Roles of phosphatidylinositol-3-kinases signaling pathway in inflammation-related cancer: Impact of rs10889677 variant and buparlisib in colitis-associated cancer

BACKGROUND

Phosphatidylinositol-3-kinases (PI3K) is a well-known route in inflammation-related cancer. Recent discovery on PI3K-related genes revealed a potential variant that links ulcerative colitis (UC) and colorectal cancer (CRC) with colitis-associated cancer (CAC). PI3K/AKT pathway has been recommended as a potential additional therapeutic option for CRC due to its substantial role in modifying cellular processes. Buparlisib is a pan-class I PI3K inhibitor previously shown to reduce tumor growth.

AIM

To investigate the regulation of rs10889677 and the role of buparlisib in the PI3K signaling pathway in CAC pathogenesis.

METHODS

Genomic DNA from 32 colonic samples, including CAC (n = 7), UC (n = 10) and CRC (n = 15), was sequenced for the rs10889677 mutation. The mutant and wildtype fragments were amplified and cloned in the pmirGLO vector. The luciferase activity of cloned vectors was assessed after transfection into the HT29 cell line. CAC mice were induced by a mixture of a single azoxymethane injection and three cycles of dextran sulphate sodium, then buparlisib was administered after 14 d. The excised colon was subjected to immunohistochemistry for Ki67 and Cleaved-caspase-3 markers and quantitative real-time polymerase chain reaction analysis for Pdk1 and Sgk2.

RESULTS

Luciferase activity decreased by 2.07-fold in the rs10889677 mutant, confirming the hypothesis that the variant disrupted miRNA binding sites, which led to an increase in IL23R expression and the activation of the PI3K signaling pathway. Furthermore, CAC-induced mice had a significantly higher disease activity index (P < 0.05). Buparlisib treatment significantly decreased mean weight loss in CAC-induced mice (P < 0.05), reduced the percentage of proliferating cells by 5%, and increased the number of apoptotic cells. The treatment also caused a downward trend of Pdk1 expression and significantly decreased Sgk2 expression.

CONCLUSION

Our findings suggested that the rs10889677 variant as a critical initiator of the PI3K signaling pathway, and buparlisib had the ability to prevent PI3K-non-AKT activation in the pathophysiology of CAC.

Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract. While therapies exist, response can be limited within the patient population. Researchers have thus studied mouse models of colitis to further understand pathogenesis and identify new treatment targets. Flow cytometry and RNA-sequencing can phenotype immune populations with single-cell resolution but provide no spatial context. Spatial context may be particularly important in colitis mouse models, due to the simultaneous presence of colonic regions that are involved or uninvolved with disease. These regions can be identified on hematoxylin and eosin (H&E)-stained colonic tissue slides based on the presence of abnormal or normal histology. However, detection of such regions requires expert interpretation by pathologists. This can be a tedious process that may be difficult to perform consistently across experiments. To this end, we trained a deep learning model to detect ‘Involved’ and ‘Uninvolved’ regions from H&E-stained colonic tissue slides. Our model was trained on specimens from controls and three mouse models of colitis–the dextran sodium sulfate (DSS) chemical induction model, the recently established intestinal epithelium-specific, inducible Klf5^ΔIND (Villin-CreER^T2;Klf5^fl/fl) genetic model, and one that combines both induction methods. Image patches predicted to be ‘Involved’ and ‘Uninvolved’ were extracted across mice to cluster and identify histological classes. We quantified the proportion of ‘Uninvolved’ patches and ‘Involved’ patch classes in murine swiss-rolled colons. Furthermore, we trained linear determinant analysis classifiers on these patch proportions to predict mouse model and clinical score bins in a prospectively treated cohort of mice. Such a pipeline has the potential to reveal histological links and improve synergy between various colitis mouse model studies to identify new therapeutic targets and pathophysiological mechanisms.

