ArticlePLoS computational biology2019
The impact of DNA methylation on the cancer proteome.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 12 citations in OpenAlex.
- Methylome-proteome integration after late-life voluntary exercise training reveals regulation and target information for improved skeletal muscle health.The Journal of physiology · 2025Article
- Detection and clinical significance of CEACAM5 methylation in colorectal cancer patients.Cancer science · 2024Article
- Identifying possible hub genes and biological mechanisms shared between bladder cancer and inflammatory bowel disease using machine learning and integrated bioinformatics.Journal of cancer research and clinical oncology · 2023Article
- DNA Methylation in the Fields of Prenatal Diagnosis and Early Detection of Cancers.International journal of molecular sciences · 2023Review
- Epigenetic inactivation of DNA repair genes as promising prognostic and predictive biomarkers in urothelial bladder carcinoma patients.Molecular genetics and genomics : MGG · 2022Article
- Crosstalk Between Inflammatory Signaling and Methylation in Cancer.Frontiers in cell and developmental biology · 2021Review
- High BLM Expression Predicts Poor Clinical Outcome and Contributes to Malignant Progression in Human Cholangiocarcinoma.Frontiers in oncology · 2021Article
- Molecular Mechanisms of Colon Cancer Progression and Metastasis: Recent Insights and Advancements.International journal of molecular sciences · 2020Review
- Whole slide images reflect DNA methylation patterns of human tumors.NPJ genomic medicine · 2020Article
- Comprehensive analysis of DNA methylation and gene expression profiles in cholangiocarcinoma.Cancer cell international · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Aberrant DNA methylation disrupts normal gene expression in cancer and broadly contributes to oncogenesis. We previously developed MethylMix, a model-based algorithmic approach to identify epigenetically regulated driver genes. MethylMix identifies genes where methylation likely executes a functional role by using transcriptomic data to select only methylation events that can be linked to changes in gene expression. However, given that proteins more closely link genotype to phenotype recent high-throughput proteomic data provides an opportunity to more accurately identify functionally relevant abnormal methylation events. Here we present a MethylMix analysis that refines nominations for epigenetic driver genes by leveraging quantitative high-throughput proteomic data to select only genes where DNA methylation is predictive of protein abundance. Applying our algorithm across three cancer cohorts we find that using protein abundance data narrows candidate nominations, where the effect of DNA methylation is often buffered at the protein level. Next, we find that MethylMix genes predictive of protein abundance are enriched for biological processes involved in cancer including functions involved in epithelial and mesenchymal transition. Moreover, our results are also enriched for tumor markers which are predictive of clinical features like tumor stage and we find clustering using MethylMix genes predictive of protein abundance captures cancer subtypes.
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.