Sexual dimorphism in cancer: molecular mechanisms and precision oncology perspectives.

Zhen Wang, Hanwen Hu, Yunjia Bao, Guohong Ren, Chenghui Yang

Abstract readReview

In one paragraph

Review in Biology of sex differences, 2026. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhen Wang *Key Laboratory of Tumor Microenvironment and Immune Therapy of Zhejiang Province, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, P.R. China.

Hanwen Hu *Key Laboratory of Tumor Microenvironment and Immune Therapy of Zhejiang Province, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, P.R. China.

Yunjia Bao *First Clinical College of Wenzhou Medical University, Wenzhou, 325000, P.R. China.

Guohong RenKey Laboratory of Tumor Microenvironment and Immune Therapy of Zhejiang Province, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, P.R. China. 11518249@zju.edu.cn.

Chenghui YangFirst Clinical College of Wenzhou Medical University, Wenzhou, 325000, P.R. China. yangch1202@wmu.edu.cn.

Funding

Medical Science and Technology Project of Zhejiang Province 2024KY1039Medical Science and Technology Project of Zhejiang Province 2024KY1250National Natural Science Foundation of China 82203663National Natural Science Foundation of China 82273449Zhejiang Provincial Natural Science Foundation of China LQ23H160013

6 · The paper itself

Abstract

Sex differences play a crucial role in determining tumor incidence, treatment sensitivity, and prognosis among men and women. However, current clinical cancer treatment strategies fail to account for these differences. Furthermore, the underlying mechanisms of tumor disparities between sexes remain elusive. Sex differences in sex chromosomes, hormone levels, metabolism, and immunity synergistically contribute to tumor-related disparities. As the demand for precision medicine escalates, there is an urgent need to conduct further exploration and research to address the tumor differences between sexes. In this review, we discuss the impact of biological sex differences on tumor cells and the tumor microenvironment, aiming to identify more effective strategies for tumor prevention and treatment.

Indexed as

NeoplasmsPrecision MedicineSex CharacteristicsAnimalsFemaleGonadal Steroid HormonesHumansMaleSex ChromosomesTumor MicroenvironmentGonadal Steroid HormonesCancerSex chromosomesSex differencesSex hormonesTumor microenvironment

Identifiers

PMID41634797

DOI10.1186/s13293-026-00843-7

PMCPMC12958634

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LicenceCC BY

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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.