High-grade serous ovarian carcinoma (HGSOC) represents the most common type of ovarian cancer, distinguished by its rapid progression, genetic instability, and poor prognosis(1). The genetic landscape of these tumours, particularly pathogenic variants in BRCA1 or BRCA2 or promoter hypermethylation of the BRCA1 or RAD51C genes, plays a key role in influencing the progression and treatment response of HGSOC(2, 3). These are important genes in homologous recombination (HR), a high-fidelity DNA repair pathway(2). HGSOC deficient in HR are sensitive to PARP inhibitor therapy (PARPi), an effective targeted therapy used in first-line maintenance and second line HGSOC therapy. HR deficiency contributes to genomic instability and an elevated tumour mutational burden and is associated with immune cell infiltration within HGSOC(2, 4).
The SOLACE2 clinical trial (NCT01675596) is interrogating the role of PAPRi combinations in platinum-sensitive recurrent HGSOC. As one component of the translational research, the relationship between the tumor microenvironment (TME) and treatment response is being examined, with a focus on any correlation with mutation/ promotor hypermethylation status of key HR pathway genes. Utilising OPAL™ 7-color multiplexed immunofluorescence imaging, chemo-naive HGSOC samples were evaluated for presence and spatial distribution of immune cells within the TME. A machine learning approach was developed to train models to define cell phenotypes and differentiate between tumor and stromal compartments.
Here we will present pilot data generated from SOLACE2 HGSOC samples and explore the spatial architecture of the immune TME in relation to HR status in chemo-naive HGSOC.