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Background Checkpoint-blockade immunotherapy targeting programmed cell death protein 1 (PD-1) has recently shown promising efficacy in hepatocellular carcinoma (HCC). However, the factors affecting and predicting the response to anti-PD-1 immunotherapy in HCC are still unclear. Herein, we report the dynamic variation characteristics and specificities of the gut microbiome during anti-PD-1 immunotherapy in HCC using metagenomic sequencing. Results Fecal samples from patients responding to immunotherapy showed higher taxa richness and more gene counts than those of non-responders. For dynamic analysis during anti-PD-1 immunotherapy, the dissimilarity of beta diversity became prominent across patients as early as Week 6. In non-responders, Proteobacteria increased from Week 3, and became predominant at Week 12. Twenty responder-enriched species, including Akkermansia muciniphila and Ruminococcaceae spp., were further identified. The related functional genes and metabolic pathway analysis, such as carbohydrate metabolism and methanogenesis, verified the potential bioactivities of responder-enriched species. Conclusions Gut microbiome may have a critical impact on the responses of HCC patients treated with anti-PD-1 immunotherapy. The dynamic variation characteristics of the gut microbiome may provide early predictions of the outcomes of immunotherapy in HCC, which is critical for disease-monitoring and treatment decision-making. Electronic supplementary material The online version of this article (10.1186/s40425-019-0650-9) contains supplementary material, which is available to authorized users.

Along with the deepening development in communication technologies and the surge of mobile devices, a brandnew computation paradigm, Edge Computing, is surging in popularity. Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the upgrade of hardware architectures. Billions of bytes of data, generated at the network edge, put great demands on data processing and structural optimization. Therefore, there exists a strong demand to integrate Edge Computing and AI, which gives birth to Edge Intelligence. In this article, we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge). The former focuses on providing a more optimal solution to the key concerns in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on edge. This article focuses on giving insights into this new inter-disciplinary field from a broader vision and perspective. It discusses the core concepts and the research road-map, which should provide the necessary background for potential future research programs in Edge Intelligence.

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Few studies on risk factors for and transmission of Clostridium difficile infection (CDI) in China have been reported. A cross-sectional study was conducted for 3 years in eastern China. Consecutive stool specimens from hospitalized patients with diarrhea were cultured for C. difficile. C. difficile isolates from these patients then were analyzed for toxin genes, genotypes, and antimicrobial resistance. A severity score for the CDI in each patient was determined by a blinded review of the medical record, and these scores ranged from 1 to 6. A total of 397 out of 3,953 patients (10.0%) with diarrhea were found to have CDI. Severity of CDI was mild to moderate, and the average (Ϯ standard deviation) severity score was 2.61 Ϯ 1.01. C. difficile was isolated from stool specimens in 432 (10.9%) of all the patients who had diarrhea. C. difficile genotypes were determined by multilocus sequence analysis and PCR ribotyping; sequence type 37 (ST37)/ribotype 017 (RT017) (n ϭ 68, 16.5%) was the dominant genotype. Eleven patients (16.2%) with this genotype had a CDI severity score of 5. Overall, three RTs and four STs were predominant; these genotypes were associated with significantly different antimicrobial resistance patterns in comparison to all genotypes ( 2 ϭ 79.56 to 97.76; P Ͻ 0.001). Independent risk factors associated with CDI included age greater than 55 years (odds ratio . CDI is clearly a problem in eastern China and has a prevalence of 10.0% in hospitalized patients. Among risk factors for CDI, the advanced age threshold was younger for Chinese patients than that reported for patients in developed countries.[

Background: Association of immune-related adverse events with tumor response has been reported. Reactive cutaneous capillary endothelial proliferation (RCCEP) is the most common adverse event related to camrelizumab, an immune checkpoint inhibitor, but lack of comprehensive analyses. In this study, we conducted comprehensive analyses on RCCEP in advanced hepatocellular carcinoma (HCC) patients treated with camrelizumab monotherapy. Methods: Data were derived from a Chinese nationwide, multicenter phase 2 trial of camrelizumab in pre-treated advanced HCC. The occurrence, clinicopathological characteristics, and prognostic value of RCCEP were analyzed.

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383 Background: The anti–PD-1 antibody pembro showed efficacy and manageable safety in the global phase 2 KEYNOTE-224 and phase 3 KEYNOTE-240 studies of patients (pts) with previously treated advanced HCC, a population of high unmet need. KEYNOTE-394 is a randomized, double-blind, phase 3 study conducted in Asia to evaluate the efficacy and safety of pembro vs placebo, both given with BSC, as second-line therapy for previously treated advanced HCC (NCT03062358). Methods: Eligible pts in Asia with confirmed advanced HCC and progression on or intolerance to sorafenib or oxaliplatin-based chemotherapy were randomized 2:1 to pembro 200 mg or placebo Q3W for ≤35 cycles plus BSC per local guidelines. The primary endpoint was OS. Secondary endpoints were PFS, ORR, DOR, DCR, and TTP, all assessed per RECIST v1.1 by blinded independent central review, and safety. Treatment differences were assessed using the stratified log-rank test (OS and PFS) or the stratified Miettinen & Nurminen method (ORR). The P value boundary for OS superiority at final analysis (FA) was 0.019307. If OS was superior, PFS and ORR superiority at the second interim analysis (IA2; primary analysis timepoint for these endpoints) could be tested at boundaries of 0.013447 and 0.009139, respectively. Results: 453 pts were randomized to pembro (N = 300) or placebo (N = 153). Baseline characteristics were generally balanced between arms; 90.7% had received sorafenib as first-line therapy. As of the June 30, 2021 cutoff date for FA, median study follow-up was 33.8 mo (range 18.7-49.0). At FA, pembro significantly improved OS vs placebo (HR 0.79, 95% CI 0.63-0.99, P = 0.0180); median (95% CI) OS was 14.6 mo (12.6-18.0) for pembro vs 13.0 mo (10.5-15.1) for placebo and 24-mo OS rate was 34.3% vs 24.9%. At IA2, pembro significantly improved PFS (HR 0.74, 95% CI 0.60-0.92, P = 0.0032) and ORR (estimated difference 11.4%, 95% CI 6.7-16.0, P = 0.00004); median (95% CI) PFS was 2.6 mo (1.5-2.8) for pembro vs 2.3 mo (1.4-2.8) for placebo, 12-mo PFS rates were 15.9% vs 1.4%, and ORR was 12.7% vs 1.3%. At FA, ORR was 13.7% vs 1.3%, median DOR was 23.9 mo vs 5.6 mo, DCR was 52.7% vs 47.7%, and median TTP was 2.7 mo vs 1.7 mo (HR 0.72, 95% CI 0.58-0.90). At FA, treatment-related AEs occurred in 66.9% of pts in the pembro arm and 49.7% in the placebo arm, including 14.4% and 5.9% with grade 3-5 events. 3 pts (1.0%) in the pembro arm and 0 in the placebo arm died of treatment-related AEs. Conclusions: Pembro plus BSC significantly improved OS, PFS, and ORR compared with placebo plus BSC as second-line therapy for patients from Asia with advanced HCC. The pembro safety profile was as expected. Overall, results were consistent with those previously observed in KEYNOTE-224 and KEYNOTE-240 and thus add to the body of evidence supporting the use of pembro as second-line therapy for advanced HCC. Clinical trial information: NCT03062358.