Longitudinal Visualization of Viable Cancer Cell Intratumoral Distribution in Mouse Models Using Oatp1a1-Enhanced Magnetic Resonance Imaging
Bibliographic record
Abstract
OBJECTIVES: Multimodality reporter gene imaging provides valuable, noninvasive information on the fate of engineered cell populations. To complement magnetic resonance imaging (MRI) measures of tumor volume and 2-dimensional reporter-based optical measures of cell viability, reporter-based MRI may offer 3-dimensional information on the distribution of viable cancer cells in deep tissues. MATERIALS AND METHODS: Here, we engineered human and murine triple-negative breast cancer cells with lentivirus encoding tdTomato and firefly luciferase for fluorescence imaging and bioluminescence imaging (BLI). A subset of these cells was additionally engineered with lentivirus encoding organic anion transporting polypeptide 1a1 (Oatp1a1) for MRI. Oatp1a1 operates by transporting gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) into cells, and it concomitantly improves BLI substrate uptake. After orthotopic implantation of engineered cells expressing or not expressing Oatp1a1, longitudinal fluorescence imaging, BLI, and 3-Tesla MRI were performed. RESULTS: Oatp1a1-expressing tumors displayed significantly increased BLI signals relative to control tumors at all time points (P < 0.05). On MRI, post-Gd-EOB-DTPA T1-weighted images of Oatp1a1-expressing tumors exhibited significantly increased contrast-to-noise ratios compared with control tumors and precontrast images (P < 0.05). At endpoint, tumors expressing Oatp1a1 displayed intratumoral MR signal heterogeneity not present at earlier time points. Pixel-based analysis of matched in vivo MR and ex vivo fluorescence microscopy images revealed a strong, positive correlation between MR intensity and tdTomato intensity for Oatp1a1-expressing tumors (P < 0.05), but not control tumors. CONCLUSIONS: These results characterize Oatp1a1 as a sensitive, quantitative, positive contrast MRI reporter gene for 3-dimensional assessment of viable cancer cell intratumoral distribution and concomitant BLI enhancement. This multimodality reporter gene system can provide new insights into the influence of viable cancer cell intratumoral distribution on tumor progression and metastasis, as well as improved assessments of anticancer therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".