Discordant effects of Janus kinases inhibition ex-vivo on inflammatory responses in colonic compared to ileal mucosa.

BACKGROUND & AIMS: Janus kinase (JAK) inhibitors are used for treating inflammatory bowel diseases (IBD). We aimed to identify molecular effects of JAK inhibition in human intestinal mucosa, considering IBD location and phenotype. METHODS: Colonic and ileal explants from patients with ulcerative colitis (UC), Crohn's disease (CD), and non-IBD controls (NC) were assessed for phosphorylated signal transducers and activators of transcription (p-STAT) levels and Inflammatory genes expression panel in response to ex-vivo JAK inhibitor (tofacitinib). Cytokine production by lamina propria lymphocytes in response to tofacitinib was assessed. Human intestinal organoids were used to investigate JAK inhibitors' effects on iNOS expression. RESULTS: Explants were collected from 68 patients (UC=20; CD=20; NC=28). p-STAT1\3\5 inhibition rates varied, being higher in colonic compared to ileal explants. p-STAT1\3 inhibition rates negatively correlated with CRP levels. While significant alterations in 120 of 255 inflammatory genes were observed in colonic explants, only 30 were observed in ileal NC explants. In colonic explants from UC, significant alterations were observed in 5 genes, including NOS2. JAK inhibition significantly decreased Th1\Th2\Th17-related cytokine production from lamina propria lymphocytes. Various JAK inhibitors reduced IFN-γ-induced increase in iNOS expression in organoids. CONCLUSIONS: Site-specific anti-inflammatory effect of JAK inhibition by tofacitinib was noticed, whereby the colon was more robustly affected than the ileum. Ex-vivo response to tofacitinib is individual. JAK inhibition may attenuate inflammation by decreasing iNOS expression. Ex-vivo mucosal platforms may be a valuable resource for studying personalized drug effects in patients with IBD.

B cell M-CLL clones retain selection against replacement mutations in their immunoglobulin gene framework regions.

Introduction: Chronic lymphocytic leukemia (CLL) is the most common adult leukemia, accounting for 30-40% of all adult leukemias. The dynamics of B-lymphocyte CLL clones with mutated immunoglobulin heavy chain variable region (IgHV) genes in their tumor (M-CLL) can be studied using mutational lineage trees. Methods: Here, we used lineage tree-based analyses of somatic hypermutation (SHM) and selection in M-CLL clones, comparing the dominant (presumably malignant) clones of 15 CLL patients to their non-dominant (presumably normal) B cell clones, and to those of healthy control repertoires. This type of analysis, which was never previously published in CLL, yielded the following novel insights. Results: CLL dominant clones undergo - or retain - more replacement mutations that alter amino acid properties such as charge or hydropathy. Although, as expected, CLL dominant clones undergo weaker selection for replacement mutations in the complementarity determining regions (CDRs) and against replacement mutations in the framework regions (FWRs) than non-dominant clones in the same patients or normal B cell clones in healthy controls, they surprisingly retain some of the latter selection in their FWRs. Finally, using machine learning, we show that even the non-dominant clones in CLL patients differ from healthy control clones in various features, most notably their expression of higher fractions of transition mutations. Discussion: Overall, CLL seems to be characterized by significant loosening - but not a complete loss - of the selection forces operating on B cell clones, and possibly also by changes in SHM mechanisms.

IgTreeZ, A Toolkit for Immunoglobulin Gene Lineage Tree-Based Analysis, Reveals CDR3s Are Crucial for Selection Analysis.

Somatic hypermutation (SHM) is an important diversification mechanism that plays a part in the creation of immune memory. Immunoglobulin (Ig) variable region gene lineage trees were used over the last four decades to model SHM and the selection mechanisms operating on B cell clones. We hereby present IgTreeZ (Immunoglobulin Tree analyZer), a python-based tool that analyses many aspects of Ig gene lineage trees and their repertoires. Using simulations, we show that IgTreeZ can be reliably used for mutation and selection analyses. We used IgTreeZ on empirical data, found evidence for different mutation patterns in different B cell subpopulations, and gained insights into antigen-driven selection in corona virus disease 19 (COVID-19) patients. Most importantly, we show that including the CDR3 regions in selection analyses - which is only possible if these analyses are lineage tree-based - is crucial for obtaining correct results. Overall, we present a comprehensive lineage tree analysis tool that can reveal new biological insights into B cell repertoire dynamics.