Purpose: Early response to ABVD, assessed with interim FDG-PET (iPET), is prognostic for classical Hodgkin lymphoma (cHL) and supports the use of response adapted therapy. The aim of this study was to identify a gene-expression profile on diagnostic biopsy to predict iPET positivity (iPET+). Experimental Design: Consecutive untreated patients with stage I-IV cHL who underwent iPET after two cycles of ABVD were identified. Expression of 770 immune-related genes was analyzed by digital expression profiling (NanoString Technology). iPET was centrally reviewed according to the five-point Deauville scale (DS 1-5). An iPET+ predictive model was derived by multivariate regression analysis and assessed in a validation set identified using the same inclusion criteria. Results: A training set of 121 and a validation set of 117 patients were identified, with 23 iPET+ cases in each group. Sixty-three (52.1%), 19 (15.7%), and 39 (32.2%) patients had stage I-II, III, and IV, respectively. Diagnostic biopsy of iPET+ cHLs showed transcriptional profile distinct from iPET-. Thirteen genes were stringently associated with iPET+. This signature comprises two functionally stromal-related nodes. Lymphocytes/monocytes ratio (LMR) was also associated to iPET+. In the training cohort a 5-gene/LMR integrated score predicted iPET+ [AUC, 0.88; 95% confidence interval (CI), 0.80-0.96]. The score achieved a 100% sensitivity to identify DS5 cases. Model performance was confirmed in the validation set (AUC, 0.68; 95% CI, 0.52-0.84). Finally, iPET score was higher in patients with event versus those without. Conclusions: In cHL, iPET is associated with a genetic signature and can be predicted by applying an integrated gene-based model on the diagnostic biopsy.

A Gene Expression–based Model to Predict Metabolic Response after Two Courses of ABVD in Hodgkin Lymphoma Patients / Luminari, Stefano; Donati, Benedetta; Casali, Massimiliano; Valli, Riccardo; Santi, Raffaella; Puccini, Benedetta; Kovalchuk, Sofya; Ruffini, Alessia; Fama, Angelo; Berti, Valentina; Fragliasso, Valentina; Zanelli, Magda; Vergoni, Federica; Versari, Annibale; Rigacci, Luigi; Merli, Francesco; Ciarrocchi, Alessia. - In: CLINICAL CANCER RESEARCH. - ISSN 1557-3265. - (2020), pp. 373-383. [10.1158/1078-0432.CCR-19-2356]

A Gene Expression–based Model to Predict Metabolic Response after Two Courses of ABVD in Hodgkin Lymphoma Patients

Luminari Stefano
;
Fragliasso Valentina;
2020-01-01

Abstract

Purpose: Early response to ABVD, assessed with interim FDG-PET (iPET), is prognostic for classical Hodgkin lymphoma (cHL) and supports the use of response adapted therapy. The aim of this study was to identify a gene-expression profile on diagnostic biopsy to predict iPET positivity (iPET+). Experimental Design: Consecutive untreated patients with stage I-IV cHL who underwent iPET after two cycles of ABVD were identified. Expression of 770 immune-related genes was analyzed by digital expression profiling (NanoString Technology). iPET was centrally reviewed according to the five-point Deauville scale (DS 1-5). An iPET+ predictive model was derived by multivariate regression analysis and assessed in a validation set identified using the same inclusion criteria. Results: A training set of 121 and a validation set of 117 patients were identified, with 23 iPET+ cases in each group. Sixty-three (52.1%), 19 (15.7%), and 39 (32.2%) patients had stage I-II, III, and IV, respectively. Diagnostic biopsy of iPET+ cHLs showed transcriptional profile distinct from iPET-. Thirteen genes were stringently associated with iPET+. This signature comprises two functionally stromal-related nodes. Lymphocytes/monocytes ratio (LMR) was also associated to iPET+. In the training cohort a 5-gene/LMR integrated score predicted iPET+ [AUC, 0.88; 95% confidence interval (CI), 0.80-0.96]. The score achieved a 100% sensitivity to identify DS5 cases. Model performance was confirmed in the validation set (AUC, 0.68; 95% CI, 0.52-0.84). Finally, iPET score was higher in patients with event versus those without. Conclusions: In cHL, iPET is associated with a genetic signature and can be predicted by applying an integrated gene-based model on the diagnostic biopsy.
23-ott-2019
373
383
A Gene Expression–based Model to Predict Metabolic Response after Two Courses of ABVD in Hodgkin Lymphoma Patients / Luminari, Stefano; Donati, Benedetta; Casali, Massimiliano; Valli, Riccardo; Santi, Raffaella; Puccini, Benedetta; Kovalchuk, Sofya; Ruffini, Alessia; Fama, Angelo; Berti, Valentina; Fragliasso, Valentina; Zanelli, Magda; Vergoni, Federica; Versari, Annibale; Rigacci, Luigi; Merli, Francesco; Ciarrocchi, Alessia. - In: CLINICAL CANCER RESEARCH. - ISSN 1557-3265. - (2020), pp. 373-383. [10.1158/1078-0432.CCR-19-2356]
Luminari, Stefano; Donati, Benedetta; Casali, Massimiliano; Valli, Riccardo; Santi, Raffaella; Puccini, Benedetta; Kovalchuk, Sofya; Ruffini, Alessia; Fama, Angelo; Berti, Valentina; Fragliasso, Valentina; Zanelli, Magda; Vergoni, Federica; Versari, Annibale; Rigacci, Luigi; Merli, Francesco; Ciarrocchi, Alessia
File in questo prodotto:
File Dimensione Formato  
HL_IPET2019_Final_CCR.docx

Open access

Tipologia: Versione originale dell'autore proposta per la pubblicazione
Dimensione 159.09 kB
Formato Microsoft Word XML
159.09 kB Microsoft Word XML Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1198510
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact