Kanagal-Shamanna, Rashmi

Introduction Chronic myelomonocytic leukemia (CMML) can be classified into dysplastic (dCMML) and proliferative (pCMML) subtypes based on a white blood cell count (WBC) ≥ 13 x 10 9/L for pCMML. Though this cutoff may seem arbitrary, there is evidence that pCMML is a unique biological entity with a distinct molecular profile and worse outcomes (Carr RM, et al. Nat Commun. 2021). We hypothesized that contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - would not adequately risk-stratify pCMML patients. Moreover, while truncating ASXL1 mutations are considered a high-risk feature in CMML, their prognostic relevance in pCMML is unknown. Methods After IRB approval, we compiled a large (n = 888), molecularly-annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation. The cohort was divided into dCMML and pCMML subgroups, which were analyzed independently alongside the entire cohort. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. Calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results We identified 474 (54%) dCMML cases and 410 (46%) pCMML cases with median age 71 years and 67% males. Patients with pCMML were more likely to have higher AMC (5.1 vs 1.5 x 10 9/L, p < 0.0001), circulating immature myeloid cells (IMC; 65% vs 36%, p < 0.0001) and abnormal karyotypes (37% vs 30%, p = 0.0187). They were also overrepresented in higher-risk categories of the MMM and CMM compared to dCMML (p < 0.0001 for each model). The number of somatic mutations was higher in pCMML than dCMML (mean 3.0 vs 2.6, p = 0.0050). Mutations in ASXL1 (53% vs 39%), NRAS (21% vs 11%), CBL (18% vs 12%), SETBP1 (14% vs 7%), JAK2 (10% vs 3%), CEBPA (5% vs 2%), GATA2 (3% vs 0%), and FLT3 (3% vs 1%) were more frequent while mutations in TET2 (38% vs 48%), SF3B1 (2% vs 8%), ZRSR2 (2% vs 8%), and NPM1 (1% vs 3%) were less frequent in pCMML compared to dCMML, respectively (p < 0.05 for all). Though the MMM and CMM effectively stratified the dCMML group, they did not provide meaningful risk stratification in the pCMML group (MMM p < 0.05 overall but could not distinguish between low and intermediate-1/2 or intermediate-1 and high risks; CMM p > 0.05). Likewise, there was no difference in the median overall survival (OS) or leukemia free survival (LFS) when pCMML patients were stratified by truncating ASXL1 mutations( Figure 1A). We then sought to better risk stratify pCMML. Univariate analysis identified increasing age, male gender, abnormal karyotype, and elevated WBC, ANC, and AMC as adverse predictors for OS. In addition, the presence of IMC and peripheral blood (PB) blast % were adverse factors for LFS, while age was not significant for LFS. None of the aforementioned mutations were significant in the univariate model for OS, whereas GATA2 and NPM1 mutations were significant for LFS. In multivariate analysis for OS, only male gender and AMC ≥ 10 x 10 9/L retained significance. In multivariate analysis for LFS, male gender, AMC ≥ 10 x 10 9/L, and peripheral blasts ≥ 5% remained significant; GATA2 and NPM1 mutations were not significant. These variables risk-stratified pCMML patients based on the presence of 0, 1, or ≥ 2 risk factors ( Figure 1B). In comparison, OS was 40.7 months (95% CI 35.2 - 50.1 mo.) for dCMML patients, 20.1 months (95% CI 18.2 - 22.7 mo.) for pCMML patients, and 31.8 months (95% CI 28.4 - 33.5 mo.) for the entire cohort. At last follow up, 586 deaths (66%) and 168 AML transformations (19%) were recorded in the cohort. Deaths in dCMML vs pCMML were 294 (62%) vs 291 (71%; p = 0.0067), with AML transformations in 83 (18%) vs 84 (21%; p = 0.2055) patients, respectively. Conclusions Truncating ASXL1 mutations, along with ASXL1-mutation weighted CMML prognostic models failed to effectively risk stratify pCMML patients. In pCMML, male gender and AMC ≥ 10 x 10 9/L, effectively risk stratified for OS, while these factors along with PB blasts ≥ 5% effectively risk stratified for LFS.

