Heinzelmann / Francis Lab / Ovarian Cancer Research

Personalized treatment in oncology requires predictive biomarkers and direct on-target drug response to tailor therapy regimens. However, many efforts to develop truly predictive biomarkers are limited due to only a handful of genetic aberrations demonstrating clear clinical benefit for ‘targeted’ treatments. Together with an emerging trend in using drug combinations rather than single compounds, large prospective clinical trials require long time and enormous investments to demonstrate only marginal benefits. In order to overcome these limitations hampering major breakthroughs, researchers have moved towards ex vivo screening or patient-derived xenograft models envisioning to provide clinically relevant data in a 4-week turnaround. Here we aim to combine single-cell transcriptomics with drug treatment on ex vivo spheroids in a prospectively collected and homogenous cohort of ascites samples derived from high-grade serous ovarian cancer patients to 1) define the cell composition of ascites, an abdominal fluid with malignant cells taken through regular drainage to release patients’ pain; 2) align patients outcome with molecular and cellular signatures and ex vivo drug response, 3) evaluate in silico predicted and cancer cell-specific drug response in patient-derived cultures, and 4) ultimately define novel non-genetic biomarker-drug axes improving personalized treatment. In detail, we will test currently applied and suggested drug regimens in real-time using a straightforward ex vivo spheroid culture system. With an already established single-cell RNA sequencing pipeline we will also identify individual patient tumor heterogeneity and evaluate in silico drug response ex vivo. Our ex vivo spheroid platform will test cell proliferation, apoptosis, and response to single drugs and combinations in ascites-derived samples. Our bimodal approach is novel and the consideration of tumor heterogeneity together with drug response in patients’ material has not been addressed. Thus, we believe that the setup described in this grant can be further developed into a clinical helpful predictive analysis scheme. Moreover, predictors and response patterns delivered by this proposal will be useful for their testing in future ovarian cancer clinical trials.

Several hundred cancer patients in Switzerland carry pathogenic germline variants associated with hereditary breast/ovarian cancer (HBOC) and Lynch syndrome (LS). HBOC and LS cases are at significantly higher risk of primary and secondary cancers and need lifelong cancer surveillance and access to different risk management options. Their close blood relatives have 12.5%-50% probability of inheriting the respective cancer predisposition and need access to genetic evaluation. European-based studies suggest that most cancer patients with hereditary cancer syndromes are not identified and do not receive adequate cancer surveillance. Most evidence comes from cross-sectional studies; there is little available information about changes in adherence to surveillance over time. Little is known about how genetic test results affect subsequent surveillance for HBOC and LS cases and blood relatives, and the overall response of the Swiss healthcare system to mutation carriers' and relatives' needs for long-term surveillance and cancer prevention.

CASCADE II will collect prospective three-year data from confirmed mutation carriers and blood relatives to examine how cancer surveillance practices, uptake of risk management options, and access to genetic services (for untested relatives) change over time. Specific Aim 1: Monitor changes over time in cancer status, surveillance practices, uptake of risk management options, and uptake of genetic testing (for previously untested relatives), and explore whether there are differences in occurrence of these events (or cumulative incidence of events) during the follow-up period among the different participant groups.

Specific Aim 2: Examine the predictive value of individual domain clusters (e.g., cancer status), interpersonal domain clusters (e.g., family environment), and healthcare system domain clusters (e.g., provider specialty) on cancer surveillance practices, uptake of risk management options, and uptake of genetic testing (for previously untested relatives). Specific Aim 3: Explore participants' preferences for the role and involvement of healthcare providers in organization of cancer surveillance and follow-up care.

Longitudinal data from the CASCADE cohort, a prospective, family-based cohort targeting HBOC and LS confirmed cases and blood relatives will address these aims. CASCADE uses surveys to assess cancer status, surveillance, management of hereditary cancer risk, and coordination of care, covering multi-level factors affecting cancer prevention and survivorship. Data from the CASCADE I and CASCADE II studies span a period of over 6 years and 4 data collection points, each approximately 18 months apart, for participants entering the cohort since its initiation. Recruitment takes place in oncology and/or genetic testing centres in three linguistic regions of Switzerland.

