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.

Ferrero A, et al. J Gynecol Oncol. 2022 Aug;33:e77. https://doi.org/10.3802/jgo.2022.33.e77

Multiple myeloma (MM) is a hematological disease characterized by the proliferation and accumulation of malignant plasmacells (PCs) in the bone marrow (BM). Despite widespread use of high-dose chemotherapy in combination with autologous stem cell transplantation (ASCT) and the introduction of novel agents (immunomodulatory drugs, IMiDs, and proteasome inhibitors, PIs), the prognosis of MM patients is still poor. CD38 is a multifunctional cell-surface glycoprotein with receptor and ectoenzymatic activities. The very high and homogeneous expression of CD38 on myeloma PCs makes it an attractive target for novel therapeutic strategies. Several anti-CD38 monoclonal antibodies have been, or are being, developed for the treatment of MM, including daratumumab and isatuximab. Here we provide an in-depth look atCD38 biology, the role of CD38 in MM progression and its complex interactions with the BM microenvironment, the importance of anti-CD38 monoclonal antibodies, and the main mechanisms of antibody resistance. We then review a number of multiparametric flow cytometry techniques exploiting CD38 antigen expression on PCs to diagnose and monitor the response to treatment in MM patients.

Background: Lung cancer (LC) tissue for immunological characterization is often scarce. We explored and compared T cell characteristics between broncho-alveolar lavage from tumor affected (t-BAL) and contralateral lung (cl-BAL), with matched peripheral blood (PB). Methods: BAL and PB were collected during bronchoscopy for diagnostic and/or therapeutic purposes in patients with monolateral primary lesion. Results: Of 33 patients undergoing BAL and PB sampling, 21 had histologically-confirmed LC. Most cases were locally-advanced or metastatic non-small cell LC. T cell characteristics were not significantly different in t-BAL vs. cl-BAL. Compared to PB, CD8 T cells in BAL presented features of immune activation and exhaustion (high PD-1, low IFN-g production). Accordingly, regulatory CD4 T cells were also higher in BAL vs. PB. When dichotomizing T cell density in t-BAL in high and low, we found that PD-L1 expression in LC was associated with T cell density in t-BAL. T-BAL with high T cell density had higher %IFN-g+CD8 T cells and lower %T-regs. Conclusion: In BAL from advanced LC patients, T cells present features of exhaustion. T cells in t-BAL could be the best surrogate of tumor-infiltrating T cell, and future studies should evaluate T cell phenotype and density as potential biomarkers for cancer immunotherapy outcome.

The Turin Metropolitan Transplant Centre (CIC 305) includes four flow-cytometry laboratories assessing quality control on hematopoietic stem cells (HSC) with different instruments and operators. Therefore, the CD34+ enumeration assay should be validated on a regular basis. We describe here the validation plan to test the inter-laboratory reproducibility of CD34+ enumeration assay, based on the risk analysis. Stabilized blood samples were analysed using Stem-Kit reagent according to manufacturer's instructions and acquired using the Beckman Coulter Navios at Regina Margherita Children's' Hospital (305-1), Beckman Coulter FC500 at Candiolo Cancer Institute FPO-IRCCS (305-2), BD Biosciences FACSLyric™ at S. Luigi Hospital (305-3), and Beckman Coulter Navios EX at Mauriziano Hospital (305-4). The ISHAGE guidelines were followed for estimating % and absolute number of CD34+ cells in single-platform method. For each sample repeatability limit (r), reproducibility error, uncertainty of reproducibility error and coefficient of variation (CV) were reported. The repeated measurements from each laboratory or instrument have a variability, expressed as reproducibility error, lower than the repeatability limit for that single parameter. The corrected reproducibility error is always lower than the repeatability limit except for the percentage value of the "low" count. The analysis of inter-laboratory variance is within the maximum acceptable variance value, and the CV of all measurements for each parameter is less than 8%, indicating low measurement variability among laboratories. Evaluating the overall data, we can conclude that the four laboratories are perfectly aligned and the results are reproducible.