Applications and efficiency of flow cytometry for leukemia diagnostics

Flow cytometric detection of leukemic blasts in Libyan pediatric patients with acute lymphoblastic leukemia

The diagnosis of acute lymphoblastic leukemia (ALL), which is the most common type of cancer in children, has become more accurate with the use of flow cytometry. Here, this technology was used to immunophenotype leukemic cells in peripheral blood samples from Libyan pediatric ALL patients. We recruited 152 newly diagnosed patients at Tripoli Medical Center (Tripoli, Libya) by morphological examination of blood and bone marrow. Twenty-three surface and cytoplasmic antigen markers were used to characterize B and T cells in circulating blood cells by four-color flow cytometry. Six children (3.9%) turned out to have biphenotypic acute leukemia, 88 (57.9%) had B ALL, and 58 (38.1%) had T ALL. There were 68 cases of pro-B ALL CD10-positive (44.7%), 8 cases of pro-B ALL CD10-negative (5.2%), 6 cases of pre-B ALL (3.9%), and 6 of mature-B ALL (3.9%). CD13 was the most commonly expressed myeloid antigen in ALL. We present immunophenotypic data for the first time describing ALL cases in Libya. The reported results indicate that the most common subtype was pro-B ALL, and the frequency of T-ALL subtype was higher compared to previous studies. Six cases were positive for both myeloid and B lymphoid markers. Our findings may provide the basis for future studies to correlate immunophenotypic profile and genetic characteristics with treatment response among ALL patients.

Deep learning model for differentiating acute myeloid and lymphoblastic leukemia in peripheral blood cell images via myeloblast and lymphoblast classification

Objective

Acute leukemia (AL) is a life-threatening malignant disease that occurs in the bone marrow and blood, and is classified as either acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). Diagnosing AL warrants testing methods, such as flow cytometry, which require trained professionals, time, and money. We aimed to develop a model that can classify peripheral blood images of 12 cell types, including pathological cells associated with AL, using artificial intelligence.

Methods

We acquired 42,386 single-cell images of peripheral blood slides from 282 patients (82 with AML, 40 with ALL, and 160 with immature granulocytes).

Results

The performance of EfficientNet-V2 (B2) using the original image size exhibited the greatest accuracy (accuracy, 0.8779; precision, 0.7221; recall, 0.7225; and F1 score, 0.7210). The next-best accuracy was achieved by EfficientNet-V1 (B1), with a 256 × 256 pixels image. F1 score was the greatest for EfficientNet-V1 (B1) with the original image size. EfficientNet-V1 (B1) and EfficientNet-V2 (B2) were used to develop an ensemble model, and the accuracy (0.8858) and F1 score (0.7361) were improved. The classification performance of the developed ensemble model for the 12 cell types was good, with an area under the receiver operating characteristic curve above 0.9, and F1 scores for myeloblasts and lymphoblasts of 0.8873 and 0.8006, respectively.

Conclusions

The performance of the developed ensemble model for the 12 cell classifications was satisfactory, particularly for myeloblasts and lymphoblasts. We believe that the application of our model will benefit healthcare settings where the rapid and accurate diagnosis of AL is difficult.

Flow cell sorting followed by PCR-based clonality testing may assist in questionable diagnosis and monitoring of acute lymphoblastic leukemia

INTRODUCTION

Multicolor flow cytometry (MFC) has highly reliable and flexible algorithms for diagnosis and monitoring of acute lymphoblastic leukemia (ALL). However, MFC analysis can be affected by poor sample quality or novel therapeutic options (e.g., targeted therapies and immunotherapy). Therefore, an additional confirmation of MFC data may be needed. We propose a simple approach for validation of MFC findings in ALL by sorting questionable cells and analyzing immunoglobulin/T-cell receptor (IG/TR) gene rearrangements via EuroClonality-based multiplex PCR.

PATIENTS AND METHODS

We obtained questionable MFC results for 38 biological samples from 37 patients. In total, 42 cell populations were isolated by flow cell sorting for downstream multiplex PCR. Most of the patients (n = 29) had B-cell precursor ALL and were investigated for measurable residual disease (MRD); 79% of them received CD19-directed therapy (blinatumomab or CAR-T).

RESULTS

We established the clonal nature of 40 cell populations (95.2%). By using this technique, we confirmed very low MRD levels (<0.01% MFC-MRD). We also applied it to several ambiguous findings for diagnostic samples, including those with mixed-phenotype acute leukemia, and the results obtained impacted the final diagnosis.

CONCLUSION

We have demonstrated possibilities of a combined approach (cell sorting and PCR-based clonality assessment) to validate MFC findings in ALL. The technique is easy to implement in diagnostic and monitoring workflows, as it does not require isolation of a large number of cells and knowledge of individual clonal rearrangements. We believe it provides important information for further treatment.