Longitudinal survey data will address Aims 1 and 2. We will use Kaplan-Meier analyses and multivariate and/or multi-level Cox Proportional Hazards models to regress "cancer surveillance" event and "use of genetic services" event on predictors. Exploratory factor analyses and hierarchical cluster analyses will generate domain clusters for participants.

Narrative data (focus groups and interviews) from selected participants to present diverse perspectives, triangulated with survey data, will address Aim 3. Data from the CASCADE cohort have considerable potential to enhance the development of high-quality comprehensive support systems to improve cancer surveillance and access to genetic specialists and coordination of cancer care services in Switzerland.

In Hereditary Breast and Ovarian Cancer (HBOC) syndrome, communication of genetic test results with relatives is essential to cascade genetic screening. Cascade genetic screening is a sequential process of identifying and testing blood relatives of a known mutation carrier to determine if they also carry the pathogenic variant, in order to propose preventive and other clinical management options that reduce morbidity and mortality. However, according to Swiss and Korean privacy laws, individuals identified with the pathogenic variant have the sole responsibility to share information about test results and health implication to relatives. Empirical evidence suggests that up to 50% of biological relatives are unaware of relevant genetic information, suggesting that potential benefits of genetic testing are not communicated effectively. Thus, interventions designed to help probands effectively communicate with relatives are critical for better management of hereditary cancer risk.

Technology could play a significant role in facilitating communication and genetic education within HBOC families. Given the lack of well-developed digital health tools to assist individuals with genetic predisposition to cancer effectively communicate genetic information to their relatives, the study aims to develop a modern, scalable, mobile friendly digital health solution for Swiss and Korean HBOC families. The digital health solution will be based on the Family Gene Toolkit (FGT), a web-based intervention designed to enhance communication of genetic test results within HBOC families that has been successfully tested for acceptability, usability, and participant satisfaction.

The study will also expand an existing research infrastructure developed in Switzerland, to enable future collaborative projects between Switzerland and Korea in this field. The Specific Aims of the project are: 1) Develop a digital health solution to support the communication of cancer predisposition among HBOC families, based on linguistic and cultural adaptation methods of the Family Gene Toolkit for the Swiss and Korean population 2) Develop the K-CASCADE research infrastructure in Korea by expanding an existing research infrastructure developed by the CASCADE Consortium in Switzerland 3) Evaluate the efficacy of the aforementioned digital solution on psychological distress and communication of genetic test results, as well as knowledge of cancer genetics, coping, decision making and quality of life 4) Explore the reach, effectiveness, adoption, implementation, and maintenance of the aforementioned digital solution.

The content for the digital health solution will be based on the FGT with linguistic adaptation to Korean, German, French and Italian, and will be made available for web and mobile access. Aim 1 will be achieved through focus groups in each country to better identify cultural context with 20 -24 HBOC mutation carriers and relatives and 6-10 healthcare providers involved in genetic services (counseling and testing).

For Aim 2 , K-CASCADE, a Korean database of HBOC families (mutation carriers and relatives) will be created based on the Swiss CASCADE Consortium database, creating a lasting research infrastructure that will facilitate future collaboration, including the possibility to apply machine learning algorithms for prediction of breast and ovarian cancer risk.

For Aim 3, feasibility and efficacy of the digital health solution against the comparison intervention will be assessed in a randomized trial, with a sample of 104 HBOC mutation carriers (52 in each study arm).

Aim 4 will be achieved with survey and interview data collected from participating HBOC families and healthcare providers during all phases of the study. Dissemination strategies will also be generated to ensure sustainable use of the digital health solution. Adapting existing interventions, rather than developing new ones, takes advantage of previous valid experiences without duplicating efforts.

Adaptation and implementation of culturally sensitive, digital health interventions that can facilitate communication processes within the family and enhance understanding of genetic cancer risk are extremely timely and relevant, given the expansion of genetic testing technology, the falling costs of genetic testing, and the increased pressure for integration of genetic knowledge in routine clinical care. The study would be one of the first resource-effective international research platforms to develop digital health solutions that can be scaled to large patient numbers and can be used in routine practice.