Disulfidptosis-associated long non-coding RNA signature predicts the prognosis, tumor microenvironment, and immunotherapy and chemotherapy options in colon adenocarcinoma.

BACKGROUND: Disulfidptosis is independent of apoptosis, ferroptosis, and cuproptosis and is associated with cancer progression, treatment response, and prognosis. However, the predictive potential of disulfidptosis-associated lncRNAs in colon adenocarcinoma (COAD) and their features in the tumor immune microenvironment (TIME) require further elucidation. METHODS: RNA transcriptome, clinical information, and mutation data of COAD samples were obtained from the TCGA database. The risk model was first constructed by co-expression analysis of disulfidptosis genes and lncRNAs, and prognostic lncRNAs were screened using Cox regression, followed by least absolute shrinkage and selection operator analysis. Enrichment analyses were performed to explore the underlying biological functions and signaling of model-associated differentially expressed genes (MADEGs). Moreover, TIME of MADEGs was analyzed to assess the immunotherapy. Finally, the expression levels of the lncRNAs were verified by taking specimens of patients with COAD from the Affiliated Hospital of Qingdao University. RESULTS: We constructed a prognosis-related risk model based on four disulfidptosis-associated lncRNAs (ZEB1-AS1, SNHG16, SATB2-AS1, and ALMS1-IT1). By analyzing the survival of patients in the whole, training, and test groups, we found that patients with COAD in the low-risk group had better overall survival than those in the high-risk group. Validation of the model via Cox analysis and clinical indicators demonstrated that the model had a decent potential for predicting the prognosis of patients with COAD. Enrichment analyses revealed that the MADEGs were related to disulfidptosis-associated biological functions and cancer pathways. Furthermore, patients with COAD in the high-risk group had more positive responses to immune checkpoint inhibitors (ICIs) than those in the low-risk group, as confirmed by TIME analysis. ZEB1-AS1, SNHG16, and ALMS1-IT1 were expressed at higher levels in tumor samples than those in the corresponding paracancerous samples (p < 0.05), whereas SATB2-AS1 was upregulated in the paracancerous samples (p < 0.05). CONCLUSIONS: This signature may guide prognosis, molecular mechanisms, and treatment strategies, including ICIs and chemotherapy, in patients with COAD.

Machine learning-based radiomics analysis of preoperative functional liver reserve with MRI and CT image.

OBJECTIVE: The indocyanine green retention rate at 15 min (ICG-R15) is a useful tool to evaluate the functional liver reserve before hepatectomy for liver cancer. Taking ICG-R15 as criteria, we investigated the ability of a machine learning (ML)-based radiomics model produced by Gd-EOB-DTPA-enhanced hepatic magnetic resonance imaging (MRI) or contrast-enhanced computed tomography (CT) image in evaluating functional liver reserve of hepatocellular carcinoma (HCC) patients. METHODS: A total of 190 HCC patients with CT, among whom 112 also with MR, were retrospectively enrolled and randomly classified into a training dataset (CT: n = 133, MR: n = 78) and a test dataset (CT: n = 57, MR: n = 34). Then, radiomics features from Gd-EOB-DTPA MRI and CT images were extracted. The features associated with the ICG-R15 classification were selected. Five ML classifiers were used for the ML-model investigation. The accuracy (ACC) and the area under curve (AUC) of receiver operating characteristic (ROC) with 95% confidence intervals (CI) were utilized for ML-model performance evaluation. RESULTS: A total of 107 different radiomics features were extracted from MRI and CT, respectively. The features related to ICG-R15 which was classified into 10%, 20% and 30% were selected. In MRI groups, classifier XGBoost performed best with its AUC = 0.917 and ACC = 0.882 when the threshold was set as ICG-R15 = 10%. When ICG-R15 = 20%, classifier Random Forest performed best with AUC = 0.979 and ACC = 0.882. When ICG-R15 = 30%, classifier XGBoost performed best with AUC = 0.961 and ACC = 0.941. For CT groups, the classifier XGBoost performed best when ICG-R15 = 10% with AUC = 0.822 and ACC = 0.842. When ICG-R15 = 20%, classifier SVM performed best with AUC = 0.860 and ACC = 0.842. When ICG-R15 = 30%, classifier XGBoost performed best with AUC = 0.938 and ACC = 0.965. CONCLUSIONS: Both the MRI- and CT-based machine learning models are proved to be valuable noninvasive methods for functional liver reserve evaluation.

Adipose-derived mesenchymal stem cells induced PAX8 promotes ovarian cancer cell growth by stabilizing TAZ protein.

Our previous studies have shown that the Adipose-derived mesenchymal stem cells (ADSCs) can regulate metastasis and development of ovarian cancer. However, its specific mechanism has yet to be fully revealed. In this study, an RNA-seq approach was adopted to compare the differences in mRNA levels in ovarian cancer cells being given or not given ADSCs. The mRNA level of paired box 8 (PAX8) changed significantly and was confirmed as an important factor in tumour-inducing effect of ADSCs. In comparison with the ovarian cancer cells cultured in the common growth medium, those cultured in the medium supplemented with ADSCs showed a significant increase of the PAX8 level. Moreover, the cancer cell growth could be restricted, even in the ADSC-treated group (P < .05), by inhibiting PAX8. In addition, an overexpression of PAX8 could elevate the proliferation of ovarian cancer cells. Moreover, Co-IP assays in ovarian cancer cells revealed that an interaction existed between endogenous PAX8 and TAZ. And the PAX8 levels regulated the degradation of TAZ. The bioluminescence images captured in vivo manifested that the proliferation and the PAX8 expression level in ovarian cancers increased in the ADMSC-treated group, and the effect of ADSCs in promoting tumours was weakened through inhibiting PAX8. Our findings indicate that the PAX8 expression increment could contribute a role in promoting the ADSC-induced ovarian cancer cell proliferation through TAZ stability regulation.

A deep metric learning approach for histopathological image retrieval.

To distinguish ambiguous images during specimen slides viewing, pathologists usually spend lots of time to seek guidance from confirmed similar images or cases, which is inefficient. Therefore, several histopathological image retrieval methods have been proposed for pathologists to easily obtain images sharing similar content with the query images. However, these methods cannot ensure a reasonable similarity metric, and some of them need lots of annotated images to train a feature extractor to represent images. Motivated by this circumstance, we propose the first deep metric learning-based histopathological image retrieval method in this paper and construct a deep neural network based on the mixed attention mechanism to learn an embedding function under the supervision of image category information. With the learned embedding function, original images are mapped into the predefined metric space where similar images from the same category are close to each other, so that the distance between image pairs in the metric space can be regarded as a reasonable metric for image similarity. We evaluate the proposed method on two histopathological image retrieval datasets: our self-established dataset and a public dataset called Kimia Path24, on which the proposed method achieves recall in top-1 recommendation (Recall@1) of 84.04% and 97.89% respectively. Moreover, further experiments confirm that the proposed method can achieve comparable performance to several published methods with less training data, which hedges the shortage of annotated medical image data to some extent. Code is available at https://github.com/easonyang1996/DML_HistoImgRetrieval.

Analysis of survival rates and prognosis of hepatoblastoma in children: a retrospective study from a single center in China.

Hepatoblastoma (HB) is the most common liver cancer in children, this study aims at analyzing the prognostic factors affecting the survival rates and summarizing the treatment experience. In this study, we reviewed patients with primary HB under the age of 14 years who underwent complete tumor resection from June 1997 to March 2019. The data of 72 patients were collected. Survival analysis was performed by Kaplan-Meier, multivariate Cox proportional hazards regression and linear mixed model for repeated measures (LMMRM). The 5-year and the 10-year event-free survival (EFS) of all patients were 78.2% and 73%, respectively. Both the 5-year and 10-year overall survival (OS) were 85.7%. Kaplan-Meier survival analysis showed that patients with tumor capsule infiltration (TCI) and patients with surgical margin less than 1 cm may also have a good prognosis. The Cox proportional hazards regression model analysis results were similar to the Kaplan-Meier analysis results. LMMRM analysis showed that there were significant differences in platelet, alpha-fetoprotein, C-reactive protein and hemoglobin values after surgery in the metastasis group (P < 0.05). This study suggests that patients with TCI or narrow surgical margin (<1 cm) may also have a good prognosis, and the risk stratification of HB can be used as the latest grading standard to evaluate the prognosis of patients.

