Citations

Alcohol consumption is a well‐established risk factor for the onset and progression of fatty liver disease. An estimated 90% of heavy drinkers are thought to develop significant liver steatosis. For these reasons, an increased understanding of the molecular basis for alcohol‐induced hepatic steatosis is important. It has become clear that autophagy, a catabolic process of intracellular degradation and recycling, plays a key role in hepatic lipid metabolism. We have shown that Rab7, a small guanosine triphosphatase known to regulate membrane trafficking, acts as a key orchestrator of hepatocellular lipophagy, a selective form of autophagy in which lipid droplets (LDs) are specifically targeted for turnover by the autophagic machinery. Nutrient starvation results in Rab7 activation on the surface of the LD and lysosomal compartments, resulting in the mobilization of triglycerides stored within the LDs for energy production. Here, we examine whether the steatotic effects of alcohol exposure are a result of perturbations to the Rab7‐mediated lipophagic pathway. Rats chronically fed an ethanol‐containing diet accumulated significantly higher levels of fat in their hepatocytes. Interestingly, hepatocytes isolated from these ethanol‐fed rats contained juxtanuclear lysosomes that exhibited impaired motility. These changes are similar to those we observed in Rab7‐depleted hepatocytes. Consistent with these defects in the lysosomal compartment, we observed a marked 80% reduction in Rab7 activity in cultured hepatocytes as well as a complete block in starvation‐induced Rab7 activation in primary hepatocytes isolated from chronic ethanol‐fed animals.Conclusion: A mechanism is supported whereby ethanol exposure inhibits Rab7 activity, resulting in the impaired transport, targeting, and fusion of the autophagic machinery with LDs, leading to an accumulation of hepatocellular lipids and hepatic steatosis. (Hepatology Communications2017;1:140‐152)

11 Background: Currently there are no serum markers of response to AA. We performed a proteome based analysis of serum from prostate cancer patients, followed by mapping of candidate markers to networks based on known molecular interactions in Ingenuity Knowledge Base (IKB). Methods: Isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS) was performed in serum of 3 non-localized prostate cancer cohorts. The first cohort included 15 paired untreated hormone-sensitive “pre AA” and 3-month “post AA” specimens; the second included 10 “early AA failure” (median failure time: 11 months) and the third included 10 “late AA failure” specimens (median failure time: 95 months). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post AA proteomes and (ii) post AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. To facilitate biological interpretation of multiple candidates identified in the comparisons, IPA was used. Candidate markers implicated in IPA networks with statistical significance were pursued in a second, independent patient cohort for association with time to AA failure using univariate Cox regression analysis. Results: Median PSA for pre/post AA first cohort were 3.15 and 0.29 ng/ml. Median PSA for the second and third cohorts were 27.3 and 4.3 ng/ml. Between post AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. Network enrichment analysis of the 47 proteins by IPA identified four interaction networks (p<0.01), one of which highlighted a role for 17-β-estradiol (E1). Gas chromatography used for measuring 3-month post AA initiation serum E1, estrone (E2) and testosterone levels (N=38) detected high E1, E2 levels associated with longer time to AA failure (P=0.07 for E1; P=0.08 for E2) in the independent cohort. Conclusions: A global proteomic analysis identified post AA initiation serum E1, E2 levels as potential response markers, which needs validation.

75 Background: We investigated the association of germline variation in ten candidate genes important in prostate cancer biology (NKX3-1, JAK2, SLCO2B1, STAT3, CYP19A1, HSD17B4, TRMT11, PRMT3, HSD17B12, NCOA4) with overall survival (OS) in a cohort of metastatic CRPC stage patients. Methods: Patients (N=497) were enrolled at the time of androgen deprivation therapy failure for D2 stage prostate cancer. Candidate genes were selected from the literature and pilot studies. Genes were tagged using SNPs from HapMap with minor allele frequency (MAF) of >5% and r2≥0.8. DNA was extracted from peripheral blood and genotyped using Illumina Veracode platform. The primary endpoint was OS, defined as time from development of CRPC to death. Principle components analysis was used for gene-levels tests. To account for multiple testing we calculated the false discovery rate (FDR). For SNP level results we estimated per allele (ordinal model) hazard ratios (HR) and 95% confidence intervals (CI) using Cox regression and adjusted for age and Gleason score (GS). Results: We successfully genotyped 60 SNPs (from 10 genes) in 497 Caucasian subjects. The median age of the CRPC cohort was 71 years (range 43,93). The GS distribution was 51% subjects with GS≥8; 32% with GS7 and 17% with GS<7. After a median follow up of 2.1 years (IQ range: 1.2-3.6), 297 subjects had died. In unadjusted gene level analyses, NKX3-1 (p=0.04; FDR=0.03) was associated with OS. After adjusting for age and GS the result remained significant (p=0.03). Two of the 5 genotyped SNPs in this gene were associated with OS after adjustment for age and GS: rs10503733 (dominant model p=0.03, HR=0.77; 95 CI=0.60-0.98; A>C; MAF = 0.22) and rs7005368 (dominant model p=0.05, HR=1.38, 95CI=1.0-1.92; G>A; MAF=0.07). Both SNPs are in Hardy Weinberg Equilibrium and in complete LD (D'=1), although r2 is low (r2=0.025) due to different allele frequencies. Conclusions: Variation in the homeobox NKX-1 gene, a prostate specific tumor suppressor gene involved in prostate development and carcinogenesis is significantly associated with OS in CRPC after accounting for age and GS. Further validation is needed to develop these as prognostic biomarkers.

255 Background: In a prior study, we found that 8 single nucleotide polymorphisms (SNPs) from 4 candidate hormone-related genes (JAK2, TRMT11, NKX3-1 and HSD17B12) were associated with overall survival (OS) in CRPC stage in a North American cohort of 519 subjects. We attempt to replicate these findings in an independent cohort of Portuguese patients. Methods: A hundred and forty CRPC stage patients in the new cohort were genotyped fort he candidate SNPs. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. For SNP level results we estimated hazard ratios (HR) and 95% confidence intervals (CI) under the dominant allele model using Cox regression and adjusted for age and Gleason score (GS). Results: The median age of the Portuguese cohort was 69 years (range 53-84). The GS distribution was 48% subjects with GS≥8; 35% with GS=7 and 17% with GS<7. Median time from castration resistance to death for the cohort was 2.2 years (IQ range: 0.8-3.4, 93 deaths). One of the 3 SNPs (rs2295005; C>G; MAF = 0.16) in the TRMT11gene was associated with OS after adjustment for age and GS: (dominant model p=0.05, HR=0.56; 95 CI=0.31-1.00). No other SNP was observed to have statistical significance with OS (Table 1). Conclusions: Variation in the TRMT11 gene is significantly associated with overall survival in patients with CRPC and warrants further validation as a potential prognostic biomarker. [Table: see text]

209 Background: Predictive markers of response to AA are not known. In a prior study, we found that 8 single nucleotide polymorphisms (SNPs) from 4 candidate hormone-related genes (JAK2, TRMT11, NKX3-1 and HSD17B12) were associated with response to AA in HSPC in a North American cohort of 519 subjects. We attempt to replicate these findings in a cohort of Portuguese patients. Methods: The Portuguese cohort consisted of 308 HSPC patients, and the primary endpoint was time to AA failure, defined as time from initiating continuous AA to two serial PSA increases over the nadir, initiation of chemotherapy for progressive disease, or clinical or imaging based progression, whichever came first. For each SNP, we calculated hazard ratios (HRs) and 95% confidence intervals (CI) for time to AA failure using a recessive model with adjustment for Gleason score (GS). Results: The median age of the Portuguese cohort was 69 years (range 43, 85). The GS distribution was 35% subjects with GS≥8; 35% with GS=7 and 30% with GS<7. Median time to AA failure for the cohort was 1.8 years (IQ range: 0.3, 3.6). Association of each SNP with time to AA failure is shown in the Table. None of the SNPs replicated. However, there was a suggestive inverse association for rs10503733 (NKX3.1) with time to AA failure (P=0.07). Conclusions: While we were not able to replicate our initial findings, there was an unexpected association with rs10503733 (NKX3.1 gene) that may warrant additional clinical validation. [Table: see text]

