Targeting pathogenic CD8+ tissue-resident T cells with chimeric antigen receptor therapy in murine autoimmune cholangitis.

Primary biliary cholangitis (PBC) is a cholestatic autoimmune liver disease characterized by autoreactive T cell response against intrahepatic small bile ducts. Here, we use Il12b-/-Il2ra-/- mice (DKO mice) as a model of autoimmune cholangitis and demonstrate that Cd8a knockout or treatment with an anti-CD8α antibody prevents/reduces biliary immunopathology. Using single-cell RNA sequencing analysis, we identified CD8+ tissue-resident memory T (Trm) cells in the livers of DKO mice, which highly express activation- and cytotoxicity-associated markers and induce apoptosis of bile duct epithelial cells. Liver CD8+ Trm cells also upregulate the expression of several immune checkpoint molecules, including PD-1. We describe the development of a chimeric antigen receptor to target PD-1-expressing CD8+ Trm cells. Treatment of DKO mice with PD-1-targeting CAR-T cells selectively depleted liver CD8+ Trm cells and alleviated autoimmune cholangitis. Our work highlights the pathogenic role of CD8+ Trm cells and the potential therapeutic usage of PD-1-targeting CAR-T cells.

Prognostic model for unresectable hepatocellular carcinoma treated with dual PD-1 and angiogenesis blockade therapy.

BACKGROUND AND AIMS: Dual programmed death 1 (PD-1) and angiogenesis blockade therapy is a frontline treatment for hepatocellular carcinoma (HCC). An accepted model for survival prediction and risk stratification in individual patients receiving this treatment is lacking. Aimed to develop a simple prognostic model specific to these patients. APPROACH AND RESULTS: Patients with unresectable HCC undergoing dual PD-1 and angiogenesis blockade therapy were included in training cohort (n=168) and validation cohort (n=72). We investigated the prognostic value of clinical variables on overall survival using a Cox model in the training set. A prognostic score model was then developed and validated. Predictive performance and discrimination were also evaluated. Largest tumor size and Alpha-fetoprotein concentration at baseline and Neutrophil count and Spleen volume change after 6 weeks of treatment were identified as independent predictors of overall survival in multivariable analysis and used to develop LANS score. Time-dependent receiver operating characteristic analysis, calibration curves, and C-index showed LANS score had favorable performance in survival prediction. Patients were divided into three risk categories based on LANS score. Median survival for patients with low, intermediate, and high LANS scores was 31.7, 23.5, and 11.5 months, respectively (p<0.0001). The disease control rates were 96.4%, 64.3%, and 32.1%, respectively (p<0.0001). The predictive performance and risk stratification ability of the LANS score were confirmed in validation and entire cohorts. CONCLUSION: The LANS score model can provide individualized survival prediction and risk stratification in patients with unresectable HCC undergoing dual PD-1 and angiogenesis blockade therapy.

A novel clinical model for risk prediction and stratification of new-onset diabetes mellitus after distal pancreatectomy.

