Introduction

For the precision medicine, patient-derived organoid (PDO) is regarded as one of the promising models. However, current PDOs were mainly derived from surgical specimen.

Aims & Methods

We aimed to analyze the single cell RNA-sequencing (scRNA-seq) of PDO from various sampling methods with different pathologic outcomes.
In 2021, three pancreatic cancer and one gallbladder cancer samples were collected from surgical specimen, endoscopic ultrasound guided-fine needle biopsy (EUS-FNB), and endoscopic retrograde cholangiopancreatography (ERCP)-guided biopsy. The samples were mechanically dissociated with dissociation buffer and incubated using shaking incubator. Dissociated cells were seeded into growth factor reduced Matrigel. From these PDOs, to evaluate the histological similarity between the PDOs and cancer tissue samples, a pathologist evaluate the PDOs and cancer samples using H&E staining. And we generated scRNA-seq data in each experimental design, and corrected batch effects that could occur when multiple samples are considered simultaneously in downstream analysis. Marker genes representing each cell subcluster were identified, and statistical hypothesis tests were performed to identify genes differentially expressed according to differences in biopsy methods and/or pathological results.

Results

Pathologically, when comparing the PDOs and cancer tissues, the PDOs showed well-visualized malignant glandular epithelium and similar architecture forming glandular structures, just like cancer tissue samples. We found the optimal 13 types of sub cell-type clusters with a resolution parameter of 0.3 in clustering analysis based on the Uniform Manifold Approximation and Projection (UMAP) algorithm in terms of silhouette score. As a result of examining the expression levels of KRT19, a marker gene for malignant ductal cells, and RGS5, a stellate marker gene, which showed the same pattern as the existing PDAC transcriptome studies, it was confirmed that most of the cells derived from PDOs were malignant ductal cells. Finally, we identified a heterogeneous effect on gene expression patterns in ductal cells depending on not only pathological positivity, but also biopsy methods for organoid.

Conclusion

According to our scRNA-seq, most cells were malignant cells and EUS-FNB could be a good sampling method for PDOs. However, further analysis about a heterogeneous effect on gene expression patterns is necessary.

Introduction

Granulocyte–monocyte apheresis (GMA) is a non-pharmacological therapy approved for the treatment of ulcerative colitis (UC), mainly in steroid-dependent cases. Its mechanism of action is based on the removal of activated leukocytes, but its exact immunological changes have not been fully described yet.

Aims & Methods

Our aim was to characterize the response in the transcriptome at the single-cell resolution level and cell population effects of GMA device. We analysed scRNASeq data from peripheral blood mononuclear cells (PBMC) of two UC patients undergoing their first GMA session. Their gene expression profile was compared before (PRE) and one month after (POST) the GMA treatment, from the inflow and outflow lines, respectively. The analytical pipeline included quality control and filtering, cell-type annotation, differential gene expression and pathway enrichment analysis.

Results

Two patients with UC (mean age 59 years; both E2) were included. Overall, the cell populations that appear to have been affected by the GMA treatment were natural killer cells and monocytes with both populations being reduced after the treatment. The distribution of the annotated cell-types was 2,369 B cells (PRE:50%, POST:49%), 11,462 CD4+ (PRE:49%, POST:50%) and 8,845 CD8+ T-cells (PRE:51%, POST:48%), 47 dendritic cells (PRE:40%, POST:59%), 3,773 natural killer cells (PRE:54%, POST:45%) and 2,352 monocytes (PRE:59%, POST:40%). Annotation at higher resolution identified 27 cell-types with monocytes being subannotated as 1,972 CD14 (PRE:62%, POST:37%) and 380 CD16 (PRE:48%, POST:51%) monocytes. Differential gene expression analysis identified in total 86 significant genes across six cell-types (CD4+ naive and central memory T-cells, natural killer cells, B intermediate cells, double-negative T-cells and CD14 monocytes) with 63% of these genes being downregulated after the GMA treatment. Pathway enrichment analysis identified higher contribution of the double-negative T-cells to the enriching genes. More specifically, after the treatment the double-negative T-cells exhibited upregulation of the NEFL that is associated with the MAPK cascade and downregulation of genes related to immune response and signalling pathways. Regarding the CD14 monocytes, after the GMA treatment we observed significant downregulation of the genes LINC02315, IGHEP1 and IGHE, with the latter being linked to innate immune response pathways.

