Abstract 2524: Investigating the role of neutrophils in muscle-invasive bladder cancer and response to radiation therapy
Bibliographic record
Abstract
Abstract Background: Radiation therapy (RT) is an increasingly used bladder-sparing therapy for patients with muscle-invasive bladder cancer (MIBC). However, 20-30% of patients do not respond to RT. Neutrophils have previously been linked to radioresistance, but the specific mechanism is still unknown. Previous work by our team has shown that neutrophil extracellular trap (NET) formation plays a role in RT resistance in an immunologically hot tumor, with high T cell infiltration, using the MB49 murine bladder cancer cell line, in a vivo model. In MIBC, a recently developed cell line can be used to study cold, luminal-like tumors. However, work on this cell line and its response to RT is still in its initial stages. Immune checkpoint inhibitors such as anti-PD-L1 have been tested by our team in these cold tumors of MIBC and have not shown to be effective in treating or radiosensitizing the tumor. Consequently, we aim to determine how neutrophil migration and neutrophil extracellular traps (NET) impact tumor growth in a cold, luminal-like tumor model. Furthermore, we aim to understand how neutrophil migration and NETs impact immunological changes in the tumor microenvironment (TME). Methods: To determine the response to RT in these cold tumors, mice were injected with 5M cells on the right flank of our luminal-like cancer model (UPPL cell line). Once tumors reached 0.1-0.15 cm3, mice were randomized into the different treatment groups: 1) Control; 2) RT; 3) Anti-PDL1 4) DNAse I; 5) RT + Anti-PDL1; 6) RT + DNAse I; 7) Anti-PDL1 + DNAse I; 8) RT + Anti-PDL1 + DNAse I. Size of the tumor was monitored. 8 mice tumors per group were collected at the primary endpoint set at 1.5 cm3 and 5 mice tumors per group were collected after 21 days (midpoint). Tumors were collected analyzed by flow cytometry and immunohistochemistry (IHC). Preliminary Results: Prolonged survival was observed in the mice treated with the triple combination when compared to the other groups. Tumor growth in this group also showed delay early on. So far, the frequency of pro-tumorigenic neutrophils infiltration in tumors seems to happen early on (midpoints) in mice treated with RT, whereas the infiltration happens later (endpoint) in the mice treated with the triple combination. Currently, we are also evaluating the NET production in these tumors through IHC. Conclusion: This ongoing experiment using RT on the UPPL cell line will allow us to understand what happens in patients who are resistant to RT. Understanding the role of neutrophils and NETs, along with the changes in the TME caused by the manipulation of these is key to understanding radiation resistance. This knowledge will bring us one step closer to developing new bladder-sparring treatments and improving patient care in the clinic. Citation Format: Sabina Fehric, Eva Michaud, Surashri Shinde-Jadhav, JiaMin Huang, Jose J. Mansure, Roni Rayes, Jonathan Spicer, Wassim Kassouf. Investigating the role of neutrophils in muscle-invasive bladder cancer and response to radiation therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2524.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".