Dataset Information

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

ABSTRACT:

Background

Patients with long-duration ulcerative colitis (UC) had a higher risk of developing ulcerative colitis-associated carcinogenesis (UCAC) when compared to those with short-duration UC. This study aimed to discover the biomarker for cancer surveillance related to disease duration.

Methods

The microarrays were divided into short-duration (<10 years) UC, long-duration (≥10 years) UC, UCAC, and normal groups in the Gene Expression Omnibus (GEO) datasets. Differentially expressed genes (DEGs) of GEO and the hub genes of the selected weighted gene co-expression network analysis (WGCNA) were intersected to obtain the overlapping genes. Among these genes, the key gene was identified by using the protein–protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the cytoHubba of Cytoscape, and the expression levels. Also, immunofluorescence of human colonic mucosa and animal experiment were used to validate the expression trend of the key gene in the progress of UC developing into UCAC.

Results

Lipocalin-2 (LCN2) was more relevant with disease duration of UC and significantly negatively correlated with the risk of UCAC. The expression level of LCN2 in short-duration UC was higher than that of long-duration UC (P < 0.01), long-duration UC was higher than that of UCAC (P = 0.001), and UC and UCAC were all higher than that of the normal (P < 0.001). We then discovered that the expression trend of LCN2 in blood and stool samples was consistent with that in colorectal mucosa.

Conclusion

The research indicates that LCN2 could be a novel biomarker to evaluate cancer surveillance related to disease duration of developing UC into UCAC. Compared with that of blood samples, stool detection of LCN2 may have more advantages for diagnosis value of early stage of UCAC as a complement to colonoscopy surveillance.

SUBMITTER: Kou F

PROVIDER: S-EPMC8801604 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundLongstanding ulcerative colitis (UC) bears a high risk for development of UC-associated colorectal carcinoma (UCC). The inflammatory microenvironment influences microRNA expression, which in turn deregulates target gene expression. microRNA-26b (miR-26b) was shown to be instrumental in normal tissue growth and differentiation. Thus, we aimed to investigate the impact of miR-26b in inflammation-associated colorectal carcinogenesis.MethodsTwo different cohorts of patients were investigated. In the retrospective group, a tissue microarray with 38 samples from 17 UC/UCC patients was used for miR-26b in situ hybridization and quantitative reverse transcription polymerase chain reaction analyses. In the prospective group, we investigated miR-26b expression in 25 fresh-frozen colon biopsies and corresponding serum samples of 6 UC and 15 non-UC patients, respectively. In silico analysis, Ago2-RNA immunoprecipitation, luciferase reporter assay, quantitative reverse transcription polymerase chain reaction examination, and miR-26b mimic overexpression were employed for target validation.ResultsmiR-26b expression was shown to be upregulated with disease progression in tissues and serum of UC and UCC patients. Using miR-26b and Ki-67 expression levels, an UCC was predicted with high accuracy. We identified 4 novel miR-26b targets (DIP1, MDM2, CREBBP, BRCA1). Among them, the downregulation of the E3 ubiquitin ligase DIP1 was closely related to death-associated protein kinase stabilization along the normal mucosa-UC-UCC sequence. In silico functional pathway analysis revealed that the common cellular pathways affected by miR-26b are highly related to cancerogenesis and the development of gastrointestinal diseases.ConclusionsWe suggest that miR-26b could serve as a biomarker for inflammation-associated processes in the gastrointestinal system. Because miR-26b expression is downregulated in sporadic colon cancer, it could discriminate between UCC and the sporadic cancer type.

Project description:To date, no comprehensive analysis of autoantibodies in sera of patients with ulcerative colitis has been conducted. To analyze the spectrum of autoantibodies and to elucidate their role serum-IgG from UC patients (n = 49) and non-UC donors (n = 23) were screened by using a human protein microarray. Screening yielded a remarkable number of 697 differentially-reactive at the nominal 0·01 significance level (FDR<0·1) of the univariate test between the UC and the non-UC group. CD99 emerged as a biomarker to discriminate between both groups (p = 1e-04, AUC = 0·8). In addition, cytokines, chemokines and growth factors were analyzed by Olink's Proseek® Multiplex Inflammation-I 96×96 immuno-qPCR assay and 31 genes were significant at the nominal 0.05 level of the univariate test to discriminate between UC and non-UC donors. MCP-3, HGF and CXCL-9 were identified as the most significant markers to discriminate between UC patients with clinically active and inactive disease. Levels of CXCL10 (cor = 0.3; p = 0.02), CCL25 (cor = 0.25; p = 0.04) and CCL28 (cor = 0.3; p = 0.02) correlated positively with levels of anti CD99. To assess whether autoantibodies are detectable prior to diagnosis with UC, sera from nine donors at two different time points (T-early, median 21 months and T-late, median 6 months) were analyzed. 1201 features were identified with higher reactivity in samples at time points closer to clinical UC presentation. In vitro, additional challenge of peripheral mononuclear cells with CD99 did not activate CD4+ T cells but induced the secretion of IL-10 (-CD99: 20.21±20.25; +CD99: 130.20±89.55; mean ±sd; p = 0.015). To examine the effect of CD99 in vivo, inflammation and autoantibody levels were examined in NOD/ScidIL2Rγnull mice reconstituted with PBMC from UC donors (NSG-UC). Additional challenge with CD99 aggravated disease symptoms and pathological phenotype as indicated by the elevated clinical score (-CD99: 1·85 ± 1·94; +CD99: 4·25 ± 1·48) and histological score (-CD99: 2·16 ± 0·83; +CD99: 3·15 ± 1·16, p = 0·01). Furthermore, levels of anti-CD99 antibodies increased (Control: 398 ± 323; mean MFI ± sd; Ethanol + PBS: 358 ±316; Ethanol + CD99: 1363 ± 1336; Control versus Ethanol + CD99: p = 0.03). In a highly inflammatory environment, frequencies of pro-inflammatory M1 monocytes (CD14+ CD64+: unchallenged 8.09±4.72; challenged 14.2±8.62; p = 0.07; CD14+ CD1a+: unchallenged 16.29 ±6.97; challenged 43.81±14.4, p = 0.0003) increased and levels of autoantibodies in serum decreased in the NSG-UC mouse model. These results suggest that autoantibodies are potent biomarkers to discriminate between UC and non-UC and indicate risk to develop UC. In an inflammatory environment, auto-antibodies may promote the pathological phenotype by activating M1 monocytes in the NSG-UC animal model and also in patients with UC.

Project description:BackgroundUlcerative 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.MethodsGene 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.ResultsGene 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.ConclusionsThe 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.

Project description:Nonresolving inflammation is correlated to carcinogenesis. Ulcerative colitis-associated colorectal cancer (UC-CRC), one of the typical carcinoma generated by inflammation that cannot be resolved properly, has been widely believed to involve a multistep process contains M-bM-^@M-^\inflammation-dysplasia-cancerM-bM-^@M-^] sequence. The exact molecular mechanisms underlying the step-wise development of UC-CRC is still not fully understood. Detecting the changes in gene expression profiles may help to reveal why and how does the prolonged inflammatory response lead to carcinogenesis, and to characterize potential diagnostic/prognostic markers or additional therapeutic targets for UC-CRC. There for, we performed temporal genome expression profiling analysis using the Affymetrix genome wide microarray system to identify broad scale changes in gene expression associated with the development of colitis-associated cancer, based on an AOM/DSS induced mouse model of UC-CRC. 6-week-old male ICR mice were given a single intraperitoneal injection of AOM (10mg/kg) at Day 1, followed by three cycles of DSS administration (cycle 1: 2%, Day 8~14; cycle 2: 1.5%, Day 29~33; cycle 3: 1.5%, Day 50~54) in the drinking water. Instead, control group of mice were given a single intraperitoneal injection of saline (10mg/kg) at Day 1 and distilled water drinking from the beginning to the end without DSS. Colorectal tissues were collected at days 14, 28, 42, 56 and 140 (at the end of the 2nd, 4th, 6th, 8th and 20th week) from the AOM/DSS group and at day 14 from the control group. Pathological changes of each sample were identified under microscope. Samples collected at the end of the 2nd week were inflamed mucosae, the 4th week were low grade dysplasias, the 6th week were high grade dysplasias, the 8th week were high grade dysplasias with active inflammation, the 20th week were carcinomas, and the control sample were normal mucosae. Total RNA were extracted and detected by Affymerix GeneChip Mouse Genome 430 2.0 Array.