Novel Approach for Pancreas Transcriptomics Reveals the Cellular Landscape in Homeostasis and Acute Pancreatitis

BACKGROUND & AIMS

Acinar cells produce digestive enzymes that impede transcriptomic characterization of the exocrine pancreas. Thus, single-cell RNA-sequencing studies of the pancreas underrepresent acinar cells relative to histological expectations, and a robust approach to capture pancreatic cell responses in disease states is needed. We sought to innovate a method that overcomes these challenges to accelerate study of the pancreas in health and disease.

METHODS

We leverage FixNCut, a single-cell RNA-sequencing approach in which tissue is reversibly fixed with dithiobis(succinimidyl propionate) before dissociation and single-cell preparation. We apply FixNCut to an established mouse model of acute pancreatitis, validate findings using GeoMx whole transcriptome atlas profiling, and integrate our data with prior studies to compare our method in both mouse and human pancreas datasets.

RESULTS

FixNCut achieves unprecedented definition of challenging pancreatic cells, including acinar and immune populations in homeostasis and acute pancreatitis, and identifies changes in all major cell types during injury and recovery. We define the acinar transcriptome during homeostasis and acinar-to-ductal metaplasia and establish a unique gene set to measure deviation from normal acinar identity. We characterize pancreatic immune cells, and analysis of T-cell subsets reveals a polarization of the homeostatic pancreas toward type-2 immunity. We report immune responses during acute pancreatitis and recovery, including early neutrophil infiltration, expansion of dendritic cell subsets, and a substantial shift in the transcriptome of macrophages due to both resident macrophage activation and monocyte infiltration.

CONCLUSIONS

FixNCut preserves pancreatic transcriptomes to uncover novel cell states during homeostasis and following pancreatitis, establishing a broadly applicable approach and reference atlas for study of pancreas biology and disease.

The covariance environment defines cellular niches for spatial inference

A key challenge of analyzing data from high-resolution spatial profiling technologies is to suitably represent the features of cellular neighborhoods or niches. Here we introduce the covariance environment (COVET), a representation that leverages the gene-gene covariate structure across cells in the niche to capture the multivariate nature of cellular interactions within it. We define a principled optimal transport-based distance metric between COVET niches that scales to millions of cells. Using COVET to encode spatial context, we developed environmental variational inference (ENVI), a conditional variational autoencoder that jointly embeds spatial and single-cell RNA sequencing data into a latent space. ENVI includes two decoders: one to impute gene expression across the spatial modality and a second to project spatial information onto single-cell data. ENVI can confer spatial context to genomics data from single dissociated cells and outperforms alternatives for imputing gene expression on diverse spatial datasets.

Microbial cancer immunotherapy reprograms hematopoietic stem cells to enhance anti-tumor immunity

Mycobacterium bovis BCG is the vaccine against tuberculosis and an immunotherapy for bladder cancer. When administered intravenously, BCG reprograms bone marrow hematopoietic stem and progenitor cells (HSPCs), leading to heterologous protection against infections. Whether HSPC-reprogramming contributes to the anti-tumor effects of BCG administered into the bladder is unknown. We demonstrate that BCG administered in the bladder in both mice and humans reprograms HSPCs to amplify myelopoiesis and functionally enhance myeloid cell antigen presentation pathways. Reconstitution of naive mice with HSPCs from bladder BCG-treated mice enhances anti-tumor immunity and tumor control, increases intratumoral dendritic cell infiltration, and synergizes with checkpoint blockade. We conclude that bladder BCG acts systemically, reprogramming HSPC-encoded innate immunity, highlighting the broad potential of modulating HSPC phenotypes to improve tumor immunity.

One Sentence Summary

BCG administered in the bladder reprograms bone marrow HSPCs and contributes to tumor control via enhanced myeloid cells.

SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data

Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here we present single-cell aggregation of cell states (SEACells), an algorithm for identifying metacells that overcome the sparsity of single-cell data while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying comprehensive, compact and well-separated metacells in both RNA and assay for transposase-accessible chromatin (ATAC) modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene-peak associations, compute ATAC gene scores and infer the activities of critical regulators during differentiation. Metacell-level analysis scales to large datasets and is particularly well suited for patient cohorts, where per-patient aggregation provides more robust units for data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a Coronavirus Disease 2019 (COVID-19) patient cohort.

Deep generative model deciphers derailed trajectories in acute myeloid leukemia

Single-cell genomics has the potential to map cell states and their dynamics in an unbiased way in response to perturbations like disease. However, elucidating the cell-state transitions from healthy to disease requires analyzing data from perturbed samples jointly with unperturbed reference samples. Existing methods for integrating and jointly visualizing single-cell datasets from distinct contexts tend to remove key biological differences or do not correctly harmonize shared mechanisms. We present Decipher, a model that combines variational autoencoders with deep exponential families to reconstruct derailed trajectories ( https://github.com/azizilab/decipher ). Decipher jointly represents normal and perturbed single-cell RNA-seq datasets, revealing shared and disrupted dynamics. It further introduces a novel approach to visualize data, without the need for methods such as UMAP or TSNE. We demonstrate Decipher on data from acute myeloid leukemia patient bone marrow specimens, showing that it successfully characterizes the divergence from normal hematopoiesis and identifies transcriptional programs that become disrupted in each patient when they acquire NPM1 driver mutations.

Supervised discovery of interpretable gene programs from single-cell data

Factor analysis decomposes single-cell gene expression data into a minimal set of gene programs that correspond to processes executed by cells in a sample. However, matrix factorization methods are prone to technical artifacts and poor factor interpretability. We address these concerns with Spectra, an algorithm that combines user-provided gene programs with the detection of novel programs that together best explain expression covariation. Spectra incorporates existing gene sets and cell-type labels as prior biological information, explicitly models cell type and represents input gene sets as a gene-gene knowledge graph using a penalty function to guide factorization toward the input graph. We show that Spectra outperforms existing approaches in challenging tumor immune contexts, as it finds factors that change under immune checkpoint therapy, disentangles the highly correlated features of CD8+ T cell tumor reactivity and exhaustion, finds a program that explains continuous macrophage state changes under therapy and identifies cell-type-specific immune metabolic programs.

Progressive plasticity during colorectal cancer metastasis

Metastasis is the principal cause of cancer death, yet we lack an understanding of metastatic cell states, their relationship to primary tumor states, and the mechanisms by which they transition. In a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that while primary tumors largely adopt LGR5 + intestinal stem-like states, metastases display progressive plasticity. Loss of intestinal cell states is accompanied by reprogramming into a highly conserved fetal progenitor state, followed by non-canonical differentiation into divergent squamous and neuroendocrine-like states, which is exacerbated by chemotherapy and associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cancer cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues than their intestinal lineage-restricted primary tumor counterparts. We identify PROX1 as a stabilizer of intestinal lineage in the fetal progenitor state, whose downregulation licenses non-canonical reprogramming.

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.

