LKB1 inactivation modulates chromatin accessibility to drive metastatic progression.
Nature cell biology
Metastasis is the leading cause of cancer-related deaths and enables cancer cells to compromise organ function by expanding in secondary sites. Since primary tumours and metastases often share the same constellation of driver mutations, the mechanisms that drive their distinct phenotypes are unclear. Here we show that inactivation of the frequently mutated tumour suppressor gene LKB1 (encoding liver kinase B1) has evolving effects throughout the progression of lung cancer, which leads to the differential epigenetic re-programming of early-stage primary tumours compared with late-stage metastases. By integrating genome-scale CRISPR-Cas9 screening with bulk and single-cell multi-omic analyses, we unexpectedly identify LKB1 as a master regulator of chromatin accessibility in lung adenocarcinoma primary tumours. Using an in vivo model of metastatic progression, we further show that loss of LKB1 activates the early endoderm transcription factor SOX17 in metastases and a metastatic-like sub-population of cancer cells within primary tumours. The expression of SOX17 is necessary and sufficient to drive a second wave of epigenetic changes in LKB1-deficient cells that enhances metastatic ability. Overall, our study demonstrates how the downstream effects of an individual driver mutation can change throughout cancer development, with implications for stage-specific therapeutic resistance mechanisms and the gene regulatory underpinnings of metastatic evolution.
View details for DOI 10.1038/s41556-021-00728-4
View details for PubMedID 34341533
ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis.
The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/ ) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells.
View details for DOI 10.1038/s41588-021-00790-6
View details for PubMedID 33633365
Finding needles in a haystack: dissecting tumor heterogeneity with single-cell transcriptomic and chromatin accessibility profiling.
Current opinion in genetics & development
2021; 66: 36–40
Tumor evolution often results in a wealth of heterogeneous cancer cell types within a single tumor - heterogeneity that can include epigenetic and gene expression changes that are impossible to identify from histological features alone. The invasion of cancer cells into nearby healthy tissue, accompanied by the infiltration of responding immune cells, results in an even more complex architecture of tumor and non-tumor cells. However, bulk genomics-based methods can only assay the aggregate transcriptomic and epigenetic profiles across all of this rich cellular diversity. Such bulk averaging hides small subpopulations of tumor cells with unique phenotypes that might result in therapeutic resistance or metastatic progression. The advent of single-cell-based genomics assays for measuring transcription and chromatin accessibility - particularly scRNA-seq and scATAC-seq - has enabled the dissection of cell-types within tumors at a scale and resolution capable of unraveling the epigenetic and gene expression programs of rare and unique cellular subpopulations. This Review focuses on recent advances in scRNA-seq and scATAC-seq technologies and their application to cancer biology in the context of furthering our understanding of tumor heterogeneity.
View details for DOI 10.1016/j.gde.2020.11.008
View details for PubMedID 33418426
High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer.
2021; 12 (1): 2969
Chromatin accessibility profiling can identify putative regulatory regions genome wide; however, pooled single-cell methods for assessing the effects of regulatory perturbations on accessibility are limited. Here, we report a modified droplet-based single-cell ATAC-seq protocol for perturbing and evaluating dynamic single-cell epigenetic states. This method (Spear-ATAC) enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at once. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations reveals the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles.
View details for DOI 10.1038/s41467-021-23213-w
View details for PubMedID 34016988
Zmat3 Is a Key Splicing Regulator in the p53 Tumor Suppression Program.
2020; 80 (3): 452
Although TP53 is the most commonly mutated gene in human cancers, the p53-dependent transcriptional programs mediating tumor suppression remain incompletely understood. Here, to uncover critical components downstream of p53 in tumor suppression, we perform unbiased RNAi and CRISPR-Cas9-based genetic screens invivo. These screens converge upon the p53-inducible gene Zmat3, encoding an RNA-binding protein, and we demonstrate that ZMAT3 is an important tumor suppressor downstream of p53 in mouse KrasG12D-driven lung and liver cancers and human carcinomas. Integrative analysis of the ZMAT3 RNA-binding landscape and transcriptomic profiling reveals that ZMAT3 directly modulates exon inclusion in transcripts encoding proteins of diverse functions, including the p53 inhibitors MDM4 and MDM2, splicing regulators, and components of varied cellular processes. Interestingly, these exons are enriched in NMD signals, and, accordingly, ZMAT3 broadly affects target transcript stability. Collectively, these studies reveal ZMAT3 as a novel RNA-splicing and homeostasis regulator and a key component of p53-mediated tumor suppression.
View details for DOI 10.1016/j.molcel.2020.10.022
View details for PubMedID 33157015
CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities.
2020; 580 (7801): 136–41
Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.
View details for DOI 10.1038/s41586-020-2099-x
View details for PubMedID 32238925
Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion.
2019; 37 (8): 925–36
Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here, we assess the performance of a massively parallel droplet-based method for mapping transposase-accessible chromatin in single cells using sequencing (scATAC-seq). We apply scATAC-seq to obtain chromatin profiles of more than 200,000 single cells in human blood and basal cell carcinoma. In blood, application of scATAC-seq enables marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping of disease-associated enhancer activity and reconstruction of trajectories of cellular differentiation. In basal cell carcinoma, application of scATAC-seq reveals regulatory networks in malignant, stromal and immune cells in the tumor microenvironment. Analysis of scATAC-seq profiles from serial tumor biopsies before and after programmed cell death protein 1 blockade identifies chromatin regulators of therapy-responsive T cell subsets and reveals a shared regulatory program that governs intratumoral CD8+ T cell exhaustion and CD4+ T follicular helper cell development. We anticipate that scATAC-seq will enable the unbiased discovery of gene regulatory factors across diverse biological systems.
View details for DOI 10.1038/s41587-019-0206-z
View details for PubMedID 31375813