Cell Sources and Influencing Factors of Liver Regeneration: A Review.

Liver regeneration (LR) is a set of complicated mechanisms between cells and molecules in which the processes of initiation, maintenance, and termination of liver repair are regulated. Although LR has been studied extensively, there are still numerous challenges in gaining its full understanding. Cells for LR have a wide range of sources and the feature of plasticity, and regeneration patterns are not the same under different conditions. Many patients undergoing partial hepatectomy develop cirrhosis or steatosis. The changes of LR in these cases are not clear. Many types of cells participate in LR. Hepatocytes, biliary epithelial cells, hepatic progenitor cells, and human liver stem cells can serve as the cell sources for LR. However, different types and degrees of damage trigger the response from the most suitable cells. Exploring the cell sources of LR is of great significance for accelerating recovery of liver function under different pathological patterns and developing a cell therapy strategy to cope with the shortage of donors for liver transplantation. In clinical practice, the background of the liver influences regeneration. Fibrosis and steatosis create different LR microenvironments and signal molecule interaction patterns. In addition, factors such as partial hepatectomy, aging, platelets, nerves, hormones, bile acids, and gut microbiota are widely involved in this process. Understanding the influencing factors of LR has practical value for individualized treatment of patients with liver diseases. In this review, we have summarized recent studies and proposed our views. We discuss cell sources and the influential factors on LR to help in solving clinical problems.

Identification of Potential Biomarkers of Prognosis-Related Long Non-Coding RNA (lncRNA) in Pediatric Rhabdoid Tumor of the Kidney Based on ceRNA Networks.

BACKGROUND Long non-coding RNA (lncRNA) can act as competing endogenous RNA (ceRNA) during tumor development. However, no study has elucidated the ceRNA network in pediatric rhabdoid tumor of the kidney (RTK) and its prognostic-related lncRNAs. The goal of the present study was to identify potential biomarkers of prognostic-related lncRNAs. MATERIAL AND METHODS RNA sequencing and clinical data were procured from the TARGET database. The "EdgeR" package was used to obtain differentially expressed lncRNA (DElncRNA), differentially expressed messenger RNAs (DEmRNA), and differentially expressed microRNAs (DEmiRNA). Cytoscape software was used to construct a ceRNA network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted on the ceRNA network-related DEmRNA. The Kaplan-Meier method was used for predicting survival with ceRNA network-related DElncRNA. Univariate and multivariate Cox analyses were used to identify prognosis-related lncRNAs in the ceRNA network, and an RTK prognostic signature was constructed. RESULTS We identified 1109 DElncRNAs, 215 DEmiRNAs, and 3436 DEmRNAs; and 107 DElncRNAs, 21 DEmiRNAs, and 74 DEmRNAs were included in the ceRNA regulatory network. GO enrichment analysis and KEGG pathway enrichment indicated that the DEmRNAs were mainly related to the regulation of phospholipase C activity and the MAPK signaling pathway. Survival analysis showed that 9 of 107 DElncRNAs were correlated with prognosis (P<0.05). Univariate and multivariate Cox analysis identified 4 DElncRNAs (HNF1A-AS1, TPTEP1, SNHG6, and ZNF503-AS2) to establish a predictive model and can be used as independent prognostic biomarkers. CONCLUSIONS We constructed a ceRNA network that reveals potential lncRNA biomarkers for pediatric RTK.

Anticancer Effect of Radix Astragali on Cholangiocarcinoma In Vitro and Its Mechanism via Network Pharmacology.

