TRBC1 in flow cytometry: Assay development, validation, and reporting considerations

The assessment of T-cell clonality by flow cytometry has long been suboptimal, relying on aberrant marker expression and/or intensity. The introduction of TRBC1 shows much promise for improving the diagnosis of T-cell neoplasms in the clinical flow laboratory. Most laboratories considering this marker already have existing panels designed for T-cell workups and will be determining how best to incorporate TRBC1. We present this comprehensive summary of TRBC1 and supplemental case examples to familiarize the flow cytometry community with its potential for routine application, provide examples of how to incorporate it into T-cell panels, and signal caution in interpreting the results in certain diagnostic scenarios where appropriate.

Technical, gating and interpretation recommendations for the partitioning of circulating monocyte subsets assessed by flow cytometry

The monocyte subset partitioning by flow cytometry, known as "monocyte assay," is now integrated into the new classifications as a supporting criterion for CMML diagnosis, if a relative accumulation of classical monocytes above 94% of total circulating monocytes is observed. Here we provide clinical flow cytometry laboratories with technical support adapted for the most commonly used cytometers. Step-by-step explanations of the gating strategy developed on whole peripheral blood are presented while underlining the most common difficulties. In a second part, interpretation recommendations of circulating monocyte partitioning from the dedicated French working group "CytHem-LMMC" are shared as well as the main pitfalls, including false positive and false negative cases. The particular flow-defined inflammatory profile is described and the usefulness of the nonclassical monocyte specific marker, namely slan, highlighted. Examples of reporting to the physician with frequent situations encountered when using the monocyte assay are also presented.

Comparing malignant monocytosis across the updated WHO and ICC classifications of 2022

ABSTRACT

The World Health Organization (WHO) classification of hematolymphoid tumors and the International Consensus Classification (ICC) of 2022 introduced major changes to the definition of chronic myelomonocytic leukemia (CMML). To assess its qualitative and quantitative implications for patient care, we started with 3311 established CMML cases (according to WHO 2017 criteria) and included 2130 oligomonocytosis cases fulfilling the new CMML diagnostic criteria. Applying both 2022 classification systems, 356 and 241 of oligomonocytosis cases were newly classified as myelodysplastic (MD)-CMML (WHO and ICC 2022, respectively), most of which were diagnosed as myelodysplastic syndrome (MDS) according to the WHO 2017 classification. Importantly, 1.5 times more oligomonocytosis cases were classified as CMML according to WHO 2022 than based on ICC, because of different diagnostic criteria. Genetic analyses of the newly classified CMML cases showed a distinct mutational profile with strong enrichment of MDS-typical alterations, resulting in a transcriptional subgroup separated from established MD and myeloproliferative CMML. Despite a different cytogenetic, molecular, immunophenotypic, and transcriptional landscape, no differences in overall survival were found between newly classified and established MD-CMML cases. To the best of our knowledge, this study represents the most comprehensive analysis of routine CMML cases to date, both in terms of clinical characterization and transcriptomic analysis, placing newly classified CMML cases on a disease continuum between MDS and previously established CMML.

Classical meets malignant hematology: a case of acquired εγδβ-thalassemia in clonal hematopoiesis

Hemoglobinopathies including thalassemias are among the most frequent genetic disorders worldwide. Primarily, these entities result from germline variants in the globin gene clusters and their cis-acting regulatory elements, and thus the WHO classifies thalassemias as inherited diseases. Non-inherited disorders of globin chain synthesis mimicking the phenotype of thalassemias have also been described and are referred to as acquired thalassemias. These forms mainly affect the alpha-globin genes and are observed at much lower frequencies...

Recommendations for using artificial intelligence in clinical flow cytometry

Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are transferable to flow cytometry and have the potential to improve efficiency and prioritization of cases, reduce errors, and highlight fundamental, previously unrecognized associations with underlying biological processes. As a multidisciplinary group of stakeholders, we review a range of critical considerations for appropriately applying AI to clinical flow cytometry, including use case identification, low and high risk use cases, validation, revalidation, computational considerations, and the present regulatory frameworks surrounding AI in clinical medicine. In particular, we provide practical guidance for the development, implementation, and suggestions for potential regulation of AI-based methods in the clinical flow cytometry laboratory. We expect these recommendations to be a helpful initial framework of reference, which will also require additional updates as the field matures.

Translating the regulatory landscape of medical devices to create fit-for-purpose artificial intelligence (AI) cytometry solutions

The implementation of medical software and artificial intelligence (AI) algorithms into routine clinical cytometry diagnostic practice requires a thorough understanding of regulatory requirements and challenges throughout the cytometry software product lifecycle. To provide cytometry software developers, computational scientists, researchers, industry professionals, and diagnostic physicians/pathologists with an introduction to European Union (EU) and United States (US) regulatory frameworks. Informed by community feedback and needs assessment established during two international cytometry workshops, this article provides an overview of regulatory landscapes as they pertain to the application of AI, AI-enabled medical devices, and Software as a Medical Device in diagnostic flow cytometry. Evolving regulatory frameworks are discussed, and specific examples regarding cytometry instruments, analysis software and clinical flow cytometry in-vitro diagnostic assays are provided. An important consideration for cytometry software development is the modular approach. As such, modules can be segregated and treated as independent components based on the medical purpose and risk and become subjected to a range of context-dependent compliance and regulatory requirements throughout their life cycle. Knowledge of regulatory and compliance requirements enhances the communication and collaboration between developers, researchers, end-users and regulators. This connection is essential to translate scientific innovation into diagnostic practice and to continue to shape the development and revision of new policies, standards, and approaches.

