High-throughput assessment of the antibody profile in ovarian cancer ascitic fluids

Cationic liposomes overcome neutralizing antibodies and enhance reovirus efficacy in ovarian cancer

Reovirus (Reo) has shown promising potential in specifically killing tumor cells, and offering new possibilities for ovarian cancer (OC) treatment. However, neutralizing antibodies in the ascites from OC patients greatly limit the further application of Reo. In this study, we employed cationic liposomes (Lipo) to deliver Reo, significantly enhancing its ability to enter OC cells and its effectiveness in killing these cells under ascitic conditions. Pre-treatment with the MβCD inhibitor notably decreased Reo-mediated tumor cell death, indicating that Lipo primarily enables Reo's cellular uptake through caveolin-mediated endocytosis. Our results demonstrate that Lipo effectively facilitates the entry of Reo into the cytoplasm and triggers cell apoptosis. The above findings provide a new strategy to overcome the obstacle of neutralizing antibodies in the clinical application of Reo.

Construction and Validation of a Prognostic Model Based on Mitochondrial Genes in Prostate Cancer

This study attempted to build a prostate cancer (PC) prognostic risk model with mitochondrial feature genes. PC-related MTGs were screened for Cox regression analyses, followed by establishing a prognostic model. Model validity was analyzed via survival analysis and receiver operating characteristic (ROC) curves, and model accuracy was validated in the GEO dataset. Combining risk score with clinical factors, the independence of the risk score was verified by using Cox analysis, followed by generating a nomogram. The Gleason score, microsatellite instability (MSI), immune microenvironment, and tumor mutation burden were analyzed in two risk groups. Finally, the prognostic feature genes were verified through a q-PCR test. Ten PC-associated MTGs were screened, and a prognostic model was built. Survival analysis and ROC curves illustrated that the model was a good predictor for the risk of PC. Cox regression analysis revealed that risk score acted as an independent prognostic factor. The Gleason score and MSI in the high-risk group were substantially higher than in the low-risk group. Levels of ESTIMATE Score, Immune Score, Stromal Score, immune cells, immune function, immune checkpoint, and immunopheno score of partial immune checkpoints in the high-risk group were significantly lower than in the low-risk group. Genes with the highest mutation frequencies in the two groups were SPOP, TTN, and TP53. The q-PCR results of the feature genes were consistent with the gene expression results in the database. The 10-gene model based on MTGs could accurately predict the prognosis of PC patients and their responses to immunotherapy.

Advancements in ovarian cancer immunodiagnostics and therapeutics via phage display technology

Ovarian cancer, ranking as the seventh most prevalent malignancy among women globally, faces significant challenges in diagnosis and therapeutic intervention. The difficulties in early detection are amplified by the limitations and inefficacies inherent in current screening methodologies, highlighting a pressing need for more efficacious diagnostic and treatment strategies. Phage display technology emerges as a pivotal innovation in this context, utilizing extensive phage-peptide libraries to identify ligands with specificity for cancer cell markers, thus enabling precision-targeted therapeutic strategies. This technology promises a paradigm shift in ovarian cancer management, concentrating on targeted drug delivery systems to improve treatment accuracy and efficacy while minimizing adverse effects. Through a meticulous review, this paper evaluates the revolutionary potential of phage display in enhancing ovarian cancer therapy, representing a significant advancement in combating this challenging disease. Phage display technology is heralded as an essential instrument for developing effective immunodiagnostic and therapeutic approaches in ovarian cancer, facilitating early detection, precision-targeted medication, and the implementation of customized treatment plans.

Prediction of Chemoresistance-How Preclinical Data Could Help to Modify Therapeutic Strategy in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is one of the most lethal tumors generally and the most fatal cancer of the female genital tract. The approved standard therapy consists of surgical cytoreduction and platinum/taxane-based chemotherapy, and of targeted therapy in selected patients. The main therapeutic problem is chemoresistance of recurrent and metastatic HGSOC tumors which results in low survival in the group of FIGO III/IV. Therefore, the prediction and monitoring of chemoresistance seems to be of utmost importance for the improvement of HGSOC management. This type of cancer has genetic heterogeneity with several subtypes being characterized by diverse gene signatures and disturbed peculiar epigenetic regulation. HGSOC develops and metastasizes preferentially in the specific intraperitoneal environment composed mainly of fibroblasts, adipocytes, and immune cells. Different HGSOC subtypes could be sensitive to distinct sets of drugs. Moreover, primary, metastatic, and recurrent tumors are characterized by an individual biology, and thus diverse drug responsibility. Without a precise identification of the tumor and its microenvironment, effective treatment seems to be elusive. This paper reviews tumor-derived genomic, mutational, cellular, and epigenetic biomarkers of HGSOC drug resistance, as well as tumor microenvironment-derived biomarkers of chemoresistance, and discusses their possible use in the novel complex approach to ovarian cancer therapy and monitoring.

