Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution

Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.

Non-invasive detection of lymphoma with circulating tumor DNA features and protein tumor markers

Background

According to GLOBOCAN 2020, lymphoma ranked as the 9th most common cancer and the 12th leading cause of cancer-related deaths worldwide. Traditional diagnostic methods rely on the invasive excisional lymph node biopsy, which is an invasive approach with some limitations. Most lymphoma patients are diagnosed at an advanced stage since they are asymptomatic at the beginning, which has significantly impacted treatment efficacy and prognosis of the disease.

Method

This study assessed the performance and utility of a newly developed blood-based assay (SeekInCare) for lymphoma early detection. SeekInCare utilized protein tumor markers and a comprehensive set of cancer-associated genomic features, including copy number aberration (CNA), fragment size (FS), end motif, and lymphoma-related virus, which were profiled by shallow WGS of cfDNA.

Results

Protein marker CA125 could be used for lymphoma detection independent of gender, and the sensitivity was 27.8% at specificity of 98.0%. After integrating these multi-dimensional features, 77.8% sensitivity was achieved at specificity of 98.0%, while its NPV and PPV were both more than 92% for lymphoma detection. The sensitivity of early-stage (I-II) lymphoma was up to 51.3% (47.4% and 55.0% for stage I and II respectively). After 2 cycles of treatment, the molecular response of SeekInCare was correlated with the clinical outcome.

Conclusion

In summary, a blood-based assay can be an alternative to detect lymphoma with adequate performance. This approach becomes particularly valuable in cases where obtaining tissue biopsy is difficult to obtain or inconclusive.

Intestinal stearoyl-CoA desaturase-1 regulates energy balance via alterations in bile acid homeostasis

Background and Aims

Stearoyl-CoA desaturase-1 (SCD1) converts saturated fatty acids into monounsaturated fatty acids and plays an important regulatory role in lipid metabolism. Previous studies have demonstrated that mice deficient in SCD1 are protected from diet-induced obesity and hepatic steatosis due to altered lipid esterification and increased energy expenditure. Previous studies in our lab have shown that intestinal SCD1 modulates intestinal and plasma lipids and alters cholesterol metabolism. Here we investigated a novel role for intestinal SCD1 in the regulation of systemic energy balance.

Methods

To interrogate the role of intestinal SCD1 in modulating whole body metabolism, intestine-specific Scd1 knockout (iKO) mice were maintained on standard chow diet or challenged with a high-fat diet (HFD). Studies included analyses of bile acid content and composition, metabolic phenotyping including body composition, indirect calorimetry, glucose tolerance analyses, and assessment of bile acid signaling pathways.

Results

iKO mice displayed elevated plasma and hepatic bile acid content and decreased fecal bile acid excretion, associated with increased expression of the ileal bile acid uptake transporter, Asbt . These increases were associated with increased expression of TGR5 targets, including Dio2 in brown adipose tissue and elevated plasma glucagon-like peptide-1 levels. Upon HFD challenge, iKO mice had reduced metabolic efficiency apparent through decreased weight gain despite higher food intake. Concomitantly, energy expenditure was increased, and glucose tolerance was improved in HFD-fed iKO mice.

Conclusion

Our results indicate that deletion of intestinal SCD1 has significant impacts on bile acid metabolism and whole-body energy balance, likely via activation of TGR5.

Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer

BACKGROUND

Treatment with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) can yield durable antitumor responses, yet not all patients respond to ICIs. Current approaches to select patients who may benefit from anti-PD-1 treatment are insufficient. 5-hydroxymethylation (5hmC) analysis of plasma-derived cell-free DNA (cfDNA) presents a novel non-invasive approach for identification of therapy response biomarkers which can tackle challenges associated with tumor biopsies such as tumor heterogeneity and serial sample collection.

METHODS

151 blood samples were collected from 31 patients with non-small cell lung cancer (NSCLC) before therapy started and at multiple time points while on therapy. Blood samples were processed to obtain plasma-derived cfDNA, followed by enrichment of 5hmC-containing cfDNA fragments through biotinylation via a two-step chemistry and binding to streptavidin coated beads. 5hmC-enriched cfDNA and whole genome libraries were prepared in parallel and sequenced to obtain whole hydroxymethylome and whole genome plasma profiles, respectively.

RESULTS

Comparison of on-treatment time point to matched pretreatment samples from same patients revealed that anti-PD-1 treatment induced distinct changes in plasma cfDNA 5hmC profiles of responding patients, as judged by Response evaluation criteria in solid tumors, relative to non-responders. In responders, 5hmC accumulated over genes involved in immune activation such as inteferon (IFN)-γ and IFN-α response, inflammatory response and tumor necrosis factor (TNF)-α signaling, whereas in non-responders 5hmC increased over epithelial to mesenchymal transition genes. Molecular response to anti-PD-1 treatment, as measured by 5hmC changes in plasma cfDNA profiles were observed early on, starting with the first cycle of treatment. Comparison of pretreatment plasma samples revealed that anti-PD-1 treatment response and resistance associated genes can be captured by 5hmC profiling of plasma-derived cfDNA. Furthermore, 5hmC profiling of pretreatment plasma samples was able to distinguish responders from non-responders using T cell-inflamed gene expression profile, which was previously identified by tissue RNA analysis.

CONCLUSIONS

These results demonstrate that 5hmC profiling can identify response and resistance associated biological pathways in plasma-derived cfDNA, offering a novel approach for non-invasive prediction and monitoring of immunotherapy response in NSCLC.

CMAUP database update 2024: extended functional and association information of useful plants for biomedical research

Knowledge of the collective activities of individual plants together with the derived clinical effects and targeted disease associations is useful for plant-based biomedical research. To provide the information in complement to the established databases, we introduced a major update of CMAUP database, previously featured in NAR. This update includes (i) human transcriptomic changes overlapping with 1152 targets of 5765 individual plants, covering 74 diseases from 20 027 patient samples; (ii) clinical information for 185 individual plants in 691 clinical trials; (iii) drug development information for 4694 drug-producing plants with metabolites developed into approved or clinical trial drugs; (iv) plant and human disease associations (428 737 associations by target, 220 935 reversion of transcriptomic changes, 764 and 154121 associations by clinical trials of individual plants and plant ingredients); (v) the location of individual plants in the phylogenetic tree for navigating taxonomic neighbors, (vi) DNA barcodes of 3949 plants, (vii) predicted human oral bioavailability of plant ingredients by the established SwissADME and HobPre algorithm, (viii) 21-107% increase of CMAUP data over the previous version to cover 60 222 chemical ingredients, 7865 plants, 758 targets, 1399 diseases, 238 KEGG human pathways, 3013 gene ontologies and 1203 disease ontologies. CMAUP update version is freely accessible at https://bidd.group/CMAUP/index.html.

Current trends and future prospects of drug repositioning in gastrointestinal oncology

Gastrointestinal (GI) cancers comprise a significant number of cancer cases worldwide and contribute to a high percentage of cancer-related deaths. To improve survival rates of GI cancer patients, it is important to find and implement more effective therapeutic strategies with better prognoses and fewer side effects. The development of new drugs can be a lengthy and expensive process, often involving clinical trials that may fail in the early stages. One strategy to address these challenges is drug repurposing (DR). Drug repurposing is a developmental strategy that involves using existing drugs approved for other diseases and leveraging their safety and pharmacological data to explore their potential use in treating different diseases. In this paper, we outline the existing therapeutic strategies and challenges associated with GI cancers and explore DR as a promising alternative approach. We have presented an extensive review of different DR methodologies, research efforts and examples of repurposed drugs within various GI cancer types, such as colorectal, pancreatic and liver cancers. Our aim is to provide a comprehensive overview of employing the DR approach in GI cancers to inform future research endeavors and clinical trials in this field.

