Uncovering the microbiome landscape in sashimi delicacies.

It is widely believed that a significant portion of the gut microbiota, which play crucial roles in overall health and disease, originates from the food we consume. Sashimi is a type of popular raw seafood cuisine. Its microbiome, however, remained to be thoroughly explored. The objective of this study is to explore the microbiome composition in sashimi at the time when it is served and ready to be eaten. Specifically, our tasks include investigating the diversity and characteristics of microbial profiles in sashimi with respect to the fish types. We utilized the Sanger-sequencing based DNA barcoding technology for fish species authentication and next-generation sequencing for sashimi microbiome profiling. We investigated the microbiome profiles of amberjack, cobia, salmon, tuna and tilapia sashimi, which were all identified using the MT-CO1 DNA sequences regardless of their menu offering names. Chao1 and Shannon indexes, as well as Bray-Curtis dissimilarity index were used to evaluate the alpha and beta diversities of sashimi microbiome. We successfully validated our previous observation that tilapia sashimi has a significantly higher proportions of Pseudomonas compared to other fish sashimi, using independent samples (P = 0.0010). Salmon sashimi exhibited a notably higher Chao1 index in its microbiome in contrast to other fish species (P = 0.0031), indicating a richer and more diverse microbial ecosystem. Non-Metric Multidimensional Scaling (NMDS) based on Bray-Curtis dissimilarity index revealed distinct clusters of microbiome profiles with respect to fish types. Microbiome similarity was notably observed between amberjack and tuna, as well as cobia and salmon. The relationship of microbiome similarity can be depicted as a tree which resembles partly the phylogenetic tree of host species, emphasizing the close relationship between host evolution and microbial composition. Moreover, salmon exhibited a pronounced relative abundance of the Photobacterium genus, significantly surpassing tuna (P = 0.0079), observed consistently across various restaurant sources. In conclusion, microbiome composition of Pseudomonas is significantly higher in tilapia sashimi than in other fish sashimi. Salmon sashimi has the highest diversity of microbiome among all fish sashimi that we analyzed. The level of Photobacterium is significantly higher in salmon than in tuna across all the restaurants we surveyed. These findings provide critical insights into the intricate relationship between the host evolution and the microbial composition. These discoveries deepen our understanding of sashimi microbiota, facilitating our decision in selecting raw seafood.

Predicting long-term time to cardiovascular incidents using myocardial perfusion imaging and deep convolutional neural networks.

Myocardial perfusion imaging (MPI) is a clinical tool which can assess the heart's perfusion status, thereby revealing impairments in patients' cardiac function. Within the MPI modality, the acquired three-dimensional signals are typically represented as a sequence of two-dimensional grayscale tomographic images. Here, we proposed an end-to-end survival training approach for processing gray-scale MPI tomograms to generate a risk score which reflects subsequent time to cardiovascular incidents, including cardiovascular death, non-fatal myocardial infarction, and non-fatal ischemic stroke (collectively known as Major Adverse Cardiovascular Events; MACE) as well as Congestive Heart Failure (CHF). We recruited a total of 1928 patients who had undergone MPI followed by coronary interventions. Among them, 80% (n = 1540) were randomly reserved for the training and 5- fold cross-validation stage, while 20% (n = 388) were set aside for the testing stage. The end-to-end survival training can converge well in generating effective AI models via the fivefold cross-validation approach with 1540 patients. When a candidate model is evaluated using independent images, the model can stratify patients into below-median-risk (n = 194) and above-median-risk (n = 194) groups, the corresponding survival curves of the two groups have significant difference (P < 0.0001). We further stratify the above-median-risk group to the quartile 3 and 4 group (n = 97 each), and the three patient strata, referred to as the high, intermediate and low risk groups respectively, manifest statistically significant difference. Notably, the 5-year cardiovascular incident rate is less than 5% in the low-risk group (accounting for 50% of all patients), while the rate is nearly 40% in the high-risk group (accounting for 25% of all patients). Evaluation of patient subgroups revealed stronger effect size in patients with three blocked arteries (Hazard ratio [HR]: 18.377, 95% CI 3.719-90.801, p < 0.001), followed by those with two blocked vessels at HR 7.484 (95% CI 1.858-30.150; p = 0.005). Regarding stent placement, patients with a single stent displayed a HR of 4.410 (95% CI 1.399-13.904; p = 0.011). Patients with two stents show a HR of 10.699 (95% CI 2.262-50.601; p = 0.003), escalating notably to a HR of 57.446 (95% CI 1.922-1717.207; p = 0.019) for patients with three or more stents, indicating a substantial relationship between the disease severity and the predictive capability of the AI for subsequent cardiovascular inciidents. The success of the MPI AI model in stratifying patients into subgroups with distinct time-to-cardiovascular incidents demonstrated the feasibility of proposed end-to-end survival training approach.

