Genotype-phenotype correlation study of structural abnormalities in a fetal brain caused by a novel KDM4B variant.

BACKGROUND: Fetal ventriculomegaly (VM), a common brain structure malformation detected during prenatal ultrasound diagnosis, is associated with an increased risk of neurodevelopmental disorders (NDDs) after birth. KDM4B encodes a lysine-specific demethylase that interacts with histone H3K23me3. Variations in KDM4B are reportedly associated with human NDDs; however, only 11 such patients have been reported. Herein, we report a fetus with VM and agenesis of the corpus callosum (ACC), which suggests that KDM4B plays an important role in fetal brain development. METHODS: Fetal skin tissue and parental peripheral venous blood samples were collected. Whole-exome and Sanger sequencing were performed to analyze fetal germline variants. Human 293T cells transfected with wild-type or mutant KDM4B were used for western blotting (WB) to analyze protein expression levels. RESULTS: An insertion variant of KDM4B, NM_015015.3: c.2889_2890insGAGAGCATCACGGTGAGCTGTGGGGTGGGGCAGGGGGCGGGGGGAGGCTGGGAGCACAGTGACAACCTGTACCCC, was identified in the fetal tissue; however, the parents carried the wild-type gene. The WB results indicated significantly reduced expression of the mutant protein, likely owing to decreased stability. CONCLUSIONS: The structural abnormalities in the brain of the studied fetus may be attributed to an insertion variant of KDM4B. This study highlights the importance of screening for KDM4B variants and considering potential copy number variations when observing VM or ACC in prenatal ultrasound imaging.

Prenatal case report of Barth syndrome caused by novel TAFAZZIN mutation: Clinical characteristics of fetal dilated cardiomyopathy with ascites.

Barth syndrome (BTHS) is a rare X-linked recessive genetic disease, which appears in infancy with myocardial and skeletal muscle diseases, neutropenia, growth retardation, and other clinical features. TAFAZZIN is the pathogenic gene of BTHS, which encodes the tafazzin protein of the inner membrane of the mitochondria, a phosphatidyltransferase involved in cardiolipin remodeling and functional maturation. At present, BTHS has been widely reported, but prenatal cases are rare. We report a 24+4-week fetus with clinical manifestations including left ventricular insufficiency and ascites. After induced labor, whole exome sequencing detection of fetal skin tissue showed that TAFAZZIN had the mutation c.311A > C/p.His104Pro and that his mother was the carrier. This His104Pro mutation has hitherto not been reported, and it is rated as likely to be pathogenic according to the American College of Medical Genetics and Genetics guidelines. Molecular dynamics and protein expression experiments on the His104Pro mutation showed that the stability of the local protein structure and protein expression were reduced. In conclusion, the case presented in this study enriches our knowledge of the TAFAZZIN mutation spectrum and suggests that His104Pro may lead to cardiac structural abnormalities in the early embryo. The possibility of BTHS should be considered when an abnormal cardiac structure or ascites appear in a prenatal ultrasound.

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.

Prenatal ultrasound-assisted identification of multiple malformations caused by a deletion in the long-arm end of chromosome 7 and review of the literature.

Clinical cases of chromosome 7 long-arm end deletion are rare. Generally, 7q terminal deletion syndrome results in complex clinical phenotypes, such as microcephaly, growth and development retardation, holoprosencephaly, and sacral hypoplasia. Herein, we report the genetic and clinical features of a fetus with multiple malformations observed by prenatal ultrasound. The results showed that there was a large fragment deletion of approximately 27.7 Mb in 7q32.3-qter. The induced fetus showed facial abnormalities of cleft lip and palate, and some organ structural abnormalities (such as diaphragmatic hernia and polycystic renal dysplasia) were observed by autopsy and pathology. To provide more reliable information for disease diagnosis and genetic counseling, we reviewed and analyzed the reported cases of isolated 7q terminal syndrome.

Lymphocyte-monocyte-neutrophil index: a predictor of severity of coronavirus disease 2019 patients produced by sparse principal component analysis.

