The Role of Heat Shock Protein 70 Expression in Oral Potentially Malignant Disorders
Bibliographic record
Abstract
Introduction: Oral Potentially Malignant Disorders (OPMD) are chronic conditions that can progress to malignancy. Heat Shock Proteins (HSP) are a group of proteins that act as molecular chaperones. Actually, HSPs can promote the growth of tumor cells. On the other hand, they stimulate immune response against tumor cells. In this review it has been aimed to identify the role of HSP70 expression in the diagnosis and prognosis of OPMD. Methods: In this systematic review study, all English and Persian articles with the keywords of lichen planus, Leukoplakia , Oral Submucous Fibrosis ,heat shock protein 70, oral premalignant disorders along with their Persian equivalents were searched from Google scholar, PubMed, science direct, Cochrane, Scopus and Sid databases until March 2020. The quality of the selected studies were evaluated by the Newcastle-Ottawa scale method. Results: Totally, 20 articles were selected and reviewed. The results of this study showed that there was an overexpression of HSP70 in OPMD. A significant correlation of HSP70 expression was observed with the severity of epithelial dysplasia. Actually, the expression of HSP70 can be a marker for the presence of dysplasia in OPMD. Conclusion: Enhanced HSP70 levels in pre-malignant and malignant cells suggests that not only the oncogenes and tumorsuppressor genes are involved in the process of oral carcinogenesis, but HSP70s may also be implicated in tumorigenesis. Taking all these into account, it can be supposed that in the future, HSP70 can be a target for an anticancer immunotherapy.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".