Evidence map›Paper›PMID 30610579›Full record

ReviewBiophysical reviews2019

Precision medicine review: rare driver mutations and their biophysical classification.

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

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Review
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  7. Article
  8. Tumors and their microenvironments: Learning from pediatric brain pathologies.Biochimica et biophysica acta. Reviews on cancer · 2025
    Review
  9. Molecular principles underlying aggressive cancers.Signal transduction and targeted therapy · 2025
    Review
  10. A protracted war against cancer drug resistance.Cancer cell international · 2024
    Review
  11. Review
  12. Anticancer drugs: How to select small molecule combinations?Trends in pharmacological sciences · 2024
    Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. AlphaFold, Artificial Intelligence (AI), and Allostery.The journal of physical chemistry. B · 2022
    Review
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

4 authors.

Ruth NussinovCancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, 1050 Boyles St., Frederick, MD, 21702, USA. NussinoR@mail.nih.gov.ORCID http://orcid.org/0000-0002-8115-6415
Hyunbum JangCancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, 1050 Boyles St., Frederick, MD, 21702, USA.
Chung-Jung TsaiCancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, 1050 Boyles St., Frederick, MD, 21702, USA.
Feixiong ChengGenomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44106, USA.

Funding

Protein Structure, Stability, and Amyloid FormationZIABC010440 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$11.8M
An individualized network medicine infrastructure for precision cardio-oncologyR00HL138272 · NHLBI · CLEVELAND CLINIC LERNER COM-CWRU · PI CHENG, FEIXIONG · 2018 to 2020
$747k
An individualized network medicine infrastructure for precision cardio-oncologyK99HL138272 · NHLBI · NORTHEASTERN UNIVERSITY · PI CHENG, FEIXIONG · 2017 to 2017
$86k
National Heart, Lung, and Blood Institute K99HL138272National Heart, Lung, and Blood Institute R00HL138272NHLBI NIH HHS K99 HL138272NHLBI NIH HHS R00 HL138272
6 · The paper itself

Abstract

How can biophysical principles help precision medicine identify rare driver mutations? A major tenet of pragmatic approaches to precision oncology and pharmacology is that driver mutations are very frequent. However, frequency is a statistical attribute, not a mechanistic one. Rare mutations can also act through the same mechanism, and as we discuss below, "latent driver" mutations may also follow the same route, with "helper" mutations. Here, we review how biophysics provides mechanistic guidelines that extend precision medicine. We outline principles and strategies, especially focusing on mutations that drive cancer. Biophysics has contributed profoundly to deciphering biological processes. However, driven by data science, precision medicine has skirted some of its major tenets. Data science embodies genomics, tissue- and cell-specific expression levels, making it capable of defining genome- and systems-wide molecular disease signatures. It classifies cancer driver genes/mutations and affected pathways, and its associated protein structural data guide drug discovery. Biophysics complements data science. It considers structures and their heterogeneous ensembles, explains how mutational variants can signal through distinct pathways, and how allo-network drugs can be harnessed. Biophysics clarifies how one mutation-frequent or rare-can affect multiple phenotypic traits by populating conformations that favor interactions with other network modules. It also suggests how to identify such mutations and their signaling consequences. Biophysics offers principles and strategies that can help precision medicine push the boundaries to transform our insight into biological processes and the practice of personalized medicine. By contrast, "phenotypic drug discovery," which capitalizes on physiological cellular conditions and first-in-class drug discovery, may not capture the proper molecular variant. This is because variants of the same protein can express more than one phenotype, and a phenotype can be encoded by several variants.

Indexed as

Conformational ensemblesDeep sequencingDrug discoveryGenomicsKRasMachine learningPharmacologyPhenotypic drug discoveryProteomicsRasSignaling pathways

Identifiers

PMID30610579
PMCPMC6381362

What OpenQuestion holds

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Registered trials

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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.