Usage Information
Citation Information: JCI Insight. 2018;3(7):e98575. https://doi.org/10.1172/jci.insight.98575.
Abstract
We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.
Authors
Hyun-Sung Lee, Hee-Jin Jang, Jong Min Choi, Jun Zhang, Veronica Lenge de Rosen, Thomas M. Wheeler, Ju-Seog Lee, Thuydung Tu, Peter T. Jindra, Ronald H. Kerman, Sung Yun Jung, Farrah Kheradmand, David J. Sugarbaker, Bryan M. Burt
Usage data is cumulative from January 2024 through January 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 577 | 172 |
| 64 | 54 | |
| Figure | 132 | 12 |
| Supplemental data | 54 | 25 |
| Citation downloads | 35 | 0 |
| Totals | 862 | 263 |
| Total Views | 1,125 | |
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.