An Overview of Global, Local, and Base-Resolution Methods for the Detection of 5-Hydroxymethylcytosine in Genomic DNA

The discovery of 5-hydroxymethylcytosine (5hmC) as a common DNA modification in mammalian genomes has ushered in new areas of inquiry regarding the dynamic epigenome. The balance between 5hmC and its precursor, 5-methylcytosine (5mC), has emerged as a determinant of key processes including cell fate specification, and alterations involving these bases have been implicated in the pathogenesis of various diseases. The identification of 5hmC separately from 5mC initially posed a challenge given that legacy epigenetic sequencing technologies could not discriminate between these two most abundant modifications, a significant blind spot considering their potentially functionally opposing roles. The growing interest in 5hmC, as well as in the Ten-Eleven Translocation (TET) family enzymes that catalyze its generation and further oxidation to 5-formylcytosine (5fC) and 5-carboxycytosine (5caC), has spurred the development of versatile methods for 5hmC detection. These methods enable the quantification and localization of 5hmC in diverse biological samples and, in some cases, at the resolution of individual nucleotides. However, navigating this growing toolbox of methods for 5hmC detection can be challenging. Here, we detail existing and emerging methods for the detection, quantification, and localization of 5hmC at global, locus-specific, and base resolution levels. These methods are discussed in the context of their advantages and limitations, with the goal of providing a framework to help guide researchers in choosing the level of resolution and the associated method that could be most suitable for specific needs.

Identification of hub genes to determine drug-disease correlation in breast carcinomas

The exact molecular mechanism underlying the heterogeneous drug response against breast carcinoma remains to be fully understood. It is urgently required to identify key genes that are intricately associated with varied clinical response of standard anti-cancer drugs, clinically used to treat breast cancer patients. In the present study, the utility of transcriptomic data of breast cancer patients in discerning the clinical drug response using machine learning-based approaches were evaluated. Here, a computational framework has been developed which can be used to identify key genes that can be linked with clinical drug response and progression of cancer, offering an immense opportunity to predict potential prognostic biomarkers and therapeutic targets. The framework concerned utilizes DeSeq2, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape, and machine learning techniques to find these crucial genes. Total RNA extraction and qRT-PCR were performed to quantify relative expression of few hub genes selected from the networks. In our study, we have experimentally checked the expression of few key hub genes like APOA2, DLX5, APOC3, CAMK2B, and PAK6 that were predicted to play an immense role in breast cancer tumorigenesis and progression in response to anti-cancer drug Paclitaxel. However, further experimental validations will be required to get mechanistic insights of these genes in regulating the drug response and cancer progression which will likely to play pivotal role in cancer treatment and precision oncology.

Plasma cell-free DNA 5-hydroxymethylcytosine and whole-genome sequencing signatures for early detection of esophageal cancer

Esophageal cancer is a highly incidence and deadly disease with a poor prognosis, especially in developing countries. Owing to the lack of specific symptoms and early diagnostic biomarkers, most patients are diagnosed with advanced disease, leading to a 5-year survival rate of less than 15%. Early (n = 50) and middle-advanced (n = 50) esophageal squamous cell carcinoma (ESCC) patients, as well as 71 healthy individuals, underwent 5-hydroxymethylcytosine (5hmC) sequencing on their plasma cell-free DNA (cfDNA). A Northern Chinese cohort of cfDNA 5hmC dataset of 150 ESCC patients and 183 healthy individuals were downloaded for validation. A diagnostic model was developed using cfDNA 5hmC signatures and then improved by low-pass whole genome sequencing (WGS) features of cfDNA. Conserved cfDNA 5hmC modification motifs were observed in the two independent ESCC cohorts. The diagnostic model with 5hmC features achieved an AUC of 0.810 and 0.862 in the Southern and Northern cohorts, respectively, with sensitivities of 69.3-74.3% and specificities of 82.4-90.7%. The performance was well maintained in Stage I to Stage IV, with accuracy of 70-100%, but low in Stage 0, 33.3%. Low-pass WGS of cfDNA improved the AUC to 0.934 with a sensitivity of 82.4%, a specificity of 88.2%, and an accuracy of 84.3%, particularly significantly in Stage 0, with an accuracy up to 80%. 5hmC and WGS could efficiently differentiate very early ESCC from healthy individuals. These findings imply a non-invasive and convenient method for ESCC detection when clinical treatments are available and may eventually prolong survival.

IDH1-mutant preleukemic hematopoietic stem cells can be eliminated by inhibition of oxidative phosphorylation

Rare preleukemic hematopoietic stem cells (pHSCs) harboring only the initiating mutations can be detected at the time of AML diagnosis. pHSCs are the origin of leukemia and a potential reservoir for relapse. Using primary human samples and gene-editing to model isocitrate dehydrogenase 1 (IDH1) mutant pHSCs, we show epigenetic, transcriptional, and metabolic differences between pHSCs and healthy hematopoietic stem cells (HSCs). We confirm that IDH1 driven clonal hematopoiesis is associated with cytopenia, suggesting an inherent defect to fully reconstitute hematopoiesis. Despite giving rise to multilineage engraftment, IDH1-mutant pHSCs exhibited reduced proliferation, blocked differentiation, downregulation of MHC Class II genes, and reprogramming of oxidative phosphorylation metabolism. Critically, inhibition of oxidative phosphorylation resulted in complete eradication of IDH1-mutant pHSCs but not IDH2-mutant pHSCs or wildtype HSCs. Our results indicate that IDH1-mutant preleukemic clones can be targeted with complex I inhibitors, offering a potential strategy to prevent development and relapse of leukemia.

The changing face of circulating tumor DNA (ctDNA) profiling: Factors that shape the landscape of methodologies, technologies, and commercialization

Liquid biopsies, in particular the profiling of circulating tumor DNA (ctDNA), have long held promise as transformative tools in cancer precision medicine. Despite a prolonged incubation phase, ctDNA profiling has recently experienced a strong wave of development and innovation, indicating its imminent integration into the cancer management toolbox. Various advancements in mutation-based ctDNA analysis methodologies and technologies have greatly improved sensitivity and specificity of ctDNA assays, such as optimized preanalytics, size-based pre-enrichment strategies, targeted sequencing, enhanced library preparation methods, sequencing error suppression, integrated bioinformatics and machine learning. Moreover, research breakthroughs have expanded the scope of ctDNA analysis beyond hotspot mutational profiling of plasma-derived apoptotic, mono-nucleosomal ctDNA fragments. This broader perspective considers alternative genetic features of cancer, genome-wide characterization, classical and newly discovered epigenetic modifications, structural variations, diverse cellular and mechanistic ctDNA origins, and alternative biospecimen types. These developments have maximized the utility of ctDNA, facilitating landmark research, clinical trials, and the commercialization of ctDNA assays, technologies, and products. Consequently, ctDNA tests are increasingly recognized as an important part of patient guidance and are being implemented in clinical practice. Although reimbursement for ctDNA tests by healthcare providers still lags behind, it is gaining greater acceptance. In this work, we provide a comprehensive exploration of the extensive landscape of ctDNA profiling methodologies, considering the multitude of factors that influence its development and evolution. By illuminating the broader aspects of ctDNA profiling, the aim is to provide multiple entry points for understanding and navigating the vast and rapidly evolving landscape of ctDNA methodologies, applications, and technologies.

Analysis of genome-wide 5-hydroxymethylation of blood samples stored in different anticoagulants: opportunities for the expansion of clinical resources for epigenetic research

BACKGROUND

Elucidating epigenetic mechanisms could provide new biomarkers for disease diagnosis and prognosis. Technological advances allow genome-wide profiling of 5-hydroxymethylcytosines (5hmC) in liquid biopsies. 5hmC-Seal followed by NGS is a highly sensitive technique for 5hmC biomarker discovery in cfDNA. Currently, 5hmC Seal is optimized for EDTA blood collection. We asked whether heparin was compatible with 5hmC Seal as many clinical and biobanked samples are stored in heparin.

