Comparison of DNA methylation based classification models for precision diagnostics of central nervous system tumors.

As part of the advancement in therapeutic decision-making for brain tumor patients at St. Jude Children's Research Hospital (SJCRH), we developed three robust classifiers, a deep learning neural network (NN), k-nearest neighbor (kNN), and random forest (RF), trained on a reference series DNA-methylation profiles to classify central nervous system (CNS) tumor types. The models' performance was rigorously validated against 2054 samples from two independent cohorts. In addition to classic metrics of model performance, we compared the robustness of the three models to reduced tumor purity, a critical consideration in the clinical utility of such classifiers. Our findings revealed that the NN model exhibited the highest accuracy and maintained a balance between precision and recall. The NN model was the most resistant to drops in performance associated with a reduction in tumor purity, showing good performance until the purity fell below 50%. Through rigorous validation, our study emphasizes the potential of DNA-methylation-based deep learning methods to improve precision medicine for brain tumor classification in the clinical setting.

Somatic mitochondrial DNA mutations are a source of heterogeneity among primary leukemic cells.

Somatic mitochondrial DNA (mtDNA) mutations are prevalent in tumors, yet defining their biological significance remains challenging due to the intricate interplay between selective pressure, heteroplasmy, and cell state. Utilizing bulk whole-genome sequencing data from matched tumor and normal samples from two cohorts of pediatric cancer patients, we uncover differences in the accumulation of synonymous and nonsynonymous mtDNA mutations in pediatric leukemias, indicating distinct selective pressures. By integrating single-cell sequencing (SCS) with mathematical modeling and network-based systems biology approaches, we identify a correlation between the extent of cell-state changes associated with tumor-enriched mtDNA mutations and the selective pressures shaping their distribution among individual leukemic cells. Our findings also reveal an association between specific heteroplasmic mtDNA mutations and cellular responses that may contribute to functional heterogeneity among leukemic cells and influence their fitness. This study highlights the potential of SCS strategies for distinguishing between pathogenic and passenger somatic mtDNA mutations in cancer.

Genomic Determinants of Outcome in Acute Lymphoblastic Leukemia.

PURPOSE: Although cure rates for childhood acute lymphoblastic leukemia (ALL) exceed 90%, ALL remains a leading cause of cancer death in children. Half of relapses arise in children initially classified with standard-risk (SR) disease. MATERIALS AND METHODS: To identify genomic determinants of relapse in children with SR ALL, we performed genome and transcriptome sequencing of diagnostic and remission samples of children with SR (n = 1,381) or high-risk B-ALL with favorable cytogenetic features (n = 115) enrolled on Children's Oncology Group trials. We used a case-control study design analyzing 439 patients who relapsed and 1,057 who remained in complete remission for at least 5 years. RESULTS: Genomic subtype was associated with relapse, which occurred in approximately 50% of cases of PAX5-altered ALL (odds ratio [OR], 3.31 [95% CI, 2.17 to 5.03]; P = 3.18 × 10-8). Within high-hyperdiploid ALL, gain of chromosome 10 with disomy of chromosome 7 was associated with favorable outcome (OR, 0.27 [95% CI, 0.17 to 0.42]; P = 8.02 × 10-10; St Jude Children's Research Hospital validation cohort: OR, 0.22 [95% CI, 0.05 to 0.80]; P = .009), and disomy of chromosomes 10 and 17 with gain of chromosome 6 was associated with relapse (OR, 7.16 [95% CI, 2.63 to 21.51]; P = 2.19 × 10-5; validation cohort: OR, 21.32 [95% CI, 3.62 to 119.30]; P = .0004). Genomic alterations were associated with relapse in a subtype-dependent manner, including alterations of INO80 in ETV6::RUNX1 ALL, IKZF1, and CREBBP in high-hyperdiploid ALL and FHIT in BCR::ABL1-like ALL. Genomic alterations were also associated with the presence of minimal residual disease, including NRAS and CREBBP in high-hyperdiploid ALL. CONCLUSION: Genetic subtype, patterns of aneuploidy, and secondary genomic alterations determine risk of relapse in childhood ALL. Comprehensive genomic analysis is required for optimal risk stratification.

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes.

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.

Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials.

