Derivation and characterization of matched cell lines from primary and recurrent serous ovarian cancer

Oncolytic vesicular stomatitis virus alone or in combination with JAK inhibitors is effective against ovarian cancer

Therapy-resistant ovarian cancers have a poor prognosis and novel effective treatment options are urgently needed. In this study, we evaluated the therapeutic efficacy of the oncolytic vesicular stomatitis virus (VSV) against a panel of patient-derived ovarian cancer cell lines of all epithelial subtypes. Notably, we found that most of the cell lines were sensitive to VSV virotherapy. With the objective of improving treatment efficacy for the oncolytic virus-resistant cell lines, we tested various combinations with ovarian cancer standard of care drugs: olaparib, carboplatin, paclitaxel, doxorubicin, cyclophosphamide, and gemcitabine. While none of these combinations revealed to be beneficial, further experiments demonstrated that the antiviral interferon pathway was functional in VSV-resistant cell lines. Given that interferons signal through Janus kinase (JAK)-STAT to mediate their antiviral function, we tested combinations of oncolytic VSV with clinically relevant JAK inhibitors. Our results show that combining VSV with various JAK inhibitors, including ruxolitinib, enhances VSV virotherapy and treatment efficacy. Altogether, we show that VSV, either as a stand-alone treatment or in combination with JAK inhibitors provides an effective therapeutic option for ovarian cancer patients.

The journey from bench to bedside-it takes a science village

I was fortunate enough to start my career at what was the dawn of modern-day molecular biology and to apply it to an important health problem. While my early work focused on fundamental science, the desire to understand human disease better and to find practical applications for research discoveries resulted, over the following decades, in creating a stream of translational research directed specifically toward epithelial cancers. This could only have been possible through multiple collaborations. This type of team science would eventually become a hallmark of my career. With the development of higher throughput molecular techniques, the pace of research and discovery has quickened, and the concept of personalized medicine based on genomics is now coming to fruition. I hope my legacy will not just reflect my published works, but will also include the impact I have had on the development of the next generation of scientists and clinician scientists who inspired me with their dedication, knowledge, and enthusiasm.

Plasma Gelsolin Inhibits Natural Killer Cell Function and Confers Chemoresistance in Epithelial Ovarian Cancer

Plasma gelsolin (pGSN) overexpression in ovarian cancer (OVCA) disarms immune function, contributing to chemoresistance. The aim of this study was to investigate the immunoregulatory effects of pGSN expression on natural killer (NK) cell function in OVCA. OVCA tissues from primary surgeries underwent immunofluorescent staining of pGSN and the activated NK cell marker natural cytotoxicity triggering receptor 1 to analyze the prognostic impact of pGSN expression and activated NK cell infiltration. The immunoregulatory effects of pGSN on NK cells were assessed using apoptosis assay, cytokine secretion, immune checkpoint-receptor expression, and phosphorylation of STAT3. In OVCA tissue analyses, activated NK cell infiltration provided survival advantages to patients. However, high pGSN expression attenuated the survival benefits of activated NK cell infiltration. In the in vitro experiment, pGSN in OVCA cells induced NK cell death through cell-to-cell contact. pGSN increased T-cell immunoglobulin and mucin-domain-containing-3 expression (TIM-3) on activated NK cells. Further, it decreased interferon-γ production in activated TIM-3+ NK cells, attenuating their anti-tumor effects. Thus, increased pGSN expression suppresses the anti-tumor functions of NK cells. The study provides insights into why immunotherapy is rarely effective in patients with OVCA and suggests novel treatment strategies.

Joint inference of clonal structure using single-cell genome and transcriptome sequencing data

Latest advancements in the high-throughput single-cell genome (scDNA) and transcriptome (scRNA) sequencing technologies enabled cell-resolved investigation of tissue clones. However, it remains challenging to cluster and couple single cells for heterogeneous scRNA and scDNA data generated from the same specimen. In this study, we present a computational framework called CCNMF, which employs a novel Coupled-Clone Non-negative Matrix Factorization technique to jointly infer clonal structure for matched scDNA and scRNA data. CCNMF couples multi-omics single cells by linking copy number and gene expression profiles through their general concordance. It successfully resolved the underlying coexisting clones with high correlations between the clonal genome and transcriptome from the same specimen. We validated that CCNMF can achieve high accuracy and robustness using both simulated benchmarks and real-world applications, including an ovarian cancer cell lines mixture, a gastric cancer cell line, and a primary gastric cancer. In summary, CCNMF provides a powerful tool for integrating multi-omics single-cell data, enabling simultaneous resolution of genomic and transcriptomic clonal architecture. This computational framework facilitates the understanding of how cellular gene expression changes in conjunction with clonal genome alternations, shedding light on the cellular genomic difference of subclones that contributes to tumor evolution.

The regulation of plasma gelsolin by DNA methylation in ovarian cancer chemo-resistance

BACKGROUND

Ovarian cancer (OVCA) is the most lethal gynecologic cancer and chemoresistance remains a major hurdle to successful therapy and survival of OVCA patients. Plasma gelsolin (pGSN) is highly expressed in chemoresistant OVCA compared with their chemosensitive counterparts, although the mechanism underlying the differential expression is not known. Also, its overexpression significantly correlates with shortened survival of OVCA patients. In this study, we investigated the methylation role of Ten eleven translocation isoform-1 (TET1) in the regulation of differential pGSN expression and chemosensitivity in OVCA cells.

METHODS

Chemosensitive and resistant OVCA cell lines of different histological subtypes were used in this study to measure pGSN and TET1 mRNA abundance (qPCR) as well as protein contents (Western blotting). To investigate the role of DNA methylation specifically in pGSN regulation and pGSN-induced chemoresistance, DNMTs and TETs were pharmacologically inhibited in sensitive and resistant OVCA cells using specific inhibitors. DNA methylation was quantified using EpiTYPER MassARRAY system. Gain-and-loss-of-function assays were used to investigate the relationship between TET1 and pGSN in OVCA chemoresponsiveness.

RESULTS

We observed differential protein and mRNA expressions of pGSN and TET1 between sensitive and resistant OVCA cells and cisplatin reduced their expression in sensitive but not in resistant cells. We observed hypomethylation at pGSN promoter upstream region in resistant cells compared to sensitive cells. Pharmacological inhibition of DNMTs increased pGSN protein levels in sensitive OVCA cells and decreased their responsiveness to cisplatin, however we did not observe any difference in methylation level at pGSN promoter region. TETs inhibition resulted in hypermethylation at multiple CpG sites and decreased pGSN protein level in resistant OVCA cells which was also associated with enhanced response to cisplatin, findings that suggested the methylation role of TETs in the regulation of pGSN expression in OVCA cells. Further, we found that TET1 is inversely related to pGSN but positively related to chemoresponsiveness of OVCA cells.

CONCLUSION

Our findings broaden our knowledge about the epigenetic regulation of pGSN in OVCA chemoresistance and reveal a novel potential target to re-sensitize resistant OVCA cells. This may provide a future therapeutic strategy to improve the overall OVCA patient survival.

