Evidence map›Paper›PMID 42023161›Full record

ArticleiScience2026

Sex differences in gene regulation and its impact on cancer incidence.

Camila M Lopes-Ramos, Rebekka Burkholz, Marouen Ben Guebila, Viola Fanfani, Enakshi Saha, Katherine H Shutta, Kimberly Glass, John Quackenbush, Dawn L DeMeo

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Camila M Lopes-RamosDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Rebekka BurkholzCISPA Helmholtz Center for Information Security, Saarbrücken, Germany.
Marouen Ben GuebilaDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Viola FanfaniDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Enakshi SahaDepartment of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
Katherine H ShuttaDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Kimberly GlassDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
John QuackenbushDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Dawn L DeMeoChanning Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA.

Funding

Multi-omic network methods for mapping molecular trajectories of age-related lung diseasesK25HL175222 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI Katherine Hoff Shutta · 2025 to 2026
$267k
NHLBI NIH HHS K25 HL175222
6 · The paper itself

Abstract

There are significant sex differences in cancer incidence, yet the underlying regulatory mechanisms in normal tissues remain poorly understood. We studied 8,279 gene regulatory networks across 29 non-cancerous tissues and compared network centrality by sex. Cancer genes were differentially targeted by transcription factors in males and females, with an overrepresentation on the X chromosome, particularly among X-inactivation escapees, and key signaling pathways such as WNT, NOTCH, and p53. We observed higher targeting of cancer-related pathways in females for tissues that have higher tumor incidence in females (breast, lung, and thyroid) and higher targeting in males for tissues with increased tumor incidence in males (stomach, colon, and liver), a pattern replicated in independent lung data. Sex-biased transcription factors were enriched for sex hormone response elements. These findings suggest that sex-biased transcriptional programs in normal tissues contribute to sex differences in cancer incidence and should be considered in cancer prevention strategies.

Indexed as

CancerPublic health

Identifiers

PMID42023161
PMCPMC13098508

What OpenQuestion holds

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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.