Macrophage migration inhibitory factor (MIF): A multifaceted cytokine regulated by genetic and physiological strategies

Sumaiya, Krishnamoorthi; Langford, Dianne; Natarajaseenivasan, Kalimuthusamy; Shanmughapriya, Santhanam

doi:10.1016/j.pharmthera.2021.108024

Cited by 98 publications

(86 citation statements)

References 219 publications

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“…Surg. 26 (2), 305-313. doi:10.1007/ s11605-021-05101-2 Wallace, D., Figueras, F., Wegener, W., and Goldenberg, D. (2021). Experience with milatuzumab, an anti-CD74 antibody against immunomodulatory macrophage migration inhibitory factor (MIF) receptor, for systemic lupus erythematosus (SLE).…”

Section: Data Availability Statementmentioning

confidence: 99%

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Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

et al. 2022

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Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.

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Section: Data Availability Statementmentioning

confidence: 99%

“…Genome Res. 30 (2), 205-213. doi:10.1101/gr.254557.119 Wang, B., Zhang, Y., Qing, T., Xing, K., Li, J., Zhen, T., et al (2021). Comprehensive analysis of metastatic gastric cancer tumour cells using singlecell RNA-seq.…”

Section: Data Availability Statementmentioning

confidence: 99%

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

et al. 2022

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“…The SELPLG and MIF signalling pathways play important roles in immune cell activation and migration 44,45 . Here, CellChat predicted that the SELPLG and MIF signalling pathways were downregulated during pregnancy (Figure S5C and D).…”

Section: Resultsmentioning

confidence: 90%

Single‐cell atlas of peripheral blood mononuclear cells from pregnant women

Chen

Wang

et al. 2022

Clinical & Translational Med

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Background During pregnancy, mother–child interactions trigger a variety of subtle changes in the maternal body, which may be reflected in the status of peripheral blood mononuclear cells (PBMCs). Although these cells are easy to access and monitor, a PBMC atlas for pregnant women has not yet been constructed. Methods We applied single‐cell RNA sequencing (scRNA‐seq) to profile 198,356 PBMCs derived from 136 pregnant women (gestation weeks 6 to 40) and a control cohort. We also used scRNA‐seq data to establish a transcriptomic clock and thereby predicted the gestational age of normal pregnancy. Results We identified reconfiguration of the peripheral immune cell phenotype during pregnancy, including interferon‐stimulated gene upregulation, activation of RNA splicing‐related pathways and immune activity of cell subpopulations. We also developed a cell‐type‐specific model to predict gestational age of normal pregnancy. Conclusions We constructed a single‐cell atlas of PBMCs in pregnant women spanning the entire gestation period, which should help improve our understanding of PBMC composition turnover in pregnant women.

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“…In this study, MIF was the last marker included in the models. MIF is a multipotent cytokine expressed by various cell types and tissues, e.g., cells of the immune and nervous systems, epithelial, endothelial, smooth muscle, and mesenchymal cells [ 57 ]. MIF mediates host innate and adaptive immunity and regulates survival pathways, important for pathogen elimination during infectious disease.…”

Section: Discussionmentioning

confidence: 99%

“…MIF mediates host innate and adaptive immunity and regulates survival pathways, important for pathogen elimination during infectious disease. As an immunomodulator, MIF accelerates inflammation, promotes metastasis and cancer progression [ 57 ]. MIF is abundant in borderline and malignant ovarian tumors.…”

Section: Discussionmentioning

confidence: 99%

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study

Watrowski

Obermayr

Wallisch

et al. 2022

Cancers

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Ovarian cancer (OC) is the most lethal genital malignancy in women. We aimed to develop and validate new proteomic-based models for non-invasive diagnosis of OC. We also compared them to the modified Risk of Ovarian Malignancy Algorithm (ROMA-50), the Copenhagen Index (CPH-I) and our earlier Proteomic Model 2017. Biomarkers were assessed using bead-based multiplex technology (Luminex®) in 356 women (250 with malignant and 106 with benign ovarian tumors) from five European centers. The training cohort included 279 women from three centers, and the validation cohort 77 women from two other centers. Of six previously studied serum proteins (CA125, HE4, osteopontin [OPN], prolactin, leptin, and macrophage migration inhibitory factor [MIF]), four contributed significantly to the Proteomic Model 2021 (CA125, OPN, prolactin, MIF), while leptin and HE4 were omitted by the algorithm. The Proteomic Model 2021 revealed a c-index of 0.98 (95% CI 0.96, 0.99) in the training cohort; however, in the validation cohort it only achieved a c-index of 0.82 (95% CI 0.72, 0.91). Adding patient age to the Proteomic Model 2021 constituted the Combined Model 2021, with a c-index of 0.99 (95% CI 0.97, 1) in the training cohort and a c-index of 0.86 (95% CI 0.78, 0.95) in the validation cohort. The Full Combined Model 2021 (all six proteins with age) yielded a c-index of 0.98 (95% CI 0.97, 0.99) in the training cohort and a c-index of 0.89 (95% CI 0.81, 0.97) in the validation cohort. The validation of our previous Proteomic Model 2017, as well as the ROMA-50 and CPH-I revealed a c-index of 0.9 (95% CI 0.82, 0.97), 0.54 (95% CI 0.38, 0.69) and 0.92 (95% CI 0.85, 0.98), respectively. In postmenopausal women, the three newly developed models all achieved a specificity of 1.00, a positive predictive value (PPV) of 1.00, and a sensitivity of >0.9. Performance in women under 50 years of age (c-index below 0.6) or with normal CA125 (c-index close to 0.5) was poor. CA125 and OPN had the best discriminating power as single markers. In summary, the CPH-I, the two combined 2021 Models, and the Proteomic Model 2017 showed satisfactory diagnostic accuracies, with no clear superiority of either model. Notably, although combining values of only four proteins with age, the Combined Model 2021 performed comparably to the Full Combined Model 2021. The models confirmed their exceptional diagnostic performance in women aged ≥50. All models outperformed the ROMA-50.

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Macrophage migration inhibitory factor (MIF): A multifaceted cytokine regulated by genetic and physiological strategies

Cited by 98 publications

References 219 publications

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Single‐cell atlas of peripheral blood mononuclear cells from pregnant women

Biomarker-Based Models for Preoperative Assessment of Adnexal Mass: A Multicenter Validation Study

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