Analytical Validation of an Early Detection Pancreatic Cancer Test Using 5-Hydroxymethylation Signatures

Early detection of pancreatic cancer has been shown to improve patient survival rates. However, effective early detection tools to detect pancreatic cancer do not currently exist. The Avantect Pancreatic Cancer Test, leveraging the 5-hydroxymethylation [5-hydroxymethylcytosine (5hmC)] signatures in cell-free DNA, was developed and analytically validated to address this unmet need. We report a comprehensive analytical validation study encompassing precision, sample stability, limit of detection, interfering substance studies, and a comparison with an alternative method. The assay performance on an independent case-control patient cohort was previously reported with a sensitivity for early-stage (stage I/II) pancreatic cancer of 68.3% (95% CI, 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%). Precision studies showed a cancer classification of 100% concordance in biological replicates. The sample stability studies revealed stable assay performance for up to 7 days after blood collection. The limit of detection studies revealed equal results between early- and late-stage cancer samples, emphasizing strong early-stage performance characteristics. Comparisons of concordance of the Avantect assay with the enzymatic methyl sequencing (EM-Seq) method, which measures both methylation (5-methylcytosine) and 5hmC, were >95% for all samples tested. The Avantect Pancreatic Cancer Test showed strong analytical validation in multiple validation studies required for laboratory-developed test accreditation. The comparison of 5hmC versus EM-Seq further validated the 5hmC approach as a robust and reproducible assay.

Editor-in-Chief articles of choice and comments from January to June 2024

As the Editor-in-Chief of the World Journal of Gastroenterology, I carefully review all articles every week before a new issue’s online publication, including the title, clinical and research importance, originality, novelty, and ratings by the peer reviewers. Based on this review, I select the papers of choice and suggest pertinent changes (e.g., in the title or text) to the company editors responsible for publication. This process, while time-consuming, is essential for assuring the quality of publications and highlighting important articles that readers may revisit.

Genome-wide characterization of dynamic DNA 5-hydroxymethylcytosine and TET2-related DNA demethylation during breast tumorigenesis

BACKGROUND

Breast tumorigenesis is a complex and multistep process accompanied by both genetic and epigenetic dysregulation. In contrast to the extensive studies on DNA epigenetic modifications 5-hydroxymethylcytosine (5hmC) and 5-methylcytosine (5mC) in malignant breast tumors, their roles in the early phases of breast tumorigenesis remain ambiguous.

RESULTS

DNA 5hmC and 5mC exhibited a consistent and significant decrease from usual ductal hyperplasia to atypical ductal hyperplasia and subsequently to ductal carcinoma in situ (DCIS). However, 5hmC showed a modest increase in invasive ductal breast cancer compared to DCIS. Genomic analyses showed that the changes in 5hmC and 5mC levels occurred around the transcription start sites (TSSs), and the modification levels were strongly correlated with gene expression levels. Meanwhile, it was found that differentially hydroxymethylated regions (DhMRs) and differentially methylated regions (DMRs) were overlapped in the early phases and accompanied by the enrichment of active histone marks. In addition, TET2-related DNA demethylation was found to be involved in breast tumorigenesis, and four transcription factor binding sites (TFs: ESR1, FOXA1, GATA3, FOS) were enriched in TET2-related DhMRs/DMRs. Intriguingly, we also identified a certain number of common DhMRs between tumor samples and cell-free DNA (cfDNA).

CONCLUSIONS

Our study reveals that dynamic changes in DNA 5hmC and 5mC play a vital role in propelling breast tumorigenesis. Both TFs and active histone marks are involved in TET2-related DNA demethylation. Concurrent changes in 5hmC signals in primary breast tumors and cfDNA may play a promising role in breast cancer screening.

Reversal Gene Expression Assessment for Drug Repurposing, a Case Study of Glioblastoma

Glioblastoma (GBM) is a rare brain cancer with an exceptionally high mortality rate, which illustrates the pressing demand for more effective therapeutic options. Despite considerable research efforts on GBM, its underlying biological mechanisms remain unclear. Furthermore, none of the United States Food and Drug Administration (FDA) approved drugs used for GBM deliver satisfactory survival improvement. This study presents a novel computational pipeline by utilizing gene expression data analysis for GBM for drug repurposing to address the challenges in rare disease drug development, particularly focusing on GBM. The GBM Gene Expression Profile (GGEP) was constructed with multi-omics data to identify drugs with reversal gene expression to GGEP from the Integrated Network-Based Cellular Signatures (iLINCS) database. We prioritized the candidates via hierarchical clustering of their expression signatures and quantification of their reversal strength by calculating two self-defined indices based on the GGEP genes' log 2 foldchange (LFCs) that the drug candidates could induce. Among eight prioritized candidates, in-vitro experiments validated Clofarabine and Ciclopirox as highly efficacious in selectively targeting GBM cancer cells. The success of this study illustrated a promising avenue for accelerating drug development by uncovering underlying gene expression effect between drugs and diseases, which can be extended to other rare diseases and non-rare diseases.

Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

MOTIVATION

5-Hydroxymethylcytosine (5hmC), a crucial epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Despite its importance, predicting 5hmC modification across the genome remains a challenging task, especially when considering the complex interplay between DNA sequences and various epigenetic factors such as histone modifications and chromatin accessibility.

RESULTS

Using tissue-specific 5hmC sequencing data, we introduce Deep5hmC, a multimodal deep learning framework that integrates both the DNA sequence and epigenetic features such as histone modification and chromatin accessibility to predict genome-wide 5hmC modification. The multimodal design of Deep5hmC demonstrates remarkable improvement in predicting both qualitative and quantitative 5hmC modification compared to unimodal versions of Deep5hmC and state-of-the-art machine learning methods. This improvement is demonstrated through benchmarking on a comprehensive set of 5hmC sequencing data collected at four developmental stages during forebrain organoid development and across 17 human tissues. Compared to DeepSEA and random forest, Deep5hmC achieves close to 4% and 17% improvement of Area Under the Receiver Operating Characteristic (AUROC) across four forebrain developmental stages, and 6% and 27% across 17 human tissues for predicting binary 5hmC modification sites; and 8% and 22% improvement of Spearman correlation coefficient across four forebrain developmental stages, and 17% and 30% across 17 human tissues for predicting continuous 5hmC modification. Notably, Deep5hmC showcases its practical utility by accurately predicting gene expression and identifying differentially hydroxymethylated regions (DhMRs) in a case-control study of Alzheimer's disease (AD). Deep5hmC significantly improves our understanding of tissue-specific gene regulation and facilitates the development of new biomarkers for complex diseases.

AVAILABILITY AND IMPLEMENTATION

Deep5hmC is available via https://github.com/lichen-lab/Deep5hmC.

