Organoid models of human and mouse ductal pancreatic cancer.

Pancreatic cancer is one of the most lethal malignancies due to its late diagnosis and limited response to treatment. Tractable methods to identify and interrogate pathways involved in pancreatic tumorigenesis are urgently needed. We established organoid models from normal and neoplastic murine and human pancreas tissues. Pancreatic organoids can be rapidly generated from resected tumors and biopsies, survive cryopreservation, and exhibit ductal- and disease-stage-specific characteristics. Orthotopically transplanted neoplastic organoids recapitulate the full spectrum of tumor development by forming early-grade neoplasms that progress to locally invasive and metastatic carcinomas. Due to their ability to be genetically manipulated, organoids are a platform to probe genetic cooperation. Comprehensive transcriptional and proteomic analyses of murine pancreatic organoids revealed genes and pathways altered during disease progression. The confirmation of many of these protein changes in human tissues demonstrates that organoids are a facile model system to discover characteristics of this deadly malignancy.

DNA Methylation Profiling Enables Accurate Classification of Nonductal Primary Pancreatic Neoplasms.

BACKGROUND & AIMS: Cytologic and histopathologic diagnosis of non-ductal pancreatic neoplasms can be challenging in daily clinical practice, whereas it is crucial for therapy and prognosis. The cancer methylome is successfully used as a diagnostic tool in other cancer entities. Here, we investigate if methylation profiling can improve the diagnostic work-up of pancreatic neoplasms. METHODS: DNA methylation data were obtained for 301 primary tumors spanning 6 primary pancreatic neoplasms and 20 normal pancreas controls. Neural Network, Random Forest, and extreme gradient boosting machine learning models were trained to distinguish between tumor types. Methylation data of 29 nonpancreatic neoplasms (n = 3708) were used to develop an algorithm capable of detecting neoplasms of non-pancreatic origin. RESULTS: After benchmarking 3 state-of-the-art machine learning models, the random forest model emerged as the best classifier with 96.9% accuracy. All classifications received a probability score reflecting the confidence of the prediction. Increasing the score threshold improved the random forest classifier performance up to 100% with 87% of samples with scores surpassing the cutoff. Using a logistic regression model, detection of nonpancreatic neoplasms achieved an area under the curve of >0.99. Analysis of biopsy specimens showed concordant classification with their paired resection sample. CONCLUSIONS: Pancreatic neoplasms can be classified with high accuracy based on DNA methylation signatures. Additionally, non-pancreatic neoplasms are identified with near perfect precision. In summary, methylation profiling can serve as a valuable adjunct in the diagnosis of pancreatic neoplasms with minimal risk for misdiagnosis, even in the pre-operative setting.

Somatic loss of ATM is a late event in pancreatic tumorigenesis.

Understanding the timing and spectrum of genetic alterations that contribute to the development of pancreatic cancer is essential for effective interventions and treatments. The aim of this study was to characterize somatic ATM alterations in noninvasive pancreatic precursor lesions and invasive pancreatic adenocarcinomas from patients with and without pathogenic germline ATM variants. DNA was isolated and sequenced from the invasive pancreatic ductal adenocarcinomas and precursor lesions of patients with a pathogenic germline ATM variant. Tumor and precursor lesions from these patients as well as colloid carcinoma from patients without a germline ATM variant were immunolabeled to assess ATM expression. Among patients with a pathogenic germline ATM variant, somatic ATM alterations, either mutations and/or loss of protein expression, were identified in 75.0% of invasive pancreatic adenocarcinomas but only 7.1% of pancreatic precursor lesions. Loss of ATM expression was also detected in 31.0% of colloid carcinomas from patients unselected for germline ATM status, significantly higher than in pancreatic precursor lesions [pancreatic intraepithelial neoplasms (p = 0.0013); intraductal papillary mucinous neoplasms, p = 0.0040] and pancreatic ductal adenocarcinoma (p = 0.0076) unselected for germline ATM status. These data are consistent with the second hit to ATM being a late event in pancreatic tumorigenesis. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Precancerous neoplastic cells can move through the pancreatic ductal system.

