Archival single-cell genomics reveals persistent subclones during DCIS progression.

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.

Dissociation protocols used for sarcoma tissues bias the transcriptome observed in single-cell and single-nucleus RNA sequencing.

BACKGROUND: Single-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the methods used for tissue processing, cell disaggregation, and preservation can significantly bias gene expression and alter the observed cell types. To determine whether sarcomas - tumors of mesenchymal origin - are subject to the same technical artifacts, we profiled patient-derived tumor explants (PDXs) propagated from three aggressive subtypes: osteosarcoma (OS), Ewing sarcoma (ES), desmoplastic small round cell tumor (DSRCT). Given the rarity of these sarcoma subtypes, we explored whether single-nuclei RNA-seq from more widely available archival frozen specimens could accurately be identified by gene expression signatures linked to tissue phenotype or pathognomonic fusion proteins. RESULTS: We systematically assessed dissociation methods across different sarcoma subtypes. We compared gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from ES, DSRCT, and OS PDXs. We detected warm dissociation artifacts in single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of the dissociation method. In addition, we showed that dissociation method biases could be computationally corrected. CONCLUSIONS: We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.

Dimeric p53 Mutant Elicits Unique Tumor-Suppressive Activities through an Altered Metabolic Program.

Cancer-related alterations of the p53 tetramerization domain (TD) abrogate wild-type (WT) p53 function. They result in a protein that preferentially forms monomers or dimers, which are also normal p53 states under basal cellular conditions. However, their physiologic relevance is not well understood. We have established in vivo models for monomeric and dimeric p53, which model Li-Fraumeni syndrome patients with germline p53 TD alterations. p53 monomers are inactive forms of the protein. Unexpectedly, p53 dimers conferred some tumor suppression that is not mediated by canonical WT p53 activities. p53 dimers upregulate the PPAR pathway. These activities are associated with lower prevalence of thymic lymphomas and increased CD8+ T-cell differentiation. Lymphomas derived from dimeric p53 mice show cooperating alterations in the PPAR pathway, further implicating a role for these activities in tumor suppression. Our data reveal novel functions for p53 dimers and support the exploration of PPAR agonists as therapies. SIGNIFICANCE: New mouse models with TP53R342P (monomer) or TP53A347D (dimer) mutations mimic Li-Fraumeni syndrome. Although p53 monomers lack function, p53 dimers conferred noncanonical tumor-suppressive activities. We describe novel activities for p53 dimers facilitated by PPARs and propose these are "basal" p53 activities. See related commentary by Stieg et al., p. 1046. See related article by Choe et al., p. 1250. This article is highlighted in the In This Issue feature, p. 1027.

Reconstructing mutational lineages in breast cancer by multi-patient-targeted single-cell DNA sequencing.

Single-cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells; however, most genomic regions sequenced in single cells are non-informative. To overcome this issue, we developed a multi-patient-targeted (MPT) scDNA-seq method. MPT involves first performing bulk exome sequencing across a cohort of cancer patients to identify somatic mutations, which are then pooled together to develop a single custom targeted panel for high-throughput scDNA-seq using a microfluidics platform. We applied MPT to profile 330 mutations across 23,500 cells from 5 patients with triple negative-breast cancer (TNBC), which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From these data, we reconstructed mutational lineages and identified early mutational and copy-number events, including early TP53 mutations that occurred in all five patients. Collectively, our data suggest that MPT can overcome a major technical obstacle for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.

Targeting T cell checkpoints 41BB and LAG3 and myeloid cell CXCR1/CXCR2 results in antitumor immunity and durable response in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is considered non-immunogenic, with trials showing its recalcitrance to PD1 and CTLA4 immune checkpoint therapies (ICTs). Here, we sought to systematically characterize the mechanisms underlying de novo ICT resistance and to identify effective therapeutic options for PDAC. We report that agonist 41BB and antagonist LAG3 ICT alone and in combination, increased survival and antitumor immunity, characterized by modulating T cell subsets with antitumor activity, increased T cell clonality and diversification, decreased immunosuppressive myeloid cells and increased antigen presentation/decreased immunosuppressive capability of myeloid cells. Translational analyses confirmed the expression of 41BB and LAG3 in human PDAC. Since single and dual ICTs were not curative, T cell-activating ICTs were combined with a CXCR1/2 inhibitor targeting immunosuppressive myeloid cells. Triple therapy resulted in durable complete responses. Given similar profiles in human PDAC and the availability of these agents for clinical testing, our findings provide a testable hypothesis for this lethal disease.

