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Chemoprevention is cost-effective for colorectal cancer when targeted at intermediate- or high-risk populations. Bufalin is a cardiac glycoside extracted from the traditional Chinese medicine (TCM) “Chan Su,” which has been used as an anticancer agent. On the basis of the relative safety of bufalin, we investigated whether bufalin could act as a chemoprophylactic agent to prevent colon tumorigenesis in two murine models, namely colitis-associated colorectal cancer and Apc germline mutation-developed colorectal cancer. Our results revealed that long-term (12–16 weeks) administration of low-dose bufalin (0.5 mg/kg) effectively suppressed tumorigenesis in both colorectal cancer models, accompanied by attenuated epithelial cell proliferation (reduced bromodeoxyuridine incorporation, lower levels of cyclin A, cyclin D1, cyclin E, and cyclin-dependent kinases-2/4, and higher levels of p21 and p27) and promoted apoptosis (increased TUNEL positivity and caspase-3/9 cleavages, reduced levels of Bcl-2, Bcl-xL and survivin, and increased levels of Bax and Bak). Bufalin also suppressed the expression of proinflammatory mediators [reduced levels of cyclooxygenase-2, tumor TNFα, IL1β, IL6, C-X-C motif chemokine ligand (CXCL)-1, CXCL-2, and CXCL-5] in the colitis-associated colorectal cancer model. These effects were associated with the inhibition of oncogenic NF-κB and PI3K/Akt pathways. Our findings unveil a novel chemoprophylactic action of bufalin in colorectal cancer in vivo and provided efficacy data and mechanistic evidence for further clinical evaluation of this TCM compound for colorectal cancer chemoprevention in individuals at risk of colorectal cancer.

Supplementary Table 1: Published publications and cohorts

Fig. S1: Optimization of number of molecular subtypes and assessment of batch effects.

DNA repair gene mutations, SMGs, and hotspot mutations in RGC and HGC.

Frequent mutations of newly identified SMGs across multiple human cancer types.

Clinical data of gastric cancer patients whose genomic data was aggregrated for integrated analysis.

Fig. S3: Prognostic significance of CDH1 mutation.

Fig. S2: Prognostic significance of C1/2.

Supplementary Figure S1: No effect of miR-490-3p on necrosis and apoptosis.

Supplementary Table S1: Absolute expression levels of miR-490-3p, miR-375 and let-7b in non-cancerous gastric mucosa.

PDF file - 4.4MB, Figure S1 Apoptogenic function and mechanism of LL-37 in LoVo colon cancer cells

Chromatin remodeling has emerged as a hallmark of gastric cancer, but the regulation of chromatin regulators other than genetic change is unknown. Helicobacter pylori causes epigenetic dysregulation to promote gastric carcinogenesis, but the roles and functions of microRNAs (miRNA) in this multistage cascade are not fully explored. In this study, miRNA expression in preneoplastic and neoplastic lesions in murine stomachs induced by H. pylori and N-methyl-N-nitrosourea (MNU) was profiled by miRNA expression array. miR-490-3p exhibited progressive downregulation in gastritis, intestinal metaplasia, and adenocarcinoma during H. pylori and MNU-induced gastric carcinogenesis. Significant downregulation of miR-490-3p was confirmed in human gastric cancer tissues in which its regulatory region was found to be hypermethylated. miR-490-3p exerted growth- and metastasis-suppressive effects on gastric cancer cells through directly targeting SMARCD1, a SWItch/Sucrose NonFermentable (SWI/SNF) chromatin remodeling complex subunit. Knockdown of SMARCD1 significantly attenuated the protumorigenic effects of miR-490-3p inhibitor, whereas enforced expression of SMARCD1 promoted in vitro and in vivo oncogenic phenotypes of gastric cancer cells. SMARCD1 was markedly upregulated in gastric cancer in which its high expression was associated with shortened patients' survival independent of TNM staging. In conclusion, hypermethylation-mediated silencing of miR-490-3p reactivates SMARCD1 to confer malignant phenotypes, mechanistically linking H. pylori, chromatin remodeling, and gastric carcinogenesis. Cancer Res; 75(4); 754–65. ©2014 AACR.