Structure-based approaches against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has had a major impact on human life. This review highlights the versatile roles of both classical and modern structure-based approaches for COVID-19. X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryogenic electron microscopy are the three cornerstones of classical structural biology. These technologies have helped provide fundamental and detailed knowledge regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the related human host proteins as well as enabled the identification of its target sites, facilitating the cessation of its transmission. Further progress into protein structure modeling was made using modern structure-based approaches derived from homology modeling and integrated with artificial intelligence (AI), facilitating advanced computational simulation tools to actively guide the design of new vaccines and the development of anti-SARS-CoV-2 drugs. This review presents the practical contributions and future directions of structure-based approaches for COVID-19.

A multiomic investigation of lung adenocarcinoma molecular subtypes.

BACKGROUND: Lung adenocarcinoma-an aggressive and life-threatening malignancy-is a type of non-small-cell lung cancer. Despite medical advancements, the prognosis of lung adenocarcinoma remains unfavorable, likely because of its heterogeneous nature. Furthermore, few subtype-specific treatments are available for lung adenocarcinoma. This study was conducted to explore the molecular subtypes of lung adenocarcinoma. METHODS: We performed a joint analysis of transcriptome and proteome data from East Asian patients with lung adenocarcinoma (nonsmokers, 86.5%). RESULTS: Four novel subtypes were identified based on distinct molecular characteristics: subtypes I, II, III, and IV. In patients with subtype I lung adenocarcinoma, eukaryotic translation initiation factor 4 gamma 1 activates cell proliferation; inhibiting this factor suppresses tumor growth, and reducing its level induces autophagy. Subtype II is characterized by Kristen rat sarcoma viral oncogene homolog-activating oncogenesis; the onset age of this subtype is the lowest among all subtypes. Subtype III manifests as an advanced disease at diagnosis; it is characterized by a core serum response-related oncogenic signature, which indicates poor overall survival in Western patients with lung cancer. Subtype IV is more common in men than in women; it has astroglial characteristics. A Connectivity Map analysis revealed that the oncogenic expression patterns corresponding to subtypes I, II, III, and IV can be reversed by the inhibitors of Inhibitor of κB (IκB) kinase (eg, withaferin A), mammalian target of rapamycin (eg, everolimus), Src proto-oncogene (Src) (eg, saracatinib), and Transforming Growth Factor (TGF)-ß/Smad (eg, LY-364947), respectively. CONCLUSION: This study introduced an innovative multiomics data analysis pipeline. Using this approach, we successfully identified four molecular subtypes of lung adenocarcinoma and their candidate therapeutic agents. The newly identified subtypes can be combined with the current biomarkers to generate a comprehensive roadmap for treatment decision-making.

Antiviral therapy reduces hepatocellular carcinoma through suppressing hepatitis B virus replication may improve ER stress, mitochondrial and metabolic dysfunctions and decrease p62 in hybridized mice with single HBV transgene and miR-122.

Hepatitis B virus (HBV) hijacks autophagy for its replication. Nucleos(t)ide analogs (NUCs) treatment suppressed HBV replication and reduced hepatocellular carcinoma (HCC) incidence. However, the use of NUCs in chronic hepatitis B (CHB) patients with normal or minimally elevated serum alanine aminotransferase (ALT) levels is still debated. Animal models are crucial for studying the unanswered issue and evaluating new therapies. MicroRNA-122 (miR-122), which regulates fatty acid and cholesterol metabolism, is downregulated during hepatitis and HCC progression. The reciprocal inhibition of miR-122 with HBV highlights its role in HCC development as a tumor suppressor. By crossbreeding HBV-transgenic mice with miR-122 knockout mice, we generated a hybrid mouse model with a high incidence of HCC up to 89% and normal ALT levels before HCC. The model exhibited early-onset hepatic steatosis, progressive liver fibrosis, and impaired late-phase autophagy. Metabolomics and microarray analysis identified metabolic signatures, including dysregulation of lipid metabolism, inflammation, genomic instability, the Warburg effect, reduced TCA cycle flux, energy deficiency, and impaired free radical scavenging. Antiviral treatment reduced HCC incidence in hybrid mice by approximately 30-35% compared to untreated mice. This effect was linked to the activation of ER stress-responsive transcription factor ATF4, clearance of autophagosome cargo p62, and suppression of the CHOP-mediated apoptosis pathway. In summary, this study suggests that despite minimal ALT elevation, HBV replication can lead to liver injury. Endoplasmic reticulum stress, reduced miR-122 levels, mitochondrial and metabolic dysfunctions, blocking protective autophagy resulting in p62 accumulation, apoptosis, fibrosis, and HCC. Antiviral may improve the above-mentioned pathogenesis through HBV suppression.

Portable sensing devices for smart healthcare and prevention of lead poisoning.

Lead (Pb) poisoning can damage human bodies silently, without specific symptoms or conspicuous warning signs. To provide safe and user-friendly tools for detecting heavy metals at low concentrations, scientists have developed and optimized versatile biosensors. To practically employ the developed biosensors specific for Pb (eg, the optimized Met-lead 1.44 M1), smartphone applications designed for user convenience and are easily operable for the on-site detection of Pb in environmental water, drinking water, food, and blood/urine are urgently needed. To establish a monitoring system for home health maintenance, a portable device and useful apps installed on a smartphone can be integrated, and the data acquired can be sent to and stored in the cloud for further analysis and evidence preservation. With the high transmissions speeds for 4G and 4G wireless Internet, such a system can be applied for health protection; water-quality data can be provided by anyone and publicly shared for display on smartphone interfaces, alerting individuals of heavy metal contamination. In this review, we describe recent developments in heavy metal-sensing devices, including home health maintenance systems, which have been successfully and practically applied to prevent heavy metal Pb poisoning.

A Single Nucleotide Polymorphism rs1010816 Predicts Sorafenib Therapeutic Outcomes in Advanced Hepatocellular Carcinoma.

Sorafenib is currently a targeted agent widely used in the treatment of advanced hepatocellular carcinoma (aHCC). However, to date there is still a lack of a reliable marker capable of predicting sorafenib therapeutic responses. Here, we conducted a genome-wide association study (GWAS) to identify candidate single-nucleotide polymorphism outcome predictors in aHCC patients. A total of 74 real-world sorafenib-treated aHCC patients were enrolled for GWAS and outcome analysis. GWAS showed that rs1010816 (p = 2.2 × 10-7) was associated with sorafenib therapeutic response in aHCC patients. Kaplan-Meier analysis indicated that the "TT" genotype was significantly associated with a favorable therapeutic response but not significantly associated with overall survival (OS). Univariate followed by multivariate Cox proportional hazard analysis showed that ascites, main portal vein thrombosis, lower platelet count, lower total sorafenib doses, higher PALBI score in model A and higher ALBI grade in model B were significantly associated with a shorter OS. Subgroup analysis showed that only in alcoholic aHCC patients treated by sorafenib, rs1010816 "TT" genotype was significantly associated with longer OS (p = 0.021). Sorafenib had a favorable therapeutic outcome in alcoholic aHCC patients carrying rs1010816 "TT" genotype.

Smart healthcare: A prospective future medical approach for COVID-19.

COVID-19 has greatly affected human life for over 3 years. In this review, we focus on smart healthcare solutions that address major requirements for coping with the COVID-19 pandemic, including (1) the continuous monitoring of severe acute respiratory syndrome coronavirus 2, (2) patient stratification with distinct short-term outcomes (eg, mild or severe diseases) and long-term outcomes (eg, long COVID), and (3) adherence to medication and treatments for patients with COVID-19. Smart healthcare often utilizes medical artificial intelligence (AI) and cloud computing and integrates cutting-edge biological and optoelectronic techniques. These are valuable technologies for addressing the unmet needs in the management of COVID. By leveraging deep learning/machine learning capabilities and big data, medical AI can perform precise prognosis predictions and provide reliable suggestions for physicians' decision-making. Through the assistance of the Internet of Medical Things, which encompasses wearable devices, smartphone apps, internet-based drug delivery systems, and telemedicine technologies, the status of mild cases can be continuously monitored and medications provided at home without the need for hospital care. In cases that develop into severe cases, emergency feedback can be provided through the hospital for rapid treatment. Smart healthcare can possibly prevent the development of severe COVID-19 cases and therefore lower the burden on intensive care units.

