Rare Occurrence of Classical Hodgkin's Disease as a T Cell Lymphoma

Recent work identified Hodgkin and Reed-Sternberg (H/RS) cells in classical Hodgkin's disease (cHD) as clonal progeny of mature B cells. Therefore, it is generally assumed that cHD homogenously represents a B cell lymphoma. In a subset of cHD, however, H/RS cells expressing T cell–associated proteins may be candidates for alternative lineage derivation. Single H/RS cells with cytotoxic T cell phenotype were micromanipulated from three cases of cHD and analyzed by single cell polymerase chain reaction for immunoglobulin heavy (IgH) and light chain (IgL) gene rearrangements, T cell receptor (TCR)-β gene rearrangements, and germline configuration of the IgH and TCR-β loci. H/RS cells from two cases of cHD harbored clonal, somatically mutated Ig gene rearrangements, whereas TCR-β loci were in germline configuration. In contrast, H/RS cells from an additional case harbored clonal TCR-β variable/diversity/joining (VDJ) and DJ gene rearrangements, whereas the IgH locus was in germline configuration on both alleles. Thus, in two cases of cHD with H/RS cells expressing cytotoxic T cell molecules, the tumor cells are derived from mature B cells that aberrantly express T cell markers. In a third case, however, H/RS cells were derived from a T cell, demonstrating that cHD can also occur as a T cell lymphoma

Pathologist computer-aided diagnostic scoring of tumor cell fraction: A Swiss national study.

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large inter-observer variability. It thus provides an ideal testbed to evaluate potential impacts of employing a computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n=69) were asked to visually estimate TCF in 10 regions of interest (ROI) from hematoxylin and eosin (H&E) colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD created overlay highlighting predicted tumor versus non-tumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tiers scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, inter-observer variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard-deviation of estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD, p < 0.0001. The intraclass correlation coefficient increased from 0.8 to 0.93 (CI95% [0.65, 0.93] vs [0.86, 0.98]) and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs. 4.17 ± 0.82 with CAD). TCFCAD estimation support demonstrated improved scoring accuracy, inter-pathologist agreement and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems