Differentiation and immunosuppressive function of CD19+CD24hiCD27+ regulatory B cells are regulated through the miR-29a-3p/NFAT5 pathway.

BACKGROUND: Regulatory B cells (Bregs) is an indispensable element in inducing immune tolerance after liver transplantation. As one of the microRNAs (miRNAs), miR-29a-3p also inhibits translation by degrading the target mRNA, and yet the relationship between Bregs and miR-29a-3p has not yet been fully explored. This study aimed to investigate the impact of miR-29a-3p on the regulation of differentiation and immunosuppressive functions of memory Bregs (mBregs) and ultimately provide potentially effective therapies in inducing immune tolerance after liver transplantation. METHODS: Flow cytometry was employed to determine the levels of Bregs in peripheral blood mononuclear cells. TaqMan low-density array miRNA assays were used to identify the expression of different miRNAs, electroporation transfection was used to induce miR-29a-3p overexpression and knockdown, and dual luciferase reporter assay was used to verify the target gene of miR-29a-3p. RESULTS: In patients experiencing acute rejection after liver transplantation, the proportions and immunosuppressive function of mBregs in the circulating blood were significantly impaired. miR-29a-3p was found to be a regulator of mBregs differentiation. Inhibition of miR-29a-3p, which targeted nuclear factor of activated T cells 5 (NFAT5), resulted in a conspicuous boost in the differentiation and immunosuppressive function of mBregs. The inhibition of miR-29a-3p in CD19+ B cells was capable of raising the expression levels of NFAT5, thereby promoting B cells to differentiate into mBregs. In addition, the observed enhancement of differentiation and immunosuppressive function of mBregs upon miR-29a-3p inhibition was abolished by the knockdown of NFAT5 in B cells. CONCLUSIONS: miR-29a-3p was found to be a crucial regulator for mBregs differentiation and immunosuppressive function. Silencing miR-29a-3p could be a potentially effective therapeutic strategy for inducing immune tolerance after liver transplantation.

Apolipoprotein A-1 Accelerated Liver Regeneration Through Regulating Autophagy Via AMPK-ULK1 Pathway.

BACKGROUND & AIMS: Apolipoprotein A-1 (ApoA-1), the main apolipoprotein of high-density lipoprotein, has been well studied in the area of lipid metabolism and cardiovascular diseases. In this project, we clarify the function and mechanism of ApoA-1 in liver regeneration. METHODS: Seventy percent of partial hepatectomy was applied in male ApoA-1 knockout mice and wild-type mice to investigate the effects of ApoA-1 on liver regeneration. D-4F (ApoA-1 mimetic peptide), autophagy activator, and AMPK activator were used to explore the mechanism of ApoA-1 on liver regeneration. RESULTS: We demonstrated that ApoA-1 levels were highly expressed during the early stage of liver regeneration. ApoA-1 deficiency greatly impaired liver regeneration after hepatectomy. Meanwhile, we found that ApoA-1 deficiency inhibited autophagy during liver regeneration. The activation of autophagy protected against ApoA-1 deficiency in inhibiting liver regeneration. Furthermore, ApoA-1 deficiency impaired autophagy through AMPK-ULK1 pathway, and AMPK activation significantly improved liver regeneration. The administration of D-4F could accelerated liver regeneration after hepatectomy. CONCLUSIONS: These findings suggested that ApoA-1 played an essential role in liver regeneration through promoting autophagy in hepatocytes via AMPK-ULK1 pathway. Our findings enrich the understanding of the underlying mechanism of liver regeneration and provide a potential therapeutic strategy for liver injury.

Translating imaging traits of mass-forming intrahepatic cholangiocarcinoma into the clinic: From prognostic to therapeutic insights.

