ReviewBreast cancer research : BCR2006
High-throughput genomic technology in research and clinical management of breast cancer. Evolving landscape of genetic epidemiological studies.
Review in Breast cancer research : BCR, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Integrative Genomic and Functional Approaches Identify FUOM as a Key Driver and Therapeutic Target in Cervical Cancer.Cancer reports (Hoboken, N.J.) · 2025Article
- A new SNP genotyping technology Target SNP-seq and its application in genetic analysis of cucumber varieties.Scientific reports · 2020Article
- Multi-parameter systematic strategies for predictive, preventive and personalised medicine in cancer.The EPMA journal · 2013Article
- Quality control genotyping for assessment of genetic identity and purity in diverse tropical maize inbred lines.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012Article
- Evaluation of the imputation performance of the program IMPUTE in an admixed sample from Mexico City using several model designs.BMC medical genomics · 2012Article
- Molecular characterization of diverse CIMMYT maize inbred lines from eastern and southern Africa using single nucleotide polymorphic markers.BMC genomics · 2012Article
- Association mapping via regularized regression analysis of single-nucleotide-polymorphism haplotypes in variable-sized sliding windows.American journal of human genetics · 2007Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Candidate polymorphism-based genetic epidemiological studies have yielded little success in the search for low-penetrance breast cancer susceptibility genes. The lack of progress is partially due to insufficient coverage of genomic regions with genetic markers, as well as economic constraints, limiting both the number of genetic targets and the number of individuals being studied. Recent rapid advances in high-throughput genotyping technology and our understanding of genetic variation patterns across the human genome are now revolutionizing the way in which genetic epidemiological studies are being designed and conducted. Genetic epidemiological studies are quickly progressing from candidate gene studies to comprehensive pathway investigation and, further, to genomic epidemiological studies where the whole human genome is being interrogated to identify susceptibility alleles. This paper reviews the evolving approaches in the search for low-penetrance breast cancer susceptibility gene variants and discusses their potential promises and pitfalls.
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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.