Evidence map›Paper›PMID 41825704›Full record

ArticleAnalytical biochemistry2026

Coupled-enzyme assay for MTAP activity in biological samples.

Nord Gilaj, Andrew G Wagner, Terence Li, Dior Dedushi, Roozbeh Eskandari, Chaoyuan Kuang, Vern L Schramm

Abstract read
In one paragraph

Article in Analytical biochemistry, 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

7 authors.

Nord GilajDepartment of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Andrew G WagnerDepartment of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Terence LiDepartments of Medicine, Oncology and Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Dior DedushiDepartments of Medicine, Oncology and Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Roozbeh EskandariDepartment of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Chaoyuan KuangDepartments of Medicine, Oncology and Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, 10461, United States.
Vern L SchrammDepartment of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, United States. Electronic address: vern.schramm@einsteinmed.edu.

Funding

Targeting the PNP - SAMHD1 synthetic-lethal combination in cancerR01CA290537 · NCI · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI Vern L. Schramm · 2024 to 2026
$1.8M
NCI NIH HHS R01 CA290537
6 · The paper itself

Abstract

5'-Methylthioadenosine phosphorylase (MTAP) catalyzes the reversible phosphorolysis of 5'-methylthioadenosine (MTA), a product of polyamine synthesis. The resulting products, adenine and 5-methylthio-α-d-ribose 1-phosphate (MTR-1-P), are salvaged to the adenylate and methionine pathways. Homozygous deletion of MTAP occurs in approximately 15% of all human cancers due to its chromosomal proximity to the CDKN2A/B locus. Loss of MTAP creates a metabolic vulnerability to PRMT5 and MAT2A inhibition, resulting in a synthetic lethal interaction. Consequently, MTAP has emerged as a target for enzymatic inhibition to enable synthetic lethal strategies in the 85% of cancers that are MTAP

Indexed as

Enzyme AssaysPurine-Nucleoside PhosphorylaseHumans5'-methylthioadenosine phosphorylasePurine-Nucleoside PhosphorylaseAdenine detectionContinuous enzyme assayIn vivo enzyme assayMethionine pathwaySynthetic-lethal interactions

Identifiers

PMID41825704
PMCPMC13316717

What OpenQuestion holds

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Registered trials

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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.