ReviewCancer metastasis reviews2010
Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer.
Review in Cancer metastasis reviews, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- DNA methylation analysis in plants: review of computational tools and future perspectives.Briefings in bioinformatics · 2020Review
- High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.Frontiers in genetics · 2019Article
- Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes.Oncotarget · 2018Article
- Integrative miRNA and mRNA analysis in penile carcinomas reveals markers and pathways with potential clinical impact.Oncotarget · 2017Article
- Synthetic lethality in lung cancer and translation to clinical therapies.Molecular cancer · 2016Review
- Strategies for Integrated Analysis of Genetic, Epigenetic, and Gene Expression Variation in Cancer: Addressing the Challenges.Frontiers in genetics · 2016Review
- Recurring DNA copy number gain at chromosome 9p13 plays a role in the activation of multiple candidate oncogenes in progressing oral premalignant lesions.Cancer medicine · 2014Article
- YEATS4 is a novel oncogene amplified in non-small cell lung cancer that regulates the p53 pathway.Cancer research · 2013Article
- Writing and rewriting the epigenetic code of cancer cells: from engineered proteins to small molecules.Molecular pharmacology · 2013Review
- Article
- Oncogene Ras/phosphatidylinositol 3-kinase signaling targets histone H3 acetylation at lysine 56.The Journal of biological chemistry · 2012Article
- Identification of aberrant pathways and network activities from high-throughput data.Briefings in bioinformatics · 2012Review
- Translating cancer 'omics' to improved outcomes.Genome research · 2012Article
- dbDEPC 2.0: updated database of differentially expressed proteins in human cancers.Nucleic acids research · 2012Article
- Evidence of epigenetic regulation of the tumor suppressor gene cluster flanking RASSF1 in breast cancer cell lines.Epigenetics · 2011Article
- Bioinformatics tools for cancer metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2011Article
- Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.PloS one · 2011Article
- Deciphering squamous cell carcinoma using multidimensional genomic approaches.Journal of skin cancer · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.
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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.