Evidence map›Paper›PMID 39229040›Full record

ArticlebioRxiv : the preprint server for biology2024

Optimal methods for analyzing targeted pairwise knockout screens.

Juihsuan Chou, Nazanin Esmaeili Anvar, Reem Elghaish, Junjie Chen, Traver Hart

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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
–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

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

5 authors.

Juihsuan ChouDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Nazanin Esmaeili AnvarDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Reem ElghaishDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Junjie ChenDepartment of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-1493-2189
Traver HartDepartment of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-1880-3341

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Exploring DNA damage response pathways as targets for cancer therapyR35CA274234 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Junjie Chen · 2022 to 2026
$4.4M
Identifying and targeting collateral lethal vulnerabilities in cancersU01CA275886 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RONALD ANTHONY DEPINHO, Traver Hart · 2023 to 2026
$3.9M
High-content microscopy platform for multiplex perturbation/multiplex readout studiesR35GM130119 · NIGMS · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Traver Hart · 2018 to 2026
$3.9M
NCI NIH HHS P30 CA016672NCI NIH HHS R35 CA274234NCI NIH HHS U01 CA275886NIGMS NIH HHS R35 GM130119
6 · The paper itself

Abstract

Background: Synthetic lethality offers a promising strategy for cancer treatment by targeting genetic vulnerabilities unique to tumor cells, leading to selective tumor cell death. However, single-gene knockout screens often miss functional redundancy due to paralog genes. Multiplex CRISPR systems, including various Cas9 and Cas12a platforms, have been developed to assay genetic interactions, yet no systematic comparison of method to identify synthetic lethality from CRISPR screens has been conducted. Results: We evaluated data from four in4mer CRISPR/Cas12a screens in cancer cell lines, using three bioinformatic approaches to identify synthetic lethal interactions: delta log fold change (dLFC), Z-transformed dLFC (ZdLFC), and rescaled dLFC (RdLFC). Both ZdLFC and RdLFC provided more consistent identification of synthetic lethal pairs across cell lines compared to the unscaled dLFC method. Conclusions: The ZdLFC method offers a robust framework for scoring synthetic lethal interactions from paralog screens, providing consistent results across different cell lines without requiring a training set of known positive interactors.

Identifiers

PMID39229040
PMCPMC11370406

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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.