Background: The incidence of new-onset diabetes mellitus (NODM) after distal pancreatectomy (DP) remains high. Few studies have focused on NODM in patients with pancreatic benign or low-grade malignant lesions (PBLML). This study aimed to develop and validate an effective clinical model for risk prediction and stratification of NODM after DP in patients with PBLML. Methods: A follow-up survey was conducted to investigate NODM in patients without preoperative DM who underwent DP. Four hundred and forty-eight patients from Peking Union Medical College Hospital (PUMCH) and 178 from Guangdong Provincial People's Hospital (GDPH) met the inclusion criteria. They constituted the training cohort and the validation cohort, respectively. Univariate and multivariate Cox regression, as well as least absolute shrinkage and selection operator (LASSO) analyses, were used to identify the independent risk factors. The nomogram was constructed and verified. Concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis (DCA) were applied to assess its predictive performance and clinical utility. Accordingly, the optimal cut-off point was determined by maximally selected rank statistics method, and the cumulative risk curves for the high- and low-risk populations were plotted to evaluate the discrimination ability of the nomogram. Results: The median follow-up duration was 42.8 months in the PUMCH cohort and 42.9 months in the GDPH cohort. The postoperative cumulative 5-year incidences of DM were 29.1% and 22.1%, respectively. Age, body mass index (BMI), length of pancreatic resection, intraoperative blood loss, and concomitant splenectomy were significant risk factors. The nomogram demonstrated significant predictive utility for post-pancreatectomy DM. The C-indexes of the nomogram were 0.739 and 0.719 in the training and validation cohorts, respectively. ROC curves demonstrated the predictive accuracy of the nomogram, and the calibration curves revealed that prediction results were in general agreement with the actual results. The considerable clinical applicability of the nomogram was certified by DCA. The optimal cut-off point for risk prediction value was 2.88, and the cumulative risk curves of each cohort showed significant differences between the high- and low-risk groups. Conclusions: The nomogram could predict and identify the NODM risk population, and provide guidance to physicians in monitoring and controlling blood glucose levels in PBLML patients after DP.

Laboratory scoring system to predict hepatic indocyanine green clearance ability during fluorescence imaging-guided laparoscopic hepatectomy.

BACKGROUND: Indocyanine green (ICG) fluorescence played an important role in tumor localization and margin delineation in hepatobiliary surgery. However, the preoperative regimen of ICG administration was still controversial. Factors associated with tumor fluorescence staining effect were unclear. AIM: To investigate the preoperative laboratory indexes corelated with ICG fluorescence staining effect and establish a novel laboratory scoring system to screen specifical patients who need ICG dose adjustment. METHODS: To investigate the predictive indicators of ICG fluorescence characteristics in patients undergoing laparoscopic hepatectomy from January 2018 to January 2021 were included. Blood laboratory tests were completed within 1 wk before surgery. All patients received 5 mg ICG injection 24 h before surgery for preliminary tumor imaging. ImageJ software was used to measure the fluorescence intensity values of regions of interest. Correlation analysis was used to identify risk factors. A laboratory risk model was established to identify individuals at high risk for high liver background fluorescence. RESULTS: There were 110 patients who were enrolled in this study from January 2019 to January 2021. The mean values of fluorescence intensity of liver background (FI-LB), fluorescence intensity of gallbladder, and fluorescence intensity of target area were 18.87 ± 17.06, 54.84 ± 33.29, and 68.56 ± 36.11, respectively. The receiver operating characteristic (ROC) curve showed that FI-LB was a good indicator for liver clearance ability [area under the ROC curve (AUC) = 0.984]. Correlation analysis found pre-operative aspartate aminotransferase, alanine aminotransferase, gamma-glutamyl transpeptidase, adenosine deaminase, and lactate dehydrogenase were positively associated with FI-LB and red blood cell, cholinesterase, and were negatively associated with FI-LB. Total laboratory risk score (TLRS) was calculated according to ROC curve (AUC = 0.848, sensitivity = 0.773, specificity = 0.885). When TLRS was greater than 6.5, the liver clearance ability of ICG was considered as poor. CONCLUSION: Preoperative laboratory blood indicators can predict hepatic ICG clearance ability. Surgeons can adjust the dose and timing of ICG preoperatively to achieve better liver fluorescent staining.

Peripheral Th and NK cells are associated with response to lenvatinib plus PD-1 inhibitor in unresectable hepatocellular carcinoma.

The value of peripheral blood lymphocyte subpopulations in predicting responses to lenvatinib combination with programmed death-1 (PD-1) inhibitors in unresectable hepatocellular carcinoma (HCC) was investigated. Fifteen patients received objective responses (OR) and sixteen patients had non-objective responses (NOR) were analyzed. The counts of peripheral blood lymphocyte subpopulations from patients were measured before treatment, second (at week 3), and third doses (at week 6) of the PD-1 inhibitor administration, and correlated with responses. Helper T (Th) cells and natural killers (NK) cells were more abundant in the OR group and found to be important predictors of OR in a stepwise multivariate logistic regression analysis. These cutoff values of Th and NK cells could help to distinguish OR from NOR cases accurately and provide clinical benefits.

