ALKBH5 promotes hepatocellular carcinoma cell proliferation, migration and invasion by regulating TTI1 expression.

The objective of this research was to investigate the potential mechanisms of AlkB homolog 5, RNA demethylase (ALKBH5) in hepatocellular carcinoma (HCC). We used The Cancer Genome Atlas (TCGA), Kruskal-Wallis method and Kaplan-Meier (KM) survival analysis to study the expression of ALKBH5 and its correlation with clinical factors in HCC. In vitro experiments verified the expression of ALKBH5 and its effect on HCC cell phenotype. We screened differentially expressed genes (DEGs) from HCC patients associated with ALKBH5. Through this screening we identified the downstream gene TTI1 which is associated with ALKBH5 and investigated its function using Gene Expression Profiling Interaction Analysis (GEPIA) along with univariate Cox proportional hazards regression analysis. Finally, we analyzed the functions of ALKBH5 and TTI1 in HCC cells. Across numerous pan-cancer types, we observed significant overexpression of ALKBH5. In vitro experiments confirmed ALKBH5 as an oncogene in HCC, with its knockdown leading to suppressed cell proliferation, migration, and invasion. Bioinformatics analyses also demonstrated a significant positive correlation between ALKBH5 and TTI1. TTI1, highly expressed in cells, showed promising prognostic ability for patients. Further experiments confirmed that suppressing TTI1 impeded cell growth and movement, with this effect partially offset by increased ALKBH5 expression. Conversely, promoting these cellular processes was observed with TTI1 overexpression, but was dampened by decreased ALKBH5 expression. In conclusion, our findings suggest that ALKBH5 may influence proliferation, migration and invasion of HCC by modulating TTI1 expression, providing a new direction for treating HCC.

Single-cell mapping reveals several immune subsets associated with liver metastasis of pancreatic ductal adenocarcinoma.

BACKGROUND: Identifying a metastasis-correlated immune cell composition within the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) will help to develop promising and innovative therapeutic strategies. However, the dynamics of immune cell lineages in the TME of advanced PDAC remains elusive. METHODS: Twenty-six samples from 11 patients (including 11 primary tumor tissues, 10 blood, and 5 lymph nodes) with different stages were used to develop a multiscale immune profile. High-dimensional single-cell analysis with mass cytometry was performed to search for metastasis-correlated immune changes in the microenvironment. The findings were further validated by published single-cell RNA sequencing (scRNA-seq) data and multiplex fluorescent immunohistochemistry. FINDINGS: High-dimensional single-cell profiling revealed that the three immune-relevant sites formed a distinct immune atlas. Interestingly, the PDAC microenvironment with the potential for metastatic spread to the liver was characterized by a decreased proportion of CD103+PD-1+CD39+ T cells with cytotoxic and exhausted functional status and an increased proportion of CD73+ macrophages. Analysis of scRNA-seq data of PDAC further confirmed the identified subsets and revealed strong potential interactions via various ligand-receptor pairs between the identified T subsets and the macrophages. Moreover, stratified patients with different immune compositions correlated with clinical outcomes of PDAC. CONCLUSIONS: Our study uncovered metastasis-correlated immune changes, suggesting that ecosystem-based patient classification in PDAC will facilitate the identification of candidates likely to benefit from immunotherapy. FUNDING: This work was supported by the National Key Research and Development Program of China, the Shanghai International Science and Technology Collaboration Program, the Shanghai Sailing Program, and the Key Laboratory of diagnosis and treatment of severe hepato-pancreatic diseases of Zhejiang Province.

Subpopulations of cancer-associated fibroblasts link the prognosis and metabolic features of pancreatic ductal adenocarcinoma.

Background: Cancer-associated fibroblasts (CAFs) are a vital constituent of the tumor microenvironment (TME) and have several activities, but the effect of CAF heterogeneity on the molecular features and clinical outcomes of pancreatic ductal adenocarcinoma (PDAC) remains unknown. Methods: An algorithm "scFrac" based on single-cell sequencing data from the Gene Expression Omnibus was introduced to emulate the enrichment of CAF subtypes in a TCGA-PDAC cohort and their prognostic influence, and confirmed by an external validation group (66 patients with PDAC) with multiplex immunohistochemistry staining. A comprehensive analysis including metabolic profile and transcription factor regulon activity was carried out among CAF subtypes. Results: Three distinct CAF populations were confirmed: myofibroblast (myCAF), inflammatory CAF (iCAF), and antigen-presenting CAF (apCAF). These subtypes expressed distinct metabolic profiles and transcriptional regulon activity. KEGG pathway annotation demonstrated that complement and coagulation cascades, as well as cytokine-cytokine receptor interaction were dominant in iCAFs, and pathways related to focal adhesion, and ECM-receptor interaction showed dominance in myCAFs, while antigen processing and presentation were the top enriched pathways in apCAFs. iCAFs trended to glycolysis with CREB3L1, EGR2 and SOX4 activation, whereas myCAFs depend on the tricarboxylic acid cycle and its derivatives with NRF2, CEBPD and YBX1 activation. iCAF is a protective factor associated with an inflammatory phenotype, but myCAF is an important factor in the poor prognosis of PDAC. Conclusions: We identified distinct molecular characteristics of 3 CAF subtypes in PDAC and plotted their metabolism profile. We introduced a novel algorism, scFrac, for exploring how CAF subgroups dysregulate cancer biology, and also shed a new therapeutic light on targeting the CAF subtype in TME.

High RPS11 level in hepatocellular carcinoma associates with poor prognosis after curative resection.

BACKGROUND: Ribosomal protein S11 (RPS11), a member of ribosomal protein family, is reported to overexpress in diverse malignancies and correlates with tumor recurrence. However, our current knowledge on RPS11 in hepatocellular carcinoma (HCC) remains limited. In this study, we are going to explore the potential prognostic value of RPS11 in HCC patients after curative resection. METHODS: Immunohistochemistry (IHC) was performed to evaluate RPS11 expression on tissue microarrays in training cohort comprising 182 HCC patients and validation cohort enrolling 90 HCC patients in Zhongshan Hospital, Fudan University. Western blot and quantitative reverse transcription PCR (qRT-PCR) were also used to determine the expression level of RPS11 in liver cell lines. Two nomograms, calibration curves and decision curve analysis (DCA) were further performed to assess the performance of RPS11 level in predicting clinical outcomes of HCC patients. Additionally, single-sample gene-set enrichment analysis (ssGSEA) was conducted in TCGA liver cancer database to investigate the potential biological pathways involved in RPS11. RESULTS: Both increased mRNA and protein levels of RPS11 were observed in most HCC cell lines when compared to the normal hepatocytes, and high tumor RPS11 level was associated with shorter overall survival (OS) and recurrence-free survival (RFS) of HCC patients after curative resection. Univariate and multivariate analysis indicated that RPS11 was an independent prognostic factor in HCC. Two nomograms, calibration and DCA curves were further established and displayed a superior prognostic accuracy of OS and RFS, and showed more clinical benefits than traditional staging systems in HCC. Furthermore, several pathways and molecules related to tumor resistance, survival and recurrence were enriched in high RPS11 expression by ssGSEA. CONCLUSIONS: Tumorous RPS11 acts as a potential prognostic biomarker for HCC patients who received curative resection.

A robust 6-mRNA signature for prognosis prediction of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. PDAC prognostic and diagnostic biomarkers are still being explored. The aim of this study is to establish a robust molecular signature that can improve the ability to predict PDAC prognosis. 155 overlapping differentially expressed genes between tumor and non-tumor tissues from three Gene Expression Omnibus (GEO) datasets were explored. A least absolute shrinkage and selection operator method (LASSO) Cox regression model was employed for selecting prognostic genes. We developed a 6-mRNA signature that can distinguish high PDAC risk patients from low risk patients with significant differences in overall survival (OS). We further validated this signature prognostic value in three independent cohorts (GEO batch, P < 0.0001; ICGC, P = 0.0036; Fudan, P = 0.029). Furthermore, we found that our signature remained significant in patients with different histologic grade, TNM stage, locations of tumor entity, age and gender. Multivariate cox regression analysis showed that 6-mRNA signature can be an independent prognostic marker in each of the cohorts. Receiver operating characteristic curve (ROC) analysis also showed that our signature possessed a better predictive role of PDAC prognosis. Moreover, the gene set enrichment analysis (GSEA) analysis showed that several tumorigenesis and metastasis related pathways were indeed associated with higher scores of risk. In conclusion, identifying the 6-mRNA signature could provide a valuable classification method to evaluate clinical prognosis and facilitate personalized treatment for PDAC patients. New therapeutic targets may be developed upon the functional analysis of the classifier genes and their related pathways.

Comparison of pharmacokinetics of mycophenolic acid and its metabolites between living donor liver transplant recipients and deceased donor liver transplant recipients.

