From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology.

Q2 Biochemistry, Genetics and Molecular Biology
High-Throughput Pub Date : 2018-10-26 DOI:10.3390/ht7040033
Maria Eugenia Gallo Cantafio, Katia Grillone, Daniele Caracciolo, Francesca Scionti, Mariamena Arbitrio, Vito Barbieri, Licia Pensabene, Pietro Hiram Guzzi, Maria Teresa Di Martino
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引用次数: 39

Abstract

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

Abstract Image

Abstract Image

从单水平分析到多组学综合方法:迈向精准肿瘤学的有力策略。
将来自不同分子水平的多组学数据与临床数据以及流行病学风险因素相结合,代表了一种准确而有前途的方法,可以理解包括癌症在内的人类疾病生物系统的复杂性。通过广泛使用新技术平台,可以从健康和疾病系统的分析中获得大量多维数据。因此,迫切需要在一个综合框架中对多组学数据进行全面分析,其中包括生物学途径背景下的累积效应。这一策略可以识别可能适合治疗干预的癌细胞通路成瘾。然而,转化为临床环境需要将组学数据与临床视觉进行优化整合,以充分利用精准癌症医学。我们将讨论现有的技术方法和特定领域的最新发展。
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来源期刊
High-Throughput
High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: -Microarrays -DNA Sequencing -RNA Sequencing -Protein Identification and Quantification -Cell-based Approaches -Omics Technologies -Imaging -Bioinformatics -Computational Biology/Chemistry -Statistics -Integrative Omics -Drug Discovery and Development -Microfluidics -Lab-on-a-chip -Data Mining -Databases -Multiplex Assays
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