CGA Gene (Coding for the α Subunit of Glycoprotein Hormones) Overexpression in ERα-Positive Prostate Tumors

Bièche, Ivan; Latil, Alain; Parfait, Béatrice; Vidaud, Dominique; Laurendeau, Ingrid; Lidereau, Rosette; Cussenot, Olivier; Vidaud, Michel

doi:10.1016/s0302-2838(02)00020-9

Cited by 18 publications

(12 citation statements)

References 21 publications

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“… 34 , 35 However, compared with the beta subunit of glycoprotein hormones, 36 the alpha subunit may be a marker of tumors with low aggressiveness, eg, ER+ but not ER− cancer cells. 37 , 38 In this study, we also found the upregulated expression of CGA in ER+ breast cancer patients (log2 FC =2.63, FDR =2.82×10 −34 ).…”

Section: Discussionsupporting

confidence: 64%

Screening of feature genes in distinguishing different types of breast cancer using support vector machine

Wang¹,

Li²

2015

OTT

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ObjectiveTo screen the feature genes in estrogen receptor-positive (ER+) breast cancer in comparison with estrogen receptor-negative (ER−) breast cancer.MethodsNine microarray data of ER+ and ER− breast cancer samples were collected from Gene Expression Omnibus database. After preprocessing, data in five training sets were analyzed using significance analysis of microarrays to screen the differentially expressed genes (DEGs). The DEGs were further analyzed via support vector machine (SVM) function in e1071 package of R to construct a SVM classifier, the efficacy of which was verified by four testing sets and its combination with training sets using a leave-one-out cross-validation. Feature genes obtained by SVM classifier were subjected to function- and pathway-enrichment via the Database for Annotation, Visualization and Integrated Discovery and KEGG Orthology Based Annotation System, respectively.ResultsA total of 526 DEGs were screened between ER+ and ER− breast cancer. The SVM classifier demonstrated that these genes could distinguish different subtype samples with high accuracy of larger than 90%, and also showed good sensitivity, specificity, positive/negative predictive value, and area under receiver operating characteristic curve. The inflammatory and hormone biological processes were the common enriched results for two different function analyses, indicating that the inflammatory (ie, IL8) and hormone regulation (ie, CGA) genes may be the involved feature genes to distinguish ER+ and ER− types of breast cancer.ConclusionThe gene-expression profile data can provide feature genes to distinguish ER+ and ER− samples, and the identified genes can be used for biomarkers for ER+ samples.

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Section: Discussionsupporting

confidence: 64%

Screening of feature genes in distinguishing different types of breast cancer using support vector machine

Wang¹,

Li²

2015

OTT

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“…In fact, F2r/PAR1 was one of a 4-gene cohort which discriminated between patients with localized prostate cancer who did or did not experience relapse. F2R/PAR1 encodes CGA, which is the a subunit of human glycoprotein hormone chorionic gonadotropin, was overexpressed in patients who did not relapse, and its overexpression has been associated with a good prognosis in prostate cancer [8] and breast cancer [9]. Here, its downregulation was observed in a more aggressive breast cancer phenotype.…”

Section: Discussionmentioning

confidence: 96%

Capsaicin-induced inactivation of sensory neurons promotes a more aggressive gene expression phenotype in breast cancer cells

Erin

Zhao

Bylander

et al. 2006

Breast Cancer Res Treat

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Capsaicin-induced inactivation of sensory neurons has been reported to enhance metastasis of a murine breast cancer cell line, specifically enhancing myocardial metastases. Here we characterized changes in gene expression patterns in primary tumors which developed in capsaicin-treated vs. control mice. We identified a small cohort of genes (17) which all showed significant decreases in expression levels. All of the identified genes have been linked to cell growth, differentiation, and/or cancer progression. Three representative genes, Caspase-7 (an executor of apoptosis), ADAM-10 (A Disintegrin and Metalloprotease), and Elk-3 (a transcriptional repressor of the ternary factor subfamily of the Ets factors) were further investigated. All three showed dramatic downregulation at the protein level in primary tumors from capsaicin-treated animals compared with control (vehicle-treated) animals, and their expression was also lost in cell culture. Elk-3 and Caspase-7 were not expressed in vitro in cultured cell lines, suggesting that their expression was induced by the tumor microenvironment. Loss of Caspase-7 expression can be expected to result in loss of function of apoptotic pathways. At first glance, loss of ADAM-10 expression would be expected to result in decreased invasive capability, due to loss of matrix metalloprotease activity. However, just the opposite appears to be true. We found that ADAM-10 actually hydrolyzes Substance P. Specifically ADAM-10 produces the same growth-inhibitory products from Substance P (i.e., SP (1-7)) that Neprilysin does, so that loss of ADAM-10 expression actually results in loss of production of growth inhibitory peptides from Substance P. Similarly, ADAM-10 also efficiently hydrolyzes Calcitonin Gene-Related Peptide, which may act in concert with Substance P. Finally, overactivity of Ets transcriptional suppressor functions has been linked to inhibition of tumorigenesis (e.g., Erf and Mef), and in addition loss of Elk-3 expression might also be be linked to tumorigenesis via loss of its putative anti-inflammatory activities. There is anecdotal evidence in the literature to indicate that the rest of the down-regulated genes may also contribute to development of a more aggressive phenotype in this breast cancer model.

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“…After literature screening, 12 reviews [7,8,9,10,11,12,13,14,15,16,17,18] and 137 research papers [19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102...…”

Section: Resultsmentioning

confidence: 99%

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

et al. 2017

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Objectives: The aim of the study is to review biotechnology advances in gene expression profiling on prostate cancer (PCa), focusing on experimental platform development and gene discovery, in relation to different study designs and outcomes in order to understand how they can be exploited to improve PCa diagnosis and clinical management. Methods: We conducted a systematic literature review on gene expression profiling studies through PubMed/MEDLINE and Web of Science between 2000 and 2016. Tissue biopsy and clinical gene profiling studies with different outcomes (e.g., recurrence, survival) were included. Results: Over 3,000 papers were screened and 137 full-text articles were selected. In terms of technology used, microarray is still the most popular technique, increasing from 50 to 70% between 2010 and 2015, but there has been a rise in the number of studies using RNA sequencing (13% in 2015). Sample sizes have increased, as well as the number of genes that can be screened all at once, but we have also observed more focused targeting in more recent studies. Qualitative analysis on the specific genes found associated with PCa risk or clinical outcomes revealed a large variety of gene candidates, with a few consistent cross-studies. Conclusions: The last 15 years of research in gene expression in PCa have brought a large volume of data and information that has been decoded only in part, but advancements in high-throughput sequencing technology are increasing the amount of data that can be generated. The variety of findings warrants the execution of both validation studies and meta-analyses. Genetic biomarkers have tremendous potential for early diagnosis of PCa and, if coupled with other diagnostics (e.g., imaging), can effectively be used to concretize less-invasive, personalized prediction of PCa risk and progression.

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CGA Gene (Coding for the α Subunit of Glycoprotein Hormones) Overexpression in ERα-Positive Prostate Tumors

Cited by 18 publications

References 21 publications

Screening of feature genes in distinguishing different types of breast cancer using support vector machine

Screening of feature genes in distinguishing different types of breast cancer using support vector machine

Capsaicin-induced inactivation of sensory neurons promotes a more aggressive gene expression phenotype in breast cancer cells

Trends in Gene Expression Profiling for Prostate Cancer Risk Assessment: A Systematic Review

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