Evidence map›Paper›PMID 37723185›Full record

SynthesisScientific reports2023

A comprehensive analysis of the role of QPRT in breast cancer.

Yiqing Yan, Lun Li, Zixin Wang, Jian Pang, Xinyu Guan, Yunchang Yuan, Zhenkun Xia, Wenjun Yi

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

13 citing papers in PubMed, 13 citations in OpenAlex.

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  13. Inhibitors of NADInternational journal of molecular sciences · 2024
    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 at 2 institutions in 1 country.

Yiqing Yan *Department of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Lun Li *Department of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Zixin WangDepartment of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Jian PangDepartment of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Xinyu GuanDepartment of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Yunchang YuanDepartment of Thoracic Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China.
Zhenkun XiaDepartment of Thoracic Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China. xwvfye@126.com.
Wenjun YiDepartment of General Surgery, The Second Xiangya Hospital, Central South University, No. 139, Renmin Central Road, Changsha, 410011, China. yiwenjun@csu.edu.cn.
Central South University · CNSecond Xiangya Hospital of Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the clinical role of QPRT in breast cancer. The gene expression, methylation levels and prognostic value of QPRT in breast cancer was analyzed using TCGA data. Validation was performed using the data from GEO dataset and TNMPLOT database. Meta analysis method was used to pool the survival data for QPRT. The predictive values of QPRT for different drugs were retrieved from the ROC plot. The expression differences of QPRT in acquired drug-resistant and sensitive cell lines were analyzed using GEO datasets. GO and KEGG enrichment analysis were conducted for those genes which were highly co-expressed with QPRT in tissue based on TCGA data and which changed after QPRT knockdown. Timer2.0 was utilized to explore the correlation between QPRT and immune cells infiltration, and the Human Protein Atlas was used to analyse QPRT's single-cell sequencing data across different human tissues. The expression of QPRT in different types of macrophages, and the expression of QPRT were analysed after coculturing HER2+ breast cancer cells with macrophages. Additionally, TargetScan, Comparative Toxicogenomics and the connectivity map were used to research miRNAs and drugs that could regulate QPRT expression. Cytoscape was used to map the interaction networks between QPRT and other proteins. QPRT was highly expressed in breast cancer tissue and highly expressed in HER2+ breast cancer patients (P < 0.01). High QPRT expression levels were associated with worse OS, DMFS, and RFS (P < 0.01). Two sites (cg02640602 and cg06453916) were found to be potential regulators of breast cancer (P < 0.01). QPRT might predict survival benefits in breast cancer patients who received taxane or anthracycline. QPRT was associated with tumour immunity, especially in macrophages. QPRT may influence the occurrence and progression of breast cancer through the PI3K-AKT signalling pathway, Wnt signalling pathway, and cell cycle-related molecules.

Indexed as

Breast NeoplasmsMicroRNAsPentosyltransferasesAnthracyclinesFemaleHumansNicotinate-Nucleotide Diphosphorylase (Carboxylating)Phosphatidylinositol 3-KinasesAnthracyclinesMicroRNAsNicotinate-Nucleotide Diphosphorylase (Carboxylating)PentosyltransferasesPhosphatidylinositol 3-Kinases

Identifiers

PMID37723185
PMCPMC10507026
OpenAlexW4386833346

What Socratic 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 Socratic graph.