Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration.

Background: The development of diverse spatial profiling technologies has provided an unprecedented insight into molecular mechanisms driving cancer pathogenesis. Here, we conducted the first integrated cross-species assessment of spatial transcriptomics and spatial metabolomics alterations associated with progression of intraductal papillary mucinous neoplasms (IPMN), bona fide cystic precursors of pancreatic ductal adenocarcinoma (PDAC). Methods: Matrix Assisted Laster Desorption/Ionization (MALDI) mass spectrometry (MS)-based spatial imaging and Visium spatial transcriptomics (ST) (10X Genomics) was performed on human resected IPMN tissues (N= 23) as well as pancreata from a mutant Kras;Gnas mouse model of IPMN. Findings were further compared with lipidomic analyses of cystic fluid from 89 patients with histologically confirmed IPMNs, as well as single-cell and bulk transcriptomic data of PDAC and normal tissues. Results: MALDI-MS analyses of IPMN tissues revealed long-chain hydroxylated sulfatides, particularly the C24:0(OH) and C24:1(OH) species, to be selectively enriched in the IPMN and PDAC neoplastic epithelium. Integrated ST analyses confirmed that the cognate transcripts engaged in sulfatide biosynthesis, including UGT8, Gal3St1 , and FA2H , were co-localized with areas of sulfatide enrichment. Lipidomic analyses of cystic fluid identified several sulfatide species, including the C24:0(OH) and C24:1(OH) species, to be significantly elevated in patients with IPMN/PDAC compared to those with low-grade IPMN. Targeting of sulfatide metabolism via the selective galactosylceramide synthase inhibitor, UGT8-IN-1, resulted in ceramide-induced lethal mitophagy and subsequent cancer cell death in vitro , and attenuated tumor growth of mutant Kras;Gnas allografts. Transcript levels of UGT8 and FA2H were also selectively enriched in PDAC transcriptomic datasets compared to non-cancerous areas, and elevated tumoral UGT8 was prognostic for poor overall survival. Conclusion: Enhanced sulfatide metabolism is an early metabolic alteration in cystic pre-cancerous lesions of the pancreas that persists through invasive neoplasia. Targeting sulfatide biosynthesis might represent an actionable vulnerability for cancer interception.

Spatial Transcriptomics of Intraductal Papillary Mucinous Neoplasms of the Pancreas Identifies NKX6-2 as a Driver of Gastric Differentiation and Indolent Biological Potential.

Intraductal papillary mucinous neoplasms (IPMN) of the pancreas are bona fide precursor lesions of pancreatic ductal adenocarcinoma (PDAC). The most common subtype of IPMNs harbors a gastric foveolar-type epithelium, and these low-grade mucinous neoplasms are harbingers of IPMNs with high-grade dysplasia and cancer. The molecular underpinning of gastric differentiation in IPMNs is unknown, although identifying drivers of this indolent phenotype might enable opportunities for intercepting progression to high-grade IPMN and cancer. We conducted spatial transcriptomics on a cohort of IPMNs, followed by orthogonal and cross-species validation studies, which established the transcription factor NKX6-2 as a key determinant of gastric cell identity in low-grade IPMNs. Loss of NKX6-2 expression is a consistent feature of IPMN progression, while reexpression of Nkx6-2 in murine IPMN lines recapitulates the aforementioned gastric transcriptional program and glandular morphology. Our study identifies NKX6-2 as a previously unknown transcription factor driving indolent gastric differentiation in IPMN pathogenesis. SIGNIFICANCE: Identification of the molecular features driving IPMN development and differentiation is critical to prevent cancer progression and enhance risk stratification. We used spatial profiling to characterize the epithelium and microenvironment of IPMN, which revealed a previously unknown link between NKX6-2 and gastric differentiation, the latter associated with indolent biological potential. See related commentary by Ben-Shmuel and Scherz-Shouval, p. 1768. This article is highlighted in the In This Issue feature, p. 1749.

Adar1 deletion causes degeneration of the exocrine pancreas via Mavs-dependent interferon signaling.

Adenosine deaminase acting on RNA 1 (ADAR1) is an RNA-binding protein that deaminates adenosine (A) to inosine (I). A-to-I editing alters post-transcriptional RNA processing, making ADAR1 a crucial regulator of gene expression. Consequently, Adar1 has been implicated in organogenesis. To determine the role of Adar1 in pancreatic development and homeostasis, we conditionally deleted Adar1 from the murine pancreas (Ptf1aCre/+; Adar1Fl/Fl). The resulting mice had stunted growth, likely due to malabsorption associated with exocrine pancreatic insufficiency. Analyses of pancreata revealed ductal cell expansion, heightened interferon-stimulated gene expression and an increased influx of immune cells. Concurrent deletion of Adar1 and Mavs, a signaling protein implicated in the innate immune pathway, rescued the degenerative phenotype and resulted in normal pancreatic development. Taken together, our work suggests that the primary function of Adar1 in the pancreas is to prevent aberrant activation of the Mavs-mediated innate immune pathway, thereby maintaining pancreatic homeostasis.

