RESUMO
Glioblastoma, the most common malignant brain tumor in adults, is associated with a median overall survival duration of less than 2 years. Extraneural metastases occur in less than 1% of all patients with glioblastoma. The mechanism of extraneural metastasis is unclear. We present a case of extensive extraneural, extraosseous, epidural, and soft-tissue metastasis of glioblastoma. The diagnosis of metastatic glioblastoma was made only after next-generation sequencing (NGS) of the metastatic paraspinal lesions was completed. The CDK4, pTERT, PTEN, and TP53 molecular alterations seen in the initial intracranial glioblastoma were found in the paraspinal tumor, along with the addition of MYC, which is implicated in angiogenesis and epidermal-to-mesenchymal transition. Immunohistochemical stains showed that neoplastic cells were negative for GFAP. In conclusion, this case raises awareness about the role of NGS in the diagnosis of extraneural glioblastoma. This diagnosis was not possible with histology alone and only became evident after molecular profiling of the metastatic lesions and its comparison to the original tumor.
RESUMO
Choosing the right drug(s) for the right patient via advanced genomic sequencing and multi-omic interrogation is the sine qua non of precision cancer medicine. Traditional cancer clinical trial designs follow well-defined protocols to evaluate the efficacy of new therapies in patient groups, usually identified by their histology/tissue of origin of their malignancy. In contrast, precision medicine seeks to optimize benefit in individual patients, i.e., to define who benefits rather than determine whether the overall group benefits. Since cancer is a disease driven by molecular alterations, innovative trial designs, including biomarker-defined tumor-agnostic basket trials, are driving ground-breaking regulatory approvals and deployment of gene- and immune-targeted drugs. Molecular interrogation further reveals the disruptive reality that advanced cancers are extraordinarily complex and individually distinct. Therefore, optimized treatment often requires drug combinations and N-of-1 customization, addressed by a new generation of N-of-1 trials. Real-world data and structured master registry trials are also providing massive datasets that are further fueling a transformation in oncology. Finally, machine learning is facilitating rapid discovery, and it is plausible that high-throughput computing, in silico modeling, and 3-dimensional printing may be exploitable in the near future to discover and design customized drugs in real time.