ReviewCancer research2013
From integrative genomics to therapeutic targets.
Review in Cancer research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.BMC bioinformatics · 2017Pooled it
- Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer.Journal of personalized medicine · 2021Review
- Article
- Breast cancer molecular subtype classifier that incorporates MRI features.Journal of magnetic resonance imaging : JMRI · 2016Article
- A tumor deconstruction platform identifies definitive end points in the evaluation of drug responses.Oncogene · 2016Article
- Integrated genomics approach to identify biologically relevant alterations in fewer samples.BMC genomics · 2015Article
- Whole genome and transcriptome sequencing of matched primary and peritoneal metastatic gastric carcinoma.Scientific reports · 2015Article
- OncoRep: an n-of-1 reporting tool to support genome-guided treatment for breast cancer patients using RNA-sequencing.BMC medical genomics · 2015Article
- New concepts in breast cancer genomics and genetics.Breast cancer research : BCR · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Combinatorial approaches that integrate conventional pathology with genomic profiling and functional genomics have begun to enhance our understanding of the genetic basis of breast cancer. These methods have identified key genotypic-phenotypic correlations in different breast cancer subtypes that have led to the discovery of genetic dependencies that drive their behavior. Moreover, this knowledge has been applied to define novel tailored therapies for these groups of patients with cancer. With the current emphasis on characterizing the mutational repertoire of breast cancers by next-generation sequencing, the question remains as to what constitutes a driver event. By focusing efforts on homogenous subgroups of breast cancer and integrating orthogonal data-types combined with functional approaches, we can begin to unravel the heterogeneity and identify aberrations that can be therapeutically targeted.
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.