Identification and verification of HCAR3 and INSL5 as new potential therapeutic targets of colorectal cancer

Identification of hub genes related to metastasis and prognosis of osteosarcoma and establishment of a prognostic model with bioinformatic methods

Osteosarcoma (OS) is the most common primary malignant bone tumor occurring in children and adolescents. Improvements in our understanding of the OS pathogenesis and metastatic mechanism on the molecular level might lead to notable advances in the treatment and prognosis of OS. Biomarkers related to OS metastasis and prognosis were analyzed and identified, and a prognostic model was established through the integration of bioinformatics tools and datasets in multiple databases. 2 OS datasets were downloaded from the Gene Expression Omnibus database for data consolidation, standardization, batch effect correction, and identification of differentially expressed genes (DEGs); following that, gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the DEGs; the STRING database was subsequently used for protein-protein interaction (PPI) network construction and identification of hub genes; hub gene expression was validated, and survival analysis was conducted through the employment of the TARGET database; finally, a prognostic model was established and evaluated subsequent to the screening of survival-related genes. A total of 701 DEGs were identified; by gene ontology and KEGG pathway enrichment analyses, the overlapping DEGs were enriched for 249 biological process terms, 13 cellular component terms, 35 molecular function terms, and 4 KEGG pathways; 13 hub genes were selected from the PPI network; 6 survival-related genes were identified by the survival analysis; the prognostic model suggested that 4 genes were strongly associated with the prognosis of OS. DEGs related to OS metastasis and survival were identified through bioinformatics analysis, and hub genes were further selected to establish an ideal prognostic model for OS patients. On this basis, 4 protective genes including TPM1, TPM2, TPM3, and TPM4 were yielded by the prognostic model.

Pathological image profiling identifies onco-microbial, tumor immune microenvironment, and prognostic subtypes of colorectal cancer

Histology slide, tissue microbes, and the host gene expression can be independent prognostic factors of colorectal cancer (CRC), but the underlying associations and biological significance of these multimodal omics remain unknown. Here, we comprehensively profiled the matched pathological images, intratumoral microbes, and host gene expression characteristics in 527 patients with CRC. By clustering these patients based on histology slide features, we classified the patients into two histology slide subtypes (HSS). Onco-microbial community and tumor immune microenvironment (TIME) were also significantly different between the two subtypes (HSS1 and HSS2) of patients. Furthermore, variation in intratumoral microbes-host interaction was associated with the prognostic heterogeneity between HSS1 and HSS2. This study proposes a new CRC classification based on pathological image features and elucidates the process by which tumor microbes-host interactions are reflected in pathological images through the TIME.

Developing insulin-like peptide 5-based antagonists for the G protein-coupled receptor, RXFP4

Human insulin-like peptide 5 (INSL5) is a gut hormone produced by colonic L-cells, and its biological functions are mediated by Relaxin Family Peptide Receptor 4 (RXFP4). Our preliminary data indicated that RXFP4 agonists are potential drug leads for the treatment of constipation. More recently, we designed and developed a novel RXFP4 antagonist, A13-nR that was shown to block agonist-induced activity in cells and animal models. We showed that A13-nR was able to block agonist-induced increases in colon motility in mice of both genders that express the receptor, RXFP4. Our data also showed that colorectal propulsion induced by intracolonic administration of short-chain fatty acids was antagonized by A13-nR. Therefore, A13-nR is an important research tool and potential drug lead for the treatment of colon motility disorders, such as bacterial diarrhea. However, A13-nR acted as a partial agonist at high concentrations in vitro and demonstrated modest antagonist potency (∼35 nM). Consequently, the primary objective of this study is to pinpoint novel modifications to A13-nR that eliminate partial agonist effects while preserving or augmenting antagonist potency. In this work, we detail the creation of a series of A13-nR-modified analogues, among which analogues 3, 4, and 6 demonstrated significantly improved RXFP4 affinity (∼3 nM) with reduced partial agonist activity, enhanced antagonist potency (∼10 nM) and maximum agonist inhibition (∼80 %) when compared with A13-nR. These compounds have potential as candidates for further preclinical evaluations, marking a significant stride toward innovative therapeutics for colon motility disorders.

