Novel Ultrastructural Insights into the Clear-Cell Carcinoma of the Pancreas: A Case Report.

Pancreatic cancer, most frequently as ductal adenocarcinoma (PDAC), is the third leading cause of cancer death. Clear-cell primary adenocarcinoma of the pancreas (CCCP) is a rare, aggressive, still poorly characterized subtype of PDAC. We report here a case of a 65-year-old male presenting with pancreatic neoplasia. A histochemical examination of the tumor showed large cells with clear and abundant intracytoplasmic vacuoles. The clear-cell foamy appearance was not related to the hyperproduction of mucins. Ultrastructural characterization with transmission electron microscopy revealed the massive presence of mitochondria in the clear-cell cytoplasm. The mitochondria showed disordered cristae and various degrees of loss of structural integrity. Immunohistochemistry staining for NADH dehydrogenase [ubiquinone] 1 alpha subcomplex, 4-like 2 (NDUFA4L2) proved specifically negative for the clear-cell tumor. Our ultrastructural and molecular data indicate that the clear-cell nature in CCCP is linked to the accumulation of disrupted mitochondria. We propose that this may impact on the origin and progression of this PDAC subtype.

Artificial intelligence-based algorithms for the diagnosis of prostate cancer: A systematic review.

OBJECTIVES: The high incidence of prostate cancer causes prostatic samples to significantly affect pathology laboratories workflow and turnaround times (TATs). Whole-slide imaging (WSI) and artificial intelligence (AI) have both gained approval for primary diagnosis in prostate pathology, providing physicians with novel tools for their daily routine. METHODS: A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was carried out in electronic databases to gather the available evidence on the application of AI-based algorithms to prostate cancer. RESULTS: Of 6290 articles, 80 were included, mostly (59%) dealing with biopsy specimens. Glass slides were digitized to WSI in most studies (89%), roughly two-thirds of which (66%) exploited convolutional neural networks for computational analysis. The algorithms achieved good to excellent results about cancer detection and grading, along with significantly reduced TATs. Furthermore, several studies showed a relevant correlation between AI-identified histologic features and prognostic predictive variables such as biochemical recurrence, extraprostatic extension, perineural invasion, and disease-free survival. CONCLUSIONS: The published evidence suggests that AI can be reliably used for prostate cancer detection and grading, assisting pathologists in the time-consuming screening of slides. Further technologic improvement would help widening AI's adoption in prostate pathology, as well as expanding its prognostic predictive potential.

A diffuse glioma with oligodendroglial-like cells and extensive calcifications.

The tumor showed extensive microcalcifications and cells with oval, nuclei and a clear perinuclear halo (A), positive immunostaining for OLIG-2 (B), GFAP (C), and CD34 (D), and intermingled Neu-N-positive neurons (E). FISH revealed multiple signals for the centromere of chromosome 7 (gains) (green probe) and the EGFR locus (red probe) (F, left), and a single signal for the centromere of chromosome 10 (loss) (F, right).

Clinical and Genomic Characterization of Pancreatic Ductal Adenocarcinoma with Signet-Ring/Poorly Cohesive Cells.

Signet-ring cell (SRC)/poorly cohesive cell carcinoma is an aggressive variant of pancreatic ductal adenocarcinoma (PDAC). This study aimed to clarify its clinicopathologic and molecular profiles based on a multi-institutional cohort of 20 cases. The molecular profiles were investigated using DNA and RNA sequencing. The clinicopathologic parameters and molecular alterations were analyzed based on survival indices and using a validation/comparative cohort of 480 conventional PDAC patients. The primary findings were as follows: (1) clinicopathologic features: SRC carcinomas are highly aggressive neoplasms with poor prognosis, and the lungs are elective metastatic sites; (2) survival analysis: a higher SRC component was indicative of poorer prognosis. In particular, the most clinically significant threshold of SRC was 80%, showing statistically significant differences in both disease-specific and disease-free survival; (3) genomic profiles: SRC carcinomas are similar to conventional PDAC with the most common alterations affecting the classic PDAC drivers KRAS (70% of cases), TP53 (55%), SMAD4 (25%), and CDKN2A (20%). EGFR alterations, RET::CCDC6 fusion gene, and microsatellite instability (3 different cases, 1 alteration per case) represent novel targets for precision oncology. The occurrence of SMAD4 mutations was associated with poorer prognosis; (4) pancreatic SRC carcinomas are genetically different from gastric SRC carcinomas: CDH1, the classic driver gene of gastric SRC carcinoma, is not altered in pancreatic SRC carcinoma; (5) transcriptome analysis: the cases clustered into 2 groups, one classical/exocrine-like, and the other squamous-like; and (6) SRC carcinoma-derived organoids can be successfully generated, and their cultures preserve the histologic and molecular features of parental SRC carcinoma. Although pancreatic SRC carcinoma shares similarities with conventional PDAC regarding the most important genetic drivers, it also exhibits important differences. A personalized approach for patients with this tumor type should consider the clinical relevance of histologic determination of the SRC component and the presence of potentially actionable molecular targets.

Characterization and digital spatial deconvolution of the immune microenvironment of intraductal oncocytic papillary neoplasms (IOPN) of the pancreas.

Intraductal oncocytic papillary neoplasm (IOPN) of the pancreas is a distinct entity from intraductal papillary mucinous neoplasms (IPMNs) and is considered one of the precursor lesions of pancreatic cancer. Through immunohistochemistry (IHC) and an artificial intelligence (AI)-based approach, this study aims at characterizing its immune microenvironment. Whole-slide IHC was performed on a cohort of 15 IOPNs, 2 of which harboring an associated adenocarcinoma. The following markers were tested: CD3, CD4, CD8, CD20, CD68, CD163, PD-1, PD-L1, MLH1, PMS2, MSH2, and MSH6. The main findings can be summarized as follows: (i) CD8+ T lymphocytes were the predominant immune cells (p < 0.01); (ii) the vast majority of macrophages were concurrently CD68+ and CD163+; (iii) all tumors showed an activated PD-1/PD-L1 axis, but none had mismatch repair deficiency; (iv) AI-based analysis revealed the presence of 2 distinct regions in each case, namely, Re1, localized at the center of the tumor, and Re2, located at tumor periphery; (v) the infiltrating component of the 2 invasive IOPNs showed a smaller extent of Re1 and a reduced rate of CD4+ cells, as well as a larger extent of Re2 and increased rate of CD8+ cells. IOPNs are lesions enriched in immune cells, with a predominance of CD8+ T lymphocytes and class 2 macrophages. Differently from IPMN-oncogenesis, the progression towards invasive carcinoma is accompanied by an increased rate of CD8+ lymphocytes. This finding may suggest the presence of an active self-immune surveillance in invasive IOPNs, potentially explaining, at least in part, the excellent survival rate of IOPN patients.

Extrahepatic Distal Cholangiocarcinoma vs. Pancreatic Ductal Adenocarcinoma: Histology and Molecular Profiling for Differential Diagnosis and Treatment.

Pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are very aggressive tumors with a high mortality rate. Pancreas and distal bile ducts share a common embryonic development. Hence, PDAC and dCCA exhibit similar histological features that make a differential diagnosis during routine diagnostic practice challenging. However, there are also significant differences, with potential clinical implications. Even if PDAC and dCCA are generally associated with poor survival, patients with dCCA seem to present a better prognosis. Moreover, although precision oncology-based approaches are still limited in both entities, their most important targets are different and include alterations affecting BRCA1/2 and related genes in PDAC, as well as HER2 amplification in dCCA. Along this line, microsatellite instability represents a potential contact point in terms of tailored treatments, but its prevalence is very low in both tumor types. This review aims at defining the most important similarities and differences in terms of clinicopathological and molecular features between these two entities, also discussing the main theranostic implications derived from this challenging differential diagnosis.

An Insight on Functioning Pancreatic Neuroendocrine Neoplasms.

Pancreatic neuroendocrine neoplasms (PanNENs) are rare neoplasms arising from islets of the Langerhans in the pancreas. They can be divided into two groups, based on peptide hormone secretion, functioning and nonfunctioning PanNENs. The first group is characterized by different secreted peptides causing specific syndromes and is further classified into subgroups: insulinoma, gastrinoma, glucagonoma, somatostatinoma, VIPoma and tumors producing serotonin and adrenocorticotrophic hormone. Conversely, the second group does not release peptides and is usually associated with a worse prognosis. Today, although the efforts to improve the therapeutic approaches, surgery remains the only curative treatment for patients with PanNENs. The development of high-throughput techniques has increased the molecular knowledge of PanNENs, thereby allowing us to understand better the molecular biology and potential therapeutic vulnerabilities of PanNENs. Although enormous advancements in therapeutic and molecular aspects of PanNENs have been achieved, there is poor knowledge about each subgroup of functioning PanNENs.Therefore, we believe that combining high-throughput platforms with new diagnostic tools will allow for the efficient characterization of the main differences among the subgroups of functioning PanNENs. In this narrative review, we summarize the current landscape regarding diagnosis, molecular profiling and treatment, and we discuss the future perspectives of functioning PanNENs.