BACKGROUND. Primary therapy for high-risk bladder cancer (BCa) is repeated instillations of the tuberculosis vaccine Bacillus Calmette-Guerin (BCG). Although BCG reduces the risk of recurrence by more than half, the mechanisms underlying its immune-activating effects remain unknown. Our objective was to investigate how the immune response differs between BCG responders and non-responders and to compare systemic and local immune responses. METHODS. We performed single-cell RNA sequencing (scRNA-seq) of isolated immune cells adjacent to high-risk bladders in BCG responders and non-responders before and after BCG. We also compared concurrent scRNA-seq profiles of circulating immune cell populations with those of bladder immune cells. RESULTS. We identify an increase in Th17-like Th1 cells in BCG responders, characterized by greater expression of pro-inflammatory cytokines. Alternatively, non-responders show increased CD8+ T-cell exhaustion and T regulatory cells. We identify that the primary mechanism driving divergent T-cell activity is altered polarization and immunosuppressive signaling with myeloid cells. Using a machine-learning-based approach, we identify that Th17-like Th1 cytokines, such as IL-17, IL-21, and IL-26, are predictive of response, which is subsequently validated in a separate BCG-treated BCa cohort. CONCLUSION. Together, these findings suggest that dynamic regulation of myeloid-T cell interactions can be critical for outcomes of BCG treated bladder cancer.
Ryan J. Brown, Mairah T. Khan, Andrew J. Houston, Hongshen Niu, Joseph R. Podojil, Bonnie Choy, Weiguo Cui, Joshua James Meeks
Usage data is cumulative from May 2026 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 382 | 0 |
| 152 | 0 | |
| Supplemental data | 68 | 0 |
| Citation downloads | 15 | 0 |
| Totals | 617 | 0 |
| Total Views | 617 | |
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.