Evidence map›Paper›PMID 34596864›Full record

ReviewHepatology international2021

Application of CRISPR-Cas9 based gene editing to study the pathogenesis of colon and liver cancer using organoids.

Gayatri Ramakrishna, Preedia E Babu, Ravinder Singh, Nirupma Trehanpati

Abstract readReview
PubMed Publisher
In one paragraph

Review in Hepatology international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–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

21 citing papers in PubMed.

  1. Review
  2. Patient-derived organoids in gynaecological cancers: emerging tools for therapy and disease modelling.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  20. Frontiers in oncology · 2022
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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

4 authors.

Gayatri RamakrishnaDepartment of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, D1 Block, Vasant Kunj, Delhi, 110070, India. rgayatri@ilbs.in.ORCID http://orcid.org/0000-0003-4345-294X
Preedia E BabuDepartment of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, D1 Block, Vasant Kunj, Delhi, 110070, India.
Ravinder SinghDepartment of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, D1 Block, Vasant Kunj, Delhi, 110070, India.
Nirupma TrehanpatiDepartment of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, D1 Block, Vasant Kunj, Delhi, 110070, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two breakthrough techniques that have totally revolutionized biology in last 1 decade are the discovery of genome editing tools and growing the stem cells/primary tissue explants in defined 3D culture. In this regard the discovery of CRISPR-Cas9 as a specific gene editing tool and organoid culture from adult stem cell has provided easy handy tools to uncover the process of organ development and also modeling cancer. Genetically modified organoids have been developed by sequential knockout and knockin of driver mutations by genome editing followed by niche-based selection. The modified organoids when xenotransplanted in animal models faithfully recapitulate the neoplastic events of human tumors. The present review focuses on the merging of these two powerful technologies in understanding the complexities of colon and liver cancer.

Indexed as

Gene EditingLiver NeoplasmsAnimalsColonCRISPR-Cas SystemsHumansOrganoidsCancerColonCRISPR-Cas9LiverOrganoids

Identifiers

PMID34596864

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.