Carcinoma Cell Hyaluronan as a “Portable” Cancerized Prometastatic Microenvironment
Bibliographic record
Abstract
Hyaluronan (HA) is a structurally simple polysaccharide, but its ability to act as a template for organizing pericellular matrices and its regulated synthesis and degradation are key to initiating repair responses. Importantly, these HA functions are usurped by tumor cells to facilitate progression and metastasis. Recent advances have identified the functional complexities associated with the synthesis and degradation of HA-rich matrices. Three enzymes synthesize large HA polymers while multiple hyaluronidases or tissue free radicals degrade these into smaller bioactive fragments. A family of extracellular and cell-associated HA-binding proteins/receptors translates the bioinformation encrypted in this complex polymer mixture to activate signaling networks required for cell survival, proliferation, and migration in an actively remodeling microenvironment. Changes in HA metabolism within both the peritumor stroma and parenchyma are linked to tumor initiation, progression, and poor clinical outcome. We review evidence that metastatic tumor cells must acquire the capability to autonomously synthesize, assemble, and process their own "portable" HA-rich microenvironments to survive in the circulation, metastasize to ectopic sites, and escape therapeutic intervention. Strategies to disrupt the HA machinery of primary tumor and circulating tumor cells may enhance the effectiveness of current conventional and targeted therapies. Cancer Res; 76(9); 2507-12. ©2016 AACR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 teacher head, 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".