Identification of Prognostic Biomarkers of Ovarian High Grade Serous Carcinoma through Spatial Transcriptome Analysis and Multispectral imaging

The identification of reliable predictive biomarkers is crucial for assessing optimal therapeutic responsiveness in high grade serous ovarian carcinoma (HGSC). The immune profile of the tumor microenvironment (TME) influenced the prognosis of HGSC patients. Using spatial transcriptome analysis, We investigated the characteristics of the tumor microenvironment associated with treatment response and identified multiple biomarkers associated with treatment benefit in HGSC patients. 12 HGSC patients who were treated with platinum-based chemotherapy were selected for this analysis.Among the 12 patients, 2 ROIs (region of interset) were obtained from each of 11 patients, while 1 ROI was obtained from patient P12. A total of 23 ROIs were obtained from 12 patients. Each ROI consisted of 3 Areas of Interest (AOIs) of morphologic markers (PanCK, SMA, CD45). PanCK was for epithelial tumor area, SMA was for stroma, and CD45 was for pan-immune cells. A total of 69 AOIs were generated for this analysis.