ReviewMedScience2026
Proteogenomics: decoding cancer in multiple dimensions.
Review in MedScience, 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A key challenge in cancer precision oncology is the limited ability of genomic analyses to accurately predict changes in protein expression or function, even though proteins serve as the main targets of numerous modern therapies. Bridging this gap necessitates precise quantification of proteins and their post-translational modifications (PTMs). Recent advances in mass spectrometry (MS)-based proteomics now enable large-scale, quantitative characterization of proteins and PTMs in tumor tissues. To link genomic aberrations to cancer phenotypes, the emerging field of proteogenomics integrates proteomic data, including PTMs, with genomic, epigenomic, and transcriptomic information. This comprehensive approach offers a deeper understanding of cancer biology at multiple levels. This review highlights recent advancements in MS-based proteomics, key discoveries in cancer proteogenomics, and the transformative potential of this field in decoding the complexities of cancer across diverse dimensions.
Indexed as
Identifiers
42008080What 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.