Evidence map›Paper›PMID 40200332›Full record

ArticleSystematic reviews2025

Synthetic lethality in cancer: a protocol for scoping review of gene interactions from synthetic lethal screens and functional studies.

Raashi Chauhan, Rama Rao Damerla, Vijay Shree Dhyani

Abstract read
In one paragraph

Article in Systematic reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Raashi ChauhanDepartment of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Rama Rao DamerlaDepartment of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India. rama.damerla@manipal.edu.ORCID 0000-0001-6815-0097
Vijay Shree DhyaniKasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India.

Funding

Department of Biotechnology, Ministry of Science and Technology, India BT/RLF/Re-entry/21/2018
6 · The paper itself

Abstract

backgroundTwo genes are synthetically lethal if loss of function of either one of the two genes does not result in cell death, whereas loss of function of both genes together results in being detrimental to cell survival. This concept has been the basis for developing personalized, precision treatments, which can selectively damage tumor cells and minimize toxicity to normal tissues. Tumor cells often harbor mutations in genes involved in DNA repair pathways, forcing them to switch to alternative repair pathways, leading to chemotherapeutic resistance. These interactions, if targeted, could be synthetically lethal. We aimed to summarize synthetically lethal gene pairs that could be utilized to selectively target cancer cells and minimize side effects on normal tissues. The objective of this review is to study druggable synthetically lethal gene pairs for targeted cancer therapy that have been identified through various genetic screens and functional studies.

methodsA systematic literature search will be conducted to extract synthetically lethal gene pairs that can be specifically targeted to cancer cells. Owing to the relatively recent research pertaining to this field, the literature search will incorporate data from 1956. The search will be conducted on PubMed, Web of Science, Embase, and Scopus. The narrative approach will guide the analysis and synthesis of the results. DISCUSSION: This review highlights scientific articles that report druggable synthetically lethal gene pairs by testing the efficacy of targeted inhibitors in clonogenic assays. These include research studies that identify synthetically lethal gene pairs detected through CRISPR screens by knocking out one or two genes within the same cell and testing the potency of inhibitors to specifically kill malignant cells. SYSTEMATIC REVIEW REGISTRATION: https://doi.org/10.17605/OSF.IO/5BCW6 .

Indexed as

NeoplasmsSynthetic Lethal MutationsHumansScoping Reviews as TopicCancerCRISPR/Cas9DNA damage repair pathwaysSynthetic lethalTargeted therapy

Identifiers

PMID40200332
PMCPMC11978169

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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.