see Glioma biomarkers.
The management of gliomas is based on precise histologic diagnosis. The tumor tissue can be obtained during open surgery or via stereotactic biopsy. Intraoperative tissue imaging could substantially improve biopsy precision and, ultimately, the extent of resection.
While a change in tumor classification aims to improve patient management and treatment, it implies the requirement for invasive tissue sampling to the detriment of potentially severe biopsy and/or surgical complications, resulting in a mortality rate of 2.8% 1).
As a result, there is a high demand for non-invasive tissue analysis to initiate adequate therapy regimens without potential biopsy-associated side effects. In particular, this is true for inoperable tumors that would be solely biopsied. Over the past few years, a number of studies demonstrated the great potential of MRI-based image analyses for the tumor decoding of gliomas 2).
Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments.
In the past, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use.
Technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future 3).
Ferreyra Vega et al. investigated the potential utility of DNA methylation profiling to achieve molecular diagnosis in adult primary diffuse lower-grade glioma (dLGG) according to the World Health Organization Classification of Tumors of the Central Nervous System 2016. They also evaluated whether methylation profiling could provide improved molecular characterization and identify prognostic differences beyond the classical histological WHO grade together with IDH mutation status and 1p/19q co-deletion status. All patients diagnosed with dLGG in the period 2007-2016 from the Västra Götaland region in Sweden were assessed for inclusion in the study.
A total of 166 dLGG cases were subjected to genome-wide DNA methylation analysis. Of these, 126 (76%) were assigned a defined diagnostic methylation class with a class prediction score ≥ 0.84 and a subclass score ≥ 0.50. The assigned methylation classes were highly associated with their IDH mutation status and 1p/19q codeletion status. IDH-wild-type gliomas were further divided into subgroups with distinct molecular features.
The stratification of the patients by methylation profiling was as effective as the integrated WHO 2016 molecular reclassification at predicting the clinical outcome of the patients. The study shows that DNA methylation profiling is a reliable and robust approach for the classification of dLGG into molecularly defined subgroups, providing accurate detection of molecular markers according to WHO 2016 classification 4).
Conventional genetic analyzers require surgically obtained tumor tissues to confirm the molecular diagnostics of diffuse glioma. Recent technical breakthroughs have enabled increased utilization of circulating tumor DNA (ctDNA) in body fluids as a reliable resource for molecular diagnosis in various cancers.
Fujioka et al. tested the application of a chip-based digital PCR system for the less invasive diagnosis (i.e., liquid biopsy) of diffuse glioma using the cerebrospinal fluid (CSF).
CSF samples from 34 patients with diffuse glioma were collected from the surgical field during craniotomy. Preoperative lumbar CSF collection was also performed in 11 patients. Extracted ctDNA was used to analyze diagnostic point mutations in IDH1 R132H, TERT promoter (C228T and C250T), and H3F3A (K27M) on the QuantStudio® 3D Digital PCR System. These results were compared with their corresponding tumor DNA samples.
They detected either of the diagnostic mutations in tumor DNA samples from 28 of 34 patients. Among them, they achieved precise molecular diagnoses using intracranial CSF in 20 (71%). Univariate analyses revealed that the World Health Organization (WHO) grade (p = 0.0034), radiographic enhancement (p = 0.0006), and Mib1 index (p = 0.01) were significant predictors of precise CSF-based molecular diagnosis. They precisely diagnosed WHO grade III or IV diffuse gliomas using lumbar CSF obtained from 6 (87%) of 7 patients with tumors harboring any mutation.
Fujioka et al. established a novel, non-invasive molecular diagnostics using a chip-based digital PCR system targeting circulating tumor DNA derived from CSF with high sensitivity and specificity, especially for high-grade gliomas 5).
Apparent diffusion coefficient (ADC) values had a better correlation with overall survival than relative cerebral blood flow (CBV) values. A preoperative prognostic model based on patient age, relative cerebral blood volume, and ADC values predicted overall survival of patients with diffuse gliomas independent of pathology 6).