Our group has conducted extensive basic and preclinical studies of the use of human induced pluripotent cell (iPSC)-derived neural stem/progenitor cell (hiPSC-NS/PC) grafts in models of spinal cord injury (SCI). Evidence from animal experiments suggests this approach is safe and effective. We are preparing to initiate a first-in-human clinical study of hiPSC-NS/PC transplantation in subacute SCI. NS/PCs were prepared at a Good Manufacturing Practice-grade cell processing facility at Osaka National Hospital using a clinical-grade integration-free hiPSC line established by the iPSC Stock Project organized by the Kyoto University Center for iPS Cell Research and Application. After performing all quality checks, the long-term safety and efficacy of cells were confirmed using immunodeficient mouse models. The forthcoming clinical study uses an open-label, single-arm design. The initial follow-up period is 1 year. The primary objective is to assess the safety of hiPSC-NS/PC transplantation in patients with subacute SCI. The secondary objective is to obtain preliminary evidence of its impact on neurological function and quality-of-life outcomes. Four patients with C3/4-Th10 level, complete subacute (within 24 days post-injury) SCI will be recruited. After obtaining consent, cryopreserved cells will be thawed and prepared following a multi-step process including treatment with a γ-secretase inhibitor to promote cell differentiation. A total of 2 × 10⁶ cells will be transplanted into the injured spinal cord parenchyma 14–28 days post-injury. Patients will also receive transient immunosuppression. This study protocol has been reviewed and approved by the Certified Committee for Regenerative Medicine and the Japanese Ministry of Health, Labor and Welfare (University Hospital Medical Information Network Clinical Trials Registry [UMIN-CTR] number, UMIN000035074; Japan Registry of Clinical Trials [jRCT] number, jRCTa031190228). We plan to start recruiting a patient as soon as the COVID-19 epidemic subsides. The primary focus of this clinical study is safety, and the number of transplanted cells may be too low to confirm efficacy. After confirming safety, a dose-escalation study is planned.

Medulloblastoma (MB) is one of the most frequent malignant brain tumors in children. The current standard treatment regimen consists of surgical resection, craniospinal irradiation, and adjuvant chemotherapy. Although these treatments have the potential to increase the survival of 70-80% of patients with MB, they are also associated with serious treatment-induced morbidity. The current risk stratification of MB is based on clinical factors, including age at presentation, metastatic status, and the presence of residual tumor following resection. In addition, recent genomic studies indicate that MB consists of at least four distinct molecular subgroups: WNT, sonic hedgehog (SHH), Group 3, and Group 4. WNT and SHH MBs are characterized by aberrations in the WNT and SHH signaling pathways, respectively. WNT MB has the best prognosis compared to the other MBs, while SHH MB has an intermediate prognosis. The underlying signaling pathways associated with Group 3 and 4 MBs have not been identified. Group 3 MB is frequently associated with metastasis, resulting in a poor prognosis, while Group 4 is sometimes associated with metastasis and has an intermediate prognosis. Group 4 is the most frequent MB and represents 35% of all MBs. These findings suggest that MB is a heterogeneous disease, and that MB subgroups have distinct molecular, demographic, and clinical characteristics. The molecular classification of MBs is redefining the risk stratification of patients with MB, and has the potential to identify new therapeutic strategies for the treatment of MB.

