ArticleNature communications2024
Single-cell encoded gene silencing for high-throughput combinatorial siRNA screening.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
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Who cites it
1 citing paper in PubMed.
- Unraveling the influence of TGF-β rs9282871 and miRNA let-7c relative expression on TGF-β production in hepatocellular carcinoma patients.Journal, genetic engineering & biotechnology · 2026Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of combinatorial siRNAs shows great promise for drug discovery, but the identification of safe and effective siRNA combinations remains challenging. Here, we develop a massively multiplexed technology for systematic screening of siRNA-based cocktail therapeutics. We employ composite micro-carriers that are responsive to near infrared light and magnetic field to achieve photoporation-facilitated siRNA transfection to individual cells. Thus, randomized gene silencing by different siRNA formulations can be performed with high-throughput single-cell-based analyses. For screening anti-cancer siRNA cocktails, we test more than 1300 siRNA combinations for knocking down multiple genes related to tumor growth, discovering effective 3-siRNA formulations with an emphasis on the critical role of inhibiting Cyclin D1 and survivin, along with their complementary targets for synergic efficacy. This approach enables orders of magnitude reduction in time and cost associated with largescale siRNA screening, and resolves key insights to siRNA pharmacology that are not permissive to existing methods.
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