Relling, Mary V.

PURPOSE Acute lymphoblastic leukemia (ALL) can occur across all age groups, with a strikingly higher cure rate in children compared with adults. However, the pharmacological basis of age-related differences in ALL treatment response remains unclear. METHODS Studying 767 children and 309 adults with newly diagnosed B-cell ALL enrolled on frontline trials at St Jude Children's Research Hospital, MD Anderson Cancer Center, the Alliance for Clinical Trials in Oncology, and the ECOG-ACRIN Cancer Research Group, we determined the ex vivo sensitivity of leukemia cells to 21 drugs. Twenty-three ALL molecular subtypes were identified using RNA sequencing. We systematically characterized the associations between drug response and ALL genomics in children, adolescents and young adults, and elderly adults. We evaluated the effect of age-related gene expression signature on ALL treatment outcomes. RESULTS Seven ALL drugs (asparaginase, prednisolone, mercaptopurine, dasatinib, nelarabine, daunorubicin, and inotuzumab ozogamicin) showed differential activity between children and adults, of which six were explained by age-related differences in leukemia molecular subtypes. Adolescents and young adults showed similar patterns of drug resistance as older adults, relative to young children. Mercaptopurine exhibited subtype-independent greater sensitivity in children. Transcriptomic profiling uncovered subclusters within CRLF2 -, DUX4 -, and KMT2A -rearranged ALL that were linked to age and cytotoxic drug resistance. In particular, a subset of children had adult-like ALL on the basis of leukemia gene expression patterns across subtypes, despite their chronological age. Resistant to cytotoxic drugs, children with adult-like ALL exhibited poor prognosis in pediatric ALL trials, even after adjusting for age and minimal residual diseases. CONCLUSION Our results provide pharmacogenomic insights into age-related disparities in ALL cure rates and identify leukemia prognostic features for treatment individualization across age groups.

While the cure rate of pediatric acute lymphoblastic leukemia (ALL) now exceeds ~90% with contemporary combination chemotherapy, the prognosis for adults with ALL remains significantly inferior with long-term overall survival ranging from 50% to 70%. Recent studies have uncovered marked differences in ALL genomics between children and adults, with some high-risk subtypes becoming more prevalent with age. However, the underlying biology of age-related disparities in ALL is not fully understood, especially with regard to differences in leukemia sensitivity to chemotherapy. To address this knowledge gap, we performed ex vivo drug sensitivity profiling (i.e., pharmacotyping) of 21 anti-leukemia agents on primary B-ALL diagnostic samples from 767 pediatric (age, 0-18 years) and 309 adult (19-84 years) patients. Drug sensitivity was measured as LC 50: the concentration of drug required to kill 50% of the leukemia cells (PMID: 36604538). A total of 7,975 unique LC 50 values were experimentally determined. RNA-seq was used for subtype classification and gene expression analysis. Among 21 drugs, seven showed significant differences in overall LC 50 between children and adults ( P<0.05 after Bonferroni correction): children displayed higher sensitivity to asparaginase, prednisolone, mercaptopurine, daunorubicin, and inotuzumab, while adults showed higher sensitivity to dasatinib and nelarabine. In multivariate models adjusting for 23 ALL molecular subtypes, only mercaptopurine remained significantly associated with age ( P=1.5×10 -5), suggesting that age-related differences in drug sensitivity can be primarily attributed to the variation in ALL subtypes between children and adults. For mercaptopurine, within KMT2A, CRLF2, and DUX4 subtypes, pediatric samples consistently showed a lower LC 50 than adults carrying the same genomic abnormality ( P=0.032, 0.0045, and 0.02, respectively). To explore intra-subtype heterogeneity, we performed unsupervised clustering using gene expression data for each of these three subtypes. Remarkably, within each of these subtypes, we identified two clusters with distinct transcriptomic profiles that were also largely segregated by age group, i.e., an adult-dominated cluster (C-a) and a pediatric-dominated cluster (C-p). In the KMT2A subtype, cases in C-a exhibited an over-representation of the KMT2A:: AFF1 fusion, and resistance to mercaptopurine ( P=0.029), prednisolone ( P=0.0039), vincristine ( P=0.046) and cytarabine ( P=0.0037). Within CRLF2 ALL, cases in C-a were associated with the presence of BCR:: ABL1-like signature and IGH:: CRLF2 rearrangements, and were more resistant to mercaptopurine ( P=0.0073) and prednisolone ( P=0.00036) compared to those in C-p. For DUX4 ALL, C-a was characterized by an under-representation of ERG deletions and resistance to mercaptopurine ( P=0.0056) and prednisolone ( P=0.0031), compared to C-p within DUX4. To explore the clinical relevance of this heterogeneity, we analyzed the in vivo treatment response of KMT2A (N=35), CRLF2 (N=59) and DUX4 (N=118) B-ALL enrolled in six frontline ALL trials. Compared to cases in C-p (usually drug-sensitive), those in C-a (usually drug-resistant) consistently had significantly poorer initial treatment responses as measured by persistent end-of-induction minimal residual disease (≥0.01%) in KMT2A (58% vs 9%; P=0.0063), CRLF2 (74% vs 41%; P=0.030), and DUX4 (66% vs 40%; P=0.0058) ALL. In conclusion, these studies have revealed important new insights into the pharmacogenomic basis of age-related differences in B-ALL treatment response. These results indicate that both inter- and intra-subtype heterogeneity contribute to inferior prognosis in adults with ALL, but also point to therapeutic opportunities to improve their outcomes.

Abstract Objective The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled “Developing a Clinical Genomic Informatics Research Agenda”. The meeting’s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and Methods Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

Abstract Lineage-ambiguous leukemias are high-risk malignancies of poorly understood genetic basis. Here, we describe a distinct subgroup of acute leukemia with expression of myeloid, T lymphoid, and stem cell markers driven by aberrant allele-specific deregulation of BCL11B, a master transcription factor responsible for thymic T-lineage commitment and specification. Mechanistically, this deregulation was driven by chromosomal rearrangements that juxtapose BCL11B to superenhancers active in hematopoietic progenitors, or focal amplifications that generate a superenhancer from a noncoding element distal to BCL11B. Chromatin conformation analyses demonstrated long-range interactions of rearranged enhancers with the expressed BCL11B allele and association of BCL11B with activated hematopoietic progenitor cell cis-regulatory elements, suggesting BCL11B is aberrantly co-opted into a gene regulatory network that drives transformation by maintaining a progenitor state. These data support a role for ectopic BCL11B expression in primitive hematopoietic cells mediated by enhancer hijacking as an oncogenic driver of human lineage-ambiguous leukemia. Significance: Lineage-ambiguous leukemias pose significant diagnostic and therapeutic challenges due to a poorly understood molecular and cellular basis. We identify oncogenic deregulation of BCL11B driven by diverse structural alterations, including de novo superenhancer generation, as the driving feature of a subset of lineage-ambiguous leukemias that transcend current diagnostic boundaries. This article is highlighted in the In This Issue feature, p. 2659

