Reovirus therapy of lymphoid malignancies
Bibliographic record
Abstract
Reoviruses infect cells that manifest an activated Ras-signaling pathway, and have been shown to effectively destroy many different types of neoplastic cells, including those derived from brain, breast, colon, ovaries, and prostate. In this study, we investigated the reovirus as a potential therapeutic agent against lymphoid malignancies. A total of 9 lymphoid cell lines and 27 primary human lymphoid malignancies, as well as normal lymphocytes and hematopoietic stem/progenitor cells, were tested for susceptibility to reovirus infection. For in vitro studies, the cells were challenged with reovirus (serotype 3 Dearing), and viral infection was assessed by cytopathic effects, viability, viral protein synthesis, and progeny virus production. We present evidence of efficient reovirus infection and cell lysis in the diffuse large B-cell lymphoma cell lines and Burkitt lymphoma cell lines Raji and CA46 but not Daudi, Ramos, or ST486. Moreover, when Raji and Daudi cell lines were grown subcutaneously in severe combined immunodeficient/nonobese diabetic (SCID/NOD) mice and subsequently injected with reovirus intratumorally or intravenously, significant regression was observed in the Raji-induced, but not the Daudi-induced, tumors, which is consistent with the in vitro results. Susceptibility to reovirus infection was also detected in 21 of the 27 primary lymphoid neoplasias tested but not in the normal lymphocytes or hematopoietic stem/progenitor cells. Our results suggest that reovirus may be an effective agent against several types of human lymphoid malignancies.
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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 | 0.001 |
| 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".