Hydroxyphenylpyruvate Dioxygenase Is a Metabolic Immune Checkpoint for UTX-deficient Colorectal Cancer.

BACKGROUND & AIMS: Aberrant epigenetic events mediated by histone methyltransferases and demethylases contribute to malignant progression of colorectal cancer (CRC). However, the role of the histone demethylase ubiquitously transcribed tetratricopeptide repeat on chromosome X (UTX) in CRC remains poorly understood. METHODS: UTX conditional knockout mice and UTX-silenced MC38 cells were used to investigate UTX function in tumorigenesis and development of CRC. We performed time of flight mass cytometry to clarify the functional role of UTX in remodeling immune microenvironment of CRC. To investigate metabolic interaction between myeloid-derived suppressor cells (MDSCs) and CRC, we analyzed metabolomics data to identify metabolites secreted by UTX-deficient cancer cells and taken up by MDSCs. RESULTS: We unraveled a tyrosine-mediated metabolic symbiosis between MDSC and UTX-deficient CRC. Loss of UTX in CRC resulted in methylation of phenylalanine hydroxylase, preventing its degradation and subsequently increasing tyrosine synthesis and secretion. Tyrosine taken up by MDSCs was metabolized to homogentisic acid by hydroxyphenylpyruvate dioxygenase. Homogentisic acid modified protein inhibitor of activated STAT3 via carbonylation of Cys 176, and relieved the inhibitory effect of protein inhibitor of activated STAT3 on signal transducer and activator of transcription 5 transcriptional activity. This in turn, promoted MDSC survival and accumulation, enabling CRC cells to acquire invasive and metastatic traits. CONCLUSIONS: Collectively, these findings highlight hydroxyphenylpyruvate dioxygenase as a metabolic checkpoint to restrict immunosuppressive MDSCs and to counteract malignant progression of UTX-deficient CRC.

Electrokinetic ion enrichment in asymmetric charged nanochannels.

Artificial bionic nanochannels have attracted wide attention and successfully used in various fields. In this work, a novel nanochannel with asymmetric surface charge is proposed to investigate the ion enrichment effect. The results show that the proposed nanochannel has excellent ion enrichment performance and the obtained ion enrichment ratio is up to 1500 when the ion concentration is 0.01 mM, which is much higher than precedent researches typically ranging from tens to hundreds. Besides, we found that the forward voltage bias will produce ions enrichment and the reverse voltage bias will produce ions depletion. The ion enrichment ratio is higher at the larger voltage bias, absolute surface charge density and smaller nanochannel height. In addition, the ion enrichment performance is more sensitive to the change of charged wall length and not sensitive to the change of uncharged wall length. The research report offers important information and instructions for the design and optimum on ion enrichment performance.

Chinese expert consensus statement on the clinical application of AFP/AFP-L3%/DCP using GALAD and GALAD-like algorithm in HCC.

BACKGROUND: Primary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up. RESULTS: Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer. CONCLUSIONS: The compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Common DNA methylation changes in biliary tract cancers identify subtypes with different immune characteristics and clinical outcomes.

