Absolute quantification of the pretreatment PML-RARA transcript defines the relapse risk in acute promyelocytic leukemia
Metrics: PDF 1984 views | HTML 1549 views | ?
Francesco Albano1, Antonella Zagaria1, Luisa Anelli1, Nicoletta Coccaro1, Giuseppina Tota1, Claudia Brunetti1, Crescenzio Francesco Minervini1, Luciana Impera1, Angela Minervini1, Angelo Cellamare1, Paola Orsini1, Cosimo Cumbo1, Paola Casieri1, Giorgina Specchia1
1Department of Emergency and Organ Transplantation (D.E.T.O.), Hematology Section, University of Bari, 70124, Bari, Italy
Francesco Albano, e-mail: firstname.lastname@example.org
Keywords: acute promyelocytic leukemia, PML-RARA, relapse risk, droplet digital PCR, prognostic factor
Received: February 25, 2015 Accepted: April 06, 2015 Published: April 18, 2015
In this study we performed absolute quantification of the PML-RARA transcript by droplet digital polymerase chain reaction (ddPCR) in 76 newly diagnosed acute promyelocytic leukemia (APL) cases to verify the prognostic impact of the PML-RARA initial molecular burden. ddPCR analysis revealed that the amount of PML-RARA transcript at diagnosis in the group of patients who relapsed was higher than in that with continuous complete remission (CCR) (272 vs 89.2 PML-RARA copies/ng, p = 0.0004, respectively). Receiver operating characteristic analysis detected the optimal PML-RARA concentration threshold as 209.6 PML-RARA/ng (AUC 0.78; p < 0.0001) for discriminating between outcomes (CCR versus relapse). Among the 67 APL cases who achieved complete remission after the induction treatment, those with >209.6 PML-RARA/ng had a worse relapse-free survival (p = 0.0006). At 5-year follow-up, patients with >209.6 PML-RARA/ng had a cumulative incidence of relapse of 50.3% whereas 7.5% of the patients with suffered a relapse (p < 0.0001). Multivariate analysis identified the amount of PML-RARA before induction treatment as the sole independent prognostic factor for APL relapse.
Our results show that the pretreatment PML-RARA molecular burden could therefore be used to improve risk stratification in order to develop more individualized treatment regimens for high-risk APL cases.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.