Citations

AbstractIdentifying biomarkers associated with disease progression and drug resistance are important for personalized care. We investigated the expression of 121 curated genes, related to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) responsiveness. We analyzed 28 human multiple myeloma (MM) cell lines with known drug sensitivities and 130 primary MM patient samples collected at different disease stages, including newly diagnosed (ND), on therapy (OT), and relapsed and refractory (RR, collected within 12 months before the patients’ death) timepoints. Our findings led to the identification of a subset of genes linked to clinical drug resistance, poor survival, and disease progression following combination treatment containing IMIDs and/or PIs. Finally, we built a seven‐gene model (MM‐IMiD and PI sensitivity‐7 genes [IP‐7]) using digital gene expression profiling data that significantly separates ND patients from IMiD‐ and PI‐refractory RR patients. Using this model, we retrospectively analyzed RNA sequcencing (RNAseq) data from the Mulltiple Myeloma Research Foundation (MMRF) CoMMpass (n = 578) and Mayo Clinic MM patient registry (n = 487) to divide patients into probabilities of responder and nonresponder, which subsequently correlated with overall survival, disease stage, and number of prior treatments. Our findings suggest that this model may be useful in predicting acquired resistance to treatments containing IMiDs and/or PIs.

AbstractBackgroundTau deposition is a key biological feature of Alzheimer’s disease (AD) that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau accumulation while others are more resistant. The recent availability of tau positron emission tomography (tau‐PET) provides an opportunity to test the hypothesis that genetic factors are associated with differential tau deposition.MethodsWe performed a genome‐wide association study (GWAS) of tau‐PET on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.4% cognitively unimpaired) from the population‐based Mayo Clinic Study of Aging. Following genotyping with the Illumina GSA array and standard quality control, 515,206 single nucleotide polymorphisms (SNPs) were tested for association with entorhinal cortex 18F‐flortaucipir tau‐PET burden using linear regression under an additive genetic model and covarying for age and sex.ResultA genome‐wide significant association was identified for rs75546066, an intergenic SNP on chromosome 9 between MED27 (mediator complex subunit 27) and NTNG2 (netrin G2), with the minor (A) allele associated with lower tau burden (p=2.85 x 10‐8, β=‐0.48). Linkage disequilibrium and public expression quantitative trait loci (eQTL) data suggested a functional relationship between rs75546066 and NTNG2, the latter of which is highly expressed in the brain. In addition to this novel finding, three SNPs within MAPT (microtubule‐associated protein tau) displayed nominal associations to tau‐PET burden, including rs3785883 (p=0.04, β=0.07) which was previously associated with higher cerebrospinal fluid tau in an independent cohort. No associations with tau‐PET burden were identified for the APOE (apolipoprotein E) ɛ4 or ɛ2 alleles or for genotyped SNPs previously associated with AD in large case‐control studies.ConclusionTo our knowledge, this study represents the first reported neuroimaging GWAS of tau pathology. Our findings confirm the association of MAPT with tau burden and nominate the rs75546066‐NTNG2 locus as a novel potential protective influence against tau pathology which warrants further functional characterization. Our data also supports the inference that tau accumulation may have a genetic architecture distinct from APOE and other known AD susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting models.

AbstractTau deposition is a key biological feature of Alzheimer’s disease that is closely related to cognitive impairment. However, it remains poorly understood why certain individuals may be more susceptible to tau deposition while others are more resistant. The recent availability of in vivo assessment of tau burden through positron emission tomography provides an opportunity to test the hypothesis that common genetic variants may influence tau deposition. We performed a genome-wide association study of tau-positron emission tomography on a sample of 754 individuals over age 50 (mean age 72.4 years, 54.6% men, 87.6% cognitively unimpaired) from the population-based Mayo Clinic Study of Aging. Linear regression was performed to test nucleotide polymorphism associations with AV-1451 (18F-flortaucipir) tau-positron emission tomography burden in an Alzheimer’s-signature composite region of interest, using an additive genetic model and covarying for age, sex and genetic principal components. Genome-wide significant associations with higher tau were identified for rs76752255 (P = 9.91 × 10−9, β = 0.20) in the tau phosphorylation regulatory gene PPP2R2B (protein phosphatase 2 regulatory subunit B) and for rs117402302 (P = 4.00 × 10−8, β = 0.19) near IGF2BP3 (insulin-like growth factor 2 mRNA-binding protein 3). The PPP2R2B association remained genome-wide significant after additionally covarying for global amyloid burden and cerebrovascular disease risk, while the IGF2BP3 association was partially attenuated after accounting for amyloid load. In addition to these discoveries, three single nucleotide polymorphisms within MAPT (microtubule-associated protein tau) displayed nominal associations with tau-positron emission tomography burden, and the association of the APOE (apolipoprotein E) ɛ4 allele with tau-positron emission tomography was marginally nonsignificant (P = 0.06, β = 0.07). No associations with tau-positron emission tomography burden were identified for other single nucleotide polymorphisms associated with Alzheimer’s disease clinical diagnosis in prior large case–control studies. Our findings nominate PPP2R2B and IGF2BP3 as novel potential influences on tau pathology which warrant further functional characterization. Our data are also supportive of previous literature on the associations of MAPT genetic variation with tau, and more broadly supports the inference that tau accumulation may have a genetic architecture distinct from known Alzheimer’s susceptibility genes, which may have implications for improved risk stratification and therapeutic targeting.