BACKGROUND This study used network pharmacology method and cell model to assess the effects of Radix Astragali (RA) on cholangiocarcinoma (CCA) and to predict core targets and molecular mechanisms. MATERIAL AND METHODS We performed an in vitro study to assess the effect of RA on CCA using CCK8 assay, the Live-Cell Analysis System, and trypan blue staining. The components and targets of RA were analyzed using the Traditional Chinese Medicine Systems Pharmacology database, and genes associated with CCA were retrieved from the GeneCards and OMIM platforms. Protein-protein interactions were analyzed with the STRING platform. The components-targets-disease network was built by Cytoscape. The TIMER database revealed the expression of core targets with diverse immune infiltration levels. GO and KEGG analyses were performed to identify molecular-biology processes and signaling pathways. The predictions were verified by Western blotting. RESULTS Concentration-dependent antitumor activity was confirmed in the cholangiocarcinoma QBC939 cell line treated with RA. RA contained 16 active compounds, with quercetin and kaempferol as the core compounds. The most important biotargets for RA in CCA were caspase 3, MAPK8, MYC, EGFR, and PARP. The TIMER database revealed that the expression of caspase3 and MYC was related with diverse immune infiltration levels of CCA. The results of Western blotting showed RA significantly influenced the expression of the 5 targets that network pharmacology predicted. CONCLUSIONS RA is an active medicinal material that can be developed into a safe and effective multi-targeted anticancer treatment for CCA.

The prognostic value of lncRNA SNHG1 in cancer patients: a meta-analysis.

BACKGROUND: Increasing evidence revealed that high expression level of lncRNA SNHG1 was associated with the unfavorable prognosis of cancer and maybe used as a valuable biomarker for cancer patients. The present meta->analysis is to analyze existing data to reveal potential clinical application of SNHG1 on cancer prognosis and tumor progression. All of the included studies were collected through a variety of retrieval strategies. And the articles were qualified by MOOSE and PRISMA checklists. METHODS: Up to Mar 20, 2018, literature collection was performed by comprehensive search through electronic databases, including the Cochrane library, PubMed, Embase, Web of science, Springer, Science direct, and three Chinese databases: CNKI, Weipu, and Wanfang. We analyzed 14 studies that met the criteria, and concluded that the increased SHNG1 level was correlated with poor OS and tumor progression. RESULTS: The combined results indicated that elevated SNHG1 expression level was significantly associated with poor OS (HR = 2.06, 95% CI: 1.69-2.52, P < 0.01) and PFS (HR = 2.78, 95% CI: 1.69-4.55, P < 0.01) in various cancers. Moreover, the promoted SNHG1 expression was also associated with tumor progression ((III/IV vs. I/II: HR = 1.89, 95% CI: 1.53-2.34, P < 0.01). In stratified analyses, a significantly unfavorable association of elevated lncRNA SNHG1 and OS was observed in both digestive system (HR = 2.04, 95% CI: 1.56-2.68, P < 0.01) and non-digestive system (HR = 2.09, 95% CI: 1.55-2.83, P < 0.01) cancer patients. CONCLUSIONS: The present analysis indicated that the increased SNHG1 is associated with poor OS in patients with general tumors and may be served as a useful prognostic biomarker.

Crohn's Disease Complicated With Extensive Thrombosis of Limbs and Mesenteric Arteries: A Case Report and Literature Review.

BACKGROUND: Crohn's disease (CD) is a lifelong disease characterized by purulent inflammation in the gastrointestinal tract from any part of the mouth to the anus. Various studies have reported complications of the CD. However, arterial thrombosis is an extremely rare complication of CD. We report a patient with CD with extensive thrombosis of the extremities and mesenteric arteries. METHODS: A 41-year-old man came to our hospital for 2 months of discomfort in the right upper abdomen and had previous left lower extremity arterial occlusive disease and left upper limb ischemic contraction for more than 2 months. The patient developed fever and abdominal pain repeatedly after admission; because of the increased abdominal pain, we urgently performed a laparotomy for him. And according to the findings in the surgery, we decided to perform partial small intestine resection, cholecystectomy, common bile duct exploration, and T-tube drainage. RESULTS: Pathological findings of postoperative specimens showed Crohn's disease and mesenteric atherosclerosis with mesenteric artery thrombosis. We performed a series of treatments such as 5-aminosalicylic acid, intravenous infusion, broad-spectrum antibiotic infection treatment, nutritional support, and low molecular weight heparin. The patient was successfully discharged from the hospital. CONCLUSIONS: The occurrence of IBD with arterial thromboembolism is extremely rare but can lead to serious consequences. During IBD treatment, we should be aware of the possibility of TEs (especially arterial TEs) and should be alert to the possibility of arterial TEs in young patients with IBD with active and extensive disease.

M3 muscarinic acetylcholine receptors regulate epithelial-mesenchymal transition, perineural invasion, and migration/metastasis in cholangiocarcinoma through the AKT pathway.

BACKGROUND: Cholangiocarcinoma is a highly malignant tumor type that is not sensitive to radiotherapy or chemotherapy due to aggressive perineural invasion and metastasis. Unfortunately, the mechanisms underlying these processes and the signaling factors involved are largely unknown. In this study, we analyzed the role of M3 muscarinic acetylcholine receptors (M3-mAChR) in cell migration, perineural invasion, and metastasis during cholangiocarcinoma. METHODS: We assessed 60 human cholangiocarcinoma tissue samples and 30 normal biliary tissues. Immunohistochemical staining was used to detect M3-mAChR expression and the relationship between expression and clinical prognosis was evaluated. The biological functions of M3-mAChR in cholangiocarcinoma cell migration, perineural invasion, and epithelial-mesenchymal transition (EMT) were investigated using the human cholangiocarcinoma cell lines FRH0201 and RBE in conjunction with various techniques, including agonist/antagonist treatment, RNA interference, M3-mAChR overexpression, dorsal root ganglion co-culturing, immunohistochemistry, western blotting, etc. RESULTS: M3-mAChR were highly expressed in cholangiocarcinoma tissue and expression was closely related to differentiation and lymphatic metastasis, affecting patient survival. Treatment with the M3-mAChR agonist pilocarpine and M3-mAChR overexpression significantly promoted migration and perineural invasion, while the M3-mAChR antagonist atropine blocked these effects. Similarly, M3-mAChR knock-down also weakened cell migration and perineural invasion. The expression of phosphatase and tensin homolog, AKT, E-cadherin, vimentin, and Snail, which are components of the phosphatidylinositol 3-kinase/AKT signaling pathway and EMT, were altered by pilocarpine, and these effects were again blocked by atropine. Notably, AKT knock-down decreased M3-mAChR expression and reversed the downstream effects of this receptor. CONCLUSIONS: M3-mAChR are involved in tumor cell migration, perineural invasion, and EMT during cholangiocarcinoma, and these effects are modulated via the AKT signaling pathway.

KISS1 Associates with Better Outcome via Inhibiting Matrix Metalloproteinase-9 in Colorectal Liver Metastasis.

BACKGROUND: Cancer metastasis is a major contributor to patient death because of its systemic nature and resistance to therapeutic agents. KISS1, originally identified to be a metastasis suppressor, couples to its receptor KISS1R and plays a pivotal role in suppressing cancer metastasis. In this study, we investigated KISS1 and KISS1R expression in colorectal liver metastasis (CRLM), and analyzed their correlation with patients' clinicopathological variables, including prognosis. METHODS: Overall, 55 patients with CRLM who underwent hepatectomy between 2003 and 2013 were enrolled in this study. Immunohistochemistry was performed to evaluate the protein expression of KISS1, KISS1R, and matrix metalloproteinase-9 (MMP-9). Clinicopathological variables, including prognosis, were compared between low- and high-expressing groups of KISS1 or KISS1R. We analyzed the correlation of KISS1 or KISS1R protein expression with MMP-9. RESULTS: Expression of both KISS1 and KISS1R was significantly correlated with overall survival (p = 0.0283 and p = 0.0275, respectively). The 5-year overall survival rate of the KISS1 and KISS1R low groups was 44.3 and 39.3 %, and 73.7 and 67.9 % in the high groups, respectively. Multivariate analysis revealed that KISS1 low expression was an independent prognostic factor (p = 0.037, hazard ratio 0.20). Moreover, KISS1 low-expression patients had more frequent distant metastasis (p < 0.05). Furthermore, KISS1 low-expressing tumor tissues expressed more MMP-9 protein (p = 0.034), which was mainly expressed in neutrophils at the metastatic tumor edge. CONCLUSION: KISS1 could be a promising prognostic and therapeutic marker in CRLM. KISS1 low expression may induce high MMP-9 expression in neutrophils.

