ArticleProceedings of the National Academy of Sciences of the United States of America2012
Integrated cross-species transcriptional network analysis of metastatic susceptibility.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 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
44 citing papers in PubMed, 63 citations in OpenAlex.
- Genetic background and oncogenic driver determines the genomic evolution and transcriptomics of mammary tumor metastasis.Communications biology · 2025Article
- Investigating the genomic landscape of mouse models of breast cancer metastasis.bioRxiv : the preprint server for biology · 2025Article
- Article
- SMARCD1 is an essential expression-restricted metastasis modifier.Communications biology · 2024Article
- Telomere-related gene risk model for prognosis prediction in colorectal cancer.Translational cancer research · 2024Article
- SMARCD1 is a "Goldilocks" metastasis modifier.bioRxiv : the preprint server for biology · 2024Article
- Changes in spindle morphology driven by TPX2 overexpression in MYC-driven breast cancer cells.microPublication biology · 2024Article
- Transcriptomic Modulation Reveals the Specific Cellular Response in Chinese Sea Bass (International journal of molecular sciences · 2023Article
- PARP1 proximity proteomics reveals interaction partners at stressed replication forks.Nucleic acids research · 2022Article
- TIMM13 as a prognostic biomarker and associated with immune infiltration in skin cutaneous melanoma (SKCM).Frontiers in surgery · 2022Article
- Identification of key genes as predictive biomarkers for osteosarcoma metastasis using translational bioinformatics.Cancer cell international · 2021Article
- Phosphorylation-dependent BRD4 dimerization and implications for therapeutic inhibition of BET family proteins.Communications biology · 2021Article
- New immunological potential markers for triple negative breast cancer: IL18R1, CD53, TRIM, Jaw1, LTB, PTPRCAP.Discover oncology · 2021Article
- Article
- MYC Dysregulates Mitosis, Revealing Cancer Vulnerabilities.Cell reports · 2020Article
- Investigation of miRNA and mRNA Co-expression Network in Ependymoma.Frontiers in bioengineering and biotechnology · 2020Article
- Discovering Rare Genes Contributing to Cancer Stemness and Invasive Potential by GBM Single-Cell Transcriptional Analysis.Cancers · 2019Article
- An integrative functional genomics framework for effective identification of novel regulatory variants in genome-phenome studies.Genome medicine · 2018Article
- CEP55 promotes the proliferation, migration and invasion of esophageal squamous cell carcinoma via the PI3K/Akt pathway.OncoTargets and therapy · 2018Article
- Mitochondrial Haplotype Alters Mammary Cancer Tumorigenicity and Metastasis in an Oncogenic Driver-Dependent Manner.Cancer research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Metastatic disease is the proximal cause of mortality for most cancers and remains a significant problem for the clinical management of neoplastic disease. Recent advances in global transcriptional analysis have enabled better prediction of individuals likely to progress to metastatic disease. However, minimal overlap between predictive signatures has precluded easy identification of key biological processes contributing to the prometastatic transcriptional state. To overcome this limitation, we have applied network analysis to two independent human breast cancer datasets and three different mouse populations developed for quantitative analysis of metastasis. Analysis of these datasets revealed that the gene membership of the networks is highly conserved within and between species, and that these networks predicted distant metastasis free survival. Furthermore these results suggest that susceptibility to metastatic disease is cell-autonomous in estrogen receptor-positive tumors and associated with the mitotic spindle checkpoint. In contrast, nontumor genetics and pathway activities-associated stromal biology are significant modifiers of the rate of metastatic spread of estrogen receptor-negative tumors. These results suggest that the application of network analysis across species may provide a robust method to identify key biological programs associated with human cancer progression.
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.