Literature DB >> 28821459

Clinical multi-omics strategies for the effective cancer management.

Byong Chul Yoo1, Kyung-Hee Kim2, Sang Myung Woo3, Jae Kyung Myung4.   

Abstract

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis. BIOLOGICAL SIGNIFICANCE: In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarker discovery; Cancer; Omics strategy; Predictive, preventive, and personalized medicine

Mesh:

Year:  2017        PMID: 28821459     DOI: 10.1016/j.jprot.2017.08.010

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  16 in total

Review 1.  Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis.

Authors:  Hidetaka Arimura; Mazen Soufi; Kenta Ninomiya; Hidemi Kamezawa; Masahiro Yamada
Journal:  Radiol Phys Technol       Date:  2018-10-29

2.  Acquisition of Invasiveness by Breast Adenocarcinoma Cells Engages Established Hallmarks and Novel Regulatory Mechanisms.

Authors:  Hanaa Mousa; Mahmoud Elgamal; Reham Ghazal Marei; Nazariy Souchelnytskyi; Kah-Wai Lin; Serhiy Souchelnytskyi
Journal:  Cancer Genomics Proteomics       Date:  2019 Nov-Dec       Impact factor: 4.069

3.  Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer.

Authors:  Yi Shen; Wei Xiong; Qi Gu; Qin Zhang; Jia Yue; Changsong Liu; Duan Wang
Journal:  Front Med (Lausanne)       Date:  2021-05-24

Review 4.  MicroRNA in Glioblastoma: An Overview.

Authors:  Barbara Banelli; Alessandra Forlani; Giorgio Allemanni; Anna Morabito; Maria Pia Pistillo; Massimo Romani
Journal:  Int J Genomics       Date:  2017-11-06       Impact factor: 2.326

5.  New Analysis Framework Incorporating Mixed Mutual Information and Scalable Bayesian Networks for Multimodal High Dimensional Genomic and Epigenomic Cancer Data.

Authors:  Xichun Wang; Sergio Branciamore; Grigoriy Gogoshin; Shuyu Ding; Andrei S Rodin
Journal:  Front Genet       Date:  2020-06-18       Impact factor: 4.599

Review 6.  Insulin-Like Growth Factor Binding Proteins in Autoimmune Diseases.

Authors:  Huihua Ding; Tianfu Wu
Journal:  Front Endocrinol (Lausanne)       Date:  2018-08-30       Impact factor: 5.555

Review 7.  Computational Oncology in the Multi-Omics Era: State of the Art.

Authors:  Guillermo de Anda-Jáuregui; Enrique Hernández-Lemus
Journal:  Front Oncol       Date:  2020-04-07       Impact factor: 6.244

8.  Editorial: Molecular Network Study of Pituitary Adenomas.

Authors:  Xianquan Zhan; Dominic M Desiderio
Journal:  Front Endocrinol (Lausanne)       Date:  2020-02-18       Impact factor: 5.555

Review 9.  Precision Medicine and Melanoma: Multi-Omics Approaches to Monitoring the Immunotherapy Response.

Authors:  Fabio Valenti; Italia Falcone; Sara Ungania; Flora Desiderio; Patrizio Giacomini; Chiara Bazzichetto; Fabiana Conciatori; Enzo Gallo; Francesco Cognetti; Gennaro Ciliberto; Aldo Morrone; Antonino Guerrisi
Journal:  Int J Mol Sci       Date:  2021-04-07       Impact factor: 5.923

10.  Integrated TCGA analysis implicates lncRNA CTB-193M12.5 as a prognostic factor in lung adenocarcinoma.

Authors:  Xuehai Wang; Gang Li; Qingsong Luo; Jiayong Xie; Chongzhi Gan
Journal:  Cancer Cell Int       Date:  2018-02-22       Impact factor: 5.722

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