Large B-cell lymphomas with CCND1 rearrangement have different immunoglobulin gene breakpoints and genomic profile than mantle cell lymphoma.

Mantle cell lymphoma (MCL) is genetically characterized by the IG::CCND1 translocation mediated by an aberrant V(D)J rearrangement. CCND1 translocations and overexpression have been identified in occasional aggressive B-cell lymphomas with unusual features for MCL. The mechanism generating CCND1 rearrangements in these tumors and their genomic profile are not known. We have reconstructed the IG::CCND1 translocations and the genomic profile of 13 SOX11-negative aggressive B-cell lymphomas using whole genome/exome and target sequencing. The mechanism behind the translocation was an aberrant V(D)J rearrangement in three tumors and by an anomalous IGH class-switch recombination (CSR) or somatic hypermutation (SHM) mechanism in ten. The tumors with a V(D)J-mediated translocation were two blastoid MCL and one high-grade B-cell lymphoma. None of them had a mutational profile suggestive of DLBCL. The ten tumors with CSR/SHM-mediated IGH::CCND1 were mainly large B-cell lymphomas, with mutated genes commonly seen in DLBCL and BCL6 rearrangements in 6. Two cases, which transformed from marginal zone lymphomas, carried mutations in KLF2, TNFAIP3 and KMT2D. These findings expand the spectrum of tumors carrying CCND1 rearrangement that may occur as a secondary event in DLBCL mediated by aberrant CSR/SHM and associated with a mutational profile different from that of MCL.

Intratumoral Heterogeneity Assessment of the Extracellular Bone Matrix and Immune Microenvironment in Osteosarcoma Using Digital Imaging to Predict Therapeutic Response.

The assessment of chemotherapy response in osteosarcoma (OS) based on the average percentage of viable cells is limited, as it overlooks the spatial heterogeneity of tumor cell response (foci of resistant cells), immune microenvironment, and bone microarchitecture. Despite the resulting positive classification for response to chemotherapy, some patients experience early metastatic recurrence, demonstrating that our conventional tools for evaluating treatment response are insufficient. We studied the interactions between tumor cells, immune cells (lymphocytes, histiocytes, and osteoclasts), and bone extracellular matrix (ECM) in 18 surgical resection samples of OS using multiplex and conventional immunohistochemistry (IHC: CD8, CD163, CD68, and SATB2), combined with multiscale characterization approaches in territories of good and poor response (GRT/PRT) to treatment. GRT and PRT were defined as subregions with <10% and ≥10% of viable tumor cells, respectively. Local correlations between bone ECM porosity and density of immune cells were assessed in these territories. Immune cell density was then correlated to overall patient survival. Two patterns were identified for histiocytes and osteoclasts. In poor responder patients, CD68 osteoclast density exceeded that of CD163 histiocytes but was not related to bone ECM load. Conversely, in good responder patients, CD163 histiocytes were more numerous than CD68 osteoclasts. For both of them, a significant negative local correlation with bone ECM porosity was found (P < .01). Moreover, in PRT, multinucleated osteoclasts were rounded and intermingled with tumor cells, whereas in GRT, they were elongated and found in close contact with bone trabeculae. CD8 levels were always low in metastatic patients, and those initially considered good responders rapidly died from their disease. The specific recruitment of histiocytes and osteoclasts within the bone ECM, and the level of CD8 represent new features of OS response to treatment. The associated prognostic signatures should be integrated into the therapeutic stratification algorithm of patients after surgery.

Analysis by TeloView® Technology Predicts the Response of Hodgkin's Lymphoma to First-Line ABVD Therapy.

Classic Hodgkin's lymphoma (cHL) is a curable cancer with a disease-free survival rate of over 10 years. Over 80% of diagnosed patients respond favorably to first-line chemotherapy, but few biomarkers exist that can predict the 15-20% of patients who experience refractory or early relapsed disease. To date, the identification of patients who will not respond to first-line therapy based on disease staging and traditional clinical risk factor analysis is still not possible. Three-dimensional (3D) telomere analysis using the TeloView® software platform has been shown to be a reliable tool to quantify genomic instability and to inform on disease progression and patients' response to therapy in several cancers. It also demonstrated telomere dysfunction in cHL elucidating biological mechanisms related to disease progression. Here, we report 3D telomere analysis on a multicenter cohort of 156 cHL patients. We used the cohort data as a training data set and identified significant 3D telomere parameters suitable to predict individual patient outcomes at the point of diagnosis. Multivariate analysis using logistic regression procedures allowed for developing a predictive scoring model using four 3D telomere parameters as predictors, including the proportion of t-stumps (very short telomeres), which has been a prominent predictor for cHL patient outcome in a previously published study using TeloView® analysis. The percentage of t-stumps was by far the most prominent predictor to identify refractory/relapsing (RR) cHL prior to initiation of adriamycin, bleomycin, vinblastine, and dacarbazine (ABVD) therapy. The model characteristics include an AUC of 0.83 in ROC analysis and a sensitivity and specificity of 0.82 and 0.78 respectively.

Integrated spatial and multimodal single-cell transcriptomics reveal patient-dependent cell heterogeneity in splenic marginal zone lymphoma.

Biological hallmarks of splenic marginal zone lymphoma (SMZL) remain poorly described. Herein, we performed in-depth SMZL characterization through multimodal single-cell analyses of paired blood/spleen samples. The 3'-single-cell RNA-sequencing, Cellular Indexing of Transcriptomes and Epitopes by sequencing, and 5'-V(D)J single-cell RNA-sequencing datasets were integrated to characterize SMZL transcriptome profiles, including B-cell receptor and T-cell receptor repertoires. Hyperexpanded B-cell clones in the spleen were at a memory-like stage, whereas recirculating tumor B-cells in blood encompassed multiple differentiation stages, indicating an unexpected desynchronization of the B-cell maturation program in SMZL cells. Spatial transcriptomics showed the enrichment of T-effector and T-follicular helper (TFH) signatures in the nodular subtype of SMZL. This latter also exhibited gene-based cell-cell interactions suggestive of dynamic crosstalk between TFH and cancer cells in transcriptomics, further substantiated by using imaging mass cytometry. Our findings provide a comprehensive high-resolution description of SMZL biological hallmarks and characterize, for the first time in situ, inter- and intra-patient heterogeneity at both transcriptomic and protein levels. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images.

Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus weakening pathologists' trust in these tools. Technically, it is well known that microscopic images are altered by tissue processing and staining procedures, being one of the main sources of bias in machine learning for digital pathology. So as to deal with it, many teams have written about color normalization and augmentation methods. However, only a few of them have monitored their effects on bias reduction and model generalizability. In our study, two methods for stain augmentation (AugmentHE) and fast normalization (HEnorm) have been created and their effect on bias reduction has been monitored. Actually, they have also been compared to previously described strategies. To that end, a multicenter dataset created for breast cancer histological grading has been used. Thanks to it, classification models have been trained in a single center before assessing its performance in other centers images. This setting led to extensively monitor bias reduction while providing accurate insight of both augmentation and normalization methods. AugmentHE provided an 81% increase in color dispersion compared to geometric augmentations only. In addition, every classification model that involved AugmentHE presented a significant increase in the area under receiving operator characteristic curve (AUC) over the widely used RGB shift. More precisely, AugmentHE-based models showed at least 0.14 AUC increase over RGB shift-based models. Regarding normalization, HEnorm appeared to be up to 78x faster than conventional methods. It also provided satisfying results in terms of bias reduction. Altogether, our pipeline composed of AugmentHE and HEnorm improved AUC on biased data by up to 21.7% compared to usual augmentations. Conventional normalization methods coupled with AugmentHE yielded similar results while being much slower. In conclusion, we have validated an open-source tool that can be used in any deep learning-based digital pathology project on H&E whole slide images (WSI) that efficiently reduces stain-induced bias and later on might help increase pathologists' confidence when using AI-based products.

BCL3 rearrangements in B-cell lymphoid neoplasms occur in two breakpoint clusters associated with different diseases.

The t(14;19)(q32;q13) often juxtaposes BCL3 with immunoglobulin heavy chain (IGH) resulting in overexpression of the gene. In contrast to other oncogenic translocations, BCL3 rearrangement (BCL3-R) has been associated with a broad spectrum of lymphoid neoplasms. Here we report an integrative whole-genome sequence, transcriptomic, and DNA methylation analysis of 13 lymphoid neoplasms with BCL3-R. The resolution of the breakpoints at single base-pair revealed that they occur in two clusters at 5' (n=9) and 3' (n=4) regions of BCL3 associated with two different biological and clinical entities. Both breakpoints were mediated by aberrant class switch recombination of the IGH locus. However, the 5' breakpoints (upstream) juxtaposed BCL3 next to an IGH enhancer leading to overexpression of the gene whereas the 3' breakpoints (downstream) positioned BCL3 outside the influence of the IGH and were not associated with its expression. Upstream BCL3-R tumors had unmutated IGHV, trisomy 12, and mutated genes frequently seen in chronic lymphocytic leukemia (CLL) but had an atypical CLL morphology, immunophenotype, DNA methylome, and expression profile that differ from conventional CLL. In contrast, downstream BCL3-R neoplasms were atypical splenic or nodal marginal zone lymphomas (MZL) with mutated IGHV, complex karyotypes and mutated genes typical of MZL. Two of the latter four tumors transformed to a large B-cell lymphoma. We designed a novel fluorescence in situ hybridization assay that recognizes the two different breakpoints and validated these findings in 17 independent tumors. Overall, upstream or downstream breakpoints of BCL3-R are mainly associated with two subtypes of lymphoid neoplasms with different (epi)genomic, expression, and clinicopathological features resembling atypical CLL and MZL, respectively.

Exploring the basis of heterogeneity of cancer aggressiveness among the mutated POLE variants.

Germline pathogenic variants in the exonuclease domain of the replicative DNA polymerase Pol ε encoded by the POLE gene, predispose essentially to colorectal and endometrial tumors by inducing an ultramutator phenotype. It is still unclear whether all the POLE alterations influence similar strength tumorigenesis, immune microenvironment, and treatment response. In this review, we summarize the current understanding of the mechanisms and consequences of POLE mutations in human malignancies; we highlight the heterogeneity of mutation rate and cancer aggressiveness among POLE variants, propose some mechanistic basis underlining such heterogeneity, and discuss novel considerations for the choice and efficacy of therapies of POLE tumors.

Ultrafast Gene Fusion Assessment for Nonsquamous NSCLC.

Introduction: Gene fusion testing of ALK, ROS1, RET, NTRK, and MET exon 14 skipping mutations is guideline recommended in nonsquamous NSCLC (NS-NSCLC). Nevertheless, assessment is often hindered by the limited availability of tissue and prolonged next-generation sequencing (NGS) testing, which can protract the initiation of a targeted therapy. Therefore, the development of faster gene fusion assessment is critical for optimal clinical decision-making. Here, we compared two ultrafast gene fusion assays (UFGFAs) using NGS (Genexus, Oncomine Precision Assay, Thermo Fisher Scientific) and a multiplex reverse-transcriptase polymerase chain reaction (Idylla, GeneFusion Assay, Biocartis) approach at diagnosis in a retrospective series of 195 NS-NSCLC cases and five extrapulmonary tumors with a known NTRK fusion. Methods: A total of 195 NS-NSCLC cases (113 known gene fusions and 82 wild-type tumors) were included retrospectively. To validate the detection of a NTRK fusion, we added five NTRK-positive extrathoracic tumors. The diagnostic performance of the two UFGFAs and standard procedures was compared. Results: The accuracy was 92.3% and 93.1% for Idylla and Genexus, respectively. Both systems improved the sensitivity for detection by including a 5'-3' imbalance analysis. Although detection of ROS1, MET exon 14 skipping, and RET was excellent with both systems, ALK fusion detection was reduced with sensitivities of 87% and 88%, respectively. Idylla had a limited sensitivity of 67% for NTRK fusions, in which only an imbalance assessment was used. Conclusions: UFGFA using NGS and reverse-transcriptase polymerase chain reaction approaches had an equal level of detection of gene fusion but with some technique-specific limitations. Nevertheless, UFGFA detection in routine clinical care is feasible with both systems allowing faster initiation of therapy and a broad degree of screening.

Evolution in the definition and diagnosis of the Hodgkin lymphomas and related entities.

Hodgkin lymphoma was the first of the lymphomas to be recognized as a specific disease entity. However, recent studies have highlighted the heterogeneity of the diseases associated with this eponym warranting clarification and refinement of diagnostic terminology. While classic Hodgkin lymphoma (CHL) remains an essentially unchanged diagnostic entity in the 2022 International Consensus Classification of Mature Lymphoid Neoplasms (2022 ICC), nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is now renamed nodular lymphocyte predominant B cell lymphoma (NLPBL) in recognition of the distinct pathologic, biologic, and clinical differences. Fan patterns A, B, and C (sharing the presence of evident follicular structures, and retention of a B cell rich background) will be combined in "typical" or grade 1, while the other "variant" patterns, D, E, and F, are considered grade 2. T-cell/histiocyte-rich large B cell lymphoma (THRBCL) is considered part of the "variant" NLPHL continuum.The entity previously known as "B cell lymphoma, unclassifiable (BCLU), with features intermediate between diffuse large B cell lymphoma (DLBCL) and CHL" has been renamed "mediastinal gray zone lymphoma" (MGZL) in recognition of the importance of the thymic niche in the biology of this tumor. The diagnostic criteria for MGZL have been refined and require both a high tumor cell density and a strongly preserved B cell program.This article will describe updates on CHL, NLPBL, and MGZL in the recently published 2022 ICC and provide some useful differential diagnostic clues in cases with atypical morphology or immunophenotype.

