Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease

BACKGROUND

Higher-than-normal levels of circulating triglycerides are a risk factor for ischemic cardiovascular disease. Activation of lipoprotein lipase, an enzyme that is inhibited by angiopoietin-like 4 (ANGPTL4), has been shown to reduce levels of circulating triglycerides.

METHODS

We sequenced the exons of ANGPTL4 in samples obtain from 42,930 participants of predominantly European ancestry in the DiscovEHR human genetics study. We performed tests of association between lipid levels and the missense E40K variant (which has been associated with reduced plasma triglyceride levels) and other inactivating mutations. We then tested for associations between coronary artery disease and the E40K variant and other inactivating mutations in 10,552 participants with coronary artery disease and 29,223 controls. We also tested the effect of a human monoclonal antibody against ANGPTL4 on lipid levels in mice and monkeys.

RESULTS

We identified 1661 heterozygotes and 17 homozygotes for the E40K variant and 75 participants who had 13 other monoallelic inactivating mutations in ANGPTL4. The levels of triglycerides were 13% lower and the levels of high-density lipoprotein (HDL) cholesterol were 7% higher among carriers of the E40K variant than among noncarriers. Carriers of the E40K variant were also significantly less likely than noncarriers to have coronary artery disease (odds ratio, 0.81; 95% confidence interval, 0.70 to 0.92; P=0.002). K40 homozygotes had markedly lower levels of triglycerides and higher levels of HDL cholesterol than did heterozygotes. Carriers of other inactivating mutations also had lower triglyceride levels and higher HDL cholesterol levels and were less likely to have coronary artery disease than were noncarriers. Monoclonal antibody inhibition of Angptl4 in mice and monkeys reduced triglyceride levels.

CONCLUSIONS

Carriers of E40K and other inactivating mutations in ANGPTL4 had lower levels of triglycerides and a lower risk of coronary artery disease than did noncarriers. The inhibition of Angptl4 in mice and monkeys also resulted in corresponding reductions in these values. (Funded by Regeneron Pharmaceuticals.).

Abstract P2-08-31: Tumor and axillar downstaging as a prognostic factor and evaluation of effectiveness to primary chemotherapy in breast cancer: A retrospective analysis

Introduction: Evaluation of the benefit of primary chemotherapy (PC) is not easy to establish. Pathologic complete response (pCR) has been considered the main surrogate prognostic factor of patient's survival. However, patients achieving a pCR are not the only ones who benefit from PC. The purpose of our study is to find a measure of response that includes the maximum of patients that benefit from PC in terms of survival.

Patients and methods: 224 breast cancer patients were treated in Breast Cancer Unit from Institut Català d'Oncologia (ICO) L'Hospitalet with taxans and antracyclines-based PC +/- trastuzumab between 2009 and 2011. pCR was defined as no invasive carcinoma found in the tumor and in the axillary lymph nodes (ypT0/ypTis ypN0). Tumor and nodal downstaging (TNDS) was calculated according to the "neoadjuvant response index" (NRI) from Rodenhuis and also as a dichotomic variable: Positive includes those patients achieving dowstaging of both T and N plus T downstaging N0 and negatives those patients without downstaging in any of both variables. Those parameters were related to patient's overall survival (OS). Statistical analysis was performed with SPSS version 15.

Results: Median age 45.5 years (24-83). Main tumor characteristics: T2 (62.6%); N1 (50%); ductal infiltrating carcinoma (95.5%) and grade III (57.1%). Biological sub-type according to the last St Gallen classification: luminal A: 28 patients (pts); luminal B/Her2-: 61 pts; luminal B/HER2+: 34 pts; HER2+: 33 pts and triple negative: 69 pts. Pathologic complete response was achieved in 49 pts (22.5%). TNDS was evaluated in 181 patients and of those 90 was positive. According to NRI 74 patients presented cut-off> 0.5 and 52 pts > 0.7. Parameters related to OS were: biological subtype (P: 0.007); achieving a pCR (p: 0.007); NRI cut-off 0.5 (P: 0.001) and TNDS (p:0.000). In the multivariate analysis only TNDS and biological subtype remained statistically significant. When comparing those patients with positive vs. negative TNDS, the HR for recurrence was of 10.05 (IC 2.33 -43.57). The median OS of the series has not been reached. OS at 5y was 82.7% (IC: 77.1%-88%) and specific breast cancer OS at 5 y was 85% (IC:79.5%-90%). The number of events (breast cancer deaths) for each biological subtype according to positive vs. negative TNDS was: luminal A: 0/5 vs. 0/18; luminal B Her2-: 0/10 vs. 8/43; luminal B HER2+:0/23 vs. 2/9; HER2+: 0/22 vs. 0/2 and TN: 2/30 vs. 8/18. Survival data per subtypes and TNDS is immature due to the scarce number of events. Estimated 5y OS for TNDS positive vs. negative in luminal A: 100% vs. 100%; luminal B Her2-: 100% vs. 82%; luminal B HER2+:100 vs.77.7%; HER2+: 100% vs. 100% and TN: 93% vs. 55%, respectively.

