Identification and high-throughput genotyping of single nucleotide polymorphism markers in a non-model conifer (Abies nordmanniana (Steven) Spach).

Single nucleotide polymorphism (SNP) markers are powerful tools for investigating population structures, linkage analysis, and genome-wide association studies, as well as for breeding and population management. The availability of SNP markers has been limited to the most commercially important timber species, primarily due to the cost of genome sequencing required for SNP discovery. In this study, a combination of reference-based and reference-free approaches were used to identify SNPs in Nordmann fir (Abies nordmanniana), a species previously lacking genomic sequence information. Using a combination of a genome assembly of the closely related Silver fir (Abies alba) species and a de novo assembly of low-copy regions of the Nordmann fir genome, we identified a high density of reliable SNPs. Reference-based approaches identified two million SNPs in common between the Silver fir genome and low-copy regions of Nordmann fir. A combination of one reference-free and two reference-based approaches identified 250 shared SNPs. A subset of 200 SNPs were used to genotype 342 individuals and thereby tested and validated in the context of identity analysis and/or clone identification. The tested SNPs successfully identified all ramets per clone and five mislabeled individuals via identity and genomic relatedness analysis. The identified SNPs will be used in ad hoc breeding of Nordmann fir in Denmark.

Estimating waves via measured ship responses.

Optimisation of energy efficiency and operational performance as well as assessment of safety levels and emissions of marine operations require detailed information about the acting wave system. It is possible-with an analogy to classical wave buoys-to estimate the directional wave spectrum by processing sensor measurements of wave-induced responses (e.g., motions and structural responses) from a ship. Compared to other sources of wave data (e.g., buoys, satellites, third-generation wave models), estimation concepts using the ship itself as a buoy provide the wave spectrum at the exact spatio-temporal point, potentially increasing accuracy and with minimal associated cost. This paper gives an overview of the technology, discusses associated uncertainties, and highlights new developments made for estimating waves via measured ship responses.

Accumulated effects of factors determining plant development from somatic embryos of Abies nordmanniana and Abies bornmuelleriana.

Despite a much later inception of somatic embryogenesis (SE) propagation protocols for gymnosperms than for angiosperm species, SE is becoming increasingly important due to its applications for commercial forestry. For many conifers, there are however still major bottlenecks in the SE plant production process limiting the use of SE for forestry operations, Christmas tree production and research projects. In the present case study, the effects on plant growth from different cultural factors applied during the SE developmental process were studied in two conifer species of high value for Christmas tree production. Seven clones of Abies nordmanniana and two clones of Abies bornmuelleriana were included in the study. Accumulated effects from cultural treatments were recorded from the start of germination of mature embryos of different quality scores through development into plants in the third growing period. Experimental factors of the cultural treatments included were: germination temperature, germination time, light conditions, survival ex vitro and traits for plant growth and vitality. The results reveal that most of the studied experimental factors influenced plant growth during the first three years however their relative importance was different. Plant survival rate at end of the nursery stage was strongly impacted by germination temperature (p<0.001), initial embryo score (p=0.007), clone (p<0.001) and to a lesser extend week of germination (p=0.017). This case-study highlights and quantifies the strong interrelation between the developmental steps of somatic embryogenesis and show the importance of considering all cultural steps when optimizing SE plant production protocols.

Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses.