Conclusion

GMA induces a range of modifications in the gene expression profile across different cell types that change the immunological environment of UC patients.

Disclosure

Financial support from an unrestricted grant from Adacyte, who had no role in the study design, interpretation of data or drafting the abstract.

Introduction

Ulcerative colitis (UC) is an inflammatory disorder of the colon of unknown aetiology characterised by intestinal barrier dysfunction associated with colonic epithelial goblet cell depletion and a shift in intestinal stem cell retention and function^1,2. Pancreastatin (PST), an intestinal epithelial cells-derived peptide highly expressed in colonic tissues of patients with active UC, positively correlates with UC early onset, disease severity, and inflammatory markers³. However, the effect of PST inhibition on colonic epithelial barrier function remains undetermined.

Aims & Methods

This study aimed to investigate the impact of pancreastatin inhibitor 8 (PSTI8) on colonic epithelial barrier function in a preclinical mouse model of UC. Male and female C57BL/6 mice were treated intrarectally with PSTi8 (2.5mg/mL/kg) or PBS for six days and received 5% dextran sulfate sodium (DSS) to induce colitis or water (control) for five days. The disease activity index (DAI) was assessed daily. ELISA quantified inflammatory cytokines, interleukin (IL)-6, IL-18 and IL-22. Markers to characterise differentiated goblet cells (Mucin, MUC2), transcription factors for goblets’ lineage commitment (growth factor independent, GFI1 and Kruppel-like factor, KLF1), and colonic stem cells plasticity (fast-cycling Lgr5, fetal-like Ly6a, and reserve Hopx cells) were quantified via RT-PCR and immunofluorescence.

Results

PSTi8 treatment increased stool consistency (p<0.01) and delayed the onset of bleeding in colitic male mice compared to PBS-treated mice (2-4 days). Conversely, no differences in the DAI were noted between colitic PSTi8 and PBS-treated female mice. In non-colitic conditions, PSTi8 treatment increased (p<0.03) IL-22 in males and decreased (p<0.01) its level in female mice with no effect of IL-6. In colitic conditions, although IL-22 levels were decreased (p<0.01) in female mice and IL-6 levels were increased (p<0.001) in male mice, PSTi8 treatment did not show any effect. Conversely, in colitic females, IL-18 was significantly increased (p<0.02), and PSTi8 abolished that increase. The mRNA expression level of MUC2 remains unaltered in male and female non-colitic and colitic mice treated or not with PSTi8. Yet, immunofluorescence staining in non-colitic and colitic conditions demonstrated a decrease of MUC2 in PSTi8-treated female mice. In concordance, transcription factors KLF1 and GFI1 were significantly increased (p<0.001 and p<0.02, respectively) in colitic female mice, and PSTi8 treatment abolished that increase. No differences were seen in male mice except for a significant increase of KLF1 in PSTi8-treated colitic mice. In colitic conditions, fast-cycling cells marker Lgr5 expression in both sexes was significantly decreased (p<0.0001), and treatment with PSTi8 did not show any effect. However, in colitic male mice, fetal-like stem cells makers Ly6a expression was significantly increased (p<0.007), and PSTi8 treatment significantly decreased (p<0.02) that expression. Although a significant decrease (p<0.0001) of reserve cells marker Hopx was only seen in colitic female mice, PSTi8 treatment did not regulate that marker in male and female mice.

Conclusion

PST inhibition protects male mice from DSS-mediated colitis while exacerbating susceptibility to colitis in female mice. PST inhibition regulates the expansion of goblet and intestinal stem cells in a sex-dependent manner. Further investigation is needed to delineate the signalling pathways involved in PST action on the mucosa in both sexes. Targeting PST may lead to novel therapeutic strategies in UC.

