Development of a digital algorithm for assessing tumor-stroma ratio, tumor budding and tumor infiltrating lymphocytes in vulvar squamous cell carcinomas

Abstract

Tumor-stroma ratio (TSR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs) are prognostic markers in some cancers but with unknown significance in vulvar squamous cell carcinoma (VSCC). This pilot study primarily aimed to develop a digital method for evaluating TSR, TB and TILs in VSCC and secondarily to investigate variation in these factors by p16 status. An independent training set stained with CD3/cytokeratin and CD8/cytokeratin was used to develop a deep learning-based Application Protocol Package (APP) segmenting tissue into background, epithelium, or stroma. TSR was defined as percentage of tumor epithelium relative to total tumor area, and tumor buds were defined as clusters of 1–4 tumor cells. A second APP quantified CD3+ and CD8+ lymphocytes in the intraepithelial and stromal compartments, respectively. The digital algorithms were applied to the study cohort of 41 VSCC cases, achieving satisfactory performance without manual corrections. TSR ranged between 33 and 91% with median of 64%, and median number of buds was 4 (range: 0–48) buds/mm². Median density and range of CD3+ lymphocytes were 222 (13-2320) cells/mm² in the intraepithelial and 1978 (397–6683) cells/mm² in the stromal compartment, respectively. CD8+ lymphocyte counts were lower. There was a tendency towards lower TSR and higher number of buds in p16-negative compared with p16-positive VSCC. Finally, automated measures were compared with manual evaluations showing high concordance. The developed automated method provided precise and objective measurements of TSR, TB and TILs. The algorithms should be validated in a larger cohort and correlated with clinicopathological characteristics and prognosis to determine their clinical relevance.