Development and Validation of a Digital Analysis Method to Quantify CD3-immunostained T Lymphocytes in Whole Slide Images of Crohn's Disease Biopsies

The T-lymphocyte-mediated inflammation in Crohn's disease can be assessed by quantifying CD3-positive T-lymphocyte counts in colonic sections. We developed and validated a process to reliably quantify immunohistochemical marker-positive cells in a high-throughput setting using whole slide images (WSIs) of CD3-immunostained colonic and ileal tissue sections. In regions of interest (ROIs) and/or whole tissue sections of 40 WSIs from 36 patients with Crohn's disease, CD3-positive cells were quantified by an expert gastrointestinal pathologist (gold standard) and by image analysis algorithms developed with software from 3 independent vendors. Semiautomated quantification of CD3-positive cell counts estimated in 1 ROI per section were accurate when compared with manual analysis (Pearson correlation coefficient, 0.877 to 0.925). Biological variability was acceptable in digitally determined CD3-positive cell measures between 2 to 5 ROIs annotated on the same tissue section (coefficient of variation <25%). Results from computer-aided analysis of CD3-positive T lymphocytes in a whole tissue section and the average of results from 2 to 5 ROIs per tissue section lacked reliability (overestimation or underestimation and systematic bias), suggesting that absolute quantification of CD3-positive T lymphocytes in a whole tissue section may be more accurate. Semiautomated image analysis in WSIs demonstrated reproducible CD3-positive cell measures across 3 independent algorithms. A computer-aided digital image analysis method was developed and validated to quantify CD3-positive T lymphocytes in colonic and ileal biopsy sections from patients with Crohn's disease. Results support consideration of this digital analysis method for use in future Crohn's disease clinical studies.

An Image Analysis Solution For Quantification and Determination of Immunohistochemistry Staining Reproducibility

Supplemental Digital Content is available in the text.

With immunohistochemical (IHC) staining increasingly being used to guide clinical decisions, variability in staining quality and reproducibility are becoming essential factors in generating diagnoses using IHC tissue preparations. The current study tested a method to track and quantify the interrun, intrarun, and intersite variability of IHC staining intensity. Our hypothesis was that staining precision between laboratory sites, staining runs, and individual slides may be verified quantitatively, efficiently and effectively utilizing algorithm-based, automated image analysis. To investigate this premise, we tested the consistency of IHC staining in 40 routinely processed (formalin-fixed, paraffin-embedded) human tissues using 10 common antibiomarker antibodies on 2 Dako Omnis instruments at 2 locations (Carpinteria, CA: 30 m above sea level and Longmont, CO: 1500 m above sea level) programmed with identical, default settings and sample pretreatments. Digital images of IHC-labeled sections produced by a whole slide scanner were analyzed by a simple commercially available algorithm and compared with a board-certified veterinary pathologist’s semiquantitative scoring of staining intensity. The image analysis output correlated well with pathology scores but had increased sensitivity for discriminating subtle variations and providing reproducible digital quantification across sites as well as within and among staining runs at the same site. Taken together, our data indicate that digital image analysis offers an objective and quantifiable means of verifying IHC staining parameters as a part of laboratory quality assurance systems.

Proof of Concept for a Deep Learning Algorithm for Identification and Quantification of Key Microscopic Features in the Murine Model of DSS-Induced Colitis

Inflammatory bowel disease (IBD) is a complex disease which leads to life-threatening complications and decreased quality of life. The dextran sulfate sodium (DSS) colitis model in mice is known for rapid screening of candidate compounds. Efficacy assessment in this model relies partly on microscopic semiquantitative scoring, which is time-consuming and subjective. We hypothesized that deep learning artificial intelligence (AI) could be used to identify acute inflammation in H&E-stained sections in a consistent and quantitative manner. Training sets were established using ×20 whole slide images of the entire colon. Supervised training of a Convolutional Neural Network (CNN) was performed using a commercial AI platform to detect the entire colon tissue, the muscle and mucosa layers, and 2 categories within the mucosa (normal and acute inflammation E1). The training sets included slides of naive, vehicle-DSS and cyclosporine A-DSS mice. The trained CNN was able to segment, with a high level of concordance, the different tissue compartments in the 3 groups of mice. The segmented areas were used to determine the ratio of E1-affected mucosa to total mucosa. This proof-of-concept work shows promise to increase efficiency and decrease variability of microscopic scoring of DSS colitis when screening candidate compounds for IBD.

Digital Microscopy, Image Analysis, and Virtual Slide Repository

Advancements in technology and digitization have ushered in novel ways of enhancing tissue-based research via digital microscopy and image analysis. Whole slide imaging scanners enable digitization of histology slides to be stored in virtual slide repositories and to be viewed via computers instead of microscopes. Easier and faster sharing of histologic images for teaching and consultation, improved storage and preservation of quality of stained slides, and annotation of features of interest in the digital slides are just a few of the advantages of this technology. Combined with the development of software for digital image analysis, digital slides further pave the way for the development of tools that extract quantitative data from tissue-based studies. This review introduces digital microscopy and pathology, and addresses technical and scientific considerations in slide scanning, quantitative image analysis, and slide repositories. It also highlights the current state of the technology and factors that need to be taken into account to insure optimal utility, including preanalytical considerations and the importance of involving a pathologist in all major steps along the digital microscopy and pathology workflow.

