Evidence map›Paper›PMID 29119048›Full record

ReviewAmerican journal of cancer research2017

Elucidating immunometabolic targets in glioblastoma.

Pooja Agarwal, Michael J Pajor, David M Anson, Maheedhara R Guda, Collin M Labak, Andrew J Tsung, Kiran K Velpula

Abstract readReview
In one paragraph

Review in American journal of cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Metabolic Drivers of Invasion in Glioblastoma.Frontiers in cell and developmental biology · 2021
    Review
  5. Review
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

7 authors.

Pooja AgarwalDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
Michael J PajorDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
David M AnsonDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
Maheedhara R GudaDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
Collin M LabakDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
Andrew J TsungDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.
Kiran K VelpulaDepartment of Cancer Biology and Pharmacology, University of Illinois College of Medicine at PeoriaPeoria, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunometabolism has recently emerged on the forefront of cancer research as a new avenue to potentially develop more effective and targeted treatment options. Several pathologically altered metabolic targets across various cancer types have been identified, including lactate in aerobic glycolysis; tryptophan in amino acid metabolism; and arginine in the urea cycle. Numerous advancements have improved our understanding of the dual function of these targets in influencing immune functions as an auxiliary function to their well-established metabolic role. This paper provides a comprehensive overview of immunometabolism research and attempts to provide insight into potential immunometabolic targets in glioblastoma for the purpose of future development and study of targeted therapies.

Indexed as

Arg1arginineglioblastomaIDOImmunometabolismiNOSlactatelactic acidLDHATDOtryptophan

Identifiers

PMID29119048
PMCPMC5665846

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.