High-grade serous ovarian cancer (HGSOC) often becomes resistant to chemotherapy based on carboplatin and paclitaxel, reducing treatment success and survival. This study aims to identify optical and molecular biomarkers associated with chemotherapy resistance using a multimodal spatial profiling approach. Tissue microarrays (TMAs) comprising primary ovarian tumours and ascites-derived tumour samples will be analysed to characterise resistance-associated alterations within the tumour microenvironment. Immunohistochemistry (IHC) will be performed for established resistance markers to evaluate differential protein expression across treatment-sensitive and resistant tissues. In parallel, Raman microscopy–based spatial lipidomics will be employed to generate label-free molecular maps of tumour and stromal regions with high spatial resolution. By integrating optical signatures with histopathologic and molecular features, we aim to identify tumour cell–specific and microenvironment associated lipidomic fingerprints linked to drug resistance. This approach could identify biomarkers for early chemotherapy resistance prediction and shed light on metabolic changes in ovarian cancer.