Evidence map›Paper›PMID 35715864›Full record

ArticleJournal of translational medicine2022

Identification of characteristic metabolic panels for different stages of prostate cancer by

Xi Zhang, Binbin Xia, Hong Zheng, Jie Ning, Yinjie Zhu, Xiaoguang Shao, Binrui Liu, Baijun Dong, Hongchang Gao

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

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  16. Prostate cancer in omics era.Cancer cell international · 2022
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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

9 authors at 3 institutions in 1 country.

Xi Zhang *School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China.
Binbin Xia *Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Hong Zheng *School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China.
Jie NingSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China.
Yinjie ZhuDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Xiaoguang ShaoDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Binrui LiuSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China.
Baijun DongDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China. dongbaijun@renji.com.
Hongchang GaoSchool of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, China. gaohc27@wmu.edu.cn.
Wenzhou Medical University · CNRenji Hospital · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer (PCa) is the second most prevalent cancer in males worldwide, yet detecting PCa and its metastases remains a major challenging task in clinical research setups. The present study aimed to characterize the metabolic changes underlying the PCa progression and investigate the efficacy of related metabolic panels for an accurate PCa assessment.

methodsIn the present study, 75 PCa subjects, 62 PCa patients with bone metastasis (PCaB), and 50 benign prostatic hyperplasia (BPH) patients were enrolled, and we performed a cross-sectional metabolomics analysis of serum samples collected from these subjects using a

resultsMultivariate analysis revealed that BPH, PCa, and PCaB groups showed distinct metabolic divisions, while univariate statistics integrated with variable importance in the projection (VIP) scores identified a differential metabolite series, which included energy, amino acid, and ketone body metabolism. Herein, we identified a series of characteristic serum metabolic changes, including decreased trends of 3-HB and acetone as well as elevated trends of alanine in PCa patients compared with BPH subjects, while increased levels of 3-HB and acetone as well as decreased levels of alanine in PCaB patients compared with PCa. Additionally, our results also revealed the metabolic panels of discriminant metabolites coupled with the clinical parameters (age and body mass index) for discrimination between PCa and BPH, PCaB and BPH, PCaB and PCa achieved the AUC values of 0.828, 0.917, and 0.872, respectively.

conclusionsOverall, our study gave successful discrimination of BPH, PCa and PCaB, and we characterized the potential metabolic alterations involved in the PCa progression and its metastases, including 3-HB, acetone and alanine. The defined biomarker panels could be employed to aid in the diagnosis and classification of PCa in clinical practice.

Indexed as

Prostatic HyperplasiaProstatic NeoplasmsAcetoneAlanineCross-Sectional StudiesHumansMagnetic Resonance SpectroscopyMaleMetabolomicsProton Magnetic Resonance SpectroscopyAcetoneAlanineBiomarkerDiagnosisMetabolomicsProstate cancerSerum

Identifiers

PMID35715864
PMCPMC9205125
OpenAlexW4283019138

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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.