PIN1 promotes the metastasis of cholangiocarcinoma cells by RACK1-mediated phosphorylation of ANXA2.

BACKGROUND: Cholangiocarcinoma (CCA), a primary hepatobiliary malignancy, is characterized by a poor prognosis and a lack of effective treatments. Therefore, the need to explore novel therapeutic approaches is urgent. While the role of Peptidylprolyl Cis/Trans Isomerase, NIMA-Interacting 1 (PIN1) has been extensively studied in various tumor types, its involvement in CCA remains poorly understood. METHODS: In this study, we employed tissue microarray (TMA), reverse transcription-polymerase chain reaction (RT-PCR), and The Cancer Genome Atlas (TCGA) database to assess the expression of PIN1. Through in vitro and in vivo functional experiments, we investigated the impact of PIN1 on the adhesion and metastasis of CCA. Additionally, we explored downstream molecular pathways using RNA-seq, western blotting, co-immunoprecipitation, immunofluorescence, and mass spectrometry techniques. RESULTS: Our findings revealed a negative correlation between PIN1 overexpression and prognosis in CCA tissues. Furthermore, high PIN1 expression promoted CCA cell proliferation and migration. Mechanistically, PIN1 functioned as an oncogene by regulating ANXA2 phosphorylation, thereby promoting CCA adhesion. Notably, the interaction between PIN1 and ANXA2 was facilitated by RACK1. Importantly, pharmacological inhibition of PIN1 using the FDA-approved drug all-trans retinoic acid (ATRA) effectively suppressed the metastatic potential of CCA cells in a nude mouse lung metastasis model. CONCLUSION: Overall, our study emphasizes the critical role of the PIN1/RACK1/ANXA2 complex in CCA growth and functionality, highlighting the potential of targeting PIN1 as a promising therapeutic strategy for CCA.

Single-cell RNA-sequencing atlas reveals an FABP1-dependent immunosuppressive environment in hepatocellular carcinoma.

BACKGROUND: Single-cell RNA sequencing, also known as scRNA-seq, is a method profiling cell populations on an individual cell basis. It is particularly useful for more deeply understanding cell behavior in a complicated tumor microenvironment. Although several previous studies have examined scRNA-seq for hepatocellular carcinoma (HCC) tissues, no one has tested and analyzed HCC with different stages. METHODS: In this investigation, immune cells isolated from surrounding normal tissues and cancer tissues from 3 II-stage and 4 III-stage HCC cases were subjected to deep scRNA-seq. The analysis included 15 samples. We distinguished developmentally relevant trajectories, unique immune cell subtypes, and enriched pathways regarding differential genes. Western blot and co-immunoprecipitation were performed to demonstrate the interaction between fatty acid binding protein 1 (FABP1) and peroxisome proliferator-activated receptor gamma(PPARG). In vivo experiments were performed in a C57BL/6 mouse model of HCC established via subcutaneous injection. RESULTS: FABP1 was discovered to be overexpressed in tumor-associated macrophages (TAMs) with III-stage HCC tissues compared with II-stage HCC tissues. This finding was fully supported by immunofluorescence detection in significant amounts of HCC human samples. FABP1 deficiency in TAMs inhibited HCC progression in vitro. Mechanistically, FABP1 interacted with PPARG/CD36 in TAMs to increase fatty acid oxidation in HCC. When compared with C57BL/6 mice of the wild type, tumors in FABP1-/- mice consistently showed attenuation. The FABP1-/- group's relative proportion of regulatory T cells and natural killer cells showed a downward trend, while dendritic cells, M1 macrophages, and B cells showed an upward trend, according to the results of mass cytometry. In further clinical translation, we found that orlistat significantly inhibited FABP1 activity, while the combination of anti-programmed cell death 1(PD-1) could synergistically treat HCC progression. Liposomes loaded with orlistat and connected with IR780 probe could further enhance the therapeutic effect of orlistat and visualize drug metabolism in vivo. CONCLUSIONS: ScRNA-seq atlas revealed an FABP1-dependent immunosuppressive environment in HCC. Orlistat significantly inhibited FABP1 activity, while the combination of anti-PD-1 could synergistically treat HCC progression. This study identified new treatment targets and strategies for HCC progression, contributing to patients with advanced HCC from new perspectives.

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.

Imaging features based on CT and MRI for predicting prognosis of patients with intrahepatic cholangiocarcinoma: a single-center study and meta-analysis.