The characteristics of Laennec's capsule around the hepatic veins: A histological study based on 71 liver surgical specimens.

Background: Laennec's capsule is a fibrous membrane attached to the surface of the liver, which is independent of the hepatic veins. However, the presence of Laennec's capsule surrounding the peripheral hepatic veins is controversial. This study aims to describe the characteristic of Laennec's capsule around the hepatic veins at all levels. Methods: Seventy-one hepatic surgical specimens were collected along the cross and longitudinal sections of the hepatic vein. Tissue sections of 3-4 mm were cut and stained with hematoxylin and eosin (H&E), resorcinol-fuchsin (R&F), and Victoria blue (V&B). Elastic fibers were observed around the hepatic veins. They were measured using K-Viewer software. Results: Morphologically, we observed a thin, dense fibrous layer (so-called Laennec's capsule) around the hepatic veins at all levels, which was different from the thick elastic fibers of the hepatic vein wall. Therefore, there was a potential gap between Laennec's capsule and the hepatic veins. Laennec's capsule was visualized significantly better with R&F and V&B staining compared to H&E staining. The thickness of Laennec's capsule around the main, first, and secondary branches of the hepatic vein were 79.86 ± 24.20 µm, 48.41 ± 18.25 µm, and 23.56 ± 10.03 µm in the R&F staining, and 80.15 ± 21.85 µm, 49.46 ± 17.52 µm, and 25.05 ± 11.03 µm in the V&B staining, respectively. They were significantly different from each other (P < .001). Conclusion: The hepatic veins were surrounded by Laennec's capsule at all levels, including the peripheral hepatic veins. However, it is thinner along the vein branches. The gap between the Laennec's capsule and hepatic veins shows potential supplemental value for liver surgery.

Conversion surgery for advanced hepatocellular carcinoma after combination treatment of lenvatinib and camrelizumab: a case report.

BACKGROUND: Hepatocellular carcinoma (HCC) is an aggressive malignancy with high morbidity and mortality. Conversion therapy can improve surgical resection rate and prolong survival time for patients with advanced HCC. We show that combination therapy with lenvatinib and camrelizumab is a novel approach to downstage unresectable HCC. CASE PRESENTATION: A 49-year-old man was diagnosed with massive HCC with hilar lymph node and lung metastases. Since radical resection was not feasible, lenvatinib and camrelizumab were administered as first-line therapy. After 10 cycles of camrelizumab and continuous oral administration of lenvatinib, the tumor exhibited striking shrinkage in volume indicating a partial radiological response, accompanied by a reduction in the alpha-fetoprotein levels, followed by salvage resection. Intriguingly, an improvement in predictive biomarkers, like lactate dehydrogenase (LDH) and neutrophil-to-lymphocyte ratio (NLR), was observed. Notably, the pathological examination found high levels of necrosis in the resected tumor, and flow cytometry analysis indicated a significant increase in the ratio of CD5+ and CD5- B lymphocytes in the peripheral blood. After the treatment, the overall survival period was over 24 months, and no recurrence was observed 17-month post-surgery. CONCLUSIONS: A combination of lenvatinib and camrelizumab may be a new conversion therapy for initially unresectable HCC to resectable HCC, thus contributing to improve the disease prognosis. In addition, the combination regimen could cause an activated immune response, and LDH, NLR, and CD5+ B-cell levels might be predictors for immunotherapy efficacy.

Nomogram Based on Inflammatory Biomarkers to Predict the Recurrence of Hepatocellular Carcinoma-A Multicentre Experience.

