Evidence map›Paper›PMID 29908887›Full record

ReviewJournal of molecular biology2018

The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine.

Kivilcim Ozturk, Michelle Dow, Daniel E Carlin, Rafael Bejar, Hannah Carter

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
9.3field-weighted citation impact, top 1% 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

44 citing papers in PubMed, 92 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Network analysis of driver genes in human cancers.Frontiers in bioinformatics · 2024
    Article
  10. Article
  11. Article
  12. The core symptom in multiple myeloma patients undergoing chemotherapy: a network analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
  13. Review
  14. Article
  15. Article
  16. Network-based approaches for modeling disease regulation and progression.Computational and structural biotechnology journal · 2023
    Review
  17. Article
  18. 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

5 authors at 2 institutions in 2 countries.

Kivilcim OzturkDepartment of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA.
Michelle DowDepartment of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA.
Daniel E CarlinDepartment of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA.
Rafael BejarMoores Cancer Center, Division of Hematology and Oncology, University of California San Diego, La Jolla, CA 92093, USA.
Hannah CarterDepartment of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA; Moores Cancer Center and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA; CIFAR, MaRS Centre, West Tower, 661 University Ave., Suite 505, Toronto, ON M5G 1M1, Canada. Electronic address: hkcarter@ucsd.edu.
University of California San Diego Medical Center · USUniversity of California, San Diego · US

Funding

SYNTHETIC SYSTEMSP50GM085764 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WINZELER, ELIZABETH A · 2010 to 2018
$23.3M
Using Networks to Seed Hierarchical Whole-cell Models of CancerU54CA209891 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ASHWORTH, ALAN · 2017 to 2021
$10.9M
San Diego Biomedical Informatics Education & Research (SABER)T15LM011271 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SHAMIM NEMATI · 2012 to 2026
$9.7M
Network approaches to identify cancer drivers from high-dimensional tumor dataDP5OD017937 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CARTER, HANNAH KATHRYN · 2013 to 2017
$1.9M
NCI NIH HHS U54 CA209891NIGMS NIH HHS P50 GM085764NIH HHS DP5 OD017937NLM NIH HHS T15 LM011271
6 · The paper itself

Abstract

Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR-ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However, biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but also by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis, and the path for such tools to the clinic.

Indexed as

AlgorithmsDisease SusceptibilityGenomicsHumansMedical OncologyNeoplasmsNeural Networks, ComputerPrecision MedicinePrognosisSystems Biologycancer systems biologynetwork analysisprecision cancer medicine

Identifiers

PMID29908887
PMCPMC6097914
OpenAlexW2808263699

What OpenQuestion holds

Textmetadata
LicenceTDM
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.