BACKGROUND: To evaluate the prognostic role of imaging features based on CT and MRI in intrahepatic cholangiocarcinoma (ICC). METHODS: Two hundred and four patients from a single-center database who underwent radical ICC surgery from 2010 to 2019 were enrolled in the study. Cox proportional hazard model was used for survival analysis of imaging features. A meta-analysis was performed to determine imaging features that predict overall survival (OS) and event-free survival (EFS) in ICC. RESULTS: In the CT group of the retrospective cohort, tumor multiplicity, infiltrative tumor margin, lymph node metastasis, enhancement pattern in hepatic arterial phase and tumor necrosis correlated with poorer EFS and OS; moreover, enhancing capsules, high carcinoembryonic antigen levels contributed to poor OS. In the MRI group, tumor multiplicity and enhancement pattern were prognostic factors for OS; tumor multiplicity and enhancement pattern resulted in poor EFS. A total of 13 articles containing 1822 patients with ICC were enrolled in the adjusted hazard ratios meta-analysis. The results showed that enhancement pattern and infiltrative tumor margin were predictors of OS and EFS, whereas bile duct invasion was a predictor of OS. CONCLUSIONS: Arterial enhancement patterns and tumor margin status were associated with both OS and EFS of ICC patients following resection.

Rim Enhancement and Peripancreatic Fat Stranding in Preoperative MDCT as Predictors for Occult Metastasis in PDAC Patients.

RATIONALE AND OBJECTIVE: To identify the radiological features and clinical biomarkers that could predict the occult metastasis (OM) of pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: This retrospective study included PDAC patients who were radiologically diagnosed resectable (R) or borderline resectable (BR) and underwent surgical exploration from January 2018 to December 2021. Depending on whether distant metastases were found during the exploration, patients were divided into OM and non-OM groups. Univariate and multivariable logistic regression analyses were performed to determine the radiological and clinical predictive factors for occult metastasis. Model performance was determined by discrimination and calibration. RESULTS: A total of 502 patients (median age, 64 years; interquartile range, 57-70 years; 294 men) were enrolled, among which 68 (13.5%) patients were found with distant metastases, with 45 liver-only, 19 peritoneal-only, four patients had both liver and peritoneal metastases. Rim enhancement and peripancreatic fat stranding were more frequent in the OM group than in the non-OM group. Tumor size (p = 0.028), tumor resectability (p = 0.031), rim enhancement (p < 0.001), peripancreatic fat stranding (p < 0.001) and level of CA125 (p = 0.021) were independent predictors of occult metastasis according to the multivariable analyses, and the areas under the curve (AUCs) of these characteristics were 0.703, 0.594, 0.638, 0.655, 0.631, respectively. The combined model showed the highest AUC of 0.823. CONCLUSIONS: Rim enhancement, peripancreatic fat stranding, tumor size, tumor resectability and level of CA125 are risk factors for OM of PDAC. The combined model of radiological and clinical features may help the preoperative prediction of OM in PDAC.

A comprehensive framework of the right posterior section for tailored anatomical liver resection based on three-dimensional simulation system.

Background: The anatomical right posterior sectionectomy (ARPS) is a technically challenging procedure. We aimed to develop and validate a novel framework of the right posterior section for a safe and tailored anatomical liver resection (ALR) based on a three-dimensional (3D) simulation system. Methods: 3D hepatectomy simulations of healthy participants who underwent contrast-enhanced computed tomography of the upper abdomen were retrospectively reviewed to develop the framework according to the relationship between the simulated plane determined by the right posterior portal pedicle (RPP) and the course of the right hepatic vein (RHV) trunk. The framework was validated in the practice of ARPS for hepatocellular carcinoma (HCC) prospectively. Results: Scans from 336 eligible participants were assessed. The framework was summarized into four types: normal, caudal-redundant, cranial-deficient, and combined types, accounting for 43.4% (146/336), 25.3% (85/336), 18.5% (62/336), and 12.8% (43/336) respectively. The caudal-redundant type was associated with the variable portal branches of the RPP or segment 6 branch across the ventral side of RHV. The mean aberrant volume proportion in type IIa was significantly greater than that in type IIb (P<0.001), which were 7.0%±3.5% and 4.4%±1.8% respectively. The cranial-deficient type was associated with the aberrant segment 7 portal pedicle originating from the right portal trunk or the dorsal portal branch of segment 8 crossing over to the RHV. The median aberrant volume proportion in type IIIa was significantly greater than that in type IIIb (P<0.001), which were 10.9% (8.5-13.3%) and 4.0% (3.0-6.1%), respectively. The combined type represented a combination of the caudal-redundant type and the cranial-deficient type. The framework provided instructions on tailored ARPS in 6 patients with HCC by maximizing lesion removal and functional liver remnant with favorable perioperative outcomes. Conclusions: Precise preoperative planning with an individualized surgical approach based on our framework allows safe anatomical liver resections for cases with lesions in the right posterior section.