High-grade serous ovarian carcinoma organoids as models of chromosomal instability

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

The Application of an Extracellular Vesicle-Based Biosensor in Early Diagnosis and Prediction of Chemoresponsiveness in Ovarian Cancer

BACKGROUND

Ovarian cancer (OVCA) is the most fatal gynecological cancer with late diagnosis and plasma gelsolin (pGSN)-mediated chemoresistance representing the main obstacles to treatment success. Since there is no reliable approach to diagnosing patients at an early stage as well as predicting chemoresponsiveness, there is an urgent need to develop a diagnostic platform for such purposes. Small extracellular vesicles (sEVs) are attractive biomarkers given their potential accuracy for targeting tumor sites.

METHODS

We have developed a novel biosensor which utilizes cysteine-functionalized gold nanoparticles that simultaneously bind to cisplatin (CDDP) and plasma/cell-derived EVs, affording us the advantage of predicting OVCA chemoresponsiveness, and early diagnosis using surface-enhanced Raman spectroscopy.

RESULTS

We found that pGSN regulates cortactin (CTTN) content resulting in the formation of nuclear- and cytoplasmic-dense granules facilitating the secretion of sEVs carrying CDDP; a strategy used by resistant cells to survive CDDP action. The clinical utility of the biosensor was tested and subsequently revealed that the sEV/CA125 ratio outperformed CA125 and sEV individually in predicting early stage, chemoresistance, residual disease, tumor recurrence, and patient survival.

CONCLUSION

These findings highlight pGSN as a potential therapeutic target and provide a potential diagnostic platform to detect OVCA earlier and predict chemoresistance; an intervention that will positively impact patient-survival outcomes.

Insights into high-grade serous carcinoma pathobiology using three-dimensional culture model systems

Epithelial ovarian cancer (EOC) research has become more complex as researchers try to fully understand the metastatic process. Especially as we delve into the concept of tumour dormancy, where cells transition between proliferative and dormant states to survive during disease progression. Thus, the in vitro models used to conduct this research need to reflect this vast biological complexity. The innovation behind the many three-dimensional (3D) spheroid models has been refined to easily generate reproducible spheroids so that we may understand the various molecular signaling changes of cells during metastasis and determine therapeutic efficacy of treatments. This ingenuity was then used to develop the 3D ex vivo patient-derived organoid model, as well as multiple co-culture model systems for EOC research. Although, researchers need to continue to push the boundaries of these current models for in vitro and even in vivo work in the future. In this review, we describe the 3D models already in use, where these models can be developed further and how we can use these models to gain the most knowledge on EOC pathogenesis and discover new targeted therapies.

Inhibition of nicotinamide dinucleotide salvage pathway counters acquired and intrinsic poly(ADP-ribose) polymerase inhibitor resistance in high-grade serous ovarian cancer

Epithelial ovarian cancer is the most lethal gynecological malignancy, owing notably to its high rate of therapy-resistant recurrence in spite of good initial response to chemotherapy. Although poly(ADP-ribose) polymerase inhibitors (PARPi) have shown promise for ovarian cancer treatment, extended therapy usually leads to acquired PARPi resistance. Here we explored a novel therapeutic option to counter this phenomenon, combining PARPi and inhibitors of nicotinamide phosphoribosyltransferase (NAMPT). Cell-based models of acquired PARPi resistance were created through an in vitro selection procedure. Using resistant cells, xenograft tumors were grown in immunodeficient mice, while organoid models were generated from primary patient tumor samples. Intrinsically PARPi-resistant cell lines were also selected for analysis. Our results show that treatment with NAMPT inhibitors effectively sensitized all in vitro models to PARPi. Adding nicotinamide mononucleotide, the resulting NAMPT metabolite, abrogated the therapy-induced cell growth inhibition, demonstrating the specificity of the synergy. Treatment with olaparib (PARPi) and daporinad (NAMPT inhibitor) depleted intracellular NAD+ , induced double-strand DNA breaks, and promoted apoptosis as monitored by caspase-3 cleavage. The two drugs were also synergistic in mouse xenograft models and clinically relevant patient-derived organoids. Therefore, in the context of PARPi resistance, NAMPT inhibition could offer a promising new option for ovarian cancer patients.

Reconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics

Functional characterization of the cancer clones can shed light on the evolutionary mechanisms driving cancer's proliferation and relapse mechanisms. Single-cell RNA sequencing data provide grounds for understanding the functional state of cancer as a whole; however, much research remains to identify and reconstruct clonal relationships toward characterizing the changes in functions of individual clones. We present PhylEx that integrates bulk genomics data with co-occurrences of mutations from single-cell RNA sequencing data to reconstruct high-fidelity clonal trees. We evaluate PhylEx on synthetic and well-characterized high-grade serous ovarian cancer cell line datasets. PhylEx outperforms the state-of-the-art methods both when comparing capacity for clonal tree reconstruction and for identifying clones. We analyze high-grade serous ovarian cancer and breast cancer data to show that PhylEx exploits clonal expression profiles beyond what is possible with expression-based clustering methods and clear the way for accurate inference of clonal trees and robust phylo-phenotypic analysis of cancer.

Single-cell genomic variation induced by mutational processes in cancer

How cell-to-cell copy number alterations that underpin genomic instability1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer2, remains understudied. Here, by applying scaled single-cell whole-genome sequencing3 to wild-type, TP53-deficient and TP53-deficient;BRCA1-deficient or TP53-deficient;BRCA2-deficient mammary epithelial cells (13,818 genomes), and to primary triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSC) cells (22,057 genomes), we identify three distinct 'foreground' mutational patterns that are defined by cell-to-cell structural variation. Cell- and clone-specific high-level amplifications, parallel haplotype-specific copy number alterations and copy number segment length variation (serrate structural variations) had measurable phenotypic and evolutionary consequences. In TNBC and HGSC, clone-specific high-level amplifications in known oncogenes were highly prevalent in tumours bearing fold-back inversions, relative to tumours with homologous recombination deficiency, and were associated with increased clone-to-clone phenotypic variation. Parallel haplotype-specific alterations were also commonly observed, leading to phylogenetic evolutionary diversity and clone-specific mono-allelic expression. Serrate variants were increased in tumours with fold-back inversions and were highly correlated with increased genomic diversity of cellular populations. Together, our findings show that cell-to-cell structural variation contributes to the origins of phenotypic and evolutionary diversity in TNBC and HGSC, and provide insight into the genomic and mutational states of individual cancer cells.

The Development of a Three-Dimensional Platform for Patient-Derived Ovarian Cancer Tissue Models: A Systematic Literature Review

There is an unmet biomedical need for ex vivo tumour models that would predict drug responses and in turn help determine treatment regimens and potentially predict resistance before clinical studies. Research has shown that three dimensional models of ovarian cancer (OvCa) are more realistic than two dimensional in vitro systems as they are able to capture patient in vivo conditions in more accurate manner. The vast majority of studies aiming to recapitulate the ovarian tumour morphology, behaviors, and study chemotherapy responses have been using ovarian cancer cell lines. However, despite the advantages of utilising cancer cell lines to set up a platform, they are not as informative as systems applying patient derived cells, as cell lines are not able to recapitulate differences between each individual patient characteristics. In this review we discussed the most recent advances in the creation of 3D ovarian cancer models that have used patient derived material, the challenges to overcome and future applications.

