Mutations In MLL2 Research Articles

Beat-AML 2024 ELN–refined risk stratification for older adults with newly diagnosed AML given lower-intensity therapy

AbstractAlthough the 2022 European LeukemiaNet (ELN) acute myeloid leukemia (AML) risk classification reliably predicts outcomes in younger patients treated with intensive chemotherapy, it is unclear whether it applies to adults ≥60 years treated with lower-intensity treatment (LIT). We aimed to test the prognostic impact of ELN risk in patients with newly diagnosed (ND) AML aged ≥60 years given LIT and to further refine risk stratification for these patients. A total of 595 patients were included: 11% had favorable-, 11% intermediate-, and 78% had adverse-risk AML. ELN risk was prognostic for overall survival (OS) (P < .001) but did not stratify favorable- from intermediate-risk (P = .71). Within adverse-risk AML, the impact of additional molecular abnormalities was further evaluated. Multivariable analysis was performed on a training set (n = 316) and identified IDH2 mutation as an independent favorable prognostic factor, and KRAS, MLL2, and TP53 mutations as unfavorable (P < .05). A “mutation score” was calculated for each combination of these mutations, assigning adverse-risk patients to 2 risk groups: −1 to 0 points (“Beat-AML intermediate”) vs 1+ points (“Beat-AML adverse”). In the final refined risk classification, ELN favorable- and intermediate-risk were combined into a newly defined “Beat-AML favorable-risk” group, in addition to mutation scoring within the ELN adverse-risk group. This approach redefines risk for older patients with ND AML and proposes refined Beat-AML risk groups with improved discrimination for OS (2-year OS, 48% vs 33% vs 11%, respectively; P < .001), providing patients and providers additional information for treatment decision-making.

Label-Free Identification of Biochemical Footprints of Key Mutations in Acute Myeloid Leukemia Using Raman Spectroscopy

Introduction: With increasing understanding of the complexity and heterogeneity of acute myeloid leukemia (AML), the diagnostic process becomes more complicated and time-consuming. Therefore, there is a need to supplement AML diagnostics with a quick method to identify key, druggable genetic lesions that serve as a target for small molecule drugs. To address this need, we used Raman spectroscopy (RS)-based imaging methods. RS uses non-elastic scattering of laser light on cell biomolecules. When coupled to computational image segmentation and analysis, composition of the analyzed fragment of the cytoplasm can be characterized. In this way, by mapping the focal surface of the cell, we obtain a multidimensional image containing information about the distribution of its biochemical components. In our study, we utilized RS microscopy to investigate how single mutations affect the Raman spectral images of leukemic cells. The primary objective was to determine whether this technique could be utilized to identify mutations in key genes related to leukemia development. Methods: Genetic models of AML were generated by introducing wild-type and mutated forms of three frequently mutated and/or druggable genes (FLT3, IDH1/2, and MLL) into myeloid cell lines (THP1, HEL, HL60). The presence of the desired phenotype was confirmed using flow cytometry, immunoblotting, high-throughput kinase activity assay (Pamgene), and confocal microscopy. For RS experiments, the cells were fixed, and subjected to Raman imaging measurements using the WITec Alpha 300 microscope. Reference or control samples consisted of cells with wild-type genes (WT). The recorded hyperspectral data was subjected to multidimensional chemometric analysis, including k-means cluster analysis (KMCA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). To validate the findings from the cell models, primary AML cells from 30 patients diagnosed with FLT-3 ITD, MLL or IDH1/2 mutations were examined with RS. Peripheral blood mononuclear cells (PBMC) isolated from healthy donors blood served as reference. Results: The spectral differences between cells with wild-type FLT3 and FLT3/ITD were subtle, yet significant. The results revealed distinct variances in lipid (1440, 1240, 1660, and 2850 cm -1) and hemoprotein content (740-760 cm -1). Additionally, we successfully distinguished cells harboring IDH1/2 and MLL mutations from those with the wild-type genes. In these cases Raman bands corresponding to protein and nucleic acids composition were changed in comparison to control cells. Raman features in PCA loadings were also related to proteins and nucleic acids. Using the PLS-DA method and simple AI model, we built successful algorithm for distinguishing transgenic models carrying mutation from wild-type cells. PCA analysis also enabled us to distinguish AML primary cells from PBMC. Analysis weather primary cells carrying the selected mutations can be distinguished from non-mutated AML cells is concordant with our findings on models, however, it requires further analysis in larger group of patients to increase statistical power of these observations. Conclusions: Collectively, these findings suggest that Raman spectroscopy coupled with appropriate chemometric analysis may serve as rapid, label-free tool for identification of key druggable mutations in AML. Acknowledgements: The studies were performed as a part of the “ Label-free and rapid optical imaging, detection and sorting of leukemia cells” project carried out within the Team-Net programme of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund.

Intestinal-Type Adenocarcinoma in Head and Neck: Dissecting Oncogenic Gene Alterations Through Whole Transcriptome and Exome Analysis

Adenocarcinomas of the nasal/paranasal sinuses are uncommon, but intestinal-type adenocarcinomas (ITACs) are important. Due to the rarity of these tumors, their molecular profile is not well known. To further investigate the molecular profile and find potential oncogenic drivers, we compared the whole transcriptome and exome of ITACs at different anatomic locations in the head and neck. Twenty-one head and neck adenocarcinomas were used in this study, divided into 10 sinonasal adenocarcinomas (SNT) and 11 extrasinonasal (T) head and neck adenocarcinomas according to anatomic location and histology. Tumor samples along with normal mucosa were microdissected from formalin-fixed, paraffin-embedded samples, and RNA and DNA were subjected to whole-transcriptome and -exome shotgun sequencing. Analysis of ITACs at sinonasal locations showed 410 subtype-specific differentially expressed (DE) genes and noncoding transcripts compared with the group of other anatomic locations, with 2909 subtype-specific DE genes. The groups shared 872 genes, with 17 highly different or opposing DE genes. Whole-exome mutation analysis revealed the gene MLL3 (KMT2C) to be exhibiting the most frequent loss-of-function mutations in all adenocarcinomas investigated. The results suggest that the head and neck ITACs investigated were mainly caused by loss-of-function mutations in MLL3 that disabled chromatin methylation and remodeling of all MLL3-targeted enhancers in the tumors. This changed the activity of multiple genes/gene clusters, supporting oncogenicity mostly via pathways of signaling, dedifferentiation, proliferation, migration, and immune and inflammatory deregulation, indicating a truly epigenetic event as the root cause for the heterogenous diversity of these enteric types of cancer. The data of this study form the basis for understanding cell fate determination and cellular homeostasis in the normal respiratory mucosa at different anatomic sites and show the contribution of different mucosal components to the etiology/molecular pathology of ITAC.