Tankyrase1/2 inhibitor XAV-939 reverts EMT and suggests that PARylation partially regulates aerobic activities in human hepatocytes and HepG2 cells

The maintenance of a highly functional metabolic epithelium in vitro is challenging. Metabolic impairments in primary human hepatocytes (PHHs) over time is primarily due to epithelial-to-mesenchymal transitioning (EMT). The immature hepatoma cell line HepG2 was used as an in vitro model to explore strategies for enhancing the hepatic phenotype. The phenotypic characterization includes measuring the urea cycle, lipid storage, tricarboxylic acid-related metabolites, reactive oxygen species, endoplasmic reticulum calcium efflux, mitochondrial membrane potentials, oxygen consumptions rate, and CYP450 biotransformation capacity. Expression studies were performed with transcriptomics, co-immunoprecipitation and proteomics. CRISPR/Cas9 was also employed to genetically engineer HepG2 cells. After confirming that PHHs develop an EMT phenotype, expression of tankyrase1/2 was found to increase over time. EMT was reverted when blocking tankyrases1/2-dependent poly-ADP-ribosylation (PARylation) activity, by biochemical and genetic perturbation. Wnt/β-catenin inhibitor XAV-939 blocks tankyrase1/2 and treatment elevated several oxygen-consuming reactions (electron-transport chain, OXHPOS, CYP450 mono-oxidase activity, phase I/II xenobiotic biotransformation, and prandial turnover), suggesting that cell metabolism was enhanced. Glutathione-dependent redox homeostasis was also significantly improved in the XAV-939 condition. Oxygen consumption rate and proteomics experiments in tankyrase1/2 double knockout HepG2 cells then uncovered PARylation as master regulator of aerobic-dependent cell respiration. Furthermore, novel tankyrase1/2-dependent PARylation targets, including mitochondrial DLST, and OGDH, were revealed. This work exposed a new mechanistic framework by linking PARylation to respiration and metabolism, thereby broadening the current understanding that underlies these vital processes. XAV-939 poses an immediate and straightforward strategy to improve aerobic activities, and metabolism, in (immature) cell cultures.

Current trends and hotspots of depressive disorders with colorectal cancer: A bibliometric and visual study

BACKGROUND

Depression is strongly associated with colorectal cancer (CRC). Few bibliometric analyses have systematically summarized the research focus and recent progress in this field.

AIM

To determine the research status and hotspots by bibliometric analysis of relevant publications on the relationship between CRC and depression.

METHODS

Articles on depression in CRC patients were collected from the Web of Science Core Collection. CiteSpace and VOSviewer software were used to visualize bibliometric networks.

RESULTS

From 2001 to 2022, Supportive Care in Cancer, the United States, Tilburg University, and Mols were the most productive and influential journal, country, institution, and author name. Co-occurrence cluster analysis of keywords placed quality of life, anxiety, and psychological stress in the center of the visual network diagram. Further clustering was performed for the clusters with studies of the relevant mechanism of action, which showed that: (1) Cytokines have a role essential for the occurrence and development of depressive disorders in CRC; (2) MicroRNAs have a role essential for the development of depressive disorders in CRC; (3) Some anticancer drugs have pro-depressant activity; and (4) Selective serotonin reuptake inhibitors have both antitumor and antidepressant activity.

CONCLUSION

Life quality and psychological nursing of the cancer population were key topics. The roles of cytokines and microRNAs, the pro-depression activity of anticancer drugs and their antitumor properties deserve in-depth study.

A 5-Hydroxymethylcytosine-Based Noninvasive Model for Early Detection of Colorectal Carcinomas and Advanced Adenomas: The METHOD-2 Study

PURPOSE

Detection of colorectal carcinomas at a time when there are more treatment options is associated with better outcomes. This prospective case-control study assessed the 5-hydroxymethylcytosine (5hmC) biomarkers in circulating cell-free DNA (cfDNA) for early detection of colorectal carcinoma and advanced adenomas (AA).

EXPERIMENTAL DESIGN

Plasma cfDNA samples from 2,576 study participants from the multicenter METHOD-2 study (NCT03676075) were collected, comprising patients with newly diagnosed colorectal carcinoma (n = 1,074), AA (n = 356), other solid tumors (n = 80), and non-colorectal carcinoma/AA controls (n = 1,066), followed by genome-wide 5hmC profiling using the 5hmC-Seal technique and the next-generation sequencing. A weighted diagnostic model for colorectal carcinoma (stage I-III) and AA was developed using the elastic net regularization in a discovery set and validated in independent samples.

RESULTS

Distribution of 5hmC in cfDNA reflected gene regulatory relevance and tissue of origin. Besides being confirmed in internal validation, a 96-gene model achieved an area under the curve (AUC) of 90.7% for distinguishing stage I-III colorectal carcinoma from controls in 321 samples from multiple centers for external validation, regardless of primary location or mutation status. This model also showed cancer-type specificity as well as high capacity for distinguishing AA from controls with an AUC of 78.6%. Functionally, differential 5hmC features associated with colorectal carcinoma and AA demonstrated relevance to colorectal carcinoma biology, including pathways such as calcium and MAPK signaling.

CONCLUSIONS

Genome-wide mapping of 5hmC in cfDNA shows promise as a highly sensitive and specific noninvasive blood test to be integrated into screening programs for improving early detection of colorectal carcinoma and high-risk AA.

Pancreatic Cancer Surveillance and Survival of High-Risk Individuals

Importance

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with increasing incidence. The majority of PDACs are incurable at presentation, but population-based screening is not recommended. Surveillance of high-risk individuals for PDAC may lead to early detection, but the survival benefit is unproven.

Objective

To compare the survival of patients with surveillance-detected PDAC with US national data.

Design, Setting, and Participants

This comparative cohort study was conducted in multiple US academic medical centers participating in the Cancer of the Pancreas Screening program, which screens high-risk individuals with a familial or genetic predisposition for PDAC. The comparison cohort comprised patients with PDAC matched for age, sex, and year of diagnosis from the Surveillance, Epidemiology, and End Results (SEER) program. The Cancer of the Pancreas Screening program originated in 1998, and data collection was done through 2021. The data analysis was performed from April 29, 2022, through April 10, 2023.

Exposures

Endoscopic ultrasonography or magnetic resonance imaging performed annually and standard-of-care surgical and/or oncologic treatment.

Main Outcomes and Measures

Stage of PDAC at diagnosis, overall survival (OS), and PDAC mortality were compared using descriptive statistics and conditional logistic regression, Cox proportional hazards regression, and competing risk regression models. Sensitivity analyses and adjustment for lead-time bias were also conducted.

Results

A total of 26 high-risk individuals (mean [SD] age at diagnosis, 65.8 [9.5] years; 15 female [57.7%]) with PDAC were compared with 1504 SEER control patients with PDAC (mean [SD] age at diagnosis, 66.8 [7.9] years; 771 female [51.3%]). The median primary tumor diameter of the 26 high-risk individuals was smaller than in the control patients (2.5 [range, 0.6-5.0] vs 3.6 [range, 0.2-8.0] cm, respectively; P < .001). The high-risk individuals were more likely to be diagnosed with a lower stage (stage I, 10 [38.5%]; stage II, 8 [30.8%]) than matched control patients (stage I, 155 [10.3%]; stage II, 377 [25.1%]; P < .001). The PDAC mortality rate at 5 years was lower for high-risk individuals than control patients (43% vs 86%; hazard ratio, 3.58; 95% CI, 2.01-6.39; P < .001), and high-risk individuals lived longer than matched control patients (median OS, 61.7 [range, 1.9-147.3] vs 8.0 [range, 1.0-131.0] months; 5-year OS rate, 50% [95% CI, 32%-80%] vs 9% [95% CI, 7%-11%]).

Conclusions and Relevance

These findings suggest that surveillance of high-risk individuals may lead to detection of smaller, lower-stage PDACs and improved survival.