Supplementary Materials and Methods

Supplementary Figure Legends

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Backgroud: Cancer-associated fibroblasts (CAFs), a component of the tumor microenvironment, play a critical role in cancer progression, either pro- or anti-tumorigenic functions. Due to the original, phenotypic, and functional heterogeneity, CAFs can be subgrouped into several subpopulations. So far, no molecular classifications of CAFs based on a single-cell pan-cancer scale have been provided. Methods: This study employs a pan-cancer single-cell transcriptional atlas on 9 types of solid tumors (breast cancer, cholangiocarcinoma, colon adenocarcinoma, hepatocellular carcinoma, lung adenocarcinoma, neuroendocrine prostate cancer, pancreatic adenocarcinoma, prostate adenocarcinoma, and stomach adenocarcinoma) to provide a novel molecular classification, elucidate the CAF evolution. The function of each CAF subtype was analyzed by single-cell regulatory network inference and clustering (SCENIC) and single-cell GSEA, and the clinical significance was assessed using survival curves. Furthermore, we used molecular docking to screen small molecules targeting matCAF and conducted in vivo experiments to verify. Results: We distinguished CAFs in the solid tumor as 4 molecular clusters: progenitor CAF (proCAF), inflammatory CAF (iCAF), myofibroblastic CAF (myCAF), and matrix-producing CAF (matCAF) based on the prominent molecular features. The classification is universally applied in all the 9 solid tumors. The 4 CAF subtypes exhibit distinct evolutionary trajectories, functional roles, and clinical significance in different solid tumors. Besides, the matCAF signatures were found to have poor prognoses among multiple cancer types. Targeting matCAF by a screened small molecule, Procyanidin C1, exerted anti-tumor effects in suppressing tumor growth. Conclusions: Together, CAF subtypes play essential roles in cancer initiation and progression, especially mat CAF. Targeting matAF in solid tumors has tumor therapeutic potential.

The annual epidemics of seasonal influenza is partly attributed to the continued virus evolution. It is challenging to evaluate the effect of influenza virus mutations on evading population immunity. In this study, we introduce a novel statistical and computational approach to measure the dynamic molecular determinants underlying epidemics using effective mutations (EMs), and account for the time of waning mutation advantage against herd immunity by measuring the effective mutation periods (EMPs). Extensive analysis is performed on the sequencing and epidemiology data of H3N2 epidemics in ten regions from season to season. We systematically identified 46 EMs in the hemagglutinin (HA) gene, in which the majority were antigenic sites. Eight EMs were located in immunosubdominant stalk domain, an important target for developing broadly reactive antibodies. The EMs might provide timely information on key substitutions for influenza vaccines antigen design. The EMP suggested that major genetic variants of H3N2 circulated in South-east Asia for an average duration of 4.5 years (SD 2.4) compared to a significantly shorter 2.0 years (SD 1.0) in temperate regions. The proposed method bridges population epidemics and molecular characteristics of infectious diseases, and would find broad applications in various pathogens mutation estimations.

OBJECTIVE To investigate the antibiofilm and remineralising effects of the dual-action peptide GA-KR12 on artificial enamel caries. MATERIALS AND METHODS Enamel blocks with artificial caries were treated with sterilised deionised water as control or GA-KR12. The blocks underwent biochemical cycling with Streptococcus mutans for 3 weeks. The architecture, viability, and growth kinetics of the biofilm were determined, respectively, by scanning electron microscopy (SEM), confocal laser scanning microscopy, and quantitative (culture colony-forming units, CFUs). The mineral loss, calcium-to-phosphorus ratio, surface morphology, and crystal characteristics of the enamel surface were determined, respectively, using micro-computed tomography, energy dispersive spectroscopy, SEM, and X-ray diffraction (XRD). RESULTS SEM showed confluent growth of S. mutans in the control group but not in the GA-KR12-treated group. The dead-to-live ratios of the control and GA-KR12-treated groups were 0.42 ± 0.05 and 0.81 ± 0.08, respectively (p

Background The treatment for herpetic-related neuralgia focuses on symptom control by use of antiviral drugs, anticonvulsants, and tricyclic antidepressants. We aimed to explore the clinical characteristics associated with medication responsiveness, and to build a classifier for identification of patients who have risk of inadequate pain management. Methods We recruited herpetic-related neuralgia patients during a 3-year period. Patients were stratified into a medication-resistant pain (MRP) group when the pain decrease in the visual analogue scale (VAS) is