DHCR7 promotes lymph node metastasis in cervical cancer through cholesterol reprogramming-mediated activation of the KANK4/PI3K/AKT axis and VEGF-C secretion

Cervical cancer (CC) patients with lymph node metastasis (LNM) have a poor prognosis. However, the molecular mechanism of LNM in CC is unclear, and there is no effective clinical treatment. Here, we found that 7-dehydrocholesterol reductase (DHCR7), an enzyme that catalyzes the last step of cholesterol synthesis, was upregulated in CC and closely related to LNM. Gain-of-function and loss-of-function experiments proved that DHCR7 promoted the invasion ability of CC cells and lymphangiogenesis in vitro and induced LNM in vivo. The LNM-promoting effect of DHCR7 was partly mediated by upregulating KN motif and ankyrin repeat domains 4 (KANK4) expression and subsequently activating the PI3K/AKT signaling pathway. Alternatively, DHCR7 promoted the secretion of vascular endothelial growth factor-C (VEGF-C), and thereby lymphangiogenesis. Interestingly, cholesterol reprogramming was needed for the DHCR7-mediated promotion of activation of the KANK4/PI3K/AKT axis, VEGF-C secretion, and subsequent LNM. Importantly, treatment with the DHCR7 inhibitors AY9944 and tamoxifen (TAM) significantly inhibited LNM of CC, suggesting the clinical application potential of DHCR7 inhibitors in CC. Collectively, our results uncover a novel molecular mechanism of LNM in CC and identify DHCR7 as a new potential therapeutic target.

The diverse influences of relaxin-like peptide family on tumor progression: Potential opportunities and emerging challenges

Relaxin-like peptide family exhibit differential expression patterns in various types of cancers and play a role in cancer development. This family participates in tumorigenic processes encompassing proliferation, migration, invasion, tumor microenvironment, immune microenvironment, and anti-cancer resistance, ultimately influencing patient prognosis. In this review, we explore the mechanisms underlying the interaction between the RLN-like peptide family and tumors and provide an overview of therapeutic approaches utilizing this interaction.

Gibson T, McCain S, Stone BC, Gill T, Pickett BE. Pathway2Targets: an open-source pathway-based approach to repurpose therapeutic drugs and prioritize human targets

Background

Recent efforts to repurpose existing drugs to different indications have been accompanied by a number of computational methods, which incorporate protein-protein interaction networks and signaling pathways, to aid with prioritizing existing targets and/or drugs. However, many of these existing methods are focused on integrating additional data that are only available for a small subset of diseases or conditions.

Methods

We have designed and implemented a new R-based open-source target prioritization and repurposing method that integrates both canonical intracellular signaling information from five public pathway databases and target information from public sources including OpenTargets.org. The Pathway2Targets algorithm takes a list of significant pathways as input, then retrieves and integrates public data for all targets within those pathways for a given condition. It also incorporates a weighting scheme that is customizable by the user to support a variety of use cases including target prioritization, drug repurposing, and identifying novel targets that are biologically relevant for a different indication.

Results

As a proof of concept, we applied this algorithm to a public colorectal cancer RNA-sequencing dataset with 144 case and control samples. Our analysis identified 430 targets and ~700 unique drugs based on differential gene expression and signaling pathway enrichment. We found that our highest-ranked predicted targets were significantly enriched in targets with FDA-approved therapeutics for colorectal cancer (p-value < 0.025) that included EGFR, VEGFA, and PTGS2. Interestingly, there was no statistically significant enrichment of targets for other cancers in this same list suggesting high specificity of the results. We also adjusted the weighting scheme to prioritize more novel targets for CRC. This second analysis revealed epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase (PI3K), and two mitogen-activated protein kinases (MAPK14 and MAPK3). These observations suggest that our open-source method with a customizable weighting scheme can accurately prioritize targets that are specific and relevant to the disease or condition of interest, as well as targets that are at earlier stages of development. We anticipate that this method will complement other approaches to repurpose drugs for a variety of indications, which can contribute to the improvement of the quality of life and overall health of such patients.

Silencing LCN2 enhances RSL3-induced ferroptosis in T cell acute lymphoblastic leukemia

BACKGROUND

T-cell acute lymphoblastic leukemia (T-ALL) is a life-threatening malignancy and therapeutic toxicity remains a huge challenge for survival rates. A novel iron-dependent form of cell death, ferroptosis, shows potentials in cancer therapy. This study aimed to identify ferroptosis-associated hub genes within a proteinprotein interaction (PPI) network.

