Zepeda‐Mendoza, Cinthya

Abstract MGMT is primarily inactivated via promoter methylation, but MGMT homozygous deletion (hmzdel) has been rarely reported as an alternative inactivating mechanism. Although functionally similar to a methylated MGMT promoter, MGMT hmzdel is associated with an unmethylated MGMT promoter test result reflecting the MGMT promoter status of the non-neoplastic cells invariably present in any tumor specimen. Thus, patients whose tumors have MGMT hmzdel (and unmethylated MGMT promoter) would be inaccurately predicted to lack benefit from alkylating chemotherapy based on MGMT promoter methylation testing alone. To evaluate the impact of this clinical scenario, we estimated the frequency and distribution of MGMT hmzdel in routine clinical testing of CNS tumors. Among 12,424 CNS tumors (3,044 with provided diagnosis of glioblastoma) tested using Oncoscan chromosomal microarray (2015-2025), 10 tumors (0.08%) had MGMT hmzdel: 8 with entire gene hmzdel and 2 with partial gene hmzdel favored to be inactivating (RNA-sequencing underway to exclude possibility of activating rearrangements). All tumors were supratentorial and non-midline. Median age at diagnosis was 58.5 years (range, 34-81), with 3:2 male:female. Of the 10 cases, 9 (of 3,044; 0.3%) had integrated diagnosis of glioblastoma, IDH-wildtype; the remaining case was a recurrent astrocytoma, IDH-mutant, CNS WHO grade 4. All 10 cases had loss of chromosome 10q and a highly unmethylated MGMT promoter by droplet digital PCR testing of downstream CpG sites 75-80/84-87, with median fraction abundance of 0.19% (range, 0-0.85). In summary, MGMT hmzdel only occurred in high-grade adult-type diffuse astrocytic gliomas, and is a rare potential pitfall for MGMT promoter methylation testing leading to inaccurate patient stratification. It is critical that laboratories performing routine CNS tumor copy number testing include MGMT in the curated list of reportable genes, and that clinicians be aware of this rare clinical scenario to accurately stratify patients despite misleading MGMT promoter test results.

Abstract Motivation Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual’s genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. Results Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual’s genetic similarity to a continental group. Availability and implementation AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

e18590 Background: TP53 mutations ( TP53 MUT ) are known to be associated with adverse prognosis in acute myeloid leukemia (AML) and multihit TP53 MUT in myelodysplastic syndromes (MDS). The prognostic relevance of multihit TP53 MUT in myeloproliferative neoplasms (MPN) was recently highlighted. The current study illustrates survival comparisons in multihit TP53- mutated MPN vs. AML and analysis of associated risk factors. Methods: A Mayo Clinic enterprise-wide database search identified 61 MPN and 81 AML cases with multihit TP53 MUT . Conventional statistical methods were used for analyses. Results: 142 patients with multihit TP53 MUT were included: i) chronic phase MPN (MPN-CP; N=19), ii) accelerated phase MPN (MPN-AP; N=14), iii) blast phase MPN (MPN-BP; N=28) and iv) AML, not including MPN-BP (N=81). Concomitant ASXL1 MUT , EZH2 MUT , IDH1 MUT and IDH2 MUT were more common in MPN-BP, compared to AML. At a median follow up of 0.6 years, 124 (87%) deaths and 19 (13%) allogeneic stem cell transplantations (ASCT) were documented. Overall survival (OS), calculated from time of TP53 MUT detection was similar between MPN-BP (median 4.6 months) and MPN-AP (5.6 months; p=0.5). OS in MPN-BP/AP (median 4.8 months) was inferior to that of AML (median 7.4 months; p=0.04) while that of MPN-CP (median 11.6 months) was similar to AML (0.07) but superior to that of MPN-BP/AP (p<0.01). Age-adjusted multivariable analysis (MVA) confirmed the independent prognostic significance of undergoing ASCT (HR 0.4, p=0.03), MPN-CP or achieving response to pre-transplant therapy (HR 0.2, p<0.01), and concurrent TET2 MUT or DNMT3A MUT (HR 2.7, p<0.01) on OS. Based on these risk factors, a 3-tiered risk model was constructed: low (no risk factors; N=18; median OS 23.8 months); intermediate (1 risk factor; N=44; median 11.1 months); and high (2 or more risk factors; N=80; median 4 months; p<0.01). Comparative analysis of risk factors among distinct diseases confirmed the prognostic significance of ASCT (HR 0.3, p=0.03), achieving response to pre-transplant therapy (0.4, p<0.01) and concurrent TET2 MUT or DNMT3A MUT (HR 5.0, p<0.01) in AML. In MPN AP/BP, OS was influenced by having received chemotherapy vs. supportive care (HR 0.1; p<0.01) and achieving response to pre-transplant therapy (0.2, p<0.01). No significant risk factors for OS were identified in MPN-CP. In MVA, ASCT did not appear to influence OS in MPN AP/BP (p=0.7) and MPN-CP (p=0.4) but the number of informative cases was too low to make definitive conclusions. Conclusions: The current study highlights the equally detrimental impact of multihit TP53 MUT in securing long-term survival in MPN and AML. Short-term survival was positively influenced by ASCT, at least in AML, and disease stage or remission status at time of mutation detection and ASCT, respectively.