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p < 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p < 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.

Abstract The comprehensive evaluation of somatic variants in cancer requires consensus interpretation of their potential clinical significance (diagnosis, prognosis, and treatment response) and oncogenicity. To aid precision medicine through public interpretations, a multifaceted collaborative effort is required to bring together a community, structured guidance, and a public platform. The over 200 multi-disciplinary experts in the Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group (CDWG) provide a community that develops data curation guidelines and standards and curates evidence to determine the clinical significance and oncogenicity of somatic alterations in cancer. The Somatic CDWG established the Pediatric Cancer, Hematological Cancer, and Solid Tumor Taskforces to facilitate membership growth and targeted curation projects. Within these Taskforces, Somatic Cancer Variant Curation Expert Panels (SC-VCEPs) are developed through a 4-step approval process adapted from ClinGen germline VCEP procedures. Five SC-VCEPs (NTRK-fusions, FGFR variants, FLT3 variants, Histone H3 variants, and BCR::ABL1-like B-ALL alterations) are working through the approval process and one (Established Significance) is in the planning stage. SC-VCEPs tailor AMP/ASCO/CAP [PMID:27993330] and ClinGen/CGC/VICC Oncogenicity [PMID:35101336] guidelines, or create new classification guidance to aid granular assessment of their genomic alterations of interest. The Clinical Interpretations of Variants in Cancer (CIViC) knowledgebase provides the public platform for the Taskforces and SC-VCEPs to display their high-quality somatic cancer variant interpretations. These groups curate evidence from published literature and create Assertions summarizing evidence collected. These Assertions are further disseminated through other resources like ClinVar and the Variant Interpretation for Cancer Consortium (VICC) MetaKB. CIViC supports the application of AMP/ASCO/CAP tiering and levels for clinical significance Assertions. CIViC recently created Oncogenic Assertions, which supports the application of ClinGen/CGC/VICC codes. Three SC-VCEPs (FGFR, FLT3, and Histone H3) are tailoring the ClinGen/CGC/VICC Oncogenicity guidelines to their specific genes and CIViC will enable their ClinGen-approved, modified codes to be applied directly to their Oncogenic Assertions. Also, two SC-VCEPs (NTRK and BCR::ABL1-like) are developing fusion specific oncogenicity classification guidelines, which will be applied to their fusion specific CIViC Oncogenic Assertions. ClinGen Somatic groups have generated 695 CIViC Evidence Items and 33 Assertions from over 400 published papers. These numbers will continue to grow along with the development of more SC-VCEPs. ClinGen Somatic and CIViC foster collaboration, innovation, and most importantly the advancement of precision medicine. Citation Format: Jason Saliba, Arpad Danos, Kilannin Krysiak, Adam Coffman, Susanna Kiwala, Joshua McMichael, Cameron J. Grisdale, Ian King, Shamini Selvarajah, Xinjie Xu, Rashmi Kanagal-Shamanna, Laveniya Satgunaseelan, David Meredith, Mark Evans, Charles G. Mullighan, Yassmine Akkari, Gordana Raca, Angshumoy Roy, Alex H. Wagner, Ramaswamy Govindan, Obi L. Griffith, Malachi Griffith, on behalf of the ClinGen Somatic Clinical Domain Working Group. ClinGen Somatic and CIViC collaborate to comprehensively evaluate somatic variants in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6569.

