Non-synonymous Single Nucleotide Variants Research Articles

Effect of rare coding variants of charged amino acid residues on the function of human organic anion transporting polypeptide 1B3 (SLCO1B3)

Human organic anion transporting polypeptide 1B3 (OATP1B3, gene symbol SLCO1B3) is a liver-specific uptake transporter. Its function was reported to be largely affected by some positively charged amino acid residues. However, so far the effect of naturally occurring genetic variants of charged residues on OATP1B3’s function has not been explored yet. Therefore, in the present study nonsynonymous single nucleotide variants that led to the replacement of charged residues of OATP1B3 were investigated. Our results demonstrated that rare coding variants c.542G > A (p.R181H) and c.592G > A (p.D198N) had a great effect on the function of OATP1B3 mainly due to their influence on protein’s surface expression. Further mutation studies showed that a negatively charged residue at position 198 was indispensable to the proper expression of OATP1B3 on the plasma membrane, while a positively charged reside at position 181 was not a must. Structural modeling indicated that R181 is located at the center of putative transmembrane domain 4 (TM4) and its side chain faces towards TM2 instead of towards the substrate translocation pathway, whereas D198 is located at the border of TM4 and intracellular loop 2 and may electrostatically repulse negatively charged phospholipid head groups. In conclusion, our results indicated that rare coding variants that cause changes of charged amino acid residues might have large influence on the function and expression of OATP1B3.

Higher Mutation Burden in High Proliferation Compartments of Heterogeneous Melanoma Tumors.

Melanoma tumors are the most heterogeneous of all tumor types. Tumor heterogeneity results in difficulties in diagnosis and is a frequent cause of failure in treatment. Novel techniques enable accurate examination of the tumor cells, considering their heterogeneity. The study aimed to determine the somatic variations among high and low proliferating compartments of melanoma tumors. In this study, 12 archival formalin-fixed paraffin-embedded samples of previously untreated primary cutaneous melanoma were stained with Ki-67 antibody. High and low proliferating compartments from four melanoma tumors were dissected using laser-capture microdissection. DNA was isolated and analyzed quantitatively and qualitatively. Libraries for amplicon-based next-generation sequencing (NGS) were prepared using NEBNext Direct Cancer HotSpot Panel. NGS detected 206 variants in 42 genes in melanoma samples. Most of them were located within exons (135, 66%) and were predominantly non-synonymous single nucleotide variants (99, 73.3%). The analysis showed significant differences in mutational profiles between high and low proliferation compartments of melanoma tumors. Moreover, a significantly higher percentage of variants were detected only in high proliferation compartments (39%) compared to low proliferation regions (16%, p < 0.05). Our results suggest a significant functional role of genetic heterogeneity in melanoma.

Functional variability of rhesus macaque (Macaca mulatta) NAT2 gene for drug-metabolising arylamine N-acetyltransferase 2

Human NAT2 is a polymorphic pharmacogene encoding for N-acetyltransferase 2, a hepatic enzyme active towards arylamine and arylhydrazine drugs, including the anti-tubercular antibiotic isoniazid. The isoenzyme also modulates susceptibility to chemical carcinogenesis, particularly of the bladder. Human NAT2 represents an ideal model for anthropological investigations into the demographic adaptation of worldwide populations to their xenobiotic environment. Its sequence appears to be subject to positive selection pressures that are population-specific and may be attributed to gene-environment interactions directly associated with exogenous chemical challenges. However, recent evidence suggests that the same evolutionary pattern may not be observed in other primates. Here, we report NAT2 polymorphism in 25 rhesus macaques (Macaca mulatta) and compare the frequencies and functional characteristics of 12 variants. Seven non-synonymous single nucleotide variations (SNVs) were identified, including one nonsense mutation. The missense SNVs were demonstrated to affect enzymatic function in a substrate-dependent manner, albeit more moderately than certain NAT1 SNVs recently characterised in the same cohort. Haplotypic and functional variability of NAT2 was comparable to that previously observed for NAT1 in the same population sample, suggesting that the two paralogues may have evolved under similar selective pressures in the rhesus macaque. This is different to the population variability distribution pattern reported for humans and chimpanzees. Recorded SNVs were also different from those found in other primates. The study contributes to further understanding of NAT2 functional polymorphism in the rhesus macaque, a non-human primate model used in biomedicine and pharmacology, indicating variability in xenobiotic acetylation that could affect drug metabolism.

