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

Stefano Luminari, Benedetta Donati, Massimiliano Casali, Riccardo Valli, Raffaella Santi, Benedetta Puccini, Sofya Kovalchuk, Alessia Ruffini, Angelo Fama, Valentina Berti, Valentina Fragliasso, Magda Zanelli, Federica Vergoni, Annibale Versari, Luigi Rigacci, Francesco Merli, Alessia Ciarrocchi

Research output: Contribution to journalArticle

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.

Original languageEnglish
JournalClinical Cancer Research
DOIs
Publication statusE-pub ahead of print - Oct 23 2019

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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