A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease

Sakaram, Suraj; Hasin-Brumshtein, Yehudit; Khatri, Purvesh; He, Yudong; Sweeney, Timothy E.

doi:10.3390/diagnostics11101902

Cited by 3 publications

(1 citation statement)

References 51 publications

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“…IBD is a complex disease, and those signatures may offer a complete vision of the putative predicting factors. Recently, it was reported seven-gene and 13-gene signatures capable of discriminating anti-TNF responders from non-responders with high accuracy in several mucosal biopsy datasets [65,66]. In the same way, an even larger signature displayed an 87% accuracy [67], demonstrating the use of transcriptional groups could improve prediction effectiveness.…”

Section: Transcriptomic-derived Data Is Boosting Predictive and Perso...mentioning

confidence: 99%

Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populations

Arosa,

Camba-Gómez,

Golubnitschaja

et al. 2024

EPMA Journal

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Inflammatory bowel disease (IBD) is a global health burden which carries lifelong morbidity affecting all age groups in populations with the disease-specific peak of the age groups ranging between 15 and 35 years, which are of great economic importance for the society. An accelerating incidence of IBD is reported for newly industrialised countries, whereas stabilising incidence but increasing prevalence is typical for countries with a Westernised lifestyle, such as the European area and the USA. Although the aetiology of IBD is largely unknown, the interplay between the genetic, environmental, immunological, and microbial components is decisive for the disease manifestation, course, severity and individual outcomes. Contextually, the creation of an individualised patient profile is crucial for the cost-effective disease management in primary and secondary care of IBD. The proposed pathomechanisms include intestinal pathoflora and dysbiosis, chronic inflammation and mitochondrial impairments, amongst others, which collectively may reveal individual molecular signatures defining IBD subtypes and leading to clinical phenotypes, patient stratification and cost-effective protection against health-to-disease transition and treatments tailored to individualised patient profiles—all the pillars of an advanced 3PM approach. The paradigm change from reactive medical services to predictive diagnostics, cost-effective targeted prevention and treatments tailored to individualised patient profiles in overall IBD management holds a promise to meet patient needs in primary and secondary care, to increase the life-quality of affected individuals and to improve health economy in the area of IBD management. This article analyses current achievements and provides the roadmap for future developments in the area in the context of 3P medicine benefiting society at large.

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Section: Transcriptomic-derived Data Is Boosting Predictive and Perso...mentioning

confidence: 99%

Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populations

Arosa,

Camba-Gómez,

Golubnitschaja

et al. 2024

EPMA Journal

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Prediction of anti-TNF therapy failure in ulcerative colitis patients by ensemble machine learning: A prospective study

Derakhshan Nazari,

Shahrokh,

Ghanbari-Maman

et al. 2023

Heliyon

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Novel mRNA Signature for Anti-TNF-α Therapy Primary Response in Patients With Ulcerative Colitis

Yang

Shi

Wang

et al. 2023

Inflammatory Bowel Diseases

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Background Ulcerative colitis (UC), an idiopathic, chronic inflammatory disorder of the colonic mucosa, is commonly treated with antitumor necrosis factor α (anti-TNF-α) agents. However, only approximately two-thirds have an initial response to these therapies. Methods We integrated gene expression profiling from 3 independent data sets of 79 UC patients before they began anti-TNF-α therapy and calculated the differentially expressed genes between patient response and nonresponse to anti-TNF-α therapy and developed a de novo response-associated transcription signature score (logOR_Score) to demonstrate the predictive capability of anti-TNF-α therapy for therapeutic efficacy. Furthermore, we performed association analysis of the logOR_Score and clinical features, such as disease activity and immune microenvironment. Results A total of 2522 responsive and 1824 nonresponsive genes were identified from the integrated data set. Responsive genes were significantly enriched in metabolism-related pathways, whereas nonresponsive ones were associated with immune response–related pathways. The logOR_Score enabled the accurate prediction of the therapeutic efficacy of anti-TNF-α in 4 independent patient cohorts and outperformed the predictions made based on 6 transcriptome-based signatures. In terms of clinical features, the logOR_Score correlated highly with the activity of UC. From an immune microenvironment perspective, logOR_Scores of CD8+ IL-17+ T cells, follicular B cells, and innate lymphoid cells significantly decreased in inflamed UC tissue. Conclusions The de novo response-associated transcription signature may provide novel insights into the personalized treatment of patients with UC. Comprehensive analyses of the response-related subtypes and the association between logOR_Score and clinical features and immune microenvironment may provide insights into the underlying UC pathogenesis.

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A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease

Cited by 3 publications

References 51 publications

Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populations

Predictive, preventive and personalised approach as a conceptual and technological innovation in primary and secondary care of inflammatory bowel disease benefiting affected individuals and populations

Prediction of anti-TNF therapy failure in ulcerative colitis patients by ensemble machine learning: A prospective study

Novel mRNA Signature for Anti-TNF-α Therapy Primary Response in Patients With Ulcerative Colitis

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