High-dose (HD) IL-2 therapy in patients with cancer increases the general population of Tregs, which are positive for CD4, CD25, and the Treg-specific marker Foxp3. It is unknown whether specific subsets of Tregs are activated and expanded during HD IL-2 therapy or whether activation of any particular Treg subset correlates with clinical outcome. Here, we evaluated Treg population subsets that were induced in patients with melanoma following HD IL-2 therapy. We identified a Treg population that was positive for CD4, CD25, Foxp3, and the inducible T cell costimulator (ICOS). This Treg population increased more than any other lymphocyte subset during HD IL-2 therapy and had an activated Treg phenotype, as indicated by high levels of CD39, CD73, and TGF-β. ICOS+ Tregs were the most proliferative lymphocyte population in the blood after IL-2 therapy. Patients with melanoma with enhanced expansion of ICOS+ Tregs in blood following the first cycle of HD IL-2 therapy had worse clinical outcomes than patients with fewer ICOS+ Tregs. However, there was no difference in total Treg expansion between HD IL-2 responders and nonresponders. These data suggest that increased expansion of the ICOS+ Treg population following the first cycle of HD IL-2 therapy may be predictive of clinical outcome.
Geok Choo Sim, Natalia Martin-Orozco, Lei Jin, Yan Yang, Sheng Wu, Edwina Washington, Deborah Sanders, Carol Lacey, Yijun Wang, Luis Vence, Patrick Hwu, Laszlo Radvanyi
Usage data is cumulative from April 2023 through April 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 821 | 129 |
106 | 79 | |
Figure | 223 | 7 |
Supplemental data | 16 | 3 |
Citation downloads | 26 | 0 |
Totals | 1,192 | 218 |
Total Views | 1,410 |
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.