an immune-based signature, which is a promising prognostic biomarker in ovarian cancer. Prospective studies are needed to further validate its analytical accuracy and test the clinical utility.

Collagen-rich omentum is a premetastatic niche for integrin α2-mediated peritoneal metastasis

The extracellular matrix (ECM) plays critical roles in tumor progression and metastasis. However, the contribution of ECM proteins to early metastatic onset in the peritoneal cavity remains unexplored. Here, we suggest a new route of metastasis through the interaction of integrin alpha 2 (ITGA2) with collagens enriched in the tumor coinciding with poor outcome in patients with ovarian cancer. Using multiple gene-edited cell lines and patient-derived samples, we demonstrate that ITGA2 triggers cancer cell adhesion to collagen, promotes cell migration, anoikis resistance, mesothelial clearance, and peritoneal metastasis in vitro and in vivo. Mechanistically, phosphoproteomics identify an ITGA2-dependent phosphorylation of focal adhesion kinase and mitogen-activated protein kinase pathway leading to enhanced oncogenic properties. Consequently, specific inhibition of ITGA2-mediated cancer cell-collagen interaction or targeting focal adhesion signaling may present an opportunity for therapeutic intervention of metastatic spread in ovarian cancer.

Investigating genetic drivers of dermatomyositis pathogenesis using meta-analysis

Aims

Dermatomyositis (DM) is a progressive, idiopathic inflammatory myopathy with poorly understood pathogenesis. A hallmark of DM is an increased risk for developing breast, ovarian, and lung cancer. Since autoantibodies against anti-TIF-1-γ, a member of the tripartite motif (TRIM) proteins, has a strong association with malignancy, we examined expression of the TRIM gene family to identify pathways that may be contributing to DM pathogenesis.

Materials and methods

We employed the Search Tag Analyze Resource for GEO platform to search the NCBI Gene Expression Omnibus to elucidate TRIM family gene expression as well as oncogenic drivers in DM pathology. We conducted meta-analysis of the data from human skin (60 DM vs 34 healthy) and muscle (71 DM vs 22 healthy).

Key findings

We identified genes involved in innate immunity, antigen presentation, metabolism, and other cellular processes as facilitators of DM disease activity and confirmed previous observations regarding the presence of a robust interferon signature. Moreover, analysis of DM muscle samples revealed upregulation of TRIM14, TRIM22, TRIM25, TRIM27, and TRIM38. Likewise, analysis of DM skin samples showed upregulation of TRIM5, TRIM6, TRIM 14, TRIM21, TRIM34, and TRIM38 and downregulation of TRIM73. Additionally, we noted upregulation of oncogenes IGLC1, IFI44, POSTN, MYC, NPM1, and IDO1 and related this change to interferon signaling. While the clinical data associated with genetic data that was analyzed did not contain clinical data regarding malignancy in these cohorts, the observed genetic changes may be associated with homeostatic and signaling changes that relate to the increased risk in malignancy in DM.

Significance

Our results implicate previously unknown genes as potential drivers of DM pathology and suggest certain TRIM family members may have disease-specific roles with potential diagnostic and therapeutic implications.

GAB2 and GAB3 are expressed in a tumor stage-, grade- and histotype-dependent manner and are associated with shorter progression-free survival in ovarian cancer

Ovarian cancer is the most lethal gynecological malignancy and molecular mechanisms of its progression and metastasis are not completely understood. Some members of GAB (GRB2-associated binding) protein family have been reported to be involved in tumor cell proliferation and metastasis in various cancer types. In the present study, we analyzed the expression of GAB proteins (GAB1, GAB2 and GAB3) in ovarian cancer compared to normal ovarian tissue, in terms of tumor stage, tumor grade and histological type. Differential expression analyses performed in R programming environment using multiple transcriptome datasets (n = 1449) showed that GAB1 expression is decreased in ovarian cancer independently of tumor stage, grade and histotype. Unlike GAB1, expression of GAB2 and GAB3 are increased from early stage to late stage and from low grade to high grade in epithelial ovarian cancer. GAB2 and GAB3 also showed histotype-dependent expression. GAB3 was computed as a top gene whose expression most significantly changed between tumor cells from primary tumor, metastases and ascites. High expression of GAB2 and GAB3 was shown to be associated with shorter progression-free survival in ovarian cancer. This study shows that GAB2 and GAB3 can be important regulators of tumor progression and metastasis in ovarian cancer.

Prognostic gene expression signature for high-grade serous ovarian cancer

BACKGROUND

Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.