Purpose: Our study aimed to identify inflammatory biomarkers and develop a prediction model to stratify high-risk patients for hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) recurrence after curative resection. Patients and Methods: A total of 583 eligible HBV-HCC patients with curative hepatectomy from Guangdong Provincial People's Hospital (GDPH) and Sun Ya-sen University Cancer Centre (SYSUCC) were enrolled in our study. Cox proportional hazards regression was utilized to evaluate potential risk factors for disease-free survival (RFS). The area under the receiver operating characteristic (ROC) curve (AUC) was utilized to assess the discrimination performance. Calibration plots and decision curve analyses (DCA) were used to evaluate the calibration of the nomogram and the net benefit, respectively. Results: Based on the systemic inflammation response index (SIRI), aspartate aminotransferase to neutrophil ratio index (ANRI), China Liver Cancer (CNLC) stage and microvascular invasion, a satisfactory nomogram was developed. The AUC of our nomogram for predicting 1-, 2-, and 3-year RFS was 0.767, 0.726, and 0.708 in the training cohort and 0.761, 0.716, and 0.715 in the validation cohort, respectively. Furthermore, our model demonstrated excellent stratification as well as clinical applicability. Conclusion: The novel nomogram showed a higher prognostic power for the RFS of HCC patients with curative hepatectomy than the CNLC, AJCC 8th edition and BCLC staging systems and may help oncologists identify high-risk HCC patients.

A Pyroptosis-Based Prognostic Model for Immune Microenvironment Estimation of Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC), an aggressive malignant tumor, has a high incidence and unfavorable prognosis. Recently, the synergistic effect of pyroptosis in antitumor therapy and regulation of tumor immune microenvironment has made it possible to become a novel therapeutic method, but its potential mechanism still needs further exploration. METHODS: Differentially expressed genes with prognostic value in Liver Hepatocellular Carcinoma Project of The Cancer Genome Atlas (TCGA-LIHC) cohort were screened and incorporated into the risk signature by Cox proportional hazards regression model and least absolute shrinkage and selection operator. Kaplan-Meier (KM) curves and receiver operating characteristic (ROC) curves were applied to conduct survival comparisons and estimate prediction ability. The dataset of Liver Cancer-RIKEN, Japan Project from International Cancer Genome Consortium (ICGC-LIRI-JP) cohort was used to verify the reliability of the signature. Correlation analysis between clinicopathological characteristics, immune infiltration, drug sensitivities, and risk scores was conducted. Functional annotation analyses were performed for the genes differentially expressed between high-risk and low-risk groups. RESULTS: A risk signature consisting of 6 pyroptosis-related genes in HCC was developed and validated. KM curves and ROC curves revealed its considerable predictive accuracy. Higher risk scores meant more advanced grade, higher alpha-fetoprotein level, and stronger invasive ability. Overexpressed genes in high-risk population were more enriched in the immune-associated pathways, and these patients might be more sensitive to immune checkpoint inhibitors instead of Sorafenib. Intriguingly, 6 identified genes were promising to be prognostic biomarkers and therapeutic targets of HCC. CONCLUSIONS: The signature may have crucial clinical significance in predicting survival prognosis, immune infiltration, and drug efficacy based on pyroptosis-related genes.

A novel prognostic signature based on four glycolysis-related genes predicts survival and clinical risk of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common cancer with limited cure and poor survival. In our study, a bioinformatic analysis was conducted to investigate the role of glycolysis in the pathogenesis and progression of HCC. METHODS: Single-sample gene set enrichment analysis (ssGESA) was used to calculate enrichment scores for each sample in TCGA-LIHC and GEO14520 according to the glycolysis gene set. Weighted gene co-expression network analysis identified a gene module closely related to glycolysis, and their function was investigated. Prognostic biomarkers were screened from these genes. Cox proportional hazard model and least absolute shrinkage and selection operator regression were used to construct the prognostic signature. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curve analyses evaluated the prediction performance of the prognostic signature in TCGA-LIHC and ICGC-LIRI-JP. Combination analysis data of clinical features and prognostic signature constructed a nomogram. Area under ROC curves and decision curve analysis were used to compare the nomogram and its components. RESULTS: The glycolysis pathway was upregulated in HCC and was unfavorable for survival. The determined gene module was mainly enriched in cell proliferation. A prognostic signature (CDCA8, RAB5IF, SAP30, and UCK2) was developed and validated. KM and ROC curves showed a considerable predictive effect. The risk score derived from the signature was an independent prognostic factor. The nomogram increased prediction efficiency by combining risk signature and TNM stage and performed better than component factors in net benefit. CONCLUSION: The gene signature may contribute to individual risk estimation, survival prognosis, and clinical management.

Functional anatomical hepatectomy guided by indocyanine green fluorescence imaging in patients with localized cholestasis: Report of four cases.

BACKGROUND: Liver cancer is a malignant tumor with a high incidence. At present, the most effective treatment is laparoscopic hepatectomy (LH). Indocyanine green fluorescence imaging (ICG-FI) has become an important tool in LH, and the most common fluorescent types of tumors are total fluorescence, partial fluorescence, and rim fluorescence. CASE SUMMARY: We presented four cases of LH guided by ICG-FI in which we also observed the fourth special fluorescent type. When the tumor or intrahepatic stone compresses the adjacent bile duct to cause local cholestasis, the liver segment or subsegment with obstructed bile drainage will show strong fluorescence. Complete removal of the lesion together with the fluorescent liver parenchyma may help reduce the risk of tumor or stone recurrence. CONCLUSION: This type of partial fluorescence can indicate local biliary compression, and the resection method is related to bile drainage, which may be called functional anatomical hepatectomy and ensures radical resection of the lesion.

Risk Signature Related to Immunotherapy Reaction of Hepatocellular Carcinoma Based on the Immune-Related Genes Associated With CD8+ T Cell Infiltration.

Background: Hepatocellular carcinoma (HCC) is the most common histological type of liver cancer, with an unsatisfactory long-term survival rate. Despite immune checkpoint inhibitors for HCC have got glories in recent clinical trials, the relatively low response rate is still a thorny problem. Therefore, there is an urgent need to screen biomarkers of HCC to predict the prognosis and efficacy of immunotherapy. Methods: Gene expression profiles of HCC were retrieved from TCGA, GEO, and ICGC databases while the immune-related genes (IRGs) were retrieved from the ImmPort database. CIBERSORT and WGCNA algorithms were combined to identify the gene module most related to CD8+ T cells in the GEO cohort. Subsequently, the genes in hub modules were subjected to univariate, LASSO, and multivariate Cox regression analyses in the TCGA cohort to develop a risk signature. Afterward, the accuracy of the risk signature was validated by the ICGC cohort, and its relationships with CD8+ T cell infiltration and PDL1 expression were explored. Results: Nine IRGs were finally incorporated into a risk signature. Patients in the high-risk group had a poorer prognosis than those in the low-risk group. Confirmed by TCGA and ICGC cohorts, the risk signature possessed a relatively high accuracy. Additionally, the risk signature was demonstrated as an independent prognostic factor and closely related to the CD8+ T cell infiltration and PDL1 expression. Conclusion: A risk signature was constructed to predict the prognosis of HCC patients and detect patients who may have a higher positive response rate to immune checkpoint inhibitors.

Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment.

