Caroline Elizabeth Ford

Cell adhesion is a key property of cancer cells, as it relates to their potential for dissemination and metastasis. The in vitro assays used to measure it and, however, are characterized by several drawbacks, including low temporal resolution and limited procedural standardization, which reduce their usefulness and accuracy. In this work, we propose an alternative analytical approach, based on live-cell imaging, which enables the study of cell adhesion dynamics at the single-cell level. The increased resolution afforded by this method was instrumental for the identification of cell division prior to attachment and the co-existence of markedly different proliferation rates across the culture, previously unidentified patterns of behavior in the adhesion process. Finally, we generalize our method by substituting the segmentation algorithm and showing that this approach can be integrated within routine laboratory analytical procedures and does not require high-performance microscopy and imaging setups. Our new analytical approach improves the in vitro quantification of cell adhesion, enabling the study of this process with high temporal resolution and increased level of detail. The extension of the analysis to the single-cell level, additionally, uncovered the role of population variability and proliferation in this process. The simple and cost-effective procedure here described enables the accurate characterization of cell adhesion. In addition to improving our understanding of adhesion dynamics, its results could support the development of treatments targeting the ability of cancer cells to adhere to surrounding tissues by allowing detailed quantification of cell adhesion metrics.

Background: Drug repurposing has emerged as an effective strategy to accelerate drug discovery. Using the pipeline established from a large collaborative drug repurposing project focused on high-grade serous ovarian cancer (HGSOC), we identified ivacaftor, an FDA-approved cystic fibrosis medication, as a drug candidate predicted to interact with the receptor tyrosine kinase-like orphan receptor 1 (ROR1) which we have previously demonstrated as a therapeutic target in ovarian cancer. Objectives: This study aimed to provide preclinical evidence supporting the potential repurposing of ivacaftor for HGSOC treatment. Design: Ivacaftor was tested in 2D and 3D preclinical models as well as patient-derived organoid models in vitro. Methods: Dose–response analysis was undertaken in ROR1 expressing HGSOC cell lines OVCAR4, KURAMOCHI, COV362 and COV318 in both 2D adherent and 3D bioprinted formats. Real-time live/dead and apoptosis cell staining were performed over a 72 h period using the IncuCyte live cell imaging platform. Flow cytometry was used to assess apoptosis, DNA damage and cell proliferation following treatment with either 15 µM ivacaftor or 30 µM carboplatin at 24, 48 and 72 h. Additionally, ROR1-expressing HGSOC patient-derived organoids (OC029, OC043 and OC058) underwent ivacaftor dose–response analysis. Cell apoptosis following 15 µM ivacaftor treatment was measured in real-time using an Annexin V assay in two additional organoid models (OC062 and OC075). Finally, the mechanisms associated with response to ivacaftor were explored in HGSOC cell lines through Western blotting. Results: The IC50 for ivacaftor ranged from 6.5 to 13.2 µM in 2D cultures and 11.6 to 18.2 µM in 3D cultures. Treatment with 10 and 15 µM ivacaftor resulted in significantly increased cell death and reduced live cell counts compared to the vehicle control over 72 h. Organoids displayed IC50 values between 11.2 and 14.1 µM. Ivacaftor treatment induced apoptosis in organoids, with no significant impact on DNA damage or cell cycle in HGSOC cells. ROR1 signalling associated oncogenic pathways including the BMI-1 and the PI3K/AKT pathways were modulated following ivacaftor treatment. Conclusion: In summary, ivacaftor demonstrated significant anti-tumour potential in preclinical HGSOC models, supporting its further investigation as a repurposed therapy for ovarian cancer.