Efficacy and safety of camrelizumab plus apatinib during the perioperative period in resectable hepatocellular carcinoma: a single-arm, open label, phase II clinical trial.

OBJECTIVE: This study aimed to assess the efficacy and safety of camrelizumab plus apatinib in patients with resectable hepatocellular carcinoma (HCC) as neoadjuvant therapy. METHODS: Initially, 20 patients with HCC were screened and 18 patients with resectable HCC were enrolled in this open-label, single-arm, phase II clinical trial. Patients received three cycles of neoadjuvant therapy including three doses of camrelizumab concurrent with apatinib for 21 days followed by surgery. Four to 8 weeks after surgery, patients received eight cycles of adjuvant therapy with camrelizumab in combination with apatinib. Major pathological reactions (MPR), complete pathological reactions (pCR), objective response rate (ORR), relapse-free survival (RFS), and adverse events (AE) were assessed. In addition, cancer tissue and plasma samples were collected before and after treatment, and genetic differences between responding and non-responding lesions were compared by tumor immune microenvironment (TIME) analysis, circulating tumor DNA (ctDNA) analysis and proteomics analysis. RESULTS: In 18 patients with HCC who completed neoadjuvant therapy, 3 (16.7%) and 6 (33.3%) patients with HCC reached ORR based on Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1 and modified RECIST criteria, respectively. Of the 17 patients with HCC who received surgical resection, 3 (17.6%) patients with HCC reported MPR and 1 (5.9%) patient with HCC achieved pCR. The 1-year RFS rate of the enrolled patients was 53.85% (95% CI: 24.77% to 75.99%). Grade 3/4 AEs were reported in 3 (16.7%) of the 18 patients, with the most common AEs being rash (11.1%), hypertension (5.6%), drug-induced liver damage (5.6%), and neutropenia (5.6%) in the preoperative phase. The 289 NanoString panel RNA sequencing showed that TIME cell infiltration especially dendritic cells (DCs) infiltration was better in responding tumors than in non-responding tumors. Our results of ctDNA revealed a higher positive rate (100%) among patients with HCC with stage IIb-IIIa disease. When comparing patients with pCR/MPR and non-MPR, we observed more mutations in patients who achieved pCR/MPR at baseline (6 mutations vs 2.5 mutations, p=0.025). Patients who were ctDNA positive after adjuvant therapy presented a trend of shorter RFS than those who were ctDNA negative. Proteomic analysis suggested that abnormal glucose metabolism in patients with multifocal HCC might be related to different sensitivity of treatment in different lesions. CONCLUSION: Perioperative camrelizumab plus apatinib displays a promising efficacy and manageable toxicity in patients with resectable HCC. DCs infiltration might be a predictive marker of response to camrelizumab and apatinib as well as patients' recurrence. ctDNA as a compose biomarker can predict pathological response and relapse. Abnormal glucose metabolism in patients with multifocal HCC may be related to different sensitivity of treatment in different lesions. TRIAL REGISTRATION NUMBER: NCT04297202.

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.

Surgical Strategy for Resecting Hepatocellular Carcinoma in the Caudate Lobe: Isolated or Combined Lobectomy? A Single-Center Study and Meta-Analysis.

BACKGROUND: Resection of hepatocellular carcinoma (HCC) originating in the caudate lobe remains challenging, while the optimal extent of resection is debated. We aimed to evaluate the relative benefits of combined caudate lobectomy (CCL) versus isolated caudate lobectomy (ICL) for caudate HCC. METHODS: Patients who underwent curative-intent resection for caudate HCC between January 2010 and December 2018 were identified from a single-center database. Surgical outcomes of the two strategy groups were analyzed before and after propensity score matching. A systematic review with meta-analysis was also performed to compare outcomes of CCL versus ICL for caudate HCC. RESULTS: A total of 28 patients were included: 11 in the CCL and 17 in the ICL group. Compared with ICL, the CCL group contained patients with larger tumors and a higher incidence of vascular invasion. After propensity score matching, 6 pairs of patients were selected. In the well-matched cohort, CCL demonstrated significantly improved recurrence-free survival (RFS) (P = 0.047) compared with ICL; no significant differences were noted for overall survival (OS), operation time, blood loss and morbidity rate. A total of 227 patients from nine eligible studies and ours were involved in the systematic review. Meta-analysis revealed that CCL provided better RFS (hazard ratio 0.54, 95% confidence interval 0.31-0.92) than ICL; no significant differences were observed in OS, operation time, blood loss and morbidity rate. CONCLUSION: CCL confers superior RFS over ICL without compromise of perioperative outcomes and should be prioritized for patients with caudate HCC when feasible, especially for those with large-sized tumors.