Three-dimensional in vitro culture models in oncology research

Cancer is a multifactorial disease that is responsible for 10 million deaths per year. The intra- and inter-heterogeneity of malignant tumors make it difficult to develop single targeted approaches. Similarly, their diversity requires various models to investigate the mechanisms involved in cancer initiation, progression, drug resistance and recurrence. Of the in vitro cell-based models, monolayer adherent (also known as 2D culture) cell cultures have been used for the longest time. However, it appears that they are often less appropriate than the three-dimensional (3D) cell culture approach for mimicking the biological behavior of tumor cells, in particular the mechanisms leading to therapeutic escape and drug resistance. Multicellular tumor spheroids are widely used to study cancers in 3D, and can be generated by a multiplicity of techniques, such as liquid-based and scaffold-based 3D cultures, microfluidics and bioprinting. Organoids are more complex 3D models than multicellular tumor spheroids because they are generated from stem cells isolated from patients and are considered as powerful tools to reproduce the disease development in vitro. The present review provides an overview of the various 3D culture models that have been set up to study cancer development and drug response. The advantages of 3D models compared to 2D cell cultures, the limitations, and the fields of application of these models and their techniques of production are also discussed.

Targeting a Tumor-Specific Epitope on Podocalyxin Increases Survival in Human Tumor Preclinical Models

Podocalyxin (Podxl) is a CD34-related cell surface sialomucin that is normally highly expressed by adult vascular endothelia and kidney podocytes where it plays a key role in blocking adhesion. Importantly, it is also frequently upregulated on a wide array of human tumors and its expression often correlates with poor prognosis. We previously showed that, in xenograft studies, Podxl plays a key role in metastatic disease by making tumor initiating cells more mobile and invasive. Recently, we developed a novel antibody, PODO447, which shows exquisite specificity for a tumor-restricted glycoform of Podxl but does not react with Podxl expressed by normal adult tissue. Here we utilized an array of glycosylation defective cell lines to further define the PODO447 reactive epitope and reveal it as an O-linked core 1 glycan presented in the context of the Podxl peptide backbone. Further, we show that when coupled to monomethyl auristatin E (MMAE) toxic payload, PODO447 functions as a highly specific and effective antibody drug conjugate (ADC) in killing ovarian, pancreatic, glioblastoma and leukemia cell lines in vitro. Finally, we demonstrate PODO447-ADCs are highly effective in targeting human pancreatic and ovarian tumors in xenografted NSG and Nude mouse models. These data reveal PODO447-ADCs as exquisitely tumor-specific and highly efficacious immunotherapeutic reagents for the targeting of human tumors. Thus, PODO447 exhibits the appropriate characteristics for further development as a targeted clinical immunotherapy.

Plasma Gelsolin Confers Chemoresistance in Ovarian Cancer by Resetting the Relative Abundance and Function of Macrophage Subtypes

Simple Summary

Ovarian cancer is one of the deadliest female cancers with very poor survival, primarily due to late diagnosis, recurrence and chemoresistance. Although the over-expression of plasma gelsolin (pGSN) protects ovarian cancer cells from chemotherapy-induced death, its immunological role in the tumor microenvironment is less explored. Here, we demonstrate that pGSN over-expression downregulates the anti-tumor functions of M1 macrophages, an effect that contributes to chemoresistance and poor patient survival. This study demonstrates the novel inhibitory role of pGSN on tumor-infiltrated M1 macrophages and also offers new insights in maximizing the effectiveness of immunotherapy for ovarian cancer patients.

Abstract

Ovarian cancer (OVCA) is the most lethal gynaecological cancer with a 5-year survival rate less than 50%. Despite new therapeutic strategies, such as immune checkpoint blockers (ICBs), tumor recurrence and drug resistance remain key obstacles in achieving long-term therapeutic success. Therefore, there is an urgent need to understand the cellular mechanisms of immune dysregulation in chemoresistant OVCA in order to harness the host’s immune system to improve survival. The over-expression of plasma gelsolin (pGSN) mRNA is associated with a poorer prognosis in OVCA patients; however, its immuno-modulatory role has not been elucidated. In this study, for the first time, we report pGSN as an inhibitor of M1 macrophage anti-tumor functions in OVCA chemoresistance. Increased epithelial pGSN expression was associated with the loss of chemoresponsiveness and poor survival. While patients with increased M1 macrophage infiltration exhibited better survival due to nitric-oxide-induced ROS accumulation in OVCA cells, cohorts with poor survival had a higher infiltration of M2 macrophages. Interestingly, increased epithelial pGSN expression was significantly associated with the reduced survival benefits of infiltrated M1 macrophages, through apoptosis via increased caspase-3 activation and reduced production of iNOS and TNFα. Additionally, epithelial pGSN expression was an independent prognostic marker in predicting progression-free survival. These findings support our hypothesis that pGSN is a modulator of inflammation and confers chemoresistance in OVCA, in part by resetting the relative abundance and function of macrophage subtypes in the ovarian tumor microenvironment. Our findings raise the possibility that pGSN may be a potential therapeutic target for immune-mediated chemoresistance in OVCA.

Clone decomposition based on mutation signatures provides novel insights into mutational processes

Intra-tumor heterogeneity is a phenomenon in which mutation profiles differ from cell to cell within the same tumor and is observed in almost all tumors. Understanding intra-tumor heterogeneity is essential from the clinical perspective. Numerous methods have been developed to predict this phenomenon based on variant allele frequency. Among the methods, CloneSig models the variant allele frequency and mutation signatures simultaneously and provides an accurate clone decomposition. However, this method has limitations in terms of clone number selection and modeling. We propose SigTracer, a novel hierarchical Bayesian approach for analyzing intra-tumor heterogeneity based on mutation signatures to tackle these issues. We show that SigTracer predicts more reasonable clone decompositions than the existing methods against artificial data that mimic cancer genomes. We applied SigTracer to whole-genome sequences of blood cancer samples. The results were consistent with past findings that single base substitutions caused by a specific signature (previously reported as SBS9) related to the activation-induced cytidine deaminase intensively lie within immunoglobulin-coding regions for chronic lymphocytic leukemia samples. Furthermore, we showed that this signature mutates regions responsible for cell-cell adhesion. Accurate assignments of mutations to signatures by SigTracer can provide novel insights into signature origins and mutational processes.