Background: Endometriosis is a chronic, heterogeneous disease with limited non-hormonal treatment options. Drug repurposing provides an accelerated route to identify safe, tolerable, and potentially effective therapies for endometriosis. Receptor tyrosine kinase-like orphan receptor 1 (ROR1) was investigated as a potential target based on its restricted expression in adult tissues and emerging role in the pathogenesis of multiple diseases. Methods: ROR1 expression was assessed in transcriptomic datasets including 408 endometriosis samples and 53 controls and validated at the protein level in an independent cohort of tissue microarrays comprising 179 tissues. Candidate compounds predicted to bind ROR1 were prioritized using the BLAZE platform, filtered for pharmacological safety and patient acceptability, and screened in the 12Z endometriotic epithelial cell line. The compound that showed the greatest reduction in proliferation and viability, rimegepant, was further tested in three patient-derived organoid models representing deep infiltrating endometriosis to evaluate viability, growth, and morphological responses. Results: ROR1 was transcriptionally upregulated in endometriosis and overexpressed at the protein level across lesions. Of three shortlisted compounds, cabergoline and pirenzepine did not alter proliferation, while rimegepant significantly reduced viability in 12Z cells. In patient-derived organoids, responses were patient-specific: two models showed concentration-dependent antiproliferative and cytotoxic effects, while one model was less responsive at the concentrations tested. Morphological features consistent with cell death were observed in sensitive lines. Conclusion: This study provides the first evidence in human-derived endometriosis models supporting rimegepant, a clinically approved calcitonin gene-related peptide antagonist with a favorable safety profile, as a potential therapy. The integrated pipeline combining molecular validation, computational prioritization, and patient-derived functional testing illustrates a translational approach to accelerate drug discovery in endometriosis.

STUDY QUESTION: Can patient-derived organoid models be reliably established from diverse surgical phenotypes of endometriosis, and how do clinical factors such as hormonal treatment affect their growth success and morphology? SUMMARY ANSWER: Endometriosis organoids can be established across all major surgical phenotypes with variable efficiency, and hormonal treatment at the time of biospecimen collection significantly reduces organoid establishment success. WHAT IS KNOWN ALREADY: Organoid cultures have been developed from eutopic endometrium and select endometriosis tissue biospecimens previously, but their feasibility as pre-clinical models of endometriosis across diverse tissue types and clinical presentations remains unclear. STUDY DESIGN, SIZE, DURATION: Twenty-eight endometriosis tissue biospecimens were obtained from 23 patients undergoing surgery, with organoid cultures assessed through successive stages of establishment, passage, and cryopreservation. PARTICIPANTS/MATERIALS, SETTING, METHODS: Endometriosis biospecimens, including deep infiltrating endometriosis (DIE), ovarian endometrioma (OMA), and superficial peritoneal (SUP) biospecimens, were processed into organoid cultures using a validated low-Wnt culture system. Organoid viability, morphology, hormone receptor expression, and cellular composition were evaluated by microscopy, immunohistochemistry, and quantitative morphometric analysis. MAIN RESULTS AND THE ROLE OF CHANCE: Overall, 22/28 (78.6%) biospecimens established 3-dimensional structures, with 15/28 (53.6%) remaining viable after cryopreservation. Establishment success differed by phenotype (OMA 71.4%, DIE 63.6%, SUP 30%). Progesterone receptor expression was retained in SUP and DIE-derived organoids (7/7, 100%), while OMA-derived organoids showed substantial reductions (4/5 cases). Biospecimens from patients receiving hormonal treatment were smaller (P = 0.038) and had reduced organoid establishment success (3/13, 23.1% vs 12/15, 80.0%, P = 0.003). Organoids exhibited distinct morphological patterns correlating with disease phenotype. LIMITATIONS, REASONS FOR CAUTION: Uniform culture conditions may limit growth of certain subtypes, and the in vitro organoid models may not fully represent in vivo tissue complexity. Sample sizes were modest, and pooling tissues from the same patient could mask intra-patient heterogeneity. WIDER IMPLICATIONS OF THE FINDINGS: These organoid models offer a promising platform for studying subtype-specific endometriosis biology, including hormone resistance mechanisms, and could inform personalized therapeutic development. The impact of hormonal treatment on organoid viability underscores the need to consider clinical context in pre-clinical models of endometriosis. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Endometriosis Clinical and Scientific Trials (NECST) Network, funded by the Australian Government Department of Health and Aged Care (Grant 4-I66SNMA), and by a research grant from Endometriosis Australia to C.E.F., D.L., and J.A.A. K.G. is supported by an Australian Government Research Training Program Scholarship and a NECST Network Top-Up Scholarship, which did not influence the conduct or outcomes of this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. J.A.A. has received consulting fees from Hologic, Gedeon Richter, and BD, personal payments from Hologic, Bayer, Organon, and Gedeon Richter, travel support from Gedeon Richter, and participated on data safety monitoring advisory boards for Hologic and Gideon Richter. He was the former chair of the Australian Endometriosis Guideline Committee and is the Co-Editor-in-Chief of the Journal of Minimally Invasive Gynaecology. All other authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.

