ReviewDrug discovery today. Technologies2014
Use of RNAi screens to uncover resistance mechanisms in cancer cells and identify synthetic lethal interactions.
Review in Drug discovery today. Technologies, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Identification of Antibacterial Cyclic Peptides with a High-Throughput Cell-Based Dropout Screen.Journal of the American Chemical Society · 2026Article
- A genome-wide shRNA screen uncovers a novel potential ligand for NK cell activating receptors.Frontiers in immunology · 2025Article
- Evolution of Resistance to Irinotecan in Cancer Cells Involves Generation of Topoisomerase-Guided Mutations in Non-Coding Genome That Reduce the Chances of DNA Breaks.International journal of molecular sciences · 2023Article
- Combined genetic and chemical screens indicate protective potential for EGFR inhibition to cardiomyocytes under hypoxia.Scientific reports · 2021Article
- A Gene Expression High-Throughput Screen (GE-HTS) for Coordinated Detection of Functionally Similar Effectors in Cancer.Cancers · 2020Review
- Article
- Liver Cancer Gene Discovery Using Gene Targeting, Sleeping Beauty, and CRISPR/Cas9.Seminars in liver disease · 2019Review
- Pathway sensor-based functional genomics screening identifies modulators of neuronal activity.Scientific reports · 2018Article
- Bcl-2-dependent synthetic lethal interaction of the IDF-11774 with the V0 subunit C of vacuolar ATPase (ATP6V0C) in colorectal cancer.British journal of cancer · 2018Article
- Toward a Microparticle-Based System for Pooled Assays of Small Molecules in Cellular Contexts.ACS chemical biology · 2018Article
- Identification of proteasomal catalytic subunit PSMA6 as a therapeutic target for lung cancer.Cancer science · 2017Article
- Sources of Error in Mammalian Genetic Screens.G3 (Bethesda, Md.) · 2016Article
- Oncogene addiction: pathways of therapeutic response, resistance, and road maps toward a cure.EMBO reports · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
RNAi loss-of-function screens, which have proven effective to identify genes functionally responsible for cellular phenotypes, can be designed to use different genetic backgrounds or altered environmental conditions to elucidate genetic dependencies. These sorts of screening approaches can be exploited to identify genetic targets that minimize resistance to approved drugs, and provide a basis on which to develop new targeted therapies and predict the secondary targets for combinatorial treatments. Four types of pooled short hairpin RNA (shRNA) screens, in particular, have been used to look for genetic targets that work together with known drugs or other anticancer targets, either in an additive or synergistic fashion. Each method produces results that provide a useful but limited picture of the genetic elements driving oncogenesis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.