Integrative Genomic and Transcriptomic Analysis of Primary Malignant Gliomas Revealed Different Patterns Between Grades and Somatic Mutations Related to Glioblastoma Prognosis

Comparative genomic landscape of lower-grade glioma and glioblastoma

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.

On the Boundary of Exploratory Genomics and Translation in Sequential Glioblastoma

OMICS methods brought significant advancements to the understanding of tumor cell biology, which transformed the treatment and prognosis of several cancers. Clinical practice and outcomes, however, changed significantly less in the case of glioblastoma (GBM). In this study, we aimed to assess the utility of whole exome (WES) sequencing in the clinical setting. Ten pairs of formalin-fixed, paraffin-embedded (FFPE) GBM specimens were obtained at onset (GBM-P) and at recurrence (GBM-R). Histopathological and molecular features of all samples supported the diagnosis of GBM based on WHO CNS5. WES data were filtered, applying a strict and custom-made pipeline, and occurrence of oncogenic and likely oncogenic variants in GBM-P, GBM-R or both were identified by using the VarSeq program version 2.5.0 (Golden Helix, Inc.). Characteristics and recurrence of the variants were analyzed in our own cohort and were also compared to those available in the COSMIC database. The lists of oncogenic and likely oncogenic variants corresponded to those identified in other studies. The average number of these variants were 4 and 5 out of all detected 24 and 34 variants in GBM-P and GBM-R samples, respectively. On average, one shared oncogenic/likely oncogenic variant was found in the pairs. We assessed the identified variants' therapeutic significance, also taking into consideration the guidelines by the Association for Molecular Pathology (AMP). Our data support that a thorough WES analysis is suitable for identifying oncogenic and likely oncogenic variants in an individual clinical sample or a small cohort of FFPE glioma specimens, which concur with those of comprehensive research studies. Such analyses also allow us to monitor molecular dynamics of sequential GBM. In addition, careful evaluation of data according to the AMP guideline reveal that though therapeutic applicability of the variants is generally limited in the clinic, such information may be valuable in selected cases, and can support innovative preclinical and clinical trials.

Comprehensive somatic mutational analysis in glioblastoma: Implications for precision medicine approaches

Glioblastoma multiforme (GBM), a malignant neoplasm originating from glial cells, remains challenging to treat despite the current standard treatment approach that involves maximal safe surgical resection, radiotherapy, and adjuvant temozolomide chemotherapy. This underscores the critical need to identify new molecular targets for improved therapeutic interventions. The current study aimed to explore the somatic mutations and potential therapeutic targets in GBM using somatic mutational information from four distinct GBM datasets including CGGA, TCGA, CPTAC and MAYO-PDX. The analysis included the evaluation of whole exome sequencing (WES) of GBM datasets, tumor mutation burden assessment, survival analysis, drug sensitivity prediction, and examination of domain-specific amino acid changes. The results identified the top ten commonly altered genes in the aforementioned GBM datasets and patients with mutations in OBSCN and AHNAK2 alone or in combination had a more favorable overall survival (OS). Also, the study identified potential drug sensitivity patterns in GBM patients with mutations in OBSCN and AHNAK2, and evaluated the impact of amino acid changes in specific protein domains on the survival of GBM patients. These findings provide important insights into the genetic alterations and somatic interactions in GBM, which could have implications for the development of new therapeutic strategies for this aggressive malignancy.