PATIENTS AND METHODS

Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.

RESULTS

Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years.

CONCLUSION

The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.

DNA methylation biomarkers for nasopharyngeal carcinoma

Background

Aberrant methylation of DNA plays an important role in the pathogenesis of nasopharyngeal carcinoma (NPC). In the current study, we aimed to integrate three cohorts profile datasets to identify abnormally methylated-differentially expressed genes and pathways associated with NPC.

Methods

Data of gene expression microarrays (GSE53819, GSE412452) and gene methylation microarrays (GSE52068) obtained from the GEO database. Aberrantly methylated differentially expressed genes (DEGs) were obtained by GEO2R. The David database was utilized to perform enrichment and functional analysis regarding selected genes. To create a protein-protein interaction (PPI), STRING and Cytoscape software were utilized. The MCODE was used for module analysis of the PPI network.

Results

In total, 181 hypomethylation-high expression genes were identified, which were enriched in the biological mechanisms involved in the differentiation of endodermal cell, mitotic nuclear division, mitotic cell cycle process, chromosome segregation and cell cycle phase transition, etc. Pathway enrichment showed ECM-receptor interaction, PI3K-Akt signaling pathway, Focal adhesion, Protein digestion and absorption and Amoebiasis, etc. The top 3 hub genes of PPI network were FANCI, POSTN, and IFIH1. Additionally, 210 hypermethylation-low expression genes were identified, and our data revealed enrichment in biological processes including axoneme assembly, micro tubular formation, assembly of axonemal dynein complex, cilium movement and cilium organization, etc. Pathway analysis indicated enrichment in B cell receptor signaling pathway, Hematopoietic cell lineage, Leukocyte transendothelial migration, Complement and coagulation cascades and Fc gamma R-mediated phagocytosis, etc. The ZMYND10, PACRG and POU2AF1 were identified as the top three hub genes of PPI network. After validation in TCGA and GEPIA database, most hub genes remained significant. Patients with high expression of POSTN found to have shorter overall survival, while in patients with high expression of ZMYND10 and POU2AF1 longer overall survival was identified.

Conclusions

The data revealed novel aberrantly methylated-differentially expressed genes and pathways in NPC by bioinformatics analysis, potentially providing novel insights for the molecular mechanisms governing NPC progression. Hub genes including FANCI, POSTN, IFIH1, ZMYND10, PACRG and POU2AF1 might serve as novel biomarkers for precision diagnosis and providing medical treatment for patient with NPC.

The Significance of MicroRNAs Expression in Regulation of Extracellular Matrix and Other Drug Resistant Genes in Drug Resistant Ovarian Cancer Cell Lines

Ovarian cancer rates the highest mortality among all gynecological malignancies. The main reason for high mortality is the development of drug resistance. It can be related to increased expression of drug transporters and increased expression of extracellular matrix (ECM) proteins. Our foremost aim was to exhibit alterations in the miRNA expression levels in cisplatin (CIS), paclitaxel (PAC), doxorubicin (DOX), and topotecan (TOP)-resistant variants of the W1 sensitive ovarian cancer cell line-using miRNA microarray. The second goal was to identify miRNAs responsible for the regulation of drug-resistant genes. According to our observation, alterations in the expression of 40 miRNAs were present. We could observe that, in at least one drug-resistant cell line, the expression of 21 miRNAs was upregulated and that of 19 miRNAs was downregulated. We identified target genes for 22 miRNAs. Target analysis showed that miRNA regulates key genes responsible for drug resistance. Among others, we observed regulation of the ATP-binding cassette subfamily B member 1 gene (ABCB1) in the paclitaxel-resistant cell line by miR-363 and regulation of the collagen type III alpha 1 chain gene (COL3A1) in the topotekan-resistant cell line by miR-29a.

The Repertoire of Serous Ovarian Cancer Non-genetic Heterogeneity Revealed by Single-Cell Sequencing of Normal Fallopian Tube Epithelial Cells

The inter-differentiation between cell states promotes cancer cell survival under stress and fosters non-genetic heterogeneity (NGH). NGH is, therefore, a surrogate of tumor resilience but its quantification is confounded by genetic heterogeneity. Here we show that NGH in serous ovarian cancer (SOC) can be accurately measured when informed by the molecular signatures of the normal fallopian tube epithelium (FTE) cells, the cells of origin of SOC. Surveying the transcriptomes of ∼6,000 FTE cells, predominantly from non-ovarian cancer patients, identified 6 FTE subtypes. We used subtype signatures to deconvolute SOC expression data and found substantial intra-tumor NGH. Importantly, NGH-based stratification of ∼1,700 tumors robustly correlated with survival. Our findings lay the foundation for accurate prognostic and therapeutic stratification of SOC.