Prl and B4GALT-1 gene polymorphism and their association with milk production traits in crossbred cattle of Kerala

The main objective of present study was to explore the genetic variation in exon 3 of PRL (185 bp) and exon-2 of B4GALT-1 (256 bp) locus and analyze their associations with milk production traits. The study was conducted on 200 crossbred cattle distributed in different farms under Kerala Veterinary and Animal Sciences University and field centres of ICAR-FPT scheme, Mannuthy. Polymorphism of both the genes was detected by Single Strand Confirmation Polymorphism (PCR-SSCP). Similar banding pattern were noticed in exon-3 region of PRL, population was found to be monomorphic, indicating conserved nature of this fragment in the screened crossbred cattle population of Kerala. Two unique band patterns were detected in 256 bp fragment of B4GALT-1. Sequencing revealed a nonsynonymous single nucleotide variation in c.521T&gt;C in exon 2 of B4GALT-1, resulted in an amino acid substitution of methionine to threonine due to a codon change of ATG to ACG. Different genetic variants of B4GALT-1 was significantly associated with 305 days milk yield and protein percent. The study indicates the existence of genetic variability in B4GALT-1 gene on crossbred cattle population of Kerala and suggests a scope of considering genetic variants of B4GALT-1 gene in selection of cattle for higher milk production.

In-silico study to identify the pathogenic single nucleotide polymorphisms in the coding region of CDKN2A gene

Background: CDKN2A, encoding two important tumor suppressor proteins p16 and p14, is a tumor suppressor gene. Mutations in this gene and subsequently the defect in p16 and p14 proteins lead to the downregulation of RB1/p53 and cancer malignancy. To identify the structural and functional effects of mutations, various powerful bioinformatics tools are available. The aim of this study is the identification of high-risk non-synonymous single nucleotide variants in the CDKN2A gene via bioinformatics tools. Materials and Methods: Among the identified polymorphisms in this gene, 353 missense variants are retrieved from the national center for biotechnology information/single nucleotide polymorphism database (NCBI/dbSNP). Then, the pathogenicity of missense variants are considered using different bioinformatics tools. The stability of these mutant proteins, conservation of amino acids and the secondary and tertiary structural changes are analyzed by bioinformatics tools. After the identification of high-risk mutations, the changes in the hydrophobicity of high-risk amino acid substitutions are considered. Results: Deleterious single nucleotide polymorphisms (SNPs) were screened step by step using the bioinformatics tools. The results obtained from the set of bioinformatics tools identify high-risk mutations in CDKN2A gene. Conclusion: 18 high-risk mutations including L16R/Q, G23D/R/S, L32P, N42K, G55D, G67D/R, P81R, H83R, G89D/S, A102E, G101R, G122R, and V126D were identified. According to the previous experimental studies, the association of L16R, G23D/R/S, L32P, G67R, H83R, G89D, G101R, and V126D amino acid substitutions with various cancers has been confirmed.

Low Diversity of Human Variation Despite Mostly Mild Functional Impact of De Novo Variants.

Non-synonymous Single Nucleotide Variants (nsSNVs), resulting in single amino acid variants (SAVs), are important drivers of evolutionary adaptation across the tree of life. Humans carry on average over 10,000 SAVs per individual genome, many of which likely have little to no impact on the function of the protein they affect. Experimental evidence for protein function changes as a result of SAVs remain sparse – a situation that can be somewhat alleviated by predicting their impact using computational methods. Here, we used SNAP to examine both observed and in silico generated human variation in a set of 1,265 proteins that are consistently found across a number of diverse species. The number of SAVs that are predicted to have any functional effect on these proteins is smaller than expected, suggesting sequence/function optimization over evolutionary timescales. Additionally, we find that only a few of the yet-unobserved SAVs could drastically change the function of these proteins, while nearly a quarter would have only a mild functional effect. We observed that variants common in the human population localized to less conserved protein positions and carried mild to moderate functional effects more frequently than rare variants. As expected, rare variants carried severe effects more frequently than common variants. In line with current assumptions, we demonstrated that the change of the human reference sequence amino acid to the reference of another species (a cross-species variant) is unlikely to significantly impact protein function. However, we also observed that many cross-species variants may be weakly non-neutral for the purposes of quick adaptation to environmental changes, but may not be identified as such by current state-of-the-art methodology.

