Despite an increase in the reports of intraductal papillary neoplasm of the bile duct (IPN-B), the clinical characteristics and long-term prognosis of this disease are not well known compared with those of intraductal papillary mucinous neoplasms of the pancreas. The objective of our study was to compare the clinical features, radiologic findings, and clinical outcomes of IPN-B according to histologic subtype. A retrospective analysis was performed on the medical records of 97 patients diagnosed with IPN-B by pathologic analysis of their surgical specimens between May 1995 and May 2010. We compared the clinical manifestations, radiological findings, pathologic grade, curative resection rate, recurrence, and overall survival according to four histologic subtypes: gastric (n=15), intestinal (n=46), pancreaticobiliary (n=33), and oncocytic (n=3), which were classified on the basis of hematoxylin and eosin staining and the immunohistochemical profile of mucin core proteins. Mucin hypersecretion was significantly more frequent in patients with gastric and intestinal types than it was in those with oncocytic and pancreaticobiliary types (P=0.014). There were no significant differences between groups regarding the presence of bile duct stones or tumor location. The frequency of invasive carcinoma in the pancreaticobiliary type was significantly higher than those in the gastric and intestinal types (72.7 vs. 26.7 and 32.6%, P<0.001 and P<0.001). When comparing the survival curves according to histologic subtype, patients with pancreaticobiliary type demonstrated significantly worse survival compared to those with gastric and intestinal types (P=0.035). Gastric and intestinal types of IPN-B have similar clinical characteristics compared with the pancreaticobiliary type, which has a worse prognosis.

SIRT1 (silent mating‐type information regulation 2 homologue 1)‐mediated cellular resistance to various stresses is negatively regulated by deleted in breast cancer 1 (DBC1), which was originally reported to be deleted in breast cancer. However, the suggested functions of SIRT1 as a potential tumor promoter and of DBC1 as a potential tumor suppressor have been challenged by observations of their respective down‐ and up‐regulation in various cancers. The aim of the present study was to simultaneously evaluate the expression levels of SIRT1 and DBC1 in the normal and tumor breast tissues from 28 breast cancer patients and to determine correlations with clinicopathological variables. SIRT1 and DBC1 expression was higher in tumor tissues than in matched normal tissues at the protein level, but not at the transcriptional level. Overexpression of SIRT1 and DBC1 in tumor tissue was correlated with favorable and unfavorable clinicopathological factors, suggesting their pleiotropic functions as a potential tumor promoter and tumor suppressor in tumorigenesis. Interestingly, although the overall expression of SIRT1 and DBC1 increased in tumor breast tissues, the correlation between SIRT1 and DBC1 expression was weaker in tumor tissue than in normal tissue. This suggests that the negative regulation of SIRT1 by DBC1 may retard tumorigenesis in breast tissue. Therefore, the correlation between SIRT1 and DBC1 is a potential prognostic indicator in breast cancer. (Cancer Sci 2010)

In histopathology, acquiring subcellular-level three-dimensional (3D) tissue structures efficiently and without damaging the tissues during serial sectioning and staining remains a formidable challenge. We address this by integrating holotomography with deep learning and creating 3D virtual hematoxylin and eosin (H&E) images from label-free thick cancer tissues. This method involves measuring the tissues’ 3D refractive index (RI) distribution using holotomography, followed by processing with a deep learning-based image translation framework to produce virtual H&E staining in 3D. Applied to colon cancer tissues up to 50 µm thick—far surpassing conventional slide thickness—this technique provides direct methodological validation through chemical H&E staining. It reveals quantitative 3D microanatomical structures of colon cancer with subcellular resolution. Further validation of our method’s repeatability and scalability is demonstrated on gastric cancer samples across different institutional settings. This innovative 3D virtual H&E staining method enhances histopathological efficiency and reliability, marking a significant advancement in extending histopathology to the 3D realm and offering substantial potential for cancer research and diagnostics.

Recent advances in spatial transcriptomics (ST) technologies have transformed our ability to profile gene expression while preserving crucial spatial context within tissues. However, existing ST platforms are constrained by high costs, long turnaround times, low resolution, limited gene coverage and inherently small tissue capture areas, which hinder their broad applications. Here we present iSCALE, a method that reconstructs large-scale, super-resolution gene expression landscapes and automatically annotates cellular-level tissue architecture in samples exceeding capture areas of current ST platforms. The performance of iSCALE was assessed by comprehensive evaluations involving benchmarking experiments, immunohistochemistry staining and manual annotations by pathologists. When applied to multiple sclerosis human brain samples, iSCALE uncovered lesion-associated cellular characteristics undetectable by conventional ST experiments. Our results demonstrate the utility of iSCALE in analyzing large tissues by enabling unbiased annotation, resolving cell type composition, mapping cellular microenvironments and revealing spatial features beyond the reach of standard ST analysis or routine histopathological assessment.