Malignant pleural mesothelioma (MPM) is characterized as an incredibly aggressive form of cancer with a dismal diagnosis and a dearth of specific biomarkers and therapeutic options. For MPM patients, the effectiveness of immunotherapy may be influenced by damage-associated molecular pattern (DAMP)-induced immunogenic cell death (ICD).The objective of this work is to create a molecular profile associated with DAMPs to categorize MPM patients and predict their prognosis and response to immunotherapy.
The RNA-seq of 397 patients (263 patients with clinical data, 57.2% male, 73.0% over 60 yrs.) were gathered from eight public datasets as a training cohort to identify the DAMPs-associated subgroups of MPMs using K-means analysis. Three validation cohorts of patients or murine were established from TCGA and GEO databases. Comparisons were made across each subtype’s immune status, gene mutations, survival prognosis, and predicted response to therapy.
Based on the DAMPs gene expression, MPMs were categorized into two subtypes: the nuclear DAMPs subtype, which is classified by the upregulation of immune-suppressed pathways, and the inflammatory DAMPs subtype, which is distinguished by the enrichment of proinflammatory cytokine signaling. The inflammatory DAMPs subgroup had a better prognosis, while the nuclear DAMPs subgroup exhibited a worse outcome. In validation cohorts, the subtyping system was effectively verified. We further identified the genetic differences between the two DAMPs subtypes. It was projected that the inflammatory DAMPs subtype will respond to immunotherapy more favorably, suggesting that the developed clustering method may be implemented to predict the effectiveness of immunotherapy.
We constructed a subtyping model based on ICD-associated DAMPs in MPM, which might serve as a signature to gauge the outcomes of immune checkpoint blockades. Our research may aid in the development of innovative immunomodulators as well as the advancement of precision immunotherapy for MPM.