Therapeutic targeting of metabolic vulnerabilities in cancers with MLL3/4-COMPASS epigenetic regulator mutations.

Epigenetic status-altering mutations in chromatin-modifying enzymes are a feature of human diseases, including many cancers. However, the functional outcomes and cellular dependencies arising from these mutations remain unresolved. In this study, we investigated cellular dependencies, or vulnerabilities, that arise when enhancer function is compromised by loss of the frequently mutated COMPASS family members MLL3 and MLL4. CRISPR dropout screens in MLL3/4-depleted mouse embryonic stem cells (mESCs) revealed synthetic lethality upon suppression of purine and pyrimidine nucleotide synthesis pathways. Consistently, we observed a shift in metabolic activity toward increased purine synthesis in MLL3/4-KO mESCs. These cells also exhibited enhanced sensitivity to the purine synthesis inhibitor lometrexol, which induced a unique gene expression signature. RNA-Seq identified the top MLL3/4 target genes coinciding with suppression of purine metabolism, and tandem mass tag proteomic profiling further confirmed upregulation of purine synthesis in MLL3/4-KO cells. Mechanistically, we demonstrated that compensation by MLL1/COMPASS was underlying these effects. Finally, we demonstrated that tumors with MLL3 and/or MLL4 mutations were highly sensitive to lometrexol in vitro and in vivo, both in culture and in animal models of cancer. Our results depicted a targetable metabolic dependency arising from epigenetic factor deficiency, providing molecular insight to inform therapy for cancers with epigenetic alterations secondary to MLL3/4 COMPASS dysfunction.

Proteomics-Based Strategy for the Recommendation of Conventional Chemotherapy Vs Venetoclax Plus Hypomethylating Agents in Adult Acute Myeloid Leukemia (AML)

INTRODUCTION: Newer AML therapies with Hypomethylating Agents & Venetoclax (HV) provide an alternative to Conventional Chemotherapy (CC), with anthracycline and cytosine arabinoside, but criteria to select which to use are lacking. We investigated whether proteomic classification could provide guidance. METHODS: Using Reverse Phase Protein Array (RPPA) methodology, the level of 405 proteins (327 total; 78 post-translational modified) were measured in 818 samples from newly diagnosed adult AML patients and normalized to normal CD34+ cells. Patients treated with HV (N=85) or CC (N=335) were analyzed. Overall Survival (OS) and Complete Remission Duration (RD) analysis was performed with pairwise LogRank tests (p < 0.05), adjusted for False Discovery Rate (FDR), to identify individual proteins predictive of outcome. Patients were clustered based on protein expression. Categorical clinical variables were compared with Fisher's Exact test with simulated p-values (10000 replicates), and continuous ones with Kruskal-Wallis test. Univariate (UV) and Multivariate (MV) models were built with Cox proportional hazards model (CoxPH). Deep neural network analysis using random forest was performed to create a Protein Classifier for treatment recommendation. RESULTS: Individual protein analysis found 55 prognostic proteins (Protein Selector 1 - PS1), which clustered patients into 3 groups. A preferred therapy for cluster 2 was not identified with PS1, so a second Protein Selector 2 (PS2) was generated, identifying 45 predictive proteins in this subset. From the PS1/2 analysis, the 95 proteins formed 4 distinct expression profiles (C1=red, C2=gold, C3=magenta, C4=green) which were stratified by treatment (HV or CC), as shown in Fig. 1. Patients in C2 were enriched for secondary AML (57% vs C1=41%, C3=33%, C4=32%; p<0.001) and unfavorable cytogenetics (41% vs C1=32%, C3=39%, C4=35%; p<0.001), and were older (60yo vs C1=61yo, C3=54yo, C4=56yo; p<0.001). Mutations in CEBPA, GATA2, FLT3 and NPM1 were more common in C4 (22%, 13%, 35%, 35% vs C1=12%, 1.7%, 5.7%, 6%; C2=7.8%, 6.2%, 18%, 15%; C3=9.3%; 1.4%, 29%, 21%; p=0.037, p=0.013, p<0.001, p<0.001, respectively), highlighting the heterogeneity between groups. We evaluated OS and RD (Fig. 2) in each cluster (C1=red, C2=gold, C3=magenta, C4=green), considering each treatment (HV= solid line, CC=dashed line). Patients in C1 and C2 treated with HV had a diametrically different and superior response compared to those treated with CC (C1-HV: Median OS (MS)>65mo, Median RD (MRD)>60mo; C2-HV: MS=15mo, MRD=24mo vs C1-CC: MS=20mo, MRD=39mo; C2-CC: MS=10mo, MRD=17mo). C3 showed the opposite, with CC outperforming HV (MS=19mo, MRD>102mo vs MS=7mo, MRD=9mo). Similarly, in C4, CC patients did dramatically better, (MS=40mo, MRD>96mo vs MS=9mo, MRD=7mo). In the UV CoxPH model, we included variables for PS cluster and treatment and all groups predicted OS, except for C3-CC and C4-CC, as did age, secondary AML, complex karyotype, and CEBPA, FLT3, KIT, MLL, NPM1, PTPN11 and TP53 mutations. In the MV model, all clusters were predictive for OS, together with age, secondary AML, complex karyotype and NPM1 mutation. Regarding RD, in the UV model, only C2-HV, C2-CC, and C4-HV predicted RD, as did age, secondary AML, complex karyotype, unfavorable cytogenetics, and FLT3, RUNX1 and TP53 mutations. In the MV model of RD, all clusters, except for C3-HV were predictors, together with age. Importantly, optimized treatment triaging based on PS1/2 would have reassigned 52% (218/420) of cases, and is estimated to increase the 3yrs OS of the whole cohort from 35.6% to 48.8%, a 37.2% increase. Moreover, the 2yrs Relapse Free Survival would increase from 57,9% to 63,9%, a 10.39% increment. Furthermore, our Protein Classifier identified a set of 3 proteins (SPI1, NOTCH1.cle, and TGM2) whose expression can be used to rapidly classify patients and recommend either HV or CC. This classifier has a very high c-index (a measure of individual patient discriminatory power) of 0.93 (>0.7 is considered predictive, 1 would indicate perfection) demonstrating that it robustly predicts optimal therapy choice. CONCLUSION: Protein profiling identified protein expression patterns which had diametrically different responses according to treatment (HV or CC). Given the US annual incidence of 20000 newly diagnosed AML cases, proteomic triaging could result in ~2600 more cures using existing therapy. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Racial and Ethnic Disparities in Acute Myeloid Leukemia: 15-Year Experience at a Safety-Net Health System

