ArticleBioMed research international2013
Molecular profiling predicts the existence of two functionally distinct classes of ovarian cancer stroma.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses 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
37 citing papers in PubMed, 3 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis.International journal of molecular sciences · 2023Pooled it
- Meta-analysis based gene expression profiling reveals functional genes in ovarian cancer.Bioscience reports · 2020Pooled it
- MARCKS contributes to stromal cancer-associated fibroblast activation and facilitates ovarian cancer metastasis.Oncotarget · 2016Pooled it
- Comprehensive analysis of molecular characteristics between primary and breast-derived metastatic ovarian cancer.Translational cancer research · 2025Article
- The extracellular matrix protein type I collagen and fibronectin are regulated by β-arrestin-1/endothelin axis in human ovarian fibroblasts.Journal of experimental & clinical cancer research : CR · 2025Article
- pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods.BMC bioinformatics · 2023Article
- PTEN deficiency exposes a requirement for an ARF GTPase module for integrin-dependent invasion in ovarian cancer.The EMBO journal · 2023Article
- Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.BMC cancer · 2023Article
- Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach.Frontiers in molecular biosciences · 2023Article
- Cytotoxic lymphocytes-related gene ITK from a systematic CRISPR screen could predict prognosis of ovarian cancer patients with distant metastasis.Journal of translational medicine · 2021Article
- Bioinformatic Analysis for Influential Core Gene Identification and Prognostic Significance in Advanced Serous Ovarian Carcinoma.Medicina (Kaunas, Lithuania) · 2021Article
- CENPA is one of the potential key genes associated with the proliferation and prognosis of ovarian cancer based on integrated bioinformatics analysis and regulated by MYBL2.Translational cancer research · 2021Article
- Non-Tumor CCAAT/Enhancer-Binding Protein Delta Potentiates Tumor Cell Extravasation and Pancreatic Cancer Metastasis Formation.Biomolecules · 2021Article
- Knockdown of KIF15 promotes cell apoptosis by activating crosstalk of multiple pathways in ovarian cancer: bioinformatic and experimental analysis.International journal of clinical and experimental pathology · 2021Article
- Common miRNAs, candidate genes and their interaction network across four subtypes of epithelial ovarian cancer.Bioinformation · 2021Article
- Targeting the tumor stroma: integrative analysis reveal GATA2 and TORYAIP1 as novel prognostic targets in breast and ovarian cancer.Turkish journal of biology = Turk biyoloji dergisi · 2021Article
- Cancer Exacerbates Chemotherapy-Induced Sensory Neuropathy.Cancer research · 2020Article
- Expression of long noncoding RNAs in cancer-associated fibroblasts linked to patient survival in ovarian cancer.Cancer science · 2020Article
- Ketamine Inhibits Ovarian Cancer Cell Growth by Regulating the lncRNA-PVT1/EZH2/p57 Axis.Frontiers in genetics · 2020Article
- How Autophagy Shapes the Tumor Microenvironment in Ovarian Cancer.Frontiers in oncology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although stromal cell signaling has been shown to play a significant role in the progression of many cancers, relatively little is known about its importance in modulating ovarian cancer development. The purpose of this study was to investigate the process of stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues. RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133 Plus 2.0) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of ovarian cancer patients (Cepi) and matched sets of surrounding cancer stroma (CS). For controls, ovarian surface epithelial cells (OSE) were isolated from the normal (noncancerous) ovaries and normal stroma (NS). Hierarchical clustering of the microarray data resulted in clear separations between the OSE, Cepi, NS, and CS samples. Expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples indicate the existence of two subgroups of cancer stroma (CS) with different propensities to support tumor growth. Our results indicate that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate 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.