Know your molecule: pharmacological characterization of drug candidates to enhance efficacy and reduce late-stage attrition

Despite advances in chemical, computational and biological sciences, the rate of attrition of drug candidates in clinical development is still high. A key point in the small-molecule discovery process that could provide opportunities to help address this challenge is the pharmacological characterization of hit and lead compounds, culminating in the selection of a drug candidate. Deeper characterization is increasingly important, because the 'quality' of drug efficacy, at least for G protein-coupled receptors (GPCRs), is now understood to be much more than activation of commonly evaluated pathways such as cAMP signalling, with many more 'efficacies' of ligands that could be harnessed therapeutically. Such characterization is being enabled by novel assays to characterize the complex behaviour of GPCRs, such as biased signalling and allosteric modulation, as well as advances in structural biology, such as cryo-electron microscopy. This article discusses key factors in the assessments of the pharmacology of hit and lead compounds in the context of GPCRs as a target class, highlighting opportunities to identify drug candidates with the potential to address limitations of current therapies and to improve the probability of them succeeding in clinical development.

Circulating tumour DNA analysis for early detection of lung cancer: a systematic review

Background

Circulating tumor DNA (ctDNA) analysis has been applied in cancer diagnostics including lung cancer. Specifically for the early detection purpose, various modalities of ctDNA analysis have demonstrated their potentials. Such analyses have showed diverse performance across different studies.

Methods

We performed a systematic review of original studies published before 1 January 2023. Studies that evaluated ctDNA alone and in combination with other biomarkers for early detection of lung cancer were included.

Results

The systematic review analysis included 56 original studies that were aimed for early detection of lung cancer. There were 39 studies for lung cancer only and 17 for pan-cancer early detection. Cancer and control cases included were heterogenous across studies. Different molecular features of ctDNA have been evaluated, including 7 studies on cell-free DNA concentration, 17 on mutation, 29 on methylation, 5 on hydroxymethylation and 8 on fragmentation patterns. Among these 56 studies, 17 have utilised different combinations of the above-mentioned ctDNA features and/or circulation protein markers. For all the modalities, lower sensitivities were reported for the detection of early-stage cancer.

Conclusions

The systematic review suggested the clinical utility of ctDNA analysis for early detection of lung cancer, alone or in combination with other biomarkers. Future validation with standardised testing protocols would help integration into clinical care.

Targeting Hepatic Cancer Stem Cells (CSCs) and Related Drug Resistance by Small Interfering RNA (siRNA)

Tumor recurrence after curative therapy and hepatocellular carcinoma (HCC) cells' resistance to conventional therapies is the reasons for the worse clinical results of HCC patients. A tiny population of cancer cells with a strong potential for self-renewal, differentiation, and tumorigenesis has been identified as cancer stem cells (CSCs). The discovery of CSC surface markers and the separation of CSC subpopulations from HCC cells have been made possible by recent developments in the study of hepatic (liver) CSCs. Hepatic CSC surface markers include epithelial cell adhesion molecules (EpCAM), CD133, CD90, CD13, CD44, OV-6, ALDH, and K19. CSCs have a significant influence on the development of cancer, invasiveness, self-renewal, metastasis, and drug resistance in HCC, and thus provide a therapeutic chance to treat HCC and avoid its recurrence. Therefore, it is essential to develop treatment approaches that specifically and effectively target hepatic stem cells. Given this, one potential treatment approach is to use particular small interfering RNA (siRNA) to target CSC, disrupting their behavior and microenvironment as well as changing their epigenetic state. The characteristics of CSCs in HCC are outlined in this study, along with new treatment approaches based on siRNA that may be used to target hepatic CSCs and overcome HCC resistance to traditional therapies.

Superior Anticancer and Antifungal Activities of New Sulfanyl-Substituted Niclosamide Derivatives

The approved anthelmintic salicylanilide drug niclosamide has shown promising anticancer and antimicrobial activities. In this study, new niclosamide derivatives with trifluoromethyl, trifluoromethylsulfanyl, and pentafluorosulfanyl substituents replacing the nitro group of niclosamide were prepared (including the ethanolamine salts of two promising salicylanilides) and tested for their anticancer activities against esophageal adenocarcinoma (EAC) cells. In addition, antifungal activity against a panel of Madurella mycetomatis strains, the most abundant causative agent of the neglected tropical disease eumycetoma, was evaluated. The new compounds revealed higher activities against EAC and fungal cells than the parent compound niclosamide. The ethanolamine salt 3a was the most active compound against EAC cells (IC50 = 0.8-1.0 µM), and its anticancer effects were mediated by the downregulation of anti-apoptotic proteins (BCL2 and MCL1) and by decreasing levels of β-catenin and the phosphorylation of STAT3. The plausibility of binding to the latter factors was confirmed by molecular docking. The compounds 2a and 2b showed high in vitro antifungal activity against M. mycetomatis (IC50 = 0.2-0.3 µM) and were not toxic to Galleria mellonella larvae. Slight improvements in the survival rate of G. mellonella larvae infected with M. mycetomatis were observed. Thus, salicylanilides such as 2a and 3a can become new anticancer and antifungal drugs.

Metachronous multifocal carcinoma: A case report

BACKGROUND

The incidence of multiple primary carcinomas (MPC) varies greatly, ranging from 0.73% to 11.70% in foreign countries, with duo-duplex carcinoma being the most common, trio-duplex carcinoma and above being rare, and simultaneous multigenic carcinoma being even rarer, accounting for 18.4% to 25.3% of the incidence of MPC. However, there is no report regarding patients presenting with simultaneous dual-origin carcinoma of the liver and colon and heterochronous pancreatic cancer.

CASE SUMMARY

We report a special case of multifocal carcinoma, in which one patient had a medical condition of primary liver and colon cancer and pancreatic cystadenocarcinoma 2 years after surgery. Through aggressive advanced fluorescent laparoscopic techniques, standardized immunotherapy, targeting, and chemotherapy, a better prognosis and a desirable survival period were achieved for the patient.

CONCLUSION

There is a need to clarify the nature of MPC through advanced surgical means to ensure better diagnosis and treatment.

Research trends and hotspots in the immune microenvironment related to hepatocellular carcinoma: A bibliometric and visualization study

BACKGROUND

The immune microenvironment (IME) in hepatocellular carcinoma (HCC) plays a pivotal role in determining patient outcomes and responses to treatment. This area is witnessing rapid growth in research interest. However, there is a lack of comprehensive bibliometric analyses that dissect trends and potential focal points in this field.

AIM

To explore the evolution of research on the IME in HCC from January 1, 2004, to December 31, 2023, using bibliometric methodologies.

METHODS

English articles and reviews concerning the IME of HCC were retrieved from the Web of Science Core Collection with a search date of December 31, 2023. The R package Bibliometrix was employed to compute basic bibliometric characteristics, illustrate collaborations among countries and authors, and create a three-field diagram illustrating the connections between authors, affiliations, and keywords. Analyses of country and institutional co-authorship, as well as keyword co-occurrence, were conducted using VOSviewer. Additionally, CiteSpace was utilized for the cite burst analysis of keywords and cited literature.