ObjectiveTo develop an end-to-end deep learning framework based on a protein–protein interaction (PPI) network to make synergistic anticancer drug combination predictions.Materials and MethodsWe propose a deep learning framework named Graph Convolutional Network for Drug Synergy (GraphSynergy). GraphSynergy adapts a spatial-based Graph Convolutional Network component to encode the high-order topological relationships in the PPI network of protein modules targeted by a pair of drugs, as well as the protein modules associated with a specific cancer cell line. The pharmacological effects of drug combinations are explicitly evaluated by their therapy and toxicity scores. An attention component is also introduced in GraphSynergy, which aims to capture the pivotal proteins that play a part in both PPI network and biomolecular interactions between drug combinations and cancer cell lines.ResultsGraphSynergy outperforms the classic and state-of-the-art models in predicting synergistic drug combinations on the 2 latest drug combination datasets. Specifically, GraphSynergy achieves accuracy values of 0.7553 (11.94% improvement compared to DeepSynergy, the latest published drug combination prediction algorithm) and 0.7557 (10.95% improvement compared to DeepSynergy) on DrugCombDB and Oncology-Screen datasets, respectively. Furthermore, the proteins allocated with high contribution weights during the training of GraphSynergy are proved to play a role in view of molecular functions and biological processes, such as transcription and transcription regulation.ConclusionThe introduction of topological relations between drug combination and cell line within the PPI network can significantly improve the capability of synergistic drug combination identification.

Herpes zoster results from latent varicella zoster virus reactivation in the dorsal root ganglia, causing blistering rash along the dermatomal distribution and post-herpetic neuralgia. Increasing studies indicated that there may be a correlation between herpes zoster and COVID-19. Nevertheless, the detailed pathophysiological mechanism is still unclear. We used bioinformatic analyses to study the potential genetic crosstalk between herpes zoster and COVID-19. COVID-19 and herpes zoster were associated with a similar subset of genes involved in “cytokine-cytokine receptor interaction,” “Jak-STAT signaling pathway,” and “IL-17 signaling pathway,” including TNF, IL10, ESR1, INFG, HLA-A, CRP, STAT3, IL6, IL7, and IL17A. Protein-protein interaction network assay showed that the combined gene set indicated a raised connectivity as compared to herpes zoster or COVID-19 alone, particularly the potentiated interactions with APOE, ARSA, CCR2, CCR5, CXCL13, EGFR, GAL, GP2, HLA-B, HLA-DRB1, IL5, TECTA, and THBS1, and these genes are related to “cytokine-cytokine receptor interaction”. Augmented Th17 cell differentiation and the resulting enhanced IL-17 signaling were identified in both COVID-19 and herpes zoster. Our data suggested aberrant interleukin-17 signaling as one possible mechanism through which COVID-19 could raise the risk of herpes zoster.

Recently, during the pandemic infection of the novel SARS-CoV-2, some cases of Miller Fisher syndrome (MFS) have been reported. We want to summarize the main features of patients with MFS and COVID-19. A PubMed search was performed on 8 October to identify references reporting cases with MFS associated with COVID-19 from the first report of COVID-19 to 8 October 2020 using the following keywords: “Miller Fisher syndrome” AND “COVID-19” OR “SARS-CoV-2”. A systematic review from the first report of coronavirus disease 2019 (COVID-19) to 8 October 2020 revealed 7 cases with Miller Fisher syndrome (MFS) associated with COVID-19. The 7 cases came from 5 countries but most of these patients were from Europe (85.7%), especially Spain. There are 5 cases of MFS diagnosed after the laboratory confirmation of SARS-CoV-2 infection. The mean onset time of MFS-associated neurological symptoms was 14.75 days after the diagnosis of COVID-19. However, the two remaining cases presented initially with MFS-associated neurological symptoms followed by the diagnosis of COVID-19. The most common symptoms of COVID-19-associated MFS were perioral paresthesias (57.1%), ataxia (57.1%), blurred vision (42.9), ophthalmoplegia (42.9), and generalized areflexia (42.9). However, more cohort and case-control studies are required to establish the epidemiological linkage.

The effectiveness of seasonal influenza vaccines varies with the matching of vaccine strains to circulating strains. Based on the genetic distance of hemagglutinin and neuraminidase gene of the influenza viruses to vaccine strains, we statistically quantified the relationship between the genetic mismatch and vaccine effectiveness (VE) for influenza A/H1N1pdm09, A/H3N2 and B. We also proposed a systematic approach to integrate multiple genes and influenza types for overall VE estimation. Evident linear relationships were identified and validated in independent data. The modelling framework may enable in silico prediction for VE on a real-time basis and inform the influenza vaccine selection strategy.

Surveillance of C. difficile infections suggests correlation of incidence to antibiotic stewardship programs., We conducted a territorywide survey to investigate the epidemiology, risk factors, and clinical outcomes of Clostridioides difficile infection (CDI) among hospitalized patients in Hong Kong. A total of 17,105 cases of CDI were identified, of which 15,717 (91.9%) were healthcare-associated and 1,025 (6.0%) were community-associated. Although CDI incidence increased substantially from 2006 to 2017, it plateaued in 2018 and 2019. The 30-day mortality rates decreased from 20.1% in 2015 to 16.8% in 2019, whereas the 60-day recurrence rates remained constant at ≈11% during the study period. Cross-correlation statistic showed significant correlations between incidence trend and overall antimicrobial drug use (r = 0.865, p

OBJECTIVE Stress hyperglycemia is associated with an increased risk of diabetes among survivors of critical illness. We investigated whether patients without diabetes hospitalized for bacteremia or nonbacteremic diseases with transient stress hyperglycemia would have a higher risk of subsequent diabetes development compared with those who remained normoglycemic. RESEARCH DESIGN AND METHODS This retrospective observational study was conducted on 224,534 in-patients with blood culture records. Stress hyperglycemia was defined based on the highest random glucose level ≥7.8 mmol/L during the index admission period. Diagnosis of diabetes, as the primary end point of interest, was defined based on diagnostic codes, blood test results, or medication records. Differences in cumulative incidence and hazard ratios (HRs) of diabetes between groups were assessed using the Kaplan-Meier estimator and Cox regression. RESULTS After exclusion of patients with preexisting or undiagnosed diabetes or indeterminate diabetes status and propensity score matching, bacteremic patients with stress hyperglycemia had a significantly higher cumulative incidence of diabetes (HR 1.7, 95% CI 1.2–2.4) compared with those who remained normoglycemic. Stress hyperglycemia was further confirmed to be a diabetes predictor independent of age, sex, comorbidity, and other serological markers. For the nonbacteremic patients, stress hyperglycemia was similarly associated with a higher cumulative incidence of diabetes (HR 1.4, 95% CI 1.2–1.7). CONCLUSIONS Hospitalized patients with transient stress hyperglycemia had a higher risk of subsequent diabetes development compared with their normoglycemic counterparts. Recognition of an increased risk of diabetes in these patients can allow early detection and monitoring in their subsequent follow-ups.

Fibroblast growth factor receptor type 2 (FGFR2) has emerged as a key oncogenic factor that regulates gastric cancer (GC) progression, but the underlying mechanism of FGF–FGFR2 signaling pathway remains largely unknown. To identify the potential molecular mechanisms of the oncogenic FGFR2 in gastric carcinogenesis and convey a novel therapeutic strategy, we profiled the FGFR alterations and analyzed their clinical associations in TCGA and Hong Kong GC cohorts. We found that FGFR2 overexpression in GC cell lines and primary tumors predicted poor survival and was associated with advanced stages of GC. Functionally, growth abilities and cell cycle progression of GC were inhibited by inactivation of ERK–MAPK signal transduction after FGFR2 knockdown, while apoptosis was promoted. Meanwhile, the first-line anti-cancer drug sensitivity was enhanced. RNA-seq analysis further revealed that YAP1 signaling serves as a significant downstream modulator and mediates the oncogenic signaling of FGFR2. When stimulating FGFR2 by rhFGF18, we observed intensified F-actin, nuclear accumulation of YAP1, and overexpression of YAP1 targets, but these effects were attenuated by either FGFR2 depletion or AZD4547 administration. Additionally, the FGF18–FGFR2 signaling upregulated YAP1 expression through activating c-Jun, an effector of MAPK signaling. In our cohort, 28.94% of GC cases were characterized as FGFR2, c-Jun, and YAP1 co-positive and demonstrated worse clinical outcomes. Remarkably, we also found that co-targeting FGFR2 and YAP1 by AZD4547 and Verteporfin synergistically enhanced the antitumor effects in vitro and in vivo. In conclusion, we have identified the oncogenic FGF–FGFR2 regulates YAP1 signaling in GC. The findings also highlight the translational potential of FGFR2–c-Jun–YAP1 axis, which may serve as a prognostic biomarker and therapeutic target for GC.

