Innovative Novel Ovarian cancer treatment Approaches
In 70% of all cases, high grade serous ovarian cancer (HGSOC) is diagnosed at an advanced stage with spread into the peritoneal cavity. At present, successful debulking surgery followed by adjuvant chemotherapy, consisting of a combination of taxane and platinum based drugs, serves as the most efficient treatment options and enhances survival chances for the patients.
However, most of the patients relapse with 70% of them being chemoresistant. Despite development of surgical techniques and chemotherapeutic regimens, the overall survival is still below 45%.Much emphasis has been placed on investigating the use of the tumour marker cancer antigen 125 (Ca125) and imaging modalities as a possible predictive model of surgical outcome but without success. If tumour biology did determine surgical success, then biomarkers could potentially be developed that predicted outcomes of surgery and aided clinical treatment decisions.
The new “Cancer Immunogram” is a framework proposed for describing the different interactions between cancer and the immune system in individual cases, with the aim to focus biomarker research and to help guide treatment choice on a more patient specific approach.
The last years we have used much efforts to establish relevant mouse models for ovarian cancer, and a bioluminescent orthotopic combined surgical/chemotherapeutic xenograft model in immunosuppressed mice has been developed. New knowledge and demands necessitate, however, improvements. Immune-competent patient-derived xenograft (iPDX) models are suggested to be the most suitable preclinical models. These models contain both a functional human immune system as well as an orthotopically-implanted tumor from the same individual.
The main focus of INOvA is to establish Innovative Novel Ovarian Cancer Treatment Approaches. We aim to establish our own “cancer immunogram” with specific parameters, to identify interesting biomarker/immunotherapeutic targets, to be able to stratify patients based on the immunogram scoring system and to propose treatment options accordingly.
We are also focusing on developing an Immunocompetent Patient Derived Xenograft model (iPDX). Further, we would like to analyse if the developed iPDX models i) Conserve genetic, phenotypic and functional characteristics of the primary tumor ii) Represent a precise and predictive preclinical model to improve image-guided surgery iii) to test the in vivo efficacy of the identified candidate biomarkers and also to validate the accuracy of the immunotherapeutic treatment option proposed based on the immunogram.