PARP1 Is Up-Regulated in Non-small Cell Lung Cancer Tissues in the Presence of the Cyanobacterial Toxin Microcystin.

Non-small cell lung cancer (NSCLC) is the major form of lung cancer, with adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being its major subtypes. Smoking alone cannot completely explain the lung cancer etiology. We hypothesize that altered lung microbiome and chronic inflammatory insults in lung tissues contribute to carcinogenesis. Here we explore the microbiome composition of LUAD samples, compared to LUSC and normal samples. Extraction of microbiome DNA in formalin-fixed, paraffin-embedded (FFPE) lung tumor and normal adjacent tissues was meticulously performed. The 16S rRNA product from extracted microbiota was subjected to microbiome amplicon sequencing. To assess the contribution of the host genome, CD36 expression levels were analyzed then integrated with altered NSCLC subtype-specific microbe sequence data. Surprisingly phylum Cyanobacteria was consistently observed in LUAD samples. Across the NSCLC subtypes, differential abundance across four phyla (Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes) was identified based on the univariate analysis (p-value < 6.4e-4 to 3.2e-2). In silico metagenomic and pathway analyses show that presence of microcystin correlates with reduced CD36 and increased PARP1 levels. This was confirmed in microcystin challenged NSCLC (A427) cell lines and Cyanobacteria positive LUAD tissues. Controlling the influx of Cyanobacteria-like particles or microcystin and the inhibition of PARP1 can provide a potential targeted therapy and prevention of inflammation-associated lung carcinogenesis.

Diagnosis of lung tumor types based on metabolomic profiles in lymph node aspirates.

BACKGROUND: Treatment of lung cancer is evolving from the use of cytotoxic drugs to drugs that interrupt pathways specific to a malignancy. The field of metabolomics has promise with respect to identification of tumor-specific processes and therapeutic targets, but to date has yielded inconsistent data in patients with lung cancer. Lymph nodes are often aspirated in the process of evaluating lung cancer, as malignant cells in lymph nodes are used for diagnosis and staging. We hypothesized that fluids from lymph node aspirates contains tumor-specific metabolites and are a suitable source for defining the metabolomic phenotype of lung cancers. PATIENTS AND MATERIALS: Metabolic profiles were generated from nodal aspirates of ten patients with adenocarcinoma, ten with squamous cell carcinoma, and ten with non-malignant conditions using time-of-flight mass spectrometry. In addition, concentrations of selected metabolites participating in the kynurenine and glutathione pathways were measured in a second set of aspirates using tandem mass spectrometry. RESULTS: A list of consensus features that separated these three groups was identified. Two of the consensus features were tentatively identified as kynurenine and as oxidized glutathione. It was shown that metabolite concentrations in these pathways are different for patients with and without malignancy. CONCLUSION: Together the data suggest that metabolomic analysis of lymph node aspirates can identify tumor-specific differences in cancer metabolism and reveal novel therapeutic targets. This proof-of-concept study demonstrates the validity to complement and refine diagnosis of lung cancer based on metabolic signature in lymph node aspirates. MICRO ABSTRACT: Treatment of lung cancer is evolving from the use of cytotoxic drugs to drugs that interrupt metabolic pathways specific to a malignancy. We report here in that the metabolic phenotype of lung cancer can be determined in lymph node aspirates harboring malignant tumor cells. Knowledge about metabolic activity of malignant tumor cells may aide to personalize therapy.

Glutamine drives glutathione synthesis and contributes to radiation sensitivity of A549 and H460 lung cancer cell lines.

BACKGROUND: Increased glutamine uptake is known to drive cancer cell proliferation, making tumor cells glutamine-dependent. Glutamine provides additional carbon and nitrogen sources for cell growth. The first step in glutamine utilization is its conversion to glutamate by glutaminase (GLS). Glutamate is a precursor for glutathione synthesis, and we investigated the hypothesis that glutamine drives glutathione synthesis and thereby contributes to cellular defense systems. METHODS: The importance of glutamine for glutathione synthesis was studied in H460 and A549 lung cancer cell lines using glutamine-free medium and bis-2-(5-phenyl-acetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide (BPTES) a GLS inhibitor. Metabolic activities were determined by targeted mass spectrometry. RESULTS: A significant correlation between glutamine consumption and glutathione excretion was demonstrated in H460 and A549 tumor cells. Culturing in the presence of [(13)C5]glutamine demonstrated that by 12h >50% of excreted glutathione was derived from glutamine. Culturing in glutamine-free medium or treatment with BPTES, a GLS-specific inhibitor, reduced cell proliferation and viability and abolished glutathione excretion. Treatment with glutathione-ester prevented BPTES-induced cytotoxicity. Inhibition of GLS markedly radiosensitized the lung tumor cell lines, suggesting an important role of glutamine-derived glutathione in determining radiation sensitivity. CONCLUSIONS: We demonstrate here for the first time that a significant amount of extracellular glutathione is directly derived from glutamine. This finding adds yet another important function to the already known glutamine dependence of tumor cells and probably tumors as well. GENERAL SIGNIFICANCE: Glutamine is essential for synthesis and excretion of glutathione to promote cell growth and viability.