References

1. Singh V, Johnson K, Yin J, et al. Chronic Inflammation in Ulcerative Colitis Causes Long-Term Changes in Goblet Cell Function. Cmgh. 2022;13(1):219-232.
2. Yui S, Azzolin L, Maimets M, et al. YAP/TAZ-dependent reprogramming of colonic epithelium links ECM remodeling to tissue regeneration. Cell Stem Cell. 2018;22(1):35-49.e7.
3. Eissa N, Elgazzar O, Hussein H, Hendy GN, Bernstein CN, Ghia JE. Pancreastatin reduces alternatively activated macrophages, disrupts the epithelial homeostasis and aggravates colonic inflammation. A descriptive analysis. Biomedicines. 2021;9(2):1-18.

Introduction

The melanocortin 1 receptor (MC1R)–specific agonist PL8177 and its main metabolite PL8435 have demonstrated MC1R binding affinity and functional activity that mirrors that of α-melanocyte–stimulating hormone, which has been shown to be effective in reducing inflammation in numerous experimental models. This study investigates the effects of PL8177 on inflammation, cell population composition, and gene and protein expression in colons from a dextran sulfate sodium (DSS)–induced rat model of colitis. The objective is to determine the effectiveness of PL8177 in this model and to characterize its underlying mechanism of action.

Aims & Methods

Male Wistar rats received 5% DSS in drinking water for 3 days to induce colitis (each group n=6). Rats in the sham group received drinking water only. The other groups received vehicle control (placebo)–filled capsules; PL8177-filled capsules at 20, 50, and 100 μg per animal (by oral gavage); or oral mesalazine (positive control). At termination on day 8, 24 hours after the last dose, colon tissues were harvested, dissected, and snap frozen with liquid nitrogen. Colon samples were analyzed for cytokine levels, single nuclei RNA-seq, and data-independent acquisition tandem mass spectrometry. Colitis was assessed by a disease activity index (diarrhea and rectal bleeding), colon length shortening, colon weight gain, and histopathological assessment. The total colitis index was used to assess inflammatory damage.

Results

Colitis was induced in rats treated with DSS. Treatment with oral PL8177 50 μg showed a significant (P<0.05) improvement in colon weight (53% reduction), stool consistency, and fecal occult blood score compared to vehicle. There was a significant (P<0.05) improvement in the total colitis index for the PL8177 100-μg group vs vehicle control group. All PL8177 cohorts showed greater improvement in the total colitis index compared to the mesalazine-treated cohort. PL8177 50 μg showed a significant (P<0.05) improvement in colon weight (53% reduction), whereas mesalazine treatment was associated with a marked reduction in colon length, but only moderate improvement (35%) in colon weight. Single nuclei RNA-seq analysis showed that after oral PL8177 100 µg treatment, relative cell populations and key gene expression levels were closer to those of healthy controls. A subclustering analysis revealed significant differences between the PL8177 100-µg and vehicle populations. Although both showed the presence of macrophages, those present in vehicle-treated colons were primarily M1 macrophages that are involved in inflammation. In the PL8177 100 µg–treated colons, macrophages were primarily M2, which are pro-resolution. Proteomic analysis showed that the colons of PL8177-treated rats are more similar to sham colons than to vehicle colons. Additionally, after treatment with PL8177, a protein known to promote intestinal homeostasis and a blood-based biomarker protein showed expression similar to that seen in the sham group, a result not seen in vehicle-treated colons.

Conclusion

In a rat model, oral PL8177 treatment of colonic inflammation showed significant improvement in anatomical markers of colitis vs the vehicle and mesalazine control groups, supporting the aim of treating inflammatory bowel disease (IBD) in humans. Transcriptomics and proteomics data show that oral PL8177 treatment causes diseased colons to move toward the healthy state and to resolve inflammation. Resolving inflammation—rather than blocking it—provides the possibility of efficacy coupled with safety in treating IBD.

