Single Cell and Imaging Genomics for Early Detection and Dynamic Monitoring of Cancer Evolution

Abstract

Early diagnosis and follow-up of the cancer development is a critical issue to enhance patient outcomes and permit interventions in time. Conventional diagnostic tools, including tissue biopsies and imaging peri-procedures, are usually not able to offer real-time information about tumor evolution and heterogeneity. This paper is an integration of single-cell genomics and imaging genomics, which is more dynamic and comprehensive in detecting and monitoring cancer. With the help of single-cell RNA sequencing (scRNA-seq), the major genetic mutations, such as TP53 (mutation frequency: 0.75) and KRAS (mutation frequency: 0.65), that are associated with the progression of tumors and resistance to therapy, were identified. Spatial and metabolic information of PET, MRI, and CT indicated that there were areas of high metabolic activity (level of activity in PET: 1.20), and vascular density (1.15) which is characteristic of aggressive tumor behavior. Clonal evolution was supported through longitudinal analysis whereby KRAS mutations were more common in metastatic subpopulations leading to an increase in tumor size (3.5 cm to 5.0 cm) and metastatic spread (2.0). On-going tumor adaptation was indicated by immune cell infiltration (CXCL12, CCL2 expression: 0.40) on the high tumorigenic areas. Combining genomic and imaging data makes it possible to monitor dynamically, which gives real-time and actionable information to consider in treating each patient individually. This research paper will show how these technologies can be used together to transform the method of detecting, monitoring and treating cancer.