RESULTS

The study encompassed 3125 documents in the research areas related to HCC of IME, revealing a substantial and continuous increase in the annual publication trend over time. China and Fudan University emerged as leading contributors, with 2103 and 165 publications, respectively. Frontiers in immunology was the most prolific journal in this domain. Among the top ten researchers in the field, eight are based in China. Key research terms identified include tumour microenvironment, expression, immunotherapy, and prognosis.

CONCLUSION

The relationship between HCC and IME is receiving increasing attention, and related research is in a highly developed stage. Key focus areas, including IME and immune checkpoint inhibitors, immunotherapy are poised to be central to future research endeavors, offering promising pathways for further exploration.

Cancer screening with multicancer detection tests: A translational science review

Multicancer detection (MCD) tests use a single, easily obtainable biospecimen, such as blood, to screen for more than one cancer concurrently. MCD tests can potentially be used to improve early cancer detection, including cancers that currently lack effective screening methods. However, these tests have unknown and unquantified benefits and harms. MCD tests differ from conventional cancer screening tests in that the organ responsible for a positive test is unknown, and a broad diagnostic workup may be necessary to confirm the location and type of underlying cancer. Among two prospective studies involving greater than 16,000 individuals, MCD tests identified those who had some cancers without currently recommended screening tests, including pancreas, ovary, liver, uterus, small intestine, oropharyngeal, bone, thyroid, and hematologic malignancies, at early stages. Reported MCD test sensitivities range from 27% to 95% but differ by organ and are lower for early stage cancers, for which treatment toxicity would be lowest and the potential for cure might be highest. False reassurance from a negative MCD result may reduce screening adherence, risking a loss in proven public health benefits from standard-of-care screening. Prospective clinical trials are needed to address uncertainties about MCD accuracy to detect different cancers in asymptomatic individuals, whether these tests can detect cancer sufficiently early for effective treatment and mortality reduction, the degree to which these tests may contribute to cancer overdiagnosis and overtreatment, whether MCD tests work equally well across all populations, and the appropriate diagnostic evaluation and follow-up for patients with a positive test.

Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data

INTRODUCTION

Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of cancer deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many patients eventually develop disease recurrence and metastasis. Without effective treatments, patients with aggressive PC display very poor survival. To curb the current high mortality rate, many investigations have been carried out to identify efficacious therapeutics. Compared to de novo drug designs, computational methods have been widely employed to offer actionable drug predictions in a fast and cost-efficient way. Particularly, powered by an increasing availability of next-generation sequencing molecular profiles from PC patients, computer-aided approaches can be tailored to screen for candidate drugs.

AREAS COVERED

Herein, the authors review the recent advances in computational methods for drug discovery utilizing molecular profiles from PC patients. Given the uniqueness in PC therapeutic needs, they discuss in detail the drug discovery goals of these studies, highlighting their translational values for clinically impactful drug nomination.

EXPERT OPINION

Evolving molecular profiling techniques may enable new perspectives for computer-aided approaches to offer drug candidates for different tumor microenvironments. With ongoing efforts to incorporate new compounds into large-scale high-throughput screens, the authors envision continued expansion of drug candidate pools.

Liquid Biopsy Based on Cell-Free DNA and RNA

This review delves into the rapidly evolving landscape of liquid biopsy technologies based on cell-free DNA (cfDNA) and cell-free RNA (cfRNA) and their increasingly prominent role in precision medicine. With the advent of high-throughput DNA sequencing, the use of cfDNA and cfRNA has revolutionized noninvasive clinical testing. Here, we explore the physical characteristics of cfDNA and cfRNA, present an overview of the essential engineering tools used by the field, and highlight clinical applications, including noninvasive prenatal testing, cancer testing, organ transplantation surveillance, and infectious disease testing. Finally, we discuss emerging technologies and the broadening scope of liquid biopsies to new areas of diagnostic medicine.

Mapping global research trends: Nutrition associations with nonalcoholic fatty liver disease - a Scopus bibliometric analysis

BACKGROUND

Several bibliometric analyses have been carried out to identify research hotspots and trends in nonalcoholic fatty liver disease (NAFLD) research. Nonetheless, there are still significant knowledge gaps that must be filled to advance our understanding of and ability to treat NAFLD.

AIM

To evaluate, through bibliometric and visual analysis, the current status of related research, related research frontiers, and the developmental trends in the field of diet and NAFLD.

METHODS

We retrieved publications about diet and NAFLD published between 1987 and 2022 from Scopus. Next, we used VOSviewer 1.6.20 to perform bibliometric analysis and visualization.

RESULTS

We found a total of 1905 studies, including 1637 (85.93%) original articles and 195 (10.24%) reviews, focused on the examination of NAFLD and its correlation with diet that were published between 1987 and 2022. Among the remaining five types of documents, 38 were letters, notes, editorials, meeting minutes, or brief surveys, representing 1.99% of the total documents. The countries with the most publications on this topic were China (n = 539; 28.29%), followed by the United States (n = 379; 19.90%), Japan (n = 133; 6.98%), and South Korea (n = 127; 6.6%). According to the citation analysis, the retrieved papers were cited an average of 32.3 times and had an h-index of 106, with 61014 total citations. The two main clusters on the map included those related to: (1) Inflammation and oxidative stress; and (2) Dietary interventions for NAFLD.

CONCLUSION

This was the first study to use data taken from Scopus to visualize network mapping in a novel bibliometric analysis of studies focused on diet and NAFLD. After 2017, the two domains that received the most attention were "dietary interventions for NAFL"' and "'inflammation and oxidative stress implicated in NAFLD and its correlation with diet." We believe that this study provides important information for academics, dietitians, and doctors, and that additional research on dietary interventions and NAFLD is warranted.

Mapping the global research landscape on nonalcoholic fatty liver disease and insulin resistance: A visualization and bibliometric study

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is a liver condition that is prevalent worldwide and associated with significant health risks and economic burdens. As it has been linked to insulin resistance (IR), this study aimed to perform a bibliometric analysis and visually represent the scientific literature on IR and NAFLD.

AIM

To map the research landscape to underscore critical areas of focus, influential studies, and future directions of NAFLD and IR.

METHODS

This study conducted a bibliometric analysis of the literature on IR and NAFLD indexed in the SciVerse Scopus database from 1999 to 2022. The search strategy used terms from the literature and medical subject headings, focusing on terms related to IR and NAFLD. VOSviewer software was used to visualize research trends, collaborations, and key thematic areas. The analysis examined publication type, annual research output, contributing countries and institutions, funding agencies, journal impact factors, citation patterns, and highly cited references.

RESULTS

This analysis identified 23124 documents on NAFLD, revealing a significant increase in the number of publications between 1999 and 2022. The search retrieved 715 papers on IR and NAFLD, including 573 (80.14%) articles and 88 (12.31%) reviews. The most productive countries were China (n = 134; 18.74%), the United States (n = 122; 17.06%), Italy (n = 97; 13.57%), and Japan (n = 41; 5.73%). The leading institutions included the Università degli Studi di Torino, Italy (n = 29; 4.06%), and the Consiglio Nazionale delle Ricerche, Italy (n = 19; 2.66%). The top funding agencies were the National Institute of Diabetes and Digestive and Kidney Diseases in the United States (n = 48; 6.71%), and the National Natural Science Foundation of China (n = 37; 5.17%). The most active journals in this field were Hepatology (27 publications), the Journal of Hepatology (17 publications), and the Journal of Clinical Endocrinology and Metabolism (13 publications). The main research hotspots were "therapeutic approaches for IR and NAFLD" and "inflammatory and high-fat diet impacts on NAFLD".