Disclosure

Priyanka Dhingra, Alison Obr, Carl Spana, John H. Dodd, and Paul S. Kayne are employees of Palatin Technologies, Inc.

Introduction

Screening for Barrett’s esophagus (BE) could lead to earlier detection (EAC) and improve survival of esophageal adenocarcinoma (EAC). The Cytosponge, a non-endoscopic cell collection device that is coupled with the biomarker Trefoil Factor 3 (TFF3), has been shown in the Barrett’s Esophagus Screening Trial 3 (BEST3) trial, to lead to a 10-fold increase in BE diagnosis in a reflux population. The aims of this study were to: 1) Estimate the proportion of missed BE or stage-1 EAC under the current primary care reflux referral pathway, 2) Define a target screening population and, 3) To estimate the trade-off between the target population to screen and the proportion of BE or stage-1 EAC diagnosed.

Aims & Methods

This was a retrospective analysis and modelling from the multicentre, pragmatic, randomised controlled BEST3 trial that took place across 109 general practices in England. The findings from the main study were previously reported.¹ For aim 1, we used the BEST3 intervention (n=6834) and control arm (n=6388) data to estimate the number of missed BE or stage-1 EAC under the current reflux referral pathway. For aim 2, we determined which clinical risk factors predict a diagnosis of BE or stage-1 EAC in individuals who swallowed the Cytosponge (n=1654) and then modelled the probability of a diagnosis of BE and stage-1 EAC. For aim 3, we used different probabilities of a diagnosis of BE and stage-1 EAC to estimate the starting age to screen, to estimate the trade-off of the number-needed-to-screen and the proportion of BE or stage-1 EAC that would be diagnosed.

Results

Among usual care (control), 0.2% (13/6388) of individuals had BE or stage-1 EAC whereas, the expected prevalence of BE or stage-1 EAC within the intervention (Cytosponge) arm was 10.6% (680/6388), leading to the estimation that the proportion of missed pre-symptomatic BE and stage-1 EAC cases under current care is ~98%. Using logistic regression, we showed that male gender (Odds Ratio, OR 2.46, 95% Confidence Interval, CI 1.67-3.64, p<0.001), age (OR 1.05, 95% CI 1.03-1.07, p<0.001) and family history (OR 1.81, 95% CI 1.04-3.15, p=0.036) were significant predictors of BE or stage-1 EAC diagnosis. Next we modelled and simulate the trade-off for the numbers-needed-to screen on a population level according to different probability thresholds for a diagnosis of BE or stage-1 EAC (≥3%, ≥5%, and ≥10% among individuals with reflux). For these models we set an upper age limit of 74 years for practical considerations (Table 1). These data suggest that a 5% threshold is likely the optimal strategy. This reduces the screening population by 45.2% (males age 55-74 and females 65-74) while still diagnosing 71.0% of cases with a number-needed-to-screen to detect one case of 10.7.

Conclusion

A targeted screening strategy has the potential to substantially improve detection rates for BE and stage-1 EAC compared with current care. The trial data can be used to inform the optimal age for screening in males versus females in order to maximise the yield of screening according to the resources available.

References

Fitzgerald RC, di Pietro M, O'Donovan M, et al. Cytosponge-trefoil factor 3 versus usual care to identify Barrett's oesophagus in a primary care setting: a multicentre, pragmatic, randomised controlled trial. The Lancet 2020;396(10247):333-44.

Disclosure

R.C.F. and M.O. are named inventors on patents pertaining to the Cytosponge and associated technology. R.C.F. and M.O are shareholders of Cyted Ltd., a company working on early detection technology. The other authors declare no conflict of interest.

Introduction

Accurate distinction between benign and malignant biliary strictures (BS) is challenging. The use of bile duct biopsies and brush cytology via endoscopic retrograde cholangiopancreatography (ERCP) remains suboptimal. Single-operator cholangioscopy increases the diagnostic yield in BS but has limited availability and high costs. Convolutional neural network (CNN)-based systems have the potential to assist in the diagnostic process and improve reproducibility. Thus, we assessed the feasibility of using deep learning to differentiate BS out of fluoroscopy images during ERCP.

