A machine learning-based choledocholithiasis prediction tool to improve ERCP decision making: a proof-of-concept study.

BACKGROUND: Previous studies demonstrated limited accuracy of existing guidelines for predicting choledocholithiasis, leading to overutilization of endoscopic retrograde cholangiopancreatography (ERCP). More accurate stratification may improve patient selection for ERCP and allow use of lower-risk modalities. METHODS: A machine learning model was developed using patient information from two published cohort studies that evaluated performance of guidelines in predicting choledocholithiasis. Prediction models were developed using the gradient boosting model (GBM) machine learning method. GBM performance was evaluated using 10-fold cross-validation and area under the receiver operating characteristic curve (AUC). Important predictors of choledocholithiasis were identified based on relative importance in the GBM. RESULTS: 1378 patients (mean age 43.3 years; 61.2% female) were included in the GBM and 59.4% had choledocholithiasis. Eight variables were identified as predictors of choledocholithiasis. The GBM had accuracy of 71.5% (SD 2.5%) (AUC 0.79 [SD 0.06]) and performed better than the 2019 American Society for Gastrointestinal Endoscopy (ASGE) guidelines (accuracy 62.4% [SD 2.6%]; AUC 0.63 [SD 0.03]) and European Society of Gastrointestinal Endoscopy (ESGE) guidelines (accuracy 62.8% [SD 2.6%]; AUC 0.67 [SD 0.02]). The GBM correctly categorized 22% of patients directed to unnecessary ERCP by ASGE guidelines, and appropriately recommended as the next management step 48% of ERCPs incorrectly rejected by ESGE guidelines. CONCLUSIONS: A machine learning-based tool was created, providing real-time, personalized, objective probability of choledocholithiasis and ERCP recommendations. This more accurately directed ERCP use than existing ASGE and ESGE guidelines, and has the potential to reduce morbidity associated with ERCP or missed choledocholithiasis.

Zenker's peroral endoscopic myotomy for management of large Zenker's diverticulum.

BACKGROUND: Zenker's diverticulum peroral endoscopic myotomy (zPOEM) is a minimally invasive treatment strategy for Zenker's diverticulum, with excellent results for management of small-to-moderate Zenker's diverticulum. We evaluated its use in the management of large Zenker's diverticulum. METHODS: This was a retrospective multicenter cohort study across 11 international centers including adult patients with large Zenker's diverticulum ≥ 40 mm treated by zPOEM between March 2017 and March 2022. The primary outcome was clinical success (dysphagia score ≤ 1 without need for further intervention). Secondary outcomes included technical success (complete myotomy as intended), adverse events (AEs), and rate of recurrence. RESULTS: 83 patients (male 62.7 %, mean age 72.6 [SD 11.5] years) underwent zPOEM for treatment of large Zenker's diverticulum (median size 50 mm, interquartile range [IQR] 41-55 mm, range 40-80 mm). The zPOEM procedure was technically successful in 82 patients (98.8 %), with a mean procedure time of 48.7 (SD 23.2) minutes. Clinical success was achieved in 71 patients (85.5 %). Median (IQR) symptom scores improved significantly from baseline for dysphagia (2 2 3 vs. 0 [0-2]; P < 0.001), regurgitation (3 2 3 4 vs. 0 [0-0]; P < 0.001), and respiratory symptoms (2 [0-3] vs. 0 [0-0]; P < 0.001). Among patients achieving clinical success, only one recurrence (1.4 %) was recorded during a median follow-up of 12.2 months (IQR 3-28). Post-procedure AEs, all mild to moderate, occurred in four patients (4.8 %). CONCLUSION: This study demonstrated safe and effective use of zPOEM in the management of large Zenker's diverticulum.

Injectable, Drug-Eluting Nanocrystals Prevent Fibrosis and Stricture Formation In Vivo.

BACKGROUND & AIMS: Tissue fibrosis results from uncontrolled healing responses leading to excessive mesenchymal cell activation and collagen and other extracellular matrix deposition. In the gastrointestinal tract, fibrosis leads to narrowing of the lumen and stricture formation. A drug treatment to prevent fibrosis and strictures in the gastrointestinal tract would be transformational for patient care. We aimed to develop a stricture treatment with the following characteristics and components: a small molecule with strong antifibrotic effects that is delivered locally at the site of the stricture to ensure correct lesional targeting while protecting the systemic circulation, and that is formulated with sustained-release properties to act throughout the wound healing processes. METHODS: A high-throughput drug screening was performed to identify small molecules with antifibrotic properties. Next, we formulated an antifibrotic small molecule for sustained release and tested its antifibrotic potential in 3 animal models of fibrosis. RESULTS: Sulconazole, a US Food and Drug Administration-approved drug for fungal infections, was found to have strong antifibrotic properties. Sulconazole was formulated as sulconazole nanocrystals for sustained release. We found that sulconazole nanocrystals provided superior or equivalent fibrosis prevention with less frequent dosing in mouse models of skin and intestinal tissue fibrosis. In a patient-like swine model of bowel stricture, a single injection of sulconazole nanocrystals prevented stricture formation. CONCLUSIONS: The current data lay the foundation for further studies to improve the management of a range of diseases and conditions characterized by tissue fibrosis.

Effective, safe and efficient porcine model of Forrest Ib bleeding gastric and colonic ulcers.

BACKGROUND: Developing effective gastrointestinal (GI) bleeding animal models is necessary to advance endoscopic hemostasis methods and train endoscopists on their use. Our aim, therefore, was to develop an effective and safe porcine GI bleeding model in the stomach and colon of large and small-sized oozing-type ulcers. METHODS: Gastric and colonic bleeding ulcers were created using either a hybrid endoscopic submucosal dissection (ESD) technique or a cap-assisted endoscopic mucosal resection (EMR-C) technique in 14 pigs. Prior to ulcer creation, animals were treated with either oral apixaban or intravenous (IV) unfractionated heparin anticoagulation in combination with clopidogrel and aspirin. The primary outcome was the technical success of inducing oozing-type Forrest Ib bleeding ulcers. Secondary outcomes included ulcer diameter, number, creation time and the number of complications associated with each technique. RESULTS: Using hybrid ESD and IV heparin anticoagulation, bleeding was observed in 21/23 (91.3%) gastric ulcers and 6/7 (85.7%) colonic ulcers created. The mean diameter and ulcer creation time were 2.3 ± 0.3 cm and 5.3 ± 0.5 min, respectively, for gastric ulcers and 2.2 ± 0.4 cm and 4.06 ± 0.6 min, respectively, for colonic ulcers. Using EMR-C and IV heparin anticoagulation, bleeding was observed in 14/15 (93.3%) gastric ulcers and 6/6 (100%) colonic ulcers created. The mean diameter and ulcer creation time were 0.8 ± 0.2 cm and 2.1 ± 0.5 min, respectively, for gastric ulcers and 0.7 ± 0.2 cm and 1.7 ± 0.3 min, respectively, for colonic ulcers. None of the ulcers created in animals anticoagulated with apixaban developed bleeding. None of the 14 pigs developed any complications. CONCLUSION: We have demonstrated the effectiveness and safety of a porcine GI bleeding model utilizing IV heparin anticoagulation and either hybrid ESD or EMR-C techniques to create oozing-type bleeding ulcers in the stomach and colon with customizable size.

Bulking agents in gastrointestinal endoscopy: present applications and future advances.

PURPOSE OF REVIEW: Bulking agents are inert materials injected into an organ to affect the physical properties of the organ for a therapeutic purpose. Various agents have been developed to aid in the treatment of diseases like gastroesophageal reflux disease (GERD), fecal incontinence, obesity, malignancy, hemostasis, and tissue dissection. Here, we review the state of the art in bulking agents in gastrointestinal endoscopy, past failures, current limitations, and where we see the field heading in the future. RECENT FINDINGS: Though bulking agents have been trialed for various different gastrointestinal diseases, there are currently limited uses in gastrointestinal endoscopy. Though various agents have been trialed for GERD, numerous complications and adverse events have limited its current use. However, for the treatment of fecal incontinence endoscopic bulking agent therapy is a reasonable option. Though in early stages of exploration, bulking agent therapy for enteric protection from radiotherapy may be a promising tool to improve treatment of pancreatic cancer. Bulking agents for tissue dissection have substantially improved lifting agents and complex polyp removal. Bulking agent therapy has not really been explored for endoscopic bariatric therapy or hemostasis but may be a fruitful area for exploration in the future. SUMMARY: Bulking agent therapy has been trialed for various gastrointestinal diseases with mixed success. There is currently a therapeutic roll in the endoscopic management of fecal incontinence and tissue dissection. A future role in the treatment of GERD, obesity, malignancy, and hemostasis seem feasible.

Human Microphysiological Models of Intestinal Tissue and Gut Microbiome.

The gastrointestinal (GI) tract is a complex system responsible for nutrient absorption, digestion, secretion, and elimination of waste products that also hosts immune surveillance, the intestinal microbiome, and interfaces with the nervous system. Traditional in vitro systems cannot harness the architectural and functional complexity of the GI tract. Recent advances in organoid engineering, microfluidic organs-on-a-chip technology, and microfabrication allows us to create better in vitro models of human organs/tissues. These micro-physiological systems could integrate the numerous cell types involved in GI development and physiology, including intestinal epithelium, endothelium (vascular), nerve cells, immune cells, and their interplay/cooperativity with the microbiome. In this review, we report recent progress in developing micro-physiological models of the GI systems. We also discuss how these models could be used to study normal intestinal physiology such as nutrient absorption, digestion, and secretion as well as GI infection, inflammation, cancer, and metabolism.

Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition.

We present the epithelial-to-mesenchymal transition (EMT) from two perspectives: experimental/technological and theoretical. We review the state of the current understanding of the regulatory networks that underlie EMT in three physiological contexts: embryonic development, wound healing, and metastasis. We describe the existing experimental systems and manipulations used to better understand the molecular participants and factors that influence EMT and metastasis. We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate intermediate hybrid states between the epithelial and mesenchymal states. Ultimately, the understanding gained about these networks should be translated into methods to control phenotypic outcomes, especially in the context of cancer therapeutic strategies. We present emerging theories of how to drive the dynamics of a network toward a desired dynamical attractor (e.g. an epithelial cell state) and emerging synthetic biology technologies to monitor and control the state of cells.

Discrete dynamic network modeling of oncogenic signaling: Mechanistic insights for personalized treatment of cancer.

Targeted drugs disrupting proteins that are dysregulated in cancer have emerged as promising treatments because of their specificity to cancer cell aberrations and thus their improved side effect profile. However, their success remains limited, largely due to existing or emergent therapy resistance. We suggest that this is due to limited understanding of the entire relevant cellular landscape. A class of mathematical models called discrete dynamic network models can be used to understand the integrated effect of an individual tumor's aberrations. We review the recent literature on discrete dynamic models of cancer and highlight their predicted therapeutic strategies. We believe dynamic network modeling can be used to drive treatment decision-making in a personalized manner to direct improved treatments in cancer.

Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome.

We present a novel methodology to construct a Boolean dynamic model from time series metagenomic information and integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic underpinnings for microbial interactions. We apply this in the context of a critical health issue: clindamycin antibiotic treatment and opportunistic Clostridium difficile infection. Our model recapitulates known dynamics of clindamycin antibiotic treatment and C. difficile infection and predicts therapeutic probiotic interventions to suppress C. difficile infection. Genome-scale metabolic network reconstructions reveal metabolic differences between community members and are used to explore the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of our computational model, that B. intestinihominis can in fact slow C. difficile growth.

The EGFR/ErbB3 Pathway Acts as a Compensatory Survival Mechanism upon c-Met Inhibition in Human c-Met+ Hepatocellular Carcinoma.

