Evidence map›Paper›PMID 37461500›Full record

ArticlebioRxiv : the preprint server for biology2023

Epigenetic Germline Variants Predict Cancer Prognosis and Risk and Distribute Uniquely in Topologically Associating Domains.

Shervin Goudarzi, Meghana Pagadala, Adam Klie, James V Talwar, Hannah Carter

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a highly heterogeneous disease caused by genetic and epigenetic alterations in normal cells. A recent study uncovered methylation quantitative trait loci (meQTLs) associated with different levels of local DNA methylation in cancers. Here, we investigated whether the distribution of cancer meQTLs reflected functional organization of the genome in the form of chromatin topologically associated domains (TADs), and evaluated whether cancer meQTLs near known driver genes have the potential to influence cancer risk or progression. At TAD boundaries, we observed differences in the distribution of meQTLs when one or both of the adjacent TADs was transcriptionally active, with higher densities near inactive TADs. Furthermore, we found differences in cancer meQTL distributions in active versus inactive TADs and observed an enrichment of meQTLs in active TADs near tumor suppressors, whereas there was a depletion of such meQTLs near oncogenes. Several meQTLs were associated with cancer risk in the UKBioBank, and we were able to reproduce breast cancer risk associations in the DRIVE cohort. Survival analysis in TCGA implicated a number of meQTLs in 13 tumor types. In 10 of these, polygenic meQTL scores were associated with increased hazard in a CoxPH analysis. Risk and survival-associated meQTLs tended to affect cancer genes involved in DNA damage repair and cellular adhesion and reproduced cancer-specific associations reported in prior literature. In summary, this study provides evidence that genetic variants that influence local DNA methylation are affected by chromatin structure and can impact tumor evolution.

Identifiers

PMID37461500
PMCPMC10349948

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Registered trials

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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.