Background & Aims: The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour underlying imaging traits. We developed and validated imaging-based prognostic systems for resected MICCs with an appraisal of the tumour immune microenvironment (TIME) underpinning patient-specific imaging traits. Methods: Between January 2009 and December 2019, a total of 322 patients who underwent dynamic computed tomography/magnetic resonance imaging and curative-intent resection for MICC at three hepatobiliary institutions were retrospectively recruited, divided into training (n = 193) and validation (n = 129) datasets. Two radiological and clinical scoring (RACS) systems, one integrating preoperative variables and one integrating preoperative and postoperative variables, were developed using Cox regression analysis. We then prospectively analysed the TIME of tissue samples from 20 patients who met study criteria from January 2021 to December 2021 using multiplexed immunofluorescence. Results: Preoperative and postoperative MICC-RACS systems built on carbohydrate antigen 19-9, albumin, tumour number, radiological/pathological nodal status, pathological necrosis, and three radiological traits (arterial enhancement pattern, tumour boundary, and capsular retraction) demonstrated good performance in predicting disease-specific (C-statistic >0.80) and disease-free (C-statistic >0.75) survival that outperformed rival models and staging systems across study cohorts (P <0.05 for all). Patients with MICC-RACS score of 0-2 (low risk), 3-5 (medium risk), and ≥6 (high risk) had incrementally worse prognosis after surgery. Significant differences in spatial distribution and infiltration level of immune cells were identified between arterial enhancement patterns. Enhanced infiltration of immunosuppressive regulatory T cells and M2-like macrophages at the invasive margin were noted in tumours with distinct boundary and capsular retraction, respectively. Conclusions: Our MICC-RACS systems are simple but powerful prognostic tools that may facilitate the understanding of spatially distinct TIMEs and patient-tailored immunotherapy approach. Impact and Implications: The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour of MICC underlying imaging traits. In this study, we proposed novel and easy-to-use tools, built on radiological and clinical features, that demonstrated good performance in predicting the prognosis either before or after surgery and outperformed rival models/systems across major imaging modalities. The characteristic radiological traits integrated into prognostic systems (arterial enhancement pattern, tumour boundary, and capsular retraction) were highly correlated with heterogeneous tumour-immune microenvironments, thereby renovating treatment paradigms for this difficult-to-treat disease.

Apolipoprotein A-1 protected hepatic ischaemia-reperfusion injury through suppressing macrophage pyroptosis via TLR4-NF-κB pathway.

BACKGROUND AND AIMS: Apolipoprotein A-1 (ApoA-1), the major apolipoprotein of high-density lipoprotein, plays anti-atherogenic role in cardiovascular diseases and exerts anti-inflammation effect in various inflammatory and infectious diseases. However, the role and mechanism of ApoA-1 in hepatic ischaemia-reperfusion (I/R) injury is unknown. METHODS: In this study, we measured ApoA-1 expression in human liver grafts after transplantation. Mice partial hepatic I/R injury model was made in ApoA-1 knockout mice, ApoA-1 mimetic peptide D-4F treatment mice and corresponding control mice to examine the effect of ApoA-1 on liver damage, inflammation response and cell death. Primary hepatocytes and macrophages were isolated for in vitro study. RESULTS: The results showed that ApoA-1 expression was down-regulated in human liver grafts after transplantation and mice livers subjected to hepatic I/R injury. ApoA-1 deficiency aggravated liver damage and inflammation response induced by hepatic I/R injury. Interestingly, we found that ApoA-1 deficiency increased pyroptosis instead of apoptosis during acute phase of hepatic I/R injury, which mainly occurred in macrophages rather than hepatocytes. The inhibition of pyroptosis compensated for the adverse impact of ApoA-1 deficiency. Furthermore, the up-regulated pyroptosis process was testified to be mediated by ApoA-1 through TLR4-NF-κB pathway and TLR4 inhibition significantly improved hepatic I/R injury. In addition, we confirmed that D-4F ameliorated hepatic I/R injury. CONCLUSIONS: Our study has identified the protective role of ApoA-1 in hepatic I/R injury through inhibiting pyroptosis in macrophages via TLR4-NF-κB pathway. The effect of ApoA-1 may provide a novel therapeutic approach for hepatic I/R injury.