METHODS

We obtained 60 samples in EDTA matched to 60 samples in heparin from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Samples were comprised of 30 controls and 30 individuals who were later diagnosed with colon cancer. We profiled genome-wide 5hmC in cfDNA using 5hmC-Seal assay followed by NGS. The 5hmC profiling data from samples collected in EDTA were systematically compared to those in heparin across various genomic features.

RESULTS

cfDNA isolation and library construction appeared comparable in heparin vs. EDTA. Typical genomic distribution patterns of 5hmC, including gene bodies and enhancer markers, were comparable in heparin vs. EDTA. 5hmC analysis of cases and controls yielded highly correlated differential features suggesting that both anticoagulants were compatible with 5hmC Seal assay.

CONCLUSIONS

While not currently recommended for the 5hmC-Seal protocol, blood samples stored in heparin were successfully used to generate analysable and biologically relevant genome-wide 5hmC profiling. Our findings are the first to support opportunities to expand the biospecimen resource to heparin samples for 5hmC Seal and perhaps other PCR-based technologies in epigenetic research.

Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma

Background: Drug repurposing is a strategy that complements the conventional approach of developing new drugs. Hepatocellular carcinoma (HCC) is a highly prevalent type of liver cancer, necessitating an in-depth understanding of the underlying molecular alterations for improved treatment. Methods: We searched for a vast array of microarray experiments in addition to RNA-seq data. Through rigorous filtering processes, we have identified highly representative differentially expressed genes (DEGs) between tumor and non-tumor liver tissues and identified a distinct class of possible new candidate drugs. Results: Functional enrichment analysis revealed distinct biological processes associated with metal ions, including zinc, cadmium, and copper, potentially implicating chronic metal ion exposure in tumorigenesis. Conversely, up-regulated genes are associated with mitotic events and kinase activities, aligning with the relevance of kinases in HCC. To unravel the regulatory networks governing these DEGs, we employed topological analysis methods, identifying 25 hub genes and their regulatory transcription factors. In the pursuit of potential therapeutic options, we explored drug repurposing strategies based on computational approaches, analyzing their potential to reverse the expression patterns of key genes, including AURKA, CCNB1, CDK1, RRM2, and TOP2A. Potential therapeutic chemicals are alvocidib, AT-7519, kenpaullone, PHA-793887, JNJ-7706621, danusertibe, doxorubicin and analogues, mitoxantrone, podofilox, teniposide, and amonafide. Conclusion: This multi-omic study offers a comprehensive view of DEGs in HCC, shedding light on potential therapeutic targets and drug repurposing opportunities.

Histomolecular characterisation of hepatitis B virus induced liver cancer

Hepatitis B virus (HBV)-associated liver cancer is the third most prevalent cancer-related cause of death worldwide. Different studies have been done on the histomolecular analysis of HBV induced-liver cancer including epigenetics which are dynamic molecular mechanisms to control gene expression without altering the host deoxyribonucleic acid, genomics characterise the integration of the viral genome with host genome, proteomics characterise how gene modifies and results overexpression of proteins, glycoproteomics discover different glyco-biomarker candidates and show glycosylation in malignant hepatocytes, metabolomics characterise how HBV impairs a variety of metabolic functions during hepatocyte immortalisation, exosomes characterise immortalised liver cells in terms of their differentiation and proliferation, and autophagy plays a role in the development of hepatocarcinogenesis linked to HBV infection.

Current advances in detecting genetic and epigenetic biomarkers of colorectal cancer

Colorectal carcinoma (CRC) is the third most common cancer in terms of diagnosis and the second in terms of mortality. Recent studies have shown that various proteins, extracellular vesicles (i.e., exosomes), specific genetic variants, gene transcripts, cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and altered epigenetic patterns, can be used to detect, and assess the prognosis of CRC. Over the last decade, a plethora of conventional methodologies (e.g., polymerase chain reaction [PCR], direct sequencing, enzyme-linked immunosorbent assay [ELISA], microarray, in situ hybridization) as well as advanced analytical methodologies (e.g., microfluidics, electrochemical biosensors, surface-enhanced Raman spectroscopy [SERS]) have been developed for analyzing genetic and epigenetic biomarkers using both optical and non-optical tools. Despite these methodologies, no gold standard detection method has yet been implemented that can analyze CRC with high specificity and sensitivity in an inexpensive, simple, and time-efficient manner. Moreover, until now, no study has critically reviewed the advantages and limitations of these methodologies. Here, an overview of the most used genetic and epigenetic biomarkers for CRC and their detection methods are discussed. Furthermore, a summary of the major biological, technical, and clinical challenges and advantages/limitations of existing techniques is also presented.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.

Integrating population-level and cell-based signatures for drug repositioning

Drug repositioning presents a streamlined and cost-efficient way to expand the range of therapeutic possibilities. Furthermore, drugs with genetic evidence are more likely to progress successfully through clinical trials towards FDA approval. Exploiting these developments, single gene-based drug repositioning methods have been implemented, but approaches leveraging the entire spectrum of molecular signatures are critically underexplored. Most multi-gene-based approaches rely on differential gene expression (DGE) analysis, which is prone to identify the molecular consequence of disease and renders causal inference challenging. We propose a framework TReD (Transcriptome-informed Reversal Distance) that integrates population-level disease signatures robust to reverse causality and cell-based drug-induced transcriptome response profiles. TReD embeds the disease signature and drug profile in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell screen assay. The robustness is ensured by evaluation in additional cell screens. For an application, we implement the framework to identify potential drugs against COVID-19. Taking transcriptome-wide association study (TWAS) results from four relevant tissues and three DGE results as disease features, we identify 37 drugs showing potential reversal roles in at least four of the seven disease signatures. Notably, over 70% (27/37) of the drugs have been linked to COVID-19 from other studies, and among them, eight drugs are supported by ongoing/completed clinical trials. For example, TReD identifies the well-studied JAK1/JAK2 inhibitor baricitinib, the first FDA-approved immunomodulatory treatment for COVID-19. Novel potential candidates, including enzastaurin, a selective inhibitor of PKC-beta which can be activated by SARS-CoV-2, are also identified. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screens that can accelerate the search for new therapeutic strategies.

Gut microbiota and autism spectrum disorders: where do we stand?

BACKGROUND

Children with autism spectrum disorder (ASD) often have digestive problems and microbial imbalances in their guts, suggesting that these conditions may play a role in the development of the disorder. Scopus-based research on the gut microbiota and ASD was examined in this bibliometric analysis to shed light on the current state of research and identify potential hotspots for future work in this area.

METHODS

We searched documents from the Scopus database and reference citation analysis to collect published data on the gut microbiota and ASD from 2003 to 2022. The downloaded document records were exported to VOSviewer v.1.6.19 to examine and visualize the collaboration between countries and determine the research hotspots.

RESULTS

The search yielded 958 articles specifically dedicated to gut microbiota and ASD. The number of publications in this field increased rapidly after 2013, with a peak in 2022. The United States (n = 267; 27.87%) was the most active country, followed by China (n = 171; 17.85%) and Italy (n = 96; 10.02). International collaboration was observed, with the USA playing a central role. University College Cork, Ireland, was the most productive institution (n = 24; 2.51%). The National Natural Science Foundation of China was the most active funding agency (n = 76; 7.93%). Nutrients journal had the highest number of publications (n = 28; 2.92%). The articles related to gut microbiota and ASD were highly cited, with an h-index of 108. The research themes identified focused on the modulation of gut microbiota as a potential therapy for children with ASD and gut-brain axis dysfunction in ASD.

