The Role of Tumor Microenvironment in the Pathogenesis of Sézary Syndrome

Sézary syndrome is an aggressive leukemic variant of cutaneous T-cell lymphomas, characterized by erythroderma, lymphadenopathy, and peripheral blood involvement by CD4+ malignant T-cells. The pathogenesis of Sézary syndrome is not fully understood. However, the course of the disease is strongly influenced by the tumor microenvironment, which is altered by a combination of cytokines, chemokines, and growth factors. The crosstalk between malignant and reactive cells affects the immunologic response against tumor cells causing immune dysregulation. This review focuses on the interaction of malignant Sézary cells and the tumor microenvironment.

Pediatric Patient With Neurological And Leukemic Peripheral Blood Involvement By Small Cell Variant Of ALK- Positive Anaplastic Large Cell Lymphoma (ALCL): Case Study

Casestudy Anaplastic large cell lymphoma (ALCL), is a T-cell lymphoma typically consisting of large lymphoid cells including characteristic horseshoe- shaped hallmark cells. The rare small cell morphological variant of ALCL may pose a challenge in diagnosis, especially when the initial presentation is unusual. Results Our patient, a 7-year-old girl presented with a headache. A complete blood count showed leukocytosis and anemia. The smear was reported to have segmented neutrophils, reactive lymphocytes, and monocytes. A spinal tap was performed and flow analysis identified a minute aberrant T cell population (0.3% of total), positive for CD3, CD4, bright CD7; negative CD5, CD8 in the CSF sample. The peripheral blood sample was reviewed again; some small- medium atypical lymphocytes, with irregular nuclear contours and cytoplasmic azurophilic granules were noted. Flow immunophenotyping displayed an aberrant T cell population positive for CD45, CD2, CD3, bright CD7, CD4, CD13; negative CD30, TdT CD5, CD8, CD117, CD34; consistent with T cell lymphoma/leukemia. A cell block prepared from peripheral blood sample showed blood with numerous atypical cells with irregular nuclei positive for ALK, CD30, CD3, CD4, CD7; negative CD5 and CD8. A diagnosis of leukemic ALK(+) ALCL was rendered, though classic hallmark cells were difficult to see. A marrow biopsy showed interstitial and sinusoidal pattern of mainly small to medium-sized cells with irregular nuclei. Molecular study revealed ALK gene alteration showing characteristic NPM1-ALK fusion. The patient underwent a bone bone marrow transplantation but recently relapsed with a submandibular lymph hode biopsy showing the presence of many larger ALCL cells. Conclusion Correct clinical diagnosis of the small-cell variant of ALCL is often challenging as the scarce “hallmark cells” are scattered and difficult to recognize. While leukemic peripheral blood involvement is rare in ALCL, an association has been reported with small-cell variants, which may be a potential explanation for the poor prognosis and aggressive nature of small-cell variant ALCL. A meticulous examination of peripheral blood smears, comprehensive immunophenotypic studies, and early bone marrow and lymph node/tissue biopsy are needed to facilitate diagnosis.

A Clinically Applicable Approach to the Classification of B-Cell Non-Hodgkin Lymphomas with Flow Cytometry and Machine Learning

The immunophenotype is a key element to classify B-cell Non-Hodgkin Lymphomas (B-NHL); while it is routinely obtained through immunohistochemistry, the use of flow cytometry (FC) could bear several advantages. However, few FC laboratories can rely on a long-standing practical experience, and the literature in support is still limited; as a result, the use of FC is generally restricted to the analysis of lymphomas with bone marrow or peripheral blood involvement. In this work, we applied machine learning to our database of 1465 B-NHL samples from different sources, building four artificial predictive systems which could classify B-NHL in up to nine of the most common clinico-pathological entities. Our best model shows an overall accuracy of 92.68%, a mean sensitivity of 88.54% and a mean specificity of 98.77%. Beyond the clinical applicability, our models demonstrate (i) the strong discriminatory power of MIB1 and Bcl2, whose integration in the predictive model significantly increased the performance of the algorithm; (ii) the potential usefulness of some non-canonical markers in categorizing B-NHL; and (iii) that FC markers should not be described as strictly positive or negative according to fixed thresholds, but they rather correlate with different B-NHL depending on their level of expression.