CONCLUSION

This is the first bibliometric analysis to examine the relationship between IR and NAFLD. In response to the escalating global health challenge of NAFLD, this research highlights an urgent need for a better understanding of this condition and for the development of intervention strategies. Policymakers need to prioritize and address the increasing prevalence of NAFLD.

Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery

Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles offer a comprehensive view of drug mechanisms, inherent noise often obscures the true signal, hindering their potential for meaningful insights. Here, we highlight the development of TranSiGen, a deep generative model employing self-supervised representation learning. TranSiGen analyzes basal cell gene expression and molecular structures to reconstruct chemical-induced transcriptional profiles with high accuracy. By capturing both cellular and compound information, TranSiGen-derived representations demonstrate efficacy in diverse downstream tasks like ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. Notably, in vitro validation of TranSiGen's application in pancreatic cancer drug discovery highlights its potential for identifying effective compounds. We envisage that integrating TranSiGen into the drug discovery and mechanism research holds significant promise for advancing biomedicine.

Intravesical instillation-based mTOR-STAT3 dual targeting for bladder cancer treatment

BACKGROUND

Recent intravesical administration of adenoviral vectors, either as a single injection or in combination with immune checkpoint inhibitors, exemplified by cretostimogene grenadenorepvec and nadofaragene firadenovec, has demonstrated remarkable efficacy in clinical trials for non-muscle invasive bladder cancer. Despite their ability to induce an enhanced immune reaction within the lesion, the intracellular survival signaling of cancer cells has not been thoroughly addressed.

METHODS

An analysis of the prognostic data revealed a high probability of therapeutic efficacy with simultaneous inhibition of mTOR and STAT3. Considering the challenges of limited pharmaco-accessibility to the bladder due to its pathophysiological structure and the partially undruggable nature of target molecules, we designed a dual siRNA system targeting both mRNAs. Subsequently, this dual siRNA system was encoded into the adenovirus 5/3 (Ad 5/3) to enhance in vivo delivery efficiency.

RESULTS

Gene-targeting efficacy was assessed using cells isolated from xenografted tumors using a single-cell analysis system. Our strategy demonstrated a balanced downregulation of mTOR and STAT3 at the single-cell resolution, both in vitro and in vivo. This approach reduced tumor growth in bladder cancer xenograft and orthotopic animal experiments. In addition, increased infiltration of CD8+ T cells was observed in a humanized mouse model. We provided helpful and safe tissue distribution data for intravesical therapy of siRNAs coding adenoviruses.

CONCLUSIONS

The bi-specific siRNA strategy, encapsulated in an adenovirus, could be a promising tool to augment cancer treatment efficacy and overcome conventional therapy limitations associated with "undruggability." Hence, we propose that dual targeting of mTOR and STAT3 is an advantageous strategy for intravesical therapy using adenoviruses.

Exploring the potential of drug repurposing for liver diseases: A comprehensive study

Drug repurposing involves the investigation of existing drugs for new indications. It offers a great opportunity to quickly identify a new drug candidate at a lower cost than novel discovery and development. Despite the importance and potential role of drug repurposing, there is no specific definition that healthcare providers and the World Health Organization credit. Unfortunately, many similar and interchangeable concepts are being used in the literature, making it difficult to collect and analyze uniform data on repurposed drugs. This research was conducted based on understanding general criteria for drug repurposing, concentrating on liver diseases. Many drugs have been investigated for their effect on liver diseases even though they were originally approved (or on their way to being approved) for other diseases. Some of the hypotheses for drug repurposing were first captured from the literature and then processed further to test the hypothesis. Recently, with the revolution in bioinformatics techniques, scientists have started to use drug libraries and computer systems that can analyze hundreds of drugs to give a short list of candidates to be analyzed pharmacologically. However, this study revealed that drug repurposing is a potential aid that may help deal with liver diseases. It provides available or under-investigated drugs that could help treat hepatitis, liver cirrhosis, Wilson disease, liver cancer, and fatty liver. However, many further studies are needed to ensure the efficacy of these drugs on a large scale.

Advances in the joint profiling technologies of 5mC and 5hmC

DNA cytosine methylation, a crucial epigenetic modification, involves the dynamic interplay of 5-methylcytosine (5mC) and its oxidized form, 5-hydroxymethylcytosine (5hmC), generated by ten-eleven translocation (TET) DNA dioxygenases. This process is central to regulating gene expression, influencing critical biological processes such as development, disease progression, and aging. Recognizing the distinct functions of 5mC and 5hmC, researchers often employ restriction enzyme-based or chemical treatment methods for their simultaneous measurement from the same genomic sample. This enables a detailed understanding of the relationship between these modifications and their collective impact on cellular function. This review focuses on summarizing the technologies for detecting 5mC and 5hmC together but also discusses the limitations and potential future directions in this evolving field.

Predicting gene expression state and prioritizing putative enhancers using 5hmC signal

BACKGROUND

Like its parent base 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) is a direct epigenetic modification of cytosines in the context of CpG dinucleotides. 5hmC is the most abundant oxidized form of 5mC, generated through the action of TET dioxygenases at gene bodies of actively-transcribed genes and at active or lineage-specific enhancers. Although such enrichments are reported for 5hmC, to date, predictive models of gene expression state or putative regulatory regions for genes using 5hmC have not been developed.

RESULTS

Here, by using only 5hmC enrichment in genic regions and their vicinity, we develop neural network models that predict gene expression state across 49 cell types. We show that our deep neural network models distinguish high vs low expression state utilizing only 5hmC levels and these predictive models generalize to unseen cell types. Further, in order to leverage 5hmC signal in distal enhancers for expression prediction, we employ an Activity-by-Contact model and also develop a graph convolutional neural network model with both utilizing Hi-C data and 5hmC enrichment to prioritize enhancer-promoter links. These approaches identify known and novel putative enhancers for key genes in multiple immune cell subsets.

CONCLUSIONS

Our work highlights the importance of 5hmC in gene regulation through proximal and distal mechanisms and provides a framework to link it to genome function. With the recent advances in 6-letter DNA sequencing by short and long-read techniques, profiling of 5mC and 5hmC may be done routinely in the near future, hence, providing a broad range of applications for the methods developed here.

Wnt/β-catenin signalling, epithelial-mesenchymal transition and crosslink signalling in colorectal cancer cells

Colorectal cancer (CRC), with its significant incidence and metastatic rates, profoundly affects human health. A common oncogenic event in CRC is the aberrant activation of the Wnt/β-catenin signalling pathway, which drives both the initiation and progression of the disease. Persistent Wnt/β-catenin signalling facilitates the epithelial-mesenchymal transition (EMT), which accelerates CRC invasion and metastasis. This review provides a summary of recent molecular studies on the role of the Wnt/β-catenin signalling axis in regulating EMT in CRC cells, which triggers metastatic pathogenesis. We present a comprehensive examination of the EMT process and its transcriptional controllers, with an emphasis on the crucial functions of β-catenin, EMT transcription factors (EMT-TFs). We also review recent evidences showing that hyperactive Wnt/β-catenin signalling triggers EMT and metastatic phenotypes in CRC via "Destruction complex" of β-catenin mechanisms. Potential therapeutic and challenges approache to suppress EMT and prevent CRC cells metastasis by targeting Wnt/β-catenin signalling are also discussed. These include direct β-catenin inhibitors and novel targets of the Wnt pathway, and finally highlight novel potential combinational treatment options based on the inhibition of the Wnt pathway.