METHODS

We screened differential expressed genes (DEGs) in GSE46170 dataset and obtained ferroptosis-related genes from FerrDb database. Through overlapping between DEGs and ferroptosis-related genes, ferroptosis-associated DEGs were identified for further PPI network construction. Molecular complex detection (MCODE) algorithm in Cytoscape was employed to determine tightly connected protein clusters. Chord diagram of Gene Ontology (GO) was generated to reveal the potential biological process of hub genes. Through transfection with siRNA of lipocalin 2 (LCN2) into TALL cells, the regulatory role of LCN2 in ferroptosis was investigated.

RESULTS

Venn diagram identified a total of 37 ferroptosis-associated DEGs between GSE46170 and ferroptosis-associated genes, which were mainly enriched in ferroptosis and necroptosis. Based on PPI network analysis, 5 hub genes (LCN2, LTF, HP, SLC40A1 and TFRC) were found. These hub genes were involved in iron ion transport and could distinguish T-ALL from normal individuals. Further experimental studies demonstrated that LCN2 was highly expressed in T-ALL, while silencing LCN2 promoted RSL3-induced ferroptotic cell death in T-ALL cells.

CONCLUSION

This study identified novel ferroptosis-associated hub genes, which shed new insights into the underlying mechanism of ferroptosis in T-ALL and also provide promising therapeutic targets for T-ALL.

Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents

BACKGROUND

Detection of appropriate receptor proteins and drug agents are equally important in the case of drug discovery and development for any disease. In this study, an attempt was made to explore colorectal cancer (CRC) causing molecular signatures as receptors and drug agents as inhibitors by using integrated statistics and bioinformatics approaches.

METHODS

To identify the important genes that are involved in the initiation and progression of CRC, four microarray datasets (GSE9348, GSE110224, GSE23878, and GSE35279) and an RNA_Seq profiles (GSE50760) were downloaded from the Gene Expression Omnibus database. The datasets were analyzed by a statistical r-package of LIMMA to identify common differentially expressed genes (cDEGs). The key genes (KGs) of cDEGs were detected by using the five topological measures in the protein-protein interaction network analysis. Then we performed in-silico validation for CRC-causing KGs by using different web-tools and independent databases. We also disclosed the transcriptional and post-transcriptional regulatory factors of KGs by interaction network analysis of KGs with transcription factors (TFs) and micro-RNAs. Finally, we suggested our proposed KGs-guided computationally more effective candidate drug molecules compared to other published drugs by cross-validation with the state-of-the-art alternatives of top-ranked independent receptor proteins.

RESULTS

We identified 50 common differentially expressed genes (cDEGs) from five gene expression profile datasets, where 31 cDEGs were downregulated, and the rest 19 were up-regulated. Then we identified 11 cDEGs (CXCL8, CEMIP, MMP7, CA4, ADH1C, GUCA2A, GUCA2B, ZG16, CLCA4, MS4A12 and CLDN1) as the KGs. Different pertinent bioinformatic analyses (box plot, survival probability curves, DNA methylation, correlation with immune infiltration levels, diseases-KGs interaction, GO and KEGG pathways) based on independent databases directly or indirectly showed that these KGs are significantly associated with CRC progression. We also detected four TFs proteins (FOXC1, YY1, GATA2 and NFKB) and eight microRNAs (hsa-mir-16-5p, hsa-mir-195-5p, hsa-mir-203a-3p, hsa-mir-34a-5p, hsa-mir-107, hsa-mir-27a-3p, hsa-mir-429, and hsa-mir-335-5p) as the key transcriptional and post-transcriptional regulators of KGs. Finally, our proposed 15 molecular signatures including 11 KGs and 4 key TFs-proteins guided 9 small molecules (Cyclosporin A, Manzamine A, Cardidigin, Staurosporine, Benzo[A]Pyrene, Sitosterol, Nocardiopsis Sp, Troglitazone, and Riccardin D) were recommended as the top-ranked candidate therapeutic agents for the treatment against CRC.

CONCLUSION

The findings of this study recommended that our proposed target proteins and agents might be considered as the potential diagnostic, prognostic and therapeutic signatures for CRC.

Identification of Specific Biomarkers and Pathways in the Treatment Response of Infliximab for Inflammatory Bowel Disease: In-Silico Analysis

Background: Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. In biological therapy, infliximab became the first anti-tumor necrosis factor (TNF) agent approved for IBD. Despite this success, infliximab is expensive, often ineffective, and associated with adverse events. Prediction of infliximab resistance would improve overall potential outcomes. Therefore, there is a pressing need to widen the scope of investigating the role of genetics in IBD to their association with therapy response. Methods: In the current study, an in-silico analysis of publicly available IBD patient transcriptomics datasets from Gene Expression Omnibus (GEO) are used to identify subsets of differentially expressed genes (DEGs) involved in the pathogenesis of IBD and may serve as potential biomarkers for Infliximab response. Five datasets were found that met the inclusion criteria. The DEGs for datasets were identified using limma R packages through the GEOR2 tool. The probes’ annotated genes in each dataset intersected with DGEs from all other datasets. Enriched gene Ontology Clustering for the identified genes was performed using Metascape to explore the possible connections or interactions between the genes. Results: 174 DEGs between IBD and healthy controls were found from analyzing two datasets (GSE14580 and GSE73661), indicating a possible role in the pathogenesis of IBD. Of the 174 DEGs, five genes (SELE, TREM1, AQP9, FPR2, and HCAR3) were shared between all five datasets. Moreover, these five genes were identified as downregulated in the infliximab responder group compared to the non-responder group. Conclusions: We hypothesize that alteration in the expression of these genes leads to an impaired response to infliximab in IBD patients. Thus, these genes can serve as potential biomarkers for the early detection of compromised infliximab response in IBD patients.

Identification of Key MicroRNAs and Genes between Colorectal Adenoma and Colorectal Cancer via Deep Learning on GEO Databases and Bioinformatics

Background

Deep learning techniques are gaining momentum in medical research. Colorectal adenoma (CRA) is a precancerous lesion that may develop into colorectal cancer (CRC) and its etiology and pathogenesis are unclear. This study aims to identify transcriptome differences between CRA and CRC via deep learning on Gene Expression Omnibus (GEO) databases and bioinformatics in the Chinese population.

Methods

In this study, three microarray datasets from the GEO database were used to identify the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in CRA and CRC. The FunRich software was performed to predict the targeted mRNAs of DEMs. The targeted mRNAs were overlapped with DEGs to determine the key DEGs. Molecular mechanisms of CRA and CRC were evaluated using enrichment analysis. Cytoscape was used to construct protein-protein interaction (PPI) and miRNA-mRNA regulatory networks. We analyzed the expression of key DEMs and DEGs, their prognosis, and correlation with immune infiltration based on the Kaplan-Meier plotter, UALCAN, and TIMER databases.

Results

A total of 38 DEGs are obtained after the intersection, including 11 upregulated genes and 27 downregulated genes. The DEGs were involved in the pathways, including epithelial-to-mesenchymal transition, sphingolipid metabolism, and intrinsic pathway for apoptosis. The expression of has-miR-34c (P = 0.036), hsa-miR-320a (P = 0.045), and has-miR-338 (P = 0.0063) was correlated with the prognosis of CRC patients. The expression levels of BCL2, PPM1L, ARHGAP44, and PRKACB in CRC tissues were significantly lower than normal tissues (P < 0.001), while the expression levels of TPD52L2 and WNK4 in CRC tissues were significantly higher than normal tissues (P < 0.01). These key genes are significantly associated with the immune infiltration of CRC.

Conclusion

This preliminary study will help identify patients with CRA and early CRC and establish prevention and monitoring strategies to reduce the incidence of CRC.

Ligand recognition mechanism of the human relaxin family peptide receptor 4 (RXFP4)

Members of the insulin superfamily regulate pleiotropic biological processes through two types of target-specific but structurally conserved peptides, insulin/insulin-like growth factors and relaxin/insulin-like peptides. The latter bind to the human relaxin family peptide receptors (RXFPs). Here, we report three cryo-electron microscopy structures of RXFP4-G_i protein complexes in the presence of the endogenous ligand insulin-like peptide 5 (INSL5) or one of the two small molecule agonists, compound 4 and DC591053. The B chain of INSL5 adopts a single α-helix that penetrates into the orthosteric pocket, while the A chain sits above the orthosteric pocket, revealing a peptide-binding mode previously unknown. Together with mutagenesis and functional analyses, the key determinants responsible for the peptidomimetic agonism and subtype selectivity were identified. Our findings not only provide insights into ligand recognition and subtype selectivity among class A G protein-coupled receptors, but also expand the knowledge of signaling mechanisms in the insulin superfamily.

