<p style='text-indent:20px;'>Complete deconvolution analysis for bulk RNA-seq data is important and helpful to distinguish whether the differences of disease-associated GEPs (gene expression profiles) in tissues of patients and normal controls are due to changes in cellular composition of tissue samples, or due to GEPs changes in specific cells. One of the major techniques to perform complete deconvolution is nonnegative matrix factorization (NMF), which also has a wide-range of applications in the machine learning community. However, the NMF is a well-known strongly ill-posed problem, so a direct application of NMF to RNA-seq data will suffer severe difficulties in the interpretability of solutions. In this paper, we develop an NMF-based mathematical model and corresponding computational algorithms to improve the solution identifiability of deconvoluting bulk RNA-seq data. In our approach, we combine the biological concept of marker genes with the solvability conditions of the NMF theories, and develop a geometric structures guided optimization model. In this strategy, the geometric structure of bulk tissue data is first explored by the spectral clustering technique. Then, the identified information of marker genes is integrated as solvability constraints, while the overall correlation graph is used as manifold regularization. Both synthetic and biological data are used to validate the proposed model and algorithms, from which solution interpretability and accuracy are significantly improved.</p>
Identification of Two Genetic Loci Associated with Leukopenia after Chemotherapy in Patients with Breast Cancer
Abstract Purpose: To identify molecular predictors of grade 3/4 neutropenic or leukopenic events (NLE) after chemotherapy using a genome-wide association study (GWAS). Experimental Design: A GWAS was performed on patients in the phase III chemotherapy study SUCCESS-A (n = 3,322). Genotyping was done using the Illumina HumanOmniExpress-12v1 array. Findings were functionally validated with cell culture models and the genotypes and gene expression of possible causative genes were correlated with clinical treatment response and prognostic outcomes. Results: One locus on chromosome 16 (rs4784750; NLRC5; P = 1.56E-8) and another locus on chromosome 13 (rs16972207; TNFSF13B; P = 3.42E-8) were identified at a genome-wide significance level. Functional validation revealed that expression of these two genes is altered by genotype-dependent and chemotherapy-dependent activity of two transcription factors. Genotypes also showed an association with disease-free survival in patients with an NLE. Conclusions: Two loci in NLRC5 and TNFSF13B are associated with NLEs. The involvement of the MHC I regulator NLRC5 implies the possible involvement of immuno-oncological pathways.
Genetic Polymorphisms and Correlation with Treatment-Induced Cardiotoxicity and Prognosis in Patients with Breast Cancer
Abstract Purpose: Cardiac toxicity is a serious potential complication of HER2-directed therapies and anthracyclines. HER2 codon 655 and SLC28A3 gene polymorphisms have been reported to be associated with cardiac toxicity from anti-HER2 and anthracycline therapy, respectively. Association of the polymorphism at HER2 codon 655 with prognosis has also been reported. Experimental Design: Whole blood samples from patients treated on a randomized adjuvant breast cancer trial (BCIRG-006) that compared chemotherapy with or without trastuzumab plus either anthracycline or nonanthracycline chemotherapy were tested for genetic polymorphisms in HER2 codon 655 and SLC28A3. Genotypes were correlated with cardiac function and disease-free survival (DFS) outcomes. Results: Of 3,222 patients enrolled in BCIRG-006, 662 patient samples were successfully genotyped for the rs1136201 allele in HER2 (codon 655): 424 (64%) were AA, 30 (4.5%) were GG, and 208 (31%) were AG genotype. In addition, 665 patient samples were successfully genotyped for the rs7853758 allele in the SLC28A3 gene: 19 (3%) were AA, 475 (71%) were GG, and 171 (26%) were AG genotype. Follow-up time was 10 years. No correlation between DFS, cardiac event rate, or mean left ventricular ejection fraction (LVEF) and rs1136201 genotype was seen in the trastuzumab-treated or non–trastuzumab-treated patients. Moreover, mean LVEF and cardiac event rates were similar in all rs7853758 genotype groups treated with anthracycline-based therapy. Conclusions: In the largest study to date to evaluate whether two polymorphisms are associated with DFS and/or cardiac toxicity in HER2-positive breast cancer treated with trastuzumab and/or anthracyclines, we observed no correlation.
