COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer

Wu, Yi Hui; Chang, Tzu Hao; Huang, Yu Fang; Huang, Hsien Da; Chou, Cheng Yang

doi:10.1038/onc.2013.307

Cited by 180 publications

(186 citation statements)

References 45 publications

Supporting

Mentioning

174

Contrasting

Order By: Relevance

“…A previous study demonstrated that COL11A1 promoted tumor progression in EOC via ECM-receptor interactions (22), a similar result to that which the present study revealed using enrichment analysis. In ovarian cancer cells, the ECM-receptor interaction signaling pathway is affected by COL1A1 (23).…”

Section: Discussionsupporting

confidence: 79%

Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data

Xu³

et al. 2017

Oncology Letters

View full text Add to dashboard Cite

Abstract. Epithelial ovarian cancer (EOC) is a common cancer in women worldwide. The present study assessed effective biomarkers for the prognosis of EOC metastasis. The GSE30587 dataset, containing 9 EOC primary tumor samples and 9 matched omental metastasis samples, was analyzed. Following normalization, the differentially expressed genes (DEGs) between these samples were identified using the limma package for R. Subsequently, pathway enrichment analysis was performed using ClueGO, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes database. The microRNA (mRNA/miR)-target network was established using the multiMiR package. A set of 272 DEGs was identified in metastatic EOC samples, including 189 upregulated and 83 downregulated genes. Collagen type I α 1 chain (COL1A1), COL1A2, collagen type XI α 1 chain (COL11A1) and thrombospondin (THBS)1 were enriched in the phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), focal adhesion and extracellular matrix (ECM)-receptor interaction signaling pathways. THBS1 and tissue inhibitor of metalloproteinase (TIMP)3 were two dominant nodes in the PPI network and were key in the miRNA-target network, being targeted by hsa-miR-1. Multiple DEGs and miRNAs were identified as potential biomarkers for the prognosis of EOC metastasis in the present study, which likely affected metastasis by regulating the PI3K/Akt, ECM-receptor interaction and cell adhesion signaling pathways. In addition, THBS1 and TIMP3 were identified as potential targets of hsa-miR-1.

show abstract

Section: Discussionsupporting

confidence: 79%

Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data

Xu³

et al. 2017

Oncology Letters

View full text Add to dashboard Cite

show abstract

“…3D and SI Appendix, Table S1), resulting in a considerably altered collagen landscape in the FLHCC tissue. One of these, COL11A1, promotes tumor progression in ovarian cancer, where it is regulated by TGF-β1, which triggers the activation of SMAD2 (35). In FLHCC we observe increases in both TGF-β1 receptor and SMAD2 transcripts (Dataset S1, FLHCC v normal).…”

Section: Resultsmentioning

confidence: 76%

Transcriptomic characterization of fibrolamellar hepatocellular carcinoma

Simon

Freije

Farber

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

114

174

View full text Add to dashboard Cite

Fibrolamellar hepatocellular carcinoma (FLHCC) tumors all carry a deletion of ∼400 kb in chromosome 19, resulting in a fusion of the genes for the heat shock protein, DNAJ (Hsp40) homolog, subfamily B, member 1, DNAJB1, and the catalytic subunit of protein kinase A, PRKACA. The resulting chimeric transcript produces a fusion protein that retains kinase activity. No other recurrent genomic alterations have been identified. Here we characterize the molecular pathogenesis of FLHCC with transcriptome sequencing (RNA sequencing). Differential expression (tumor vs. adjacent normal tissue) was detected for more than 3,500 genes (log2 fold change ≥1, false discovery rate ≤0.01), many of which were distinct from those found in hepatocellular carcinoma. Expression of several known oncogenes, such as ErbB2 and Aurora Kinase A, was increased in tumor samples. These and other dysregulated genes may serve as potential targets for therapeutic intervention.

show abstract

“…Recent studies to identify ovarian cancer gene signatures capable of predicting clinical outcome also revealed the importance of genes involved in extracellular matrix remodeling and signaling. 31,32 In our study, we were also able to identify a differentially expressed ncRNA, SLC6A10P, which is a pseudogene of the creatine transporter, SLC6A8.…”

Section: Discussionmentioning

confidence: 92%

“…Increased expression of COL11A1 has been associated with poor outcome in ovarian tumors. 31,32 In contrast, upregulation of a COL2A1 following depletion of the oncogenic microRNA, miR-301, was shown to decrease migration and invasion of MCF-7 and MDA-MB-231 breast cancer cells. 33 The latter result is consistent with our observation associating COL2A1 with longer TTR.…”

Section: Discussionmentioning

confidence: 99%

Expression profile of COL2A1 and the pseudogene SLC6A10P predicts tumor recurrence in high‐grade serous ovarian cancer

Ganapathi

Jones

Sehouli

et al. 2015

Intl Journal of Cancer

View full text Add to dashboard Cite

Tumor recurrence, following initial response to adjuvant chemotherapy, is a major problem in women with high-grade serous ovarian cancer (HGSOC). Microarray analysis of primary tumors has identified genes that may be useful in risk stratification/overall survival, but are of limited value in predicting the >70% rate for tumor recurrence. In this study, we performed RNA-Seq analysis of primary and recurrent HGSOC to first identify unique differentially expressed genes. From this dataset, we selected 21 archetypical coding genes and one noncoding RNA, based on statistically significant differences in their expression profile between tumors, for validation by qPCR in a larger cohort of 110 ovarian tumors (71 primary and 39 recurrent) and for testing association of specific genes with time-to-recurrence (TTR). Kaplan-Meier tests revealed that high expression of collagen type II, alpha 1 (COL2A1) was associated with delayed TTR (HR 5 0.47, 95% CI: 0.27-0.82, p 5 0.008), whereas low expression of the pseudogene, solute carrier family 6 member 10 (SLC6A10P), was associated with longer TTR (HR 5 0.53, 95% CI: 0.30-0.93, p 5 0.027). Notably, TTR was significantly delayed for tumors that simultaneously highly expressed COL2A1 and lowly expressed SLC6A10P (HR 5 0.21, 95% CI: 0.082-0.54, p 5 0.0011), an estimated median of 95 months as compared to an estimated median of 16 months for subjects expressing other levels of COL2A1 and SLC6A10P. Thus, evaluating expression levels of COL2A1 and SLC6A10P at primary surgery could be beneficial for clinically managing recurrence of HGSOC.Deaths from all gynecological malignancies are about 30% but mortality for ovarian cancer is disproportionately high approaching 65%. Epithelial ovarian cancer is a heterogeneous disease with histological subtypes that differ in tissue of origin, genetic profile and outcome.1 High-grade serous ovarian cancer (HGSOC) is the most common subtype and >70% of women are diagnosed at an advanced stage of the disease owing to the lack of reliable early detection tests. Notwithstanding this problem, the standard of care involving tumor debulking surgery followed by adjuvant platinum/taxane-based chemotherapy can lead to a favorable response in 80% of the patients, but unfortunately the rate for recurrence is >70%. While resistance to the primary adjuvant chemotherapy regimen can contribute significantly to early tumor recurrence (<6 months), there is limited information on the mechanisms or genes that could predict for late recurrence. Genomic analysis of serous ovarian cancer has been useful for distinguishing low malignant potential, low-grade and high-grade tumors and these efforts have led to identification of molecular subtypes that can be linked to outcome. 2-7 Several studies on gene profiling of the primary tumor using microarray technology have described potential genes/pathways contributing to chemotherapy resistance and their association with risk stratification/overall survival. [8][9][10][11][12][13][14][15][16][17][18] Unlike the clinical impact...

show abstract

COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer

Cited by 180 publications

References 45 publications

Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data

Identification of candidate biomarkers for epithelial ovarian cancer metastasis using microarray data

Transcriptomic characterization of fibrolamellar hepatocellular carcinoma

Expression profile of COL2A1 and the pseudogene SLC6A10P predicts tumor recurrence in high‐grade serous ovarian cancer

Contact Info

Product

Resources

About