ArticlePloS one2009
Transitions at CpG dinucleotides, geographic clustering of TP53 mutations and food availability patterns in colorectal cancer.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 8 citations in OpenAlex.
- High polygenic risk score is a risk factor associated with colorectal cancer based on data from the UK Biobank.PloS one · 2023Article
- How does inflammation drive mutagenesis in colorectal cancer?Trends in cancer research · 2017Article
- Epidemiological transition of colorectal cancer in developing countries: environmental factors, molecular pathways, and opportunities for prevention.World journal of gastroenterology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColorectal cancer is mainly attributed to diet, but the role exerted by foods remains unclear because involved factors are extremely complex. Geography substantially impacts on foods. Correlations between international variation in colorectal cancer-associated mutation patterns and food availabilities could highlight the influence of foods on colorectal mutagenesis. METHODOLOGY: To test such hypothesis, we applied techniques based on hierarchical clustering, feature extraction and selection, and statistical pattern recognition to the analysis of 2,572 colorectal cancer-associated TP53 mutations from 12 countries/geographic areas. For food availabilities, we relied on data extracted from the Food Balance Sheets of the Food and Agriculture Organization of the United Nations. Dendrograms for mutation sites, mutation types and food patterns were constructed through Ward's hierarchical clustering algorithm and their stability was assessed evaluating silhouette values. Feature selection used entropy-based measures for similarity between clusterings, combined with principal component analysis by exhaustive and heuristic approaches. CONCLUSION/SIGNIFICANCE: Mutations clustered in two major geographic groups, one including only Western countries, the other Asia and parts of Europe. This was determined by variation in the frequency of transitions at CpGs, the most common mutation type. Higher frequencies of transitions at CpGs in the cluster that included only Western countries mainly reflected higher frequencies of mutations at CpG codons 175, 248 and 273, the three major TP53 hotspots. Pearson's correlation scores, computed between the principal components of the datamatrices for mutation types, food availability and mutation sites, demonstrated statistically significant correlations between transitions at CpGs and both mutation sites and availabilities of meat, milk, sweeteners and animal fats, the energy-dense foods at the basis of "Western" diets. This is best explainable by differential exposure to nitrosative DNA damage due to foods that promote metabolic stress and chronic inflammation.
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.