Exploiting Tumor Neoantigens to Target Cancer Evolution: Current Challenges and Promising Therapeutic Approaches.

Immunotherapeutic manipulation of the antitumor immune response offers an attractive strategy to target genomic instability in cancer. A subset of tumor-specific somatic mutations can be translated into immunogenic and HLA-bound epitopes called neoantigens, which can induce the activation of helper and cytotoxic T lymphocytes. However, cancer immunoediting and immunosuppressive mechanisms often allow tumors to evade immune recognition. Recent evidence also suggests that the tumor neoantigen landscape extends beyond epitopes originating from nonsynonymous single-nucleotide variants in the coding exome. Here we review emerging approaches for identifying, prioritizing, and immunologically targeting personalized neoantigens using polyvalent cancer vaccines and T-cell receptor gene therapy. SIGNIFICANCE: Several major challenges currently impede the clinical efficacy of neoantigen-directed immunotherapy, such as the relative infrequency of immunogenic neoantigens, suboptimal potency and priming of de novo tumor-specific T cells, and tumor cell-intrinsic and -extrinsic mechanisms of immune evasion. A deeper understanding of these biological barriers could help facilitate the development of effective and durable immunotherapy for any type of cancer, including immunologically "cold" tumors that are otherwise therapeutically resistant.

A genomic variant of ALPK2 is associated with increased liver fibrosis risk in HIV/HCV coinfected women.

HIV coinfection is associated with more rapid liver fibrosis progression in hepatitis C (HCV) infection. Recently, much work has been done to improve outcomes of liver disease and to identify targets for pharmacological intervention in coinfected patients. In this study, we analyzed clinical data of 1,858 participants from the Women's Interagency HIV Study (WIHS) to characterize risk factors associated with changes in the APRI and FIB-4 surrogate measurements for advanced fibrosis. We assessed 887 non-synonymous single nucleotide variants (nsSNV) in a subset of 661 coinfected participants for genetic associations with changes in liver fibrosis risk. The variants utilized produced amino acid substitutions that either altered an N-linked glycosylation (NxS/T) sequon or mapped to a gene related to glycosylation processes. Seven variants were associated with an increased likelihood of liver fibrosis. The most common variant, ALPK2 rs3809973, was associated with liver fibrosis in HIV/HCV coinfected patients; individuals homozygous for the rare C allele displayed elevated APRI (0.61, 95% CI, 0.334 to 0.875) and FIB-4 (0.74, 95% CI, 0.336 to 1.144) relative to those coinfected women without the variant. Although warranting replication, ALPK2 rs3809973 may show utility to detect individuals at increased risk for liver disease progression.

Dengue Virus Serotype 2 Intrahost Diversity in Patients with Different Clinical Outcomes.

Intrahost genetic diversity is thought to facilitate arbovirus adaptation to changing environments and hosts, and it might also be linked to viral pathogenesis. Dengue virus serotype 2 (DENV-2) has circulated in Brazil since 1990 and is associated with severe disease and explosive outbreaks. Intending to shed light on the viral determinants for severe dengue pathogenesis, we sought to analyze the DENV-2 intrahost genetic diversity in 68 patient cases clinically classified as dengue fever (n = 31), dengue with warning signs (n = 19), and severe dengue (n = 18). Unlike previous DENV intrahost diversity studies whose approaches employed PCR, here we performed viral whole-genome deep sequencing from clinical samples with an amplicon-free approach, representing the real intrahost diversity scenario. Striking differences were detected in the viral population structure between the three clinical categories, which appear to be driven mainly by different infection times and selection pressures, rather than being linked with the clinical outcome itself. Diversity in the NS2B gene, however, showed to be constrained, irrespective of clinical outcome and infection time. Finally, 385 non-synonymous intrahost single-nucleotide variants located along the viral polyprotein, plus variants located in the untranslated regions, were consistently identified among the samples. Of them, 124 were exclusively or highly detected among cases with warning signs and among severe cases. However, there was no variant that by itself appeared to characterize the cases of greater severity, either due to its low intrahost frequency or the conservative effect on amino acid substitution. Although further studies are necessary to determine their real effect on viral proteins, this heightens the possibility of epistatic interactions. The present analysis represents an initial effort to correlate DENV-2 genetic diversity to its pathogenic potential and thus contribute to understanding the virus’s dynamics within its human host.