Pemigatinib in previously treated Chinese patients with locally advanced or metastatic cholangiocarcinoma carrying FGFR2 fusions or rearrangements: A phase II study.

OBJECTIVE: This study evaluated the antitumor activity and safety of pemigatinib in previously treated Chinese patients with advanced cholangiocarcinoma and fibroblast growth factor receptor 2 (FGFR2) fusions or rearrangements. BACKGROUND: Pemigatinib provided clinical benefits for previously treated patients with cholangiocarcinoma carrying FGFR2 fusions or rearrangements and was approved for this indication in multiple countries. METHODS: In this ongoing, multicenter, single-arm, phase II study, adult patients with locally advanced or metastatic cholangiocarcinoma carrying centrally confirmed FGFR2 fusions or rearrangements who had progressed on ≥1 systemic therapy received 13.5 mg oral pemigatinib once daily (3-week cycle; 2 weeks on, 1 week off) until disease progression, unacceptable toxicity, or consent withdrawal. The primary endpoint was objective response rate (ORR) assessed by an independent radiology review committee. RESULTS: As of January 29, 2021, 31 patients were enrolled. The median follow-up was 5.1 months (range, 1.5-9.3). Among 30 patients with FGFR2 fusions or rearrangements evaluated for efficacy, 15 patients achieved partial response (ORR, 50.0%; 95% confidence interval [CI], 31.3-68.7); 15 achieved stable disease, contributing to a disease control rate of 100% (95% CI, 88.4-100). The median time to response was 1.4 months (95% CI, 1.3-1.4), the median duration of response was not reached, and the median progression-free survival was 6.3 months (95% CI, 4.9-not estimable [NE]). Eight (25.8%) of 31 patients had ≥grade 3 treatment-emergent adverse events. Hyperphosphatemia, hypophosphatasemia, nail toxicities, and ocular disorders were mostly

CT-based clinico-radiological nomograms for prognosis prediction in patients with intrahepatic mass-forming cholangiocarcinoma: a multi-institutional study.

OBJECTIVES: To establish prognostic nomograms based on CT imaging features for predicting the prognosis in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) before and after surgery. METHODS: Two models were established for overall survival (OS) prediction in a training set (179 IMCC patients underwent surgery at institution 1 from 2009 to 2019): imaging-based nomogram included imaging features and clinical characteristics acquired before surgery; postoperative nomogram included imaging-based score, equal to the linear predictor of the imaging-based nomogram, and pathological parameters. Both prognostic nomograms were validated in an independent external dataset (103 IMCC patients received surgical treatment at two independent institutions from 2009 to 2019). Predictive performance and discrimination were evaluated and compared with the common prognostic models. RESULTS: The imaging-based nomogram was developed according to preoperative serum carbohydrate antigen 19-9 and four imaging features including multiple nodules, arterial enhancement pattern, CT-reported lymph node (LN) metastasis, and capsular retraction; the postoperative nomogram was built based on the imaging-based score and three pathological parameters including tumor differentiation grade, capsular invasion, and LN status. Both nomograms presented improved prognostic performance and discrimination (concordance index, 0.770-0.812; integrated Brier score, 0.120-0.138) compared with the common prognostic models in the training and external validation datasets. Besides, the nomograms stratified IMCC patients into two risk strata for OS. CONCLUSIONS: Nomograms based on CT imaging features can provide accurate individual survival prediction for IMCC patients before and after surgery, which may help to improve personalized treatment. KEY POINTS: • Imaging features including multiple nodules, arterial enhancement pattern, CT-reported LN metastasis, and capsular retraction were poor independent prognostic factors for IMCC patients. • The imaging-based nomograms presented improved prognostic performance and discrimination compared with the common prognostic models. • The nomograms can provide accurate individual survival prediction for IMCC patients before and after surgery.

Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.

