Mutations associated with a 17-gene leukemia stem cell score and the score's prognostic relevance in the context of the European LeukemiaNet classification of acute myeloid leukemia

A 4-gene prognostic index for enhancing acute myeloid leukaemia survival prediction

Despite advancements in utilizing genetic markers to enhance acute myeloid leukaemia (AML) outcome prediction, significant disease heterogeneity persists, hindering clinical management. To refine survival predictions, we assessed the transcriptome of non-acute promyelocytic leukaemia chemotherapy-treated AML patients from five cohorts (n = 975). This led to the identification of a 4-gene prognostic index (4-PI) comprising CYP2E1, DHCR7, IL2RA and SQLE. The 4-PI effectively stratified patients into risk categories, with the high 4-PI group exhibiting TP53 mutations and cholesterol biosynthesis signatures. Single-cell RNA sequencing revealed enrichment for leukaemia stem cell signatures in high 4-PI cells. Validation across three cohorts (n = 671), including one with childhood AML, demonstrated the reproducibility and clinical utility of the 4-PI, even using cost-effective techniques like real-time quantitative polymerase chain reaction. Comparative analysis with 56 established prognostic indexes revealed the superior performance of the 4-PI, highlighting its potential to enhance AML risk stratification. Finally, the 4-PI demonstrated to be potential marker to reclassified patients from the intermediate ELN2017 category to the adverse category. In conclusion, the 4-PI emerges as a robust and straightforward prognostic tool to improve survival prediction in AML patients.

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling

Complex karyotype (CK) is associated with a poor prognosis in both acute myeloid leukemia (AML) and myelodysplastic syndrome with excess blasts (MDS-EB). Transcriptomic analyses have improved our understanding of the disease and risk stratification of myeloid neoplasms; however, CK-specific gene expression signatures have been rarely investigated. In this study, we developed and validated a CK-specific gene expression signature. Differential gene expression analysis between the CK and non-CK groups using data from 348 patients with AML and MDS-EB from four cohorts revealed enrichment of the downregulated genes localized on chromosome 5q or 7q, suggesting that haploinsufficiency due to the deletion of these chromosomes possibly underlies CK pathogenesis. We built a robust transcriptional model for CK prediction using LASSO regression for gene subset selection and validated it using the leave-one-out cross-validation method for fitting the logistic regression model. We established a 10-gene CK signature (CKS) predictive of CK with high predictive accuracy (accuracy 94.22%; AUC 0.977). CKS was significantly associated with shorter overall survival in three independent cohorts, and was comparable to that of previously established risk stratification models for AML. Furthermore, we explored of therapeutic targets among the genes comprising CKS and identified the dysregulated expression of superoxide dismutase 1 (SOD1) gene, which is potentially amenable to SOD1 inhibitors.

LSC17 score complements genetics and measurable residual disease in acute myeloid leukemia: an ALFA study

Whether the LSC17 gene expression can improve risk stratification in the context of next generation sequencing-based risk stratification and measurable residual disease (MRD) in patients with intensively treated AML has not been explored. We analyzed LSC17 in 504 adult patients prospectively treated in the ALFA-0702 trial. RUNX1 or TP53 mutations were associated with higher LSC1 scores while CEBPA and NPM1 mutations were associated with lower scores. Patients with high LSC17 scores had a lower rate of complete response (CR) in a multivariable analysis (odds ratio, 0.41; P = .0007), accounting for European LeukemiaNet 2022 (ELN22), age, and white blood cell count (WBC). LSC17-high status was associated with shorter overall survival (OS) (3-year OS: 70.0% vs 52.7% in patients with LSC17-low status; P < .0001). In a multivariable analysis considering ELN22, age, and WBC, patients with LSC17-high status had shorter disease-free survival (DFS) (hazard ratio [HR], 1.36; P = .048) than those with LSC17-low status. In 123 patients with NPM1-mutated AML in CR, LSC17-high status predicted poorer DFS (HR, 2.34; P = .01), independent of age, WBC, ELN22 risk, and NPM1-MRD. LSC-low status and negative NPM1-MRD identified a subset comprising 48% of patients with mutated NPM1 with a 3-year OS from CR of 93.1% compared with 60.7% in those with LSC17-high status and/or positive NPM1-MRD (P = .0001). Overall, LSC17 assessment refines genetic risk stratification in adult patients with AML treated intensively. Combined with MRD, LSC17 identifies a subset of patients with NPM1-mutated AML with excellent clinical outcome.

Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors

An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on "knowledge banks". Indeed, more robust prognostic estimations can be obtained by matching each patient's genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed.

TP53-Mutated Myelodysplasia and Acute Myeloid Leukemia

TP53-mutated myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) form a distinct and heterogeneous group of myeloid malignancies associated with poor outcomes. Studies carried out in the last years have in part elucidated the complex role played by TP53 mutations in the pathogenesis of these myeloid disorders and in the mechanisms of drug resistance. A consistent number of studies has shown that some molecular parameters, such as the presence of a single or multiple TP53 mutations, the presence of concomitant TP53 deletions, the association with co-occurring mutations, the clonal size of TP53 mutations, the involvement of a single (monoallelic) or of both TP53 alleles (biallelic) and the cytogenetic architecture of concomitant chromosome abnormalities are major determinants of outcomes of patients. The limited response of these patients to standard treatments, including induction chemotherapy, hypomethylating agents and venetoclax-based therapies and the discovery of an immune dysregulation have induced a shift to new emerging therapies, some of which being associated with promising efficacy. The main aim of these novel immune and nonimmune strategies consists in improving survival and in increasing the number of TP53-mutated MDS/AML patients in remission amenable to allogeneic stem cell transplantation.

Immune dysfunction signatures predict outcomes and define checkpoint blockade-unresponsive microenvironments in acute myeloid leukemia

BackgroundImmune exhaustion and senescence are dominant dysfunctional states of effector T cells and major hurdles for the success of cancer immunotherapy. In the current study, we characterized how acute myeloid leukemia (AML) promotes the generation of senescent-like CD8+ T cells and whether they have prognostic relevance.METHODSWe analyzed NanoString, bulk RNA-Seq and single-cell RNA-Seq data from independent clinical cohorts comprising 1,896 patients treated with chemotherapy and/or immune checkpoint blockade (ICB).ResultsWe show that senescent-like bone marrow CD8+ T cells were impaired in killing autologous AML blasts and that their proportion negatively correlated with overall survival (OS). We defined what we believe to be new immune effector dysfunction (IED) signatures using 2 gene expression profiling platforms and reported that IED scores correlated with adverse-risk molecular lesions, stemness, and poor outcomes; these scores were a more powerful predictor of OS than 2017-ELN risk or leukemia stem cell (LSC17) scores. IED expression signatures also identified an ICB-unresponsive tumor microenvironment and predicted significantly shorter OS.ConclusionThe IED scores provided improved AML-risk stratification and could facilitate the delivery of personalized immunotherapies to patients who are most likely to benefit.TRIAL REGISTRATIONClinicalTrials.gov; NCT02845297.FUNDINGJohn and Lucille van Geest Foundation, Nottingham Trent University's Health & Wellbeing Strategic Research Theme, NIH/NCI P01CA225618, Genentech-imCORE ML40354, Qatar National Research Fund (NPRP8-2297-3-494).

Large-Scale In Vitro and In Vivo CRISPR-Cas9 Knockout Screens Identify a 16-Gene Fitness Score for Improved Risk Assessment in Acute Myeloid Leukemia

PURPOSE

The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and guiding risk-adapted therapy decisions.

EXPERIMENTAL DESIGN

We systematically integrated and analyzed the genome-wide CRISPR-Cas9 data from more than 1,000 in vitro and in vivo knockout screens to identify the AML-specific fitness genes. A prognostic fitness score was developed using the sparse regression analysis in a training cohort of 618 cases and validated in five publicly available independent cohorts (n = 1,570) and our RJAML cohort (n = 157) with matched RNA sequencing and targeted gene sequencing performed.

RESULTS

A total of 280 genes were identified as AML fitness genes and a 16-gene AML fitness (AFG16) score was further generated and displayed highly prognostic power in more than 2,300 patients with AML. The AFG16 score was able to distill downstream consequences of several genetic abnormalities and can substantially improve the European LeukemiaNet classification. The multi-omics data from the RJAML cohort further demonstrated its clinical applicability. Patients with high AFG16 scores had significantly poor response to induction chemotherapy. Ex vivo drug screening indicated that patients with high AFG16 scores were more sensitive to the cell-cycle inhibitors flavopiridol and SNS-032, and exhibited strongly activated cell-cycle signaling.

CONCLUSIONS

Our findings demonstrated the utility of the AFG16 score as a powerful tool for better risk stratification and selecting patients most likely to benefit from chemotherapy and alternative experimental therapies.

The 17‐gene stemness score associates with relapse risk and long‐term outcomes following allogeneic haematopoietic cell transplantation in acute myeloid leukaemia

A 17‐gene stemness (LSC17) score determines risk in acute myeloid leukaemia patients treated with standard chemotherapy regimens. The present study further analysed the impact of the LSC17 score at diagnosis on outcomes following allogeneic haematopoietic cell transplantation (HCT). Out of 452 patients with available LSC17 score, 123 patients received allogeneic HCT. Transplant outcomes, including overall (OS), leukaemia‐free survival (LFS), relapse incidence (RI) and non‐relapse mortality (NRM), were compared according to the LSC17 scored group. The patients with a low LSC17 score had higher OS (56.2%) and LFS (54.4%) at 2 years compared to patients with high LSC17 score (47.2%, p = 0.0237 for OS and 46.0%, p = 0.0181 for LFS). The low LSC17 score group also had a lower relapse rate at 2 years (12.7%) compared to 25.3% in the high LSC17 score group (p = 0.017), but no difference in NRM (p = 0.674). Worse outcomes in the high LSC17 score group for OS, LFS and relapse were consistently observed across all stratified sub‐groups. The use of more intensive conditioning did not improve outcomes for either group. In contrast, chronic graft‐versus‐host‐disease was associated with more favourable outcomes in both groups. The 17‐gene stemness score is highly prognostic for survival and relapse risk following allogeneic HCT.

Human acute myeloid leukemia stem cells: evolution of concept

The history of human acute myeloid leukemia stem cells (AMLSCs) began in a seminal study performed by Lapidot and Dick, proving that only CD34+CD38- human primary acute myeloid leukemia (AML) cells can repopulate in severe combined immunodeficient mice. The concept of leukemic stem cells (LSCs) has impeded a huge change in the treatment strategy against AML from killing proliferating leukemic cells to eradicating quiescent/dormant LSCs. As next-generation sequencing technologies have developed, multiple and recurrent genetic mutations have been discovered in large cohorts of patients with AML, and the updated understanding of leukemogenesis has improved the old concept of LSC to a revised version of a serial developmental model of LSC; that is, pre-LSCs are generated as seeds by the first hit on epigenetic regulators, and then, leukemia-initiating LSCs emerge from seeds by the second hits on genes involved in transcription and signaling. Dreams for universal and targetable AMLSC biomarker sparing healthy hematopoietic stem cells have weakened after the confrontation of significant heterogeneity of AMLSCs from genomic and immunophenotypic viewpoints. However, there is still hope for effective targets for AMLSCs since there is evidence that grouped gene signatures, such as 17-gene LSC score, and common epigenetic signatures, such as HOXA clusters, independent of various gene mutations, exist. Recently, the LSC niche in the bone marrow has been actively investigated and has expanded our knowledge of the physiology and vulnerability of AMLSCs. Presently, an applicable treatment that always works in AMLSCs is lacking. However, we will find a way, we always have.

Multimerin-1 and cancer: a review

Multimerin-1 (MMRN1) is a platelet protein with a role in haemostasis and coagulation. It is also present in endothelial cells (ECs) and the extracellular matrix (ECM), where it may be involved in cell adhesion, but its molecular functions and protein–protein interactions in these cellular locations have not been studied in detail yet. In recent years, MMRN1 has been identified as a differentially expressed gene (DEG) in various cancers and it has been proposed as a possible cancer biomarker. Some evidence suggest that MMRN1 expression is regulated by methylation, protein interactions, and non-coding RNAs (ncRNAs) in different cancers. This raises the questions if a functional role of MMRN1 is being targeted during cancer development, and if MMRN1’s differential expression pattern correlates with cancer progression. As a result, it is timely to review the current state of what is known about MMRN1 to help inform future research into MMRN1’s molecular mechanisms in cancer.