Background Significant disparities in AML have been reported in the non-Hispanic black (NHB) population compared to Caucasians. Much less is known about the disparities seen in Hispanics (H), who face unique barriers to healthcare access and treatment. Recent reports suggest that Hispanics have decreased overall survival (OS) compared to non-Hispanic whites (NHW) despite higher prevalence of favorable cytogenetics, younger age at diagnosis and similar rates of chemotherapy. We conducted a single center study investigating the outcomes of AML patients treated at a non-transplant safety net hospital in Texas where the majority of the population is Hispanic. Our primary goal was to compare the impact of race/ethnicity on outcomes and further evaluate the underlying genomic differences between these groups. Methods We reviewed the medical records of 162 adult AML patients treated at Parkland Health (Dallas, TX) from January 2007 to June 2022. Demographics, baseline disease characteristics including cytogenetics and genomic profile, and AML directed therapies were collected. Patients were grouped based on race/ethnicity into H, NHW and NHB populations. Cytogenetic risk was classified as favorable, normal, complex or other, per the 2017 European Leukemia Net (ELN) risk classification. Genomic testing was performed using the FoundationOne Heme panel. Overall AML risk was classified per 2017 ELN stratification. Response was assessed using the IWG criteria. Categorical and continuous variables were compared using Chi square test and Kruskal-Wallis one-way analysis of variance. OS plots were calculated using Kaplan Meier method, and groups were compared using log rank testing. Multivariable Cox proportional hazard model was used for survival analysis. Results In our cohort of 162 patients, 82 (50.6%) were Hispanic (H), 36 (22.2%) were NHB and 44 (27.2%) were NHW. Hispanics were diagnosed at a significantly younger age compared to NHB (42.5 years (y) vs 49 y) and NHW (42.5 y vs 52.5 y, p=.02). Hispanics were found to have higher rates of complex cytogenetics (20.3% for H vs 11.8% for NHB vs 9.5% for NHW), similar rates of favorable cytogenetics (20.3% vs 20.6% vs 19.0%) and lower rates of normal cytogenetics (29.1% vs 44.1% vs 40.5%). Hispanic patients had a lower frequency of NPM1 mutations (p=.058) and higher frequency of CEBPA, NRAS, MLL, WT1, RUNX1 and TET2 mutations. Per ELN risk classification, Hispanics were less likely to have favorable risk AML (23.2% vs 36.1% vs 29.5%) and more likely to have intermediate (53.7% vs 44.4% vs 50.0%) or high-risk disease (23.2% vs 19.4% vs 20.5%) than NHB and NHW. Hispanics were less likely to receive intensive induction chemotherapy with 7+3 (85.4% vs 97.2% vs 90.9%), despite their overall younger age of presentation, but achieved similar remission rates post frontline therapy (78.0% vs 86.1% vs 75.0%). Hispanics had a numerically longer OS compared to NHB and NHW (mOS 43 months (m) vs 17 m, vs 14 m), although differences were not statistically significant (p=.20) likely due to the small size of the cohort. When Hispanics were compared against a combined cohort of NHB/NHW, they had longer OS in the high-risk group (p=.03). In a multivariate Cox regression analysis, OS was negatively associated with age at diagnosis (HR 1.022, p=.0063) and intermediate or high ELN risk (HR 3.431, p=.0002 and HR 4.689, p=3.84 x 10-05 respectively) and positively associated with Hispanics (HR .614, p=.0259). In our cohort, only 14 patients (8.6%), 3 of which had high risk disease, were able to proceed to transplant. Conclusion Our study of underserved patients with AML demonstrate a younger age at presentation for Hispanics but suggest that, contradictory to previously reported results, Hispanics have improved overall survival, particularly in the high-risk group, compared to NHB/NHW in the non-transplant setting. Our results may suggest that when healthcare access is not a barrier to treatment, Hispanic patients with AML can have similar, if not improved, outcomes to other populations. However, access to transplant remains a major barrier that needs to be further addressed to improve outcomes for this patient population. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Abstract 2557: Slit2 inhibits small cell lung cancer by targeting tumor microenvironment

Abstract Small cell lung cancer (SCLC) is the deadliest subtype of lung cancer with a 5-year survival rate of &amp;lt;5% in extensive-state disease and is designated by US Congress as a “recalcitrant cancer”. Recently approved by FDA, immune checkpoint blockade (ICB) immunotherapy showed marginally improved survival and only in a few patients, suggesting an inert immune tumor microenvironment (TME) and the existence of SCLC subtypes. Therefore, there is a significant need to develop more effective therapies for SCLC. In addition to the nearly universal biallelic inactivation of Rb and Tp53 genes in human SCLC tumors, comprehensive genome-wide screening studies have identified major co-occurring mutations in PTEN, CREBBP, EP300, SLIT2, MLL, COBL, and EPHA7 genes. Among them, SLIT2 showed the highest level of genomic abnormalities defined by a pronounced clustering of mutations and frequent genomic loss. However, the role of Slit2 in SCLC has not been defined yet. By using genetically engineered human SCLC cells overexpressing Slit2 or recombinant Slit2 (rSlit2) protein, we show that Slit2 inhibits SCLC cells proliferation, migration, and invasion properties and tumor sphere formation ability of drug-resistant SCLC cells in vitro. The mechanistic studies have identified inhibition of AKT and β-catenin mediated signaling pathways by Slit2 overexpression. Next, we implanted human SCLC cell lines into the immunocompromised NSG mice subcutaneously followed by treatment with rSlit2 or sterile saline. Analysis of tumor volume over the 4 weeks showed that rSlit2 treatment significantly reduced the growth of SCLC tumors. Further analysis of tumors showed that rSlit2 treated tumors harbor less M2-like CD206+ macrophages. Overall, these results suggest that Slit2 possesses tumor suppressive properties and could be developed as a novel therapeutic agent against SCLC. Citation Format: Dinesh K. Ahirwar, Manish Charan, Swati Misri, Konstantin Shilo, Ramesh Ganju. Slit2 inhibits small cell lung cancer by targeting tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2557.