The Omicron variant wave: Where are we now and what are the prospects?

The Omicron variant BA.2 is the dominant form of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in many countries, including those that have already implemented the strictest quarantine mandates that effectively contained the spread of the previous variants. Although many individuals were partially or fully vaccinated, confirmed Omicron infections have far surpassed all other variants combined in just a couple of months since the Omicron variant emerged. The ChAdOx1-S (AstraZeneca), BNT162b2 (Pfizer-BioNTech), and mRNA-1273 (Moderna) vaccines offer protection against the severe illness of SARS-CoV-2 infection; however, these currently available vaccines are less effective in terms of preventing Omicron infections. As a result, a booster dose of BNT162b2 or mRNA-1273 is recommended for individuals >12 years old who had received their second dose of the approved vaccines for >5 months. Herein, we review the studies that assessed the clinical benefits of the booster dose of vaccines against Omicron infections. We also analyzed public data to address whether early booster vaccination effectively prevented the surge of the Omicron infections. Finally, we discuss the consideration of a fourth dose of vaccine as a way to prevent possible upcoming infections.

Oncogenic Roles of Polycomb Repressive Complex 2 in Bladder Cancer and Upper Tract Urothelial Carcinoma.

Cancers of the urinary tract are one of the most common malignancies worldwide, causing high morbidity and mortality, and representing a social burden. Upper tract urothelial carcinoma (UTUC) accounts for 5−10% of urinary tract cancers, and its oncogenic mechanisms remain elusive. We postulated that cancers of the lower and the upper urinary tract may share some important oncogenic mechanisms. Therefore, the oncogenic mechanisms discovered in the lower urinary tract may guide the investigation of molecular mechanisms in the upper urinary tract. Based on this strategy, we revisited a high-quality transcriptome dataset of 510 patients with non-muscle invasive bladder cancer (NMIBC), and performed an innovative gene set enrichment analysis of the transcriptome. We discovered that the epigenetic regulation of polycomb repressive complex 2 (PRC2) is responsible for the recurrence and progression of lower-track urinary cancers. Additionally, a PRC2-related gene signature model was discovered to be effective in classifying bladder cancer patients with distinct susceptibility of subsequent recurrence and progression (log-rank p < 0.001 and = 0.001, respectively). We continued to discover that the same model can differentiate stage T3 UTUC patients from stage Ta/T1 patients (p = 0.026). Immunohistochemical staining revealed the presence of PRC2 components (EZH2, EED, and SUZ12) and methylated PRC2 substrates (H3K27me3) in the archived UTUC tissues. The H3K27me3 exhibited higher intensity and area intensity product in stage T3 UTUC tissues than in stage Ta/T1 tissues (p = 0.006 and 0.015, respectively), implicating stronger PRC2 activity in advanced UTUC. The relationship between H3K27 methylation and gene expression is examined using correlations. The H3K27me3 abundance is positively correlated with the expression levels of CDC26, RP11-2B6, MAPK1IP1L, SFR1, RP11-196B3, CDK5RAP2, ANXA5, STX11, PSMD5, and FGFRL1. It is also negatively correlated with CNPY2, KB-1208A12, RP11-175B9, ZNF692, RANP8, RP11-245C17, TMEM266, FBXW9, SUGT1P2, and PRH1. In conclusion, PRC2 and its epigenetic effects are major oncogenic mechanisms underlying both bladder cancer and UTUC. The epigenetically regulated genes of PRC2 in urothelial carcinoma were also elucidated using correlation statistics.

SARS-CoV-2 vaccines in children and adolescents: Can immunization prevent hospitalization?

