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Detection of the G17V RHOA Mutation in Angioimmunoblastic T-Cell Lymphoma and Related Lymphomas Using Quantitative Allele-Specific PCR

Nakamoto-Matsubara, Rie, Sakata-Yanagimoto, Mamiko, Enami, Terukazu, Yoshida, Kenichi, Yanagimoto, Shintaro, Shiozawa, Yusuke, Nanmoku, Tohru, Satomi, Kaishi, Muto, Hideharu, Obara, Naoshi, Kato, Takayasu, Kurita, Naoki, Yokoyama, Yasuhisa, Izutsu, Koji, Ota, Yasunori, Sanada, Masashi, Shimizu, Seiichi, Komeno, Takuya, Sato, Yuji, Ito, Takayoshi, Kitabayashi, Issay, Takeuchi, Kengo, Nakamura, Naoya, Ogawa, Seishi, Chiba, Shigeru·2014·PLoS ONE

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Figure 1 Design of primers used in the study. A WT allele-specific primer forward primer (Upper), a mutant allele-specific forward primer (Lower), and a common primer were designed. The 3′ end of the forward mutant primer was specific to the mutant site (G to T) and an internal mismatch at the second nucleotide from 3′ end (G to A) was introduced to improve specificity.
Figure 1 Design of primers used in the study. A WT allele-specific primer forward primer (Upper), a mutant allele-specific forward primer (Lower), and a common primer were designed. The 3′ end of the forward mutant primer was specific to the mutant site (G to T) and an internal mismatch at the second nucleotide from 3′ end (G to A) was introduced to improve specificity.CC BY · PubMed Central
Figure 2 Melting curve analysis. A. Melting curve constructed using WT allele-specific primers. B. Melting curve constructed using mutant allele-specific primer set.
Figure 2 Melting curve analysis. A. Melting curve constructed using WT allele-specific primers. B. Melting curve constructed using mutant allele-specific primer set.CC BY · PubMed Central
Figure 3 Standard curve showing linearity of quantitative allele-specific PCR. A standard curve was generated by serial dilution of WT or G17V cDNA that had been subcloned into pBluescript. A. Serial dilution of pBS/mutRHOA. Black dots correspond to 1.0×10−9∼1.0 unit of mutant plasmid (duplicate samples). The titration slope is −3.550 and R2 is 0.996. B. pBS/mutRHOA was mixed with pBS/wtRHOA at 100%, 10%, 1.0%, 0.1%, 0.01% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with allele-specific mutant primers. Horizonal axis indicates the amount of DNA per well. Vertical axis indicates unit for each sample. Black dot, MUT 100%; open dot, MUT 10%; square, MUT 1%; open square, MUT 0.1%; diamond, MUT 0.01%; triangle, MUT 0% (WT 100%) C. Serial dilution of pBS/wtRHOA. Black dots correspond to 1.0×10−6∼1.0 unit of WT cDNA (duplicate samples). The titration slope is −4.256, and R2 is 0.998. D. pBS/wtRHOA was mixed with pBS/mutRHOA at 100%, 10%, 1.0%, 0.1%, 0.1% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with WT allele-specific primers. Black dot, WT 100%; open dot, WT 10%; square, WT 1%; open square, WT 0.1%; triangle, WT 0% (MUT 100%).
Figure 3 Standard curve showing linearity of quantitative allele-specific PCR. A standard curve was generated by serial dilution of WT or G17V cDNA that had been subcloned into pBluescript. A. Serial dilution of pBS/mutRHOA. Black dots correspond to 1.0×10−9∼1.0 unit of mutant plasmid (duplicate samples). The titration slope is −3.550 and R2 is 0.996. B. pBS/mutRHOA was mixed with pBS/wtRHOA at 100%, 10%, 1.0%, 0.1%, 0.01% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with allele-specific mutant primers. Horizonal axis indicates the amount of DNA per well. Vertical axis indicates unit for each sample. Black dot, MUT 100%; open dot, MUT 10%; square, MUT 1%; open square, MUT 0.1%; diamond, MUT 0.01%; triangle, MUT 0% (WT 100%) C. Serial dilution of pBS/wtRHOA. Black dots correspond to 1.0×10−6∼1.0 unit of WT cDNA (duplicate samples). The titration slope is −4.256, and R2 is 0.998. D. pBS/wtRHOA was mixed with pBS/mutRHOA at 100%, 10%, 1.0%, 0.1%, 0.1% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with WT allele-specific primers. Black dot, WT 100%; open dot, WT 10%; square, WT 1%; open square, WT 0.1%; triangle, WT 0% (MUT 100%).CC BY · PubMed Central
Figure 4 qAS-PCR of AITL and PTCL-NOS samples. A, Shown are [mut]/([wt]+[mut]) values for each sample. N, mutation negative determined by MiSeq; P, mutation positive determined by MiSeq; Amp, amplified; PLP, periodate/lysine/paraformaldehyde-fixed; FFPE, formalin-fixed/paraffin-embedded. B, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 95 original or whole genome-amplified DNA samples, including 43 AITL and 52 PTCL-NOS. Cut-off values were determined as 1.5×10−2 for [mut]/([wt]+[mut]) by qAS-PCR and as 0.02 for mutant allele frequencies as determined by MiSeq. C, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 95 DNA samples in a log scales. D, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 13 FFPE PCR-amplicon samples.
Figure 4 qAS-PCR of AITL and PTCL-NOS samples. A, Shown are [mut]/([wt]+[mut]) values for each sample. N, mutation negative determined by MiSeq; P, mutation positive determined by MiSeq; Amp, amplified; PLP, periodate/lysine/paraformaldehyde-fixed; FFPE, formalin-fixed/paraffin-embedded. B, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 95 original or whole genome-amplified DNA samples, including 43 AITL and 52 PTCL-NOS. Cut-off values were determined as 1.5×10−2 for [mut]/([wt]+[mut]) by qAS-PCR and as 0.02 for mutant allele frequencies as determined by MiSeq. C, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 95 DNA samples in a log scales. D, Comparison of [mut]/([wt]+[mut]) values by qAS-PCR and mutant allele frequencies as determined by MiSeq for 13 FFPE PCR-amplicon samples.CC BY · PubMed Central
Figure 5 qAS-PCR for 275 tumor and control samples. qAS-PCR was performed for tumor samples, including 43 AITL (a), 52 PTCL-NOS (b), 5 T-cell lymphoma other than AITL and PTCL-NOS (c), 19 B-cell lymphomas (d), 129 myeloid malignancies (e) and 27 control samples (f).
Figure 5 qAS-PCR for 275 tumor and control samples. qAS-PCR was performed for tumor samples, including 43 AITL (a), 52 PTCL-NOS (b), 5 T-cell lymphoma other than AITL and PTCL-NOS (c), 19 B-cell lymphomas (d), 129 myeloid malignancies (e) and 27 control samples (f).CC BY · PubMed Central

