Evidence map›Paper›PMID 37907864›Full record

ArticleBMC cancer2023

Estrogen-related genes for thyroid cancer prognosis, immune infiltration, staging, and drug sensitivity.

Leiying Zhang, Man Zhou, Xiaoni Gao, Yang Xie, Junqi Xiao, Tao Liu, Xiangtai Zeng

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 19 citations in OpenAlex.

  1. The Molecular Heterogeneity of NRAS Variants in Thyroid Nodules.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2026
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  14. Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates.International journal of molecular sciences · 2024
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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

7 authors at 5 institutions in 1 country.

Leiying ZhangSuzhou Medical College of Soochow University, Suzhou, China.
Man ZhouCollege of Pharmacy, Gannan Medical University, Ganzhou, China.
Xiaoni GaoThe First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Yang XieThe First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Junqi XiaoThe First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Tao LiuThe First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Xiangtai ZengSuzhou Medical College of Soochow University, Suzhou, China. xiangtai.zeng@gmu.edu.cn.
First Affiliated Hospital of Gannan Medical University · CNSoochow University · CNBeijing Technology and Business University · CNGannan Medical University · CNGanzhou People's Hospital · CN

Funding

Ganzhou Key Laboratory of Thyroid Tumors No. 202101034685The First Affiliated Hospital of the Gannan Medical University Doctor Start-up Fund Project No. QD202211
6 · The paper itself

Abstract

backgroundThyroid cancer (THCA) has become increasingly common in recent decades, and women are three to four times more likely to develop it than men. Evidence shows that estrogen has a significant impact on THCA proliferation and growth. Nevertheless, the effects of estrogen-related genes (ERGs) on THCA stages, immunological infiltration, and treatment susceptibility have not been well explored.

methodsClinicopathological and transcriptome data of patients with THCA from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were cleaned before consensus clustering. Differential expression analysis was performed on the genes expressed between THCA and paraneoplastic tissues in TCGA, and Wayne analysis was performed on the ERGs obtained from the Gene Set Enrichment Analysis MsigDB and differentially expressed genes (DEGs). Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were used to identify the set of estrogen-related differentially expressed genes (ERDEGs) associated with progression-free intervals (PFI) and to establish a prediction model. Receiver operating characteristic curves were plotted to calculate the risk scores and PFI status to validate the predictive effect of the model. Enrichment analyses and immune infiltration analyses were performed to analyze DEGs between the high- and low-risk groups, and a nomogram plot was used in the risk model to predict the PFI of THCA.

resultsThe expression of 120 ERDEGs differed significantly between the two groups (P < 0.05). Five (CD24, CAV1, TACC1, TIPARP, and HSD17B10) of the eight ERDEGs identified using univariate Cox and LASSO regression were validated via RT-qPCR and immunohistochemistry analysis of clinical tissue samples and were used for clinical staging and drug sensitivity analysis. Risk-DEGs were shown to be associated with immune modulation and tumor immune evasion, as well as defense systems, signal transduction, the tumor microenvironment, and immunoregulation. In 19 of the 28 immune cells, infiltration levels differed between the high- and low-risk groups. High-risk patients in the immunotherapy dataset had considerably shorter survival times than low-risk patients.

conclusionWe identified and confirmed eight ERDEGs using a systematic analysis and screened sensitive drugs for ERDEGs. These results provide molecular evidence for the involvement of ERGs in controlling the immunological microenvironment and treatment response in THCA.

Indexed as

Thyroid NeoplasmsEstrogensFemaleGenes, cdcHumansMalePrognosisTumor MicroenvironmentEstrogensClinical relevanceDrug sensitivityEstrogen-related differential expressed genesEstrogen-related genesImmune infiltrationProgression-free intervalThyroid cancer

Identifiers

PMID37907864
PMCPMC10619281
OpenAlexW4388041877

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LicenceCC BY
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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.