LCN2 as a Potential Diagnostic Biomarker for Ulcerative Colitis-Associated Carcinogenesis Related to Disease Duration

Integrated analysis and single-cell sequencing of mitochondrial metabolism related gene molecular subtype and diagnostic model in ulcerative colitis

Ulcerative colitis (UC) is a chronic inflammatory bowel disease that seriously affects the life expectancy of patients. Although increasingly sophisticated combinations of drugs can alleviate symptoms, 10-20% of patients still do not respond well. Therefore, it is necessary to further explore the pathogenesis and potential biomarkers of UC. Many clues have suggested the important value of mitochondrial metabolism in UC, but its role and related targets need to be further explored. By public database data, we identified differentially expressed mitochondrial metabolism related genes (MMRG) in UC. Subsequently, we identified biomarkers associated with MMRG based on a machine learning approach. After classifying the MMRG-associated molecular subtypes of UC, we comprehensively analyzed the MMRG biomarkers and the relationship between the MMRG molecular subtypes and immune infiltration characteristics. Single-cell sequencing analysis showed significant expression pattern of MMRG signatures in different cell subtypes. qRT-PCR and western blot further confirmed the abnormal expressions of selected genes in vitro. Our findings provided a new perspective on the role of MMRG in UC.

Lipocalin-2 and intestinal diseases

Dysfunction of the intestinal barrier is a prevalent phenomenon observed across a spectrum of diseases, encompassing conditions such as mesenteric artery dissection, inflammatory bowel disease, cirrhosis, and sepsis. In these pathological states, the integrity of the intestinal barrier, which normally serves to regulate the selective passage of substances between the gut lumen and the bloodstream, becomes compromised. This compromised barrier function can lead to a range of adverse consequences, including increased permeability to harmful substances, the translocation of bacteria and their products into systemic circulation, and heightened inflammatory responses within the gut and beyond. Understanding the mechanisms underlying intestinal barrier dysfunction in these diverse disease contexts is crucial for the development of targeted therapeutic interventions aimed at restoring barrier integrity and ameliorating disease progression. Lipocalin-2 (LCN2) expression is significantly upregulated during episodes of intestinal inflammation, making it a pivotal indicator for gauging the extent of such inflammatory processes. Notably, however, LCN2 derived from distinct cellular sources, whether intestinal epithelial cells or immune cells, exhibits notably divergent functional characteristics. Furthermore, the multifaceted nature of LCN2 is underscored by its varying roles across different diseases, sometimes even demonstrating contradictory effects.

Non-Invasive Methods of Diagnosis and Management of Patients with Ulcerative Colitis

The global incidence and age-standardized prevalence rate of ulcerative colitis (UC) is increasing worldwide. It is a debilitating and lifelong inflammatory disease affecting both pediatric and adult patients. Thus, it is important to focus on modern treat-to-target approach, based on a tight control of the disease with close monitoring through interval assessments and modification of the treatment. Endoscopy remains the key method for UC assessment, but recent guidelines focus on implementation of non-invasive methods for UC diagnosis and management such as biomarkers (C-reactive protein, fecal calprotectin, and fecal lactofferin) and imaging methods (intestinal ultrasound). We summarize the diagnostic performance of non-invasive tests and present current evidence-based non-invasive strategy recommendations for UC monitoring.

Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment

Background

The main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.

Methods

In this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.

Results

RRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs-THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients.

Conclusions

THY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC.

Phosphoproteomics Reveals Novel Insights into the Pathogenesis and Identifies New Therapeutic Kinase Targets of Ulcerative Colitis

BACKGROUND

Ulcerative colitis (UC) is a chronic recurrent inflammatory disease with unclear etiology. Currently, safe and effective treatment options for UC remain to be developed. Kinases, which catalyze the phosphorylation of substrates, have emerged as promising therapeutic targets for inflammatory diseases. We clarified the kinase activity profile and phosphorylation network in UC and aimed to reveal new pathogenic mechanisms and potential therapeutic targets.

