A single center case series of immune checkpoint inhibitor-induced type 1 diabetes mellitus, patterns of disease onset and long-term clinical outcome

BackgroundType 1 diabetes mellitus (T1DM) is a rare, but serious immune-related adverse event (irAE) of immune checkpoint inhibitors (ICIs). Our goal was to characterize treatment outcomes associated with ICI-induced T1DM through analysis of clinical, immunological and proteomic data.MethodsThis was a single-center case series of patients with solid tumors who received ICIs and subsequently had a new diagnosis of T1DM. ICD codes and C-peptide levels were used to identify patients for chart review to confirm ICI-induced T1DM. Baseline blood specimens were studied for proteomic and immunophenotypic changes.ResultsBetween 2011 and 2023, 18 of 3744 patients treated at Huntsman Cancer Institute with ICIs were confirmed to have ICI-induced T1DM (0.48%). Eleven of the 18 patients received anti-PD1 monotherapy, 4 received anti-PD1 plus chemotherapy or targeted therapy, and 3 received ipilimumab plus nivolumab. The mean time to onset was 218 days (range 22-418 days). Patients had sudden elevated serum glucose within 2-3 weeks prior to diagnosis. Sixteen (89%) presented with diabetic ketoacidosis. Three of 12 patients had positive T1DM-associated autoantibodies. All patients with T1DM became insulin-dependent through follow-up. At median follow-up of 21.9 months (range 8.4-82.4), no patients in the melanoma group had progressed or died from disease. In the melanoma group, best responses were 2 complete response and 2 partial response while on active treatment; none in the adjuvant group had disease recurrence. Proteomic analysis of baseline blood suggested low inflammatory (IL-6, OSMR) markers and high metabolic (GLO1, DXCR) markers in ICI-induced T1DM cohort.ConclusionsOur case series demonstrates rapid onset and irreversibility of ICI-induced T1DM. Melanoma patients with ICI-induced T1DM display excellent clinical response and survival. Limited proteomic data also suggested a unique proteomic profile. Our study helps clinicians to understand the unique clinical presentation and long-term outcomes of this rare irAE for best clinical management

Characterization of DNA Methylomic signatures in induced pluripotent stem cells during neuronal differentiation

In development, differentiation from a pluripotent state results in global epigenetic changes, although the extent to which this occurs in induced pluripotent stem cell based neuronal models has not been extensively characterized. In the present study, induced pluripotent stem cell colonies (33Qn1 line) were differentiated and collected at four time-points, with DNA methylation assessed using the Illumina Infinium Human Methylation EPIC BeadChip array. Dynamic changes in DNA methylation occurring during differentiation were investigated using a data-driven trajectory inference method. We identified a large number of Bonferroni-significant loci that showed progressive alterations in DNA methylation during neuronal differentiation. A gene-gene interaction network analysis identified 60 densely connected genes that were influential in the differentiation of neurons, with STAT3 being the gene with the highest connectivity

Characterization of DNA Methylomic Signatures in Induced Pluripotent Stem Cells During Neuronal Differentiation

In development, differentiation from a pluripotent state results in global epigenetic changes, although the extent to which this occurs in induced pluripotent stem cell-based neuronal models has not been extensively characterized. In the present study, induced pluripotent stem cell colonies (33Qn1 line) were differentiated and collected at four time-points, with DNA methylation assessed using the Illumina Infinium Human Methylation EPIC BeadChip array. Dynamic changes in DNA methylation occurring during differentiation were investigated using a data-driven trajectory inference method. We identified a large number of Bonferroni-significant loci that showed progressive alterations in DNA methylation during neuronal differentiation. A gene-gene interaction network analysis identified 60 densely connected genes that were influential in the differentiation of neurons, with STAT3 being the gene with the highest connectivity.The article is available via Open Access. Click on the 'Additional link' above to access the full-text.Published version, accepted versio