EPMA Journal

, Volume 8, Issue 1, pp 51–60

Pattern recognition for predictive, preventive, and personalized medicine in cancer

Review

DOI: 10.1007/s13167-017-0083-9

Cite this article as:
Cheng, T. & Zhan, X. EPMA Journal (2017) 8: 51. doi:10.1007/s13167-017-0083-9

Abstract

Predictive, preventive, and personalized medicine (PPPM) is the hot spot and future direction in the field of cancer. Cancer is a complex, whole-body disease that involved multi-factors, multi-processes, and multi-consequences. A series of molecular alterations at different levels of genes (genome), RNAs (transcriptome), proteins (proteome), peptides (peptidome), metabolites (metabolome), and imaging characteristics (radiome) that resulted from exogenous and endogenous carcinogens are involved in tumorigenesis and mutually associate and function in a network system, thus determines the difficulty in the use of a single molecule as biomarker for personalized prediction, prevention, diagnosis, and treatment for cancer. A key molecule-panel is necessary for accurate PPPM practice. Pattern recognition is an effective methodology to discover key molecule-panel for cancer. The modern omics, computation biology, and systems biology technologies lead to the possibility in recognizing really reliable molecular pattern for PPPM practice in cancer. The present article reviewed the pathophysiological basis, methodology, and perspective usages of pattern recognition for PPPM in cancer so that our previous opinion on multi-parameter strategies for PPPM in cancer is translated into real research and development of PPPM or precision medicine (PM) in cancer.

Keywords

Pattern recognition Predictive preventive personalized medicine Genomics Transcriptomics Proteomics Peptidomics Metabolomics Radiomics Systems biology 

Abbreviations

ADTEx

Aberration detection in tumour exome

CTC

Circulating tumor cell

ctDNA

Circulating tumor DNA

DF-SNPs

Decision forest for SNPs

LMIs

Low-mass ions

MALDI-TOF-MS

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

mRNA

Messenger RNA

ncRNA

Non-coding RNA

PM

Precision medicine

PPPM

Predictive, preventive and personalized medicine

RT-PCR

Real-time quantitative PCR

SNP

Single nucleotide polymorphisms

VOC

Volatile organic compounds

Funding information

Funder NameGrant NumberFunding Note
China “863” Plan Project
  • Grant No. 2014AA020610-1 to XZ
National Natural Science Foundation of China
  • Grant No. 81272798 and 81572278 to XZ
Hunan Provincial Natural Science Foundation of China
  • Grant No. 14JJ7008 to XZ

Copyright information

© European Association for Predictive, Preventive and Personalised Medicine (EPMA) 2017

Authors and Affiliations

  1. 1.Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China
  2. 2.Hunan Engineering Laboratory for Structural Biology and Drug Design, Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China
  3. 3.State Local Joint Engineering Laboratory for Anticancer Drugs, Xiangya HospitalCentral South UniversityChangshaPeople’s Republic of China
  4. 4.The State Key Laboratory of Medical GeneticsCentral South UniversityChangshaPeople’s Republic of China

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