Conclusion: In our series, TNDS measured either with the NRI from Rodenhuis or as a dichotomic variable was the best parameter to evaluate response to PC in terms of OS. OS of luminal A and luminal B/Her2 negative is less influenced by PC than the rest of subgroups. In fact both subgroups have good prognosis despite their poor sensitivity to chemotherapy. Those tumors that benefit most from PC were luminal B/ Her2+; Her2+ and triple negative patients who achieved a positive TNDS.

Citation Format: Falo C, Ventura LM, Petit A, Perez J, Cañellas J, Perez L, Loayza C, Gil M, Varela M, Garcia A, Pla MJ, Lopez A, Guma A, Pernas S. Tumor and axillar downstaging as a prognostic factor and evaluation of effectiveness to primary chemotherapy in breast cancer: A retrospective analysis. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-08-31.

107 FACTORS THAT INFLUENCE FERTILITY IN AN IVF EMBRYO TRANSFER PROGRAM IN DAIRY HEIFERS

A retrospective study was performed to evaluate factors that influence pregnancy per embryo transfer (P/ET) in an IVF-embryo transfer program. A total of 5026 fresh in vitro-produced embryos were transferred during 2014 and evaluated for effects of embryo quality, embryo stage, size of corpus luteum (CL; 18–19.9 mm or ≥20 mm), interval from GnRH to embryo transfer, number of previous embryo transfer (0, 1, 2, 3, ≥4); and interaction of embryo stage and interval from GnRH to embryo transfer. One group (n = 850) had detection of oestrus after prostaglandin F2α application but most heifers (n = 4176) received fixed timed embryo transfer after a 5-day CIDR-Synch protocol: Day –8 CIDR inserted; Day –3 CIDR removed and prostaglandin F2α; Day –2 prostaglandin F2α; Day 0 GnRH. Ultrasound was performed on Day 6 after GnRH or oestrus to measure CL size and on Day 32 and 60 to determine pregnancy. Data for P/ET were analysed by logistic regression (LOGISTIC procedure, SAS 9.4). Embryo quality influenced P/ET at Day 32 [Grade 1 48.4% (1273/2631) v. Grade 2 37.6% (900/2395); P < 0.01] and at Day 60 [Grade 1 38.9% (1023/2631) v. Grade 2 29.0% (694/2395); P < 0.01], and altered pregnancy loss [Grade 1 19.6% (250/1273) v. Grade 2 22.9% (206/900); P = 0.03]. Stage of the embryo also had an effect on P/ET at Day 32 [Stage 6 35.5%a (582/1641), Stage 7 46.3%b (1431/3092), and Stage 8 54.6%c (160/293); P < 0.01] and at Day 60 [Stage 6 28.2%a (462/1641), Stage 7 36.6%b (1131/3092), and Stage 8 41.6%b (122/293); P < 0.01], but did not affect pregnancy loss (P = 0.22). Interestingly, interval from GnRH (or oestrus) until embryo transfer did not affect P/ET at Day 32 (P = 0.10), 60 (P = 0.23), or pregnancy loss (P = 0.3), nor was there an interaction between interval and embryo stage at Day 32 (P = 0.77), 60 (P = 0.96) or pregnancy loss (P = 0.55). As shown in Table 1, embryo stage 6 was always the lowest and stage 8 always the greatest P/ET regardless of interval from GnRH to embryo transfer. Size of CL also did not affect P/ET at Day 32 (P = 0.09), 60 (P = 0.21), or pregnancy loss (P = 0.90). Number of previous embryo transfer also did not alter P/ET at Day 32 [0 = 43.3% (886/2046), 1 = 44.1% (639/1450), 2 = 43.4% (444/1024), 3 = 42.6% (146/343), and ≥4 = 35.6% (58/163); P = 0.33] or 60 (P = 0.51) or pregnancy loss (P = 0.12). In conclusion, embryo stage and quality are the major factors that impacted P/ET in this study, with surprisingly little effect of interval from GnRH to embryo transfer, size of the CL, and number of previous embryo transfer. Thus, recipient programs for IVF-embryo transfer can be designed with substantial flexibility. Table 1.Effect of embryo stage and recipient synchrony on pregnancies per embryo transfer on Day 32 in recipient dairy heifers

Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data

We present a computational framework tailored for the modeling of the complex, dynamic relationships that are encountered in splicing regulation. The starting point is whole-genome transcriptomic data from high-throughput array or sequencing methods that are used to quantify gene expression and alternative splicing across multiple contexts. This information is used as input for state of the art methods for Graphical Model Selection in order to recover the structure of a composite network that simultaneously models exon co-regulation and their cognate regulators. Community structure detection and social network analysis methods are used to identify distinct modules and key actors within the network. As a proof of concept for our framework we studied the splicing regulatory network for Drosophila development using the publicly available modENCODE data. The final model offers a comprehensive view of the splicing circuitry that underlies fly development. Identified modules are associated with major developmental hallmarks including maternally loaded RNAs, onset of zygotic gene expression, transitions between life stages and sex differentiation. Within-module key actors include well-known developmental-specific splicing regulators from the literature while additional factors previously unassociated with developmental-specific splicing are also highlighted. Finally we analyze an extensive battery of Splicing Factor knock-down transcriptome data and demonstrate that our approach captures true regulatory relationships.