NR1D1 regulation by Ran GTPase via miR4472 identifies an essential vulnerability linked to aneuploidy in ovarian cancer

While aneuploidy is a main enabling characteristic of cancers, it also creates specific vulnerabilities. Here we demonstrate that Ran inhibition targets epithelial ovarian cancer (EOC) survival through its characteristic aneuploidy. We show that induction of aneuploidy in rare diploid EOC cell lines or normal cells renders them highly dependent on Ran. We also establish an inverse correlation between Ran and the tumor suppressor NR1D1 and reveal the critical role of Ran/NR1D1 axis in aneuploidy-associated endogenous DNA damage repair. Mechanistically, we show that Ran, through the maturation of miR4472, destabilizes the mRNA of NR1D1 impacting several DNA repair pathways. We showed that NR1D1 interacts with both PARP1 and BRCA1 leading to the inhibition of DNA repair. Concordantly, loss of Ran was associated with NR1D1 induction, accumulation of DNA damages, and lethality of aneuploid EOC cells. Our findings suggest a synthetic lethal strategy targeting aneuploid cells based on their dependency to Ran.

Carboplatin response in preclinical models for ovarian cancer: comparison of 2D monolayers, spheroids, ex vivo tumors and in vivo models

Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer. Among the key challenges in developing effective therapeutics is the poor translation of preclinical models used in the drug discovery pipeline. This leaves drug attrition rates and costs at an unacceptably high level. Previous work has highlighted the discrepancies in therapeutic response between current in vitro and in vivo models. To address this, we conducted a comparison study to differentiate the carboplatin chemotherapy response across four different model systems including 2D monolayers, 3D spheroids, 3D ex vivo tumors and mouse xenograft models. We used six previously characterized EOC cell lines of varying chemosensitivity and performed viability assays for each model. In vivo results from the mouse model correlated with 2D response in 3/6 cell lines while they correlated with 3D spheroids and the ex vivo model in 4/6 and 5/5 cell lines, respectively. Our results emphasize the variability in therapeutic response across models and demonstrate that the carboplatin response in EOC cell lines cultured in a 3D ex vivo model correlates best with the in vivo response. These results highlight a more feasible, reliable, and cost-effective preclinical model with the highest translational potential for drug screening and prediction studies in EOC.

A Keratin 7 and E-Cadherin Signature Is Highly Predictive of Tubo-Ovarian High-Grade Serous Carcinoma Prognosis

During tubo-ovarian high-grade serous carcinoma (HGSC) progression, tumoral cells undergo phenotypic changes in their epithelial marker profiles, which are essential for dissemination processes. Here, we set out to determine whether standard epithelial markers can predict HGSC patient prognosis. Levels of E-CADH, KRT7, KRT18, KRT19 were quantified in 18 HGSC cell lines by Western blot and in a Discovery cohort tissue microarray (TMA) (n = 101 patients) using immunofluorescence. E-CADH and KRT7 levels were subsequently analyzed in the TMA of the Canadian Ovarian Experimental Unified Resource cohort (COEUR, n = 1158 patients) and in public datasets. Epithelial marker expression was highly variable in HGSC cell lines and tissues. In the Discovery cohort, high levels of KRT7 and KRT19 were associated with an unfavorable prognosis, whereas high E-CADH expression indicated a better outcome. Expression of KRT7 and E-CADH gave a robust combination to predict overall survival (OS, p = 0.004) and progression free survival (PFS, p = 5.5 × 10⁻⁴) by Kaplan–Meier analysis. In the COEUR cohort, the E-CADH-KRT7 signature was a strong independent prognostic biomarker (OS, HR = 1.6, p = 2.9 × 10⁻⁴; PFS, HR = 1.3, p = 0.008) and predicted a poor patient response to chemotherapy (p = 1.3 × 10⁻⁴). Our results identify a combination of two epithelial markers as highly significant indicators of HGSC patient prognosis and treatment response.

Candidate Markers of Olaparib Response from Genomic Data Analyses of Human Cancer Cell Lines

The benefit of PARP inhibitor olaparib in relapsed and advanced high-grade serous ovarian carcinoma (HGSOC) is well established especially in BRCA1/2 mutation carriers. Identification of additional biomarkers can help expand the population of patients most likely to benefit from olaparib treatment. To identify candidate markers of olaparib response we analyzed genomic and in vitro olaparib response data from two independent groups of cancer cell lines. Using pan-cancer cell lines (n = 896) from the Genomics of Drug Sensitivity in Cancer database, we applied linear regression methods to identify statistically significant gene predictors of olaparib response based on mRNA expression. We then analyzed whole exome sequencing and mRNA gene expression data from our collection of 18 HGSOC cell lines previously classified as sensitive, intermediate, or resistant based on in vitro olaparib response for mutations, copy number variation and differential expression of candidate olaparib response genes. We identify genes previously associated with olaparib response (SLFN11, ABCB1), and discover novel candidate olaparib sensitivity genes with known functions including interaction with PARP1 (PUM3, EEF1A1) and involvement in homologous recombination DNA repair (ELP4). Further investigations at experimental and clinical levels are required to validate novel candidates, and ultimately determine their efficacy as potential biomarkers of olaparib sensitivity.

Carboplatin sensitivity in epithelial ovarian cancer cell lines: The impact of model systems

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy in North America, underscoring the need for the development of new therapeutic strategies for the management of this disease. Although many drugs are pre-clinically tested every year, only a few are selected to be evaluated in clinical trials, and only a small number of these are successfully incorporated into standard care. Inaccuracies with the initial in vitro drug testing may be responsible for some of these failures. Drug testing is often performed using 2D monolayer cultures or 3D spheroid models. Here, we investigate the impact that these different in vitro models have on the carboplatin response of four EOC cell lines, and in particular how different 3D models (polydimethylsiloxane-based microfluidic chips and ultra low attachment plates) influence drug sensitivity within the same cell line. Our results show that carboplatin responses were observed in both the 3D spheroid models tested using apoptosis/cell death markers by flow cytometry. Contrary to previously reported observations, these were not associated with a significant decrease in spheroid size. For the majority of the EOC cell lines (3 out of 4) a similar carboplatin response was observed when comparing both spheroid methods. Interestingly, two cell lines classified as resistant to carboplatin in 2D cultures became sensitive in the 3D models, and one sensitive cell line in 2D culture showed resistance in 3D spheroids. Our results highlight the challenges of choosing the appropriate pre-clinical models for drug testing.

