Preclinical <i>In Vivo</i> Imaging of Multiple Myeloma with [ 18f]Fluorohomoleucine (FHL) PET/CT
Bibliographic record
Abstract
Purpose: Imaging of patients with multiple myeloma (MM) remains challenging due to its multi-focal nature affecting bone marrow, bone structures and soft tissue. As a result, current diagnostic methods like X-rays, CT and MRI scans only provide a partial understanding of disease activity and treatment response, lacking a comprehensive overview. Although 2-deoxy-2-[ 18F]fluoro-D-glucose (FDG) positron emission tomography (PET) has become the standard for detecting multifocal cancer spread, its use in MM patients is limited due to metabolic heterogeneity of MM and limited sensitivity in detecting extramedullary disease leading to false negative and false positive scans. To overcome these limitations, we developed a novel radiopharmaceutical L-[ 18F]Fluorohomoleucine (FHL) targeting LAT1 amino acid transporter. LAT1 has been significantly correlated with the proliferative activity of MM cells, poor prognosis and response to treatment in MM patients, presenting an appealing molecular target for assessing disease activity. Methods: FHL was synthesized as described by Nodwell et al. (J Nucl Med, 2019) and FDG was obtained from BC Cancer. LAT1 expression in multiple myeloma (MM) cell lines was confirmed by flow cytometry. Cell uptake assays were conducted using luciferase-transfected MM1S, L363, NCI H929 and AMO1 MM cells, and 2-amino-bicyclo[2.2.1]heptanes-2-carboxylic acid (BCH) was used as a blocking agent. For in vivo studies, male NRG mice were injected either with 1 x 10 6 MM cells intravenously (i.v.) via the caudal vein or subcutaneously (SQ) with 1 x 10 7 cells. Tumor engraftment was monitored weekly on an in vivo bioluminescence imager Perkin Elmer's IVIS Ilumina 5, starting at 2 weeks post-injection (p.i.). Biodistribution and PET/CT imaging studies were conducted at 4-6 weeks p.i. Results: All MM cells tested exhibited LAT1-specific FHL uptake in vitro with L363 and NCI H929 demonstrating the highest tracer uptake and average blocking efficacy over 83% and 93%, respectively. We were able to observe weekly progression of disease in the i.v. cohort using IVIS imaging. Biodistribution and PET imaging studies revealed FHL accumulation in the SQ xenografts, pancreas and excretion via the urinary tract. The SQ tumor uptake values were 4.53±0.82 %ID/g in AMO1 xenografts, 5.55±0.82 %ID/g in NCI H929, and 6.37±0.70 %ID/g in L363 tumors. In the i.v. cohort, the mouse intravenously injected with L363 cells demonstrated accumulation of radioactivity in the skull and vertebrae, as anticipated from the IVIS images. Furthermore, preliminary data suggests that FHL was able to detect a more extensive bone and lymphatic involvement than FDG in MM xenografts. Conclusion: We have demonstrated the ability of FHL for in vivo imaging of three human multiple myeloma tumors in SQ murine models, with the tumor uptake ranging from 4.53±0.82 %ID/g in AMO1 xenografts to 6.37±0.70 %ID/g in L363 tumors. Work is underway to establish the utility of this tracer in detecting disease dissemination in the orthotopic murine models of multiple myeloma, with promising preliminary results presented herein.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".