Aneustat (OMN54) has aerobic glycolysis‐inhibitory activity and also immunomodulatory activity as indicated by a first‐generation PDX prostate cancer model
Bibliographic record
Abstract
Aneustat (OMN54) is a multivalent, botanical anticancer candidate therapeutic. A recent Phase‐I clinical trial has indicated that it is well tolerated by patients and has immunomodulatory activity. In our study, using in vitro and in vivo prostate cancer models, we investigated Aneustat with regard to effects on (i) cancer‐generated immunosuppression based on aerobic glycolysis leading to acidification of the tumor microenvironment, and (ii) immune‐related processes such as macrophage differentiation and shifts in the intratumoral levels of host immune cells. Aneustat markedly reduced glucose consumption, lactic acid secretion, glycolysis‐related gene expressions and proliferation of human LNCaP prostate cancer cells. In addition, Aneustat induced differentiation of RAW264.7 macrophages to the M1 anticancer phenotype. Treatment of LNCaP xenografts and first‐generation patient‐derived prostate cancer tissue xenografts with Aneustat in both cases led to a marked shift in intratumoral host (mouse/patient) immune cell levels: a higher ratio of cytotoxic CD8+ T/Treg cells, higher numbers of NK cells, lower numbers of Treg cells and MDSCs, i.e. changes favoring the host anticancer immune response. Taken together, the data indicate that Aneustat has immunomodulatory activity based on inhibition of aerobic glycolysis which in patients may lead to reduction of cancer‐induced immunosuppression. Furthermore, first‐generation patient‐derived cancer tissue xenograft models may be used for screening compounds for immunomodulatory activity.
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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) | 0.002 | 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".