The advent of Next-Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data. The Genomic Data Commons (GDC) Data Portal is a platform that contains different genomic studies including the ones from The Cancer Genome Atlas (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiatives, accounting for more than 40 tumor types originating from nearly 30000 patients. Such platforms, although very attractive, must make sure the stored data are easily accessible and adequately harmonized. Moreover, they have the primary focus on the data storage in a unique place, and they do not provide a comprehensive toolkit for analyses and interpretation of the data. To fulfill this urgent need, comprehensive but easily accessible computational methods for integrative analyses of genomic data that do not renounce a robust statistical and theoretical framework are required. In this context, the R/Bioconductor package TCGAbiolinks was developed, offering a variety of bioinformatics functionalities. Here we introduce new features and enhancements of TCGAbiolinks in terms of i) more accurate and flexible pipelines for differential expression analyses, ii) different methods for tumor purity estimation and filtering, iii) integration of normal samples from other platforms iv) support for other genomics datasets, exemplified here by the TARGET data. Evidence has shown that accounting for tumor purity is essential in the study of tumorigenesis, as these factors promote confounding behavior regarding differential expression analysis. With this in mind, we implemented these filtering procedures in TCGAbiolinks. Moreover, a limitation of some of the TCGA datasets is the unavailability or paucity of corresponding normal samples. We thus integrated into TCGAbiolinks the possibility to use normal samples from the Genotype-Tissue Expression (GTEx) project, which is another large-scale repository cataloging gene expression from healthy individuals. The new functionalities are available in the TCGAbiolinks version 2.8 and higher released in Bioconductor version 3.7.

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating and dose-limiting complication of cancer treatment. Thus far, the impact of CIPN has not been studied in a systematic clinimetric manner. The objective of the study was to select outcome measures for CIPN evaluation and to establish their validity and reproducibility in a cross-sectional multicenter study. Patients and methods:After literature review and a consensus meeting among experts, face/content validity were obtained for the following selected scales: the National Cancer Institute-Common Toxicity Criteria (NCI-CTC), the Total Neuropathy Score clinical version (TNSc), the modified Inflammatory Neuropathy Cause and Treatment (INCAT) group sensory sumscore (mISS), the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30, and CIPN20 quality-of-life measures. A total of 281 patients with stable CIPN were examined. Validity (correlation) and reliability studies were carried out.Results: Good inter-/intra-observer scores were obtained for the TNSc, mISS, and NCI-CTC sensory/motor subscales. Test-retest values were also good for the EORTC QLQ-C30 and CIPN20. Acceptable validity scores were obtained through the correlation among the measures. Conclusion:Good validity and reliability scores were demonstrated for the set of selected impairment and quality-of-life outcome measures in CIPN. Future studies are planned to investigate the responsiveness aspects of these measures.

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The application of intra- and internerve CSA variability measures allows us to quantify the heterogeneity of nerves and nerve segments and identify different US patterns in diverse immune-related neuropathies.

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