Are 3D Tumor Cell Spheroids a Utile System for the In Vitro Evaluation of Diagnostic Radiotracers?
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide By possibly bridging the gap between 2D in vitro cell assays and in vivo applications, tumor cell spheroid cultures offer promising avenues for advancing innovation in nuclear medicine. Regarding the in vitro evaluation of therapeutic radioligands, tumor cell spheroids have been successfully used to assess the therapeutic efficacy against human tumors. However, studies employing spheroids for testing diagnostic tracers are missing. The present work investigated the receptor interaction of a diagnostic radioligand with different tumor cell spheroids and compared the results to those received from a standard 2D cell assay to validate the usefulness of 3D cell systems for diagnostic radiotracer testing. For this purpose, a new agent─[ 68 Ga]Ga-NODAGA-PEG 5 -c(RGDfK)─was developed. In competitive displacement assays against [ 125 I]I-echistatin in human U87MG glioblastoma cell monolayers, NODAGA-PEG 5 -c(RGDfK) demonstrated specific binding and IC 50 values of 3.08 ± 0.12 and 10.39 ± 0.89 μM in the absence and presence of basal membrane extract (BME), respectively. Compared to cell monolayers, the 3D cell aggregates yielded considerably higher IC 50 values of 16.46 ± 2.88, 20.52 ± 4.41, and 18.44 ± 6.06 μM in spheroids generated without additive, collagen-1, and BME supplementation and showed considerable unspecific binding. The obtained data were contextualized by investigating differences in morphology, cell viability, and integrin content per cell of the 2D and 3D cell models as well as the influence of ECM composition. Integrin expression per cell was stable, while spheroid density and the associated radioligand uptake were varying, depending on the culture conditions. This suggests a correlation between the NODAGA-PEG 5 -c(RGDfK)-integrin α v β 3 -interaction and cell model compactness. Further, a considerable influence of matrix components on ligand–receptor interaction could be demonstrated. Overall, the results showed profound differences between the 2D and 3D radiotracer assays investigated, and further work is warranted to verify the expected added value of 3D tumor cell spheroids for the evaluation of diagnostic radioligands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".