In Vivo Effects of Stereotactic Body Radiation Therapy on the Pancreatic Tumor Microenvironment
Bibliographic record
Abstract
Despite decades of improvements in cancer therapies, the current standard of care for locally advanced pancreatic cancer (LAPC) provides, on average, only a few months of survival benefit. Stereotactic Body Radiation Therapy (SBRT), a technique that accurately delivers high doses of radiation to tumors, has emerged as a promising therapy to improve local control of LAPC; however, its effects on the tumor microenvironment and hypoxia remain poorly understood. Our group and others have shown that high-dose radiotherapy can cause significant damage to tumor blood vessels. Thus, we hypothesized that SBRT would result in vascular damage that may further lead to tumor hypoxia, potentially generating a more aggressive tumor phenotype. To explore this hypothesis, orthotopic pancreatic tumors in mice were treated with SBRT in 5 daily fractions (8 Gy/fraction, or ‘5×8Gy’) to simulate a typical SBRT dose regimen for LAPC patients. A small animal micro-irradiator with integrated three-dimensional bioluminescence imaging provided accurate spatial targeting for pancreatic tumors in the orthotopic setting. A novel experimental platform using intravital fluorescence microscopy was also developed to enable the longitudinal study of the pancreatic tumor microenvironment in vivo, including real-time quantification of pancreatic tumor cell hypoxia, blood vessels, and collagen structures, at cellular resolution. Contrary to our hypothesis, this platform demonstrated a persistent decrease in pancreatic tumor hypoxia as early as one day after SBRT, with no evidence of vascular damage. This coincided with significant tumor cell death and growth arrest from treatment, indicating that a decrease in the demand for oxygen within the pancreatic tumor microenvironment significantly contributed to its reoxygenation. Overall, the unique combination of a small animal irradiator with the orthotopic intravital imaging platform presented in this thesis provides a novel methodology to investigate the effects of SBRT on the pancreatic tumor microenvironment in vivo. The findings from this work allow us to better understand the mechanisms that influence the tumor response to SBRT and may help to inform clinical practice, potentially guiding the design of future SBRT-based clinical trials.
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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) | 0.001 | 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".