TERT promoter mutations are commonly associated with 1p/19q codeletion in IDH-mutated gliomas. However, whether these mutations have an impact on patient survival independent of 1p/19q codeletion is unknown. In this study, we investigated the impact of TERT promoter mutations on survival in IDH-mutated glioma cases. Detailed clinical information and molecular status data were collected for a cohort of 560 adult patients with IDH-mutated gliomas. Among these patients, 279 had both TERT promoter mutation and 1p/19q codeletion, while 30 had either TERT promoter mutation (n = 24) or 1p/19q codeletion (n = 6) alone. A univariable Cox proportional hazard analysis for survival using clinical and genetic factors indicated that a Karnofsky performance status score (KPS) of 90 or 100, WHO grade II or III, TERT promoter mutation, 1p/19q codeletion, radiation therapy, and extent of resection (90–100%) were associated with favorable prognosis (p < 0.05). A multivariable Cox regression model revealed that TERT promoter mutation had a significantly favorable prognostic impact (hazard ratio = 0.421, p = 0.049), while 1p/19q codeletion did not have a significant impact (hazard ratio = 0.648, p = 0.349). Analyses incorporating patient clinical and genetic information were further conducted to identify subgroups showing the favorable prognostic impact of TERT promoter mutation. Among the grade II-III glioma patients with a KPS score of 90 or 100, those with IDH-TERT co-mutation and intact 1p/19q (n = 17) showed significantly longer survival than those with IDH mutation, wild-type TERT, and intact 1p/19q (n = 185) (5-year overall survival, 94% and 77%, respectively; p = 0.032). Our results demonstrate that TERT promoter mutation predicts favorable prognosis independent of 1p/19q codeletion in IDH-mutated gliomas. Combined with its adverse effect on survival among IDH-wild glioma cases, the bivalent prognostic impact of TERT promoter mutation may help further refine the molecular diagnosis and prognostication of diffuse gliomas.

Machine learning models for automated magnetic resonance image segmentation may be useful in aiding glioma detection. However, the image differences among facilities cause performance degradation and impede detection. This study proposes a method to solve this issue. We used the data from the Multimodal Brain Tumor Image Segmentation Benchmark (BraTS) and the Japanese cohort (JC) datasets. Three models for tumor segmentation are developed. In our methodology, the BraTS and JC models are trained on the BraTS and JC datasets, respectively, whereas the fine-tuning models are developed from the BraTS model and fine-tuned using the JC dataset. Our results show that the Dice coefficient score of the JC model for the test portion of the JC dataset was 0.779 ± 0.137, whereas that of the BraTS model was lower (0.717 ± 0.207). The mean Dice coefficient score of the fine-tuning model was 0.769 ± 0.138. There was a significant difference between the BraTS and JC models (p < 0.0001) and the BraTS and fine-tuning models (p = 0.002); however, no significant difference between the JC and fine-tuning models (p = 0.673). As our fine-tuning method requires fewer than 20 cases, this method is useful even in a facility where the number of glioma cases is small.

The diagnosis and prognostication of glioblastoma (GBM) remain to be solely dependent on histopathological findings and few molecular markers, despite the clinical heterogeneity in this entity. To address this issue, we investigated the prognostic impact of copy number alterations (CNAs) using two population-based IDH-wild-type GBM cohorts: an original Japanese cohort and a dataset from The Cancer Genome Atlas (TCGA). The molecular disproportions between these cohorts were dissected in light of cohort differences in GBM. The Japanese cohort was collected from cases registered in Kansai Molecular Diagnosis Network for CNS tumors (KNBTG). The somatic landscape around CNAs was analyzed for 212 KNBTG cases and 359 TCGA cases. Next, the clinical impacts of CNA profiles were investigated for 140 KNBTG cases and 152 TCGA cases treated by standard adjuvant therapy using temozolomide-based chemoradiation. The comparative profiling indicated unequal distribution of specific CNAs such as EGFR, CDKN2A, and PTEN among the two cohorts. Especially, the triple overlap CNAs in these loci (triple CNA) were much higher in frequency in TCGA (70.5%) than KNBTG (24.3%), and its prognostic impact was independently validated in both cohorts. The KNBTG cohort significantly showed better prognosis than the TCGA cohort (median overall survival 19.3 vs 15.6 months). This survival difference between the two cohorts completely resolved after subclassifying all cases according to the triple CNA status. The prognostic significance of triple CNA was identified in IDH-wild-type GBM. Distribution difference in prognostic CNA profiles potentially could cause survival differences across cohorts in clinical studies.