Genotypic and allelic variability in CYP19A1 among populations of African and European ancestry.

CYP19A1 facilitates the bioconversion of estrogens from androgens. CYP19A1 intron single nucleotide polymorphisms (SNPs) may alter mRNA splicing, resulting in altered CYP19A1 activity, and potentially influencing disease susceptibility. Genetic studies of CYP19A1 SNPs have been well documented in populations of European ancestry; however, studies in populations of African ancestry are limited. In the present study, ten 'candidate' intronic SNPs in CYP19A1 from 125 African Americans (AA) and 277 European Americans (EA) were genotyped and their frequencies compared. Allele frequencies were also compared with HapMap and ASW 1000 Genomes populations. We observed significant differences in the minor allele frequencies between AA and EA in six of the ten SNPs including rs10459592 (p<0.0001), rs12908960 (p<0.0001), rs1902584 (p = 0.016), rs2470144 (p<0.0001), rs1961177 (p<0.0001), and rs6493497 (p = 0.003). While there were no significant differences in allele frequencies between EA and CEU in the HapMap population, a 1.2- to 19-fold difference in allele frequency for rs10459592 (p = 0.004), rs12908960 (p = 0.0006), rs1902584 (p<0.0001), rs2470144 (p = 0.0006), rs1961177 (p<0.0001), and rs6493497 (p = 0.0092) was observed between AA and the Yoruba (YRI) population. Linkage disequilibrium (LD) blocks and haplotype clusters that is unique to the EA population but not AA was also observed. In summary, we demonstrate that differences in the allele frequencies of CYP19A1 intron SNPs are not consistent between populations of African and European ancestry. Thus, investigations into whether CYP19A1 intron SNPs contribute to variations in cancer incidence, outcomes and pharmacological response seen in populations of different ancestry may prove beneficial.

Effect of MRP2 and MRP3 Polymorphisms on Anastrozole Glucuronidation and MRP2 and MRP3 Gene Expression in Normal Liver Samples.

Anastrozole is an aromatase inhibitor (AI) used as adjuvant therapy for breast cancer. Anastrozole is subject to direct glucuronidation catalyzed by UDP-glucuronosyltransferase1A4 (UGT1A4). Interindividual variability in anastrozole glucuronidation may be affected by UGT1A4 SNPs. Interplay between drug metabolizing genes such as UGT1A4 and transporter genes may also be affected by genetic variability. Thus, we hypothesize that genetic variability in MRPs could influence anastrozole glucuronidation. The correlation between UGT1A4 and MRP2 or MRP3 transporter gene expressions and the correlation between MRP2 or MRP3 mRNA and anastrozole glucuronidation were analyzed in normal human liver samples. MRP2 and MRP3 mRNA levels were significantly correlated with UGT1A4 mRNA, with anastrozole glucuronidation and with each other (p<0.05). The data also demonstrated that MRP2 SNPs are positively correlated with MRP2 mRNA expression, while there was no association between MRP3 SNPs from this study and MRP3 expression. Significant correlations (p<0.05) between certain MRP2 SNPs (3972C>T, 2366C>T and -24C>T) and anastrozole glucuronidation were observed. There were no observed correlations between MRP3 SNPs and anastrozole glucuronidation. MRP2 polymorphisms have been identified as playing a role in the disposition of other drugs, and the data presented here indicate for the first time that MRP2 SNPs could influence anastrozole metabolism and contribute to interindividual variation in treatment responses.

CYP19A1 single nucleotide polymorphism associations with CYP19A1, NFκB1, and IL6 gene expression in human normal colon and normal liver samples.