BACKGROUND: Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival in resected ICC based on readily-available clinical parameters using machine learning technique. METHODS: A gradient boosting machine (GBM) was trained and validated to predict the likelihood of cancer-specific survival (CSS) on data from a Chinese hospital-based database using nested cross-validation, and then tested on the Surveillance, Epidemiology, and End Results (SEER) database. The performance of GBM model was compared with that of proposed prognostic score and staging system. RESULTS: A total of 1050 ICC patients (401 from China and 649 from SEER) treated with resection were included. Seven covariates were identified and entered into the GBM model: age, tumor size, tumor number, vascular invasion, number of regional lymph node metastasis, histological grade, and type of surgery. The GBM model predicted CSS with C-Statistics ≥ 0.72 and outperformed proposed prognostic score or system across study cohorts, even in sub-cohort with missing data. Calibration plots of predicted probabilities against observed survival rates indicated excellent concordance. Decision curve analysis demonstrated that the model had high clinical utility. The GBM model was able to stratify 5-year CSS ranging from over 54% in low-risk subset to 0% in high-risk subset. CONCLUSIONS: We trained and validated a GBM model that allows a more accurate estimation of patient survival after resection compared with other prognostic indices. Such a model is readily integrated into a decision-support electronic health record system, and may improve therapeutic strategies for patients with resected ICC.

Machine Learning to Improve Prognosis Prediction of Early Hepatocellular Carcinoma After Surgical Resection.

BACKGROUND: Improved prognostic prediction is needed to stratify patients with early hepatocellular carcinoma (EHCC) to refine selection of adjuvant therapy. We aimed to develop a machine learning (ML)-based model to predict survival after liver resection for EHCC based on readily available clinical data. METHODS: We analyzed data of surgically resected EHCC (tumor≤5 cm without evidence of extrahepatic disease or major vascular invasion) patients from the Surveillance, Epidemiology, and End Results (SEER) Program to train and internally validate a gradient-boosting ML model to predict disease-specific survival (DSS). We externally tested the ML model using data from 2 Chinese institutions. Patients treated with resection were matched by propensity score to those treated with transplantation in the SEER-Medicare database. RESULTS: A total of 2778 EHCC patients treated with resection were enrolled, divided into 1899 for training/validation (SEER) and 879 for test (Chinese). The ML model consisted of 8 covariates (age, race, alpha-fetoprotein, tumor size, multifocality, vascular invasion, histological grade and fibrosis score) and predicted DSS with C-Statistics >0.72, better than proposed staging systems across study cohorts. The ML model could stratify 10-year DSS ranging from 70% in low-risk subset to 5% in high-risk subset. Compared with low-risk subset, no remarkable survival benefits were observed in EHCC patients receiving transplantation before and after propensity score matching. CONCLUSION: An ML model trained on a large-scale dataset has good predictive performance at individual scale. Such a model is readily integrated into clinical practice and will be valuable in discussing treatment strategies.

Current Progress and Future Perspectives of Immune Checkpoint Inhibitors in Biliary Tract Cancer.

Biliary tract cancer (BTC) is an uncommon and aggressive neoplasm, with most patients presenting in an advanced stage. Systemic chemotherapy is the limited treatment available but is unsatisfactory, while targeted therapy is still awaiting validation from clinical trials. Given the potential effect of immune checkpoint inhibitors (ICIs) in the treatment of BTC, this review aims to summarize the evidence-based benefits and predictive biomarkers for using inhibitors of cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) ligand, or programmed cell death protein-1 and its ligand (PD-1 and PD-L1) as monotherapy or combined with other anti-tumor therapies, while also pointing out certain pitfalls with the use of ICIs which need to be addressed.

BUB1B promotes extrahepatic cholangiocarcinoma progression via JNK/c-Jun pathways.