BACKGROUND: DNA methylation-associated studies on biliary tract cancer (BTC), including cholangiocarcinoma (CCA) and gallbladder cancer (GBC), may improve the BTC classification scheme. We proposed to identify the shared methylation changes of BTCs and investigate their associations with genomic aberrations, immune characteristics, and survival outcomes. METHODS: Multi-dimensional data concerning mutation, DNA methylation, immune-related features, and clinical data of 57 CCAs and 48 GBCs from Eastern Hepatobiliary Surgery Hospital (EHSH) and 36 CCAs in the TCGA-CHOL cohort were analyzed. RESULTS: In our cohort including 24 intrahepatic CCAs (iCCAs), 20 perihilar CCAs (pCCAs), 13 distal CCAs (dCCAs), and 48 GBCs, 3369 common differentially methylated regions (DMRs) were identified by comparing tumor and non-tumor samples. A lower level of methylation changes of these common DMRs was associated with fewer copy number variations, fewer mutational burden, and remarkably longer overall survival (OS, hazard ratio [HR] = 0.07, 95% confidence interval [CI] 0.01-0.65, P = 0.017). Additionally, a 12-marker model was developed and validated for prognostication after curative surgery (HR = 0.21, 95% CI 0.10-0.43, P < 0.001), which exhibited undifferentiated prognostic effects in subgroups defined by anatomic location (iCCAs, d/pCCAs, GBCs), TNM stage, and tumor purity. Its prognostic utility remained significant in multivariable analysis (HR = 0.26, 95% CI 0.11-0.59, P = 0.001). Moreover, the BTCs with minimal methylation changes exhibited higher immune-related signatures, infiltration of CD8+ lymphocytes, and programmed death-ligand 1 (PD-L1) expression, indicating an inflamed tumor immune microenvironment (TIME) with PD-L1 expression elicited by immune attack, potentially suggesting better immunotherapy efficacy. CONCLUSIONS: In BTCs, DNA methylation is a powerful tool for molecular classification, serving as a robust indicator of genomic aberrations, survival outcomes, and tumor immune microenvironment. Our integrative analysis provides insights into the prognostication after curative surgery and patient selection for immunotherapy.

Sparse logistic regression revealed the associations between HBV PreS quasispecies and hepatocellular carcinoma.

BACKGROUND: Chronic infection with hepatitis B virus (HBV) has been proved highly associated with the development of hepatocellular carcinoma (HCC). AIMS: The purpose of the study is to investigate the association between HBV preS region quasispecies and HCC development, as well as to develop HCC diagnosis model using HBV preS region quasispecies. METHODS: A total of 104 chronic hepatitis B (CHB) patients and 117 HBV-related HCC patients were enrolled. HBV preS region was sequenced using next generation sequencing (NGS) and the nucleotide entropy was calculated for quasispecies evaluation. Sparse logistic regression (SLR) was used to predict HCC development and prediction performances were evaluated using receiver operating characteristic curves. RESULTS: Entropy of HBV preS1, preS2 regions and several nucleotide points showed significant divergence between CHB and HCC patients. Using SLR, the classification of HCC/CHB groups achieved a mean area under the receiver operating characteristic curve (AUC) of 0.883 in the training data and 0.795 in the test data. The prediction model was also validated by a completely independent dataset from Hong Kong. The 10 selected nucleotide positions showed significantly different entropy between CHB and HCC patients. The HBV quasispecies also classified three clinical parameters, including HBeAg, HBVDNA, and Alkaline phosphatase (ALP) with the AUC value greater than 0.6 in the test data. CONCLUSIONS: Using NGS and SLR, the association between HBV preS region nucleotide entropy and HCC development was validated in our study and this could promote the understanding of HCC progression mechanism.

Targeting oxidative pentose phosphate pathway prevents recurrence in mutant Kras colorectal carcinomas.

Recurrent tumors originate from cancer stem cells (CSCs) that survive conventional treatments. CSCs consist of heterogeneous subpopulations that display distinct sensitivity to anticancer drugs. Such a heterogeneity presents a significant challenge in preventing tumor recurrence. In the current study, we observed that quiescent CUB-domain-containing protein 1 (CDCP1)+ CSCs are enriched after chemotherapy in mutant Kirsten rat sarcoma viral oncogene homolog (Kras) colorectal carcinomas (CRCs) and serve as a reservoir for recurrence. Mechanistically, glucose catabolism in CDCP1+ CSCs is routed to the oxidative pentose phosphate pathway (PPP); multiple cycling of carbon backbones in the oxidative PPP potentially maximizes NADPH reduction to counteract chemotherapy-induced reactive oxygen species (ROS) formation, thereby allowing CDCP1+ CSCs to survive chemotherapeutic attack. This is dependent on silent mating type information regulation 2 homolog 5 (Sirt5)-mediated inhibition of the glycolytic enzyme triosephosphate isomerase (TPI) through demalonylation of Lys56. Blocking demalonylation of TPI at Lys56 increases chemosensitivity of CDCP1+ CSCSs and delays recurrence of mutant Kras CRCs in vivo. These findings pinpoint a new therapeutic approach for combating mutant Kras CRCs.

Validation of the GALAD model for early diagnosis and monitoring of hepatocellular carcinoma in Chinese multicenter study.

BACKGROUND: GALAD is an algorithm model estimating the presence of hepatocellular carcinoma (HCC). However, the participants enrolled in the GALAD differ from those of Chinese subjects whose HCCs are mainly hepatitis B virus infection related. Therefore, the cross-sectional as well as longitudinal multicenter study was designed to assess the clinical performances of GALAD in the Chinese population. METHODS: A case-control study of 602 patients with HCC (34.10% within Barcelona Clinic Liver Cancer 0-A stage) and 923 subjects without HCC from five Chinese medical centres was conducted. Longitudinally the performances of GALAD identifying HCC were assessed using receiver operating characteristic curves analyses. Furthermore, the surveillance performance of GALAD for 204 HCC patients after radical surgery and for the early detection of HCC prospectively in an independent cohort of chronic hepatitis B were analysed, respectively. RESULTS: We found the GALAD identified early stage HCC at an area under the receiver operating characteristic curve (AUC) above 0.85 and outperformed significantly than AFP, PIVKAII, AFP-L3 and BALAD-2 respectively. Meanwhile the GALAD could stratify HCC into two distinct subgroups with high or low risks of overall survival and recurrence. The GALAD could detection HCC 24 (AUC: 0.848) or even 48 (AUC: 0.833) weeks before clinical diagnosis. CONCLUSIONS: Our study indicates that the GALAD exhibits outstanding performance in the early diagnosis, prognosis prediction as well as risk monitoring of HCC in our cross-sectional and longitudinal multicenter study of 1561 patients. GALAD should be implanted into clinical practice early so as to improve the clinical efficacy of individual biomarkers in HCC early monitoring and prognosis prediction.

N-glycan profiling alterations of serum and immunoglobulin G in immune thrombocytopenia.

BACKGROUND: The glycosylation alterations of serum and IgG are involved in a variety of autoimmune and inflammatory diseases and have shown great potential in biomarker field. The diagnosis of immune thrombocytopenia (ITP) is exclusive. Our study aimed to discover the potential glyco-biomarkers for auxiliary diagnosis of ITP. METHODS: The serum samples were obtained from 61 ITP patients and 35 healthy controls, and IgG samples were purified from 34 out of 61 ITP patients and 35 healthy controls. DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) was used to analyze serum and IgG N-glycan profiling. RESULTS: 6 of 12 serum N-glycan peaks, 6 of 7 IgG N-glycan peaks, serum fucosylation, and IgG galactosylation were significantly different between ITP patients and healthy controls (p < 0.05). IgG peak 7 showed good diagnostic efficacy for discriminating ITP patients from healthy individuals (AUC 0.967). ITP patients with severe thrombocytopenia had a significantly lower serum fucosylation than ITP patients with mild and moderate thrombocytopenia (p < 0.05). Serum fucosylation and serum peak 5 were correlated with platelet counts in ITP patients with severe thrombocytopenia, and the absolute values of correlation coefficient were both over 0.5. CONCLUSIONS: The specific N-glycan patterns of serum and IgG were observed in ITP patients. IgG peak 7 was a potential biomarker for auxiliary diagnosis of ITP.

Genetic studies discover novel coding and non-coding mutations in patients with Wilson's disease in China.

