Multifunctional Proteins Bridge Mitosis with Motility and Cancer with Inflammation and Arthritis
Bibliographic record
Abstract
While most secreted proteins contain defined signal peptides that direct their extracellular transport through the ER-Golgi pathway, nonclassical transport of leaderless peptides/proteins was first described 20 years ago and the mechanisms responsible for unconventional export of such proteins have been thoroughly reviewed. In addition to directed nonclassical secretion, a number of leaderless secreted proteins have been classified as damage-associated molecular-pattern (DAMP) molecules, which are nuclear or cytoplasmic proteins that, under necrotic or apoptotic conditions, are released outside the cell and function as proinflammatory signals. A strong association between persistent release of DAMPs, chronic inflammation, and the hypoxic tumor microenvironment has been proposed. Thus, protein localization and function can change fundamentally from intracellular to extracellular compartments, often under conditions of inflammation, cancer, and arthritis. If we are truly to understand, model, and treat such biological states, it will be important to investigate these multifunctional proteins and their contribution to degenerative diseases. Here, we will focus our discussion on intracellular proteins, both cytoplasmic and nuclear, that play critical extracellular roles. In particular, the multifunctional nature of HMMR/RHAMM and survivin will be highlighted and compared, as these molecules are the subject of extensive biological and therapeutic investigations within hematology and oncology fields. For these and other genes/proteins, we will highlight points of structural and functional intersection during cellular division and differentiation, as well as states associated with cancer, such as tumor-initiation and epithelial-to-mesenchymal transition (EMT). Finally, we will discuss the potential targeting of these proteins for improved therapeutic outcomes within these degenerative disorders. Our goal is to highlight a number of commonalities among these multifunctional proteins for better understanding of their putative roles in tumor initiation, inflammation, arthritis, and cancer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".