Faculty Bibliography

OBJECTIVE:To retrospectively compare inter- and intra-reader agreement of abbreviated MRCP (aMRCP) with comprehensive MRI (cMRCP) protocol for detection of worrisome features, high-risk stigmata, and concomitant pancreatic cancer in pancreatic cyst surveillance. METHODS:151 patients (104 women, mean age: 69[10] years) with baseline and follow-up contrast-enhanced MRIs were included. This comprised 138 patients under cyst surveillance with 5-year follow-up showing no pancreatic ductal adenocarcinoma (PDAC), 6 with pancreatic cystic lesion-derived malignancy, and 7 with concomitant PDAC. The aMRCP protocol used four sequences (axial and coronal Half-Fourier Single-shot Turbo-spin-Echo, axial T1 fat-saturated pre-contrast, and 3D-MRCP), while cMRCP included all standard sequences, including post-contrast. Three blinded abdominal radiologists assessed baseline cyst characteristics, worrisome features, high-risk stigmata, and PDAC signs using both aMRCP and cMRCP, with a 2-week washout period. Intra- and inter-reader agreement were calculated using Fleiss' multi-rater kappa and Intra-class Correlation Coefficient (ICC). 95% confidence intervals (CI) were calculated. RESULTS:Cyst size, growth, and abrupt main pancreatic duct transition had strong intra- and inter-reader agreement. Intra-reader agreement was ICC = 0.93-0.99 for cyst size, ICC = 0.71-1.00 for cyst growth, and kappa = 0.83-1.00 for abrupt duct transition. Inter-reader agreement for cyst size was ICC = 0.86 (aMRCP) and ICC = 0.83 (cMRCP), and for abrupt duct transition was kappa = 0.84 (aMRCP) and kappa = 0.69 (cMRCP). Thickened cyst wall, mural nodule and cyst-duct communication demonstrated varying intra-reader agreements and poor inter-reader agreements. CONCLUSION/CONCLUSIONS:aMRCP showed high intra- and inter-reader agreement for most pancreatic cyst parameters that highly rely on T2-weighted sequences.

BACKGROUND/UNASSIGNED:Neoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its specific effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study aims to investigate how NAT differentially impacts PDAC's carcinoma cells and TME. METHODS/UNASSIGNED:Spatial transcriptomics was used to compare gene expression profiles in carcinoma cells and the TME between 23 NAT-treated and 13 NAT-naïve PDAC patients, correlating with their clinicopathologic features. Analysis of an online single-nucleus RNA sequencing (snRNA-seq) dataset was performed for validation of the specific cell types responsible for NAT-induced gene expression alterations. RESULTS/UNASSIGNED:T cells, monocytes, and mast cells; and reduced immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement was specifically upregulated in CAFs but not in other stroma cell types. CONCLUSIONS/UNASSIGNED:NAT can enhance complement production and signaling within the TME, which is associated with reduced immunosuppression in PDAC. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients.

The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8 + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8 + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.

RATIONALE AND OBJECTIVES/OBJECTIVE:To date, no clinically useful classification system has been developed for reliably differentiating mucinous cystic neoplasm (MCN) from a benign hepatic cyst (BHC) in the liver. The objective was to use machine learning and a multi-center study design to develop and assess the performance of a novel classification system for predicting whether a hepatic cystic lesion represents MCN or BHC. MATERIALS AND METHODS/METHODS:A multi-center cohort study identified 154 surgically resected hepatic cystic lesions in 154 subjects which were pathologic confirmed as MCN (43) or BHC (111). Readers at each institution recorded seven pre-determined imaging features previously identified as potential differentiating features from prior publications. The contribution of each of these features to differentiating MCN from BHC was assessed by machine learning to develop an optimal classification system. RESULTS:Although several of the assessed imaging features demonstrated statistical significance, only 3 imaging features were found by machine learning to significantly contribute to a potential classification system: (1) solid enhancing nodule (2) all septations arising from an external macro-lobulation (3) whether the lesion was solitary or one of multiple cystic liver lesions. The optimal classification system had only four categories and correctly identified 144/154 lesion (93.5%). CONCLUSION/CONCLUSIONS:This multi-center follow-up study was able to use machine learning to develop a highly accurate classification system for differentiation of hepatic MCN from BHC, which could be readily applied to clinical practice.

Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-cancer single-cell RNA-sequencing analysis across 15 cancer types and identify a catalog of gene modules whose expression defines recurrent cancer cell states including 'stress', 'interferon response', 'epithelial-mesenchymal transition', 'metal response', 'basal' and 'ciliated'. Spatial transcriptomic analysis linked the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Using mouse models, we further found that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance and metastasis.

Anastomosing hemangioma (AH) is a rare, benign vascular neoplasm with distinctive histopathology and characteristic tumor distribution. AHs show marked proclivity to involve the kidneys, gonads and the retroperitoneal soft tissues; kidney is the most common target site often in the context of end stage renal disease. Recent studies have identified activating mutations of GNA genes that drive the molecular pathogenesis of AHs. AH appears as a solitary, well-circumscribed, hypervascular tumor that charters a benign course with an excellent prognosis. The purpose of this article is to provide a current update on clinical, pathological and imaging features of anastomotic hemangioma.

Background: Bile duct brush cytology (B

Tumor genotype can influence the immune microenvironment, which plays a critical role in cancer development and therapy resistance. However, the immune effects of gain-of-function Trp53 mutations have not been defined in pancreatic cancer. We compare the immune profiles generated by Kras^G12D-mutated mouse pancreatic ductal epithelial cells (PDECs) engineered genetically to express the Trp53^R172H mutation with their p53 wild-type control. Kras^G12D/+;Trp53^R172H/+ tumors have a distinct immune profile characterized by an influx of CD11b⁺Ly6G⁺ neutrophils and concomitant decreases in CD3⁺ T cells, CD8⁺ T cells, and CD4⁺ T helper 1 cells. Knockdown of CXCL2, a neutrophil chemokine, in the tumor epithelial compartment of CRISPR Kras^G12D/+;Trp53^R172H/+ PDEC tumors reverses the neutrophil phenotype. Neutrophil depletion of mice bearing CRISPR Kras^G12D/+;Trp53^R172H/+ tumors augments sensitivity to combined CD40 immunotherapy and chemotherapy. These data link Trp53^R172H to the presence of intratumoral neutrophils in pancreatic cancer and suggest that tumor genotypes could inform selection of affected individuals for immunotherapy.