Background Currently there are only two population studies on sepsis incidence in Asia. The burden of sepsis in Hong Kong is unknown. We developed a sepsis surveillance method to estimate sepsis incidence from a population electronic health record (EHR) in Hong Kong using objective clinical data. The study objective was to assess our method’s performance in identifying sepsis using a retrospective cohort. We compared its accuracy to administrative sepsis surveillance methods such as Angus’ and Martin’s methods. Method In this single centre retrospective study we applied our sepsis surveillance method on adult patients admitted to a tertiary hospital in Hong Kong. Two clinicians independently reviewed the clinical notes to determine which patients had sepsis. Performance was assessed by sensitivity, specificity, positive predictive value, negative predictive value and area under the curve (AUC) of Angus’, Martin’s and our surveillance methods using clinical review as “gold standard.” Results Between January 1 and February 28, 2018, our sepsis surveillance method identified 1352 adult patients hospitalised with suspected infection. We found that 38.9% (95%CI 36.3–41.5) of these patients had sepsis. Using a 490 patient validation cohort, two clinicians had good agreement with weighted kappa of 0.75 (95% CI 0.69–0.81) before coming to consensus on diagnosis of uncomplicated infection or sepsis for all patients. Our method had sensitivity 0.93 (95%CI 0.89–0.96), specificity 0.86 (95%CI 0.82–0.90) and an AUC 0.90 (95%CI 0.87–0.92) when validated against clinician review. In contrast, Angus’ and Martin’s methods had AUCs 0.56 (95%CI 0.53–0.58) and 0.56 (95%CI 0.52–0.59), respectively. Conclusions A sepsis surveillance method based on objective data from a population EHR in Hong Kong was more accurate than administrative methods. It may be used to estimate sepsis population incidence and outcomes in Hong Kong. Trial registration This study was retrospectively registered at clinicaltrials.gov on October 3, 2019 (NCT04114214).

Background Altered microbiome composition and aberrant promoter hypermethylation of tumor suppressor genes (TSGs) are two important hallmarks of colorectal cancer (CRC). Here we performed concurrent 16S rRNA gene sequencing and methyl-CpG binding domain-based capture sequencing in 33 tissue biopsies (5 normal colonic mucosa tissues, 4 pairs of adenoma and adenoma-adjacent tissues, and 10 pairs of CRC and CRC-adjacent tissues) to identify significant associations between TSG promoter hypermethylation and CRC-associated bacteria, followed by functional validation of the methylation-associated bacteria. Results Fusobacterium nucleatum and Hungatella hathewayi were identified as the top two methylation-regulating bacteria. Targeted analysis on bona fide TSGs revealed that H. hathewayi and Streptococcus spp. significantly correlated with CDX2 and MLH1 promoter hypermethylation, respectively. Mechanistic validation with cell-line and animal models revealed that F. nucleatum and H. hathewayi upregulated DNA methyltransferase. H. hathewayi inoculation also promoted colonic epithelial cell proliferation in germ-free and conventional mice. Conclusion Our integrative analysis revealed previously unknown epigenetic regulation of TSGs in host cells through inducing DNA methyltransferase by F. nucleatum and H. hathewayi, and established the latter as CRC-promoting bacteria.