BACKGROUND: It is important to recognize the coronavirus disease 2019 (COVID-19) patients in severe conditions from moderate ones, thus more effective predictors should be developed. METHODS: Clinical indicators of COVID-19 patients from two independent cohorts (Training data: Hefei Cohort, 82 patients; Validation data: Nanchang Cohort, 169 patients) were retrospected. Sparse principal component analysis (SPCA) using Hefei Cohort was performed and prediction models were deduced. Prediction results were evaluated by receiver operator characteristic curve and decision curve analysis (DCA) in above two cohorts. RESULTS: SPCA using Hefei Cohort revealed that the first 13 principal components (PCs) account for 80.8% of the total variance of original data. The PC1 and PC12 were significantly associated with disease severity with odds ratio of 4.049 and 3.318, respectively. They were used to construct prediction model, named Model-A. In disease severity prediction, Model-A gave the best prediction efficiency with area under curve (AUC) of 0.867 and 0.835 in Hefei and Nanchang Cohort, respectively. Model-A's simplified version, named as LMN index, gave comparable prediction efficiency as classical clinical markers with AUC of 0.837 and 0.800 in training and validation cohort, respectively. According to DCA, Model-A gave slightly better performance than others and LMN index showed similar performance as albumin or neutrophil-to-lymphocyte ratio. CONCLUSIONS: Prediction models produced by SPCA showed robust disease severity prediction efficiency for COVID-19 patients and have the potential for clinical application.

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.

A Nomogram Predicting Extrahepatic Metastases for Patients with Adjuvant Transarterial Chemoembolization after Hepatectomy.

Background: Prognosis remains poor for hepatocellular carcinoma (HCC) patients with extrahepatic metastases (EHMs). This study aimed to develop a nomogram to predict EHMs in HCC patients who underwent adjuvant transarterial chemoembolization (TACE) following hepatectomy. Methods: Data of 578 HCC patients who underwent TACE after hepatectomy at the Eastern Hepatobiliary Surgery Hospital was retrospectively reviewed. Cox regression analyses was used to select variables to construct the nomogram. Predictive accuracy and discriminative ability of the model were performed using concordance index (C-index), calibration curve and the area under time-dependent receiver operating characteristic (ROC) curve. Results: Postoperative EHMs were detected in 89 and 31 patients in the training cohort (n = 453) and validation cohort (n = 125), respectively. Multivariate analysis showed that tumor size (HR, 1.099; 95% CI, 1.049-1.152), coarse beam type of tumor histopathological structure (HR, 2.382; 95% CI, 1.030-5.512), presence of satellite nodules (HR, 1.936; 95% CI, 1.156-3.244) and alpha-fetoprotein (AFP) (HR, 1.399; 95% CI, 1.098-1.783) were independent risk factors for EHMs (all p < 0.05). The nomogram incorporated these factors achieved good agreement between prediction and actual observation with a concordance index (C-index) of 0.73 (95% CI, 0.68 to 0.78) and 0.71 (95% CI, 0.63 to 0.79) in the training cohort and validation cohort, respectively. In addition, patients who had a nomogram score > 17 were considered to have higher risk for EHMs compared with those scored ≤ 12. Furthermore, the time-dependent area under the ROC curve indicated comparative stability and adequate discriminative ability of the model. Conclusions: This novel nomogram can identify those with high risk of EHMs after adjuvant TACE following hepatectomy. The validation cohort showed a good performance, suggesting it could benefit surgeons on decision-making.

Clinical evaluation of hepatitis B core-related antigen in chronic hepatitis B and hepatocellular carcinoma patients.

BACKGROUND: Hepatitis B core-related antigen (HBcrAg) has been revealed as an important marker of Hepatitis B virus (HBV) infection recently. We aimed to evaluate the HBcrAg assay for indication of HBV loads in chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients and assess the association between HBcrAg/cccDNA and HCC recurrence. METHODS: HBcrAg was measured by chemiluminescence enzyme immunoassay. Intrahepatic covalently closed circular DNA (cccDNA) was measured by real-time PCR with TaqMan fluorescent probes based on liver specimens from 89 HCC patients. RESULTS: HBcrAg correlated positively with HBV DNA irrespective of HBeAg status. Both HBcrAg and HBV DNA were associated with cccDNA in patients with elevated serum HBV DNA (>4 log IU/mL). In patients with non-elevated HBV DNA (≤4 log IU/mL), no relationship between HBV DNA and cccDNA was observed, but we still documented a modest correlation between HBcrAg and cccDNA. Finally, the recurrence-free survival rates were significantly lower in HCC patients with high intrahepatic cccDNA and serum HBcrAg levels than those with low cccDNA/HBcrAg levels (p = 0.035, p = 0.003 respectively). CONCLUSIONS: HBcrAg not only can serve as a biomarker to assess HBV loads in patients as well as provide a good method for monitoring cccDNA in HCC, but also can be used as a good prognostic predictor for HCC patients.

A nomogram incorporating six easily obtained parameters to discriminate intrahepatic cholangiocarcinoma and hepatocellular carcinoma.

Intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are the most prevalent histologic types of primary liver cancer (PLC). Although ICC and HCC share similar risk factors and clinical manifestations, ICC usually bears poorer prognosis than HCC. Confidently discriminating ICC and HCC before surgery is beneficial to both treatment and prognosis. Given the lack of effective differential diagnosis biomarkers and methods, construction of models based on available clinicopathological characteristics is in need. Nomograms present a simple and efficient way to make a discrimination. A total of 2894 patients who underwent surgery for PLC were collected. Of these, 1614 patients formed the training cohort for nomogram construction, and thereafter, 1280 patients formed the validation cohort to confirm the model's performance. Histopathologically confirmed ICC was diagnosed in 401 (24.8%) and 296 (23.1%) patients in these two cohorts, respectively. A nomogram integrating six easily obtained variables (Gender, Hepatitis B surface antigen, Aspartate aminotransferase, Alpha-fetoprotein, Carcinoembryonic antigen, Carbohydrate antigen 19-9) is proposed in accordance with Akaike's Information Criterion (AIC). A score of 15 was determined as the cut-off value, and the corresponding discrimination efficacy was sufficient. Additionally, patients who scored higher than 15 suffered poorer prognosis than those with lower scores, regardless of the subtype of PLC. A nomogram for clinical discrimination of ICC and HCC has been established, where a higher score indicates ICC and poor prognosis. Further application of this nomogram in multicenter investigations may confirm the practicality of this tool for future clinical use.

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.

Next-generation sequencing revealed divergence in deletions of the preS region in the HBV genome between different HBV-related liver diseases.

In order to investigate if deletion patterns of the preS region can predict liver disease advancement, the preS region of the hepatitis B virus (HBV) genome in 45 chronic hepatitis B (CHB) and 94 HBV-related hepatocellular carcinoma (HCC) patients was sequenced by next-generation sequencing (NGS) and the percentages of nucleotide deletion in the preS region were analysed. Hierarchical clustering and heatmaps based on deletion percentages of preS revealed different deletion patterns between CHB and HCC patients. Intergenotype comparison also indicated divergence in preS deletions between HBV genotype B and C. No significant difference was found in preS deletion patterns between sera and matched adjacent non-tumour tissues. Based on hierarchical clustering, HCC patients were classed into two groups with different preS deletion patterns and different clinical features. Finally, the support vector machine (SVM) model was trained on preS nucleotide deletion percentages and used to predict HCC versus CHB patients. The prediction performance was assessed with fivefold cross-validation and independent cohort validation. The median area under the curve (AUC) was 0.729 after repeating SVM 500 times with fivefold cross-validations. After parameter optimization, the SVM model was used to predict an independent cohort with 51 CHB patients and 72 HCC patients and the AUC was 0.727. In conclusion, the use of the NGS method revealed a prominent divergence in preS deletion patterns between disease groups and virus genotypes, but not between different tissue types. Quantitative NGS data combined with a machine learning method could be a powerful approach for prediction of the status of different diseases.

Hepatitis B virus core antigen mutations predict post-operative prognosis of patients with primary hepatocellular carcinoma.

The aim of this study was to explore the relationship between hepatitis B virus (HBV) core antigen (HBc) mutations and the post-operative prognosis of HBV-related hepatocellular carcinoma (HCC). In total, 98 patients suffering from HBV-related HCC and treated with surgery were enrolled, with a 48 month follow-up. The preCore/Core region of the HBV genome from tumour tissue (TT) and paired adjacent non-tumour tissue (ANTT) of these patients was sequenced, and a phylogenetic tree was reconstructed. The correlations between the viral features and evolutionary divergence of preCore/Core amino acid sequences from 67 paired TTs and ANTTs were analysed. Cox proportional hazard model analysis was applied for post-operative hazard risk evaluation. Phylogenetic analysis revealed that all of the sequences were ascribed to genotype C. The evolutionary divergence of amino acid sequences from matched TTs and ANTTs was significantly negatively correlated with serum and intrahepatic HBV DNA levels. Multivariate analysis showed that the HBc E77 mutation was associated with shorter overall survival, and HBc S87 and P156 mutations were independent risk factors for relapse. Furthermore, in contrast to with patients without the S87 mutation, no correlation was observed between serum HBV DNA and intrahepatic HBV DNA in HCC patients with the S87 mutation. Analysis of the intrahepatic sequence may advance our understanding of viral status; thus, it is useful for prognosis prediction for HBV-related HCC.