BACKGROUND: Pancreatic adenocarcinoma (PaC) patients with positive lymph nodes (PLNs) have a dismal prognosis and lack a specific prognostic stage. This study aimed to construct a nomogram for the prediction of overall survival (OS) in these patients. METHODS: A total of 1,340 patients screened from the Surveillance, Epidemiology, and End Results database were included and randomly divided at a ratio of 7:3 into a training set (n=940) and an internal validation set (n=400). Cox regression analyses were conducted to select independent predictors in the training set, and a nomogram was constructed. The model was verified in the internal validation set and in an external validation set, which comprised 64 patients from a Chinese institute. RESULTS: Six independent prognostic factors (age at diagnosis, tumor grade, lymph node ratio, T stage, radiotherapy, and chemotherapy) were identified in PaC patients with PLNs and were entered into the nomogram. The final model had a higher C-index for predicting OS than the American Joint Committee on Cancer-8th edition staging system (training set: 0.658 vs. 0.546; internal validation set: 0.661 vs. 0.546; external validation set: 0.691 vs. 0.581). The 1-, 2-, and 3-year area under the receiver operating characteristic curve values indicated better discrimination power for the established nomogram with respect to the prediction of OS in the training, internal validation, and external validation sets than for the American Joint Committee on Cancer-8th edition staging system. Furthermore, the nomogram performed well in both calibration and decision curve analyses (DCA) of clinical applicability. OS in PaC patients with PLNs was significantly distinguished among the three risk groups stratified according to the nomogram score (P<0.001). CONCLUSIONS: The well-calibrated nomogram was determined to be extremely efficient in predicting survival, and defining a high-risk population based on the nomogram score among PaC patients with PLNs after surgery.

A Novel Blood Index-Based Model to Predict Hepatitis B Virus-Associated Hepatocellular Carcinoma Recurrence After Curative Hepatectomy: Guidance on Adjuvant Transcatheter Arterial Chemoembolization Choice.

BACKGROUND: Postoperative recurrence is a significant obstacle in hepatocellular carcinoma (HCC) treatment. This study aimed to construct a blood index-based model to predict hepatitis B virus-associated HCC (HBV-HCC) recurrence after curative hepatectomy. METHODS: A total of 370 patients who received initially curative hepatectomy for HBV-HCC were included in this study. A novel blood index signature (BIS) was identified and systematically analyzed for its recurrence predictive value. Following this, multivariate Cox regression analysis was performed to build a blood index-based nomogram. RESULTS: A BIS based on the aminotransferase-to-platelet ratio index and a systemic inflammatory response index was used to construct a nomogram. The model showed good clinical applicability and reliability. Notably, the patients in the high recurrence risk group tended to benefit from adjuvant transcatheter arterial chemoembolization (TACE). CONCLUSION: A reliable model was constructed to predict the HBV-HCC recurrence after curative hepatectomy. This model can guide the surgeons in selecting patients with high recurrence risk patients who may benefit from adjuvant TACE.

Construction of Nomograms for Predicting Lung and Bone Metastases in Patients with Intrahepatic Cholangiocarcinoma and Identification of Patients Who Can Benefit from Chemotherapy.

OBJECTIVE: The purpose of our study is to build nomograms for predicting the possibility of lung metastasis (LM) and bone metastasis (BM) in patients with intrahepatic cholangiocarcinoma (ICC). METHODS: 1527 patients diagnosed with ICC between 2010 and 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable logistic regression analyses were used to recognize the predictors of LM and BM, respectively. Then two nomograms were established. We applied the C-index, calibration plot, receiver-operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the novel nomograms. The maximum values of the Youden indexes from the ROC curves were utilized to select the cutoff points of the nomograms. The Kaplan-Meier survival curves were used to evaluate the effect of chemotherapy in different groups. The bootstrap resampling method was chosen for internal validation. RESULTS: Five predictors for LM and three predictors for BM were identified, and two nomograms were constructed. The nomograms had high values of C-indexes, reaching 0.821 (95% CI 0.772-0.871) for LM and 0.759 (95% CI 0.700-0.818) for BM. C-indexes of 0.814 for LM and 0.749 for BM were also observed in internal validation. The calibration plots, ROC curves, and DCAs exhibited favorable performances for predicting LM and BM. The cutoff points of total points in nomograms were 108 for LM and 144 for BM, which could distinguish between high-risk and low-risk groups for LM and BM. Chemotherapy is suggested to undergo for patients in high-risk groups. CONCLUSIONS: The nomograms could assess the possibility of LM and BM in ICC patients and determine the optimal treatment.