Most adult carcinomas develop from noninvasive precursor lesions, a progression that is supported by genetic analysis. However, the evolutionary and genetic relationships among co-existing lesions are unclear. Here we analysed the somatic variants of pancreatic cancers and precursor lesions sampled from distinct regions of the same pancreas. After inferring evolutionary relationships, we found that the ancestral cell had initiated and clonally expanded to form one or more lesions, and that subsequent driver gene mutations eventually led to invasive pancreatic cancer. We estimate that this multi-step progression generally spans many years. These new data reframe the step-wise progression model of pancreatic cancer by illustrating that independent, high-grade pancreatic precursor lesions observed in a single pancreas often represent a single neoplasm that has colonized the ductal system, accumulating spatial and genetic divergence over time.

Grading Pancreatic Neuroendocrine Tumors Via Endoscopic Ultrasound-guided Fine Needle Aspiration: A Multi-institutional Study.

OBJECTIVES: To identify factors associated with concordance between World Health Organization (WHO) grade on cytological analysis (c-grade) and histopathological analysis (h-grade) of surgical specimen in patients with PanNETs and examine trends in utilization and accuracy of EUS-FNA in preoperatively predicting grade. BACKGROUND: WHO grading system is prognostic in pancreatic neuroendo-crine tumors (PanNETs). The concordance between c-grade and h-grade is reported to be between 50% and 92%. METHODS: A multicenter retrospective study was performed on patients undergoing resection for PanNETs at four high-volume centers between 2010 and 2019. Patients with functional or syndrome-associated tumors, and those receiving neoadjuvant therapy were excluded. Factors associated with concordance between c-grade and h-grade and trends of utilization of EUS-FNA were assessed. RESULTS: Of 869 patients included, 517 (59.5%) underwent EUS-FNA; 452 (87.4%) were diagnostic of PanNETs and WHO-grade was reported for 270 (59.7%) patients. The concordance between c-grade and h-grade was 80.4% with moderate concordance ( Kc = 0.52, 95% CI: 0.41-0.63). Significantly higher rates of concordance were observed in patients with smaller tumors (<2 vs. ≥2cm, 81.1% vs. 60.4%, P = 0.005). Highest concordance (98.1%) was observed in patients with small tumors undergoing assessment between 2015-2019 with a near-perfect concordance ( Kc = 0.88, 95% CI: 0.61-1.00). An increase in the utilization of EUS-FNA (56.1% to 64.1%) was observed over the last 2 decades ( P = 0.017) and WHO-grade was more frequently reported (44.2% vs. 77.6%, P < 0.001). However, concordance between c-grade and h-grade did not change significantly (P = 0.118). CONCLUSION: Recently, a trend towards increasing utilization and improved diagnostic accuracy of EUS-FNA has been observed in PanNETs. Concordance between c-grade and h-grade is associated with tumor size with near-perfect agreement when assessing PanNETs <2cm in size.

Integrated Genomic and Clinicopathologic Approach Distinguishes Pancreatic Grade 3 Neuroendocrine Tumor From Neuroendocrine Carcinoma and Identifies a Subset With Molecular Overlap.

Distinguishing grade 3 pancreatic neuroendocrine tumor (G3 PanNET) from neuroendocrine carcinoma (PanNEC) is a known diagnostic challenge, and accurate classification is critical because clinical behavior and therapies differ. Although current recommendations suggest that immunohistochemistry for p53, Rb, ATRX, and DAXX can distinguish most cases, some cases remain difficult to classify using this approach. In this study, we reviewed 47 high-grade neoplasms originally diagnosed as pancreatic neuroendocrine neoplasms. In addition to the currently recommended stains, we performed capture-based sequencing of approximately 500 cancer genes and immunohistochemistry for p16 and trypsin or chymotrypsin. Using an integrated molecular and clinicopathologic approach, 42 (89%) of 47 cases had a clear final diagnosis of either G3 PanNET (n = 17), PanNEC (n = 17), or mixed acinar-NEC (n = 8). The 17 G3 PanNETs demonstrated frequent alterations in MEN1 (71%), DAXX (47%), ATRX (24%), TSC2 (35%), SETD2 (42%), and CDKN2A (41%). Contrary to prior reports, TP53 alterations were also common in G3 PanNETs (35%) but were always mutually exclusive with CDKN2A alterations in this group. The 17 PanNECs demonstrated frequent alterations in TP53 (88%), cell cycle genes RB1 (47%), CCNE1/CCND1 (12%), CDKN2A (29%), and in KRAS (53%) and SMAD4 (41%); TP53 was coaltered with a cell cycle gene in 76% of PanNECs. Diffuse strong p16 staining was observed in 69% of PanNECs in contrast to 0% of G3 PanNETs. The 8 acinar-NECs had recurrent alterations in ATM (25%), APC (25%), and STK11 (25%). Five cases remained difficult to classify, 3 of which exhibited overlapping molecular features with alterations in MEN1 with or without ATRX, and RB1 with or without TP53, making it unclear whether to classify as PanNET or PanNEC. Our data demonstrate that molecular profiling and immunohistochemistry for p16 greatly improve the diagnostic accuracy of high-grade pancreatic neuroendocrine neoplasms and identify a subset of rare cases with overlapping features of both PanNET and PanNEC.