CONCLUSIONS

In recent years, the study of gut microbiota and its association with ASD has garnered considerable interest as an emergent field of study. The results of this study substantially enhance our current understanding of the knowledge landscape in this field and illuminate potential avenues for future research. It is essential to emphasize the significance of devoting more resources to the newest and most promising research areas, such as investigating the potential therapeutic benefits of modulating the intestinal microbiota in children with ASD. This research has enormous potential and merits intensified focus and investigation.

Disease Diagnosis Based on Nucleic Acid Modifications

Nucleic acid modifications include a wide range of epigenetic and epitranscriptomic factors and impact a wide range of nucleic acids due to their profound influence on biological inheritance, growth, and metabolism. The recently developed methods of mapping and characterizing these modifications have promoted their discovery as well as large-scale studies in eukaryotes, especially in humans. Because of these pioneering strategies, nucleic acid modifications have been shown to have a great impact on human disorders such as cancer. Therefore, whether nucleic acid modifications could become a new type of biomarker remains an open question. In this review, we briefly look back at classical nucleic acid modifications and then focus on the progress made in investigating these modifications as diagnostic biomarkers in clinical therapy and present our perspective on their development prospects.

Applying a Gene Reversal Rate Computational Methodology to Identify Drugs for a Rare Cancer: Inflammatory Breast Cancer

The aim of this study was to utilize a computational methodology based on Gene Reversal Rate (GRR) scoring to repurpose existing drugs for a rare and understudied cancer: inflammatory breast cancer (IBC). This method uses IBC-related gene expression signatures (GES) and drug-induced gene expression profiles from the LINCS database to calculate a GRR score for each candidate drug, and is based on the idea that a compound that can counteract gene expression changes of a disease may have potential therapeutic applications for that disease. Genes related to IBC with associated differential expression data (265 up-regulated and 122 down-regulated) were collated from PubMed-indexed publications. Drug-induced gene expression profiles were downloaded from the LINCS database and candidate drugs to treat IBC were predicted using their GRR scores. Thirty-two (32) drug perturbations that could potentially reverse the pre-compiled list of 297 IBC genes were obtained using the LINCS Canvas Browser (LCB) analysis. Binary combinations of the 32 perturbations were assessed computationally to identify combined perturbations with the highest GRR scores, and resulted in 131 combinations with GRR greater than 80%, that reverse up to 264 of the 297 genes in the IBC-GES. The top 35 combinations involve 20 unique individual drug perturbations, and 19 potential drug candidates. A comprehensive literature search confirmed 17 of the 19 known drugs as having either anti-cancer or anti-inflammatory activities. AZD-7545, BMS-754807, and nimesulide target known IBC relevant genes: PDK, Met, and COX, respectively. AG-14361, butalbital, and clobenpropit are known to be functionally relevant in DNA damage, cell cycle, and apoptosis, respectively. These findings support the use of the GRR approach to identify drug candidates and potential combination therapies that could be used to treat rare diseases such as IBC.

Diagnosing and monitoring pancreatic cancer through cell-free DNA methylation: progress and prospects

Pancreatic cancer is one of the most challenging cancers due to its high mortality rates. Considering the late diagnosis and the limited survival benefit with current treatment options, it becomes imperative to optimize early detection, prognosis and prediction of treatment response. To address these challenges, significant research efforts have been undertaken in recent years to develop liquid-biopsy-based biomarkers for pancreatic cancer. In particular, an increasing number of studies point to cell-free DNA (cfDNA) methylation analysis as a promising non-invasive approach for the discovery and validation of epigenetic biomarkers with diagnostic or prognostic potential. In this review we provide an update on recent advancements in the field of cfDNA methylation analysis in pancreatic cancer. We discuss the relevance of DNA methylation in the context of pancreatic cancer, recent cfDNA methylation research, its clinical utility, and future directions for integrating cfDNA methylation analysis into routine clinical practice.

Associations of MTHFR Polymorphisms and Cytosine Modifications with Early-Gestational Diabetes Mellitus in Chinese Pregnant Women

Early-Gestational Diabetes Mellitus (Early-GDM) is a complex condition that may cause complications in infants of affected mothers. The aim of this case-control study was to analyze the effects of genetic-epigenetic interaction on Early-GDM and fetal development with respect to cytosine modifications (i.e., 5mC, 5-methylcytosines; and 5hmC, 5-hydroxymethylcytosines) and single nucleotide polymorphisms (SNPs) of MTHFR, a key gene involving cytosine modifications. Peripheral blood samples were collected from 92 women in their first or second trimester of pregnancy (Early-GDM, n = 14; Controls, n = 78). Global DNA 5mC and 5hmC were quantified by HPLC-MS/MS, and MTHFR SNPs (rs1801133 C > T and rs1801131 A > C) were determined by TaqMan-qPCR. Association analysis suggested that MTHFR rs1801133 TT genotype was a risk factor of Early-GDM (OR [odds ratio] = 4.00; 95% CI [confidence interval]: 1.24, 12.86; p = 0.02). The C allele of rs1801131 appeared to be a protective factor for the 2-h OGTT (oral glucose tolerance test) (OR = -0.79; 95% CI: -1.48, -0.10; p = 0.03). Patients with Early-GDM had higher global 5mC and lower global 5hmC. The reduction of global 5hmC and the TT genotype of rs1801133 were associated with higher level of the 1st-FBG (fasting blood glucose in the first trimester) (p < 0.05). Additionally, global 5mC showed a positive correlation with birth weight, body length and head circumference of newborns, while global 5hmC showed a negative correlation with birth weight. The current study implicated MTHFR SNPs and cytosine modifications in the development of Early-GDM and potential complications in their newborns.

Intestinal barrier in inflammatory bowel disease: A bibliometric and knowledge-map analysis

BACKGROUND

Barrier surfaces composed of specialized epithelial cells separate the host body from the external environment, and are essential for maintaining proper intestinal physiologic and immune homeostasis.

AIM

To explore the development trends and research hotspots of intestinal barrier research in inflammatory bowel disease (IBD).

METHODS

The publications related to the intestinal barrier in IBD were obtained from the Web of Science Core Collection database. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace and R software.

RESULTS

A total of 4482 articles published between 2002 and 2022 were identified. The United States is dominant in intestinal barrier research, whereas the University of Chicago is the most active institution. Jerrold from Harvard Medical School was the most productive authors with the most citations. The journals Inflammatory Bowel Disease and Gastroenterology have made significant contributions in this field. The keywords appearing at high frequency related to the intestinal barrier in IBD were detected, including nuclear factor kappa B, tumor necrosis factor-α, apoptosis, oxidative stress and probiotics. Among them, antioxidants, Akkermansia muciniphila, nanoparticles, short-chain fatty acids and extracellular vesicles have received growing interest in recent research.

CONCLUSION

The intestinal barrier field is developing rapidly with extensive cooperation. Targeting the gut microbiota and dietary metabolism to regulate the intestinal barrier has shown promising prospective applications and has generated broad interest. The importance of the intestinal barrier in IBD is gradually being fully recognized, providing a new therapeutic perspective for improving inflammation and prognosis.

COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming

Immune evasion and metabolism reprogramming have been regarded as two vital hallmarks of the mechanism of carcinogenesis. Thus, targeting the immune microenvironment and the reprogrammed metabolic processes will aid in developing novel anti-cancer drugs. In recent decades, herbal medicine has been widely utilized to treat cancer through the modulation of the immune microenvironment and reprogrammed metabolic processes. However, labor-based herbal ingredient screening is time consuming, laborious and costly. Luckily, some computational approaches have been proposed to screen candidates for drug discovery rapidly. Yet, it has been challenging to develop methods to screen drug candidates exclusively targeting specific pathways, especially for herbal ingredients which exert anti-cancer effects by multiple targets, multiple pathways and synergistic ways. Meanwhile, currently employed approaches cannot quantify the contribution of the specific pathway to the overall curative effect of herbal ingredients. Hence, to address this problem, this study proposes a new computational framework to infer the contribution of the immune microenvironment and metabolic reprogramming (COIMMR) in herbal ingredients against human cancer and specifically screen herbal ingredients targeting the immune microenvironment and metabolic reprogramming. Finally, COIMMR was applied to identify isoliquiritigenin that specifically regulates the T cells in stomach adenocarcinoma and cephaelin hydrochloride that specifically targets metabolic reprogramming in low-grade glioma. The in silico results were further verified using in vitro experiments. Taken together, our approach opens new possibilities for repositioning drugs targeting immune and metabolic dysfunction in human cancer and provides new insights for drug development in other diseases. COIMMR is available at https://github.com/LYN2323/COIMMR.

Unveiling the hidden world of gut health: Exploring cutting-edge research through visualizing randomized controlled trials on the gut microbiota

BACKGROUND

The gut microbiota plays a crucial role in gastrointestinal and overall health. Randomized clinical trials (RCTs) play a crucial role in advancing our knowledge and evaluating the efficacy of therapeutic interventions targeting the gut microbiota.

AIM

To conduct a comprehensive bibliometric analysis of the literature on RCTs involving the gut microbiota.

METHODS

Using bibliometric tools, a descriptive cross-sectional investigation was conducted on scholarly publications concentrated on RCTs related to gut microbiota, spanning the years 2003 to 2022. The study used VOSviewer version 1.6.9 to examine collaboration networks between different countries and evaluate the frequently employed terms in the titles and abstracts of the retrieved publications. The primary objective of this analysis was to identify key research areas and focal points associated with RCTs involving the gut microbiota.

RESULTS

A total of 1061 relevant articles were identified from the 24758 research articles published between 2003 and 2022. The number of publications showed a notable increase over time, with a positive correlation (R2 = 0.978, P < 0.001). China (n = 276, 26.01%), the United States (n = 254, 23.94%), and the United Kingdom (n = 97, 9.14%) were the leading contributing countries. Københavns Universitet (n = 38, 3.58%) and Dankook University (n = 35, 3.30%) were the top active institutions. The co-occurrence analysis shows current gut microbiota research trends and important topics, such as obesity interventions targeting the gut microbiota, the efficacy and safety of fecal microbiota transplantation, and the effects of dietary interventions on humans.

CONCLUSION

The study highlights the rapid growth and importance of research on RCTs that involve the gut microbiota. This study provides valuable insight into research trends, identifies key players, and outlines potential future directions in this field. Additionally, the co-occurrence analysis identified important topics that play a critical role in the advancement of science and provided insights into future research directions in this field.

DARESOME enables concurrent profiling of multiple DNA modifications with restriction enzymes in single cells and cell-free DNA

5-Methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are the most abundant DNA modifications that have important roles in gene regulation. Detailed studies of these different epigenetic marks aimed at understanding their combined effects and dynamic interconversion are, however, hampered by the inability of current methods to simultaneously measure both modifications, particularly in samples with limited quantities. We present DNA analysis by restriction enzyme for simultaneous detection of multiple epigenomic states (DARESOME), an assay based on modification-sensitive restriction digest and sequential tag ligation that can concurrently perform quantitative profiling of unmodified cytosine, 5mC, and 5hmC in CCGG sites genome-wide. DARESOME reveals the opposing roles of 5mC and 5hmC in gene expression regulation as well as their interconversion during aging in mouse brain. Implementation of DARESOME in single cells demonstrates pronounced 5hmC strand bias that reflects the semiconservative replication of DNA. Last, we showed that DARESOME enables integrative genomic, 5mC, and 5hmC profiling of cell-free DNA that uncovered multiomics cancer signatures in liquid biopsy.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

An inexpensive semi-automated sample processing pipeline for cell-free RNA extraction

Despite advances in automated liquid handling and microfluidics, preparing samples for RNA sequencing at scale generally requires expensive equipment, which is beyond the reach of many academic laboratories. Manual sample preparation remains a slow, expensive and error-prone process. Here, we describe a low-cost, semi-automated pipeline to extract cell-free RNA using one of two commercially available, inexpensive and open-source robotic systems: the Opentrons OT1.0 or OT2.0. Like many RNA isolation protocols, ours can be decomposed into three subparts: RNA extraction, DNA digestion and RNA cleaning and concentration. RT-qPCR data using a synthetic spike-in confirms comparable RNA quality to the gold standard, manual sample processing. The semi-automated pipeline also shows improvement in sample throughput (+12×), time spent (-11×), cost (-3×) and biohazardous waste produced (-4×) compared with its manual counterpart. This protocol enables cell-free RNA extraction from 96 samples simultaneously in 4.5 h; in practice, this dramatically improves the time to results, as we recently demonstrated. Importantly, any laboratory already has most of the parts required (manual pipette and corresponding tips and kits for RNA isolation, cleaning and concentration) to build a semi-automated sample processing pipeline of their own and would only need to purchase or three-dimensionally print a few extra parts (US$5.5 K-12 K in total). This pipeline is also generalizable for many nucleic acid extraction applications, thereby increasing the scale of studies, which can be performed in small research laboratories.

Endometriosis in the era of precision medicine and impact on sexual and reproductive health across the lifespan and in diverse populations

Endometriosis is a common estrogen-dependent disorder wherein uterine lining tissue (endometrium) is found mainly in the pelvis where it causes inflammation, chronic pelvic pain, pain with intercourse and menses, and infertility. Recent evidence also supports a systemic inflammatory component that underlies associated co-morbidities, e.g., migraines and cardiovascular and autoimmune diseases. Genetics and environment contribute significantly to disease risk, and with the explosion of omics technologies, underlying mechanisms of symptoms are increasingly being elucidated, although novel and effective therapeutics for pain and infertility have lagged behind these advances. Moreover, there are stark disparities in diagnosis, access to care, and treatment among persons of color and transgender/nonbinary identity, socioeconomically disadvantaged populations, and adolescents, and a disturbing low awareness among health care providers, policymakers, and the lay public about endometriosis, which, if left undiagnosed and under-treated can lead to significant fibrosis, infertility, depression, and markedly diminished quality of life. This review summarizes endometriosis epidemiology, compelling evidence for its pathogenesis, mechanisms underlying its pathophysiology in the age of precision medicine, recent biomarker discovery, novel therapeutic approaches, and issues around reproductive justice for marginalized populations with this disorder spanning the past 100 years. As we enter the next revolution in health care and biomedical research, with rich molecular and clinical datasets, single-cell omics, and population-level data, endometriosis is well positioned to benefit from data-driven research leveraging computational and artificial intelligence approaches integrating data and predicting disease risk, diagnosis, response to medical and surgical therapies, and prognosis for recurrence.

Global research trends and mapping knowledge structure of depression in dialysis patients

BACKGROUND

Depression is one of the most common and important psychological issues faced by dialysis patients. It can make it more difficult for them to adhere to their treatment regimen, which, in turn, can worsen their physical symptoms and lead to poorer health outcomes.

AIM

To examine the evolution and growth of publications related to dialysis and depression. The objectives were to identify the number of publications, the top active countries, the contributed institutions, funding agencies and journals, as well as to perform citation and research theme analysis.

METHODS

The search was conducted using the Scopus database for publications related to dialysis and depression between 1970 and 2022. Subsequently, bibliometric analysis was carried out on the data obtained using VOSviewer software, version 1.6.9. This analysis included visualization analysis, co-occurrence analysis and examination of publication trends in dialysis and depression.