METHODS

We first performed the phosphoproteomic analysis of rectal tissues from UC patients and healthy individuals. Further bioinformatic analyses revealed the remodeling of key kinases and signaling pathways. Then, we conducted a screening of kinases to identify new potential therapeutic targets through in vivo and in vitro experiments.

RESULTS

Phosphoproteomics revealed a drastic remodeling of signaling pathways in UC, such as pathways related to tight junction, adhesion junction, and necroptosis. Additionally, the activity of kinases such as CDK2, CLK1 and AURKB were significantly changed. Additional screening of these kinases identified CDK2 as a potential therapeutic target for UC, as inhibiting CDK2 effectively alleviated dextran sulfate sodium-induced colitis in mice. Further research revealed that suppressing CDK2 remarkably inhibited RIPK1, RIPK3, and MLKL phosphorylation, as well as MLKL oligomerization, thereby inhibiting epithelial necroptosis and protecting the intestinal barrier.

CONCLUSIONS

Our research deepened the understanding of UC pathogenesis through the lens of phosphorylation. Moreover, we identified CDK2 as a new potential therapeutic target for UC, revealing a novel role for CDK2 in necroptosis.

HIF-1α Pathway Orchestration by LCN2: A Key Player in Hypoxia-Mediated Colitis Exacerbation

In this study, we investigated the role of hypoxia in the development of chronic inflammatory bowel disease (IBD), focusing on its impact on the HIF-1α signaling pathway through the upregulation of lipocalin 2 (LCN2). Using a murine model of colitis induced by sodium dextran sulfate (DSS) under hypoxic conditions, transcriptome sequencing revealed LCN2 as a key gene involved in hypoxia-mediated exacerbation of colitis. Bioinformatics analysis highlighted the involvement of crucial pathways, including HIF-1α and glycolysis, in the inflammatory process. Immune infiltration analysis demonstrated the polarization of M1 macrophages in response to hypoxic stimulation. In vitro studies using RAW264.7 cells further elucidated the exacerbation of inflammation and its impact on M1 macrophage polarization under hypoxic conditions. LCN2 knockout cells reversed hypoxia-induced inflammatory responses, and the HIF-1α pathway activator dimethyloxaloylglycine (DMOG) confirmed LCN2's role in mediating inflammation via the HIF-1α-induced glycolysis pathway. In a DSS-induced colitis mouse model, oral administration of LCN2-silencing lentivirus and DMOG under hypoxic conditions validated the exacerbation of colitis. Evaluation of colonic tissues revealed altered macrophage polarization, increased levels of inflammatory factors, and activation of the HIF-1α and glycolysis pathways. In conclusion, our findings suggest that hypoxia exacerbates colitis by modulating the HIF-1α pathway through LCN2, influencing M1 macrophage polarization in glycolysis. This study contributes to a better understanding of the mechanisms underlying IBD, providing potential therapeutic targets for intervention.

Identification of Early Events in Serrated Pathway Colorectal Tumorigenesis by Using Digital Spatial Profiling

INTRODUCTION

The colorectal serrated pathway involves precursor lesions known as sessile serrated lesions (SSL) and traditional serrated adenomas (TSA). Mutations in BRAF or KRAS are crucial early events in this pathway. Additional genetic and epigenetic changes contribute to the progression of these lesions into high-grade lesions and, eventually, invasive carcinoma.

METHODS

We employed digital spatial profiling to investigate the transcriptional changes associated with SSL and TSA. The genes identified are confirmed by immunohistochemical (IHC) staining. Colorectal cancer (CRC) cell lines with CEACAM6 overexpression and knockdown were established to study the roles of CEACAM6 on tumorigenesis of CRC.

RESULTS

Ten genes were upregulated in SSL and TSA, and seven were upregulated in both types of lesions. IHC staining confirmed overexpression of CEACAM6, LCN2, KRT19, and lysozyme in SSL and TSA. CEACAM6 expression is an early event in the serrated pathway but a late event in the conventional pathway. Using cell line models, we confirmed that CEACAM6 promotes CRC cells' proliferation, migration, and invasion abilities.

CONCLUSION

These results highlight that the transcriptional changes in the early stages of tumorigenesis exhibit relative uniformity. Identifying these early events may hold significant promise in elucidating the mechanisms behind tumor initiation.