The clinical and genomic landscape of patients with DDX41 variants identified during diagnostic sequencing

Deleterious germ line variants in DDX41 are a common cause of genetic predisposition to hematologic malignancies, particularly myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML). Targeted next-generation sequencing was performed in a large cohort of sequentially recruited patients with myeloid malignancy, covering DDX41 as well as 30 other genes frequently mutated in myeloid malignancy. Whole genome transcriptome sequencing data was analyzed on a separate cohort of patients with a range of hematologic malignancies to investigate the spectrum of cancer predisposition. Altogether, 5737 patients with myeloid malignancies were studied, with 152 different DDX41 variants detected. Multiple novel variants were detected, including synonymous variants affecting splicing as demonstrated by RNA-sequencing. The presence of a somatic DDX41 variant was highly associated with DDX41 germ line variants in patients with MDS and AML, and we developed a statistical approach to incorporate the co-occurrence of a somatic DDX41 variant into germ line variant classification at a very strong level (as per the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines). Using this approach, the MDS cohort contained 108 of 2865 (3.8%) patients with germ line likely pathogenic/pathogenic (LP/P) variants, and the AML cohort 106 of 2157 (4.9%). DDX41 LP/P variants were markedly enriched in patients with AML and MDS compared with those in patients with myeloproliferative neoplasms, B-cell neoplasm, and T- or B-cell acute lymphoblastic leukemia. In summary, we have developed a framework to enhance DDX41 variant curation as well as highlighted the importance of assessment of all types of genomic variants (including synonymous and multiexon deletions) to fully detect the landscape of possible clinically relevant DDX41 variants.

Interplay of TP53 allelic state, blast count, and complex karyotype on survival of patients with AML and MDS

Several clinical and genetic factors impact overall survival (OS) in myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML), including complex karyotype (CK), TP53 allelic state, and blast count. We analyzed the interplay of these factors by performing Cox regression analysis and by determining the frequency of TP53 single-hit (sh) and double-hit (dh) events and OS in MDS (n = 747) with <5% blasts, with ≥5% but <10% blasts, and ≥10% but <20% blasts and AML (n = 772). MDS with <5% blasts showed the best outcome, followed by with ≥5% but <10% blasts, and ≥10% but <20% blasts, and AML (median OS: 75, 54, 27, and 18 months, respectively). The same hierarchy was observed when each subgroup was divided into TP53sh, TP53dh, and without TP53 alterations (alt), revealing a dismal outcome of TP53dh in all subgroups (17, 10, 8, and 1 month[s], respectively). MDS with <5% blasts differed from the other subgroups by showing predominantly TP53sh (76% of TP53alt cases), and by an independent adverse impact of CK on OS (hazard ratio, 5.2; P < .001). The remaining subgroups displayed many similarities, with TP53dh found at high frequencies (67%, 91%, and 71%, respectively) and only TP53alt but not CK independently influencing OS, and TP53dh showing the strongest influence. When the total cohort was split based on TP53 state, only the blast count and not CK had an independent adverse impact on OS in all subgroups. Thus, TP53dh is the strongest prognostic factor, further supporting its integration into risk stratification guidelines and classification as a separate entity. However, the blast count also influences OS independent of TP53 state, whereas CK plays a minor prognostic role.

Surface-Initiated Polymerizations Mediated by Novel Germanium-Based Photoinitiators

Since surface-initiated photopolymerization techniques have gained increasing interest within the last decades, the coupling of photoinitiators to surfaces and particles has become an important research topic in material and surface sciences. In terms of surface modification and functionalization, covalently coupled photoinitiators and subsequent photopolymerizations are employed to provide a huge variety of surface properties, such as wettability, stimulus responsive features, antifouling behavior, protein binding, friction control, drug delivery, and many more. For this purpose, numerous type I and type II photoinitiators or other photosensitive moieties have been attached to different substrates so far. In our studies, a convenient and straightforward synthetic protocol to prepare a novel germanium-based photoinitiator (bromo-tris(2,4,6-trimethylbenzoyl)germane) in good yields was developed. The immobilization of this photoinitiator at the surface of silicon wafers and quartz plates was evidenced by X-ray photoelectron spectroscopy (XPS). Employing visible-light-triggered surface-initiated polymerization of different functional monomers, including acrylamide, perfluorodecyl acrylate, and fluorescein-o-acrylate, surfaces with various features such as hydrophilic/hydrophobic and fluorescent properties were prepared. This was also achieved in a spatially resolved manner. The polymer layers were characterized by contact angle measurements, UV-vis/fluorescence spectroscopy, spectroscopic ellipsometry, and XPS. The thicknesses of the surface grafted polymer layers ranged between 10 and 126 nm.

Real-World Validation of Molecular International Prognostic Scoring System for Myelodysplastic Syndromes

PURPOSE

Myelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M.

METHODS

A total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed.

RESULTS

IPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively).In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk.Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score.

CONCLUSION

IPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevant genes may facilitate the clinical implementation of the score.

