Error-corrected sequencing strategies enable comprehensive detection of leukemic mutations relevant for diagnosis and minimal residual disease monitoring

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.

Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.

Error-corrected next generation sequencing - Promises and challenges for genotoxicity and cancer risk assessment

Error-corrected Next Generation Sequencing (ecNGS) is rapidly emerging as a valuable, highly sensitive and accurate method for detecting and characterizing mutations in any cell type, tissue or organism from which DNA can be isolated. Recent mutagenicity and carcinogenicity studies have used ecNGS to quantify drug-/chemical-induced mutations and mutational spectra associated with cancer risk. ecNGS has potential applications in genotoxicity assessment as a new readout for traditional models, for mutagenesis studies in 3D organotypic cultures, and for detecting off-target effects of gene editing tools. Additionally, early data suggest that ecNGS can measure clonal expansion of mutations as a mechanism-agnostic early marker of carcinogenic potential and can evaluate mutational load directly in human biomonitoring studies. In this review, we discuss promising applications, challenges, limitations, and key data initiatives needed to enable regulatory testing and adoption of ecNGS - including for advancing safety assessment, augmenting weight-of-evidence for mutagenicity and carcinogenicity mechanisms, identifying early biomarkers of cancer risk, and managing human health risk from chemical exposures.

Novel Tools for Diagnosis and Monitoring of AML

In recent years, major advances in the understanding of acute myeloid leukemia (AML) pathogenesis, together with technological progress, have led us into a new era in the diagnosis and follow-up of patients with AML. A combination of immunophenotyping, cytogenetic and molecular studies are required for AML diagnosis, including the use of next-generation sequencing (NGS) gene panels to screen all genetic alterations with diagnostic, prognostic and/or therapeutic value. Regarding AML monitoring, multiparametric flow cytometry and quantitative PCR/RT-PCR are currently the most implemented methodologies for measurable residual disease (MRD) evaluation. Given the limitations of these techniques, there is an urgent need to incorporate new tools for MRD monitoring, such as NGS and digital PCR. This review aims to provide an overview of the different technologies used for AML diagnosis and MRD monitoring and to highlight the limitations and challenges of current versus emerging tools.

Clonal Hematopoiesis: Connecting Aging and Inflammation in Atherosclerosis

PURPOSE OF REVIEW

Clonal hematopoiesis (CH) is a prevalent condition that results from the acquisition of somatic mutations in hematopoietic stem cells. When these mutations occur in "driver" genes, they can potentially confer fitness advantages to the cell, leading to a clonal expansion. While most clonal expansions of mutant cells are generally considered to be asymptomatic since they do not impact overall blood cell numbers, CH carriers display long-term risks of all-cause mortality and age-associated diseases including cardiovascular disease (CVD). This review summarizes recent findings in CH related to aging, atherosclerotic CVD, and inflammation, emphasizing epidemiological and mechanistic studies, and potential therapeutic options to treat CVDs that are promoted by CH.

RECENT FINDINGS

Epidemiological studies have revealed associations between CH and CVDs. Experimental studies with CH models employing the Tet2- and Jak2-mutant mouse lines display inflammasome activation and a chronic inflammatory state that leads to accelerated atherosclerotic lesion growth. A body of evidence suggests that CH represents a new causal risk factor for CVD. Studies also indicate that understanding an individual's CH status could provide guidance for personalized approaches to treat atherosclerosis and other CVDs with anti-inflammatory drugs.

Measurable Residual Disease and Clonal Evolution in Acute Myeloid Leukemia from Diagnosis to Post-Transplant Follow-Up: The Role of Next-Generation Sequencing

It has now been ascertained that acute myeloid leukemias-as in most type of cancers-are mixtures of various subclones, evolving by acquiring additional somatic mutations over the course of the disease. The complexity of leukemia clone architecture and the phenotypic and/or genotypic drifts that can occur during treatment explain why more than 50% of patients-in hematological remission-could relapse. Moreover, the complexity and heterogeneity of clone architecture represent a hindrance for monitoring measurable residual disease, as not all minimal residual disease monitoring methods are able to detect genetic mutations arising during treatment. Unlike with chemotherapy, which imparts a relatively short duration of selective pressure on acute myeloid leukemia clonal architecture, the immunological effect related to allogeneic hematopoietic stem cell transplant is prolonged over time and must be overcome for relapse to occur. This means that not all molecular abnormalities detected after transplant always imply inevitable relapse. Therefore, transplant represents a critical setting where a measurable residual disease-based strategy, performed during post-transplant follow-up by highly sensitive methods such as next-generation sequencing, could optimize and improve treatment outcome. The purpose of our review is to provide an overview of the role of next-generation sequencing in monitoring both measurable residual disease and clonal evolution in acute myeloid leukemia patients during the entire course of the disease, with special focus on the transplant phase.