S754 Risankizumab as Induction Therapy in Patients with Moderately to Severely Active Crohn’s Disease Who Failed 1 vs >1 Prior Biologic Treatment: Results From the MOTIVATE Study
Major depressive disorder (MDD), the number one psychiatric disease and a major cause of medical disability worldwide, is a heterogeneous disease. Efforts to identify biomarkers for antidepressant therapy response by the use of genome‐wide association studies (GWAS) have generally yielded disappointing results, e.g. only a few markers have been replicated across studies. By applying a “pharmacometabolomics‐informed pharmacogenomic” research strategy, we previously identified a genome‐wide significant single‐nucleotide polymorphism (SNP) signal in the glutamate‐rich 3 ( ERICH3 ) gene that was associated with plasma serotonin concentrations which were themselves associated with selective serotonin reuptake inhibitor (SSRI) response in MDD patients enrolled in the Mayo Clinic PGRN‐AMPS SSRI trial. The same ERICH3 SNPs were associated with SSRI response in other GWAS, including the STAR*D and ISPC studies. However, the function of ERICH3 and the molecular mechanism(s) by which it might be associated with plasma serotonin concentrations and with SSRI response remain unknown. Functional characterization of ERICH3 and its encoded protein might make it possible to identify novel mechanisms of antidepressant treatment response. In the present study, ERICH3 mRNA and protein were studied in cell lines from human peripheral blood and brain. ERICH3 cDNA constructs and specific antibodies were generated to make it possible to study its function. Two ERICH3 mRNA splice variants and protein isoforms, one “full‐length” and the other encoding a C‐terminal protein, were identified in a variety of human cell lines and in human brain tissue. ERICH3 mRNA expression and immunofluorescent staining suggested both cytosolic and vesicular localizations for ERICH3 as well as co‐localization with serotonin and dopamine in both mouse and human neurons. Co‐immunoprecipitation studies identified several ERICH3 interacting proteins, including PIK3C2A, CLTC and AP2A2, proteins known to play a role in vesicular trafficking, as well as ALK and CUX1, both of which display genetic polymorphisms that have been associated with SSRI response in GWAS studies of antidepressant treatment response in MDD patients. This series of experiments suggests that ERICH3 may play a role in vesicular trafficking and, as a result, may influence neurotransmitter actions in the brain that are associated with antidepressant treatment response. Support or Funding Information This work was supported by the NIH grants U19 GM61388, R01 GM28157 and T32 GM008685. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
SNPs Outside Response Elements Impact Aryl Hydrocarbon Receptor (AHR) Binding and Gene Regulation: Genome‐wide SNP‐dependent Transcriptional Regulation
BACKGROUND Most functionally‐significant single nucleotide polymorphisms (SNPs) are outside of open reading frames. Mechanisms by which these SNPs contribute to gene regulation are poorly understood. Aryl hydrocarbon receptor (AHR) is a nuclear receptor that regulates drug metabolism, xenobiotic response and immune response. Our previous data indicate that SNPs outside response elements can impact transcription factor binding and gene regulation. We hypothesized that SNPs near but outside AHR response elements (AhREs) might impact AHR binding and gene regulation. METHODS We have collected dense SNP‐genotypes across 300 lymphoblastoid cell lines (LCLs) – a powerful tool for generating and testing pharmacogenomic hypotheses. Eight LCLs were used to generate hypotheses about AHR SNP‐dependent transcription utilizing RNA‐ and ChIP‐seq, which were tested in additional LCLs using qRT‐PCR and ChIP after AHR agonist or antagonist treatment. RESULTS 69 genes were highly significantly differentially expressed after agonist or antagonist treatment and 80% of those genes had an AhRE within 50kb. Five SNP‐gene pairs have been functionally validated in additional LCLs (Table 1). CONCLUSION SNPs that are outside of AhREs can alter AHR binding and gene transcription. This is a general phenomenon that may have large‐scale influence on gene transcriptional regulation and pharmacogenomics. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Influence of the Area of the Aqueduct on Quantification of Stroke Volume and Max Velocity in Healthy Volunteers Using Phase Contrast Cine MRI
Abstract Background: The relationship of the area of the aqueduct on quantification of the aqueductal stroke volume (SV) and max velocity need further investigation. Our aim was to assess the influence of the area of the aqueduct on quantification of the aqueductal SV and max velocity measured with phase contrast magnetic resonance imaging (PC-MRI) within the cerebral aqueduct at the level of the intercollicular sulcus.Materials and Methods: Nine healthy volunteers (mean age 29.6 yrs) were enrolled in the study and brain MRIs were performed on a 3.0T system. Quantitative analysis of aqueductal cerebrospinal fluid (CSF) flow was performed using manual regions of interest (ROI) placement. ROIs were separately drawn for each of 12 phases of the cardiac cycle, and changes in aqueduct size during the cardiac cycle were determined. Stroke volumes were calculated uses the first and ninth aqueductal ROIs and compared to each other. Max velocities at the 12 phases were also collected, and the relationship between the area and max velocity and the impact on SV were analyzed.Results: There was variation in the size of the aqueduct during the cardiac cycle, the first area(S1)was larger than the ninth(S9). The first max velocity(Vmax1)was less than the ninth(Vmax9). Additionally, there was a significant different between the stroke volume calculated using the first aqueductal ROI (SV1) and the ninth(SV9). Conclusions: There is variation in the size of the cerebral aqueduct which is used to calculate stroke volume and other CSF flow parameters during the cardiac cycle. The maximum velocity may be inversely proportional to the area of the aqueduct. In order to establish reliable reference values for CSF flow parameters in future studies, a variable ROI, to account for cardiac cycle variation, should be considered and incorporated.
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
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