Exposure to air pollution is known to increase the risks for cardiovascular, pulmonary and metabolic diseases. Growing evidences also indicated that air pollution exposure during pregnancy could negatively impact on early embryonic development and children’s health. We performed RNA sequencing to identify deregulated mRNAs in air pollution-exposed rat embryos. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to analyse the potential cellular functions of deregulated mRNAs. Our analysis indicated that a total of 1678 mRNAs were differentially expressed on gestation day 9 upon in utero exposure to fine particulate matter of > 200 μg/m3, among which 1098 mRNAs were downregulated and 580 mRNAs were upregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed gap junction, cell adhesion, axon guidance and the neurotrophin signalling pathway as key biological processes perturbed by air pollution exposure. Furthermore, reconstruction of the mRNA regulatory network highlighted the central roles of Tbx4, Bmp4, Sox10, Wnt9b, Bmp7 and Foxc2. These data suggested that embryonic mRNA deregulation may underlie the formation of air pollution-associated congenital defects.

Atopic dermatitis (AD) is a chronic and recurrent inflammatory skin disease, affecting up to 10% to 20% of children and 3% of adults. Although allergen sensitization, skin barrier abnormalities and type 2 immune responses are involved, the exact molecular pathogenesis of AD remains unclear. MicroRNAs (miRNAs) are short (19‐25 nucleotides) single‐stranded RNA molecules that regulate gene expression at post‐transcriptional level and are implicated in the pathogenesis of many inflammatory and immunological skin disorders. This systematic review sought to summarize our current understanding regarding the role of miRNAs in AD development. We searched articles indexed in PubMed (MEDLINE) and Web of Science databases using Medical Subject Heading (MeSH) or Title/Abstract words (‘microRNA/miRNA’ and ‘atopic dermatitis/eczema’) from inception through January 2020. Observational studies revealed dysregulation of miRNAs, including miR‐143, miR‐146a, miR‐151a, miR‐155 and miR‐223, in AD patients. Experimental studies confirmed their functions in regulating keratinocyte proliferation/apoptosis, cytokine signalling and nuclear factor‐κB‐dependent inflammatory responses, together with T helper 17 and regulatory T cell activities. Altogether, this systematic review brings together contemporary findings on how deregulation of miRNAs contributes to AD.

Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New Background Low 25-hydroxyvitamin D is associated with cardiovascular, renal, and infectious risks. Postsurgical patients are susceptible to similar complications, but whether vitamin D deficiency contributes to postoperative complications remains unclear. We tested whether low preoperative vitamin D is associated with cardiovascular events within 30 days after noncardiac surgery. Methods We evaluated a subset of patients enrolled in the biobank substudy of the Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) study, who were at least 45 yr with at least an overnight hospitalization. Blood was collected preoperatively, and 25-hydroxyvitamin D was measured in stored samples. The primary outcome was the composite of cardiovascular events (death, myocardial injury, nonfatal cardiac arrest, stroke, congestive heart failure) within 30 postoperative days. Secondary outcomes were kidney injury and infectious complications. Results A total of 3,851 participants were eligible for analysis. Preoperative 25-hydroxyvitamin D concentration was 70 ± 30 nmol/l, and 62% of patients were vitamin D deficient. Overall, 26 (0.7%) patients died, 41 (1.1%) had congestive heart failure or nonfatal cardiac arrest, 540 (14%) had myocardial injury, and 15 (0.4%) had strokes. Preoperative vitamin D concentration was not associated with the primary outcome (average relative effect odds ratio [95% CI]: 0.93 [0.85, 1.01] per 10 nmol/l increase in preoperative vitamin D, P = 0.095). However, it was associated with postoperative infection (average relative effect odds ratio [95% CI]: 0.94 [0.90, 0.98] per 10 nmol/l increase in preoperative vitamin D, P adjusted value = 0.005) and kidney function (estimated mean change in postoperative estimated glomerular filtration rate [95% CI]: 0.29 [0.11, 0.48] ml min-1 1.73 m-2 per 10 nmol/l increase in preoperative vitamin D, P adjusted value = 0.004). Conclusions Preoperative vitamin D was not associated with a composite of postoperative 30-day cardiac outcomes. However, there was a significant association between vitamin D deficiency and a composite of infectious complications and decreased kidney function. While renal effects were not clinically meaningful, the effect of vitamin D supplementation on infectious complications requires further study.

Colorectal cancer (CRC) is a common cancer globally. It is a complex disease influenced by genetic and environmental factors. Early studies on familial cases have identified major genes involved in CRC, such as proto-oncogenes KRAS, PIK3CA and BRAF, and tumour-suppressor genes APC and TP53. These genes have provided valuable insight into the molecular pathogenesis of CRC, and some have made ways to clinical utility to help diagnose cancer syndromes, prognosticate oncological outcomes and predict treatment responses. While these genetic factors are important, recent studies have suggested contribution of microorganisms to colorectal carcinogenesis. Observational studies, animal experiments and translational works have identified several microorganisms as potential carcinogenic bacteria, such as Fusobacterium nucleatum and Peptostreptococcus anaerobius. With the advent of sequencing technology and bioinformatics, more genomic and metagenomic factors are being uncovered as important players in CRC carcinogenesis. This article aims to review recent genomic and metagenomic discoveries relating to CRC.

To develop an end-to-end deep learning framework based on a protein-protein interaction (PPI) network to make synergistic anticancer drug combination predictions.We propose a deep learning framework named Graph Convolutional Network for Drug Synergy (GraphSynergy). GraphSynergy adapts a spatial-based Graph Convolutional Network component to encode the high-order topological relationships in the PPI network of protein modules targeted by a pair of drugs, as well as the protein modules associated with a specific cancer cell line. The pharmacological effects of drug combinations are explicitly evaluated by their therapy and toxicity scores. An attention component is also introduced in GraphSynergy, which aims to capture the pivotal proteins that play a part in both PPI network and biomolecular interactions between drug combinations and cancer cell lines.GraphSynergy outperforms the classic and state-of-the-art models in predicting synergistic drug combinations on the 2 latest drug combination datasets. Specifically, GraphSynergy achieves accuracy values of 0.7553 (11.94% improvement compared to DeepSynergy, the latest published drug combination prediction algorithm) and 0.7557 (10.95% improvement compared to DeepSynergy) on DrugCombDB and Oncology-Screen datasets, respectively. Furthermore, the proteins allocated with high contribution weights during the training of GraphSynergy are proved to play a role in view of molecular functions and biological processes, such as transcription and transcription regulation.The introduction of topological relations between drug combination and cell line within the PPI network can significantly improve the capability of synergistic drug combination identification.

Background Gut microbiota contributes to colorectal cancer (CRC) pathogenesis through specific pathogens and their metabolites. We aim to determine gut microbiota-associated metabolites and their linkage to CRC. Methods We performed metabolomics by gas chromatography coupled to time-of-flight mass spectrometry, and shotgun metagenomics analysis on fecal samples from 386 subjects [118 CRC patients, 140 colorectal adenomas (CRA) patients and 128 normal controls (NC)]. Stepwise logistic regression models were used to identify metabolites and bacterial markers discriminating CRC stages. Associations among CRC-associated metabolites and bacteria were estimated with zero-inflated negative binomial regressions analysis. Results Principal component analysis and partial least squares-discriminant analysis showed differences in the gut metabolite profiles among CRC, CRA and NC groups. Norvaline and myristic acid showed increasing trends from NC, through CRA, to CRC. CRC-associated metabolites were enriched in branched-chain amino acids and aminoacyl-tRNA biosynthesis pathways. Twenty metabolites classified CRC from NC subjects with an area under the curve (AUC) of 0.80, and CRC from CRA with AUC of 0.79. Combinations of metabolites and bacterial markers improved the diagnostic performances (CRC vs NC, AUC: 0.94; CRC vs CRA, AUC 0.92; CRA vs NC, AUC: 0.86), indicating a potential for early diagnosis of colorectal neoplasia. Moreover, relationships among CRC-associated metabolites and bacteria were altered across CRC stages; certain associations exhibited increasing or decreasing strengths while some were reversed from negative to positive or vice versa. Conclusions Gut metabolites are altered in colorectal carcinogenesis. The combination of metabolites and bacterial species can increase the chance of a non-invasive diagnosis of colorectal neoplasia.

The novel coronavirus disease 2019 (COVID-19) has spread worldwide and threatened human life. Diagnosis is crucial to contain the spread of SARS-CoV-2 infections and save lives. Diagnostic tests for COVID-19 have varying sensitivity and specificity, and the false-negative results would have substantial consequences to patient treatment and pandemic control. To detect all suspected infections, multiple testing is widely used. However, it may be challenging to build an assertion when the testing results are inconsistent. Considering the situation where there is more than one diagnostic outcome for each subject, we proposed a Bayesian probabilistic framework based on the sensitivity and specificity of each diagnostic method to synthesize a posterior probability of being infected by SARS-CoV-2. We demonstrated that the synthesized posterior outcome outperformed each individual testing outcome. A user-friendly web application was developed to implement our analytic framework with free access via http://www2.ccrb.cuhk.edu.hk/statgene/COVID_19/ . The web application enables the real-time display of the integrated outcome incorporating two or more tests and calculated based on Bayesian posterior probability. A simulation-based assessment demonstrated higher accuracy and precision of the Bayesian probabilistic model compared with a single-test outcome. The online tool developed in this study can assist physicians in making clinical evaluations by effectively integrating multiple COVID-19 tests.

Neuropathic pain is a major type of chronic pain caused by the disease or injury of the somatosensory nervous system. It afflicts about 10% of the general population with a significant proportion of patients’ refractory to conventional medical treatment. This highlights the importance of a better understanding of the molecular pathogenesis of neuropathic pain so as to drive the development of novel mechanism‐driven therapy. Circular RNAs (circRNAs) are a type of non‐coding, regulatory RNAs that exhibit tissue‐ and disease‐specific expression. An increasing number of studies reported that circRNAs may play pivotal roles in the development of neuropathic pain. In this review, we first summarize circRNA expression profiling studies on neuropathic pain. We also highlight the molecular mechanisms of specific circRNAs (circHIPK3, circAnks1a, ciRS‐7, cZRANB1, circZNF609 and circ_0005075) that play key functional roles in the pathogenesis of neuropathic pain and discuss their potential diagnostic, prognostic, and therapeutic utilization in the clinical management of neuropathic pain., CircRNAs‐regulated genes expression via sponging miRNAs and played crucial roles in excitability and inflammation in neuropathic pain.

Highlights • ANXA2 is a novel MOR1-interacting protein regulating MOR1 sub-cellular localization. • ANXA2 retains MOR1 in late recycling endosomes after remifentanil exposure.

IntroductionPatients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains.Research design and methodsThis study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method.ResultsA total of 273 678 patients (mean age: 65.4±12.7 years, male: 48.2%, median follow-up: 142 (IQR=106–142) months) were included, with 91 155 deaths occurring on follow-up (33.3%; annualized mortality rate: 3.4%/year; 2.7 million patient-years). Multivariate Cox regression found the following significant predictors of all-cause mortality: age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG. The above parameters were incorporated into a score-based predictive risk model that had a c-statistic of 0.73 (95% CI 0.66 to 0.77), which was improved to 0.86 (0.81 to 0.90) and 0.87 (0.84 to 0.91) using random survival forests and deep survival learning models, respectively.ConclusionsA multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus. The predictive and modeling capabilities of machine/deep learning survival analysis achieved more accurate predictions.

Background Numerous studies related to Helicobacter pylori (H. pylori) eradication have been published since the discovery of H. pylori. This study aimed to use a quantitative method to assess the development of this field. Materials and methods We performed a search of related articles from Web of Science published in 1983-2020 using a combination of the search terms "H. pylori" and "eradication". Eligible studies were included after a two-stage screening process, and the following data were extracted: title, author, institution, country, study type, sample size, eradication regimen, publication year, number of citations, journal, and H-index. Results A total of 1402 studies were finally identified. The results showed that the period from 1994-2003 was the most influential period in this field. Italy and the USA were dominant countries in this field, while China's publication number increased sharply in the last ten years. Baylor College of Medicine was the most influential institution. Alimentary Pharmacology Therapeutics was the most productive journal. The effects of H. pylori eradication on peptic ulcers and gastric cancer and H. pylori eradication therapy were the most cited topics in this field. After the publish of Maastricht/Florence Ⅳ guideline, the research of quadruple therapy was more than triple therapy. Bismuth-containing quadruple therapy became the most focused regimen after Maastricht/Florence Ⅴ guideline. Conclusions In this study, we summarized the characteristics of the publications; identified the most influential countries, institutions, journals; identified the popular research topics and eradication regimen of clinical H. pylori eradication.