Fibronectin and Periostin as Prognostic Markers in Ovarian Cancer

Previously, based on a DNA microarray experiment, we identified a 96-gene prognostic signature associated with the shorter survival of ovarian cancer patients. We hypothesized that some differentially expressed protein-coding genes from this signature could potentially serve as prognostic markers. The present study was aimed to validate two proteins, namely fibronectin (FN1) and periostin (POSTN), in the independent set of ovarian cancer samples. Both proteins are mainly known as extracellular matrix proteins with many important functions in physiology. However, there are also indications that they are implicated in cancer, including ovarian cancer. The expression of these proteins was immunohistochemically analyzed in 108 surgical samples of advanced ovarian cancer (majority: high-grade serous) and additionally on tissue arrays representing different stages of the progression of ovarian and fallopian tube epithelial tumors, from normal epithelia, through benign tumors, to adenocarcinomas of different stages. The correlation with clinical, pathological, and molecular features was evaluated. Kaplan-Meier survival analysis and Cox-proportional hazards models were used to estimate the correlation of the expression levels these proteins with survival. We observed that the higher expression of fibronectin in the tumor stroma was highly associated with shorter overall survival (OS) (Kaplan-Meier analysis, log-rank test p = 0.003). Periostin was also associated with shorter OS (p = 0.04). When we analyzed the combined score, calculated by adding together individual scores for stromal fibronectin and periostin expression, Cox regression demonstrated that this joint FN1&POSTN score was an independent prognostic factor for OS (HR = 2.16; 95% CI: 1.02-4.60; p = 0.044). The expression of fibronectin and periostin was also associated with the source of ovarian tumor sample: metastases showed higher expression of these proteins than primary tumor samples (χ² test, p = 0.024 and p = 0.032). Elevated expression of fibronectin and periostin was also more common in fallopian cancers than in ovarian cancers. Our results support some previous observations that fibronectin and periostin have a prognostic significance in ovarian cancer. In addition, we propose the joint FN1&POSTN score as an independent prognostic factor for OS. Based on our results, it may also be speculated that these proteins are related to tumor progression and/or may indicate fallopian-epithelial origin of the tumor.

Gene signature characteristic of elevated stromal infiltration and activation is associated with increased risk of hematogenous and lymphatic metastasis in serous ovarian cancer

Background

The clinical significance of hematogenous and lymphatic metastasis in ovarian cancer has been increasingly addressed, as it plays an imperative role in the formation of both intraperitoneal and distant metastases. Our objective is to identify the key molecules and biological processes potentially related to this relatively novel metastatic route in serous ovarian cancer.

Methods

Since lymphovascular space invasion (LVSI) is considered as the first step of hematogenous and lymphatic dissemination, we developed a gene signature mainly based on the transcriptome profiles with available information on LVSI status in the Cancer Genome Atlas (TCGA) dataset. We then explored the underlying biological rationale and prognostic value of the identified gene signature using multiple public databases.

Results

We observe that primary tumors with increased risk of hematogenous and lymphatic metastasis highly express a panel of genes, namely POSTN, LUM, THBS2, COL3A1, COL5A1, COL5A2, FAP1 and FBN1. The identified geneset is characterized by enhanced deposition of extracellular matrix and extensive stromal activation. Mechanistically, both the recruitment and the activation of stromal cells, especially fibroblasts, are closely associated with lymphovascular metastasis. Survival analysis further reveals that the elevated expression of the identified genes correlates to cancer progression and poor prognosis in patients with serous ovarian cancer.

Conclusions

Our findings indicate that tumor stroma supports the hematogenous and lymphatic spread of ovarian cancer, increasing tumor invasiveness and ultimately resulting in worse survival. Thus stroma-targeted therapies may improve the clinical outcomes in combination with cytoreductive surgery and chemotherapy.

