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

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 multiparameter strategies for PPPM in cancer is translated into real research and development of PPPM or precision medicine (PM) in cancer.

Recognition of Multiomics-Based Molecule-Pattern Biomarker for Precise Prediction, Diagnosis, and Prognostic Assessment in Cancer

“…Multiomics-generated biomarkers can make up integrative molecule-pattern biomarkers and pattern recognition for cancer treatment. This section mainly addresses the previous mentioned five omics approaches combined with computation biology and systems biology contribute to the development of cancer precise medicine (Figure 2) [9].…”

“…Another kind of biomarkers does not need to be causal to the occurrence and development of the disease, but requires to be provided with specificity and a certain number of changes to be easily detected. Based on Bayes' rule, three or more key molecules can form molecule-pattern biomarker Recognition of Multiomics-Based Molecule-Pattern Biomarker for Precise Prediction, Diagnosis… DOI: http://dx.doi.org /10.5772/intechopen.84221 to improve the accuracy of cancer diagnosis and therapy [9,37]. In summary, due to the complex pathophysiological basis of cancer, recognition of molecule-pattern biomarker for precise prediction, diagnosis, and prognostic assessment in cancer is an urgent demand to study and further close to realize precision medicine (PM) and PPPM.…”

“…Pattern recognition is an effective methodology to identify those molecule-panels. In fact, pattern recognition means that recognize molecule-pattern biomarkers, in other words, to use a set of patterns that consist of several biomarkers to improve the accuracy and specificity of prediction, prevention, diagnosis, treatment, and prognostic assessment of tumor [9].…”

Editorial: Molecular Network Study of Pituitary Adenomas

“…Of course, the mechanism of the invasiveness of pituitary adenomas is very complex. Multiomicsbased molecular network investigation might provide novel insights into the molecular mechanisms and therapeutic targets of pituitary adenoma invasiveness (5,11). Molecular networks are an effective approach to annotate the interactome in pituitary adenomas for in-depth insight into its molecular mechanisms and discovery of effective biomarkers and therapeutic targets (12,13).…”

“…Future issues will collect more multiomics-based molecular network studies with large-scale clinical information for basic research, translational research, and clinical practice in pituitary adenomas. We strongly believe that multiomics-based molecular network studies, molecular network-based therapeutic target and drug studies, and molecular network-based pattern biomarker studies (5,10,11,13,(32)(33)(34)(35)(36)(37) will bring a brighter future for pituitary adenoma patients through the realization of personalized and precision medicine.…”