Prediction of Deleterious Protein Mutations

Human Single Amino Acid Polymorphisms (SAPs) or Single Amino Acid Variants (SAVs) represent the most frequent type of genetic variation among the population. They originate from non-synonymous single nucleotide variations (missense variants) where a single base pair substitution alters the genetic code in such a way that it produces a different amino acid at a given position. Since mutations are commonly associated with the development of various genetic diseases, it is of utmost importance to understand and predict which variations are deleterious and which are neutral. Computational tools based on machine learning are becoming promising alternatives to tedious and highly costly mutagenic experiments. Generally, varying quality, incompleteness and inconsistencies of SAVs datasets degrade the usefulness of machine learning approaches. Consequently, robust and more accurate approaches are essential to address these issues. In this paper, we present the application of a consensus classifier based on the holdout sampling, which shows robust and accurate results, outperforming currently available tools. We generated 100 holdouts to sample different classifiers’ architectures and different classification variables during the training stage. The best performing holdouts were selected to construct a consensus classifier and tested by blindly utilizing a K5-fold cross-validation approach. We also performed an analysis of the best protein attributes for predicting the effects of SAVs by calculating their discriminatory power.

Genetic variant effect prediction by supervised nonnegative matrix tri-factorization.

Discriminating between deleterious and neutral mutations among numerous non-synonymous single nucleotide variants (nsSNVs) that may be observed through whole exome sequencing (WES) is considered a great challenge. In this regard, many machine learning methods have been developed for the prediction of variant consequences based on the analysis of either protein amino acid sequences or protein structures or their integration with features extracted from various gene level data and phenotype information. Due to the availability of a high number of features and heterogeneity of sources, implementing a suitable integration method plays an important role in predictive models. In this study, we proposed a novel supervised nonnegative matrix tri-factorization (sNMTF) algorithm to integrate current variant prediction scores into the gene level data and disease networks. In this regard, a new feature space was constructed by the integration of all input data using sNMTF to provide appropriate inputs for training a classifier. For the assessment of the proposed model, we utilized two benchmark datasets. The first one contained 11 207 deleterious and 19 839 neutral nsSNPs, whereas for the other dataset we used 4416 and 4960 deleterious and neutral nsSNPs, respectively. In general, the evaluation of our proposed supervised NMTF method on both datasets indicated that, in comparison with the existing nsSNV effect prediction approaches, regardless of whether they are ensemble-based or not, our method exhibited a better performance, which resulted in a higher prediction accuracy on average of 15% than other ensemble scores. In addition, excluding any kind of data that were integrated into the final model led to a substantial decrease in deleterious variant prediction. The proposed model can be used as an extensible framework for integrating more hetergeneous sources.

Identification of novel single-nucleotide polymorphism at exon1 and 2 region of B4GALT1 gene and its association with milk production traits in crossbred cattle of Kerala, India