e18600 Background: Recent studies have suggested that basophilia in myeloproliferative neoplasms (MPN), in general, and in primary myelofibrosis (PMF), in particular, might be associated with poor prognosis. In the current study, we examined for clinical and genotype correlates as well as the prognostic impact of absolute eosinophil (AEC) and basophil (ABC) counts in essential thrombocythemia (ET) and polycythemia vera (PV). Methods: Diagnostic criteria were according to the International Consensus Classification. Study patients were selected based on the availability of information on AEC and ABC. Institutional reference range for AEC was 0.03 to 0.48 x 10 9 /L and for ABC 0.01 to 0.08 x 10 9 /L. "Eosinophilia" was defined as an AEC of ≥0.5 x 10 9 /L. "Basophilia" was evaluated both at an ABC of ≥0.1 x 10 9 /L and ABC of ≥0.3 x 10 9 /L, the latter representing 3 x the upper limit of the normal reference range. Results: Essential thrombocythemia 660 patients were considered. Median (range) values for AEC and ABC were 0.2 x 10 9 /L (0-2.8) and 0.07 x 10 9 /L (0-1.7), respectively. On univariate analysis, AEC and ABC, as continuous variables, were predictive of inferior overall (OS; p<0.01 for both) but not leukemia-free (LFS), myelofibrosis-free (MFFS), venous thrombosis-free (VTFS), or arterial thrombosis-free (ATFS) survival. In univariable analysis, AEC ≥0.5 x 10⁹/L and ABC ≥0.1 x 10⁹/L negatively impacted OS (p<0.01 for both); significance was sustained during multivariate analysis that included IPSET risk variables: AEC ≥0.5 x 10⁹/L (p<0.01; HR 1.9) and ABC ≥0.1 x 10 9 /L (p<0.01; HR 1.7). Polycythemia vera 478 patients were considered. Median (range) values for AEC and ABC were 0.27 x 10 9 /L (0-6.5) and 0.12 x 10 9 /L (0-3.2), respectively. In univariable analysis, neither AEC nor ABC, as continuous variables were predictive of OS, LFS, MFFS, VTFS, or ATFS. AEC ≥0.5 x 10⁹/L also did not have any impact on disease progression or thromboses. However, ABC ≥0.1 x 10 9 /L was associated with a lower risk of post-diagnosis arterial thrombosis (p=0.03; HR 0.6), and ABC ≥0.3 x 10 9 /L was predictive of inferior LFS (p<0.01; HR 6.5) and MFFS (p<0.01; HR 2.5). ABC ≥0.3 x 10 9 /L sustained prognostic relevance in LFS (p<0.01; HR 7.6) during multivariable analysis that included leukocytosis, platelet count, basophil percentage, age, and palpable splenomegaly. Similar findings were noted with regards to MFFS for ABC ≥0.3 x 10 9 /L (p=0.01; HR 2.3) when compared against palpable splenomegaly and age. Conclusions: The current study suggests that AEC ≥0.5 x 10 9 /L and ABC ≥0.1 x 10 9 /L in ET are independently associated with shortened overall survival, while basophilia (ABC ≥0.3 x 10 9 /L) in PV is an independent predictor of leukemic and myelofibrotic disease progression.