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Research works printed but not linked: 18

  1. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, et al. (2008) WHO classification of tumors of haematopoietic and lymphoid tissues. 4th ed. Lyon, France. IARC Press: 306–311.
  2. L de Leval, 2010, Advances in the understanding and management of angioimmunoblastic T-cell lymphoma, Br J Haematol, 148, 673, 10.1111/j.1365-2141.2009.08003.x · DOI
  3. G Frizzera, 1974, Angio-immunoblastic lymphadenopathy with dysproteinaemia, Lancet, 1, 1070, 10.1016/S0140-6736(74)90553-4 · DOI
  4. A Dogan, 2003, Angioimmunoblastic T-cell lymphoma, Br J Haematol, 121, 681, 10.1046/j.1365-2141.2003.04335.x · DOI
  5. PP Piccaluga, 2013, Molecular profiling improves classification and prognostication of nodal peripheral T-cell lymphomas: results of a phase III diagnostic accuracy study, J Clin Oncol, 31, 3019, 10.1200/JCO.2012.42.5611 · DOI
  6. B Papadi, 2012, Atypical angioimmunoblastic T-cell lymphomas masquerading as systemic polyclonal B-immunoblastic proliferation, Virchows Arch, 461, 323, 10.1007/s00428-012-1280-5 · DOI
  7. L Couronne, 2012, TET2 and DNMT3A mutations in human T-cell lymphoma, N Engl J Med, 366, 95, 10.1056/NEJMc1111708 · DOI · Paper page
  8. RA Cairns, 2012, IDH2 mutations are frequent in angioimmunoblastic T-cell lymphoma, Blood, 119, 1901, 10.1182/blood-2011-11-391748 · DOI
  9. SM Langemeijer, 2009, Acquired mutations in TET2 are common in myelodysplastic syndromes, Nat Genet, 41, 838, 10.1038/ng.391 · DOI · Paper page
  10. M Sakata-Yanagimoto, 2014, Somatic RHOA mutation in angioimmunoblastic T cell lymphoma, Nat Genet, 46, 171, 10.1038/ng.2872 · DOI
  11. T Palomero, 2014, Recurrent mutations in epigenetic regulators, RHOA and FYN kinase in peripheral T cell lymphomas, Nat Genet, 46, 166, 10.1038/ng.2873 · DOI
  12. P Wangkumhang, 2007, WASP: a Web-based Allele-Specific PCR assay designing tool for detecting SNPs and mutations, BMC Genomics, 8, 275, 10.1186/1471-2164-8-275 · DOI
  13. D Shammaa, 2010, JAK2 V617F mutation detection: laboratory comparison of two kits using RFLP and qPCR, Genet Test Mol Biomarkers, 14, 13, 10.1089/gtmb.2009.0119 · DOI
  14. C Frantz, 2007, Comparative evaluation of three JAK2V617F mutation detection methods, Am J Clin Pathol, 128, 865, 10.1309/LW7Q3739RBRMBXXP · DOI
  15. Z Wu, 2011, Development and inter-laboratory validation of unlabeled probe melting curve analysis for detection of JAK2 V617F mutation in polycythemia vera, PLoS One, 6, e26534, 10.1371/journal.pone.0026534 · DOI
  16. E Tiacci, 2011, BRAF mutations in hairy-cell leukemia, N Engl J Med, 364, 2305, 10.1056/NEJMoa1014209 · DOI
  17. SP Treon, 2013, A new era for Waldenstrom macroglobulinemia: MYD88 L265P, Blood, 121, 4434, 10.1182/blood-2013-04-494849 · DOI
  18. HL Koskela, 2012, Somatic STAT3 mutations in large granular lymphocytic leukemia, N Engl J Med, 366, 1905, 10.1056/NEJMoa1114885 · DOI

Cited by

Metadata

Authors
Nakamoto-Matsubara, R., Sakata-Yanagimoto, M., Enami, T., Yoshida, K., Yanagimoto, S., Shiozawa, Y., Nanmoku, T., Satomi, K., Muto, H., Obara, N., Kato, T., Kurita, N., Yokoyama, Y., Izutsu, K., Ota, Y., Sanada, M., Shimizu, S., Komeno, T., Sato, Y., Ito, T., Kitabayashi, I., Takeuchi, K., Nakamura, N., Ogawa, S., & Chiba, S.
Venue
PLoS ONE
Published
2014-10-13
Volume
9
Issue
10
Pages
e109714
ISSN
1932-6203
Cited by
25
References
1
Language
en

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