Beta 1,4-galactosyltransferase-I gene (B4GALT1) is an important candidate gene for milk performance traits, encodes catalytic part of lactose synthesis. Main objectives of present study is identification of single-nucleotide polymorphism in exon 1 and 2 region of B4GALT1 and to find significant association of genetic variants with milk performance traits in crossbred cattle of Kerala. The study was conducted on two hundred crossbred cattle maintained at various farms of Kerala Veterinary and Animal Sciences University, India. Genomic DNA was isolated and polymorphism of gene were detected by Single Strand Confirmation Polymorphism. Genotype and allelic frequency were estimated. Chi-square analysis revealed that screened population is under Hardy Weinberg equilibrium. Nucleotide sequence analysis revealed a novel non-synonymous single-nucleotide variation (T94A) in exon 1 and a non-synonymous mutation of T97C in exon 2 of B4GALT1 gene in the screened cattle population. Association analysis of genetic variants was done with milk production traits and major non-genetic factors using fixed models. Different genetic variants of B4GALT1 was significantly associated with 305 days milk yield, lactose, protein percent. Study indicates existence of genetic variability in B4GALT1 gene on crossbred cattle of Kerala and suggests a scope of considering genetic variants of B4GALT1in selection strategies.

DbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs

Whole exome sequencing has been increasingly used in human disease studies. Prioritization based on appropriate functional annotations has been used as an indispensable step to select candidate variants. Here we present the latest updates to dbNSFP (version 4.1), a database designed to facilitate this step by providing deleteriousness prediction and functional annotation for all potential nonsynonymous and splice-site SNVs (a total of 84,013,093) in the human genome. The current version compiled 36 deleteriousness prediction scores, including 12 transcript-specific scores, and other variant and gene-level functional annotations. The database is available at http://database.liulab.science/dbNSFP with a downloadable version and a web-service.

Genetic Diversity of the Flavohemoprotein Gene of Giardia lamblia: Evidence for High Allelic Heterozygosity and Copy Number Variation.

PurposeThe flavohemoprotein (gFlHb) in Giardia plays an important role in managing nitrosative and oxidative stress, and potentially also in virulence and nitroimidazole drug tolerance. The aim of this study was to analyze the genetic diversity of gFlHb in Giardia assemblages A and B clinical isolates.MethodsgFlHb genes from 20 cultured clinical Giardia isolates were subjected to PCR amplification and cloning, followed by Sanger sequencing. Sequences of all cloned PCR fragments from each isolate were analyzed for single nucleotide variants (SNVs) and compared to genomic Illumina sequence data. Identical clone sequences were sorted into alleles, and diversity was further analyzed. The number of gFlHb gene copies was assessed by mining PacBio de novo assembled genomes in eight isolates. Homology models for assessment of SNV’s potential impact on protein function were created using Phyre2.ResultsA variable copy number of the gFlHb gene, between two and six copies, depending on isolate, was found. A total of 37 distinct sequences, representing different alleles of the gFlHb gene, were identified in AII isolates, and 41 were identified in B isolates. In some isolates, up to 12 different alleles were found. The total allelic diversity was high for both assemblages (>0.9) and was coupled with a nucleotide diversity of <0.01. The genetic variation (SNVs per CDS length) was 4.8% in sub-assemblage AII and 5.4% in assemblage B. The number of non-synonymous (ns) SNVs was high in gFIHb of both assemblages, 1.6% in A and 3.0% in B, respectively. Some of the identified nsSNV are predicted to alter protein structure and possibly function.ConclusionIn this study, we present evidence that gFlHb, a putative protective enzyme against oxidative and nitrosative stress in Giardia, is a variable copy number gene with high allelic diversity. The genetic variability of gFlHb may contribute metabolic adaptability against metronidazole toxicity.

Predictive values of genomic variation, tumor mutational burden, and PD-L1 expression in advanced lung squamous cell carcinoma treated with immunotherapy.

