The challenges of tumor genetic diversity

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

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.

Detection of Intratumor Heterogeneity in Modern Pathology: A Multisite Tumor Sampling Perspective

Current sampling protocols of neoplasms along the digestive tract and in the urinary bladder have to be updated, as they do not respond to the necessities of modern personalized medicine. We show here that an adapted version of multisite tumor sampling (MSTS) is a sustainable model to overcome current deficiencies in digestive and bladder tumors when they are large enough so as to make unaffordable a total sampling. The new method is based on the divide-and-conquer algorithm and includes a slight modification of the MSTS, which proved to be useful very recently in clear cell renal cell carcinoma. This in silico analysis confirms the usefulness of MSTS for detecting intratumor heterogeneity (ITH) in tumors arising in hollow viscera. However, MSTS does not seem to improve routine traditional sampling in detecting tumor budding, extramural venous invasion, and perineural invasion. We conclude that (1) MSTS is the best method for tumor sampling to detect ITH balancing high performance and sustainable cost, (2) MSTS must be adapted to tumor shape and tumor location for an optimal performance.