ReviewFrontiers in oncology2023
Paralog-based synthetic lethality: rationales and applications.
Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 12 citations in OpenAlex.
- Evolutionary study of oncogenes and tumor suppressor genes in breast carcinoma.Journal of Taibah University Medical Sciences · 2026Article
- VRK1 Is a Novel Therapeutic Target for Small Cell Neuroendocrine Carcinoma of the Cervix.Cancer science · 2026Article
- Synthetic lethality in cancer therapy: Mechanisms, models and clinical translation for overcoming therapeutic resistance.Clinical and translational medicine · 2026Review
- A novel bispecific siRNA concept: Efficient dual knockdown ofMolecular therapy. Nucleic acids · 2025Article
- An allosteric cyclin E-CDK2 site mapped by paralog hopping with covalent probes.Nature chemical biology · 2025Article
- Expanding the ligandable proteome by paralog hopping with covalent probes.bioRxiv : the preprint server for biology · 2024Article
- Predicting host-based, synthetic lethal antiviral targets from omics data.NAR molecular medicine · 2024Article
- Predicting host-based, synthetic lethal antiviral targets from omics data.bioRxiv : the preprint server for biology · 2023Article
- Using graph-based model to identify cell specific synthetic lethal effects.Computational and structural biotechnology journal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell's survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.
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.