Histological Subtypes Drive Distinct Prognostic Immune Signatures in Classical Hodgkin Lymphoma.

Despite the success of standard front-line chemotherapy, 20% of classical Hodgkin lymphoma (cHL) patients still relapse or have refractory disease (r/r), and a subset of them die due to disease progression. There is a critical lack of predictive factors for early identification of those r/r patients who may benefit from new therapeutic strategies. This study aimed to evaluate the dynamic expression of 586 immune-related genes in a cohort of 42 cHL patients including 30 r/r cHL after first-line chemotherapy. Gene expression profiling (GEP) using NanoString technology identified a 19-gene immune signature at diagnosis predictive of cHL relapse, but dependent on histological subtypes. Genes related to tumor survival were found upregulated while genes related to B-lineage were downregulated at diagnosis in r/r nodular sclerosis cHL. In contrast to the mixed-cellularity subtype, comparative GEP analyses between paired diagnosis/relapse biopsies of nodular sclerosis cHL showed 118 differentially expressed genes, supporting an immune contexture switch at relapse with upregulation of immunosuppressive cytokines, such as LGALS1 and TGFB1, and downregulation of the T-cell co-stimulatory receptor ICOS. These results indicate that the predictive value of immune signature in cHL is strongly influenced by histological subtype which should be considered when assessing new immunotherapy target strategies.

Lymph node excisions provide more precise lymphoma diagnoses than core biopsies: a French Lymphopath network survey.

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.

The International Consensus Classification of Mature Lymphoid Neoplasms: a report from the Clinical Advisory Committee.

Since the publication of the Revised European-American Classification of Lymphoid Neoplasms in 1994, subsequent updates of the classification of lymphoid neoplasms have been generated through iterative international efforts to achieve broad consensus among hematopathologists, geneticists, molecular scientists, and clinicians. Significant progress has recently been made in the characterization of malignancies of the immune system, with many new insights provided by genomic studies. They have led to this proposal. We have followed the same process that was successfully used for the third and fourth editions of the World Health Organization Classification of Hematologic Neoplasms. The definition, recommended studies, and criteria for the diagnosis of many entities have been extensively refined. Some categories considered provisional have now been upgraded to definite entities. Terminology for some diseases has been revised to adapt nomenclature to the current knowledge of their biology, but these modifications have been restricted to well-justified situations. Major findings from recent genomic studies have impacted the conceptual framework and diagnostic criteria for many disease entities. These changes will have an impact on optimal clinical management. The conclusions of this work are summarized in this report as the proposed International Consensus Classification of mature lymphoid, histiocytic, and dendritic cell tumors.

Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training-The Case of Cancer Detection.

The class distribution of a training dataset is an important factor which influences the performance of a deep learning-based system. Understanding the optimal class distribution is therefore crucial when building a new training set which may be costly to annotate. This is the case for histological images used in cancer diagnosis where image annotation requires domain experts. In this paper, we tackle the problem of finding the optimal class distribution of a training set to be able to train an optimal model that detects cancer in histological images. We formulate several hypotheses which are then tested in scores of experiments with hundreds of trials. The experiments have been designed to account for both segmentation and classification frameworks with various class distributions in the training set, such as natural, balanced, over-represented cancer, and over-represented non-cancer. In the case of cancer detection, the experiments show several important results: (a) the natural class distribution produces more accurate results than the artificially generated balanced distribution; (b) the over-representation of non-cancer/negative classes (healthy tissue and/or background classes) compared to cancer/positive classes reduces the number of samples which are falsely predicted as cancer (false positive); (c) the least expensive to annotate non-ROI (non-region-of-interest) data can be useful in compensating for the performance loss in the system due to a shortage of expensive to annotate ROI data; (d) the multi-label examples are more useful than the single-label ones to train a segmentation model; and (e) when the classification model is tuned with a balanced validation set, it is less affected than the segmentation model by the class distribution of the training set.