F221Y mutation in hepatitis B virus reverse transcriptase is associated with hepatocellular carcinoma prognosis following liver resection.

Hepatitis B virus (HBV) reverse transcriptase (RT) is encoded by the polymerase gene in the reverse transcriptase region, which overlaps with the S gene. The association between mutations of HBV RT and the pathobiological features of hepatocellular carcinoma (HCC) remain to be elucidated. The present study aimed to examine mutations in this region of the HBV genome and its clinical significance. Briefly, HBV total DNA was extracted from 84 pairs of HCC tumor tissue and corresponding adjacent non­tumor tissue samples. The RT/S regions (nt130­1161) were amplified and sequenced using the Sanger method, and associations between RT mutations and the clinical characteristics of patients with HCC were analyzed. Finally, 27 and 29 mutations with frequencies >5% were identified in the RT and S regions, respectively. The rtF221Y variation and a tumor size >8 cm were found to be independent risk factors for the postoperative recurrence of HCC, with hazard ratios of 2.345 (95% CI, 1.391­3.953; P=0.001) and 1.838 (95% CI, 1.069­3.161; P=0.028), respectively. rtF221Y was also an independent risk factor for poor overall survival rates (HR=2.557; 95% CI, 1.344­4.866; P=0.004). The mutation of R122 K in the HBV S protein was closely associated with tumor recurrence (P<0.001). As a result, rtF221Y was identified as a risk factor for poor prognosis and may be a potential viral marker for predicting prognosis in HCC.

Phage-based molecular directed evolution yields multiple tandem human IgA affibodies with intramolecular binding avidity.

Affibodies are a group of affinity proteins that are based on a 58-amino-acid residue protein domain derived from one of the IgG-binding domains of staphylococcal protein A. A single human IgA affibody with high IgA affinity has been generated by directed evolution. It remains interesting whether tandem IgA affibody proteins could increase binding capacity. Here, we report the generation of multiple tandem IgA affibodies by directed evolution using a combinatorial phage library displaying the IgA affibody A1 and/or A2 linked with three random amino acids. These affibodies exhibited markedly increased IgA binding capacity, as shown by enzyme linked immunosorbent assay, immunoblotting and surface plasmon resonance assays. We further showed that these tandem IgA affibodies displayed preferential binding to intact IgA molecules compared to individual IgA chain, suggesting intramolecular binding avidity. Our data demonstrates that artificial multiple tandem human IgA affibodies with relevant biological binding avidity were successfully yielded by phage-based molecular evolution. These results have broad implications for the design and development of binding proteins that target important biological molecules.

Evolutional selection of a combinatorial phage library displaying randomly-rearranged various single domains of immunoglobulin (Ig)-binding proteins (IBPs) with four kinds of Ig molecules.

BACKGROUND: Protein A, protein G and protein L are three well-defined immunoglobulin (Ig)-binding proteins (IBPs), which show affinity for specific sites on Ig of mammalian hosts. Although the precise functions of these molecules are not fully understood, it is thought that they play an important role in pathogenicity of bacteria. The single domains of protein A, protein G and protein L were all demonstrated to have function to bind to Ig. Whether combinations of Ig-binding domains of various IBPs could exhibit useful novel binding is interesting. RESULTS: We used a combinatorial phage library which displayed randomly-rearranged various-peptide-linked molecules of D and A domains of protein A, designated PA(D) and PA(A) respectively, B2 domain of protein G (PG) and B3 domain of protein L (PL) for affinity selection with human IgG (hIgG), human IgM (hIgM), human IgA (hIgA) and recombinant hIgG1-Fc as bait respectively. Two kinds of novel combinatorial molecules with characteristic structure of PA(A)-PG and PA(A)-PL were obtained in hIgG (hIgG1-Fc) and hIgM (hIgA) post-selection populations respectively. In addition, the linking peptides among all PA(A)-PG and PA(A)-PL structures was strongly selected, and showed interestingly divergent and convergent distribution. The phage binding assays and competitive inhibition experiments demonstrated that PA(A)-PG and PA(A)-PL combinations possess comparable binding advantages with hIgG/hIgG1-Fc and hIgM/hIgA respectively. CONCLUSION: In this work, a combinatorial phage library displaying Ig-binding domains of protein A, protein G, or protein L joined by various random linking peptides was used to conducted evolutional selection in vitro with four kinds of Ig molecules. Two kinds of novel combinations of Ig-binding domains, PA(A)-PG and PA(A)-PL, were obtained, and demonstrate the novel Ig binding properties.