Evidence map›Paper›PMID 34165724›Full record

ReviewMethods in molecular biology (Clifton, N.J.)2021

Pseudogenes as Biomarkers and Therapeutic Targets in Human Cancers.

Cristina Sisu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
9.4field-weighted citation impact, top 1% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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  5. Increased Expression ofIranian journal of public health · 2025
    Article
  6. Review
  7. Review
  8. Introduction ofIranian journal of basic medical sciences · 2024
    Article
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  11. Review
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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

1 author at 1 institution in 1 country.

Cristina SisuDepartment of Life Sciences, College of Medicine, Health and Life Sciences, Brunel University London, London, UK. Cristina.Sisu@brunel.ac.uk.
Brunel University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pseudogenes are commonly labeled as "junk DNA" given their perceived nonfunctional status. However, the advent of large-scale genomics projects prompted a revisit of pseudogene biology, highlighting their key functional and regulatory roles in numerous diseases, including cancers. Integrative analyses of cancer data have shown that pseudogenes can be transcribed and even translated, and that pseudogenic DNA, RNA, and proteins can interfere with the activity and function of key protein coding genes, acting as regulators of oncogenes and tumor suppressors. Capitalizing on the available clinical research, we are able to get an insight into the spread and variety of pseudogene biomarker and therapeutic potential. In this chapter, we describe pseudogenes that fulfill their role as diagnostic or prognostic biomarkers, both as unique elements and in collaboration with other genes or pseudogenes. We also report that the majority of prognostic pseudogenes are overexpressed and exert an oncogenic role in colorectal, liver, lung, and gastric cancers. Finally, we highlight a number of pseudogenes that can establish future therapeutic avenues.

Indexed as

PseudogenesAntineoplastic AgentsBiomarkers, TumorDNA, NeoplasmForecastingGene Expression Regulation, NeoplasticGenes, NeoplasmHumansMolecular Targeted TherapyNeoplasmsOrgan SpecificityPrognosisTranscription, GeneticAntineoplastic AgentsBiomarkers, TumorDNA, NeoplasmBiomarkerHuman cancerPseudogeneTherapeutic target

Identifiers

PMID34165724
OpenAlexW3173573262

What OpenQuestion holds

Textmetadata
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.