Pancreatobiliary Maljunction-associated Gallbladder Cancer Is as Common in the West, Shows Distinct Clinicopathologic Characteristics and Offers an Invaluable Model for Anatomy-induced Reflux-associated Physio-chemical Carcinogenesis.

OBJECTIVE: To determine the associations of pancreatobiliary maljunction (PBM) in the West. BACKGROUND: PBM (anomalous union of common bile duct and pancreatic duct) is mostly regarded as an Asian-only disorder, with 200X risk of gallbladder cancer (GBc), attributed to reflux of pancreatic enzymes. Methods: Radiologic images of 840 patients in the US who underwent pancreatobiliary resections were reviewed for PBM and contrasted with 171 GBC cases from Japan. RESULTS: Eight % of the US GBCs (24/300) had PBM (similar to Japan; 15/ 171, 8.8%), in addition to 1/42 bile duct carcinomas and 5/33 choledochal cysts. None of the 30 PBM cases from the US had been diagnosed as PBM in the original work-up. PBM was not found in other pancreatobiliary disorders. Clinicopathologic features of the 39 PBM-associated GBCs (US:24, Japan:15) were similar; however, comparison with non-PBM GBCs revealed that they occurred predominantly in females (F/M = 3); at younger (<50-year-old) age (21% vs 6.5% in non-PBM GBCs; P = 0.01); were uncommonly associated with gallstones (14% vs 58%; P < 0.001); had higher rate of tumor-infiltrating lymphocytes (69% vs 44%; P = 0.04); arose more often through adenoma-carcinoma sequence (31% vs 12%; P = 0.02); and had a higher proportion of nonconventional carcinomas (21% vs 7%; P = 0.03). Conclusions: PBM accounts for 8% of GBCs also in the West but is typically undiagnosed. PBM-GBCs tend to manifest in younger age and often through adenoma-carcinoma sequence, leading to unusual carcinoma types. If PBM is encountered, cholecystectomy and surveillance of bile ducts is warranted. PBM-associated GBCs offer an invaluable model for variant anatomy-induced chemical (reflux-related) carcinogenesis.

Integrating digital pathology into clinical practice.

The field of anatomic pathology has been evolving in the last few decades and the advancements have been largely fostered by innovative technology. Immunohistochemistry enabled a paradigm shift in discovery and diagnostic evaluation, followed by booming genomic advancements which allowed for submicroscopic pathologic characterization, and now the field of digital pathology coupled with machine learning and big data acquisition is paving the way to revolutionize the pathology medical domain. Whole slide imaging (WSI) is a disruptive technology where glass slides are digitized to produce on-screen whole slide images. Specifically, in the past decade, there have been significant advances in digital pathology systems that have allowed this technology to promote integration into clinical practice. Whole slide images (WSI), or digital slides, can be viewed and navigated comparable to glass slides on a microscope, as digital files. Whole slide imaging has increased in adoption among pathologists, pathology departments, and scientists for clinical, educational, and research initiatives. Integration of digital pathology systems requires a coordinated effort with numerous stakeholders, not only within the pathology department, but across the entire enterprise. Each pathology department has distinct needs, use cases and blueprints, however the framework components and variables for successful clinical integration can be generalized across any organization seeking to undergo a digital transformation at any scale. This article will review those components and considerations for integrating digital pathology systems into clinical practice.