The Evolving Landscape of B Cells in Cancer Metastasis

Metastasis is the leading cause of cancer mortality. Functional and clinical studies have documented diverse B-cell and antibody responses in cancer metastasis. The presence of B cells in tumor microenvironments and metastatic sites has been associated with diverse effects that can promote or inhibit metastasis. Specifically, B cells can contribute to the spread of cancer cells by enhancing tumor cell motility, invasion, angiogenesis, lymphangiogenesis, and extracellular matrix remodeling. Moreover, they can promote metastatic colonization by triggering pathogenic immunoglobulin responses and recruiting immune suppressive cells. Contrastingly, B cells can also exhibit antimetastatic effects. For example, they aid in enhanced antigen presentation, which helps activate immune responses against cancer cells. In addition, B cells play a crucial role in preventing the dissemination of metastatic cells from the primary tumor and secrete antibodies that can aid in tumor recognition. Here, we review the complex roles of B cells in metastasis, delineating the heterogeneity of B-cell activity and subtypes by metastatic site, antibody class, antigen (if known), and molecular phenotype. These important attributes of B cells emphasize the need for a deeper understanding and characterization of B-cell phenotypes to define their effects in metastasis.

Regulatory mechanisms of the cAMP-responsive element binding protein 3 (CREB3) family in cancers

The CREB3 family of proteins, encompassing CREB3 and its four homologs (CREB3L1, CREB3L2, CREB3L3, and CREB3L4), exerts pivotal control over cellular protein metabolism in response to unfolded protein reactions. Under conditions of endoplasmic reticulum stress, activation of the CREB3 family occurs through regulated intramembrane proteolysis within the endoplasmic reticulum membrane. Perturbations in the function and expression of the CREB3 family have been closely associated with the development of diverse diseases, with a particular emphasis on cancer. Recent investigations have shed light on the indispensable role played by CREB3 family members in modulating the onset and progression of various human cancers. This comprehensive review endeavors to provide an in-depth examination of the involvement of CREB3 family members in distinct human cancer types, accentuating their significance in the pathogenesis of cancer and the manifestation of malignant phenotypes.

EXOSC10 is a novel hepatocellular carcinoma prognostic biomarker: a comprehensive bioinformatics analysis and experiment verification

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor. There are few studies on EXOSC10 (exosome component 10) in HCC; however, the importance of EXOSC10 for HCC remains unclear.

Methods

In the study, the prognosis value of EXOSC10 and the immune correlation were explored by bioinformatics. The expression of EXOSC10 was verified by tissue samples from clinical patients and in vitro experiment (liver cancer cell lines HepG2, MHCC97H and Huh-7; normal human liver cell line LO2). Immunohistochemistry (IHC) was used to detect EXOSC10 protein expression in clinical tissue from HCC. Huh-7 cells with siEXOSC10 were constructed using lipofectamine 3000. Cell counting kit 8 (CCK-8) and colony formation were used to test cell proliferation. The wound healing and transwell were used to analyze the cell migration capacity. Mitochondrial membrane potential, Hoechst 33342 dye, and flow cytometer were used to detect the change in cell apoptosis, respectively. Differential expression genes (DEGs) analysis and gene set enrichment analysis (GSEA) were used to investigate the potential mechanism of EXOSC10 and were verified by western blotting.

Results

EXOSC10 was highly expressed in tissues from patients with HCC and was an independent prognostic factor for overall survival (OS) in HCC. Increased expression of EXOSC10 was significantly related to histological grade, T stage, and pathological stage. Multivariate analysis indicated that the high expression level of EXOSC10 was correlated with poor overall survival (OS) in HCC. GO and GSEA analysis showed enrichment of the cell cycle and p53-related signaling pathway. Immune analysis showed that EXOSC10 expression was a significant positive correlation with immune infiltration in HCC. In vitro experiments, cell proliferation and migration were inhibited by the elimination of EXOSC10. Furthermore, the elimination of EXOSC10 induced cell apoptosis, suppressed PARP, N-cadherin and Bcl-2 protein expression levels, while increasing Bax, p21, p53, p-p53, and E-cadherin protein expression levels.