OBJECTIVES: Wilson disease (WD) is a rare autosomal recessive genetic disorder associated with various mutations in the ATP7B gene and leads to significant disability or death if untreated. Early diagnosis and proper therapy usually predict a good prognosis, especially in pre-symptomatic WD. Genetic testing provides an accurate and effective diagnostic method for the early diagnosis of WD. METHODS: We recruited 18 clinically diagnosed WD patients from 16 unrelated families and two independent individuals. The next-generation sequencing of the ATP7B gene was performed. The 293T cell lines were divided into wild-type (WT) ATP7B and mutated ATP7B groups. Cell proliferation was determined by Cell Counting Kit-8 (CCK-8) assay and apoptosis was detected by Annexin V/propidium iodide (PI) assays. RESULTS: Pedigree analysis showed that compound heterozygous variants (17/18, 94.44%) were present in the majority of WD patients. A total of 33 ATP7B gene variants were identified, including three variants with uncertain significance (VUS) [two splice mutations (c.51+2T>G, c.1543+40G>A) and one frameshift mutation (c.3532_3535del)]. The CCK-8 and apoptosis assays demonstrated that the VUS of ATP7B could significantly affect the transportation of copper. CONCLUSIONS: The study revealed genetic defects of 16 Chinese families and two independent individuals with WD, which enriched the mutation spectrum of the ATP7B gene worldwide and provided valuable information for studying the mutation types of ATP7B in the Chinese populations. Genetic testing in WD patients is necessary to shorten the time to initiate therapy, reduce damage to the liver and improve the prognosis.

Quantitative detections of TP53 gene mutations improve the diagnosis and prognostic prediction of biliary tract cancers using droplet digital PCR.

OBJECTIVE: Biliary tract cancer (BTC) is a rare malignancy and lack of effective diagnostic and prognostic marker. Here, we aimed to investigate the clinical implication of TP53 mutation detection in BTC using droplet digital PCR (ddPCR). METHODS: TP53 gene (loci p.R175H, p.R248Q, p.R248W, and p.R273H) mutation frequencies of 45 pairs of tumor tissues (TTs) and adjacent normal tissues (ANTTs) were analyzed, respectively, using ddPCR. Meanwhile, the same detections were conducted in plasma cell-free DNA (cfNDA) of 156 subjects including BTC, disease control (DC), and healthy controls (HC). The logistic regression algorithm was established to identify BTC. The correlations between mutations and clinicopathological features as well as the effects of TP53 mutation frequency on BTC prognosis were assessed. RESULTS: The higher mutation of p.R175H was found in TTs compared with ANTT (p = 0.006). The mutation at p.R273H in cfDNA was also higher in BTC when compared with DC and HC (p < 0.05). The logistic algorithms combining p.R273H mutation demonstrated the higher diagnostic efficacy trend than carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP) in identifying BTC from DC (the area under the curves of the algorithm: 0.845, 95% CI:0.775-0.914). The median overall survival (OS) and progression-free survival (PFS) were significantly shorter when the BTC patients harboring the p.R273H mutation (OS: p = 0.032; PFS: p = 0.046). CONCLUSION: This study revealed for the first time that the quantitative TP53 mutations using the ddPCR might serve as a potential genetic biomarker for BTC diagnosis and prognosis assessment.

A long noncoding RNA distributed in both nucleus and cytoplasm operates in the PYCARD-regulated apoptosis by coordinating the epigenetic and translational regulation.

Long noncoding RNAs (lncRNAs) participate in various biological processes such as apoptosis. The function of lncRNAs is closely correlated with their localization within the cell. While regulatory potential of many lncRNAs has been revealed at specific subcellular location, the biological significance of discrete distribution of an lncRNA in different cellular compartments remains largely unexplored. Here, we identified an lncRNA antisense to the pro-apoptotic gene PYCARD, named PYCARD-AS1, which exhibits a dual nuclear and cytoplasmic distribution and is required for the PYCARD silencing in breast cancer cells. The PYCARD-regulated apoptosis is controlled by PYCARD-AS1; moreover, PYCARD-AS1 regulates apoptosis in a PYCARD-dependent manner, indicating that PYCARD is a critical downstream target of PYCARD-AS1. Mechanistically, PYCARD-AS1 can localize to the PYCARD promoter, where it facilitates DNA methylation and H3K9me2 modification by recruiting the chromatin-suppressor proteins DNMT1 and G9a. Moreover, PYCARD-AS1 and PYCARD mRNA can interact with each other via their 5' overlapping region, leading to inhibition of ribosome assembly in the cytoplasm for PYCARD translation. This study reveals a mechanism whereby an lncRNA works at different cellular compartments to regulate the pro-apoptotic gene PYCARD at both the epigenetic and translational levels, contributing to the PYCARD-regulated apoptosis, and also sheds new light on the role of discretely distributed lncRNAs in diverse biological processes.

