A Simple RNA Target Capture NGS Strategy for Fusion Genes Assessment in the Diagnostics of Pediatric B-cell Acute Lymphoblastic Leukemia

Comprehensive Molecular Profiling of NPM1-Mutated Acute Myeloid Leukemia Using RNAseq Approach

Acute myeloid leukemia (AML) is a complex hematologic malignancy with high morbidity and mortality. Nucleophosmin 1 (NPM1) mutations occur in approximately 30% of AML cases, and NPM1-mutated AML is classified as a distinct entity. NPM1-mutated AML patients without additional genetic abnormalities have a favorable prognosis. Despite this, 30-50% of them experience relapse. This study aimed to investigate the potential of total RNAseq in improving the characterization of NPM1-mutated AML patients. We explored genetic variations independently of myeloid stratification, revealing a complex molecular scenario. We showed that total RNAseq enables the uncovering of different genetic alterations and clonal subtypes, allowing for a comprehensive evaluation of the real expression of exome transcripts in leukemic clones and the identification of aberrant fusion transcripts. This characterization may enhance understanding and guide improved treatment strategies for NPM1mut AML patients, contributing to better outcomes. Our findings underscore the complexity of NPM1-mutated AML, supporting the incorporation of advanced technologies for precise risk stratification and personalized therapeutic strategies. The study provides a foundation for future investigations into the clinical implications of identified genetic variations and highlights the importance of evolving diagnostic approaches in leukemia management.

Decoding the genetic symphony: Profiling protein-coding and long noncoding RNA expression in T-acute lymphoblastic leukemia for clinical insights

T-acute lymphoblastic leukemia (T-ALL) is a heterogeneous malignancy characterized by the abnormal proliferation of immature T-cell precursors. Despite advances in immunophenotypic classification, understanding the molecular landscape and its impact on patient prognosis remains challenging. In this study, we conducted comprehensive RNA sequencing in a cohort of 35 patients with T-ALL to unravel the intricate transcriptomic profile. Subsequently, we validated the prognostic relevance of 23 targets, encompassing (i) protein-coding genes-BAALC, HHEX, MEF2C, FAT1, LYL1, LMO2, LYN, and TAL1; (ii) epigenetic modifiers-DOT1L, EP300, EML4, RAG1, EZH2, and KDM6A; and (iii) long noncoding RNAs (lncRNAs)-XIST, PCAT18, PCAT14, LINC00202, LINC00461, LINC00648, ST20, MEF2C-AS1, and MALAT1 in an independent cohort of 99 patients with T-ALL. Principal component analysis revealed distinct clusters aligning with immunophenotypic subtypes, providing insights into the molecular heterogeneity of T-ALL. The identified signature genes exhibited associations with clinicopathologic features. Survival analysis uncovered several independent predictors of patient outcomes. Higher expression of MEF2C, BAALC, HHEX, and LYL1 genes emerged as robust indicators of poor overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS). Higher LMO2 expression was correlated with adverse EFS and RFS outcomes. Intriguingly, increased expression of lncRNA ST20 coupled with RAG1 demonstrated a favorable prognostic impact on OS, EFS, and RFS. Conclusively, several hitherto unreported associations of gene expression patterns with clinicopathologic features and prognosis were identified, which may help understand T-ALL's molecular pathogenesis and provide prognostic markers.

Current assessment and management of measurable residual disease in patients with acute lymphoblastic leukemia in the setting of CAR-T-cell therapy

ABSTRACT

Chimeric antigen receptor (CAR)-modified T-cell therapy has achieved remarkable success in the treatment of acute lymphoblastic leukemia (ALL). Measurable/minimal residual disease (MRD) monitoring plays a significant role in the prognostication and management of patients undergoing CAR-T-cell therapy. Common MRD detection methods include flow cytometry (FCM), polymerase chain reaction (PCR), and next-generation sequencing (NGS), and each method has advantages and limitations. It has been well documented that MRD positivity predicts a poor prognosis and even disease relapse. Thus, how to perform prognostic evaluations, stratify risk based on MRD status, and apply MRD monitoring to guide individual therapeutic decisions have important implications in clinical practice. This review assesses the common and novel MRD assessment methods. In addition, we emphasize the critical role of MRD as a prognostic biomarker and summarize the latest studies regarding MRD-directed combination therapy with CAR-T-cell therapy and allogeneic hematopoietic stem cell transplantation (allo-HSCT), as well as other therapeutic strategies to improve treatment effect. Furthermore, this review discusses current challenges and strategies for MRD detection in the setting of disease relapse after targeted therapy.

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.

PAX5 fusion genes are frequent in poor risk childhood acute lymphoblastic leukaemia and can be targeted with BIBF1120

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Genetic characterisation of childhood B-other-acute lymphoblastic leukaemia in UK patients by fluorescence in situ hybridisation and Multiplex Ligation-dependent Probe Amplification

While next-generation sequencing technologies provide excellent strategies to screen for newly defined genetic abnormalities of prognostic or therapeutic significance in patients with B-other-acute lymphoblastic leukaemia (ALL), they are not widely available. We used a dual screening approach, incorporating fluorescence in situ hybridisation (FISH) and Multiplex Ligation-dependent Probe Amplification (MLPA), to establish the frequency and long-term outcome of a representative cohort of specific subgroups of B-other-ALL recruited to the childhood ALL trial, UKALL2003. We focussed on abnormalities of known prognostic significance, including ABL-class fusions and ERG deletions, as a surrogate marker for DUX4-rearranged ALL. ABL-class fusions accounted for ~4% of B-other-ALL and were associated with high levels of minimal residual disease (MRD; 14/23 with MRD >5%) and a high relapse rate (55·7%) following treatment without tyrosine kinase inhibitor (TKI), confirming the importance of prospective screening with a view to incorporating TKI into therapy. Patients with deletions of ERG (~10% of B-other-ALL) had a 10-year event-free-survival of 97·2%, validating previous reports of their excellent outcome. Rearrangements of ZNF384, MEF2D and NUTM1 were observed at low frequencies. Here, we estimate that approximately one third of B-other-ALL patients can be reliably classified into one of the known genetic subgroups using our dual screening method. This approach is rapid, accurate and readily incorporated into routine testing.

Fusion genes as biomarkers in pediatric cancers: A review of the current state and applicability in diagnostics and personalized therapy

The incidence of pediatric cancers is rising steadily across the world, along with the challenges in understanding the molecular mechanisms and devising effective therapeutic strategies. Pediatric cancers are presented with diverse molecular characteristics and more distinct subtypes when compared to adult cancers. Recent studies on the genomic landscape of pediatric cancers using next-generation sequencing (NGS) approaches have redefined this field by providing better subtype characterization and novel actionable targets. Since early identification and personalized treatment strategies influence therapeutic outcomes, survival, and quality of life in pediatric cancer patients, the quest for actionable biomarkers is of great value in this field. Fusion genes that are prevalent and recurrent in several pediatric cancers are ideally suited in this context due to their disease-specific occurrence. In this review, we explore the current status of fusion genes in pediatric cancer subtypes and their use as biomarkers for diagnosis and personalized therapy. We discuss the technological advancements made in recent years in NGS sequencing and their impact on fusion detection algorithms that have revolutionized this field. Finally, we also discuss the advantages of pairing liquid biopsy protocols for fusion detection and their eventual use in diagnosis and treatment monitoring.