Pancreatoblastomas and mixed and pure acinar cell carcinomas share epigenetic signatures distinct from other neoplasms of the pancreas.

Pancreatic neoplasms are heterogenous and have traditionally been classified by assessing their lines of cellular differentiation using histopathologic methods, particularly morphologic and immunohistochemical evaluation. These methods frequently identify overlapping differentiation along ductal, acinar, and neuroendocrine lines, raising diagnostic challenges as well as questions regarding the relationship of these neoplasms. Neoplasms with acinar differentiation, in particular, frequently show more than one line of differentiation based on immunolabeling. Genome methylation signatures, in contrast, are better conserved within cellular lineages, and are increasingly used to support the classification of neoplasms. We characterized the epigenetic relationships between pancreatoblastomas, acinar cell carcinomas (including mixed variants), pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, and pancreatic ductal adenocarcinomas using a genome-wide array platform. Using unsupervised learning approaches, pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, ductal adenocarcinomas, and normal pancreatic tissue samples all localized to distinct clusters based on their methylation profiles, whereas all neoplasms with acinar differentiation occupied a broad overlapping region located between the predominantly acinar normal pancreatic tissue and ductal adenocarcinoma clusters. Our data provide evidence to suggest that acinar cell carcinomas and pancreatoblastomas are similar at the epigenetic level. These findings are consistent with genomic and clinical observations that mixed acinar neoplasms are closely related to pure acinar cell carcinomas rather than to neuroendocrine tumors or ductal adenocarcinomas.

A modular and flexible ESC-based mouse model of pancreatic cancer.

Genetically engineered mouse models (GEMMs) have greatly expanded our knowledge of pancreatic ductal adenocarcinoma (PDAC) and serve as a critical tool to identify and evaluate new treatment strategies. However, the cost and time required to generate conventional pancreatic cancer GEMMs limits their use for investigating novel genetic interactions in tumor development and maintenance. To address this problem, we developed flexible embryonic stem cell (ESC)-based GEMMs that facilitate the rapid generation of genetically defined multiallelic chimeric mice without further strain intercrossing. The ESCs harbor a latent Kras mutant (a nearly ubiquitous feature of pancreatic cancer), a homing cassette, and other genetic elements needed for rapid insertion and conditional expression of tetracycline-controlled transgenes, including fluorescence-coupled shRNAs capable of efficiently silencing gene function by RNAi. This system produces a disease that recapitulates the progression of pancreatic cancer in human patients and enables the study and visualization of the impact of gene perturbation at any stage of pancreas cancer progression. We describe the use of this approach to dissect temporal roles for the tumor suppressor Pten and the oncogene c-Myc in pancreatic cancer development and maintenance.

Distinct functions of macrophage-derived and cancer cell-derived cathepsin Z combine to promote tumor malignancy via interactions with the extracellular matrix.

During the process of tumor progression, cancer cells can produce the requisite growth- and invasion-promoting factors and can also rely on noncancerous cells in the tumor microenvironment as an alternative, cell-extrinsic source. However, whether the cellular source influences the function of such tumor-promoting factors remains an open question. Here, we examined the roles of the cathepsin Z (CtsZ) protease, which is provided by both cancer cells and macrophages in pancreatic neuroendocrine tumors in humans and mice. We found that tumor proliferation was exclusively regulated by cancer cell-intrinsic functions of CtsZ, whereas tumor invasion required contributions from both macrophages and cancer cells. Interestingly, several of the tumor-promoting functions of CtsZ were not dependent on its described catalytic activity but instead were mediated via the Arg-Gly-Asp (RGD) motif in the enzyme prodomain, which regulated interactions with integrins and the extracellular matrix. Together, these results underscore the complexity of interactions within the tumor microenvironment and indicate that cellular source can indeed impact molecular function.

Diagnosis of digestive system tumours.

The WHO Classification of Tumours provides the international standards for the classification and diagnosis of tumours. It enables direct comparisons to be made between different countries. In the new fifth edition, the series has gone digital with the launch of a website as well as a series of books, known widely as the WHO Blue Books. The first volume to be produced is on the classification of Digestive System tumours, replacing the successful 2010 version. It has been rewritten and updated accordingly. This article summarises the major diagnostic innovations that have occurred over the last decade and that have now been incorporated in the classification. As an example, it incorporates the recently proposed classification of neuroendocrine tumours, based on the recognition that neuroendocrine tumours and carcinomas differ substantially in the genetic abnormalities that drive their growth, findings relevant to treatment selection and outcome prediction. Several themes have emerged during the production process. One is the importance of the progression from hyperplasia to dysplasia to carcinoma in the evolution of the malignant process. Advances in imaging techniques and endoscopy have resulted in enhanced access to precancerous lesions in the gastrointestinal and biliary tract, necessitating both changes in classification schema and clinical practice. Diagnosis of tumours is no longer the sole purview of pathologists, and some patients now receive treatment before tissue is obtained, based on clinical, radiological and liquid biopsy results. This makes the classification relevant to many disciplines involved in the care of patients with tumours of the digestive system.

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy.

Prostate cancer is a leading cause of morbidity and mortality for adult males in the US. The diagnosis of prostate carcinoma is usually made on prostate core needle biopsies obtained through a transrectal approach. These biopsies may account for a significant portion of the pathologists' workload, yet variability in the experience and expertise, as well as fatigue of the pathologist may adversely affect the reliability of cancer detection. Machine-learning algorithms are increasingly being developed as tools to aid and improve diagnostic accuracy in anatomic pathology. The Paige Prostate AI-based digital diagnostic is one such tool trained on the digital slide archive of New York's Memorial Sloan Kettering Cancer Center (MSKCC) that categorizes a prostate biopsy whole-slide image as either "Suspicious" or "Not Suspicious" for prostatic adenocarcinoma. To evaluate the performance of this program on prostate biopsies secured, processed, and independently diagnosed at an unrelated institution, we used Paige Prostate to review 1876 prostate core biopsy whole-slide images (WSIs) from our practice at Yale Medicine. Paige Prostate categorizations were compared to the pathology diagnosis originally rendered on the glass slides for each core biopsy. Discrepancies between the rendered diagnosis and categorization by Paige Prostate were each manually reviewed by pathologists with specialized genitourinary pathology expertise. Paige Prostate showed a sensitivity of 97.7% and positive predictive value of 97.9%, and a specificity of 99.3% and negative predictive value of 99.2% in identifying core biopsies with cancer in a data set derived from an independent institution. Areas for improvement were identified in Paige Prostate's handling of poor quality scans. Overall, these results demonstrate the feasibility of porting a machine-learning algorithm to an institution remote from its training set, and highlight the potential of such algorithms as a powerful workflow tool for the evaluation of prostate core biopsies in surgical pathology practices.

A Consensus-Developed Morphological Re-Evaluation of 196 High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms and Its Clinical Correlations.

High-grade gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are classified according to morphology as well-differentiated neuroendocrine tumours (NETs) G3 or poorly differentiated neuroendocrine carcinomas (NECs). Little data exist concerning which morphological criteria this subdivision should be based on. Uncertainty exists if the NEC group should be further subdivided according to proliferation rate. Clinical data on NET G3 and NEC with a lower Ki-67 range are limited. A total of 213 patients with high-grade GEP-NEN (Ki-67 >20%) were included from the Nordic NEC Registries. Four experienced NET pathologists re-evaluated the cases to develop the best morphological criteria to separate NET G3 from NEC, assuming longer survival in NET G3. Organoid growth pattern, capillary network in direct contact to tumour cells, and absence of desmoplastic stroma were found to best separate NET G3 from NEC. Of 196 patients with metastatic disease, NET G3 was found in 12.3%, NEC with a Ki-67 <55% (NEC < 55) in 29.6%, and NEC with a Ki-67 ≥55% (NEC ≥ 55) in 56.6%. Only in 1.5%, the morphology was ambiguous. Of 164 patients receiving first-line chemotherapy, 88% received platinum/etoposide treatment. Response rate was higher for NEC ≥ 55 (44%) than that of NEC < 55 (25%) and NET G3 (24%) (p = 0.025 and p = 0.026). Median progression-free survival was 5 months for all groups. Median overall survival was 33 months for NET G3 compared to 11 months for both NEC < 55 and NEC ≥ 55 (p = 0.004 and 0.003). Specific morphological criteria can separate NET G3 from NECs and show prognostic significance. High-grade GEP-NEN patients stratified by morphology and proliferation rate demonstrate significant differences in response to chemotherapy and survival.

