It is better to light a candle than to curse the darkness: single-cell transcriptomics sheds new light on pancreas biology and disease

Metabolic reprogramming by mutant GNAS creates an actionable dependency in intraductal papillary mucinous neoplasms of the pancreas

BACKGROUND

Oncogenic 'hotspot' mutations of KRAS and GNAS are two major driver alterations in intraductal papillary mucinous neoplasms (IPMNs), which are bona fide precursors to pancreatic ductal adenocarcinoma. We previously reported that pancreas-specific Kras G12D and Gnas R201C co-expression in p48Cre; KrasLSL-G12D; Rosa26LSL-rtTA; Tg (TetO-GnasR201C) mice ('Kras;Gnas' mice) caused development of cystic lesions recapitulating IPMNs.

OBJECTIVE

We aim to unveil the consequences of mutant Gnas R201C expression on phenotype, transcriptomic profile and genomic dependencies.

DESIGN

We performed multimodal transcriptional profiling (bulk RNA sequencing, single-cell RNA sequencing and spatial transcriptomics) in the 'Kras;Gnas' autochthonous model and tumour-derived cell lines (Kras;Gnas cells), where Gnas R201C expression is inducible. A genome-wide CRISPR/Cas9 screen was conducted to identify potential vulnerabilities in KrasG12D;GnasR201C co-expressing cells.

RESULTS

Induction of Gnas R201C-and resulting G(s)alpha signalling-leads to the emergence of a gene signature of gastric (pyloric type) metaplasia in pancreatic neoplastic epithelial cells. CRISPR screening identified the synthetic essentiality of glycolysis-related genes Gpi1 and Slc2a1 in Kras G12D;Gnas R201C co-expressing cells. Real-time metabolic analyses in Kras;Gnas cells and autochthonous Kras;Gnas model confirmed enhanced glycolysis on Gnas R201C induction. Induction of Gnas R201C made Kras G12D expressing cells more dependent on glycolysis for their survival. Protein kinase A-dependent phosphorylation of the glycolytic intermediate enzyme 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) was a driver of increased glycolysis on Gnas R201C induction.

CONCLUSION

Multiple orthogonal approaches demonstrate that Kras G12D and Gnas R201C co-expression results in a gene signature of gastric pyloric metaplasia and glycolytic dependency during IPMN pathogenesis. The observed metabolic reprogramming may provide a potential target for therapeutics and interception of IPMNs.

ROR2 Regulates Cellular Plasticity in Pancreatic Neoplasia and Adenocarcinoma

Cellular plasticity is a hallmark of pancreatic ductal adenocarcinoma (PDAC) starting from the conversion of normal cells into precancerous lesions, to the progression of carcinoma subtypes associated with aggressiveness and therapeutic response. We discovered that normal acinar cell differentiation, maintained by the transcription factor PDX1, suppresses a broad gastric cell identity that is maintained in metaplasia, neoplasia, and the classical subtype of PDAC in a mouse and human. We identified the receptor tyrosine kinase ROR2 as marker of a gastric metaplasia-like identity in pancreas neoplasms. Ablation of Ror2 in a mouse model of pancreatic tumorigenesis promoted a switch to a gastric pit cell identity that largely persisted through progression to the classical subtype of PDAC. In both human and mouse pancreatic cancer, ROR2 activity continued to antagonize the gastric pit cell identity, strongly promoting an epithelial to mesenchymal transition, conferring resistance to KRAS inhibition, and vulnerability to AKT inhibition. Significance: We discovered the receptor tyrosine kinase ROR2 as an important regulator of cellular identity in pancreatic precancerous lesions and pancreatic cancer. ROR2 drives an aggressive PDAC phenotype and confers resistance to KRAS inhibitors, suggesting that targeting ROR2 will enhance sensitivity to this new generation of targeted therapies. See related commentary by Marasco and Misale, p. 2018.

Defining precancer: a grand challenge for the cancer community

The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.