BACKGROUND: Estrogen is known to decrease the risk of colon cancer in postmenopausal women, and may exert its actions by decreasing interleukin-6 (IL6) production via stabilization of the transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB). Estrogens are biosynthesized by CYP19A1 (aromatase), so it is possible that genetic variations in CYP19A1 influences the risk of colon cancer by altering expression of CYP19A1. Further, studies on gene-gene interactions suggest that single nucleotide polymorphisms in one gene may affect expression of other genes. The current study aims to explore the role of CYP19A1 single nucleotide polymorphisms on CYP19A1, NFκB1 and IL6 gene expression. METHODS: Phenotype-genotype associations, cross-associations between genes, and haplotype analyses were performed in both normal human colon (n=82) and liver (n=238) samples. RESULTS: CYP19A1 rs10459592, rs1961177, and rs6493497 were associated with CYP19A1 expression in colon samples (P=0.042, P=0.041, and P=0.013, respectively). CYP19A1 single nucleotide polymorphisms (rs12908960, rs730154, rs8025191, and rs17523880) were correlated with NFκB1 expression (P=0.047, P=0.04, P=0.05, and P=0.03, respectively), and CYP19A1 rs11856927, rs2470152, and rs2470144 (P=0.049, P=0.025, P=0.047, respectively) were associated with IL6 expression in the colon. While rs730154 and rs17523880 could not be analyzed in the liver samples, none of the other associations with the colon were replicated in the liver samples. Haplotype analysis revealed three separate haplotypes of the CYP19A1 single nucleotide polymorphism that were significantly associated with CYP19A1, NFκB1, and IL6 gene expression. CONCLUSION: CYP19A1 single nucleotide polymorphisms are associated not only with CYP19A1 expression but also with NFκB1 and IL6 expression. These data demonstrate the possible functional consequences of genetic variation within the CYP19A1 gene on other genes in a biologically plausible pathway.

Influence of CHIEF pathway genes on gene expression: a pathway approach to functionality.

BACKGROUND: Candidate pathway approaches in disease association studies often utilize a tagSNP approach to capture genetic variation. In this paper we assess gene expression patterns with SNPs in genes in the CHIEF pathway to help determine their potential functionality. METHODS: Quantitative real-time RT-PCR was run to determine gene expression of 13 genes in normal colon tissue samples from 82 individuals. TagSNP genotype data were obtained from a GoldenGate Illumina multiplex bead array platform. Age, sex, and genetic ancestry adjusted general linear models were used to estimate beta coefficients and p values. RESULTS: Genetic variation in mTOR (1 SNP), NFKB1 (4 SNPs), PRKAG2 (3 SNPs), and TSC2 (1 SNP) significantly influenced their expression. After adjustment for multiple comparisons several associations between pathway genes and expression of other genes were significant. These included AKT1 rs1130214 associated with expression of PDK1; NFκB1 rs13117745 and rs4648110 with STK11 expression; PRKAG2 rs6965771 with expression of NFκB1, PIK3CA, and RPS6KB2; RPS6KB1 rs80711475 with STK11 expression; STK11 rs741765 with PIK3CA and PRKAG2 expression; and TSC2 rs3087631 with AKT1, IkBκB, NFκB1, PDK1, PIK3CA, PRKAG2, and PTEN expression. The higher levels of differential expression were noted for TSC2 rs3087631 (percent difference ranges from 108% to 198% across genes). Many of these SNPs and genes also were associated with colon and rectal cancer risk. CONCLUSIONS: Our results suggest that pathway genes may regulate expression of other genes in the pathway. The convergence of these genes in several biological pathways involved in cancer further supports their importance to the carcinogenic process.

Sulfotransferase 1A1 (SULT1A1) gene expression is regulated by members of the NFI transcription factors in human breast cancer cells.

BACKGROUND: Sulfotransferase 1A1 (SULT1A1) gene expression is tissue specific, with little to no expression in normal breast epithelia. Expression in breast tumors has been documented, but the transcriptional regulation of SULT1A1 in human breast tissue is poorly understood. We identified Nuclear Factor I (NFI) as a transcription factor family involved in the regulation of SULT1A1 expression. METHODS: Transcription Factor Activation Profiling Plate Array assay was used to identify the possible transcription factors that regulate the gene expression of SULT1A1in normal breast MCF-10A cells and breast cancer ZR-75-1 cells. Expression levels of NFI-C and SULT1A1 were determined by real-time RT-PCR using total RNA isolated from 84 human liver samples. Expression levels of SULT1A1, NFI-A, NFI-B, NFI-C, and NFI-X were also determined in different human breast cancer cell lines (MCF-7, T-47D, ZR-75-1, and MDA-MB-231), in the transformed human epithelial cell line MCF-10A, and in ZR-75-1 cells that were transfected with siRNAs directed against NFI-A, NFI-B, NFI-C, or NFI-X for 48 h. The copy numbers of SULT1A1 in cell lines ZR-75-1, MCF-7, T-47D, MDA-MB-231, and MCF-10A were determined using a pre-designed Custom Plus TaqMan® Copy Number kit from Life Technologies. RESULTS: In normal human liver samples, SULT1A1 mRNA level was positively associated with NFI-C. In different human breast cancer and normal epithelial cell lines, SULT1A1 expression was positively correlated with NFI-B and NFI-C. SULT1A1 expression was decreased 41% and 61% in ZR-75-1 cells treated with siRNAs against NFI-A and NFI-C respectively. SULT1A1 gene expression was higher in cells containing more than one SULT1A1 copy numbers. CONCLUSIONS: Our data suggests that SULT1A1 expression is regulated by NFI, as well as SULT1A1 copy number variation in human breast cancer cell lines. These data provide a mechanistic basis for the differential expression of SULT1A1 in different tissues and different physiological states of disease.

Fulvestrant up regulates UGT1A4 and MRPs through ERα and c-Myb pathways: a possible primary drug disposition mechanism.

Fulvestrant (Faslodex™) is a pure antiestrogen that is effective in treating estrogen receptor-(ER) positive breast cancer tumors that are resistant to selective estrogen receptor modulators such as tamoxifen. Clinical trials investigating the utility of adding fulvestrant to other therapeutics have not been shown to affect cytochrome P450-mediated metabolism. Effects on phase II metabolism and drug resistance have not been explored. This study demonstrates that fulvestrant up regulates the expression of UDP glucuronosyltransferase 1A4 (UGT1A4) >2.5- and >3.5-fold in MCF7 and HepG2 cells, respectively. Up regulation occurred in a time- and concentration-dependent manner, and was inhibited by siRNA silencing of ERα. Fulvestrant also up regulates multidrug resistance-associated proteins (MRPs). There was an up regulation of MRP2 (1.5- and 3.5-fold), and MRP3 (5.5- and 4.5-fold) in MCF7 and HepG2 cell lines, respectively, and an up regulation of MRP1 (4-fold) in MCF7 cells. UGT1A4 mRNA up regulation was significantly correlated with UGT1A4 protein expression, anastrozole glucuronidation, ERα mRNA expression and MRP mRNA expression, but not with ERα protein expression. Genetic variants in the UGT1A4 promoter (-163A, -217G and -219T) reduced the basal activity of UGT1A4 by 40-60%. In silico analysis indicated that transcription factor c-Myb binding capacity may be affected by these variations. Luciferase activity assays demonstrate that silencing c-Myb abolished UGT1A4 up regulation by fulvestrant in promoters with the common genotype (-163G, -217 T and -219C) in MCF7 cells. These data indicate that fulvestrant can influence the disposition of other UGT1A4 substrates. These findings suggest a clinically significant role for UGT1A4 and MRPs in drug efficacy.

Lack of correlation between in silico projection of function and quantitative real-time PCR-determined gene expression levels in colon tissue.

There are a number of in silico programs that use algorithms and external web sources to predict the effect of single nucleotide polymorphisms (SNPs). While many of these programs have been shown to predict accurately the effect of SNPs in functional areas of the gene, such as 5' upstream or coding regions, empiric research may be warranted to confirm the functional consequences of SNPs that are predicted to have little to no effect. We compared predictions from FASTSNP (Function Analysis and Selection Tool for Single Nucleotide Polymorphism) and F-SNP (Functional Single Nucleotide Polymorphism) with experimentally derived genotype-phenotype correlations to determine the accuracy of these programs in predicting SNP functionality. We used normal colon tissue to evaluate 24 TagSNPs within six genes. Two of 16 SNPs that were predicted to have no functional effect in FASTSNP were significantly associated with gene expression. Only one of the eight SNPs that were predicted to have a low to high effect was significantly associated with gene expression. While the two in silico programs that were used were similar in their results for the SNPs predicted by FASTSNP to have no effect, of SNPs with scores from low to high, there were three that received an F-SNP score below what is considered functionally significant. In silico programs can fail to identify functional SNPs, supporting a continuing role for empiric analysis of SNP function. Laboratory analysis is necessary to identify causal SNPs accurately, establish biological plausibility of the effect, and ultimately inform cancer prevention strategies.