Histopathological growth patterns of gastric cancer liver metastasis and their association with patient prognosis.

484 Background: The histopathological growth patterns (HGPs) of liver metastasis reflect the complicated and varied interactions between tumor cells and the host microenvironment. We studied HGPs of gastric cancer liver metastasis (GCLM) and sought to predict them using radiomic and clinical variables. Methods: Hepatectomy was performed in 62 patients with GCLM at our university hospital between 2011 and 2021. HGPs were evaluated according to international consensus guidelines, and were classified as either desmoplastic HGP (dHGP) or non-dHGP. CD4, CD8, VEGF and CD31 were analyzed by immunohistochemistry. Eight hundred and fifty-one radiomics features were extracted from CT portal venous phase images and the optimal radiomics signature was determined by univariate analysis and LASSO regression. Multivariable regression analyses and ROC curves were used to assess the predictive performance of HGPs with a radiomic and clinical combined model. Results: Among 62 patients, 14 were categorized as dHGP, and 48 as non-dHGP. Non-dHGP vs. d-HGP was associated with higher tumor N stage and CEA level, and with decreased CD8 + T cells, and lower VEGF and CD31 expression. HGP status was independently associated with patient cancer-specific survival (CSS) (P＜0.05) multivariately.Analysis of percent relative contribution revealed that HGP ranked first for CSS (35.9%), ahead of T (28.9%) and N (28.9%) stage. A model with combined radiomic and clinical features demonstrated robust performance with area under the curve (AUC) values of 0.993 and 0.933 in the training and validation sets, respectively. Conclusions: Non-invasive determination of radiomic and clinical features was shown to predict HGPs types. Compared to dHGP, GCLM with non-dHGP exhibited significantly lower immune cell infiltration and decreased angiogenesis. Among features examined in GCLM, HGP was the most robust for prognostication. Univariate and multivariate analysis of prognostic factors for cancer-specific survival. Characteristics Univariate analysis Multivariate rergression analysis HR (95%CI) P HR (95%CI) P Gender ( Women vs Men ) 1.13(0.61-2.09) 0.71 Age ( >60years vs ≤60years) 1.08(0.60-1.70) 0.98 HGP ( non-desmoplastic HGP vs desmoplastic HGP ) 3.63(1.78-7.41) 0.00 3.48(1.37-8.88) 0.01 T stage ( T3-T4 vs T1-T2 ) 2.03(1.08-3.80) 0.03 2.29(1.15-4.58) 0.02 N stage ( N1-N3 vs N0 ) 3.46(1.66-7.23) 0.00 2.54(1.17-5.56) 0.02 CEA ( >5ng/ml vs ≤5ng/ml ) 2.37(1.25-4.48) 0.01 1.56(0.70-3.48) 0.27