2.1 Data Collection: All datasets included in our study were downloaded and collected from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). GEO is one of the largest public databases which included microarray data and high-throughput gene expression data submitted by research institutions around the world. To collect the data on the ineffectiveness of infliximab treatment for Crohn's disease, the keywords “Crohn’s disease” and “infliximab” were searched, and finally, the datasets “GSE52746” were included in our study. The database contains a total of 36 patients with CD, of which 19 patients were infliximab responders and 17 patients were infliximab non-responders[18].
2.2 Differential Genes Analysis: The differential expressed genes (DEGs) from “GSE52746” were identified using the “Limma” R package. The parameters |Log2FC| > 0.5 and adj. P < 0.05 were used as the screening criteria for DEGs[21]. Volcano plot and heatmap of DEGs from the “GSE52746” were constructed using “ComplexHeatmap” and “ggplot2” R packages.
2.3 Principal Component Analysis: To investigate whether gene expression differs between the infliximab effective and infliximab ineffective groups, the Principal Component Analysis (PCA) was performed using the R package “FactoMineR”. Next, the R package “FactoExtra” was used to visualize the PCA results.
2.4 Immune Infiltration Analysis: The online platform CIBERSORTx (https://cibersortx.stanford.edu/) was used to perform the immune infiltration analysis and then the immune infiltration matrix generated from CIBERSORTx was imported into R software for visualization by using the R package “ggplot2”. The differences between the two groups were compared by using the Wilcoxon test and the correlation between the 22 infiltrating immune cells and key genes and immune cells were visualized.
2.5 Functional Enrichment Analysis: Functional enrichment analysis was performed to explore the biological functions and pathways involved in the genes we identified. The top ten biological process (BP) from gene ontology (GO) were used to describe functions. The pathway results were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases[22, 23]. Clustering Heatmap, network map and chordal graph were used to describe the enrichment between differential genes and functions as well as pathways. R packages “enrichplot” and “clusterProfiler” were used to perform the GO and KEGG analysis and visualization.
2.6 Patients and Sample Collection: All the patients included in this study were admitted to the Department of Gastroenterology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China. CD diagnosis was followed by the guidelines from 3rd European Evidence-based Consensus [24]. The intestinal biopsy specimens from 11 CD patients with infliximab-responders and 13 infliximab non-responders were collected. Among them, the tissues from 6 responders and 8 non-responders were detected CCL2 and CCR2 mRNA expression. Ten samples were used to examine the infiltration degree of CD68+ macrophage[18]. Primary non-response (PNR) to infliximab was defined as exit before week 14 because of treatment failure (including resectional CD-related surgery) or corticosteroid use at week 14 (new prescriptions or if previous dose had not been stopped). Patients whose CRP did not decrease to 3 mg/L or less or by 50% or more from baseline (week 0), and whose SES-CD did not decrease to 4 points or more from baseline, were also classified as having primary non-response[4].
This study was approved by the Review Boards for Clinical Research from Shanghai Tenth People's Hospital (SHSY-IEC-4.1/20–152/01) and performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
2.7. RNA Isolation and Quantitative real-time PCR: Trizol reagent (T9424, sigma) was used for RNA extraction and PrimeScript RT Master Mix (RR036A, Takara) for cDNA generation. Gene expression was determined with Hieff® qPCR SYBR® Green Master Mix (Low Rox Plus) (11202ES08, YEASEN) utilizing the QuantStudio Dx and analyzed using the delta delta Ct method. The primer sequences are: forward primer: TCCTGGTGGGCTACAAATTAC and reverse primer: ACAGCAGATCCATGGCAT
AATA for GAPDH; forward primer: TCATAGCAGCCA CCTTCATT C and reverse
primer: CTCTGCACTGA GATCTTCCTATTG for CCL2. Forward primer: TCATAG
CAGCCACCTTCATTC and reverse primer: CTCTGCACTGAGATCTTCCTATTG for CCR2.
2.8. Immunohistochemistry staining: Immunohistochemical staining were performed as described previously. All samples were fixed in 4% paraformaldehyde and embedded in paraffin. Each paraffin block was cut into 5-µm sections. After rehydration with 80% methanol, PBS and PBS with 12% bovine serum albumin (BSA), the sections were incubated with CD68 monoclonal antibody (1:2000, 66231-2-Ig, Proteintech) overnight at 4°C. Then, those sections were washed with TBS-Tween and incubated with secondary antibodies. The positively stained cells and collagen/area ratio were counted in five randomly selected fields at a magnification of 200× using ImageJ software (National Institutes of Health, Bethesda, MD, USA).
2.9 Statistical Analysis: Continuous variables were presented as mean ± standard deviation and were evaluated by independent Student’s t-test for normally distributed variables and by Wilcoxon rank-sum test for non-normally distributed data. GraphPad Prism version 8.0.1 (GraphPad Software San Diego, United States) and R software version 4.1.1 (R Foundation for Statistical Computing, Vienna, Austria) were used to run the statistical analyses. All p-values below 0.05 were deemed statistically significant.