Correlation of DNA Copy Number, Gene Expression, Protein Expression and Clinical Outcome in a Group of Patients with Diffuse Large B Cell Lymphoma (DLBCL) Treated with CHOP Plus Rituximab (CHOP-R).
Notice bibliographique
Résumé
Abstract Background: DLBCL is the most common subtype of Non-Hodgkin lymphoma and has a mortality rate of 40%. It is characterized by marked clinical and biological heterogeneity. Tumors with similar histology have different genetic abnormalities. The influence of many of these genetic changes on clinical outcome is unknown. Furthermore, treatment itself can influence the prognostic significance of certain biomarkers. Exploring the impact of genetic aberrations on gene expression, protein expression and clinical outcome is the focus of this investigation. Understanding the biology of DLBCL from patients treated with CHOP-R may lead to the discovery of novel biomarkers that are relevant in the CHOP-R era. Methods: RNA and DNA were extracted from frozen de novo DLBCL biopsies taken at the time of diagnosis from April 2001 to April 2005. Cases were selected based on their clinical outcome (11 patients with a >2 year remission with CHOP-R and 10 patients who progressed or relapsed after CHOP-R). We studied DNA amplifications and deletions using array comparative genomic hybridization (aCGH) comprising of >26,000 overlapping bacterial artificial chromosomes. This provides a >95% coverage of the human genome and the capability to reproducibly detect amplifications and deletions as small as 120 kb. We performed gene expression profiling (GEP) using the Affymetrix Human Genome U133 Plus 2 array. A tissue microarray was constructed to assess protein expression using paraffin active antibodies. BCL2, BCL6, P53 and MUM1 genes were assessed using all three platforms and results were correlated with clinical outcome. Results: DNA gains and losses were identified in all patients with an average of 19 alterations per tumor with amplifications being more frequent than deletions. GEP revealed a predominance (57%) of Activated B Cell (ABC) type. A supervised analysis identified a list of 471 genes that were differentially expressed (p<0.01) between treatment failures and successes, many of which are implicated in nucleic acid binding and cell cycle regulation. The correlation between DNA copy number and gene expression was poor especially in areas of DNA gain. The correlation between gene expression and copy number was greater for BCL2 and P53 than for BCL6 and MUM1 (r= 0.67 and 0.80 versus −0.02 and −0.08). The correlation between protein expression and gene expression were r = 0.22, 0.65, 0.66 and 0.53 for BCL2, P53, BCL6 and MUM1, respectively. In this small group of patients treated with CHOP-R, the international prognostic index (IPI) was higher in the patients “failing” CHOP-R (mean IPI 3.2 vs. 1.7). Deletions of 17p13.1 (P53) and high P53 protein expression were predominantly seen in the failures (7 vs 1). High BCL2 protein, low BCL6 protein and ABC signature were randomly distributed in both CHOP-R successes and failures. Conclusion: In this limited group of patients with DLBCL treated with CHOP-R, IPI had the strongest prognostic value. Candidate genes that could predict CHOP-R successes and failures will be validated by RT-PCR and TMA on a larger cohort of patients. The unpredictable correlation between gene expression and DNA copy number suggests that alternate mechanisms of gene regulation are involved in the pathogenesis of DLBCL.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».