Conclusions

EXOSC10 had a predictive value for the prognosis of HCC and may regulate the progression of HCC through the p53-related signaling pathway.

Identification and prioritization of tumour-associated antigens for immunotherapeutic and diagnostic capacity in epithelial ovarian cancer: a systematic literature review

Epithelial ovarian cancer (EOC) is a prevalent carcinoma in the female population associated with poor prognostic outcomes, in part due to the late stage of the disease at diagnosis. Aiming to identify tumour-associated antigens (TAAs) with the potential to facilitate earlier detection and targeted therapy of EOC, five scientific literature repositories were systemically searched for primary literature sources reporting the expression of a TAA in the tissue or serum of adult females diagnosed with EOC and healthy women. We identified 7120 articles of which 32 met our inclusion criteria and passed the bias-quality assessment. Subsequently, data were collated on 29 TAAs whose expression had been analysed in 2181 patients and 589 healthy individuals. Reports of CA125 and EpCAM expression were numerous while tissue expression data were available for 28 TAAs. Data were segregated into three meta-cohorts for statistical scrutiny and their capacity for diagnostic and treatment targeting was assessed. We showed that CA-125 was expressed homogenously in EOC patients while EpCAM was expressed heterogeneously. CA-125 was the most promising TAA target for both diagnosis and treatment, gaining a priority score of 12 (/12) while EpCAM gained a priority score of seven. Tissue expression of EOC TAAs was homogenous; 90% of the EOC population express any identified TAA while just 20% of healthy individuals will be positive for the same TAA. We suggest TAA profiling should be a fundamental aspect of EOC diagnosis, sitting alongside the FIGO framework, promoting reduced mortality and directing the development of TAA-targeted therapeutics.

RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment

Ovarian cancer (OC), an important cause of cancer-related death in women worldwide, is one of the most malignant cancers and is characterized by a poor prognosis. RNA-binding proteins (RBPs), a class of endogenous proteins that can bind to mRNAs and modify (or even determine) the amount of protein they can generate, have attracted great attention in the context of various diseases, especially cancers. Compelling studies have suggested that RBPs are aberrantly expressed in different cancer tissues and cell types, including OC tissues and cells. More specifically, RBPs can regulate proliferation, apoptosis, invasion, metastasis, tumorigenesis and chemosensitivity and serve as potential therapeutic targets in OC. Herein, we summarize what is currently known about the biogenesis, molecular functions and potential roles of human RBPs in OC and their prospects for application in the clinical treatment of OC.

Clinical Significance of Screening Differential Metabolites in Ovarian Cancer Tissue and Ascites by LC/MS

Tumor cells not only show a vigorous metabolic state, but also reflect the disease progression and prognosis from their metabolites. To judge the progress and prognosis of ovarian cancer is generally based on the formation of ascites, or whether there is ascites recurrence during chemotherapy after ovarian cancer surgery. To explore the relationship between the production of ascites and ovarian cancer tissue, metabolomics was used to screen differential metabolites in this study. The significant markers leading to ascites formation and chemoresistance were screened by analyzing their correlation with the formation of ascites in ovarian cancer and the clinical indicators of patients, and then provided a theoretical basis. The results revealed that nine differential metabolites were screened out from 37 ovarian cancer tissues and their ascites, among which seven differential metabolites were screened from 22 self-paired samples. Sebacic acid and 20-COOH-leukotriene E4 were negatively correlated with the high expression of serum CA125. Carnosine was positively correlated with the high expression of serum uric acid. Hexadecanoic acid was negatively correlated with the high expression of serum γ-GGT and HBDH. 20a,22b-Dihydroxycholesterol was positively correlated with serum alkaline phosphatase and γ-GGT. In the chemotherapy-sensitive and chemotherapy-resistant ovarian cancer tissues, the differential metabolite dihydrothymine was significantly reduced in the chemotherapy-resistant group. In the ascites supernatant of the drug-resistant group, the differential metabolites, 1,25-dihydroxyvitamins D3-26, 23-lactonel and hexadecanoic acid were also significantly reduced. The results indicated that the nine differential metabolites could reflect the prognosis and the extent of liver and kidney damage in patients with ovarian cancer. Three differential metabolites with low expression in the drug-resistant group were proposed as new markers of chemotherapy efficacy in ovarian cancer patients with ascites.

Unusual aggregation property of recombinantly expressed cancer-testis antigens in mammalian cells

Transient expression of human intracellular proteins in human embryonic kidney (HEK) 293 cells is a reliable system for obtaining soluble proteins with biologically active conformations. Contrary to conventional concepts, we found that recombinantly expressed intracellular cancer-testis antigens (CTAs) showed frequent aggregation in HEK293 cells. Although experimental subcellular localization of recombinant CTAs displayed proper cytosolic or nuclear localization, some proteins showed aggregated particles in the cell. This aggregative property was not observed in recombinant housekeeping proteins. No significant correlation was found between the aggregative and biophysical properties, such as hydrophobicity, contents of intrinsically disordered regions, and expression levels, of CTAs. These results can be explained in terms of structural instability of CTAs, which are specifically expressed in the testis and aberrantly expressed in cancer cells and function as a hub in the protein-protein network using intrinsically disordered regions. Hence, we speculate that recombinantly expressed CTAs failed to form this protein complex. Thus, unfolded CTAs formed aggregated particles in the cell.

Potential functional variants of KIAA genes are associated with breast cancer risk in a case control study

Background

KIAA genes identified in the Kazusa cDNA-sequencing project may play important roles in biological processes and are involved in carcinogenesis of many cancers. Genetic variants of KIAA genes are implicated in the abnormal expression of these genes and are linked to susceptibility of several human complex diseases.

Methods

The differentially expressed KIAA genes were screened and identified in The Cancer Genome Atlas (TCGA) database of breast cancer. A total of 48 variants located in the 28 KIAA genes were selected to investigate the associations between polymorphism and breast cancer in 1,032 cases and 1,063 cancer-free controls in a Chinese population.

Results

Two coding variants, which included a SNP rs2306369 in KIAA1109 and a SNP rs1205434 in KIAA1755, were identified to be associated with the incidences of breast cancer. Logistic regression analysis showed that the SNP rs2306369 G allele was associated with a decreased risk of breast cancer (additive model: OR =0.81, 95% CI: 0.66-0.99, P=0.038), whereas the SNP rs1205434 A allele was involved with a higher risk of breast cancer (additive model: OR =1.19, 95% CI: 1.02-1.38, P= 0.025). Further stratified analysis revealed that the SNP rs1205434 showed a significant difference for age at menarche strata (heterogeneity test P=0.009). Multiplicative interaction analysis indicated that there was positive multiplicative interaction between the SNP rs1205434 and menarche age (OR =1.09, 95% CI: 1.01-1.17, P=0.036). Additionally, expression quantitative trait loci analysis revealed that the SNP rs1205434 A allele could decrease the KIAA1755 expression in the Genotype-Tissue Expression (GTEx) database (P=0.002). The Kaplan-Meier plotter showed that breast cancer patients with high KIAA1755 expression have significantly better outcomes than those with low levels of expression (HR =0.84, 95% CI: 0.72-0.99, P=0.033).

Conclusions

The results indicate that the genetic variants (rs2306369 and rs1205434) in the coding region of KIAA1109 and KIAA1755 respectively may affect Chinese females' breast cancer susceptibility and act as potential predictive biomarkers for breast cancer.

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

Growing evidence suggest that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. A 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score and cluster models were effective at accurately distinguishing the overall survival of SOC. Analysis of genomic alterations were used to elaborate on the association between the 17-TFs related prognostic signature and genomic aberrations. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. The potential immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups. The results indicated that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients. In conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.

Anti-Cancer Auto-Antibodies: Roles, Applications and Open Issues

Auto-antibodies are classically associated with autoimmune diseases, where they are an integral part of diagnostic panels. However, recent evidence is accumulating on the presence of auto-antibodies against single or selected panels of auto-antigens in many types of cancer. Auto-antibodies might initially represent an epiphenomenon derived from the inflammatory environment induced by the tumor. However, their effect on tumor evolution can be crucial, as is discussed in this paper. It has been demonstrated that some of these auto-antibodies can be used for early detection and cancer staging, as well as for monitoring of cancer regression during treatment and follow up. Interestingly, certain auto-antibodies were found to promote cancer progression and metastasis, while others contribute to the body's defense against it. Moreover, auto-antibodies are of a polyclonal nature, which means that often several antibodies are involved in the response to a single tumor antigen. Dissection of these antibody specificities is now possible, allowing their identification at the genetic, structural, and epitope levels. In this review, we report the evidence available on the presence of auto-antibodies in the main cancer types and discuss some of the open issues that still need to be addressed by the research community.

