Citations

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most prevalent types of primary liver cancer. These malignancies have limited treatment options, resulting in poor patient outcomes. Metabolism reprogramming, including increased de novo lipogenesis, is one of the hallmarks of cancer. Fatty acid synthase (FASN) catalyzes the de novo synthesis of long‐chain fatty acids from acetyl‐coenzyme A and malonyl‐coenzyme A. Increased FASN expression has been reported in multiple tumor types, and inhibition of FASN expression has been shown to have tumor‐suppressing activity. Intriguingly, we found that while FASN is up‐regulated in human HCC samples, its expression is frequently low in human ICC specimens. Similar results were observed in mouse ICC models induced by different oncogenes. Ablating FASN in the mouse liver did not affect activated AKT and Notch (AKT/Notch intracellular domain 1) induced ICC formation in vivo. Furthermore, while both HCC and ICC lesions develop in mice following hydrodynamic injection of AKT and neuroblastoma Ras viral oncogene homolog oncogenes (AKT/Ras), deletion of FASN in AKT/Ras mice triggered the development almost exclusively of ICCs. In the absence of FASN, ICC cells might receive lipids for membrane synthesis through exogenous fatty acid uptake. In accordance with the latter hypothesis, ICC cells displayed high expression of fatty acid uptake‐related proteins and robust long‐chain fatty acid uptake. Conclusion: Our data demonstrate that FASN dependence is not a universal feature of liver tumors: while HCC development is highly dependent of FASN and its mediated lipogenesis, ICC tumorigenesis can be insensitive to FASN deprivation; our study supports novel therapeutic approaches to treat this pernicious tumor type with the inhibition of exogenous fatty acid uptake. (Hepatology 2016;63:1900‐1913)

Abstract Purpose: Obesity promotes pancreatic and breast cancer progression via mechanisms that are poorly understood. Although obesity is associated with increased systemic levels of placental growth factor (PlGF), the role of PlGF in obesity-induced tumor progression is not known. PlGF and its receptor VEGFR-1 have been shown to modulate tumor angiogenesis and promote tumor-associated macrophage (TAM) recruitment and activity. Here, we hypothesized that increased activity of PlGF/VEGFR-1 signaling mediates obesity-induced tumor progression by augmenting tumor angiogenesis and TAM recruitment/activity. Experimental Design: We established diet-induced obese mouse models of wild-type C57BL/6, VEGFR-1 tyrosine kinase (TK)-null, or PlGF-null mice, and evaluated the role of PlGF/VEGFR-1 signaling in pancreatic and breast cancer mouse models and in human samples. Results: We found that obesity increased TAM infiltration, tumor growth, and metastasis in pancreatic cancers, without affecting vessel density. Ablation of VEGFR-1 signaling prevented obesity-induced tumor progression and shifted the tumor immune environment toward an antitumor phenotype. Similar findings were observed in a breast cancer model. Obesity was associated with increased systemic PlGF, but not VEGF-A or VEGF-B, in pancreatic and breast cancer patients and in various mouse models of these cancers. Ablation of PlGF phenocopied the effects of VEGFR-1-TK deletion on tumors in obese mice. PlGF/VEGFR-1-TK deletion prevented weight gain in mice fed a high-fat diet, but exacerbated hyperinsulinemia. Addition of metformin not only normalized insulin levels but also enhanced antitumor immunity. Conclusions: Targeting PlGF/VEGFR-1 signaling reprograms the tumor immune microenvironment and inhibits obesity-induced acceleration of tumor progression. Clin Cancer Res; 22(12); 2993–3004. ©2016 AACR.

Background: Recent advances in accuracy and reliability of continuous glucose monitoring (CGM) devices have focused renewed interest on the use of such technology for therapeutic dosing of insulin without the need for independent confirmatory blood glucose meter measurements. An important issue that remains is the susceptibility of CGM devices to erroneous readings in the presence of common pharmacologic interferences. We report on a new method of assessing CGM sensor error to pharmacologic interferences using the example of oral administration of acetaminophen. Materials and Methods: We examined the responses of several different Food and Drug Administration–approved and commercially available CGM systems (Dexcom [San Diego, CA] Seven ® Plus™, Medtronic Diabetes [Northridge, CA] Guardian ® , and Dexcom G4 ® Platinum) to oral acetaminophen in 10 healthy volunteers without diabetes. Microdialysis catheters were placed in the abdominal subcutaneous tissue. Blood and microdialysate samples were collected periodically and analyzed for glucose and acetaminophen concentrations before and after oral ingestion of 1 g of acetaminophen. We compared the response of CGM sensors with the measured acetaminophen concentrations in the blood and interstitial fluid. Results: Although plasma glucose concentrations remained constant at approximately 90 mg/dL (approximately 5 m M ) throughout the study, CGM glucose measurements varied between approximately 85 to 400 mg/dL (from approximately 5 to 22 m M ) due to interference from the acetaminophen. The temporal profile of CGM interference followed acetaminophen concentrations measured in interstitial fluid (ISF). Conclusions: This is the first direct measurement of ISF concentrations of putative CGM interferences with simultaneous measurements of CGM performance in the presence of the interferences. The observed interference with glucose measurements in the tested CGM devices coincided temporally with appearance of acetaminophen in the ISF. The method applied here can be used to determine the susceptibility of current and future CGM systems to interference from acetaminophen or other exogenous pharmacologic agents.

Abstract Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6; Pcorrected = 0.01). Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446–54. ©2016 AACR.

Abstract Purpose: There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets. Experimental Design: We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score. Results: Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S). Conclusions: To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes. Clin Cancer Res; 22(7); 1777–86. ©2015 AACR.

BACKGROUNDThe objective of this study was to demonstrate that computer‐extracted image phenotypes (CEIPs) of biopsy‐proven breast cancer on magnetic resonance imaging (MRI) can accurately predict pathologic stage.METHODSThe authors used a data set of deidentified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. In total, 91 biopsy‐proven breast cancers were analyzed from patients who had information available on pathologic stage (stage I, n = 22; stage II, n = 58; stage III, n = 11) and surgically verified lymph node status (negative lymph nodes, n = 46; ≥ 1 positive lymph node, n = 44; no lymph nodes examined, n = 1). Tumors were characterized according to 1) radiologist‐measured size and 2) CEIP. Then, models were built that combined 2 CEIPs to predict tumor pathologic stage and lymph node involvement, and the models were evaluated in a leave‐1‐out, cross‐validation analysis with the area under the receiver operating characteristic curve (AUC) as the value of interest.RESULTSTumor size was the most powerful predictor of pathologic stage, but CEIPs that captured biologic behavior also emerged as predictive (eg, stage I and II vs stage III demonstrated an AUC of 0.83). No size measure was successful in the prediction of positive lymph nodes, but adding a CEIP that described tumor “homogeneity” significantly improved discrimination (AUC = 0.62; P = .003) compared with chance.CONCLUSIONSThe current results indicate that MRI phenotypes have promise for predicting breast cancer pathologic stage and lymph node status. Cancer 2016;122:748–757. © 2015 American Cancer Society.