Discovery of microarray-identified genes associated with ovarian cancer progression

Liu, Xia; Gao, Yanning; Zhao, Bingbing; Li, Xiaofeng; Lü, Yi; Zhang, Jian; Li, Danrong; Li, Li; Yin, Fuqiang

doi:10.3892/ijo.2015.2971

Cited by 35 publications

(37 citation statements)

References 62 publications

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“…Our data also underscore a role for the ALDH1A2 enzyme in supporting a TIC phenotype comparable to the ALDH1A1 enzyme already established in ovarian cancer (40–42). These findings expand on recent studies implicating ALDH1A2 in drug resistance and pathogenesis of ovarian cancer and reveals the diversity of ALDH enzymes in supporting cancer cells (43–46). We show that RelB regulates ALDH1A2 expression that is enhanced in culture conditions that enrich TICs.…”

Section: Discussionsupporting

confidence: 84%

NFκB Promotes Ovarian Tumorigenesis via Classical Pathways That Support Proliferative Cancer Cells and Alternative Pathways That Support ALDH+ Cancer Stem–like Cells

et al. 2017

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Understanding the mechanisms supporting tumor-initiating cells (TIC) is vital to combat advanced stage recurrent cancers. Here we show that in advanced ovarian cancers NF-kB signaling via the RelB transcription factor supports TIC populations by directly regulating the cancer stem-like associated enzyme aldehyde dehydrogenase (ALDH). Loss of RelB significantly inhibited spheroid formation, ALDH expression and activity, chemoresistance, and tumorigenesis in subcutaneous and intrabursal mouse xenograft models of human ovarian cancer. RelB also affected expression of the ALDH gene ALDH1A2. Interestingly, classical NF-kB signaling through the RelA transcription factor was equally important for tumorigenesis in the intrabursal model, but had no effect on ALDH. In this case, classical signaling via RelA was essential for proliferating cells, whereas the alternative signaling pathway was not. Our results show how NF-kB sustains diverse cancer phenotypes via distinct classical and alternative signaling pathways, with implications for improved understanding of disease recurrence and therapeutic response.

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Section: Discussionsupporting

confidence: 84%

NFκB Promotes Ovarian Tumorigenesis via Classical Pathways That Support Proliferative Cancer Cells and Alternative Pathways That Support ALDH+ Cancer Stem–like Cells

et al. 2017

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“…In particular, reusing of the data has the potential to predict treatment response and disease progression and was advantageous to develop precision therapies [12]. For example, based on data retrieved from Oncomine, TCGA, and GEO, Liu et al identified several genes associated with ovarian cancer progression [13] and drug resistance [14]. In a similar manner, we identified that upregulation of E2F transcription factor 3 is associated with poor prognosis in HCC [15].…”

Section: Introductionmentioning

confidence: 82%

Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma

Yin

Shu

Liu

et al. 2016

J Exp Clin Cancer Res

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BackgroundHepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful biomarkers to predict prognosis.MethodsPublic data portals including Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) profiles were used to retrieve the HCC-related microarrays and to identify potential genes contributed to cancer progression. Bioinformatics analyses including pathway enrichment, protein/gene interaction and text mining were used to explain the potential roles of the identified genes in HCC. Quantitative real-time polymerase chain reaction analysis and Western blotting were used to measure the expression of the targets. The data were analysed by SPSS 20.0 software.ResultsWe identified 80 genes that were significantly dysregulated in HCC according to four independent microarrays covering 386 cases of HCC and 327 normal liver tissues. Twenty genes were consistently and stably dysregulated in the four microarrays by at least 2-fold and detection of gene expression by RT-qPCR and western blotting showed consistent expression profiles in 11 HCC tissues compared with corresponding paracancerous tissues. Eleven of these 20 genes were associated with disease-free survival (DFS) or overall survival (OS) in a cohort of 157 HCC patients, and eight genes were associated with tumour pathologic PT, tumour stage or vital status. Potential roles of those 20 genes in regulation of HCC progression were predicted, primarily in association with metastasis. INTS8 was specifically correlated with most clinical characteristics including DFS, OS, stage, metastasis, invasiveness, diagnosis, and age.ConclusionThe significantly dysregulated genes identified in this study were associated with cancer progression and prognosis in HCC, and might be potential therapeutic targets for HCC treatment or potential biomarkers for diagnosis and prognosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-016-0403-2) contains supplementary material, which is available to authorized users.

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“…For instance, by retrieving data from Oncomine and TCGA, Yin et al () successfully identified a group of genes related to cancer progression and prognosis in hepatocellular carcinoma. Liu et al () identified six genes that may be potential therapeutic targets and biomarkers for diagnosis and prognosis in ovarian cancer, based on data retrieved from Oncomine, GEO, and TCGA. Thus, bioinformatics analysis is a feasible and valuable method to mine data and predict gene function.…”

Section: Introductionmentioning

confidence: 99%

Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases

Liu

Ouyang

Zhou

et al. 2018

Molec Gen & Gen Med

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Background Lung adenocarcinoma (LUAD) accounts for approximately 40% of all lung cancer patients. There is an urgent need to understand the mechanisms of cancer progression in LUAD and to identify useful biomarkers to predict prognosis. Methods In this study, Oncomine database was used to identify potential genes contributed to cancer progression. Bioinformatics analysis including pathway enrichment and text mining was used to explain the potential roles of identified genes in LUAD. The Cancer Genome Atlas database was used to analyze the association of gene expression with survival result. Results Our results indicated that 80 genes were significantly dysregulated in LUAD according to four microarrays covering 356 cases of LUAD and 164 cases of normal lung tissues. Twenty genes were consistently and stably dysregulated by more than twofold. Ten of 20 genes had a relationship with overall survival or disease‐free survival in a cohort of 516 LUAD patients, and 19 genes were associated with tumor stage, gender, age, lymph node, or smoking. Low expression of AGER and high expression of CCNB1 were specifically associated with poor survival. Conclusion Our findings implicate AGER and CCNB1 might be potential biomarkers for diagnosis and prognosis targets for LUAD.

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Discovery of microarray-identified genes associated with ovarian cancer progression

Cited by 35 publications

References 62 publications

NFκB Promotes Ovarian Tumorigenesis via Classical Pathways That Support Proliferative Cancer Cells and Alternative Pathways That Support ALDH+ Cancer Stem–like Cells

NFκB Promotes Ovarian Tumorigenesis via Classical Pathways That Support Proliferative Cancer Cells and Alternative Pathways That Support ALDH+ Cancer Stem–like Cells

Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma

Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases

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