Establishment of Acquired Cisplatin Resistance in Ovarian Cancer Cell Lines Characterized by Enriched Metastatic Properties with Increased Twist Expression

Ovarian cancer (OC) is the most lethal of the gynecologic cancers, and platinum-based treatment is a part of the standard first-line chemotherapy regimen. However, rapid development of acquired cisplatin resistance remains the main cause of treatment failure, and the underlying mechanism of resistance in OC treatment remains poorly understood. Faced with this problem, our aim in this study was to generate cisplatin-resistant (CisR) OC cell models in vitro and investigate the role of epithelial–mesenchymal transition (EMT) transcription factor Twist on acquired cisplatin resistance in OC cell models. To achieve this aim, OC cell lines OV-90 and SKOV-3 were exposed to cisplatin using pulse dosing and stepwise dose escalation methods for a duration of eight months, and a total of four CisR sublines were generated, two for each cell line. The acquired cisplatin resistance was confirmed by determination of 50% inhibitory concentration (IC₅₀) and clonogenic survival assay. Furthermore, the CisR cells were studied to assess their respective characteristics of metastasis, EMT phenotype, DNA repair and endoplasmic reticulum stress-mediated cell death. We found the IC₅₀ of CisR cells to cisplatin was 3–5 times higher than parental cells. The expression of Twist and metastatic ability of CisR cells were significantly greater than those of sensitive cells. The CisR cells displayed an EMT phenotype with decreased epithelial cell marker E-cadherin and increased mesenchymal proteins N-cadherin and vimentin. We observed that CisR cells showed significantly higher expression of DNA repair proteins, X-ray repair cross-complementing protein 1 (XRCC1) and poly (ADP-ribose) polymerases 1 (PARP1), with significantly reduced endoplasmic reticulum (ER) stress-mediated cell death. Moreover, Twist knockdown reduced metastatic ability of CisR cells by suppressing EMT, DNA repair and inducing ER stress-induced cell death. In conclusion, we highlighted the utilization of an acquired cisplatin resistance model to identify the potential role of Twist as a therapeutic target to reverse acquired cisplatin resistance in OC.

Modeling the Diversity of Epithelial Ovarian Cancer through Ten Novel Well Characterized Cell Lines Covering Multiple Subtypes of the Disease

Cancer cell lines are amongst the most important pre-clinical models. In the context of epithelial ovarian cancer, a highly heterogeneous disease with diverse subtypes, it is paramount to study a wide panel of models in order to draw a representative picture of the disease. As this lethal gynaecological malignancy has seen little improvement in overall survival in the last decade, it is all the more pressing to support future research with robust and diverse study models. Here, we describe ten novel spontaneously immortalized patient-derived ovarian cancer cell lines, detailing their respective mutational profiles and gene/biomarker expression patterns, as well as their in vitro and in vivo growth characteristics. Eight of the cell lines were classified as high-grade serous, while two were determined to be of the rarer mucinous and clear cell subtypes, respectively. Each of the ten cell lines presents a panel of characteristics reflective of diverse clinically relevant phenomena, including chemotherapeutic resistance, metastatic potential, and subtype-associated mutations and gene/protein expression profiles. Importantly, four cell lines formed subcutaneous tumors in mice, a key characteristic for pre-clinical drug testing. Our work thus contributes significantly to the available models for the study of ovarian cancer, supplying additional tools to better understand this complex disease.

Plasma Gelsolin Inhibits CD8+ T-cell Function and Regulates Glutathione Production to Confer Chemoresistance in Ovarian Cancer

Although initial treatment of ovarian cancer is successful, tumors typically relapse and become resistant to treatment. Because of poor infiltration of effector T cells, patients are mostly unresponsive to immunotherapy. Plasma gelsolin (pGSN) is transported by exosomes (small extracellular vesicle, sEV) and plays a key role in ovarian cancer chemoresistance, yet little is known about its role in immunosurveillance. Here, we report the immunomodulatory roles of sEV-pGSN in ovarian cancer chemoresistance. In chemosensitive conditions, secretion of sEV-pGSN was low, allowing for optimal CD8⁺ T-cell function. This resulted in increased T-cell secretion of IFNγ, which reduced intracellular glutathione (GSH) production and sensitized chemosensitive cells to cis-diaminedichloroplatinum (CDDP)-induced apoptosis. In chemoresistant conditions, increased secretion of sEV-pGSN by ovarian cancer cells induced apoptosis in CD8⁺ T cells. IFNγ secretion was therefore reduced, resulting in high GSH production and resistance to CDDP-induced death in ovarian cancer cells. These findings support our hypothesis that sEV-pGSN attenuates immunosurveillance and regulates GSH biosynthesis, a phenomenon that contributes to chemoresistance in ovarian cancer. SIGNIFICANCE: These findings provide new insight into pGSN-mediated immune cell dysfunction in ovarian cancer chemoresistance and demonstrate how this dysfunction can be exploited to enhance immunotherapy.

In vitro cell culture of patient derived malignant pleural and peritoneal effusions for personalised drug screening

Background

Malignant serous effusion (MSE) denotes a manifestation of metastatic disease with typical high concentrations of both cancer and immune cells, making them an ideal resource for in vitro cytologic studies. Hence, the aim of the study was to investigate the features of 2D and 3D MSE culture systems as well as their feasibilities for in vitro drug screening.

Methods

Pleural and peritoneal effusions from 8 patients were collected and processed for 2D monolayer and 3D hanging drop cell culture into GravityPLUS™ plates. Representative markers for cell components, proliferation rate and tumour classification were investigated by immunohistochemistry, followed by absolute quantification using a digitalised image analysis approach. Further, we implemented another 3D cell culture model based on a low attachment method for in vitro drug sensitivity testing of carboplatin, pemetrexed and pembrolizumab for 5 patients.

Results

Monolayer cell culture was favourable for the growth of mesothelial cells, while hanging drop culture in GravityPLUS™ plates showed better ability for preserving cancer cells, inducing positive diagnostic markers expression and restraining the growth of mesothelial cells. For in vitro drug testing, MSE from five patients presented various drug sensitivities, and one case showed strong response to PD-1 checkpoint inhibition (pembrolizumab). For some patients, the application of combinatorial drugs had better therapeutic responses compared to monotherapy.

Conclusions

Digitalised quantification of data offers a better understanding of different MSE culture models. More importantly, the proposed platforms are practical and amenable for performing in vitro chemo-/immunotherapeutic drug testing by using routine cytologic MSE in a personalised manner. Next to cell blocks, our work demonstrates the prognostic and predictive value of cytologic effusion samples.

Cordyceps militarisExerts Antitumor Effect on Carboplatin-Resistant Ovarian Cancer via Activation of ATF3/TP53 Signaling In Vitro and In Vivo

This study aimed to investigate the effect of Cordyceps militaris extract on the proliferation and apoptosis of carboplatin- resistant SKOV-3 and determine the underlying mechanisms for overcoming carboplatin resistance in human ovarian cancer. We cultured the carboplatin-resistant SKOV-3 cells in vitro until the exponential growth phase and then treated with different concentrations of C. militaris for 24, 48, and 72 hours. We performed cell proliferation assay, cell morphological change assessment using transmission electron microscopy, apoptosis assay, and immunoblotting to measure the protein expression of caspase-3 and -8, poly (ADP-ribose) polymerase (PARP)-1, B-cell lymphoma (Bcl)-2, and activating transcription factor 3 (ATF3)/TP53 signaling-related proteins. As a result, C. militaris reduced the viability of carboplatin-resistant SKOV-3 and induced morphological disruptions in a dose- and time-dependent manner. The gene expression profiles indicated a reprogramming pattern of the previously known and unknown genes and transcription factors associated with the action of TCTN3 on carboplatin-resistant SKOV-3 cells. We also confirmed the C. militaris-induced activation of the ATF3/TP53 pathway. Immunoblotting indicated that cotreatment of C. militaris and carboplatin-mediated ATF3/TP53 upregulation induced apoptosis in the carboplatin-resistant SKOV-3 cells, which are involved in the serial activation of pro-apoptotic proteins, including Bcl-2, Bax, caspases, and PARP-1. Further, when the ATF3 and TP53 expression increased, the CHOP and PUMA expressions were upregulated. Consequently, the upregulated CHOP/PUMA expression activated the positive regulation of the apoptotic signaling pathway. In addition, it decreased the Bcl-2 expression, leading to marked ovarian cancer cells sensitive to carboplatin by enhancing apoptosis. We then corroborated these results using in vivo experiments. Taken together, C. militaris inhibits carboplatin-resistant SKOV-3 cell proliferation and induces apoptosis possibly through ATF3/TP53 signaling upregulation and CHOP/PUMA activation. Therefore, our findings provide new insights into the treatment of carboplatin-resistant ovarian cancer using C. militaris.