Currently, the controversy regarding the expression profile and function of BUB1B in different malignancies still exist. In this project, we aimed to explore the role and molecular mechanism of BUB1B in the progression of extrahepatic cholangiocarcinoma (ECC). The expression levels of BUB1B in human ECC were evaluated by immunohistochemistry, western blot, and real-time PCR. The role and mechanism of BUB1B in CCA cell proliferation and invasion were investigated in both in vitro and in vivo functional studies. To indicate the clinical significance, a tissue microarray was performed on 113 ECC patients, followed by univariate and multivariate analyses. The expression of BUB1B was increased in both human CCA tissues and CCA cells. Results from loss-of-function and gain-of-function experiments suggested that the inhibition of BUB1B decreased the proliferation and invasiveness of CCA cells in vitro and in vivo, while overexpression of BUB1B achieved the opposite effect. Furthermore, the activation of c-Jun N-terminal kinase-c-Jun (JNK)-c-Jun pathway was regulated by BUB1B. BUB1B regulated the proliferation and invasiveness of CAA cells in a JNK-c-Jun-dependent manner. Clinically, ECC patients with BUB1B high expression had worse overall survival and recurrence-free survival than those with BUB1B low expression. Multivariate analysis identified that BUB1B was an independent predictor for postoperative recurrence and overall survival of ECC patients. In conclusion, BUB1B promoted ECC progression via JNK/c-Jun pathways. These findings suggested that BUB1B could be a potential therapeutic target and a biomarker for predicting prognosis for ECC patients.

Integrating Machine Learning and Tumor Immune Signature to Predict Oncologic Outcomes in Resected Biliary Tract Cancer.

BACKGROUND: Improved methods are needed to predict outcomes in biliary tract cancers (BTCs). We aimed to build an immune-related signature and establish holistic models using machine learning. METHODS: Samples were from 305 BTC patients treated with curative-intent resection, divided into derivation and validation cohorts in a two-to-one ratio. Spatial resolution of T cell infiltration and PD-1/PD-L1 expression was assessed by immunohistochemistry. An immune signature was constructed using classification and regression tree. Machine learning was applied to develop prediction models for disease-specific survival (DSS) and recurrence-free survival (RFS). RESULTS: The immune signature composed of CD3+, CD8+, and PD-1+ cell densities and PD-L1 expression within tumor epithelium significantly stratified patients into three clusters, with median DSS varying from 11.7 to 80.8 months and median RFS varying from 6.2 to 62.0 months. Gradient boosting machines (GBM) outperformed rival machine-learning algorithms and selected the same 11 covariates for DSS and RFS prediction: immune signature, tumor site, age, bilirubin, albumin, carcinoembryonic antigen, cancer antigen 19-9, tumor size, tumor differentiation, resection margin, and nodal metastasis. The clinical-immune GBM models accurately predicted DSS and RFS, with respective concordance index of 0.776-0.816 and 0.741-0.781. GBM models showed significantly improved performance compared with tumor-node-metastasis staging system. CONCLUSIONS: The immune signature promises to stratify prognosis and allocate treatment in resected BTC. The clinical-immune GBM models accurately predict recurrence and death from BTC following surgery.

Development and Validation of Pre- and Post-Operative Models to Predict Recurrence After Resection of Solitary Hepatocellular Carcinoma: A Multi-Institutional Study.

BACKGROUND: The ideal candidates for resection are patients with solitary hepatocellular carcinoma (HCC); however, postoperative recurrence rate remains high. We aimed to establish prognostic models to predict HCC recurrence based on readily accessible clinical parameters and multi-institutional databases. PATIENTS AND METHODS: A total of 485 patients undergoing curative resection for solitary HCC were recruited from two independent institutions and the Cancer Imaging Archive database. We randomly divided the patients into training (n=323) and validation cohorts (n=162). Two models were developed: one using pre-operative and one using pre- and post-operative parameters. Performance of the models was compared with staging systems. RESULTS: Using multivariable analysis, albumin-bilirubin grade, serum alpha-fetoprotein and tumor size were selected into the pre-operative model; albumin-bilirubin grade, serum alpha-fetoprotein, tumor size, microvascular invasion and cirrhosis were selected into the postoperative model. The two models exhibited better discriminative ability (concordance index: 0.673-0.728) and lower prediction error (integrated Brier score: 0.169-0.188) than currently used staging systems for predicting recurrence in both cohorts. Both models stratified patients into low- and high-risk subgroups of recurrence with distinct recurrence patterns. CONCLUSION: The two models with corresponding user-friendly calculators are useful tools to predict recurrence before and after resection that may facilitate individualized management of solitary HCC.

