The infusion of ex vivo, interleukin-15 and -21-activated donor NK cells after haploidentical HCT in high-risk AML and MDS patients-a randomized trial.

Clinical effect of donor-derived natural killer cell infusion (DNKI) after HLA-haploidentical hematopoietic cell transplantation (HCT) was evaluated in high-risk myeloid malignancy in phase 2, randomized trial. Seventy-six evaluable patients (aged 21-70 years) were randomized to receive DNKI (N = 40) or not (N = 36) after haploidentical HCT. For the HCT conditioning, busulfan, fludarabine, and anti-thymocyte globulin were administered. DNKI was given twice 13 and 20 days after HCT. Four patients in the DNKI group failed to receive DNKI. In the remaining 36 patients, median DNKI doses were 1.0 × 108/kg and 1.4 × 108/kg on days 13 and 20, respectively. Intention-to-treat analysis showed a lower disease progression for the DNKI group (30-month cumulative incidence, 35% vs 61%, P = 0.040; subdistribution hazard ratio, 0.50). Furthermore, at 3 months after HCT, the DNKI patients showed a 1.8- and 2.6-fold higher median absolute blood count of NK and T cells, respectively. scRNA-sequencing analysis in seven study patients showed that there was a marked increase in memory-like NK cells in DNKI patients which, in turn, expanded the CD8+ effector-memory T cells. In high-risk myeloid malignancy, DNKI after haploidentical HCT reduced disease progression. This enhanced graft-vs-leukemia effect may be related to the DNKI-induced, post-HCT expansion of NK and T cells. Clinical trial number: NCT02477787.

Global stabilizing control of large-scale biomolecular regulatory networks.

MOTIVATION: Cellular behavior is determined by complex non-linear interactions between numerous intracellular molecules that are often represented by Boolean network models. To achieve a desired cellular behavior with minimal intervention, we need to identify optimal control targets that can drive heterogeneous cellular states to the desired phenotypic cellular state with minimal node intervention. Previous attempts to realize such global stabilization were based solely on either network structure information or simple linear dynamics. Other attempts based on non-linear dynamics are not scalable. RESULTS: Here, we investigate the underlying relationship between structurally identified control targets and optimal global stabilizing control targets based on non-linear dynamics. We discovered that optimal global stabilizing control targets can be identified by analyzing the dynamics between structurally identified control targets. Utilizing these findings, we developed a scalable global stabilizing control framework using both structural and dynamic information. Our framework narrows down the search space based on strongly connected components and feedback vertex sets then identifies global stabilizing control targets based on the canalization of Boolean network dynamics. We find that the proposed global stabilizing control is superior with respect to the number of control target nodes, scalability, and computational complexity. AVAILABILITY AND IMPLEMENTATION: We provide a GitHub repository that contains the DCGS framework written in Python as well as biological random Boolean network datasets (https://github.com/sugyun/DCGS). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Management of multiple odontogenic keratocysts associated with nevoid basal cell carcinoma syndrome: a case report of 11-year follow-up.

Multiple odontogenic keratocysts (OKC) are a distinguishing feature of nevoid basal cell carcinoma syndrome (NBCCS). Owing to the high recurrence rate of syndromes associated OKCs, complete surgical resection is generally recommended as a definitive treatment. Herein, we report the management of multiple OKCs with marsupialization followed by excision with peripheral ostectomy in an NBCCS patient. We then discuss lesion progression over 11 years of annual follow-ups.