Avoidance of apoptotic death via a hyperploid salvage survival pathway after platinum treatment in high grade serous carcinoma cell line models

The alkylating agent platinum is first-line chemotherapy treatment for high-grade serous carcinomas (HGSC) of tubal-ovarian origin. Platinum compounds cause DNA damage and induce apoptotic cell death in the bulk tumor population. However, subpopulations of tumor cells may exhibit diverging behaviors from the bulk tumor due to an alternate stress response that diverts tumor cells from apoptotic death. In this study, we identified a salvage survival pathway in which G2-arrested tumor cells bypassed apoptosis and progressed through aberrant mitotic events to then emerge as a distinct subpopulation of viable large hyperploid cells but with uncertain long-term propagation potential. Platinum-induced large hyperploid cells were flow sorted and showed rare regrowth capacity as compared to their more proficiently regenerating non-hyperploid counterparts. However, detailed time-lapse microscopy provided direct evidence that these hyperploid cells were mitotically active and could divide successfully to produce viable daughter cells. The hyperploid survival response was observed across different cell lines and utilization of this survival pathway was dependent on the strength of the G2-M checkpoint. Conceivably, this salvage survival strategy may contribute to increased genomic diversity of the regenerating tumor cell line through a coupled hyperploidization and de-polyploidization process that may be relevant for drug resistance.

Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

Characteristics of in Vivo Model Systems for Ovarian Cancer Studies

An understanding of the molecular pathogenesis and heterogeneity of ovarian cancer holds promise for the development of early detection strategies and novel, efficient therapies. In this review, we discuss the advantages and limitations of animal models available for basic and preclinical studies. The fruit fly model is suitable mainly for basic research on cellular migration, invasiveness, adhesion, and the epithelial-to-mesenchymal transition. Higher-animal models allow to recapitulate the architecture and microenvironment of the tumor. We discuss a syngeneic mice model and the patient derived xenograft model (PDX), both useful for preclinical studies. Conditional knock-in and knock-out methodology allows to manipulate selected genes at a given time and in a certain tissue. Such models have built our knowledge about tumor-initiating genetic events and cell-of-origin of ovarian cancers; it has been shown that high-grade serous ovarian cancer may be initiated in both the ovarian surface and tubal epithelium. It is postulated that clawed frog models could be developed, enabling studies on tumor immunity and anticancer immune response. In laying hen, ovarian cancer develops spontaneously, which provides the opportunity to study the genetic, biochemical, and environmental risk factors, as well as tumor initiation, progression, and histological origin; this model can also be used for drug testing. The chick embryo chorioallantoic membrane is another attractive model and allows the study of drug response.

Exploiting interconnected synthetic lethal interactions between PARP inhibition and cancer cell reversible senescence

Senescence is a tumor suppression mechanism defined by stable proliferation arrest. Here we demonstrate that the known synthetic lethal interaction between poly(ADP-ribose) polymerase 1 inhibitors (PARPi) and DNA repair triggers p53-independent ovarian cancer cell senescence defined by senescence-associated phenotypic hallmarks including DNA-SCARS, inflammatory secretome, Bcl-XL-mediated apoptosis resistance, and proliferation restriction via Chk2 and p21 (CDKN1A). The concept of senescence as irreversible remains controversial and here we show that PARPi-senescent cells re-initiate proliferation upon drug withdrawal, potentially explaining the requirement for sustained PARPi therapy in the clinic. Importantly, PARPi-induced senescence renders ovarian and breast cancer cells transiently susceptible to second-phase synthetic lethal approaches targeting the senescence state using senolytic drugs. The combination of PARPi and a senolytic is effective in preclinical models of ovarian and breast cancer suggesting that coupling these synthetic lethalities provides a rational approach to their clinical use and may together be more effective in limiting resistance.

Exploiting interconnected synthetic lethal interactions between PARP inhibition and cancer cell reversible senescence

Senescence is a tumor suppression mechanism defined by stable proliferation arrest. Here we demonstrate that the known synthetic lethal interaction between poly(ADP-ribose) polymerase 1 inhibitors (PARPi) and DNA repair triggers p53-independent ovarian cancer cell senescence defined by senescence-associated phenotypic hallmarks including DNA-SCARS, inflammatory secretome, Bcl-XL-mediated apoptosis resistance, and proliferation restriction via Chk2 and p21 (CDKN1A). The concept of senescence as irreversible remains controversial and here we show that PARPi-senescent cells re-initiate proliferation upon drug withdrawal, potentially explaining the requirement for sustained PARPi therapy in the clinic. Importantly, PARPi-induced senescence renders ovarian and breast cancer cells transiently susceptible to second-phase synthetic lethal approaches targeting the senescence state using senolytic drugs. The combination of PARPi and a senolytic is effective in preclinical models of ovarian and breast cancer suggesting that coupling these synthetic lethalities provides a rational approach to their clinical use and may together be more effective in limiting resistance.

Exploiting interconnected synthetic lethal interactions between PARP inhibition and cancer cell reversible senescence

Senescence is a tumor suppression mechanism defined by stable proliferation arrest. Here we demonstrate that the known synthetic lethal interaction between poly(ADP-ribose) polymerase 1 inhibitors (PARPi) and DNA repair triggers p53-independent ovarian cancer cell senescence defined by senescence-associated phenotypic hallmarks including DNA-SCARS, inflammatory secretome, Bcl-XL-mediated apoptosis resistance, and proliferation restriction via Chk2 and p21 (CDKN1A). The concept of senescence as irreversible remains controversial and here we show that PARPi-senescent cells re-initiate proliferation upon drug withdrawal, potentially explaining the requirement for sustained PARPi therapy in the clinic. Importantly, PARPi-induced senescence renders ovarian and breast cancer cells transiently susceptible to second-phase synthetic lethal approaches targeting the senescence state using senolytic drugs. The combination of PARPi and a senolytic is effective in preclinical models of ovarian and breast cancer suggesting that coupling these synthetic lethalities provides a rational approach to their clinical use and may together be more effective in limiting resistance.