BACKGROUND: c-Met, a high-affinity receptor for Hepatocyte Growth Factor (HGF), plays a critical role in tumor growth, invasion, and metastasis. Hepatocellular carcinoma (HCC) patients with activated HGF/c-Met signaling have a significantly worse prognosis. Targeted therapies using c-Met tyrosine kinase inhibitors are currently in clinical trials for HCC, although receptor tyrosine kinase inhibition in other cancers has demonstrated early success. Unfortunately, therapeutic effect is frequently not durable due to acquired resistance. METHODS: We utilized the human MHCC97-H c-Met positive (c-Met+) HCC cell line to explore the compensatory survival mechanisms that are acquired after c-Met inhibition. MHCC97-H cells with stable c-Met knockdown (MHCC97-H c-Met KD cells) were generated using a c-Met shRNA vector with puromycin selection and stably transfected scrambled shRNA as a control. Gene expression profiling was conducted, and protein expression was analyzed to characterize MHCC97-H cells after blockade of the c-Met oncogene. A high-throughput siRNA screen was performed to find putative compensatory survival proteins, which could drive HCC growth in the absence of c-Met. Findings from this screen were validated through subsequent analyses. RESULTS: We have previously demonstrated that treatment of MHCC97-H cells with a c-Met inhibitor, PHA665752, results in stasis of tumor growth in vivo. MHCC97-H c-Met KD cells demonstrate slower growth kinetics, similar to c-Met inhibitor treated tumors. Using gene expression profiling and siRNA screening against 873 kinases and phosphatases, we identified ErbB3 and TGF-α as compensatory survival factors that are upregulated after c-Met inhibition. Suppressing these factors in c-Met KD MHCC97-H cells suppresses tumor growth in vitro. In addition, we found that the PI3K/Akt signaling pathway serves as a negative feedback signal responsible for the ErbB3 upregulation after c-Met inhibition. Furthermore, in vitro studies demonstrate that combination therapy with PHA665752 and Gefitinib (an EGFR inhibitor) significantly reduced cell viability and increased apoptosis compared with either PHA665752 or Gefitinib treatment alone. CONCLUSION: c-Met inhibition monotherapy is not sufficient to eliminate c-Met+ HCC tumor growth. Inhibition of both c-Met and EGFR oncogenic pathways provides superior suppression of HCC tumor growth. Thus, combination of c-Met and EGFR inhibition may represent a superior therapeutic regimen for c-Met+ HCC.

Induction of tumor initiation is dependent on CD44s in c-Met⁺ hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) patients with active hepatocyte growth factor (HGF)/c-Met signaling have a significantly worse prognosis. c-Met, a high affinity receptor for HGF, plays a critical role in cancer growth, invasion and metastasis. c-Met and CD44 have been utilized as cell surface markers to identify mesenchymal tumor-initiating stem-like cells (TISC) in several cancers including HCC. In this work, we examine the complex relationship between c-Met and CD44s (standard form), and investigate the specific role of CD44s as a tumor initiator and stemness marker in HCC. METHODS: Gene and protein expression assays were utilized to investigate the relationship between CD44s and c-Met in HCC cell lines. Tumor-sphere assays and in vivo tumor assays were performed to investigate the role of CD44+ cells as TISCs. Student's t-test or one-way ANOVA with Tukeys post-hoc test was performed to test for differences amongst groups with a p < .05 as significant. RESULTS: In an immunohistochemical and immunoblot analysis of human HCC samples, we observed that more than 39% of human HCC samples express c-Met and CD44. To study the relationship between c-Met and CD44, we used MHCC97-H cells, which are CD44(+)/c-Met(+). The knockdown of c-Met in MHCC97-H cells decreased CD44s, reduced TISC characteristics and decreased tumorsphere formation. Furthermore, we demonstrate that the inhibition of PI3K/AKT signaling decreased CD44s expression and subsequently decreased tumorsphere formation. The down-regulation of CD44s leads to a significant loss of a TISC and mesenchymal phenotype. Finally, the down-regulation of CD44s in MHCC97-H cells decreased tumor initiation in vivo compared with the scrambled control. CONCLUSIONS: In summary, our data suggest that CD44s is modulated by the c-Met-PI3K-AKT signaling cascade to support a mesenchymal and TISC phenotype in HCC cells. Moreover, c-Met could be a potential therapeutic drug for targeting HCC cells with TISC and mesenchymal phenotypes.

Targeting IL-15 in large granular lymphocyte leukemia.

IL-15 is a cytokine that stimulates the proliferation of NK and T cells. Previous studies have shown that IL-15 is critical to the induction of T-cell large granular lymphocyte (T-LGL) leukemia. A Phase I trial of a humanized antibody (Hu-Mikß1) to the IL2/IL15Rß receptor, expressed on T-LGL, is explored in this trial to evaluate the safety, pharmacokinetics, specificity and clinical efficacy of Hu-Mikß1. The study demonstrated no toxicity and favorable saturation of IL2/IL15Rß receptor, but no clinical efficacy in this Phase I study.

JCoDA: a tool for detecting evolutionary selection.

BACKGROUND: The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences. RESULTS: JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway. CONCLUSIONS: JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda.