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Proteomic Analysis of Potential Targets for Non-Response to Infliximab in Patients With Ulcerative Colitis.

ABSTRACT: Background: Infliximab (IFX) is a potent therapeutic agent used for the treatment of conventional refractory ulcerative colitis (UC). However, the high non-response rate of IFX brings difficulties to clinical applications. In the context of proteomics research, our study of differentially expressed proteins (DEPs) is essential for non-response to IFX in UC patients and provides powerful insights into underlying drug resistance mechanisms. Methods: A total of 12 UC patients were divided into responders to IFX (UCinfG), non-responders to IFX (UCinfL), severe UC (UCsevere) without an IFX treatment history, and mild UC (UCmild) without an IFX treatment history. Subsequently, DEPs were identified from intestinal biopsy tissue between responders and non-responders to IFX by a label-free proteomic quantitative approach, and the general principle of functional protein screening was followed to deduce the potential drug targets and predictors for non-response to IFX in UC patients. Meanwhile, these targets excluded DEPs caused by the severity of inflammation for the first time. The differential expressions of candidate protein targets were validated at the gene sequence level using GEO2R analysis of the GEO database and qRT-PCR in some independent cohorts. Results: A total of 257 DEPs were screened out by mass spectrometry between UCinfG and UCinfL groups, excluding 22 DEPs caused by the severity of inflammation, and compared and verified at the gene sequence level in the Gene Expression Omnibus (GEO) database. Finally, five DEPs, including ACTBL2 (Q562R1), MBL2 (P11226), BPI (P17213), EIF3D (O15371), and CR1 (P17927), were identified as novel drug targets and predictive biomarkers for non-response to IFX. The drug targets were confirmed in the GEO database of the microarray results from three independent cohorts of 70 human intestinal biopsies and validated in qPCR data from 17 colonic mucosal biopsies. Among them, CR1 might affect the activation of the lectin pathway via complement-coated bacteria to play an opsonizing role in inflammation-related pathways closely associated with non-responders to IFX. Conclusion: This is the first report of proteomics analysis for the identification of novel drug targets based on intestinal biopsy tissue, which is significant for hypotheses for mechanistic investigation that are responsible for non-response to IFX and the development of clinical new pharmaceutical drugs.

SUBMITTER: Liu L

PROVIDER: S-EPMC9234463 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to IFX. Our study analyzed three Gene Expression Omnibus (GEO) datasets and used the RobustRankAggreg (RRA) algorithm to assist in identifying differentially expressed genes (DEGs) between IFX responders and non-responders. Then, an artificial intelligence (AI) technology, artificial neural network (ANN) analysis, was applied to validate the predictive value of the selected genes. The results showed that the combination of CDX2, CHP2, HSD11B2, RANK, NOX4, and VDR is a good predictor of patients' response to IFX therapy. The range of repeated overall area under the receiver-operating characteristic curve (AUC) was 0.850 ± 0.103. Moreover, we used an independent GEO dataset to further verify the value of the six DEGs in predicting PNR to IFX, which has a range of overall AUC of 0.759 ± 0.065. Since protein detection did not require fresh tissue and can avoid multiple biopsies, our study tried to discover whether the key information, analyzed by RNA levels, is suitable for protein detection. Therefore, immunohistochemistry (IHC) staining of colonic biopsy tissues from UC patients treated with IFX and a receiver-operating characteristic (ROC) analysis were used to further explore the clinical application value of the six DEGs at the protein level. The IHC staining of colon tissues from UC patients confirmed that VDR and RANK are significantly associated with IFX efficacy. Total IHC scores lower than 5 for VDR and lower than 7 for RANK had an AUC of 0.828 (95% CI: 0.665-0.991, p = 0.013) in predicting PNR to IFX. Collectively, we identified a predictive RNA model for PNR to IFX and explored an immune-related protein model based on the RNA model, including VDR and RANK, as a predictor of IFX non-response, and determined the cutoff value. The result showed a connection between the RNA and protein model, and both two models were available. However, the composite signature of VDR and RANK is more conducive to clinical application, which could be used to guide the preselection of patients who might benefit from pharmacological treatment in the future.

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Proteomic Analysis of Potential Targets for Non-Response to Infliximab in Patients With Ulcerative Colitis.

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