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.

Microdissected Tissue vs Tissue Slices-A Comparative Study of Tumor Explant Models Cultured On-Chip and Off-Chip.

Predicting patient responses to anticancer drugs is a major challenge both at the drug development stage and during cancer treatment. Tumor explant culture platforms (TECPs) preserve the native tissue architecture and are well-suited for drug response assays. However, tissue longevity in these models is relatively low. Several methodologies have been developed to address this issue, although no study has compared their efficacy in a controlled fashion. We investigated the effect of two variables in TECPs, specifically, the tissue size and culture vessel on tissue survival using micro-dissected tumor tissue (MDT) and tissue slices which were cultured in microfluidic chips and plastic well plates. Tumor models were produced from ovarian and prostate cancer cell line xenografts and were matched in terms of the specimen, total volume of tissue, and respective volume of medium in each culture system. We examined morphology, viability, and hypoxia in the various tumor models. Our observations suggest that the viability and proliferative capacity of MDTs were not affected during the time course of the experiments. In contrast, tissue slices had reduced proliferation and showed increased cell death and hypoxia under both culture conditions. Tissue slices cultured in microfluidic devices had a lower degree of hypoxia compared to those in 96-well plates. Globally, our results show that tissue slices have lower survival rates compared to MDTs due to inherent diffusion limitations, and that microfluidic devices may decrease hypoxia in tumor models.

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.

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.

Fluorescence hyperspectral imaging for live monitoring of multiple spheroids in microfluidic chips.

Tumor spheroids represent a realistic 3D in vitro cancer model because they provide a missing link between monolayer cell culture and live tissues. While microfluidic chips can easily form and assay thousands of spheroids simultaneously, few commercial instruments are available to analyze this massive amount of data. Available techniques to measure spheroid response to external stimuli, such as confocal imaging and flow cytometry, are either not appropriate for 3D cultures, or destructive. We designed a wide-field hyperspectral imaging system to analyze multiple spheroids trapped in a microfluidic chip in a single acquisition. The system and its fluorescence quantification algorithm were assessed using liquid phantoms mimicking spheroid optical properties. Spectral unmixing was tested on three overlapping spectral entities. Hyperspectral images of co-culture spheroids expressing two fluorophores were compared with confocal microscopy and spheroid growth was measured over time. The system can spectrally analyze multiple fluorescent markers simultaneously and allows multiple time-points assays, providing a fast and versatile solution for analyzing lab on a chip devices.

STAT1-associated intratumoural TH1 immunity predicts chemotherapy resistance in high-grade serous ovarian cancer.

High-grade serous ovarian carcinoma (HGSC) accounts for 70% of all epithelial ovarian cancers but clinical management is challenged by a lack of accurate prognostic and predictive biomarkers of chemotherapy response. This study evaluated the role of Signal Transducer and Activator of Transcription 1 (STAT1) as an independent prognostic and predictive biomarker and its correlation with intratumoural CD8+ T cells in a second independent biomarker validation study. Tumour STAT1 expression and intratumoural CD8+ T cell infiltration were assessed by immunohistochemistry as a multicentre validation study conducted on 734 chemotherapy-naïve HGSCs. NanoString-based profiling was performed to correlate expression of STAT1 target genes CXCL9, CXCL10 and CXCL11 with CD8A transcript expression in 143 primary tumours. Multiplexed cytokine analysis of pre-treatment plasma from resistant and sensitive patients was performed to assess systemic levels of STAT1-induced cytokines. STAT1 was validated as a prognostic and predictive biomarker in both univariate and multivariate models and its expression correlated significantly with intra-epithelial CD8+ T cell infiltration in HGSC. STAT1 levels increased the prognostic and predictive value of intratumoural CD8+ T cells, confirming their synergistic role as biomarkers in HGSC. In addition, expression of STAT1 target genes (CXCL9, CXCL10 and CXCL11) correlated significantly with levels of, and CD8A transcripts from intratumoural CD8+ T cells within the resistant and sensitive tumours. Our findings provide compelling evidence that high levels of STAT1, STAT1-induced chemokines and CD8+ T cells correlate with improved chemotherapy response in HGSC. These results identify STAT1 and its target genes as novel biomarkers of chemosensitivity in HGSC. These findings provide new translational opportunities for patient stratification for immunotherapies based on emerging biomarkers of inflammation in HGSC. An improved understanding of the role of interferon-inducible genes will be foundational for developing immunomodulatory therapies in ovarian cancer.

Combination of serum biomarkers to differentiate malignant from benign ovarian tumours.

OBJECTIVE: To investigate biomarkers and clinical parameters to distinguish ovarian cancers from benign ovarian tumours. METHODS: Serum biomarkers (CA 125, human epididymis protein 4 [HE 4], interleukin-18 [IL-18], leptin, macrophage migration inhibitory factor [MIF], fibroblast growth factor 2 [FGF-2], insulin-like growth factor, osteopontin, prolactin) and the risk of malignancy indexes I and II (RMI-I and RMI-II) scores were obtained prior to surgery in 52 patients with ovarian tumours (37 malignant and 15 benign). ROC curves were built for each individual marker, for logistic regression models using all markers, and for models combining both biomarkers and RMI scores. RESULTS: The model with nine biomarkers performed well (specificity 93%, sensitivity 84%) and was more reliable than the RMI-I or RMI-II alone. A regression model combining RMI-II and six of the biomarkers (CA 125, HE  4, IL-18, leptin, MIF, and FGF-2) allowed differentiation between the cancer and non-cancer cases in this pilot study. CONCLUSION: The regression models using biomarkers combined with clinical scoring systems warrant further investigation to improve triage of patients with ovarian tumours to enhance utilization of resources and optimize patient care.