Low Expression of AGPAT5 Is Associated With Clinical Stage and Poor Prognosis in Colorectal Cancer and Contributes to Tumour Progression

Background:

Colorectal cancer (CRC) has a high prevalence and poor prognosis. This study aimed to identify biomarkers related to the clinical stage (I-IV) of CRC.

Methods:

The LinkedOmics database was used as the discovery cohort, and two Gene Expression Omnibus (GEO) databases (GSE41258 and GSE422848) served as validation cohorts. The trend test of genes related to clinical stage (I-IV) of CRC patients was identified by the Jonckheere-Terpstra test. The cBioPortal database, Gene Expression Profiling Interactive Analysis (GEPIA) and PrognoScan databases were used to explore the expression change and prognostic value of clinical stage-related genes in CRC patients. CRC cells overexpressed AGPAT5 were constructed and used for cell counting kit-8 (CCK-8), flow cytometric, and wound healing assays in vitro.

Results:

We identified four clinical stage-related genes, GSR, AGPAT5, CRLF1, and NPR3, in CRC. The CNA frequencies of GSR, CRLF1, AGPAT5, and NPR3 occurred in 11%, 2.4%, 13%, and 3% of patients, respectively. The expression of GSR and AGPAT5 tended to decrease with CRC stage (I-IV) progression, and the expression of CRLF1 and NPR3 tended to increase with CRC stage (I-IV) progression. Compared with the normal group, AGPAT5 expression was markedly decreased in stage IV CRC. Higher GSR and AGPAT5 expression levels were associated with better overall survival (OS) and disease-free survival (DFS) in CRC patients. Lower CRLF1 and NPR3 expression levels were associated with better OS and DFS in CRC. GSR, CRLF1, AGPAT5, and NPR3 expression were related to CRC progression, microsatellite instability, and tumour purity in CRC. Furthermore, AGPAT5 was downregulated in CRC cell lines, and overexpression of AGPAT5 inhibited cell proliferation and migration and promoted cell apoptosis in CRC cells.

Conclusion:

Low AGPAT5 expression may serve as a poor prognostic factor and clinical stage biomarker in CRC. In addition, AGPAT5 acts as a tumour suppressor in CRC progression.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.

Early growth response 1 transcription factor is essential for the pathogenic properties of human endometriotic epithelial cells

Although a non-malignant gynecological disorder, endometriosis displays some pathogenic features of malignancy, such as cell proliferation, migration, invasion and adaptation to hypoxia. Current treatments of endometriosis include pharmacotherapy and/or surgery, which are of limited efficacy and often associated with adverse side effects. Therefore, to develop more effective therapies to treat this disease, a broader understanding of the underlying molecular mechanisms that underpin endometriosis needs to be attained. Using immortalized human endometriotic epithelial and stromal cell lines, we demonstrate that the early growth response 1 (EGR1) transcription factor is essential for cell proliferation, migration and invasion, which represent some of the pathogenic properties of endometriotic cells. Genome-wide transcriptomics identified an EGR1-dependent transcriptome in human endometriotic epithelial cells that potentially encodes a diverse spectrum of proteins that are known to be involved in tissue pathologies. To underscore the utility of this transcriptomic data set, we demonstrate that carbonic anhydrase 9 (CA9), a homeostatic regulator of intracellular pH, is not only a molecular target of EGR1 but is also important for maintaining many of the cellular properties of human endometriotic epithelial cells that are also ascribed to EGR1. Considering therapeutic intervention strategies are actively being developed for EGR1 and CAIX in the treatment of other pathologies, we believe EGR1 and its transcriptome (which includes CA9) will offer not only a new conceptual framework to advance our understanding of endometriosis but will also furnish new molecular vulnerabilities to be leveraged as potential therapeutic options in the future treatment of endometriosis.