Immunohistochemical Characterization of H3K4Me3 in Reactive Lymph Nodes and Follicular Lymphoma

Abstract Introduction/Objective Genes involved in histone methylation are frequently mutated in non-Hodgkin’s lymphomas. For instance, frequent mutations in genes encoding histone methytransferases MML2 and EZH2 are present in diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL). The aim of this study was to characterize the immunohistochemical expression of H3K4Me3 in benign/reactive lymph nodes (LNs) with comparison to follicular lymphoma (FL). Methods/Case Report Immunohistochemical staining with an anti-H3K4Me3 antibody was performed on FFPE whole slide section from patients with benign/reactive LNs (n=21), low grade (grade 1-2) FL (n=21). H3K4Me3 reactivity was scored for staining intensity and percentage of lymphocytes showing reactivity. Results (if a Case Study enter NA) The majority of the reactive LN sections (15 out of 21 cases) showed a distinct distribution of H3K4Me3 staining, with the majority of cells in the mantle zone and the interfollicular zones showing moderate-strong staining, whereas reactive germinal centers (GCs) showed significantly decreased or close to negative staining. Neoplastic follicles in all the FL cases contained positive cells with significantly stronger staining compared to that in the germinal centers in benign lymph nodes. The interfollicular zones, while diminished in FL due to expanded neoplastic follicles, showed retained H3K4Me3 staining. The difference in staining intensity between follicles and mantle/interfollicular zones became indistinct in FL. Conclusion H3K4Me3 expression in benign/reactive LNs is characterized by positive expression in lymphocytes in interfollicular and mantle zones and significantly decreased in GCs. However, the expression pattern is different in FL, which showed significantly increased expression in the follicles compared to that in reactive GCs. In FL, the expression in GCs is similar to that in the interfollicular and mantle zone lymphocytes. It is reported that about 90% of FL have MLL2 mutation and MLL2 is the enzyme responsible for the methylation of H3K4. So far, it is unclear whether the mutation of MLL2 in FL affects the overall methylation activity of the enzyme. In our study, there is increased methylation of H3K4 in the follicles of FL, which raises the possibility that MLL2 mutation somehow increases H3K4 methylation.

Characterization of the Immunogenomic Landscape of Follicular Lymphoma

Background: Follicular Lymphoma (FL) is an indolent, but incurable form of non-Hodgkin lymphoma (NHL), with variable clinical behavior. The immune environment plays a major role in dictating the biology of FL. For example, gene expression profiling experiments have demonstrated that recurring “immune response” gene signatures in diagnostic FL specimens were more accurate in predicting clinical outcomes than gene expression patterns in FL cells themselves. Furthermore, immune cells, including T cells, are often found infiltrating or surrounding malignant follicles in FL, and our group has identified the presence of highly clonal T cell populations in most FL samples, suggesting that FL cells express antigens that drive the expansion of lymphoma-specific T cells. In addition, inactivating mutations in B2 microglobulin are relatively common in FL, indicating that down-regulation of antigen expression may occur as a result of host immune surveillance. Lastly, FL is responsive to immunotherapies, such as PD-1 antibody blockade. Importantly, the FL antigens that promote spontaneous immune recognition remain unknown. Emerging data has revealed a critical relationship between the genetic landscape and the immunogenicity of cancer. Somatic mutations in malignant cells encode for altered proteins (i.e. neoantigens) that are “sensed” as foreign by T cells, and the mutational “load” of a given tumor has direct implications for the host immune response.Methods: To address the hypothesis that somatic mutations generate neo-antigens which are the targets of T cell recognition in patients with FL, whole exome sequencing (WES) was performed on FACS-purified FL B cells (CD10+CD19+ cells) and matched T cells from 7 FL biopsy samples. HLA A, B and C haplotypes were predicted using PolySolver, OptiType, Phlat and Seq2hla software with >90% concordance. HLA binding affinity was predicted for all possible 8-11-mer peptides generated from each somatic mutation and corresponding wild-type peptides using NetMHCpan v2.8. These tiled peptides were analyzed for their predicted binding affinities (IC50 nM) to HLA class I molecules. An IC50 <150 nM was considered a predicted strong binder, ≥150 but ≤500 nM an intermediate to weak binder, and >500 nM a non-binder.Results: A median number of 71 somatic mutations were identified in each sample (range, 8-135). Non-synonymous single nucleotide variants (SNV) were cataloged, and in silico analysis was utilized to predict potential high-affinity epitopes capable of binding patient-specific HLA molecules. We achieved an average of 90% proportion of nucleotides > Phred quality score 30 of total bases, according to the base calling accuracy (range, 89.02%-92.06%). G>A/C>T transitions were the most common nucleotide substitutions observed. Consistent with published reports, recurrent somatic mutations were identified in EZH2, CREBBP, IGLL5, MUC21, PCLO, and PIM1. We also identified recurrent mutations in BCL2 and MLL2 (frameshift insertions) known to dominate the mutational landscape of FL. Mutations in HLA class II alleles were common, occurring in 3/7 samples. In silico analysis was next employed to identify putative neo-antigens. A total of 139 candidate neo-antigenic peptides were predicted across all patients. On average, 19 neo-antigens were predicted for each patient (range, 3-41). No public neo-antigens were identified, suggesting that the neo-antigens arising in FL are patient-specific. This observation is consistent with what has been described for other cancer subtypes. Functional validation of lead candidate neo-antigen peptides is ongoing.Conclusion: While overall numbers of somatic mutations are modest in FL, putative neo-antigens were identified in all patient samples analyzed. Our findings suggest that immune therapies incorporating neo-antigen-specific approaches, such as personalized vaccines, should be explored in FL patients. DisclosuresNo relevant conflicts of interest to declare.

Personalized Prognostic Predictions for Patients with Myeloproliferative Neoplasms through Integration of Comprehensive Genomic and Clinical Information

▪The vast majority of Philadelphia-negative myeloproliferative neoplasms share a narrow set of phenotypic driver mutations affecting the erythropoietin/thrombopoietin signalling pathways. Despite this, there is significant heterogeneity in disease phenotype at diagnosis, as well as in patient outcome with respect to thrombosis, disease progression and survival. Current risk stratification models are useful for predicting outcome and guiding treatment in those patients with MF. However, there remains significant heterogeneity within risk subgroups, and no models are available for identifying poor risk patients with chronic phase disease.We sequenced the full coding regions of 68 genes and genome-wide single nucleotide polymorphisms in 2041 patients (1326 essential thrombocytosis (ET), 355 polycythemia vera (PV) and 311 primary/post-ET/post-PV myelofibrosis (MF), 49 with other MPN diagnoses) to characterize the associations between somatic mutations, copy number variant profiles, germline predisposition, order of mutation acquisition, clinical phenotype and patient outcome.Mutations in established myeloid driver genes other than JAK2, CALR or MPL were identified in 827 patients (41%). The presence and number of additional mutations correlated with both MPN phenotype and age at diagnosis. Non-canonical JAK2 and MPL mutations were found in 51 patients, of whom 17 had “triple-negative” disease. Novel protein truncating mutations in PPM1D and MLL3 were identified in 54 (2.6%) and 25 patients (1.2%) respectively. Chromosomal events, predominantly uniparental disomy of chromosome 9p (9p UPD), were seen in only 8% of those with ET, compared to 45% and 55% of those with MF and PV respectively. The JAK2 46/1 haplotype correlated with the presence of JAK2V617F, 9pUPD, increased JAK2 clone size and a PV phenotype. In addition, a range of other genetic and non-genetic factors were found to significantly correlate with phenotype at presentation.Mutation timing was assessed to characterize the patterns of tumor evolution. Many genes were specifically acquired either early or late in disease. The sequence of mutation acquisition was also linked to phenotype. In JAK2 -mutated patients, JAK2 was the earliest detected event (and/or was present in the dominant clone) in 80% of cases of PV and MF, but was preceded by other mutations in the majority of patients with ET. DNMT3A and SF3B1 mutations preceding JAK2 mutations were almost exclusively seen in ET, while EZH2 and ASXL1 mutations post- JAK2 were commonly a feature of MF.There were 422 different combinations of mutational/chromosomal events observed in this study, of which only 37 were recurrent in at least 5 cases. Bayesian network analysis and clustering using Bayesian Dirichlet processes were used to identify distinct patterns and genetic groups within MPNs. Two groups in particular were enriched in MF (as well as MDS) patients and were associated with adverse outcomes. Mutations in TP53 in association with chromosome 17p aberrations and/or 5q- were a distinct group associated with an increased risk of AML transformation in both chronic phase and MF patients.We then developed a unifying predictive model for all MPN patients. In order to take into account the striking degree of heterogeneity in genetic events, clinical characteristics and potential clinical outcomes, we developed a multi-state random effects Cox proportional hazards model. This allowed integration of a total of 63 clinical and genomic variables in order to generate individualised patient predictions for survival and disease transformation for all MPN patients. The model generated accurate predictions on the training cohort, and performed well on internal cross-validation and on application to an external validation cohort. In patients with MF, the model was more accurate for predictions of event-free survival than DIPSS or IPSS (concordance 81% v 69% v 77% respectively). We have devised an online calculator that can generate personalised outcome predictions for individual patients (and impute missing information where unavailable). This could be used to guide the management of chronic phase and MF patients and improve stratification within clinical trials.Together our results demonstrate the utility of combining genomic data with clinical parameters to refine disease classification and improve prognostication. DisclosuresHasselbalch:AOR Orphan: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding. McMullin:Shire, Novartis: Honoraria, Speakers Bureau; Italfarmaco S.p.A.: Consultancy. Vannucchi:Shire: Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Harrison:Celgene: Consultancy; Shire: Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; CTI: Speakers Bureau.

Whole-Exome Sequencing of Paroxysmal Nocturnal Hemoglobinuria

OBJECTIVE: In order to elucidate the possible mechanism on the proliferation of paroxysmal nocturnal hemoglobinuria (PNH) clone, and investigate the significance of gene mutation in PNH patients with thrombosis and provide a theoretical basis for related molecules markers and potential therapeutic targets in PNH, we performed the whole genome exon sequencing in PNH patients.METHODS: The peripheral blood and nail specimens of 7 PNH and 6 AA-PNH patients were obtained and we have used V2's NimbleGen capture probe to capturethe whole exon group (WES), and performed whole genome sequencing of exon in patients, meanwhile, processing and analysis of sequencing data were obtained and compared with the 1000 genome project database, to obtain high frequency variation genes and further gene enrichment pathway analysis in these patients. Using a combination of KEGG pathway analysis and GO pathway enrichment analysis methods to analyze the experimental data.RESULTS: We detected somatic PIGA mutations in the PNH fractions of 8 of 13 cases analyzed by WES. And we identified a total of 4 shear site, 4 non-synonymous, 4 truncation, and 6 frame-shift mutations in cases analyzed by WES. All mutations were grade one. We performed KEGG pathway enrichment analysis and GO gene annotation of 5717 mutated genes screened, the union as a target gene set, there were 25 target genes, SUZ12, CUX1, MLL2, MUC4, CTBP1, AXIN2, MLL, SDHA, CARD11, MLH1, RB1, SMO and NKX2-1 mutations were recurrent in PNH patients; FGFR3, ERCC5, MPL, FLT3, TSC2, POLE, TET2, MLL3, MSH6, FAT1, CIC and ZFHX3 mutations were recurrent in AA-PNH patients. Among them, SUZ12, FLT3, CUX1, MUC4, TET2, and RB1 gene are involved in the regulation of cell proliferation and differentiation, promote the growth, metastasis and invasion of tumor cells. In addition, the pathways enriched by mutant genes included pathways in cancer, central carbon metabolism in cancer signaling pathway and cell cycle signal pathways. GO analysis showed that the coding protein CDP has the functions of cell proliferation regulation, metabolism regulation, gene expression regulation, cell invasiveness, cell motility, cell apoptosis, extracellular matrix compositions, and so on. Furthermore, we analyzed the gene mutations in patients with thrombosis, which includes several genes with the higher deleterious mutation in protein structure, such as BMPR2, ZFPM2, F5, F8, F12, F13A1, MCL1, MMRN1, NBEAL2, NOS1and PC. The major functions of mutation sites were non synonymous single nucleotide variants and synonymous single nucleotide variants. The pathways enriched by mutant genes included the Notch signaling pathway, Ribosome biogenesis in eukaryotes signaling pathway, Wnt signaling pathway and Arachidonic acid metabolism signaling pathways, which may be related to the pathogenesis of PNH associated thrombosis.CONCLUSION: We identified additional somatic mutations that resulted in a complex hierarchical clonal architecture, similar to that observed in myeloid neoplasms and solid tumors. In addition to PIG-A mutations, mutations were found in genes known to be involved in myeloid neoplasm pathogenesis and solid tumors, including SUZ12, FLT3, CUX1, MUC4, TET2, and RB1. Our data indicate that in addition to PIG-A mutations, accessory genetic events are frequent in PNH, suggesting a stepwise clonal evolution derived from a singular stem cell clone. Meanwhile, several genes with higher deleterious mutation in PNH patients with thrombosis were found: F5, F8, F12, F13A1, THBD, ITGA2 and BMPR2, which enriched the Notch signaling pathway, Ribosome biogenesis in eukaryotes signaling pathway, Wnt signaling pathway and Arachidonic acid metabolism signaling pathways. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Molecular and Clinical Features of Hospital Admissions in Patients with Thoracic Malignancies on Immune Checkpoint Inhibitors.