Mapping the intellectual structure and emerging trends for the application of nanomaterials in gastric cancer: A bibliometric study

BACKGROUND

Recent reviews have outlined the main nanomaterials used in relation to gastrointestinal tumors and described the basic properties of these materials. However, the research hotspots and trends in the application of nanomaterials in gastric cancer (GC) remain obscure.

AIM

To demonstrate the knowledge structure and evolutionary trends of research into the application of nanomaterials in GC.

METHODS

Publications related to the application of nanomaterials in GC were retrieved from the Web of Science Core Collection for this systematic review and bibliometric study. VOSviewer and CiteSpace were used for bibliometric and visualization analyses.

RESULTS

From 2000 to 2022, the application of nanomaterials in GC developed rapidly. The keyword co-occurrence analysis showed that the related research topics were divided into three clusters: (1) The application of nanomaterials in GC treatment; (2) The application and toxicity of nanomaterials in GC diagnosis; and (3) The effects of nanomaterials on the biological behavior of GC cells. Complexes, silver nanoparticles, and green synthesis are the latest high-frequency keywords that represent promising future research directions.

CONCLUSION

The application of nanomaterials in GC diagnosis and treatment and the mechanisms of their effects on GC cells have been major themes in this field over the past 23 years.

Drug repurposing for metabolic disorders: Scientific, technological and economic issues

Obesity, diabetes, and other metabolic disorders place a huge burden on both the physical health and financial well-being of the community. While the need for effective treatment of metabolic disorders remains urgent and the reality is that traditional drug development involves high costs and a very long time with many pre-clinical and clinical trials, the need for drug repurposing has emerged as a potential alternative. Scientific evidence has shown the anti-diabetic and anti-obesity effects of old drugs, which were initially utilized for the treatment of inflammation, depression, infections, and even cancers. The drug library used modern technological methods to conduct drug screening. Computational molecular docking, genome-wide association studies, or omics data mining are advantageous and unavoidable methods for drug repurposing. Drug repurposing offers a promising avenue for economic efficiency in healthcare, especially for less common metabolic diseases, despite the need for rigorous research and validation. In this chapter, we aim to explore the scientific, technological, and economic issues surrounding drug repurposing for metabolic disorders. We hope to shed light on the potential of this approach and the challenges that need to be addressed to make it a viable option in the treatment of metabolic disorders, especially in the future fight against metabolic disorders.

Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates

Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.e., limma, DESeq2, and MultiPLIER) and prioritized the resulting drug repurposing candidates for four low-survival human cancers. Our results were enriched for candidates that had been used in clinical trials or performed well in the PRISM drug screen. Additionally, we found that pamidronate and nimodipine, drugs predicted to be efficacious against the brain tumor glioblastoma (GBM), inhibited the growth of a GBM cell line and cells isolated from a patient-derived xenograft (PDX). Our results demonstrate that by applying multiple disease-associated gene signature methods, we prioritized several drug repurposing candidates for low-survival cancers.

Antiretroviral Drug Repositioning for Glioblastoma

Outcomes for glioblastoma (GBM) remain poor despite standard-of-care treatments including surgical resection, radiation, and chemotherapy. Intratumoral heterogeneity contributes to treatment resistance and poor prognosis, thus demanding novel therapeutic approaches. Drug repositioning studies on antiretroviral therapy (ART) have shown promising potent antineoplastic effects in multiple cancers; however, its efficacy in GBM remains unclear. To better understand the pleiotropic anticancer effects of ART on GBM, we conducted a comprehensive drug repurposing analysis of ART in GBM to highlight its utility in translational neuro-oncology. To uncover the anticancer role of ART in GBM, we conducted a comprehensive bioinformatic and in vitro screen of antiretrovirals against glioblastoma. Using the DepMap repository and reversal of gene expression score, we conducted an unbiased screen of 16 antiretrovirals in 40 glioma cell lines to identify promising candidates for GBM drug repositioning. We utilized patient-derived neurospheres and glioma cell lines to assess neurosphere viability, proliferation, and stemness. Our in silico screen revealed that several ART drugs including reverse transcriptase inhibitors (RTIs) and protease inhibitors (PIs) demonstrated marked anti-glioma activity with the capability of reversing the GBM disease signature. RTIs effectively decreased cell viability, GBM stem cell markers, and proliferation. Our study provides mechanistic and functional insight into the utility of ART repurposing for malignant gliomas, which supports the current literature. Given their safety profile, preclinical efficacy, and neuropenetrance, ARTs may be a promising adjuvant treatment for GBM.

Circulating tumor cells et al.: towards a comprehensive liquid biopsy approach in breast cancer

Liquid biopsy has emerged as a crucial tool in managing breast cancer (BC) patients, offering a minimally invasive approach to detect circulating tumor biomarkers. Until recently, the majority of the studies in BC focused on evaluating a single liquid biopsy analyte, primarily circulating tumor DNA and circulating tumor cells (CTCs). Despite the proven prognostic and predictive value of CTCs, their low abundance when detected using enrichment methods, especially in the early stages, poses a significant challenge. It is becoming evident that combining diverse circulating biomarkers, each representing different facets of tumor biology, has the potential to enhance the management of patients with BC. This article emphasizes the importance of considering these biomarkers as complementary/synergistic rather than competitive, recognizing their ability to contribute to a comprehensive disease profile. The review provides an overview of the clinical significance of simultaneously analyzing CTCs and other biomarkers, including cell-free circulating DNA, extracellular vesicles, non-canonical CTCs, cell-free RNAs, and non-malignant cells. Such a comprehensive liquid biopsy approach holds promise not only in BC but also in other cancer types, offering opportunities for early detection, prognostication, and therapy monitoring. However, addressing associated challenges, such as refining detection methods and establishing standardized protocols, is crucial for realizing the full potential of liquid biopsy in transforming our understanding and approach to BC. As the field evolves, collaborative efforts will be instrumental in unlocking the revolutionary impact of liquid biopsy in BC research and management.

Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for endometriosis.

Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy

Patients with high tumor mutational burden (TMB) levels do not consistently respond to immune checkpoint inhibitors (ICIs), possibly because a high TMB level does not necessarily result in adequate infiltration of CD8+ T cells. Using bulk ribonucleic acid sequencing (RNA-seq) data from 9311 tumor samples across 30 cancer types, we developed a novel tool called the modulator of TMB-associated immune infiltration (MOTIF), which comprises genes that can determine the extent of CD8+ T cell infiltration prompted by a certain TMB level. We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle. By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors, we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8+ T cell infiltration. Using pretreatment RNA-seq data from 13 ICI-treated cohorts, we validated the use of MOTIF in predicting CD8+ T cell infiltration and ICI efficacy. Among the components of MOTIF, we identified EMC3 as a negative regulator of CD8+ T cell infiltration, which was validated via in vivo studies. Additionally, MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8+ T cell infiltration and improve ICI efficacy.