BackgroundImmune checkpoint inhibitors (ICIs) prolong overall survival (OS) in patients with advanced lung squamous cell carcinoma (LUSC). However, predictive and prognostic factors related to ICIs in LUSC remain elusive. This study aimed to identify predictors that are related to better clinical benefit and outcomes in LUSC patients treated with immunotherapy.MethodsCapture-based targeted sequencing was performed in 64 patients with advanced LUSC who underwent immunotherapy. Tumor mutational burden (TMB) was defined as the sum of nonsynonymous single nucleotide and indel variants. Programmed cell death ligand-1 (PD-L1) expression was evaluated by immunohistochemical analysis. Clinicopathological characteristics including age, sex, performance status, smoking history, body mass index (BMI), blood fat, brain metastases, liver metastases, previous thoracic radiotherapy, and treatment lines were analyzed.ResultsThe most commonly mutated genes included TP53, CDKN2A, KEAP1, CREBBP, KRAS, BIM, AMER1, and APC. Copy number variations most frequently occurred in AR, SOX2, PIK3CA, EGFR, RICTOR, FGFR1, and ZNF703. The median and mean TMB was 9.35 and 10.62 mutations per megabase, respectively. Positive PD-L1 expression was detected in 29.7% patients. Patients with a history of heavy smoking (≥ 40 pack-years) were more likely to have positive PD-L1 expression (35% vs. 16.7%, P=0.04) and higher TMB (11.1 vs. 9.8 mut/Mb, P=0.04). Gene alterations had no impact on PD-L1 expression or TMB level. The median progression-free survival (PFS) was 6.7 months and median OS was 13.7 months. Higher TMB was independently associated with longer PFS (P=0.01) and OS (P=0.02), and this correlation was more pronounced in patients treated with ICIs as a single agent (P=0.0001). Higher TMB was also associated with better disease control rate (DCR) (P=0.02). Compared with wild-type, patients with KRAS mutation and EGFR amplification had higher objective response rates (ORR, P=0.01).ConclusionsThe predictive value of TMB is more significant in LUSC patients receiving ICI as a single agent than as a combination therapy. The combination of Eastern Cooperative Oncology Group performance status (ECOG-PS), smoking status, TMB, PD-L1, and genomic variation might be helpful for personalized immunotherapy decisions in clinical practice for advanced LUSC.

FAT1 and MSH2 Are Predictive Prognostic Markers for Chinese Osteosarcoma Patients Following Chemotherapeutic Treatment.

Osteosarcoma is characterized by diverse genetic mutations, including single-nucleotide variants (SNVs), which can complicate clinical outcomes of the treatment. This study identified key mutations or polymorphisms in genes that correlate with osteosarcoma prognoses. A total of 110 patients with osteosarcoma were assigned to "good" or "poor" cohorts depending on their 5-year disease-free survival (DFS) after surgery and chemotherapeutic treatment. We performed next-generation sequencing analysis of tumor tissues for prognosis-associated SNVs in 315 tumorigenesis-related genes, followed by modeling of clinical outcomes for these patients using random forest classification via a support vector machine (SVM). Data from the Chinese Millionome Database were used to compare SNV frequency in osteosarcoma patients and healthy people. SVM screening identified 17 nonsynonymous SNVs located in 15 genes, of which rs17224367 and rs3733406 (located in MSH2 and FAT1, respectively) were strongly correlated with osteosarcoma prognosis. These results were verified in a 26-patient validation cohort, confirming that these SNVs could be used to predict prognosis. These results demonstrated that two SNVs located in MSH2 and FAT1 are associated with prognosis of osteosarcoma patients. © 2022 American Society for Bone and Mineral Research (ASBMR).

Molecular Epidemiology of AML: Association of Somatic Gene Mutations with Epidemiologic Exposures and Outcomes in the Mayo Clinic AML Epidemiology Cohort