RESULTS

We identified 800 publications that met the search criteria. The number of publications related to dialysis and depression has increased significantly in the past two decades. The USA led the way with 144 publications, which is 18% of all publications on this topic. Turkey came second with 88 publications (11%), followed by China with 55 publications (6.88%) and Iran with 52 publications (6.5%). Analysis of the research theme identified three main clusters related to gender differences in prevalence, identification of depression as a risk factor, and effective interventions to relieve depression. Future research direction analysis shows a shift toward effective interventions to relieve depression in dialysis patients.

CONCLUSION

This study provides a comprehensive overview of growth, trends and research themes related to dialysis and depression that could help researchers identify gaps in the literature and develop future research.

Steadfast Toll Like Receptor 4 (TLR4) 5-Hydroxymethylcytosine Levels in Cell-Free DNA: A Promising Consistency Marker for Colorectal Cancer Patients

Cell-free DNA (cfDNA) from patient blood is emerging as a noninvasive diagnostic avenue for various cancers. We aimed to identify reliable biomarkers in cfDNA by investigating genes exhibiting significant differences between colorectal cancer and control samples. Our objective was to identify genes that showed a positive difference between cancer and control samples. To achieve this, we conducted an in silico analysis to identify genes that exhibit no significant variation in methylation between genomic DNA (gDNA) and cfDNA. We collected experimental data from publicly available repositories, which included 5-hydroxymethylcytosine (5hmC) profiles of gDNA and cfDNA samples from both cancer patients and healthy individuals. By comparing and overlapping these two groups, we identified 187 genes of interest, of which 53 genes had a positive difference among colon cancer patients and healthy individuals. Next, we performed an ANOVA test on these genes, resulting in the identification of 12 genes that showed statistically significant higher levels of 5hmC in cfDNA and gDNA from cancer patients compared to healthy individuals. Additionally, we compared the 5hmC status of these genes between cfDNA and gDNA from cancer patients. Interestingly, we found that the 5hmC of the toll like receptor 4 (TLR4) gene was not statistically different between cfDNA and gDNA from cancer patients, indicating consistency between cfDNA and gDNA. These findings have important implications, not only for experimental validation but also for the development of more sensitive and robust noninvasive methods to improve diagnostic, prognostic, and treatment options for colon cancer.

Thymic lymphoma detection in RORγ knockout mice using 5-hydroxymethylcytosine profiling of circulating cell-free DNA

A high incidence of thymic lymphoma has been noted in mice deficient of retinoid-related orphan receptor γ2 (RORγ2), which is required for differentiation of naïve CD4+ T cells into TH17 cells. Using a RORγ homozygous knockout (KO) mouse model of thymic lymphoma, we characterized this tumor progression and investigated the utility of 5-hydroxymethylcytosine (5hmC) signatures as a non-invasive circulating biomarker for early prediction of malignancy. No evidence for malignancy was noted in the wild-type mice, while primary thymic lymphoma with multi-organ metastasis was observed microscopically in 97% of the homozygous RORγ KO mice. The severity of thymic lymphoma was not age-dependent in the KO mice of 2 to 4 months old. Differential enrichment of 5hmC in thymic DNA and plasma cell-free DNA (cfDNA) was compared across different stages of tumor progression. Random forest modeling of plasma cfDNA achieved good predictivity (AUC = 0.74) in distinguishing early non-metastatic thymic lymphoma compared to cancer-free controls, while perfect predictivity was achieved with advanced multi-organ metastatic disease (AUC = 1.00). Lymphoid-specific genes involved in thymocyte selection during T cell development (Themis, Tox) were differentially enriched in both plasma and thymic tissue. This could help in differentiating thymic lymphoma from other tumors commonly detected in rodent carcinogenicity studies used in pharmaceutical drug development to inform human malignancy risk. Overall, these results provide a proof-of-concept for using circulating cfDNA profiles in rodent carcinogenicity studies for early risk assessment of novel pharmaceutical targets.

TET (Ten-eleven translocation) family proteins: structure, biological functions and applications

Ten-eleven translocation (TET) family proteins (TETs), specifically, TET1, TET2 and TET3, can modify DNA by oxidizing 5-methylcytosine (5mC) iteratively to yield 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxycytosine (5caC), and then two of these intermediates (5fC and 5caC) can be excised and return to unmethylated cytosines by thymine-DNA glycosylase (TDG)-mediated base excision repair. Because DNA methylation and demethylation play an important role in numerous biological processes, including zygote formation, embryogenesis, spatial learning and immune homeostasis, the regulation of TETs functions is complicated, and dysregulation of their functions is implicated in many diseases such as myeloid malignancies. In addition, recent studies have demonstrated that TET2 is able to catalyze the hydroxymethylation of RNA to perform post-transcriptional regulation. Notably, catalytic-independent functions of TETs in certain biological contexts have been identified, further highlighting their multifunctional roles. Interestingly, by reactivating the expression of selected target genes, accumulated evidences support the potential therapeutic use of TETs-based DNA methylation editing tools in disorders associated with epigenetic silencing. In this review, we summarize recent key findings in TETs functions, activity regulators at various levels, technological advances in the detection of 5hmC, the main TETs oxidative product, and TETs emerging applications in epigenetic editing. Furthermore, we discuss existing challenges and future directions in this field.

Transcriptomic clock predicts vascular changes of prodromal diabetic retinopathy

Diabetic retinopathy is a common complication of long-term diabetes and that could lead to vision loss. Unfortunately, early diabetic retinopathy remains poorly understood. There is no effective way to prevent or treat early diabetic retinopathy until patients develop later stages of diabetic retinopathy. Elevated acellular capillary density is considered a reliable quantitative trait present in the early development of retinopathy. Hence, in this study, we interrogated whole retinal vascular transcriptomic changes via a Nile rat model to better understand the early pathogenesis of diabetic retinopathy. We uncovered the complexity of associations between acellular capillary density and the joint factors of blood glucose, diet, and sex, which was modeled through a Bayesian network. Using segmented regressions, we have identified different gene expression patterns and enriched Gene Ontology (GO) terms associated with acellular capillary density increasing. We developed a random forest regression model based on expression patterns of 14 genes to predict the acellular capillary density. Since acellular capillary density is a reliable quantitative trait in early diabetic retinopathy, and thus our model can be used as a transcriptomic clock to measure the severity of the progression of early retinopathy. We also identified NVP-TAE684, geldanamycin, and NVP-AUY922 as the top three potential drugs which can potentially attenuate the early DR. Although we need more in vivo studies in the future to support our re-purposed drugs, we have provided a data-driven approach to drug discovery.

Liquid biopsies for cancer: From bench to clinic

Over the past two decades, liquid biopsy has been increasingly used as a supplement, or even, a replacement to the traditional biopsy in clinical oncological practice, due to its noninvasive and early detectable properties. The detections can be based on a variety of features extracted from tumor‑derived entities, such as quantitative alterations, genetic changes, and epigenetic aberrations, and so on. So far, the clinical applications of cancer liquid biopsy mainly aimed at two aspects, prediction (early diagnosis, prognosis and recurrent evaluation, therapeutic response monitoring, etc.) and intervention. In spite of the rapid development and great contributions achieved, cancer liquid biopsy is still a field under investigation and deserves more clinical practice. To better open up future work, here we systematically reviewed and compared the latest progress of the most widely recognized circulating components, including circulating tumor cells, cell-free circulating DNA, noncoding RNA, and nucleosomes, from their discovery histories to clinical values. According to the features applied, we particularly divided the contents into two parts, beyond epigenetics and epigenetic-based. The latter was considered as the highlight along with a brief overview of the advances in both experimental and bioinformatic approaches, due to its unique advantages and relatively lack of documentation.