BACKGROUND: Sequencing data enable the detection of causal loci or single nucleotide polymorphisms (SNPs) highly linked to causal loci to improve genomic prediction. However, until now, studies on integrating such SNPs using a single-step genomic best linear unbiased prediction (ssGBLUP) model are scarce. We investigated the integration of sequencing SNPs selected by association (1262 SNPs) and bioinformatics (2359 SNPs) analyses into the currently used 54K-SNP chip, using three ssGBLUP models which make different assumptions on the distribution of SNP effects: a basic ssGBLUP model, a so-called featured ssGBLUP (ssFGBLUP) model that considered selected sequencing SNPs as a feature genetic component, and a weighted ssGBLUP (ssWGBLUP) model in which the genomic relationship matrix was weighted by the SNP variances estimated from a Bayesian whole-genome regression model, with every 1, 30, or 100 adjacent SNPs within a chromosome region sharing the same variance. We used data on milk production and female fertility in Danish Jersey. In total, 15,823 genotyped and 528,981‬ non-genotyped females born between 1990 and 2013 were used as reference population and 7415 genotyped females and 33,040 non-genotyped females born between 2014 and 2016 were used as validation population. RESULTS: With basic ssGBLUP, integrating SNPs selected from sequencing data improved prediction reliabilities for milk and protein yields, but resulted in limited or no improvement for fat yield and female fertility. Model performances depended on the SNP set used. When using ssWGBLUP with the 54K SNPs, reliabilities for milk and protein yields improved by 0.028 for genotyped animals and by 0.006 for non-genotyped animals compared with ssGBLUP. However, with the SNP set that included SNPs selected from sequencing data, no statistically significant difference in prediction reliability was observed between the three ssGBLUP models. CONCLUSIONS: In summary, when using 54K SNPs, a ssWGBLUP model with a common weight on the SNPs in a given region is a feasible approach for single-trait genetic evaluation. Integrating relevant SNPs selected from sequencing data into the standard SNP chip can improve the reliability of genomic prediction. Based on such SNP data, a basic ssGBLUP model was suggested since no significant improvement was observed from using alternative models such as ssWGBLUP and ssFGBLUP.

Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data.

The availability of whole genome sequencing (WGS) data enables the discovery of causative single nucleotide polymorphisms (SNPs) or SNPs in high linkage disequilibrium with causative SNPs. This study investigated effects of integrating SNPs selected from imputed WGS data into the data of 54K chip on genomic prediction in Danish Jersey. The WGS SNPs, mainly including peaks of quantitative trait loci, structure variants, regulatory regions of genes, and SNPs within genes with strong effects predicted with variant effect predictor, were selected in previous analyses for dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA). Animals genotyped with 54K chip, standard LD chip, and customized LD chip which covered selected WGS SNPs and SNPs in the standard LD chip, were imputed to 54K together with DFS and FRA SNPs. Genomic best linear unbiased prediction (GBLUP) and Bayesian four-distribution mixture models considering 54K and selected WGS SNPs as one (a one-component model) or two separate genetic components (a two-component model) were used to predict breeding values. For milk production traits and mastitis, both DFS (0.025) and FRA (0.029) sets of additional WGS SNPs improved reliabilities, and inclusions of all selected WGS SNPs generally achieved highest improvements of reliabilities (0.034). A Bayesian four-distribution model yielded higher reliabilities than a GBLUP model for milk and protein, but extra gains in reliabilities from using selected WGS SNPs were smaller for a Bayesian four-distribution model than a GBLUP model. Generally, no significant difference was observed between one-component and two-component models, except for using GBLUP models for milk.

MM-131, a bispecific anti-Met/EpCAM mAb, inhibits HGF-dependent and HGF-independent Met signaling through concurrent binding to EpCAM.

Activation of the Met receptor tyrosine kinase, either by its ligand, hepatocyte growth factor (HGF), or via ligand-independent mechanisms, such as MET amplification or receptor overexpression, has been implicated in driving tumor proliferation, metastasis, and resistance to therapy. Clinical development of Met-targeted antibodies has been challenging, however, as bivalent antibodies exhibit agonistic properties, whereas monovalent antibodies lack potency and the capacity to down-regulate Met. Through computational modeling, we found that the potency of a monovalent antibody targeting Met could be dramatically improved by introducing a second binding site that recognizes an unrelated, highly expressed antigen on the tumor cell surface. Guided by this prediction, we engineered MM-131, a bispecific antibody that is monovalent for both Met and epithelial cell adhesion molecule (EpCAM). MM-131 is a purely antagonistic antibody that blocks ligand-dependent and ligand-independent Met signaling by inhibiting HGF binding to Met and inducing receptor down-regulation. Together, these mechanisms lead to inhibition of proliferation in Met-driven cancer cells, inhibition of HGF-mediated cancer cell migration, and inhibition of tumor growth in HGF-dependent and -independent mouse xenograft models. Consistent with its design, MM-131 is more potent in EpCAM-high cells than in EpCAM-low cells, and its potency decreases when EpCAM levels are reduced by RNAi. Evaluation of Met, EpCAM, and HGF levels in human tumor samples reveals that EpCAM is expressed at high levels in a wide range of Met-positive tumor types, suggesting a broad opportunity for clinical development of MM-131.

