Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York

Background and aims Recent advances in DNA sequencing technologies have revolutionized approaches to the prevention, risk assessment, early detection, diagnosis, and treatment of cancers. However, many ethnic groups, especially non-European populations, have been significantly under-represented in cancer research, including clinical trials, and have not received equal benefits in clinical practice. As a result, our current knowledge about tumor biology, cancer risk, and response to treatment has primarily been derived from patients of European descent. These inequities limit our understanding of the many types of cancer and may exacerbate health disparities in the United States. This multi-institutional study, named Polyethnic-1000, aims to address both the scientific and social issues by creating a dynamic research platform within the ethnically diverse greater New York City area. Methods and results Polyethnic-1000 is a collaborative effort organized by the New York Genome Center (NYGC), involving staff and patients at academic centers and partnering hospitals in the New York City region. The genomics and informatics capabilities of the NYGC will be used to determine how inherited and somatically acquired genetic variations affect the behavior of cancers occurring in ethnically diverse populations. In a first, retrospective stage we are establishing the necessary infrastructure and workflow from sample acquisition to whole-exome and RNA sequencing, data analysis and data sharing within the consortium. Then we will start a prospective study enabling the formation of cohorts of interest for particular cancer types and particular ethnicities, with uniform consent allowing germline and somatic sequencing with broad data sharing of the somatic variants identified. Conclusion By establishing a collaborative network, Polyethnic-1000 will deepen our understanding of the contributions that ethnicities make to the incidence and biology of cancers, potentially improving outcomes for patients who currently lack access to the most recent advances in medical science

Molecular and Clinical Epidemiology of SARS-CoV-2 Infection among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations, from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOCs) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOCs, including Alpha (n = 714), Delta (n = 1877), and Omicron (n = 1802). Omicron isolates were further sub-typed as BA.1 (n = 899), BA.2 (n = 853), or BA.4/BA.5 (n = 50); the remaining 614 isolates were classified as “Other”. Approximately 31.5% (1577/5007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p p p < 0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact

Integrative Analysis of the Mutational Landscape of Mouse and Human AML Identifies Functionally Relevant Leukemia Disease Alleles

Abstract t(8;21) is the most frequent chromosomal abnormality in acute myeloid leukemia (AML), occurring in 4-12% of adult and 12-30% of pediatric patients. This translocation fuses the N-terminus of AML1 to nearly the entire coding region of ETO, resulting in expression of the fusion protein AML1-ETO. Observations that mice expressing AML1-ETO develop AML only if treated with mutagenic agents have suggested that AML1-ETO requires cooperating disease alleles for leukemogenesis. Consistent with this, t(8;21)+ AML patients harbor multiple genetic abnormalities. Recent exome/genome sequencing studies have expanded the number of known mutations in t(8;21)+ AML patients; however, efforts to distinguish driver from passenger mutations have yielded few cooperative events and the requirements for AML1-ETO leukemogenesis remain largely unknown. To better define the genetic landscape in AML and distinguish driver from passenger mutations, we compared the mutational profiles of two specific AML1-ETO driven mouse models of leukemia to the mutational profiles of human AML patients. We found that the mouse models of AML1-ETO driven AML were phenotypically similar in terms of their extensive latency, myeloid progenitor immunophenotype, and the acquired secondary disease alleles. The first model relies upon the expression of AML1-ETO in transplanted p21 null cells, while the second model relies upon the expression of AML1-ETO9a, a splice variant of AML1-ETO, in transplanted wild type cells. p21 is neither disrupted, nor methylated in t(8;21)+ AML. Because loss of p21 prevents the repair of damaged DNA, leukemogenesis may occur in this model once a cooperating disease allele has been naturally acquired in an AML1-ETO positive hematopoietic progenitor. AML1-ETO9a itself deregulates the expression of several DNA repair genes, suggesting that AML1-ETO9a could similarly facilitate the acquisition of a cooperating disease allele. When we compared the mutational landscape of these murine leukemias to AML patients, we found that the murine leukemias enrich for disease alleles present in human AML (hypergeometric p ≤ 4.26x10-20) and that there is a significant tendency for disease alleles mutated in both species to possess mutations in the same protein domain (hypergeometric p ≤ 4.23x10-3). Furthermore, domains mutated in both species were affected by recurrent mutations (Spearman correlation of domain p-values r = 0.53, p ≤ 2.73x10-8). While the frequency with which various protein classes were affected by mutations was significantly different in MLL-AF9 and AML1-ETO/AML1-ETO9a positive murine AML compared to MLL-fusion and t(8;21)+ positive human AML (p = 0.049), the protein classes targeted in AML1-ETO/AML1-ETO9a murine AML vs. human t(8;21)+ AML were not significantly different (p = 0.327). To identify disease alleles capable of cooperating with AML1-ETO, we determined that of the 424 genes mutated in both species, 38 of those genes were significantly mutated in human AML (Genome MuSiC SMG FDR ≤ 30%). These 38 genes represented 45 mouse orthologues, 38 of which were significantly mutated in AML1-ETO driven murine leukemias (FDR ≤ 10%). These 38 orthologues corresponded to 32 human orthologues, 3 of which were annotated in COSMIC as cancer-related genes: TET2, PTPN11, and THRAP3. Using retroviral transduction and transplantation experiments, we demonstrated that the expression of AML1-ETO in transplanted Tet2 null cells or PTPN11 D61Y cells was sufficient for leukemogenesis. At euthanasia, mice exhibited leukocytosis, anemia, thrombocytopenia, splenomegaly, and an expansion in the myeloid progenitor compartment. Our identification of Tet2 loss as a cooperating allele implicates mutations in epigenetic regulators as potential driving events in t(8;21)+ AML, while the discovery of PTPN11 D61Y solidifies the role of constitutive MAPK signaling in t(8;21)+ AML. This integrative genetic profiling approach allowed us to accurately predict cooperating events in t(8;21)+ AML in a robust and unbiased manner, while also revealing functional convergence in mouse and human AML. Collectively, these findings illustrate the power of integrating murine and human genomic profiling to identify functionally relevant disease alleles in AML. Disclosures Levine: CTI BioPharma: Membership on an entity's Board of Directors or advisory committees; Loxo Oncology: Membership on an entity's Board of Directors or advisory committees; Foundation Medicine: Consultancy

Integrative genetic analysis of mouse and human AML identifies cooperating disease alleles

t(8;21) is one of the most frequent chromosomal abnormalities observed in acute myeloid leukemia (AML). However, expression of AML1-ETO is not sufficient to induce transformation in vivo. Consistent with this observation, patients with this translocation harbor additional genetic abnormalities, suggesting a requirement for cooperating mutations. To better define the genetic landscape in AML and distinguish driver from passenger mutations, we compared the mutational profiles of AML1-ETO–driven mouse models of leukemia with the mutational profiles of human AML patients. We identified TET2 and PTPN11 mutations in both mouse and human AML and then demonstrated the ability of Tet2 loss and PTPN11 D61Y to initiate leukemogenesis in concert with expression of AML1-ETO in vivo. This integrative genetic profiling approach allowed us to accurately predict cooperating events in t(8;21)(+) AML in a robust and unbiased manner, while also revealing functional convergence in mouse and human AML