A Programmable In Vivo CRISPR Activation Model Elucidates the Oncogenic and Immunosuppressive Functions of MYC in Lung Adenocarcinoma.

Conventional genetically engineered mouse models (GEMM) are time-consuming, laborious, and offer limited spatiotemporal control. Here, we describe the development of a streamlined platform for in vivo gene activation using CRISPR activation (CRISPRa) technology. Unlike conventional GEMMs, this model system allows for flexible, sustained, and timed activation of one or more target genes using single or pooled lentiviral guides. Myc and Yap1 were used as model oncogenes to demonstrate gene activation in primary pancreatic organoid cultures in vitro and enhanced tumorigenic potential in Myc-activated organoids when transplanted orthotopically in vivo. Implementation of this model as an autochthonous lung cancer model showed that transduction-mediated activation of Myc led to accelerated tumor progression and significantly reduced overall survival relative to nontargeted tumor controls. Furthermore, Myc activation led to the acquisition of an immune suppressive, "cold" tumor microenvironment. Cross-species validation of these results using publicly available RNA/DNA-seq datasets linked MYC to a previously described immunosuppressive molecular subtype in patient tumors, thus identifying a patient cohort that may benefit from combined MYC- and immune-targeted therapies. Overall, this work demonstrates how CRISPRa can be used for rapid functional validation of putative oncogenes and may allow for the identification and evaluation of potential metastatic and oncogenic drivers through competitive screening. SIGNIFICANCE: A streamlined platform for programmable CRISPR gene activation enables rapid evaluation and functional validation of putative oncogenes in vivo.

Acquired chemoresistance drives spatial heterogeneity, chemoprotection and collective migration in pancreatic tumor spheroids.

Tumors display rich cellular heterogeneity and typically consist of multiple co-existing clones with distinct genotypic and phenotypic characteristics. The acquisition of resistance to chemotherapy has been shown to contribute to the development of aggressive cancer traits, such as increased migration, invasion and stemness. It has been hypothesized that collective cellular behavior and cooperation of cancer cell populations may directly contribute to disease progression and lack of response to treatment. Here we show that the spontaneous emergence of chemoresistance in a cancer cell population exposed to the selective pressure of a chemotherapeutic agent can result in the emergence of collective cell behavior, including cell-sorting, chemoprotection and collective migration. We derived several gemcitabine resistant subclones from the human pancreatic cancer cell line BxPC3 and determined that the observed chemoresistance was driven of a focal amplification of the chr11p15.4 genomic region, resulting in over-expression of the ribonucleotide reductase (RNR) subunit RRM1. Interestingly, these subclones display a rich cell-sorting behavior when cultured as mixed tumor spheroids. Furthermore, we show that chemoresistant cells are able to exert a chemoprotective effect on non-resistant cells in spheroid co-culture, whereas no protective effect is seen in conventional 2D culture. We also demonstrate that the co-culture of resistant and non-resistant cells leads to collective migration where resistant cells enable migration of otherwise non-migratory cells.

APOBEC3A drives deaminase domain-independent chromosomal instability to promote pancreatic cancer metastasis.

Despite efforts in understanding its underlying mechanisms, the etiology of chromosomal instability (CIN) remains unclear for many tumor types. Here, we identify CIN initiation as a previously undescribed function for APOBEC3A (A3A), a cytidine deaminase upregulated across cancer types. Using genetic mouse models of pancreatic ductal adenocarcinoma (PDA) and genomics analyses in human tumor cells we show that A3A-induced CIN leads to aggressive tumors characterized by enhanced early dissemination and metastasis in a STING-dependent manner and independently of the canonical deaminase functions of A3A. We show that A3A upregulation recapitulates numerous copy number alterations commonly observed in patients with PDA, including co-deletions in DNA repair pathway genes, which in turn render these tumors susceptible to poly (ADP-ribose) polymerase inhibition. Overall, our results demonstrate that A3A plays an unexpected role in PDA as a specific driver of CIN, with significant effects on disease progression and treatment.

anti-EGFR capture mitigates EMT- and chemoresistance-associated heterogeneity in a resistance-profiling CTC platform.

