Usage Information
Abstract
Recent years have witnessed the groundbreaking success of immune checkpoint blockage (ICB) in metastasized malignant melanoma. However, biomarkers predicting the response to ICB are still urgently needed. In the present study, we investigated CTLA4 promoter methylation (mCTLA4) in 470 malignant melanoma patients from The Cancer Genome Atlas (non-ICB cohort) and in 50 individuals with metastasized malignant melanomas under PD-1/CTLA-4–targeted immunotherapy (ICB cohort). mCTLA4 levels were quantified using the Infinium HumanMethylation450 BeadChip (non-ICB cohort) and methylation-specific quantitative real-time PCR in DNA formalin-fixed and paraffin-embedded tissues (ICB cohort). Methylation levels were associated with molecular and clinicopathological variables and analyzed with respect to response (irRECIST) and overall survival. CTLA-4 mRNA and mCTLA4 showed a significant inverse correlation (non-ICB cohort: Spearman’s ρ = –0.416, P < 0.001). In ICB-treated melanoma patients, low mCTLA4 was further strongly correlated with response to therapy (P = 0.009, ANOVA) and overall survival (hazard ratio = 2.06 [95% CI: 1.29–3.29], P = 0.003). Our data strongly support the assumption that mCTLA4 predicts response to both anti–PD-1 and anti–CTLA-4 targeted ICB in melanoma and provides paramount information for the selection of patients likely to respond to ICB.
Authors
Diane Goltz, Heidrun Gevensleben, Timo J. Vogt, Joern Dietrich, Carsten Golletz, Friedrich Bootz, Glen Kristiansen, Jennifer Landsberg, Dimo Dietrich
Usage data is cumulative from June 2025 through June 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 1,353 | 61 |
| 221 | 21 | |
| Figure | 475 | 0 |
| Supplemental data | 94 | 2 |
| Citation downloads | 215 | 0 |
| Totals | 2,358 | 84 |
| Total Views | 2,442 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
