SynthesisBMC cancer2010
Prioritizing genes associated with prostate cancer development.
Synthesis in BMC cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Connective Tissue Growth Factor in Digestive System Cancers: A Review and Meta-Analysis.BioMed research international · 2020Pooled it
- CTGF (CCN2): a multifaceted mediator in breast cancer progression and therapeutic targeting.Cancer metastasis reviews · 2025Review
- Article
- Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.Frontiers in genetics · 2023Article
- Anoikis in phenotypic reprogramming of the prostate tumor microenvironment.Frontiers in endocrinology · 2023Review
- Potentials of C-C motif chemokine 2-C-C chemokine receptor type 2 blockers including propagermanium as anticancer agents.Cancer science · 2019Review
- Overexpression of connective tissue growth factor is associated with tumor progression and unfavorable prognosis in endometrial cancer.Cancer biomarkers : section A of Disease markers · 2019Article
- Effects of connective tissue growth factor on prostate cancer bone metastasis and osteoblast differentiation.Oncology letters · 2018Article
- Clinical evaluation of macrophages in cancer: role in treatment, modulation and challenges.Cancer immunology, immunotherapy : CII · 2017Review
- The prognostic utility of the transcription factor SRF in docetaxel-resistant prostate cancer: in-vitro discovery and in-vivo validation.BMC cancer · 2017Article
- The cholesterol metabolite 27-hydroxycholesterol stimulates cell proliferation via ERβ in prostate cancer cells.Cancer cell international · 2017Article
- Targeting the CCL2-CCR2 signaling axis in cancer metastasis.Oncotarget · 2016Review
- CCL2 Chemokine as a Potential Biomarker for Prostate Cancer: A Pilot Study.Cancer research and treatment · 2015Article
- Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.British journal of cancer · 2014Article
- Role of SMAD4 in the mechanism of valproic acid's inhibitory effect on prostate cancer cell invasiveness.International urology and nephrology · 2014Article
- Evaluation of protein biomarkers of prostate cancer aggressiveness.BMC cancer · 2014Article
- miR-888 is an expressed prostatic secretions-derived microRNA that promotes prostate cell growth and migration.Cell cycle (Georgetown, Tex.) · 2014Article
- Article
- Androgen-responsive serum response factor target genes regulate prostate cancer cell migration.Carcinogenesis · 2013Article
- The present and future of prostate cancer urine biomarkers.International journal of molecular sciences · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThe genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development.
methodsA Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data.
resultsGenes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes--CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA--that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development.
conclusionsBy using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development.
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.