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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

Supplementary Table from Single-Cell Sequencing Reveals Trajectory of Tumor-Infiltrating Lymphocyte States in Pancreatic Cancer

Supplementary Figure from Single-Cell Sequencing Reveals Trajectory of Tumor-Infiltrating Lymphocyte States in Pancreatic Cancer

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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.

Pancreatic ductal adenocarcinoma (PDAC) is considered ‘non-immunogenic’ with trials demonstrating its recalcitrance to PD1 and CTLA4 immune checkpoint therapies (ICTs). Here, we sought to systematically characterize the mechanisms underlying de novo ICT resistance and identify effective therapeutic options for PDAC. We report that agonist 41BB and antagonist LAG3 ICT alone and in combination, increased survival and anti-tumor immunity, characterized by modulating T cell subsets with anti-tumor 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 presence 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 availability of these agents for clinical testing, our findings provide a testable hypothesis for this lethal disease.

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

Ductal-carcinoma-in-situ (DCIS) is the most common early-stage breast cancer and a non-obligate precursor to invasive breast cancer. However our understanding of the spatial microenvironment and the reprogramming of cell types in DCIS remains limited. To address this question, we developed a Spatial Nucleus Barcoding (SNuBar) method that utilizes a single oligonucleotide adaptor to preserve spatial information followed by performing single nucleus RNA sequencing. We validated the accuracy and scalability of SNuBar in cell lines and applied this method to investigate the spatial microenvironment of 4 normal breast tissues, 7 normal adjacent DCIS tissues, and 8 DCIS cancers. The analysis of single cells isolated from 596 macrodissected spatial regions identified 13 major cell types and 43 cell states, that co-localized in different combinations across four main topographic areas. Spatial analysis revealed that vascular and myoepithelial cells were reprogrammed in localized zones near the premalignant cells, while fibroblasts, T-cells and myeloid cells were reprogrammed across broader fields. Our data shows that many diverse cell types are reprogrammed in spatially-defined areas in the DCIS microenvironment, relative to the normal breast tissue regions. Citation Format: Kaile Wang, Zhenna Xiao, Yiyun Lin, Runmin Wei, Jie Ye, Rui Ye, Min Hu, Shanshan Bai, Emi Sei, Aatish Thennavan, Bora Lim, Andrew Futreal, Alastair Thompson, Savitri Krishnamurthy, Nicholas Navin. Reprogramming of the preinvasive breast microenvironment identified by spatial nucleus barcoding [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 76.

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer (IBC), yet the genomic progression to recurrent disease remains poorly understood. A main contributor to this gap in knowledge arises from technical challenges with genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. To address this challenge, we developed Arc-well, the first high-throughput method that can perform single cell DNA sequencing of thousands of cells from FFPE materials and frozen tissues. Using Arc-well, we profiled genomic copy number in 27,851 single cells from 26 archival FFPE tissues that were stored for 3-31 years. Analysis of genomic evolution in 10 patients with matched DCIS and recurrent cancers (DCIS or IBC) separated by 2-16 years showed that many primary DCIS lesions had already undergone whole-genome-doubling and had extensive clonal diversity, similar to the paired recurrence. The data from most patients (8/10) suggest an evolutionary bottleneck model of progression, in which a single subclone persisted during the progression to the recurrent disease, revealing copy number aberrations associated with invasion and recurrence. Citation Format: Kaile Wang, Tapsi Kumar, Junke wang, Darlan Minussi, Emi Sei, Jianzhuo li, Tuan Tran, Aatish Thennavan, Min Hu, Anna Casasent, Zhenna Xiao, Shanshan Bai, Yuehui Zhao, Amado Zurita, Ana Aparicio, Brian Chapin, Jie ye, Jianjun Zhang, Don Gibbons, Andrew Futreal, Lorraine King, Jeffrey Marks, E. Shelley Hwang, Vandna Shah, Ellinor Sawyer, Petra Kristel, Jelle Wesseling, Esther H. Lips, Nicholas Navin. Archival single cell sequencing reveals persistent subclones over years to decades of DCIS progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 125.

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. Single-cell analysis of genomes from primary human breast tumours and cell lines shows that chromosomal aberrations continue to evolve during primary tumour expansion, resulting in a milieu of subclones within the tumour.

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. Clonal subpopulations in human tumors are identified from single-cell RNA-seq data.

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.

High-throughput methods for single cell copy number sequencing have enabled the profiling of thousands of cells in parallel, yet there remains a significant bottleneck for data analysis. Here we present CopyKit, a comprehensive set of computational methods for the pre-processing and analysis of single cell copy number data to resolve clonal substructure and reconstruct genetic lineages in tumors. We performed single cell DNA sequencing of 2977 cells from multiple spatial regions in two liver metastasis and 7365 cells from three primary tumors with matched metastatic tissues. In the liver metastases, CopyKit resolved clonal substructure in different spatial regions, which revealed both clonal intermixing and spatial segregation in the tumor mass. In the matched metastatic colorectal and breast cancers, CopyKit resolved metastatic lineages and identified subclones and genomic events that were associated with metastases. These applications show that CopyKit is comprehensive tool for resolving copy number substructure in tumors.

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called CellTrek that combines these two datasets to achieve single cell spatial mapping. We benchmarked CellTrek using a simulation study and two in situ datasets. We then applied CellTrek to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) 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 shows that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization.

Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells, however most genomic regions characterized in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq sequencing 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 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this 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 suggests that MPT can overcome technical obstacles for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites.

Ductal carcinoma in situ (DCIS) is early-stage non-malignant breast cancer that tumor cells are confined to the lumens of ducts. Over 50,000 DCIS patients are diagnosed each year in the United States, however, less than half of DCIS will develop into invasive breast cancer (IBC), suggesting a risk of overtreatment for some DCIS patients. A comprehensive investigation of the molecular mechanisms of DCIS initiation and progression is urgently needed that can facilitate us stratifying the risk of DCIS invasion and design better intervention approaches. In this study, we conducted single-cell RNA-seq and spatial transcriptomics (ST) on DCIS and IBC samples (most estrogen receptor positive). We first inferred copy number aberrations (CNA) in these samples and found that DCIS and IBC shared the most copy number events while only marginal differences were identified. Tumor CNA subclones colocalized in different ductal regions from the ST data. Further, we applied a sample-wise non-negative matrix factorization (NMF) to identify robust gene expression metaprograms across tumor samples. On the ST data, we found these metaprograms also displayed distinct spatial patterns. For non-tumor cells in the TME, we sub-clustering them into cell states and identified that some cell states showed a gradual change along breast cancer initiation and progression. To recapitulate the tumor ecosystems, we also conducted an ecotype analysis in DCIS samples and identified that some ecotypes showed an increasing/decreasing trend in IBC patients. Further, tumor and TME ecotypes also showed spatially colocalizations based on our ST data. In summary, these results demonstrated that genomic signatures could hardly predict the DCIS progression while tumor metaprograms and TME ecotypes might serve as a potential risk stratification approach for DCIS patients. Citation Format: Runmin Wei, Siyuan He, Shanshan Bai, Emi Sei, Min Hu, Chandandeep Nagi, Brian Menegaz, Huma Javaid, Jelle Wesseling, Andrew Futreal, Alastair Thompson, Savitri Krishnamurthy, Nicholas Navin. A single-cell and spatial investigation of tumor and TME for DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA013.

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.

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.

Summary Background Taxane–platinum combinations have shown promising activity in metastatic castration-resistant prostate cancers in single-group clinical studies but not in randomised trials. Distinct biological subsets of the disease might derive the greatest benefit from the addition of platinum. We aimed to determine whether adding carboplatin to cabazitaxel would improve the outcomes of men with metastatic castration-resistant prostate cancer. Methods We did a phase 1–2, open label, randomised study at two centres in men with progressive metastatic castration-resistant prostate cancer. In phase 1, patients received intravenous cabazitaxel 20–25 mg/m2 and intravenous carboplatin area under the curve (AUC) 3–4 mg/mL per min every 21 days. The maximum tolerated dose was defined as the highest dose cohort studied in which one of six or fewer patients experienced a dose-limiting toxicity. In phase 2, patients were randomly assigned (1:1) centrally by a computerised algorithm to intravenous cabazitaxel 25 mg/m2 with or without intravenous carboplatin AUC 4 mg/mL per min. All patients received growth factor support and oral prednisone 10 mg daily. The primary endpoints were the maximum tolerated dose of the combination in phase 1 and investigator-assessed progression-free survival in phase 2. This trial is registered at ClinicalTrials.gov , number NCT01505868 . Findings Between Aug 17, 2012, and May 11, 2015, nine patients completed phase 1 as planned, and 160 were randomly assigned to cabazitaxel (n=79) or cabazitaxel plus carboplatin (n=81) in phase 2. During phase I, grade 3 adverse events were anaemia (n=2), fatigue (n=1), thrombocytopenia (n=1), hypomagnesaemia (n=1), diarrhoea (n=1), hypokalaemia (n=1), anorexia (n=1), and dehydration (n=1), and no grade 4 adverse events occurred. No dose-limiting toxicities were observed, therefore, a maximum tolerated dose of cabazitaxel of 25 mg/m2 and carboplatin of AUC 4 mg/mL per min was selected for phase 2. At a median follow-up of 31·0 months (IQR 20·5–37·1), the combination improved the median progression-free survival from 4·5 months (95% CI 3·5–5·7) to 7·3 months (95% CI 5·5–8·2; hazard ratio 0·69, 95% CI 0·50–0·95, p=0·018). In the phase 2 study, the most common grade 3–5 adverse events were fatigue (7 [9%] of 79 in the cabazitaxel group vs 16 [20%] of 81 in the combination group), anaemia (3 [4%] vs 19 [23%]), neutropenia (3 [4%] vs 13 [16%]), and thrombocytopenia (1 [1%] vs 11 [14%]). There were no treatment-related deaths. Interpretation Carboplatin added to cabazitaxel showed improved clinical efficacy compared with cabazitaxel alone for men with metastatic castration-resistant prostate cancer. Although adverse events were more common with the combination, the treatment was safe and generally well tolerated. Our data suggest that taxane–platinum combinations have a clinically beneficial role in advanced prostate cancer and a randomised phase 3 study is planned. Funding Sanofi Genzyme, University of Texas MD Anderson Cancer Center Prostate Cancer Moon Shot Program, Solon Scott III Prostate Cancer Research Fund, National Institutes of Health, and National Cancer Institute.

Intra-tumor heterogeneity (ITH) of human tumors is important for tumor progression, treatment response, and drug resistance. However, the spatial distribution of ITH remains incompletely understood. Here, we present spatial analysis of ITH in lung adenocarcinomas from 147 patients using multi-region mass spectrometry of5,000 regions, single-cell copy number sequencing of ~2,000 single cells, and cyclic immunofluorescence of10 million cells. We identified two distinct spatial patterns among tumors, termed clustered and random geographic diversification (GD). These patterns were observed in the same samples using both proteomic and genomic data. The random proteomic GD pattern, which is characterized by decreased cell adhesion and lower levels of tumor-interacting endothelial cells, was significantly associated with increased risk of recurrence or death in two independent patient cohorts. Our study presents comprehensive spatial mapping of ITH in lung adenocarcinoma and provides insights into the mechanisms and clinical consequences of GD.

Pure ductal carcinoma in situ (DCIS) is being diagnosed more frequently through breast screening programmes and is associated with an increased risk of developing invasive breast cancer. We assessed the clonal relatedness of 143 cases of pure DCIS and their subsequent events using a combination of whole exome, targeted and copy number sequencing, supplemented by single cell analysis. Unexpectedly, 18% of all invasive events after DCIS were clonally unrelated to the primary DCIS. Single cell sequencing of selected pairs confirmed our findings. In contrast, synchronous DCIS and invasive disease (n=44) were almost always (93%) clonally related. This challenges the dogma that almost all invasive events after DCIS represent invasive transformation of the initial DCIS and suggests that DCIS could be an independent risk factor for developing invasive disease as well as a precursor lesion. Our findings support a paradigm shift that confirms a more complex role for DCIS than previously recognized, and that the future management of DCIS should take into account both the precursor and risk factor implications of this diagnosis.

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal tumor-type with very few effective treatment strategies. Attempts to improve outcomes using immune checkpoint blockade therapy have also failed, likely because the overall Tcell infiltration in this tumor-type is low. Despite this, the presence of CD3+CD8+ tumor-infiltrating lymphocytes (TIL) in PDAC is associated with improved survival outcomes, suggesting that other immune-based strategies could be more successful. Here, we examine ex vivo tumor-infiltrating Tcell expansion for adoptive Tcell therapy (ACT) as a potential strategy for treating PDAC. The focus of this study is to understand the transcriptional states of Tcells in the pancreas and PDACs and how they change with ex vivo expansion and re-infusion into patients as treatment strategy. We have performed both single cell transcriptome and TCR sequencing (scRNA-TCRseq) on 54,579 Tcells from 8 human PDAC samples and the ex vivo grown TIL from a subset of 6 patients and found 13 purported substates. Through TCR tracking of the Tcell clonotypes, we find that the expansion protocol is able to expand Tcells found in many different Tcell states in the primary tumor. Furthermore, we compared our thirteen tumor-infiltrating substates with 41,935 Tcells from two other independent single cell studies across 71 samples, and confirmed our substates to be present across all datasets. Citation Format: Aislyn Schalck, Donastas Sakellariou-Thompson, Marie-Andrée Forget, Emi Sei, Tara Hughes, Shanshan Bai, Min Hu, Tapsi Kumar, Mark Hurd, Matthew Katz, Chine-Wei Tzeng, Shubham Pant, Milind Javle, Anirban Maitra, Cara Haymaker, Michael Kim, Nicholas Navin, Chantale Bernatchez. Simultaneous TCR and transcriptomic sequencing of single Tcells defines biological subtypes in pancreatic cancer for adoptive Tcell therapy [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 2847.

Advances in single cell copy number sequencing technologies have enabled the generation of data on hundreds to thousands of cells in parallel. Despite the rapid development in these technologies, there is a significant bottleneck for the analysis of the resulting large-scale datasets. Here we present CopyKit, a comprehensive and user-friendly toolkit for the analysis of single cell copy number data. CopyKit provides a suite of tools for pre-processing, QC, copy number inference, and subclone clustering to delineate the clonal diversity of tumors. We performed single cell copy number sequencing of 2977 cells from two breast tumor liver metastasis. CopyKit identified 4 and 12 subclonal populations, including amplification of PDGFRA, KRAS, and MYC as well as losses of PTEN, FOXO1, RB1, and BRCA1, many of which were spatially segregated in the tumor mass of the two tumors. Additionally, we applied CopyKit to study metastatic dissemination from a primary ER+ breast tumor with two matched metastatic sites and two colorectal carcinomas with matched liver metastatic tissues. This analysis demonstrated that the breast metastatic tumors selected for subclones that were lacking ERBB2 amplification in the primary site. Furthermore, the liver metastasis had deletions of chromosomes 18, 19, and 20p and a focal gain of FGFR1, while the pleural effusion acquired two additional focal gains on chromosome 8, including MYC. The colorectal metastatic tumors diverged from the primary tumor with copy number events affecting important cancer genes such as gain of SOX4, MYC, CDK8 and deletions of FHIT, CHEK1, and CHEK2. Collectively, this study shows that CopyKit provides a comprehensive set of tools for resolving clonal substructure from single cell copy number data for diverse applications in cancer biology. Citation Format: Darlan Conterno Minussi, Junke Wang, Aislyn Schalck, Yun Yan, Hua-Jun Wu, Cheng Peng, Min Hu, Emi Sei, Mary Edgerton, Hui Chen, Alejandro Contreras, David Hui, Senthil Damodaran, Scott Kopetz, Bora Lim, Nicholas Navin. Resolving clonal substructure from single cell genomic data in primary and metastatic tumors using CopyKit [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 1210.

Prostate cancer is the most commonly diagnosed cancer among men and a major cause of cancer-related deaths in the modern world. Metastatic castration-resistant prostate cancer (mCRPC) is the most lethal form and has complex and heterogeneous genomic patterns. Despite the recent development of life-prolonging therapies, mCRPC remains incurable since most patients develop resistance over time. A better understanding of the evolution of resistance to therapy in mCRPC is urgently needed. A major logistical challenge is that collecting serial tissue biopsies from the prostate and metastatic sites such as bone is not feasible. To overcome this issue, we developed a minimally invasive liquid biopsy approach to study the genomic basis of resistance through circulating tumor DNA (ctDNA) from longitudinally collected plasma samples. To best account for interpatient tumor heterogeneity and treatment history, we selected 60 mCRPC patients who were serially treated with life-prolonging second generation androgen signaling inhibitors (abiraterone, enzalutamide, or the combination) and taxane-based chemotherapy, and prospectively collected longitudinal blood samples (2 to 10 per patient). ctDNA was isolated from each blood plasma sample for sparse whole-genome sequencing and exome sequencing at 200x coverage depth. Somatic copy number alterations (CNA) and exome mutations were profiled and the resulting data was used to reconstruct the clonal substructure and infer clonal evolutionary dynamics across the treatment timepoints. The mutation signatures and the CNA signatures were also characterized. One of the CNA signatures identified the patients who carry CDK12 mutations through genome-wide focal tandem duplications in ctDNA. The subclones resistant to second-generation androgen signaling inhibitors and taxane-based chemotherapy were also identified, along with their associated genomic aberrations affecting AR, RB1, and PTEN. Furthermore, by analyzing the evolutionary dynamics patterns, we identified three distinct genomic responses to therapy: intrinsic resistance, clonal progression, and clonal responders, which correlated with overall survival outcomes. In summary, our data show that clonal evolutionary dynamics in mCRPC can be tracked over time and in response to treatment with minimally invasive liquid biopsy methods. Our results provide insights into the genomic evolution of life-prolonging therapy resistance in mCRPC and identified candidate resistance biomarkers for subsequent validation. Citation Format: Yuehui Zhao, Naveen Ramesh, Emi Sei, Min Hu, Shanshan Bai, Patricia Troncoso, Paul Corn, Ana Aparicio, Christopher J. Logothetis, Nicholas E. Navin, Amado J. Zurita. Investigating longitudinal therapeutic resistance in serially treated metastatic castration resistant prostate cancer by liquid biopsy genome sequencing [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 3791.

Single cell DNA sequencing (scDNA-seq) methods are powerful tools for profiling mutations in cancer cells, however most genomic regions characterized in single cells are non-informative. To overcome this issue, we developed a Multi-Patient-Targeted (MPT) scDNA-seq sequencing 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 TNBC patients, which showed that 3 tumors were monoclonal and 2 tumors were polyclonal. From this 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 suggests that MPT can overcome technical obstacles for studying tumor evolution using scDNA-seq by profiling information-rich mutation sites. Citation Format: Jake Leighton, Min Hu, Emi Sei, Funda Meric-Bernstam, Nicholas Navin. Reconstructing mutational lineages in breast cancer by multi-patient-targeted single cell DNA sequencing [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 6088.

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections but do not have single cell genomic resolution. To address this issue, computational approaches (e.g., cell2location, RCTD) have been designed to deconvolute ST spots into proportions of different cell types. However, the spatial deconvolution method has the following limitations, 1) it can only infer cell type proportions of each spot and cannot reach higher granular "cell states" mapping; 2) it only predict categorical labels and cannot infer continuous cell information (e.g., lineage trajectories, gene signatures, continuous phenotypes) at a spatial resolution. Here, we developed a computational approach called CellTrek that combines these two datasets to achieve single cell spatial mapping. Using a machine learning-based metric learning approach, CellTrek learned a cell-spot graph and then transfer spatial coordinates to cells. The CellTrek toolkit also provides two downstream analysis modules, including SColoc for spatial colocalization analysis and SCoexp for spatial co-expression analysis. We benchmarked CellTrek using a simulation and two in situ datasets. We then applied CellTrek to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied CellTrek to identify subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization into cellular neighborhoods and tissue structures. This method provides a new paradigm that is distinct from ST deconvolution, enabling a more flexible and direct investigation of single cell data with spatial topography. Citation Format: Runmin Wei, Siyuan He, Shanshan Bai, Emi Sei, Min Hu, Alastair Thompson, Ken Chen, Savitri Krishnamurthy, Nicholas Navin. Spatial charting of single cell transcriptomes in tissues [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 2129.

Chemoradiation (CRT) is widely used to treat locally advanced non-small cell lung cancer (NSCLC) patients, but only around 30% of patients achieve pathological complete response. Here, we utilized an in vitro high-content clonogenic survival screening method to identify CRT sensitizers from the NCI Cancer Therapy Evaluation Program (CTEP) portfolio. Talazoparib (PARPi) was identified among the top candidates to show potent CRT sensitization effects in both KRAS mutant and TP53 mutant NCSLC cell lines. We validated the CRT sensitization effect of PARPi on lung tumors in vivo with cell line xenografts mouse models. To further investigate alterations in the tumor microenvironment (TME) induced by PARPi, we utilized syngeneic mouse models and showed that the combination of radiotherapy, PARPi, and PD-L1 blockade achieved superior tumor control effects. By applying single cell RNA sequencing technologies to the mouse tumors, we found that PARPi combined with CRT or immunotherapy significantly reprogrammed the tumor cells and TME, resulting in the increase of tumor-infiltrating T cells which elicit potent tumor control effects. Our data showed that PARPi sensitizes NSCLC tumors to CRT and immunotherapy through a combination of tumor-intrinsic and extrinsic phenomenon. Citation Format: Rui Ye, Kaile Wang, Yawei Qiao, Zhenna Xiao, Yun Yan, Jianzhong He, Nan Li, Yifan Wang, Min Hu, Shanshan Bai, Emi Sei, Nicholas Navin, Steven Lin. Chemoradiation sensitization effect of PARPi in non-small cell lung cancer [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 3308.

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.

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.

Metastasis is a complex biological process that has been difficult to delineate in human colorectal cancer (CRC) patients. A major obstacle in understanding metastatic lineages is the extensive intra-tumor heterogeneity at the primary and metastatic tumor sites. To address this problem, we developed a highly multiplexed single-cell DNA sequencing approach to trace the metastatic lineages of two CRC patients with matched liver metastases. Single-cell copy number or mutational profiling was performed, in addition to bulk exome and targeted deep-sequencing. In the first patient, we observed monoclonal seeding, in which a single clone evolved a large number of mutations prior to migrating to the liver to establish the metastatic tumor. In the second patient, we observed polyclonal seeding, in which two independent clones seeded the metastatic liver tumor after having diverged at different time points from the primary tumor lineage. The single-cell data also revealed an unexpected independent tumor lineage that did not metastasize, and early progenitor clones with the “first hit” mutation in APC that subsequently gave rise to both the primary and metastatic tumors. Collectively, these data reveal a late-dissemination model of metastasis in two CRC patients and provide an unprecedented view of metastasis at single-cell genomic resolution.

Single-cell DNA sequencing methods are challenged by poor physical coverage, high technical error rates and low throughput. To address these issues, we developed a single-cell DNA sequencing protocol that combines flow-sorting of single nuclei, time-limited multiple-displacement amplification (MDA), low-input library preparation, DNA barcoding, targeted capture and next-generation sequencing (NGS). This approach represents a major improvement over our previous single nucleus sequencing (SNS) Nature Protocols paper in terms of generating higher-coverage data (>90%), thereby enabling the detection of genome-wide variants in single mammalian cells at base-pair resolution. Furthermore, by pooling 48–96 single-cell libraries together for targeted capture, this approach can be used to sequence many single-cell libraries in parallel in a single reaction. This protocol greatly reduces the cost of single-cell DNA sequencing, and it can be completed in 5–6 d by advanced users. This single-cell DNA sequencing protocol has broad applications for studying rare cells and complex populations in diverse fields of biological research and medicine.

Our knowledge of copy number evolution during the expansion of primary breast tumors is limited. To investigate this process, we developed a single-cell, single-molecule DNA sequencing method and performed copy number analysis of 13,808 single cells from six triple-negative breast cancers (TNBCs) and two breast cancer cell lines. Our data shows that breast tumors and cell lines are comprised of a large milieu (17-26) of subclones that are organized into a few (4-8) major superclones. Phylogenetic analysis and mathematical modeling show that copy number evolution was ongoing during the expansion of the primary tumor, after the initial punctuated burst of genomic instability. By expanding single daughter cells in culture, we show that cancer cells re-diversify their genomes and do not retain isogenic properties. These data elucidate modes of evolution and show that TNBCs maintain a vast reservoir of subclonal copy number diversity during the expansion of the primary tumor mass. Citation Format: Darlan Conterno Minussi, Michael Nicholson, Hanghui Ye, Alexander Davis, Kaile Wang, Emi Sei, Haowei Du, Mashiat Rabbani, Cheng Peng, Min Hu, Shanshan Bai, Thomas McDonald, Aislyn Schalck, Anna Casasent, Angelica Barrera, Hui Chen, Bora Lim, Banu Arun, Funda Meric-Bernstam, Franziska Michor, Nicholas Navin. Breast tumors maintain a reservoir of subclonal diversity during primary expansion [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-133.

High-throughput single cell transcriptomics analysis is widely used to study human tumors, however a major challenge is distinguishing the stromal cells from the malignant cancer cells, as well as clonal substructure within tumors. To address this challenge, we developed an integrative Bayesian segmentation approach, COPYKAT to estimate genomic copy numbers at 5MB resolution from high-throughput single cell RNA-seq data. We applied COPYKAT to 39,709 single cells from 16 tumors across 4 cancer types, including premalignant and triple-negative breast cancers, pancreatic ductal adenocarcinomas, and anaplastic thyroid cancer. From these data we could accurately (98%) classify tumor cells from stromal cells. In three TNBC tumors COPYKAT resolved multiple clonal subpopulations of genotypes that differed in expression of breast cancer genes and enrichment of cancer hallmarks including EMT and hypoxia. These data show that COPYKAT can accurately resolve clonal copy number substructure in tumors and classify tumor and normal cells in a variety of human cancers. Citation Format: Ruli Gao, Shanshan Bai, Henderson Ying, Yiyun Lin, Tapsi Seth, Min Hu, Emi Sei, Alexander Davis, Fang Wang, Jennifer Rui Wang, Ken Chen, Stacey Moulder, Stephen Lai, Nicholas Navin. Inferring copy number substructure from single-cell transcriptomics in human tumors with CopyKat [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-020.

Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high rates of metastasis. Although copy number aberrations (CNAs) and genome doubling have been extensively studied in relation to TNBC initiation, little is known regarding the timing and impact of point mutations during tumor initiation, outside of TP53. A major challenge in sequencing mutations in single cells is the significant cost of unbiased whole-exome analysis of many cells. To address this challenge, we developed an approach called multi-patient-panel (MPP) sequencing which involves first performing bulk deep-exome sequencing of many patient's tumors, after which hundreds of mutations are identified and pooled across patients to design a targeted panel for high-throughput single cell DNA sequencing. We applied MPP sequencing to profile 330 mutations across 23,000 single cells from 5 TNBC patients using a microdroplet system (Mission Bio). From this data we identified 1-4 major clonal subpopulations in each tumor which shared a common evolutionary lineage. Copy number data was inferred from the targeted panel coverage depth, which showed that CNAs were correlated with different subpopulations in the tumor. By integrating both the mutation and copy number data, we inferred phylogenetic lineages and identified the timing of mutations during primary tumor growth, which detected early truncal mutations (in addition to TP53) that were involved in the initiation of TNBC tumors. The MPP approach provides a powerful method to scale-up single cell DNA sequencing to tens of thousands of cells to detect mutations and infer cancer lineages and clonal substructure. Citation Format: Jake Leighton, Min Hu, Alexander Davis, Emi Sei, Yong Wang, Nicholas Navin. Delineating mutational lineages with single cell DNA sequencing using multi-patient specific panels [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2501.

The human breast consists of lobules connected to an intricate network of ducts that are surrounded by fatty tissues, designed to produce and transport milk to nourish offspring. Histopathology has identified 10 major cell types based on morphological features but have provided limited information on cell states - the transcriptional programs of cell types that reflect different biological functions. In this study we have generated an unbiased ‘cell atlas' of the normal human breast to define the cell types and cell states using single cell RNA sequencing and spatial transcriptomics methods. We performed 3' microdroplet based single cell and nuclei RNA sequencing of 248,687 stromal cells and 89,301 nuclei from 24 women with pathologically normal breast tissues that were collected from mastectomies and reduction mammoplasties. Unbiased expression analysis identified four major cell types: adipocytes, epithelial cells (luminal and basal), fibroblasts and endothelial cells and defined their transcriptional programs. Additionally, 8 minor cell types were identified in the breast, including macrophages, T-cells, natural killer cells, mast cells, pericytes, apocrine cells, neurons and smooth muscle cells. Our data revealed hundreds of novel markers of these cell types and defined their transcriptional programs and cell states. Most cell types had multiple transcriptional programs including luminal epithelial cells (hormone receptor positive and secretory), basal epithelial cells (myoepithelial or basal), endothelial cells (E1, E2, E3), myeloid cells, T-cells and fibroblasts (F1-F4) and provided insight into developmental lineages. We further delineated the spatial organization of these cell types and cell states within the tissue architecture using spatial transcriptomics assay. The breast cell atlas data provides an invaluable normal reference for the research community to understand how normal cell types are reprogrammed in diseases such as breast cancer. Citation Format: Tapsi Kumar, Quy Nguyen, Kevin Nee, Shanshan Bai, Min Hu, Emi Sei, Anita Wood, Jie Wiley, Hui Chen, Alejandro Contreras, Mediget Teshome, Ken Chen, Bora Lim, Devon Lawson, Nicholas Navin, Kai Kessenbrock. A spatially resolved single cell atlas of the human breast [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5702.

This protocol was developed for the human breast cell atlas (HBCA) project to obtain high-viability cell suspensions from freshly dissociated breast tissues from human patients. There are two options for performing this protocol: rapid-dissociation (15-30 min) or exhaustive dissociation (overnight). In our experience the rapid dissociation protocol will provide higher cell viability and better representation of breast cell types, however the total number of cells dissociated may be lower after enumeration. In contrast the exhaustive protocol provides higher cell numbers and maintains good cell viability but may result in skewing of cell type representations over the long time period. The rapid-dissociation protocol was used to generate most of the cell suspensions for the MD Anderson human breast cell atlas project and has been optimized and tested more extensively.

This protocol can be used to prepare nuclear suspensions from fresh or frozen tissue for single cell DNA or RNA sequencing experiments. For RNA analysis it is recommended to use fresh tissue samples, due to RNA degradation that occurs during freeze- thaw cycles, however for DNA analysis either frozen or fresh tissue can be used. The protocol has been tested on breast tissues, and many frozen tumor tissues including breast, colon prostate and pancreatic samples.

Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.

The human breast tissue consists of lobules connected to a complex network of ducts that are evolutionarily designed to produce and transport milk to nourish offspring. Histopathology has identified 10 major cell types based on morphological features but have provided limited information on cell states - the transcriptional programs of cell types that reflect different biological functions. In this study, we have generated an unbiased 'cell atlas' of the normal human breast to define the cell types and cell states using single cell RNA sequencing methods. We performed 3' microdroplet based single cell RNA sequencing of 31,442 stromal cells from 11 women with pathologically normal breast tissues that were collected from mastectomies. Unbiased expression analysis identified three major cell types: epithelial cells (luminal and basal), fibroblasts and endothelial cells, in addition to several minor cell types: macrophages, T-cells, natural killer cells, pericytes and smooth muscle cells. Analysis of cell states of these cell types revealed different transcriptional programs in luminal epithelial cells (hormone receptor positive and secretory), basal epithelial cells (myoepithelial or basement-like), endothelial cells (lymphatic or vascular), macrophages (M1 or M2) and fibroblasts (three subgroups) and provided insight into progenitors of each cell types. These data provide a valuable reference for the research community and will provide new insights into how normal cell types are transformed in the tumor microenvironment to promote or inhibit the progression of breast cancer. Citation Format: Seth TK, Bai S, Hu M, Sei E, Wood A, Wiley J, Chen H, Contreras A, Teshome M, Lim B, Navin NE. Towards a human breast cell atlas [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS1-02.

Single cell RNA sequencing has emerged as a powerful tool for resolving transcriptional diversity in tumors, but is limited by throughput, cost and the ability to process archival frozen tissue samples. Here we develop a high-throughput 3′ single-nucleus RNA sequencing approach that combines nanogrid technology, automated imaging, and cell selection to sequence up to ~1800 single nuclei in parallel. We compare the transcriptomes of 485 single nuclei to 424 single cells in a breast cancer cell line, which shows a high concordance (93.34%) in gene levels and abundance. We also analyze 416 nuclei from a frozen breast tumor sample and 380 nuclei from normal breast tissue. These data reveal heterogeneity in cancer cell phenotypes, including angiogenesis, proliferation, and stemness, and a minor subpopulation (19%) with many overexpressed cancer genes. Our studies demonstrate the utility of nanogrid single-nucleus RNA sequencing for studying the transcriptional programs of tumor nuclei in frozen archival tissue samples., Single cell RNA sequencing is a powerful tool for understanding cellular diversity but is limited by cost, throughput and sample preparation. Here the authors use nanogrid technology with integrated imaging to sequence thousands of cancer nuclei in parallel from fresh or frozen tissue.

Castration-resistant prostate cancer (CRPC) is a lethal disease. A subset of these patients present with atypical clinical characteristics and aggressive disease behavior. These patients, classified as Aggressive Variant Prostate Cancer (AVPC), may derive benefit from platinum-based chemotherapy. However, the identification of AVPC patients is often challenging due to heterogeneity in clinical presentations and potentially in biological drivers, which may not be fully reflected in a biopsy obtained from a single tumor site. To address these challenges, we developed an unbiased genome sequencing method called PEGASUS (Plasma Exome and Genome Analysis by Size-Selection and Unbiased Sequencing) that enables the simultaneous detection of copy number aberrations and exome mutations from circulating-tumor DNA (ctDNA). We applied this method to plasma specimens obtained from 160 CRPC patients with and without AVPC participating in a randomized trial of cabazitaxel alone or in combination with carboplatin. We were able to successfully isolate ctDNA (>2 ng) for genomic profiling using PEGASUS in 91/160 (57%) CRPC patients. Among these 91 CRPC patients, we detected common prostate cancer mutations as well as genomic copy number changes in genes such as RB1, PTEN and TP53 and several other genes associated with DNA repair. One of the most salient features that distinguished the patients’ outcomes was whether they had diploid or aneuploid genomes detected by whole genome profiling of the ctDNA. Patients with aneuploid ctDNA had worse progression-free and overall survival. Overall, our data shows the feasibility of performing whole-genome and exome profiling of ctDNA in CRPC patients to characterize the molecular features associated with distinct clinical presentations. Candidate markers associated to benefit from platinum-based chemotherapy are being evaluated. These results pave the way for future clinical applications in biomarker discovery to assist treatment decisions in prostate cancer patients. Citation Format: Naveen Ramesh, Emi Sei, Pei Ching Tsai, Christopher Logothetis, Paul Corn, Ana Aparicio, Amado J. Zurita, Nicholas E. Navin. Plasma genome sequencing identifies prostate cancer patients that are sensitive to platinum-based therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 446.

Canonical Wnt/β-catenin signaling is strongly associated with cancer development and metastasis, but non-canonical Wnt signaling and its role in pancreatic ductal adenocarcinoma (PDAC) metastasis is not well understood. Wnt11 is implicated in cancer cell motility through non-canonical Wnt signaling pathways, however, previously described mechanisms are diverse and tissue specific. We investigated Wnt11 expression and its effects on PDAC cell motility/invasion and correlated these with gene expression signatures generated through single cell RNA-sequencing of PDAC tumors. Expression of Wnt11 was confirmed by RT-qPCR in PDAC cell lines derived from genetically engineered mouse models (KPC) and PDAC patient derived xenografts. Wnt11 was overexpressed in three PDAC cell lines following transfection with Wnt11 cDNA cloned into a pcDNA3.1 backbone and confirmed by RT-qPCR and western blot. siRNAs targeting Wnt11 were used to silence Wnt11 in PDAC cell lines relative to non-targeting controls and confirmed by RT-qPCR. Transwell migration/invasion assays were performed in triplicate with matched MTT proliferation assays in 3 PDAC cell lines with stable Wnt11 overexpression and 3 PDAC cell lines following Wnt11 siRNA knockdown. For single cell transcriptomic analysis, single cell suspensions were generated from 14 unique patient PDAC tumors. 10x GemCode microfluidics technology was used to isolate single cells into gel-bead in emulsion (GEM) units and were individually barcoded, lysed and reverse-transcribed. Barcoded cDNA libraries were then amplified and underwent next-generation sequencing. PDAC cell subpopulations with >4-fold levels of Wnt11 expression relative to all sequenced cells were identified and compared to the remaining tumor cell population to develop differentially expressed gene profiles. Pathways analysis of this gene set was performed using ENRICHR. Single cell transcriptomic analysis of PDAC cells derived from 14 different PDAC patients confirmed strong Wnt11 expression in subpopulations of PDAC cells. Wnt11 overexpression resulted in a 3.2-fold increase in migration and invasion (p4-fold) Wnt11 expression, ERICHR analysis using the NCI pathway interaction database revealed significant enrichment in β-integrin signaling (p Citation Format: Tara Hughes, Xinqun Li, Bingbing Dai, Jenying Deng, Christian Siangco, Kaberi Das, Shanshan Bai, Min Hu, Emi Sei, Tapsi Seth, Nicholas Navin, Michael Kim. Wnt11 regulates migration and invasion in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2738.

The Kaposi's sarcoma-associated herpesvirus (KSHV) open reading frame 57 (ORF57)-encoded protein (Mta) is a multifunctional regulator of viral gene expression. ORF57 is essential for viral replication, so elucidation of its molecular mechanisms is important for understanding KSHV infection. ORF57 has been implicated in nearly every aspect of viral gene expression, including transcription, RNA stability, splicing, export, and translation. Here we demonstrate that ORF57 interacts with the KSHV K-bZIP protein in vitro and in cell extracts from lytically reactivated infected cells. To further test the biological relevance of the interaction, we performed a chromatin immunoprecipitation and microarray (ChIP-chip) analysis using anti-ORF57 antibodies and a KSHV tiling array. The results revealed four specific areas of enrichment, including the ORF4 and K8 (K-bZIP) promoters, as well as oriLyt, all of which interact with K-bZIP. In addition, ORF57 associated with DNA corresponding to the PAN RNA transcribed region, a known posttranscriptional target of ORF57. All of the peaks were RNase insensitive, demonstrating that ORF57 association with the viral genome is unlikely to be mediated exclusively by an RNA tether. Our data demonstrate that ORF57 associates with the viral genome by using at least two modes of recruitment, and they suggest that ORF57 and K-bZIP coregulate viral gene expression during lytic infection.

The Kaposi's sarcoma-associated herpesvirus (KSHV) ORF57 protein is an essential multifunctional regulator of gene expression. ORF57 interaction with RNA is necessary for ORF57-mediated posttranscriptional functions, but little is known about the RNA elements that drive ORF57-RNA specificity. Here, we investigate the cis -acting factors on the KSHV PAN RNA that dictate ORF57 binding and activity. We show that ORF57 binds directly to the 5′ end of PAN RNA in KSHV-infected cells. Furthermore, we employ in vitro and cell-based assays to define a 30-nucleotide (nt) core ORF57-responsive element (ORE) that is necessary and sufficient for ORF57 binding and activity. Mutational analysis of the core ORE further suggests that a 9-nt sequence is a specific binding site for ORF57. These studies provide insight into ORF57 specificity determinants and lay a foundation for future analyses of cellular and viral ORF57 targets.

Leptomeningeal disease (LMD) involves the dissemination of tumor cells from the primary breast tumors into the membranes surrounding the central nervous system and spinal cords. LMD occurs in about 5% of breast cancer patients and is associated with very poor survival. The genomic evolution of LMD in breast cancer patients has remained difficult to study, in part due to technical challenges in collecting longitudinal biopsy samples from the central nervous system. Liquid biopsies of the cerebral spinal fluid (CSF) may provide a unique opportunity to profile circulating tumor DNA (ctDNA) and has not been compared directly to non-invasive monitoring of ctDNA in blood samples. Furthermore, most non-invasive ctDNA profiling methods are limited to a targeted set of genes and have not allowed unbiased whole-genome profiling. To address these limitations, we developed an unbiased method for ctDNA analysis called PEGASUS (Plasma Exome and Genome Analysis by Size-selection and Unbiased Sequencing) that enables whole-genome sequencing of copy number aberrations and somatic mutations from ctDNA. We applied PEGASUS to sequence matched blood samples and CSF from 10 breast cancer patients with LMD. Quantitation of ctDNA levels showed that ctDNA was detected in CSF samples from 9/10 patients, while blood ctDNA was detected in only 1 LMD patient with extensive metastatic disease. Whole-genome copy number profiling at 220kb resolution and mutational profiling of a 2000 cancer gene panel of the matched CSF and blood samples was performed in 10 LMD patients using PEGASUS. Our data identified aneuploid copy number aberrations and somatic mutations (range: 11-25) in the CSF of 7 patients, including mutations in known driver genes such as BRAF, RB1, TP53 and amplifications of MYC and ERBB2. In contrast the matched blood samples showed only diploid copy number profiles and no detectable somatic mutations in 9/10 LMD patients. In one patient with extensive cranial metastatic disease with matched CSF and blood ctDNA, we found a high concordance in copy number profiles (R= 0.75) and modest concordance of somatic mutations (59.5%), but also additional CNAs and mutations that were specific to the CSF. Collectively, these data show that genomic profiling of ctDNA in CSF is technically feasible for patients with LMD, and provides a major advantage over blood ctDNA which cannot be detected in mostcases. Citation Format: Masahiro Oikawa, Naveen Ramesh, Emi Sei, Shanshan Bai, Min Hu, de Groot F. John, Murthy Rshmi, Barbara O'Brien, Nicholas Navin. Noninvasive genomic profiling of cerebral spinal fluid in breast cancer patient with leptomeningeal disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5599.