Hypomethylation of long interspersed nuclear element-1 (LINE-1) is associated with poor prognosis via activation of c-MET in hepatocellular carcinoma.

BACKGROUND: Long interspersed nuclear element-1 (LINE-1) methylation status, representing global DNA methylation levels, is associated with patient prognosis in several types of cancer. This study was designed to examine the prognostic significance of LINE-1 methylation in patients with hepatocellular carcinoma (HCC) and the possible mechanisms related to oncogene activation. METHODS: Seventy-five HCC patients who underwent hepatectomy between 2006 and 2012 were enrolled in this study. Quantitative pyrosequencing was performed to quantify the methylation level of three CpG sites in the LINE-1 promoter. Clinicopathological variables and prognosis were compared between LINE-1 hypo- and hypermethylation groups. LINE-1-inserted c-MET (L1-MET) gene expression and its correlation with LINE-1 methylation levels also were analyzed. RESULTS: LINE-1 was significantly hypomethylated in tumor tissues compared with nontumor tissues (48.3 ± 12.2 % vs. 68.2 ± 2.0 %, respectively, p < 0.0001). LINE-1 hypomethylation was not associated with any clinicopathological factors in HCC patients, except sex (p < 0.05). However, patients with LINE-1 hypomethylation exhibited significantly poorer outcome, and multivariate analysis revealed that LINE-1 hypomethylation was an independent risk factor for overall survival (hazard ratio (HR) = 6.1, p = 0.031) and disease-free survival (HR = 2.34, p = 0.045). L1-MET expression was significantly higher in tumor tissues (p < 0.01). L1-MET expression levels were inversely correlated with LINE-1 methylation levels, and positively correlated with c-MET expression (p < 0.05). Furthermore, higher c-MET protein expression was observed in the LINE-1 hypomethylated tumor tissues compared with hypermethylated tumor tissues (p = 0.032). CONCLUSIONS: LINE-1 hypomethylation is significantly associated with poor prognosis in patients with HCC, possibly due to activation of c-MET expression.

High STAT4 expression is a better prognostic indicator in patients with hepatocellular carcinoma after hepatectomy.

BACKGROUND: Signal transducer and activator of transcription 4 (STAT4) mediates the intracellular effects of interleukin-12, leading to the production of interferon gamma (IFN-γ) and natural killer cells cytotoxicity. However, the clinical significance of STAT4 expression in patients with hepatocellular carcinoma (HCC) remains virtually unknown. METHODS: A total of 66 HCC patients who underwent hepatectomy were enrolled in this study. Quantitative real-time polymerase chain reaction was performed to determine STAT4 and IFNG mRNA expression levels. Tissue microarray-based immunohistochemistry was performed to examine CD8(+) T cells, STAT4, and INF-γ proteins. RESULTS: STAT4 was differentially expressed in tumor and nontumor tissues (P = 0.001) and positively correlated with IFNG expression (R (2) = 0.506, P < 0.05) and CD8(+) T cell infiltration (R (2) = 0.53, P < 0.001). Significant correlations were observed between STAT4 expression and tumor TNM stage (P = 0.043), hepatic venous invasion (P = 0.003), des-gamma-carboxy prothrombin (P = 0.011), tumor size (P = 0.036), and tumor differentiation (P = 0.034). Patients with high STAT4 expression had significantly better recurrence-free survival (P = 0.009). Low STAT4 expression (P = 0.030) and presence of portal venous invasion or hepatic venous invasion (P = 0.006) were independent risk factors for HCC recurrence. CONCLUSIONS: Downregulation of STAT4 in HCC indicated aggressive tumor behavior and predicted a worse clinical outcome. STAT4 might be a useful biomarker to identify patients at high risk of recurrence after hepatectomy.

Senescence-related genes possibly responsible for poor liver regeneration after hepatectomy in elderly patients.

