Plasmacytoid dendritic cells in the setting of myeloid neoplasms: Diagnostic guide to challenging pathologic presentations.

In this article, we describe three broad pathologic presentations of plasmacytoid dendritic cells (pDCs) that may be encountered in clinical practice, in which an association between pDCs and myeloid neoplasms is identified: (1) myeloid neoplasms with mature pDC expansion, most commonly seen in chronic myelomonocytic leukaemia (CMML); (2) myeloid neoplasms with pDC differentiation, in which pDCs show a spectrum of maturation from early immature pDCs to mature forms, most commonly seen in acute myeloid leukaemia (AML); (3) myeloid neoplasms associated with blastic plasmacytoid dendritic cell neoplasm (BPDCN), either stemming from the same precursor or representing an independent clonal process. Additionally, we also discuss AML with pDC-like phenotype, in which myeloblasts show immunophenotypic features that may mimic those seen in pDCs. Using these presentations, we provide a diagnostic algorithm for appropriate pathologic classification, while attempting to clarify and homogenize nomenclatures pertaining to different biologic states of pDCs.

Clinicopathologic Features of Therapy-Related Myeloid Neoplasms in Patients with Myeloma in the Era of Novel Therapies.

The development of therapy-related myeloid neoplasms (t-MN) is a rare complication that can occur in myeloma patients treated primarily with novel therapies. To better understand t-MNs in this context, we reviewed 66 such patients and compared them with a control group of patients who developed t-MN after cytotoxic therapies for other malignancies. The study group included 50 men and 16 women, with a median age of 68 years (range, 48-86 years). Therapies included proteasome inhibitors, immunomodulatory agents, and high-dose melphalan-based autologous stem cell transplantation (HDM-ASCT) in 64 (97%), 65 (98.5%), and 64 (97%) patients, respectively; 29 (43.9%) patients were exposed to other cytotoxic drugs besides HDM. The latency interval from therapy to t-MN was 4.9 years (range, 0.6-21.9 years). Patients who received HDM-ASCT in addition to other cytotoxic therapies had a longer latency period to t-MN compared with patients who only received HDM-ASCT (6.1 vs 4.7 years, P = .009). Notably, 11 patients developed t-MN within 2 years. Therapy-related myelodysplastic syndrome was the most common type of neoplasm (n = 60), followed by therapy-related acute myeloid leukemia (n = 4) and myelodysplastic syndrome/myeloproliferative neoplasm (n = 2). The most common cytogenetic aberrations included complex karyotypes (48.5%), del7q/-7 (43.9%), and/or del5q/-5 (40.9%). The most frequent molecular alteration was TP53 mutation, in 43 (67.2%) patients and the sole mutation in 20 patients. Other mutations included DNMT3A, 26.6%; TET2, 14.1%; RUNX1, 10.9%; ASXL1, 7.8%; and U2AF1, 7.8%. Other mutations in less than 5% of cases included SRSF2, EZH2, STAG2, NRAS, SETBP, SF3B1, SF3A1, and ASXL2. After a median follow-up of 15.3 months, 18 patients were alive and 48 died. The median overall survival after the diagnosis of t-MN in the study group was 18.4 months. Although the overall features are comparable to the control group, the short interval to t-MN (<2 years) underscores the unique vulnerable status of myeloma patients.

Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma.