AML classification in the year 2023: How to avoid a Babylonian confusion of languages

In parallel to the 5th edition of the World Health Organization Classification of Haematolymphoid Tumours (WHO 2022), an alternative International Consensus Classification (ICC) has been proposed. To evaluate the impact of the new classifications on AML diagnoses and ELN-based risk classification, we analyzed 717 MDS and 734 AML non-therapy-related patients diagnosed according to the revised 4th WHO edition (WHO 2017) by whole genome and transcriptome sequencing. In both new classifications, the purely morphologically defined AML entities decreased from 13% to 5%. Myelodysplasia-related (MR) AML increased from 22% to 28% (WHO 2022) and 26% (ICC). Other genetically-defined AML remained the largest group, and the abandoned AML-RUNX1 was mainly reclassified as AML-MR (WHO 2022: 77%; ICC: 96%). Different inclusion criteria of AML-CEBPA and AML-MR (i.a. exclusion of TP53 mutated cases according to ICC) were associated with differences in overall survival. In conclusion, both classifications focus on more genetics-based definitions with similar basic concepts and a large degree of agreement. The remaining non-comparability (e.g., TP53 mutated AML) needs additional studies to definitely answer open questions on disease categorization in an unbiased way.

Artificial intelligence in hematological diagnostics: Game changer or gadget?

The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve the integration of artificial intelligence (AI)-based systems into routine practice to support the hematologists' decision making. Several studies have shown that AI-based models can already be used to automatically differentiate cells, reliably detect malignant cell populations, support chromosome banding analysis, and interpret clinical variants, contributing to early disease detection and prognosis. However, even the best tool can become useless if it is misapplied or the results are misinterpreted. Therefore, in order to comprehensively judge and correctly apply newly developed AI-based systems, the hematologist must have a basic understanding of the general concepts of machine learning. In this review, we provide the hematologist with a comprehensive overview of various machine learning techniques, their current implementations and approaches in different diagnostic subfields (e.g., cytogenetics, molecular genetics), and the limitations and unresolved challenges of the systems.

Identification of a specific immunophenotype associated with a consistent pattern of genetic mutations including SRFS2 and gene expression profile in MDS

BACKGROUND

Myelodysplastic syndromes (MDS) comprise a heterogeneous group of diseases classified by comprehensive diagnostics. Identification of homogeneous subgroups is desirable to understand differences in clinical course and to develop targeted treatment approaches. We identified a specific CD11b/CD16 expression pattern in granulocytes associated with reduced CD45 expression in myeloid progenitor cells (MPC) in MDS cases and assessed its genetic background by whole genome (WGS) and whole transcriptome sequencing (WTS).

METHODS

The cohort consisted of 32 MDS cases with the specific aberrant immunophenotype. Since all these 32 cases were found to be SRSF2 mutated additional 51 SRSF2 mutated MDS cases without this specific immunophenotype were selected as controls. For all cases WGS and WTS were performed.

RESULTS

The immunophenotype newly identified in SRSF2 mutated MDS patients is characterized (1) by a specific maturation pattern, i.e. an increase of CD11b expression without CD16 expression followed by an increase in CD16 expression without further CD11b expression and (2) by only dim CD45 expression of MPC. STAG2 mutations were exclusively found in MDS cases with the specific immunophenotype (17/32, 53% vs. 0%, p < 0.001). Hence, >50% of cases with the specific immunophenotype were characterized by co-mutations in SRSF2 and STAG2. In addition, cluster analysis revealed a specific gene expression profile of such cases.

CONCLUSION

We here for the first time describe a specific immunophenotype which defines MDS cases with SRSF2 mutations and a consistent and specific mutational and gene expression profile. This comprehensive data warrants analysis of further such cases to assess the feasibility of defining a new sub-entity of MDS.

Novel causative variants of VEXAS in UBA1 detected through whole genome transcriptome sequencing in a large cohort of hematological malignancies

UBA1 is an X-linked gene and encodes an ubiquitin-activating enzyme. Three somatic mutations altering the alternative start codon (M41) in UBA1 in hematopoietic precursor cells have recently been described, resulting in a syndrome of severe inflammation, cytopenias, and the presence of intracellular vacuoles in hematopoietic precursors - termed VEXAS syndrome, a predominantly male disease. Here we present a patient with clinical features of VEXAS who harbored two novel somatic variants in UBA1 (I894S and N606I). To better understand the clinical relevance and biological consequences of non-M41 (UBA1^non-M41) variants, we analyzed the whole genome and transcriptome data of 4168 patients with hematological malignancies and detected an additional 16 UBA1^non-M41 putative somatic variants with a clear sex-bias in patients with myeloid malignancies. Patients diagnosed with myeloid malignancies carrying UBA1^non-M41 putative somatic variants either had vacuoles or immunodysregulatory symptoms. Analysis of the transcriptome confirmed neutrophil activation in VEXAS patients compared to healthy controls but did not result in a specific transcriptomic signature of UBA1^M41 patients in comparison with MDS patients. In summary, we have described multiple putative novel UBA1^non-M41 variants in patients with various hematological malignancies expanding the genomic spectrum of VEXAS syndrome.

Multiparameter flow cytometry in the evaluation of myelodysplasia: Analytical issues: Recommendations from the European LeukemiaNet/International Myelodysplastic Syndrome Flow Cytometry Working Group

Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow-up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work-up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34⁺ CD19^- ) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work-up. Looking forward, several machine-learning-based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine-learning-based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS.

