Evidence map›Paper›PMID 38063952›Full record

ArticleBiochemical genetics2024

Identification of the Shared Gene Signatures and Biological Mechanisms in Hyperplastic Enlarged Lobular Units and Breast Cancer.

Kuiyuan Tong, Zihao Yang, Shiyu Jin, Wanli Yang, Ruihua Yu, Shiyan Wang, Chao Yang, Feng Jiang

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Article in Biochemical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Kuiyuan Tong *Faculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, Jiangsu, China.
Zihao Yang *Faculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, Jiangsu, China.
Shiyu Jin *Faculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, Jiangsu, China.
Wanli YangTranslational Institute for Cancer Pain, Chongming Hospital Affiliated to Shanghai University of Health & Medicine Sciences (Xinhua Hospital Chongming Branch), Shanghai, 202150, China.
Ruihua YuTranslational Institute for Cancer Pain, Chongming Hospital Affiliated to Shanghai University of Health & Medicine Sciences (Xinhua Hospital Chongming Branch), Shanghai, 202150, China.
Shiyan WangFaculty of Life Science and Food Engineering, Huaiyin Institute of Technology, Huaian, 223003, Jiangsu, China. shiyanwanghyit@163.com.
Chao YangTranslational Institute for Cancer Pain, Chongming Hospital Affiliated to Shanghai University of Health & Medicine Sciences (Xinhua Hospital Chongming Branch), Shanghai, 202150, China. yangchao@xinhuamed.com.cn.
Feng JiangTranslational Institute for Cancer Pain, Chongming Hospital Affiliated to Shanghai University of Health & Medicine Sciences (Xinhua Hospital Chongming Branch), Shanghai, 202150, China. fengjiang@xinhuamed.com.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a common cancer worldwide. Hyperplastic enlarged lobular units (HELUs) are common changes in the breasts of adult women. HELUs may be closely related to the occurrence and development of breast cancer. In this study, genes that are commonly contained in the expression profiles of the genomes of the two diseases and have significant differences in expression before and after the respective diseases were identified. Various enrichment analyses were performed according to the expression levels of these differentially expressed genes. Furthermore, LASSO regression analysis was performed on the differentially expressed genes to identify genes significantly related to survival. The optimal risk model for the survival of patients with breast cancer was established, and the accuracy of the model was verified on multiple data sets. A gene combination containing 17 genes was ultimately determined to be an independent prognostic factor. Kaplan‒Meier survival analysis demonstrated the good performance of this risk model. The study found that Shared Gene Signatures and Biological Mechanisms in Hyperplastic Enlarged Lobular Units and Breast Cancer, screened 17 important Shared Gene Signatures of Hyperplastic Enlarged Lobular Units which are closely related to the survival of breast cancer patients through machine learning, and established a prognosis model with high-accuracy, which is worthy of further exploration.

Indexed as

Breast NeoplasmsHyperplasiaBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimatePrognosisTranscriptomeBiomarkers, TumorBreast cancerCancer riskGene signatureHELUMachine learning

Identifiers

PMID38063952

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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.