Evidence map›Paper›PMID 30921324›Full record

ReviewPLoS computational biology2019

Review: Precision medicine and driver mutations: Computational methods, functional assays and conformational principles for interpreting cancer drivers.

Ruth Nussinov, Hyunbum Jang, Chung-Jung Tsai, Feixiong Cheng

Erratum issuedAbstract readReview
In one paragraph

Review in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

58 citing papers in PubMed.

  1. Article
  2. Article
  3. Cancer-associated TRF1 mutations alter PARP1 interaction dynamics: an in silico study.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Anticancer drugs: How to select small molecule combinations?Trends in pharmacological sciences · 2024
    Review
  10. Review
  11. Review
  12. Article
  13. Network analysis of driver genes in human cancers.Frontiers in bioinformatics · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ruth NussinovComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.ORCID 0000-0002-8115-6415
Hyunbum JangComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.
Chung-Jung TsaiComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, Maryland, United States of America.
Feixiong ChengGenomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.ORCID 0000-0002-1736-2847

Funding

Protein Structure, Stability, and Amyloid FormationZIABC010440 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$11.8M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor's genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses-all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

Indexed as

Computer SimulationMutationPrecision MedicineHigh-Throughput Nucleotide SequencingHumansNeoplasm ProteinsNeoplasmsProtein ConformationSignal TransductionNeoplasm Proteins

Identifiers

PMID30921324
PMCPMC6438456

What OpenQuestion holds

Textmetadata
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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.