In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the previously reported pLSC6 maintained strong significant association in all validation cohorts. For pLSC6/ADE-RS5-integrated-score analysis, using Group-1 (low-scores for ADE-RS5 and pLSC6) as reference, Group-4 (high-scores for ADE-RS5 and pLSC6) showed worst outcome (EFS: p < 0.0001 and OS: p < 0.0001). Groups-2/3 (one high and one low-score) showed intermediate outcome (p < 0.001). Integrated score groups remained an independent predictor of outcome in multivariable-analysis after adjusting for established prognostic factors (EFS: Group 2 vs. 1, HR = 4.68, p < 0.001, Group 3 vs. 1, HR = 3.22, p = 0.01, and Group 4 vs. 1, HR = 7.26, p < 0.001). These results highlight the significant prognostic value of transcriptomics-based scores capturing disease aggressiveness through pLSC6 and drug resistance via ADE-RS5. The pLSC6 stemness score is a significant predictor of outcome and associates with high-risk group features, the ADE-RS5 drug resistance score adds further value, reflecting the clinical utility of simultaneous testing of both for optimizing treatment strategies.

Bootstrap Evaluation of Association Matrices (BEAM) for Integrating Multiple Omics Profiles with Multiple Outcomes.

Motivation: Large datasets containing multiple clinical and omics measurements for each subject motivate the development of new statistical methods to integrate these data to advance scientific discovery. Model: We propose bootstrap evaluation of association matrices (BEAM), which integrates multiple omics profiles with multiple clinical endpoints. BEAM associates a set omic features with clinical endpoints via regression models and then uses bootstrap resampling to determine statistical significance of the set. Unlike existing methods, BEAM uniquely accommodates an arbitrary number of omic profiles and endpoints. Results: In simulations, BEAM performed similarly to the theoretically best simple test and outperformed other integrated analysis methods. In an example pediatric leukemia application, BEAM identified several genes with biological relevance established by a CRISPR assay that had been missed by univariate screens and other integrated analysis methods. Thus, BEAM is a powerful, flexible, and robust tool to identify genes for further laboratory and/or clinical research evaluation. Availability: Source code, documentation, and a vignette for BEAM are available on GitHub at: https://github.com/annaSeffernick/BEAMR. The R package is available from CRAN at: https://cran.r-project.org/package=BEAMR. Contact: Stanley.Pounds@stjude.org. Supplementary Information: Supplementary data are available at the journal's website.

Pharmacogenomic Score Effectively Personalizes Treatment of Acute Myeloid Leukemia.

PURPOSE: Cytarabine (also known as ara-C) has been the backbone of acute myeloid leukemia (AML) chemotherapy for more than five decades. Recent pharmacogenomics-based 10-SNP ara-C (ACS10) scores showed low ACS10 (≤0) to be associated with poor outcomes in patients with AML treated with standard chemotherapy. Here, we evaluated the ACS10 score in the context of three different induction I regimens in patients with pediatric AML. EXPERIMENTAL DESIGN: ACS10 score groups (low, ≤0, or high, >0) were evaluated for association with event-free survival (EFS) and overall survival (OS) by three randomized treatment arms in patients treated on the AML02 (NCT00136084) and AML08 (NCT00703820) clinical trials: AML02 low-dose ara-C (LDAC arm, n = 91), AML02 + AML08 high-dose ara-C (HDAC arm, n = 194), and AML08 clofarabine + ara-C (Clo/ara-C arm, n = 105) induction I regimens. RESULTS: Within the low-ACS10 score (≤0) group, significantly improved EFS and OS were observed among patients treated with Clo/ara-C as compared with LDAC (EFS, HR = 0.45; 95% CI, 0.23-0.88; P = 0.020; OS, HR = 0.44; 95% CI, 0.19-0.99; P = 0.048). In contrast, within the high-ACS10 score group (score >0), augmentation with Clo/ara-C was not favorable as compared with LDAC (Clo/ara-C vs. LDAC, EFS, HR = 1.95; 95% CI, 1.05-3.63; P = 0.035; OS, HR = 2.10; 95% CI, 0.96-4.59; P = 0.063). Personalization models predicted 9% improvement in the outcome in ACS10 score-based tailored induction (Clo/ara-C for low and LDAC for high-ACS10 score groups) as compared with nonpersonalized approaches (P < 0.002). CONCLUSIONS: Our findings suggest that tailoring induction regimens using ACS10 scores can significantly improve outcomes in patients with AML. Given the SNPs are germline, preemptive genotyping can accelerate matching the most effective remission induction regimen.