We sought to develop a survival model in chronic myelomonocytic leukemia (CMML) that is primarily based on clinical variables and examine additional impact from mutations and karyotype. 457 molecularly-annotated patients were considered. Multivariable analysis identified circulating Blasts ≥2% (1 point), Leukocytes ≥13 x 109/L (1 point), and severe (2 points) or moderate (1 point) Anemia as preferred risk variables in developing a clinical risk Stratification Tool for overall survival (OS), acronymized to "BLAST": low-risk (0 points; median 63 months); intermediate-risk (1 point; median 28 months; HR 2.2, 95% CI 1.6-3.0), and high-risk (2-4 points; median 13 months; 5.4, 4.1-7.3); the corresponding 3/5 year OS rates were 68%/53%, 43%/18%, and 12%/1%. BLAST model performance (AUC 0.77/0.85 at 3/5-years) was shown to be comparable to that of the molecular CMML-specific prognostic scoring system (CMML-mol; AUC 0.73/0.75) and the international prognostic scoring system-molecular (IPSS-M; AUC 0.73/0.74). Multivariable analysis of mutations and karyotype identified PHF6MUT and TET2MUT as being "favorable" and DNMT3AMUT, U2AF1MUT, BCORMUT, SETBP1MUT, ASXL1MUT, NRASMUT, PTPN11MUT, RUNX1MUT, TP53MUT, and adverse karyotype, "unfavorable". Molecular information was subsequently encoded in a combined clinical-molecular risk model (BLAST-mol; AUC 0.80/0.86 at 3/5-years) that included the aforementioned BLAST clinical risk variables and a 3-tiered molecular risk score. BLAST and BLAST-mol were subsequently validated by two separate external cohorts. Independent risk factors for blast transformation included DNMT3AMUT, ASXL1MUT, PHF6WT, leukocytes ≥13 x 109/L, and ≥2% circulating or ≥10% bone marrow blasts. The current study proposes an easy to implement, globally applicable, and molecularly adaptive risk model for CMML.

ABSTRACTA total of 142 patients with myeloproliferative neoplasms (MPNs) or acute myeloid leukemia (AML) associated with multihit TP53 mutations (mTP53 MUT) were accessed from the Mayo Clinic database and included (i) chronic phase MPN (MPN‐CP; N = 19), (ii) accelerated phase MPN (MPN‐AP; N = 14), (iii) blast phase MPN (MPN‐BP; N = 28), and (iv) AML (N = 81). Concurrent ASXL1 MUT, EZH2 MUT, IDH1,MUT and IDH2 MUT were more common in MPN‐MUTBP‐mTP53 compared to AML‐mTP53 MUT. At median of 11.6 months follow‐up, 124 (87%) deaths and 19 (13%) allogeneic stem cell transplantations (ASCT) were documented. Overall survival (OS), calculated from the time of mTP53 MUT detection, was similar between MPN‐BP‐mTP53 MUT (median 4.6 months) and MPN‐AP‐mTP53 MUT (5.6 months; p = 0.5) but both were inferior to MPN‐CP‐mTP53 MUT (11.6 months, p < 0.01). OS in MPN‐CP‐mTP53 MUT was similar to that of AML‐mTP53 MUT (median 7.4 months, p = 0.07). In multivariable analysis, OS was favorably affected by ASCT (HR 0.4, p = 0.03) and disease stage (i.e., chronic phase disease) or achieving response to pre‐transplant chemotherapy (HR 0.2, p < 0.01) and unfavorably by the presence of concurrent TET2 MUT or DNMT3A MUT (HR 2.7, p < 0.01). Based on these risk factors, a 3‐tiered risk model was constructed: low (no risk factors; N = 18; median OS 23.8 months); intermediate (one risk factor; N = 44; 11.1 months); and high (two or more risk factors; N = 80; 4 months; p < 0.01). The current study highlights the equally detrimental impact of mTP53 MUT on long‐term survival in MPN and AML and identifies predictors of short‐term survival.