BACKGROUND AND AIM: Liver regeneration likely decreases with age by an, as yet, incompletely understood mechanism, restricting the extent of hepatectomy. We therefore analyzed the effect of aging on liver regeneration and investigated mechanisms associate with poor regeneration of human liver. METHODS: We assessed 130 patients who underwent hepatectomy at our institute between 2005 and 2012. The patients were divided into two groups, a younger (age < 65 years, n = 59) and an older (age > 65 years, n = 71) group. The expression of hepatocyte growth factor (HGF), its ligand Met, and the senescence-related genes p16, SIRT1 and SMP30 were assessed by qRT-PCR. Simulated preoperative and 1 week and 6 month postoperative liver volumes were evaluated in 11 younger and 11 older patients using a 3D simulation imaging system. Regenerated liver volumes were calculated and compared with clinicopathological factors, and correlations between liver regeneration and gene expression were calculated. RESULTS: HGF and Met expression was significantly lower, and p16 expression significantly higher in older than in younger patients (P < 0.05 each). Mean increases in liver volume after 6 months were significantly greater in younger than in older patients (396.5 mL, 45.6% vs 159.4 mL, 23.3%, P < 0.05) but did not differ significantly at 1 week. Furthermore, p16 expression was negatively correlated with liver regeneration in older patients (R = -0.67, P < 0.05). CONCLUSION: Poor liver regeneration in older patients may be associated with the upregulation of senescence-related genes, such as p16, and the downregulation of regeneration-promoting genes, such as HGF and Met.

Pancreatobiliary reflux increases macrophage-secreted IL-8 and activates the PI3K/NFκB pathway to promote cholangiocarcinoma progression.

BACKGROUND: Persistent pancreaticobiliary reflux (PBR) is associated with a high risk of biliary malignancy. This study aimed to evaluate the proportion of PBR in biliary tract diseases and mechanisms by which PBR promoted cholangiocarcinoma progression. METHODS: Overall 227 consecutive patients with primary biliary tract disease participated in this study. The amylase levels in the collected bile were analyzed. The mechanisms underlying the effect of high-amylase bile on bile duct epithelial and cholangiocarcinoma cells progression were analyzed. The source of interleukin-8 (IL-8) and its effects on the biological functions of cholangiocarcinoma cells were investigated. RESULTS: The bile amylase levels in 148 of 227 patients were higher than the upper serum amylase limit of 135 IU/L. PBR was significantly correlated with sex, pyrexia, and serum gamma-glutamyl transferase (GGT) levels in the patient cohort. High-amylase bile-induced DNA damage and genetic differences in the transcript levels of the gallbladder mucosa and facilitated the proliferation and migration of bile duct cancer cells (HUCCT1 and QBC939 cells). The concentration of many cytokines increased in high-amylase bile. IL-8 is secreted primarily by macrophages via the mitogen-activated protein kinase pathway and partially by bile duct epithelial cells. IL-8 promotes the progression of HUCCT1 and QBC939 cells by regulating the expression of epithelial-mesenchymal transition-associated proteins and activating the phosphatidylinositol 3-kinase/nuclear factor kappa-B pathway. CONCLUSIONS: PBR is one of the primary causes of biliary disease. IL-8 secreted by macrophages or bile duct epithelial cells stimulated by high-amylase bile promotes cholangiocarcinoma progression.

Machine Learning Model Based on the Neutrophil-to-Eosinophil Ratio Predicts the Recurrence of Hepatocellular Carcinoma After Surgery.

Background: Circulating eosinophils are associated with tumor development. An eosinophil-related index, the neutrophil to eosinophil ratio (NER), can be used to predict the prognosis of patients with tumors. However, there is still a lack of efficient prognostic biomarkers for HCC. In this study, we aimed to investigate the predictive value of the NER and develop an optimal machine learning model for the recurrence of HCC patients. Patients and methods: A retrospective collection of 562 patients who underwent hepatectomy with a pathologic diagnosis of HCC was performed. The relationship between NER and progression-free survival (PFS) was investigated. We developed a new machine learning framework with 10 machine learning algorithms and their 101 combinations to select the best model for predicting recurrence after hepatectomy. The performance of the model was assessed by the area under the curve (AUC) of characteristics and calibration curves, and clinical utility was evaluated by decision curve analysis (DCA). Results: Kaplan‒Meier curves showed that the PFS in the low NER group was significantly better than that in the high NER group. Multivariate Cox regression analysis showed that NER was an independent risk factor for recurrence after surgery. The random survival forests (RSF) model was selected as the best model that had good predictive efficacy and outperformed the TNM, BCLC, and CNLC staging systems. Conclusion: The NER has good predictive value for postoperative recurrence in patients with hepatocellular carcinoma. Machine learning model based on NER can be used for accurate predictions.

