Clonal structures and cell interactions in cancer

Despite sharing an identical genome, cells of higher order multicellular organisms display a large degree of phenotypic diversity. This diversity is maintained by a sophisticated regulatory machinery that integrates information from both intrinsic and extrinsic factors, ultimately coordinating the appropriate gene expression. Sequencing methods such as RNA and DNA sequencing have become indispensable tools in the pursuit to understand gene regulation. In recent years, the integration of single-cell sequencing techniques and CRISPR-based methods has ushered in a new era of genomic exploration, providing unprecedented opportunities to investigate the intricate interplay between genes, cellular processes, and disease progression. These cutting-edge advances have transformed the research landscape, enabling in-depth studies of gene regulation in single cells, and paving the way for future discoveries in both healthy and malignant tissues.

While cancer has traditionally been studied as a genetic disease, it is now evident that mutations alone do not determine cancer initiation or progression. This notion is supported by two key observations: first, cancer-driving mutations do not always lead to malignancy; and second, identical mutations can yield different outcomes depending on the cell type in which they occur. Consequently, a deeper understanding of gene regulation and the various ways it is modulated is critical for deciphering the complex relationship between genetic changes and cancer initiation.

In this thesis we aimed to develop novel single-cell methodologies applicable to studying biological complex systems. We have developed four techniques: CIM-seq, DNTR-seq, Smart3-ATAC, and ACTIseq, described in papers I-IV, respectively. The methods all capture additional modalities in combination with single-cell RNA-seq data, including spatial information, whole genome sequencing, accessible chromatin, and direct read out of guide RNAs. We applied these methods to investigate biological systems at the single-cell level, offering a more comprehensive understanding of cellular behavior in health and disease. Our approaches have allowed us to characterize stem cell niches and regeneration dynamics in the epithelial layer of the colon, and delve into the effects of gene dosage, quantifying how mutational changes impact transcriptional output. Furthermore, we have explored the complex landscape of gene regulation within pancreatic ductal adenocarcinomas, identifying mechanisms that enable cancer growth and proliferation.

This body of work emphasizes the importance of multimodal and integrative approaches for unraveling the complexities of biological systems at a cellular level. The methods we've developed represent a significant step forward, promising to facilitate the discovery of molecular targets for cancer therapeutics.

List of scientific papers

I. Nathanael Andrews*, Jason T. Serviss*, Natalie Geyer, Agneta B. Andersson, Ewa Dzwonkowska, Iva Šutevski, Rosan Heijboer, Ninib Baryawno, Marco Gerling, and Martin Enge. An Unsupervised Method for Physical Cell Interaction Profiling of Complex Tissues. Nat Methods. 18, 912–920 (2021). *These authors contributed equally.
https://doi.org/10.1038/s41592-021-01196-2

II. Vasilios Zachariadis, Huaitao Cheng, Nathanael Andrews, and Martin Enge. A Highly Scalable Method for Joint Whole-Genome Sequencing and Gene-Expression Profiling of Single Cells. Mol Cell. 80: 541-+ (2020).
https://doi.org/10.1016/j.molcel.2020.09.025

III. Huaitao Cheng, Han-pin Pui, Antonio Lentini, Solrún Kolbeinsdóttir, Nathanael Andrews, Yu Pei, Björn Reinius, Qiaolin Deng, and Martin Enge. Smart3-ATAC: a Highly Sensitive Method for Joint Accessibility and Full-Length Transcriptome Analysis in Single Cells. bioRxiv. (2021). [Manuscript]
https://doi.org/10.1101/2021.12.02.470912

IV. Nathanael Andrews, Huaitao Cheng, and Martin Enge. Simultaneous Sequencing of Full-Length RNA Transcripts, Accessible Chromatin, and Guide RNAs for Isoform-Sensitive CRISPR Perturbation Analysis. [Manuscript]