Abstract Detection of hallmark genomic aberrations in acute myeloid leukemia (AML) is essential for diagnostic subtyping, prognosis, and patient management. However, cytogenetic/cytogenomic techniques used to identify those aberrations, such as karyotyping, fluorescence in situ hybridization (FISH), or chromosomal microarray analysis (CMA), are limited by the need for skilled personnel as well as significant time, cost, and labor. Optical genome mapping (OGM) provides a single, cost-effective assay with a significantly higher resolution than karyotyping and with a comprehensive genome-wide analysis comparable with CMA and the added unique ability to detect balanced structural variants (SVs). Here, we report in a real-world setting the performance of OGM in a cohort of 100 AML cases that were previously characterized by karyotype alone or karyotype and FISH or CMA. OGM identified all clinically relevant SVs and copy number variants (CNVs) reported by these standard cytogenetic methods when representative clones were present in >5% allelic fraction. Importantly, OGM identified clinically relevant information in 13% of cases that had been missed by the routine methods. Three cases reported with normal karyotypes were shown to have cryptic translocations involving gene fusions. In 4% of cases, OGM findings would have altered recommended clinical management, and in an additional 8% of cases, OGM would have rendered the cases potentially eligible for clinical trials. The results from this multi-institutional study indicate that OGM effectively recovers clinically relevant SVs and CNVs found by standard-of-care methods and reveals additional SVs that are not reported. Furthermore, OGM minimizes the need for labor-intensive multiple cytogenetic tests while concomitantly maximizing diagnostic detection through a standardized workflow.

Abstract CIViC (Clinical Interpretation of Variants in Cancer; civicdb.org) is a crowd-sourced, public domain knowledgebase composed of literature-derived evidence characterizing the clinical utility of cancer variants. As clinical sequencing becomes more prevalent in cancer management, the need for cancer variant interpretation has grown beyond the capability of any single institution. CIViC contains peer-reviewed, published literature curated and expertly-moderated into structured data units (Evidence Items) that can be accessed globally and in real time, reducing barriers to clinical variant knowledge sharing. We have extended CIViC’s functionality to support emergent variant interpretation guidelines, increase interoperability with other variant resources, and promote widespread dissemination of structured curated data. To support the full breadth of variant interpretation from basic to translational, including integration of somatic and germline variant knowledge and inference of drug response, we have enabled curation of three new Evidence Types (Predisposing, Oncogenic and Functional). The growing CIViC knowledgebase has over 300 contributors and distributes clinically-relevant cancer variant data currently representing >3200 variants in >470 genes from >3100 publications.

Abstract Clinical significance of somatic gene variants needs to be comprehensively characterized for their diagnostic, prognostic and/or therapeutic actionability in patient management. However, challenges remain due to discrepancies in interpretation and reporting of these somatic variants among different testing labs. Therefore, standardized curation, clinical interpretation and reporting of somatic variants in hematologic cancers is critical. To address this issue, the Hematologic Cancer Taskforce (HCT), composed of 52 multi-disciplinary experts including oncologists, molecular pathologists, lab directors, genomic scientists and biocurators, was formed in January 2020 within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematologic malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, HCT members curate, edit, and verify Evidence Items for each variant extracted from peer-reviewed publications. Monthly discussions based on these Evidence Items lead to the preparation of variant Assertions, which summarize the state of the field consensus variant interpretation and include tiering based on the AMP/ASCO/CAP guidelines (PMID: 27993330). FMS-like tyrosine kinase 3 (FLT3) encodes a class III receptor tyrosine kinase expressed in hematopoietic cells. FLT3 mutations, including both internal tandem duplication (ITD) and mutations in the tyrosine kinase domain (TKD), are the most common mutations in acute myeloid leukemia (AML), occurring in approximately 30% of all AML cases. Implementing FLT3 tyrosine kinase inhibitors (TKIs) in different treatment regimens for FLT3 mutated AML patients has led to significantly improved overall survival. Type I FLT3 inhibitors, including midostaurin, gilteritinib, sunitinib, lestaurtinib, and crenolanib, bind to the ATP-binding site when the receptor is in active conformation. Type II FLT3 inhibitors, including sorafenib, ponatinib, and quizartinib, interact with a hydrophobic region directly adjacent to the ATP-binding domain that is only accessible when the receptor is