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnostic question is the determination of chronic lymphocytic leukemia (CLL) progression to accelerated CLL (aCLL) or transformation to diffuse large B-cell lymphoma (Richter transformation; RT) in patients who develop progressive disease. The morphologic assessment of CLL, aCLL, and RT can be diagnostically challenging. Using established diagnostic criteria of CLL progression/transformation, we designed four artificial intelligence-constructed biomarkers based on cytologic (nuclear size and nuclear intensity) and architectural (cellular density and cell to nearest-neighbor distance) features. We analyzed the predictive value of implementing these biomarkers individually and then in an iterative sequential manner to distinguish tissue samples with CLL, aCLL, and RT. Our model, based on these four morphologic biomarker attributes, achieved a robust analytic accuracy. This study suggests that biomarkers identified using artificial intelligence-based tools can be used to assist in the diagnostic evaluation of tissue samples from patients with CLL who develop aggressive disease features. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Artificial intelligence-assisted mapping of proliferation centers allows the distinction of accelerated phase from large cell transformation in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL) is characterized morphologically by numerous small lymphocytes and pale nodules composed of prolymphocytes and paraimmunoblasts known as proliferation centers (PCs). Patients with CLL can undergo transformation to a more aggressive lymphoma, most often diffuse large B-cell lymphoma (DLBCL), known as Richter transformation (RT). An accelerated phase of CLL (aCLL) also may be observed which correlates with subsequent transformation to DLBCL, and may represent an early stage of transformation. Distinguishing PCs in CLL from aCLL or RT can be diagnostically challenging, particularly in small needle biopsy specimens. Available guidelines pertaining to distinguishing CLL from its' progressive forms are limited, subject to the morphologist's experience and are often not completely helpful in the assessment of scant biopsy specimens. To objectively assess the extent of PCs in aCLL and RT, and enhance diagnostic accuracy, we sought to design an artificial intelligence (AI)-based tool to identify and delineate PCs based on feature analysis of the combined individual nuclear size and intensity, designated here as the heat value. Using the mean heat value from the generated heat value image of all cases, we were able to reliably separate CLL, aCLL and RT with sensitive diagnostic predictive values.

Clinicopathologic spectrum of myeloid neoplasms with concurrent myeloproliferative neoplasm driver mutations and SRSF2 mutations.

Myeloproliferative neoplasms (MPNs) are frequently associated with classic driver mutations involving JAK2, MPL or CALR. SRSF2 is among the most frequently mutated splicing genes in myeloid neoplasms and SRSF2 mutations are known to confer a poor prognosis in patients with MPNs. In this study, we sought to evaluate the clinicopathologic spectrum of myeloid neoplasms harboring concurrent MPN-driver mutations and SRSF2 mutations. The study cohort included 27 patients, 22 (82%) men and five (19%) women, with a median age of 71 years (range, 51-84). These patients presented commonly with organomegaly (n = 15; 56%), monocytosis (n = 13; 48%), morphologic dysplasia (n = 11; 41%), megakaryocytic hyperplasia and/or clustering (n = 10; 37%) and bone marrow fibrosis >MF-1 (17/22; 77%). About one third of patients either initially presented with acute myeloid leukemia (AML) or eventually progressed to AML. Eighteen (68%) patients had a dominant clone with SRSF2 mutation and nine (33%) patients had a dominant clone with a classic MPN-associated driver mutation. Our data suggest that the presence of an SRSF2 mutation preceding the acquisition of a MPN driver mutations is not a disease-defining alteration nor is it restricted to any specific disease entity within the spectrum of myeloid neoplasms. In summary, patients with myeloid neoplasms associated with concurrent SRSF2 and classic MPN driver mutations have clinical and morphologic features close to that of classic MPNs often with frequent dysplasia and monocytosis.

Primary mediastinal germ cell tumor and clonally related and unique hematologic neoplasms with i(12p) and TP53 mutation: A report of two cases.

The development of clonally related hematologic neoplasms in the setting of primary mediastinal germ cell tumors (PMGCTs) has been recognized previously and is associated with a dismal prognosis. However, the presentation of hematologic neoplasms as chronic myelomonocytic leukemia (CMML) and hemophagocytic lymphohistiocytosis (HLH) has been rarely reported. Here we report two patients with PMGCTs and hematologic neoplasms. The PMGCT was composed mostly of yolk sac tumor whereas the hematologic neoplasms had morphologic features that resembled CMML and HLH. The hematologic neoplasms from both patients harbored isochromosome 12p [i(12p)] and TP53 mutations, supporting a clonal relationship between these tumors. This association represents a unique clinical syndrome that likely contributes to the poor clinical outcome of these patients.

