Dataset Information

An Oncogenic NTRK Fusion in a Patient with Soft-Tissue Sarcoma with Response to the Tropomyosin-Related Kinase Inhibitor LOXO-101.

ABSTRACT: Oncogenic TRK fusions induce cancer cell proliferation and engage critical cancer-related downstream signaling pathways. These TRK fusions occur rarely, but in a diverse spectrum of tumor histologies. LOXO-101 is an orally administered inhibitor of the TRK kinase and is highly selective only for the TRK family of receptors. Preclinical models of LOXO-101 using TRK-fusion-bearing human-derived cancer cell lines demonstrate inhibition of the fusion oncoprotein and cellular proliferation in vitro, and tumor growth in vivo. The tumor of a 41-year-old woman with soft-tissue sarcoma metastatic to the lung was found to harbor an LMNA-NTRK1 gene fusion encoding a functional LMNA-TRKA fusion oncoprotein as determined by an in situ proximity ligation assay. In a phase I study of LOXO-101 (ClinicalTrials.gov no. NCT02122913), this patient's tumors underwent rapid and substantial tumor regression, with an accompanying improvement in pulmonary dyspnea, oxygen saturation, and plasma tumor markers.TRK fusions have been deemed putative oncogenic drivers, but their clinical significance remained unclear. A patient with a metastatic soft-tissue sarcoma with an LMNA-NTRK1 fusion had rapid and substantial tumor regression with a novel, highly selective TRK inhibitor, LOXO-101, providing the first clinical evidence of benefit from inhibiting TRK fusions.

SUBMITTER: Doebele RC

PROVIDER: S-EPMC4635026 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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An Oncogenic NTRK Fusion in a Patient with Soft-Tissue Sarcoma with Response to the Tropomyosin-Related Kinase Inhibitor LOXO-101.

Doebele Robert C RC Davis Lara E LE Vaishnavi Aria A Le Anh T AT Estrada-Bernal Adriana A Keysar Stephen S Jimeno Antonio A Varella-Garcia Marileila M Aisner Dara L DL Li Yali Y Stephens Philip J PJ Morosini Deborah D Tuch Brian B BB Fernandes Michele M Nanda Nisha N Low Jennifer A JA

Cancer discovery 20150727 10

<h4>Unlabelled</h4>Oncogenic TRK fusions induce cancer cell proliferation and engage critical cancer-related downstream signaling pathways. These TRK fusions occur rarely, but in a diverse spectrum of tumor histologies. LOXO-101 is an orally administered inhibitor of the TRK kinase and is highly selective only for the TRK family of receptors. Preclinical models of LOXO-101 using TRK-fusion-bearing human-derived cancer cell lines demonstrate inhibition of the fusion oncoprotein and cellular proli ...[more]

PMID: 26216294

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Project description:BackgroundVarious fusion strategies (feature-level fusion, matrix-level fusion, and image-level fusion) were used to fuse PET and MR images, which might lead to different feature values and classification performance. The purpose of this study was to measure the classification capability of features extracted using various PET/MR fusion methods in a dataset of soft-tissue sarcoma (STS).MethodsThe retrospective dataset included 51 patients with histologically proven STS. All patients had pre-treatment PET and MR images. The image-level fusion was conducted using discrete wavelet transformation (DWT). During the DWT process, the MR weight was set as 0.1, 0.2, 0.3, 0.4, …, 0.9. And the corresponding PET weight was set as 1- (MR weight). The fused PET/MR images was generated using the inverse DWT. The matrix-level fusion was conducted by fusing the feature calculation matrix during the feature extracting process. The feature-level fusion was conducted by concatenating and averaging the features. We measured the predictive performance of features using univariate analysis and multivariable analysis. The univariate analysis included the Mann-Whitney U test and receiver operating characteristic (ROC) analysis. The multivariable analysis was used to develop the signatures by jointing the maximum relevance minimum redundancy method and multivariable logistic regression. The area under the ROC curve (AUC) value was calculated to evaluate the classification performance.ResultsBy using the univariate analysis, the features extracted using image-level fusion method showed the optimal classification performance. For the multivariable analysis, the signatures developed using the image-level fusion-based features showed the best performance. For the T1/PET image-level fusion, the signature developed using the MR weight of 0.1 showed the optimal performance (0.9524(95% confidence interval (CI), 0.8413-0.9999)). For the T2/PET image-level fusion, the signature developed using the MR weight of 0.3 showed the optimal performance (0.9048(95%CI, 0.7356-0.9999)).ConclusionsFor the fusion of PET/MR images in patients with STS, the signatures developed using the image-level fusion-based features showed the optimal classification performance than the signatures developed using the feature-level fusion and matrix-level fusion-based features, as well as the single modality features. The image-level fusion method was more recommended to fuse PET/MR images in future radiomics studies.

Dataset Information

An Oncogenic NTRK Fusion in a Patient with Soft-Tissue Sarcoma with Response to the Tropomyosin-Related Kinase Inhibitor LOXO-101.

Publications

An Oncogenic NTRK Fusion in a Patient with Soft-Tissue Sarcoma with Response to the Tropomyosin-Related Kinase Inhibitor LOXO-101.

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