ArticleProceedings of the National Academy of Sciences of the United States of America2026
Mining cancer genomes for copy number alterations identifies glycosylation enzymes as oncogenic drivers.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Altered cell-surface glycans are established cancer biomarkers, yet no oncogenes have been identified within glycan biosynthesis machinery. This represents a critical gap, as defining a gene as a true oncogene, rather than merely a component of an oncogenic pathway, reveals targetable dependencies that can improve clinical decisions. To date, no gain-of-function mutations have been detected in glycogenes, and the search for such mutations is largely saturated. To address this gap, we developed a bioinformatic-experimental pipeline to identify copy number alteration (CNA)-based driver genes, overcoming noise from passenger genes. The approach recovered known oncogenes and tumor suppressors, while revealing novel candidates, including glyco-oncogenes. Focusing on the glycosphingolipid (GSL) biosynthetic pathway, we validated
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.