B-cell lymphoma/leukaemia 11B (BCL11B) expression status helps distinguish early T-cell precursor acute lymphoblastic leukaemia/lymphoma (ETP-ALL/LBL) from other subtypes of T-cell ALL/LBL.

B-cell lymphoma/leukaemia 11B (BCL11B) is an essential transcription factor for T-cell lineage commitment and maturation. We investigated BCL11B expression by immunohistochemistry in T-lymphoblastic leukaemia/lymphoma (T-ALL/LBL) (n = 115). The majority (83%) of early T-cell precursor T-ALL/LBL (ETP-ALL) cases showed negative BCL11B expression, while most (84%) of non-ETP-ALL/LBL were positive for BCL11B. A simplified three-marker [BCL11B, cluster of differentiation 5 (CD5), CD13] immunophenotypic score discriminated reliably between ETP-ALL and non-ETP-ALL/LBL. In ETP-ALL, patients with positive BCL11B expression had a better overall survival than those with negative BCL11B (P = 0·009). In summary, BCL11B is a valuable marker for T-ALL/LBL subtyping and serves as a potential prognostic marker in patients with ETP-ALL.

Next-Generation Scholarship: Rebranding Hematopathology Using Twitter: The MD Anderson Experience.

Hematopathologists are witnessing very exciting times, as a new era of unsurpassed technological advances is unfolding exponentially, enhancing our understanding of diseases at the genomic and molecular levels. In the evolving field of precision medicine, our contributions as hematopathologists to medical practice are of paramount importance. Social media platforms such as Twitter have helped facilitate and enrich our professional  interactions and collaborations with others in our field and in other medical disciplines leading to a more holistic approach to patient care. These platforms also have created a novel means for instantaneous dissemination of new findings and recent publications, and are proving to be increasingly useful tools that can be harnessed to expand our knowledge and amplify our presence in the medical community. In this Editorial, we share our experience as hematopathologists with Twitter, and how we leveraged this platform to boost scholarly activities within and beyond our subspecialty, and as a powerful medium for worldwide dissemination of educational material and to promote our remote teaching activities during the COVID-19 pandemic.

Outcome of T-cell acute lymphoblastic leukemia/lymphoma: Focus on near-ETP phenotype and differential impact of nelarabine.

Early T-cell precursor acute lymphoblastic leukemia/lymphoma (ETP-ALL/LBL) is characterized by a distinct immunophenotype (CD1a-negative, CD8-negative, CD5-negative or weak-positive <75%, myeloid/stem-cell markers positive) and poor clinical outcomes. Near-ETP ALL is transcriptionally similar to ETP-ALL but CD5 expression level is not low enough to meet the criteria of ETP immunophenotype. Outcomes of near-ETP ALL are not well characterized. We reviewed 171 patients with newly-diagnosed T-ALL/LBL. Patients were categorized into three groups; ETP (N = 27), near-ETP (N = 24), and non-ETP ALL/LBL (N = 120). ETP-ALL/LBL was associated with a significantly worse survival compared with non-ETP ALL/LBL: 5-year overall survival (OS) rates 32% versus 63% (p < .001). Outcome was similar between near-ETP and non-ETP ALL/LBL: 5-year OS rates 56% versus 63% (p = .543). Landmark analysis showed that allogeneic stem cell transplant (allo-SCT) in first remission was beneficial in ETP-ALL/LBL (5-year event-free survival rates 36% versus 18%, p = .030) but not in near-ETP or non-ETP ALL/LBL. Multivariate analysis selected the following as significant independent prognostic factors for OS: age ≥ 60 years (HR 3.11; p = .003); elevated WBC ≥100 × 109 /L (HR 2.60; p = .005); and ETP immunophenotype (HR 2.29; p = .010). A survival advantage with adding nelarabine to hyper-CVAD was observed in non-ETP ALL (5-year OS rates 83% versus 38% with hyper-CVAD plus neralabine versus hyper-CVAD, p = .003). In conclusion, outcome of ETP-ALL/LBL was poor and improved with allo-SCT; outcome of near-ETP ALL/LBL was similar to non-ETP ALL/LBL; the addition of nelarabine to hyper-CVAD improved the survival in non-ETP ALL only.

