Mass Culture and Characterization of Tumor Cells From a Naturally Occurring Invertebrate Cancer Model: Applications for Human and Animal Disease and Environmental Health
Bibliographic record
Abstract
On the northeastern coast of the United States and Canada, Mya arenaria, the soft shell clam, develops a diffuse, hemopoetic tumor (a fatal leukemia-like cancer) resulting from inactivation of p53-like family member proteins.These malignant cells provide a model for an unrelated set of human cancer cells that are also characterized by mortalin-based cytoplasmic sequestration of wild-type p53 tumor suppressor protein (mortalin is the mitochondrial Hsp70 protein). Here we describe methods for mass culture and long-term storage of tumor cells from this cancer. These are the first successful efforts at maintaining malignant cells from any marine invertebrate in vitro. Following passage (subculture), these cultures undergo transition from primary cultures to non-immortalized cell lines that continue to proliferate and do not re-differentiate the normal hemocyte phenotype. We also characterize normal clam hemocytes and the pathology of cancerous clam hemocytes in vitro and in vivo using light and electron microscopy, cyto- and immunocytochemistry, molecular biology, and a phagocytosis assay. Our protocols provide biomedical and environmental researchers with ready access to this naturally occurring cancer model. We discuss the clam cancer model regarding (a) human health and disease; (b) animal health, disease, and aquaculture; (c) environmental health monitoring; and (d) future research directions.
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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".