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Development of a radiosensitivity gene signature for patients with soft tissue sarcoma.

ABSTRACT: Adjuvant radiotherapy is an important clinical treatment option for the majority of sarcomas. The motivation of current study is to identify a gene signature and to predict radiosensitive patients who are most likely to benefit from radiotherapy. Using the public available data of soft tissue sarcoma from The Cancer Genome Atlas, we developed a cross-validation procedure for identifying a gene signature and predicting radiosensitive patients through. The result showed that the predicted radiosensitive patients who received radiotherapy had a significantly better survival with a reduced rate of new tumor event and disease progression. Strata analysis showed that the predicted radiosensitive patients had significantly better survival under radiotherapy independent of histologic types. A hierarchical cluster analysis was used to validate the gene signature, and the results showed the predicted sensitivity for each patient well matched the results from cluster analysis. Together, we demonstrate a radiosensitive molecular signature that can be potentially used for identifying radiosensitive patients with sarcoma.

SUBMITTER: Tang Z

PROVIDER: S-EPMC5432346 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Development of a radiosensitivity gene signature for patients with soft tissue sarcoma.

Tang Zaixiang Z Zeng Qinghua Q Li Yan Y Zhang Xinyan X Ma Jinlu J Suto Mark J MJ Xu Bo B Yi Nengjun N

Oncotarget 20170401 16

Adjuvant radiotherapy is an important clinical treatment option for the majority of sarcomas. The motivation of current study is to identify a gene signature and to predict radiosensitive patients who are most likely to benefit from radiotherapy. Using the public available data of soft tissue sarcoma from The Cancer Genome Atlas, we developed a cross-validation procedure for identifying a gene signature and predicting radiosensitive patients through. The result showed that the predicted radiosen ...[more]

PMID: 28404969

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Project description:Objective: Trabectedin is an anti-cancer drug commonly used for the treatment of patients with metastatic soft tissue sarcoma (mSTS). Despite its recognized efficacy, significant variability in pharmacological response has been observed among mSTS patients. To address this issue, this pharmacometabolomics study aimed to identify pre-dose plasma metabolomics signatures that can explain individual variations in trabectedin pharmacokinetics and overall clinical response to treatment. Methods: In this study, 40 mSTS patients treated with trabectedin administered by 24 h-intravenous infusion at a dose of 1.5 mg/m2 were enrolled. The patients' baseline plasma metabolomics profiles, which included derivatives of amino acids and bile acids, were analyzed using multiple reaction monitoring LC-MS/MS together with their pharmacokinetics profile of trabectedin. Multivariate Partial least squares regression and univariate statistical analyses were utilized to identify correlations between baseline metabolite concentrations and trabectedin pharmacokinetics, while Partial Least Squares-Discriminant Analysis was employed to evaluate associations with clinical response. Results: The multiple regression model, derived from the correlation between the AUC of trabectedin and pre-dose metabolomics, exhibited the best performance by incorporating cystathionine, hemoglobin, taurocholic acid, citrulline, and the phenylalanine/tyrosine ratio. This model demonstrated a bias of 4.6% and a precision of 17.4% in predicting drug AUC, effectively accounting for up to 70% of the inter-individual pharmacokinetic variability. Through the use of Partial least squares-Discriminant Analysis, cystathionine and hemoglobin were identified as specific metabolic signatures that effectively distinguish patients with stable disease from those with progressive disease. Conclusions: The findings from this study provide compelling evidence to support the utilization of pre-dose metabolomics in uncovering the underlying causes of pharmacokinetic variability of trabectedin, as well as facilitating the identification of patients who are most likely to benefit from this treatment. Graphical Abstract

Dataset Information

Development of a radiosensitivity gene signature for patients with soft tissue sarcoma.

Publications

Development of a radiosensitivity gene signature for patients with soft tissue sarcoma.

Similar Datasets

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