One-pot trimodal mapping of unmethylated, hydroxymethylated, and open chromatin sites unveils distinctive 5hmC roles at dynamic chromatin loci

We present a method, named Mx-TOP, for profiling of three epigenetic regulatory layers-chromatin accessibility, general DNA modification, and DNA hydroxymethylation-from a single library. The approach is based on chemo-enzymatic covalent tagging of unmodified CG sites and hydroxymethylated cytosine (5hmC) along with GC sites in chromatin, which are then mapped using tag-selective base-resolution TOP-seq sequencing. Our in-depth validation of the approach revealed its sensitivity and informativity in evaluating chromatin accessibility and DNA modification interactions that drive transcriptional regulation. We employed the technology in a study of chromatin and DNA demethylation dynamics during in vitro neuronal differentiation. The study highlighted the involvement of gene body 5hmC in modulating an extensive decoupling between promoter accessibility and transcription. The importance of 5hmC in chromatin remodeling was further demonstrated by the observed resistance of the developmentally acquired open loci to the global 5hmC erasure in neuronal progenitors.

Lipid-Based Self-Microemulsion of Niclosamide Achieved Enhanced Oral Delivery and Anti-Tumor Efficacy in Orthotopic Patient-Derived Xenograft of Hepatocellular Carcinoma in Mice

Introduction

We previously identified niclosamide as a promising repurposed drug candidate for hepatocellular carcinoma (HCC) treatment. However, it is poorly water soluble, limiting its tissue bioavailability and clinical application. To overcome these challenges, we developed an orally bioavailable self-microemulsifying drug delivery system encapsulating niclosamide (Nic-SMEDDS).

Methods

Nic-SMEDDS was synthesized and characterized for its physicochemical properties, in vivo pharmacokinetics and absorption mechanisms, and in vivo therapeutic efficacy in an orthotopic patient-derived xenograft (PDX)-HCC mouse model. Niclosamide ethanolamine salt (NEN), with superior water solubility, was used as a positive control.

Results

Nic-SMEDDS (5.6% drug load) displayed favorable physicochemical properties and drug release profiles in vitro. In vivo, Nic-SMEDDS displayed prolonged retention time and plasma release profile compared to niclosamide or NEN. Oral administration of Nic-SMEDDS to non-tumor bearing mice improved niclosamide bioavailability and Cmax by 4.1- and 1.8-fold, respectively, compared to oral niclosamide. Cycloheximide pre-treatment blocked niclosamide absorption from orally administered Nic-SMEDDS, suggesting that its absorption was facilitated through the chylomicron pathway. Nic-SMEDDS (100 mg/kg, bid) showed greater anti-tumor efficacy compared to NEN (200 mg/kg, qd); this correlated with higher levels (p < 0.01) of niclosamide, increased caspase-3, and decreased Ki-67 in the harvested PDX tissues when Nic-SMEDDS was given. Biochemical analysis at the treatment end-point indicated that Nic-SMEDDS elevated lipid levels in treated mice.

Conclusion

We successfully developed an orally bioavailable formulation of niclosamide, which significantly enhanced oral bioavailability and anti-tumor efficacy in an HCC PDX mouse model. Our data support its clinical translation for the treatment of solid tumors.

Mapping drug biology to disease genetics to discover drug impacts on the human phenome

Motivation

Medications can have unexpected effects on disease, including not only harmful drug side effects, but also beneficial drug repurposing. These effects on disease may result from hidden influences of drugs on disease gene networks. Then, discovering how biological effects of drugs relate to disease biology can both provide insight into the mechanism of latent drug effects, and can help predict new effects.

Results

Here, we develop Draphnet, a model that integrates molecular data on 429 drugs and gene associations of nearly 200 common phenotypes to learn a network that explains drug effects on disease in terms of these molecular signals. We present evidence that our method can both predict drug effects, and can provide insight into the biology of unexpected drug effects on disease. Using Draphnet to map a drug's known molecular effects to downstream effects on the disease genome, we put forward disease genes impacted by drugs, and we suggest a new grouping of drugs based on shared effects on the disease genome. Our approach has multiple applications, including predicting drug uses and learning drug biology, with implications for personalized medicine.

Availability and implementation

Code to reproduce the analysis is available at https://github.com/RDMelamed/drug-phenome.

Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal due to limited therapeutic options and expensive/burdensome drug discovery processes. Utilizing genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting may improve pancreatic cancer (PC) patient outcomes. Initially, we mapped CMAP data to gene expression from 106 PC patients, identifying nine negatively connected drugs. These drugs were further narrowed down using a similar analysis for PC cell lines, human tumoroids, and patient-derived xenografts datasets, where ISOX emerged as the most potent agent to target PC. We used human and mouse syngeneic PC cells, human and mouse tumoroids, and in vivo mice to assess the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Global transcriptomic and pathway analysis of the ISOX-LINCS signature identified HDAC 6/cMyc as the target axis for ISOX. Specifically, we discovered that genetic and pharmacological targeting of HDAC 6 affected non-histone protein cMyc acetylation, leading to cMyc instability, thereby disrupting PC growth and metastasis by affecting cancer stemness. Finally, KrasG12D harboring tumoroids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a new drug to treat advanced PC patients without toxicity to normal cells. Our study supports the clinical utility of ISOX along with 5FU in future PC clinical trials.

Deep5hmC: Predicting genome-wide 5-Hydroxymethylcytosine landscape via a multimodal deep learning model

5-hydroxymethylcytosine (5hmC), a critical epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Using tissue-specific 5hmC sequencing data, we introduce Deep5hmC, a multimodal deep learning framework that integrates both the DNA sequence and the histone modification information to predict genome-wide 5hmC modification. The multimodal design of Deep5hmC demonstrates remarkable improvement in predicting both qualitative and quantitative 5hmC modification compared to unimodal versions of Deep5hmC and state-of-the-art machine learning methods. This improvement is demonstrated through benchmarking on a comprehensive set of 5hmC sequencing data collected at four time points during forebrain organoid development and across 17 human tissues. Notably, Deep5hmC showcases its practical utility by accurately predicting gene expression and identifying differentially hydroxymethylated regions in a case-control study of Alzheimer's disease.

5-Hydroxymethylcytosine: the many faces of the sixth base of mammalian DNA

Epigenetic phenomena play a central role in cell regulatory processes and are important factors for understanding complex human disease. One of the best understood epigenetic mechanisms is DNA methylation. In the mammalian genome, cytosines (C) in CpG dinucleotides were long known to undergo methylation at the 5-position of the pyrimidine ring (mC). Later it was found that mC can be oxidized to 5-hydroxymethylcytosine (hmC) or even further to 5-formylcytosine (fC) and to 5-carboxylcytosine (caC) by the action of 2-oxoglutarate-dependent dioxygenases of the TET family. These findings unveiled a long elusive mechanism of active DNA demethylation and bolstered a wave of studies in the area of epigenetic regulation in mammals. This review is dedicated to critical assessment of recent data on biochemical and chemical aspects of the formation and conversion of hmC in DNA, analytical techniques used for detection and mapping of this nucleobase in mammalian genomes as well as epigenetic roles of hmC in DNA replication, transcription, cell differentiation and human disease.

A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer

Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n = 727), healthy controls (HEA, n = 1,092), as well as patients with small cell lung cancer (SCLC, n = 41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p < 0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.

