Multiomic analysis of familial adenomatous polyposis reveals molecular pathways associated with early tumorigenesis.

Familial adenomatous polyposis (FAP) is a genetic disease causing hundreds of premalignant polyps in affected persons and is an ideal model to study transitions of early precancer states to colorectal cancer (CRC). We performed deep multiomic profiling of 93 samples, including normal mucosa, benign polyps and dysplastic polyps, from six persons with FAP. Transcriptomic, proteomic, metabolomic and lipidomic analyses revealed a dynamic choreography of thousands of molecular and cellular events that occur during precancerous transitions toward cancer formation.

International Guidelines for Veterinary Tumor Pathology: A Call to Action.

Standardization of tumor assessment lays the foundation for validation of grading systems, permits reproducibility of oncologic studies among investigators, and increases confidence in the significance of study results. Currently, there is minimal methodological standardization for assessing tumors in veterinary medicine, with few attempts to validate published protocols and grading schemes. The current article attempts to address these shortcomings by providing standard guidelines for tumor assessment parameters and protocols for evaluating specific tumor types.

Agreement in Histological Assessment of Mitotic Activity Between Microscopy and Digital Whole Slide Images Informs Conversion for Clinical Diagnosis.

Validating digital pathology as substitute for conventional microscopy in diagnosis remains a priority to assure effectiveness. Intermodality concordance studies typically focus on achieving the same diagnosis by digital display of whole slide images and conventional microscopy. Assessment of discrete histological features in whole slide images, such as mitotic figures, has not been thoroughly evaluated in diagnostic practice.

Automated Computational Detection, Quantitation, and Mapping of Mitosis in Whole-Slide Images for Clinically Actionable Surgical Pathology Decision Support.

Background: Determining mitotic index by counting mitotic figures (MFs) microscopically from tumor areas with most abundant MF (hotspots [HS]) produces a prognostically useful tumor grading biomarker. However, interobserver concordance identifying MF and HS can be poorly reproducible. Immunolabeling MF, coupled with computer-automated counting by image analysis, can improve reproducibility.