Textbook outcome of laparoscopic hepatectomy in the context of precision surgery: A single center experience.

OBJECTIVE: Laparoscopic hepatectomy (LH) has become a common surgery for the treatment of liver tumor. To evaluate the surgical quality of laparoscopic hepatectomy under the context of precision surgery with Textbook outcome (TO), a comprehensive and holistic assessment approach. METHODS: A total of 1056 patients who underwent laparoscopic hepatectomy from May 2016 and December 2022 were enrolled in the study. All the patients were performed hepatectomy. The rate of TO and factors associated with achieving TO were examined. RESULTS: Among the 1056 patients, 75 % patients achieved TO. The main reason limited patients achieving textbook outcomes was prolonged length of hospital stay (LOS). The univariate analysis indicated that age>65, ASA classification ≥3, liver cirrhosis, tumor size > 3 cm, tumor number ≥2, type of primary cancer, and IWATE DSS were significantly associated with non-achievement of TO. The multivariate analysis indicated that the ASA classification ≥3 and advanced difficulty level in IWATE DSS independent factors associated with achieving TO. Reaching TO can significantly prolong the postoperative recurrence time and overall survival time of hepatocellular carcinoma patients. CONCLUSION: In the context of precision surgery, 75 % patients undergoing laparoscopic hepatectomy achieved a TO. Patients who achieved TO had significantly improved survival.

MVI-Mind: A Novel Deep-Learning Strategy Using Computed Tomography (CT)-Based Radiomics for End-to-End High Efficiency Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) directly affects a patient's prognosis. The development of preoperative noninvasive diagnostic methods is significant for guiding optimal treatment plans. In this study, we investigated 138 patients with HCC and presented a novel end-to-end deep learning strategy based on computed tomography (CT) radiomics (MVI-Mind), which integrates data preprocessing, automatic segmentation of lesions and other regions, automatic feature extraction, and MVI prediction. A lightweight transformer and a convolutional neural network (CNN) were proposed for the segmentation and prediction modules, respectively. To demonstrate the superiority of MVI-Mind, we compared the framework's performance with that of current, mainstream segmentation, and classification models. The test results showed that MVI-Mind returned the best performance in both segmentation and prediction. The mean intersection over union (mIoU) of the segmentation module was 0.9006, and the area under the receiver operating characteristic curve (AUC) of the prediction module reached 0.9223. Additionally, it only took approximately 1 min to output a prediction for each patient, end-to-end using our computing device, which indicated that MVI-Mind could noninvasively, efficiently, and accurately predict the presence of MVI in HCC patients before surgery. This result will be helpful for doctors to make rational clinical decisions.

Ensemble learning based on efficient features combination can predict the outcome of recurrence-free survival in patients with hepatocellular carcinoma within three years after surgery.

Preoperative prediction of recurrence outcome in hepatocellular carcinoma (HCC) facilitates physicians' clinical decision-making. Preoperative imaging and related clinical baseline data of patients are valuable for evaluating prognosis. With the widespread application of machine learning techniques, the present study proposed the ensemble learning method based on efficient feature representations to predict recurrence outcomes within three years after surgery. Radiomics features during arterial phase (AP) and clinical data were selected for training the ensemble models. In order to improve the efficiency of the process, the lesion area was automatically segmented by 3D U-Net. It was found that the mIoU of the segmentation model was 0.8874, and the Light Gradient Boosting Machine (LightGBM) was the most superior, with an average accuracy of 0.7600, a recall of 0.7673, a F1 score of 0.7553, and an AUC of 0.8338 when inputting radiomics features during AP and clinical baseline indicators. Studies have shown that the proposed strategy can relatively accurately predict the recurrence outcome within three years, which is helpful for physicians to evaluate individual patients before surgery.