Purpose: This Phase II trial was objected to evaluate the efficacy and safety of adding fulvestrant to neoadjuvant chemotherapy in patients with estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)– locally advanced breast cancer (LABC). Additionally, the study aimed to investigate the association of 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) positron emission tomography (PET)–computed tomography (CT) and metabolites with efficacy. Materials and Methods: Fulvestrant and EC-T regimen were given to ER+/HER2– LABC patients before surgery. At baseline, patients received 18F-FES PET-CT scan, and plasma samples were taken for liquid chromatography–mass spectrometry analysis. The primary endpoint was objective response rate (ORR). Secondary endpoints included total pathologic complete response (tpCR) and safety. Results: Among the 36 patients enrolled, the ORR was 86.1%, the tpCR rate was 8.3%. The incidence of grade ≥ 3 treatment-emergent adverse events was 22%. The decrease in ER value in sensitive patients was larger than that in non-sensitive patients, as was Ki-67 (p < 0.05). The maximum standardized uptake value, mean standardized uptake values, total lesion ER expression of 18F-FES PET-CT in sensitive patients were significantly higher than those in non-sensitive patients (p < 0.05). Moreover, these parameters were significantly correlated with Miller and Payne grade and the change in ER expression before and after treatment (p < 0.05). Thirteen differential expressed metabolites were identified, which were markedly enriched in 19 metabolic pathways. Conclusion This regimen demonstrated acceptable toxicity and encouraging antitumor efficacy. 18F-FES PET-CT might serve as a tool to predict the effectiveness of this therapy. Altered metabolites or metabolic pathways might be associated with treatment response.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

Background: s/Aims: Anti-mitochondrial M2 antibody (AMA-M2) is a specific marker for primary biliary cholangitis (PBC) and it could be also present in non-PBC individuals. Methods: A total of 72,173 Chinese health check-up individuals tested AMA-M2, of which non-PBC AMA-M2 positive individuals were performed follow-up. Baseline data of both clinical characteristics and laboratory examinations were collected in all AMA-M2-positive individuals. Least absolute shrinkage and selection operator (LASSO) regression was performed to investigate the potential variables for developing PBC. Results: A total of 2,333 individuals were positive with AMA-M2. Eighty-two individuals had a medical history of PBC or fulfilled the diagnostic criteria of PBC at baseline, and 2,076 individuals were non-PBC. After a median follow-up of 6.6 years, 0.6% developed PBC, with an accumulative 5-year incidence rate of 0.5%. LASSO regression showed that levels of alkaline phosphatase (ALP), gamma-glutamyl transpeptidase (GGT), immunoglobulin M (IgM), eosinophilia proportion (EOS%), gamma globulin percentage, and hemoglobin (HGB) were potential variables for developing PBC. Multivariate Cox regression is used to construct a predictive model based on 7 selected variables, and time-dependent receiver operating characteristic analysis showed that the area under the curve of the prediction model at 3, 5, and 10 years were, respectively, 1.000, 0.875, and 0.917. Conclusions This study offers insights into the onset of PBC among individuals who tested positive for AMA-M2 during routine health check-ups. The prediction model based on ALP, GGT, IgM, EOS%, gamma globulin percentage, HGB, and sex has a certain predictive ability for the occurrence of PBC in this population.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Background/Aims: Metabolic dysfunction–associated steatotic liver disease (MASLD) is a chronic liver disease characterized by hepatic steatosis. Ubiquitin-specific protease 29 (USP29) plays pivotal roles in hepatic ischemiareperfusion injury and hepatocellular carcinoma, but its role in MASLD remains unexplored. Therefore, the aim of this study was to reveal the effects and underlying mechanisms of USP29 in MASLD progression. Methods: USP29 expression was assessed in liver samples from MASLD patients and mice. The role and molecular mechanism of USP29 in MASLD were assessed in high-fat diet-fed and high-fat/high-cholesterol diet-fed mice and palmitic acid and oleic acid treated hepatocytes. Results: USP29 protein levels were significantly reduced in mice and humans with MASLD. Hepatic steatosis, inflammation and fibrosis were significantly exacerbated by USP29 deletion and relieved by USP29 overexpression. Mechanistically, USP29 significantly activated the expression of genes related to fatty acid β-oxidation (FAO) under metabolic stimulation, directly interacted with long-chain acyl-CoA synthase 5 (ACSL5) and repressed ACSL5 degradation by increasing ACSL5 K48-linked deubiquitination. Moreover, the effect of USP29 on hepatocyte lipid accumulation and MASLD was dependent on ACSL5. Conclusions USP29 functions as a novel negative regulator of MASLD by stabilizing ACSL5 to promote FAO. The activation of the USP29-ACSL5 axis may represent a potential therapeutic strategy for MASLD.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.