Tumor-Associated Macrophages Predict Outcome in Follicular Lymphoma
Notice bibliographique
Résumé
Abstract Abstract 682 Background: Follicular lymphoma (FL) is the most common indolent lymphoma and is clinically characterized by slow progression and responsiveness to therapy, but almost inevitable disease recurrences. While patient outcomes are generally favorable, a substantial proportion of patients are at risk of early death due to treatment resistance, early progression or transformation. CD68 positive macrophages were shown to predict poor survival in the pre-rituximab era (Farinha et al., Blood 2005 Sep 15;106(6):2169–74), but their association with poor outcome was lost or even reversed since the introduction of rituximab into the routine management of FL (Taskinen et al, Clin Cancer Res. 2007 Oct 1;13(19):5784–9 and Canioni et al, J Clin Oncol. 2008 Jan 20;26(3):440–6). Macrophages can be broadly divided into M1 and M2 subtypes with the latter associated with pro-tumoral immunity. We hypothesize that CD68 alone insufficiently captures the various phenotypes of tumor-associated macrophages and that staining for CD163 as a marker for alternatively activated macrophages (M2) provides additional prognostic information. Methods: We constructed a tissue microarray (TMA) from formalin-fixed and paraffin-embedded tissue blocks of 187 systemic treatment-naive FL patients that were selected from the Lymphoid Cancer Database of the BC Cancer Agency and that had been uniformly treated between 2004 and 2010 with rituximab, cyclophosphamide, vincristine and prednisone (R-CVP). Since 2006, institutional guidelines recommended maintenance with rituximab for patients achieving a complete or partial remission after first-line therapy. Median follow-up of living patients was 56 months. Immunohistochemistry was performed on the TMA with antibodies against CD68 (clone KP1, DAKO) and CD163 (clone 10D6, Novocastra) and was analyzed by computer image analysis (Aperio) using the Positive Pixel Count algorithm. Disease-specific survival (DSS) served as the primary end-point, and progression-free survival (PFS) and time to transformation (TTT) as secondary endpoints. The statistical software X-tile was used to determine the optimum thresholds for CD68 and CD163 as the values that maximized the Chi-square value of the log-rank test. Results: Within the cores on the TMA, the mean percentage of positivity was 4.7% for CD68 (range 0.3–22.6%) and 1.8% for CD163 (range 0–13.7%). Above a threshold of 1.8%, high CD68 expression was associated with favorable DSS (p=0.03), but not with PFS (p=0.47) or TTT (p=0.82). Increased CD163 expression on the other hand, above a threshold of 1.1%, was significantly associated with poor DSS (p<0.01), but not with PFS (p=0.68) or time to transformation (p=0.13). When adjusting for the International Prognostic Index (IPI) in a Cox regression model, the association of high CD68 expression with favorable DSS (hazard ratio=0.42, p=0.05) and high CD163 expression with poor DSS (hazard ratio=2.93, p=0.01) remained significant. The correlation between CD68 and CD163 expression was low (Pearson correlation coefficient=0.25), suggesting that both markers define different subsets of tumor-associated macrophages. To explore whether additional prognostic information could be gained from combining these markers, we grouped CD68-high and CD163-low cases into one category (n=83) and compared them against all others (n=102). High CD68 and low CD163 expression was associated with favorable DSS (p<0.01), but not PFS (p=0.40) or TTT (p=0.21). Patients with high CD68 and low CD163 expression had excellent outcomes at 7 years of follow-up (96% DSS versus 68%). The impact on DSS remained significant after adjusting for IPI in a Cox regression model (hazard ratio=0.15, p<0.01). Conclusion: In FL patients treated with uniform induction therapy, CD163 defines a subset of tumor-associated macrophages that is associated with inferior DSS, but not with early progression or transformation, whereas the combination of CD68-high and CD163-low defines a patient category that has excellent prognosis. Our results suggest that the detrimental role of alternatively activated M2 type macrophages is not reversed by rituximab and that a population of non-tumor promoting macrophages exists that is correlated with favorable outcome in FL. Our study also illustrates the power of image analysis to provide accurate scoring, capable of delineating patient populations at variable risk of death. Disclosures: Al-Tourah: F. Hoffmann-La Roche (Roche Canada): Research Funding. Moccia:F. Hoffmann-La Roche (Roche Canada): Research Funding. Connors:F. Hoffmann-La Roche (Roche Canada): Research Funding. Sehn:F. Hoffmann-La Roche (Roche Canada): Research Funding.
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 | 0,001 |
| 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) | 0,002 | 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 ».