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants of concern can infect people of all ages and can cause severe diseases in children, such as encephalitis, which require intensive care. Therefore, vaccines are urgently required to prevent severe disease in all age groups. We reviewed the safety and efficacy profiles of mRNA vaccines-BNT162b2 and mRNA-1273-demonstrated by clinical trials or observed in the real world. mRNA-1273 is effective in preventing SARS-CoV-2 infection in preschool children (6 months-6 years old). Both BNT162b2 and mRNA-1273 are effective in preventing SARS-CoV-2 infection in school-aged children and adolescents, thereby preventing post-coronavirus disease (COVID) conditions. The common side effects of vaccination are pain at the injection site, fatigue, and headache. Myocarditis and pericarditis are uncommon. Monitoring post-vaccination troponin levels may help prevent severe cardiac events. The SARS-CoV-2 coronavirus mutates its genome to overcome the herd immunity provided by mass vaccinations; therefore, we may need to develop new generations of vaccines, such as those using viral nucleocapsid proteins as antigens. In conclusion, the mRNA vaccines are generally safe and effective in preventing severe diseases and hospitalization among children and adolescents.

State-of-the-Art Molecular Oncology of Lung Cancer in Taiwan.

Lung cancers are life-threatening malignancies that cause great healthcare burdens in Taiwan and worldwide. The 5-year survival rate for Taiwanese patients with lung cancer is approximately 29%, an unsatisfactorily low number that remains to be improved. We first reviewed the molecular epidemiology derived from a deep proteogenomic resource in Taiwan. The nuclear factor erythroid 2-related factor 2 (NRF2)antioxidant mechanism was discovered to mediate the oncogenesis and tumor progression of lung adenocarcinoma. Additionally, DNA replication, glycolysis and stress response are positively associated with tumor stages, while cell-to-cell communication, signaling, integrin, G protein coupled receptors, ion channels and adaptive immunity are negatively associated with tumor stages. Three patient subgroups were discovered based on the clustering analysis of protein abundance in tumors. The first subgroup is associated with more advanced cancer stages and visceral pleural invasion, as well as higher mutation burdens. The second subgroup is associated with EGFR L858R mutations. The third subgroup is associated with PI3K/AKT pathways and cell cycles. Both EGFR and PI3K/AKT signaling pathways have been shown to induce NRF2 activation and tumor cell proliferation. We also reviewed the clinical evidence of patient outcomes in Taiwan given various approved targeted therapies, such as EGFR-tyrosine kinase inhibitors and anaplastic lymphoma kinase (ALK)inhibitors, in accordance with the patients' characteristics. Somatic mutations occurred in EGFR, KRAS, HER2 and BRAF genes, and these mutations have been detected in 55.7%, 5.2%, 2.0% and 0.7% patients, respectively. The EGFR mutation is the most prevalent targetable mutation in Taiwan. EML4-ALK translocations have been found in 9.8% of patients with wild-type EGFR. The molecular profiling of advanced NSCLC is critical to optimal therapeutic decision-making. The patient characteristics, such as mutation profiles, protein expression profiles, drug-resistance profiles, molecular oncogenic mechanisms and patient subgroup systems together offer new strategies for personalized treatments and patient care.

Prognosis Comparison Between Chronic Hepatitis B Patients Receiving a Finite Course of Tenofovir and Entecavir Treatment: A Nationwide Cohort Study in Taiwan.

PURPOSE: Entecavir (ETV) and tenofovir disoproxil fumarate (TDF) are both recommended as first-line treatments for patients with chronic hepatitis B virus (CHB) infection according to international HBV treatment guidelines. However, recent studies reported conflicting results regarding the preferred antiviral in the prevention of hepatocellular carcinoma (HCC). This cohort study aimed to investigate this issue by using Taiwan's National Health Insurance Research Database, wherein a "finite" but not life-long treatment policy was applied. METHODS: From January 2008 to December 2013, a total of 12,388 consecutive adult patients with CHB who received a finite course of TDF treatment (n = 1250) or ETV treatment (n = 11,138) were analyzed through screening for study eligibility followed by the 1:4 propensity score matching method. FINDINGS: In the entire cohort, the annual incidence and survival between the ETV and TDF groups were not significantly different regarding HCC occurrence (2.05 vs 2.74 per 100 patient-years [PY]; P = 0.055; hazard ratio [HR], 0.975; log-rank, P = 0.966), cirrhosis-related complications (1.9 vs 2.4 per 100 PY; P = 0.149; HR, 0.869; log-rank, P = 0.388), or all-cause mortality (2.16 vs 1.6 per 100 PY; P = 0.119; HR, 0.831; log-rank, P = 0.342), respectively. Propensity score matching analyses yielded similar results regarding HCC occurrence, cirrhosis-related complications, and all-cause mortality. In addition, these findings were consistently reproduced in the subgroups of patients with chronic hepatitis and cirrhosis that developed before antiviral treatment. IMPLICATIONS: ETV and TDF did not significantly differ in prevention of HCC occurrence or reduction of cirrhosis-related complications and all-cause mortality in patients with CHB receiving a finite period of treatment.

