Anti-GD2 Antibody Dinutuximab Beta and Low-Dose Interleukin 2 After Haploidentical Stem-Cell Transplantation in Patients With Relapsed Neuroblastoma: A Multicenter, Phase I/II Trial

PURPOSE

Patients with relapsed high-risk neuroblastoma (rHR-NB) have a poor prognosis. We hypothesized that graft-versus-neuroblastoma effects could be elicited by transplantation of haploidentical stem cells (haplo-SCT) exploiting cytotoxic functions of natural killer cells and their activation by the anti-GD2 antibody dinutuximab beta (DB). This phase I/II trial assessed safety, feasibility, and outcomes of immunotherapy with DB plus subcutaneous interleukin-2 (scIL2) after haplo-SCT in patients with rHR-NB.

METHODS

Patients age 1-21 years underwent T-/B-cell-depleted haplo-SCT followed by DB and scIL2. The primary end point 'success of treatment' encompassed patients receiving six cycles, being alive 180 days after end of trial treatment without progressive disease, unacceptable toxicity, acute graft-versus-host-disease (GvHD) ≥grade 3, or extensive chronic GvHD.

RESULTS

Seventy patients were screened, and 68 were eligible for immunotherapy. Median number of DB cycles was 6 (range, 1-9). Median number of scIL2 cycles was 3 (1-6). The primary end point was met by 37 patients (54.4%). Median observation time was 7.8 years. Five-year event-free survival (EFS) and overall survival from start of trial treatment were 43% (95% CI, 31 to 55) and 53% (95% CI, 41 to 65), respectively. Five-year EFS among patients in complete remission (CR; 52%; 95% CI, 31 to 69) or partial remission (44%; 95% CI, 27 to 60) before immunotherapy were significantly better compared with patients with nonresponse/mixed response/progressive disease (13%; 95% CI, 1 to 42; P = .026). Overall response rate in 43 patients with evidence of disease after haplo-SCT was 51% (22 patients), with 15 achieving CR (35%). Two patients developed GvHD grade 2 and 3 each. No unexpected adverse events occurred.

CONCLUSION

DB therapy after haplo-SCT in patients with rHR-NB is feasible, with low risk of inducing GvHD, and results in long-term remissions likely attributable to increased antineuroblastoma activity by donor-derived effector cells.

QTL mapping using a memetic algorithm with modifications of BIC as fitness function

The problem of locating quantitative trait loci (QTL) for experimental populations can be approached by multiple regression analysis. In this context variable selection using a modification of the Bayesian Information Criterion (mBIC) has been well established in the past. In this article a memetic algorithm (MA) is introduced to find the model which minimizes the selection criterion. Apart from mBIC also a second modification (mBIC2) is considered, which has the property of controlling the false discovery rate. Given the Bayesian nature of our selection criteria, we are not only interested in finding the best model, but also in computing marker posterior probabilities using all models visited by MA. In a simulation study MA (with mBIC and mBIC2) is compared with a parallel genetic algorithm (PGA) which has been previously suggested for QTL mapping. It turns out that MA in combination with mBIC2 performs best, where determining QTL positions based on marker posterior probabilities yields even better results than using the best model selected by MA. Finally we consider a real data set from the literature and show that MA can also be extended to multiple interval mapping, which potentially increases the precision with which the exact location of QTLs can be estimated.