Pharmacogenomics, Race, and Treatment Outcome in Pediatric Acute Myeloid Leukemia.

Importance: Disparities in outcomes exist between Black and White patients with acute myeloid leukemia (AML), with Black patients experiencing poorer prognosis compared with their White counterparts. Objective: To assess whether varying intensity of induction therapy to treat pediatric AML is associated with reduced disparities in treatment outcome by race. Design, Setting, and Participants: A comparative effectiveness analysis was conducted of 86 Black and 359 White patients with newly diagnosed AML who were enrolled in the AML02 trial from 2002 to 2008 or the AML08 trial from 2008 to 2017. Statistical analysis was conducted from July 2023 through January 2024. Interventions: Patients in AML02 were randomly assigned to receive standard low-dose cytarabine-based induction therapy or augmented high-dose cytarabine-based induction therapy, whereas patients in AML08 received high-dose cytarabine-based therapy. Main Outcomes and Measures: Cytarabine pharmacogenomic 10-single-nucleotide variant (ACS10) scores were evaluated for association with outcome according to race and treatment arm. Results: This analysis included 86 Black patients (mean [SD] age, 8.8 [6.5] years; 54 boys [62.8%]; mean [SD] leukocyte count, 52 600 [74 000] cells/µL) and 359 White patients (mean [SD] age, 9.1 [6.2] years; 189 boys [52.6%]; mean [SD] leukocyte count, 54 500 [91 800] cells/µL); 70 individuals with other or unknown racial and ethnic backgrounds were not included. Among all patients without core binding factor AML who received standard induction therapy, Black patients had significantly worse outcomes compared with White patients (5-year event-free survival rate, 25% [95% CI, 9%-67%] compared with 56% [95% CI, 46%-70%]; P = .03). By contrast, among all patients who received augmented induction therapy, there were no differences in outcome according to race (5-year event-free survival rate, Black patients, 50% [95% CI, 38%-67%]; White patients, 48% [95% CI, 42%-55%]; P = .78). Among patients who received standard induction therapy, those with low ACS10 scores had a significantly worse 5-year event-free survival rate compared with those with high scores (42.4% [95% CI, 25.6%-59.3%] and 70.0% [95% CI, 56.6%-83.1%]; P = .004); however, among patients who received augmented induction therapy, there were no differences in 5-year event-free survival rates according to ACS10 score (low score, 60.6% [95% CI, 50.9%-70.2%] and high score, 54.8% [95% CI, 47.1%-62.5%]; P = .43). Conclusions and Relevance: In this comparative effectiveness study of pediatric patients with AML treated in 2 consecutive clinical trials, Black patients had worse outcomes compared with White patients after treatment with standard induction therapy, but this disparity was eliminated by treatment with augmented induction therapy. When accounting for ACS10 scores, no outcome disparities were seen between Black and White patients. Our results suggest that using pharmacogenomics parameters to tailor induction regimens for both Black and White patients may narrow the racial disparity gap in patients with AML.

Comprehensive genomic analysis reveals molecular heterogeneity in pediatric ALK-positive anaplastic large cell lymphoma.

Anaplastic large cell lymphoma (ALCL) is a mature T-cell lymphoma that accounts for for 10-15% of childhood lymphomas. Despite the observation that more than 90% of pediatric cases harbor the anaplastic lymphoma kinase (ALK) rearrangement resulting in aberrant ALK kinase expression, there is significant clinical, morphologic, and biological heterogeneity. To gain insights into the genomic aberrations and molecular heterogeneity within ALK-positive ALCL(ALK+ ALCL), we analyzed 46 pediatric ALK+ ALCLs by whole-exome sequencing, RNA-sequencing, and DNA methylation profiling. Whole-exome sequencing found on average 25 SNV/Indel events per sample with recurring genetic events in regulators of DNA damage (TP53, MDM4), transcription (JUNB), and epigenetic regulators (TET1, KMT2B, KMT2A, KMT2C, KMT2E). Gene expression and methylation profiling consistently subclassified ALK+ ALCLs into two groups characterized by diferential ALK expression levels. The ALK-low group showed enrichment of pathways associated with immune response, cytokine signaling, and a hypermethylated predominant pattern compared to the ALK- high group, which had more frequent copy number changes, and was enriched with pathways associated with cell growth, proliferation, metabolic pathways, and. Taken together, these findings suggest that there is molecular heterogeneity within pediatric ALK+ALCL, predicting distinct biological mechanisms that may provide novel insights into disease pathogenesis and represent prognostic markers.

A new genomic framework to categorize pediatric acute myeloid leukemia.

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.

Identification and targeting of treatment resistant progenitor populations in T-cell Acute Lymphoblastic Leukemia.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to cure in T-cell Acute Lymphoblastic Leukemia (T-ALL). Biomarker guided risk stratification and targeted therapy have the potential to improve outcomes in high-risk T-ALL; however, cellular and genetic factors contributing to treatment resistance remain unknown. Previous bulk genomic studies in T-ALL have implicated tumor heterogeneity as an unexplored mechanism for treatment failure. To link tumor subpopulations with clinical outcome, we created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic (CITE-seq/snATAC-seq) analysis to a cohort of 40 cases of T-ALL treated on the Children's Oncology Group AALL0434 clinical trial. The cohort was carefully selected to capture the immunophenotypic diversity of T-ALL, with early T-cell precursor (ETP) and Near/Non-ETP subtypes represented, as well as enriched with both relapsed and treatment refractory cases. Integrated analyses of T-ALL blasts and normal T-cell precursors identified a bone-marrow progenitor-like (BMP-like) leukemia sub-population associated with treatment failure and poor overall survival. The single-cell-derived molecular signature of BMP-like blasts predicted poor outcome across multiple subtypes of T-ALL within two independent patient cohorts using bulk RNA-sequencing data from over 1300 patients. We defined the mutational landscape of BMP-like T-ALL, finding that NOTCH1 mutations additively drive T-ALL blasts away from the BMP-like state. We transcriptionally matched BMP-like blasts to early thymic seeding progenitors that have low NR3C1 expression and high stem cell gene expression, corresponding to a corticosteroid and conventional cytotoxic resistant phenotype we observed in ex vivo drug screening. To identify novel targets for BMP-like blasts, we performed in silico and in vitro drug screening against the BMP-like signature and prioritized BMP-like overexpressed cell-surface (CD44, ITGA4, LGALS1) and intracellular proteins (BCL-2, MCL-1, BTK, NF-κB) as candidates for precision targeted therapy. We established patient derived xenograft models of BMP-high and BMP-low leukemias, which revealed vulnerability of BMP-like blasts to apoptosis-inducing agents, TEC-kinase inhibitors, and proteasome inhibitors. Our study establishes the first multi-omic signatures for rapid risk-stratification and targeted treatment of high-risk T-ALL.

Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis.

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 895 pAML into 23 molecular categories that are mutually distinct from one another, including new entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3, or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a prognostic framework for pAML based on molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.

The genomic landscape of acute lymphoblastic leukemia with intrachromosomal amplification of chromosome 21.

Intrachromosomal amplification of chromosome 21 defines a subtype of high-risk childhood acute lymphoblastic leukemia (iAMP21-ALL) characterized by copy number changes and complex rearrangements of chromosome 21. The genomic basis of iAMP21-ALL and the pathogenic role of the region of amplification of chromosome 21 to leukemogenesis remains incompletely understood. In this study, using integrated whole genome and transcriptome sequencing of 124 patients with iAMP21-ALL, including rare cases arising in the context of constitutional chromosomal aberrations, we identified subgroups of iAMP21-ALL based on the patterns of copy number alteration and structural variation. This large data set enabled formal delineation of a 7.8 Mb common region of amplification harboring 71 genes, 43 of which were differentially expressed compared with non-iAMP21-ALL ones, including multiple genes implicated in the pathogenesis of acute leukemia (CHAF1B, DYRK1A, ERG, HMGN1, and RUNX1). Using multimodal single-cell genomic profiling, including single-cell whole genome sequencing of 2 cases, we documented clonal heterogeneity and genomic evolution, demonstrating that the acquisition of the iAMP21 chromosome is an early event that may undergo progressive amplification during disease ontogeny. We show that UV-mutational signatures and high mutation load are characteristic secondary genetic features. Although the genomic alterations of chromosome 21 are variable, these integrated genomic analyses and demonstration of an extended common minimal region of amplification broaden the definition of iAMP21-ALL for more precise diagnosis using cytogenetic or genomic methods to inform clinical management.