Antimicrobial peptide KR-32 alleviates Escherichia coli K88-induced fatty acid malabsorption by improving expression of fatty acid transporter protein 4 (FATP4)1

Bacterial infection causes nutrient malabsorption in small intestine. KR-32, a kind of synthetic antimicrobial peptide, has the bacteriostatic effect. In the present study, 2 experiments were designed to analyze the effects of KR-32 on fat absorption of piglets with or without Escherichia coli infection. In Exp. 1, 12 weaning piglets (21 d old) were allocated to 2 groups: piglets with an intraperitoneal (i.p.) injection of antimicrobial peptide KR-32 (APK) and piglets with an i.p. injection of an equivalent volume (1 mL) of phosphate-buffered saline (PBS) (CON-1). Results showed that after 7 d of growth, KR-32 did not significantly change growth performance and apparent total tract digestibility (ATTD) of feed nutrients of normal pigs. To confirm whether KR-32 affects those of enterotoxigenic Escherichia coli (ETEC) K88-challenged pigs, we performed Exp. 2, in which 18 piglets (28 d old) were divided into the following 3 groups: 1) piglets orally challenged with 1 × 1010 cfu ETEC K88 on day 1 followed by an i.p. injection of 0.6 mg/kg KR-32 (K88 + APK); 2) piglets orally challenged with 1 × 1010 cfu ETEC K88 on day 1 followed by an i.p. injection of an equivalent volume (1 mL) of PBS (K88); and 3) piglets with an oral administration of fresh Luria-Bertani broth (50 mL) followed by an i.p. injection of an equivalent volume of PBS (CON-2). Results showed that ETEC K88 challenge led to poor ADFI, ADG, and G:F in piglets; decreased ATTD of feed nutrients, especially CP and ether extract (EE); and intestinal morphology disorder. After i.p. injection of KR-32, ADG and ATTD of CP and EE were greatly increased, G:F was significantly reduced (P < 0.05), and, especially, ATTD of EE returned to a normal level compared with group CON-2. Fatty acid absorption also highly increased after KR-32 injection. Then we focused on fat digestion and fatty acid uptake. The pH in the intestine and pancreas lipase showed no difference among the 3 treatment groups, whereas fatty acid transporter protein 4 (FATP4) expression was remarkably improved (P < 0.05) and the epithelial barrier was recovered after i.p. injection of KR-32. In conclusion, KR-32, given to ETEC K88-challenged piglets, improved growth performance, ATTD of EE, fatty acid absorption, and intestinal morphology, which indicated that KR-32 was likely to improve the expression of FATP4 and by repairing the epithelial barrier, thereby alleviating fatty acid malabsorption.

Dietary Prevention of Colitis by Aronia Berry is Mediated Through Increased Th17 and Treg

SCOPE

Increased fruit consumption is associated with reduced risk of colitis. It has been investigated whether the anti-colitic effects of the polyphenol-rich aronia berry (Aronia mitschurinii 'Viking') are mediated through Th17 and Treg.

METHODS AND RESULTS

Colitis is induced in recombinase activating gene-1 deficient mice injected with syngeneic CD4⁺ CD62L⁺ naïve T cells. Mice consume either 4.5% w/w aronia-berry-supplemented or a control diet concurrent with T cell transfer. The extent of colitis and immunocyte populations are evaluated at weeks 3 to 7 after transfer. Aronia consumption prevents colitic wasting and reduces colon weight/length ratios relative to the control diet at weeks 5 and 7. Compared to the control diet, aronia feeding increases Treg in mesenteric lymph node at all colitis stages. Treg and regulatory Th17 subpopulations (IL-17A⁺ IL-10⁺ and IL-17A⁺ IL-22⁺ ) are increased in lamina propria and spleen at week 5 in aronia-fed mice. Aronia feeding also decreases total CD4⁺ cells but increases colonic Tregs. The ability of aronia to modulate colonic cytokines is associated with functional T cell IL-10 and increased diversity of microbiota.

CONCLUSIONS

Aronia berry consumption inhibits adoptive transfer colitis by increasing Treg and regulatory Th17 cells. Dietary modulation of T cells is dynamic and precedes colitic wasting.