Clinical application of flow cytometry in patients with unexplained cytopenia and suspected myelodysplastic syndrome: A report of the European LeukemiaNet International MDS-Flow Cytometry Working Group

This article discusses the rationale for inclusion of flow cytometry (FCM) in the diagnostic investigation and evaluation of cytopenias of uncertain origin and suspected myelodysplastic syndromes (MDS) by the European LeukemiaNet international MDS Flow Working Group (ELN iMDS Flow WG). The WHO 2016 classification recognizes that FCM contributes to the diagnosis of MDS and may be useful for prognostication, prediction, and evaluation of response to therapy and follow-up of MDS patients.

ELN iMDS flow working group validation of the monocyte assay for chronic myelomonocytic leukemia diagnosis by flow cytometry

BACKGROUND

It was proposed that peripheral blood (PB) monocyte profiles evaluated by flow cytometry, called "monocyte assay," could rapidly and efficiently distinguish chronic myelomonocytic leukemia (CMML) from other causes of monocytosis by highlighting an increase in the classical monocyte (cMo) fraction above 94%. However, the robustness of this assay requires a large multicenter validation and the assessment of its feasibility on bone marrow (BM) samples, as some centers may not have access to PB.

METHODS

PB and/or BM samples from patients displaying monocytosis were assessed with the "monocyte assay" by 10 ELN iMDS Flow working group centers with harmonized protocols. The corresponding files were reanalyzed in a blind fashion and the cMo percentages obtained by both analyses were compared. Confirmed diagnoses were collected when available.

RESULTS

The comparison between cMo percentages from 267 PB files showed a good global significant correlation (r = 0.88) with no bias. Confirmed diagnoses, available for 212 patients, achieved a 94% sensitivity and an 84% specificity. Hence, 95/101 CMML patients displayed cMo ≥94% while cMo <94% was observed in 83/99 patients with reactive monocytosis and in 10/12 patients with myeloproliferative neoplasms (MPN) with monocytosis. The established Receiver Operator Curve again provided a 94% cut-off value of cMo. The 117 BM files reanalysis led to an 87% sensitivity and an 80% specificity, with excellent correlation between the 43 paired samples to PB.

CONCLUSIONS

This ELN multicenter study demonstrates the robustness of the monocyte assay with only limited variability of cMo percentages, validates the 94% cutoff value, confirms its high sensitivity and specificity in PB and finally, also confirms the possibility of its use in BM samples.

Multicenter prospective evaluation of diagnostic potential of flow cytometric aberrancies in myelodysplastic syndromes by the ELN iMDS flow working group

BACKGROUND

Myelodysplastic syndromes (MDS) represent a diagnostic challenge. This prospective multicenter study was conducted to evaluate pre-defined flow cytometric markers in the diagnostic work-up of MDS and chronic myelomonocytic leukemia (CMML).

METHODS

Thousand six hundred and eighty-two patients with suspected MDS/CMML were analyzed by both cytomorphology according to WHO 2016 criteria and flow cytometry according to ELN recommendations. Flow cytometric readout was categorized 'non-MDS' (i.e. no signs of MDS/CMML and limited signs of MDS/CMML) and 'in agreement with MDS' (i.e., in agreement with MDS/CMML).

RESULTS

Flow cytometric readout categorized 60% of patients in agreement with MDS, 28% showed limited signs of MDS and 12% had no signs of MDS. In 81% of cases flow cytometric readouts and cytomorphologic diagnosis correlated. For high-risk MDS, the level of concordance was 92%. A total of 17 immunophenotypic aberrancies were found independently related to MDS/CMML in ≥1 of the subgroups of low-risk MDS, high-risk MDS, CMML. A cut-off of ≥3 of these aberrancies resulted in 80% agreement with cytomorphology (20% cases concordantly negative, 60% positive). Moreover, >3% myeloid progenitor cells were significantly associated with MDS (286/293 such cases, 98%).

CONCLUSION

Data from this prospective multicenter study led to recognition of 17 immunophenotypic markers allowing to identify cases 'in agreement with MDS'. Moreover, data emphasizes the clinical utility of immunophenotyping in MDS diagnostics, given the high concordance between cytomorphology and the flow cytometric readout. Results from the current study challenge the application of the cytomorphologically defined cut-off of 5% blasts for flow cytometry and rather suggest a 3% cut-off for the latter.

Flow cytometric analysis of myelodysplasia: Pre-analytical and technical issues-Recommendations from the European LeukemiaNet

BACKGROUND

Flow cytometry (FCM) aids the diagnosis and prognostic stratification of patients with suspected or confirmed myelodysplastic syndrome (MDS). Over the past few years, significant progress has been made in the FCM field concerning technical issues (including software and hardware) and pre-analytical procedures.

METHODS

Recommendations are made based on the data and expert discussions generated from 13 yearly meetings of the European LeukemiaNet international MDS Flow working group.

RESULTS

We report here on the experiences and recommendations concerning (1) the optimal methods of sample processing and handling, (2) antibody panels and fluorochromes, and (3) current hardware technologies.

CONCLUSIONS

These recommendations will support and facilitate the appropriate application of FCM assays in the diagnostic workup of MDS patients. Further standardization and harmonization will be required to integrate FCM in MDS diagnostic evaluations in daily practice.

