Defining the cellular and molecular features of nerve-invaded cancer cells using a newly characterized experimental model
Why this work is in the frame
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Bibliographic record
Abstract
Perineural invasion (PNI) is the invasion of cancer cells into nerves. Although PNI is a risk factor for cancer recurrence and metastasis, the lack of in vitro experimental models representing natural PNI challenges basic studies and therapeutic screening. In this work, we fully characterized a dorsal root ganglia (DRG)-nerve explant model for PNI and demonstrated the characteristic cellular and molecular features of cancer cells undergoing natural PNI. Briefly, thoracic and lumbar DRGs intactly connected to nerves were co-cultured with breast and prostate cancer cells in a 3D matrix for two weeks. Time-dependent brightfield and fluorescence imaging captured the complex interactions of cancer cells, neurons, axons, and Schwann cells within nerves in the DRG-nerve preparation, demonstrating the natural invasion of cancer cells. Fundamental investigations showed that the autonomic neurotransmitters norepinephrine and acetylcholine significantly promote PNI. We also demonstrated increased survival of PNI cells in response to the treatment with the cytotoxic drug cisplatin. Additionally, we characterized the proteomics profile of PNI cells for future theranostics applications and validated the results using patient breast tumor samples. Overall, this work characterized and established a clinically relevant model for PNI and revealed the cellular crosstalk of PNI cells within nerves. The established model is suitable for fundamental studies and therapeutic screening pertaining to PNI.
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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 | 0.000 | 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) | 0.000 | 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 it