Long-term stable disease with mFOLFOX6 chemotherapy plus cetuximab for bone marrow metastasis from rectal cancer: A case report

Bone marrow metastasis from rectal cancer is a rare but severe disease associated with a poor prognosis due to limited treatment options. There is no consensus on therapeutic strategies, and better-tolerated and more effective treatment options are urgently needed. We report a case that one patient with rectal cancer developed pancytopenia 15 months after completion of radical surgery and chemotherapy and was diagnosed with bone marrow metastasis. The patient was treated with mFOLFOX6 chemotherapy plus cetuximab, considering both his poor bone marrow function and a genetic test showing a wild-type of KRAS/NRAS/PIK3CA/BRAF. Twelve cycles were successfully completed with dose modifications and supportive measures. The patient's condition improved markedly based on a comprehensive assessment that included computed tomography images, blood cell counts, tumor markers, and clinical symptoms. The patient remains alive for 11 months at the last follow up. The patient treated with mFOLFOX6 chemotherapy plus cetuximab attained long-term stable disease, suggesting its promising efficacy and safety for bone marrow metastasis from rectal cancer and may hold promise as a treatment strategy for this specific patient population. Consideration can be given to the inclusion of mFOLFOX6 chemotherapy plus cetuximab in first-line treatment regimen for bone marrow metastasis from rectal cancer.

Enfermedad mínima residual por citometría de flujo en pacientes con leucemia linfoblástica aguda

Antecedentes. La citometría de flujo (CMF) es una técnica que permite el análisis multiparamétrico de poblaciones celulares, siendo esencial en la investigación biomédica y como herramienta diagnóstica. Esta técnica rápida tiene una alta sensibilidad, evaluandocaracterísticas en la población de interés como es el caso del tamaño, granularidad, complejidad del citoplasma celular y proteínas de que permiten la clasificación fenotípica y funcional de un gran número de células. Por estas razones, esta técnica ha adquiridoimportancia en el diagnóstico y seguimiento de enfermedades y anomalías hematológicas, como leucemias, síndromes mielodisplásicos y síndromes mieloproliferativos, entre otras. Objetivo. La presente revisión se enfoca en los avances en la implementación de la CMF en la Enfermedad Mínima Residual (EMR) presente en la Leucemia Linfoblástica Aguda (LLA), la cual es una población mínima leucémica que se detecta en un paciente después de suministrar un tratamiento oncológico, donde se evalúa su eficacia, el riesgo de una recaída y el proceso de remisión completa. Metodología. Se realiza una revisión no sistemática deliteratura en bases de datos, de los últimos 15 años, donde evalúen las implicaciones del uso de citometría de flujo en la EMR, de esta revisión se extraen aspectos relevantes al momento de emplear la CMF para el diagnóstico y seguimiento de pacientes con leucemias. Resultados. La CMF es una técnica muy versátil e importante para el diagnóstico y seguimiento de la EMR por su alta sensibilidad para la detección de bajos números de células resistentes a la terapia. Adicionalmente se muestra la importancia de la estandarización de protocolos como EUROFLOW para un adecuado procesamiento y análisis clínico de las muestras de pacientes.

A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges

Acute myeloid leukemia (AML) represents a heterogeneous group of hematopoietic neoplasms deriving from the abnormal proliferation of myeloid progenitors in the bone marrow. Patients with AML may have highly variable outcomes, which are generally dictated by individual clinical and genomic characteristics. As such, the European LeukemiaNet 2017 and 2022 guidelines categorize newly diagnosed AML into favorable-, intermediate-, and adverse-risk groups, based on their molecular and cytogenetic profiles. Nevertheless, the intermediate-risk category remains poorly defined, as many patients fall into this group as a result of their exclusion from the other two. Moreover, further genomic data with potential prognostic and therapeutic influences continue to emerge, though they are yet to be integrated into the diagnostic and prognostic models of AML. This review highlights the latest therapeutic advances and challenges that warrant refining the prognostic classification of intermediate-risk AML.

