A Gene Signature to Determine Metastatic Behavior in Thymomas

Yesim Polar, Robert W. Cook, Chirayu Pankaj Goswami, Jeff Wilkinson, Derek Maetzold, John F. Stone, Kristen M. Oelschlager, Ioan Tudor Vladislav, Kristen L. Shirar, Kenneth Kesler, Patrick Loehrer, Sunil Badve

Research output: Contribution to journalArticle

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Abstract

Purpose:Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.Methods:qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75).Results:A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036).Conclusion:A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.

Original languageEnglish
Article numbere66047
JournalPLoS One
Volume8
Issue number7
DOIs
StatePublished - Jul 24 2013

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thymoma
Thymoma
metastasis
Genes
Neoplasm Metastasis
genes
Survival Rate
survival rate
Gene expression
Tumors
Assays
Classifiers
resection
Proportional Hazards Models
disease course
Neoplasms
Gene Expression
Polymerase Chain Reaction
gene expression
therapeutics

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Polar, Y., Cook, R. W., Goswami, C. P., Wilkinson, J., Maetzold, D., Stone, J. F., ... Badve, S. (2013). A Gene Signature to Determine Metastatic Behavior in Thymomas. PLoS One, 8(7), [e66047]. https://doi.org/10.1371/journal.pone.0066047

A Gene Signature to Determine Metastatic Behavior in Thymomas. / Polar, Yesim; Cook, Robert W.; Goswami, Chirayu Pankaj; Wilkinson, Jeff; Maetzold, Derek; Stone, John F.; Oelschlager, Kristen M.; Vladislav, Ioan Tudor; Shirar, Kristen L.; Kesler, Kenneth; Loehrer, Patrick; Badve, Sunil.

In: PLoS One, Vol. 8, No. 7, e66047, 24.07.2013.

Research output: Contribution to journalArticle

Polar, Y, Cook, RW, Goswami, CP, Wilkinson, J, Maetzold, D, Stone, JF, Oelschlager, KM, Vladislav, IT, Shirar, KL, Kesler, K, Loehrer, P & Badve, S 2013, 'A Gene Signature to Determine Metastatic Behavior in Thymomas', PLoS One, vol. 8, no. 7, e66047. https://doi.org/10.1371/journal.pone.0066047
Polar Y, Cook RW, Goswami CP, Wilkinson J, Maetzold D, Stone JF et al. A Gene Signature to Determine Metastatic Behavior in Thymomas. PLoS One. 2013 Jul 24;8(7). e66047. https://doi.org/10.1371/journal.pone.0066047
Polar, Yesim ; Cook, Robert W. ; Goswami, Chirayu Pankaj ; Wilkinson, Jeff ; Maetzold, Derek ; Stone, John F. ; Oelschlager, Kristen M. ; Vladislav, Ioan Tudor ; Shirar, Kristen L. ; Kesler, Kenneth ; Loehrer, Patrick ; Badve, Sunil. / A Gene Signature to Determine Metastatic Behavior in Thymomas. In: PLoS One. 2013 ; Vol. 8, No. 7.
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abstract = "Purpose:Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.Methods:qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75).Results:A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77{\%} and 26{\%} for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97{\%} and 30{\%} for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49{\%} and 41{\%} for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036).Conclusion:A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.",
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AU - Polar, Yesim

AU - Cook, Robert W.

AU - Goswami, Chirayu Pankaj

AU - Wilkinson, Jeff

AU - Maetzold, Derek

AU - Stone, John F.

AU - Oelschlager, Kristen M.

AU - Vladislav, Ioan Tudor

AU - Shirar, Kristen L.

AU - Kesler, Kenneth

AU - Loehrer, Patrick

AU - Badve, Sunil

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N2 - Purpose:Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.Methods:qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75).Results:A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036).Conclusion:A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.

AB - Purpose:Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management.Methods:qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75).Results:A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036).Conclusion:A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.

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