MicroRNA-150-5p promotes cell motility by inhibiting c-Myb-mediated Slug suppression and is a prognostic biomarker for recurrent ovarian cancer

Treatment of ovarian cancer (OvCa) remains challenging owing to its high recurrence rates. Detachment of cancer cells into the peritoneal fluid plays a key role in OvCa relapse, but how this occurs remains incompletely understood. Here we examined global miRNA expression profiles of paired primary/recurrent OvCa specimens and identified a novel biomarker, microRNA-150-5p (miR-150-5p), that was significantly upregulated in 16 recurrent OvCa tissues compared with their matched primary specimens. Analyses of cohorts from two other groups confirmed that expression of miR-150-5p was associated with early relapse and poor survival of OvCa patients. Inhibition of miR-150-5p significantly inhibited the migration and invasion of OvCa cells and induced a mesenchymal-epithelial transition (MET) phenotype. We demonstrated that the proto-oncogene, MYB, is an miR-150-5p target in OvCa cells and that the miR-150-5p/c-Myb/Slug axis plays important roles in regulating epithelial-mesenchymal transition (EMT) in OvCa cells. Expression of MYB was significantly correlated with good clinical outcome in OvCa and was negatively correlated with Slug expression in late-stage clinical specimens. These results suggest that miR-150-5p upregulation mediates the progression of recurrent OvCa by targeting the c-Myb/Slug pathway. Inhibition of miR-150-5p may serve as a new therapeutic strategy for preventing recurrence of OvCa.

Identification of hedgehog signaling as a potential oncogenic driver in an aggressive subclass of human hepatocellular carcinoma: A reanalysis of the TCGA cohort

Hepatocellular carcinoma (HCC) is a heterogeneous disease and the second most common cause of cancer-related death worldwide. Marked developments in genomic technologies helped scientists to understand the heterogeneity of HCC and identified multiple HCC-related molecular subclasses. An integrative analysis of genomic datasets including 196 patients from The Cancer Genome Atlas (TCGA) group has recently reported a new HCC subclass, which contains three subgroups (iCluster1, iCluster2, and iCluster3). However, the transcriptional molecular characteristics underlying the iClusters have not been thoroughly investigated. Herein, we identified a more aggressive subset of HCC patients in the iCluster1, and re-clustered the TCGA samples into novel HCC subclasses referred to as aggressive (Ag), moderate-aggressive (M-Ag), and less-aggressive (L-Ag) subclasses. The Ag subclass had a greater predictive power than the TCGA iCluster1, and a higher level of alpha fetoprotein, microscopic vascular invasion, immune infiltration, isocitrate dehydrogenase 1/2 mutation status, and a worse survival than M-Ag and L-Ag subclasses. Global transcriptomic analysis showed that activation of hedgehog signaling in the Ag subclass may play key roles in tumor development of aggressive HCC. GLI1, a key transcriptional regulator of hedgehog signaling upregulated in the Ag subclass, was correlated with poor prognosis of HCC, and may be a potential prognostic biomarker and therapeutic target for Ag subclass HCC patients.

Screening and identification of hub genes in pancreatic cancer by integrated bioinformatics analysis

Pancreatic cancer (Pa) is a malignant tumor of the digestive tract with high degree of malignancy, this study aimed to obtain the hub genes in the tumorigenesis of Pa. Microarray datasets GSE15471, GSE16515, and GSE62452 were downloaded from Gene Expression Omnibus (GEO) database, GEO2R was conducted to screen the differentially expressed genes (DEGs), and functional enrichment analyses were carried out by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction (PPI) network was constructed with the Search Tool for the Retrieval of Interacting Genes (STRING), and the hub genes were identified by Cytoscape. Totally 205 DEGs were identified, consisting of 51 downregulated genes and 154 upregulated genes enriched in Gene Ontology terms including extracellular matrix (ECM) organization, collagen binding, cell adhesion, and pathways associated with ECM-receptor interaction, focal adhesion, and protein digestion. Two modules in the PPI were chosen and biological process analyses showed that the module genes were mainly enriched in ECM and cell adhesion. Twenty-four hub genes were confirmed, the survival analyses from the cBioPortal online platform revealed that topoisomerase (DNA) II α (TOP2A), periostin (POSTN), plasminogen activator, urokinase (PLAU), and versican (VCAN) may be involved in the carcinogenesis and progression of Pa, and the receiver-operating characteristic curves indicated their diagnostic value for Pa. Among them, TOP2A, POSTN, and PLAU have been previously reported as biomarkers for Pa, and far too little attention has been paid to VCAN. Analysis from R2 online platform showed that Pa patients with high VCAN expression were more sensitive to gemcitabine than those with low level, suggesting that VCAN may be an indicator to guide the use of the chemotherapeutic drug. In vitro experiments also showed that the sensitivity of the VCAN siRNA group to gemcitabine was lower than that of the control group. In conclusion, this study discerned hub genes and pathways related to the development of Pa, and VCAN was identified as a novel biomarker for the diagnose and therapy of Pa.