Cell-Based Models of 'Cytokine Release Syndrome' Endorse CD40L and Granulocyte-Macrophage Colony-Stimulating Factor Knockout in Chimeric Antigen Receptor T Cells as Mitigation Strategy.

While chimeric antigen receptor (CAR) T cell therapy has shown promising outcomes among patients with hematologic malignancies, it has also been associated with undesirable side-effects such as cytokine release syndrome (CRS). CRS is triggered by CAR T-cell-based activation of monocytes, which are stimulated via the CD40L-CD40R axis or via uptake of GM-CSF to secrete proinflammatory cytokines. Mouse models have been used to model CRS, but working with them is labor-intensive and they are not amenable to screening approaches. To overcome this challenge, we established two simple cell-based CRS in vitro models that entail the co-culturing of leukemic B cells with CD19-targeting CAR T cells and primary monocytes from the same donor. Upon antigen encounter, CAR T cells upregulated CD40L and released GM-CSF which in turn stimulated the monocytes to secrete IL-6. To endorse these models, we demonstrated that neutralizing antibodies or genetic disruption of the CD40L and/or CSF2 loci in CAR T cells using CRISPR-Cas technology significantly reduced IL-6 secretion by bystander monocytes without affecting the cytolytic activity of the engineered lymphocytes in vitro. Overall, our cell-based models were able to recapitulate CRS in vitro, allowing us to validate mitigation strategies based on antibodies or genome editing.

Tumor-specific overexpression of histone gene, H3C14 in gastric cancer is mediated through EGFR-FOXC1 axis.

Incorporation of different H3 histone isoforms/variants have been reported to differentially regulate gene expression via alteration in chromatin organization during diverse cellular processes. However, the differential expression of highly conserved histone H3.2 genes, H3C14 and H3C13 in human cancer has not been delineated. In this study, we investigated the expression of H3.2 genes in primary human gastric, brain, breast, colon, liver, and head and neck cancer tissues and tumor cell lines. The data showed overexpression of H3.2 transcripts in tumor samples and cell lines with respect to normal counterparts. Furthermore, TCGA data of individual and TCGA PANCAN cohort also showed significant up-regulation of H3.2 genes. Further, overexpressed H3C14 gene coding for H3.2 protein was regulated by FOXC1 transcription factor and G4-cassette in gastric cancer cell lines. Elevated expression of FOXC1 protein and transcripts were also observed in human gastric cancer samples and cell lines. Further, FOXC1 protein was predominantly localized in the nuclei of neoplastic gastric cells compared to normal counterpart. In continuation, studies with EGF induction, FOXC1 knockdown, and ChIP-qPCR for the first time identified a novel axis, EGFR-FOXC1-H3C14 for regulation of H3C14 gene overexpression in gastric cancer. Therefore, the changes the epigenomic landscape due to incorporation of differential expression H3 variant contributes to change in gene expression pattern and thereby contributing to pathogenesis of cancer.

Time-in-range as a target in type 2 diabetes: An urgent need.

Time-in-range emerged as a valuable blood glucose metric, 'beyond HbA1c' for a deeper insight into glycemic control in people with diabetes. It denotes the proportion of time that a person's glucose level remains within the desired target range (usually 70-180 mg/dL or 3.9-10.0 mmol/L). Though clinical targets in the current recommendations for type 1 and type 2 diabetes are close enough, their clinical profiles and prevalences are quite different. Type 2 diabetes is the commonest form of diabetes. Many clinical trials have challenged the usefulness of HbA1c as a glycemic target for Type 2 diabetes mellitus. On account of the higher prevalence and complications of type 2 diabetes, more outcomes-based studies are needed to associate time-in-range with its ongoing risk. These studies strongly support the dependability of time-in-range to identify patients with elevated risk in type 2 diabetes. We discuss the utility of time-in-range, a new metric of continuous glucose monitoring as an outcome measure to correlate with type 2 diabetes risks and complications and to analyze the effectiveness of type 2 diabetes management. This approach may support the use of time-in-range as a metric for long-term health outcomes in the type 2 diabetes population.