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.

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.

Inhibition of Glycogen Synthase Kinase 3ß Increases the Proportion and Suppressive Function of CD19+CD24hiCD27+ Breg Cells.

CD19+CD24hiCD27+ memory Breg cells exhibit decreased abundance in patients with chronic graft-versus-host disease (cGVHD) after liver transplantation and produce less IL-10 than those from patients without cGVHD and healthy donors. Due to the lack of Breg cells and the difficulty in expanding them in vitro, in mouse models and early human clinical trials, the adoptive transfer of Breg cells to autoimmune diseases is greatly restricted. Glycogen synthase kinase 3ß (GSK-3ß) is a multifunctional serine/threonine (ser/thr) protein kinase that can participate in B cell growth, metabolic activity, and proliferation. Phosphoprotein array analysis showed that p-GSK-3ß-s9 was highly expressed in mBreg cells. Furthermore, here, we demonstrated that GSK-3ß expression in mBreg cells is lower than that observed in B cells by flow cytometry. We found that the treatment of B cells with the specific GSK-3ß inhibitor SB216763 can significantly increase the proportion and immunosuppressive function of mBreg cells in vitro. Nuclear factor of activated T cells (NFAT) is one of a pivotal regulator of gene expression in adaptive immune system. Here, we observed that inhibition of GSK-3ß by SB216763 results in enhanced expression of NFATc1 in B cells, which is essential in regulating the ability of B cells to secrete IL-10. By constructing a xGVHD mouse model, we observed that SB216763-treated mBreg cells effectively prevent xenogeneic GVHD. Here we propose a novel strategy using SB216763 to inhibit GSK-3ß and then enhance the proportion and immunosuppressive function of mBreg cells by increasing the expression of NFATc1. This approach may be used as a therapy to ameliorate GVHD and inflammatory diseases.

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.

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.

The proportion of CD19+CD24hiCD27+ regulatory B cells predicts the occurrence of acute allograft rejection in liver transplantation.

BACKGROUND: Regulatory B cells (Bregs) play an essential role in inflammation and transplant tolerance. Several studies have reported a decreased number of Bregs in renal transplant patients with graft rejection. However, little is known about their role in the liver alloresponse. METHODS: To investigate whether the circulating Bregs have been associated with acute allograft rejection (AR) in liver transplantation patients, 19 patients receiving liver allografts from donation after cardiac death (DCD) donors were retrospectively studied. RESULTS: The postoperative proportions of circulating CD19+CD24hiCD38hi transitional Bregs (tBregs) and CD19+CD24hiCD27+ memory Bregs (mBregs) in patients diagnosed with AR (AR group) and other patients with stable allograft liver function (SF group) were evaluated using flow cytometry (FCM) analysis. Results showed that while no significant changes were found regarding both the tBreg and mBreg, proportions across all time points in the SF group, the AR group showed significantly decreased proportions of mBregs. All of the five AR patients responded fine to the treatments, and the proportions of mBregs increased significantly after anti-rejection therapies. In addition, AR was suspected in four recipients, but gradually they were diagnosed with hemolytic or obstructive jaundice and showed no decrease in the proportion of mBregs. CONCLUSIONS: For the first time, our results suggested the potential role of a decreased proportion of circulating mBregs in predicting AR in patients with post liver transplantation.

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.

A radiomics approach to predict lymph node metastasis and clinical outcome of intrahepatic cholangiocarcinoma.

