ReviewInternational journal of molecular sciences2025
The Link Between Human Alkyladenine DNA Glycosylase and Cancer Development.
Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Substrate-Specific Inactivation of Human AAG by Tumor-Associated Single Nucleotide Polymorphic Variants.International journal of molecular sciences · 2026Article
- UV-DDB as a Dynamic Regulator Linking Base Excision and Nucleotide Excision Repair via AAG Interaction.International journal of molecular sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Alkyladenine DNA glycosylase (AAG) is a critical enzyme in the base excision repair (BER) pathway, responsible for removing a broad spectrum of alkylated DNA lesions. While AAG maintains genomic stability, dysregulated activity has been implicated in cancer development, drug resistance, and neurodegenerative diseases. This review synthesizes the current knowledge on AAG's structure, catalytic mechanism, and polymorphic variants, highlighting their potential roles in disease pathogenesis. A comprehensive bioinformatics analysis of over 370 AAG single-nucleotide polymorphisms (SNPs) is presented, identifying ~40% as high-risk variants likely to impair enzymatic function. Notably, 151 SNPs were predicted to be damaging by multiple algorithms, including substitutions at catalytic residues and non-conserved sites with unknown functional consequences. Analysis of cancer databases (COSMIC, cBioPortal, NCBI) revealed 93 tumor-associated AAG variants, with 18 classified as high-impact mutations. This work underscores the need for mechanistic studies of AAG variants using structural biology, cellular models, and clinical correlation analyses. Deciphering AAG's polymorphic landscape may unlock personalized strategies for cancer prevention and treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.