Somatic genome evolution in cancer and aging through the lens of transcription

Abstract

DNA mutations accumulate in somatic cells throughout our lifetime, making the tissues in our body patchwork of mutant clones that evolve over time. This phenomenon, referred to as “somatic evolution”, underlies the initiation and progression of cancer as well as other age-related diseases. Limitations in existing analytical tools have largely constrained our understanding of somatic genome evolution in cancer and normal tissues. Although recent advances in single-cell DNA sequencing have enabled the characterization of genomic variations at the level of individual cells, they do not produce phenotypic measurements needed for assessing variant impact. Detecting genetic aberrations from single-cell RNA sequencing (scRNA-seq) data has the potential to overcome this limitation by coupling genetic and transcriptomic measurements within the same cell. In the first part of this dissertation, I describe a novel computational method, Numbat, that utilizes population-based haplotype phasing to achieve reliable detection of chromosomal alterations and clonal phylogeny from scRNA-seq data. Analysis of tumor samples from a wide range of cancer types shows that Numbat can accurately reconstruct the tumor copy number profile, precisely identify malignant cells in the tumor microenvironment, and resolve genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. Although aneuploidy is a defining feature of cancer cells, its extent and consequences in normal tissues remain largely unknown. In the second part of this dissertation, I describe an analysis of 16,672 RNA-seq samples from 948 healthy individuals in the GTEx project using an extension of the Numbat algorithm, representing the first large-scale pan-tissue survey of mosaic chromosomal alterations (mCAs) in the human body. We found that approximately a quarter of healthy individuals carry a clonally-expanded mCA in at least one tissue, with incidence strongly correlated with age. The prevalence and genome-wide patterns of mCAs vary considerably across tissue types, suggesting tissue-specific mutagenic exposure and selection pressures. The mCA landscapes in normal adrenal and pituitary glands resemble those in tumors arising from these tissues, whereas the same is not true for the esophagus and skin. Finally, scRNA-seq analysis of a normal adult adrenal gland harboring mCAs revealed gene expression changes related to cellular proliferation and hormone secretion. Together, these findings show a widespread age-dependent emergence of mCAs across normal human tissues with intricate connections to tumorigenesis.