FTY720 Suppresses Liver Tumor Growth and Metastasis by Reducing Circulating Regulating T Cells and Enhancing the Anti-Tumor Effect of Rapamycin.

BACKGROUND: In this study, we aimed to study the effect of FTY720 treatment in reducing circulating Tregs level and then suppressing liver tumor metastasis after hepatectomy and I/R injury in animal models. Furthermore, we also investigated the synergistic anti-tumor effect of FTY720 combined with rapamycin on hepatocellular carcinoma. METHODS: The effect of FTY720 on suppressing Tregs mobilization and tumor metastasis after hepatectomy was investigated in an orthotopic liver tumor rat model with hepatectomy and hepatic ischemia/reperfusion (I/R) injury. The synergistic anti-tumor effect of FTY720 combined with rapamycin was further explored both in in vitro functional study and in orthotopic liver tumor mouse model. RESULTS: In rat model, hepatic I/R promoted tumor metastasis and increased circulating Tregs after hepatectomy. The treatment of FTY720 reduced liver tumor metastasis and the number of circulating Tregs. Furthermore, FTY720 enhanced the anti-tumor capacity of rapamycin by inhibiting tumor cell proliferation and migration in vitro and reducing tumor growth in vivo through suppressing hepatic stellate cell activation and tumor angiogenesis. CONCLUSION: FTY720 suppressed liver tumor growth and metastasis by reducing the population of circulating Tregs and enhancing the anti-tumor effect of rapamycin. It was suggested that FTY720 single or combined with rapamycin might provide novel insight for suppressing tumor growth and metastasis for HCC patients.

MiR-30a-5p promotes cholangiocarcinoma cell proliferation through targeting SOCS3.

Background: MicroRNAs (miRNAs) play important roles in the occurrence and development of cancers. In this project, we aimed to explore the role and molecular mechanism of mir-30a-5p in cholangiocarcinoma (CCA). Materials and Methods: The expression profile and clinical significance of miR-30a-5p in CCA patients were investigated in 31 ICC and 52 ECC patients respectively. The role and mechanism of miR-30a-5p in CCA cells were investigated by up-regulating and inhibiting miR-30a-5p expression in vitro functional study. Results: The expression of miR-30a-5p was increased in both CCA tissues and cells. The inhibition of miR-30a-5p decreased cell proliferation and induced cell apoptosis while overexpression of miR-30a-5p achieved the opposite effect. Furthermore, SOCS3 was down-regulated in ICC and ECC tissues and negatively regulated by miR-30a-5p. Dual-luciferase reporter assay revealed that co-transfection of miR-30a-5p significantly inhibited the activity of firefly luciferase reporter carrying the wild-type 3'UTR of SOCS3. The inhibition of SOCS3 could largely rescue the inhibitory effect of miR-30a-5p inhibition on CCA cells proliferation. In clinical, up-regulated miR-30a-5p expression was correlated with large tumor size in both ICC and ECC cohorts. Conclusions: miR-30a-5p promoted CCA cells proliferation through targeting SOCS3. These findings suggested that miR-30a-5p could be a potential therapeutic target.

Surgical Strategies for the Treatment of Bismuth Type I and II Hilar Cholangiocarcinoma: Bile Duct Resection with or Without Hepatectomy?