PI3K and tankyrase inhibitors as therapeutic targets in colorectal cancer

INTRODUCTION

The pathways like Wingless-related integration (Wnt/β-catenin) and PI3K play an important role in colorectal cancer (CRC) development; however, their roles are distinct in the process of oncogenesis. Despite their differences, these pathways interact through feedback mechanisms and regulate the common effectors both in the upstream and the downstream processes in normal and pathological conditions. Their ability to reciprocally control each other is a primary resistance mechanism for the selective inhibitors in CRC.

AREA COVERED

This review highlights the Wnt/β-catenin and PI3K pathways that are interrelated in CRC, recent advances and some key perspectives in developing inhibitors that could target the tankyrase enzyme and PI3K, apart from a brief description of the potential of dual inhibitors of PI3K and Tankyrases (TNKS).

EXPERT OPINION

Recent research has focused on overcoming the challenges particularly relating to the resistance and efficacy of dual inhibitors targeting PI3K and tankyrase proteins. Despite these challenges, PI3K as well as tankyrases remain promising therapeutic targets for the treatment of solid tumors. The design of potent inhibitors is crucial to effectively block these protein signaling pathways. Moreover, it is essential to explore the potential of dual-target inhibition of other signaling pathways in conjunction with PI3K and tankyrase.

WNT/β-catenin signaling in hepatocellular carcinoma: The aberrant activation, pathogenic roles, and therapeutic opportunities

Hepatocellular carcinoma (HCC) is a liver cancer, highly heterogeneous both at the histopathological and molecular levels. It arises from hepatocytes as the result of the accumulation of numerous genomic alterations in various signaling pathways, including canonical WNT/β-catenin, AKT/mTOR, MAPK pathways as well as signaling associated with telomere maintenance, p53/cell cycle regulation, epigenetic modifiers, and oxidative stress. The role of WNT/β-catenin signaling in liver homeostasis and regeneration is well established, whereas in development and progression of HCC is extensively studied. Herein, we review recent advances in our understanding of how WNT/β-catenin signaling facilitates the HCC development, acquisition of stemness features, metastasis, and resistance to treatment. We outline genetic and epigenetic alterations that lead to activated WNT/β-catenin signaling in HCC. We discuss the pivotal roles of CTNNB1 mutations, aberrantly expressed non-coding RNAs and complexity of crosstalk between WNT/β-catenin signaling and other signaling pathways as challenging or advantageous aspects of therapy development and molecular stratification of HCC patients for treatment.

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer

OBJECTIVE

The genome-wide profiling of 5-hydroxymethylcytosines (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for various diseases. The purpose of this study was to investigate 5hmC signals in serum cfDNA and identify novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5hmC profiles in cfDNA reflect the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. Moreover, we sought to identify predictors that would better stratify outcomes for women with intermediate-sensitive HGSOC.

METHODS

Women diagnosed with HGSOC and known platinum sensitivity status were selected for this study. Nano-hmC-Seal was performed on cfDNA isolated from archived serum samples, and differential 5hmC features were identified using DESeq2 to establish a model predictive of chemoresistance.

RESULTS

A multivariate model consisting of three features (preoperative CA-125, largest residual implant after surgery, 5hmC level of OSGEPL), stratified samples from intermediate sensitive, chemo-naive women diagnosed with HGSOC into chemotherapy-resistant- and sensitive-like strata with a significant difference in overall survival (OS). Independent analysis of The Cancer Genome Atlas data further confirmed that high OSGEPL1 expression is a favorable prognostic factor for HGSOC.

CONCLUSIONS

We have developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC modified gene, OSGEPL1, that predicted response to platinum-based chemotherapy in intermediate-sensitive HGSOC. Our multivariate model applies to chemo-naïve samples regardless if the patint was treated with adjuvant or neoadjuvant chemotherapy. These results merit further investigation of the predictive capability of our model in larger cohorts.

Outcome of transarterial radioembolization in patients with hepatocellular carcinoma as a first-line interventional therapy and after a previous transarterial chemoembolization

Purpose

Due to a lack of data, there is an ongoing debate regarding the optimal frontline interventional therapy for unresectable hepatocellular carcinoma (HCC). The aim of the study is to compare the results of transarterial radioembolization (TARE) as the first-line therapy and as a subsequent therapy following prior transarterial chemoembolization (TACE) in these patients.

Methods

A total of 83 patients were evaluated, with 38 patients having undergone at least one TACE session prior to TARE [27 male; mean age 67.2 years; 68.4% stage Barcelona clinic liver cancer (BCLC) B, 31.6% BCLC C]; 45 patients underwent primary TARE (33 male; mean age 69.9 years; 40% BCLC B, 58% BCLC C). Clinical [age, gender, BCLC stage, activity in gigabecquerel (GBq), Child-Pugh status, portal vein thrombosis, tumor volume] and procedural [overall survival (OS), local tumor control (LTC), and progression-free survival (PFS)] data were compared. A regression analysis was performed to evaluate OS, LTC, and PFS.

Results

No differences were found in OS (95% CI: 1.12, P = 0.289), LTC (95% CI: 0.003, P = 0.95), and PFS (95% CI: 0.4, P = 0.525). The regression analysis revealed a relationship between Child-Pugh score (P = 0.005), size of HCC lesions (>10 cm) (P = 0.022), and OS; neither prior TACE (Child-Pugh B patients; 95% CI: 0.120, P = 0.729) nor number of lesions (>10; 95% CI: 2.930, P = 0.087) correlated with OS.

Conclusion

Prior TACE does not affect the outcome of TARE in unresectable HCC.

Simultaneous single-cell analysis of 5mC and 5hmC with SIMPLE-seq

Dynamic 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications to DNA regulate gene expression in a cell-type-specific manner and are associated with various biological processes, but the two modalities have not yet been measured simultaneously from the same genome at the single-cell level. Here we present SIMPLE-seq, a scalable, base resolution method for joint analysis of 5mC and 5hmC from thousands of single cells. Based on orthogonal labeling and recording of 'C-to-T' mutational signals from 5mC and 5hmC sites, SIMPLE-seq detects these two modifications from the same molecules in single cells and enables unbiased DNA methylation dynamics analysis of heterogeneous biological samples. We applied this method to mouse embryonic stem cells, human peripheral blood mononuclear cells and mouse brain to give joint epigenome maps at single-cell and single-molecule resolution. Integrated analysis of these two cytosine modifications reveals distinct epigenetic patterns associated with divergent regulatory programs in different cell types as well as cell states.

Decoding the roles of heat shock proteins in liver cancer

Hepatocellular carcinoma (HCC) is one of the most common gastrointestinal malignancies, characterized by insidious onset and high propensity for metastasis and recurrence. Apart from surgical resection, there are no effective curative methods for HCC in recent years, due to resistance to radiotherapy and chemotherapy. Heat shock proteins (HSP) play a crucial role in maintaining cellular homeostasis and normal organism development as molecular chaperones for intracellular proteins. Both basic research and clinical data have shown that HSPs are crucial participants in the HCC microenvironment, as well as the occurrence, development, metastasis, and resistance to radiotherapy and chemotherapy in various malignancies, particularly liver cancer. This review aims to discuss the molecular mechanisms and potential clinical value of HSPs in HCC, which may provide new insights for HSP-based therapeutic interventions for HCC.

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.