Differentially expressed genes in systemic sclerosis: Towards predictive medicine with new molecular tools for clinicians.

Systemic sclerosis (SSc) is a rare and chronic autoimmune disease characterized by a pathogenic triad of immune dysregulation, vasculopathy, and progressive fibrosis. Clinical tools commonly used to assess patients, including the modified Rodnan skin score, difference between limited or diffuse forms of skin involvement, presence of lung, heart or kidney involvement, or of various autoantibodies, are important prognostic factors, but still fail to reflect the large heterogeneity of the disease. SSc treatment options are diverse, ranging from conventional drugs to autologous hematopoietic stem cell transplantation, and predicting response is challenging. Genome-wide technologies, such as high throughput microarray analyses and RNA sequencing, allow accurate, unbiased, and broad assessment of alterations in expression levels of multiple genes. In recent years, many studies have shown robust changes in the gene expression profiles of SSc patients compared to healthy controls, mainly in skin tissues and peripheral blood cells. The objective analysis of molecular patterns in SSc is a powerful tool that can further classify SSc patients with similar clinical phenotypes and help predict response to therapy. In this review, we describe the journey from the first discovery of differentially expressed genes to the identification of enriched pathways and intrinsic subsets identified in SSc, using machine learning algorithms. Finally, we discuss the use of these new tools to predict the efficacy of various treatments, including stem cell transplantation. We suggest that the use of RNA gene expression-based classifications according to molecular subsets may bring us one step closer to precision medicine in Systemic Sclerosis.

B cell-derived cfDNA after primary BNT162b2 mRNA vaccination anticipates memory B cells and SARS-CoV-2 neutralizing antibodies.

BACKGROUND: Much remains unknown regarding the response of the immune system to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination. METHODS: We employed circulating cell-free DNA (cfDNA) to assess the turnover of specific immune cell types following administration of the Pfizer/BioNTech vaccine. FINDINGS: The levels of B cell cfDNA after the primary dose correlated with development of neutralizing antibodies and memory B cells after the booster, revealing a link between early B cell turnover-potentially reflecting affinity maturation-and later development of effective humoral response. We also observed co-elevation of B cell, T cell, and monocyte cfDNA after the booster, underscoring the involvement of innate immune cell turnover in the development of humoral and cellular adaptive immunity. Actual cell counts remained largely stable following vaccination, other than a previously demonstrated temporary reduction in neutrophil and lymphocyte counts. CONCLUSIONS: Immune cfDNA dynamics reveal the crucial role of the primary SARS-CoV-2 vaccine in shaping responses of the immune system following the booster vaccine. FUNDING: This work was supported by a generous gift from Shlomo Kramer. Supported by grants from Human Islet Research Network (HIRN UC4DK116274 and UC4DK104216 to R.S. and Y.D.), Ernest and Bonnie Beutler Research Program of Excellence in Genomic Medicine, The Alex U Soyka Pancreatic Cancer Fund, The Israel Science Foundation, the Waldholtz/Pakula family, the Robert M. and Marilyn Sternberg Family Charitable Foundation, the Helmsley Charitable Trust, Grail, and the DON Foundation (to Y.D.). Y.D. holds the Walter and Greta Stiel Chair and Research Grant in Heart Studies. I.F.-F. received a fellowship from the Glassman Hebrew University Diabetes Center.

IL-31 induces antitumor immunity in breast carcinoma.

BACKGROUND: Immunomodulatory agents that induce antitumor immunity have great potential for treatment of cancer. We have previously shown that interleukin (IL)-31, a proinflammatory cytokine from the IL-6 family, acts as an antiangiogenic agent. Here, we characterize the immunomodulatory effect of IL-31 in breast cancer. METHODS: In vivo breast carcinoma models including EMT6 and PyMT cell lines were used to analyze the effect of IL-31 on the composition of various immune cells in the tumor microenvironment using high-throughput flow cytometry. In vitro studies using isolated cytotoxic T cells, CD4+ T cells, myeloid-derived suppressor cells (MDSCs) and macrophages were carried out to study IL-31 immunological activity. The generation of recombinant IL-31 bound to IgG backbone was used to test IL-31 therapeutic activity. RESULTS: The growth rate of IL-31-expressing breast carcinomas is decreased in comparison with control tumors due, in part, to antitumor immunomodulation. Specifically, cytotoxic T cell activity is increased, whereas the levels of CD4+ T cells, MDSCs, and tumor-associated macrophages are decreased in IL-31-expressing tumors. These cellular changes are accompanied by a cytokine profile associated with antitumor immunity. In vitro, IL-31 directly inhibits CD4+ Th0 cell proliferation, and the expression of Th2 canonical factors GATA3 and IL-4. It also promotes CD8+ T cell activation through inhibition of MDSC activity and motility. Clinically, in agreement with the mouse data, alterations in immune cell composition in human breast cancer biopsies were found to correlate with high expression of IL-31 receptor A (IL-31Ra) . Furthermore, high coexpression of IL-31Ra, IL-2 and IL-4 in tumors correlates with increased survival. Lastly, to study the therapeutic potential of IL-31, a recombinant murine IL-31 molecule was fused to IgG via a linker region (IL-31-L-IgG). This IL-31-L-IgG therapy demonstrates antitumor therapeutic activity in a murine breast carcinoma model. CONCLUSIONS: Our findings demonstrate that IL-31 induces antitumor immunity, highlighting its potential utility as a therapeutic immunomodulatory agent.