Evidence map›Paper›PMID 31732842›Full record

ArticleInternational urology and nephrology2020

A pilot investigation of a urinary metabolic biomarker discovery in renal cell carcinoma.

Mingxin Zhang, Xiaoyan Liu, Xiang Liu, Hanzhong Li, Wei Sun, Yushi Zhang

Abstract read
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In one paragraph

Article in International urology and nephrology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 29% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. [Research Progress on Tumor Metabolic Biomarkers in Liquid Biopsy of Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024
    Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Mass spectrometry imaging of L-[ring-Cancer & metabolism · 2021
    Article
  11. Urinary Metabolic Biomarkers in Cancer Patients: An Overview.Methods in molecular biology (Clifton, N.J.) · 2021
    Review
  12. 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

6 authors at 2 institutions in 1 country.

Mingxin ZhangDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Xiaoyan LiuInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China.
Xiang LiuInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China.
Hanzhong LiDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Wei SunInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China. sunweizmx@126.com.
Yushi ZhangDepartment of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China. zhangyushi2018@163.com.ORCID http://orcid.org/0000-0002-3382-7157
Chinese Academy of Medical Sciences & Peking Union Medical College · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRenal cell carcinoma (RCC) is the most common and lethal malignancy of the kidney. Distinguishing RCC from benign renal tumors and healthy controls is still a clinical challenge. Urine metabolomics has been used to identify biomarkers of clinical diseases.

methodsIn the present study, we explored the urine metabolomes of a cohort of 61 patients with renal tumors (39 RCC and 22 benign renal tumors) and 68 healthy controls using liquid chromatography coupled with high-resolution mass spectrometry (LC-MS).

resultsMetabolic profiling of urine could significantly differentiate RCC from healthy controls and benign renal tumors. Metabolic pathways, including lysine metabolism and phenylalanine metabolism, were found to be disturbed in the RCC group. Steroid hormone biosynthesis was significantly different between the benign tumor group and the RCC group. RCC biomarkers were further explored. A metabolite panel consisting of cortolone, testosterone and L-2-aminoadipate adenylate was discovered to have good ability of distinguishing RCC from benign tumors, with an AUC of 0.868 for tenfold cross-validation and 0.873 for the validation group. In addition, the panel of aminoadipic acid, 2-(formamido)-N1-(5-phospho-D-ribosyl) acetamidine and alpha-N-phenylacetyl-L-glutamine could distinguish the RCC group from the healthy control group, with an AUC of 0.841 for tenfold cross-validation and 0.894 for the validation group.

conclusionsThis pilot study suggests that urine metabolomics may be useful in differentiating RCC from healthy controls and benign renal tumors.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellKidney NeoplasmsChromatography, High Pressure LiquidDiagnosis, DifferentialFemaleHumansMaleMass SpectrometryMetabolomicsMiddle AgedNeoplasmsPilot ProjectsBiomarkers, TumorBiomarkerRenal cell carcinomaUrine metabolomics

Identifiers

PMID31732842
OpenAlexW2985836155

What OpenQuestion holds

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Read underepoch 390

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.