SF3B1 mutated MDS: Blast count, genetic co-abnormalities and their impact on classification and prognosis

Recently, MDS with mutated SF3B1 and blast count <5% was proposed as distinct entity with favorable prognosis by the international working group for the prognosis of MDS (IWG-PM), the 5th edition of the WHO classification and the International Consensus Classification. To further characterize this entity with respect to the genomic landscape, AML transformation rate and clinical outcome, we analyzed 734 MDS patients by whole genome sequencing. SF3B1 mutations were identified in 31% (n = 231), most frequently accompanied by TET2 mutations (29%). 144/231 (62%) SF3B1mut samples fulfilled entity criteria proposed by IWG-PM (SF3B1ent). These cases were associated with longer survival, lower AML transformation rate, normal karyotypes and harbored less accompanying mutations compared to SF3B1mut samples not falling into the proposed SF3B1 entity (SF3B1nent). Of SF3B1mut cases 7% (15/231; SF3B1ent: 3/144 [2%]; SF3B1nent: 12/87 [14%]) progressed to AML compared to 15% SF3B1 wild-type patients (75/503). Of these 15 SF3B1mut cases, 10 (67%) showed RUNX1 mutations at MDS or AML stage. Multivariate analysis revealed that del(5q) and RUNX1 mutations were independent negative prognostic factors for overall survival, while blast count >5% was not. In conclusion, SF3B1mut MDS has a favorable prognosis independent of blast count if karyotype and RUNX1 mutations are considered.

A Bird's-Eye View on Polymer-Based Hydrogen Carriers for Mobile Applications

Globally, reducing CO2 emissions is an urgent priority. The hydrogen economy is a system that offers long-term solutions for a secure energy future and the CO2 crisis. From hydrogen production to consumption, storing systems are the foundation of a viable hydrogen economy. Each step has been the topic of intense research for decades; however, the development of a viable, safe, and efficient strategy for the storage of hydrogen remains the most challenging one. Storing hydrogen in polymer-based carriers can realize a more compact and much safer approach that does not require high pressure and cryogenic temperature, with the potential to reach the targets determined by the United States Department of Energy. This review highlights an outline of the major polymeric material groups that are capable of storing and releasing hydrogen reversibly. According to the hydrogen storage results, there is no optimal hydrogen storage system for all stationary and automotive applications so far. Additionally, a comparison is made between different polymeric carriers and relevant solid-state hydrogen carriers to better understand the amount of hydrogen that can be stored and released realistically.

Anti-Adhesive Organosilane Coating Comprising Visibility on Demand

There is a wide application field for anti-adhesive and hydrophobic coatings, stretching from self-cleaning surfaces over anti-graffiti and release coatings to demolding aids in the production of polymers. The typical materials for the latter are hard coatings, including TiN, CrN, diamond-like carbon, etc. Alternatively, organosilane coatings based on perfluorinated compounds or molecules with long alkyl side chains can be employed. Although these functional layers are generally required to be invisible, there is a demand for a straightforward approach, which enables the temporary control of successful and homogeneous application as well as abrasion and wear of the coatings during use. For this purpose, a visibility-on-demand property was introduced to an already established anti-adhesive organosilane coating by incorporation of 1,8-naphthalimide-N-propyltriethoxysilane (NIPTES) as a fluorescent marker molecule. While the naphthalimide unit provides blue fluorescence under UV irradiation, the ethoxy groups of NIPTES enable the covalent coupling to the coating as a result of the hydrolysis and condensation reactions. As a consequence, the fluorescent marker molecule NIPTES can simply be added to the coating solution as an additional organosilane component, without the need for changes in the approved deposition procedure. The generated fluorescent anti-adhesive coatings were characterized by contact angle measurements, atomic force microscopy (AFM), as well as by different spectroscopic techniques, including FTIR, UV-Vis, fluorescence and X-ray photoelectron spectroscopy (XPS). In addition, the on-demand control function provided by the introduced fluorescence properties was evaluated along an injection molding process.

A new method for successful indirect bonding in relation to bond strength

The aim of the work was to develop a new transfer method for indirect bonding of brackets to improve the bond strength by applying a uniform contact pressure over the entire dental arch. This has a great potential to reduce the bracket loss rate during clinical treatment. A suitable shape memory polymer (SMP) was selected and prepared in the chemistry laboratory. This SMP applies a force to the brackets during bonding and thus increases the bond strength by applying uniform contact pressure. Various transfer trays were equipped with SMP platelets and the transfer of brackets from the plaster model to the real human tooth model was performed in vitro. The transfer accuracy and bond strength of the bonded brackets were investigated by 3D-overlay and shear tests, respectively. The transfer accuracy was technique sensitive and showed higher accuracy for the trays with SMPs and self-curing silicones than for the vacuum formed trays with SMPs. The bond strength of the indirectly bonded brackets with SMPs was on average 1-2 MPa higher than the bond strength of the brackets indirectly bonded with a conventional two-layer vacuum formed tray without SMPs. Thus, transfer trays with SMPs can provide a significant improvement in bond strength during indirect bonding after appropriate adjustment.

Clinical relevance of molecular characteristics in Burkitt lymphoma differs according to age

While survival has improved for Burkitt lymphoma patients, potential differences in outcome between pediatric and adult patients remain unclear. In both age groups, survival remains poor at relapse. Therefore, we conducted a comparative study in a large pediatric cohort, including 191 cases and 97 samples from adults. While TP53 and CCND3 mutation frequencies are not age related, samples from pediatric patients showed a higher frequency of mutations in ID3, DDX3X, ARID1A and SMARCA4, while several genes such as BCL2 and YY1AP1 are almost exclusively mutated in adult patients. An unbiased analysis reveals a transition of the mutational profile between 25 and 40 years of age. Survival analysis in the pediatric cohort confirms that TP53 mutations are significantly associated with higher incidence of relapse (25 ± 4% versus 6 ± 2%, p-value 0.0002). This identifies a promising molecular marker for relapse incidence in pediatric BL which will be used in future clinical trials.