Maternal polysorbate 80 exposure causes intestinal ILCs and CD4+ T cell developmental abnormalities in mouse offspring

This study aimed to investigate the transgenerational impacts of maternal intake of polysorbate 80 (P80), an emulsifier widely used in modern society, on the development of offspring immunity. Our results revealed that maternal P80 treatment led to impaired differentiation of innate lymphoid cells (ILCs) and CD4+ T cells in the small intestinal lamina propria (SiLP), resulting in intestinal dyshomeostasis in female offspring. Furthermore, we found that SiLP ILCs abundances were significantly altered in 0-day-old fetuses from P80-treated mothers, indicating a prenatal impact of P80-treated mothers on offspring immunity. Additionally, cesarean section and foster-nursing studies demonstrated that P80-induced altered SiLP ILCs in 0-day-old fetuses could further induce dysregulation of ILCs and CD4+ T cells in the SiLP, thus promoting intestinal dysregulation in offspring later in life. Overall, our findings suggest that maternal P80 intake could prenatally program the development of offspring immunity, exerting a significant and long-lasting impact.

Rosa Roxburghii Tratt Fruit Extract Prevents Dss-Induced Ulcerative Colitis in Mice by Modulating the Gut Microbiota and the IL-17 Signaling Pathway

Ulcerative colitis (UC) is a non-specific inflammatory bowel illness characterized by intestinal mucosal barrier degradation, inflammation, oxidative damage, and gut microbiota imbalances. Rosa roxburghii Tratt Fruit extract (RRTE) was extracted from Rosa roxburghii Tratt fruit, exhibiting an excellent prevention effect against UC; RRTE could prevent the damage of DSS-induced human normal colonic epithelial (NCM 460) cells, especially in cell viability and morphology, and oxidative damage. Additionally, in UC mice, RRTE could limit the intestinal mucosal barrier by increasing the expression of intestinal tight junction proteins and mucin, reducing inflammation and oxidative damage in colon tissue. More importantly, RRTE can increase the abundance of beneficial bacteria to regulate gut microbiota such as Ruminococcus, Turicibacter, and Parabacteroides, and reduce the abundance of harmful bacteria such as Staphylococcus and Shigella. Furthermore, transcriptomics of colonic mucosal findings point out that the beneficial effect of RRTE on UC could be attributed to the modulation of inflammatory responses such as the IL-17 and TNF signaling pathways. The qPCR results confirm that RRTE did involve the regulation of several genes in the IL-17 signaling pathway. In conclusion, RRTE could prevent DSS-induced damage both in vitro and in vivo.

Using LLMs and Explainable ML to Analyze Biomarkers at Single-Cell Level for Improved Understanding of Diseases

Single-cell RNA sequencing (scRNA-seq) technology has significantly advanced our understanding of the diversity of cells and how this diversity is implicated in diseases. Yet, translating these findings across various scRNA-seq datasets poses challenges due to technical variability and dataset-specific biases. To overcome this, we present a novel approach that employs both an LLM-based framework and explainable machine learning to facilitate generalization across single-cell datasets and identify gene signatures to capture disease-driven transcriptional changes. Our approach uses scBERT, which harnesses shared transcriptomic features among cell types to establish consistent cell-type annotations across multiple scRNA-seq datasets. Additionally, we employed a symbolic regression algorithm to pinpoint highly relevant, yet minimally redundant models and features for inferring a cell type's disease state based on its transcriptomic profile. We ascertained the versatility of these cell-specific gene signatures across datasets, showcasing their resilience as molecular markers to pinpoint and characterize disease-associated cell types. The validation was carried out using four publicly available scRNA-seq datasets from both healthy individuals and those suffering from ulcerative colitis (UC). This demonstrates our approach's efficacy in bridging disparities specific to different datasets, fostering comparative analyses. Notably, the simplicity and symbolic nature of the retrieved gene signatures facilitate their interpretability, allowing us to elucidate underlying molecular disease mechanisms using these models.

