Quantitative analysis of spatial distribution of lymphocytes in hepatocellular carcinoma: A biomarker correlated with survival and gene expression in cancer immune system.

Abstract

4119 Background: Tumor microenvironment (TME) is known to impact prognosis in hepatocellular carcinoma (HCC). Although digital pathology and artificial intelligence have been adopted in modern medicine and oncology, few quantitative biomarkers have been identified to predict the prognosis and guide treatment for HCC via an automated analysis of TME at the cellular level. Methods: Histopathological images and clinical data of 365 cases with HCC were obtained from TCGA (The Cancer Genome Atlas), and 60 of HCC pathology images and cancer lesion annotations were collected from PAIP2019 [1]. DenseNet-based HCC segmentation model (F1-score, 0.904) and Hover-Net-based cell detection model (F1-score, 0.914) were developed using PAIP2019 and MoNuSac datasets, respectively [2,3,4]. Each histopathology image of TME was segmented via the segmentation model into two areas: 1) non-tumoral regions that include the stroma; 2) tumoral regions where HCC cells are concentrated. The cell detection model recognized individual cells on images, specified lymphocytes, and calculated ratios of lymphocyte to total cell count (RLTCC) in segmented regions. RLTCC was then correlated with clinical survival outcomes, HCC primary risk factors, and RNA expression profiles. Results: RLTCC in tumoral regions was not significantly associated with prognosis. Patient groups with higher RLTCC in non-tumoral regions (RLTCC in NT) showed better overall survival (OS) than those with lower RLTCC in NT regardless of HCC risk factors (median OS 45.7 vs 18.6 months; log hazard ratio of -1.6 ± 1.1, p=0.006). These patients had significantly enriched expression of genes (p<0.05) related to cancer antigen presentation (higher gene expression by +33.7%), recognition of cancer cells by T-cell (+32.0%), T-cell priming and activation (+32.2%), immune cell localization to tumors (+31.9%), and killing of cancer cells (+24.7%). Those with HCC etiology of hepatitis B and C had more patients in the higher RLTCC in NT (17/21 patients, 81.0%; 23/29, 79.3%, respectively). In comparison, those with alcohol consumption showed equal distribution (26/53, 49.1%). The RLTCC in NT in hepatitis B/C groups was statistically higher than alcohol consumption group (p<0.05). Conclusions: A digital prognostic biomarker, RLTCC in NT of TME was identified as a significant prognostic indicator, and it was shown to correlate with RNA gene expression related to T-cell mediated cancer immunity. A retrospective analysis of clinical response from systemic therapy in relation to digital biomarkers is underway and will be reported.