Evidence map›Paper›PMID 33461545›Full record

ArticleCancer cell international2021

SNORD63 and SNORD96A as the non-invasive diagnostic biomarkers for clear cell renal cell carcinoma.

Xiaoling Shang, Xingguo Song, Kangyu Wang, Miao Yu, Shanshan Ding, Xiaohan Dong, Li Xie, Xianrang Song

Abstract read
In one paragraph

Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Small nucleolar RNAs: the hidden precursors of cancer ribosomes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
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  13. SNORD3A Regulates STING Transcription to Promote Ferroptosis in Acute Kidney Injury.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 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

8 authors.

Xiaoling ShangDepartment of Clinical Laboratory, Cheeloo College of Medicine, Shandong Cancer Hospital and Institute, Shandong University, Jinan, 250012, Shandong, China.
Xingguo SongDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Kangyu WangDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Miao YuDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Shanshan DingDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Xiaohan DongDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Li XieDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China.
Xianrang SongDepartment of Clinical Laboratory, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, 440 Ji-Yan Road, Jinan, 250117, Shandong, People's Republic of China. xrsong@sdfmu.edu.cn.ORCID http://orcid.org/0000-0003-1722-8207

Funding

National Natural Science Foundation of China 81972014, 81672104Shandong Provincial Natural Science Foundation ZR2019MH004, ZR2019LZL016
6 · The paper itself

Abstract

backgroundIncreasing evidence has demonstrated that snoRNAs play crucial roles in tumorigenesis of various cancer types. However, researches on snoRNAs in ccRCC were very little. This study mainly aimed to validate the differential expression and the potential diagnostic value of SNORD63 and SNORD96A in ccRCC.

methodsSnoRNAs expression was downloaded from the SNORic and TCGA database including 516 patients with ccRCC and 71 control cases. SNORD63 and SNORD96A expression were further detected in 54 tumor and adjacent FFPE ccRCC tissues, 55 plasma and 75 urinary sediment of ccRCC patients. Then, differential expression and diagnostic value of SNORD63 and SNORD96A were further calculated.

resultsSNORD63 and SNORD96A expression were significantly increased in ccRCC tissues compared with normal tissues from the TCGA database (both, P < 0.0001). In addition, we found that SNORD63 and SNORD96A localized in plasma and US stably after treating with RNase A. Meanwhile, SNORD63 and SNORD96A in FFPE and US were elevated in ccRCC patients (all, P < 0.0001). However, plasma SNORD63 expression had no significance while SNORD96A significantly increased in plasma of ccRCC patients. Notably, the AUC of SNORD63 in US was 0.7055, by comparison the AUC of plasma SNORD63 was only 0.5161. However, the AUC of plasma SNORD96A was up to 0.8909, by comparison the AUC of SNORD96A in US was 0.6788. Interestingly, the AUC of plasma SNORD96A in early stage ccRCC was highly up to 0.9359.

conclusionsOur findings revealed that SNORD63 in US and SNORD96A in plasma could act as the promising non-invasive diagnostic biomarkers for ccRCC patients.

Indexed as

ccRCCDiagnostic biomarkersSNORD63SNORD96AUrinary sediment

Identifiers

PMID33461545
PMCPMC7812721

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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.