Abstract 5788: Genomic and transcriptomic profiles of DNA damage response genes in acute myeloid leukemia

The DNA damage response (DDR) pathway is frequently deregulated in cancer and it represent an attractive therapeutic opportunity. In acute myeloid leukemia (AML), different mechanisms of DDR deregulation have been identified, but a systematic investigation on DDR alterations is missing. To understand how the DDR pathways contribute to leukemogenesis, we studied the gene expression and mutational profiles of 274 DDR genes by analysing 539 AML cases profiled by whole genome (WGS) and RNA sequencing. WGS data were used to identify mutations in genes of the DDR and in a panel of genes known to be mutated in AML (n=73). Transcriptomic data were analysed through unsupervised clustering, differential expression and enrichment analysis. We detected 150 single nucleotide variants (SNVs) in 130 patients (24%, average 0.3 SNVs/case). Genes mutated in more than 1% of cases were ATM, BLM, BRCA2, POLG and POLQ. The most frequently altered pathway was the homologous recombination/Fanconi Anemia (HR) pathway (29%), followed by the genes that coordinates the DDR pathway (20%). We detected a trend toward mutual exclusivity between mutations in TP53 and mutations in genes of HR pathway or the genes that coordinates the DDR pathway (adj-p &lt;0.02). To further investigate the interplay between TP53 mutations and the HR pathway, we analysed the expression profiles of HR genes in 539 patients. We identified two groups of patients having higher (HR-high) or lower (HR-low) expression levels of HR genes. A panel of 5 genes was able to discriminate patients between the two groups (BRCA1, RAD54B, RMI2, UBE2T and XRCC2; AUC=0.9). Enrichment analysis on differentially expressed genes and gene set enrichment analysis showed that the cell cycle pathway, together with the G2/M transition/mitotic phase, E2F targets and the fatty acid metabolism pathways were upregulated in HR-high patients, while the pRB, EZH2, RPS14 and HOXA9 pathways were downregulated. Moreover, we observed that AML expressing CBFB-MYH1, RUNX1-RUNXT1 or carrying RAD21 mutations had higher chances to express lower levels of HR genes (HR-low), while patients with STAG2, SRSF2, U2AF1, FLT3-ITD alterations had higher chances of having higher expression of HR genes (p&lt;0.05). NPM1-mutated cases without FLT3-ITD clustered within the HR-low profile (adj-p&lt;0.05), while TP53 mutated cases tended to cluster in the HR-high group, although statistical significance was not reached. In conclusion, our data showed the presence of alterations in the DDR pathway that might be the reflection of driver events in AML. Functional studies will elucidate the functional impact of these alterations. The results suggested the presence of a therapeutic window that might be exploited with DDR inhibitors in molecularly-defined subgroups of patients.

Supported by the Torsten Haferlach-Leukämiediagnostik-Stiftung and AIRC IG 2019 (project 23810).

Citation Format: Antonella Padella, Stephan Hutter, Wencke Walter, Constance Baer, Irene Azzali, Andrea Ghelli Luserna Di Rorà, Martina Ghetti, Lorenzo Ledda, Matteo Paganelli, Claudia Haferlach, Wolfgang Kern, Giorgia Simonetti, Giovanni Martinelli, Torsten Haferlach. Genomic and transcriptomic profiles of DNA damage response genes in acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5788.

Pathophysiologic and clinical implications of molecular profiles resultant from deletion 5q

BACKGROUND

Haploinsufficiency (HI) resulting from deletion of the long arm of chromosome 5 [del(5q)] and the accompanied loss of heterozygosity are likely key pathogenic factors in del(5q) myeloid neoplasia (MN) although the consequences of del(5q) have not been yet clarified.

METHODS

Here, we explored mutations, gene expression and clinical phenotypes of 388 del(5q) vs. 841 diploid cases with MN [82% myelodysplastic syndromes (MDS)].

FINDINGS

Del(5q) resulted as founder (better prognosis) or secondary hit (preceded by TP53 mutations). Using Bayesian prediction analyses on 57 HI marker genes we established the minimal del(5q) gene signature that distinguishes del(5q) from diploid cases. Clusters of diploid cases mimicking the del(5q) signature support the overall importance of del(5q) genes in the pathogenesis of MDS in general. Sub-clusters within del(5q) patients pointed towards the inherent intrapatient heterogeneity of HI genes.

INTERPRETATION

The underlying clonal expansion drive results from a balance between the "HI-driver" genes (e.g., CSNK1A1, CTNNA1, TCERG1) and the proapoptotic "HI-anti-drivers" (e.g., RPS14, PURA, SIL1). The residual essential clonal expansion drive allows for selection of accelerator mutations such as TP53 (denominating poor) and CSNK1A1 mutations (with a better prognosis) which overcome pro-apoptotic genes (e.g., p21, BAD, BAX), resulting in a clonal expansion. In summary, we describe the complete picture of del(5q) MN identifying the crucial genes, gene clusters and clonal hierarchy dictating the clinical course of del(5q) patients.