In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps

Adenomatous polyps of the colon are the most common neoplastic polyps. Although most of adenomatous polyps do not show malign transformation, majority of colorectal carcinomas originate from neoplastic polyps. Therefore, understanding of this transformation process would help in both preventive therapies and evaluation of malignancy risks. This study uncovers alterations in gene expressions as potential biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways. Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in chemokine profiles with mostly pro-tumoral activities. These biomarkers might appear as both preventive targets and biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of adenomatous polyps.

Significant co-expression of putative cancer stem cell markers, EpCAM and CD166, correlates with tumor stage and invasive behavior in colorectal cancer

BACKGROUND

The crucial oncogenic role of cancer stem cells (CSCs) in tumor maintenance, progression, drug resistance, and relapse has been clarified in different cancers, particularly in colorectal cancer (CRC). The current study was conducted to evaluate the co-expression pattern and clinical significance of epithelial cell adhesion molecules (EpCAM) and activated leukocyte cell adhesion (CD166 or ALCAM) in CRC patients.

METHODS

This study was carried out on 458 paraffin-embedded CRC specimens by immunohistochemistry on tissue microarray (TMA) slides.

RESULTS

Elevated expression of EpCAM and CD166 was observed in 61.5% (246/427) and 40.5% (164/405) of CRC cases. Our analysis showed a significant positive association of EpCAM expression with tumor size (P = 0.02), tumor stage (P = 0.007), tumor differentiate (P = 0.005), vascular (P = 0.01), neural (P = 0.01), and lymph node (P = 0.001) invasion. There were no significant differences between CD166 expression and clinicopathological parameters. Moreover, the combined analysis demonstrated a reciprocal significant correlation between EpCAM and CD166 expression (P = 0.02). Interestingly, there was a significant positive correlation between EpCAM/CD166 phenotypes expression and tumor stage (P = 0.03), tumor differentiation (P = 0.05), neural, and lymph node invasion (P =0.01).

CONCLUSIONS

The significant correlation of EpCAM and CD166 expression and their association with tumor progression and aggressive behavior is the reason for the suggestion of these two CSC markers as promising targets to promote novel effective targeted-therapy strategies for cancer treatment in the present study.

Alterations in Kynurenine and NAD+ Salvage Pathways during the Successful Treatment of Inflammatory Bowel Disease Suggest HCAR3 and NNMT as Potential Drug Targets

A meta-analysis of publicly available transcriptomic datasets was performed to identify metabolic pathways profoundly implicated in the progression and treatment of inflammatory bowel disease (IBD). The analysis revealed that genes involved in tryptophan (Trp) metabolism are upregulated in Crohn’s disease (CD) and ulcerative colitis (UC) and return to baseline after successful treatment with infliximab. Microarray and mRNAseq profiles from multiple experiments confirmed that enzymes responsible for Trp degradation via the kynurenine pathway (IDO1, KYNU, IL4I1, KMO, and TDO2), receptor of Trp metabolites (HCAR3), and enzymes catalyzing NAD⁺ turnover (NAMPT, NNMT, PARP9, CD38) were synchronously coregulated in IBD, but not in intestinal malignancies. The modeling of Trp metabolite fluxes in IBD indicated that changes in gene expression shifted intestinal Trp metabolism from the synthesis of 5-hydroxytryptamine (5HT, serotonin) towards the kynurenine pathway. Based on pathway modeling, this manifested in a decline in mucosal Trp and elevated kynurenine (Kyn) levels, and fueled the production of downstream metabolites, including quinolinate, a substrate for de novo NAD⁺ synthesis. Interestingly, IBD-dependent alterations in Trp metabolites were normalized in infliximab responders, but not in non-responders. Transcriptomic reconstruction of the NAD⁺ pathway revealed an increased salvage biosynthesis and utilization of NAD⁺ in IBD, which normalized in patients successfully treated with infliximab. Treatment-related changes in NAD⁺ levels correlated with shifts in nicotinamide N-methyltransferase (NNMT) expression. This enzyme helps to maintain a high level of NAD⁺-dependent proinflammatory signaling by removing excess inhibitory nicotinamide (Nam) from the system. Our analysis highlights the prevalent deregulation of kynurenine and NAD⁺ biosynthetic pathways in IBD and gives new impetus for conducting an in-depth examination of uncovered phenomena in clinical studies.