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.

scMGCN: A Multi-View Graph Convolutional Network for Cell Type Identification in scRNA-seq Data

Single-cell RNA sequencing (scRNA-seq) data reveal the complexity and diversity of cellular ecosystems and molecular interactions in various biomedical research. Hence, identifying cell types from large-scale scRNA-seq data using existing annotations is challenging and requires stable and interpretable methods. However, the current cell type identification methods have limited performance, mainly due to the intrinsic heterogeneity among cell populations and extrinsic differences between datasets. Here, we present a robust graph artificial intelligence model, a multi-view graph convolutional network model (scMGCN) that integrates multiple graph structures from raw scRNA-seq data and applies graph convolutional networks with attention mechanisms to learn cell embeddings and predict cell labels. We evaluate our model on single-dataset, cross-species, and cross-platform experiments and compare it with other state-of-the-art methods. Our results show that scMGCN outperforms the other methods regarding stability, accuracy, and robustness to batch effects. Our main contributions are as follows: Firstly, we introduce multi-view learning and multiple graph construction methods to capture comprehensive cellular information from scRNA-seq data. Secondly, we construct a scMGCN that combines graph convolutional networks with attention mechanisms to extract shared, high-order information from cells. Finally, we demonstrate the effectiveness and superiority of the scMGCN on various datasets.

ROR2 regulates cellular plasticity in pancreatic neoplasia and adenocarcinoma

Cellular plasticity is a hallmark of pancreatic ductal adenocarcinoma (PDAC) starting from the conversion of normal cells into precancerous lesions to the progression of carcinoma subtypes associated with aggressiveness and therapeutic response. We discovered that normal acinar cell differentiation, maintained by the transcription factor Pdx1, suppresses a broad gastric cell identity that is maintained in metaplasia, neoplasia, and the classical subtype of PDAC in mouse and human. We have identified the receptor tyrosine kinase Ror2 as marker of a gastric metaplasia (SPEM)-like identity in the pancreas. Ablation of Ror2 in a mouse model of pancreatic tumorigenesis promoted a switch to a gastric pit cell identity that largely persisted through progression to the classical subtype of PDAC. In both human and mouse pancreatic cancer, ROR2 activity continued to antagonize the gastric pit cell identity, strongly promoting an epithelial to mesenchymal transition, conferring resistance to KRAS inhibition, and vulnerability to AKT inhibition.

Imaging in Type 1 Diabetes, Current Perspectives and Directions

Type 1 diabetes (T1D) is characterized by the autoimmune-mediated attack of insulin-producing beta cells in the pancreas, leading to reliance on exogenous insulin to control a patient's blood glucose levels. As progress is being made in understanding the pathophysiology of the disease and how to better develop therapies to treat it, there is an increasing need for monitoring technologies to quantify beta cell mass and function throughout T1D progression and beta cell replacement therapy. Molecular imaging techniques offer a possible solution through both radiologic and non-radiologic means including positron emission tomography, magnetic resonance imaging, electron paramagnetic resonance imaging, and spatial omics. This commentary piece outlines the role of molecular imaging in T1D research and highlights the need for further applications of such methodologies in T1D.

Reorganization of pancreas circadian transcriptome with aging

The evolutionarily conserved circadian system allows organisms to synchronize internal processes with 24-h cycling environmental timing cues, ensuring optimal adaptation. Like other organs, the pancreas function is under circadian control. Recent evidence suggests that aging by itself is associated with altered circadian homeostasis in different tissues which could affect the organ's resiliency to aging-related pathologies. Pancreas pathologies of either endocrine or exocrine components are age-related. Whether pancreas circadian transcriptome output is affected by age is still unknown. To address this, here we profiled the impact of age on the pancreatic transcriptome over a full circadian cycle and elucidated a circadian transcriptome reorganization of pancreas by aging. Our study highlights gain of rhythms in the extrinsic cellular pathways in the aged pancreas and extends a potential role to fibroblast-associated mechanisms.