Safety, Feasibility, and Advantages of Oral Microbiota Transplantation: The First Clinical Case.

The pilot clinical study presented demonstrates the possibility, safety, and effectiveness of oral microbiota transplantation from a healthy donor to a patient with neuroblastoma to prevent chemotherapy-induced oral mucositis. A 6-month-old patient with a diagnosis of retroperitoneal neuroblastoma was treated according to the NB 2004 protocol. Due to the development of severe oral mucositis, it was decided to perform oral microbiota transplantation. During the next 3 chemotherapy cycles and conditioning regimen before autologous hematopoietic cell transplantation (auto-HCT), the patient was repeatedly injected per os with donor saliva from her healthy mother. Oral microbiota transplantation was shown to effectively prevent the development of oral mucositis after chemotherapy, and only grade 1 oral mucositis developed after auto-HCT. In all loci of the oral cavity, there was a decreased abundance of bacteria from the Staphylococcaceae, Micrococcaceae, and Xanthomonadaceae families. Conversely, there was an increase in the relative abundance of Streptococcaceae and certain other bacterial taxa. In conclusion, the transplantation of maternal saliva in this patient prevented severe mucositis and was accompanied by a compositional change of the patient's oral microbiota. No adverse events due to the transplantation of maternal saliva were noted.

A pilot study of implication of machine learning for relapse prediction after allogeneic stem cell transplantation in adults with Ph-positive acute lymphoblastic leukemia.

The posttransplant relapse in Ph-positive ALL increases the risk of death. There is an unmet need for instruments to predict the risk of relapse and plan prophylaxis. In this study, we analyzed posttransplant data by machine learning algorithms. Seventy-four Ph-positive ALL patients with a median age of 30 (range 18-55) years who previously underwent allo-HSCT, were retrospectively enrolled. Ninety-three percent of patients received prophylactic/preemptive TKIs after allo-HSCT. The values of the BCR::ABL1 level at serial assessments and over variables were collected in specified intervals after allo-HSCT. They were used to model relapse risk with several machine-learning approaches. GBM proved superior to the other algorithms and provided a maximal AUC score of 0.91. BCR::ABL1 level before and after allo-HSCT, prediction moment, and chronic GvHD had the highest value in the model. It was shown that after Day + 100, both error rates do not exceed 22%, while before D + 100, the model fails to make accurate predictions. As a result, we determined BCR::ABL1 levels at which the relapse risk remains low. Thus, the current BCR::ABL1 level less than 0.06% in patients with chronic GvHD predicts low risk of relapse. At the same time, patients without chronic GVHD after allo-HSCT should be classified as high risk with any level of BCR::ABL1. GBM model with posttransplant laboratory values of BCR::ABL1 provides a high prediction of relapse after allo-HSCT in the era of TKIs prophylaxis. Validation of this approach is warranted.

Identification and Characterization of a Novel CLCN7 Variant Associated with Osteopetrosis.

Osteopetrosis is a group of rare inheritable disorders of the skeleton characterized by increased bone density. The disease is remarkably heterogeneous in clinical presentation and often misdiagnosed. Therefore, genetic testing and molecular pathogenicity analysis are essential for precise diagnosis and new targets for preventive pharmacotherapy. Mutations in the CLCN7 gene give rise to the complete spectrum of osteopetrosis phenotypes and are responsible for about 75% of cases of autosomal dominant osteopetrosis. In this study, we report the identification of a novel variant in the CLCN7 gene in a patient diagnosed with osteopetrosis and provide evidence for its significance (likely deleterious) based on extensive comparative genomics, protein sequence and structure analysis. A set of automated bioinformatics tools used to predict consequences of this variant identified it as deleterious or pathogenic. Structure analysis revealed that the variant is located at the same "hot spot" as the most common CLCN7 mutations causing osteopetrosis. Deep phylogenetic reconstruction showed that not only Leu614Arg, but any non-aliphatic substitutions in this position are evolutionarily intolerant, further supporting the deleterious nature of the variant. The present study provides further evidence that reconstructing a precise evolutionary history of a gene helps in predicting phenotypical consequences of variants of uncertain significance.