Evidence map›Paper›PMID 23353056›Full record

ReviewCancer letters2013

Advances for studying clonal evolution in cancer.

Li Ding, Benjamin J Raphael, Feng Chen, Michael C Wendl

Open access · greenAbstract readReview
In one paragraph

Review in Cancer letters, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

41 citing papers in PubMed, 79 citations in OpenAlex.

  1. Review
  2. Combination of Lurbinectedin and Osimertinib for Treatment ofJTO clinical and research reports · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Reconstructing Clonal Evolution-A Systematic Evaluation of Current Bioinformatics Approaches.International journal of environmental research and public health · 2023
    Article
  8. Article
  9. Review
  10. Drug resistance and Cancer stem cells.Cell communication and signaling : CCS · 2021
    Review
  11. Genetic Variants ofFrontiers in oncology · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Prediction of Driver Modules via Balancing Exclusive Coverages of Mutations in Cancer Samples.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2019
    Article
  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

4 authors at 2 institutions in 1 country.

Li DingDepartment of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA; The Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA; Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA. Electronic address: lding@wustl.edu.
Benjamin J Raphael
Feng Chen
Michael C Wendl
Washington University in St. Louis · USBrown University · US

Funding

Large Scale Genome SequencingU54HG003079 · NHGRI · WASHINGTON UNIVERSITY · PI DUTCHER, SUSAN K · 2004 to 2016
$445.7M
A Turnkey System for High-throughput Variant Discovery and InterpretationU01HG006517 · NHGRI · WASHINGTON UNIVERSITY · PI DING, LI · 2012 to 2015
$3.0M
Computational Approaches for Structural Variation Studies in GenomesR01HG005690 · NHGRI · BROWN UNIVERSITY · PI RAPHAEL, BENJAMIN · 2011 to 2015
$2.4M
NFAT SIGNALING IN GLOMERULOSCLEROSISR01DK087960 · NIDDK · WASHINGTON UNIVERSITY · PI CHEN, FENG · 2010 to 2014
$1.6M
GENETIC DETERMINANTS IN KIDNEY AND URINARY TRACT DEFECTSR01DK081592 · NIDDK · WASHINGTON UNIVERSITY · PI CHEN, FENG · 2009 to 2012
$1.4M
CANCER SUSCEPTIBILITY VARIANT DISCOVERY IN HIGH THROUGHPUT SEQUENCING DATAR01CA180006 · NCI · WASHINGTON UNIVERSITY · PI DING, LI · 2013 to 2016
$1.1M
NCI NIH HHS R01 CA180006NHGRI NIH HHS R01 HG005690NHGRI NIH HHS R01HG005690NHGRI NIH HHS U01 HG006517NHGRI NIH HHS U01HG006517NHGRI NIH HHS U54 HG003079NHGRI NIH HHS U54HG003079NIDDK NIH HHS R01 DK081592NIDDK NIH HHS R01DK081592NIDDK NIH HHS R01 DK087960NIDDK NIH HHS R01DK087960
6 · The paper itself

Abstract

The "clonal evolution" model of cancer emerged and "evolved" amid ongoing advances in technology, especially in recent years during which next generation sequencing instruments have provided ever higher resolution pictures of the genetic changes in cancer cells and heterogeneity in tumors. It has become increasingly clear that clonal evolution is not a single sequential process, but instead frequently involves simultaneous evolution of multiple subclones that co-exist because they are of similar fitness or are spatially separated. Co-evolution of subclones also occurs when they complement each other's survival advantages. Recent studies have also shown that clonal evolution is highly heterogeneous: different individual tumors of the same type may undergo very different paths of clonal evolution. New methodological advancements, including deep digital sequencing of a mixed tumor population, single cell sequencing, and the development of more sophisticated computational tools, will continue to shape and reshape the models of clonal evolution. In turn, these will provide both an improved framework for the understanding of cancer progression and a guide for treatment strategies aimed at the elimination of all, rather than just some, of the cancer cells within a patient.

Indexed as

Clonal EvolutionGenome, HumanSequence Analysis, DNAAnimalsBiomarkers, TumorComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGenetic Predisposition to DiseaseGenetic TestingGenomicsHumansNeoplasmsNeoplastic Stem CellsPhenotypePrecision MedicineBiomarkers, TumorCancerClonal evolutionTumor heterogeneity

Identifiers

PMID23353056
PMCPMC3783624
OpenAlexW2041380745

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.