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      Intestinal mRNA expression profiles associated with mucosal healing in ustekinumab-treated Crohn's disease patients: bioinformatics analysis and prospective cohort validation

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          Abstract

          Background

          Variations exist in the response of patients with Crohn’s disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD.

          Methods

          The GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset.

          Results

          A total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers.

          Conclusions

          Th1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients.

          Trial registration: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.clinicaltrials.gov.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12967-024-05427-w.

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          Most cited references49

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          GSVA: gene set variation analysis for microarray and RNA-Seq data

          Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.
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            Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer.

            The complex interactions between tumors and their microenvironment remain to be elucidated. Combining large-scale approaches, we examined the spatio-temporal dynamics of 28 different immune cell types (immunome) infiltrating tumors. We found that the immune infiltrate composition changed at each tumor stage and that particular cells had a major impact on survival. Densities of T follicular helper (Tfh) cells and innate cells increased, whereas most T cell densities decreased along with tumor progression. The number of B cells, which are key players in the core immune network and are associated with prolonged survival, increased at a late stage and showed a dual effect on recurrence and tumor progression. The immune control relevance was demonstrated in three endoscopic orthotopic colon-cancer mouse models. Genomic instability of the chemokine CXCL13 was a mechanism associated with Tfh and B cell infiltration. CXCL13 and IL21 were pivotal factors for the Tfh/B cell axis correlating with survival. This integrative study reveals the immune landscape in human colorectal cancer and the major hallmarks of the microenvironment associated with tumor progression and recurrence. Copyright © 2013 Elsevier Inc. All rights reserved.
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              STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) Initiative of the International Organization for the Study of IBD (IOIBD): Determining Therapeutic Goals for Treat-to-Target strategies in IBD

              The Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) initiative of the International Organization for the Study of Inflammatory Bowel Diseases (IOIBD) has proposed treatment targets in 2015 for adult patients with inflammatory bowel disease (IBD). We aimed to update the original STRIDE statements for incorporating treatment targets in both adult and pediatric IBD.
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                Author and article information

                Contributors
                gxiang@mail.sysu.edu.cn
                chaokang3@mail.sysu.edu.cn
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                26 June 2024
                26 June 2024
                2024
                : 22
                : 595
                Affiliations
                [1 ]Department of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-Sen University, ( https://ror.org/0064kty71) No.26 Yuancun Road II, Tianhe District, Guangzhou, 510000 People’s Republic of China
                [2 ]Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, the Sixth Affiliated Hospital, Sun Yat-Sen University, ( https://ror.org/0064kty71) Guangzhou, People’s Republic of China
                [3 ]Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, ( https://ror.org/0064kty71) Guangzhou, People’s Republic of China
                [4 ]GRID grid.12981.33, ISNI 0000 0001 2360 039X, Key Laboratory of Human Microbiome and Chronic Diseases, Ministry of Education, , Sun Yat-Sen University, ; Guangzhou, People’s Republic of China
                [5 ]Biomedical Innovation Centre, The Sixth Affiliated Hospital, Sun Yat-Sen University, ( https://ror.org/0064kty71) Guangzhou, People’s Republic of China
                Author information
                http://orcid.org/0000-0003-2342-0422
                Article
                5427
                10.1186/s12967-024-05427-w
                11210135
                38926732
                c4667c25-3d88-456f-acd6-65b1d3f399b6
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 20 March 2024
                : 18 June 2024
                Funding
                Funded by: the Sixth Affiliated Hospital of Sun Yat-Sen University
                Award ID: 2022JBGS05
                Award ID: 2022JBGS03
                Funded by: the program of Guangdong Provincial Clinical Research Center for Digestive Diseases
                Award ID: 2020B1111170004
                Funded by: the Sixth Affiliated Hospital of Sun Yat-Sen University Clinical Research-'1010' Program
                Award ID: 1010CG(2023)-12
                Award Recipient :
                Categories
                Research
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                © BioMed Central Ltd., part of Springer Nature 2024

                Medicine
                crohn's disease,ustekinumab,lasso regression,kdm5d,lcn2
                Medicine
                crohn's disease, ustekinumab, lasso regression, kdm5d, lcn2

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