Establishment and validation of an RNA binding protein-associated prognostic model for ovarian cancer

Background

Ovarian cancer (OC) is one of the most common gynecological malignant tumors worldwide, with high mortality and a poor prognosis. As the early symptoms of malignant ovarian tumors are not obvious, the cause of the disease is still unclear, and the patients’ postoperative quality of life of decreases. Therefore, early diagnosis is a problem requiring an urgent solution.

Methods

We obtained the gene expression profiles of ovarian cancer and normal samples from TCGA and GTEx databases for differential expression analysis. From existing literature reports, we acquired the RNA-binding protein (RBP) list for the human species. Utilizing the online tool Starbase, we analyzed the interaction relationship between RBPs and their target genes and selected the modules of RBP target genes through Cytoscape. Finally, univariate and multivariate Cox regression analyses were used to determine the prognostic RBP signature.

Results

We obtained 527 differentially expressed RBPs, which were involved in many important cellular events, such as RNA splicing, the cell cycle, and so on. We predicted several target genes of RBPs, constructed the interaction network of RBPs and their target genes, and obtained many modules from the Cytoscape analysis. Functional enrichment of RBP target genes also includes these important biological processes. Through Cox regression analysis, OC prognostic RBPs were identified and a 10-RBP model constructed. Further analysis showed that the model has high accuracy and sensitivity in predicting the 3/5-year survival rate.

Conclusions

Our study identified differentially expressed RBPs and their target genes in OC, and the results promote our understanding of the molecular mechanism of ovarian cancer. The current study could develop novel biomarkers for the diagnosis, treatment, and prognosis of OC and provide new ideas and prospects for future clinical research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00777-1.

Abnormal Expression of Mitochondrial Ribosomal Proteins and Their Encoding Genes with Cell Apoptosis and Diseases

Mammalian mitochondrial ribosomes translate 13 proteins encoded by mitochondrial genes, all of which play roles in the mitochondrial respiratory chain. After a long period of reconstruction, mitochondrial ribosomes are the most protein-rich ribosomes. Mitochondrial ribosomal proteins (MRPs) are encoded by nuclear genes, synthesized in the cytoplasm and then, transported to the mitochondria to be assembled into mitochondrial ribosomes. MRPs not only play a role in mitochondrial oxidative phosphorylation (OXPHOS). Moreover, they participate in the regulation of cell state as apoptosis inducing factors. Abnormal expressions of MRPs will lead to mitochondrial metabolism disorder, cell dysfunction, etc. Many researches have demonstrated the abnormal expression of MRPs in various tumors. This paper reviews the basic structure of mitochondrial ribosome, focuses on the structure and function of MRPs, and their relationships with cell apoptosis and diseases. It provides a reference for the study of the function of MRPs and the disease diagnosis and treatment.

InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data

High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the 'interactome sequencing' approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains ('domainome') or epitopes ('epitome') from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/.

Defining the Helicobacter pylori Disease-Specific Antigenic Repertoire

The analysis of the interaction between Helicobacter pylori (HP) and the host in vivo is an extremely informative way to enlighten the molecular mechanisms behind the persistency/latency of the bacterium as well as in the progression of the infection. An important source of information is represented by circulating antibodies targeting the bacteria that define a specific "disease signature" with prospective diagnostic implications. The diagnosis of some of the HP induced diseases such as gastric cancer (GC), MALT lymphoma (MALT), and autoimmune gastritis (AIG) is not easy because patients do not show symptoms of illness in early-onset stages, at the same time they progress rapidly. The possibility of identifying markers able to provide an early diagnosis would be extremely beneficial since a late diagnosis results in a delay in undergoing active therapy and reduces the survival rate of patients. With the aim to identify the HP antigens recognized during the host immune-response to the infection and possibly disease progression, we applied a discovery-driven approach, that combines "phage display" and deep sequencing. The procedure is based on the selection of ORF phage libraries, specifically generated from the pathogen's genome, with sera antibodies from patients with different HP-related diseases. To this end two phage display libraries have been constructed starting from genomic DNA from the reference HP 26695 and the pathogenic HP B128 strains; libraries were filtered for ORFs by using an ORF selection vector developed by our group (Di Niro et al., 2005; Soluri et al., 2018), selected with antibodies from patients affected by GC, MALT, and AIG and putative HP antigens/epitopes were identified after Sequencing and ranking. The results show that individual selection significantly reduced the library diversity and comparison of individual ranks for each condition allowed us to highlight a pattern of putative antigens specific for the different pathological outcomes or common for all of them. Within the putative antigens enriched after selection, we have validated protein CagY/Cag7 by ELISA assay as a marker of HP infection and progression. Overall, we have defined HP antigenic repertoire and identified a panel of putative specific antigens/epitopes for three different HP infection pathological outcomes that could be validated in the next future.

