Genome Sequencing as an Alternative to Cytogenetic Analysis in Myeloid Cancers

RNA-loaded nanoparticles for the treatment of hematological cancers

Hematological cancers encompass a diverse group of malignancies affecting the blood, bone marrow, lymph nodes, and spleen. These disorders present unique challenges due to their complex etiology and varied clinical manifestations. Despite significant advancements in understanding and treating hematological malignancies, innovative therapeutic approaches are continually sought to enhance patient outcomes. This review highlights the application of RNA nanoparticles (RNA-NPs) in the treatment of hematological cancers. We delve into detailed discussions on in vitro and preclinical studies involving RNA-NPs for adult patients, as well as the application of RNA-NPs in pediatric hematological cancer. The review also addresses ongoing clinical trials involving RNA-NPs and explores the emerging field of CAR-T therapy engineered by RNA-NPs. Finally, we discuss the challenges still faced in translating RNA-NP research to clinics.

Multiomic profiling identifies predictors of survival in African American patients with acute myeloid leukemia

Genomic profiles and prognostic biomarkers in patients with acute myeloid leukemia (AML) from ancestry-diverse populations are underexplored. We analyzed the exomes and transcriptomes of 100 patients with AML with genomically confirmed African ancestry (Black; Alliance) and compared their somatic mutation frequencies with those of 323 self-reported white patients with AML, 55% of whom had genomically confirmed European ancestry (white; BeatAML). Here we find that 73% of 162 gene mutations recurrent in Black patients, including a hitherto unreported PHIP alteration detected in 7% of patients, were found in one white patient or not detected. Black patients with myelodysplasia-related AML were younger than white patients suggesting intrinsic and/or extrinsic dysplasia-causing stressors. On multivariable analyses of Black patients, NPM1 and NRAS mutations were associated with inferior disease-free and IDH1 and IDH2 mutations with reduced overall survival. Inflammatory profiles, cell type distributions and transcriptional profiles differed between Black and white patients with NPM1 mutations. Incorporation of ancestry-specific risk markers into the 2022 European LeukemiaNet genetic risk stratification changed risk group assignment for one-third of Black patients and improved their outcome prediction.

Genome sequencing and analysis of penicillin V producing Penicillium rubens strain BIONCL P45 isolated from India

BACKGROUND

A filamentous fungus Penicillium rubens is widely recognized for producing industrially important antibiotic, penicillin at industrial scale.

OBJECTIVE

To better comprehend, the genetic blueprint of the wild-type P. rubens was isolated from India to identify the genetic/biosynthetic pathways for phenoxymethylpenicillin (penicillin V, PenV) and other secondary metabolites.

METHOD

Genomic DNA (gDNA) was isolated, and library was prepared as per Illumina platform. Whole genome sequencing (WGS) was performed according to Illumina NovoSeq platform. Further, SOAPdenovo was used to assemble the short reads validated by Bowtie-2 and SAMtools packages. Glimmer and GeneMark were used to dig out total genes in genome. Functional annotation of predicted proteins was performed by NCBI non-redundant (NR), UniProt, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Ontology (GO) databases. Moreover, secretome analysis was performed by SignalP 4.1 and TargetP v1.1 and carbohydrate-active enzymes (CAZymes) and protease families by CAZy database. Comparative genome analysis was performed by Mauve 2.4.0. software to find genomic correlation between P. rubens BIONCL P45 and Penicillium chrysogenum Wisconsin 54-1255; also phylogeny was prepared with known penicillin producing strains by ParSNP tool.

RESULTS

Penicillium rubens BIONCL P45 strain was isolated from India and is producing excess PenV. The 31.09 Mb genome was assembled with 95.6% coverage of the reference genome P. chrysogenum Wis 54-1255 with 10687 protein coding genes, 3502 genes had homologs in NR, UniProt, KEGG, and GO databases. Additionally, 358 CAZymes and 911 transporter coding genes were found in genome. Genome contains complete pathways for penicillin, homogentisate pathway of phenyl acetic acid (PAA) catabolism, Andrastin A, Sorbicillin, Roquefortine C, and Meleagrin. Comparative genome analysis of BIONCL P45 and Wis 54-1255 revealed 99.89% coverage with 2952 common KEGG orthologous protein-coding genes. Phylogenetic analysis revealed that BIONCL P45 was clustered with Fleming's original isolate P. rubens IMI 15378.

CONCLUSION

This genome can be a helpful resource for further research in developing fermentation processes and strain engineering approaches for high titer penicillin production.

The Proteasome-Family-Members-Based Prognostic Model Improves the Risk Classification for Adult Acute Myeloid Leukemia

Background: The accumulation of diverse molecular and cytogenetic variations contributes to the heterogeneity of acute myeloid leukemia (AML), a cluster of hematologic malignancies that necessitates enhanced risk evaluation for prognostic prediction and therapeutic guidance. The ubiquitin-proteasome system plays a crucial role in AML; however, the specific contributions of 49 core proteasome family members (PSMs) in this context remain largely unexplored. Methods: The expression and survival significance of 49 PSMs in AML were evaluated using the data from BeatAML2.0, TCGA, and the GEO database, mainly through the K-M plots, differential genes enrichment analysis, and candidate compounds screening via R language and statistical software. Results: we employed LASSO and Cox regression analyses and developed a model comprising three PSMs (PSMB8, PSMG1, and PSMG4) aimed at predicting OS in adult AML patients, utilizing expression profiles from the BeatAML2.0 training datasets. Patients with higher risk scores were predominantly found in the AML-M2 subtype, exhibited poorer ELN stratification, showed no complete remission following induction therapies, and had a higher mortality status. Consistently, significantly worse OS was observed in high-risk patients across both the training and three validation datasets, underscoring the robust predictive capability of the three-PSMs model for AML outcomes. This model elucidated the distinct genetic abnormalities landscape between high- and low-risk groups and enhanced the ELN risk stratification system. Ultimately, the three-PSMs risk score captured AML-specific gene expression signatures, providing a molecular basis for selecting potential therapeutic agents. Conclusions: In summary, these findings manifested the significant potential of the PSM model for predicting AML survival and informed treatment strategies.

Scenario analysis and multi-criteria decision analysis to explore alternative reimbursement pathways for whole genome sequencing for blood cancer patients

BACKGROUND

Whole genome sequencing (WGS) has transformative potential for blood cancer management, but reimbursement is hindered by uncertain benefits relative to added costs. This study employed scenario planning and multi-criteria decision analysis (MCDA) to evaluate stakeholders' preferences for alternative reimbursement pathways, informing future health technology assessment (HTA) submission of WGS in blood cancer.

METHODS

Key factors influencing WGS reimbursement in blood cancers were identified through a literature search. Hypothetical scenarios describing various evidential characteristics of WGS for HTA were developed using the morphological approach. An online survey, incorporating MCDA weights, was designed to gather stakeholder preferences (consumers/patients, clinicians/health professionals, industry representatives, health economists, and HTA committee members) for these scenarios. The survey assessed participants' approval of WGS reimbursement for each scenario, and scenario preferences were determined using the geometric mean method, applying an algorithm to improve reliability and precision by addressing inconsistent responses.

RESULTS

Nineteen participants provided complete survey responses, primarily clinicians or health professionals (n = 6; 32 %), consumers/patients and industry representatives (both at n = 5; 26 %). "Clinical impact of WGS results on patient care" was the most critical criterion (criteria weight of 0.25), followed by "diagnostic accuracy of WGS" (0.21), "cost-effectiveness of WGS" (0.19), "availability of reimbursed treatment after WGS" (0.16), and "eligibility criteria for reimbursed treatment based on actionable WGS results" and "cost comparison of WGS" (both at 0.09). Participants preferred a scenario with substantial clinical evidence, high access to reimbursed targeted treatment, cost-effectiveness below $50,000 per quality-adjusted life year (QALY) gained, and affordability relative to standard molecular tests. Reimbursement was initially opposed until criteria such as equal cost to standard tests and better treatment accessibility were met.

CONCLUSION

Payers commonly emphasize acceptable cost-effectiveness, but strong clinical evidence for many variants and comparable costs to standard tests are likely to drive positive reimbursement decisions for WGS.

Cytogenetics in the management of hematological malignancies: An overview of alternative technologies for cytogenetic characterization

Genomic characterization is an essential part of the clinical management of hematological malignancies for diagnostic, prognostic and therapeutic purposes. Although CBA and FISH are still the gold standard in hematology for the detection of CNA and SV, some alternative technologies are intended to complement their deficiencies or even replace them in the more or less near future. In this article, we provide a technological overview of these alternatives. CMA is the historical and well established technique for the high-resolution detection of CNA. For SV detection, there are emerging techniques based on the study of chromatin conformation and more established ones such as RTMLPA for the detection of fusion transcripts and RNA-seq to reveal the molecular consequences of SV. Comprehensive techniques that detect both CNA and SV are the most interesting because they provide all the information in a single examination. Among these, OGM is a promising emerging higher-solution technique that offers a complete solution at a contained cost, at the expense of a relatively low throughput per machine. WGS remains the most adaptable solution, with long-read approaches enabling very high-resolution detection of CAs, but requiring a heavy bioinformatics installation and at a still high cost. However, the development of high-resolution genome-wide detection techniques for CAs allows for a much better description of chromoanagenesis. Therefore, we have included in this review an update on the various existing mechanisms and their consequences and implications, especially prognostic, in hematological malignancies.

Measurable residual disease (MRD)-testing in haematological cancers: A giant leap forward or sideways?

Measurable residual disease (MRD)-testing is used in many haematological cancers to estimate relapse risk and to direct therapy. Sometimes MRD-test results are used for regulatory approval. However, some people including regulators wrongfully believe results of MRD-testing are highly accurate and of proven efficacy in directing therapy. We review MRD-testing technologies and evaluate the accuracy of MRD-testing for predicting relapse and the strength of evidence supporting efficacy of MRD-guided therapy. We show that at the individual level MRD-test results are often an inaccurate relapse predictor. Also, no convincing data indicate that increasing therapy-intensity based on a positive MRD-test reduces relapse risk or improves survival. We caution against adjusting therapy-intensity based solely on results of MRD-testing.

Economic Impact of Whole Genome Sequencing and Whole Transcriptome Sequencing Versus Routine Diagnostic Molecular Testing to Stratify Patients with B-Cell Acute Lymphoblastic Leukemia

Whole genome and whole transcriptome sequencing (WGTS) can accurately distinguish B-cell acute lymphoblastic leukemia (B-ALL) genomic subtypes. However, whether this is economically viable remains unclear. This study compared the direct costs and molecular subtype classification yield using different testing strategies for WGTS in adolescent and young adult/adult patients with B-ALL. These approaches were: (1) combined BCR::ABL1 by fluorescence in situ hybridization (FISH) + WGTS for all patients; and (2) sequential BCR::ABL1 FISH + WGTS contingent on initial BCR::ABL1 FISH test outcome. The cost of routine diagnostic testing was estimated using Medicare or hospital fees, and the additional cost of WGTS was evaluated from the health care provider perspective using time-driven activity-based costing with resource identification elicited from experts. Molecular subtype classification yield data were derived from literature sources. Parameter uncertainty was assessed through deterministic sensitivity analysis; additional scenario analyses were performed. The total per patient cost of WGTS was $4319 (all costs reported in US dollars); consumables accounted for 74% of the overall cost, primarily driven by sequencing-related consumables. The incremental cost per additional patient categorized into molecular subtype was $8498 for combined BCR::ABL1 FISH + WGTS for all patients and $5656 for initial BCR::ABL1 FISH + WGTS for select patients compared with routine diagnostic testing. A reduction in the consumable costs of WGTS or an increase in the yield of molecular subtype classification is favorable.

Combination therapy with novel agents for acute myeloid leukaemia: Insights into treatment of a heterogenous disease

The treatment landscape of acute myeloid leukaemia (AML) is evolving rapidly. Venetoclax in combination with intensive chemotherapy or doublets or triplets with targeted or immune therapies is the focus of numerous ongoing trials. The development of mutation-targeted therapies has greatly enhanced the treatment armamentarium, with FLT3 inhibitors and isocitrate dehydrogenase inhibitors improving outcomes in frontline and relapsed/refractory (RR) AML, and menin inhibitors showing efficacy in RR NPM1mut and KMT2A-rearranged AML. With so many new drugs approved, the number of potential combinatorial approaches to leverage the maximal benefit of these agents has increased dramatically, while at the same time introducing clinical challenges, such as key preclinical and clinical data supporting the development of combinatorial therapy, how to optimally combine or sequence these novel agents, how to optimise dose and duration to maintain safety while enhancing efficacy, the optimal duration of therapy and the role of measurable residual disease in decision-making in both intensive and low-intensity therapy settings. In this review, we will outline the evidence leading to the approval of key agents in AML, their on-label current approvals and how they may be optimally combined in a safe and deliverable fashion to further improve outcomes in AML.

The impact of next-generation sequencing for diagnosis and disease understanding of myeloid malignancies

INTRODUCTION

Defining the chromosomal and molecular changes associated with myeloid neoplasms (MNs) optimizes clinical care through improved diagnosis, prognosis, treatment planning, and patient monitoring. This review will concisely describe the techniques used to profile MNs clinically today, with descriptions of challenges and emerging approaches that may soon become standard-of-care.

AREAS COVERED

In this review, the authors discuss molecular assessment of MNs using non-sequencing techniques, including conventional cytogenetic analysis, fluorescence in situ hybridization, chromosomal genomic microarray testing; as well as DNA- or RNA-based next-generation sequencing (NGS) assays; and sequential monitoring via digital PCR or measurable residual disease assays. The authors explain why distinguishing somatic from germline alleles is critical for optimal management. Finally, they introduce emerging technologies, such as long-read, whole exome/genome, and single-cell sequencing, which are reserved for research purposes currently but will become clinical tests soon.

EXPERT OPINION

The authors describe challenges to the adoption of comprehensive genomic tests for those in resource-constrained environments and for inclusion into clinical trials. In the future, all aspects of patient care will likely be influenced by the adaptation of artificial intelligence and mathematical modeling, fueled by rapid advances in telecommunications.

Cancer cytogenetics in a genomics world: Wedding the old with the new

Since the discovery of the Philadelphia chromosome in 1960, cytogenetic studies have been instrumental in detecting chromosomal abnormalities that can inform cancer diagnosis, treatment, and risk assessment efforts. The initial expansion of cancer cytogenetics was with fluorescence in situ hybridization (FISH) to assess submicroscopic alterations in dividing or non-dividing cells and has grown into the incorporation of chromosomal microarrays (CMA), and next generation sequencing (NGS). These molecular technologies add additional dimensions to the genomic assessment of cancers by uncovering cytogenetically invisible molecular markers. Rapid technological and bioinformatic advances in NGS are so promising that the idea of performing whole genome sequencing as part of routine patient care may soon become economically and logistically feasible. However, for now cytogenetic studies continue to play a major role in the diagnostic testing and subsequent assessments in leukemia with other genomic studies serving as complementary testing options for detection of actionable genomic abnormalities. In this review, we discuss the role of conventional cytogenetics (karyotyping, chromosome analysis) and FISH studies in hematological malignancies, highlighting the continued clinical utility of these techniques, the subtleties and complexities that are relevant to treating physicians and the unique strengths of cytogenetics that cannot yet be paralleled by the current high-throughput molecular technologies. Additionally, we describe how CMA, optical genome mapping (OGM), and NGS detect abnormalities that were beyond the capacity of cytogenetic studies and how an integrated approach (broad molecular testing) can contribute to the detection of actionable targets and variants in malignancies. Finally, we discuss advances in the field of genomic testing that are bridging the advantages of individual (single) cell based cytogenetic testing and broad genomic testing.

Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations

BACKGROUND

In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD.

METHODS

We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases.

RESULTS

We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations.

CONCLUSIONS

Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Raman spectroscopy can recognize the KMT2A rearrangement as a distinct subtype of leukemia

Acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) are the two most common hematologic malignancies, challenging to treat and associated with high recurrence and mortality rates. This work aims to identify specific Raman biomarkers of ALL cells with the KMT2A gene rearrangement (KMT2A-r), representing a highly aggressive subtype of childhood leukemia with a poor prognosis. The proposed approach combines the sensitivity and specificity of Raman spectroscopy with machine learning and allows us to distinguish not only myelo- and lymphoblasts but also discriminate B-cell precursor (BCP) ALL with KMT2A-r from other blasts of BCP-ALL. We have found that KMT2A-r ALL cells fixed with 0.5% glutaraldehyde exhibit a unique spectroscopic profile that enables us to identify this subtype from other leukemias and normal cells. Therefore, a rapid and label-free method was developed to identify ALL blasts with KMT2A-r based on the ratio of the two Raman bands assigned to phenylalanine - 1040 and 1008 cm-1. This is the first time that a particular group of leukemic cells has been identified in a label-free way. The identified biomarker can be used as a screening method in diagnostic laboratories or non-reference medical centers.

A practical algorithm for acute myeloid leukaemia diagnosis following the updated 2022 classifications

Disease classification of complex and heterogenous diseases, such as acute myeloid leukaemia (AML), is continuously updated to define diagnoses, appropriate treatments, and assist research and education. Recent availability of molecular profiling techniques further benefits the classification of AML. The World Health Organization (WHO) classification of haematolymphoid tumours and the International Consensus Classification of myeloid neoplasms and acute leukaemia from 2022 are two updated versions of the WHO 2016 classification. As a consequence, the European LeukemiaNet 2022 recommendations on the diagnosis and management of AML in adults have been also updated. The current review provides a practical interpretation of these guidelines to facilitate the diagnosis of AML and discusses genetic testing, disease genetic heterogeneity, and FLT3 mutations. We propose a practical algorithm for the speedy diagnosis of AML. Future classifications may need to incorporate gene mutation combinations to enable personalised treatment regimens in the management of patients with AML.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

A new genetic diagnosis strategy for paroxysmal kinesigenic dyskinesia: Targeted high-throughput detection of PRRT2 gene c.649 locus

BACKGROUND

Paroxysmal kinesigenic dyskinesia (PKD) is the most prevalent kind type of paroxysmal Dyskinesia, characterized by recurrent and transient episodes of involuntary movements. Most PKD cases were attributed to the proline-rich transmembrane protein 2 (PRRT2) gene, in which the c.649 region is a hotspot for known mutations. Even though some patients with PKD have been genetically diagnosed using whole-exome sequencing (WES) and Sanger sequencing, there are still cases of missed diagnoses due to the limitations of sequencing technology and analytic methods on throughput.

METHODS

Patients meeting the diagnosis criteria of PKD with negative results of PRRT2-Sanger sequencing and WES were included in this study. Mutation screening and targeted high-throughput sequencing were performed to analyze and verify the sequencing results of the potential mutations.

RESULTS

Six patients with PKD with high mutation ratios of c.649dupC were screened using our targeted high-throughput sequencing from 26 PKD patients with negative results of PRRT2-Sanger sequencing and WES (frequency = 23.1%), which compensated for the comparatively shallow sequencing depth and statistical flaws in this region. Compared with the local normal population and other patients with PKD, the mutation ratios of c.649dupC of these six patients with PKD were much higher and also had truncated protein structures and differentially altered mRNA expression.

CONCLUSION

Based on the above studies, we emphasize the routine targeted high-throughput sequencing of the c.649 site in the PRRT2 gene in so-called genetic-testing-negative patients with PKD, and manually calculate the deletion and duplication mutations depth and ratios to lower the rate of clinical misdiagnosis.

Interpreting and integrating genomic tests results in clinical cancer care: Overview and practical guidance

The last decade has seen rapid progress in the use of genomic tests, including gene panels, whole-exome sequencing, and whole-genome sequencing, in research and clinical cancer care. These advances have created expansive opportunities to characterize the molecular attributes of cancer, revealing a subset of cancer-associated aberrations called driver mutations. The identification of these driver mutations can unearth vulnerabilities of cancer cells to targeted therapeutics, which has led to the development and approval of novel diagnostics and personalized interventions in various malignancies. The applications of this modern approach, often referred to as precision oncology or precision cancer medicine, are already becoming a staple in cancer care and will expand exponentially over the coming years. Although genomic tests can lead to better outcomes by informing cancer risk, prognosis, and therapeutic selection, they remain underutilized in routine cancer care. A contributing factor is a lack of understanding of their clinical utility and the difficulty of results interpretation by the broad oncology community. Practical guidelines on how to interpret and integrate genomic information in the clinical setting, addressed to clinicians without expertise in cancer genomics, are currently limited. Building upon the genomic foundations of cancer and the concept of precision oncology, the authors have developed practical guidance to aid the interpretation of genomic test results that help inform clinical decision making for patients with cancer. They also discuss the challenges that prevent the wider implementation of precision oncology.

Classic and molecular cytogenetic findings in leukemia patients from the Western part of Romania

Acute lymphoblastic leukemia (ALL) is the most common type of leukemia in childhood and rare in adults, while acute myeloid leukemia (AML) is less common in children and more common in older adults. The aim of the study was to present our experience for the diagnostic of leukemia by using the classic and molecular cytogenetic methods. The study was conducted between 2009 and 2019 within the Classic and Molecular Genetic Laboratory of the Oncohematology Department from the Louis Ţurcanu Emergency Hospital for Children, Timişoara, Romania. The study group included 337 children and adults, evaluated between 2009 and 2019. By using the conventional and molecular cytogenetic technique, the cytogenetic anomalies found were 35 numerical chromosomal abnormalities, 10 (9;22)(q34;q11) [four ALL, one AML, five chronic myeloid leukemia (CML)] translocations, nine (15;17)(q24;q21) translocations, three (14;14)(q11;q32) translocations, two (4;11)(q21;q23) translocations, one (1;14)(p32;q11) translocation, one (7;14)(qter;q11) translocation, one (8;21)(q22;q22) translocation, one (9;14)(p12;q32) translocation, seven rearrangements of the MLL gene and two rearrangements of the core-binding factor subunit beta∕myosin heavy chain 11 (CBFB∕MYH11) gene. The use of conventional and molecular cytogenetic analysis is one of the most important prognostic indicators in acute leukemia patients, allowing the identification of biologically distinct subtypes of disease and selection of appropriate treatment approaches.

Potential Diagnostic Value of Abnormal Pyroptosis Genes Expression in Myelodysplastic Syndromes (MDS): A Primary Observational Cohort Study

Background: Myelodysplastic syndromes (MDS) are determined by ineffective hematopoiesis and bone marrow cytological dysplasia with somatic gene mutations and chromosomal abnormalities. Accumulating evidence has revealed the pivotal role of NLRP3 inflammasome activation and pyroptotic cell death in the pathogenesis of MDS. Although MDS can be diagnosed with a variety of morphologic and cytogenetic tests, most of these tests have limitations or problems in practice. Materials and Methods: In the present study, we evaluated the expression of genes that form the inflammasome (NLRP3, ASC, and CASP1) in bone marrow specimens of MDS patients and compared the results with those of other leukemias to evaluate their diagnostic value for MDS. Primary samples of this observational cohort study were collected from aspiration samples of patients with myelodysplastic syndromes (27 cases) and patients with non-myelodysplastic syndrome hematological cancers (45 cases). After RNA extraction and c.DNA synthesis, candidate transcripts and housekeeping transcripts were measured by real-time PCR method (SYBER Green assay). Using Kruskal-Wallis the relative gene expressions were compared and differences with p value less than 0.05 were considered as significant. Discrimination capability, cut-off, and area under curve (AUC) of all markers were analyzed with recessive operation curve (ROC) analysis. Results: We found that Caspase-1 and ASC genes expressed at more levels in MDS specimens compared to non-MDS hematological malignancies. A relative average expression of 10.22 with a p-value of 0.001 and 1.86 with p=0.019 was detected for Caspase-1 and ASC, respectively. ROC curve analysis shows an AUC of 0.739 with p=0.0001 for Caspase-1 and an AUC of 0.665 with p=0.0139 for ASC to MDS discrimination. Conclusion: Our results show that Caspase-1 and ASC gene expression levels can be used as potential biomarkers for MDS diagnosis. Prospective studies with large sample numbers are suggested.

Acute Myeloid Leukemia and Next-Generation Sequencing Panels for Diagnosis: A Comprehensive Review

Acute myeloid leukemia (AML) is a genetically heterogeneous clonal disorder characterized by the accumulation of acquired somatic genetic alterations in hematopoietic progenitor cells, which alter the normal mechanisms of self-renewal, proliferation, and differentiation. Due to significant technological advancements in sequencing technologies in the last 2 decades, classification and prognostic scoring of AML has been refined, and multiple guidelines are now available for the same. The authors have tried to summarize, latest guidelines for AML diagnosis, important markers associated, epigenetics markers, various AML fusions and their importance, etc. Review of literature suggests lack of study or comprehensive information about current NGS panels for AML diagnosis, genes and fusions covered, their technical know-how, etc. To solve this issue, the authors have tried to present detailed review about currently in use next-generation sequencing myeloid panels and their offerings.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

The role of next-generation sequencing in hematologic malignancies

Next-generation sequencing (NGS) allows high-throughput detection of molecular changes in tumors. Over the past 15 years, NGS has rapidly evolved from a promising research tool to a core component of the clinical laboratory. Sequencing of tumor cells provides an important step in detecting somatic driver mutations that not only characterize the disease but also influence treatment decisions. For patients with hematologic malignancies, NGS has been used for accurate classification and diagnosis based on genetic alterations. The recently revised World Health Organization classification and the European LeukemiaNet recommendations for acute myeloid leukemia consider genetic abnormalities as a top priority for diagnosis, prognostication, monitoring of measurable residual disease, and treatment choice. This review aims to present the role and utility of various NGS approaches for the diagnosis, treatment, and follow-up of hemato-oncology patients.

Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus

Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.

Panel-based RNA fusion sequencing improves diagnostics of pediatric acute myeloid leukemia

New methods like panel-based RNA fusion sequencing (RNA-FS) promise improved diagnostics in various malignancies. We here analyzed the impact of RNA-FS on the initial diagnostics of 241 cases with pediatric acute myeloid leukemia (AML). We show that, compared to classical cytogenetics (CCG), RNA-FS reliably detected risk-relevant fusion genes in pediatric AML. In addition, RNA-FS strongly improved the detection of cryptic fusion genes like NUP98::NSD1, KMT2A::MLLT10 and CBFA2T3::GLIS2 and thereby resulted in an improved risk stratification in 25 patients (10.4%). Validation of additionally detected non-risk-relevant high confidence fusion calls identified PIM3::BRD1, C22orf34::BRD1, PSPC1::ZMYM2 and ARHGAP26::NR3C1 as common genetic variants and MYB::GATA1 as recurrent aberration, which we here describe in AML subtypes M0 and M7 for the first time. However, it failed to detect rare cytogenetically confirmed fusion events like MNX1::ETV6 and other chromosome 12p-abnormalities. As add-on benefit, the proportion of patients for whom measurable residual disease (MRD) monitoring became possible was increased by RNA-FS from 44.4 to 75.5% as the information on the fusion transcripts' sequence allowed the design of new MRD assays.

Integrated analysis and validation reveal CYTH4 as a potential prognostic biomarker in acute myeloid leukemia

Acute myeloid leukemia (AML) is a clonal hematological malignancy with high mortality rates. The identification of novel markers is urgent for AML. Cytohesins are a subfamily of guanine nucleotide exchange factors activating the ADP-ribosylation factor family GTPases. While the important roles of cytohesins have been reported in various cancers, their function in AML remains unclear. The present study aimed to explore the prognostic impact of cytohesin-4 (CYTH4) and the underlying molecular functions. RNA sequencing and AML clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases to investigate gene expression and survival. Using the R software, differentially expressed genes were identified between the high- and the low-CYTH4 group. Functional enrichment analysis was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analyses. The CIBERSORTx tool was used to explore the proportions of different immune cell types. The molecular function of CYTH4 was also validated in vitro by examining cell growth, cell cycle, apoptosis and colony-forming ability. CYTH4 was significantly upregulated in AML compared with other cancers and normal tissues. High CYTH4 expression was associated with high white blood count (P=0.004) and higher risk status (P<0.001). Patients with high CYTH4 expression had poor overall survival (OS; HR=2.19; 95% CI, 1.40-3.44; P=0.0006; high vs. low) and event-free survival (EFS; HR=2.32; 95% CI, 1.43-3.75; P=0.0006; high vs. low), and these patients could benefit from transplantation (HR=0.29; 95% CI, 0.18-0.47; P<0.0001; transplantation vs. chemotherapy). Multivariate analysis showed that high CYTH4 expression was independently associated with inferior OS (HR=2.49; 95% CI, 1.28-4.83; P=0.007) and EFS (HR=2.56; 95% CI, 1.48-4.42; P=0.001). Functional analysis showed that CYTH4 was involved in immunoregulation. In vitro validation showed knockdown of CYTH4 adversely affected cell growth and induced cell apoptosis, while overexpression of CYTH4 enhanced cell growth. Taken together, CYTH4 is expressed at high levels in AML and can potentially function as a prognostic biomarker.

Cytogenetics and genomics of acute myeloid leukemia

The diversity of genetic and genomic abnormalities observed in acute myeloid leukemia (AML) reflects the complexity of these hematologic neoplasms. The detection of cytogenetic and molecular alterations is fundamental to diagnosis, risk stratification and treatment of AML. Chromosome rearrangements are well established in the diagnostic classification of AML, as are some gene mutations, in several international classification systems. Additionally, the detection of new mutational profiles at relapse and identification of mutations in the pre- and post-transplant settings are illuminating in understanding disease evolution and are relevant to the risk assessment of AML patients. In this review, we discuss recurrent cytogenetic abnormalities, as well as the detection of recurrent mutations, within the context of a normal karyotype, and in the setting of chromosome abnormalities. Two new classification schemes from the WHO and ICC are described, comparing these classifications in terms of diagnostic criteria and entity definition in AML. Finally, we discuss ways in which genomic sequencing can condense the detection of gene mutations and chromosome abnormalities into a single assay.

Sequential tumor molecular profiling identifies likely germline variants

PURPOSE

To identify likely germline DNA variants from sequential tumor profiling data from hematopoietic malignancies (HMs).

METHODS

The coefficient of variance was calculated from variant allele frequency of next-generation sequencing assays. Variants' likelihood of being germline was ranked on a 1 to 5 scale. Outcomes were examined in patients with such variants.

RESULTS

In a pilot set of 33 genes, 89% of grade 1, 77% of grade 2, 62% of grade 3, 52% of grade 4, and 21% of grade 5 variants were confirmed to be germline. Among those, 22% were pathogenic or likely pathogenic in genes recognized as conferring hereditary HM risk, including BRCA1/2, CHEK2, CSF3R, and DDX41. To determine if this approach identified genes with known autosomal dominant inheritance, we analyzed sequential data from 1336 genes in 1135 HM patients. Among unique variants, 16% occurred in hereditary HM genes, and 15% were deleterious. Patients with grade 1/2 alleles had decreased survival 2 years after initial molecular testing (78% versus 88%, P = .0037) and increased all-cause mortality compared with those without (hazard ratio 2.02, 95% CI 1.18-3.46, P = .019).

CONCLUSION

Variant germline status may be predicted using sequential tumor profiling and patients with likely germline variants experience inferior outcomes compared with those without.

The landscape of cytogenetic and molecular genetic methods in diagnostics for hematologic neoplasia

Improvements made during the last decades in the management of patients with hematologic neoplasia have resulted in increase of overall survival. These advancements have become possible through progress in our understanding of genetic basis of different hematologic malignancies and their role in the current risk-adapted treatment protocols. In this review, we provide an overview of current cytogenetic and molecular genetic methods, commonly used in the genetic characterization of hematologic malignancies, describe the current developments in the cytogenetic and molecular diagnostics, and give an outlook into their future development. Furthermore, we give a brief overview of the most important public databases and guidelines for sequence variant interpretation.

Genomic technologies for detecting structural variations in hematologic malignancies

Genomic structural variations in myeloid, lymphoid, and plasma cell neoplasms can provide key diagnostic, prognostic, and therapeutic information while elucidating the underlying disease biology. Several molecular diagnostic approaches play a central role in evaluating hematological malignancies. Traditional cytogenetic diagnostic assays, such as chromosome banding and fluorescence in situ hybridization, are essential components of the current diagnostic workup that guide clinical care for most hematologic malignancies. However, each assay has inherent limitations, including limited resolution for detecting small structural variations and low coverage, and can only detect alterations in the target regions. Recently, the rapid expansion and increasing availability of novel and comprehensive genomic technologies have led to their use in clinical laboratories for clinical management and translational research. This review aims to describe the clinical relevance of structural variations in hematologic malignancies and introduce genomic technologies that may facilitate personalized tumor characterization and treatment.

[Cost of high-throughput sequencing (NGS) technologies: Literature review and insights]

Although high-throughput sequencing technologies (Next-Generation Sequencing [NGS]) are revolutionizing medicine, the estimation of their production cost for pricing/tariffication by health systems raises methodological questions. The objective of this review of cost studies of high-throughput sequencing techniques is to draw lessons for producing robust cost estimates of these techniques. We analyzed, using an eleven item analysis framework, micro-costing studies of high-throughput sequencing technologies (n=17), including two studies conducted in the French context. The factors of variability between the studies that we identified were temporality (early evaluation of the innovation vs. evaluation of a mature technology), the choice of cost evaluation method (scope, micro- vs. gross-costing technique), the choice of production steps observed and the transposability of these studies. The lessons we have learned are that it is necessary to have a comprehensive vision of the sequencing production process by integrating all the steps from the collection of the biological sample to the delivery of the result to the clinician. It is also important to distinguish between what refers to the local context and what refers to the general context, by favouring the use of mixed methods to calculate costs. Finally, sensitivity analyses and periodic re-estimation of the costs of the techniques must be carried out in order to be able to revise the tariffs according to changes linked to the diffusion of the technology and to competition between reagent suppliers.

Advances in next-generation sequencing and emerging technologies for hematologic malignancies

Innovations in molecular diagnostics have often evolved through the study of hematologic malignancies. Examples include the pioneering characterization of the Philadelphia chromosome by cytogenetics in the 1970s, the implementation of polymerase chain reaction for high-sensitivity detection and monitoring of mutations and, most recently, targeted next- generation sequencing to drive the prognostic and therapeutic assessment of leukemia. Hematologists and hematopath- ologists have continued to advance in the past decade with new innovations improving the type, amount, and quality of data generated for each molecule of nucleic acid. In this review article, we touch on these new developments and discuss their implications for diagnostics in hematopoietic malignancies. We review advances in sequencing platforms and library preparation chemistry that can lead to faster turnaround times, novel sequencing techniques, the development of mobile laboratories with implications for worldwide benefits, the current status of sample types, improvements to quality and reference materials, bioinformatic pipelines, and the integration of machine learning and artificial intelligence into mol- ecular diagnostic tools for hematologic malignancies.

Real life evaluation of AlphaMissense predictions in hematological malignancies

High-throughput sequencing plays a pivotal role in hematological malignancy diagnostics, but interpreting missense mutations remains challenging. In this study, we used the newly available AlphaMissense database to assess the efficacy of machine learning to predict missense mutation effects and its impact to improve our ability to interpret them. Based on the analysis of 2073 variants from 686 patients analyzed for clinical purpose, we confirmed the very high accuracy of AlphaMissense predictions in a large real-life data set of missense mutations (AUC of ROC curve 0.95), and provided a comprehensive analysis of the discrepancies between AlphaMissense predictions and state of the art clinical interpretation.

Molecular pathology as basis for timely cancer diagnosis and therapy

Precision and personalized therapeutics have witnessed significant advancements in technology, revolutionizing the capabilities of laboratories to generate vast amounts of genetic data. Coupled with computational resources for analysis and interpretation, and integrated with various other types of data, including genomic data, electronic medical health (EMH) data, and clinical knowledge, these advancements support optimized health decisions. Among these technologies, next-generation sequencing (NGS) stands out as a transformative tool in the field of cancer treatment, playing a crucial role in precision oncology. NGS-based workflows are employed across a range of applications, including gene panels, exome sequencing, and whole-genome sequencing, supporting comprehensive analysis of the entire cancer genome, including mutations, copy number variations, gene expression profiles, and epigenetic modifications. By utilizing the power of NGS, these workflows contribute to enhancing our understanding of disease mechanisms, diagnosis confirmation, identifying therapeutic targets, and guiding personalized treatment decisions. This manuscript explores the diverse applications of NGS in cancer treatment, highlighting its significance in guiding diagnosis and treatment decisions, identifying therapeutic targets, monitoring disease progression, and improving patient outcomes.

Clonal Hematopoiesis, Inflammation, and Hematologic Malignancy

Somatic or acquired mutations are postzygotic genetic variations that can occur within any tissue. These mutations accumulate during aging and have classically been linked to malignant processes. Tremendous advancements over the past years have led to a deeper understanding of the role of somatic mutations in benign and malignant age-related diseases. Here, we review the somatic mutations that accumulate in the blood and their connection to disease states, with a particular focus on inflammatory diseases and myelodysplastic syndrome. We include a definition of clonal hematopoiesis (CH) and an overview of the origins and implications of these mutations. In addition, we emphasize somatic disorders with overlapping inflammation and hematologic disease beyond CH, including paroxysmal nocturnal hemoglobinuria and aplastic anemia, focusing on VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome. Finally, we provide a practical view of the implications of somatic mutations in clinical hematology, pathology, and beyond.

Measuring Progress in Precision Oncology

SUMMARY

In this issue of Cancer Discovery, Suehnholz and colleagues describe their efforts to quantify the gradual yet steady progress of precision oncology by surveying the regulatory approvals of targeted cancer therapies, and thus the actionability of corresponding molecular alterations in clinical practice, over more than 20 years. Their work also suggests a relationship between the discovery of candidate therapeutic targets through comprehensive tumor profiling and molecularly guided cancer drug development. See related article by Suehnholz et al., p. 49 (5).

Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears

ABSTRACT

The detection of genetic aberrations is crucial for early therapy decisions in acute myeloid leukemia (AML) and recommended for all patients. Because genetic testing is expensive and time consuming, a need remains for cost-effective, fast, and broadly accessible tests to predict these aberrations in this aggressive malignancy. Here, we developed a novel fully automated end-to-end deep learning pipeline to predict genetic aberrations directly from single-cell images from scans of conventionally stained bone marrow smears already on the day of diagnosis. We used this pipeline to compile a multiterabyte data set of >2 000 000 single-cell images from diagnostic samples of 408 patients with AML. These images were then used to train convolutional neural networks for the prediction of various therapy-relevant genetic alterations. Moreover, we created a temporal test cohort data set of >444 000 single-cell images from further 71 patients with AML. We show that the models from our pipeline can significantly predict these subgroups with high areas under the curve of the receiver operating characteristic. Potential genotype-phenotype links were visualized with 2 different strategies. Our pipeline holds the potential to be used as a fast and inexpensive automated tool to screen patients with AML for therapy-relevant genetic aberrations directly from routine, conventionally stained bone marrow smears already on the day of diagnosis. It also creates a foundation to develop similar approaches for other bone marrow disorders in the future.

Clinical Cytogenetics: Current Practices and Beyond

BACKGROUND

Throughout history, the field of cytogenetics has witnessed significant changes due to the constant evolution of technologies used to assess chromosome number and structure. Similar to the evolution of single nucleotide variant detection from Sanger sequencing to next-generation sequencing, the identification of chromosome alterations has progressed from banding to fluorescence in situ hybridization (FISH) to chromosomal microarrays. More recently, emerging technologies such as optical genome mapping and genome sequencing have made noteworthy contributions to clinical laboratory testing in the field of cytogenetics.

CONTENT

In this review, we journey through some of the most pivotal discoveries that have shaped the development of clinical cytogenetics testing. We also explore the current test offerings, their uses and limitations, and future directions in technology advancements.

SUMMARY

Cytogenetics methods, including banding and targeted assessments like FISH, continue to hold crucial roles in cytogenetic testing. These methods offer a rapid turnaround time, especially for conditions with a known etiology involving recognized cytogenetic aberrations. Additionally, laboratories have the flexibility to now employ higher-throughput methodologies to enhance resolution for cases with greater complexity.

Micro-costing of genetic diagnostics in acute leukemia in Sweden: from standard-of-care to whole-genome sequencing

AIMS AND BACKGROUND

Whole-genome sequencing (WGS) is increasingly applied in clinical practice and expected to replace standard-of-care (SoC) genetic diagnostics in hematological malignancies. This study aims to assess and compare the fully burdened cost ('micro-costing') per patient for Swedish laboratories using WGS and SoC, respectively, in pediatric and adult patients with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML).

METHODS

The resource use and cost details associated with SoC, e.g. chromosome banding analysis, fluorescent in situ hybridization, and targeted sequencing analysis, were collected via activity-based costing methods from four diagnostic laboratories. For WGS, corresponding data was collected from two of the centers. A simulation-based scenario model was developed for analyzing the WGS cost based on different annual sample throughput to evaluate economy of scale.

RESULTS

The average SoC total cost per patient was €2,465 for pediatric AML and €2,201 for pediatric ALL, while in adults, the corresponding cost was €2,458 for AML and €1,207 for ALL. The average WGS cost (90x tumor/30x normal; sequenced on the Illumina NovaSeq 6000 platform) was estimated to €3,472 based on an annual throughput of 2,500 analyses, however, with an annual volume of 7,500 analyses the average cost would decrease by 23% to €2,671.

CONCLUSION

In summary, WGS is currently more costly than SoC, however the cost can be reduced by utilizing laboratories with higher throughput and by the expected decline in cost of reagents. Our data provides guidance to decision-makers for the resource allocation needed when implementing WGS in diagnostics of hematological malignancies.

Sex-associated differences in frequencies and prognostic impact of recurrent genetic alterations in adult acute myeloid leukemia (Alliance, AMLCG)

Clinical outcome of patients with acute myeloid leukemia (AML) is associated with demographic and genetic features. Although the associations of acquired genetic alterations with patients' sex have been recently analyzed, their impact on outcome of female and male patients has not yet been comprehensively assessed. We performed mutational profiling, cytogenetic and outcome analyses in 1726 adults with AML (749 female and 977 male) treated on frontline Alliance for Clinical Trials in Oncology protocols. A validation cohort comprised 465 women and 489 men treated on frontline protocols of the German AML Cooperative Group. Compared with men, women more often had normal karyotype, FLT3-ITD, DNMT3A, NPM1 and WT1 mutations and less often complex karyotype, ASXL1, SRSF2, U2AF1, RUNX1, or KIT mutations. More women were in the 2022 European LeukemiaNet intermediate-risk group and more men in adverse-risk group. We found sex differences in co-occurring mutation patterns and prognostic impact of select genetic alterations. The mutation-associated splicing events and gene-expression profiles also differed between sexes. In patients aged <60 years, SF3B1 mutations were male-specific adverse outcome prognosticators. We conclude that sex differences in AML-associated genetic alterations and mutation-specific differential splicing events highlight the importance of patients' sex in analyses of AML biology and prognostication.

Clinical whole-genome sequencing and FISH identify two different fusion partners for NUP98 in a patient with acute myeloid leukemia: A case report

BACKGROUND

Only rare cases of acute myeloid leukemia (AML) have been shown to harbor a t(8;11)(p11.2;p15.4). This translocation is believed to involve the fusion of NSD3 or FGFR1 with NUP98; however, apart from targeted mRNA quantitative PCR analysis, no molecular approaches have been utilized to define the chimeric fusions present in these rare cases.

CASE PRESENTATION

Here we present the case of a 51-year-old female with AML with myelodysplastic-related morphologic changes, 13q deletion and t(8;11), where initial fluorescence in situ hybridization (FISH) assays were consistent with the presence of NUP98 and FGFR1 rearrangements, and suggestive of NUP98/FGFR1 fusion. Using a streamlined clinical whole-genome sequencing approach, we resolved the breakpoints of this translocation to intron 4 of NSD3 and intron 12 of NUP98, indicating NUP98/NSD3 rearrangement as the likely underlying aberration. Furthermore, our approach identified small variants in WT1 and STAG2, as well as an interstitial deletion on the short arm of chromosome 12, which were cryptic in G-banded chromosomes.

CONCLUSIONS

NUP98 fusions in acute leukemia are predictive of poor prognosis. The associated fusion partner and the presence of co-occurring mutations, such as WT1, further refine this prognosis with potential clinical implications. Using a clinical whole-genome sequencing analysis, we resolved t(8;11) breakpoints to NSD3 and NUP98, ruling out the involvement of FGFR1 suggested by FISH while also identifying multiple chromosomal and sequence level aberrations.

Diagnosis and classification of myelodysplastic syndromes

ABSTRACT

Myelodysplastic syndromes (MDSs) are neoplastic myeloid proliferations characterized by ineffective hematopoiesis resulting in peripheral blood cytopenias. MDS is distinguished from nonneoplastic clonal myeloid proliferations by the presence of morphologic dysplasia and from acute myeloid leukemia by a blast threshold of 20%. The diagnosis of MDS can be challenging because of the myriad other causes of cytopenias: accurate diagnosis requires the integration of clinical features with bone marrow and peripheral blood morphology, immunophenotyping, and genetic testing. MDS has historically been subdivided into several subtypes by classification schemes, the most recent of which are the International Consensus Classification and World Health Organization Classification (fifth edition), both published in 2022. The aim of MDS classification is to identify entities with shared genetic underpinnings and molecular pathogenesis, and the specific subtype can inform clinical decision-making alongside prognostic risk categorization. The current MDS classification schemes incorporate morphologic features (bone marrow and blood blast percentage, degree of dysplasia, ring sideroblasts, bone marrow fibrosis, and bone marrow hypocellularity) and also recognize 3 entities defined by genetics: isolated del(5q) cytogenetic abnormality, SF3B1 mutation, and TP53 mutation. It is anticipated that with advancing understanding of the genetic basis of MDS pathogenesis, future MDS classification will be based increasingly on genetic classes. Nevertheless, morphologic features in MDS reflect the phenotypic expression of the underlying abnormal genetic pathways and will undoubtedly retain importance to inform prognosis and guide treatment.

Analytic Validation of Optical Genome Mapping in Hematological Malignancies

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Standard-of-care (SOC) methods such as karyotyping and fluorescence in situ hybridization (FISH), which have been employed globally for the past three decades, have significant limitations in terms of resolution and the number of recurrent aberrations that can be simultaneously assessed, respectively. Next-generation sequencing (NGS)-based technologies are now widely used to detect clinically significant sequence variants but are limited in their ability to accurately detect SVs. Optical genome mapping (OGM) is an emerging technology enabling the genome-wide detection of all classes of SVs at a significantly higher resolution than karyotyping and FISH. OGM requires neither cultured cells nor amplification of DNA, addressing the limitations of culture and amplification biases. This study reports the clinical validation of OGM as a laboratory-developed test (LDT) according to stringent regulatory (CAP/CLIA) guidelines for genome-wide SV detection in different hematological malignancies. In total, 60 cases with hematological malignancies (of various subtypes), 18 controls, and 2 cancer cell lines were used for this study. Ultra-high-molecular-weight DNA was extracted from the samples, fluorescently labeled, and run on the Bionano Saphyr system. A total of 215 datasets, Inc.luding replicates, were generated, and analyzed successfully. Sample data were then analyzed using either disease-specific or pan-cancer-specific BED files to prioritize calls that are known to be diagnostically or prognostically relevant. Sensitivity, specificity, and reproducibility were 100%, 100%, and 96%, respectively. Following the validation, 14 cases and 10 controls were run and analyzed using OGM at three outside laboratories showing reproducibility of 96.4%. OGM found more clinically relevant SVs compared to SOC testing due to its ability to detect all classes of SVs at higher resolution. The results of this validation study demonstrate the superiority of OGM over traditional SOC methods for the detection of SVs for the accurate diagnosis of various hematological malignancies.

How to classify risk based on clinical and molecular modeling: integrating molecular markers in the risk assessment of myelodysplastic syndrome

Myelodysplastic syndrome (MDS), also known as "myelodysplastic neoplasm," is a heterogeneous group of clonal myeloid neoplasms that typically affects older adults. The clinical phenotype, symptoms, and complications relate to the depth of cytopenia and progression to acute myeloid leukemia (AML). The diagnosis of MDS relies on morphologic criteria, such as evidence of dysplasia, disordered maturation, and increasing blast counts, which separate the disease into histologic subtypes with different probabilities for progression to AML. The treatment of MDS is often risk-adapted depending on the prognostic profile of each patient's disease. There has been a coevolution of diagnostic and prognostic systems for MDS developed over the past 40 years, both of which have now incorporated molecular markers. The new International Prognostic Scoring System-Molecular (IPSS-M) improves partitioning of patients compared to prior versions with resultant upgrading of 34% of patients into higher-risk groups due to the presence of mutations. The new IPSS-M also more accurately distinguishes intermediate-risk patients separating them into two tiers. The two new diagnostic classifications include MDS defined by mutations in SF3B1 and TP53, though there are differences in diagnostic criteria. Future efforts to refine MDS prognostication could investigate the interface between MDS and clonal cytopenia of undetermined significance, expand access to genomic testing, obtain results in a less invasive manner, and develop treatment-response predictors and dynamic risk models.

Genetic mutation signature for relapse prediction in normal karyotype acute myeloid leukemia

Risk stratification for normal karyotype acute myeloid leukemia (NK-AML) remains unsatisfactory, which is reflected by the high incidence of leukemia relapse. This study aimed to evaluate the role of gene mutations and clinical characterization in predicting the relapse of patients with NK-AML. A prognostic system for NK-AML was constructed. A panel of gene mutations was explored using next-generation sequencing. A nomogram algorithm was used to build a genomic mutation signature (GMS) nomogram (GMSN) model that combines GMS, measurable residual disease, and clinical factors to predict relapse in 347 patients with NK-AML from four centers. Patients in the GMS-high group had a higher 5-year incidence of relapse than those in the GMS-low group (p < 0.001). The 5-year incidence of relapse was also higher in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001). The 5-year disease-free survival and overall survival rates were lower in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001) as confirmed by training and validation cohorts. This study illustrates the potential of GMSN as a predictor of NK-AML relapse.

Most large structural variants in cancer genomes can be detected without long reads

Short-read sequencing is the workhorse of cancer genomics yet is thought to miss many structural variants (SVs), particularly large chromosomal alterations. To characterize missing SVs in short-read whole genomes, we analyzed 'loose ends'-local violations of mass balance between adjacent DNA segments. In the landscape of loose ends across 1,330 high-purity cancer whole genomes, most large (>10-kb) clonal SVs were fully resolved by short reads in the 87% of the human genome where copy number could be reliably measured. Some loose ends represent neotelomeres, which we propose as a hallmark of the alternative lengthening of telomeres phenotype. These pan-cancer findings were confirmed by long-molecule profiles of 38 breast cancer and melanoma cases. Our results indicate that aberrant homologous recombination is unlikely to drive the majority of large cancer SVs. Furthermore, analysis of mass balance in short-read whole genome data provides a surprisingly complete picture of cancer chromosomal structure.

Functional drivers of resistance to anti-CD19 CAR-T cell therapy in diffuse large B cell lymphoma

Chimeric antigen receptor T-cell therapy targeting CD19 (CAR-19) promotes impressive durable remissions for relapsed or refractory (rel/ref) large B-cell lymphoma (LBCL) patients with historically poor prognoses. Despite this, over half of patients still fail to respond or eventually progress. Studies to reveal mechanisms of resistance have examined host clinical parameters, CAR-19 product composition, and tumor microenvironment (TME) alterations, while a relative paucity of studies has analyzed contributions by genomic alterations in tumor cells. Factors associated with outcome include increased tumor volume, specific characteristics of infused CAR-T products, infiltration by myeloid cells in tumor microenvironments, and markers of complexity in LBCL genomes. Functional laboratory studies of resistance are largely absent in the current literature, illustrating a need for experiments in genetically accurate immunocompetent systems to confirm candidate alterations' roles in resistance and inform future improvements. In this review, we highlight key studies that have elucidated biomarkers of resistance in hosts, CAR products, TMEs, and comparatively understudied tumor-intrinsic mediators encoded by tumor genomes. We conclude with an experimental framework suitable for CAR-19 resistance biomarker identification and laboratory functional validation.

Molecular Techniques and Gene Mutations in Myelodysplastic Syndromes

Sequencing technology, particularly next-generation sequencing, has highlighted the importance of gene mutations in myelodysplastic syndromes (MDSs). Mutations affecting DNA methylation, chromatin modification, RNA splicing, cohesin complex, and other pathways are present in most MDS cases and often have prognostic and clinical implications. Updated international diagnostic guidelines as well as the new International Prognostic Scoring System-Molecular incorporate molecular data into the diagnosis and prognostication of MDS. With whole-genome sequencing predicted to become the future standard of genetic evaluation, it is likely that MDS diagnosis and management will become increasingly personalized based on an individual's clinical and genomic profile.