Peripheral Blood Involvement By Flow Cytometry As a Prognostic Factor in Aggressive T Cell Lymphomas Following Autologous Stem Cell Transplantation

Introduction: Aggressive T cell lymphomas (TCL) are a heterogenous group of lymphomas that are frequently associated with poor outcomes. Autologous stem cell transplantation (ASCT) is recommended according to the NCCN guidelines and by practice standards for most subtypes as a consolidation for patients in first remission. A large prospective study of up-front ASCT by the Nordic Lymphoma group identified age, ECOG performance status <2, and bone marrow involvement as important prognostic factors. We have identified peripheral blood involvement by flow cytometry at diagnosis in up to one third of patients with aggressive TCL and analyzed whether this was a prognostic factor for outcomes after ASCT. Methods: We retrospectively analyzed data from consecutively treated patients (pts) with aggressive T-cell lymphomas who underwent ASCT at our institution from July 2009 to February 2019. Patient and disease characteristics were summarized using descriptive statistics. Kaplan-Meier analysis was used to estimate progression free survival (PFS) that was defined as the time from SCT to the first evidence of recurrence, and overall survival (OS) that was defined as the time from SCT to death or last institutional follow up with a hematologist. We collected data on age, co-morbidities, disease subtype, stage, response to therapy and treatment both pre and post SCT. Flow cytometry was obtained at diagnosis and phenotype of atypical circulating cells was compared with immunophenotype from tumor biopsy specimens. Results: 50 pts with TCL who received ASCT were identified for this analysis. Of this population, 41 (80%) of pts had peripheral blood flow available at the time of initial diagnosis. T-cell lymphoma types included peripheral T cell lymphoma not otherwise specified (PTCL NOS, 17 pts), angioimmunoblastic T cell lymphoma (AITCL, 15pts), ALK negative anaplastic large cell lymphoma (ALCL, 1pt), enteropathy-type T-cell lymphoma (EATL, 2pts), extranodal natural killer T-cell lymphoma (NKTCL, 2pts) and panniculitis like T cell lymphoma (2 pts) (Table 1). Median age of the cohort was 62 years (range 20-75 years) and all patients included had an ECOG PS 0-1 at the time of diagnosis. The majority had stage 4 disease (36/41, 87.8%), but analysis included a small number of patients with stage 2 (1/41, 2.4%) and stage 3 (4/41,9.7%) disease. Bone marrow involvement by morphologic criteria was noted on bone marrow biopsy in 8/41 (19.5%) pts; bone marrow was negative in 28/41 or 61% pts and not evaluated in 8/41 or 19.5% pts. Flow cytometry of peripheral blood performed as part of initial staging was positive for circulating malignant cells in 13/41 pts (31.7%) at the time of diagnosis. All patients underwent ASCT in first remission. The median PFS and OS were 15.2 and 29.9 months respectively in the flow positive group, while neither median PFS nor OS were reached in the flow negative group (Figures 1 and 2). Flow cytometry results from time of diagnosis was not strongly associated with PFS (log rank, p = 0.39), however, it was associated with overall survival (log rank, p = 0.012). There were 11 deaths in the cohort- 4 in the flow negative group and 7 in the flow positive group. Further, when bone marrow involvement was evaluated, 7 of 13 pts with positive flow cytometry (53.8%) and 5 of 28 (17.8%) pts with negative flow cytometry had BM involvement, suggesting a correlation between positive bone marrow and detection of lymphoma cells in the peripheral blood at the time of diagnosis. Conclusions: We demonstrate in our cohort of patients that detection of circulating lymphoma cells at diagnosis by flow cytometry was associated with a worse outcome in patients with aggressive T cell lymphomas undergoing ASCT as a consolidation in first remission. Larger cohorts will be needed to validate these findings, but these results suggest peripheral blood involvement by sensitive flow cytometry may identify patients with worse outcomes who might benefit from a more aggressive strategy such as allogeneic stem cell transplantation or alternative consolidation strategies. Disclosures Huntington: Bayer: Consultancy, Honoraria; Pharmacyclics: Honoraria; Celgene: Consultancy, Research Funding; DTRM Biopharm: Research Funding; Genentech: Consultancy; AbbVie: Consultancy. Isufi:Celgene: Consultancy; Novartis: Consultancy; Astra Zeneca: Consultancy. Foss:Seattle Genetics: Consultancy, Other: fees for non-CME/CE services ; Mallinckrodt: Consultancy; miRagen: Consultancy; Spectrum: Other: fees for non-CME/CE services ; Eisai: Consultancy; Acrotech: Consultancy.