Abstract DNA methylation plays an import role in both tumorigenesis and therapy resistance. Demethylating drug regimens have shown efficacy in hematological malignancies, and are actively studied for other cancer types. High variability in patients’ responses to these drugs has been observed and highlights the demand to identify predictive biomarkers for these demethylating drugs. In particular, decitabine (latest FDA-approved demethylating drug) demonstrated as the most potent agent and has the best response on hematological cell lines. Two public datasets were collected to identify methylation biomarkers of decitabine. The first one is from Genomics of Drug Sensitivity in Cancer, with methylation data from Illumina 450K array and drug response from cell lines. The other one is a publicly available patient dataset (methylations from RRBS sequencing and decitabine response from clinic). 64900 CpG sites common to the two methylation platforms were used to train machine learning model (Elastic Net), based on the methylation data and decitabine response (AUC) from 108 hematological cell lines in GDSC. 73 CpGs were identified as predictive biomarkers by Elastic Net. The trained model was then used to make predictions on 39 patients (20 responders and 19 non-responders) with their methylation profiles of the same set of CpGs. The predicted response of responder group is indeed better than non-responder group (p-value = 0.0501), indicating the validity of identified methylation biomarkers. The top one CpG identified by Elastic Net resides in the promoter region of gene C20orf85, and is significantly hypermethylated in non-responder group (p-value = 0.0458), suggesting its potential involvement in the resistance to decitabine. Citation Format: Xuewei Wang, Jean-Pierre Kocher, Zhifu Sun. Methylation biomarkers of cellular response to demethylating drug [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 681.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disease characterized by amyloidosis, tauopathy, and activation of microglia, the brain resident innate immune cells. We show that a RiboTag translational profiling approach can bypass biases due to cellular enrichment/cell sorting. Using this approach in models of amyloidosis, tauopathy, and aging, we revealed a common set of alterations and identified a central APOE-driven network that converged on CCL3 and CCL4 across all conditions. Notably, aged females demonstrated a significant exacerbation of many of these shared transcripts in this APOE network, revealing a potential mechanism for increased AD susceptibility in females. This study has broad implications for microglial transcriptomic approaches and provides new insights into microglial pathways associated with different pathological aspects of aging and AD.

Abstract FAM46C is one of the most recurrently mutated genes in multiple myeloma; however its role in disease pathogenesis has not been determined. Here we demonstrate that wild-type (WT) FAM46C overexpression induces substantial cytotoxicity in multiple myeloma cells. In contrast, FAM46C mutations found in multiple myeloma patients abrogate this cytotoxicity, indicating a survival advantage conferred by the FAM46C mutant phenotype. WT FAM46C overexpression downregulated IRF4, CEBPB, and MYC and upregulated immunoglobulin (Ig) light chain and HSPA5/BIP. Furthermore, pathway analysis suggests that enforced FAM46C expression activated the unfolded protein response pathway and induced mitochondrial dysfunction. CRISPR-mediated depletion of endogenous FAM46C enhanced multiple myeloma cell growth, decreased Ig light chain and HSPA5/BIP expression, activated ERK and antiapoptotic signaling, and conferred relative resistance to dexamethasone and lenalidomide treatments. Genes altered in FAM46C-depleted cells were enriched for signaling pathways regulating estrogen, glucocorticoid, B-cell receptor signaling, and ATM signaling. Together these results implicate FAM46C in myeloma cell growth and survival and identify FAM46C mutation as a contributor to myeloma pathogenesis and disease progression via perturbation in plasma cell differentiation and endoplasmic reticulum homeostasis. Cancer Res; 77(16); 4317–27. ©2017 AACR.