Molecular and morphologic characterization of intraductal tubulopapillary neoplasms of pancreas with novel potentially targetable fusions.

Intraductal tubulopapillary neoplasms (ITPNs) are rare pancreatic tumors with distinct histological and molecular features. Distinction of ITPN from other pancreatic neoplasms is crucial given the known favorable prognosis and the high frequency and diversity of potentially targetable fusions in ITPN. While the histological features of ITPN are well documented, there are few reports on the cytological features, and molecular characterization of ITPN. The authors reported three cases diagnosed in their laboratory between 2016 and 2021. Clinical data, cytomorphological and histological features, with immunophenotypic and molecular characterizations of these cases are described and compared with those reported in the literature. All 3 cases were diagnosed as ITPN based on the microscopic presence of intraductal nodules composed of tightly packed small tubular glands lined by cuboidal cells lacking apparent mucin. On molecular profiling KRAS and TP53 variants were found in Case 1, FGFR2-INA fusion in Case 2, and STARD3NL-BRAF fusion was detected in Case 3. Immunohistochemistry (IHC) revealed that the neoplastic cells in Case 1 were MUC2 positive and MUC6 negative, but in Cases 2 and 3, were negative for MUC2 and positive for MUC6. These results demonstrate the immunophenotypic and molecular variabilities of histologically similar pancreatic neoplasms. The absence of alterations characteristic of more common pancreatic neoplasms should prompt the consideration of fusion studies in morphologically relevant cases. The combination of morphological, IHC, and molecular analyses is important for reliable identification of ITPN given its potential clinical management implications.

High risk features in colorectal adenomatous polyps: A multi-institutional study.

High risk features in colorectal adenomatous polyps include size >1 cm and advanced histology: high-grade dysplasia and villous architecture. We investigated whether the diagnostic rates of advanced histology in colorectal adenomatous polyps were similar among institutions across the United States, and if not, could differences be explained by patient age, polyp size, and/or CRC rate. Nine academic institutions contributed data from three pathologists who had signed out at least 100 colorectal adenomatous polyps each from 2018 to 2019 taken from patients undergoing screening colonoscopy. For each case, we recorded patient age and sex, polyp size and location, concurrent CRC, and presence or absence of HGD and villous features. A total of 2700 polyps from 1886 patients (mean age: 61 years) were collected. One hundred twenty-four (5 %) of the 2700 polyps had advanced histology, including 35 (1 %) with HGD and 101 (4 %) with villous features. The diagnostic rate of advanced histology varied by institution from 1.7 % to 9.3 % (median: 4.3 %, standard deviation [SD]: 2.5 %). The rate of HGD ranged from 0 % to 3.3 % (median: 1 %, SD: 1.2 %), while the rate of villous architecture varied from 1 % to 8 % (median: 3.7 %, SD: 2.5 %). In a multivariate analysis, the factor most strongly associated with advanced histology was polyp size >1 cm with an odds ratio (OR) of 31.82 (95 % confidence interval [CI]: 20.52-50.25, p < 0.05). Inter-institutional differences in the rate of polyps >1 cm likely explain some of the diagnostic variance, but pathologic subjectivity may be another contributing factor.

Multimodal mass spectrometry imaging identifies cell-type-specific metabolic and lipidomic variation in the mammalian liver.

Spatial single-cell omics provides a readout of biochemical processes. It is challenging to capture the transient lipidome/metabolome from cells in a native tissue environment. We employed water gas cluster ion beam secondary ion mass spectrometry imaging ([H2O]n>28K-GCIB-SIMS) at ≤3 µm resolution using a cryogenic imaging workflow. This allowed multiple biomolecular imaging modes on the near-native-state liver at single-cell resolution. Our workflow utilizes desorption electrospray ionization (DESI) to build a reference map of metabolic heterogeneity and zonation across liver functional units at tissue level. Cryogenic dual-SIMS integrated metabolomics, lipidomics, and proteomics in the same liver lobules at single-cell level, characterizing the cellular landscape and metabolic states in different cell types. Lipids and metabolites classified liver metabolic zones, cell types and subtypes, highlighting the power of spatial multi-omics at high spatial resolution for understanding celluar and biomolecular organizations in the mammalian liver.