A prospective study of inflammatory biomarkers and growth factors and risk of glioma in the UK Biobank

Recent Developments in Blood Biomarkers in Neuro-oncology

PURPOSE OF REVIEW

Given the invasive and high-risk nature of brain surgery, the need for non-invasive biomarkers obtained from the peripheral blood is greatest in tumors of the central nervous system (CNS). In this comprehensive review, we highlight recent advances in blood biomarker development for adult and pediatric brain tumors.

RECENT FINDINGS

We summarize recent blood biomarker development for CNS tumors across multiple key analytes, including peripheral blood mononuclear cells, cell-free DNA, cell-free RNA, proteomics, circulating tumor cells, and tumor-educated platelets. We also discuss methods for enhancing blood biomarker detection through transient opening of the blood-brain barrier. Although blood-based biomarkers are not yet used in routine neuro-oncology practice, this field is advancing rapidly and holds great promise for improved and non-invasive management of patients with brain tumors. Prospective and adequately powered studies are needed to confirm the clinical utility of any blood biomarker prior to widespread clinical implementation.

Pre-diagnostic blood biomarkers for adult glioma

Glioma is one of the most common malignant primary brain tumours in adults, of which, glioblastoma is the most prevalent and malignant entity. Glioma is often diagnosed at a later stage of disease progression, which means it is associated with significant mortality and morbidity. Therefore, there is a need for earlier diagnosis of these tumours, which would require sensitive and specific biomarkers. These biomarkers could better predict glioma onset to improve diagnosis and therapeutic options for patients. While liquid biopsies could provide a cheap and non-invasive test to improve the earlier detection of glioma, there is little known on pre-diagnostic biomarkers which predate disease detection. In this review, we examine the evidence in the literature for pre-diagnostic biomarkers in glioma, including metabolomics and proteomics. We also consider the limitations of these approaches and future research directions of pre-diagnostic biomarkers for glioma.

Prediagnostic biomarkers for early detection of glioma—using case–control studies from cohorts as study approach

Background

Understanding the trajectory and development of disease is important and the knowledge can be used to find novel targets for therapy and new diagnostic tools for early diagnosis.

Methods

Large cohorts from different parts of the world are unique assets for research as they have systematically collected plasma and DNA over long-time periods in healthy individuals, sometimes even with repeated samples. Over time, the population in the cohort are diagnosed with many different diseases, including brain tumors.

Results

Recent studies have detected genetic variants that are associated with increased risk of glioblastoma and lower grade gliomas specifically. The impact for genetic markers to predict disease in a healthy population has been deemed low, and a relevant question is if the genetic variants for glioma are associated with risk of disease or partly consist of genes associated to survival. Both metabolite and protein spectra are currently being explored for early detection of cancer.

Conclusions

We here present a focused review of studies of genetic variants, metabolomics, and proteomics studied in prediagnostic glioma samples and discuss their potential in early diagnostics.

Systemic inflammatory biomarkers in primary central nervous system lymphoma versus high-grade glioma: exploratory, comparative and correlative analysis

Aim:

To assess systemic inflammatory biomarkers in non invasive differential diagnosis of primary central nervous system lymphoma (PCNSL) from high-grade glioma (HGG).

Materials & methods:

Patients with similar morphology (PCNSL or HGG) on conventional neuro-imaging were included. Systemic inflammatory indices were calculated from pretreatment complete blood counts and liver function tests and compared against histopathology as reference standard.

Results:

Mean values of absolute lymphocyte count and prognostic nutritional index were significantly different between PCNSL (n = 42) versus HGG (n = 16). Area under receiver operating characteristics curve for absolute lymphocyte count and prognostic nutritional index in the diagnosis of PCNSL was 0.70 and 0.72 respectively suggesting fair and acceptable diagnostic accuracy.

Conclusion:

Systemic inflammatory biomarkers complement established clinico-radiological features and aid in the differential diagnosis of PCNSL from HGG.

There exists a complex interplay between cancer and inflammation that can manifest as increased inflammatory biomarkers in blood. However, utility of systemic inflammatory biomarkers in the non invasive differential diagnosis of primary brain lymphoma from high-grade glioma is generally lacking. Two simple serum biomarkers, absolute lymphocyte count and prognostic nutritional index, easily derived from routine pretreatment blood tests have fair correlation and acceptable diagnostic accuracy in differentiating brain lymphoma from glioma in patients with similar morphology on MRI.