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

doi:10.1007/s13167-017-0083-9

Review

. 2017 Mar 9;8(1):51-60.

doi: 10.1007/s13167-017-0083-9. eCollection 2017 Mar.

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

Tingting Cheng^{1

2

3}, Xianquan Zhan^{1

2

3

4}

Affiliations

¹ Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
² Hunan Engineering Laboratory for Structural Biology and Drug Design, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
³ State Local Joint Engineering Laboratory for Anticancer Drugs, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
⁴ The State Key Laboratory of Medical Genetics, Central South University, 88 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.

PMID: 28620443
PMCID: PMC5471804
DOI: 10.1007/s13167-017-0083-9

Review

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

Tingting Cheng et al. EPMA J. 2017.

. 2017 Mar 9;8(1):51-60.

doi: 10.1007/s13167-017-0083-9. eCollection 2017 Mar.

Authors

Tingting Cheng^{1

2

3}, Xianquan Zhan^{1

2

3

4}

Affiliations

¹ Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
² Hunan Engineering Laboratory for Structural Biology and Drug Design, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
³ State Local Joint Engineering Laboratory for Anticancer Drugs, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.
⁴ The State Key Laboratory of Medical Genetics, Central South University, 88 Xiangya Road, Changsha, Hunan 410008 People's Republic of China.

PMID: 28620443
PMCID: PMC5471804
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: Genomics; Metabolomics; Pattern recognition; Peptidomics; Predictive preventive personalized medicine; Proteomics; Radiomics; Systems biology; Transcriptomics.

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Figures

**Fig. 1**
Types of biomarkers for cancer

**Fig. 2**
Integrative pattern based on omics data

**Fig. 3**
Ideal model about pattern recognition

See this image and copyright information in PMC

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References

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[1] Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Jr, Kinzler KW. Cancer genome landscapes. Science. 2013;339:1546–58. doi: 10.1126/science.1235122. - DOI - PMC - PubMed

[2] Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Jr, Kinzler KW. Cancer genome landscapes. Science. 2013;339:1546–58. doi: 10.1126/science.1235122. - DOI - PMC - PubMed

[3] Hoth M. CRAC channels, calcium, and cancer in light of the driver and passenger concept. Biochim Biophys Acta. 2016;1863(6 Pt B):1408–17. doi: 10.1016/j.bbamcr.2015.12.009. - DOI - PubMed

[4] Hoth M. CRAC channels, calcium, and cancer in light of the driver and passenger concept. Biochim Biophys Acta. 2016;1863(6 Pt B):1408–17. doi: 10.1016/j.bbamcr.2015.12.009. - DOI - PubMed

[5] Liu J, Mao Y, Li Z, Zhang D, Zhang Z, Hao S, et al. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma. J Magn Reson Imaging. 2016;44:445–55. doi: 10.1002/jmri.25156. - DOI - PubMed

[6] Liu J, Mao Y, Li Z, Zhang D, Zhang Z, Hao S, et al. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma. J Magn Reson Imaging. 2016;44:445–55. doi: 10.1002/jmri.25156. - DOI - PubMed

[7] Derks S, Cleven AH, Melotte V, Smits KM, Brandes JC, Azad N, et al. Emerging evidence for CHFR as a cancer biomarker: from tumor biology to precision medicine. Cancer Metastasis Rev. 2014;33:161–71. - PMC - PubMed

[8] Derks S, Cleven AH, Melotte V, Smits KM, Brandes JC, Azad N, et al. Emerging evidence for CHFR as a cancer biomarker: from tumor biology to precision medicine. Cancer Metastasis Rev. 2014;33:161–71. - PMC - PubMed

[9] Liu FF. Novel gene therapy approach for nasopharyngeal carcinoma. Semin Cancer Biol. 2002;12:505–15. doi: 10.1016/S1044579X02000937. - DOI - PubMed

[10] Liu FF. Novel gene therapy approach for nasopharyngeal carcinoma. Semin Cancer Biol. 2002;12:505–15. doi: 10.1016/S1044579X02000937. - DOI - PubMed

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

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

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