Conserved transcriptional connectivity of regulatory T cells in the tumor microenvironment informs new combination cancer therapy strategies

While regulatory T (Treg) cells are traditionally viewed as professional suppressors of antigen presenting cells and effector T cells in both autoimmunity and cancer, recent findings of distinct Treg cell functions in tissue maintenance suggest that their regulatory purview extends to a wider range of cells and is broader than previously assumed. To elucidate tumoral Treg cell 'connectivity' to diverse tumor-supporting accessory cell types, we explored immediate early changes in their single-cell transcriptomes upon punctual Treg cell depletion in experimental lung cancer and injury-induced inflammation. Before any notable T cell activation and inflammation, fibroblasts, endothelial and myeloid cells exhibited pronounced changes in their gene expression in both cancer and injury settings. Factor analysis revealed shared Treg cell-dependent gene programs, foremost, prominent upregulation of VEGF and CCR2 signaling-related genes upon Treg cell deprivation in either setting, as well as in Treg cell-poor versus Treg cell-rich human lung adenocarcinomas. Accordingly, punctual Treg cell depletion combined with short-term VEGF blockade showed markedly improved control of PD-1 blockade-resistant lung adenocarcinoma progression in mice compared to the corresponding monotherapies, highlighting a promising factor-based querying approach to elucidating new rational combination treatments of solid organ cancers.

Modeling collective cell behavior in cancer: Perspectives from an interdisciplinary conversation

Collective cell behavior contributes to all stages of cancer progression. Understanding how collective behavior emerges through cell-cell interactions and decision-making will advance our understanding of cancer biology and provide new therapeutic approaches. Here, we summarize an interdisciplinary discussion on multicellular behavior in cancer, draw lessons from other scientific disciplines, and identify future directions.

Cross-platform dataset of multiplex fluorescent cellular object image annotations

Defining cellular and subcellular structures in images, referred to as cell segmentation, is an outstanding obstacle to scalable single-cell analysis of multiplex imaging data. While advances in machine learning-based segmentation have led to potentially robust solutions, such algorithms typically rely on large amounts of example annotations, known as training data. Datasets consisting of annotations which are thoroughly assessed for quality are rarely released to the public. As a result, there is a lack of widely available, annotated data suitable for benchmarking and algorithm development. To address this unmet need, we release 105,774 primarily oncological cellular annotations concentrating on tumor and immune cells using over 40 antibody markers spanning three fluorescent imaging platforms, over a dozen tissue types and across various cellular morphologies. We use readily available annotation techniques to provide a modifiable community data set with the goal of advancing cellular segmentation for the greater imaging community.

Abstract 6421: Molecular profiles and single cell analysis identify immunogenic pancreatic ductal adenocarcinoma (iPDAC)

Most pancreatic ductal adenocarcinomas (PDAC) are lethal and resistant to immunotherapy. Thus, identifying the immunogenic subgroup (iPDAC) and therapeutic targets can save lives. Herein, we present molecular features of iPDAC. 3 cohorts (A, B, C) from 288 patients whose sequenced tumors (MSK-IMPACT) were classified by homologous recombination deficiency groups. MSI-H were excluded. Survival, tumor mutation burden, genomic instability score, and enriched pathways for each cohort are included in Table 1. Patients in A (BRCA1/2/PALB2) had longer survivals vs B/C. 61 samples were selected for bulk RNAseq analysis for A vs C. Gene Ontology was enriched for upregulated humoral, T cell, and neutrophil immunity. CIBERSORT suggested higher infiltration of gamma delta T (Tgd) cells (p=0.039) and neutrophils (p=0.012), but lower Treg (p=0.001). Multidimensional insights in cellular components of cancer, immune, stroma, and neural genes were obtained by single nuclear RNA (snRNAseq) analysis from 30 biopsies for A vs C. 10x Genomics Chromium platform for library and Scanpy for computational analysis after Cell Ranger pipelines were used. 61,868 nuclei were profiled from 18 (13 baseline and 5 matched longitudinal) samples after quality evaluation. UMAP accurately clustered cells from each patient. Long-term survivors (LTS) had heterogenous baseline immune cell infiltrates of plasma cells, neutrophils, and CD8 (+) cytotoxic T cells. In matched samples of LTS, evolution of more prominent CD8 (+) T cells, macrophage, plasma cell, and neutrophil were observed. Single nucleus T-Cell Receptor sequencing for clonal trajectory inference will be done to determine the associated single cell molecular features contributing to iPDAC and identify novel targets for future intervention.

Table 1. Cohort (Total: N=288) A: core HRD (BRCA1/2/PALB2) B: non-core HRD (ATM, BARD1, BLM, CHEK2, RAD50, RAD51C, RTEL1, MUTYH) C: others without HR-gene alterations Number (%) 48 (16.6) 19 (6.5) 221 (76) Median overall survival (95% confidence Interval) 33 months (3.6-64) 16 (11- not reached) 16 (14-18) Tumor Mutation Burden (TMB) 4.4 3.5 3.9 Genomic Instability Score (GIS, HRD score) 26 12 13 Gene Ongology term, enrichment score, adjusted p-value Adaptive immune response, GO:0002250, 0.49, 1.69e-10 Not included Reference to cohort A Humoral immune response, GO:0006959, 0.58, 1.67e-9 T cell activation, GO:0042110, 0.44, 2.75e-8 Neutrophil chemotaxis, GO:0030593, 0.73, 4.3e-10

Citation Format: Wungki Park, Catherine O'Connor, Shigeaki Umeda, Roshan Sharma, Yingjie Zhu, Elias-Ramzey Karnoub, Anna Varghese, Kevin C. Soares, Alejandro Jimemez, Asli Yavas, Kenneth H. Yu, Balachandran P. Vinod, Joanne F. Chou, Danny N. Khalil, Kelsen David, Hulya Sahin Ozkan, Olca Basturk, Marinela Capanu, Tal Nawy, Michael F. Berger, Ghassan K. Abou-Alfa, Jorge S. Reis-Filho, Ronan Chaligne, Nadeem Riaz, Dana Pe'er, Christine Iacobuzio-Donahue, Eileen M. O'Reilly. Molecular profiles and single cell analysis identify immunogenic pancreatic ductal adenocarcinoma (iPDAC) [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 6421.

Abstract 1167: Single-cell transcriptomic profiling of SCLC transformation reveals increased intratumoral diversity of variant and non-neuroendocrine subtypes

Lineage plasticity is the ability for a cell to change its phenotypic state under evolutionary pressure. This process mediates acquired resistance to EGFR-targeted therapies in lung adenocarcinoma (LUAD), through transformation to small cell lung cancer (SCLC), an aggressive cancer type of neuroendocrine (NE) histology. This transformed SCLC has worse clinical outcomes than either its LUAD or de novo SCLC counterparts, with less than one-year overall survival following transformation. Classical SCLC itself can display plasticity through interconversion between classical, variant, and non-NE transcriptional subtypes, with non-classical subtypes displaying increased metastasis and chemoresistance. It is poorly understood what factors drive SCLC transformation or subtype switching. Prior studies poorly model intratumoral heterogeneity because they profile tumors in bulk, which only estimates the average phenotype. However, SCLC transformation often results in admixed LUAD/SCLC tumors. We sought to capture the full intratumoral heterogeneity of SCLC transformation and identify potential molecular determinants of plasticity by applying single-cell RNA sequencing (scRNA-seq) to 41 tumors and patient-derived xenografts from 22 patients with transformed or combined LUAD/NE histology, with matched targeted DNA sequencing and 17 de novo SCLC tumors, 10 LUAD tumors with concurrent EGFR/RB1/TP53 mutations, and 4 tumor-adjacent normal lung samples for comparison. Of 234,322 single transcriptomes assessed, we found 89,113 NE cancer cells and 18,197 LUAD cancer cells. We confirmed that NE and LUAD components within the same tumor shared clonal mutations and common ancestry. Compared to de novo, transformed SCLC harbored greater phenotypic diversity across patients (p < 1 × 10−10), driven largely by enrichment of variant and non-NE subtypes (p < 0.02), including NEUROD1, POU2F3, and YAP1-high subtypes, the latter of which was completely absent in de novo. Within each tumor, transformed SCLC displayed higher intratumoral subtype diversity than de novo SCLC (likelihood ratio p < 0.025). After adjusting for SCLC subtype, differential expression and pathway analysis demonstrated that transformed SCLC is a distinct phenotype from de novo and shares features of the ancestral clone that include residual EGFR and NSCLC gene signatures, as well as pathways in neuronal stemness, MYC targets, AKT/MTOR signaling, JAK/STAT inflammation, and chromatin remodeling. In sum, we find increased intratumoral phenotypic diversity in transformed SCLC, including variant and non-NE subtypes, that may explain worse clinical outcomes. We show that transformed SCLC is a distinct phenotype from de novo, marked by pathways that may offer new potential drug targets to constrain plasticity, with the goal of restoring original sensitivity to targeted therapies.

Citation Format: Joseph Minhow Chan, Alvaro Quintanal-Villalonga, Amin Sabet, Parvathy Manoj, Ojasvi Chaudhary, Tianhao Xu, Ignas Masilionis, Jacklynn Egger, Noor Sohail, Jaeyoung Chun, Tal Nawy, Linas Mazutis, Triparna Sen, Ronan Chaligne, Helena Yu, Dana Pe'er, Charles Rudin. Single-cell transcriptomic profiling of SCLC transformation reveals increased intratumoral diversity of variant and non-neuroendocrine subtypes [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 1167.

STING inhibits the reactivation of dormant metastasis in lung adenocarcinoma

Metastasis frequently develops from disseminated cancer cells that remain dormant after the apparently successful treatment of a primary tumour. These cells fluctuate between an immune-evasive quiescent state and a proliferative state liable to immune-mediated elimination1-6. Little is known about the clearing of reawakened metastatic cells and how this process could be therapeutically activated to eliminate residual disease in patients. Here we use models of indolent lung adenocarcinoma metastasis to identify cancer cell-intrinsic determinants of immune reactivity during exit from dormancy. Genetic screens of tumour-intrinsic immune regulators identified the stimulator of interferon genes (STING) pathway as a suppressor of metastatic outbreak. STING activity increases in metastatic progenitors that re-enter the cell cycle and is dampened by hypermethylation of the STING promoter and enhancer in breakthrough metastases or by chromatin repression in cells re-entering dormancy in response to TGFβ. STING expression in cancer cells derived from spontaneous metastases suppresses their outgrowth. Systemic treatment of mice with STING agonists eliminates dormant metastasis and prevents spontaneous outbreaks in a T cell- and natural killer cell-dependent manner-these effects require cancer cell STING function. Thus, STING provides a checkpoint against the progression of dormant metastasis and a therapeutically actionable strategy for the prevention of disease relapse.

Leptomeningeal anti-tumor immunity follows unique signaling principles

Metastasis to the cerebrospinal fluid (CSF)-filled leptomeninges, or leptomeningeal metastasis (LM), represents a fatal complication of cancer. Proteomic and transcriptomic analyses of human CSF reveal a substantial inflammatory infiltrate in LM. We find the solute and immune composition of CSF in the setting of LM changes dramatically, with notable enrichment in IFN-γ signaling. To investigate the mechanistic relationships between immune cell signaling and cancer cells within the leptomeninges, we developed syngeneic lung, breast, and melanoma LM mouse models. Here we show that transgenic host mice, lacking IFN-γ or its receptor, fail to control LM growth. Overexpression of Ifng through a targeted AAV system controls cancer cell growth independent of adaptive immunity. Instead, leptomeningeal IFN-γ actively recruits and activates peripheral myeloid cells, generating a diverse spectrum of dendritic cell subsets. These migratory, CCR7+ dendritic cells orchestrate the influx, proliferation, and cytotoxic action of natural killer cells to control cancer cell growth in the leptomeninges. This work uncovers leptomeningeal-specific IFN-γ signaling and suggests a novel immune-therapeutic approach against tumors within this space.

Effect of Janus kinase (JAK) signaling inhibition on lineage plasticity and drug sensitivity in castrate resistant prostate cancer

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Background: Despite the remarkable successes of targeted cancer therapies, certain cancers, including lung, breast, and prostate cancer and melanoma, invariably become resistant to therapy. One mechanism of secondary resistance—lineage plasticity—arises when cells alter their identity and transition into aggressive states. In the case of prostate cancer, cells can acquire a neuroendocrine histology. This is often associated with a loss of tumor suppressor genes, such as TP53, RB1, and PTEN. However, while these genomic events initiate plasticity, tumor progression is not always associated with successive genomic alterations. This, in essence, not only poses a clinical challenge, but also confronts us with a wide-open biological question—what are the molecular underpinnings of lineage plasticity, and importantly, can the process be reversed? Methods: To study the temporal evolution of lineage plasticity and its relationship to androgen receptor signaling inhibitor (ARSI) resistance, we utilized genetically engineered mouse models (GEMMs) and murine organoids that were deleted for Tp53, Rb1, and/or Pten. Single cell RNA analyses were utilized to dissect which genes and pathways were up-regulated and most associated with the progression of plasticity. Plasticity-associated genes and pathways were perturbed using FDA-approved inhibitors or genetic editing tools. The presence of these pathways was confirmed in a subset of metastatic index lesions obtained by radiologically guided biopsies and as visualized by metabolic imaging. Furthermore, relevant findings were functionally validated in human tumor derived organoids (“tumoroids”). Results: Using GEMMs and organoid models, we found the lineage plasticity depended on increased Janus Kinase (JAK) and fibroblast growth factor receptor (FGFR) activity. Pharmacologic inhibition using FDA–approved inhibitors of JAK/STAT (ruxolitinib) and FGFR (erdafinitib), or through genetic knockdown, demonstrated increased androgen receptor (AR) signaling and restored ARSI sensitivity. These findings were further validated in a subset of ARSI-insensitive human tumoroids. By performing single cell RNA sequencing on mCRPC tumors biopsies, the presence of highly plastic JAK/STAT- and FGFR-high cells were confirmed, with implications for stratifying patients for clinical trials. Conclusions: JAK/STAT and FGFR signaling pathways promote lineage plasticity and result in complete insensitivity to androgen receptor signaling inhibitors (ARSIs). FDA-approved inhibitors of JAK/STAT (ruxolitinib) and FGFR (erdafitinib) synergize to reverse lineage plasticity and restore ARSI sensitivity.

Distinct tumor architectures for metastatic colonization of the brain

Brain metastasis is a dismal cancer complication, hinging on the initial survival and outgrowth of disseminated cancer cells. To understand these crucial early stages of colonization, we investigated two prevalent sources of cerebral relapse, triple-negative (TNBC) and HER2+ breast cancer (HER2BC). We show that these tumor types colonize the brain aggressively, yet with distinct tumor architectures, stromal interfaces, and autocrine growth programs. TNBC forms perivascular sheaths with diffusive contact with astrocytes and microglia. In contrast, HER2BC forms compact spheroids prompted by autonomous extracellular matrix components and segregating stromal cells to their periphery. Single-cell transcriptomic dissection reveals canonical Alzheimer's disease-associated microglia (DAM) responses. Differential engagement of tumor-DAM signaling through the receptor AXL suggests specific pro-metastatic functions of the tumor architecture in both TNBC perivascular and HER2BC spheroidal colonies. The distinct spatial features of these two highly efficient modes of brain colonization have relevance for leveraging the stroma to treat brain metastasis.

Abstract B016: Quantifying and dissecting pancreatic cancer cell phenotypic plasticity using lineage tracing, single-cell multiomics and CRISPR perturbations reveals novel regulators of plastic states

Pancreatic cancer is a lethal disease in part because tumor cells exist in distinct transcriptional phenotypes (e.g. basal and classical states), each with a selective ability to evade current chemotherapy regimens. Two major mechanisms have been suggested for treatment evasion: 1) intrinsic resistance of certain phenotypes to particular chemotherapy regimens and 2) plasticity of treatment sensitive phenotypes to adopt more resistant phenotypes. However, the relative contribution of these mechanisms to treatment resistance is still poorly understood. Whereas previous work has described the redistribution of tumor cell states under selective treatment pressure, there is no direct evidence that tumor cells exhibit phenotypic plasticity at steady state or with treatment. By leveraging technological advancements in single-cell methods, lineage tracing and functional genomics, we have now shown direct evidence of phenotypic state switching in human pancreatic cancer cell lines. By performing single-cell RNA-seq on 5 barcoded PDAC cell lines over a steady state timecourse and under chemotherapy selective pressure (>600k cells total), we identify unique plasticity phenotypes within these cell lines and infer regulators of these plastic states. We validate the role of several of these regulators using bulk phenotypic CRISPRi screens in these cell lines. We next perform CRISPRi perturbations along with lineage tracing and single-cell multiomics (>300k cells) to dissect the regulatory relationships that underlie these cell states. We identify several novel epithelial and mesenchymal biasing factors, including those with unique roles in the most plastic clones. Collectively, we nominate several regulators that bias PDAC cell states thus posing a paradigm whereby perturbations may be used to homogenize tumor populations towards treatment-sensitive phenotypes. We believe this approach combined with current chemotherapy regimens could benefit pancreatic cancer patients by targeting residual, resistant tumor cells in the localized and metastatic disease settings to improve patient survival.

Citation Format: Arnav Mehta, Lynn Bi, Aziz Al'Khafaji, Martin Jankowiak, Milan Parikh, Mehrtash Babadi, Alex Bloemendal, Marc Schwartz, Glen Munson, Joeseph Chan, Cassandra Burdziak, Elisa Donnard, Ryan Park, Chen Lu, Philippe Rigollet, Andrew Aguirre, Vidya Subramanian, Ray Jones, Eric S. Lander, David T. Ting, Dana Pe'er, Nir Hacohen. Quantifying and dissecting pancreatic cancer cell phenotypic plasticity using lineage tracing, single-cell multiomics and CRISPR perturbations reveals novel regulators of plastic states [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B016.

Abstract C012: Dissecting the reorganization of pancreatic tumor microenvironments after radiation and immunotherapy reveals insights into immunotherapy resistance

Immune checkpoint blockade (ICB) has revolutionized the treatment of many cancers but has been ineffective for the treatment of microsatellite stable (MSS) PDAC. The lack of efficacy of immunotherapies in PDAC is due to: 1) a desmoplastic tumor microenvironment (TME); 2) the presence of suppressive cells, including myeloid derived suppressor cells and regulatory T cells; and 3) the lack of antigen-presenting dendritic cells (DCs) that are important in priming an effective immune response to generate functionally effective tumor antigen-specific T cells. We recently completed a pilot study of dual ICB (Ipilumamab and Nivolumab) with radiation therapy (SBRT 8Gy for 3 fractions) in a cohort of 25 metastatic PDAC patients that had progressed on conventional chemotherapy; this combination conferred an impressive 18% ORR and 29% disease control rate measured on non-irradiated lesions (historical 0% ORR with ICB in PDAC). This led to a phase 2 study in 30 metastatic PDAC patients using this dual modality treatment paradigm. To understand the role of radiation and ICB in altering the PDAC tumor microenvironment we performed single-cell RNA-sequencing and TCR-sequencing (>180k cells), and single-nucleus RNA-sequencing (>300k cells) on 36 tumor biopsies (23 pre-treatment, 13 paired on-treatment between day 10 and 21) from patients undergoing treatment in our phase 2 study. Tumor tissue was taken from distinct tissue sites, including primary tumors in the pancreas, and liver and abdominal wall metastases. We identified distinct tumor cell state distributions within different tissues, and a redistribution of cells from basal/mesenchymal states to classical states after radiation. We identified several state-specific interferon stimulated gene programs thus cataloging distinct responses of epithelial cells with different transcriptional states. Importantly, we found a redistribution of T cells states towards proliferating and exhausted T cells with unique clonality after radiation. Additionally, the myeloid compartment after radiation was enriched for C1QC+ and MHCII+ macrophage subsets, as well as infiltrating CD16/CD16 monocytes and CD14 monocytes, each showing induction of unique sets of interferon stimulated genes (ISGs). We next sought to better understand immunotherapy resistance mechanisms within these PDAC patients despite finding strong ISG induction in several subsets. We analyzed covarying gene programs and identified multicellular communities of cells before and after radiation that underlie interaction networks associated with radiation. Together our data provides the most comprehensive single-cell atlas of paired biopsies to study tumor and immune cell states in the context of radiation and ICB response.

Citation Format: Arnav Mehta, Aparna Parikh, Milan Parikh, Ryan Park, Moshe Sade-Feldman, Lynn Bi, Nicole Carzo, Tarin M. Grillo, Islam Baiev, Olanike Asupoto, Irena Gushterova, Tom LaSalle, Anna Gonye, Emily Blaum, Sebastien Vigneau, Ronan Chaligne, Ana Lako, Thomas Lila, David Nelson, Caroline Porter, Orr Ashenberg, Karthik Jagadesh, William L. Hwang, Christopher Smillie, David P. Ryan, David T. Ting, Theodore Hong, Dana Pe'er, Nir Hacohen. Dissecting the reorganization of pancreatic tumor microenvironments after radiation and immunotherapy reveals insights into immunotherapy resistance [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C012.

MACHETE identifies interferon-encompassing chromosome 9p21.3 deletions as mediators of immune evasion and metastasis

The most prominent homozygous deletions in cancer affect chromosome 9p21.3 and eliminate CDKN2A/B tumor suppressors, disabling a cell-intrinsic barrier to tumorigenesis. Half of 9p21.3 deletions, however, also encompass a type I interferon (IFN) gene cluster; the consequences of this co-deletion remain unexplored. To functionally dissect 9p21.3 and other large genomic deletions, we developed a flexible deletion engineering strategy, MACHETE (molecular alteration of chromosomes with engineered tandem elements). Applying MACHETE to a syngeneic mouse model of pancreatic cancer, we found that co-deletion of the IFN cluster promoted immune evasion, metastasis and immunotherapy resistance. Mechanistically, IFN co-deletion disrupted type I IFN signaling in the tumor microenvironment, leading to marked changes in infiltrating immune cells and escape from CD8+ T-cell surveillance, effects largely driven by the poorly understood interferon epsilon. These results reveal a chromosomal deletion that disables both cell-intrinsic and cell-extrinsic tumor suppression and provide a framework for interrogating large deletions in cancer and beyond.

Protocol to dissociate, process, and analyze the human lung tissue using single-cell RNA-seq

We report a protocol for obtaining high-quality single-cell transcriptomics data from human lung biospecimens acquired from core needle biopsies, fine-needle aspirates, surgical resection, and pleural effusions. The protocol relies upon the brief mechanical and enzymatic disruption of tissue, enrichment of live cells by fluorescence-activated cell sorting (FACS), and droplet-based single-cell RNA sequencing (scRNA-seq). The protocol also details a procedure for analyzing the scRNA-seq data. For complete details on the use and execution of this protocol, please refer to Chan et al. (2021).

Abstract 1728: Single cell RNA-seq analysis reveals a role of pro-inflammatory tumor-associated macrophages in driving prostate cancer progression

Genomic amplification and increased expression of C-MYC are found in high-grade intraepithelial neoplasm (HGPIN) and primary prostate adenocarcinoma. What role C-MYC plays in the initiation and progression of prostate cancer remains unclear. A genetically engineered mouse model with a high level of human C-MYC protein expression under a probasin promoter (Hi-Myc model) was developed that captures prostate cancer progression from hyperplasia at 6-week-old, to HGPIN at 3-6 month-old, and ultimately to invasive adenocarcinoma at 8-month-old. Applying single-cell RNA sequencing (scRNA-seq) technology, we have carefully studied the temporal transcriptional change in MYC-expressing tumor-initiating cells and the tumor-infiltrating immune cells to understand the cell-intrinsic and -extrinsic mechanisms by which C-MYC promotes the transition from HGPIN to invasive prostate cancer. We have identified a particular type of luminal cells, Prom1+ L1 cells, as the likely tumor initiating cells in the Hi-Myc model. The MYC-expressing L1 tumor initiating cells were more abundant and cycling more often in the invasive cancer at 8-month-old, compared to the pre-invasive stage. Interestingly, significant infiltration of novel M1-like tumor-associated macrophages (TAMs) correlated with the histologic tumor progression from HGPIN to invasive cancer. Targeting TAMs with anti-CSF1R antibody delayed prostate cancer progression and invasion, which appears to be independent of CD8 T-cells. Mechanistically, TAMs expressed a high level of IL-1b, which stimulated Hi-Myc prostate cell proliferation in an organoid co-culture system. More importantly, depleting IL-1b with a neutralizing antibody slowed prostate cancer progression in Hi-Myc mice. Lastly, we found that increased macrophage gene expression was associated with higher Gleason scores and worse disease-free survival in a TCGA clinical patient cohort. In summary, we have identified a molecular mechanism involving pro-inflammatory TAMs and IL-1b in driving early prostate cancer progression in a MYC-driven prostate cancer model, opening a potential therapeutic avenue to target TAMs and pro-inflammatory cytokine in preventing early prostate cancer progression.

Citation Format: Jimmy L. Zhao, Joseph Chan, Max Land, Perianne Smith, Anuradha Gopalan, Michael Haffner, Dana Pe'er, Charles Sawyers. Single cell RNA-seq analysis reveals a role of pro-inflammatory tumor-associated macrophages in driving prostate cancer progression [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 1728.

Abstract 1594: Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition

The inherent plasticity of tumor cells provides a mechanism of resistance to many molecularly targeted therapies, exemplified by adeno-to-neuroendocrine lineage transitions seen in prostate and lung cancer. Here we investigate the root cause of this lineage plasticity in a primary murine prostate organoid model that mirrors the lineage transition seen in patients. These cells lose luminal identity within weeks following deletion of Trp53 and Rb1, ultimately acquiring an Ar-negative, Syp+ phenotype after orthotopic in vivo transplantation. We performed single-cell transcriptomic analysis of a time-course experiment on the prostate organoid following Trp53 and Rb1 deletion. Critical to this study, we developed SEACells, a method that enumerates distinct, highly granular cell states, allowing for robust transcriptomic quantification. Leveraging the SEACell platform, we developed several graph-based computational approaches based on Markov absorption, diffusion maps, and attributed stochastic block models to quantify dynamic changes in plasticity. These quantitative models independently confirmed rapid collapse of cell-type fidelity in the form of a mixed luminal-basal phenotype following tumor suppressor gene deletion. These methods compute metrics for plasticity that we correlated to candidate driver gene programs. Among the strongest plasticity correlates, Jak-Stat and Fgfr signaling stood out as gene programs activated early in the time-course prior to any corresponding morphological changes. We further developed a regression-based approach to nominate ligand-receptor interactions that activate downstream Jak-Stat signaling, which identified Fgf-Fgfr interactions that were functionally validated with growth factor addition and pharmacological inhibition. Most strikingly, genetic or pharmacologic inhibition of Jak1/2 in combination with Fgfr blockade not only reversed the plastic state and restored organoids to their wild-type morphology, but also re-sensitized drug-resistant cells to antiandrogen therapy in models with residual AR expression. We additionally confirm early activation of Jak/Stat transcriptional programs in an Rb1/Trp53/Pten-deleted genetically engineered mouse model undergoing substantial cell-type diversification under plasticity in the context of the tumor microenvironment. Collectively, we show that lineage plasticity initiates quickly as a largely cell-autonomous process that is further increased in the in vivo setting, and through newly developed computational approaches, we identify a pharmacological strategy that restores lineage identity using clinical grade inhibitors.

Citation Format: Joseph M. Chan, Wouter R. Karthaus, Manu Setty, Jillian R. Love, Samir Zaidi, Jimmy Zhao, Zi-ning Choo, Sitara Persad, Justin LaClair, Kayla E. Lawrence, Ojasvi Chaudhary, Ignas Masilionis, Linas Mazutis, Ronan Chaligne, Dana Pe'er, Charles Sawyers. Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition [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 1594.

Abstract 2200: Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling

Lineage plasticity is a well-established mechanism of resistance to targeted therapies in lung and prostate cancer, where tumors transition from adenocarcinoma to small-cell or neuroendocrine carcinoma. Single-cell analysis of a cohort of late stage castration-resistant human prostate cancers (CRPC) revealed a greater degree of plasticity than previously appreciated, with multiple distinct neuroendocrine (NEPC), mesenchymal (EMT-like), and other subpopulations detected within single biopsies. To explore the steps responsible for initiation of this process, we utilized two genetically engineered mouse models of prostate cancer that recapitulate progression from adenocarcinoma to neuroendocrine disease. Time course studies reveal expansion of stem-like luminal epithelial cells (Sca1+, Psca+, called L2) that, based on trajectories, gave rise to at least 4 distinct subpopulations, NEPC (Ascl1+), POU2F3 (Pou2f3+), TFF3 (Tff3+) and EMT-like (Vim+, Ncam1+). Such populations are also seen in human prostate and small cell lung cancers. Furthermore, transformed L2-like cells express stem-like and gastrointestinal endoderm-like transcriptional programs, indicative of reemerging developmental plasticity programs, as well as elevated Jak/Stat, interferon, and FGF pathways. Strikingly pharmacologic inhibition of Jak/Stat and FGFR results in reversal of plasticity states and subsequent sensitivity to androgen receptor inhibitors (ARSIs). In sum, while the magnitude of multilineage heterogeneity, both within and across patients, raises considerable treatment challenges, the identification of highly plastic luminal cells as the likely source of this heterogeneity provides a target for more focused therapeutic intervention.

Citation Format: Samir Zaidi, Jimmy Zhao, Joseph Chan, Roudier Martine, Kristine Wadosky, Anuradha Gopalan, Wouter Karthaus, Philip Watson, Lawrence True, Peter Nelson, Howard Scher, Michael Morris, Michael Haffner, David Goodrich, Dana Pe'er, Charles Sawyers. Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling [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 2200.

Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data.

Spatial CRISPR genomics identifies regulators of the tumor microenvironment

While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying extracellular gene functions, particularly in the tissue context. Here, we developed an approach for spatial functional genomics called Perturb-map. We applied Perturb-map to knock out dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Moreover, we paired Perturb-map and spatial transcriptomics for unbiased analysis of CRISPR-edited tumors. We found that in Tgfbr2 knockout tumors, the tumor microenvironment (TME) was converted to a fibro-mucinous state, and T cells excluded, concomitant with upregulated TGFβ and TGFβ-mediated fibroblast activation, indicating that TGFβ-receptor loss on cancer cells increased TGFβ bioavailability and its immunosuppressive effects on the TME. These studies establish Perturb-map for functional genomics within the tissue at single-cell resolution with spatial architecture preserved and provide insight into how TGFβ responsiveness of cancer cells can affect the TME.

MITI minimum information guidelines for highly multiplexed tissue images

The imminent release of tissue atlases combining multi-channel microscopy with single cell sequencing and other omics data from normal and diseased specimens creates an urgent need for data and metadata standards that guide data deposition, curation and release. We describe a Minimum Information about highly multiplexed Tissue Imaging (MITI) standard that applies best practices developed for genomics and other microscopy data to highly multiplexed tissue images and traditional histology.

CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.

CellRank infers directed cell state transitions and cell fates incorporating RNA velocity information into a graph based Markov process.

Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy

To elucidate mechanisms by which T cells eliminate leukemia, we study donor lymphocyte infusion (DLI), an established immunotherapy for relapsed leukemia. We model T cell dynamics by integrating longitudinal, multimodal data from 94,517 bone marrow-derived single T cell transcriptomes in addition to chromatin accessibility and single T cell receptor sequencing from patients undergoing DLI. We find that responsive tumors are defined by enrichment of late-differentiated T cells before DLI and rapid, durable expansion of early differentiated T cells after treatment, highly similar to "terminal" and "precursor" exhausted subsets, respectively. Resistance, in contrast, is defined by heterogeneous T cell dysfunction. Surprisingly, early differentiated T cells in responders mainly originate from pre-existing and novel clonotypes recruited to the leukemic microenvironment, rather than the infusion. Our work provides a paradigm for analyzing longitudinal single-cell profiling of scenarios beyond adoptive cell therapy and introduces Symphony, a Bayesian approach to infer regulatory circuitry underlying T cell subsets, with broad relevance to exhaustion antagonists across cancers.

Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively). To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 155,098 transcriptomes from 21 human biospecimens, including 54,523 SCLC transcriptomes. We observe greater tumor diversity in SCLC than lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discover a PLCG2-high SCLC phenotype with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival. SCLC exhibits greater immune sequestration and less immune infiltration than lung adenocarcinoma, and SCLC-N shows less immune infiltrate and greater T cell dysfunction than SCLC-A. We identify a profibrotic, immunosuppressive monocyte/macrophage population in SCLC tumors that is particularly associated with the recurrent, PLCG2-high subpopulation.

Tumor heterogeneity

Tumor heterogeneity was traditionally considered in the genetic terms, but it has now been broadened into many more facets. These facets represent a challenge in our understanding of cancer etiology but also provide opportunity for us to understand prognosis and therapy response.

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across experimental and clinical settings. By carrying out a unified analysis of over 300 assay for transposase-accessible chromatin sequencing (ATAC-seq) and RNA sequencing (RNA-seq) experiments from 12 studies of CD8 T cells in cancer and infection, we defined a shared differentiation trajectory toward dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell states across models. Experimental dissection of acute and chronic viral infection using single-cell ATAC (scATAC)-seq and allele-specific single-cell RNA (scRNA)-seq identified state-specific drivers and captured the emergence of similar TCF1+ progenitor-like populations at an early branch point, at which functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

Signatures of plasticity and immunosuppression in a single-cell atlas of human small cell lung cancer

8509

Background: Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. The emerging consensus on SCLC subtypes has led to new questions, such as whether subtypes are associated with different disease stages, metastatic potential, or immune microenvironments; whether there is plasticity between subtypes; and whether novel SCLC phenotypes exist. Single cell RNA sequencing (scRNA-seq) offers a unique opportunity to address these questions by dissecting intratumoral transcriptional heterogeneity and the surrounding tumor microenvironment (TME). However, efforts to apply this technology to human SCLC tumors have been limited, as these tumors are infrequently resected. Methods: We have optimized protocols to process both surgical resections and biopsies to construct the first single-cell atlas of SCLC patient tumors (N = 21), with comparative lung adenocarcinoma (LUAD) and normal lung data. We leverage computational methods including diffusion maps and non-negative matrix factorization to perform a deep annotation of SCLC phenotypes and the surrounding immune TME. We perform validation experiments using flow cytometry, Vectra, and immunohistochemistry in independent SCLC cohorts, as well as genetic manipulation in preclinical SCLC models. Results: Our data reveals substantial transcriptional heterogeneity in SCLC both within and across tumors and confirms a pro-metastatic gene program in SCLC-N subtype characterized by epithelial-mesenchymal transformation and axonogenesis. Beyond known subtypes, we discover a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts significantly worse overall survival. Manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis. Conclusions: This atlas of SCLC illustrates how canonical subtypes and a novel PLCG2-high recurrent tumor subclone enlist diverse gene programs to create tumor heterogeneity and facilitate metastasis in a profoundly immunosuppressed TME. Our dataset provides further insight into tumor and immune biology in SCLC at single-cell resolution, with potential implications for design of novel targeted therapies and immunotherapeutic approaches.

Abstract LT008: Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy

Immune therapies have transformed the cancer therapeutic landscape but fail to benefit most patients. To elucidate the underlying mechanisms by which T cells mediate elimination of leukemia, we generated a high-resolution map of longitudinal T cell dynamics within the same tumor microenvironment (TME; bone marrow) during response or resistance to donor lymphocyte infusion (DLI), a widely used immunotherapy for relapsed leukemia. We analyzed 87,939 bone marrow-derived single T cell transcriptomes, along with chromatin accessibility and single T cell receptor clonality profiles, by developing novel machine learning tools for integrating longitudinal and multimodal data. We found that pre-treatment enrichment and post-treatment rapid, durable expansion of ‘terminal’ (TEX) and ‘precursor’ (TPEX) exhausted subsets, respectively, defined DLI response. In contrast to the common, shared pathways marking DLI response, a heterogeneous pattern of T cell dysfunction marked DLI resistance. Unexpectedly, TPEX cells that expanded in responders did not arise from the infusion product but instead from both pre-existing and novel clonotypes recruited to the TME. Further, we introduce a Bayesian method, Symphony, to define the T cell regulatory circuitry and master regulators underlying TEX and TPEX subsets that may be broadly relevant to other exhaustion antagonists across cancers. In conclusion, our data implicate the hierarchy of both TEX and TPEX subsets for immunotherapeutic responses in leukemia, extending the scope of their relevance beyond checkpoint blockade to adoptive cellular therapy. Moreover, our results provocatively suggest that immunologic ‘help’ from DLI, rather than direct transfer of anti-leukemic T cells, drove leukemic remission. Finally, we provide a general analysis paradigm for exploiting temporal single-cell genomic profiling for deep understanding of how immune therapies differentially shape the evolutionary trajectories of the TME in accordance with clinical outcome.

Citation Format: Pavan Bachireddy, Elham Azizi, Cassandra Burdziak, Vinhkhang Nguyen, Christina Ennis, Zi- Ning Choo, Shuqiang Li, Kenneth Livak, Donna Neuberg, Robert Soiffer, Jerome Ritz, Edwin Alyea, Dana Pe'er, Catherine Wu. Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr LT008.

A gene-environment-induced epigenetic program initiates tumorigenesis

Tissue damage increases the risk of cancer through poorly understood mechanisms1. In mouse models of pancreatic cancer, pancreatitis associated with tissue injury collaborates with activating mutations in the Kras oncogene to markedly accelerate the formation of early neoplastic lesions and, ultimately, adenocarcinoma2,3. Here, by integrating genomics, single-cell chromatin assays and spatiotemporally controlled functional perturbations in autochthonous mouse models, we show that the combination of Kras mutation and tissue damage promotes a unique chromatin state in the pancreatic epithelium that distinguishes neoplastic transformation from normal regeneration and is selected for throughout malignant evolution. This cancer-associated epigenetic state emerges within 48 hours of pancreatic injury, and involves an 'acinar-to-neoplasia' chromatin switch that contributes to the early dysregulation of genes that define human pancreatic cancer. Among the factors that are most rapidly activated after tissue damage in the pre-malignant pancreatic epithelium is the alarmin cytokine interleukin 33, which recapitulates the effects of injury in cooperating with mutant Kras to unleash the epigenetic remodelling program of early neoplasia and neoplastic transformation. Collectively, our study demonstrates how gene-environment interactions can rapidly produce gene-regulatory programs that dictate early neoplastic commitment, and provides a molecular framework for understanding the interplay between genetic and environmental cues in the initiation of cancer.

A Single-Cell Atlas of the Human Healthy Airways

Rationale: The respiratory tract constitutes an elaborate line of defense that is based on a unique cellular ecosystem.Objectives: We aimed to investigate cell population distributions and transcriptional changes along the airways by using single-cell RNA profiling.Methods: We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. A total of 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree.Measurements and Main Results: The resulting atlas is composed of a high percentage of epithelial cells (89.1%) but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type-specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine cells, and brush cells and identifies a related population of NREP-positive cells. We also report the association of KRT13 with dividing cells that are reminiscent of previously described mouse "hillock" cells and with squamous cells expressing SCEL and SPRR1A/B.Conclusions: Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

Frontiers in cancer immunotherapy-a symposium report

Cancer immunotherapy has dramatically changed the approach to cancer treatment. The aim of targeting the immune system to recognize and destroy cancer cells has afforded many patients the prospect of achieving deep, long-term remission and potential cures. However, many challenges remain for achieving the goal of effective immunotherapy for all cancer patients. Checkpoint inhibitors have been able to achieve long-term responses in a minority of patients, yet improving response rates with combination therapies increases the possibility of toxicity. Chimeric antigen receptor T cells have demonstrated high response rates in hematological cancers, although most patients experience relapse. In addition, some cancers are notoriously immunologically "cold" and typically are not effective targets for immunotherapy. Overcoming these obstacles will require new strategies to improve upon the efficacy of current agents, identify biomarkers to select appropriate therapies, and discover new modalities to expand the accessibility of immunotherapy to additional tumor types and patient populations.

Single-Cell Transcriptomics Reveals Early Emergence of Liver Parenchymal and Non-parenchymal Cell Lineages

The cellular complexity and scale of the early liver have constrained analyses examining its emergence during organogenesis. To circumvent these issues, we analyzed 45,334 single-cell transcriptomes from embryonic day (E)7.5, when endoderm progenitors are specified, to E10.5 liver, when liver parenchymal and non-parenchymal cell lineages emerge. Our data detail divergence of vascular and sinusoidal endothelia, including a distinct transcriptional profile for sinusoidal endothelial specification by E8.75. We characterize two distinct mesothelial cell types as well as early hepatic stellate cells and reveal distinct spatiotemporal distributions for these populations. We capture transcriptional profiles for hepatoblast specification and migration, including the emergence of a hepatomesenchymal cell type and evidence for hepatoblast collective cell migration. Further, we identify cell-cell interactions during the organization of the primitive sinusoid. This study provides a comprehensive atlas of liver lineage establishment from the endoderm and mesoderm through to the organization of the primitive sinusoid at single-cell resolution.

Abstract 5722: Acquired stemness by luminal cells

Rare cell types in the prostate are reported to have stem cell properties based on organ regeneration potential following castration. Here, we use single cell RNA-seq (scRNA-Seq) to characterize these populations from the murine and human prostate in hormonally intact and androgen deprived conditions. Prostate cells from hormonally intact mice partitioned into one large subset of basal epithelial cells, another large subset of luminal epithelial cells, which we designate luminal 1 and two rare luminal populations: luminal 2 and luminal 3. Luminal cells that persist following castration display enhanced organoid regeneration potential, particularly within 1-2 days of androgen addback, and contribute equipotently to prostatic regeneration as revealed by lineage tracing. This regeneration is mediated, in part, through the orchestrated expression of Nrg2, Igf1, Fgf10 and Rspo3 by distinct populations of androgen-responsive mesenchymal and smooth muscle cells. Thus, luminal cells that persist post-castration undergo a cell state change that primes a proliferative response to microenvironment signals, analogous to other models of tissue injury such as liver damage.

Citation Format: Wouter Karthaus, Matan Hofree, Danielle Choi, Eliot L. Linton, Mesruh Turkekul, Alborz Bejnood, Brett Carver, Anuhandra Gopalan, Vincent Laudone, Moshe Biton, Ojasvi Chaudhary, Ignas Masilionis, Linas Mazutis, Dana Pe'er, Aviv Regev, Charles Sawyers. Acquired stemness by luminal cells [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 5722.

Cancer cells deploy lipocalin-2 to collect limiting iron in leptomeningeal metastasis

The tumor microenvironment plays a critical regulatory role in cancer progression, especially in central nervous system metastases. Cancer cells within the cerebrospinal fluid (CSF)-filled leptomeninges face substantial microenvironmental challenges, including inflammation and sparse micronutrients. To investigate the mechanism by which cancer cells in these leptomeningeal metastases (LM) overcome these constraints, we subjected CSF from five patients with LM to single-cell RNA sequencing. We found that cancer cells, but not macrophages, within the CSF express the iron-binding protein lipocalin-2 (LCN2) and its receptor SCL22A17. These macrophages generate inflammatory cytokines that induce cancer cell LCN2 expression but do not generate LCN2 themselves. In mouse models of LM, cancer cell growth is supported by the LCN2/SLC22A17 system and is inhibited by iron chelation therapy. Thus, cancer cells appear to survive in the CSF by outcompeting macrophages for iron.

Publisher Correction: Lineage plasticity in cancer: a shared pathway of therapeutic resistance

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tumor Analyses Reveal Squamous Transformation and Off-Target Alterations As Early Resistance Mechanisms to First-line Osimertinib in EGFR-Mutant Lung Cancer

PURPOSE

Patterns of resistance to first-line osimertinib are not well-established and have primarily been evaluated using plasma assays, which cannot detect histologic transformation and have differential sensitivity for copy number changes and chromosomal rearrangements.

EXPERIMENTAL DESIGN

To characterize mechanisms of resistance to osimertinib, patients with metastatic EGFR-mutant lung cancers who received osimertinib at Memorial Sloan Kettering Cancer Center and had next-generation sequencing performed on tumor tissue before osimertinib initiation and after progression were identified.

RESULTS

Among 62 patients who met eligibility criteria, histologic transformation, primarily squamous transformation, was identified in 15% of first-line osimertinib cases and 14% of later-line cases. Nineteen percent (5/27) of patients treated with first-line osimertinib had off-target genetic resistance (2 MET amplification, 1 KRAS mutation, 1 RET fusion, and 1 BRAF fusion) whereas 4% (1/27) had an acquired EGFR mutation (EGFR G724S). Patients with squamous transformation exhibited considerable genomic complexity; acquired PIK3CA mutation, chromosome 3q amplification, and FGF amplification were all seen. Patients with transformation had shorter time on osimertinib and shorter survival compared with patients with on-target resistance. Initial EGFR sensitizing mutation, time on osimertinib treatment, and line of therapy also influenced resistance mechanism that emerged. The compound mutation EGFR S768 + V769L and the mutation MET H1094Y were identified and validated as resistance mechanisms with potential treatment options.

CONCLUSIONS

Histologic transformation and other off-target molecular alterations are frequent early emerging resistance mechanisms to osimertinib and are associated with poor clinical outcomes.See related commentary by Piotrowska and Hata, p. 2441.

Regenerative potential of prostate luminal cells revealed by single-cell analysis

Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1 ⁺ and Psca ⁺) and a large population of differentiated cells (Nkx3.1 ⁺, Pbsn ⁺). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells.

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

Adult Human Glioblastomas Harbor Radial Glia-like Cells

Radial glia (RG) cells are the first neural stem cells to appear during embryonic development. Adult human glioblastomas harbor a subpopulation of RG-like cells with typical RG morphology and markers. The cells exhibit the classic and unique mitotic behavior of normal RG in a cell-autonomous manner. Single-cell RNA sequencing analyses of glioblastoma cells reveal transcriptionally dynamic clusters of RG-like cells that share the profiles of normal human fetal radial glia and that reside in quiescent and cycling states. Functional assays show a role for interleukin in triggering exit from dormancy into active cycling, suggesting a role for inflammation in tumor progression. These data are consistent with the possibility of persistence of RG into adulthood and their involvement in tumor initiation or maintenance. They also provide a putative cellular basis for the persistence of normal developmental programs in adult tumors.

Regenerative lineages and immune-mediated pruning in lung cancer metastasis

Developmental processes underlying normal tissue regeneration have been implicated in cancer, but the degree of their enactment during tumor progression and under the selective pressures of immune surveillance, remain unknown. Here, we show that human primary lung adenocarcinomas are characterized by the emergence of regenerative cell types typically seen in response to lung injury, and by striking infidelity amongst transcription factors specifying most alveolar and bronchial epithelial lineages. In contrast, metastases are enriched for key endoderm and lung-specifying transcription factors, SOX2 and SOX9, and recapitulate more primitive transcriptional programs spanning stem-like to regenerative pulmonary epithelial progenitor states. This developmental continuum mirrors the progressive stages of spontaneous outbreak from metastatic dormancy in a mouse model and exhibits SOX9-dependent resistance to Natural Killer (NK) cells. Loss of developmental stage-specific constraint in macrometastases triggered by NK cell depletion suggests a dynamic interplay between developmental plasticity and immune-mediated pruning during metastasis.