inactive, which prevents receptor activation. Generally in AML cells, type I FLT3 inhibitors prevent activity for both ITD and TKD mutations, while Type II inhibitors target ITD but lack efficiency against TKD mutations. The development of TKD mutations in AML cells with ITD have proved to be a mechanism of acquired, or secondary resistance to Type II FLT3 inhibitors. The HCT is piloting curation assessments of FLT3 alterations, including ITD, TKD and non-TKD variants, in AML. So far, the HCT has curated 75 evidence items for FLT3 somatic variants. FLT3-ITD, as well as D835 and I836 were asserted as tier 1 level A variants based on the prediction of response to gilteritinib in relapsed/refractory AML (PMIDs: 27993330, 31665578, 28645776, 28516360, 27908881). Recent curation activities are focused on FLT3 D839G and N676K, as clinical trials using large AML patient cohorts are lacking in their ability to validate drug response/resistance associations of these two TKD variants due to their low frequency. Functional studies showed both variants result in increased proliferation and protection from apoptosis, supporting the oncogenic potential of these two variants (PMIDs: 26891877, 2468088). FLT3 D839G combined with ITD confers resistance to pexidartinib and ponatinib, both Type II FLT3 inhibitors (PMIDs: 25847190, 23430109). FLT3 N676K predicts response to the Type I FLT3 inhibitor, gilteritinib, when N676K is present alone or in combination with ITD. Interestingly, FLT3 N676K in the absence of ITD predicts response to sorafenib, a Type II FLT3 inhibitor (PMIDs: 32040554, 32984009). However, these results are mostly derived from in vitro studies. Two separate Tier II, Level D Assertions have been submitted for FLT3-ITD&D839G for its response to pexidartinib and ponatinib, and more evidence is being collected to form an Assertion for FLT3 N676K. The complexity of the prediction of response/resistance associated with FLT3 D839G and N676K supports the importance of evidence-based curation and collection for these variants in the context of the overall mutation profile, disease context and specific FLT3 TKIs to clearly define their clinical impact. Disclosures Pullarkat: Stemline Therapeutics: Honoraria.

Hematological malignancies comprise a genetically heterogeneous spectrum of diseases caused by abnormal proliferation or maturation of a variety of hematological cell lineages. Genomic abnormalities including chromosomal translocations, copy number variations and sequence level gene mutations underlie the pathogenesis of these disorders and frequently serve as important diagnostic, prognostic and/or therapeutic markers. However, the substantial discrepancy in interpretation and reporting of these genomic abnormalities among testing labs creates challenges for patient management. Therefore, standardizing the curation, clinical interpretation and reporting of somatic alterations within the context of their diagnostic, prognostic and therapeutic significance in hematological cancers is critical. In January 2020, the ClinGen Somatic Cancer Clinical Domain working group formed the Hematological Cancer Taskforce (HCT) with a goal to undertake systematic curation and evidence-based clinical interpretation of genes/somatic variants associated with hematological malignancies. The HCT has recruited 32 multi-disciplinary experts including oncologists, molecular pathologists, clinical lab directors, genomic scientists and biocurators with expertise in hematological malignancies. In collaboration with the Clinical Interpretation of Variants in Cancer (CIViC) (civicdb.org) knowledgebase, variants from peer-reviewed publications are curated with editor review for clinical utility as evidence items. Monthly discussions based on these evidence items lead to the creation of summary variant assertions using the AMP/ASCO/CAP guidelines (Li M, et al., Journal of Molecular Diagnostics, 2017). The HCT is currently focused on expert curation and clinical interpretation of somatic variants in FLT3 (internal tandem duplication, tyrosine kinase domain and non tyrosine kinase domain variants) in acute myeloid leukemia (AML). Expert curation of gene fusions in Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL) in collaboration with the ClinGen somatic pediatric cancer taskforce is currently underway. To date, the HCT has curated 45 evidence items from clinical and pre-clinical studies on the aforementioned genes/variants. In addition, three AMP Tier I, level A variant assertions of FLT3-ITD, D835 and I836, which predict response to Gilteritinib, an FDA-approved drug for relapsed or refractory AML, have been curated. In the future, the HCT plans to extend its focus on curation of BCR-ABL1 kinase domain mutations in chronic myeloid leukemia (CML). Based on the initial pilot curation phase, the HCT will develop gene-specific recommendations to standardize the reporting and interpretation of somatic variants to better assist clinical decisions and apply to become official ClinGen Somatic Expert Panels in each of these gene-disease domains. Disclosures Blombery: Novartis: Consultancy; Invivoscribe: Honoraria; Amgen: Consultancy; Janssen: Honoraria.

Venetoclax is an oral, highly selective, BCL2 inhibitor approved by the FDA for use in chronic lymphocytic leukemia/small lymphocytic lymphoma and acute myeloid leukemia. Despite favorable responses, multiple biological mechanisms lead to treatment resistance. One such mechanism includes somatic mutations in the BCL2 gene. Multiple lines of evidence suggest that hot-spot mutations in BCL2 such as Gly101Val induce treatment resistance by disrupting the binding of BCL2 to the BCL2 inhibitors such as venetoclax. Further, widespread use of high-throughput NGS technologies has identified multiple BCL2 mutations and additional concurrent molecular alterations at various variant allele frequencies in patients with progression while undergoing venetoclax therapy. In order to understand and determine the clinical significance of each of these mutations, careful expert curation and integration into somatic variant annotation AMP/ASCO/CAP guidelines is needed. Further, curation of those somatic variants that may not have sufficient functional evidence in literature may benefit from additional tools such as in silico analysis. To address these issues, we have undertaken an effort to integrate the contributions of a multidisciplinary expert panel (clinical laboratory diagnosticians, oncologists, biomedical informaticians and lab-based researchers) for curation of BCL2 variants in hematological malignancies under the umbrella of ClinGen, an NIH/NHGRI funded consortium to establish standards and centralized resources for assessing the clinical significance of gene variants. Within the ClinGen Somatic Cancer Clinical Domain Working Group (CDWG) ((https://www.clinicalgenome.org/working-groups/somatic/), the somatic hematological malignancy taskforce has identified 56 peer-reviewed publications on BCL2 inhibitors (Jan 2014 to June 2020). The functional evidence contained within these publications was curated using CIViC (Clinical Interpretation of Variants in Cancer, civicdb.org), an open access, crowdsourced aggregation of expert curated evidence. Only a fraction of the somatic variants identified in BCL2 has established functional evidence on variant induced disruption to Venetoclax inhibition. Curation of these remaining variants of unknown significance (VUS) only have in silico functional assays to provide evidence on their potential resistance to Venetoclax. The current curation guidelines do not consider in silico prediction as a strong line of evidence for the interpretation of somatic sequence variants, however this recommendation is meant to interpret generalized in silico predictors and not robust computational models of specific protein function. The latter are more comparable to an experimental functional assay, and provide curators with more trustworthy computational assessments of disruption to protein specific functions. In order to assess their potential to integrate and supplement experimental evidence, the interaction of Ventoclax with several drug resistant BCL2 variants was simulated using AutoDock Vina (J Comput Chem. 2010;31(2):455-61). Facilitated by the SNP2SIM workflow (BMC Bioinformatics. 2019;20(1):171), the relative impact on binding energy was compared to the wildtype system. The in silico binding assay accurately predicted resistance (Fig 1), and demonstrates the utility of applying these methods to the large number of VUS in BCL2. In conclusion, the evidence-based expert curation of BCL2 variants provides a standardized approach for reporting and interpretation across all labs. For those variants (Tier 3) with limited published evidence, computational models that can predict specific changes to functional protein interactions can provide additional tools to the expert curators. Development and incorporation of these tools into curation guidelines requires the refinement of the predictive models through focused validation studies. Disclosures No relevant conflicts of interest to declare.