The Crosstalk between Nerves and Cancer—A Poorly Understood Phenomenon and New Possibilities
Bibliographic record
Abstract
INTRODUCTION: Crosstalk occurs between nerve and cancer cells. These interactions are important for cancer homeostasis and metabolism. Nerve cells influence the tumor microenvironment (TME) and participate in metastasis through neurogenesis, neural extension, and axonogenesis. We summarized the past and current literature on the interaction between nerves and cancer, with a special focus on pancreatic ductal adenocarcinoma (PDAC), prostate cancer (PCa), and the role of the nerve growth factor (NGF) in cancer. MATERIALS/METHODS: We reviewed PubMed and Google Scholar for the relevant literature on the relationship between nerves, neurotrophins, and cancer in general and specifically for both PCa and PDAC. RESULTS: The NGF helped sustain cancer cell proliferation and evade immune defense. It is a neuropeptide involved in neurogenic inflammation through the activation of several cells of the immune system by several proinflammatory cytokines. Both PCa and PDAC employ different strategies to evade immune defense. The prostate is richly innervated by both the sympathetic and parasympathetic nerves, which helps in both growth control and homeostasis. Newly formed autonomic nerve fibers grow into cancer cells and contribute to cancer initiation and progression through the activation of β-adrenergic and muscarinic cholinergic signaling. Surgical or chemical sympathectomy prevents the development of prostate cancer. Beta-blockers have a high therapeutic potential for cancer, although current clinical data have been contradictory. With a better understanding of the beta-receptors, one could identify specific receptors that could have an effect on prostate cancer development or act as therapeutic agents. CONCLUSION: The bidirectional crosstalk between the nervous system and cancer cells has emerged as a crucial regulator of cancer and its microenvironment. Denervation has been shown to be promising in vitro and in animal models. Additionally, there is a potential relationship between cancer and psychosocial biology through neurotransmitters and neurotrophins.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".