FUNDING

Torsten Haferlach Leukemia Diagnostics Foundation. US National Institute of Health (NIH) grants R35 HL135795, R01HL123904, R01 HL118281, R01 HL128425, R01 HL132071, and a grant from Edward P. Evans Foundation.

Surface-Immobilized Photoinitiators for Light Induced Polymerization and Coupling Reactions

Straightforward and versatile surface modification, functionalization and coating have become a significant topic in material sciences. While physical modification suffers from severe drawbacks, such as insufficient stability, chemical induced grafting processes efficiently modify organic and inorganic materials and surfaces due to covalent linkage. These processes include the “grafting from” method, where polymer chains are directly grown from the surface in terms of a surface-initiated polymerization and the “grafting to” method where a preformed (macro)-molecule is introduced to a preliminary treated surface via a coupling reaction. Both methods require an initiating species that is immobilized at the surface and can be triggered either by heat or light, whereas light induced processes have recently received increasing interest. Therefore, a major challenge is the ongoing search for suitable anchor moieties that provide covalent linkage to the surface and include initiators for surface-initiated polymerization and coupling reactions, respectively. This review containing 205 references provides an overview on photoinitiators which are covalently coupled to different surfaces, and are utilized for subsequent photopolymerizations and photocoupling reactions. An emphasis is placed on the coupling strategies for different surfaces, including oxides, metals, and cellulosic materials, with a focus on surface coupled free radical photoinitiators (type I and type II). Furthermore, the concept of surface initiation mediated by photoiniferters (PIMP) is reviewed. Regarding controlled radical polymerization from surfaces, a large section of the paper reviews surface-tethered co-initiators, ATRP initiators, and RAFT agents. In combination with photoinitiators or photoredox catalysts, these compounds are employed for surface initiated photopolymerizations. Moreover, examples for coupled photoacids and photoacid generators are presented. Another large section of the article reviews photocoupling and photoclick techniques. Here, the focus is set on light sensitive groups, such as organic azides, tetrazoles and diazirines, which have proven useful in biochemistry, composite technology and many other fields.

Acute myeloid leukemia displaying clonal instability during treatment: implications for measurable residual disease assessments

Next-generation sequencing (NGS) is an excellent methodology for measuring residual disease in acute myeloid leukemia and survey several sub-clones simultaneously. Little experience exists regarding interpretation of differential clonal responses to therapy. We hypothesize that differential clonal response could best be studied in patients with residual disease at the time of response evaluation. We performed targeted panel sequencing of paired diagnostic and first treatment evaluation samples in 69 patients with residual disease by morphology or measurable residual disease (MRD) level >0.02. Five patients displayed a rising clone at the time of evaluation. A representative case showed the rising clone present only in the putative healthy stem cells (CD45^lowCD34⁺CD38^-CD123^-CD7^-) and not in the putative leukemic stem cells (CD34⁺CD38^-CD123⁺CD7⁺) cells, thus representing non-malignant clonal hematopoiesis. In contrast, 17/43 evaluable patients displayed a differential response in genes related to the leukemic clone. 26/43 patients displayed a clonal response that followed the overall treatment response. Patients with a differential response had a better event-free survival (EFS) as well as overall survival (OS) than those where the clonal response followed the overall response (log-rank test, EFS P=0.045, OS, P=0.050). This indicates that when following multiple leukemia-related clones the less chemotherapy-responsive clone could, in some cases, have lesser relapse potential, contrary to what is known when using standard mutation or fusion transcript-based disease surveillance. In conclusion, our results confirm the potential of refining MRD assessments by following multiple clones and warrants further studies into the precise interpretations of multi-clone NGS-MRD assays.

2021 Update on MRD in acute myeloid leukemia: a consensus document from the European LeukemiaNet MRD Working Party

Measurable residual disease (MRD) is an important biomarker in acute myeloid leukemia (AML) that is used for prognostic, predictive, monitoring, and efficacy-response assessments. The European LeukemiaNet (ELN) MRD Working Party evaluated standardization and harmonization of MRD in an ongoing manner and has updated the 2018 ELN MRD recommendations based on significant developments in the field. New and revised recommendations were established during in-person and online meetings, and a 2-stage Delphi poll was conducted to optimize consensus. All recommendations are graded by levels of evidence and agreement. Major changes include technical specifications for next-generation sequencing-based MRD testing and integrative assessments of MRD irrespective of technology. Other topics include use of MRD as a prognostic and surrogate end point for drug testing; selection of the technique, material, and appropriate time points for MRD assessment; and clinical implications of MRD assessment. In addition to technical recommendations for flow- and molecular-MRD analysis, we provide MRD thresholds and define MRD response, and detail how MRD results should be reported and combined if several techniques are used. MRD assessment in AML is complex and clinically relevant, and standardized approaches to application, interpretation, technical conduct, and reporting are of critical importance.