B-prolymphocytic leukemia: Is it time to retire this entity?

B-prolymphocytic leukemia (B-PLL) is included as a distinct entity in the current World Health Organization classification of hematolymphoid neoplasms. However, the diagnosis of B-PLL has presented several challenges since its conception, and over the past decades investigations of B-PLL have revealed substantial biologic and molecular heterogeneity. These data have shown that many B-PLL cases present many similarities with other types of small B-cell lymphomas, and that small B-cell lymphomas can undergo prolymphocytoid transformation. As a result, the frequency of B-PLL has markedly decreased, and currently B-PLL is a very rare entity. Most recent studies focused on B-PLL cases have been conducted on limited cohorts, precluding robust conclusions. In this article, we provide a concise historical review of B-PLL and describe the diagnostic and clinical challenges associated with establishing this diagnosis. We also argue that cases currently classified as B-PLL are unlikely to be a unique biologic entity, but rather represent a state of morphologic transformation characterized by many prolymphocytes that is shared by various types of small B-cell lymphoma.

Evolving insights into the genomic complexity and immune landscape of diffuse large B-cell lymphoma: opportunities for novel biomarkers.

Recently, comprehensive genomic analyses have allowed a better molecular characterization of diffuse large B-cell lymphoma (DLBCL), offering novel opportunities in patient risk stratification and management. In the era of precision medicine, this has allowed us to move closer toward a more promising therapeutic outcome in the setting of DLBCL. In this review, we highlight the newly reported heterogeneous mutational landscapes of DLBCL (from two whole-exome sequencing studies, and from a more recent work targeting a 293-gene of a hematologic malignancy-designed panel. Altogether, these studies provide further evidence of the clinical applicability of genomic tests. We also briefly review established biomarkers in DLBCL (e.g., MYC and TP53), and our understanding of the germinal center cell reaction, including its epigenetic regulation, emphasizing some of the key epigenetic modifiers that play a role in lymphomagenesis, with available therapeutic targets. In addition, we present current data regarding the role of immune landscapes in DLBCL (inflamed versus non-inflamed), how the recently defined molecular DLBCL subtypes may affect the cellular composition of the tumor microenvironment and the function of the immune cells, and how this new knowledge may result in promising therapeutic approaches in the near future.

Immunopathology of Kikuchi-Fujimoto disease: A reappraisal using novel immunohistochemistry markers.

AIMS: Kikuchi-Fujimoto disease (KFD) is a self-limited disease characterised by destruction of the lymph node parenchyma. Few studies have assessed the immunohistological features of KFD, and most employed limited antibody panels that lacked many of the novel immunohistochemistry markers currently available. METHODS AND RESULTS: We used immunohistochemistry to reappraise the microanatomical distribution of plasmacytoid dendritic cells (pDCs), follicular helper T cells and cytotoxic T cells, B cells, follicular dendritic cell (FDC) meshworks, and histiocytes in lymph nodes involved by KFD. The study group consisted of 138 KFD patients (89 women; 64.5%) with a median age of 27 years (range, 3-50 years). Cervical lymph nodes were most commonly involved, in 108 (78.3%) patients. The numbers of pDCs were increased, predominantly around and within apoptotic areas and the paracortex, and tapering off within xanthomatous areas. pDCs formed sizeable tight clusters, most notably around apoptotic/necrotic areas. T cells consisted mostly of CD8-positive cells with predominant expression of T-cell receptor-ß. There were notable increases in the numbers of CD8-positive T cells within lymphoid follicles, and their numbers correlated with alterations in FDC meshworks (P < 0.001). The number of follicular helper T cells was decreased within distorted FDC meshworks. CD21 highlighted frequent distortion of FDC meshworks, even in lymph node tissue that was distant from apoptotic/necrotic areas. Distorted FDC meshworks spanned all morphological patterns, and FDC meshwork characteristics (intact; distorted; remnant/nearly absent) correlated with morphological patterns (P < 0.01). CONCLUSIONS: The immunohistological landscape of KFD is complex and characterised by increased numbers of pDCs that frequently cluster around apoptotic/necrotic foci, increased numbers of cytotoxic T cells, and substantial distortion of FDC meshworks.

