ReviewSeminars in cancer biology2013
Integrated network analyses for functional genomic studies in cancer.
Review in Seminars in cancer biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- The online Tabloid Proteome: an annotated database of protein associations.Nucleic acids research · 2018Article
- Functional Genomics Approach Identifies Novel Signaling Regulators of TGFα Ectodomain Shedding.Molecular cancer research : MCR · 2018Article
- Multitype Network-Guided Target Controllability in Phenotypically Characterized Osteosarcoma: Role of Tumor Microenvironment.Frontiers in immunology · 2017Article
- Pathway-based network modeling finds hidden genes in shRNA screen for regulators of acute lymphoblastic leukemia.Integrative biology : quantitative biosciences from nano to macro · 2016Article
- Systematic evaluation of underlying defects in DNA repair as an approach to case-only assessment of familial prostate cancer.Oncotarget · 2015Article
- Article
- An argument for mechanism-based statistical inference in cancer.Human genetics · 2015Review
- Identification of potential glucocorticoid receptor therapeutic targets in multiple myeloma.Nuclear receptor signaling · 2015Article
- In vivo shRNA screens in solid tumors.Nature protocols · 2014Article
- Approaches to in vitro tissue regeneration with application for human disease modeling and drug development.Drug discovery today · 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
4 authors.
Funding
Abstract
RNA-interference (RNAi) studies hold great promise for functional investigation of the significance of genetic variations and mutations, as well as potential synthetic lethalities, for understanding and treatment of cancer, yet technical and conceptual issues currently diminish the potential power of this approach. While numerous research groups are usefully employing this kind of functional genomic methodology to identify molecular mediators of disease severity, response, and resistance to treatment, findings are generally confounded by "off-target" effects. These effects arise from a variety of issues beyond non-specific reagent behavior, such as biological cross-talk and feedback processes so thus can occur even with specific perturbation. Interpreting RNAi results in a network framework instead of merely as individual "hits" or "targets" leverages contributions from all hit/target contributions to pathways via their relationships with other network nodes. This interpretation can ameliorate dependence upon individual reagent performance and increase confidence in biological validation. Here we provide background on RNAi studies in cancer applications, review key challenges with functional genomics, and motivate the use of network models grounded in pathway analyses.
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.