Patient-derived cell line models revealed therapeutic targets and molecular mechanisms underlying disease progression of high grade serous ovarian cancer

High grade serous ovarian cancer (HGSOC) is the most frequent type of ovarian cancer. Most patients have primary response to platinum-based chemotherapy but frequently relapse, which leads to patient death. A lack of well documented and characterized patient-derived HGSOC cell lines is so far a major barrier to define tumor specific therapeutic targets and to study the molecular mechanisms underlying disease progression. We established 34 patient-derived HGSOC cell lines and characterized them at cellular and molecular level. Particularly, we demonstrated that a cancer-testis antigen PRAME and Estrogen Receptor could serve as therapeutic targets. Notably, data from the cell lines did not demonstrate acquired resistance due to tumor recurrence that matched with clinical observations. Finally, we presented that all HGSOC had no or very low CDKN1A (p21) expression due to loss of wild-type TP53, suggesting that loss of cell cycle control is the determinant for tumorigenesis and progression. In conclusion, patient-derived cell lines reveal that PRAME is a potential tumor specific therapeutic target in HGSOC and counteracting the down-regulation of p21 caused by loss of wild-type TP53 might be the key to impede disease progression.

An organoid platform for ovarian cancer captures intra- and interpatient heterogeneity

Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing all main subtypes of OC. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and interpatient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug-screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug-sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

clonealign: statistical integration of independent single-cell RNA and DNA sequencing data from human cancers

Measuring gene expression of tumor clones at single-cell resolution links functional consequences to somatic alterations. Without scalable methods to simultaneously assay DNA and RNA from the same single cell, parallel single-cell DNA and RNA measurements from independent cell populations must be mapped for genome-transcriptome association. We present clonealign, which assigns gene expression states to cancer clones using single-cell RNA and DNA sequencing independently sampled from a heterogeneous population. We apply clonealign to triple-negative breast cancer patient-derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either sequencing method alone.

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Among a litany of malignancies affecting the female reproductive tract, that of the ovary is the most frequently fatal. Moreover, while the steady pace of scientific discovery has fuelled recent ameliorations in the outcomes of many other cancers, the rates of mortality for ovarian cancer have been stagnant since around 1980. Yet despite the grim outlook, progress is being made towards better understanding the fundamental biology of this disease and how its biology in turn influences clinical behaviour. It has long been evident that ovarian cancer is not a unitary disease but rather a multiplicity of distinct malignancies that share a common anatomical site upon presentation. Of these, the high-grade serous subtype predominates in the clinical setting and is responsible for a disproportionate share of the fatalities from all forms of ovarian cancer. This review aims to provide a detailed overview of the clinical-pathological features of ovarian cancer with a particular focus on the high-grade serous subtype. Along with a description of the relevant clinical aspects of this disease, including novel trends in treatment strategies, this text will inform the reader of recent updates to the scientific literature regarding the origin, aetiology and molecular-genetic basis of high-grade serous ovarian cancer (HGSOC).

Paraffin-embedding lithography and micro-dissected tissue micro-arrays: tools for biological and pharmacological analysis of ex vivo solid tumors

There is an urgent need and strong clinical and pharmaceutical interest in developing assays that allow for the direct testing of therapeutic agents on primary tissues. Current technologies fail to provide the required sample longevity, throughput, and integration with standard clinically proven assays to make the approach viable. Here we report a microfluidic micro-histological platform that enables ex vivo culture of a large array of prostate and ovarian cancer micro-dissected tissue (MDT) followed by direct on-chip fixation and paraffination, a process we term paraffin-embedding lithography (PEL). The result is a high density MDT-Micro Array (MDTMA) compatible with standard clinical histopathology that can be used to analyse ex vivo tumor response or resistance to therapeutic agents. The cellular morphology and tissue architecture are preserved in MDTs throughout the 15 day culture period. We also demonstrate how this methodology can be used to study molecular pathways involved in cancer by performing in-depth characterization of biological and pharmacological mechanisms such as p65 nuclear translocation via TNF stimuli, and to predict the treatment outcome in the clinic via MDT response to taxane-based therapies.

Feedback control of the CXCR7/CXCL11 chemokine axis by estrogen receptor α in ovarian cancer

Ovarian cancer (OC) is one of the most intractable diseases, exhibiting tremendous molecular heterogeneity and lacking reliable methods for screening, resulting in late diagnosis and widespread peritoneal dissemination. Menopausal estrogen replacement therapy is a well‐recognized risk factor for OC, but little is known about how estrogen might contribute to this disease at the cellular level. This study identifies chemokine receptor CXCR7/ACKR3 as an estrogen‐responsive gene, whose expression is markedly enhanced by estrogen through direct recruitment of ERα and transcriptional active histone modifications in OC cells. The gene encoding CXCR7 chemokine ligand I‐TAC/CXCL11 was also upregulated by estrogen, resulting in Ser‐118 phosphorylation, activation, and recruitment of estrogen receptor ERα at the CXCR7 promoter locus for positive feedback regulation. Both CXCR7 and CXCL11, but not CXCR3 (also recognized to interact with CXCL11), were found to be significantly increased in stromal sections of microdissected tumors and positively correlated in mesenchymal subtype of OC. Estrogenic induction of mesenchymal markers SNAI1, SNAI2, and CDH2 expression, with a consequent increase in cancer cell migration, was shown to depend on CXCR7, indicating a key role for CXCR7 in mediating estrogen upregulation of mesenchymal markers to induce invasion of OC cells. These findings identify a feed‐forward mechanism that sustains activation of the CXCR7/CXCL11 axis under ERα control to induce the epithelial–mesenchymal transition pathway and metastatic behavior of OC cells. Such interplay underlies the complex gene profile heterogeneity of OC that promotes changes in tumor microenvironment and metastatic acquisition.

Organotypic 3D Models of the Ovarian Cancer Tumor Microenvironment

Ovarian cancer progression involves multifaceted and variable tumor microenvironments (TMEs), from the in situ carcinoma in the fallopian tube or ovary to dissemination into the peritoneal cavity as single cells or spheroids and attachment to the mesothelial-lined surfaces of the omentum, bowel, and abdominal wall. The TME comprises the tumor vasculature and lymphatics (including endothelial cells and pericytes), in addition to mesothelial cells, fibroblasts, immune cells, adipocytes and extracellular matrix (ECM) proteins. When generating 3D models of the ovarian cancer TME, researchers must incorporate the most relevant stromal components depending on the TME in question (e.g., early or late disease). Such complexity cannot be captured by monolayer 2D culture systems. Moreover, immortalized stromal cell lines, such as mesothelial or fibroblast cell lines, do not always behave the same as primary cells whose response in functional assays may vary from donor to donor; 3D models with primary stromal cells may have more physiological relevance than those using stromal cell lines. In the current review, we discuss the latest developments in organotypic 3D models of the ovarian cancer early metastatic microenvironment. Organotypic culture models comprise two or more interacting cell types from a particular tissue. We focus on organotypic 3D models that include at least one type of primary stromal cell type in an ECM background, such as collagen or fibronectin, plus ovarian cancer cells. We provide an overview of the two most comprehensive current models—a 3D model of the omental mesothelium and a microfluidic model. We describe the cellular and non-cellular components of the models, the incorporation of mechanical forces, and how the models have been adapted and utilized in functional assays. Finally, we review a number of 3D models that do not incorporate primary stromal cells and summarize how integration of current models may be the next essential step in tackling the complexity of the different ovarian cancer TMEs.