Using Quasispecies Patterns of Hepatitis B Virus to Predict Hepatocellular Carcinoma With Deep Sequencing and Machine Learning.

BACKGROUND: Hepatitis B virus (HBV) infection is one of the main leading causes of hepatocellular carcinoma (HCC) worldwide. However, it remains uncertain how the reverse-transcriptase (rt) gene contributes to HCC progression. METHODS: We enrolled a total of 307 patients with chronic hepatitis B (CHB) and 237 with HBV-related HCC from 13 medical centers. Sequence features comprised multidimensional attributes of rt nucleic acid and rt/s amino acid sequences. Machine-learning models were used to establish HCC predictive algorithms. Model performances were tested in the training and independent validation cohorts using receiver operating characteristic curves and calibration plots. RESULTS: A random forest (RF) model based on combined metrics (10 features) demonstrated the best predictive performances in both cross and independent validation (AUC, 0.96; accuracy, 0.90), irrespective of HBV genotypes and sequencing depth. Moreover, HCC risk scores for individuals obtained from the RF model (AUC, 0.966; 95% confidence interval, .922-.989) outperformed α-fetoprotein (0.713; .632-.784) in distinguishing between patients with HCC and those with CHB. CONCLUSIONS: Our study provides evidence for the first time that HBV rt sequences contain vital HBV quasispecies features in predicting HCC. Integrating deep sequencing with feature extraction and machine-learning models benefits the longitudinal surveillance of CHB and HCC risk assessment.

N-glycan fingerprint predicts alpha-fetoprotein negative hepatocellular carcinoma: A large-scale multicenter study.

Alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (ANHCC) patients account for more than 30% of the whole entity of HCC patients and are easily misdiagnosed. This three-phase study was designed to find and validate new ANHCC N-glycan markers which identified from The Cancer Genome Atlas (TCGA) database and noninvasive detection. Differentially expressed genes (DEGs) of N-glycan biosynthesis and degradation related genes were screened from TCGA database. Serum N-glycan structure abundances were analyzed using N-glycan fingerprint (NGFP) technology. Totally 1340 participants including ANHCC, chronic liver diseases and healthy controls were enrolled after propensity score matching (PSM). The Lasso algorithm was used to select the most significant N-glycan structures abundances. Three machine learning models [random forest (RF), support vector machine (SVM) and logistic regression (LR)] were used to construct the diagnostic algorithms. All 13N-glycan structure abundances analyzed by NGFP demonstrated significant and was enrolled by Lasso. Among the three machine learning models, LR algorithm demonstrated the best diagnostic performance for identifying ANHCC in training cohort (LR: AUC: 0.842, 95%CI: 0.784-0.899; RF: AUC: 0.825, 95%CI: 0.766-0.885; SVM: AUC: 0.610, 95%CI: 0.527-0.684). This LR algorithm achieved a high diagnostic performance again in the independent validation (AUC: 0.860, 95%CI: 0.824-0.897). Furthermore, the LR algorithm could stratify ANHCC into two distinct subgroups with high or low risks of overall survival and recurrence in follow-up validation. In conclusion, the biomarker panel consisting of 13N-glycan structures abundances using the best-performing algorithm (LR) was defined and indicative as an effective tool for HCC prediction and prognosis estimate in AFP negative subjects.

