Background and aims: ChatGPT is a powerful artificial intelligence (AI) chatbot developed by the OpenAI research laboratory which is capable of analysing human input and generating human‐like responses. Early research into the potential application of ChatGPT in healthcare has focused mainly on clinical and administrative functions. The diagnostic ability and utility of ChatGPT in histopathology is not well defined. We benchmarked the performance of ChatGPT against pathologists in diagnostic histopathology, and evaluated the collaborative potential between pathologists and ChatGPT to deliver more accurate diagnoses.Methods and results: In Part 1 of the study, pathologists and ChatGPT were subjected to a series of questions encompassing common diagnostic conundrums in histopathology. For Part 2, pathologists reviewed a series of challenging virtual slides and provided their diagnoses before and after consultation with ChatGPT. We found that ChatGPT performed worse than pathologists in reaching the correct diagnosis. Consultation with ChatGPT provided limited help and information generated from ChatGPT is dependent on the prompts provided by the pathologists and is not always correct. Finally, we surveyed pathologists who rated the diagnostic accuracy of ChatGPT poorly, but found it useful as an advanced search engine.Conclusions: The use of ChatGPT4 as a diagnostic tool in histopathology is limited by its inherent shortcomings. Judicious evaluation of the information and histopathology diagnosis generated from ChatGPT4 is essential and cannot replace the acuity and judgement of a pathologist. However, future advances in generative AI may expand its role in the field of histopathology.

T-cell lymphomas arise from a single neoplastic clone and exhibit identical patterns of deletions in T-cell receptor (TCR) genes. Whole genome sequencing (WGS) data represent a treasure trove of information for the development of novel clinical applications. However, the use of WGS to identify clonal T-cell proliferations has not been systematically studied. In this study, based on WGS data, we identified monoclonal rearrangements (MRs) of T-cell receptors (TCR) genes using a novel segmentation algorithm and copy number computation. We evaluated the feasibility of this technique as a marker of T-cell clonality using T-cell lymphomas (TCL, n = 44) and extranodal NK/T-cell lymphomas (ENKTLs, n = 20), and identified 98% of TCLs with one or more TCR gene MRs, against 91% detected using PCR. TCR MRs were absent in all ENKTLs and NK cell lines. Sensitivity-wise, this platform is sufficiently competent, with MRs detected in the majority of samples with tumor content under 25% and it can also distinguish monoallelic from biallelic MRs. Understanding the copy number landscape of TCR using WGS data may engender new diagnostic applications in hematolymphoid pathology, which can be readily adapted to the analysis of B-cell receptor loci for B-cell clonality determination.

Purpose: Fusion-positive myoepithelial tumors (MET) are clinicopathologically heterogeneous and variably termed mixed tumors and myoepithelial carcinomas. As FET-rearranged METs lack ductal/epithelial differentiation, we test whether FET-rearranged METs are epigenetically distinct from adnexal PLAG1-rearranged METs, which we hypothesize to be analogues of salivary gland METs. Experimental Design: DNA methylation profiling from a multi-institutional cohort of 52 fusion-positive skin, soft-tissue, and bone MET cases was performed and compared with diverse tumor types, including salivary METs. The MET subgroups harbored EWSR1::KLF15, EWSR1/FUS::KLF17, EWSR1::PBX1, EWSR1::PBX3, EWSR1/FUS::POU5F1, SS18::POU5F1, EWSR1::ZNF444, and PLAG1 rearrangements. Pooled clinicopathologic and outcome analysis with new and published cases (total 185) was performed. Results: The MET subgroups showed significant heterogeneity in age, site, and histology. Specifically, EWSR1::KLF15 METs affected predominantly young children (<5 years); EWSR1::PBX1/PBX3 METs were enriched in skin/bone; and EWSR1/FUS::POU5F1, SS18::POU5F1, and EWSR1::KLF15 METs tended to display malignant histology. Conversely, PLAG1-rearranged tumors were predominantly benign, arising in older adults and located in the skin. DNA methylation profiling revealed that FET-rearranged METs were epigenetically related to SS18::POU5F1 METs and FET::NFATC2 sarcomas but entirely distinct from PLAG1-rearranged adnexal and salivary METs. Histologic features were correlated with the degree of genome-wide copy-number variation. The median disease-specific survival was shortest in SS18::POU5F1 (31 months), EWSR1::PBX3 (38 months), and EWSR1::KLF15 (45 months) METs. On multivariate analysis, age <25 years was a significant predictor of worse progression-free survival. Conclusions: FET-rearranged METs are epigenetically unrelated to cutaneous and salivary gland METs, and their malignant counterparts are best classified as sarcomas rather than carcinomas.