Evidence map›Paper›PMID 39574883›Full record

ArticleResearch square2024

Mapping the Temporal Landscape of Breast Cancer Using Epigenetic Entropy.

Darryl Shibata, Daniel Monyak, Shannon Holloway, Graham Gumbert, Lars Grimm, Shelley Hwang, Jeffrey Marks, Marc Ryser

Abstract readPreprint
In one paragraph

Article in Research square, 2024. 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

8 authors.

Darryl ShibataUSC School of Medicine.
Daniel MonyakDuke University.
Shannon HollowayDuke University.
Graham GumbertDuke University.
Lars GrimmDuke University.
Shelley HwangDuke University.ORCID https://orcid.org/0000-0002-8571-1148
Jeffrey MarksDuke University.
Marc RyserDuke University.

Funding

Molecular, Cellular and Tissue Characterization UnitU2CCA233254 · NCI · DUKE UNIVERSITY · PI HWANG, E.SHELLEY · 2018 to 2023
$11.4M
The Role of the Microbiome in Cancer Suppression and Susceptibility Across SpeciesU54CA217376 · NCI · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI MALEY, CARLO · 2018 to 2022
$8.6M
Dynamic imaging and tissue biomarker models to delineate indolent from aggressive breast calcificationsR01CA271237 · NCI · DUKE UNIVERSITY · PI GRIMM, LARS J, MARKS, JEFFREY R. · 2022 to 2025
$2.1M
NCI NIH HHS R01 CA271237NCI NIH HHS U2C CA233254NCI NIH HHS U54 CA217376
6 · The paper itself

Abstract

Although generally unknown, the age of a newly diagnosed tumor encodes valuable etiologic and prognostic information. Here, we estimate the age of breast cancers, defined as the time from the start of growth to detection, using a measure of epigenetic entropy derived from genome-wide methylation arrays. Based on an ensemble of neutrally fluctuating CpG (fCpG) sites, this stochastic epigenetic clock differs from conventional clocks that measure age-related increases in methylation. We show that younger tumors exhibit hallmarks of aggressiveness, such as increased proliferation and genomic instability, whereas older tumors are characterized by elevated immune infiltration, indicative of enhanced immune surveillance. These findings suggest that the clock captures a tumor's effective growth rate resulting from the evolutionary-ecological competition between intrinsic growth potential and external systemic pressures. Because of the clock's ability to delineate old and stable from young and aggressive tumors, it has potential applications in risk stratification of early-stage breast cancers and guiding early detection efforts.

Identifiers

PMID39574883
PMCPMC11581123

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.