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Immune cells and their inflammatory mediators modify β cells and cause checkpoint inhibitor–induced diabetes
Ana Luisa Perdigoto, Songyan Deng, Katherine C. Du, Manik Kuchroo, Daniel B. Burkhardt, Alexander Tong, Gary Israel, Marie E. Robert, Stuart P. Weisberg, Nancy Kirkiles-Smith, Angeliki M. Stamatouli, Harriet M. Kluger, Zoe Quandt, Arabella Young, Mei-Ling Yang, Mark J. Mamula, Jordan S. Pober, Mark S. Anderson, Smita Krishnaswamy, Kevan C. Herold
Ana Luisa Perdigoto, Songyan Deng, Katherine C. Du, Manik Kuchroo, Daniel B. Burkhardt, Alexander Tong, Gary Israel, Marie E. Robert, Stuart P. Weisberg, Nancy Kirkiles-Smith, Angeliki M. Stamatouli, Harriet M. Kluger, Zoe Quandt, Arabella Young, Mei-Ling Yang, Mark J. Mamula, Jordan S. Pober, Mark S. Anderson, Smita Krishnaswamy, Kevan C. Herold
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Research Article

Immune cells and their inflammatory mediators modify β cells and cause checkpoint inhibitor–induced diabetes

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Abstract

Checkpoint inhibitors (CPIs) targeting programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) have revolutionized cancer treatment but can trigger autoimmune complications, including CPI-induced diabetes mellitus (CPI-DM), which occurs preferentially with PD-1 blockade. We found evidence of pancreatic inflammation in patients with CPI-DM with shrinkage of pancreases, increased pancreatic enzymes, and in a case from a patient who died with CPI-DM, peri-islet lymphocytic infiltration. In the NOD mouse model, anti–PD-L1 but not anti–CTLA-4 induced diabetes rapidly. RNA sequencing revealed that cytolytic IFN-γ+CD8+ T cells infiltrated islets with anti–PD-L1. Changes in β cells were predominantly driven by IFN-γ and TNF-α and included induction of a potentially novel β cell population with transcriptional changes suggesting dedifferentiation. IFN-γ increased checkpoint ligand expression and activated apoptosis pathways in human β cells in vitro. Treatment with anti–IFN-γ and anti–TNF-α prevented CPI-DM in anti–PD-L1–treated NOD mice. CPIs targeting the PD-1/PD-L1 pathway resulted in transcriptional changes in β cells and immune infiltrates that may lead to the development of diabetes. Inhibition of inflammatory cytokines can prevent CPI-DM, suggesting a strategy for clinical application to prevent this complication.

Authors

Ana Luisa Perdigoto, Songyan Deng, Katherine C. Du, Manik Kuchroo, Daniel B. Burkhardt, Alexander Tong, Gary Israel, Marie E. Robert, Stuart P. Weisberg, Nancy Kirkiles-Smith, Angeliki M. Stamatouli, Harriet M. Kluger, Zoe Quandt, Arabella Young, Mei-Ling Yang, Mark J. Mamula, Jordan S. Pober, Mark S. Anderson, Smita Krishnaswamy, Kevan C. Herold

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Figure 4

Differentially expressed pathways and genes in islet-infiltrating macrophages with anti–PD-L1 versus anti–CTLA-4 mAb treatment.

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Differentially expressed pathways and genes in islet-infiltrating macrop...
(A) Macrophages (CD68+) are highlighted on Multiscale PHATE visualization of all cells treated with anti–CTLA-4 and anti–PD-L1. (B) MELD analysis of macrophage subpopulations showed differences between anti–PD-L1 versus anti–CTLA-4 treatment conditions. (C) Metascape analysis of differentially expressed genes by scRNA-Seq between anti–PD-L1–treated and anti–CTLA-4–treated islet-infiltrating macrophages. (711 genes based on P < 0.05, q < 0.05, log2fc ≤ –0.6 and ≥ 0.6). (D) Diseases and functions represented by differentially expressed genes between anti–PD-L1– and anti–CTLA-4–treated macrophages by Ingenuity Pathway Analysis (IPA; QIAGEN). Predicted activation state is for anti–PD-L1 macrophages compared with anti–CTLA-4 macrophages. Activation z score cutoffs ≤ –2 and ≥ 2. Red = predicted to be activated, and gray = significant change without defined direction. (E) Top 20 predicted upstream regulators in macrophages by IPA. Red = upregulated in anti–PD-L1 macrophages, and blue = downregulated in anti–PD-L1–treated macrophages. (F) Volcano plot of differentially expressed genes in anti–PD-L1 versus anti–CTLA-4 treatment macrophages. Highlighted genes include IFN-γ–responsive genes. There were 1,329 differentially expressed genes based on P < 0.05, q < 0.05 (not shown), log2fc ≤ –0.6 and ≥ 0.6.

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