Title Low CD8+ density variation and R1 surgical margin as independent predictors of early post-resection recurrence in HCC patients meeting Milan criteria /
Authors Stulpinas, Rokas ; Jakiūnaitė, Ieva ; Sidabraitė, Agnė ; Rasmusson, Allan ; Žilėnaitė-Petrulaitienė, Dovilė ; Strupas, Kęstutis ; Laurinavičius, Arvydas ; Kielaitė-Gulla, Aistė
DOI 10.3390/curroncol31090394
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Is Part of Current oncology.. Basel : MDPI. 2024, vol. 31, iss. 9, p. 5344-5353.. eISSN 1718-7729
Keywords [eng] CD8 ; Milan criteria ; digital pathology ; hepatocellular carcinoma (HCC) ; liver transplantation ; tumor-infiltrating lymphocytes
Abstract [eng] Our study included 41 patients fulfilling the Milan criteria preoperatively and aimed to identify individuals at high risk of post-resection HCC relapse, which occurred in 18 out of 41 patients (43.9%), retrospectively. We analyzed whole slide images of CD8 immunohistochemistry with automated segmentation of tissue classes and detection of CD8+ lymphocytes. The image analysis outputs were subsampled using a hexagonal grid-based method to assess spatial distribution of CD8+ lymphocytes with regards to the epithelial edges. The CD8+ lymphocyte density indicators, along with clinical, radiological, post-surgical and pathological variables, were tested to predict HCC relapse. Low standard deviation of CD8+ density along the tumor edge and R1 resection emerged as independent predictors of shorter recurrence-free survival (RFS). In particular, patients presenting with both adverse predictors exhibited 100% risk of relapse within 200 days. Our results highlight the potential utility of integrating CD8+ density variability and surgical margin to identify a high relapse-risk group among Milan criteria-fulfilling HCC patients. Validation in cohorts with core biopsy could provide CD8+ distribution data preoperatively and guide preoperative decisions, potentially prioritizing liver transplantation for patients at risk of incomplete resection (R1) and thereby improving overall treatment outcomes significantly.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2024
CC license CC license description