Evidence map›Paper›PMID 32970347›Full record

ArticleCancer science2020

SCTR hypermethylation is a diagnostic biomarker in colorectal cancer.

DaPeng Li, Lei Zhang, JinMing Fu, Hao Huang, SiMin Sun, Ding Zhang, LiYuan Zhao, Justina Ucheojor Onwuka, YaShuang Zhao, BinBin Cui

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 16% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Hypomethylation ofFrontiers in immunology · 2025
    Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Dynamic liquid biopsy components as predictive and prognostic biomarkers in colorectal cancer.Journal of experimental & clinical cancer research : CR · 2022
    Review
  9. Differential DNA methylation analysis ofWorld journal of gastroenterology · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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

10 authors at 1 institution in 1 country.

DaPeng LiDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
Lei ZhangDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
JinMing FuDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
Hao HuangDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
SiMin SunDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
Ding ZhangDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
LiYuan ZhaoDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
Justina Ucheojor OnwukaDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.
YaShuang ZhaoDepartment of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China.ORCID https://orcid.org/0000-0002-7425-5773
BinBin CuiDepartment of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diagnostic markers for both colorectal cancer (CRC) and its precursor lesions are lacking. Although aberrant methylation of the secretin receptor (SCTR) gene was observed in CRC, the diagnostic performance has not been evaluated. Therefore, this study aimed to assess and verify the diagnostic value of SCTR methylation of CRC and its precursor lesions through integrating the largest methylation data. The diagnostic performance of SCTR methylation was analyzed in the discovery set from The Cancer Genome Atlas (TCGA) CRC methylation data (N = 440), and verified in a large-scale test set (N = 938) from the Gene Expression Omnibus (GEO). Targeted bisulfite sequencing analysis was developed and applied to detect the methylation status of SCTR in our independent validation set (N = 374). Our findings revealed that the SCTR gene was frequently hypermethylated at its CpG islands in CRC. In the TCGA discovery set, the diagnostic score was constructed using 4 CpG sites (cg01013590, cg20505223, cg07176264, and cg26009192) and achieved high diagnostic performance (area under the ROC curve [AUC] = 0.964). In the GEO test set, the diagnostic score had robust diagnostic ability to distinguish CRC (AUC = 0.948) and its precursor lesions (AUC = 0.954) from normal samples. Moreover, hypermethylation of the SCTR gene was also found in cell-free DNA samples collected from CRC patients, but not in those from healthy controls. In the validation set, consistent results were observed using the targeted bisulfite sequencing array. Our study highlights that hypermethylation at CpG islands of the SCTR gene is a potential diagnostic biomarker in CRCs and its precursor lesions.

Indexed as

Biomarkers, TumorCell-Free Nucleic AcidsColorectal NeoplasmsCpG IslandsGene ExpressionHumansLeukocytesMethylationProtein Array AnalysisReceptors, Gastrointestinal HormoneReceptors, G-Protein-CoupledReproducibility of ResultsSensitivity and SpecificityBiomarkers, TumorCell-Free Nucleic AcidsReceptors, Gastrointestinal HormoneReceptors, G-Protein-Coupledsecretin receptorbiomarkercolorectal cancerdiagnosisDNA methylationSCTR

Identifiers

PMID32970347
PMCPMC7734158
OpenAlexW3088396424

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.