Capture and analysis of circulating tumor cells (CTCs) holds promise for diagnosing and guiding treatment of pancreatic cancer. To accurately monitor disease progression, capture platforms must be robust to processes that increase the phenotypic heterogeneity of CTCs. Most CTC-analysis technologies rely on the recognition of epithelial-specific markers for capture and identification, in particular the epithelial cell-adhesion molecule (EpCAM) and cytokeratin. As the epithelial-to-mesenchymal transition (EMT) and the acquisition of chemoresistance are both associated with loss of epithelial markers and characteristics, the effect of these processes on the expression of commonly used CTC markers, specifically EpCAM, EGFR and cytokeratin, requires further exploration. To determine this effect, we developed an in vitro model of EMT and acquired gemcitabine resistance in human pancreatic cancer cell lines. Using this model, we show that EMT-induction and acquired chemoresistance decrease EpCAM expression and microfluidic anti-EpCAM capture performance. Furthermore, we find that EGFR capture is more robust to these processes. By measuring the expression of known mediators of chemoresistance in captured cells using automated imaging and image processing, we demonstrate the ability to resistance-profile cells on-chip. We expect that this approach will allow for the development of improved non-invasive biomarkers of pancreatic cancer progression.

Comparison and optimization of machine learning methods for automated classification of circulating tumor cells.

Advances in rare cell capture technology have made possible the interrogation of circulating tumor cells (CTCs) captured from whole patient blood. However, locating captured cells in the device by manual counting bottlenecks data processing by being tedious (hours per sample) and compromises the results by being inconsistent and prone to user bias. Some recent work has been done to automate the cell location and classification process to address these problems, employing image processing and machine learning (ML) algorithms to locate and classify cells in fluorescent microscope images. However, the type of machine learning method used is a part of the design space that has not been thoroughly explored. Thus, we have trained four ML algorithms on three different datasets. The trained ML algorithms locate and classify thousands of possible cells in a few minutes rather than a few hours, representing an order of magnitude increase in processing speed. Furthermore, some algorithms have a significantly (P < 0.05) higher area under the receiver operating characteristic curve than do other algorithms. Additionally, significant (P < 0.05) losses to performance occur when training on cell lines and testing on CTCs (and vice versa), indicating the need to train on a system that is representative of future unlabeled data. Optimal algorithm selection depends on the peculiarities of the individual dataset, indicating the need of a careful comparison and optimization of algorithms for individual image classification tasks. © 2016 International Society for Advancement of Cytometry.

Microfluidic immunocapture of circulating pancreatic cells using parallel EpCAM and MUC1 capture: characterization, optimization and downstream analysis.

We have developed and optimized a microfluidic device platform for the capture and analysis of circulating pancreatic cells (CPCs) and pancreatic circulating tumor cells (CTCs). Our platform uses parallel anti-EpCAM and cancer-specific mucin 1 (MUC1) immunocapture in a silicon microdevice. Using a combination of anti-EpCAM and anti-MUC1 capture in a single device, we are able to achieve efficient capture while extending immunocapture beyond single marker recognition. We also have detected a known oncogenic KRAS mutation in cells spiked in whole blood using immunocapture, RNA extraction, RT-PCR and Sanger sequencing. To allow for downstream single-cell genetic analysis, intact nuclei were released from captured cells by using targeted membrane lysis. We have developed a staining protocol for clinical samples, including standard CTC markers; DAPI, cytokeratin (CK) and CD45, and a novel marker of carcinogenesis in CPCs, mucin 4 (MUC4). We have also demonstrated a semi-automated approach to image analysis and CPC identification, suitable for clinical hypothesis generation. Initial results from immunocapture of a clinical pancreatic cancer patient sample show that parallel capture may capture more of the heterogeneity of the CPC population. With this platform, we aim to develop a diagnostic biomarker for early pancreatic carcinogenesis and patient risk stratification.

Detection of circulating pancreas epithelial cells in patients with pancreatic cystic lesions.

Hematogenous dissemination is thought to be a late event in cancer progression. We recently showed in a genetic model of pancreatic ductal adenocarcinoma that pancreas cells can be detected in the bloodstream before tumor formation. To confirm these findings in humans, we used microfluidic geometrically enhanced differential immunocapture to detect circulating pancreas epithelial cells in patient blood samples. We captured more than 3 circulating pancreas epithelial cells/mL in 7 of 21 (33%) patients with cystic lesions and no clinical diagnosis of cancer (Sendai criteria negative), 8 of 11 (73%) with pancreatic ductal adenocarcinoma, and in 0 of 19 patients without cysts or cancer (controls). These findings indicate that cancer cells are present in the circulation of patients before tumors are detected, which might be used in risk assessment.