Development of a Nomogram to Predict Disease-Specific Survival for Patients After Resection of a Non-Metastatic Adenocarcinoma of the Pancreatic Body and Tail.

BACKGROUND: Models for predicting patient survival after resection of a non-metastatic adenocarcinoma of the pancreatic body and tail (APBT) are scarce. We wished to establish and validate a nomogram to predict disease-specific survival (DSS) of these patients. METHODS: A total of 1,435 patients screened from the Surveillance, Epidemiology, and End Results (SEER) database were included and divided randomly into a training set (TS; n = 1,007) and internal validation set (IVS; n = 428) at a ratio of 7:3. Cox regression analyses were conducted to select independent predictors in the TS, and a nomogram was constructed. The model was subjected to the IVS and an external validation set (EVS) comprising 151 patients from two tertiary hospitals. RESULTS: Five independent risk factors (age at the diagnosis, chemotherapy, tumor grade, T stage, and the lymph node radio) were identified and integrated into the nomogram. Calibration curves indicated that the nomogram could predict DSS at 1, 2, and 3 years accurately. The nomogram had a higher concordance index for predicting DSS compared with that using the 8th edition of the American Joint 23 Committee on Cancer (AJCC8) stage (TS: 0.681 vs. 0.606; IVS: 0.662 vs. 0.590; and EVS: 0.675 vs. 0.608). The nomogram had better discrimination ability and clinical utility than the AJCC8 stage for predicting 1-, 2-, and 3-year DSS. CONCLUSION: Our developed nomogram could accurately predict DSS in patients after resection of a non-metastatic APBT.

The role of hyperthermic intraperitoneal chemotherapy in the treatment of spontaneously ruptured hepatocellular carcinoma: a pilot study.

BACKGROUND: Spontaneous tumor rupture is a distinctive disease pattern in patients with hepatocellular carcinoma (HCC). The application of hyperthermic intraperitoneal chemotherapy (HIPEC) in spontaneously ruptured hepatocellular carcinoma (srHCC) is debatable. Our study aimed to compare the long-term outcomes of srHCC vs. nrHCC and to test the role of postoperative HIPEC in patients with srHCC after hepatectomy. METHODS: From 2014 to 2018, PSM was performed to compare 57 patients who performed liver resection for srHCC and met the research criteria with 57 nrHCC patients selected from 446 consecutive patients. Then patients with srHCC were divided into two groups according to whether they underwent HIPEC after hepatectomy. RESULTS: After 1:1 PSM, the clinical characteristics of the patients with srHCC and nrHCC were comparable. In terms of long-term outcomes, the nrHCC group had significantly longer OS (P=0.026) and DFS (P<0.001) than the srHCC group. Of the 57 srHCC patients, the HIPEC group showed added complications compared to the non-HIPEC group, including an increased length of hospital stay and higher in-hospital costs. However, there were no significant differences in the metastatic patterns of these recurrent patients, and there was no statistically significant difference in DFS (P=0.28) or OS (P=0.56) between the two groups. CONCLUSIONS: The prognosis of ruptured HCC patients were worse than those of non-ruptured HCC patients. HIPEC may not be a robust treatment for srHCC now.

CDK1, CCNB1, and CCNB2 are Prognostic Biomarkers and Correlated with Immune Infiltration in Hepatocellular Carcinoma.