Multi-Omics Analyses Identify Signatures in Patients with Liver Cirrhosis and Hepatocellular Carcinoma.

Gut bacterial/viral dysbiosis, changes in circulating metabolites, and plasma cytokines/chemokines have been previously associated with various liver diseases. Here, we analyzed the associations between fecal microbial composition, circulating metabolites, and plasma cytokines/chemokines in patients with liver cirrhosis (LC) and hepatocellular carcinoma (HCC). We recruited 10 HCC patients, 18 LC patients, and 17 healthy individuals. Their stool samples were used for gene sequencing of bacterial 16S rRNA and viral genomes, while plasma samples were utilized for the determination of endotoxin, zonulin, metabolite, and cytokine/chemokine levels. Dysbiosis was observed among gut bacteria and viruses, with significant changes in abundance at the genus and species levels, respectively. However, no differences were found between cohorts in the alpha and beta diversity. Plasma lipopolysaccharides and zonulin, but not trimethylamine N-oxide, were progressively increased in LC and HCC subjects. Profiling plasma metabolites and selected cytokines/chemokines revealed differential changes in the LC and HCC cohorts. Following joint correlation and correlation network analyses, regardless of etiology, common network signatures shared by LC and HCC patients were characterized by the gut virus Stenotrophomonas virus DLP5 and the uncultured Caudovirales phage, plasma metabolites pyruvic acid and acetic acid, and plasma cytokines/chemokines eotaxin and PDGF-AB/BB, respectively. Additionally, LC- and HCC-specific correlation networks were also identified. This study provides novel insights into altered gut microbial/viral composition that may contribute to pre-HCC disorders, metabolic reprogramming, or inflammatory microenvironments for hepatocarcinogenesis.

Notch signaling and natural killer cell infiltration in tumor tissues underlie medulloblastoma prognosis.

Medulloblastoma is the most common embryonic brain tumor in children. We investigated a cohort of 52 Asian medulloblastoma patients aged between 0 and 19 years old, who received surgical resections and post-resection treatments in the Taipei Medical University Hospital and the Taipei Veterans General Hospital. Genome-wide RNA sequencing was performed on fresh-frozen surgical tissues. These data were analyzed using the CIBERSORTx immune deconvolution software. Two external clinical and molecular datasets from United States (n = 62) and Canada (n = 763) were used to evaluate the transferability of the gene-signature scores across ethnic populations. The abundance of 13 genes, including DLL1, are significantly associated with overall survival (All Cox regression P < 0.001). A gene-signature score was derived from the deep transcriptome, capable of indicating patients' subsequent tumor recurrence (Hazard Ratio [HR] 1.645, confidence interval [CI] 1.337-2.025, P < 0.001) and mortality (HR 2.720, CI 1.798-4.112, P < 0.001). After the adjustment of baseline clinical factors, the score remains indicative of recurrence-free survival (HR 1.604, CI 1.292-1.992, P < 0.001) and overall survival (HR 2.781, CI 1.762-4.390, P < 0.001). Patients stratified by this score manifest not only distinct prognosis but also different molecular characteristics: Notch signaling ligands and receptors are comparatively overexpressed in patients with poorer prognosis, while tumor infiltrating natural killer cells are more abundant in patients with better prognosis. Additionally, immunohistochemical staining showed the DLL1 protein, a major ligand in the Notch signaling pathway, and the NCAM1 protein, a representative biomarker of natural killer cells, are present in the surgical tissues of patients of four molecular subgroups, WNT, SHH, Group 3 and Group 4. NCAM1 RNA level is also positively associated with the mutation burden in tumor (P = 0.023). The gene-signature score is validated successfully in the Canadian cohort (P = 0.009) as well as its three molecular subgroups (SHH, Group 3 and Group 4; P = 0.047, 0.018 and 0.040 respectively). In conclusion, pediatric medullablastoma patients can be stratified by gene-signature scores with distinct prognosis and molecular characteristics. Ligands and receptors of the Notch signaling pathway are overexpressed in the patient stratum with poorer prognosis. Tumor infiltrating natural killer cells are more abundant in the patient stratum with better prognosis.

