Antiproliferative Effects of <sup>111</sup> In- or <sup>177</sup> Lu-DOTATOC on Cells Exposed to Low Multiplicity-of-Infection Double-Deleted Vaccinia Virus Encoding Somatostatin Subtype-2 Receptor
Bibliographic record
Abstract
Oncolytic viruses may be limited in their ability to infect and lyse tumor cells because of penetration barriers and viral elimination by the immune system. Combining virotherapy with targeted radiotherapy that uses (111)In- or (177)Lu-DOTATOC may address such issues by spatially enhancing antitumor effects through bystander and/or cross-fire phenomena. In this study, a double-deleted vaccinia virus (vvDD) encoding the gene for somatostatin subtype-2 receptor (sstr-2) infected MC-38 murine colon adenocarcinoma cells and increased their sstr-2 expression by 2-fold. A low multiplicity-of-infection (MOI = 0.1) of vvDD and short exposure time (48 hours) preserved MC-38 viability (>80%-90%) for up to 3 days, permitting targeting of sstr-2 by (111)In- or (177)Lu-DOTATOC. (111)In-DOTATOC, alone or in combination with vvDD, was less effective than (177)Lu-DOTATOC at decreasing the growth of sstr-2-gene-transfected human embryonic kidney (HEK)-293 cells or MC-38 cells in monolayer. However, (111)In- or (177)Lu-DOTATOC combined with vvDD provided equivalent growth inhibition of HEK-293 or MC-38 cells as spheroids, suggesting a bystander effect from (111)In-DOTATOC. Growth of the cells was reduced 4-fold (from 20% to <5%) at 8 days in this case. Further evaluation of low-MOI vvDD in combination with (111)In- or (177)Lu-DOTATOC for the treatment of MC-38 tumors in mice is planned.
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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 | 0.000 |
| 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".