Evidence map›Paper›PMID 42639360›Full record

ReviewFrontiers in oncology2026

Review of glioblastoma and systemic comorbidities.

Zhang Tianqing, Guo Yuan, Yu Qianyi, Li Yanchu

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhang TianqingOutpatient Department, West China Hospital of Sichuan University, Chengdu, China.
Guo YuanNursing Department, West China Hospital of Sichuan University, Chengdu, China.
Yu QianyiHead & Neck Oncology Ward, West China Hospital of Sichuan University, Chengdu, China.
Li YanchuHead & Neck Oncology Ward, West China Hospital of Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma (GBM) is a highly aggressive malignancy with a poor prognosis. Despite advanced molecular characterization, the traditional tumor-centric model ignores the patient's systemic body condition, which significantly influences disease progression and therapeutic outcomes. This review aims to elucidate the interactions between GBM and systemic comorbidities, focusing on metabolic, immune, and vascular networks. A key feature is activity-dependent gliomagenesis, in which neuronal firing via Neuroligin-3 (NLGN3) and glutamatergic signaling fuels tumor growth. This process confers a substantial cognitive reserve, thereby attenuating or masking early clinical manifestations via functional compensatory mechanisms; however, it may concomitantly promote rapid tumor proliferation. Overall, combined diabetes, glutamine-induced and hyperglycemia or dexamethasone-induced hyperglycemia may trigger tumor aggressive. The prothrombotic nature of GBM complicates the use of anti-angiogenic therapies. Thus, GBM and its comorbidities can be seen as metabolic-immune and vascular-cardiovascular cycles. Furthermore, chronic Hepatitis B (HBV) infection poses a unique risk of fatal reactivation during therapy in endemic regions, such as China. Consequently, real-world GBM management requires a shift from an isolated oncological to a patient-centric approach. Addressing systemic health disparities and the intrinsic interplay of comorbidities is essential to optimize treatment protocols and improve patient survival.

Indexed as

cognitive reservecomorbidity networksglioblastomahealth disparitiespharmacological interactions

Identifiers

PMID42639360
PMCPMC13501362

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.