Treatment of High‐grade serous ovarian cancer (HGSOC) is often ineffective due to frequent late‐stage diagnosis and development of resistance to therapy. Timely selection of the most effective (combination of) drug(s) for each patient would improve outcomes, however the tools currently available to clinicians are poorly suited to the task. We here present a computational simulator capable of recapitulating cell response to treatment in ovarian cancer. The technical development of the in silico framework is described, together with its validation on both cell lines and patient‐ derived laboratory models. A calibration procedure to identify the parameters that best recapitulate each patient's response is also presented. Our results support the use of this tool in preclinical research, to provide relevant insights into HGSOC behavior and progression. They also provide a proof of concept for its use as a personalized medicine tool and support disease monitoring and treatment selection.

As a heterogenous disease with likely multiple pathogeneses and as-yet-undefined subtypes, progress in endometriosis treatment is currently limited by a lack of appropriate models and cohorts for research. Almost half of all publicly available datasets labelled as ‘endometriosis’ do not represent true disease as they are based on eutopic endometrium. Eutopic endometrial cells and tissues are frequently being used to represent endometriotic lesions, despite the unequivocal differences at both the tissue and cellular levels. As preclinical endometriosis research increases, it is important that the unique cellular and molecular profiles of endometrium and endometriosis are distinguished. Whilst each of these biospecimens can provide invaluable information to better understand disease aetiology and identify targets for diagnosis and treatment, it is imperative that the appropriate biospecimen and model are used to answer the relevant research question because endometriosis is not the endometrium.

Background: Novel therapeutics are urgently needed for high-grade serous ovarian cancer (HGSOC). We identified the receptor tyrosine kinase-like orphan receptor 1 (ROR1) as a therapeutic target. NBE-002, an antibody–drug conjugate (ADC) consisting of a humanised anti-ROR1 antibody, huXBR1-402, linked to a highly potent anthracycline-derivative (PNU), has activity in ROR1-positive haematologic malignancies. Objectives: This study explored the anti-cancer effects of NBE-002 alone and in combination with standard HGSOC therapies, carboplatin, paclitaxel and olaparib. Design: A ROR1-ADC was tested in cell lines and in vivo models of HGSOC. Methods: Different ROR1-targeting antibodies and payload compositions were constructed and tested in vitro . The dose effect of NBE-002 alone and in combination with carboplatin, paclitaxel or olaparib was analysed in ROR1+ HGSOC cell lines. Growth inhibition and apoptosis were monitored by live cell imaging and combination effects determined. Ten HGSOC PDX models were treated with NBE-002 alone, or in combination with carboplatin or olaparib, over 4 weeks and tumour volume and overall survival evaluated. Results: Synergistic interaction was observed in two out of five HGSOC cell lines treated with NBE-002 and carboplatin (PEO4 and OC023, chemo-resistant), in one out of five treated with NBE-002 and olaparib (PEO1, BRCA2 mutated, HR deficient) and none of five treated with NBE-002 and paclitaxel. In vivo, NBE-002 exhibited activity in PA-1 xenografts and three HGSOC PDX models with high ROR1 expression, platinum sensitivity and homologous recombination DNA repair deficient (HRD). When NBE-002 was combined with carboplatin, activity was observed in 7 of 10 ROR1-expressing PDX models, regardless of platinum or HRD status. The activity was demonstrated in combination with olaparib in both PDX tested, one HRD and one HRD reverted. Conclusion: The ROR1-targeting ADC, NBE-002, has therapeutic potential in HGSOC, with single agent activity observed both in vitro and in vivo . Broader clinical applications were evident when NBE-002 was combined with carboplatin or olaparib.

Objective: Endometrial cancer is one of the few cancers for which mortality is still increasing. A lack of treatment options remains a major challenge, particularly for some subtypes of the disease. GZD824, also known as olverembatinib , is a multi‐kinase inhibitor previously investigated in clinical trials for chronic myeloid leukaemia and Ph+ acute lymphoblastic leukaemia as a BCR‐ABL inhibitor. This study aimed to investigate the pre‐clinical efficacy of GZD824 for the treatment of EC. Methods: Here, we undertook pre‐clinical evaluation of GZD824 in seven endometrial cancer cell lines (HEC‐1‐A, HEC‐1‐B, MFE296, RL95‐2, Ishikawa, KLE and ARK‐1), one normal immortalised endometrium derived cell line (E6E7hTERT) and primary mesothelial and fibroblast cells isolated from normal omentum samples. Results: GZD824 inhibited the proliferation of all endometrial cancer cell lines, which were significantly more sensitive to GZD824 compared to normal cells ( p = 0.030). GZD824 significantly inhibited migration in Ishikawa (endometrioid) and ARK1 (serous) endometrial cancer cell lines and significantly inhibited invasion in the ARK1 cells. Whole transcriptome regulation following two doses (0.1 and 1 μM) of GZD824 in Ishikawa and ARK1 cells was investigated via RNA‐seq, and key components of enriched pathways were investigated at the translational level. Key pathways altered included ROR1/Wnt, GCN2‐ATF4, epithelial to mesenchymal transition (EMT) and PI3K‐AKT. Conclusion: Together, these studies support further investigation of GZD824 as a potential therapeutic agent in endometrial cancer, potentially in combination with immune checkpoint inhibitors.

Background: Cell adhesion, that is the ability to attach to a given substrate, is a key property of cancer cells, as it relates to their potential for dissemination and metastasis. The in vitro assays used to measure it, however, are characterized by several drawbacks, including low temporal resolution and limited procedural standardisation which reduce their usefulness and accuracy. Results: In this work, we propose an alternative analytical approach, based on live-cell imaging data, that yields comprehensive information on cell adhesion dynamics at the single-cell level. It relies on a segmentation routine, to identify the pixels belonging to each cell from time-lapse microscopy images acquired during the adhesion process. A tracking algorithm then enables the study of individual cell adhesion dynamics over time. The increased resolution afforded by this method was instrumental for the identification of cell division prior to attachment and the co-existence of markedly different proliferation rates across the culture, previously unidentified patterns of behaviour in the adhesion process. Finally, we generalize our method by substituting the segmentation algorithm of the instrument used to acquire the images, with a custom-made one, showing that this approach can be integrated within routine laboratory analytical procedures and does not necessarily require high-performance microscopy and imaging setups. Conclusions: Our new analytical approach improves the in vitro quantification of cell adhesion, enabling the study of this process with high temporal resolution and increased level of detail. The extension of the analysis to the single-cell level, additionally, uncovered the role of population variability and proliferation in this process. The simple and cost-effective procedure here described enables the accurate characterisation of cell adhesion. Beside improving our understanding of adhesion dynamics, its results could support the development of treatments targeting the ability of cancer cells to adhere to surrounding tissues.