OBJECTIVES: This study was conducted in order to establish and validate a radiomics model for predicting lymph node (LN) metastasis of intrahepatic cholangiocarcinoma (IHC) and to determine its prognostic value. METHODS: For this retrospective study, a radiomics model was developed in a primary cohort of 103 IHC patients who underwent curative-intent resection and lymphadenectomy. Radiomics features were extracted from arterial phase computed tomography (CT) scans. A radiomics signature was built based on highly reproducible features using the least absolute shrinkage and selection operator (LASSO) method. Multivariate logistic regression analysis was adopted to establish a radiomics model incorporating radiomics signature and other independent predictors. Model performance was determined by its discrimination, calibration, and clinical usefulness. The model was internally validated in 52 consecutive patients. RESULTS: The radiomics signature comprised eight LN-status-related features and showed significant association with LN metastasis in both cohorts (p < 0.001). A radiomics nomogram that incorporates radiomics signature and CA 19-9 level showed good calibration and discrimination in the primary cohort (AUC 0.8462) and validation cohort (AUC 0.8921). Promisingly, the radiomics nomogram yielded an AUC of 0.9224 in the CT-reported LN-negative subgroup. Decision curve analysis confirmed the clinical utility of this nomogram. High risk for metastasis portended significantly lower overall and recurrence-free survival than low risk for metastasis (both p < 0.001). The radiomics nomogram was an independent preoperative predictor of overall and recurrence-free survival. CONCLUSIONS: Our radiomics model provided a robust diagnostic tool for prediction of LN metastasis, especially in CT-reported LN-negative IHC patients, that may facilitate clinical decision-making. KEY POINTS: • The radiomics nomogram showed good performance for prediction of LN metastasis in IHC patients, particularly in the CT-reported LN-negative subgroup. • Prognosis of high-risk patients remains dismal after curative-intent resection. • The radiomics model may facilitate clinical decision-making and define patient subsets benefiting most from surgery.

Biliary Tract Cancer at CT: A Radiomics-based Model to Predict Lymph Node Metastasis and Survival Outcomes.

Purpose To evaluate a radiomics model for predicting lymph node (LN) metastasis in biliary tract cancers (BTCs) and to determine its prognostic value for disease-specific and recurrence-free survival. Materials and Methods For this retrospective study, a radiomics model was developed on the basis of a primary cohort of 177 patients with BTC who underwent resection and LN dissection between June 2010 and December 2016. Radiomic features were extracted from portal venous CT scans. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator method. Multivariable logistic regression model was adopted to establish a radiomics nomogram. Nomogram performance was determined by its discrimination, calibration, and clinical usefulness. The model was internally validated in 70 consecutive patients with BTC between January 2017 and February 2018. Results The radiomics signature, composed of three LN-status-related features, was associated with LN metastasis in primary and validation cohorts (P < .001). The radiomics nomogram that incorporated radiomics signature and CT-reported LN status showed good calibration and discrimination in primary cohort (area under the curve, 0.81) and validation cohort (area under the curve, 0.80). Patients at high risk of LN metastasis portended lower disease-specific and recurrence-free survival than did those at low risk after surgery (both P < .001). High-risk LN metastasis was an independent preoperative predictor of disease-specific survival (hazard ratio, 3.37; P < .001) and recurrence-free survival (hazard ratio, 1.98; P = .003). Conclusion A radiomics model derived from portal phase CT of the liver has good performance for predicting lymph node metastasis in biliary tract cancer and may help to improve clinical decision making. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Laghi and Voena in this issue.

Tip60 Suppresses Cholangiocarcinoma Proliferation and Metastasis via PI3k-AKT.

BACKGROUND/AIMS: Aberrant expression of Tip60 is associated with progression in many cancers. However, the role of Tip60 in cancer progression remains contradictory. The aim of this study was to investigate the clinical significance, biological functions and underlying mechanisms of Tip60 deregulation in cholangiocarcinoma (CCA) for the first time. METHODS: Quantitative real-time PCR (QRT-PCR), western blotting and immunohistochemistry staining (IHC) were carried out to measure Tip60 expression in CCA tissues and cell lines. Kaplan-Meier analysis and the log-rank test were used for survival analysis. In vitro, cell proliferation was evaluated by flow cytometry and CCK-8, colony formation, and EDU assays. Migration/ invasion was evaluated by trans-well assays. Phosphokinase array was used to confirm the dominant signal regulated by Tip60. Tumor growth and metastasis were demonstrated in vivo using a mouse model. RESULTS: Tip60 was notably downregulated in CCA tissues, which was associated with greater tumor size, venous invasion, and TNM stage. Down-regulation of Tip60 was associated with tumor progression and poorer survival in CCA patients. In vitro and in vivo studies demonstrated that Tip60 suppressed growth and metastasis throughout the progression of CCA. We further identified the PI3K/AKT pathway as a dominant signal of Tip60 and suggested that Tip60 regulated CCA cell proliferation and metastasis via PT3K-AKT pathway. Pearson analysis revealed that PTEN was positively correlated with the Tip60 level in CCA tissues. CONCLUSION: Tip60, as a tumor suppressor in CCA via the PI3K/AKT pathway, might be a promising therapeutic target or prognostic marker for CCA.