Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Lesions

The adult healthy human pancreas has been poorly studied given the lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors, thus avoiding any warm ischemia time. The 30 donors were diverse in age and race and had no known pancreas disease. Histopathologic analysis of the samples revealed pancreatic intraepithelial neoplasia (PanIN) lesions in most individuals irrespective of age. Using a combination of multiplex IHC, single-cell RNA sequencing, and spatial transcriptomics, we provide the first-ever characterization of the unique microenvironment of the adult human pancreas and of sporadic PanIN lesions. We compared healthy pancreata to pancreatic cancer and peritumoral tissue and observed distinct transcriptomic signatures in fibroblasts and, to a lesser extent, macrophages. PanIN epithelial cells from healthy pancreata were remarkably transcriptionally similar to cancer cells, suggesting that neoplastic pathways are initiated early in tumorigenesis.

SIGNIFICANCE

Precursor lesions to pancreatic cancer are poorly characterized. We analyzed donor pancreata and discovered that precursor lesions are detected at a much higher rate than the incidence of pancreatic cancer, setting the stage for efforts to elucidate the microenvironmental and cell-intrinsic factors that restrain or, conversely, promote malignant progression. See related commentary by Hoffman and Dougan, p. 1288. This article is highlighted in the In This Issue feature, p. 1275.

KRT17high/CXCL8+ Tumor Cells Display Both Classical and Basal Features and Regulate Myeloid Infiltration in the Pancreatic Cancer Microenvironment

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is generally divided in two subtypes, classical and basal. Recently, single-cell RNA sequencing has uncovered the coexistence of basal and classical cancer cells, as well as intermediary cancer cells, in individual tumors. The latter remains poorly understood; here, we sought to characterize them using a multimodal approach.

EXPERIMENTAL DESIGN

We performed subtyping on a single-cell RNA sequencing dataset containing 18 human PDAC samples to identify multiple intermediary subtypes. We generated patient-derived PDAC organoids for functional studies. We compared single-cell profiling of matched blood and tumor samples to measure changes in the local and systemic immune microenvironment. We then leveraged longitudinally patient-matched blood to follow individual patients over the course of chemotherapy.

RESULTS

We identified a cluster of KRT17-high intermediary cancer cells that uniquely express high levels of CXCL8 and other cytokines. The proportion of KRT17high/CXCL8+ cells in patient tumors correlated with intratumoral myeloid abundance, and, interestingly, high protumor peripheral blood granulocytes, implicating local and systemic roles. Patient-derived organoids maintained KRT17high/CXCL8+ cells and induced myeloid cell migration in a CXCL8-dependent manner. In our longitudinal studies, plasma CXCL8 decreased following chemotherapy in responsive patients, while CXCL8 persistence portended worse prognosis.

CONCLUSIONS

Through single-cell analysis of PDAC samples, we identified KRT17high/CXCL8+ cancer cells as an intermediary subtype, marked by a unique cytokine profile and capable of influencing myeloid cells in the tumor microenvironment and systemically. The abundance of this cell population should be considered for patient stratification in precision immunotherapy. See related commentary by Faraoni and McAllister, p. 2297.

Using Single Cell Transcriptomics to Elucidate the Myeloid Compartment in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dismal disease with a 5-year survival rate of 10%. A hallmark feature of this disease is its abundant microenvironment which creates a highly immunosuppressive milieu. This is, in large part, mediated by an abundant infiltration of myeloid cells in the PDAC tumor microenvironment. Consequently, therapies that modulate myeloid function may augment the efficacy of standard of care for PDAC. Unfortunately, there is limited understanding about the various subsets of myeloid cells in PDAC, particularly in human studies. This review highlights the application of single-cell RNA sequencing to define the myeloid compartment in human PDAC and elucidate the crosstalk between myeloid cells and the other components of the tumor immune microenvironment.

Metabolic landscape of the healthy pancreas and pancreatic tumor microenvironment

Pancreatic cancer, one of the deadliest human malignancies, is characterized by a fibro-inflammatory tumor microenvironment and wide array of metabolic alterations. To comprehensively map metabolism in a cell type-specific manner, we harnessed a unique single-cell RNA-sequencing dataset of normal human pancreata. This was compared with human pancreatic cancer samples using a computational pipeline optimized for this study. In the cancer cells we observed enhanced biosynthetic programs. We identified downregulation of mitochondrial programs in several immune populations, relative to their normal counterparts in healthy pancreas. Although granulocytes, B cells, and CD8+ T cells all downregulated oxidative phosphorylation, the mechanisms by which this occurred were cell type specific. In fact, the expression pattern of the electron transport chain complexes was sufficient to identify immune cell types without the use of lineage markers. We also observed changes in tumor-associated macrophage (TAM) lipid metabolism, with increased expression of enzymes mediating unsaturated fatty acid synthesis and upregulation in cholesterol export. Concurrently, cancer cells exhibited upregulation of lipid/cholesterol receptor import. We thus identified a potential crosstalk whereby TAMs provide cholesterol to cancer cells. We suggest that this may be a new mechanism boosting cancer cell growth and a therapeutic target in the future.

