Annual Report 2021
Division of Cancer Differentiation
Koji Okamoto, Daisuke Shiokawa, Yuuki Obata, Hirokazu Ohata, Hiroaki Sakai, Yutaro Mori, Yusuke Kanda, Seiko Ogawa, Ayumi Yumura, Mariko Niwa, Miyuki Natsume, Shiori Hikichi, Norie Kawahara, Ikuko Kato, Yoshie Okimoto
Introduction
Clinical cancers show a variety of intratumoral heterogeneity. The refractory traits of cancers, such as chemoresistance or the ability to metastasize, are profoundly associated with heterogeneity of cancers, in which a subpopulation of cancer survives after chemotherapy and leads to a fatal outcome. In order to understand the molecular basis of cancer heterogeneity, we first developed an in vitro spheroid culture from clinical specimens of colon, ovarian, and lung cancer. The established spheroid cells are now being used to generate mouse tumor xenografts. By performing single-cell gene expression analyses of the xenograft models, we stratify cancer and non-cancer cells into distinct subgroups to establish a clear picture of cancer heterogeneity. In addition, we perform spatial transcriptomics and ultra-high multiplexed imaging to demonstrate the spatial organization of tumors at the single-cell level. By combining single-cell analyses, spatial transcriptomics, and ultra-high multiplexed imaging, we are trying to identify chemoresistant areas in refractory cancers.
The Team and What We Do
We mainly perform basic research to understand the refractory nature of cancer and to devise effective diagnosis methods and therapies. We have built 3D cultures from clinical specimens, and have used them to develop xenograft models. We have subjected the established xenograft models to single-cell analyses, spatial transcriptomics, and ultra-high multiplexed imaging to investigate cellular heterogeneity and chemoresistance of refractory cancers.
Research activities
Understanding cancer heterogeneity and chemoresistance via single-cell analyses of xenografted colon tumors
We performed single-cell gene expression analyses of xenografted tumors derived from human colon cancer spheroids. Stratification of cancer cells in the xenografted tumors revealed that the formed tumors harbored slow-cycling and fast-cycling populations of Lgr5-positive cancer stem-like cells, and the slow-cycling populations were responsible for chemoresistance. The identified slow-cycling CSC-like cells will be a promising target for novel cancer chemotherapy in combination with conventional chemotherapeutic agents. Furthermore, we found a fraction of the slow-cycling CSCs were located at invasive fronts of tumors and showed EMT-related phenotypes, suggesting that these cells were involved in tumor invasion and metastasis.
Understanding cancer heterogeneity and chemoresistance via single-cell nuclear analyses of clinical specimens of clear cell carcinoma
Clear cell carcinoma is regarded as the deadliest type of ovarian cancer. In order to identify cell populations that are associated with chemoresistance of clear cell carcinoma, we performed single-cell nuclear RNA-seq analyses of frozen specimens from resistant and sensitive cases of this cancer and stratified them into distinct cell populations. Through comparison of resistant and sensitive cases, we identified a cell population associated with chemoresitance. We identified several candidate genes that may serve as therapeutic targets.
Spatial investigation of chemoresistant regions in cancers via spatial transcriptomics and ultra-high multiplexed imaging
We examined the spatial architecture of gene expression of cancer tissues by performing spatial trancriptomic analyses (Visium, 10x Genomics) and ultra-high multiplexed imaging (PhenoCycler, Akoya Biosciences). We spatially stratified the cancer tissues into distinct locations based on gene expression profiles. Subsequently, we combined the data from the spatial transcriptomics with single-cell analyses and identified regions that were associated with cancer chemoresistance. In particular, we demonstrated that in chemoresistant regions of clear ovarian cancer, cancer cells co-localize with cancer-associated fibroblasts (CAFs). Thus, the interactions between ovarian cancer cells and CAFs should be regarded as important therapeutic targets.
Mislocalization of cancer-causing mutant molecules and organelle signaling
We found by immunofluorescence assay that cancer-causing mutants, such as EGFR (⊿ex19), KIT (D816V), K-RAS (G13D), and NRAS (Q61L), mis-localize to endosomes, lysosomes, or the Golgi apparatus. Previously, we reported that a mutant KIT in leukemia is autophosphorylated preferentially on the Golgi apparatus, where it can initiate oncogenic signaling. Furthermore, we recently showed that FLT3 mutants in acute myelogenous leukemia are also retained in the Golgi region in a manner dependent on its tyrosine kinase activity. This activates downstream molecules in the Golgi apparatus. Establishment of a new strategy of inhibition of oncogenic signals through blocking intracellular trafficking is in progress.
Education
Teaching students (one graduate student, one undergraduate student)
Future Prospects
We intend to identify key cellular networks of chemoresistant cancer by combining single-cell analyses and spatial multi-omics analyses. In the future, we intend to translate the acquired knowledge into clinical therapy and eradicate refractory cancers.
List of papers published in 2021
Journal
1. Kanda Y, Ohata H, Miyazaki T, Sakai H, Mori Y, Shiokawa D, Yokoi A, Owa T, Ochiai A, Okamoto K. NF-κB suppression synergizes with E7386, an inhibitor of CBP/β-catenin interaction, to block proliferation of patient-derived colon cancer spheroids. Biochemical and biophysical research communications, 586:93-99, 2022
2. Miyazaki T, Chung S, Sakai H, Ohata H, Obata Y, Shiokawa D, Mizoguchi Y, Kubo T, Ichikawa H, Taniguchi H, Aoki K, Soga T, Nakagama H, Okamoto K. Stemness and immune evasion conferred by the TDO2-AHR pathway are associated with liver metastasis of colon cancer. Cancer science, 113:170-181, 2022
3. Yamawaki K, Mori Y, Sakai H, Kanda Y, Shiokawa D, Ueda H, Ishiguro T, Yoshihara K, Nagasaka K, Onda T, Kato T, Kondo T, Enomoto T, Okamoto K. Integrative analyses of gene expression and chemosensitivity of patient-derived ovarian cancer spheroids link G6PD-driven redox metabolism to cisplatin chemoresistance. Cancer letters, 521:29-38, 2021
4. Yamawaki K, Shiina I, Murata T, Tateyama S, Maekawa Y, Niwa M, Shimonaka M, Okamoto K, Suzuki T, Nishida T, Abe R, Obata Y. FLT3-ITD transduces autonomous growth signals during its biosynthetic trafficking in acute myelogenous leukemia cells. Scientific reports, 11:22678, 2021
5. Asada K, Takasawa K, Machino H, Takahashi S, Shinkai N, Bolatkan A, Kobayashi K, Komatsu M, Kaneko S, Okamoto K, Hamamoto R. Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research. Biomedicines, 9:2021
6. Ono H, Arai Y, Furukawa E, Narushima D, Matsuura T, Nakamura H, Shiokawa D, Nagai M, Imai T, Mimori K, Okamoto K, Hippo Y, Shibata T, Kato M. Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model. BMC biology, 19:207, 2021