Enhancer Hijacking Drives Oncogenic BCL11B Expression in Lineage-Ambiguous Stem Cell Leukemia

Lineage-ambiguous leukemias are high-risk malignancies of poorly understood genetic basis. Here, we describe a distinct subgroup of acute leukemia with expression of myeloid, T lymphoid, and stem cell markers driven by aberrant allele-specific deregulation of BCL11B, a master transcription factor responsible for thymic T-lineage commitment and specification. Mechanistically, this deregulation was driven by chromosomal rearrangements that juxtapose BCL11B to superenhancers active in hematopoietic progenitors, or focal amplifications that generate a superenhancer from a noncoding element distal to BCL11B. Chromatin conformation analyses demonstrated long-range interactions of rearranged enhancers with the expressed BCL11B allele and association of BCL11B with activated hematopoietic progenitor cell cis-regulatory elements, suggesting BCL11B is aberrantly co-opted into a gene regulatory network that drives transformation by maintaining a progenitor state. These data support a role for ectopic BCL11B expression in primitive hematopoietic cells mediated by enhancer hijacking as an oncogenic driver of human lineage-ambiguous leukemia. SIGNIFICANCE: Lineage-ambiguous leukemias pose significant diagnostic and therapeutic challenges due to a poorly understood molecular and cellular basis. We identify oncogenic deregulation of BCL11B driven by diverse structural alterations, including de novo superenhancer generation, as the driving feature of a subset of lineage-ambiguous leukemias that transcend current diagnostic boundaries.This article is highlighted in the In This Issue feature, p. 2659.

Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms

Multi-parameter flow cytometry (MFC) is a cornerstone in clinical decision making for leukemia and lymphoma. MFC data analysis requires manual gating of cell populations, which is time-consuming, subjective, and often limited to a two-dimensional space. In recent years, deep learning models have been successfully used to analyze data in high-dimensional space and are highly accurate. However, AI models used for disease classification with MFC data are limited to the panel they were trained on. Thus, a key challenge in deploying AI into routine diagnostics is the robustness and adaptability of such models. This study demonstrates how transfer learning can be applied to boost the performance of models with smaller datasets acquired with different MFC panels. We trained models for four additional datasets by transferring the features learned from our base model. Our workflow increased the model's overall performance and, more prominently, improved the learning rate for small training sizes.

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Device capabilities and diagnostic approaches differ greatly in lymphoma MFC panels

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Single laboratories generate too little data to train an AI model with high accuracy

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Transfer learning across panels increases classification performance significantly

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Merging MFC data from multiple tubes per sample increases the model's transferability

Multi-parameter flow cytometry (MFC) is a critical tool in leukemia and lymphoma diagnostics. Advances in cytometry technology and diagnostic standardization efforts have led to an ever-increasing volume of data, presenting an opportunity to use artificial intelligence (AI) in diagnostics. However, the MFC protocol is prone to changes depending on the diagnostic workflow and the available cytometer. The changes to the MFC protocol limit the deployment of AI in routine diagnostics settings. We present a workflow that allows existing AI to adapt to multiple MFC protocols. We combine transfer learning (TL) with MFC data merging to increase the robustness of AI. Our results show that TL improves the performance of AI and allows models to achieve higher performance with less training data. This gain in performance for smaller training data allows for an already deployed AI to adapt to changes without the need for retraining a new model that requires more training data.

Whole genome sequencing demonstrates substantial pathophysiological differences of MYC rearrangements in patients with plasma cell myeloma and B-cell lymphoma

MYC rearrangements (MYCr) occur in several B-cell neoplasms and impact disease progression and overall survival. We used whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) to analyze and compare MYCr in different B-cell neoplasms. The MYCr features of cases with plasma cell myeloma (PCM) (n = 88) showed distinct characteristics compared to cases with mature B-cell lymphomas (n = 62, including Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL) and high grade lymphoma with MYC and BCL2 and/or BCL6 rearrangements (HGBL)): they were more complex and showed a wider variety of translocation partners and breakpoints. Additionally, unlike B-cell lymphomas, they showed no evidence of activation-induced deaminase (AID) involvement in the formation of MYCr with immunoglobolin heavy chain (IGH), indicating a different mechanism of origin. The different MYCr characteristics resulted in poor MYCr detection rates by fluorescence in situ hybridization of only 50% in PCM, compared to 94% in lymphoma.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia

BACKGROUND

Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified.

METHODS

We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients.

RESULTS

DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples.

CONCLUSION

As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

How artificial intelligence might disrupt diagnostics in hematology in the near future

Artificial intelligence (AI) is about to make itself indispensable in the health care sector. Examples of successful applications or promising approaches range from the application of pattern recognition software to pre-process and analyze digital medical images, to deep learning algorithms for subtype or disease classification, and digital twin technology and in silico clinical trials. Moreover, machine-learning techniques are used to identify patterns and anomalies in electronic health records and to perform ad-hoc evaluations of gathered data from wearable health tracking devices for deep longitudinal phenotyping. In the last years, substantial progress has been made in automated image classification, reaching even superhuman level in some instances. Despite the increasing awareness of the importance of the genetic context, the diagnosis in hematology is still mainly based on the evaluation of the phenotype. Either by the analysis of microscopic images of cells in cytomorphology or by the analysis of cell populations in bidimensional plots obtained by flow cytometry. Here, AI algorithms not only spot details that might escape the human eye, but might also identify entirely new ways of interpreting these images. With the introduction of high-throughput next-generation sequencing in molecular genetics, the amount of available information is increasing exponentially, priming the field for the application of machine learning approaches. The goal of all the approaches is to allow personalized and informed interventions, to enhance treatment success, to improve the timeliness and accuracy of diagnoses, and to minimize technically induced misclassifications. The potential of AI-based applications is virtually endless but where do we stand in hematology and how far can we go?