Evidence map›Paper›PMID 39175079›Full record

ArticleBiology of sex differences2024

SexAnnoDB, a knowledgebase of sex-specific regulations from multi-omics data of human cancers.

Mengyuan Yang, Yuzhou Feng, Jiajia Liu, Hong Wang, Sijia Wu, Weiling Zhao, Pora Kim, Xiaobo Zhou

Abstract read
In one paragraph

Article in Biology of sex differences, 2024. 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. Insight into the Regulation of NDRG1 Expression.International journal of molecular sciences · 2025
    Review
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

8 authors.

Mengyuan YangSchool of Life Sciences, Zhengzhou University, Zhengzhou, 450001, China. mengyuanyang@zzu.edu.cn.ORCID 0000-0001-5235-5733
Yuzhou FengWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
Jiajia LiuCenter for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, 77030, USA.
Hong WangSchool of Life Sciences, Zhengzhou University, Zhengzhou, 450001, China.
Sijia WuSchool of Life Sciences and Technology, Xidian University, Xi'an, 710126, China.
Weiling ZhaoCenter for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, 77030, USA.
Pora KimCenter for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, 77030, USA. Pora.Kim@uth.tmc.edu.
Xiaobo ZhouCenter for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, 77030, USA. Xiaobo.Zhou@uth.tmc.edu.

Funding

Systems Modeling Guided Bone regenerationU01AR069395 · NIAMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI YANG, YUNZHI, ZHOU, XIAOBO · 2016 to 2021
$3.4M
Functional annotation of new genes aided by deep learningR35GM138184 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KIM, PORA · 2020 to 2024
$1.7M
Integrative approach to studying LncRNA functionsR01GM123037 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2017 to 2020
$1.5M
Center of Excellence in Applied Computational Science and Engineering 139170052China Postdoctoral Science Foundation 2022M712900, 2023T160590National Science Foundation 2217515, 2326879NIAMS NIH HHS U01 AR069395NIGMS NIH HHS R01 GM123037NIGMS NIH HHS R35 GM138184NIH HHS R01GM123037, U01AR069395-01A1, R01CA241930NIH HHS R35GM138184West China Hospital, Sichuan University, and Sichuan Science and Technology Program 2022YFS0228,2023YFS0200
6 · The paper itself

Abstract

backgroundSexual differences across molecular levels profoundly impact cancer biology and outcomes. Patient gender significantly influences drug responses, with divergent reactions between men and women to the same drugs. Despite databases on sex differences in human tissues, understanding regulations of sex disparities in cancer is limited. These resources lack detailed mechanistic studies on sex-biased molecules.

methodsIn this study, we conducted a comprehensive examination of molecular distinctions and regulatory networks across 27 cancer types, delving into sex-biased effects. Our analyses encompassed sex-biased competitive endogenous RNA networks, regulatory networks involving sex-biased RNA binding protein-exon skipping events, sex-biased transcription factor-gene regulatory networks, as well as sex-biased expression quantitative trait loci, sex-biased expression quantitative trait methylation, sex-biased splicing quantitative trait loci, and the identification of sex-biased cancer therapeutic drug target genes. All findings from these analyses are accessible on SexAnnoDB ( https://ccsm.uth.edu/SexAnnoDB/ ).

resultsFrom these analyses, we defined 126 cancer therapeutic target sex-associated genes. Among them, 9 genes showed sex-biased at both the mRNA and protein levels. Specifically, S100A9 was the target of five drugs, of which calcium has been approved by the FDA for the treatment of colon and rectal cancers. Transcription factor (TF)-gene regulatory network analysis suggested that four TFs in the SARC male group targeted S100A9 and upregulated the expression of S100A9 in these patients. Promoter region methylation status was only associated with S100A9 expression in KIRP female patients. Hypermethylation inhibited S100A9 expression and was responsible for the downregulation of S100A9 in these female patients.

conclusionsComprehensive network and association analyses indicated that the sex differences at the transcriptome level were partially the result of corresponding sex-biased epigenetic and genetic molecules. Overall, SexAnnoDB offers a discipline-specific search platform that could potentially assist basic experimental researchers or physicians in developing personalized treatment plans.

Indexed as

NeoplasmsSex FactorsDNA MethylationFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKnowledge BasesMaleMultiomicsQuantitative Trait LociCancerMulti-omicsSex-biased regulatory networkSex difference

Identifiers

PMID39175079
PMCPMC11342657

What OpenQuestion 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 OpenQuestion graph.