The immunologic constant of rejection classification refines the prognostic value of conventional prognostic signatures in breast cancer. Issue 11 (27th November 2018)

• Record Type: Journal Article
• Authors: Bertucci, François; Finetti, Pascal; Simeone, Ines; Hendrickx, Wouter; Wang, Ena; Marincola, Francesco; Viens, Patrice; Mamessier, Emilie; Ceccarelli, Michele; Birnbaum, Daniel; Bedognetti, Davide
• Is Part Of: British journal of cancer. Volume 119:Issue 11(2018)
• Page Start: 1383
• Page End: 1391
• Publication Date: 2018-11-27
• Subjects: Cancer -- Periodicals; Cancer -- Research -- Periodicals; Tumors -- Periodicals; 616.994
• DOI: 10.1038/s41416-018-0309-1
• Languages: English
• ISSNs: 0007-0920

Abstract

Abstract Background The immunologic constant of rejection (ICR) is a broad phenomenon of Th-1 immunity-mediated, tissue-specific destruction. Methods We tested the prognostic value of a 20-gene ICR expression signature in 8766 early breast cancers. Results Thirty-three percent of tumours were ICR1, 29% ICR2, 23% ICR3, and 15% ICR4. In univariate analysis, ICR4 was associated with a 36% reduction in risk of metastatic relapse when compared with ICR1-3 (p = 2.30E–03). In multivariate analysis including notably the three major prognostic signatures (Recurrence score, 70-gene signature, ROR-P), ICR was the strongest predictive variable (p = 9.80E–04). ICR showed no prognostic value in the HR+/HER2− subtype, but prognostic value in the HER2+ and TN subtypes. Furthermore, in each molecular subtype and among the tumours defined as high risk by the three prognostic signatures, ICR4 patients had a 41–75% reduction in risk of relapse as compared with ICR1-3 patients. ICR added significant prognostic information to that provided by the clinico-genomic models in the overall population and in each molecular subtype. ICR4 was independently associated with achievement of pathological complete response to neoadjuvant chemotherapy (p = 2.97E–04). Conclusion ICR signature adds prognostic information to that of current proliferation-based signatures, with which it could be integrated to improve patients' stratification and guide adjuvant treatment.