Aims & Methods

We conducted a retrospective review of adult patients (n=251) from three university centers in Germany (Leipzig, Dresden, Halle) who underwent an ERCP. We developed and evaluated a deep learning-based model (DenseNet) by means of fluoroscopy images. We measured the area under the receiver operating characteristic curve (AUROC) to evaluate the performance of the classifier and used saliency maps analyses to understand the decision-making process of the model.

Results

In cross-validation (Leipzig cohort), malignant BS were detected with a mean AUROC of 0.88 ± 0.02. On two independent external validation cohorts (Dresden, Halle), the of the deep learned based classifier reached a mean AUROC of 0.71 ± 0.04 and 0.74 ± 0.07, respectively. The artificial intelligence model's predictions identify plausible characteristics within the fluoroscopy images.

Conclusion

By using a deep learning model, we were able to discriminate malignant BS from benign biliary conditions. Artificial intelligence improves the diagnostic yield of malignant BS and needs to be validated in prospective design.

Introduction

Capsule endoscopy (CE) is a minimally invasive exam suitable of panendoscopic evaluation of the gastrointestinal tract. Nevertheless, CE is time-consuming, with suboptimal diagnostic yield in the upper GI tract. Convolutional neural networks (CNN) are human brain architecture-based models suitable for image analysis. However, there is no study about their role in capsule panendoscopy.

Aims & Methods

Our aim was to develop an artificial intelligence (AI) model for panendoscopic automatic detection of pleomorphic lesions (namely vascular lesions, protuberant lesions, hematic residues, ulcers, and erosions). 355110 images (6977 esophageal, 12918 gastric, 258443 small bowel, 76772 colonic) from eight different CE and colon CE (CCE) devices were divided into a training and validation dataset in a patient split design. The model classification was compared to three CE experts’ classifications. The model’s performance was evaluated by its sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the precision-recall curve.

Results

The binary esophagus CNN had a diagnostic accuracy for pleomorphic lesions of 83.6%. The binary gastric CNN identified pleomorphic lesions with a 96.6% accuracy. The undenary small bowel CNN distinguished pleomorphic lesions with different hemorrhagic potential with 97.6% accuracy. The trinary colonic CNN (detection and differentiation of normal mucosa, pleomorphic lesions, and hematic residues) had 94.9% global accuracy.

Conclusion

Our group developed the first AI model for panendoscopic automatic detection of pleomorphic lesions in both CE and colon CE from multiple brands, solving a critical interoperability technological challenge. Deep learning-based tools may change the landscape of minimally invasive capsule panendoscopy.

References

1. Pennazio M, Rondonotti E, Despott EJ, Dray X, Keuchel M, Moreels T, et al. Small-bowel capsule endoscopy and device-assisted enteroscopy for diagnosis and treatment of small-bowel disorders: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2022. Endoscopy. 2023 Jan;55(1):58-95. PubMed PMID: 36423618. Epub 20221124.
2. Le Berre C, Trang-Poisson C, Bourreille A. Small bowel capsule endoscopy and treat-to-target in Crohn's disease: A systematic review. World J Gastroenterol. 2019 Aug 21;25(31):4534-54. PubMed PMID: 31496630. PMCID: PMC6710184.
3. Iddan G, Meron G, Glukhovsky A, Swain P. Wireless capsule endoscopy. Nature. 2000 May 25;405(6785):417. PubMed PMID: 10839527.
4. Rondonotti E, Pennazio M. Colon capsule for panendoscopy: a narrow window of opportunity. Endosc Int Open. 2021 Dec;9(12):E1860-E2. PubMed PMID: 34917450. PMCID: PMC8670997. Epub 20211214.
5. Vuik FER, Moen S, Spaander MCW. Colon capsule endoscopy as panendoscopy: Using current knowledge to enhance possibilities. Endosc Int Open. 2022 May;10(5):E584. PubMed PMID: 35571484. PMCID: PMC9106432. Epub 20220513.