Simple SummaryLung cancer immunotherapy has many complications and hospitalizations that often occur in non-small cell lung cancer (NSCLC) while on immunotherapy due to adverse events or other factors. The molecular and clinical profiles of these patients are often not well-defined, and the aim of our retrospective study is to better understand these clinical and molecular features. We evaluated a cohort of 90 stage IV thoracic malignancy patients who had hospital admissions after treatment with immune checkpoint inhibitors. We identified a relationship between immune-related adverse events (irAEs) and molecular markers that showed unique survival outcomes, as well as a significant overall survival improvement in patients who required discontinuation or interruption of immunotherapy due to irAEs. Lung cancer patients undergoing systemic treatment with immune checkpoint inhibitors (ICIs) can lead to severe immune-related adverse events (irAEs) that may warrant immediate hospitalization. Patients with thoracic malignancies hospitalized at City of Hope while undergoing treatment with ICIs were identified. Pathology and available next-generation sequencing (NGS) data, including the programmed death-ligand 1 (PD-L1) status and clinical information, including hospitalizations, invasive procedures, and the occurrence of irAEs, were collected. Unpaired T-tests, Chi-square/Fisher’s exact test, and logistic regression were used to analyze our cohort. The overall survival (OS) was calculated and compared using univariate and multivariate COX models. Ninety patients with stage IV lung cancer were admitted after ICI treatment. Of those patients, 28 (31.1%) had documented irAEs. Genomic analyses showed an enrichment of LRP1B mutations (n = 5/6 vs. n = 7/26, 83.3% vs. 26.9%; odds ratio (OR) (95% confidence interval (CI): 13.5 (1.7–166.1); p < 0.05) and MLL3 mutations (n = 4/6, 66.7% vs. n = 5/26, 19.2%; OR (95% CI): 8.4 (1.3–49.3), p < 0.05) in patients with irAE occurrences. Patients with somatic genomic alterations (GAs) in MET (median OS of 2.7 vs. 7.2 months; HR (95% CI): 3.1 (0.57–17.1); p < 0.05) or FANCA (median OS of 3.0 vs. 12.4 months; HR (95% CI): 3.1 (0.70–13.8); p < 0.05) demonstrated a significantly shorter OS. Patients with irAEs showed a trend toward improved OS (median OS 16.4 vs. 6.8 months, p = 0.19) compared to hospitalized patients without documented irAEs. Lung cancer patients who required treatment discontinuance or interruption due to irAEs (n = 19) had significantly longer OS (median OS 18.5 vs. 6.2 months; HR (95% CI): 0.47 (0.28–0.79); p < 0.05). Our results showed a significant survival benefit in lung cancer patients hospitalized due to irAEs that necessitated a treatment interruption. Patients with positive somatic GAs in MET and FANCA were associated with significantly worse OS compared to patients with negative GAs.

Benign vs malignant pancreatic lesions: Molecular insights to an ongoing debate.

Several benign conditions such as chronic pancreatitis, autoimmune pancreatitis, and paraduodenal pancreatitis can present as mass lesions and may mimic pancreatic ductal adenocarcinoma (PDAC) clinically and radiologically. Thorough histologic examination with attention to certain morphologic features can assist in deciphering neoplastic from reactive, however small biopsies often remain a challenge. Variable histologic patterns in conventional PDAC may also confound the diagnosis of PDAC. Uncommon subtypes of pancreatic carcinoma such as adenosquamous and squamous cell carcinoma, colloid carcinoma, medullary carcinoma, hepatoid carcinoma and signet ring cell carcinoma necessitate excluding metastasis from other sites prior to rendering the diagnosis of pancreatic carcinoma. The use of immunohistochemical staining and molecular markers can aid in separating benign from malignant and PDAC from metastasis. PDAC expresses a few non-specific epithelial and mucin immunomarkers such as CK7, CK19, MUC1, MUC4 and MUC5AC. However, the only immunohistochemical marker that is specific for PDAC in the right clinical context is SMAD4. Loss of SMAD4 within atypical glands and ducts supports the diagnosis of PDAC in a limited sample. Unfortunately, this finding is seen only in 50% of PDAC cases. The identification of certain mutations can help support a diagnosis of PDAC when benign conditions are in the differential. At the molecular level, KRAS oncogene mutations are seen in approximately 93% of PDACs. Subsequent neoplastic progression is driven by additional mutations of tumor suppressor genes, such as CDKN2A, TP53, and SMAD4. Molecular markers can also provide an insight to the prognosis. For instance, the loss of SMAD4 is associated with a poor outcome whereas mutations in MLL, MLL2, MLL3, and ARID1A are associated with improved survival.

Analysis of mutations in cutaneous squamous cell carcinoma reveals novel genes and mutations associated with patient-specific characteristics and metastasis: a systematic review.

Cutaneous squamous cell carcinoma (SCC) causes approximately 1,000,000 cases and 9000 deaths each year in the United States. While individual tumor sequencing studies have discovered driver mutations in SCC, there has yet to be a review and subsequent analysis synthesizing current studies. To conduct a comprehensive synthesis and analysis of SCC sequencing studies with individual patient-level data, a comprehensive literature search was performed. Statistical analyses were performed to identify trends. Studies meeting inclusion criteria included a total of 279 patients (189 localized SCCs, 90 metastatic SCCs). Several mutations were correlated with demographic characteristics (TP53, MLL4, BRCA2, COL4A1). TP53, TERT, SPEN, MLL3, and NOTCH2 mutations were significantly more likely to be found in metastatic versus localized SCCs even after the Bonferroni correction for multiple comparisons. Silent mutations were found more in localized SCCs than metastatic SCCs, and nonsense mutations were found more in metastatic SCCs than localized SCCs (p = 0.0003 and p = 0.04, respectively). Additional mutations were identified that have not yet been explored in SCC including AHNAK2, LRP1B, TRIO, MDN1, COL4A2, SVIL, VPS13C, DST, DMD, and DYSF. Overall, novel mutations were identified and differences between mutation patterns in localized and metastatic SCCs were found. These findings may have clinical applications.

Genotyping Squamous Cell Lung Carcinoma in Colombia (Geno1.1-CLICaP).

BackgroundLung cancer is a public health problem, and squamous cell carcinoma (SCC) is the second most prevalent subtype of this neoplasm. Compared to other subtypes, including adenocarcinoma, SCC is less well understood in terms of molecular pathogenesis, limiting therapeutic options among targeted agents approved for other disease subgroups. In this study, we sought to characterize the SCC genomic profile using a validated Next Generation Sequencing (NGS) platform.MethodsThe comprehensive NGS assay (TruSight Tumor 170) was used in order to target the full coding regions of 170 cancer-related genes on SCC samples. PD-L1 expression in tumor cells (TCs) was assessed using clone 22C3 (Dako). Clinical outcomes were correlated with molecular profile, including progression free survival (PFS), overall response rate (ORR), and overall survival (OS).ResultsA total of 26 samples were included, median age was 67 years (r, 33–83) and 53.8% were men. Tobacco consumption was identified in all subjects (mean 34-year package). For first-line treatment 80.8% of patients received cisplatin or carboplatin plus gemcitabine. In terms of molecular profile, we identified a high prevalence of inactivating mutations in TP53 (61.5%), PIK3CA (34.6%), MLL2 (34.6%), KEAP1 (38.4%), and NOTCH1 (26.9%). PD-L1 expression ranged from negative, 1, 2–49, and ≥50% in 23.1, 38.5, 26.9, and 11.5%, respectively. Interestingly, the genetic alterations did not have an effect in PFS, OS or ORR in this study. However, PDL1 expression was higher among those who had mutations in TP53 (p = 0.037) and greater expression of PDL1 was related to PIK3CA alterations (p = 0.05).ConclusionsThe genomic profile of SCC encompasses important genes including TP53, PIK3CA and KEAP1. TP53 mutations could be associated with PDL1 expression, generating hypothesis regarding specific treatment options.

Characterizing Specificities of Chronic Lymphoid Leukemia Harboring a BCL2 rearrangement

Characterizing Specificities of Chronic Lymphoid Leukemia Harboring a BCL2 rearrangement

Setbp1 Overexpression Acts in the Place of Class-Defining Somatic Mutations to Drive Mouse and Human FLT3-ITD-Mutant AMLs

Setbp1 overexpression acts in the place of class-defining somatic mutations to drive mouse and human FLT3-ITD-mutant AMLs Suruchi Pacharne,1,2 Oliver M. Dovey,1 Jonathan L. Cooper,1 Muxin Gu,1,2 MS Vijaybaskar,1,2 Mathias J. Friedrich,1,5 Malgorzata Gozdecka,1,2 Sandeep S. Rajan,1,4, Etienne De Braekeleer,1,2 Maxim Barenboim,5,6 Grace Collord,1,2 Hannes Ponstingl,1 Ruben Bautista,1 Milena Mazan,1,8 Roland Rad,5,6 Konstantinos Tzelepis,1,7 Penny Wright,3 and George S. Vassiliou1,2,9* Abstract Internal tandem duplications in FLT3 (FLT3-ITD) are found in 30% of acute myeloid leukemia (AML) cases and impart a poor prognosis. FLT3-ITD commonly synergizes with class-defining mutations such as chimeric fusion genes or mutations in NPM1, RUNX1, CEBPA or MLL to drive AML. However, 20% of FLT3-ITD-mutant AMLs bare no class-defining mutations and the mechanisms of acute leukemic transformation in these cases are unknown. To identify pathways that can drive FLT3-ITD-mutant AML in the absence of class-defining mutations, we performed an insertional mutagenesis (IM) screen in Flt3-ITD mice using the Sleeping Beauty transposon system, activated by the Mx1-Cre recombinase in hematopoietic stem cells. All mice developed acute leukemia, predominantly AML, after a median latency of 73 days (Figure A). Analysis of transposon insertions in 38 Flt3-ITD/IM leukemias identified common integration sites (CISs) in 22 loci (Figure B). The most commonly "hit" genes were Setbp1 (20/38), Ets1 (11/38), Ash1l (8/38), Notch1 (8/38), Erg (7/38), Flt3 (6/38) and Runx1 (5/38) (Figure B). Of these, Setbp1 and Runx1 were unique to Flt3-ITD and not identified as CISs in insertional mutagenesis screens of wild type, Npm1c or BCR-ABL-expressing mice. Transposon insertions in Setbp1, primarily located upstream of its first coding exon, were associated with Setbp1 and Hoxa mRNA overexpression and were invariably associated with AML development (Figure B). These findings propose that overexpression of wild type SETBP1 may collaborate with FLT3-ITD to drive leukemogenesis in human AMLs lacking mutations known to collaborate with mutant FLT3. Corroborating this, we found that SETBP1 expression was higher in human FLT3-ITD-mutant AMLs lacking class-defining mutations and in those with RUNX1 mutations (Figure C). We go on to show that Setbp1 insertions activate a Hoxa gene signature such that shares significant similarities, but also specific differences to those driven by mutant Npm1 and MLL fusion genes. We go on to show, using CRISPR-gRNA, that whilst Flt3ITD/+/SETBP1IM+AMLs are entirely dependent on Setbp1 expression, Flt3ITD/+/Npm1cA/+AMLs are not, but do depend on the expression of the homebox gene Nkx2.3. Our findings propose that SETBP1 overexpression activates a gene expression pattern that collaborates with FLT3-ITD to drive many human AMLs and that this combination represents a specific subtype of AML amongst AMLs lacking class-defining mutations. To identify genetic vulnerabilities of this AML subtype, we performed genome-wide CRISPR-Cas9 recessive screens in primary murine Flt3ITD/+SETBP1IM+AMLs and identified more than 2000 genetic vulnerabilities, of which 677 were not required for the survival of HPC7 non-leukemic hematopoietic cells including &amp;gt;100 "druggable" genes such as Brd3, Ezh2 and Hmgcr (Figure D). Collectively our study: i) identifies SETBP1overexpression as a non-genetic alteration driving a subgroup of FLT3-ITD mutant AMLs lacking class-defining somatic mutations and ii) goes on to define the genetic vulnerabilities of such AMLs as a starting point for the development of targeted therapies. Figure Disclosures Vassiliou: Kymab Ltd - Monoclonal antibody company. Currently not working in myeloid cancers or clonal haematopoiesis.: Consultancy.