Bioreactor-based advances in plant tissue and cell culture: challenges and prospects.

Bioreactors are engineered systems capable of supporting a biologically active situation for conducting aerobic or anaerobic biochemical processes. Stability, operational ease, improved nutrient uptake capacity, time- and cost-effectiveness, and large quantities of biomass production, make bioreactors suitable alternatives to conventional plant tissue and cell culture (PTCC) methods. Bioreactors are employed in a wide range of plant research, and have evolved over time. Such technological progress, has led to remarkable achievements in the field of PTCC. Since the classification of bioreactors has been extensively reviewed in numerous reviews, the current article avoids repeating the same material. Alternatively, it aims to highlight the principal advances in the bioreactor hardware s used in PTCC rather than classical categorization. Furthermore, our review summarizes the most significant steps as well as current state-of-the-art of PTCC carried out in various types of bioreactor.

Dual Inhibition of IGF-1R and ErbB3 Enhances the Activity of Gemcitabine and Nab-Paclitaxel in Preclinical Models of Pancreatic Cancer.

Purpose: Insulin-like growth factor receptor 1 (IGF-1R) is critically involved in pancreatic cancer pathophysiology, promoting cancer cell survival and therapeutic resistance. Assessment of IGF-1R inhibitors in combination with standard-of-care chemotherapy, however, failed to demonstrate significant clinical benefit. The aim of this work is to unravel mechanisms of resistance to IGF-1R inhibition in pancreatic cancer and develop novel strategies to improve the activity of standard-of-care therapies.Experimental Design: Growth factor screening in pancreatic cancer cell lines was performed to identify activators of prosurvival PI3K/AKT signaling. The prevalence of activating growth factors and their receptors was assessed in pancreatic cancer patient samples. Effects of a bispecific IGF-1R and ErbB3 targeting antibody on receptor expression, signaling, cancer cell viability and apoptosis, spheroid growth, and in vivo chemotherapy activity in pancreatic cancer xenograft models were determined.Results: Growth factor screening in pancreatic cancer cells revealed insulin-like growth factor 1 (IGF-1) and heregulin (HRG) as the most potent AKT activators. Both growth factors reduced pancreatic cancer cell sensitivity to gemcitabine or paclitaxel in spheroid growth assays. Istiratumab (MM-141), a novel bispecific antibody that blocks IGF-1R and ErbB3, restored the activity of paclitaxel and gemcitabine in the presence of IGF-1 and HRG in vitro Dual IGF-1R/ErbB3 blocking enhanced chemosensitivity through inhibition of AKT phosphorylation and promotion of IGF-1R and ErbB3 degradation. Addition of istiratumab to gemcitabine and nab-paclitaxel improved chemotherapy activity in vivoConclusions: Our findings suggest a critical role for the HRG/ErbB3 axis and support the clinical exploration of dual IGF-1R/ErbB3 blocking in pancreatic cancer. Clin Cancer Res; 24(12); 2873-85. ©2018 AACR.

Systems biology driving drug development: from design to the clinical testing of the anti-ErbB3 antibody seribantumab (MM-121).

