Evidence map›Paper›PMID 31640753›Full record

ReviewGenome medicine2019

Mapping genetic interactions in cancer: a road to rational combination therapies.

Beril Tutuncuoglu, Nevan J Krogan

Open access · goldAbstract readReview
In one paragraph

Review in Genome medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

14 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Review
  3. Application of nanomedicines in tumor immunotherapy.Journal of molecular cell biology · 2025
    Review
  4. Targeting super-enhancer activity for colorectal cancer therapy.American journal of translational research · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. IL-9 and IL-9-producing cells in tumor immunity.Cell communication and signaling : CCS · 2020
    Review
  13. Review
  14. 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

2 authors at 1 institution in 2 countries.

Beril TutuncuogluDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, 16th Street, Mission Bay Campus, San Francisco, CA, 94158-2140, USA.
Nevan J KroganDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, 16th Street, Mission Bay Campus, San Francisco, CA, 94158-2140, USA. nevan.krogan@ucsf.edu.ORCID 0000-0003-4902-337X
QB3 · US

Funding

Using Networks to Seed Hierarchical Whole-cell Models of CancerU54CA209891 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ASHWORTH, ALAN · 2017 to 2021
$10.9M
Uncovering differential functions of novel BRCA1 complexesF32CA239336 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TUTUNCUOGLU, BERIL · 2019 to 2020
$111k
National Cancer Institute (US) F32 CA-0135551NCI NIH HHS F32 CA239336NCI NIH HHS U54 CA209891
6 · The paper itself

Abstract

The discovery of synthetic lethal interactions between poly (ADP-ribose) polymerase (PARP) inhibitors and BRCA genes, which are involved in homologous recombination, led to the approval of PARP inhibition as a monotherapy for patients with BRCA1/2-mutated breast or ovarian cancer. Studies following the initial observation of synthetic lethality demonstrated that the reach of PARP inhibitors is well beyond just BRCA1/2 mutants. Insights into the mechanisms of action of anticancer drugs are fundamental for the development of targeted monotherapies or rational combination treatments that will synergize to promote cancer cell death and overcome mechanisms of resistance. The development of targeted therapeutic agents is premised on mapping the physical and functional dependencies of mutated genes in cancer. An important part of this effort is the systematic screening of genetic interactions in a variety of cancer types. Until recently, genetic-interaction screens have relied either on the pairwise perturbations of two genes or on the perturbation of genes of interest combined with inhibition by commonly used anticancer drugs. Here, we summarize recent advances in mapping genetic interactions using targeted, genome-wide, and high-throughput genetic screens, and we discuss the therapeutic insights obtained through such screens. We further focus on factors that should be considered in order to develop a robust analysis pipeline. Finally, we discuss the integration of functional interaction data with orthogonal methods and suggest that such approaches will increase the reach of genetic-interaction screens for the development of rational combination therapies.

Indexed as

Molecular Targeted TherapyAntineoplastic AgentsDrug Resistance, NeoplasmDrug Therapy, CombinationHumansNeoplasm ProteinsNeoplasmsPrognosisAntineoplastic AgentsNeoplasm Proteins

Identifiers

PMID31640753
PMCPMC6805649
OpenAlexW2981600478

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.