Molecular profiling and analysis of genetic aberrations aimed at identifying potential therapeutic targets in fibrolamellar carcinoma of the liver.

BACKGROUND: Fibrolamellar carcinoma (FLC) is a rare primary liver cancer of young adults. A functional chimeric transcript resulting from the in-frame fusion of the DNAJ homolog, subfamily B, member 1 (DNAJB1), and the catalytic subunit of protein kinase A (PRKACA) genes on chromosome 19 is believed to be unique in FLC, with a possible role in pathogenesis, yet with no established therapeutic value. The objective of the current study was to understand the molecular landscape of FLC and to identify potential novel therapeutic targets. METHODS: Archival fresh, formalin-fixed, paraffin-embedded samples from patients with FLC who prospectively consented to an institutional review board-approved protocol were analyzed using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a next-generation sequencing assay encompassing up to 468 key cancer genes. Custom targeted RNA-Seq was performed in selected patients. Demographics, treatment, and outcome data were collected prospectively. Survival outcomes were estimated and correlated with mutation and/or copy number alterations. RESULTS: A total of 33 tumor samples from 31 patients with FLC were analyzed. The median age of the patients at the time of diagnosis was 18 years and approximately 53% were women. The DNAJB1-PRKACA fusion transcript was detected in 100% of patients. In 10 of 31 patients in which MSK-IMPACT did not detect the fusion, its presence was confirmed by targeted RNA-Seq. TERT promoter mutation was the second most common, and was detected in 7 patients. The median follow up was 30 months (range, 6-153 months). The 3-year overall survival rate was 84% (95% CI, 61%-93%). CONCLUSIONS: The DNAJB1-PRKACA fusion transcript is nonspecific and nonsensitive to FLC. Its potential therapeutic value currently is under evaluation. Opportunities currently are under development for therapy that may be driven or related to the DNAJB1-PRKACA fusion transcript or any therapeutic target identified from next-generation sequencing in patients with FLC.

DNAJB1-PRKACA fusions occur in oncocytic pancreatic and biliary neoplasms and are not specific for fibrolamellar hepatocellular carcinoma.

Recently discovered DNAJB1-PRKACA oncogenic fusions have been considered diagnostic for fibrolamellar hepatocellular carcinoma. In this study, we describe six pancreatobiliary neoplasms with PRKACA fusions, five of which harbor the DNAJB1-PRKACA fusion. All neoplasms were subjected to a hybridization capture-based next-generation sequencing assay (MSK-IMPACT), which enables the identification of sequence mutations, copy number alterations, and selected structural rearrangements involving ≥410 genes (n = 6) and/or to a custom targeted, RNA-based panel (MSK-Fusion) that utilizes Archer Anchored Multiplex PCR technology and next-generation sequencing to detect gene fusions in 62 genes (n = 2). Selected neoplasms also underwent FISH analysis, albumin mRNA in-situ hybridization, and arginase-1 immunohistochemical labeling (n = 3). Five neoplasms were pancreatic, and one arose in the intrahepatic bile ducts. All revealed at least focal oncocytic morphology: three cases were diagnosed as intraductal oncocytic papillary neoplasms, and three as intraductal papillary mucinous neoplasms with mixed oncocytic and pancreatobiliary or gastric features. Four cases had an invasive carcinoma component composed of oncocytic cells. Five cases revealed DNAJB1-PRKACA fusions and one revealed an ATP1B1-PRKACA fusion. None of the cases tested were positive for albumin or arginase-1. Our data prove that DNAJB1-PRKACA fusion is neither exclusive nor diagnostic for fibrolamellar hepatocellular carcinoma, and caution should be exercised in diagnosing liver tumors with DNAJB1-PRKACA fusions as fibrolamellar hepatocellular carcinoma, particularly if a pancreatic lesion is present. Moreover, considering DNAJB1-PRKACA fusions lead to upregulated protein kinase activity and that this upregulated protein kinase activity has a significant role in tumorigenesis of fibrolamellar hepatocellular carcinoma, protein kinase inhibition could have therapeutic potential in the treatment of these pancreatobiliary neoplasms as well, once a suitable drug is developed.

Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies.

Prostate cancer (PrCa) is the second most common cancer among men in the United States. The gold standard for detecting PrCa is the examination of prostate needle core biopsies. Diagnosis can be challenging, especially for small, well-differentiated cancers. Recently, machine learning algorithms have been developed for detecting PrCa in whole slide images (WSIs) with high test accuracy. However, the impact of these artificial intelligence systems on pathologic diagnosis is not known. To address this, we investigated how pathologists interact with Paige Prostate Alpha, a state-of-the-art PrCa detection system, in WSIs of prostate needle core biopsies stained with hematoxylin and eosin. Three AP-board certified pathologists assessed 304 anonymized prostate needle core biopsy WSIs in 8 hours. The pathologists classified each WSI as benign or cancerous. After ~4 weeks, pathologists were tasked with re-reviewing each WSI with the aid of Paige Prostate Alpha. For each WSI, Paige Prostate Alpha was used to perform cancer detection and, for WSIs where cancer was detected, the system marked the area where cancer was detected with the highest probability. The original diagnosis for each slide was rendered by genitourinary pathologists and incorporated any ancillary studies requested during the original diagnostic assessment. Against this ground truth, the pathologists and Paige Prostate Alpha were measured. Without Paige Prostate Alpha, pathologists had an average sensitivity of 74% and an average specificity of 97%. With Paige Prostate Alpha, the average sensitivity for pathologists significantly increased to 90% with no statistically significant change in specificity. With Paige Prostate Alpha, pathologists more often correctly classified smaller, lower grade tumors, and spent less time analyzing each WSI. Future studies will investigate if similar benefit is yielded when such a system is used to detect other forms of cancer in a setting that more closely emulates real practice.

Genetic and clinical correlates of entosis in pancreatic ductal adenocarcinoma.

Entosis is a type of regulated cell death that promotes cancer cell competition. Though several studies have revealed the molecular mechanisms that govern entosis, the clinical and genetic correlates of entosis in human tumors is less well understood. Here we reviewed entotic cell-in-cell (CIC) patterns in a large single institution sequencing cohort (MSK IMPACT clinical sequencing cohort) of more than 1600 human pancreatic ductal adenocarcinoma (PDAC) samples to identify the genetic and clinical correlates of this cellular feature. After case selection, 516 conventional PDACs and 21 ASCs entered this study and ~45,000 HPFs (median 80 HPFs per sample) were reviewed; 549 entotic-CICs were detected through our cohort. We observed that entotic-CIC occurred more frequently in liver metastasis compared with primary in PDAC. Moreover, poorly differentiated adenocarcinoma or adenosquamous carcinoma had more entotic-CIC than well or moderately differentiated adenocarcinoma. With respect to genetic features TP53 mutations, KRAS amplification, and MYC amplification were significantly associated with entosis in PDAC tissues. From a clinical standpoint entotic CICs were independently associated with a poor prognosis by multivariate Cox regression analysis when considering all cases or primary PDACs specifically. These results provide a contextual basis for understanding entosis in PDAC, a highly aggressive cancer for which molecular insights are needed to improve survival.

Validation of a digital pathology system including remote review during the COVID-19 pandemic.