The ErbB family of receptor tyrosine kinases comprises four members: epidermal growth factor receptor (EGFR/ErbB1), human EGFR 2 (HER2/ErbB2), ErbB3/HER3, and ErbB4/HER4. The first two members of this family, EGFR and HER2, have been implicated in tumorigenesis and cancer progression for several decades, and numerous drugs have now been approved that target these two proteins. Less attention, however, has been paid to the role of this family in mediating cancer cell survival and drug tolerance. To better understand the complex signal transduction network triggered by the ErbB receptor family, we built a computational model that quantitatively captures the dynamics of ErbB signaling. Sensitivity analysis identified ErbB3 as the most critical activator of phosphoinositide 3-kinase (PI3K) and Akt signaling, a key pro-survival pathway in cancer cells. Based on this insight, we designed a fully human monoclonal antibody, seribantumab (MM-121), that binds to ErbB3 and blocks signaling induced by the extracellular growth factors heregulin (HRG) and betacellulin (BTC). In this article, we present some of the key preclinical simulations and experimental data that formed the scientific foundation for three Phase 2 clinical trials in metastatic cancer. These trials were designed to determine if patients with advanced malignancies would derive benefit from the addition of seribantumab to standard-of-care drugs in platinum-resistant/refractory ovarian cancer, hormone receptor-positive HER2-negative breast cancer, and EGFR wild-type non-small cell lung cancer (NSCLC). From preclinical studies we learned that basal levels of ErbB3 phosphorylation correlate with response to seribantumab monotherapy in mouse xenograft models. As ErbB3 is rapidly dephosphorylated and hence difficult to measure clinically, we used the computational model to identify a set of five surrogate biomarkers that most directly affect the levels of p-ErbB3: HRG, BTC, EGFR, HER2, and ErbB3. Preclinically, the combined information from these five markers was sufficient to accurately predict which xenograft models would respond to seribantumab, and the single-most accurate predictor was HRG. When tested clinically in ovarian, breast and lung cancer, HRG mRNA expression was found to be both potentially prognostic of insensitivity to standard therapy and potentially predictive of benefit from the addition of seribantumab to standard of care therapy in all three indications. In addition, it was found that seribantumab was most active in cancers with low levels of HER2, consistent with preclinical predictions. Overall, our clinical studies and studies of others suggest that HRG expression defines a drug-tolerant cancer cell phenotype that persists in most solid tumor indications and may contribute to rapid clinical progression. To our knowledge, this is the first example of a drug designed and clinically tested using the principles of Systems Biology.

Association analysis for young stock survival index with imputed whole-genome sequence variants in Nordic Holstein cattle.

Identification of the genetic variants associated with calf survival in dairy cattle will aid in the elimination of harmful mutations from the cattle population and the reduction of calf and young stock mortality rates. We used de-regressed estimated breeding values for the young stock survival (YSS) index as response variables in a genome-wide association study with imputed whole-genome sequence variants. A total of 4,610 bulls with estimated breeding values were genotyped with the Illumina BovineSNP50 (Illumina, San Diego, CA) single nucleotide polymorphism (SNP) genotyping array. Genotypes were imputed to whole-genome sequence variants. After quality control, 15,419,550 SNP on 29 Bos taurus autosomes (BTA) were used for association analysis. A modified mixed-model association analysis was used for a genome scan, followed by a linear mixed-model analysis for selected genetic variants. We identified 498 SNP on BTA5 and BTA18 that were associated with the YSS index in Nordic Holstein. The SNP rs440345507 (Chr5:94721790) on BTA5 was the putative causal mutation affecting YSS. Two haplotype-based models were used to identify haplotypes with the largest detrimental effects on YSS index. For each association signal, 1 haplotype region with harmful effects and the lead associated SNP were identified. Detected haplotypes on BTA5 and BTA18 explained 1.16 and 1.20%, respectively, of genetic variance for the YSS index. We examined whether YSS quantitative trait loci (QTL) on BTA5 and BTA18 were associated with stillbirth. YSS QTL on BTA18 overlapped a QTL region for stillbirth, but most likely 2 different causal variants were responsible for these 2 QTL. Four component traits of the YSS index, defined by sex and age, were analyzed separately by the modified mixed-model approach. The same genomic regions were associated with both bull and heifer calf mortality. Several genes (EPS8, LOC100138951, and KLK family genes) contained a lead associated SNP or were included in haplotypes with large detrimental effects on YSS in Nordic Holstein cattle.

