Prognostic significance of CXCR4 and mTOR expression in diffuse large B-cell lymphoma patients
Bibliographic record
Abstract
Background: The aim of this study was to investigate the prognostic role of mammalian target of Rapamycin (mTOR) and C-X-C chemokine receptor type 4 (CXCR4) in diffuse large-B-cell lymphoma (DLBCL) patients.Patients and methods: This retrospective study was collected data from 64 de novo DLBCL patients, who received standardized R-CHOP therapy at two oncology centers. CXCR4 and mTOR expressions were assessed by immunohistochemistry.Results: Out of the 64 DLBCL patients, 40 patients were positive for CXCR4 (62.5%) and 35 patients for mTOR (54.7%) expressions. CXCR4 expression was positively correlated with mTOR expression (r = 0.7; p < .001). While mTOR expression was significantly associated with high lactate dehydrogenase level (p = .03) and number of extranodal sites one or more (p =.02), CXCR4 expression was significantly associated with high IPI score (p < .001) and ECOG PS (p = .005). Furthermore, theexpression levels of mTOR and CXCR4 were significantly associated with older ages and poor response to treatment (p = .04, <.001 and .04, .03, respectively). After a median Follow up of 22 months, mean ± SD overall survival (OS) was 65.391 ± 4.705. Kaplan–Meier analysis showed that patients positive for mTOR and CXCR4 expression had shorter DFS (p = .01 & .02) and OS (p = .02 & .04). Multivariate analysis showed that CXCR4 and mTOR positivity is an independent prognostic factor for significantly poorer DFS (p = .03, and .02 respectively) but not for OS (p = .09 and .08 respectively) in the DLBCL pateints.Conclusion: Our results indicate that the expression of CXCR4 and mTOR may be poor prognostic biomarkers in DLBCL.
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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 | 0.000 | 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 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".