Biosensing Intestinal Alkaline Phosphatase by Pregnancy Test Strips Based on Target-Triggered CRISPR-Cas12a Activity to Monitor Intestinal Inflammation

With an increasing incidence worldwide, inflammatory bowel disease (IBD) is a chronic inflammatory disease affecting the gastrointestinal tract, which impairs the life quality of patients. Therefore, it is of great significance to construct a sensitive, simple, and convenient biosensor to analyze IBD-associated biomarkers for an auxiliary diagnosis of IBD. Intestinal alkaline phosphatase (IAP), expressed by the intestinal epithelium, is an endogenous protein that is thought to play a vital role in maintaining intestinal homeostasis and is considered a potential biomarker for IBD. Here, an IAP detection method was developed using pregnancy test strips by dephosphorylation. Initially, a double-stranded DNA (dsDNA) was designed to respond to IAP and acted as an activator of Cas12a. In the presence of IAP, the designed dsDNA was not digested by lambda exonuclease (λ exo), which hybridized to the Cas12a-crRNA duplex and resulted in the activation of the trans-cleavage of Cas12a. Further, the activated Cas12a cleaved the single-strand DNA (ssDNA) linker in the MBs-ssDNA-hCG probe, triggering the release of hCG. With magnetic separation, the released hCG could be quantitatively detected by pregnancy test strips. IAP levels were analyzed in feces from colitis and healthy mice by pregnancy test strips. The results showed that the IAP level of colitis mice (3.89 ± 1.92 U/L) was much lower than that of healthy mice (39.64 ± 24.93 U/L), indicating the correlation between IAP and intestinal inflammation. Taken together, a sensitive, user-friendly detection assay based on pregnancy test strips was constructed to monitor IAP and used as an auxiliary diagnostic approach for IBD in a clinical scene.

Identification of Lipocalin 2 as a Potential Ferroptosis-related Gene in Ulcerative Colitis

BACKGROUND

Ulcerative colitis (UC) is a chronic nonspecific inflammatory disease generally limited to the mucosa and submucosa of the colon. Recent studies suggest that ferroptosis is a novel programmed cell death that may be involved in the process of UC. However, the mechanism of ferroptosis in UC remains to be further investigated.

METHODS

The genes associated with UC and ferroptosis were screened by bioinformatics methods, and a random forest model was constructed to identify the core genes of UC and validated with external data sets. Establishment of dextran sodium sulfate (DSS) induced UC in an animal model in vivo. Interferon (IFN)-γ primed immortalized bone marrow-derived macrophages cells stimulated with Lipopolysaccharides (LPS) inflammation model and LPS-stimulated Caco-2 cells colitis model in vitro were constructed. The potential link between Lipocalin-2 (LCN2) and UC ferroptosis was explored by flow cytometry, Fe2+ assay, Western Blot, gene knockdown, hematoxylin and eosin staining, and immunohistochemistry staining.

RESULTS

Analysis of differentially expressed genes (DEGs) showed that LCN2 was highly expressed in UC. The protein-protein interaction (PPI) networks showed that ferroptosis-associated DEGs were highly correlated with the immune gene LCN2. The most important gene in the random forest model, LCN2, was identified as a core gene in UC. In the LPS/IFN-γ-induced inflammation model, LCN2 expression was elevated, lipid peroxidation, Fe2+, ACSL4 and COX-2 levels increased, whereas GPX4 and FTH1 expression decreased. Similarly, in the DSS-induced UC mouse model, Occludin, ZO-1, Claudin-1, and GPX4 expression were significantly decreased, but ACSL4 and LCN2 expression were elevated. In addition, the use of Ferrostatin-1 (Fer-1) can significantly reverse its trend. More importantly, silencing of LCN2 suppressed ferroptosis events in both the LPS/IFN-γ-induced inflammation model and the LPS-stimulated colitis model.

CONCLUSION

In conclusion, our study demonstrates that LCN2 is a key factor in the regulation of ferroptosis in UC and provides additional evidence for the important role of ferroptosis in UC.

Pursuing neutrophils: systematic scoping review on blood-based biomarkers as predictors of treatment outcomes in inflammatory bowel disease

Background

Long-term management of inflammatory bowel diseases (IBD) is challenging and the identification of reliable predictors for treatment outcomes is an unmet need. Neutrophil-related biomarkers have been mainly studied in the feces, but blood analyses have inherent advantages.