HER2+ Cancer Cell Dependence on PI3K vs. MAPK Signaling Axes Is Determined by Expression of EGFR, ERBB3 and CDKN1B.

Understanding the molecular pathways by which oncogenes drive cancerous cell growth, and how dependence on such pathways varies between tumors could be highly valuable for the design of anti-cancer treatment strategies. In this work we study how dependence upon the canonical PI3K and MAPK cascades varies across HER2+ cancers, and define biomarkers predictive of pathway dependencies. A panel of 18 HER2+ (ERBB2-amplified) cell lines representing a variety of indications was used to characterize the functional and molecular diversity within this oncogene-defined cancer. PI3K and MAPK-pathway dependencies were quantified by measuring in vitro cell growth responses to combinations of AKT (MK2206) and MEK (GSK1120212; trametinib) inhibitors, in the presence and absence of the ERBB3 ligand heregulin (NRG1). A combination of three protein measurements comprising the receptors EGFR, ERBB3 (HER3), and the cyclin-dependent kinase inhibitor p27 (CDKN1B) was found to accurately predict dependence on PI3K/AKT vs. MAPK/ERK signaling axes. Notably, this multivariate classifier outperformed the more intuitive and clinically employed metrics, such as expression of phospho-AKT and phospho-ERK, and PI3K pathway mutations (PIK3CA, PTEN, and PIK3R1). In both cell lines and primary patient samples, we observed consistent expression patterns of these biomarkers varies by cancer indication, such that ERBB3 and CDKN1B expression are relatively high in breast tumors while EGFR expression is relatively high in other indications. The predictability of the three protein biomarkers for differentiating PI3K/AKT vs. MAPK dependence in HER2+ cancers was confirmed using external datasets (Project Achilles and GDSC), again out-performing clinically used genetic markers. Measurement of this minimal set of three protein biomarkers could thus inform treatment, and predict mechanisms of drug resistance in HER2+ cancers. More generally, our results show a single oncogenic transformation can have differing effects on cell signaling and growth, contingent upon the molecular and cellular context.

A 0.5-Mbp deletion on bovine chromosome 23 is a strong candidate for stillbirth in Nordic Red cattle.

BACKGROUND: A whole-genome association study of 4631 progeny-tested Nordic Red dairy cattle bulls using imputed next-generation sequencing data revealed a major quantitative trait locus (QTL) that affects birth index (BI) on Bos taurus autosome (BTA) 23. We analyzed this QTL to identify which of the component traits of BI are affected and understand its molecular basis. RESULTS: A genome-wide scan of BI in Nordic Red dairy cattle detected major QTL on BTA6, 14 and 23. The strongest associated single nucleotide polymorphism (SNP) on BTA23 was located at 13,313,896 bp with [Formula: see text]. Analyses of component traits showed that the QTL had a large effect on stillbirth. Based on the 10 most strongly associated SNPs with stillbirth, we constructed a haplotype. Among this haplotype's alleles, HAPQTL had a large negative effect on stillbirth. No animals were found to be homozygous for HAPQTL. Analysis of stillbirth records that were categorized by carrier status for HAPQTL of the sire and maternal grandsire suggested that this haplotype had a recessive mode of inheritance. Illumina BovineHD BeadChip genotypes and genotype intensity data indicated a chromosomal deletion between 12.28 and 12.81 Mbp on BTA23. An independent set of Illumina Bovine50k BeadChip genotypes identified a recessive lethal haplotype that spanned the deleted region. CONCLUSIONS: A deleted region of approximately 500 kb that spans three genes on BTA23 was identified and is a strong candidate QTL with a large effect on BI by increasing stillbirth.

Cyclophosphamide-Mediated Tumor Priming for Enhanced Delivery and Antitumor Activity of HER2-Targeted Liposomal Doxorubicin (MM-302).