Remote digital pathology allows healthcare systems to maintain pathology operations during public health emergencies. Existing Clinical Laboratory Improvement Amendments regulations require pathologists to electronically verify patient reports from a certified facility. During the 2019 pandemic of COVID-19 disease, caused by the SAR-CoV-2 virus, this requirement potentially exposes pathologists, their colleagues, and household members to the risk of becoming infected. Relaxation of government enforcement of this regulation allows pathologists to review and report pathology specimens from a remote, non-CLIA certified facility. The availability of digital pathology systems can facilitate remote microscopic diagnosis, although formal comprehensive (case-based) validation of remote digital diagnosis has not been reported. All glass slides representing routine clinical signout workload in surgical pathology subspecialties at Memorial Sloan Kettering Cancer Center were scanned on an Aperio GT450 at ×40 equivalent resolution (0.26 µm/pixel). Twelve pathologists from nine surgical pathology subspecialties remotely reviewed and reported complete pathology cases using a digital pathology system from a non-CLIA certified facility through a secure connection. Whole slide images were integrated to and launched within the laboratory information system to a custom vendor-agnostic, whole slide image viewer. Remote signouts utilized consumer-grade computers and monitors (monitor size, 13.3-42 in.; resolution, 1280 × 800-3840 × 2160 pixels) connecting to an institution clinical workstation via secure virtual private network. Pathologists subsequently reviewed all corresponding glass slides using a light microscope within the CLIA-certified department. Intraobserver concordance metrics included reporting elements of top-line diagnosis, margin status, lymphovascular and/or perineural invasion, pathology stage, and ancillary testing. The median whole slide image file size was 1.3 GB; scan time/slide averaged 90 s; and scanned tissue area averaged 612 mm2. Signout sessions included a total of 108 cases, comprised of 254 individual parts and 1196 slides. Major diagnostic equivalency was 100% between digital and glass slide diagnoses; and overall concordance was 98.8% (251/254). This study reports validation of primary diagnostic review and reporting of complete pathology cases from a remote site during a public health emergency. Our experience shows high (100%) intraobserver digital to glass slide major diagnostic concordance when reporting from a remote site. This randomized, prospective study successfully validated remote use of a digital pathology system including operational feasibility supporting remote review and reporting of pathology specimens, and evaluation of remote access performance and usability for remote signout.

Sclerosing epithelioid mesenchymal neoplasm of the pancreas - a proposed new entity.

We have encountered pancreatic tumors with unique histologic features, which do not conform to any of the known tumors of the pancreas or other anatomical sites. We aimed to define their clinicopathologic features and whether they are characterized by recurrent molecular signatures. Eight cases were identified; studied histologically and by immunohistochemistry. Selected cases were also subjected to whole-exome sequencing (WES; n = 4), RNA-sequencing (n = 6), Archer FusionPlex assay (n = 5), methylation profiling using the Illumina MethylationEPIC (850k) array platform (n = 6), and TERT promoter sequencing (n = 5). Six neoplasms occurred in females. The mean age was 43 years (range: 26-75). Five occurred in the head/neck of the pancreas. All patients were treated surgically; none received neoadjuvant/adjuvant therapy. All patients are free of disease after 53 months of median follow-up (range: 8-94). The tumors were well-circumscribed, and the median size was 1.8 cm (range: 1.3-5.8). Microscopically, the unencapsulated tumors had a geographic pattern of epithelioid cell nests alternating with spindle cell fascicles. Some areas showed dense fibrosis, in which enmeshed tumor cells imparted a slit-like pattern. The predominant epithelioid cells had scant cytoplasm and round-oval nuclei with open chromatin. The spindle cells displayed irregular, hyperchromatic nuclei. Mitoses were rare. No lymph node metastases were identified. All tumors were positive for vimentin, CD99 and cytokeratin (patchy), while negative for markers of solid pseudopapillary neoplasm, neuroendocrine, acinar, myogenic/rhabdoid, vascular, melanocytic, or lymphoid differentiation, gastrointestinal stromal tumor as well as MUC4. Whole-exome sequencing revealed no recurrent somatic mutations or amplifications/homozygous deletions in any known oncogenes or tumor suppressor genes. RNA-sequencing and the Archer FusionPlex assay did not detect any recurrent likely pathogenic gene fusions. Single sample gene set enrichment analysis revealed that these tumors display a likely mesenchymal transcriptomic program. Unsupervised analysis (t-SNE) of their methylation profiles against a set of different mesenchymal neoplasms demonstrated a distinct methylation pattern. Here, we describe pancreatic neoplasms with unique morphologic/immunophenotypic features and a distinct methylation pattern, along with a lack of abnormalities in any of key genetic drivers, supporting that these neoplasms represent a novel entity with an indolent clinical course. Given their mesenchymal transcriptomic features, we propose the designation of "sclerosing epithelioid mesenchymal neoplasm" of the pancreas.