ModPath Chat

Our host discusses with Drs. Shaomin Hu from Cleveland Clinic and Yue Xue MD PhD, from Case Western

Our host discusses with Dr. Anna Laury, from the Department of Pathology, University of Helsinki, Finland, her team's study on the utilization of AI-guided spatial transcriptomic analysis to allow for the biological interpretation of morphologic features detected by AI algorithms when applied to WSI of standard H&E sections.

The authors previously trained an AI model to identify HGSC (high-grade serous carcinoma of the ovary) tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. In the here discussed study, Dr. Laury’s team applied spatially resolved transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy.

Our host discusses with Drs. Prendeville and Selvarajah, from the departments of Laboratory Medicine and Pathobiology at the University of Toronto, their recent study on Pathologist-Driven somatic testing for DNA Damage Repair (DDR) in prostate carcinoma (PCa).

516 FFPE samples from metastatic and localized high risk PCa cases including needle biopsies, TURP and RP specimens were tested using a custom NGS panel of 83 cancer predisposition genes encompassing 4 Homologous Recombination Repair (HRR) genes [BRCA1/2, ATM, PALB2] and 4 Mismatch Repair (MRR) [MLH1, MSH2, MSH6, PMS2]. 13.9% of patients had at least one AMP/ASCO/CAP tier I or tier II variant, whereas 21.5% patients had a tier III variant. Tier I/II variant(s) were identified in 27% of metastatic biopsy samples and 13% of primary samples.

The presence of a tier I/II variant was not significantly associated with the grade group (GG) or presence of intraductal (IDC-P) /cribriform carcinoma in the primary tumor and therefore may not be reliable to guide patient selection.

Non-small cell lung carcinomas (NSCLCs) commonly present as 2 or more separate tumors. They encompass separate primary lung carcinomas (SPLCs), representing independently arising tumors, or intrapulmonary metastases (IPMs), representing intrapulmonary spread of a single tumor. In this episode, Dr. Natasha Rekhtman, from Memorial Sloan Kettering Cancer Ctr, NY provides an update on the growing applications of genomic testing as a clinically relevant benchmark for determining clonal relationships in multiple NSCLCs. She discusses the limitations of morphology-based distinction of SPLCs vs IPMs and the pivotal insights that have emerged from studying multiple NSCLCs using genomic approaches as a gold standard.

Our host discusses with Drs. Djerroudi and Vincent-Salomon, from the Institut Curie in Paris France, their recent study comparing HER2-negative invasive breast cancer of no special type (IBC-NST), with HER2-negative ILC.

In this episode, our host and Dr. Lisa Rooper from Johns Hopkins University, on behalf of her group of esteemed coauthors, discuss their recent study on the molecular characteristics of “Olfactory Carcinoma.” Targeted molecular profiling of 23 cases of the rare sinonasal tumor was performed to help clarify their pathogenesis and classification. The authors found recurrent Wnt pathway and ARID1A alterations, suggesting that sinonasal neuroendocrine and epithelial tumors may be best regarded as a histologic and molecular spectrum.

Integration of molecular analyses in routine diagnostics is the new practice paradigm of surgical pathology practice. The 2024 USCAP Long Course led by Dr. John Hart from the University of Chicago and Daniela Allende of Cleveland Clinic focuses on hepatic neoplasms and medical diseases where there are opportunities for ancillary molecular testing to refine the diagnosis and provide clinically relevant prognostic information. In this episode, the guests offer a preview of the long course sessions encompassing the utility of germline testing to identify liver disease risk alleles and the exciting potential of emerging technologies.

In this meet the expert episode, ModPath CHAT host Dr. George Netto discusses with Dr. Liron Pantanowitz, Chair of Pathology at UPMC and a pioneer leader in the field, his views on the current status and future direction of Digital Pathology. The conversation touches the various aspects of the digital transformation journey in AP, from infrastructure requirement to talent acquisition and training, regulatory hurdles and expectation of financial return on investments.

Flow cytometric analysis of blood & bone marrow for diagnosis of acute myelogenous leukemia (AML) relies heavily on manual intervention in the processing & analysis steps. Attention-based multi-instance learning models (ABMILMs) are deep learning models that make accurate predictions & generate interpretable insights regarding the classification of a sample from individual events.
The Drs. Olga Pozdnyakova and Joshua Lewis discuss their newly developed computational pipeline using ABMILMs for the automated diagnosis of AML cases based exclusively on flow cytometric data. The study is the first to illustrate the feasibility of using deep learning-based analysis of flow cytometric data for automated AML diagnosis & molecular characterization.

Modern Pathology is publishing a seminal series of review articles highlighting the recently completed fifth edition of the World Health Organization classification of hematolymphoid tumors (WHO-HEM5). In this episode of ModPath CHAT, Dr. Sanam Loghavi from The MD Anderson Cancer Center in Houston, discusses the major updates in the classification of myeloid neoplasms, providing a comparison with WHO-HEM4R, and offering guidance on how the new classification can be applied to the diagnosis of myeloid neoplasms in routine practice.