一細胞RNA-seqによる肺腺がん細胞株薬剤反応多様性の解明

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 菅野 純夫, 東京大学教授 上田 卓也, 東京大学教授 中井 謙太, 東京大学客員教授 土原 一哉, がん研究会部長 八尾 良司University of Tokyo(東京大学

Single-cell sequencing techniques from individual to multiomics analyses

Single-cell sequencing: Greater insight through integrated data Combining data from different single-cell sequencing techniques could greatly improve understanding of the molecular profiles associated with disease. Sequencing studies provide valuable insights into diseased and healthy states at a single-cell level, for example the evolutionary paths of brain tumors and cancerous mutations. Ayako Suzuki at the University of Tokyo in Chiba, Japan, and co-workers examined the challenges of integrating data from various experimental and computational single-cell sequencing methods. These methods usually determine the genomic, epigenomic (DNA modifications) or transcriptomic (messenger RNAs) state of a cell, and can be combined to create a detailed picture. Other ‘multiomics’ techniques provide multilayered information from the same cell. The researchers recommend detailed analysis of individual data layers prior to integration, and highlight emerging techniques that analyze larger tissue sections, thus retaining the temporal and spatial information around a cell

Emergence and Evolution of ERM Proteins and Merlin in Metazoans

Ezrin, radixin, moesin, and merlin are cytoskeletal proteins, whose functions are specific to metazoans. They participate in cell cortex rearrangement, including cell–cell contact formation, and play an important role in cancer progression. Here, we have performed a comprehensive phylogenetic analysis of the proteins spanning 87 species. The results describe a possible mechanism for the protein family origin in the root of Metazoa, paralogs diversification in vertebrates, and acquisition of novel functions, including tumor suppression. In addition, a merlin paralog, present in most vertebrates but lost in mammals, has been described here for the first time. We have also highlighted a set of amino acid variations within the conserved motifs as the candidates for determining physiological differences between ERM paralogs

Alcohol consumption and the risk of heart failure: the Suita Study and meta-analysis of prospective cohort studies

Background: Alcohol consumption is a modifiable lifestyle, but its role in heart failure (HF) development is controversial. Herein, we investigated the prospective association between alcohol consumption and HF risk. Methods: A total of 2,712 participants (1,149 men and 1,563 women) from the Suita Study were followed up every two years. Cox regression was applied to calculate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of HF risk for heavy drinking (≥46 g/day in men or ≥23 g/day in women) and never drinking compared to light drinking (<23 g/day in men or <11.5 g/day in women). Then, we combined the results of the Suita Study with those from other eligible prospective cohort studies in a meta-analysis using the random-effects model. Results: In the Suita Study, within a median follow-up period of 8 years, 319 HF cases (162 in men and 157 in women) were detected. In men, but not women, never and heavy drinking carried a higher risk of HF than light drinking: HRs (95% CIs) = 1.65 (1.00, 2.73) and 2.14 (1.26, 3.66), respectively. Alike, the meta-analysis showed a higher risk of HF among heavy drinkers: HR (95% CI) = 1.37 (1.15, 1.62) and abstainers: HR (95% CI) = 1.18 (1.02, 1.37). Conclusion: We indicated a J-shaped association between alcohol consumption and HF risk among Japanese men. The results of the meta-analysis came in line with the Suita Study. Heavy-drinking men should be targeted for lifestyle modification interventions

Potentiality of multiple modalities for single-cell analyses to evaluate the tumor microenvironment in clinical specimens

Abstract Single-cell level analysis is powerful tool to assess the heterogeneity of cellular components in tumor microenvironments (TME). In this study, we investigated immune-profiles using the single-cell analyses of endoscopically- or surgically-resected tumors, and peripheral blood mononuclear cells from gastric cancer patients. Furthermore, we technically characterized two distinct platforms of the single-cell analysis; RNA-seq-based analysis (scRNA-seq), and mass cytometry-based analysis (CyTOF), both of which are broadly embraced technologies. Our study revealed that the scRNA-seq analysis could cover a broader range of immune cells of TME in the biopsy-resected small samples of tumors, detecting even small subgroups of B cells or Treg cells in the tumors, although CyTOF could distinguish the specific populations in more depth. These findings demonstrate that scRNA-seq analysis is a highly-feasible platform for elucidating the complexity of TME in small biopsy tumors, which would provide a novel strategies to overcome a therapeutic difficulties against cancer heterogeneity in TME