Histopathological diagnosis of lymphomas represents a challenge requiring either expertise or centralised review, and greatly depends on the technical process of tissue sections. Hence, we developed an innovative deep-learning framework, empowered with a certainty estimation level, designed for haematoxylin and eosin-stained slides analysis, with special focus on follicular lymphoma (FL) diagnosis. Whole-slide images of lymph nodes affected by FL or follicular hyperplasia were used for training, validating, and finally testing Bayesian neural networks (BNN). These BNN provide a diagnostic prediction coupled with an effective certainty estimation, and generate accurate diagnosis with an area under the curve reaching 0.99. Through its uncertainty estimation, our network is also able to detect unfamiliar data such as other small B cell lymphomas or technically heterogeneous cases from external centres. We demonstrate that machine-learning techniques are sensitive to the pre-processing of histopathology slides and require appropriate training to build universal tools to aid diagnosis.

According to expert guidelines, lymph node surgical excision is the standard of care for lymphoma diagnosis. However, core needle biopsy (CNB) has become widely accepted as part of the lymphoma diagnostic workup over the past decades. The aim of this study was to present the largest multicenter inventory of lymph nodes sampled either by CNB or surgical excision in patients with suspected lymphoma and to compare their diagnostic performance in routine pathologic practice. We reviewed 32 285 cases registered in the French Lymphopath network, which provides a systematic expert review of all lymphoma diagnoses in France, and evaluated the percentage of CNB and surgical excision cases accurately diagnosed according to the World Health Organization classification. Although CNB provided a definitive diagnosis in 92.3% and seemed to be a reliable method of investigation for most patients with suspected lymphoma, it remained less conclusive than surgical excision, which provided a definitive diagnosis in 98.1%. Discordance rates between referral and expert diagnoses were higher on CNB (23.1%) than on surgical excision (21.2%; P = .004), and referral pathologists provided more cases with unclassified lymphoma or equivocal lesion through CNB. In such cases, expert review improved the diagnostic workup by classifying ∼90% of cases, with higher efficacy on surgical excision (93.3%) than CNB (81.4%; P < 10−6). Moreover, diagnostic concordance for reactive lesions was higher on surgical excision than CNB (P = .009). Overall, although CNB accurately diagnoses lymphoma in most instances, it increases the risk of erroneous or nondefinitive conclusions. This large-scale survey also emphasizes the need for systematic expert review in cases of lymphoma suspicion, especially in those sampled by using CNB.

Epstein–Barr virus (EBV) is a ubiquitous virus detected in up to 95% of the general population. Most people are asymptomatic, while some may develop a wide range of EBV-associated lymphoproliferative disorders (LPD). Among them, EBV-positive T/NK LPD are uncommon diseases defined by the proliferation of T- or NK-cells infected by EBV. The 2017 World Health Organization (WHO) classification recognizes the following entities characterized by different outcomes: chronic active EBV infection of T- or NK-cell types (cutaneous and systemic forms), systemic EBV-positive T-cell lymphoma of childhood, EBV-positive aggressive NK-cell leukemia, extra nodal NK/T-cell lymphoma nasal type, and the new provisional entity known as primary EBV-positive nodal T/NK-cell lymphoma. In addition, EBV associated-hemophagocytic lymphohistiocytosis is part of EBV-positive T/NK LPD, but has not been included in the WHO classification due to its reactive nature. Despite novel insights from high-throughput molecular studies, EBV-positive NK/T-cell LPD diagnoses remain challenging, especially because of their rarity and overlap. Until now, an accurate EBV-positive NK/T LPD diagnosis has been based on its clinical presentation and course correlated with its histological features. This review aims to summarize clinical, pathological and molecular features of EBV-positive T/NK LPD subtypes and to provide an overview of new understandings regarding these rare disorders.

Mast cells (MCs) are multifaceted innate immune cells often present in the tumor microenvironment (TME). However, MCs have been only barely characterized in studies focusing on global immune infiltrate phenotyping. Consequently, their role in cancer is still poorly understood. Furthermore, their prognosis value is confusing since MCs have been associated with good and bad (or both) prognosis depending on the cancer type. In this pilot study performed on a surgical cohort of 48 patients with Non-Small Cell Lung Cancer (NSCLC), we characterized MC population within the TME and in matching non-lesional lung areas, by multicolor flow cytometry and confocal microscopy. Our results showed that tumor-associated MCs (TAMCs) harbor a distinct phenotype as compared with MCs present in non-lesional counterpart of the lung. Moreover, we found two TAMCs subsets based on the expression of CD103 (also named alphaE integrin). CD103⁺ TAMCs appeared more mature, more prone to interact with CD4⁺ T cells, and located closer to cancer cells than their CD103⁻ counterpart. In spite of these characteristics, we did not observe a prognosis advantage of a high frequency of CD103⁺ TAMCs, while a high frequency of total TAMC correlated with better overall survival and progression free survival. Together, this study reveals that TAMCs constitute a heterogeneous population and indicates that MC subsets should be considered for patients’ stratification and management in future research.

Immunomorphological diagnosis of T-cell lymphoma (TCL) may be challenging, especially on needle biopsies. Multiplex polymerase chain reaction (PCR) assays to assess T-cell receptor (TCR) gene rearrangements are now widely used to detect T-cell clones and provide diagnostic support. However, PCR assays detect only 80% of TCL, and clonal lymphocyte populations may also appear in nonneoplastic conditions. More recently, targeted next-generation sequencing (t-NGS) technologies have been deployed to improve lymphoma classification. To the best of our knowledge, the comparison of these techniques’ performance in TCL diagnosis has not been reported yet. In this study, 82 TCL samples and 25 nonneoplastic T-cell infiltrates were divided into 2 cohorts (test and validation) and analyzed with both multiplex PCR and t-NGS to investigate TCR gene rearrangements and somatic mutations, respectively. The detection of mutations appeared to be more specific (100.0%) than T-cell clonality assessment (41.7%-45.5%), whereas no differences were observed in terms of sensitivity (95.1%-97.4%). Furthermore, t-NGS provided a reliable basis for TCL diagnosis in samples with partially degraded DNA that was impossible to assess with PCR. Finally, although multiplex PCR assays appeared to be less specific than t-NGS, both techniques remain complementary, as PCR recovered some t-NGS negative cases.