Vitamin C Deficiency in Patients With Acute Myeloid Leukemia

Vitamin C has been shown to play a significant role in suppressing progression of leukemia through epigenetic mechanisms. We aimed to study the role of vitamin C in acute myeloid leukemia (AML) biology and clinical course. To this purpose, the plasma levels of vitamin C at diagnosis in 62 patients with AML (including 5 cases with acute promyelocytic leukemia, APL),7 with myelodysplastic syndrome (MDS), and in 15 healthy donors (HDs) were studied. As controls, vitamins A and E levels were analysed. Expression of the main vitamin C transporters and of the TET2 enzyme were investigated by a specific RQ-PCR while cytoplasmic vitamin C concentration and its uptake were studied in mononuclear cells (MNCs), lymphocytes and blast cells purified from AML samples, and MNCs isolated from HDs. There were no significant differences in vitamin A and E serum levels between patients and HDs. Conversely, vitamin C concentration was significantly lower in AML as compared to HDs (p&lt;0.0001), inversely correlated with peripheral blast‐counts (p=0.029), significantly increased at the time of complete remission (CR) (p=0.04) and further decreased in resistant disease (p=0.002). Expression of the main vitamin C transporters SLC23A2, SLC2A1 and SLC2A3 was also significantly reduced in AML compared to HDs. In this line, cytoplasmic vitamin C levels were also significantly lower in AML-MNCs versus HDs, and in sorted blasts compared to normal lymphocytes in individual patients. No association was found between vitamin C plasma levels and the mutation profile of AML patients, as well as when considering cytogenetics or 2017 ELN risk stratification groups. Finally, vitamin C levels did not play a predictive role for overall or relapse-free survival. In conclusion, our study shows that vitamin C levels are significantly decreased in patients with AML at the time of initial diagnosis, further decrease during disease progression and return to normal upon achievement of CR. Correspondingly, low intracellular levels may mirror increased vitamin C metabolic consumption in proliferating AML cells.

Diagnosis of Acute Leukemia by Multiparameter Flow Cytometry with the Assistance of Artificial Intelligence

We developed an artificial intelligence (AI) model that evaluates the feasibility of AI-assisted multiparameter flow cytometry (MFC) diagnosis of acute leukemia. Two hundred acute leukemia patients and 94 patients with cytopenia(s) or hematocytosis were selected to study the AI application in MFC diagnosis of acute leukemia. The kappa test analyzed the consistency of the diagnostic results and the immunophenotype of acute leukemia. Bland–Altman and Pearson analyses evaluated the consistency and correlation of the abnormal cell proportion between the AI and manual methods. The AI analysis time for each case (83.72 ± 23.90 s, mean ± SD) was significantly shorter than the average time for manual analysis (15.64 ± 7.16 min, mean ± SD). The total consistency of diagnostic results was 0.976 (kappa (κ) = 0.963). The Bland–Altman evaluation of the abnormal cell proportion between the AI analysis and manual analysis showed that the bias ± SD was 0.752 ± 6.646, and the 95% limit of agreement was from −12.775 to 13.779 (p = 0.1225). The total consistency of the AI immunophenotypic diagnosis and the manual results was 0.889 (kappa, 0.775). The consistency and speedup of the AI-assisted workflow indicate its promising clinical application.

Major Differences in Lymphocyte Subpopulations Between Cerebrospinal Fluid and Peripheral Blood in Non-Hodgkin Lymphoma Without Leptomeningeal Involvement: Flow Cytometry Evidence of a Cerebral Lymphatic System

Cerebrospinal fluid (CSF) flow cytometry has a crucial role in the diagnosis of leptomeningeal disease in onco-hematology. This report describes the flow cytometry characterization of 138 CSF samples from patients affected by non-Hodgkin lymphoma, negative for disease infiltration. The aim was to focus on the CSF non-neoplastic population, to compare the cellular composition of the CSF with paired peripheral blood samples and to document the feasibility of flow cytometry in hypocellular samples. Despite the extremely low cell count (1 cell/µl, range 1.0-35) the study was successfully conducted in 95% of the samples. T lymphocytes were the most abundant subset in CSF (77%; range 20-100%) with a predominance of CD4-positive over CD8-positive T cells (CD4/CD8 ratio = 2) together with a minority of monocytes (15%; range 0-70%). No B cells were identified in 90% of samples. Of relevance, a normal, non-clonal B-cell population was documented in 5/7 (71%) patients with primary central nervous system lymphoma at diagnosis (p<0.0001), suggesting a possible involvement of blood-brain barrier cell permeability in the pathogenesis of cerebral B-cell lymphomas. The highly significant differences between CSF and paired peripheral blood lymphoid phenotype (p<0.0001) confirms the existence of an active mechanism of lymphoid migration through the meninges.