Cellular Composition and 5hmC Signature Predict the Treatment Response of AML Patients to Azacitidine Combined with Chemotherapy

Azacitidine (AZA) is a DNA methyltransferase inhibitor and epigenetic modulator that can be an effective agent in combination with chemotherapy for patients with high-risk acute myeloid leukemia (AML). However, biological factors driving the therapeutic response of such hypomethylating agent (HMA)-based therapies remain unknown. Herein, the transcriptome and/or genome-wide 5-hydroxymethylcytosine (5hmC) is characterized for 41 patients with high-risk AML from a phase 1 clinical trial treated with AZA epigenetic priming followed by high-dose cytarabine and mitoxantrone (AZA-HiDAC-Mito). Digital cytometry reveals that responders have elevated Granulocyte-macrophage-progenitor-like (GMP-like) malignant cells displaying an active cell cycle program. Moreover, the enrichment of natural killer (NK) cells predicts a favorable outcome in patients receiving AZA-HiDAC-Mito therapy or other AZA-based therapies. Comparing 5hmC profiles before and after five-day treatment of AZA shows that AZA exposure induces dose-dependent 5hmC changes, in which the magnitude correlates with overall survival (p = 0.015). An extreme gradient boosting (XGBoost) machine learning model is developed to predict the treatment response based on 5hmC levels of 11 genes, achieving an area under the curve (AUC) of 0.860. These results suggest that cellular composition markedly impacts the treatment response, and showcase the prospect of 5hmC signatures in predicting the outcomes of HMA-based therapies in AML.

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

BACKGROUND

Using epigenetic markers and fragmentomics of cell-free DNA for cancer detection has been proven applicable.

METHODS

We further investigated the diagnostic potential of combining two features (epigenetic markers and fragmentomic information) of cell-free DNA for detecting various types of cancers. To do this, we extracted cfDNA fragmentomic features from 191 whole-genome sequencing data and studied them in 396 low-pass 5hmC sequencing data, which included four common cancer types and control samples.

RESULTS

In our analysis of 5hmC sequencing data from cancer samples, we observed aberrant ultra-long fragments (220-500 bp) that differed from normal samples in terms of both size and coverage profile. These fragments played a significant role in predicting cancer. Leveraging the ability to detect cfDNA hydroxymethylation and fragmentomic markers simultaneously in low-pass 5hmC sequencing data, we developed an integrated model that incorporated 63 features representing both fragmentomic features and hydroxymethylation signatures. This model achieved high sensitivity and specificity for pan-cancer detection (88.52% and 82.35%, respectively).

CONCLUSION

We showed that fragmentomic information in 5hmC sequencing data is an ideal marker for cancer detection and that it shows high performance in low-pass sequencing data.

Therapies for patients with coexisting heart failure with reduced ejection fraction and non-alcoholic fatty liver disease

Heart failure with reduced ejection fraction (HFrEF) and nonalcoholic fatty liver disease (NAFLD) are two common comorbidities that share similar pathophysiological mechanisms. There is a growing interest in the potential of targeted therapies to improve outcomes in patients with coexisting HFrEF and NAFLD. This manuscript reviews current and potential therapies for patients with coexisting HFrEF and NAFLD. Pharmacological therapies, including angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, mineralocorticoids receptor antagonist, and sodium-glucose cotransporter-2 inhibitors, have been shown to reduce fibrosis and fat deposits in the liver. However, there are currently no data showing the beneficial effects of sacubitril/valsartan, ivabradine, hydralazine, isosorbide nitrates, digoxin, or beta blockers on NAFLD in patients with HFrEF. This study highlights the importance of considering HFrEF and NAFLD when developing treatment plans for patients with these comorbidities. Further research is needed in patients with coexisting HFrEF and NAFLD, with an emphasis on novel therapies and the importance of a multidisciplinary approach for managing these complex comorbidities.

Research landscape on COVID-19 and liver dysfunction: A bibliometric analysis

BACKGROUND

The global spread of severe acute respiratory syndrome coronavirus 2, responsible for coronavirus disease 2019 (COVID-19), poses a significant risk to public health. Beyond the respiratory issues initially associated with the condition, severe cases of COVID-19 can also lead to complications in other organs, including the liver. Patients with severe COVID-19 may exhibit various clinical signs of liver dysfunction, ranging from minor elevations in liver enzymes without symptoms to more serious cases of impaired liver function. Liver damage is more commonly observed in patients with severe or critical forms of the disease.

AIM

To present the research landscape on COVID-19 and liver dysfunction while also offering valuable insights into the prominent areas of interest within this particular domain.

METHODS

On 18 February 2023, Scopus was utilised to conduct a comprehensive exploration of the relationship between COVID-19 and the liver dysfunction. The investigation encompassed the period from 1 January 2020 to 31 December 2022. Primary sources were meticulously examined and organised in a Microsoft Excel 2013 spreadsheet, categorised by journal, institution, funding agency, country and citation type. VOSviewer version 1.6.18 was employed to explore the prominent topics and knowledge network related to the subject.

RESULTS

There were 2336 publications on COVID-19 and liver dysfunction analysed in this study, of which 558 were published in 2020, 891 in 2021 and 887 in 2022. Researchers from 111 different countries participated in the retrieved documents. The United States contributed the most studies, with 497 documents, representing 21.28% of the total, followed by China with 393 documents (16.82%) and Italy with 255 documents (10.92%). In the context of research related to COVID-19 and the liver, co-occurrence analysis identified three distinct clusters of topics: (1) 'COVID-19 vaccines in liver transplant recipients'; (2) 'liver function tests as a predictor of the severity and clinical outcomes in hospitalised patients'; and (3) 'care of patients with liver disease during the COVID-19 pandemic'.

CONCLUSION

This bibliometric study provides a comprehensive overview of liver-related publications in COVID-19 research over the past 3 years. This study highlights the significant contributions of high-income nations, particularly the United States, China, and Italy, to the production of liver-related scholarly literature in this field. Most of the articles focused on liver dysfunction in patients with COVID-19 and the implications of the virus for gastroenterologists and hepatologists.

Targeting Wnt-β-Catenin Signaling Pathway for Hepatocellular Carcinoma Nanomedicine

Hepatocellular carcinoma (HCC) represents a high-fatality cancer with a 5-year survival of 22%. The Wnt/β-catenin signaling pathway presents as one of the most upregulated pathways in HCC. However, it has so far not been targetable in the clinical setting. Therefore, studying new targets of this signaling cascade from a therapeutic aspect could enable reversal, delay, or prevention of hepatocarcinogenesis. Although enormous advancement has been achieved in HCC research and its therapeutic management, since HCC often occurs in the context of other liver diseases such as cirrhosis leading to liver dysfunction and/or impaired drug metabolism, the current therapies face the challenge of safely and effectively delivering drugs to the HCC tumor site. In this review, we discuss how a targeted nano drug delivery system could help minimize the off-target toxicities of conventional HCC therapies as well as enhance treatment efficacy. We also put forward the current challenges in HCC nanomedicine along with some potential therapeutic targets from the Wnt/β-catenin signaling pathway that could be used for HCC therapy. Overall, this review will provide an insight to the current advances, limitations and how HCC nanomedicine could change the landscape of some of the undruggable targets in the Wnt/β-catenin pathway.

