ArticleTrends in genetics : TIG2012
Cancer heterogeneity: origins and implications for genetic association studies.
Article in Trends in genetics : TIG, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Relationship Between Interleukin-10 Gene C-819T Polymorphism and Gastric Cancer Risk: Insights From a Meta-Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2016Pooled it
- Engineering Functional Biomaterials for Targeted and Localized Cancer Drug Delivery: A Structure-Property-Performance Design Perspective.Pharmaceuticals (Basel, Switzerland) · 2026Review
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Depression and long-term mortality among 5-year breast cancer survivors in Korea: a retrospective population-based cohort study.Scientific reports · 2026Article
- Functional personalized complex combination nano therapy for osteosarcoma.Scientific reports · 2025Article
- Inhibition of Proliferation and Induction of Apoptosis by Gamma- or Delta-Tocotrienols in Human Colorectal Carcinoma Cells.BioMed research international · 2025Article
- AI-assisted discovery of potent FGFR1 inhibitors via virtual screening and in silico analysis.PloS one · 2025Article
- Comparative profiling of cellular gait on adhesive micropatterns defines statistical patterns of activity that underlie native and cancerous cell dynamics.bioRxiv : the preprint server for biology · 2023Article
- ParsVNN: parsimony visible neural networks for uncovering cancer-specific and drug-sensitive genes and pathways.NAR genomics and bioinformatics · 2021Article
- Exomes of Ductal Luminal Breast Cancer Patients from Southwest Colombia: Gene Mutational Profile and Related Expression Alterations.Biomolecules · 2020Article
- Discovery of VEGFR2 inhibitors by integrating naïve Bayesian classification, molecular docking and drug screening approaches.RSC advances · 2018Article
- SPARCoC: a new framework for molecular pattern discovery and cancer gene identification.PloS one · 2015Article
- Regularized machine learning in the genetic prediction of complex traits.PLoS genetics · 2014Article
- A multiclass likelihood ratio approach for genetic risk prediction allowing for phenotypic heterogeneity.Genetic epidemiology · 2013Article
- Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives.BioData mining · 2013Article
- A discovery study of daunorubicin induced cardiotoxicity in a sample of acute myeloid leukemia patients prioritizes P450 oxidoreductase polymorphisms as a potential risk factor.Frontiers in genetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders difficult the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goals of identifying targetable disease pathways and successfully treating individual patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.