Introduction: Population studies have identified genes with germline polymorphisms associated with acute myeloid leukemia (AML) risk and outcome. However, somatic mutations in these genes have not been reported in an AML clinical population and whether they are associated with epidemiologic exposures, clinical AML phenotypes and outcome after therapy. Methods: We systemically interrogated PubMed database (1998-2018), to identify genes with germline polymorphisms associated with AML risk, response to chemotherapy or outcome. To determine the prevalence and relevance of somatic mutations in these genes in an unselected AML population, we performed an analysis using Whole-Exome Sequencing (WES) on remnant diagnostic cytogenetic pellets from 98 patients from the Mayo Clinic AML Epidemiology Cohort, a detailed and highly-annotated cohort of 295 consecutive AML patients treated at Mayo Clinic Florida &amp; Arizona between October, 2000 and December, 2011. Patient characteristics are shown in Table 1. Samples were sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and somatic mutations including non-synonymous and truncating single nucleotide variants and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, &amp; Mayo Clinic internal biobank genetic variants database. Copy number aberrations were identified &amp; filtered using public copy number polymorphism databases. The association analyses were performed at the gene level, with a primary endpoint of whether a given patient harbored a somatic mutation in any genes linked to AML risk or outcome in literature, and to determine the associations of these mutations with epidemiologic exposures, AML phenotype and clinical outcomes. Results: From the literature search, we identified 77 unique genes with known germline polymorphisms associated with AML risk, response to chemotherapy or outcome. Fifty-eight of these were found to be somatically mutated in our WES dataset, with subsequent analysis focusing on the 11 genes (ABCB1, CYP1A1, CYP2B6, EPHX1, ERCC1, ERCC2, ERCC5, JAK2, MEFV, MTRR, and TERT) that had greater than 5 patients with nonsynonymous somatic mutations in the given gene. Significant associations with epidemiologic exposures and outcomes were noted in patients with somatic mutations in ERCC2, CYP1A1 and ERCC5 genes. Table 2 shows a comparison of patient characteristics and associations according to the presence of somatic mutations in these genes. Patients with mutations in CYP1A1 had a significantly younger age at AML diagnosis (Median: 51.7 vs. 71.0 years, P=.02) and significantly shorter OS in age-adjusted analysis (HR=4.45, P=.003). The former is a novel finding, whereas the latter is consistent with previous reports. Patients with mutations in ERCC2 more commonly used statins (66.7% vs. 21.7%, P=.03). Patients with ERCC5 mutations had a lower rate of tobacco use (20.0% vs. 54.5%, P=.049). In unadjusted analysis, there was a significant association between presence of somatic mutations in JAK2 and poorer survival after AML diagnosis (HR=2.83, P=.017), but this attenuated and did not retain significance when adjusting for age at AML diagnosis (HR=2.22, P=.067). Conclusion: Our exploratory study describes a novel association of CYP1A1 somatic nonsynonymous mutations with age of AML onset, as well as novel associations of ERCC2 and ERCC5 mutations with epidemiologic exposures in an unselect cohort of patients with AML. We confirm the association of CYP1A1 with inferior overall survival after AML diagnosis. These findings suggest that some genes associated with AML risk may also harbor somatic mutations that are clinically relevant. These results will guide a planned confirmatory prospective study to determine frequency and impact of both germline and somatic mutations of risk genes in AML patients, and may contribute to a better understanding leukemia risk assessment and potentially to prevention strategies. Disclosures Finn: Jazz Pharmaceuticals: Speakers Bureau; Celgene: Speakers Bureau; Seattle Genetics: Speakers Bureau. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Foran:Revolution Medicine: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Agios: Honoraria, Research Funding.

Associations of Clinical Outcomes after Allogeneic Hematopoietic Cell Transplantation with Number of Predicted Class II Restricted mHA