Learning to distinguish progressive and non-progressive ductal carcinoma in situ.

Ductal carcinoma in situ (DCIS) is a non-invasive breast neoplasia that accounts for 25% of all screen-detected breast cancers diagnosed annually. Neoplastic cells in DCIS are confined to the ductal system of the breast, although they can escape and progress to invasive breast cancer in a subset of patients. A key concern of DCIS is overtreatment, as most patients screened for DCIS and in whom DCIS is diagnosed will not go on to exhibit symptoms or die of breast cancer, even if left untreated. However, differentiating low-risk, indolent DCIS from potentially progressive DCIS remains challenging. In this Review, we summarize our current knowledge of DCIS and explore open questions about the basic biology of DCIS, including those regarding how genomic events in neoplastic cells and the surrounding microenvironment contribute to the progression of DCIS to invasive breast cancer. Further, we discuss what information will be needed to prevent overtreatment of indolent DCIS lesions without compromising adequate treatment for high-risk patients.

Single-Cell Sequencing Reveals Trajectory of Tumor-Infiltrating Lymphocyte States in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) has few effective treatments. Immunotherapy, an attractive alternative strategy, remains challenging with the lack of knowledge on the tumor-infiltrating lymphocyte (TIL) landscape in PDAC. To generate a reference of T-cell subpopulations, we profiled 80,000 T cells from 57 PDAC samples, 22 uninvolved/normal samples, and cultured TIL using single-cell transcriptomic and T-cell receptor analysis. These data revealed 20 cell states and heterogeneous distributions of TIL populations. The CD8+ TIL contained a putative transitional GZMK+ population based on T-cell receptor clonotype sharing, and cell-state trajectory analysis showed similarity to a GZMB+PRF1+ cytotoxic and a CXCL13+ dysfunctional population. Statistical analysis suggested that certain TIL states, such as dysfunctional and inhibitory populations, often occurred together. Finally, analysis of cultured TIL revealed that high-frequency clones from effector populations were preferentially expanded. These data provide a framework for understanding the PDAC TIL landscape for future TIL use in immunotherapy for PDAC. SIGNIFICANCE: To improve the efficacy of immunotherapy in PDAC, there is a great need to understand the PDAC TIL landscape. This study represents a reference of PDAC TIL subpopulations and their relationships and provides a foundation upon which to base future immunotherapeutic efforts. This article is highlighted in the In This Issue feature, p. 2221.

A Decade's Experience in Pediatric Chromosomal Microarray Reveals Distinct Characteristics Across Ordering Specialties.

Chromosomal microarray (CMA) is a testing modality frequently used in pediatric patients; however, published data on its utilization are limited to the genetic setting. We performed a database search for all CMA testing performed from 2010 to 2020, and delineated the diagnostic yield based on patient characteristics, including sex, age, clinical specialty of providers, indication of testing, and pathogenic finding. The indications for testing were further categorized into Human Phenotype Ontology categories for analysis. This study included a cohort of 14,541 patients from 29 different medical specialties, of whom 30% were from the genetics clinic. The clinical indications for testing suggested that neonatology patients demonstrated the greatest involvement of multiorgan systems, involving the most Human Phenotype Ontology categories, compared with developmental behavioral pediatrics and neurology patients being the least. The top pathogenic findings for each specialty differed, likely due to the varying clinical features and indications for testing. Deletions involving the 22q11.21 locus were the top pathogenic findings for patients presenting to genetics, neonatology, cardiology, and surgery. Our data represent the largest pediatric cohort published to date. This study is the first to demonstrate the diagnostic utility of this assay for patients seen in the setting of different specialties, and it provides normative data of CMA results among a general pediatric population referred for testing because of variable clinical presentations.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer.

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

Spatial charting of single-cell transcriptomes in tissues.

Single-cell RNA sequencing methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics assays can profile spatial regions in tissue sections, but do not have single-cell resolution. Here, we developed a computational method called CellTrek that combines these two datasets to achieve single-cell spatial mapping through coembedding and metric learning approaches. We benchmarked CellTrek using simulation and in situ hybridization datasets, which demonstrated its accuracy and robustness. We then applied CellTrek to existing mouse brain and kidney datasets and showed that CellTrek can detect topological patterns of different cell types and cell states. We performed single-cell RNA sequencing and spatial transcriptomics experiments on two ductal carcinoma in situ tissues and applied CellTrek to identify tumor subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data show that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization.

Single-cell multimodal glioma analyses identify epigenetic regulators of cellular plasticity and environmental stress response.

Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to therapeutic resistance. We integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes and bulk multi-omic profiles across 11 adult IDH mutant or IDH wild-type gliomas to delineate sources of intratumoral heterogeneity. We showed that local DNA methylation disorder is associated with cell-cell DNA methylation differences, is elevated in more aggressive tumors, links with transcriptional disruption and is altered during the environmental stress response. Glioma cells under in vitro hypoxic and irradiation stress increased local DNA methylation disorder and shifted cell states. We identified a positive association between genetic and epigenetic instability that was supported in bulk longitudinally collected DNA methylation data. Increased DNA methylation disorder associated with accelerated disease progression and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work identified an epigenetically facilitated adaptive stress response process and highlights the importance of epigenetic heterogeneity in shaping therapeutic outcomes.

Simple oligonucleotide-based multiplexing of single-cell chromatin accessibility.

Microdroplet single-cell ATAC-seq is widely used to measure chromatin accessibility, however, highly scalable and simple sample multiplexing procedures are not available. Here, we present a transposome-assisted single nucleus barcoding approach for ATAC-seq (SNuBar-ATAC) that utilizes a single oligonucleotide adaptor for multiplexing samples during the existing tagmentation step and does not require a pre-labeling procedure. The accuracy and scalability of SNuBar-ATAC was evaluated using cell line mixture experiments. We applied SNuBar-ATAC to investigate treatment-induced chromatin accessibility dynamics by multiplexing 28 mice with lung tumors that received different combinations of chemo, radiation, and targeted immunotherapy. We also applied SNuBar-ATAC to study spatial epigenetic heterogeneity by multiplexing 32 regions from a human breast tissue. Additionally, we show that SNuBar can multiplex single cell ATAC and RNA multiomic assays in cell lines and human breast tissue samples. Our data show that SNuBar is a highly accurate, easy-to-use, and scalable system for multiplexing scATAC-seq and scATAC and RNA co-assay experiments.

Breast tumours maintain a reservoir of subclonal diversity during expansion.

Our knowledge of copy number evolution during the expansion of primary breast tumours is limited1,2. Here, to investigate this process, we developed a single-cell, single-molecule DNA-sequencing method and performed copy number analysis of 16,178 single cells from 8 human triple-negative breast cancers and 4 cell lines. The results show that breast tumours and cell lines comprise a large milieu of subclones (7-22) that are organized into a few (3-5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple loss-of-heterozygosity events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumour expansion. By subcloning single daughter cells in culture, we show that tumour cells rediversify their genomes and do not retain isogenic properties. These data show that triple-negative breast cancers continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumour growth.

Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes.

Single-cell transcriptomic analysis is widely used to study human tumors. However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5 Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.

Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing.

BACKGROUND: Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect. RESULTS: A molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2-5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance. CONCLUSIONS: This study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer.

Accumulation of long-chain fatty acids in the tumor microenvironment drives dysfunction in intrapancreatic CD8+ T cells.

CD8+ T cells are master effectors of antitumor immunity, and their presence at tumor sites correlates with favorable outcomes. However, metabolic constraints imposed by the tumor microenvironment (TME) can dampen their ability to control tumor progression. We describe lipid accumulation in the TME areas of pancreatic ductal adenocarcinoma (PDA) populated by CD8+ T cells infiltrating both murine and human tumors. In this lipid-rich but otherwise nutrient-poor TME, access to using lipid metabolism becomes particularly valuable for sustaining cell functions. Here, we found that intrapancreatic CD8+ T cells progressively accumulate specific long-chain fatty acids (LCFAs), which, rather than provide a fuel source, impair their mitochondrial function and trigger major transcriptional reprogramming of pathways involved in lipid metabolism, with the subsequent reduction of fatty acid catabolism. In particular, intrapancreatic CD8+ T cells specifically exhibit down-regulation of the very-long-chain acyl-CoA dehydrogenase (VLCAD) enzyme, which exacerbates accumulation of LCFAs and very-long-chain fatty acids (VLCFAs) that mediate lipotoxicity. Metabolic reprogramming of tumor-specific T cells through enforced expression of ACADVL enabled enhanced intratumoral T cell survival and persistence in an engineered mouse model of PDA, overcoming one of the major hurdles to immunotherapy for PDA.

Single-Cell Circulating Tumor Cell Analysis Reveals Genomic Instability as a Distinctive Feature of Aggressive Prostate Cancer.

PURPOSE: Aggressive variant prostate cancer (AVPC) represents a clinical subset distinguished by therapy resistance and poor prognosis, linked to combined losses of the tumor suppressor genes (TSG) PTEN, RB1, and TP53. Circulating tumor cells (CTC) provide a minimally invasive opportunity for identification and molecular characterization of AVPC. We aimed to evaluate the incidence and clinical significance of compound (2+)TSG losses and genomic instability in prostate cancer CTC, and to expand the set genomic biomarkers relevant to AVPC. EXPERIMENTAL DESIGN: Genomic analysis of chromosomal copy-number alterations (CNA) at single-cell resolution was performed in CTC from patients with and without AVPC before initiating chemotherapy with cabazitaxel or cabazitaxel and carboplatin. We evaluated associations between single-CTC genomics and clinical features, progression-free survival, and overall survival. RESULTS: A total of 257 individual CTC were sequenced from 47 patients (1-22 CTC/patient). Twenty patients (42.6%) had concurrent 2+TSG losses in at least one CTC in association with poor survival and increased genomic instability, inferred by high large-scale transitions scores. Higher LST in CTC were independent of CTC enumerated, clinically more indicative of aggressive behavior than co-occurring TSG losses, and molecularly associated with gains in chromosomal regions including PTK2, Myc, and NCOA2; increased androgen receptor expression; and BRCA2 loss. In 57 patients with matched cell-free tumor DNA data, CTC were more frequently detectable and evaluable for CNA analysis (in 73.7% vs. 42.1%, respectively). CONCLUSIONS: Our findings suggest that genomic instability in CTC is a hallmark of advanced prostate cancer aggressiveness, and support single-CTC sequencing as a compelling tool to noninvasively characterize cancer heterogeneity.

SCOPIT: sample size calculations for single-cell sequencing experiments.

BACKGROUND: In single cell DNA and RNA sequencing experiments, the number of cells to sequence must be decided before running an experiment, and afterwards, it is necessary to decide whether sufficient cells were sampled. These questions can be addressed by calculating the probability of sampling at least a defined number of cells from each subpopulation (cell type or cancer clone). RESULTS: We developed an interactive web application called SCOPIT (Single-Cell One-sided Probability Interactive Tool), which calculates the required probabilities using a multinomial distribution (www.navinlab.com/SCOPIT). In addition, we created an R package called pmultinom for scripting these calculations. CONCLUSIONS: Our tool for fast multinomial calculations provide a simple and intuitive procedure for prospectively planning single-cell experiments or retrospectively evaluating if sufficient numbers of cells have been sequenced. The web application can be accessed at navinlab.com/SCOPIT.

Somatic Trp53 mutations differentially drive breast cancer and evolution of metastases.

TP53 mutations are the most frequent genetic alterations in breast cancer and are associated with more aggressive disease and worse overall survival. We have created two conditional mutant Trp53 alleles in the mouse that allow expression of Trp53R172H or Trp53R245W missense mutations in single cells surrounded by a normal stroma and immune system. Mice with Trp53 mutations in a few breast epithelial cells develop breast cancers with high similarity to human breast cancer including triple negative. p53R245W tumors are the most aggressive and exhibit metastases to lung and liver. Development of p53R172H breast tumors with some metastases requires additional hits. Sequencing of primary tumors and metastases shows p53R245W drives a parallel evolutionary pattern of metastases. These in vivo models most closely simulate the genesis of human breast cancer and will thus be invaluable in testing novel therapeutic options.