Cumulative defects in DNA repair pathways drive the PARP inhibitor response in high-grade serous epithelial ovarian cancer cell lines

PARP inhibitors (PARPi), such as Olaparib, have shown promising results in high-grade serous (HGS) epithelial ovarian cancer (EOC) treatment. PARPi sensitivity has been mainly associated with homologous recombination (HR) deficiency, but clinical trials have shown that predicting actual patient response is complex. Here, we investigated gene expression microarray, HR functionality and Olaparib sensitivity of 18 different HGS EOC cell lines and demonstrate that PARPi sensitivity is not only associated with HR defects. Gene target validation show that down regulation of genes in the nucleotide excision repair (NER) and mismatch repair (MMR) pathways (ERCC8 and MLH1, respectively) increases PARPi response. The highest sensitivity was observed when genes in both the HR and either NER or MMR pathways were concomitantly down regulated. Using clinical samples, patients with these concurrent down regulations could be identified. Based on these results, a novel model to predict PARPi sensitivity is herein proposed. This model implies that the extreme responders identified in clinical trials have deficiencies in HR and either NER or MMR.

High-throughput 3-dimensional culture of epithelial ovarian cancer cells as preclinical model of disease

BACKGROUND

Recent reports have identified distinct genomic patterns in ovarian carcinoma, including proliferative and mesenchymal-like groups, with worse outcome. The exact mechanisms driving the onset and progression of these tumors are still poorly understood. Additionally, researchers are concerned about the correct subtype stratification of the available cell line models, and the exploration of alternatives to monolayer culture. Identification of biomarkers to stratify cell lines, characterization of important processes as epithelial-mesenchymal transition (EMT), and the use of three-dimensional (3D) cultures as alternative models could be useful for cell line classification.

METHODS AND RESULTS

In this work, we present a descriptive analysis of 16 commonly used ovarian cancer cell lines. We have studied their morphology in 2- and 3D culture, and their response to cisplatin, observing in the majority of them an increased resistance in 3D. We have also performed an immunohistochemical analysis for proliferation marker Ki-67, and EMT related markers to establish phenotypes. Epithelial cells tend to show higher proliferative rates, and mesenchymal cells show an increase in EMT related markers, especially when cultured in 3D conditions.

CONCLUSIONS

We have stated the complex heterogeneity of ovarian cancer models, resembling primary tumors, agreeing with the argument that the cell line model for in vitro experiments must be carefully chosen. Our results also support that tridimensional culture could be a very helpful alternative in ovarian cancer research. Regarding EMT, a very important process for the development of this disease, some related biomarkers might be further characterized for their role in this disease development.

Engineered in-vitro cell line mixtures and robust evaluation of computational methods for clonal decomposition and longitudinal dynamics in cancer

Characterization and quantification of tumour clonal populations over time via longitudinal sampling are essential components in understanding and predicting the response to therapeutic interventions. Computational methods for inferring tumour clonal composition from deep-targeted sequencing data are ubiquitous, however due to the lack of a ground truth biological data, evaluating their performance is difficult. In this work, we generate a benchmark data set that simulates tumour longitudinal growth and heterogeneity by in vitro mixing of cancer cell lines with known proportions. We apply four different algorithms to our ground truth data set and assess their performance in inferring clonal composition using different metrics. We also analyse the performance of these algorithms on breast tumour xenograft samples. We conclude that methods that can simultaneously analyse multiple samples while accounting for copy number alterations as a factor in allelic measurements exhibit the most accurate predictions. These results will inform future functional genomics oriented studies of model systems where time series measurements in the context of therapeutic interventions are becoming increasingly common. These studies will need computational models which accurately reflect the multi-factorial nature of allele measurement in cancer including, as we show here, segmental aneuploidies.

Tissue and plasma levels of galectins in patients with high grade serous ovarian carcinoma as new predictive biomarkers

Galectins are moving closer to center stage in detecting glycosylation aberration in cancer cells. Here, we have investigated the expression of galectins in ovarian cancer (OC) and examined their potential as biomarkers in tissues and blood plasma samples of high grade serous ovarian carcinoma (HGSC) patients. In tissues, we found that increased protein expression of stromal gal-1 and epithelial gal-8/9 was associated with a poor response to treatment of HGSC patients. Gal-8/9 were both independent predictors of chemoresistance and overall survival (OS), respectively. This galectin signature increased the predictive value of the cancer antigen 125 (CA125) on 5-year disease-free survival (DFS), post-chemotherapy treatment and 5-year OS. In CA125^LOW patients, epithelial gal-9 was associated with a lower 5-year OS while stromal gal-1 and epithelial gal-8 were both associated with a lower 5-year DFS. Such negative predictive value of gal-8 and gal-9 was also found using plasma samples. In both cases, high plasma levels of gal-8 and gal-9 was associated with a lower OS and DFS. Overall, these data suggest that galectins may be promising biomarkers to identify subgroups of HGSC patients with poorer prognosis. Our study also contributes to better define the heterogeneity of the disease.

Loss of PRP4K drives anoikis resistance in part by dysregulation of epidermal growth factor receptor endosomal trafficking

Anoikis acts as a critical barrier to metastasis by inducing cell death upon cancer cell detachment from the extracellular matrix (ECM), thereby preventing tumor cell dissemination to secondary sites. The induction of anoikis requires the lysosomal-mediated downregulation of epidermal growth factor receptors (EGFRs) leading to termination of pro-survival signaling. In this study, we demonstrate that depletion of pre-mRNA splicing factor 4 kinase (PRP4K; also known as PRPF4B) causes dysregulation of EGFR trafficking and anoikis resistance. We also report a novel cytoplasmic localization of PRP4K at the late endosome, and demonstrate both nuclear and cytoplasmic localization in breast, lung and ovarian cancer tissue. Mechanistically, depletion of PRP4K leads to reduced EGFR degradation following cell detachment from the ECM and correlates with increased TrkB, vimentin and Zeb1 expression. As a result, PRP4K loss promotes sustained growth factor signaling and increased cellular resistance to anoikis in vitro and in a novel zebrafish xenotransplantation model of anoikis sensitivity, as well as increased metastasis in a mouse model of ovarian cancer. Thus, PRP4K may serve as a potential biomarker of anoikis sensitivity in ovarian and other epithelial cancers.

ReMixT: clone-specific genomic structure estimation in cancer

Somatic evolution of malignant cells produces tumors composed of multiple clonal populations, distinguished in part by rearrangements and copy number changes affecting chromosomal segments. Whole genome sequencing mixes the signals of sampled populations, diluting the signals of clone-specific aberrations, and complicating estimation of clone-specific genotypes. We introduce ReMixT, a method to unmix tumor and contaminating normal signals and jointly predict mixture proportions, clone-specific segment copy number, and clone specificity of breakpoints. ReMixT is free, open-source software and is available at http://bitbucket.org/dranew/remixt .

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.