Spatially Resolved Sequencing in Three-dimensional Cancer Tissue to Construct a High-Definition Genomic Map in Space
Wednesday, February 7
2:30 PM - 3:00 PM
Ph. D. candidate
Interdisciplinary Program for Bioengineering, Seoul National University
We all live in three-dimensional space, and so do our cells. Each of us in this globe has different characteristics and genetic information, and so do cancer cells in a tumor. We have very different attributes depending on countries and cultures, and cancer cells in a tumor also show distinct phenotypes according to their genotypes, epigenetic states, and environments. If someone thinks that the earth is a point-like zero-dimensional object, he/she has overlooked the diversity of people and would have a misleading conclusion. In the same vein, to fully understand cancer, we need to analyze cancer cells as is, without extracting and collecting their genetic material in a single tube.
Populations of cancer cells display serious heterogeneity in their phenotypic traits, which is important in both scientific and clinical aspects as it is deeply related to carcinogenesis and clinical outcomes. However, profiling genetic information in tumor cells en masse averages out variability between each tumor cells. Therefore, heterogeneous genetic information in tumor cells should be accessed by isolating each single cell or a minimal number of neighboring cells in tumor tissue into different reactors to separate their genetic information from that of surrounding populations.
In addition to the importance of each cell's identity, it is valuable to analyze a spatial organization of each cancer cell in the original tissue context. Spatial information of genetic information can affect clinical interpretation, because cancer cells evolve through geographic conditions and microenvironment of tissue, and can act differently depending on their location in the tumor. Thus, the spatially resolved sequencing platform meets the needs of cutting-edge cancer biology, which links histopathology to genomics to enable synergistic and more precise interpretation of cancer.
Here, we describe a spatially resolved sequencing method in three-dimensional cancer tissue to create a high-definition genomic map in space. To enable this, we have developed Phenotype-based High-throughput Laser Isolation and Sequencing (PHLI-seq) technology to isolate each cancer cell in consecutive tissue sections using a single laser pulse (~ 1 isolate/second). The isolated cells then underwent whole genome amplification and sequencing. The PHLI-seq system is equipped with an infrared nanosecond pulse laser and a discharging layer for cancer cell isolation. We have also developed automating software, which can be used by hospital pathologists or laboratory researchers to analyze cells remotely. We applied PHLI-seq to breast cancer tissue to analyze genome-wide copy number alterations (CNA) and single nucleotide alterations (SNA), and map each isolated cell's genomic data to the tissue's original location. Finally, we constructed a cancer genome map in 3D space of a breast cancer and visualized it using 3D visualization software. This study would provide new insights into cancer cell heterogeneity in relation to the spatial location of cancer cells.