Tenofovir Hampers the Efficacy of Sorafenib in Prolonging Overall Survival in Hepatocellular Carcinoma.

Sorafenib is a first-line treatment for patients with advanced hepatocellular carcinoma (HCC). These patients may simultaneously receive anti-hepatitis B treatment if they are viremic. The N-Acetylgalactosaminyltransferase 14 (GALNT14) gene can serve as a biomarker to guide HCC treatments. However, the enzyme substrates of its gene product, GalNAc-T14 (a glycosyltransferase), remained uncharacterized. Here, we conducted a glycoproteome-wide search for GalNAc-T14 substrates using lectin affinity chromatography followed by tandem mass spectrometry. Seventeen novel GalNAc-T14 substrates were identified. A connective map analysis showed that an antiviral drug, tenofovir, was the leading medicinal compound to down-regulate the expression of these substrates. In vitro assays showed that HCC cells were resistant to sorafenib if pretreated by tenofovir but not entecavir. Clinical analysis showed that the concomitant use of tenofovir and sorafenib was a previously unrecognized predictive factor for unfavorable overall survival (hazard ratio = 2.060, 95% confidence interval = [1.256, 3.381], p = 0.004) in a cohort of 181 hepatitis-B-related, sorafenib-treated HCC patients (concomitant tenofovir versus entecavir treatment; p = 0.003). In conclusion, by conducting a glycoproteome-wide search for GalNAc-T14 substrates, we unexpectedly found that tenofovir was a major negative regulator of GalNAc-T14 substrates and an unfavorable anti-hepatitis B drug in HCC patients receiving sorafenib.

Recent progress of biomarkers in oral cancers.

Oral cancers are the seventh most common cancer globally. While progresses in oral cancer treatment have been made, not all patients respond to these therapies in the same way. To overcome this difficulty, numerous studies have been devoted to identifying biomarkers, which enable early identification of patients who may benefit from a particular treatment modality or at risk for poor prognosis. Biomarkers are protein molecules, gene expression, DNA variants, or metabolites that are derived from tumors, adjacent normal tissue or bodily fluids, which can be acquired before treatment and during follow-up, thus extending their use to the evaluation of cancer progression and prediction of treatment outcome. In this review, we employed a basic significance level (<0.05) as the minimal requirement for candidate biomarkers. Effect sizes of the biomarkers in terms of odds ratio, hazard ratio, and area under the receiver operating characteristic curves were subsequently used to evaluate the potential of their clinical use. We identified the CCND1 from the tumor, human papillomavirus, HSP70, and IL-17 from the peripheral blood, and high density of CD45RO+ tumor-infiltrating lymphocytes as the clinically relevant biomarkers for oral cancers.

The Aldehyde Dehydrogenase ALDH2*2 Allele, Associated with Alcohol Drinking Behavior, Dates Back to Prehistoric Times.

Human alcohol-consumption behavior is partly genetically encoded. The alcohol consumption of 987 residents in Keelung, Taiwan, was evaluated by using the Alcohol Use Disorder Identification Test (AUDIT). We assessed ~750,000 genomic variants of 71 residents who drank hazardously (AUDIT score ≥ 8) and 126 residents who did not drink in their daily lives (AUDIT score = 0), using high-density single nucleotide polymorphism (SNP) arrays. The rs671 G > A manifests the highest significance of the association with drinking behavior (Fisher's exact P = 8.75 × 10-9). It is a pleiotropic, non-synonymous variant in the aldehyde dehydrogenase 2 (ALDH2) gene. The minor allele "A", commonly known as ALDH2*2, is associated with non-drinkers. Intriguingly, identity-by-descent haplotypes encompassing genomic regions with a median length of 1.6 (0.6-2.0) million nucleotide bases were found in all study participants with either heterozygous or homozygous ALDH2*2 (n = 81 and 13, respectively). We also analyzed a public-domain dataset with genome-wide genotypes of 2000 participants in Guangzhou, a coastal city in Southern China. Among them, 175 participants have homozygous ALDH2*2 genotype, and again, long ALDH2*2-carrying haplotypes were found in all 175 participants without exceptions. The median length of the ALDH2*2-carrying haplotype is 1.7 (0.5-2.8) million nucleotide bases. The haplotype lengths in the Keelung and Guangzhou cohorts combined indicate that the origin of the ALDH2*2 allele dates back to 7935 (7014-9381) years ago. In conclusion, the rs671 G > A is the leading genomic variant associated with the long-term drinking behavior among residents of Keelung, Taiwan. The ALDH2*2 allele has been in Asian populations since prehistoric times.

