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Time lapse analysis of tumor response in patients with soft tissue sarcoma treated with trabectedin: A pooled analysis of two phase II clinical trials.

ABSTRACT: The time course of the response to each drug is important to avoid inappropriate termination of treatment by misjudging tumor progression; however, little is known about soft tissue sarcoma (STS) regarding this matter. This study aimed to perform a time-lapse analysis of tumor response in patients with STS treated with trabectedin from 2 phase II clinical trials. We examined 66 patients with translocation-related sarcoma registered in 2 Japanese phase II clinical trials. All patients previously received standard therapy before the administration of trabectedin at 1.2 mg/m² every 3 weeks. Imaging evaluation was performed according to the study protocol. The sum of the maximum diameters of the target lesions was calculated and analyzed over time. Among the 66 patients, 9 (13.6%) showed partial response (PR) to trabectedin. Histological diagnoses of these 9 responders comprised 6 myxoid liposarcoma, 2 synovial sarcoma, and a mesenchymal chondrosarcoma. The median period from treatment initiation to the first PR was 123 (range, 34-328) days. The pattern of tumor response to trabectedin showed an increasing tendency in size in the initial stage, usually followed by a size decrease with repeated administration. STS response to trabectedin was characterized as delayed and potentially persistent. Clinicians treating STS with trabectedin should know the features of the response pattern to avoid interrupting the treatment before maximal efficacy is achieved.

SUBMITTER: Endo M

PROVIDER: S-EPMC7286446 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Time lapse analysis of tumor response in patients with soft tissue sarcoma treated with trabectedin: A pooled analysis of two phase II clinical trials.

Endo Makoto M Takahashi Shunji S Araki Nobuhito N Sugiura Hideshi H Ueda Takafumi T Yonemoto Tsukasa T Takahashi Mitsuru M Morioka Hideo H Hiraga Hiroaki H Hiruma Toru T Kunisada Toshiyuki T Matsumine Akihiko A Goda Kazato K Kawai Akira A

Cancer medicine 20200327 11

The time course of the response to each drug is important to avoid inappropriate termination of treatment by misjudging tumor progression; however, little is known about soft tissue sarcoma (STS) regarding this matter. This study aimed to perform a time-lapse analysis of tumor response in patients with STS treated with trabectedin from 2 phase II clinical trials. We examined 66 patients with translocation-related sarcoma registered in 2 Japanese phase II clinical trials. All patients previously ...[more]

PMID: 32220056

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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

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Time lapse analysis of tumor response in patients with soft tissue sarcoma treated with trabectedin: A pooled analysis of two phase II clinical trials.

Publications

Time lapse analysis of tumor response in patients with soft tissue sarcoma treated with trabectedin: A pooled analysis of two phase II clinical trials.

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