Clinical impact of minimal residual disease in blood and bone marrow of children with acute myeloid leukemia.

The prognostic significance of bone marrow minimal residual disease (MRD) in pediatric patients with acute myeloid leukemia (AML) is well characterized, but the impact of blood MRD is not known. We, therefore, used flow cytometric assessment of leukemia-specific immunophenotypes to measure levels of MRD in both the blood and bone marrow of patients treated in the AML08 (NCT00703820) clinical trial. Blood samples were obtained on days 8 and 22 of therapy, whereas bone marrow samples were obtained on day 22. Among patients who tested as having MRD-negative bone marrow on day 22, neither day-8 nor day-22 blood MRD was significantly associated with the outcome. However, day-8 blood MRD was highly predictive of the outcome among patients who tested as having MRD-positive bone marrow on day 22. Although the measurement of blood MRD on day 8 cannot be used to identify patients who have day-22 MRD-negative bone marrow who are likely to relapse, our findings suggest that day-8 blood MRD results can identify patients with MRD-positive bone marrow who have a dismal prognosis and may be candidates for the early use of experimental therapy.

Clinical characteristics and outcomes of children with newly diagnosed acute myeloid leukemia and hyperleukocytosis managed with different cytoreductive methods.

BACKGROUND: Hyperleukocytosis in patients with acute myeloid leukemia (AML) has been associated with worse outcomes. For cytoreduction, leukapheresis has been used but its clinical utility is unknown, and low-dose cytarabine (LD-cytarabine) is used as an alternative method. METHODS: Children with newly diagnosed AML treated between 1997 and 2017 in institutional protocols were studied. Hyperleukocytosis was defined as a leukocyte count of ≥100 × 109 /L at diagnosis. Clinical characteristics, early complications, survival data, and effects of cytoreductive methods were reviewed. Among 324 children with newly diagnosed AML, 49 (15.1%) presented with hyperleukocytosis. Initial management of hyperleukocytosis included leukapheresis or exchange transfusion (n = 16, considered as one group), LD-cytarabine (n = 18), hydroxyurea (n = 1), and no leukoreduction (n = 14). RESULTS: Compared with patients who received leukapheresis, the percentage decrease in leukocyte counts following intervention was greater among those who received LD-cytarabine (48% vs. 75%; p = .02), with longer median time from diagnosis to initiation of protocol therapy (28.1 vs. 95.2 hours; p < .001). The incidence of infection was higher in patients (38%) who had leukapheresis than those who receive LD-cytarabine (0%) or leukoreduction with protocol therapy (14%) (p = .008). No differences were noted in the outcomes among the intervention groups. Although patients with hyperleukocytosis had higher incidences of pulmonary and metabolic complications than did those without, no early deaths occurred, and the complete remission, event-free survival, overall survival rates, and outcomes of both groups were similar. CONCLUSION: LD-cytarabine treatment appears to be a safe and effective means of cytoreduction for children with AML and hyperleukocytosis.

Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics.

Pediatric cancer multi-omics is a uniquely rewarding and challenging domain of biomedical research. Public generosity bestows an abundance of resources for the study of extremely rare diseases; this unique dynamic creates a research environment in which problems with high-dimension and low sample size are commonplace. Here, we present a few statistical methods that we have developed for our research setting and believe will prove valuable in other biomedical research settings as well. The genomic random interval (GRIN) method evaluates the loci and frequency of genomic abnormalities in the DNA of tumors to identify genes that may drive the development of malignancies. The association of lesions with expression (ALEX) method evaluates the impact of genomic abnormalities on the RNA transcription of nearby genes to inform the formulation of biological hypotheses on molecular mechanisms. The projection onto the most interesting statistical evidence (PROMISE) method identifies omic features that consistently associate with better prognosis or consistently associate with worse prognosis across multiple measures of clinical outcome. We have shown that these methods are statistically robust and powerful in the statistical bioinformatic literature and successfully used these methods to make fundamental biological discoveries that have formed the scientific rationale for ongoing clinical trials. We describe these methods and illustrate their application on a publicly available T-cell acute lymphoblastic leukemia (T-ALL) data set. A companion github site ( https://github.com/stjude/TALL-example ) provides the R code and data necessary to recapitulate the example data analyses of this chapter.