Deep proteogenomic investigations elucidate the NRF2 antioxidant mechanism as a major driving mechanism of lung adenocarcinoma in Asia.

BACKGROUND: Lung adenocarcinoma is a global leading cause of death. Despite modern therapeutic interventions, undesirable outcomes such as drug resistances and disease recurrence still occur. Therefore, continued investigations of disease driving mechanisms and counteracting strategies are urgently needed. METHODS: We re-visited two deep-proteogenomic resources of lung adenocarcinoma published recently. These resources were derived from patient cohorts with decent sizes in Taiwan and China. The gene set enrichment analysis (GSEA) was performed. A heatmap was produced by the generalized association plot (GAP). RESULTS: Among 189 common oncogenic pathways investigated, the nuclear factor erythroid 2-related factor 2 (NRF2) downstream antioxidant mechanism was uncovered for the first time the leading oncogenic mechanism of lung adenocarcinoma in Taiwan. The gene levels of NRF2 (also known as NFE2L2) is negatively correlated with those of KEAP1 (Pearson's correlation = -0.275, p = 0.009) in patients' tumor tissues. Furthermore, the protein levels of EIF2S2 and PGD are higher in patients with more advanced stages in the Taiwan cohort (p = 0.001 and 0.05, respectively), and are indicative of poorer progression-free survival (PFS) and overall survival (OS) in the China cohort (all Cox-regression p < 0.05). On the other hand, EPHX1 is higher in patients with earlier stages in Taiwan (p = 0.003), and are indicative of better PFS and OS in China (both Cox-regression p < 0.05). When the patients were stratified using the median protein abundances for Kaplan-Meier visualizations, patient strata with higher EIF2S2, PGD, and EPHX1 have significantly poorer PFS (log-rank p = 0.041); poorer OS (p = 0.006), and better PFS and OS (p = 0.001 and 0.030), respectively. CONCLUSION: The NRF2 downstream antioxidant mechanism is one major driving mechanism of lung adenocarcinoma in Asia, and represents important directions for future therapeutic interventions. Major downstream proteins such as EIF2S2, PGD, and EPHX1 are indicative of cancer stages and prognosis.

Plasma interleukin-17 and alpha-fetoprotein combination effectively predicts imminent hepatocellular carcinoma occurrence in liver cirrhotic patients.

BACKGROUND: Predicting imminent hepatocellular carcinoma (HCC) in liver cirrhotic patients is an unmet medical need. We aimed to investigate circulatory biomarkers and their optimum combinations in a prospective study. METHODS: We investigated plasma interleukin 17 (IL-17) concentrations, quantified using enzyme-linked immunosorbent assay (ELISA), for the prediction of HCC in a large cohort of 404 HCC-naïve liver cirrhotic patients regularly followed after recruitment. Additionally, IL-17 in surgically resected tumor tissues were evaluated using immunohistochemistry staining. RESULTS: IL-17 was detected in HCC tissues. The IL-17 concentrations in the peripheral blood do not have correlation with an extensive list of 31 common demographic, metabolic and liver function variables in the cohort of liver cirrhotic patients. Furthermore, patients stratified by IL-17 and alpha-fetoprotein (AFP) showed distinctive cumulative incidence of HCC. Imminent HCC, defined here as HCC occurrence within 1 year, can be predicted by IL-17 alone with an area under the receiver operating characteristic curve [AUC] of 0.762 (P = 0.002). An multivariate analysis showed that age, hepatitis C viral infection, AFP and IL-17 were four independent factors associated with imminent HCC (adjusted P = 0.03, 0.041, 0.024 and 0.008 respectively). An explicit risk score (R) combining the concentrations of two plasma biomarkers, AFP and IL-17, achieved a high AUC of 0.933 (95% confidence interval 0.893-0.972, P < 0.001) in predicting imminent HCC, with 100% sensitivity and 79.9% specificity at the optimum cutoff. The score is defined as: [Formula: see text] CONCLUSIONS: The circulatory IL-17 concentration is a predictor of subsequent HCC occurrence in liver cirrhotic patients. The combination of AFP and IL-17 is highly effective in predicting imminent HCC within 1 year.