Abstract A006: Integrating single cell and spatial transcriptomics define gene signature for pancreatic ductal adenocarcinoma pre-neoplastic lesion

Pancreatic Cancer Ductal Adenocarcinoma (PDAC) is one of the deadliest cancers with 5-year survival of 11%. Understanding the intratumor heterogeneity is a pivotal piece to unravel the complexity of PDAC. While single cell RNASeq identifies the heterogeneous cell populations within the tumor tissue, spatially characterizing the transcriptomic profile of neoplastic and pre-neoplastic populations within the tissue remains a challenge, as the spatial dimension is usually lost upon tissue dissociation. We identified an approach to integrate spatial transcriptomics data with single cell RNASeq data. To characterize the cell populations within the tissue we performed single cell RNASeq on disease pathology-free pancreas tissue and primary PDAC samples. We profiled the transcriptomic profile of Acinar, Ductal, Acinar-to-Ductal (ADM), and Pancreatic Intraepithelial Neoplasia (PanINs) regions of interest (ROIs) across the tissue using the Nanostring GeoMx platform. Differential gene expression analysis using linear mixed-effect models of the cell-type specific ROIs defined pan-marker gene sets for each cell type, which were mapped to UMAP projections of single cell RNA sequencing data using AUCell scoring. As expected, the acinar pan-markers gene set derived from the spatial transcriptomics mapped to the manually annotated acinar population in the single cell data. On the other hand, Ductal, ADM, and PanIN pan-marker gene sets were mapped to distinct clusters that previously were not well-defined by single cell sequencing. The analysis coupled with orthogonal validation using RNAScope revealed gene signatures uniquely specific to ADM lesions and PanINs, respectively. Interestingly, our list included known markers as well as novel findings, supporting the validity of the findings. Furthermore, RNA velocity analysis using scVelo revealed a trajectory of cell evolution originating from acinar cells passing through the newly-defined ADM population and ending towards the ductal population derived from tumor samples. Overall, this integration approach of spatial and single cell transcriptomics can further define the characteristics that differentiate neoplastic and pre-neoplastic populations, as well as the potential drivers for tumorigenesis that could be therapeutically targeted.

Citation Format: Ahmed M. Elhossiny, Eileen Carpenter, Padma Kadiyala, Yaqing Zhang, Filip Bednar, Arvind Rao, Timothy Frankel, Marina Pasca Di Magliano. Integrating single cell and spatial transcriptomics define gene signature for pancreatic ductal adenocarcinoma pre-neoplastic lesion [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 A006.

Oncogenic KRAS-Dependent Stromal Interleukin-33 Directs the Pancreatic Microenvironment to Promote Tumor Growth

Pancreatic cancer is characterized by an extensive fibroinflammatory microenvironment. During carcinogenesis, normal stromal cells are converted to cytokine-high cancer-associated fibroblasts (CAF). The mechanisms underlying this conversion, including the regulation and function of fibroblast-derived cytokines, are poorly understood. Thus, efforts to therapeutically target CAFs have so far failed. Herein, we show that signals from epithelial cells expressing oncogenic KRAS-a hallmark pancreatic cancer mutation-activate fibroblast autocrine signaling, which drives the expression of the cytokine IL33. Stromal IL33 expression remains high and dependent on epithelial KRAS throughout carcinogenesis; in turn, environmental stress induces interleukin-33 (IL33) secretion. Using compartment-specific IL33 knockout mice, we observed that lack of stromal IL33 leads to profound reprogramming of multiple components of the pancreatic tumor microenvironment, including CAFs, myeloid cells, and lymphocytes. Notably, loss of stromal IL33 leads to an increase in CD8+ T-cell infiltration and activation and, ultimately, reduced tumor growth. Significance: This study provides new insights into the mechanisms underlying the programming of CAFs and shows that during this process, expression of the cytokine IL33 is induced. CAF-derived IL33 has pleiotropic effects on the tumor microenvironment, supporting its potential as a therapeutic target.

Immune heterogeneity in small-cell lung cancer and vulnerability to immune checkpoint blockade

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.

Proximogram-A multi-omics network-based framework to capture tissue heterogeneity integrating single-cell omics and spatial profiling

The increasing availability of patient-derived multimodal biological data for various diseases has opened up avenues for finding the optimal methods for jointly leveraging the information extracted in a customizable and scalable manner. Here, we propose the Proximogram, a graph-based representation that provides a joint construct for embedding independently obtained omics and spatial data. To evaluate the representation, we generated proximograms from 2 distinct biological sources, namely, multiplexed immunofluorescence images and single-cell RNA-seq data obtained from patients across two pancreatic diseases that include normal and chronic Pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC). The generated proximograms were used as inputs to 2 distinct graph deep-learning models. The improved classification results over simpler spatial-data-based input graphs point to the increased discriminatory power obtained by integrating structural information from single-cell ligand-receptor signaling data and the spatial architecture of cells in each disease class, which can help point to markers of high diagnostic significance.

Analysis of donor pancreata defines the transcriptomic signature and microenvironment of early pre-neoplastic pancreatic lesions

The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. The 30 donors were diverse in age and race and had no known pancreas disease. Histopathological analysis of the samples revealed PanIN lesions in most individuals irrespective of age. Using a combination of multiplex immunohistochemistry, single cell RNA sequencing, and spatial transcriptomics, we provide the first ever characterization of the unique microenvironment of the adult human pancreas and of sporadic PanIN lesions. We compared healthy pancreata to pancreatic cancer and peritumoral tissue and observed distinct transcriptomic signatures in fibroblasts, and, to a lesser extent, macrophages. PanIN epithelial cells from healthy pancreata were remarkably transcriptionally similar to cancer cells, suggesting that neoplastic pathways are initiated early in tumorigenesis.

Statement of significance

The causes underlying the onset of pancreatic cancer remain largely unknown, hampering early detection and prevention strategies. Here, we show that PanIN are abundant in healthy individuals and present at a much higher rate than the incidence of pancreatic cancer, setting the stage for efforts to elucidate the microenvironmental and cell intrinsic factors that restrain, or, conversely, promote, malignant progression.