Publications by authors named "M Purde"

Immune checkpoint inhibitor (ICI)-related pneumonitis is a serious autoimmune event affecting as many as 20% of patients with non-small-cell lung cancer (NSCLC), yet the factors underpinning its development in some patients and not others are poorly understood. To investigate the role of autoantibodies and autoreactive T cells against surfactant-related proteins in the development of pneumonitis. The study cohort consisted of patients with NSCLC who provided blood samples before and during ICI treatment.

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Harnessing the immune system to eradicate tumors requires identification and targeting of tumor antigens, including tumor-specific neoantigens and tumor-associated self-antigens. Tumor-associated antigens are subject to existing immune tolerance, which must be overcome by immunotherapies. Despite many novel immunotherapies reaching clinical trials, inducing self-antigen-specific immune responses remains challenging.

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Background: The role of autoreactive T cells on the course of Coronavirus disease-19 (COVID-19) remains elusive. Type II pneumocytes represent the main target cells of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Autoimmune responses against antigens highly expressed in type II pneumocytes may influence the severity of COVID-19 disease.

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Background: Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs.

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Cancer treatment with immune checkpoint blockade (ICB) often induces immune-related adverse events (irAEs). We hypothesized that proteins coexpressed in tumors and normal cells could be antigenic targets in irAEs and herein described DITAS (discovery of tumor-associated self-antigens) for their identification. DITAS computed transcriptional similarity between lung tumors and healthy lung tissue based on single-sample gene set enrichment analysis.

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