Given the bulky nature of nanotherapeutics relative to small molecules, it is hypothesized that effective tumor delivery and penetration are critical barriers to their clinical activity. HER2-targeted PEGylated liposomal doxorubicin (MM-302, HER2-tPLD) is an antibody-liposomal drug conjugate designed to deliver doxorubicin to HER2-overexpressing cancer cells while limiting uptake into nontarget cells. In this work, we demonstrate that the administration and appropriate dose sequencing of cyclophosphamide can improve subsequent MM-302 delivery and enhance antitumor activity in preclinical models without negatively affecting nontarget tissues, such as the heart and skin. We demonstrate that this effect is critically dependent on the timing of cyclophosphamide administration. Furthermore, the effect was found to be unique to cyclophosphamide and related analogues, and not shared by other agents, such as taxanes or eribulin, under the conditions examined. Analysis of the cyclophosphamide-treated tumors suggests that the mechanism for improved MM-302 delivery involves the induction of tumor cell apoptosis, reduction of overall tumor cell density, substantial lowering of interstitial fluid pressure, and increasing vascular perfusion. The novel dosing strategy for cyclophosphamide described herein is readily translatable to standard clinical regimens, represents a potentially significant advance in addressing the drug delivery challenge, and may have broad applicability for nanomedicines. This work formed the basis for clinical evaluation of cyclophosphamide for improving liposome deposition as part of an ongoing phase I clinical trial of MM-302 in HER2-positive metastatic breast cancer.

Heregulin-ErbB3-Driven Tumor Growth Persists in PI3 Kinase Mutant Cancer Cells.

PI3K is frequently mutated in cancer and plays an important role in cell growth and survival. Heregulin (HRG)-mediated autocrine or paracrine signaling through the receptor tyrosine kinase ErbB3 potently activates the PI3K/AKT pathway and has been shown to mediate resistance to a wide variety of anticancer agents. Although PI3K functions downstream of HRG-ErbB3, it is unknown whether activating mutations in PI3K render HRG ineffective. If so, patients with PI3K mutations would not be expected to benefit from ErbB3-directed therapies. Here, we find that a subset of cell lines harboring activating PI3K mutations can be further growth-stimulated by HRG, and this effect is blocked by incubation with seribantumab (MM-121), a monoclonal anti-ErbB3 antibody. Although expression of mutant PI3K in wild-type PI3K cells frequently results in loss of HRG-stimulated growth, some cell lines continue to respond to HRG. In cell lines where HRG-stimulated growth is lost, this loss is invariably accompanied by a reduction in ErbB3 levels, a corresponding increase in basal phosphorylation levels of FOXO-family transcription factors, and a reduction in HRG-induced downstream signaling. Importantly, HRG-stimulated growth is partially rescued by re-expressing ErbB3. This response is blocked by seribantumab, indicating that ErbB3 levels rather than downstream signaling proteins limit HRG-stimulated growth in PI3K mutant cells. Overall, these results suggest that activating mutations in PI3K do not preclude potential benefit from ErbB3-directed therapy, but that it may be important to measure ErbB3 levels in patients with PI3K mutant cancers to determine if they would benefit.

Enhanced Targeting of the EGFR Network with MM-151, an Oligoclonal Anti-EGFR Antibody Therapeutic.

