• Title/Summary/Keyword: AMACR

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Expression and Characterization of ${\alpha}$-Methylacyl CoA Racemase from Anisakis simplex Larvae

  • Kim, Bong-Jin;Kim, Sun-Mi;Cho, Min-Kyung;Yu, Hak-Sun;Lee, Yong-Seok;Cha, Hee-Jae;Ock, Mee-Sun
    • Parasites, Hosts and Diseases
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    • v.50 no.2
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    • pp.165-171
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    • 2012
  • Larval excretory-secretory products of Anisakis simplex are known to cause allergic reactions in humans. A cDNA library of A. simplex 3rd-stage larvae (L3) was immunoscreened with polyclonal rabbit serum raised against A. simplex L3 excretory-secretory products to identify an antigen that elicits the immune response. One cDNA clone, designated as ${\alpha}$-methylacyl CoA racemase (Amacr) contained a 1,412 bp cDNA transcript with a single open reading frame that encoded 418 amino acids. A. simplex Amacr showed a high degree of homology compared to Amacr orthologs from other species. Amacr mRNA was highly and constitutively expressed regardless of temperature (10-$40^{\circ}C$) and time (24-48 hr). Immunohistochemical analysis revealed that Amacr was expressed mainly in the ventriculus of A. simplex larvae. The Amacr protein produced in large quantities from the ventriculus is probably responsible for many functions in the development and growth of A. simplex larvae.

Evaluation of Combined Quantification of PCA3 and AMACR Gene Expression for Molecular Diagnosis of Prostate Cancer in Moroccan Patients by RT-qPCR

  • Maane, Imane Abdellaoui;El Hadi, Hicham;Qmichou, Zineb;Al Bouzidi, Abderrahmane;Bakri, Youssef;Sefrioui, Hassan;Dakka, Nadia;Moumen, Abdeladim
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.12
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    • pp.5229-5235
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    • 2016
  • Prostate cancer (PCa) remains one of the most widespread and perplexing of all human malignancies. Assessment of gene expression is thought to have an important impact on cancer diagnosis, prognosis and therapeutic decisions. In this context, we explored combined expression of PCa related target genes AMACR and PCA3 in 126 formalin fixed paraffin embedded prostate tissues (FFPE) from Moroccan patients, using quantitative real time reverse transcription-PCR (RT-qPCR). This quantification required data normalization accomplished using stably expressed reference genes (RGs). A panel of twelve RG was assessed, data being analyzed using GenEx V6 based on geNorm, NormFinder and statistical methods. Accordingly, the hnRNP A1 gene was identified and selected as the most stably expressed RG for reliable and accurate gene expression quantification in prostate tissues. The ratios of both PCA3 and AMACR gene expression relative to that of the hnRNP A1 gene were calculated and the performance of each target gene for PCa diagnosis was evaluated using receiver-operating characteristics. PCA3 and AMACR mRNA quantification based on RT-qPCR may prove useful in PCa diagnosis. Of particular interesting, combining PCA3 and AMACR quantification improved PCa prediction by increasing sensitivity with retention of good specificity.

Significant Association of Alpha-Methylacyl-CoA Racemase Gene Polymorphisms with Susceptibility to Prostate Cancer: a Meta-Analysis

  • Chen, Nan;Wang, Jia-Rong;Huang, Lin;Yang, Yang;Jiang, Ya-Mei;Guo, Xiao-Jiang;He, Ya-Zhou;Zhou, Yan-Hong
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.5
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    • pp.1857-1863
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    • 2015
  • Background: Alpha-methylacyl-CoA racemase(AMACR) is thought to play key roles in diagnosis and prognosis of prostate cancer. However, studies of associations between AMACR gene polymorphisms and prostate cancer risk reported inconsistent results. Therefore, we conducted the present meta-analysis to clarify the link between AMACR gene polymorphisms and prostate cancer risk. Materials and Methods: A literature search was performed in PubMed, Embase, China National Knowledge Infrastructure (CNKI), Wanfang and Weipu databases. Odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated to assess the strength of any association between AMACR polymorphisms and prostate cancer risk. Subgroup analyses by ethnicity, source of controls, quality control and sample size were also conducted. Results: Five studies covering 3,313 cases and 3,676 controls on five polymorphisms (D175G, M9V, S201L, K277E and Q239H) were included in this meta-analysis. Significant associations were detected between prostate cancer and D175G (dominant model: OR=0.89, 95%CI=0.80-0.99, P=0.04) and M9V (dominant model: OR=0.87, 95%CI=0.78-0.97, P=0.01) polymorphisms as well as that in subgroup analyses. We also observed significant decreased prostate cancer risk in the dominant model (OR=0.90, 95%CI=0.81-0.99, P=0.04) for the S201L polymorphism. However, K277E and Q239H polymorphisms did not appear to be related to prostate cancer risk. Conclusions: The current meta-analysis indicated that D175G and M9V polymorphisms of the AMACR gene are related to prostate cancer. The S201L polymorphism might also be linked with prostate cancer risk to some extent. However, no association was observed between K277E or Q239H polymorphisms and susceptibility to prostate cancer.

Biomarkers for Evaluation of Prostate Cancer Prognosis

  • Esfahani, Maryam;Ataei, Negar;Panjehpour, Mojtaba
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.7
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    • pp.2601-2611
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    • 2015
  • Prostate cancer, with a lifetime prevalence of one in six men, is the second cause of malignancy-related death and the most prevalent cancer in men in many countries. Nowadays, prostate cancer diagnosis is often based on the use of biomarkers, especially prostate-specific antigen (PSA) which can result in enhanced detection at earlier stage and decreasing in the number of metastatic patients. However, because of the low specificity of PSA, unnecessary biopsies and mistaken diagnoses frequently occur. Prostate cancer has various features so prognosis following diagnosis is greatly variable. There is a requirement for new prognostic biomarkers, particularly to differentiate between inactive and aggressive forms of disease, to improve clinical management of prostate cancer. Research continues into finding additional markers that may allow this goal to be attained. We here selected a group of candidate biomarkers including PSA, PSA velocity, percentage free PSA, $TGF{\beta}1$, AMACR, chromogranin A, IL-6, IGFBPs, PSCA, biomarkers related to cell cycle regulation, apoptosis, PTEN, androgen receptor, cellular adhesion and angiogenesis, and also prognostic biomarkers with Genomic tests for discussion. This provides an outline of biomarkers that are presently of prognostic interest in prostate cancer investigation.