Vinorelbine Augments Radiotherapy in Hepatocellular Carcinoma.

There is a need to improve the effectiveness of radiotherapy (RT) in hepatocellular carcinoma (HCC). Therefore, the purpose of this study was to explore the efficacy and toxicity of the anti-microtubule agent Vinorelbine as a radiosensitizer in HCC. The radio sensitivity of 16 HCC patient-derived xenograft (PDX) models was determined by quantifying the survival fraction following irradiation in vitro, and Vinorelbine radio sensitization was determined by clonogenic assay. Ectopic HCC xenografts were treated with a single dose of 8 Gy irradiation and twice-weekly 3 mg/kg Vinorelbine. Tumor growth and changes in the proteins involved in DNA repair, angiogenesis, tumor cell proliferation, and survival were assessed, and the 3/16 (18.75%), 7/16 (43.75%), and 6/16 (37.5%) HCC lines were classified as sensitive, moderately sensitive, and resistant, respectively. The combination of RT and Vinorelbine significantly inhibited tumor growth, DNA repair proteins, angiogenesis, and cell proliferation, and promoted more apoptosis compared with RT or Vinorelbine treatment alone. Vinorelbine improved HCC tumor response to standard irradiation with no increase in toxicity. HCC is prevalent in less developed parts of the world and is mostly unresectable on presentation. Vinorelbine and conventional radiotherapy are cost-effective, well-established modalities of cancer treatment that are readily available. Therefore, this strategy can potentially address an unmet clinical need, warranting further investigation in early-phase clinical trials.

Comparison of radiomics tools for image analyses and clinical prediction in nasopharyngeal carcinoma.

OBJECTIVE: Radiomics pipelines have been developed to extract novel information from radiological images, which may help in phenotypic profiling of tumours that would correlate to prognosis. Here, we compared two publicly available pipelines for radiomics analyses on head and neck CT and MRI in nasopharynx cancer (NPC). METHODS AND MATERIALS: 100 biopsy-proven NPC cases stratified by T- and N-categories were enrolled in this study. Two radiomics pipeline, Moddicom (v. 0.51) and Pyradiomics (v. 2.1.2) were used to extract radiomics features of CT and MRI. Segmentation of primary gross tumour volume was performed using Velocity v. 4.0 by consensus agreement between three radiation oncologists. Intraclass correlation between common features of the two pipelines was analysed by Spearman's rank correlation. Unsupervised hierarchical clustering was used to determine association between radiomics features and clinical parameters. RESULTS: We observed a high proportion of correlated features in the CT data set, but not for MRI; 76.1% (51 of 67 common between Moddicom and Pyradiomics) of CT features and 28.6% (20 of 70 common) of MRI features were significantly correlated. Of these, 100% were shape-related for both CT and MRI, 100 and 23.5% were first-order-related, 61.9 and 19.0% were texture-related, respectively. This interpipeline heterogeneity affected the downstream clustering with known prognostic clinical parameters of cTN-status and GTVp. Nonetheless, shape features were the most reproducible predictors of clinical parameters among the different radiomics modules. CONCLUSION: Here, we highlighted significant heterogeneity between two publicly available radiomics pipelines that could affect the downstream association with prognostic clinical factors in NPC. ADVANCES IN KNOWLEDGE: The present study emphasized the broader importance of selecting stable radiomics features for disease phenotyping, and it is necessary prior to any investigation of multicentre imaging datasets to validate the stability of CT-related radiomics features for clinical prognostication.