BACKGROUND: The role of hepatic resection in the treatment of type I and II hilar cholangiocarcinoma (HCCA) remains controversial. In the present study, we aimed to identify whether hepatic resection was necessary for type I and II HCCA. METHODS: A total of 23 patients classified as type I and II HCCA undergoing surgical resection were included in this study. The patients were divided into two groups: bile duct resection (BDR) group (n = 15) and hepatic resection (HR) group (n = 8). Systematic review and meta-analysis were performed to compare the R0 resection and long-term survival between BDR and HR for Bismuth type I and II HCCA. A total of 7 studies with 260 cases were included in this meta-analysis. RESULTS: In our cohort, the R0 resection rate was 73.3% in BDR group and 87.5% in HR group. The HR group had a higher number of postoperative complications than the BDR group (P = 0.002). There was no difference in long-term survival (P = 0.544) and recurrence (P = 0.846) between BDR and HR in Bismuth type I and II HCCA. The meta-analysis showed that HR was associated with better R0 resection rate (RR 4.45, 95% CI 2.34-8.48) and overall survival (HR 2.15, 95% CI 1.34-3.44) compared with BDR group. There was no publication bias and undue influence of any single study. CONCLUSIONS: The meta-analysis showed that HR was associated with better R0 resection rate and overall survival compared with BDR for type I and II HCCA patients. More aggressive surgical strategies should be increasingly considered for the treatment of type I and II HCCA patients.

The Inhibition of Aldose Reductase Accelerates Liver Regeneration through Regulating Energy Metabolism.

OBJECTIVES: Our previous study showed that aldose reductase (AR) played key roles in fatty liver ischemia-reperfusion (IR) injury by regulating inflammatory response and energy metabolism. Here, we aim to investigate the role and mechanism of AR in the regeneration of normal and fatty livers after liver surgery. METHODS: The association of AR expression with liver regeneration was studied in the rat small-for-size liver transplantation model and the mice major hepatectomy and hepatic IR injury model with or without fatty change. The direct role and mechanism of AR in liver regeneration was explored in the AR knockout mouse model. RESULTS: Delayed regeneration was detected in fatty liver after liver surgery in both rat and mouse models. Furthermore, the expression of AR was increased in liver after liver surgery, especially in fatty liver. In a functional study, the knockout of AR promoted liver regeneration at day 2 after major hepatectomy and IR injury. Compared to wild-type groups, the expressions of cyclins were increased in normal and fatty livers of AR knockout mice. AR inhibition increased the expressions of PPAR-α and PPAR-γ in both normal liver and fatty liver groups after major hepatectomy and IR injury. In addition, the knockout of AR promoted the expressions of SDHB, AMPK, SIRT1, and PGC1-α and PPAR. CONCLUSIONS: The knockout of AR promoted the regeneration of normal and fatty livers through regulating energy metabolism. AR may be a new potential therapeutic target to accelerate liver regeneration after surgery.

Radiomic Features at Contrast-enhanced CT Predict Recurrence in Early Stage Hepatocellular Carcinoma: A Multi-Institutional Study.

Background Early stage hepatocellular carcinoma (HCC) is the ideal candidate for resection in patients with preserved liver function; however, cancer will recur in half of these patients and no reliable prognostic tool has been established. Purpose To investigate the effectiveness of radiomic features in predicting tumor recurrence after resection of early stage HCC. Materials and Methods In total, 295 patients (median age, 58 years; interquartile range, 50-65 years; 221 men) who underwent contrast material-enhanced CT and curative resection for early stage HCC that met the Milan criteria between February 2009 and December 2016 were retrospectively recruited from three independent institutions. Follow-up consisted of serum α-fetoprotein level, liver function tests, and dynamic imaging examinations every 3 months during the first 2 years and then every 6 months thereafter. In the development cohort of 177 patients from institution 1, recurrence-related radiomic features were computationally extracted from the tumor and its periphery and a radiomics signature was built with least absolute shrinkage and selection operator regression. Two models, one integrating preoperative and one integrating pre- and postoperative variables, were created by using multivariable Cox regression analysis. An independent external cohort of 118 patients from institutions 2 and 3 was used to validate the proposed models. Results The preoperative model integrated radiomics signature with serum α-fetoprotein level and tumor number; the postoperative model incorporated microvascular invasion and satellite nodules into the above-mentioned predictors. In both study cohorts, two radiomics-based models provided better predictive performance (concordance index ≥0.77, P < .05 for all), lower prediction error (integrated Brier score ≤0.14), and larger net benefits, as determined by means of decision curve analysis, than rival models without radiomics and widely adopted staging systems. The radiomics-based models gave three risk strata with high, intermediate, or low risk of recurrence and distinct profiles of recurrent tumor number. Conclusion The proposed radiomics models with pre- and postresection features helped predict tumor recurrence for early stage hepatocellular carcinoma. © RSNA, 2020 Online supplemental material is available for this article.