Although EGFR is a validated therapeutic target across multiple cancer indications, the often modest clinical responses to current anti-EGFR agents suggest the need for improved therapeutics. Here, we demonstrate that signal amplification driven by high-affinity EGFR ligands limits the capacity of monoclonal anti-EGFR antibodies to block pathway signaling and cell proliferation and that these ligands are commonly coexpressed with low-affinity EGFR ligands in epithelial tumors. To develop an improved antibody therapeutic capable of overcoming high-affinity ligand-mediated signal amplification, we used a network biology approach comprised of signaling studies and computational modeling of receptor-antagonist interactions. Model simulations suggested that an oligoclonal antibody combination may overcome signal amplification within the EGFR:ERK pathway driven by all EGFR ligands. Based on this, we designed MM-151, a combination of three fully human IgG1 monoclonal antibodies that can simultaneously engage distinct, nonoverlapping epitopes on EGFR with subnanomolar affinities. In signaling studies, MM-151 antagonized high-affinity EGFR ligands more effectively than cetuximab, leading to an approximately 65-fold greater decrease in signal amplification to ERK. In cell viability studies, MM-151 demonstrated antiproliferative activity against high-affinity EGFR ligands, either singly or in combination, while cetuximab activity was largely abrogated under these conditions. We confirmed this finding both in vitro and in vivo in a cell line model of autocrine high-affinity ligand expression. Together, these preclinical studies provide rationale for the clinical study of MM-151 and suggest that high-affinity EGFR ligand expression may be a predictive response marker that distinguishes MM-151 from other anti-EGFR therapeutics.

Across-country test-day model evaluations for Holstein, Nordic Red Cattle, and Jersey.

Three random regression models were developed for routine genetic evaluation of Danish, Finnish, and Swedish dairy cattle. Data included over 169 million test-day records with milk, protein, and fat yield observations from over 8.7 million dairy cows of all breeds. Variance component analyses showed significant differences in estimates between Holstein, Nordic Red Cattle, and Jersey, but only small to moderate differences within a breed across countries. The obtained variance component estimates were used to build, for each breed, their own set of covariance functions. The covariance functions describe the animal effects on milk, protein, and fat yields of the first 3 lactations as 9 different traits, assuming the same heritabilities and a genetic correlation of unity across countries. Only 15, 27, and 7 eigenfunctions with the largest eigenvalues were used to describe additive genetic animal effects and nonhereditary animal effects across lactations and within later lactations, respectively. These reduced-rank covariance functions explained 99.0 to 99.9% of the original variances but reduced the number of animal equations to be solved by 44%. Moderate rank reduction for nonhereditary animal effects and use of one-third-smaller measurement error correlations than obtained from variance component estimation made the models more robust against extreme observations. Estimation of the genetic levels of the countries' subpopulations within a breed was found sensitive to the way the breed effects were modeled, especially for the genetically heterogeneous Nordic Red Cattle. Means to ensure that only additive genetic effects entered the estimated breeding values were to describe the crossbreeding effects by fixed and random cofactors and the calving age effect by an age × breed proportion interaction, and to model phantom parent groups as random effects. To ensure that genetic variances were the same across the 3 countries in breeding value estimation, as suggested by the variance component estimates, the applied multiplicative heterogeneous variance adjustment method had to be tailored using country-specific reference measurement error variances. Results showed the feasibility of across-country genetic evaluation of cows and sires based on original test-day phenotypes. Nevertheless, applying a thorough model validation procedure is essential throughout the model building process to obtain reliable breeding values.

Comprehensive optimization of a single-chain variable domain antibody fragment as a targeting ligand for a cytotoxic nanoparticle.

Antibody-targeted nanoparticles have the potential to significantly increase the therapeutic index of cytotoxic anti-cancer therapies by directing them to tumor cells. Using antibodies or their fragments requires careful engineering because multiple parameters, including affinity, internalization rate and stability, all need to be optimized. Here, we present a case study of the iterative engineering of a single chain variable fragment (scFv) for use as a targeting arm of a liposomal cytotoxic nanoparticle. We describe the effect of the orientation of variable domains, the length and composition of the interdomain protein linker that connects VH and VL, and stabilizing mutations in both the framework and complementarity-determining regions (CDRs) on the molecular properties of the scFv. We show that variable domain orientation can alter cross-reactivity to murine antigen while maintaining affinity to the human antigen. We demonstrate that tyrosine residues in the CDRs make diverse contributions to the binding affinity and biophysical properties, and that replacement of non-essential tyrosines can improve the stability and bioactivity of the scFv. Our studies demonstrate that a comprehensive engineering strategy may be required to identify a scFv with optimal characteristics for nanoparticle targeting.

Preclinical activity of nanoliposomal irinotecan is governed by tumor deposition and intratumor prodrug conversion.

A major challenge in the clinical use of cytotoxic chemotherapeutics is maximizing efficacy in tumors while sparing normal tissue. Irinotecan is used for colorectal cancer treatment but the extent of its use is limited by toxic side effects. Liposomal delivery systems offer tools to modify pharmacokinetic and safety profiles of cytotoxic drugs. In this study, we defined parameters that maximize the antitumor activity of a nanoliposomal formulation of irinotecan (nal-IRI). In a mouse xenograft model of human colon carcinoma, nal-IRI dosing could achieve higher intratumoral levels of the prodrug irinotecan and its active metabolite SN-38 compared with free irinotecan. For example, nal-IRI administered at doses 5-fold lower than free irinotecan achieved similar intratumoral exposure of SN-38 but with superior antitumor activity. Tumor response and pharmacokinetic modeling identified the duration for which concentrations of SN-38 persisted above a critical intratumoral threshold of 120 nmol/L as determinant for antitumor activity. We identified tumor permeability and carboxylesterase activity needed for prodrug activation as critical factors in achieving longer duration of SN-38 in tumors. Simulations varying tumor permeability and carboxylesterase activity predicted a concave increase in tumor SN-38 duration, which was confirmed experimentally in 13 tumor xenograft models. Tumors in which higher SN-38 duration was achieved displayed more robust growth inhibition compared with tumors with lower SN-38 duration, confirming the importance of this factor in drug response. Overall, our work shows how liposomal encapsulation of irinotecan can safely improve its antitumor activity in preclinical models by enhancing accumulation of its active metabolite within the tumor microenvironment.

Insulin-like growth factor promotes cardiac lineage induction in vitro by selective expansion of early mesoderm.

A thorough understanding of the developmental signals that direct pluripotent stem cells (PSCs) toward a cardiac fate is essential for translational applications in disease modeling and therapy. We screened a panel of 44 cytokines/signaling molecules for their ability to enhance Nkx2.5(+) cardiac progenitor cell (CPC) formation during in vitro embryonic stem cell (ESC) differentiation. Treatment of murine ESCs with insulin or insulin-like growth factors (IGF1/2) during early differentiation increased mesodermal cell proliferation and, consequently, CPC formation. Furthermore, we show that downstream mediators of IGF signaling (e.g., phospho-Akt and mTOR) are required for this effect. These data support a novel role for IGF family ligands to expand the developing mesoderm and promote cardiac differentiation. Insulin or IGF treatment could provide an effective strategy to increase the PSC-based generation of CPCs and cardiomyocytes for applications in regenerative medicine.

A 660-Kb deletion with antagonistic effects on fertility and milk production segregates at high frequency in Nordic Red cattle: additional evidence for the common occurrence of balancing selection in livestock.

In dairy cattle, the widespread use of artificial insemination has resulted in increased selection intensity, which has led to spectacular increase in productivity. However, cow fertility has concomitantly severely declined. It is generally assumed that this reduction is primarily due to the negative energy balance of high-producing cows at the peak of lactation. We herein describe the fine-mapping of a major fertility QTL in Nordic Red cattle, and identify a 660-kb deletion encompassing four genes as the causative variant. We show that the deletion is a recessive embryonically lethal mutation. This probably results from the loss of RNASEH2B, which is known to cause embryonic death in mice. Despite its dramatic effect on fertility, 13%, 23% and 32% of the animals carry the deletion in Danish, Swedish and Finnish Red Cattle, respectively. To explain this, we searched for favorable effects on other traits and found that the deletion has strong positive effects on milk yield. This study demonstrates that embryonic lethal mutations account for a non-negligible fraction of the decline in fertility of domestic cattle, and that associated positive effects on milk yield may account for part of the negative genetic correlation. Our study adds to the evidence that structural variants contribute to animal phenotypic variation, and that balancing selection might be more common in livestock species than previously appreciated.