Living-donor liver transplantation (LDLT) has been considered an alternative method for treatment of patients with end-stage liver disease. However, the characteristics of pharmacokinetics of mycophenolic acid (MPA) in patients who underwent LDLT were not clear. This study was designed to compare the pharmacokinetics of MPA and its metabolites between LDLT patients and deceased donor liver transplant (DDLT) patients after oral administration of mycophenolate mofetil (MMF). Thirteen patients who underwent LDLT and 14 patients who underwent DDLT were enrolled prospectively. All patients received oral MMF administration (1.0 g, twice daily) in combination with tacrolimus (TAC). The plasma concentrations of MPA, free MPA, glucuronide (MPAG), and acyl glucuronide (AcMPAG) was determined by high-performance liquid chromatography method. There was a wide variation in various pharmacokinetic parameters of MPA and its metabolites in patients who underwent LDLT and DDLT after oral MMF administration. Although mean MPA area under the plasma concentration time curve for 0-12 hours (AUC(0-12h)) of MPA and MPAG in DDLT patients were higher than those in LDLT patients, there was no significant difference between the two groups. MPA concentration at 6 hours (C(6h)), C(10h), C(12h), and MPA AUC(6-12h) were significantly higher in DDLT group than those in LDLT group (P < 0.05). Inversely, higher free MPA AUC(0-12h) and significant free MPA fraction (P < 0.05) in LDLT patients were observed in DDLT patients when compared with DDLT group. AcMPAG concentrations at 4, 8, and 10 hours and AcMPAG AUC(0-12h) were significantly higher in the DDLT group (P < 0.05). In conclusion, after a fixed oral dose of MMF, DDLT patients had higher enterohepatic recycling contributing to total MPA exposure compared with LDLT patients. The function of glucuronide conjugation in LDLT patients was decreased compared with that in DDLT patients. Higher free MPA AUC(0-12h) and a significantly higher fraction of free MPA in LDLT patients suggested that a lower oral dose of MMF may be administered for patients who underwent LDLT.

Models for the prediction of mycophenolic acid area under the curve using a limited-sampling strategy and an enzyme multiplied immunoassay technique in Chinese patients undergoing liver transplantation.

BACKGROUND: An enzyme multiplied immunoassay technique (EMIT) provides convenient and accurate measurements of mycophenolic acid (MPA) concentrations for determination of immunosuppression during treatment with mycophenolate mofetil (MMF). No abbreviated model for estimating the full 12-hour MPA AUC using an EMIT assay in liver transplant recipients has been described previously. OBJECTIVE: This study was conducted to determine the best model for predicting the MPA AUC using the EMIT method and a limited-sampling strategy in Chinese patients undergoing liver transplantation. METHODS: The study enrolled consecutive liver transplant patients who were receiving MMF 1 g BID along with tacrolimus. A complete MPA pharmacokinetic profile was obtained for each patient on a single day, 7 to 14 days after transplantation. The EMIT method was used to determine MPA concentrations before dosing and at 0.5, 1, 1.5, 2, 4, 6, 8, 10, and 12 hours after dosing on the sampling day. Multiple linear regression analysis was used to evaluate potential models for estimating the full 12-hour MPA AUC. The accuracy and robustness of the models were evaluated using bootstrap analysis. Prediction error and prediction bias were calculated. Agreement between the estimated MPA AUC(0-12) and the full 12-hour MPA AUC was investigated using Bland-Altman analysis. RESULTS: The study enrolled 48 Chinese liver transplant recipients (45 male, 3 female) with a mean (SD) age of 50 (12) years, mean weight of 64 (12) kg, and mean height of 169 (6) cm. Twenty-four models that included blood sampling at 1 through 4 time points were developed (r(2) = 0.015-0.950). Four models with the highest r(2) values were selected; the lack of significant differences from the original dataset on bootstrap analysis indicated acceptable accuracy and robustness. The best model for predicting the MPA AUC(0-12) employed concentrations at 1, 2, 4, and 8 hours; 40 of 48 (83.3%) MPA AUC(0-12) values estimated using this model were within 15% of the full 12-hour MPA AUC. This model had a minimal mean prediction error (mean [SD], 0.27% [1.79%]) and mean absolute prediction error (8.83% [1.24%]). On Bland-Altman analysis, this model also had the best agreement between the estimated MAP AUC(0-12) and the full 12-hour MPA AUC, with a mean error of 9.02 mg . h/L. CONCLUSIONS: In this small group of Chinese liver transplant patients receiving MMF and concomitant tacrolimus, models for estimating the MPA AUC(0-12) were developed using the EMIT method and a limited-sampling strategy. The best model for prediction of the full 12-hour MPA AUC was 4.46 + 0.81 . C1 + 1.78 . C(2)+2.51.C(4)+4.94.C8.