A Clinical Laboratory-Developed LSC17 Stemness Score Assay for Rapid Risk Assessment of Acute Myeloid Leukemia Patients

Leukemia stem cells (LSC) are linked to relapse in acute myeloid leukemia (AML). The LSC17 gene expression score robustly captures LSC stemness properties in AML and can be used to predict survival outcomes and response to therapy, enabling risk-adapted upfront treatment approaches. The LSC17 score was developed and validated in a research setting. To enable wide use of the LSC17 score in clinical decision-making, we established a Laboratory Developed Test (LDT) for the LSC17 score that can be deployed broadly in clinical molecular diagnostic laboratories. We extensively validated the LSC17 LDT in a College of American Pathologists/Clinical Laboratory Improvements Act (CAP/CLIA)-certified laboratory, determining specimen requirements, a synthetic control, and performance parameters for the assay. Importantly, we correlated values from the LSC17 LDT to clinical outcome for a reference cohort of AML patients, establishing a median assay value that can be used for clinical risk stratification of individual patients with newly-diagnosed AML. The assay was established in a second independent CAP/CLIA-certified laboratory and its technical performance validated using an independent cohort of AML patient samples, demonstrating that the LSC17 LDT can be readily implemented in other settings. This study enables the clinical use of the LSC17 score for upfront risk-adapted management of AML patients.

Integrating genetic and epigenetic factors in chronic myeloid leukemia risk assessment: toward gene expression-based biomarkers

Cancer treatment is constantly evolving from a one-size-fits-all towards bespoke approaches for each patient. In certain solid cancers, including breast and lung, tumor genome profiling has been incorporated into therapeutic decision-making. For chronic phase chronic myeloid leukemia (CML), while tyrosine kinase inhibitor therapy is the standard treatment, current clinical scoring systems cannot accurately predict the heterogeneous treatment outcomes observed in patients. Biomarkers capable of segregating patients according to outcome at diagnosis are needed to improve management, and facilitate enrollment in clinical trials seeking to prevent blast crisis transformation and improve the depth of molecular responses. To this end, gene expression (GE) profiling studies have evaluated whether GE signatures at diagnosis are clinically informative. Patient material from a variety of sources has been profiled using microarrays, RNA sequencing and, more recently, single-cell RNA sequencing. However, differences in the cell types profiled, the technologies used, and the inherent complexities associated with the interpretation of genomic data pose challenges in distilling GE datasets into biomarkers with clinical utility. The goal of this paper is to review previous studies evaluating GE profiling in CML, and explore their potential as risk assessment tools for individualized CML treatment. We also review the contribution that acquired mutations, including those seen in clonal hematopoiesis, make to GE profiles, and how a model integrating contributions of genetic and epigenetic factors in resistance to tyrosine kinase inhibitors and blast crisis transformation can define a route to GE-based biomarkers. Finally, we outline a four-stage approach for the development of GE-based biomarkers in CML.

Precision oncology in AML: validation of the prognostic value of the knowledge bank approach and suggestions for improvement

Recently, a novel knowledge bank (KB) approach to predict outcomes of individual patients with acute myeloid leukemia (AML) was developed using unbiased machine learning. To validate its prognostic value, we analyzed 1612 adults with de novo AML treated on Cancer and Leukemia Group B front-line trials who had pretreatment clinical, cytogenetics, and mutation data on 81 leukemia/cancer-associated genes available. We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate the predictive values of the KB algorithm and other risk classifications. The KB algorithm predicted 3-year overall survival (OS) probability in the entire patient cohort (AUC_KB = 0.799), and both younger (< 60 years) (AUC_KB = 0.747) and older patients (AUC_KB = 0.770). The KB algorithm predicted non-remission death (AUC_KB = 0.860) well but was less accurate in predicting relapse death (AUC_KB = 0.695) and death in first complete remission (AUC_KB = 0.603). The KB algorithm’s 3-year OS predictive value was higher than that of the 2017 European LeukemiaNet (ELN) classification (AUC_2017ELN = 0.707, p < 0.001) and 2010 ELN classification (AUC_2010ELN = 0.721, p < 0.001) but did not differ significantly from that of the 17-gene stemness score (AUC_17-gene = 0.732, p = 0.10). Analysis of additional cytogenetic and molecular markers not included in the KB algorithm revealed that taking into account atypical complex karyotype, infrequent recurrent balanced chromosome rearrangements and mutational status of the SAMHD1, AXL and NOTCH1 genes may improve the KB algorithm. We conclude that the KB algorithm has a high predictive value that is higher than those of the 2017 and 2010 ELN classifications. Inclusion of additional genetic features might refine the KB algorithm.

Gene expression signature predicts relapse in adult patients with cytogenetically normal acute myeloid leukemia

Although ∼80% of adult patients with cytogenetically normal acute myeloid leukemia (CN-AML) achieve a complete remission (CR), more than half of them relapse. Better identification of patients who are likely to relapse can help to inform clinical decisions. We performed RNA sequencing on pretreatment samples from 268 adults with de novo CN-AML who were younger than 60 years of age and achieved a CR after induction treatment with standard "7+3" chemotherapy. After filtering for genes whose expressions were associated with gene mutations known to impact outcome (ie, CEBPA, NPM1, and FLT3-internal tandem duplication [FLT3-ITD]), we identified a 10-gene signature that was strongly predictive of patient relapse (area under the receiver operating characteristics curve [AUC], 0.81). The signature consisted of 7 coding genes (GAS6, PSD3, PLCB4, DEXI, JMY, NRP1, C10orf55) and 3 long noncoding RNAs. In multivariable analysis, the 10-gene signature was strongly associated with relapse (P < .001), after adjustment for the FLT3-ITD, CEBPA, and NPM1 mutational status. Validation of the expression signature in an independent patient set from The Cancer Genome Atlas showed the signature's strong predictive value, with AUC = 0.78. Implementation of the 10-gene signature into clinical prognostic stratification could be useful for identifying patients who are likely to relapse.

Minimally myelosuppressive regimen for remission induction in pediatric AML: long-term results of an observational study

Treatment refusal and death as a result of toxicity account for most treatment failures among children with acute myeloid leukemia (AML) in resource-constrained settings. We recently reported the results of treating children with AML with a combination of low-dose cytarabine and mitoxantrone or omacetaxine mepesuccinate with concurrent granulocyte colony-stimulating factor (G-CSF) (low-dose chemotherapy [LDC]) for remission induction followed by standard postremission strategies. We have now expanded the initial cohort and have provided long-term follow-up. Eighty-three patients with AML were treated with the LDC regimen. During the study period, another 100 children with AML received a standard-dose chemotherapy (SDC) regimen. Complete remission was attained in 88.8% and 86.4% of patients after induction in the LDC and SDC groups, respectively (P = .436). Twenty-two patients in the LDC group received SDC for the second induction course. Significantly more high-risk AML patients were treated with the SDC regimen (P = .035). There were no significant differences between the LDC and SDC groups in 5-year event-free survival (61.4% ± 8.7% vs 65.2% ± 7.4%, respectively; P = .462), overall survival (72.7% ± 6.9% vs 72.5% ± 6.2%, respectively; P = .933), and incidence of relapse (20.5% ± 4.5% vs 17.6% ± 3.9%, respectively; P = .484). Clearance of mutations based on the average variant allele frequency at complete remission in the LDC and SDC groups was 1.9% vs 0.6% (P < .001) after induction I and 0.17% vs 0.078% (P = .052) after induction II. In conclusion, our study corroborated the high remission rate reported for children with AML who received at least 1 course of LDC. The results, although preliminary, also suggest that long-term survival of these children is comparable to that of children who receive SDC regimens.

Genomic analysis of cellular hierarchy in acute myeloid leukemia using ultrasensitive LC-FACSeq

Hematopoiesis is hierarchical, and it has been postulated that acute myeloid leukemia (AML) is organized similarly with leukemia stem cells (LSCs) residing at the apex. Limited cells acquired by fluorescence activated cell sorting in tandem with targeted amplicon-based sequencing (LC-FACSeq) enables identification of mutations in small subpopulations of cells, such as LSCs. Leveraging this, we studied clonal compositions of immunophenotypically-defined compartments in AML through genomic and functional analyses at diagnosis, remission and relapse in 88 AML patients. Mutations involving DNA methylation pathways, transcription factors and spliceosomal machinery did not differ across compartments, while signaling pathway mutations were less frequent in putative LSCs. We also provide insights into TP53-mutated AML by demonstrating stepwise acquisition of mutations beginning from the preleukemic hematopoietic stem cell stage. In 10 analyzed cases, acquisition of additional mutations and del(17p) led to genetic and functional heterogeneity within the LSC pool with subclones harboring varying degrees of clonogenic potential. Finally, we use LC-FACSeq to track clonal evolution in serial samples, which can also be a powerful tool to direct targeted therapy against measurable residual disease. Therefore, studying clinically significant small subpopulations of cells can improve our understanding of AML biology and offers advantages over bulk sequencing to monitor the evolution of disease.