Evidence map›Paper›PMID 21264404›Full record

ReviewIntegrative biology : quantitative biosciences from nano to macro2011

Cancer evolution and individual susceptibility.

Jesús Pérez-Losada, Andrés Castellanos-Martín, Jian-Hua Mao

Open access · greenAbstract readReview
In one paragraph

Review in Integrative biology : quantitative biosciences from nano to macro, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 8% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Evolutionary Origins of Metabolic Reprogramming in Cancer.International journal of molecular sciences · 2022
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Cancer Immunoprevention and Public Health.Frontiers in public health · 2017
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. ICAM-1 +469 A/G polymorphism and cancer risk: a meta-analysis involving 9375 subjects.International journal of clinical and experimental medicine · 2014
    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

3 authors at 3 institutions in 2 countries.

Jesús Pérez-LosadaInstituto de Biología Molecular y Celular del Cáncer (IBMCC), Instituto Mixto Universidad de Salamanca/CSIC, Campus Miguel de Unamuno s/n, Salamanca, 37007, Spain. jperezlosada@usal.es
Andrés Castellanos-Martín
Jian-Hua Mao
Centro de Investigación del Cáncer · ESLawrence Berkeley National Laboratory · USUniversidad de Salamanca · ES

Funding

The Role of Fbxw7 in genetic instability and cancerR01CA116481 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MAO, JIAN-HUA · 2008 to 2012
$1.7M
NCI NIH HHS R01 CA116481
6 · The paper itself

Abstract

Cancer susceptibility is due to interactions between inherited genetic factors and exposure to environmental carcinogens. The genetic component is constituted mainly by weakly acting low-penetrance genetic variants that interact among themselves, as well as with the environment. These low susceptibility genes can be categorized into two main groups: one includes those that control intrinsic tumor cell activities (i.e. apoptosis, proliferation or DNA repair), and the other contains those that modulate the function of extrinsic tumor cell compartments (i.e. stroma, angiogenesis, or endocrine and immune systems). Genome-Wide Association Studies (GWAS) of human populations have identified numerous genetic loci linked with cancer risk and behavior, but nevertheless the major component of cancer heritability remains to be explained. One reason may be that GWAS cannot readily capture gene-gene or gene-environment interactions. Mouse model approaches offer an alternative or complementary strategy, because of our ability to control both the genetic and environmental components of risk. Recently developed genetic tools, including high-throughput technologies such as SNP, CGH and gene expression microarrays, have led to more powerful strategies for refining quantitative trait loci (QTL) and identifying the critical genes. In particular, the cross-species approaches will help to refine locations of QTLs, and reveal their genetic and environmental interactions. The identification of human tumor susceptibility genes and discovery of their roles in carcinogenesis will ultimately be important for the development of methods for prediction of risk, diagnosis, prevention and therapy for human cancers.

Indexed as

Disease SusceptibilityAnimalsEnvironmental ExposureGenome-Wide Association StudyHumansNeoplasmsQuantitative Trait Loci

Identifiers

PMID21264404
PMCPMC3125395
OpenAlexW2048806453

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.