Evidence map›Paper›PMID 24202319›Full record

ArticleCancers2013

Synthetic genetic targeting of genome instability in cancer.

Babu V Sajesh, Brent J Guppy, Kirk J McManus

Abstract read
In one paragraph

Article in Cancers, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Frontiers in cell and developmental biology · 2026
    Article
  2. Review
  3. Unveiling the vulnerabilities of synthetic lethality in triple-negative breast cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Review
  4. Article
  5. Review
  6. Article
  7. The SCF Complex Is Essential to Maintain Genome and Chromosome Stability.International journal of molecular sciences · 2021
    Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Synthetic lethal targeting of RNF20 through PARP1 silencing and inhibition.Cellular oncology (Dordrecht, Netherlands) · 2017
    Article
  15. Article
  16. Article
  17. Review
  18. Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  19. Article
  20. Article
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.

Babu V SajeshManitoba Institute of Cell Biology, Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0V9, Canada. mcmanusk@cc.umanitoba.ca.
Brent J Guppy
Kirk J McManus

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a leading cause of death throughout the World. A limitation of many current chemotherapeutic approaches is that their cytotoxic effects are not restricted to cancer cells, and adverse side effects can occur within normal tissues. Consequently, novel strategies are urgently needed to better target cancer cells. As we approach the era of personalized medicine, targeting the specific molecular defect(s) within a given patient's tumor will become a more effective treatment strategy than traditional approaches that often target a given cancer type or sub-type. Synthetic genetic interactions are now being examined for their therapeutic potential and are designed to target the specific genetic and epigenetic phenomena associated with tumor formation, and thus are predicted to be highly selective. In general, two complementary approaches have been employed, including synthetic lethality and synthetic dosage lethality, to target aberrant expression and/or function associated with tumor suppressor genes and oncogenes, respectively. Here we discuss the concepts of synthetic lethality and synthetic dosage lethality, and explain three general experimental approaches designed to identify novel genetic interactors. We present examples and discuss the merits and caveats of each approach. Finally, we provide insight into the subsequent pre-clinical work required to validate novel candidate drug targets.

Identifiers

PMID24202319
PMCPMC3795363

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.