Clinical [18F]FSPG Positron Emission Tomography Imaging Reveals Heterogeneity in Tumor-Associated System xc− Activity
Bibliographic record
Abstract
Background: (4S)-4-(3-[18F]fluoropropyl)-L-glutamic acid ([18F]FSPG) positron emission tomography/computed tomography (PET/CT) provides a readout of system xc− transport activity and has been used for cancer detection in clinical studies of different cancer types. As system xc− provides the rate-limiting precursor for glutathione biosynthesis, an abundant antioxidant, [18F]FSPG imaging may additionally provide important prognostic information. Here, we performed an analysis of [18F]FSPG radiotracer distribution between primary tumors, metastases, and normal organs from cancer patients. We further assessed the heterogeneity of [18F]FSPG retention between cancer types, and between and within individuals. Methods: This retrospective analysis of prospectively collected data compared [18F]FSPG PET/CT in subjects with head and neck squamous cell cancer (HNSCC, n = 5) and non-small-cell lung cancer (NSCLC, n = 10), scanned at different institutions. Using semi-automated regions of interest drawn around tumors and metastases, the maximum standardized uptake value (SUVmax), SUVmean, SUV standard deviation and SUVpeak were measured. [18F]FSPG time–activity curves (TACs) for normal organs, primary tumors and metastases were subsequently compared to 18F-2-fluoro-2-deoxy-D-glucose ([18F]FDG) PET/CT at 60 min post injection (p.i.). Results: The mean administered activity of [18F]FSPG was 309.3 ± 9.1 MBq in subjects with NSCLC and 285.1 ± 11.3 MBq in those with HNSCC. The biodistribution of [18F]FSPG in both cohorts showed similar TACs in healthy organs from cancer patients. There was no statistically significant overall difference in the average SUVmax of tumor lesions at 60 min p.i. for NSCLC (8.1 ± 7.1) compared to HNSCC (6.0 ± 4.1; p = 0.29) for [18F]FSPG. However, there was heterogeneous retention between and within cancer types; the SUVmax at 60 min p.i. ranged from 1.4 to 23.7 in NSCLC and 3.1–12.1 in HNSCC. Conclusion: [18F]FSPG PET/CT imaging from both NSCLC and HNSCC cohorts showed the same normal-tissue biodistribution, but marked tumor heterogeneity across subjects and between lesions. Despite rapid elimination through the urinary tract and low normal-background tissue retention, the diagnostic potential of [18F]FSPG was limited by variability in tumor retention. As [18F]FSPG retention is mediated by the tumor’s antioxidant capacity and response to oxidative stress, this heterogeneity may provide important insights into an individual tumor’s response or resistance to therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".