Abstract IA29: Genome-estimated African ancestry is associated with distinct tumor mutations and poorer survival in patients with diffuse large B-cell lymphoma

Abstract Significant differences have been observed in the incidence, age of onset, and clinical outcomes of diffuse large B-cell lymphoma (DLBCL) by race in the United States. However, it remains unclear what factors underlie these differences and whether genomic differences contribute to these disparities. In this talk Dr. Flowers will address the identified differences in baseline clinical characteristics for black and white patients with DLBCL and the relationships between race, sociodemographic factors, and outcomes. To understand the influences of genetic ancestry on tumor genomic alterations, in a recent paper (Lee et al., Cancer 2020), we estimated the genetic ancestry of 1,001 previously described patients with DLBCL (Reddy et al., Cell 2017) using unsupervised model-based Admixture global ancestry analysis applied to exome sequencing data and examined the mutational profile of 150 DLBCL driver genes in tumors obtained from this cohort. Global ancestry prediction identified 619 patients with &amp;gt;90% European ancestry, 81 patients with &amp;gt;90% African ancestry, and 50 patients with &amp;gt;90% Asian ancestry. Compared with patients with DLBCL with European ancestry, patients with African ancestry were aged &amp;gt;10 years younger at the time of diagnosis and were more likely to present with B symptoms, elevated serum lactate dehydrogenase, extranodal disease, and advanced stage disease. Patients with African ancestry demonstrated worse overall survival compared with patients with European ancestry (median, 4.9 years vs. 8.8 years; P = .04). Recurrent mutations of MLL2 (KMT2D), HIST1H1E, MYD88, BCL2, and PIM1 were found across all ancestry groups, suggesting shared mechanisms underlying tumor biology. The authors also identified 6 DLBCL driver genes that were more commonly mutated in patients with African ancestry compared with patients with European ancestry: ATM (21.0% vs. 7.75%; P &amp;lt; .001), MGA (19.7% vs. 5.33%; P &amp;lt; .001), SETD2 (17.3% vs. 5.17%; P &amp;lt; .001), TET2 (12.3% vs. 5.82%; P = .029), MLL3 (KMT2C) (11.1% vs. 4.36%; P = .013), and DNMT3A (11.1% vs. 4.52%; P = .016). Distinct prevalence and patterns of mutation highlight an important difference in the mutational landscapes of DLBCL arising in different ancestry groups. This characterization of genetic alterations among patients with African descent who are diagnosed with DLBCL provides a roadmap for future studies in other lymphoid malignancies and a pathway for drug development in areas where these genetic alterations are found to be associated with worse clinical outcomes. Citation Format: Christopher R. Flowers. Genome-estimated African ancestry is associated with distinct tumor mutations and poorer survival in patients with diffuse large B-cell lymphoma [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr IA29.

Genome-defined African ancestry is associated with distinct mutations and worse survival in patients with diffuse large B-cell lymphoma.

Significant racial differences have been observed in the incidence and clinical outcomes of diffuse large B-cell lymphoma (DLBCL) in the United States, but to the authors' knowledge it remains unclear whether genomic differences contribute to these disparities. To understand the influences of genetic ancestry on tumor genomic alterations, the authors estimated the genetic ancestry of 1001 previously described patients with DLBCL using unsupervised model-based Admixture global ancestry analysis applied to exome sequencing data and examined the mutational profile of 150 DLBCL driver genes in tumors obtained from this cohort. Global ancestry prediction identified 619 patients with >90% European ancestry, 81 patients with >90% African ancestry, and 50 patients with >90% Asian ancestry. Compared with patients with DLBCL with European ancestry, patients with African ancestry were aged >10years younger at the time of diagnosis and were more likely to present with B symptoms, elevated serum lactate dehydrogenase, extranodal disease, and advanced stage disease. Patients with African ancestry demonstrated worse overall survival compared with patients with European ancestry (median, 4.9years vs 8.8years; P=.04). Recurrent mutations of MLL2 (KMT2D), HIST1H1E, MYD88, BCL2, and PIM1 were found across all ancestry groups, suggesting shared mechanisms underlying tumor biology. The authors also identified 6 DLBCL driver genes that were more commonly mutated in patients with African ancestry compared with patients with European ancestry: ATM (21.0% vs 7.75%; P<.001), MGA (19.7% vs 5.33%; P<.001), SETD2 (17.3% vs 5.17%; P<.001), TET2 (12.3% vs 5.82%; P=.029), MLL3 (KMT2C) (11.1% vs 4.36%; P=.013), and DNMT3A (11.1% vs 4.52%; P=.016). Distinct prevalence and patterns of mutation highlight an important difference in the mutational landscapes of DLBCL arising in different ancestry groups. To the authors' knowledge, the results of the current study provide the first-ever characterization of genetic alterations among patients with African descent who are diagnosed with DLBCL.

Association of survival and genomic mutation signature with immunotherapy in patients with hepatocellular carcinoma.

BackgroundCurrent guidelines lack recommendations for the use of immunotherapy and immune-related biomarkers for hepatocellular carcinoma (HCC). We aim to provide reliable evidence of the association of survival with HCC immunotherapy and to demonstrate that genomic mutation signature could be an effective biomarker to predict immunotherapy efficacy of HCC patients.MethodsWe conducted a meta-analysis of 17 randomized trials with 2055 patients and an individual patient-level analysis of 31 patients. Trial data were identified in PubMed, EMBASE and Cochrane Central library, and individual patient data were obtained from the cBioPortal database. Overall survival (OS) and progression-free survival (PFS) were assessed with the hazard ratio (HR) and 95% CI. This study is registered with PROSPERO, number CRD42018083991.ResultsThe meta-analysis showed that compared to conventional therapy, immunotherapy resulted in prolonged OS (HR =0.65, P<0.0001, high quality) and PFS (HR =0.81, P<0.0001, high quality); the benefits were observed for cellular immunotherapy, tumor vaccine, and cytokine immunotherapy. Findings were robust to subgroup and trial sequential analyses. In the individual patient-level analysis of patients treated with immune checkpoint inhibitor, mutations in TERT, CTNNB1, BRD4, or MLL, and co-mutations in TP53 and TERT or BRD4 were associated with significantly worse survival. These oncogenes were used to develop a novel integrated mutation risk score, which exhibited better utility in predicting survival than the tumor mutation burden (TMB). Patients with low- versus high- mutation risk score had longer OS (HR =0.18, P=0.02) and PFS (HR =0.33, P=0.018). A nomogram comprising the mutation risk score and essential clinical factors further improved the predictive accuracy (AUC =0.840 for both 1- and 2-year OS).ConclusionsImmunotherapy showed longer OS and PFS than conventional therapy among HCC patients, especially patients with a low mutation risk score. The nomogram based on genomic and clinical characteristics is effective in predicting survival of HCC patients undergoing immune checkpoint inhibitor.