Abstract

Abstract Cancer results from somatic mutations such as copy number alterations (CNAs) that continue to accumulate during disease progression. These mutations can lead to functional heterogeneity within tumors and can influence the efficacy of cancer therapy. Therefore, studying the functional characteristics and spatial distribution of genetically distinct subclones is crucial to the understanding of tumor evolution and the design of cancer treatment. Here, we present Spatioscope, a method for subclone detection using copy number profiles that can be applied to spatial transcriptomics (ST) data and data from single-cell sequencing platforms such as scRNA-seq, scATAC-seq and scDNA-seq. Spatioscope implements a nested Chinese restaurant process, which mimics the tumor evolutionary process, to identify de novo subclones within one or multiple samples from the same patient. Spatioscope incorporates prior information from paired whole-genome or whole-exome sequencing (WGS/WES) data to achieve more reliable subclone detection and malignant cell labeling. We first applied Spatioscope on ST data from breast cancer, colorectal cancer and squamous cell carcinoma, as well as on scRNA-seq from three primary and metastatic gastrointestinal tumor samples. Spatioscope successfully distinguished malignant cells from stromal cells, and identified genetically distinct subclones which were validated using matched WGS/WES data, pathology annotations, or scDNA-seq data. On ST data, we show that Spatioscope accurately delineates the tumor’s invasive front, allowing for detailed characterization of interactions between stromal cells and malignant cells of different subclonal origins. In previous work, we showed the pervasive occurrence of highly complex subclonal allele-specific copy number alterations, and thus, we extended Spatioscope to identify subclones with different allele-specific copy number profiles. On three gastrointestinal tumor samples with scDNA-seq and two additional scATAC-seq datasets from a basal cell carcinoma and a gastric cancer cell line, Spatioscope successfully reconstructed complex recurrently mutated subclonal copy number regions. This is especially useful for data with sparse signals such as scATAC-seq when matched scDNA-seq data are unavailable. Using Spatioscope, we detected subclones based on copy number profiles in spatial and single cell tumor sequencing, enabling the investigation of the interplay between genome, transcriptome, and spatial environment during tumor evolution. Citation Format: Chi-Yun Wu, Paul R. Hess, Anuja Sathe, Jiazhen Rong, Billy T. Lau, Susan M. Grimes, Hanlee P. Ji, Nancy R. Zhang. Reconstructing the spatial evolution of cancer through subclone detection on copy number profiles in tumor sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5042.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.