The 9th symposium

Speech

Special　Lecture

“Elucidation of Genomic and Epigenomic Evolution and Diversity in Colorectal Cancer”
Koshi Mimori, Professor of Surgery (Kyushu University Beppu Hospital)

Both the morbidity and mortality of colorectal cancer in Japan have been increasing, and it is indisputable that intratumor heterogeneity/diversity is one of the major factors responsible. To improve the survival prognosis in patients with colorectal cancer, it is crucial to understand both the genomic and epigenomic evolution events that determine the evolutionary mechanisms of the cancer cells themselves, comprehensively, in chronological order. We performed intratumoral diversity analysis in a single colorectal cancer tumor by the multiple region partitioning analysis method, and elucidated the evolutionary patterns of the spatio-temporal cancer genome and epigenome by leading their lineage trees through mathematical and statistical processing of the “founder genome mutations (main clone)” ubiquitously existing in the whole tumor, and “progressor genome mutations (subclone)” that contribute to the generation of diversity (PLos Genet, 2016). Interestingly, the results revealed that at the genomic level, driver gene mutations were not found in the subclones, and only minor mutations contributed to the generation of diversity. Furthermore, at the epigenomic level, hypermethylation of CpG islands was ubiquitously observed throughout the tumor, while hypomethylation of sea or shore was unevenly distributed, resulting in the formation of diversity. The evolutionary patterns we found were different from those observed in existing cancer evolution models (ex. Big Bang model). We also found that the currently detected cancer evolutionary mechanisms generating intratumor heterogeneity had hardly been known previously. Therefore, to achieve elucidation of the mechanisms, we would like to demonstrate the results of our exhaustive search for conditions that would allow reproduction of such extensive intratumor heterogeneity, as observed in experimental data on colorectal cancer by establishing a cancer divergent evolution model (branching evolutionary process model; BEP model) and performing highly concurrent simulation with the super computer “Kei,” and also explain selective-pressure generating cancer diversity.

Research Presentation

“Identification of Cancer Treatment Resistance Genes based on a Comprehensive Gene Search Using Microarray Technologies and Comparative Oncology”
Keishi Yamashita, Junior Associate Professor (Kitasato University Department of Surgery)

The patterns of expression of tumor suppressor genes or proto-oncogenes can be dynamically changed in tumor tissues, and abnormalities may arise from those in either the genome or the epigenome. We have initiated a research project to identify therapeutic targets focusing on whether control of epigenetic abnormalities can suppress cancer, and how epigenetic abnormalities may be involved in treatment resistance. Phenylbutyrate (PB) has an antagonistic action on histone deacetylation (HDAC), and strongly suppresses cancer cell proliferation through epigenetic mechanisms. The degree of suppression may vary depending on the type of cancer cell; therefore, while considering treatment strategies, it is important to identify the molecular mechanisms responsible for such variations. Exploratory studies on breast and colorectal cancers revealed close involvement the Zeb1 and Ascl2 genes, respectively, in treatment resistance of. In the former, the abnormalities were of epigenetic origin, while in the latter, they were of genetic origin. Anti- significant differences in the resistance and sensitivity to OBP801, which is a more effective HDAC inhibitor than PB, were observed among cell lines of esophagus cancer. Considering this result, we identified SOX2 and delta p63 as candidate genes to explain such differences, and are conducting their functional analyses. Thus, the molecules associated with drug resistance can vary by type of cancer, and both genomic and epigenetic mechanisms may be involved in their expression. Thus, the molecular strategies needed for identification of target molecules aimed at cancer treatment can vary by the type of cancer.