The role of next-generation sequencing in acute myeloid leukemia

PURPOSE OF REVIEW

The development of high-throughput techniques like next-generation sequencing (NGS) has unraveled the genetic profile of cancer. In this review, we discuss the role of NGS on the diagnostic, risk stratification, and follow-up of patients with acute myeloid leukemia (AML).

RECENT FINDINGS

NGS has become an essential tool in clinical practice for AML management. Therefore, efforts are being made to improve its applications, automation, and turnaround time. Other high-throughput techniques, such as whole genome sequencing or RNA-sequencing, can be also used to this end. However, not all institutions may be able to implement these approaches. NGS is being investigated for measurable residual disease (MRD) assessment, especially with the development of error-correction NGS. New data analysis approaches like machine learning are being investigated in order to integrate genomic and clinical data and develop comprehensive classifications and risk scores.

SUMMARY

NGS has proven to be a useful approach for the analysis of genomic alterations in patients with AML, which aids patient management. Current research is being directed at reducing turnaround time and simplifying processes so that these techniques can be universally integrated into clinical practice.

Distinct Patterns of Clonal Evolution Drive Myelodysplastic Syndrome Progression to Secondary Acute Myeloid Leukemia

Clonal evolution in myelodysplastic syndrome (MDS) can result in clinical progression and secondary acute myeloid leukemia (sAML). To dissect changes in clonal architecture associated with this progression, we performed single-cell genotyping of paired MDS and sAML samples from 18 patients. Analysis of single-cell genotypes revealed patient-specific clonal evolution and enabled the assessment of single-cell mutational cooccurrence. We discovered that changes in clonal architecture proceed via distinct patterns, classified as static or dynamic, with dynamic clonal architectures having a more proliferative phenotype by blast count fold change. Proteogenomic analysis of a subset of patients confirmed that pathogenic mutations were primarily confined to primitive and mature myeloid cells, though we also identify rare but present mutations in lymphocyte subsets. Single-cell transcriptomic analysis of paired sample sets further identified gene sets and signaling pathways involved in two cases of progression. Together, these data define serial changes in the MDS clonal landscape with clinical and therapeutic implications.

SIGNIFICANCE

Precise clonal trajectories in MDS progression are made possible by single-cell genomic sequencing. Here we use this technology to uncover the patterns of clonal architecture and clonal evolution that drive the transformation to secondary AML. We further define the phenotypic and transcriptional changes of disease progression at the single-cell level. See related article by Menssen et al., p. 330 (31). See related commentary by Romine and van Galen, p. 270. This article is highlighted in the In This Issue feature, p. 265.

Screening of early-staged colorectal neoplasia by clonal hematopoiesis-based liquid biopsy and machine-learning

Liquid biopsy test has a better uptake for colorectal cancer (CRC) screening. However, suboptimal detection of early-staged colorectal neoplasia (CRN) limits its application. Here, we established an early-staged CRN blood test using error-corrected sequencing by comparing clonal hematopoiesis (CH) of 63 CRN patients and that of 32 controls. We identified 1,446 variants and classified the uniqueness in CRN patients. There was no significance difference in the amount of variant between CRNs and controls, but the uniqueness of variants with defective DNA mismatch repair-related mutational signature was addressed from peripheral blood in early-staged CRN patients. By machine learning approach, the early-staged CRNs was discriminated from controls with an AUC of 0.959 and an accuracy of 0.937 (95% CI, 0.863 to 0.968). The CRN predictive model was further validated by additional 20 CRNs and 10 controls and showed the accuracy, sensitivity, specificity, positive prediction value (PPV) and negative prediction value (NPV) of 0.933 (95% CI: 0.779 to 0.992), 0.95, 0.90, 0.95 and 0.90, respectively. In summary, we develop a CH-based liquid biopsy test with machine learning approach, which not only increase screening uptake but also improve the detection rate of early-staged CRN.

The hematopoietic saga of clonality in sickle cell disease

Sickle cell disease (SCD) is associated with an increased risk of vascular-occlusive events and of leukemia. Clonal hematopoiesis (CH) may increase both risks. In turn, physiologic abnormalities in SCD may modify the incidence and/or distribution of genetic alterations in CH. In a recent issue of the JCI, Liggett et al. found no difference in CH rate between individuals with versus without SCD. Here we contextualize this report and discuss the complex interplay between CH and SCD with particular attention to consequences for emerging gene therapies. We further consider the limitations in our current understanding of these topics that must be addressed in order to optimize therapeutic strategies for SCD.

Systematic Profiling of DNMT3A Variants Reveals Protein Instability Mediated by the DCAF8 E3 Ubiquitin Ligase Adaptor

Clonal hematopoiesis is a prevalent age-related condition associated with a greatly increased risk of hematologic disease; mutations in DNA methyltransferase 3A (DNMT3A) are the most common driver of this state. DNMT3A variants occur across the gene with some particularly associated with malignancy, but the functional relevance and mechanisms of pathogenesis of the majority of mutations are unknown. Here, we systematically investigated the methyltransferase activity and protein stability of 253 disease-associated DNMT3A mutations, and found that 74% were loss-of-function mutations. Half of these variants exhibited reduced protein stability and, as a class, correlated with greater clonal expansion and acute myeloid leukemia development. We investigated the mechanisms underlying the instability using a CRISPR screen and uncovered regulated destruction of DNMT3A mediated by the DCAF8 E3 ubiquitin ligase adaptor. We establish a new paradigm to classify novel variants that has prognostic and potential therapeutic significance for patients with hematologic disease. SIGNIFICANCE: DNMT3A has emerged as the most important epigenetic regulator and tumor suppressor in the hematopoietic system. Our study represents a systematic and high-throughput method to characterize the molecular impact of DNMT3A missense mutations and the discovery of a regulated destruction mechanism of DNMT3A offering new prognostic and future therapeutic avenues.See related commentary by Ma and Will, p. 23.This article is highlighted in the In This Issue feature, p. 1.

Intensive monitoring of minimal residual disease and chimerism after allogeneic hematopoietic stem cell transplantation for acute leukemia in children

Posttransplant leukemia detection before overt relapse is key to the success of immunotherapeutic interventions, as they are more efficient when leukemia burden is low. However, optimal schedule and monitoring methods are not well defined. We report the intensive bone marrow monitoring of minimal residual disease (MRD) using flow cytometry (FC) and nested reverse transcription polymerase chain reaction (RT-PCR) whenever a fusion transcript allowed it and chimerism by PCR at 11 timepoints in the first 2 years after transplant. Seventy-one transplants were performed in 59 consecutive children, for acute myeloid (n = 38), lymphoid (n = 31), or mixed-phenotype (n = 2) leukemia. MRD was monitored in 62 cases using FC (n = 58) and/or RT-PCR (n = 35). Sixty-seven percent of leukemia recurrences were detected before overt relapse, with a detection rate of 89% by RT-PCR and 40% by FC alone. Increased mixed chimerism was never the first evidence of recurrence. Two patients monitored by RT-PCR relapsed without previous MRD detection, one after missed scheduled evaluation and the other 4.7 years post transplant. Among the 22 cases with MRD detection without overt relapse, 19 received therapeutic interventions. Eight (42%) never relapsed. In conclusion, intensive marrow monitoring by RT-PCR effectively allows for early detection of posttransplant leukemia recurrence.

CBFB Break-Apart FISH Testing: An Analysis of 1629 AML Cases with a Focus on Atypical Findings and Their Implications in Clinical Diagnosis and Management

Fluorescence in situ hybridization (FISH) is a confirmatory test to establish a diagnosis of inv(16)/t(16;16) AML. However, incidental findings and their clinical diagnostic implication have not been systemically studied. We studied 1629 CBFB FISH cases performed in our institution, 262 (16.1%), 1234 (75.7%), and 133 (8.2%) were reported as positive, normal, and abnormal, respectively. The last included CBFB copy number changes (n = 120) and atypical findings such as 3'CBFB deletion (n = 11), 5'CBFB deletion (n = 1), and 5'CBFB gain (n = 1). Correlating with CBFB-MYH11 RT-PCR results, totally 271 CBFB rearrangement cases were identified, including five with discrepancies between FISH and RT-PCR due to new partner genes (n = 3), insertion (n = 1), or rare CBFB-MYH11 variant (n = 1) and eight with 3'CBFB deletion. All cases with atypical findings and/or discrepancies presented clinical diagnostic challenges. Correlating FISH signal patterns and karyotypes, additional chromosome 16 aberrations (AC16As) show impacts on the re-definition of a complex karyotype and prognostic prediction. The CBFB rearrangement but not all AC16As will be detected by NGS-based methods. Therefore, FISH testing is currently still needed to provide a quick and straightforward confirmatory inv(16)/t(16;16) AML diagnosis and additional information related to clinical management.

Strong concordance between RNA structural and single nucleotide variants identified via next generation sequencing techniques in primary pediatric leukemia and patient-derived xenograft samples

Acute leukemia represents the most common pediatric malignancy comprising diverse subtypes with varying prognosis and treatment outcomes. New and targeted treatment options are warranted for this disease. Patient-derived xenograft (PDX) models are increasingly being used for preclinical testing of novel treatment modalities. A novel approach involving targeted error-corrected RNA sequencing using ArcherDX HemeV2 kit was employed to compare 25 primary pediatric acute leukemia samples and their corresponding PDX samples. A comparison of the primary samples and PDX samples revealed a high concordance between single nucleotide variants and gene fusions whereas other complex structural variants were not as consistent. The presence of gene fusions representing the major driver mutations at similar allelic frequencies in PDX samples compared to primary samples and over multiple passages confirms the utility of PDX models for preclinical drug testing. Characterization and tracking of these novel cryptic fusions and exonal variants in PDX models is critical in assessing response to potential new therapies.