Skip to main content
Premium Trial:

Request an Annual Quote

Secondary Glioblastoma Genomics Study Leads to Proposed Treatment Target

NEW YORK (GenomeWeb) – A research team from China and Korea has characterized the mutations found in secondary glioblastoma (GBM), uncovering potentially-targetable MET alterations in cases with more rampant disease progression and poorer outcomes.

Investigators at Capital Medical University, Hong Kong University, and elsewhere used whole-genome, exome, and/or targeted DNA sequencing to assess samples from 145 East Asian individuals with secondary GBM — a recurrent form of the disease that arose after standard treatment with the non-selective, DNA-damaging chemotherapy temozolomide (TMZ).

Together with RNA sequence data for a subset of the cases, their genomic data revealed hypermutated secondary GBM cases and cases marked by recurrent TP53 mutations, MET amplifications, fusions involving the PTPRZ1-MET genes, and exon skipping events affecting exon 14 of MET.

In a paper published online today in Cell, the team noted that there appeared to be potential for targeting the MET exon 14 skipping and PTPRZ1-MET fusions — which often co-occur — using a MET kinase inhibitor known as PLB-1001. That compound produced promising results in cell line or tumor xenografts experiments, as well as in a phase I clinical trial which included 18 secondary GBM or glioma patients with exon 14-skipped MET or PTPRZ1-MET fusions, the group reported.

"Given the lack of therapeutic options for recurrent tumor[s] under TMZ treatment, our study has provided a promising therapeutic strategy of PLB-1001 mono- and combinatorial treatments with TMZ chemotherapy for patients with MET alterations," the authors wrote.

The researchers brought together samples from 188 secondary GBM patients enrolled through efforts such as the Chinese Glioma Genome Atlas project or at the Samsung Medical Center. Using Illumina instruments, they sequenced genomes, exomes, or a panel of 272 Agilent SureSelect-captured gene sequences in matched tumor and normal samples from 145 cases.

Along with somatic alterations identified from these sequences, the team did RNA sequencing in 78 of the secondary GBM samples to get a closer look at the gene fusions and MET exon 14 skipping events. The latter alterations were present in 14 percent of the cases, and a comparison with available primary GBM and low-grade glioma (LGG) data pointed to particularly low overall survival rates for secondary GBM cases with METex14.

The researchers examined the MET changes in more detail in secondary GBM, primary GBM, and LGG. They found that METex14 alterations — linked to enhanced MET/STAT3 signaling, a boost tumor growth, and tumor gene expression and microenvironment differences — often occurred in conjunction with the PTPRZ1-MET fusions.

Based on the growth inhibition they saw in cell lines treated with several MET inhibitors, the researchers pursued a phase I clinical trial using PLB-1001, which has binding abilities that suggested it should cross the blood brain barrier to get into the brain. In that dose escalation study, which involved nine secondary GBM and nine advanced glioma patients with METex14 or PTPRZ1-MET fusions in their tumors, they reported a partial response in two patients with secondary GBM.

The median response duration spanned more than 62 days, the team noted, while the median progression-free survival reached 80 days during the monotherapy trial.

"Encouragingly, PLB-1001 achieves partial response in at least two advanced [secondary GBM] patients with rarely significant side effects," the authors wrote, "underscoring the clinical potential for precisely treating gliomas using this therapy."

The Scan

Study Links Genetic Risk for ADHD With Alzheimer's Disease

A higher polygenic risk score for attention-deficit/hyperactivity disorder is also linked to cognitive decline and Alzheimer's disease, a new study in Molecular Psychiatry finds.

Study Offers Insights Into Role of Structural Variants in Cancer

A new study in Nature using cell lines shows that structural variants can enable oncogene activation.

Computer Model Uses Genetics, Health Data to Predict Mental Disorders

A new model in JAMA Psychiatry finds combining genetic and health record data can predict a mental disorder diagnosis before one is made clinically.

Study Tracks Off-Target Gene Edits Linked to Epigenetic Features

Using machine learning, researchers characterize in BMC Genomics the potential off-target effects of 19 computed or experimentally determined epigenetic features during CRISPR-Cas9 editing.