Network neighborhood operates as a drug repositioning method for cancer treatment

Computational drug repositioning approaches are important, as they cost less compared to the traditional drug development processes. This study proposes a novel network-based drug repositioning approach, which computes similarities between disease-causing genes and drug-affected genes in a network topology to suggest candidate drugs with highest similarity scores. This new method aims to identify better treatment options by integrating systems biology approaches. It uses a protein-protein interaction network that is the main topology to compute a similarity score between candidate drugs and disease-causing genes. The disease-causing genes were mapped on this network structure. Transcriptome profiles of drug candidates were taken from the LINCS project and mapped individually on the network structure. The similarity of these two networks was calculated by different network neighborhood metrics, including Adamic-Adar, PageRank and neighborhood scoring. The proposed approach identifies the best candidates by choosing the drugs with significant similarity scores. The method was experimented on melanoma, colorectal, and prostate cancers. Several candidate drugs were predicted by applying AUC values of 0.6 or higher. Some of the predictions were approved by clinical phase trials or other in-vivo studies found in literature. The proposed drug repositioning approach would suggest better treatment options with integration of functional information between genes and transcriptome level effects of drug perturbations and diseases.

Niclosamide (NA) overcomes cisplatin resistance in human ovarian cancer

Ovarian cancer (OC) is one of the most lethal malignancies of the female reproductive system. OC patients are usually diagnosed at advanced stages due to the lack of early diagnosis. The standard treatment for OC includes a combination of debulking surgery and platinum-taxane chemotherapy, while several targeted therapies have recently been approved for maintenance treatment. The vast majority of OC patients relapse with chemoresistant tumors after an initial response. Thus, there is an unmet clinical need to develop new therapeutic agents to overcome the chemoresistance of OC. The anti-parasite agent niclosamide (NA) has been repurposed as an anti-cancer agent and exerts potent anti-cancer activities in human cancers including OC. Here, we investigated whether NA could be repurposed as a therapeutic agent to overcome cisplatin-resistant (CR) in human OC cells. To this end, we first established two CR lines SKOV3CR and OVCAR8CR that exhibit the essential biological characteristics of cisplatin resistance in human cancer. We showed that NA inhibited cell proliferation, suppressed cell migration, and induced cell apoptosis in both CR lines at a low micromole range. Mechanistically, NA inhibited multiple cancer-related pathways including AP1, ELK/SRF, HIF1, and TCF/LEF, in SKOV3CR and OVCAR8CR cells. NA was further shown to effectively inhibit xenograft tumor growth of SKOV3CR cells. Collectively, our findings strongly suggest that NA may be repurposed as an efficacious agent to combat cisplatin resistance in chemoresistant human OC, and further clinical trials are highly warranted.

Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA

BACKGROUND & AIMS

Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma.

METHODS

Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs.

RESULTS

5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%).

CONCLUSIONS

The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

Transcriptomics-driven drug repositioning for the treatment of diabetic foot ulcer

Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU.

Repurposing of neprilysin inhibitor 'sacubitrilat' as an anti-cancer drug by modulating epigenetic and apoptotic regulators

Modifications in the epigenetic landscape have been considered a hallmark of cancer. Histone deacetylation is one of the crucial epigenetic modulations associated with the aggressive progression of various cancer subtypes. Herein, we have repurposed the neprilysin inhibitor sacubitrilat as a potent anticancer agent using in-silico protein-ligand interaction profiler (PLIP) analysis, molecular docking, and in vitro studies. The screening of PLIP profiles between vorinostat/panobinostat and HDACs/LTA4H followed by molecular docking resulted in five (Sacubitrilat, B65, BDS, BIR, and NPV) FDA-approved, experimental and investigational drugs. Sacubitrilat has demonstrated promising anticancer activity against colorectal cancer (SW-480) and triple-negative breast cancer (MDA-MB-231) cells, with IC₅₀ values of 14.07 μg/mL and 23.02 μg/mL, respectively. FACS analysis revealed that sacubitrilat arrests the cell cycle at the G0/G1 phase and induces apoptotic-mediated cell death in SW-480 cells. In addition, sacubitrilat inhibited HDAC isoforms at the transcriptomic level by 0.7-0.9 fold and at the proteomic level by 0.5-0.6 fold as compared to the control. Sacubitrilat increased the protein expression of tumor-suppressor (p53) and pro-apoptotic makers (Bax and Bid) by 0.2-2.5 fold while decreasing the expression of anti-apoptotic Bcl2 and Nrf2 proteins by 0.2-0.5 fold with respect to control. The observed cleaved PARP product indicates that sacubitrilat induces apoptotic-mediated cell death. This study may pave the way to identify the anticancer potential of sacubitrilat and can be explored in human clinical trials.

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes

Introduction

Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes.

Methods

In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival.

Results

We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line.

Conclusion

We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

Global research trends on diet and nutrition in Crohn's disease

BACKGROUND

Crohn's disease represents a challenge for patients concerned with the modified diet regimen as well as practitioners who seek the best nutritional therapy. Crohn's disease can alter the body's ability to digest food and to absorb nutrients, resulting in severe vitamin deficiencies, malnutrition and sometimes life-threatening complications. However, a comprehensive bibliometric analysis is lacking to map the current links between nutrition and Crohn's disease in terms of the number of citations, geographic distribution and growth trends of publications.

AIM

To introduce the current state of research as well as hotspots in the field of nutrition and Crohn's disease from a bibliometric standpoint.

METHODS

We searched the Scopus database and selected the relevant literature on nutrition and Crohn's disease that met the inclusion criteria. We analyzed the publication trends and research hotspots by using video object segmentation viewer software.

RESULTS

We included 1237 publications. The number of documents published each year has increased steadily. The United States and the University of Otago, Christchurch, have had the highest productivity, with 208 (16.81%) and 29 (2.34%) documents, respectively. The "role of exclusive enteral nutrition for complicated Crohn's disease" and "manipulation of the gut microbiota as a key target for Crohn's disease" were the major research areas in 2016-2021, and they could be extensively investigated in the future. Meanwhile, research on "malnutrition in patients with Crohn's disease" appeared to be an area that attracted more research attention before 2016.

CONCLUSION

This is the first bibliometric analysis to map the knowledge structure and trends regarding nutrition in Crohn's disease research over the past two decades. The results provide a comprehensive summary and identification of the frontiers of nutrition and Crohn's disease-related research, which may be used as a resource by researchers in the field.

Rational design, synthesis and structural characterization of peptides and peptidomimetics to target Hsp90/Cdc37 interaction for treating hepatocellular carcinoma

Heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) work together as a molecular chaperone complex to regulate the activity of a multitude of client protein kinases. These kinases belong to a wide array of intracellular signaling networks that mediate multiple cellular processes including proliferation. As a result, Hsp90 and Cdc37 represent innovative therapeutic targets in various cancers (such as leukemia, multiple myeloma, and hepatocellular carcinoma (HCC)) in which their expression levels are elevated. Conventional small molecule Hsp90 inhibitors act by blocking the conserved adenosine triphosphate (ATP) binding site. However, by targeting less conserved sites in a more specific manner, peptides and peptidomimetics (modified peptides) hold potential as more efficacious and less toxic alternatives to the conventional small molecule inhibitors. Using a rational approach, we herein developed bioactive peptides targeting Hsp90/Cdc37 interaction. A six amino acid linear peptide derived from Cdc37, KTGDEK, was designed to target Hsp90. We used in silico computational docking to first define its mode of interaction, and binding orientation, and then conjugated the peptide with a cell penetrating peptide, TAT, and a fluorescent dye to confirm its ability to colocalize with Hsp90 in HCC cells. Based on the parent linear sequence, we developed a peptidomimetics library of pre-cyclic and cyclic derivatives. These peptidomimetics were evaluated for their binding affinity to Hsp90, and bioactivity in HCC cell lines. Among them, a pre-cyclic peptidomimetic demonstrates high binding affinity and bioactivity in HCC cells, causing reduced cell proliferation that is associated with induction of cell apoptosis, and down-regulation of phosphorylated MEK1/2. Overall, this generalized approach of rational design, structural optimization, and cellular validation of 'drug-like' peptidomimetics against Hsp90/Cdc37 offers a feasible and promising way to design novel therapeutic agents for malignancies and other diseases that are dependent on this molecular chaperone complex.