Title |
Genetic risk analysis of a patient with fulminant autoimmune type 1 diabetes mellitus secondary to combination ipilimumab and nivolumab immunotherapy
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Published in |
Journal for Immunotherapy of Cancer, December 2016
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DOI | 10.1186/s40425-016-0196-z |
Pubmed ID | |
Authors |
Jared R. Lowe, Daniel J. Perry, April K. S. Salama, Clayton E. Mathews, Larry G. Moss, Brent A. Hanks |
Abstract |
Checkpoint inhibitor immunotherapy is becoming an effective treatment modality for an increasing number of malignancies. As a result, autoinflammatory side-effects are also being observed more commonly in the clinic. We are currently unable to predict which patients will develop more severe toxicities associated with these treatment regimens. We present a patient with stage IV melanoma that developed rapid onset autoimmune type 1 diabetes (T1D) in response to combination ipilimumab and nivolumab immunotherapy. At the time of the patient's presentation with diabetes ketoacidosis, a confirmed anti-GAD antibody seroconversion was noted. Longer-term follow-up of this patient has demonstrated a durable complete response based on PET CT imaging along with a persistently undetectable C-peptide level. Single nucleotide polymorphism gene sequencing and HLA risk allele analysis has revealed the patient to lack any established genetic predisposition to the development of autoimmune T1D. While larger studies are necessary to better understand the role of genetic risk factors for the development of autoimmune toxicities in those patients undergoing checkpoint inhibitor immunotherapy, these results suggest that pre-screening patients for known T1D risk alleles may not be indicated. Additional investigation is needed to determine whether an approach such as T cell receptor clonotypic analysis to identify the presence of autoreactive T cell clones may be an effective approach for predicting which patients are at risk for the development of autoinflammatory toxicities while undergoing checkpoint inhibitor immunotherapy. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 78 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 23% |
Student > Master | 10 | 13% |
Student > Ph. D. Student | 9 | 12% |
Other | 7 | 9% |
Student > Bachelor | 5 | 6% |
Other | 16 | 21% |
Unknown | 13 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 41 | 53% |
Biochemistry, Genetics and Molecular Biology | 4 | 5% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
Agricultural and Biological Sciences | 3 | 4% |
Immunology and Microbiology | 2 | 3% |
Other | 6 | 8% |
Unknown | 19 | 24% |