The untapped potential of ascites in ovarian cancer research and treatment

The build-up of fluid in the peritoneal cavity-ascites-is a hallmark of ovarian cancer, the most lethal of all gynaecological malignancies. This remarkable fluid, which contains a variety of cellular and acellular components, is known to contribute to patient morbidity and mortality by facilitating metastasis and contributing to chemoresistance, but remains largely under-researched. In this review, we will critically analyse the evidence associating ascites with metastasis and chemoresistance in ovarian cancer and provide an update on research in the field. We will argue the case for ascites as a unique and accessible substrate for tracking tumour progression and for translational research that will enhance our understanding of this cancer and lead to improvements in patient outcomes.

Proteome Profiling Uncovers an Autoimmune Response Signature That Reflects Ovarian Cancer Pathogenesis

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53–MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

WNT signaling inducing activity in ascites predicts poor outcome in ovarian cancer

High grade serous carcinoma of the ovary, fallopian tube, and peritoneum (HGSC) is the deadliest gynecological disease which results in a five-year survival rate of 30% or less. HGSC is characterized by the early and rapid development of metastases accompanied by a high frequency of ascites i.e. the pathological accumulation of fluid in peritoneum. Ascites constitute a complex tumor microenvironment and contribute to disease progression by largely unknown mechanisms. Methods: Malignant ascites obtained from HGSC patients who had undergone cytoreductive surgery were tested for their ability to induce WNT signaling in the Kuramochi cell line, a novel and clinically relevant in vitro model of HGSC. Next, cancer spheroids (the main form of metastatic cancer cells in ascites) were evaluated with respect to WNT signaling. Kuramochi cells were used to determine the role of individual WNT signaling branches in the adoption of metastatic stem cell-like behavior by HGSC cells. Furthermore, we analyzed genomic and transcriptomic data on WNT/Planar Cell Polarity (PCP) components retrieved from public cancer databases and corroborated with primary patient samples and validated antibodies on the protein level. Results: We have shown that ascites are capable of inducing WNT signaling in primary HGSC cells and HGSC cell line, Kuramochi. Importantly, patients whose ascites cannot activate WNT pathway present with less aggressive disease and a considerably better outcome including overall survival (OS). Functionally, the activation of non-canonical WNT/PCP signaling by WNT5A (and not canonical WNT/β-catenin signaling by WNT3A) promoted the metastatic stem-cell (metSC) like behavior (i.e. self-renewal, migration, and invasion) of HGSC cells. The pharmacological inhibition of casein kinase 1 (CK1) as well as genetic ablation (dishevelled 3 knock out) of the pathway blocked the WNT5A-induced effect. Additionally, WNT/PCP pathway components were differentially expressed between healthy and tumor tissue as well as between the primary tumor and metastases. Additionally, ascites which activated WNT/PCP signaling contained the typical WNT/PCP ligand WNT5A and interestingly, patients with high levels of WNT5A protein in their ascites exhibited poor progression-free survival (PFS) and OS in comparison to patients with low or undetectable ascitic WNT5A. Together, our results suggest the existence of a positive feedback loop between tumor cells producing WNT ligands and ascites that distribute WNT activity to cancer cells in the peritoneum, in order to promote their pro-metastatic features and drive HGSC progression. Conclusions: Our results highlight the role of WNT/PCP signaling in ovarian cancerogenesis, indicate a possible therapeutic potential of CK1 inhibitors for HGSC, and strongly suggest that the detection of WNT pathway inducing activity ascites (or WNT5A levels in ascites as a surrogate marker) could be a novel prognostic tool for HGSC patients.