Advanced Flow Cytometry Assays for Immune Monitoring of CAR-T Cell Applications

Adoptive immunotherapy using chimeric antigen receptor (CAR)-T cells has achieved successful remissions in refractory B-cell leukemia and B-cell lymphomas. In order to estimate both success and severe side effects of CAR-T cell therapies, longitudinal monitoring of the patient's immune system including CAR-T cells is desirable to accompany clinical staging. To conduct research on the fate and immunological impact of infused CAR-T cells, we established standardized 13-colour/15-parameter flow cytometry assays that are suitable to characterize immune cell subpopulations in the peripheral blood during CAR-T cell treatment. The respective staining technology is based on pre-formulated dry antibody panels in a uniform format. Additionally, further antibodies of choice can be added to address specific clinical or research questions. We designed panels for the anti-CD19 CAR-T therapy and, as a proof of concept, we assessed a healthy individual and three B-cell lymphoma patients treated with anti-CD19 CAR-T cells. We analyzed the presence of anti-CD19 CAR-T cells as well as residual CD19+ B cells, the activation status of the T-cell compartment, the expression of co-stimulatory signaling molecules and cytotoxic agents such as perforin and granzyme B. In summary, this work introduces standardized and modular flow cytometry assays for CAR-T cell clinical research, which could also be adapted in the future as quality controls during the CAR-T cell manufacturing process.

A Flow Cytometry-Based Serological Assay to Detect Visceral Leishmaniasis in HIV-Infected Patients

Visceral Leishmaniasis (VL) is a severe parasitic disease that has emerged as an important opportunistic condition in HIV-infected patients and whose control is impaired by inaccurate identification. This is mainly due to the serological tests used for VL having a reduced performance in cases of VL-HIV coinfection due to a low humoral response. In this situation, however, a positive test has even greater diagnostic value when combined with the clinical status. This study aimed to evaluate the application and performance of flow cytometry to detect anti-Leishmania infantum antibodies in HIV-infected patients. Sera from VL/HIV coinfected patients, characterized using "gold standard" techniques, were compared with sera from healthy controls plus sera from HIV-infected individuals. The flow cytometry results were expressed as levels of IgG reactivity, based on the percentage of positive fluorescent parasites (PPFP). A ROC curve analysis of a serum titration indicated a PPFP of 1.26% as being the cutoff point to segregate positive and negative results. At the 1:2,048 dilution, with 89% sensitivity and 83% specificity, flow cytometry showed greater sensitivity in relation to the serological tests evaluated. Futhermore, flow cytometry was the only assay that positively identified all VL-HIV patients with quantified HIV load. Together, these findings suggest that flow cytometry may be used as an alternative serological approach for VL identification and as a tool to characterize the humoral response against Leishmania infantum in HIV-infected patients.

The diagnostic and prognostic value of MRI in central nervous system involvement of acute myeloid leukemia: a retrospective cohort of 84 patients

ABSTRACT Objective: To assess the diagnostic and prognostic value of magnetic resonance imaging (MRI) in Acute Myeloid Leukemia (AML) complicated with central nervous system leukemia (CNSL). Methods: A total of 84 patients with AML and confirmed of CNSL from January 2010 to September 2019 were selected and underwent MRI scan. We retrospectively analyzed their MRI findings, summarized the imaging features of AML central infiltration, and assessed the guiding significance of MRI on diagnosis and prognosis of this disease. Results: A total of 52 patients (61.90%, 52/84) had abnormal MRI findings, of which 31 cases clearly indicated intracranial infiltration of leukemia. Among the 31 patients, the most common site of infiltration is parenchyma (19/31). Most MRI of these patients showed multiple lesions with low T1 signal and high T2 signal, which were more obvious on enhanced scan. Sensitivity of MRI in diagnosing AML central infiltration was 36.90%. Despite of its low sensitivity, it still had superior diagnostic value on some patients with false-negative CSF. The median disease-free survival (DFS) and overall survival (OS) time of patients with MRI clearly indicated central invasion were 4 and 9 months, respectively. But there was no significant difference in survival analysis compared with MRI negative patients (including abnormal but non-invasive). Conclusion: MRI manifestation of central infiltration in AML patients has certain characteristic findings, which is helpful to improve the diagnostic efficiency. Prognosis of MRI positive patients is relatively worse than that of MRI negative patients however there is no siginificant difference.

Deep learning-based light scattering microfluidic cytometry for label-free acute lymphocytic leukemia classification

The subtyping of Acute lymphocytic leukemia (ALL) is important for proper treatment strategies and prognosis. Conventional methods for manual blood and bone marrow testing are time-consuming and labor-intensive, while recent flow cytometric immunophenotyping has the limitations such as high cost. Here we develop the deep learning-based light scattering imaging flow cytometry for label-free classification of ALL. The single ALL cells confined in three dimensional (3D) hydrodynamically focused stream are excited by light sheet. Our label-free microfluidic cytometry obtains big-data two dimensional (2D) light scattering patterns from single ALL cells of B/T subtypes. A deep learning framework named Inception V3-SIFT (Scale invariant feature transform)-Scattering Net (ISSC-Net) is developed, which can perform high-precision classification of T-ALL and B-ALL cell line cells with an accuracy of 0.993 ± 0.003. Our deep learning-based 2D light scattering flow cytometry is promising for automatic and accurate subtyping of un-stained ALL.