Evidence map›Paper›PMID 36097111›Full record

ReviewMolecular biology reports2022

Applications of CRISPR/Cas technology against drug-resistant lung cancers: an update.

Mayank Chaudhary, Pooja Sharma, Tapan Kumar Mukherjee

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Mayank ChaudharyDepartment of Biotechnology, Maharishi Markandeshwar (Deemed to Be University), Mullana, Ambala, Haryana, 133207, India.
Pooja SharmaDepartment of Biotechnology, Maharishi Markandeshwar (Deemed to Be University), Mullana, Ambala, Haryana, 133207, India.
Tapan Kumar MukherjeeDepartment of Biotechnology, Maharishi Markandeshwar (Deemed to Be University), Mullana, Ambala, Haryana, 133207, India. tapan400@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Out of all the cancer types, the most prevalent one is lung cancer. Multiple genes and signaling pathways play role in the progression of lung cancer. Considering the wider prevalence and fatality of lung cancer it has become the focus of current cancer research. Though currently used approaches have shown positive results against lung cancer but success against non-small cell lung cancer (NSCLC) still looms as an enigma for the entire research fraternity. The development of resistance against inhibitors within a short span is one of the reasons responsible for the failure and relapse of lung cancer. Under these prevailing conditions genome/gene-editing technology using clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR associated proteins (Cas), popularly known as CRISPR/Cas technology offers a convenient and flexible method for inducing precise changes within the lung cancer cell. Additionally, CRISPR-barcoding and CRISPR knockout screens at the genome-wide level can help in the functional investigation of specific mutations and identification of novel cancer drivers respectively. Several variants of the CRISPR/Cas system are being developed to limit off-targeting with enhanced precision. The present review article updates the usefulness of CRISPR/Cas technology against various types of lung cancers.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsCRISPR-Cas SystemsHumansNeoplasm Recurrence, LocalTechnologyChemotherapyClustered regularly interspaced short palindromic repeat (CRISPR)CRISPR associated proteins (Cas)Drug resistanceGenome/gene editingLung cancers

Identifiers

What OpenQuestion holds

Textmetadata
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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.