Evidence map›Paper›PMID 30717315›Full record

ArticleCancers2019

Potential Applications of DNA, RNA and Protein Biomarkers in Diagnosis, Therapy and Prognosis for Colorectal Cancer: A Study from Databases to AI-Assisted Verification.

Xueli Zhang, Xiao-Feng Sun, Bairong Shen, Hong Zhang

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Prognostic and predictive values of CXCL10 in colorectal cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. EBD: an eye biomarker database.Bioinformatics (Oxford, England) · 2023
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Knockdown ofAging · 2019
    Article
  20. 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

4 authors at 3 institutions in 2 countries.

Xueli ZhangSchool of Medicine, Institute of Medical Sciences, Örebro University, SE-70182 Örebro, Sweden. zhang.xueli@oru.se.ORCID 0000-0001-5963-9261
Xiao-Feng SunDepartment of Oncology and Clinical and Experimental Medicine, Linköping University, SE-58183 Linköping, Sweden. xiao-feng.sun@liu.se.
Bairong ShenCentre for Systems Biology, Soochow University, Suzhou 215006, China. bairong.shen@suda.edu.cn.
Hong ZhangSchool of Medicine, Institute of Medical Sciences, Örebro University, SE-70182 Örebro, Sweden. hong.zhang@oru.se.ORCID 0000-0003-1834-1578
Örebro University · SELinköping University · SESoochow University · CN

Funding

Svenska Forskningsrådet Formas 2016-01098Swedish Cancer Foundation CAN 2016/341
6 · The paper itself

Abstract

In order to find out the most valuable biomarkers and pathways for diagnosis, therapy and prognosis in colorectal cancer (CRC) we have collected the published CRC biomarkers and established a CRC biomarker database (CBD: http://sysbio.suda.edu.cn/CBD/index.html). In this study, we analysed the single and multiple DNA, RNA and protein biomarkers as well as their positions in cancer related pathways and protein-protein interaction (PPI) networks to describe their potential applications in diagnosis, therapy and prognosis. CRC biomarkers were collected from the CBD. The RNA and protein biomarkers were matched to their corresponding DNAs by the miRDB database and the PubMed Gene database, respectively. The PPI networks were used to investigate the relationships between protein biomarkers and further detect the multiple biomarkers. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) annotation were used to analyse biological functions of the biomarkers. AI classification techniques were utilized to further verify the significances of the multiple biomarkers in diagnosis and prognosis for CRC. We showed that a large number of the DNA, RNA and protein biomarkers were associated with the diagnosis, therapy and prognosis in various degrees in the CRC biomarker networks. The CRC biomarkers were closely related to the CRC initiation and progression. Moreover, the biomarkers played critical roles in cellular proliferation, apoptosis and angiogenesis and they were involved in Ras, p53 and PI3K pathways. There were overlaps among the DNA, RNA and protein biomarkers. AI classification verifications showed that the combined multiple protein biomarkers played important roles to accurate early diagnosis and predict outcome for CRC. There were several single and multiple CRC protein biomarkers which were associated with diagnosis, therapy and prognosis in CRC. Further, AI-assisted analysis revealed that multiple biomarkers had potential applications for diagnosis and prognosis in CRC.

Indexed as

cancer-related pathwayscolorectal cancerDNAmultiple-biomarkersproteinRNAsingle-biomarkers

Identifiers

PMID30717315
PMCPMC6407036
OpenAlexW2913470918

What OpenQuestion 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 OpenQuestion graph.