Sun, Jing

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

483 Background: Heterogeneity exists in recurrence and survival among patients with intestinal-type gastric cancer (IGC). Nucleotyping is the alterations in chromatin organization. We sought to identify the prognostic utility of nucleotyping, tumor stroma ratio (TSR) and DNA ploidy in these patients. Methods: Radical resection of gastric carcinoma (> 15 LNs removed) was performed in 283 patients (stage I, n=73; stage II, n=102; stage III, n=108) at our university hospital between 2010 and 2018. Automated image cytometry tools were used to quantitatively measure nucleotyping, TSR and DNA ploidy. Cutpoints of nucleotyping and TSR were 0.044 and 50%, respectively. Associations of these features with clinicopathological characteristics, time-to-recurrence (TTR) and cancer specific survival (CSS) were analyzed by univariate and multivariate analysis. Results: Among 283 patients, chromatin heterogeneity, high TSR and non-diploid were significantly associated with larger tumor size, higher T and N stage, and poorer TTR and CSS at 5 years. In a Cox multivariable analysis, nucleotyping and TSR were independently associated with TTR and CSS (P＜0.05) (Table). The top three contributors to TTR were N stage (33.9%), nucleotying (29.7%) and TSR (25.5%). The top three contributors to CSS were N stage (35.6%), nucleotying (29.7%) and TSR (18.0%). As a combined variable, the percent relative contribution of nucleotyping and TSR ranked first for TTR and CSS (56.0%, 50.0%), ahead of N stage (33.4%, 34.6%) and TILs (8.4%, 10.6%). Conclusions: Nucleotyping and TSR were each significantly and independently associated with TTR and CSS, and their combined variable was more strongly prognostic than either alone. Cox multivariable analysis of TTR and CSS. Features TTR HR (95%CI) TTR P value CSS HR (95%CI) CSS P value Tumor size (>3cm vs ≤3cm) 1.10 (0.48-2.54) 0.83 0.77 (0.35-1.70) 0.56 T stage (T3-T4 vs T1-T2) 1.07 (0.46-2.49) 0.87 1.41 (0.53-3.76) 0.49 N stage (N2N3 vs N0N1) 2.84 (1.39-5.78) <0.01 7.69 (3.37-17.55) <0.01 Adjuvant Therapy (with vs without) 1.32 (0.72-2.40) 0.37 0.85 (0.48-1.52) 0.59 TB (high vs low) 1.29 (0.62-2.69) 0.50 1.61 (0.85-3.07) 0.15 TILs（low vs high） 1.73 (0.96-3.13) 0.07 1.90 (1.06-3.40) 0.03 Nucleotyping (Chromatin heterogeneous vs Chromatin homogeneous) 2.19 (1.21-3.99) 0.01 3.44 (1.96-6.03) <0.01 TSR (high vs low) 2.12 (1.16-3.82) 0.01 2.51 (1.43-4.41) <0.01 DNA ploidy (Non-diploid vs Diploid) 1.20 (0.55-2.63) 0.65 0.98 (0.44-2.15) 0.95 1 TTR, time-to-recurrence; 2 CSS, cancer specific survival.