Background and study aims: Qualified esophagogastroduodenoscopy (EGD) is a prerequisite for detecting upper gastrointestinal lesions especially early gastric cancer (EGC). Our previous report showed that artificial intelligence system could monitor blind spots during EGD. Here, we updated the system to a new one (named ENDOANGEL), verified its effectiveness on improving endoscopy quality and pre-tested its performance on detecting EGC in a multi-center randomized controlled trial. Patients and methods: ENDOANGEL was developed using deep convolutional neural networks and deep reinforcement learning. Patients undergoing EGD examination in 5 hospitals were randomly assigned to ENDOANGEL-assisted (EA) group or normal control (NC) group. The primary outcome was the number of blind spots. The second outcome includes performance of ENDOANGEL on predicting EGC in clinical setting. Results: 1,050 patients were recruited and randomized. 498 and 504 patients in EA and NC groups were respectively analyzed. Compared with NC, the number of blind spots was less (5.382±4.315 vs. 9.821±4.978, p<0.001) and the inspection time was prolonged (5.400±3.821 min vs. 4.379±3.907 min, p<0.001) in EA group. In the 498 patients from EA group, 196 gastric lesions with pathological results were identified. ENDOANGEL correctly predicted all 3 EGC (1 mucosal carcinoma and 2 high-grade neoplasia) and 2 advanced gastric cancer, with a per-lesion accuracy of 84.69%, sensitivity of 100% and specificity of 84.29% for detecting GC. Conclusions: The results of the multi-center study confirmed that ENDOANGEL is an effective and robust system to improve the quality of EGD and has the potential to detect EGC in real time.

BaCKgRoUND aND aIMS:The dynamic N6methyladenosine (m 6 A) mRNA modification is essential for acute stress response and cancer progression. Sublethal heat stress from insufficient radiofrequency ablation (IRFA) has been confirmed to promote HCC progression; however, whether m 6 A machinery is involved in IRFA-induced HCC recurrence remains open for study. appRoaCH aND ReSUltS: Using an IRFA HCC orthotopic mouse model, we detected a higher level of m 6 A reader YTH N6-methyladenosine RNA binding protein 1-3 (YTHDF1) in the sublethal-heat-exposed transitional zone close to the ablation center than that in the farther area. In addition, we validated the increased m 6 A modification and elevated YTHDF1 protein level in sublethal-heat-treated HCC cell lines, HCC patient-derived xenograft (PDX) mouse model, and patients' HCC tissues. Functionally, gain-of-function/lossof-function assays showed that YTHDF1 promotes HCC cell viability and metastasis. Knockdown of YTHDF1 drastically restrains the tumor metastasis evoked by sublethal heat treatment in tail vein injection lung metastasis and orthotopic HCC mouse models. Mechanistically, we found that sublethal heat treatment increases epidermal factor growth receptor (EGFR) m 6 A modification in the vicinity of the 5′ untranslated region and promotes its binding with YTHDF1, which enhances the translation of EGFR mRNA. The sublethalheat-induced up-regulation of EGFR level was further confirmed in the IRFA HCC PDX mouse model and patients' tissues. Combination of YTHDF1 silencing and EGFR inhibition suppressed the malignancies of HCC cells synergically. CoNClUSIoNS:The m 6 A-YTHDF1-EGFR axis promotes HCC progression after IRFA, supporting the rationale for targeting m 6 A machinery combined with EGFR inhibitors to suppress HCC metastasis after RFA. (Hepatology 2021;74:1339-1356). R adiofrequency ablation (RFA) is now recommended as one of the curative therapies for early-stage HCC by guidelines of the American Association for the Study of Liver

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