313 Background: We evaluated variation in candidate genes implicated in either initiation or progression of prostate cancer with survival in CRPC stage. Methods: Germline DNA was extracted from peripheral blood mononuclear cells of CRPC patients enrolled in a clinically annotated registry. Fourteen candidate genes were tagged using single nucleotide polymorphisms (SNPs) from HapMap with minor allele frequency of > 5%. The primary endpoint was overall survival (OS), defined as time from development of CRPC to death. Principal component analysis was used for gene levels tests of significance. For SNP level results the per allele hazard ratios (HR) and 95% confidence intervals (CI) under the additive allele model using Cox regression adjusted for age at CRCP and Gleason score (GS) were used. Results: Two hundred and forty five CRPC patients who met the criteria of having adequate DNA were genotyped (14 genes, 84 SNPs). The median age of the cohort was 69 years (range 43-93). The GS distribution was 55% with GS≥8, 32% with GS = 7 and 13% with GS < 7 or unknown. Median time from castration resistance to death for the cohort was 2.67 years (IQ range: 1.6-4.07, 144 deaths). At the gene level JAK2 was detected to be associated with OS. Six of 18 JAK2 SNPs were associated with OS after adjustment for age and GS as well as pruning of SNPs in high linkage disequilibrium with each other (see table). In our multivariate model including age, GS, rs2149556, and rs4372063, the adjusted HRs for rs2149556 and rs4372063 were 0.67 (95% CI 0.38-1.18) and 2.17 (95% CI 1.25-3.76), respectively. The protective effect of rs2149556 appears after adjusting for the presence of minor alleles for rs4372063 in this dataset. Conclusions: Germline variation in the JAK2gene is associated with survival in CRPC stage and warrants further validation as a potential prognostic biomarker. [Table: see text]

104 Background: Currently there are no serum predictive markers of response to AA. We used a proteomic based analytic approach to identify candidates. Methods: Serum from three non-localized prostate cancer cohorts was analyzed. The first included15 paired untreated hormone-sensitive “pre-AA” and 3-month “post-AA” specimens; the second included 10 “early AA failure” (median time to AA failure:11 months) and the third included 10 “late AA failure” specimens (median time to AA failure: 95 months). Proteomic analysis was performed with isobaric mass tags for relative and absolute quanititation (iTRAQ) analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC/MS/MS). Differentially expressed candidate proteins were identified by comparisons of (i) paired pre/post-AA proteomes and (ii) post-AA proteome with the combined AA failure cohorts at a False Discovery Rate of 0.2. ELISA assays were used to verify candidate markers in a second stored aliquot of first cohort specimens. This cohort was followed for AA failure. Association of post-AA ELISA levels of candidate markers with time to AA failure was performed using Cox proportional hazards regression, summarized as relative risk (RR) for AA failure. Results: Median PSA in pre/post-AA first cohort were 3.15 ng/ml and 0.29 ng/ml. Median PSA in the second and third cohorts were 27.3 and 4.3 ng/ml. Between post-AA and AA failure cohorts, 149 proteins were differentially expressed. Between early and late AA failure 98 proteins were differentially expressed; 47 proteins were common in both comparisons. ELISA assays verified expression levels of 2/47 proteins in the first cohort; zinc alpha-2 macroglobulin (ZAG), and Neuropilin-2 (NPL2). Median change in ZAG decreased by 2073.5 ng/ml (post versus pre-AA) while median change in NPL2 levels increased by 2.9 ng/ml. After a median follow-up of 43 months from the post-AA time-point, 4/15 first cohort subjects had failed AA. The RR of AA failure for ZAG levels below the median change was 3.8 (95% CI: 0.4-37) and 3.0 (95% CI: 0.3-29) for NPL2. Conclusions: A global proteomic analysis identified ZAG and NPL2 as candidate serum predictive markers of AA response which needs further validation.

Abstract Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer. Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed. Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34–0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44–1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27–0.74), P = 0.0015]. Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794–801. ©2017 AACR.