Gene Expression Signature Associated with Clinical Outcome in ALK-Positive Anaplastic Large Cell Lymphoma.

Anaplastic large cell lymphomas associated with ALK translocation have a good outcome after CHOP treatment; however, the 2-year relapse rate remains at 30%. Microarray gene-expression profiling of 48 samples obtained at diagnosis was used to identify 47 genes that were differentially expressed between patients with early relapse/progression and no relapse. In the relapsing group, the most significant overrepresented genes were related to the regulation of the immune response and T-cell activation while those in the non-relapsing group were involved in the extracellular matrix. Fluidigm technology gave concordant results for 29 genes, of which FN1, FAM179A, and SLC40A1 had the strongest predictive power after logistic regression and two classification algorithms. In parallel with 39 samples, we used a Kallisto/Sleuth pipeline to analyze RNA sequencing data and identified 20 genes common to the 28 genes validated by Fluidigm technology-notably, the FAM179A and FN1 genes. Interestingly, FN1 also belongs to the gene signature predicting longer survival in diffuse large B-cell lymphomas treated with CHOP. Thus, our molecular signatures indicate that the FN1 gene, a matrix key regulator, might also be involved in the prognosis and the therapeutic response in anaplastic lymphomas.

Molecular diagnosis of T-cell lymphoma: a correlative study of PCR-based T-cell clonality assessment and targeted NGS.

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.

Opposite Roles for ZEB1 and TMEJ in the Regulation of Breast Cancer Genome Stability.

Breast cancer cells frequently acquire mutations in faithful DNA repair genes, as exemplified by BRCA-deficiency. Moreover, overexpression of an inaccurate DNA repair pathway may also be at the origin of the genetic instability arising during the course of cancer progression. The specific gain in expression of POLQ, encoding the error-prone DNA polymerase Theta (POLθ) involved in theta-mediated end joining (TMEJ), is associated with a characteristic mutational signature. To gain insight into the mechanistic regulation of POLQ expression, this review briefly presents recent findings on the regulation of POLQ in the claudin-low breast tumor subtype, specifically expressing transcription factors involved in epithelial-to-mesenchymal transition (EMT) such as ZEB1 and displaying a paucity in genomic abnormality.

High-grade Follicular Lymphomas Exhibit Clinicopathologic, Cytogenetic, and Molecular Diversity Extending Beyond Grades 3A and 3B.

Although follicular lymphoma (FL) is usually graded as FL1-2, FL3A, and FL3B, some borderline cases can be observed and led us to investigate the clinicopathologic diversity of grade 3 FL (FL3). Among 2449 FL patients enrolled in Lymphoma Study Association (LYSA) trials, 1921 cases with sufficient material underwent a central pathologic review. The resulting diagnoses comprised 89.6% FL1-2 (n=1723), 7.2% FL3A (n=138), and 0.5% purely follicular FL3B (n=9). The remaining 51 unclassifiable cases (2.7%) exhibited high-grade features but did not meet WHO criteria for either FL3A or FL3B; and were considered as "unconventional" high-grade FL (FL3U). FL3U morphological pattern consisted of nodular proliferation of large cleaved cells or small-sized to medium-sized blast cells. Compared with FL3A, FL3U exhibited higher MUM1 and Ki67 expression, less BCL2 breaks and more BCL6 rearrangements, together with a higher number of cases without any BCL2, BCL6 or MYC rearrangement. FL3U harbored less frequent mutations in BCL2, KMT2D, KMT2B, and CREBBP than FL3A. MYC and BCL2 were less frequently mutated in FL3U than FL3B. Rituximab cyclophosphamide, doxorubicin, vincristine, and prednisone treated FL3U patients had a worse survival than FL1-2 patients with similar follicular lymphoma international prognostic index and treatment. These results suggest that high-grade FLs encompass a heterogeneous spectrum of tumors with variable morphology and genomic alterations, including FL3U cases that do not strictly fit WHO criteria for either FL3A or FL3B, and display a worse outcome than FL1-2. The distinction of FL3U may be useful to allow a better comprehension of high-grade FLs and to design clinical trials.

Epstein-Barr Virus-Associated T- and NK-Cell Lymphoproliferative Diseases: A Review of Clinical and Pathological Features.

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.

Management of T-Cell Lymphoma: In Quest of the Holy Grail.

T-cell lymphomas (TCL) represent a very heterogeneous group of lymphoid tumors which are clearly distinct from B-cell neoplasms [...].