Co‐expression of c‐kit and stem cell factor in primary and metastatic nasopharyngeal carcinomas and nasopharyngeal epithelium
Bibliographic record
Abstract
Expression of c-kit has been demonstrated in 33% of adult nasopharyngeal carcinomas (NPCs) and in 88% of paediatric NPCs. Patients with tumours expressing c-kit tend to exhibit better survival, but a paracrine/autocrine function for the stem cell factor (SCF)/c-kit system in nasopharyngeal carcinomas has not been reported. This study evaluated the expression of c-kit and SCF by immunohistochemical staining of nasopharyngeal epithelium (NPE) and of primary and metastatic NPCs. In addition, c-kit and SCF expression were studied in HONE-1 NPC cells by immunoprecipitation and western blotting. Expression of c-kit and SCF was detected in 75% and 57% of NPE, respectively, and there was 48% co-expression. In primary NPCs, 86% expressed c-kit, 69% had SCF expression, and there was 67% co-expression. In metastatic NPCs, 76% expressed c-kit, 72% expressed SCF and there was 68% co-expression. Co-expression of c-kit and SCF with tyrosine autophosphorylation of p145(c - kit) was demonstrated in HONE-1 NPC cells. In addition, the expression level of c-kit and its autophosphorylation status was not obviously influenced by the transient co-expression of Epstein-Barr nuclear antigen 1 (EBNA1) and latent membrane protein 1 (LMP1). Co-expression of c-kit and SCF is therefore commonly found in nasopharyngeal epithelium and NPCs, and in HONE-1 NPC cells with autoactivation possibly independent of the co-expression of EBNA1 and LMP1. All of these findings suggest that autoactivation of SCF/c-kit signalling may be a potent regulator of the nasopharyngeal epithelial barrier and of immune function at the nasopharyngeal mucosa surface, and may contribute to the carcinogenesis and progression of NPC. Further molecular analysis is required to evaluate the possibility of treatment with tyrosine kinase inhibitors in NPC, analogous to the treatment of gastrointestinal stromal tumours with STI571.
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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 | 0.001 | 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".