Abstract Introduction B progenitor acute lymphoblastic leukemia (B-ALL) is a leading cause of childhood cancer death. Many chimeric genes have been identified and led to a refined classification of B-ALL and tailored therapies. Still, up to 30% of B-ALL cannot be classified into established subtypes, and the outcome for many is poor. Methods To identify novel subtypes of B-ALL, we performed integrative genomic analysis including transcriptome sequencing (RNA-seq) of 1,988 cases from St. Jude, Children's Oncology Group and adult cooperative group studies and analyzed chromosomal rearrangements, gene-expression profiles (GEP), somatic mutations and chromosome-level copy-number alterations. Cases lacking known or putative subtype-defining alterations underwent whole genome sequencing. Effects on proliferation and transformation of novel lesions were assessed by retroviral expression in cell lines and point-mutation knock-in mice using CRISPR/Cas9 genome editing. Results Using integrated genetic alterations and gene expression profiling, we classified 23 B-ALL subtypes (Table and Figure). Three groups included cases with similar GEP as canonical subtypes (ETV6-RUNX1, KMT2A-rearranged, and ZNF384-rearranged), but lacking the expected drivers (e.g., ETV6-RUNX1-like, n=42). Eighteen cases (0.9%) had rearrangements of BCL2, MYC and/or BCL6 showing a distinct GEP; they were mostly adults (n=16) with very poor outcome. These alterations, rarely seen in ALL, are identical to those observed in "double/triple hit" lymphoma, and are of pre-B immunophenotype. Eight cases with tightly clustered GEP comprised a novel subtype defined by IKZF1 N159Y missense mutation. N159Y is in the DNA-binding domain of IKZF1, and is known to perturb IKZF1 function, with distinct nuclear mislocalization and induction of aberrant intercellular adhesion. We identified two subtypes with distinct GEP characterized by PAX5 alterations. One, herein termed PAX5 altered (PAX5alt), comprised 148 (7.4%) cases, was characterized by diverse PAX5 alterations including rearrangements (n=57), sequence mutations (n=46) and/or focal intragenic amplifications (n=8). These PAX5 alterations were found in 73.6% of PAX5alt cases and different alteration types were mutually exclusive. Other PAX5 alterations, including deletions and large-scale amplifications were also assessed using SNP array, but were not enriched in the PAX5alt group. Clinically, PAX5alt pediatric and adult patients had favorable (96.8±3.2%) and intermediate (42.1±10.2%) 5-year overall survival (OS), respectively. The other GEP distinct subtype comprised 44 cases, all with PAX5 P80R missense mutations. In 30 of these cases, PAX5 P80R was homozygous due to deletion of the wild-type (WT) PAX5 allele or copy-neutral loss of heterozygosity. Of the other 14 cases with heterozygous PAX5 P80R mutations, 13 had a second frameshift (n=7), nonsense (n=2) or deleterious missense (n=4) PAX5 mutation. Four of the remaining 1,944 cases also had the PAX5 P80R mutation, but all were heterozygous with preservation of a WT PAX5 allele, consistent with the notion that homozygous or compound heterozygous PAX5 P80R mutation is the hallmark of this subtype. Adult PAX5 P80R cases (n=14) showed better 5-year OS (61.9±13.4%) than those in PAX5alt subtype (42.1±10.2%). To examine the effects of PAX5 P80R on B-cell maturation, WT PAX5, PAX5 P80R, V26G and P34Q were expressed in Pax5-/- lineage-depleted bone marrow cells. Expression of WT PAX5, PAX5 V26G and P34Q resulted in near complete rescue of B cell differentiation; however, expression of PAX5 P80R blocked the differentiation at the pre-pro-B stage of B-cell maturation. Further, Pax5 P80R heterozygous or homozygous mice developed pre-B-ALL with a median latency of 166 and 87 days, respectively, with heterozygous mice acquiring alterations on the second allele. In contrast, Pax5+/- mice, and those harboring G183S mutation observed in familial leukemia, do not spontaneously develop B-ALL. Conclusions These results show the utility of transcriptome sequencing in defining subtypes and founding genetic alterations in B-ALL, provide a revised taxonomy of the disease across the age spectrum, and reinforce the central role of PAX5 as a checkpoint in B lymphoid maturation and leukemogenesis. Disclosures McKay: ImmunoGen Inc.: Employment. Tallman:Orsenix: Other: Advisory board; AROG: Research Funding; BioSight: Other: Advisory board; Cellerant: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board; ADC Therapeutics: Research Funding. Stock:Jazz Pharmaceuticals: Consultancy. Konopleva:Stemline Therapeutics: Research Funding. Relling:Shire Pharmaceuticals: Research Funding. Mullighan:Cancer Prevention and Research Institute of Texas: Consultancy; Amgen: Honoraria, Speakers Bureau; Abbvie: Research Funding; Loxo Oncology: Research Funding; Pfizer: Honoraria, Research Funding, Speakers Bureau.