SAMHD1 single nucleotide polymorphisms impact outcome in children with newly diagnosed acute myeloid leukemia.

Cytarabine arabinoside (Ara-C) has been the cornerstone of acute myeloid leukemia (AML) chemotherapy for decades. After cellular uptake, it is phosphorylated into its active triphosphate form (Ara-CTP), which primarily exerts its cytotoxic effects by inhibiting DNA synthesis in proliferating cells. Interpatient variation in the enzymes involved in the Ara-C metabolic pathway has been shown to affect intracellular abundance of Ara-CTP and, thus, its therapeutic benefit. Recently, SAMHD1 (SAM and HD domain-containing deoxynucleoside triphosphate triphosphohydrolase 1) has emerged to play a role in Ara-CTP inactivation, development of drug resistance, and, consequently, clinical response in AML. Despite this, the impact of genetic variations in SAMHD1 on outcome in AML has not been investigated in depth. In this study, we evaluated 25 single nucleotide polymorphisms (SNPs) within the SAMHD1 gene for association with clinical outcome in 400 pediatric patients with newly diagnosed AML from 2 clinical trials, AML02 and AML08. Three SNPs, rs1291128, rs1291141, and rs7265241 located in the 3' region of SAMHD1 were significantly associated with at least 1 clinical outcome: minimal residual disease after induction I, event-free survival (EFS), or overall survival (OS) in the 2 cohorts. In an independent cohort of patients from the COG-AAML1031 trial (n = 854), rs7265241 A>G remained significantly associated with EFS and OS. In multivariable analysis, all the SNPs remained independent predictors of clinical outcome. These results highlight the relevance of the SAMHD1 pharmacogenomics in context of response to Ara-C in AML and warrants the need for further validation in expanded patient cohorts.

An inflammatory state remodels the immune microenvironment and improves risk stratification in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a hematopoietic malignancy with poor prognosis and limited treatment options. Here we provide a comprehensive census of the bone marrow immune microenvironment in adult and pediatric patients with AML. We characterize unique inflammation signatures in a subset of AML patients, associated with inferior outcomes. We identify atypical B cells, a dysfunctional B-cell subtype enriched in patients with high-inflammation AML, as well as an increase in CD8+GZMK+ and regulatory T cells, accompanied by a reduction in T-cell clonal expansion. We derive an inflammation-associated gene score (iScore) that associates with poor survival outcomes in patients with AML. Addition of the iScore refines current risk stratifications for patients with AML and may enable identification of patients in need of more aggressive treatment. This work provides a framework for classifying patients with AML based on their immune microenvironment and a rationale for consideration of the inflammatory state in clinical settings.

Genome-wide CRISPR/Cas9 screen identifies etoposide response modulators associated with clinical outcomes in pediatric AML.

Etoposide is used to treat a wide range of malignant cancers, including acute myeloid leukemia (AML) in children. Despite the use of intensive chemotherapeutic regimens containing etoposide, a significant proportion of pediatric patients with AML become resistant to treatment and relapse, leading to poor survival. This poses a pressing clinical challenge to identify mechanisms underlying drug resistance to enable effective pharmacologic targeting. We performed a genome-wide CRISPR/Cas9 synthetic-lethal screening to identify functional modulators of etoposide response in leukemic cell line and integrated results from CRISPR-screen with gene expression and clinical outcomes in pediatric patients with AML treated with etoposide-containing regimen. Our results confirmed the involvement of well-characterized genes, including TOP2A and ABCC1, as well as identified novel genes such as RAD54L2, PRKDC, and ZNF451 that have potential to be novel drug targets. This study demonstrates the ability for leveraging CRISPR/Cas9 screening in conjunction with clinically relevant endpoints to make meaningful discoveries for the identification of prognostic biomarkers and novel therapeutic targets to overcome treatment resistance.