BACKGROUND Orderly G2/M transition in the cell cycle is controlled by the cyclin-dependent kinase 1/cyclin B (CDK1/CCNB) complex. We aimed to comprehensively investigate the roles of CDK1, CCNB1, and CCNB2 via multi-omics analysis and their relationships with immune infiltration in hepatocellular carcinoma (HCC). MATERIAL AND METHODS The transcriptional data and the epigenetic and genetic alterations of CDK1, CCNB1, and CCNB2, as well as their impacts on prognosis in HCC patients, were identified using multiple databases. The correlations between expression of these genes and immune infiltration in HCC were then explored using the TIMER database. RESULTS Overall, mRNA expression of CDK1, CCNB1, and CCNB2 was up-regulated in various tumor tissues including HCC. Higher expression of these genes was associated with poorer prognosis in HCC patients. Lower promoter methylation of these genes might cause higher expression levels in tumor tissues of HCC. Genetic alterations and several methylated-CpG sites in these genes were significantly associated with survival. Notably, expression levels of CDK1, CCNB1, and CCNB2 were positively correlated with infiltrating levels of CD4⁺ T cells, CD8⁺ T cells, neutrophils, macrophages, and dendritic cells in HCC. In addition, significant correlations between the expression of these genes and various immune markers in HCC, such as PD-1, PDL-1, and CTLA-4, were also observed. CONCLUSIONS CDK1, CCNB1, and CCNB2 are potential prognostic biomarkers and associated with immune cell infiltration in HCC. The genes may be utilized to predict the reaction of immunotherapy. Combining inhibitors of these genes with immunotherapy may improve the survival time of HCC patients.

Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival.

This study aimed to identify aberrantly methylated differentially methylated CpG sites (DMCs) and investigate their prognostic value in hepatocellular carcinoma (HCC). A total of 2,404 DMCs were selected from Gene Expression Omnibus (GEO) and validated by The Cancer Genome Atlas (TCGA). The TCGA cohort was divided into a training cohort and a validating cohort. First, the prognostic model based on six DMCs, including cg08351331, cg02910574, cg09947274, cg17589341, cg24652919, and cg26545968, was constructed based on the least absolute shrinkage and selection operator (LASSO) regression Cox analysis. The area under the curve (AUC) of the DMC-based model was 0.765 in the training cohort and 0.734 in the validating cohort. The accuracy of a model combining the DMC signature and American Joint Committee on Cancer (AJCC) stage, with an AUC of 0.795, was better than that of the DMCs or AJCC stage alone. Second, further analysis revealed that the methylation rate of cg08351331 was negatively associated with the expression of its relative gene, lipopolysaccharide-binding protein (LBP). Besides, the gene expression of LBP was significantly associated with poor overall survival in patients with hepatitis B virus (HBV) infection. Finally, these findings were confirmed by GSE57956 data and our own cohort. In conclusion, we established an accurate DMC-based prognostic model that could be combined with AJCC stage to improve the accuracy of prognostic prediction in HCC. Moreover, our preliminary data indicate that LBP may be a new key factor in HBV-induced HCC initiation through the regulation of its methylation.

The cross-talk between DDR1 and STAT3 promotes the development of hepatocellular carcinoma.

OBJECTIVE: To investigate the function of discoidin domain receptor 1 (DDR1) in hepatocellular carcinoma (HCC) and to further clarify the underlying mechanism. RESULTS: DDR1 was significantly increased in HCC tissues and cells, which was related to clinical staging and prognosis of HCC. Upregulation of DDR1 promoted EMT and glutamine metabolism in HCC cells, while loss of DDR1 showed the opposite effects. STAT3 bound with the promoter of DDR1, and facilitated the phosphorylation of STAT3. In turn, activation of STAT3 increased the expression of DDR1. Silencing of STAT3 removed the promoting effect of DDR1 on proliferation, migration and invasion of HCC cells. The in vivo tumor growth assay showed that the cross-talk between DDR1 and STAT3 promoted HCC tumorigenesis. CONCLUSIONS: Our research revealed the positive feedback of DDR1 and STAT3 promoted EMT and glutamine metabolism in HCC, which provided some experimental basis for clinical treatment or prevention of HCC. MATERIALS AND METHODS: The mRNA expression of DDR1 was detected by qRT-PCR. CCK8 assay, wound healing assay and transwell assay were used to detect the DDR1/ STAT3 function on proliferation, migration and invasion in HCC cells. Western blot was used to calculate protein level of DDR1, STAT3, epithelial-mesenchymal transition (EMT) related proteins.