Background: Leukemia relapse after allogeneic hematopoietic cell transplantation (alloHCT) has been associated with loss of heterozygosity of class II HLA, suggesting that T cells targeting leukemia via class II interactions may be critical for graft-vs-leukemia (GvL) effects and protection from relapse (Zeiser &amp; Vago, 2019). Therefore, we aimed to determine whether the number of predicted class-II restricted minor histocompatibility antigens (mHAs) in alloHCT recipients associates with clinical outcome. Specifically, we investigated: (1) if the number of mHAs expressed on leukemia and bone marrow cells (GvL mHAs) is correlated with incidence of leukemia relapse, and/or (2) if mHAs expressed on acute graft versus host disease (GvHD) target organs (GvH mHAs) correlated with incidence of GvHD. We expected increased GvL mHAs to be associated with increased survival, and increased GvH mHAs to be associated with increased incidence of GvHD. Methods: The study population was derived from donor-recipient alloHCT pairs (DRPs) treated for Acute Myeloid Leukemia (AML), Acute Lymphocytic Leukemia (ALL), and Myelodysplastic Syndrome (MDS) from the CIBMTR and previously analyzed in DISCOVeRY-BMT. To predict HLA class II restricted mHAs in alloHCT recipients, we translated nonsynonymous single nucleotide variants present in each recipient, but absent in their respective donor, into all possible peptides 15-24 amino acids long. We used netMHCIIpan to score these peptides and select those most likely to be presented (Reynisson et al., 2020). Predicted mHAs highly expressed in skin, hepatobiliary, and bowel tissues were classified as GvH mHAs, and those highly expressed highly in, testis, and bone marrow were classified as GvL mHAs. The impact of mHA on disease related mortality (DRM), leukemia free survival (LFS), disease relapse and death due to GVHD were assessed with competing risk models. We next determined whether knowledge of the number of GvL and GvH mHAs improves the ability of models to predict clinical outcome. We fit optimal logistic regression models (elastic net regularization with Monte Carlo cross validation) to predict GvHD mortality and relapse mortality at 1 year after alloHCT using: (1) clinical data only, and (2) both clinical data and number of GvH/GvL mHAs. Lastly, using the same regularization and cross-validation procedures as above, we determined which variables contributed most to the Cox regression models of overall survival. Results: The number of GvL-restricted and GvH-restricted class-II mHAs were significantly correlated (Figure 1). Patients who died of disease before 1 year after alloHCT had significantly fewer GvL mHAs when controlling for covariates (HR=.89, 95% CI .89, .99, P= 0.04) (Figure 2). There was no association between GvL mHAs and LFS or relapse. Surprisingly, death due to GvHD by 1 year after alloHCT was lower for recipients with more GvL mHAs (HR=.88, 95% CI= .76, 1.01 , P=.08) (Figure 3), however, because GvH and GvL mHAs are highly correlated, we believe this reflects better overall survival associated with increased GvL mHAs. Neither the predictive models that included the number of GvH/GvL mHAs nor the Cox regression models fitted with GvL mHA numbers performed better than models trained on clinical data alone (Figure 4). Conclusions: GvL mHAs were inversely associated with DRM at 1-year post-alloHCT as expected. Contrary to our hypothesis, the number of GvH mHAs was inversely associated with GvHD mortality at 1 year. This may reflect better overall survival associated with increased GvL mHAs, as GvH and GvL mHAs are highly correlated. The potential association between class-II mHAs and DRM warrant further investigation and validation. If validated, this supports the development of class-II mHA targeted immunotherapies. Disclosures Pasquini: Bristol Myers Squibb: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Other; Novartis: Research Funding; Kite: Research Funding. Armistead:GeneCentric: Consultancy; Cell Microsystems: Patents &amp; Royalties: Patent application U.S. 16/347,104 "Automated collection of a specified number of cells". Vincent:GeneCentric Therapeutics: Consultancy.

Validity of whole genomes sequencing results in neoplasms in precision medicine

ObjectiveTo compare the whole genomes sequencing (WGS) results in the 100K Genomes project with the results of routine molecular diagnostics in precision medicine.Materials and methodsWe analysed 374 cancers including a...

Association of an IGHV3-66 gene variant with Kawasaki disease.

In a meta-analysis of three GWAS for susceptibility to Kawasaki disease (KD) conducted in Japan, Korea, and Taiwan and follow-up studies with a total of 11,265 subjects (3428 cases and 7837 controls), a significantly associated SNV in the immunoglobulin heavy variable gene (IGHV) cluster in 14q33.32 was identified (rs4774175; OR = 1.20, P = 6.0 × 10−9). Investigation of nonsynonymous SNVs of the IGHV cluster in 9335 Japanese subjects identified the C allele of rs6423677, located in IGHV3-66, as the most significant reproducible association (OR = 1.25, P = 6.8 × 10−10 in 3603 cases and 5731 controls). We observed highly skewed allelic usage of IGHV3-66, wherein the rs6423677 A allele was nearly abolished in the transcripts in peripheral blood mononuclear cells of both KD patients and healthy adults. Association of the high-expression allele with KD strongly indicates some active roles of B-cells or endogenous immunoglobulins in the disease pathogenesis. Considering that significant association of SNVs in the IGHV region with disease susceptibility was previously known only for rheumatic heart disease (RHD), a complication of acute rheumatic fever (ARF), these observations suggest that common B-cell related mechanisms may mediate the symptomology of KD and ARF as well as RHD.