Serum N-glycan fingerprint helps to discriminate intrahepatic cholangiocarcinoma from hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are two main types of primary liver cancer, and reliable discrimination is important for optimal treatment. Aberrant glycosylation was detected in HCC and ICC. Both cross-sectional and follow-up studies were performed to establish a differential diagnosis model using N-glycans. A total of 420 participants were enrolled, with 310 patients in training cohort and 110 patients in validation cohort. The follow-up cohort was used to assess the prognosis of ICC. As the results, the diagnostic efficacy of the model was superior to alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) when identifying ICC from HCC (AUC of the nomogram: 0.845, 95%CI: 0.788-0.902; AFP: 0.793, 95%CI: 0.732-0.854; CEA: 0.592, 95%CI: 0.496-0.687; CA 19-9: 0.674, 95%CI: 0.582-0.767) in training cohort. In validation cohort, this model (AUC: 0.810, 95% CI: 0.728-0.891) also demonstrated high efficacy in distinguishing ICC from HCC. Furthermore, the nomogram helps to stratify ICC into two subgroups with high or low risk of survival and recurrence. Therefore, a nomogram integrating six N-glycans [NGA2FB(Peak2), NG1A2F (Peak3), NA2 (Peak5), NA2F (Peak6), NA3 (Peak8) and NA4 (Peak11)] was established for ICC and HCC differentiation, and for prognosis assessment in ICC patients.

Serum N-glycan fingerprint nomogram predicts liver fibrosis: a multicenter study.

OBJECTIVES: Liver cirrhosis (LC) is the end-stage of fibrosis in chronic liver diseases, non-invasive early detection of liver fibrosis (LF) is particularly essential for therapeutic decision. Aberrant glycosylation of glycoproteins has been demonstrated to be closely related to liver abnormalities. METHODS: This study was designed to enroll a total of 1,565 participants with LC/LF, chronic hepatitis virus (CHB) and healthy controls. Fibrosis was confirmed by liver biopsy. Using capillary electrophoresis N-glycan fingerprint (NGFP) analysis, we developed a nomogram algorithm (FIB-G) to discriminate LC from non-cirrhotic subjects. RESULTS: The FIB-G demonstrated good diagnostic performances in identifying LC with the area under the curve (AUC) 0.895 (95%CI: 0.857-0.915). Furthermore, the diagnostic efficiencies of FIB-G were superior to that of log (P2/P8), procollagen III N-terminal (PIIINP), type IV collage (IV-C), laminin (LN), hyaluronic acid (HA), aspartate transaminase to platelets ratio index (APRI), and FIB-4 when detecting significant fibrosis (S0-1 vs. S2-4, AUC: 0.787, 95%CI: 0.701-0.873), severe fibrosis (S0-2 vs. S3-4, AUC: 0.844, 95%CI: 0.763-0.924), and LC (S0-3 vs. S4, AUC: 0.773, 95%CI: 0.667-0.880). Besides, changes of FIB-G were associated well with the regression of fibrosis and liver function Child-Pugh classification. CONCLUSIONS: FIB-G is an accurate multivariant N-glycomic algorithm for LC prediction and fibrosis progression/regression monitoring. The high throughput feasible NGFP using only 2 µL of serum could help physicians make the more precise non-invasive staging of LF or cirrhosis and reduce the need for invasive liver biopsy.

Comprehensive analysis of genomic alterations of Chinese hilar cholangiocarcinoma patients.

BACKGROUND: Cholangiocarcinoma (CCA) is a rare malignant tumor of the biliary system. The heterogeneity of CCA leads to the lack of effective targeted treatment for CCA subtypes. The molecular characteristic of hilar CCA (hCCA) is still unclear. METHODS: A total of 63 hCCA patients were enrolled from Shanghai Eastern Hepatobiliary Surgery Hospital. Formalin-fixed, paraffin-embedded tumor tissues, and matched blood were collected and deep sequencing targeting 450 cancer genes were performed. Tumor mutation burden (TMB) was measured by an algorithm developed in-house. Correlation analysis was performed by Fisher's exact test. RESULTS: The most commonly mutated genes were TP53 (51.7%), NF1 and KRAS (20%, for both), SMAD4 (16.7%), FAT3 and FRS2 (13.3%, for both), NF1 (11.7%), and KMT2C, MDM2, and ATM (10%, for each) in hCCA. ARID1A, GATA6, and PREX2 mutations commonly occurred in female and KMT2C mutations mainly occurred in patients under 60 years old. Statistical analysis showed the association between ARID1A mutation and tumor stage (P = 0.041) and between NF1 mutation and high TMB (P = 0.0095). Furthermore, ARID1B mutation was identified to associate with the poor prognosis of Chinese hCCA patients (P = 0.004). CONCLUSION: The mutational characterization of hCCA is different from both extrahepatic CCA and intrahepatic CCA. ARID1B is a potential biomarker for prognosis prediction of Chinese hCCA patients.

Serum N-glycan profiling as a diagnostic biomarker for the identification and assessment of psoriasis.

BACKGROUND: Glycosylation is an important post-translational modification of protein. The change in glycosylation is involved in the occurrence and development of various diseases, and this study verified that N-glycan markers might be a diagnostic marker in psoriasis. METHODS: A total of 76 psoriasis patients were recruited. We used Psoriasis Area Severity Index (PASI) scores to evaluate the state of psoriasis, 41 of whom were divided into three subgroups: mild, moderate, and severe. At the same time, 76 healthy subjects were enrolled as a control group. We used DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) to analyze serum N-glycan profiling. RESULTS: Compared with the healthy controls, the relative abundance of structures in peaks 5(NA2), 9(NA3Fb), 11(NA4), and 12(NA4Fb) was elevated (p < .05), while that in peaks 3(NG1A2F), 4(NG1A2F), 6(NA2F), and 7(NA2FB) was decreased (p < .05) in the psoriasis group. The abundance of peak 5 (NA2) increased gradually with the aggravation of disease severity though there was no statistically significant, was probably correlated with the disease severity. The best area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression model (PglycoA) to diagnose psoriasis was 0.867, with a sensitivity of 72.37%, a specificity of 85.53%, a positive predictive value(PPV) of 83.33%, a negative predictive value(NPV) of 75.58%, and an accuracy of 78.95%. CONCLUSIONS: Our study indicated that the N-glycan-based diagnostic model would be a new, valuable, and noninvasive alternative for diagnosing psoriasis. Furthermore, the characteristic distinctive N-glycan marker might be correlated with the severity gradation of the psoriasis disease.

The clinical application of PIVKA-II in hepatocellular carcinoma and chronic liver diseases: A multi-center study in China.

BACKGROUND: Due to the absence of specific symptoms and low survival rate, efficient biomarkers for hepatocellular carcinoma (HCC) diagnosis are urgently required. The purpose of this study was to evaluate the diagnostic performance of protein induced by vitamin K absence or antagonist-II (PIVKA-II) and to determine the optimal cutoff values for HBV infection-related HCC. METHODS: We conducted a cross-sectional, multi-center study in China to ascertain the cutoff value for HCC patients in the context of CHB- and HBV-related cirrhosis. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were used to evaluate the diagnostic performance of PIVKA-II. RESULTS: This study enrolled 784 subjects and demonstrated that PIVKA-II had a sensitivity of 84.08% and a specificity of 90.43% in diagnosis HCC from chronic liver diseases. PIVKA-II at a cutoff of 37.5 mAU/mL yielded an AUC of 0.9737 (sensitivity 91.78% and specificity 96.30%) in discriminating HCC from chronic hepatitis B (CHB) patients. PIVKA-II at a cutoff of 45 mAU/mL yielded an AUC of 0.9419 (sensitivity 77.46% and specificity 95.12%) in discriminating HCC- from HBV-related cirrhosis patients. Furthermore, using a cutoff value of 40 mAU/mL for PIVKA-II as an HCC marker, only 4.81% (15/312) was positive in chronic hepatitis and 12.80% (37/289) in cirrhosis patients, revealing the satisfactory specificity of PIVKA-II in chronic liver disease of different etiologies. CONCLUSION: Our data indicated that PIVKA-II had satisfactory diagnostic efficiencies and could be used as a screening or surveillance biomarker in HCC high-risk population.

Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC.

Hepatitis B virus (HBV) infection is a common problem in the world, especially in China. More than 60-80% of hepatocellular carcinoma (HCC) cases can be attributed to HBV infection in high HBV prevalent regions. Although traditional Sanger sequencing has been extensively used to investigate HBV sequences, NGS is becoming more commonly used. Further, it is unknown whether word pattern frequencies of HBV reads by Next Generation Sequencing (NGS) can be used to investigate HBV genotypes and predict HCC status. In this study, we used NGS to sequence the pre-S region of the HBV sequence of 94 HCC patients and 45 chronic HBV (CHB) infected individuals. Word pattern frequencies among the sequence data of all individuals were calculated and compared using the Manhattan distance. The individuals were grouped using principal coordinate analysis (PCoA) and hierarchical clustering. Word pattern frequencies were also used to build prediction models for HCC status using both K-nearest neighbors (KNN) and support vector machine (SVM). We showed the extremely high power of analyzing HBV sequences using word patterns. Our key findings include that the first principal coordinate of the PCoA analysis was highly associated with the fraction of genotype B (or C) sequences and the second principal coordinate was significantly associated with the probability of having HCC. Hierarchical clustering first groups the individuals according to their major genotypes followed by their HCC status. Using cross-validation, high area under the receiver operational characteristic curve (AUC) of around 0.88 for KNN and 0.92 for SVM were obtained. In the independent data set of 46 HCC patients and 31 CHB individuals, a good AUC score of 0.77 was obtained using SVM. It was further shown that 3000 reads for each individual can yield stable prediction results for SVM. Thus, another key finding is that word patterns can be used to predict HCC status with high accuracy. Therefore, our study shows clearly that word pattern frequencies of HBV sequences contain much information about the composition of different HBV genotypes and the HCC status of an individual.

The diagnostic value of serum DSA-TRF in hepatocellular carcinoma.

TRF is a glycoprotein mainly secreted by hepatocytes, The aim of this study was to explore the diagnostic value of aberrant glycosylated serum transferrin (TRF) especially containing multi-antennary glycans in hepatocellular carcinoma (HCC).A total of 581 subjects including HCC patients, liver cirrhosis (LC) patients, chronic hepatitis (CHB) patients and healthy controls (HC) were recruited. All the subjects were randomly assigned to training group (n = 411) and validation group (n = 170). We firstly analyzed the serum protein N-glycome profiling of HCC, LC, and HC by DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) technology. We established a lectin-antibody sandwich ELISA (Lectin-ELISA) method to detect multi-antennary glycans-contained TRF (DSA-TRF) in serum, in which Datura stramonium Agglutinin (DSA) was used for specific recognition. Levels of serum DSA-TRF and TRF were analyzed respectively. The diagnostic efficacies of DSA-TRF and TRF of differentiating HCC patients from CHB, LC patients and HC within the training group were evaluated using receiver operating characteristic (ROC) curve and tested in the validation group.The result found that in training group, serum TRF and DSA-TRF levels differed significantly between HCC (1.86 ± 0.50, g/L, 0.285 ± 0.06), CHB + LC (2.39 ± 0.74, g/L, 0.189 ± 0.07) and HC (1.92 ± 0.69, g/L, 0.249 ± 0.09) (HCC vs. CHB + LC, P < 0.001; HCC vs. HC, P < 0.001; CHB + LC vs. HC, P < 0.001). The area under the ROC curve (AUC) of DSA-TRF was significantly superior to AFP (0.880, 95%CI: 0.834-0.925 vs. 0.776, 95%CI: 0.725-0.827, P = 0.003) in differentiating HCC from CHB + LC. The AUC of diagnostic model GlycoTRF1 (0.981, 95%CI: 0.969-0.993) was higher than DSA-TRF and AFP alone (P<0.001) in differentiating HCC from CHB + LC, which was verified in validation group.The results indicated that the serum DSA-TRF might serve as a potential glycan biomarker for distinguishing HCC from CHB and LC.