Preoperative Bilirubin Level Predicts Overall Survival and Tumor Recurrence After Resection for Perihilar Cholangiocarcinoma Patients.

OBJECTIVE: Currently, the correlation between preoperative bilirubin level and overall survival (OS) remains poorly defined in respectable perihilar cholangiocarcinoma (CC). The objectives of the current study were to evaluate the outcomes of perihilar CC after resection and then to analyze factors influencing curative resection, tumor recurrence and OS. METHODS: 115 patients with perihilar CC underwent surgical resection were retrospectively analyzed based on clinic characteristics, operative details, tumor recurrence and long-term survival data. RESULTS: The 1-, 3-, and 5-year OS rates after resection were 75.9%, 36.5%, 21.7%, whereas the corresponding tumor recurrence rates were 29.6%, 70.8%, 85.3%, respectively. Preoperative bilirubin level combined with liver resection, resection margin, vascular invasion and perineural invasion, lymph node metastasis and TNM stage were found to be correlated with OS and tumor recurrence. Multivariate analysis showed that preoperative bilirubin level together with resection margin, perineural invasion, and TNM stage were independent predictors of OS and tumor recurrence. Furthermore, preoperative bilirubin level was related with R0 resection, lymph node metastasis, TNM stage and postoperative liver function recovery. CONCLUSION: Preoperative bilirubin level may effectively reflect the severity of perihilar CC and predict the OS and tumor recurrence after resection for perihilar CC patients.

Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study.

BACKGROUND: Current guidelines recommend surgical resection as the first-line option for patients with solitary hepatocellular carcinoma (HCC); unfortunately, postoperative recurrence rate remains high and there is no reliable prediction tool. We explored the potential of radiomics coupled with machine-learning algorithms to improve the predictive accuracy for HCC recurrence. METHODS: A total of 470 patients who underwent contrast-enhanced CT and curative resection for solitary HCC were recruited from 3 independent institutions. In the training phase of 210 patients from Institution 1, a radiomics-derived signature was generated based on 3384 engineered features extracted from primary tumor and its periphery using aggregated machine-learning framework. We employed Cox modeling to build predictive models. The models were then validated using an internal dataset of 107 patients and an external dataset of 153 patients from Institution 2 and 3. FINDINGS: Using the machine-learning framework, we identified a three-feature signature that demonstrated favorable prediction of HCC recurrence across all datasets, with C-index of 0.633-0.699. Serum alpha-fetoprotein, albumin-bilirubin grade, liver cirrhosis, tumor margin, and radiomics signature were selected for preoperative model; postoperative model incorporated satellite nodules into above-mentioned predictors. The two models showed superior prognostic performance, with C-index of 0.733-0.801 and integrated Brier score of 0.147-0.165, compared with rival models without radiomics and widely used staging systems (all P < 0.05); they also gave three risk strata for recurrence with distinct recurrence patterns. INTERPRETATION: When integrated with clinical data sources, our three-feature radiomics signature promises to accurately predict individual recurrence risk that may facilitate personalized HCC management.