Objective

To review the recent learnings on the ability of blood-based neutrophil-expressed biomarkers to predict treatment outcomes in IBD.

Design

Systematic scoping review.

Data sources and methods

We performed a literature search in Pubmed, EMBASE, SCOPUS, Web of Science, ScienceDirect, and Cochrane Central Register of Controlled Trials from inception until May 2022 according to Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. All human studies associating blood-based neutrophil-related compounds with the prediction of disease progression, complication onset, or treatment outcomes were included.

Results

From 1032 retrieved entries, 34 studies were selected, 32 published in 2013 or later. In all, 17 biomarkers from granules, cytoplasm, plasmatic membrane, and plasma were explored. In total, 1850 Crohn's disease (CD) and 1122 ulcerative colitis non-duplicated patients were included. The most mentioned biomarkers were nCD64, serum calprotectin (SC), oncostatin M (OSM), neutrophil elastase-generated calprotectin fragment (CPa9-HNE), and triggering receptor expressed on myeloid cells 1 (TREM1). Six biomarkers showed promising results: OSM, SC, eNAMPT, nCD64, TREM1, and CPa9-HNE. Variable positive signals were found for human neutrophil peptide 1-3, LL-37, S100A12, and neutrophil gelatinase-associated lipocalin. No predictive ability was found for the remaining markers. Sharing a neutrophil compartment did not indicate similar behavior.

Conclusion

Advances in the last decade began to unveil the untapped potential of the readily accessible blood neutrophil-expressed biomarkers, especially nCD64, TREM1, and CPa9-HNE. Current evidence suggests that future research should focus on well-defined subpopulations instead of a one-size-fits-all biomarker.

Registration

https://osf.io/kes9a.

Identification of ferroptosis-related genes in ulcerative colitis: a diagnostic model with machine learning

Background

Ulcerative colitis (UC) is an idiopathic, chronic disorder characterized by inflammation, injury, and disruption of the colonic mucosa. However, there are still many difficulties in the diagnosis and differential diagnosis of UC. An increasing amount of research has shown a connection between ferroptosis and the etiology of UC. Therefore, our study aimed to identify the key genes related to ferroptosis in UC to provide new ideas for diagnosis UC.

Methods

Gene expression profiles of normal and UC samples were extracted from the Gene Expression Omnibus (GEO) database. By combining differentially expressed genes (DEGs), Weighted correlation network analysis (WGCNA) genes, and ferroptosis-related genes, hub genes were identified and then screened using Lasso regression. Based on the key genes, gene ontology (GO) and gene set enrichment analysis (GSEA) analyses were performed. We used NaiveBeyas, Logistic, IBk, and RandomForest algorithms to build a disease diagnosis model using the hub genes. The model was validated using GSE87473 as the validation set.

Results

Gene expression matrices of GSE87466 and GSE75214 were downloaded from the GEO database, including 184 UC patients and 43 control samples. A total of 699 DEGs were obtained. From FerrDb, 565 genes related to ferroptosis were identified. The 1,513 genes with the highest absolute correlation coefficient value in the MEblue module were obtained from WGCNA analysis. Five hub genes (LCN2, MUC1, PARP8, PLIN2, and TIMP1) were identified using the Lasso regression algorithm based on the overlapped DEGs, WGCNA-identified genes, and ferroptosis-related genes. GO and GSEA analyses revealed that 5 hub genes were identified as being involved in the negative regulation of transcription by competitive promoter binding, cellular response to citrate cycle_tca_cycle, cytosolic_dna_sensing pathway, UV-A, and beta-alanine metabolism. The logistic algorithm's values of the area under the curve (AUC)were 1.000 and 0.995 for training and validation cohorts, and sensitivity is 0.962, specificity is 1.000, respectively, as determined by comparing various methods.

Conclusions

The previously described hub genes were identified as being intimately related to ferroptosis in UC and capable of distinguishing UC patients from controls. By detecting the expression of several genes, this model may aid in diagnosing UC and understanding the etiology and treatment of the disease.