Usage Information
Abstract
The presence of B cells in tumors is correlated with favorable prognosis and efficient response to immunotherapy. While tumor-reactive antibodies have been detected in several cancer types, identifying antibodies that specifically target tumor-associated antigens remains a challenge. Here, we investigated the antibodies spontaneously elicited during breast and lung cancer that bind the cancer-associated antigen MET. We screened patients with lung (n = 25) and breast (n = 75) cancer and found that 13% had antibodies binding to both the recombinant ectodomain of MET, and the ligand binding part of MET, SEMA. MET binding in the breast cancer cohort was significantly correlated with hormone receptor–positive status. We further conducted immunoglobulin sequencing of peripheral MET-enriched B cells from 6 MET-reactive patients. The MET-enriched B cell repertoire was found to be polyclonal and prone to non-IgG1 subclass. Nine monoclonal antibodies were cloned and analyzed, and these exhibited MET binding, low thermostability, and high polyreactivity. Among these, antibodies 87B156 and 69B287 effectively bound to tumor cells and inhibited MET-expressing breast cancer cell lines. Overall, our data demonstrate that some patients with breast and lung cancer develop polyreactive antibodies that cross-react with MET. These autoantibodies have a potential contribution to immune responses against tumors.
Authors
Michal Navon, Noam Ben-Shalom, Maya Dadiani, Michael Mor, Ron Yefet, Michal Bakalenik-Gavry, Dana Chat, Nora Balint-Lahat, Iris Barshack, Ilan Tsarfaty, Einav Nili Gal-Yam, Natalia T. Freund
Usage data is cumulative from May 2025 through December 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 974 | 102 |
| 277 | 31 | |
| Figure | 312 | 1 |
| Table | 47 | 0 |
| Supplemental data | 194 | 6 |
| Citation downloads | 75 | 0 |
| Totals | 1,879 | 140 |
| Total Views | 2,019 | |
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.