Lymphoid enhancer binding factor 1 (LEF1) expression is significantly higher in Hodgkin lymphoma associated with Richter syndrome relative to de novo classic Hodgkin lymphoma.

Lymphoid enhancer binding factor 1 (LEF1) is consistently upregulated in chronic lymphocytic leukemia (CLL) and in a subset of large B cell lymphoma. Knowledge of LEF1 expression in Hodgkin lymphoma is limited. In this study, we used immunohistochemistry to survey LEF1 expression in various subsets of Hodgkin lymphoma, de novo classic Hodgkin lymphoma (CHL) (n = 43), Hodgkin lymphoma associated with Richter syndrome (HL-RS) (n = 20), and nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) (n = 9). LEF1 expression was significantly higher in HL-RS compared with de novo CHL (12/20, 60% vs. 12/43, 28%; p = 0.0248). Only a single case (1/9; 11%) of NLPHL showed LEF1 expression. Epstein-Barr virus encoded RNA (EBER) was detected in 17 (40%) cases of de novo CHL and 14 (70%) HL-RS. Notably, we identified a correlation between LEF1 expression and EBER positivity (p = 0.0488). We concluded that LEF1 is commonly positive in CHL but not in NLPHL, and such a distinction may be helpful in this differential diagnosis. The higher frequency of LEF1 upregulation in HL-RS relative to de novo CHL suggests that these neoplasms might have different underlying pathogenic mechanisms and warrants further investigation.

Pituicytoma: Review of commonalities and distinguishing features among TTF-1 positive tumors of the central nervous system.

Pituicytoma is a rare low-grade glial neoplasm that originates in the distribution of the neurohypophysis, including the posterior pituitary lobe and infundibular stalk. The tumor cells resemble pituicytes, which are specialized glial cells of the neurohypophysis. Pituicytoma can be misdiagnosed pre-operatively as a pituitary adenoma due to overlapping clinical and neuroimaging features between these two entities. Pituicytoma can also mimic other neoplasms of the sellar and parasellar regions microscopically - meningioma, schwannoma and pilocytic astrocytoma - and shares immunohistochemical expression of TTF-1 with spindle cell oncocytoma and granular cell tumor of the sellar region, suggesting a common histogenesis. In this short review, we present the key features of pituicytoma, discuss commonalities and distinguishing features from other neoplasms of the sellar and parasellar regions and highlight the importance of recognizing this tumor entity for clinical and surgical management.

Flow Cytometry Profiling of Plasmacytoid Dendritic Cell Neoplasms.

In this review, we aim to provide a summary of the diverse immunophenotypic presentations of distinct entities associated with plasmacytoid dendritic cell (pDC) proliferation. These entities include the following: (1) blastic plasmacytoid dendritic cell neoplasm (BPDCN); (2) mature pDC proliferation (MPDCP), most commonly seen in chronic myelomonocytic leukemia (CMML); and (3) myeloid neoplasms with pDC differentiation, in which pDCs show a spectrum of maturation from early immature pDCs to mature forms, most commonly seen in acute myeloid leukemia (pDC-AML). Our aim is to provide a flow cytometry diagnostic approach to these distinct and sometimes challenging entities and to clarify the immunophenotypic spectrum of neoplastic pDCs in different disease presentations. In this review, we also cover the strategies in the evaluation of residual disease, as well as the challenges and pitfalls we face in the setting of immune and targeted therapy. The differential diagnosis will also be discussed, as blasts in some AML cases can have a pDC-like immunophenotype, mimicking pDCs.