Abstract Acute lymphoblastic leukemia (ALL) in adolescents and young adults (AYA) is characterized by distinct presenting features and inferior prognosis compared to pediatric ALL. Age, as a continuous variable, is negatively correlated with prognosis, in spite of risk-adapted combination chemotherapy. To better understand the etiology of ALL in this age group, we performed the first genome-wide association study (GWAS) to comprehensively examine germline single nucleotide polymorphisms (SNPs) for their association with susceptibility to B-ALL in AYAs. In the discovery GWAS, we compared genotype frequency at 635,297 SNPs between 308 AYA ALL cases (age 16-39 years, treated on the Children’s Oncology Group [COG], the Alliance-Cancer and Leukemia Group B, Eastern Cooperative Oncology Group, MD Anderson Cancer Center, and St. Jude Children’s Research Hospital trials) vs. 6,661 non-ALL controls. The association between genotypes at each SNP and ALL susceptibility was tested by using a logistic regression model after adjusting for genetic ancestries to control for population stratification. SNPs that reached P≤ 5×10-8 in the discovery GWAS were tested in an independent cohort of 82 AYA ALL cases from the COG protocols and 5,755 non-ALL controls. We identified a single genome-wide significant susceptibility locus on 10p14 signified by two SNPs within the GATA3 gene: rs3824662, P=2.8x10-10, odds ratio (OR)=1.77; rs3781093, P=3.2x10-9, OR=1.73, both of which were validated in the replication cohort (P=1.9x10-8 and P=4.3x10-5, respectively). We also examined the association signals in AYAs for susceptibility loci previously identified in pediatric ALL: ARID5B, IKZF1 and PIP4K2A variants were nominally significant in AYAs in the discovery GWAS and/or in the replication analysis, whereas CEBPE or CDKN2A/CDKN2B were not significant. These results imply both similarities and differences in genetic predisposition to ALL between children and AYAs. At the GATA3 locus, rs3824662 risk variant was over-represented in Philadelphia chromosome (Ph)-like ALL in AYAs (P=0.02), confirming our previous report of Ph-like ALL susceptibility variants in GATA3 (Nat Genet 45:1494). Importantly, even after excluding Ph-like cases, rs3824662 remained associated with the risk of developing ALL in AYAs, suggesting that the influence of the GATA3risk variant on ALL susceptibility in AYAs extends beyond the predisposition to Ph-like subtype. We next examined the relationship between GATA3 risk allele frequency and age at diagnosis in a cohort of unselected childhood and adolescent ALL cases enrolled in the COG P9900 protocols (N=1,827). Dividing patients into four consecutives age groups (<5, 5-10, 10-15 and >15 years), we observed a clear progressive increase in the risk allele frequency at rs3824662 (P=6.29×10-11) with increasing allelic odds ratio (i.e. relative risk of ALL conferred by each copy of the risk allele). This correlation between genotype and age was evident regardless of genetic ancestry, although the risk variant was more common among individuals with higher Native American ancestry. In contrast, the frequency of ALL susceptibility variant in ARID5B decreased progressively with increasing age at diagnosis (P=0.006), whereas PIP4K2A, CDKN2A/CDKN2B, IKZF1 and CEBPE variants were not related to age. Finally, we compared rs3824662 risk variant frequency by age in the COG P9900 protocols after stratifying the ALL cases into TCF3-PBX1, ETV6-RUNX1, hyperdiploid, MLL-rearranged and B-other. There was a trend that the risk allele was more frequent in cases older than 16 years compared to those below 16 in the five subtypes examined. In conclusion, we have identified inherited GATA3 genetic variants that strongly influence ALL susceptibility in adolescent and young adults, indicating potential age-related differences in ALL biology. Disclosures No relevant conflicts of interest to declare.

Thiopurine methyltransferase (TPMT) activity exhibits a monogenic codominant inheritance and catabolizes thiopurines. TPMT variant alleles are associated with low enzyme activity and pronounced pharmacologic effects of thiopurines. Loss‐of‐function alleles in the NUDT15 gene are common in Asians and Hispanics and reduce the degradation of active thiopurine nucleotide metabolites, also predisposing to myelosuppression. We provide recommendations for adjusting starting doses of azathioprine, mercaptopurine, and thioguanine based on TPMT and NUDT15 genotypes (updates on www.cpicpgx.org ).

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real‐world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene–drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.