Abstract
Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that
CDKN2A
deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH–wild-type glioma. In all glioma subtypes,
MYC
gain or
MYC-
target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by
MYC
gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.
Machine learning of 544 initial-recurrent glioma pairs identified c-MYC as an early predictor of hypermutation and histological grade progression.
Diffuse gliomas are the most common primary brain tumors in adults, and the underlying molecular mechanism of its evolution is unknown. To shed light on this, Mu
et al
. collected 544 matching initial and recurrent samples from patients with diffuse glioma and performed whole-genome sequencing to evaluate correlations to progression. They identified that MYC gain or activation at diagnosis correlated to the worst patient prognosis and was able to drive temozolomide resistance in vitro. These data provide a resource that can lead to potential targets for therapy to overcome these therapeutic limitations in diffuse gliomas. —Dorothy Hallberg