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Objectives: The aim of this study is to describe the incidence and demographics of laryngeal papillomatosis (LP) in Denmark, including sex and age distribution, recurrence rates, and HPV subtypes, using a new method of register identification., Methods: The data were extracted from the Danish Pathology Data Bank using SNOMED codes instead of the usual method using ICD codes from the Danish National Health Register. The derived pathology records were manually verified by three medical doctors. The study period was 1994-2021. Patients were categorized according to age as either juvenile-onset RRP (JoRRP) if <18 years or adult-onset RRP (AoRRP) if 18 years or older., Results: We identified 1819 RRP patients (JoRRP: 56; AoRRP:1763). The overall incidence per 100,000 inhabitants were 0.17 for JoRRP and 1.45 for AoRRP. The vast majority (72%) of the patients were male, but there was no significant difference in age at onset of RRP or recurrence rates between the sexes. Children below 3 years of age had the highest recurrence probability. Extracting data using SNOMED codes resulted in a positive predictive value of 99% regarding total number of biopsies and 98% regarding individuals. The incidence decreased throughout the study period., Conclusion: Comparable incidence and recurrence rates of RRP were found between Denmark and Norway. In this study, the Danish Pathology Register was found to be a highly valuable method for identifying LP patients. The effect of the nationwide HPV vaccination program can be evaluated using this method as the vaccinated cohort is starting to grow older and reproduce., Level of Evidence: Retrospective registry-based national cohort study, level of evidence 3 Laryngoscope, 2024., (© 2024 The Author(s). The Laryngoscope published by Wiley Periodicals LLC on behalf of The American Laryngological, Rhinological and Otological Society, Inc.)

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., (© 2023. The Author(s).)

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., (© 2023. Springer Nature Limited.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Nielsen, Hansen, Hansen, Johansen and Egertsdotter.)

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.

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.

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., Competing Interests: Conflict of interest statement: Several authors are or were employees of Merrimack Pharmaceuticals, Inc. at the time of contributing to the manuscript.

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.

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 vivo Conclusions: 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 ., (©2018 American Association for Cancer Research.)

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., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: The authors declare no conflict of interest.

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.

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.

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., (©2015 American Association for Cancer Research.)

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., (©2015 American Association for Cancer Research.)

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., (©2015 American Association for Cancer Research.)

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., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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.

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., (©2014 American Association for Cancer Research.)

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., (© 2014 AlphaMed Press.)

Although inhibition of the insulin-like growth factor (IGF) signaling pathway was expected to eliminate a key resistance mechanism for EGF receptor (EGFR)-driven cancers, the effectiveness of IGF-I receptor (IGF-IR) inhibitors in clinical trials has been limited. A multiplicity of survival mechanisms are available to cancer cells. Both IGF-IR and the ErbB3 receptor activate the PI3K/AKT/mTOR axis, but ErbB3 has only recently been pursued as a therapeutic target. We show that coactivation of the ErbB3 pathway is prevalent in a majority of cell lines responsive to IGF ligands and antagonizes IGF-IR-mediated growth inhibition. Blockade of the redundant IGF-IR and ErbB3 survival pathways and downstream resistance mechanisms was achieved with MM-141, a tetravalent bispecific antibody antagonist of IGF-IR and ErbB3. MM-141 potency was superior to monospecific and combination antibody therapies and was insensitive to variation in the ratio of IGF-IR and ErbB3 receptors. MM-141 enhanced the biologic impact of receptor inhibition in vivo as a monotherapy and in combination with the mTOR inhibitor everolimus, gemcitabine, or docetaxel, through blockade of IGF-IR and ErbB3 signaling and prevention of PI3K/AKT/mTOR network adaptation.

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.

Using genomic data, lethal recessives may be discovered from haplotypes that are common in the population but never occur in the homozygote state in live animals. This approach only requires genotype data from phenotypically normal (i.e. live) individuals and not from the affected embryos that die. A total of 7,937 Nordic Holstein animals were genotyped with BovineSNP50 BeadChip and haplotypes including 25 consecutive markers were constructed and tested for absence of homozygotes states. We have identified 17 homozygote deficient haplotypes which could be loosely clustered into eight genomic regions harboring possible recessive lethal alleles. Effects of the identified haplotypes were estimated on two fertility traits: non-return rates and calving interval. Out of the eight identified genomic regions, six regions were confirmed as having an effect on fertility. The information can be used to avoid carrier-by-carrier mattings in practical animal breeding. Further, identification of causative genes/polymorphisms responsible for lethal effects will lead to accurate testing of the individuals carrying a lethal allele.

Crosstalk and compensatory circuits within cancer signaling networks limit the activity of most targeted therapies. For example, altered signaling in the networks activated by the ErbB family of receptors, particularly in ERBB2-amplified cancers, contributes to drug resistance. We developed a multiscale systems model of signaling networks in ERBB2-amplified breast cancer to quantitatively investigate relationships between biomarkers (markers of network activity) and combination drug efficacy. This model linked ErbB receptor family signaling to breast tumor growth through two kinase cascades: the PI3K/AKT survival pathway and the Ras/MEK/ERK growth and proliferation pathway. The model predicted molecular mechanisms of resistance to individual therapeutics. In particular, ERBB2-amplified breast cancer cells stimulated with the ErbB3 ligand heregulin were resistant to growth arrest induced by inhibitors of AKT and MEK or coapplication of two inhibitors of the receptor ErbB2 [Herceptin (trastuzumab) and Tykerb (lapatinib)]. We used model simulations to predict the response of ErbB2-positive breast cancer xenografts to combination therapies and verified these predictions in mice. Treatment with trastuzumab, lapatinib, and the ErbB3 inhibitor MM-111 was more effective in inhibiting tumor growth than the combination of AKT and MEK inhibitors and even induced tumor regression, indicating that targeting both ErbB3 and ErbB2 may be an improved therapeutic approach for ErbB2-positive breast cancer patients.

Multispecific antibody-like molecules have the potential to advance the standard-of-care in many human diseases. The design of therapeutic molecules in this class, however, has proven to be difficult and, despite significant successes in preclinical research, only one trivalent antibody, catumaxomab, has demonstrated clinical utility. The challenge originates from the complexity of the design space where multiple parameters such as affinity, avidity, effector functions, and pharmaceutical properties need to be engineered in concurrent fashion to achieve the desired therapeutic efficacy. Here, we present a rapid prototyping approach that allows us to successfully optimize these parameters within one campaign cycle that includes modular design, yeast display of structure focused antibody libraries and high throughput biophysical profiling. We delineate this approach by presenting a design case study of MM-141, a tetravalent bispecific antibody targeting two compensatory signaling growth factor receptors: insulin-like growth factor 1 receptor (IGF-1R) and v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (ErbB3). A MM-141 proof-of-concept (POC) parent molecule did not meet initial design criteria due to modest bioactivity and poor stability properties. Using a combination of yeast display, structured-guided antibody design and library-scale thermal challenge assay, we discovered a diverse set of stable and active anti-IGF-1R and anti-ErbB3 single-chain variable fragments (scFvs). These optimized modules were reformatted to create a diverse set of full-length tetravalent bispecific antibodies. These re-engineered molecules achieved complete blockade of growth factor induced pro-survival signaling, were stable in serum, and had adequate activity and pharmaceutical properties for clinical development. We believe this approach can be readily applied to the optimization of other classes of bispecific or even multispecific antibody-like molecules.

Background: A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population., Methods: The data consisted of de-regressed proofs (DRP) for 5,214 genotyped and 9,374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect., Results: Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods., Conclusions: The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix.

Anthracycline-based regimens are a mainstay of early breast cancer therapy, however their use is limited by cardiac toxicity. The potential for cardiotoxicity is a major consideration in the design and development of combinatorial therapies incorporating anthracyclines and agents that target the HER2-mediated signaling pathway, such as trastuzumab. In this regard, HER2-targeted liposomal doxorubicin was developed to provide clinical benefit by both reducing the cardiotoxicity observed with anthracyclines and enhancing the therapeutic potential of HER2-based therapies that are currently available for HER2-overexpressing cancers. While documenting the enhanced therapeutic potential of HER2-targeted liposomal doxorubicin can be done with existing models, there has been no validated human cardiac cell-based assay system to rigorously assess the cardiotoxicity of anthracyclines. To understand if HER2-targeting of liposomal doxorubicin is possible with a favorable cardiac safety profile, we applied a human stem cell-derived cardiomyocyte platform to evaluate the doxorubicin exposure of human cardiac cells to HER2-targeted liposomal doxorubicin. To the best of our knowledge, this is the first known application of a stem cell-derived system for evaluating preclinical cardiotoxicity of an investigational agent. We demonstrate that HER2-targeted liposomal doxorubicin has little or no uptake into human cardiomyocytes, does not inhibit HER2-mediated signaling, results in little or no evidence of cardiomyocyte cell death or dysfunction, and retains the low penetration into heart tissue of liposomal doxorubicin. Taken together, this data ultimately led to the clinical decision to advance this drug to Phase I clinical testing, which is now ongoing as a single agent in HER2-expressing cancers., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Aberrant expression and activation of EGF receptor (EGFR) has been implicated in the development and progression of many human cancers. As such, targeted therapeutic inhibition of EGFR, for example by antibodies, is a promising anticancer strategy. The overall efficacy of antibody therapies results from the complex interplay between affinity, valence, tumor penetration and retention, and signaling inhibition. To gain better insight into this relationship, we studied a panel of EGFR single-chain Fv (scFv) antibodies that recognize an identical epitope on EGFR but bind with intrinsic monovalent affinities varying by 280-fold. The scFv were converted to Fab and IgG formats, and investigated for their ability to bind EGFR, compete with EGF binding, and inhibit EGF-mediated downstream signaling and proliferation. We observed that the apparent EGFR-binding affinity for bivalent IgG plateaus at intermediate values of intrinsic affinity of the cognate Fab, leading to a biphasic curve describing the ratio of IgG to Fab affinity. Mathematical modeling of antibody-receptor binding indicated that the biphasic effect results from nonequilibrium assay limitations. This was confirmed by further observation that the potency of EGF competition for antibody binding to EGFR improved with both intrinsic affinity and antibody valence. Similarly, both higher intrinsic affinity and bivalent binding improved the potency of antibodies in blocking cellular signaling and proliferation. Overall, our work indicates that higher intrinsic affinity combined with bivalent binding can achieve avidity that leads to greater in vitro potency of antibodies, which may translate into greater therapeutic efficacy., (©2012 AACR.)

The prevalence of ErbB2 amplification in breast cancer has resulted in the heavy pursuit of ErbB2 as a therapeutic target. Although both the ErbB2 monoclonal antibody trastuzumab and ErbB1/ErbB2 dual kinase inhibitor lapatinib have met with success in the clinic, many patients fail to benefit. In addition, the majority of patients who initially respond will unfortunately ultimately progress on these therapies. Activation of ErbB3, the preferred dimerization partner of ErbB2, plays a key role in driving ErbB2-amplified tumor growth, but we have found that current ErbB2-directed therapies are poor inhibitors of ligand-induced activation. By simulating ErbB3 inhibition in a computational model of ErbB2/ErbB3 receptor signaling, we predicted that a bispecific antibody that docks onto ErbB2 and subsequently binds to ErbB3 and blocks ligand-induced receptor activation would be highly effective in ErbB2-amplified tumors, with superior activity to a monospecific ErbB3 inhibitor. We have developed a bispecific antibody suitable for both large scale production and systemic therapy by generating a single polypeptide fusion protein of two human scFv antibodies linked to modified human serum albumin. The resulting molecule, MM-111, forms a trimeric complex with ErbB2 and ErbB3, effectively inhibiting ErbB3 signaling and showing antitumor activity in preclinical models that is dependent on ErbB2 overexpression. MM-111 can be rationally combined with trastuzumab or lapatinib for increased antitumor activity and may in the future complement existing ErbB2-directed therapies to treat resistant tumors or deter relapse.

Immunoliposomes provide a complementary, and in many instances advantageous, drug delivery strategy to antibody-drug conjugates. Their high carrying capacity of 20,000-150,000 drug molecules/liposome, allows for the use of a significantly broader range of moderate-to-high potency small molecule drugs when compared to the comparably few subnanomolar potency maytansinoid- and auristatin-based immunoconjugates. The multivalent display of 5-100 antibody fragments/liposome results in an avidity effect that can make use of even moderate affinity antibodies, as well as a cross-linking of cell surface receptors to induce the internalization required for intracellular drug release and subsequent activity. The underlying liposomal drug must be effectively engineered for long circulating pharmacokinetics and stable in vivo drug retention in order to allow for the drug to be efficiently delivered to the target tissue and take advantage of the site-specific bioavailability provided for by the targeting arm. In this chapter, we describe the rationale for engineering stable immunoliposome-based therapeutics, methods required for preparation of immunoliposomes, as well as for their physicochemical and in vivo characterization., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Monoclonal antibodies are valuable as anticancer therapeutics because of their ability to selectively bind tumor-associated target proteins like receptor tyrosine kinases. Kinetic computational models that capture protein-protein interactions using mass action kinetics are a valuable tool for understanding the binding properties of monoclonal antibodies to their targets. Insights from the models can be used to explore different formats, to set antibody design specifications such as affinity and valence, and to predict potency. Antibody binding to target is driven by both intrinsic monovalent affinity and bivalent avidity. In this chapter, we describe a combined experimental and computational method of assessing the relative importance of these effects on observed drug potency. The method, which we call virtual flow cytometry (VFC), merges experimental measurements of monovalent antibody binding kinetics and affinity curves of antibody-antigen binding into a kinetic computational model of antibody-antigen interaction. The VFC method introduces a parameter χ, the avidity factor, which characterizes the ability of an antibody to cross-link its target through bivalent binding. This simple parameterization of antibody cross-linking allows the model to successfully describe and predict antibody binding curves across a wide variety of experimental conditions, including variations in target expression level and incubation time of antibody with target. We further demonstrate how computational models of antibody binding to cells can be used to predict target inhibition potency. Importantly, we demonstrate computationally that antibodies with high ability to cross-link antigen have significant potency advantages. We also present data suggesting that the parameter χ is a physical, epitope-dependent property of an antibody, and as a result propose that determination of antibody cross-linking and avidity should be incorporated into the screening of antibody panels for therapeutic development. Overall, our results suggest that antibody cross-linking, in addition to monovalent binding affinity, is a key design parameter of antibody performance., (Copyright © 2012 Elsevier Inc. All rights reserved.)

ErbB3 is a critical activator of phosphoinositide 3-kinase (PI3K) signaling in epidermal growth factor receptor (EGFR; ErbB1), ErbB2 [human epidermal growth factor receptor 2 (HER2)], and [hepatocyte growth factor receptor (MET)] addicted cancers, and reactivation of ErbB3 is a prominent method for cancers to become resistant to ErbB inhibitors. In this study, we evaluated the in vivo efficacy of a therapeutic anti-ErbB3 antibody, MM-121. We found that MM-121 effectively blocked ligand-dependent activation of ErbB3 induced by either EGFR, HER2, or MET. Assessment of several cancer cell lines revealed that MM-121 reduced basal ErbB3 phosphorylation most effectively in cancers possessing ligand-dependent activation of ErbB3. In those cancers, MM-121 treatment led to decreased ErbB3 phosphorylation and, in some instances, decreased ErbB3 expression. The efficacy of single-agent MM-121 was also examined in xenograft models. A machine learning algorithm found that MM-121 was most effective against xenografts with evidence of ligand-dependent activation of ErbB3. We subsequently investigated whether MM-121 treatment could abrogate resistance to anti-EGFR therapies by preventing reactivation of ErbB3. We observed that an EGFR mutant lung cancer cell line (HCC827), made resistant to gefitinib by exogenous heregulin, was resensitized by MM-121. In addition, we found that a de novo lung cancer mouse model induced by EGFR T790M-L858R rapidly became resistant to cetuximab. Resistance was associated with an increase in heregulin expression and ErbB3 activation. However, concomitant cetuximab treatment with MM-121 blocked reactivation of ErbB3 and resulted in a sustained and durable response. Thus, these results suggest that targeting ErbB3 with MM-121 can be an effective therapeutic strategy for cancers with ligand-dependent activation of ErbB3.

The signaling network downstream of the ErbB family of receptors has been extensively targeted by cancer therapeutics; however, understanding the relative importance of the different components of the ErbB network is nontrivial. To explore the optimal way to therapeutically inhibit combinatorial, ligand-induced activation of the ErbB-phosphatidylinositol 3-kinase (PI3K) axis, we built a computational model of the ErbB signaling network that describes the most effective ErbB ligands, as well as known and previously unidentified ErbB inhibitors. Sensitivity analysis identified ErbB3 as the key node in response to ligands that can bind either ErbB3 or EGFR (epidermal growth factor receptor). We describe MM-121, a human monoclonal antibody that halts the growth of tumor xenografts in mice and, consistent with model-simulated inhibitor data, potently inhibits ErbB3 phosphorylation in a manner distinct from that of other ErbB-targeted therapies. MM-121, a previously unidentified anticancer therapeutic designed using a systems approach, promises to benefit patients with combinatorial, ligand-induced activation of the ErbB signaling network that are not effectively treated by current therapies targeting overexpressed or mutated oncogenes.

The ErbB signaling pathways, which regulate diverse physiological responses such as cell survival, proliferation and motility, have been subjected to extensive molecular analysis. Nonetheless, it remains poorly understood how different ligands induce different responses and how this is affected by oncogenic mutations. To quantify signal flow through ErbB-activated pathways we have constructed, trained and analyzed a mass action model of immediate-early signaling involving ErbB1-4 receptors (EGFR, HER2/Neu2, ErbB3 and ErbB4), and the MAPK and PI3K/Akt cascades. We find that parameter sensitivity is strongly dependent on the feature (e.g. ERK or Akt activation) or condition (e.g. EGF or heregulin stimulation) under examination and that this context dependence is informative with respect to mechanisms of signal propagation. Modeling predicts log-linear amplification so that significant ERK and Akt activation is observed at ligand concentrations far below the K(d) for receptor binding. However, MAPK and Akt modules isolated from the ErbB model continue to exhibit switch-like responses. Thus, key system-wide features of ErbB signaling arise from nonlinear interaction among signaling elements, the properties of which appear quite different in context and in isolation.

Background: Discovery of tumor-selective antibodies or antibody fragments is a promising approach for delivering therapeutic agents to antigen over-expressing cancers. Therefore it is important to develop methods for the identification of target- and function specific antibodies for effective drug delivery. Here we describe a highly selective and sensitive method for characterizing the internalizing potential of multivalently displayed antibodies or ligands conjugated to liposomes into tumor cells. The assay requires minute amounts of histidine-tagged ligand and relies on the non-covalent coupling of these antibodies to fluorescent liposomes containing a metal ion-chelating lipid. Following incubation of cells with antibody-conjugated liposomes, surface bound liposomes are gently removed and the remaining internalized liposomes are quantitated based on fluorescence in a high throughput manner. We have termed this methodology "Chelated Ligand Internalization Assay", or CLIA., Results: The specificity of the assay was demonstrated with different antibodies to the ErbB-2 and EGF receptors. Antibody-uptake correlated with receptor expression levels in tumor cell lines with a range of receptor expression. Furthermore, Ni-NTA liposomes containing doxorubicin were used to screen for the ability of antibodies to confer target-specific cytotoxicity. Using an anti-ErbB2 single chain Fv (scFv) (F5) antibody, cytotoxicity could be conferred to ErbB2-overexpressing cells; however, a poly(ethylene glycol)-linked lipid (DSPE-PEG-NTA-Ni) was necessary to allow for efficient loading of the drug and to reduce nonspecific drug leakage during the course of the assay., Conclusion: The CLIA method we describe here represents a rapid, sensitive and robust assay for the identification and characterization of tumor-specific antibodies capable of high drug-delivery efficiency when conjugated to liposomal nanocarriers.

Combinatorial control of biological processes, in which redundancy and multifunctionality are the norm, fundamentally limits the therapeutic index that can be achieved by even the most potent and highly selective drugs. Thus, it will almost certainly be necessary to use new 'targeted' pharmaceuticals in combinations. Multicomponent drugs are standard in cytotoxic chemotherapy, but their development has required arduous empirical testing. However, experimentally validated numerical models should greatly aid in the formulation of new combination therapies, particularly those tailored to the needs of specific patients. This perspective focuses on opportunities and challenges inherent in the application of mathematical modeling and systems approaches to pharmacology, specifically with respect to the idea of achieving combinatorial selectivity through use of multicomponent drugs.

We describe evidence for a novel mechanism of monoclonal antibody (MAb)-directed nanoparticle (immunoliposome) targeting to solid tumors in vivo. Long-circulating immunoliposomes targeted to HER2 (ErbB2, Neu) were prepared by the conjugation of anti-HER2 MAb fragments (Fab' or single chain Fv) to liposome-grafted polyethylene glycol chains. MAb fragment conjugation did not affect the biodistribution or long-circulating properties of i.v.-administered liposomes. However, antibody-directed targeting also did not increase the tumor localization of immunoliposomes, as both targeted and nontargeted liposomes achieved similarly high levels (7-8% injected dose/g tumor tissue) of tumor tissue accumulation in HER2-overexpressing breast cancer xenografts (BT-474). Studies using colloidal gold-labeled liposomes showed the accumulation of anti-HER2 immunoliposomes within cancer cells, whereas matched nontargeted liposomes were located predominantly in extracellular stroma or within macrophages. A similar pattern of stromal accumulation without cancer cell internalization was observed for anti-HER2 immunoliposomes in non-HER2-overexpressing breast cancer xenografts (MCF-7). Flow cytometry of disaggregated tumors posttreatment with either liposomes or immunoliposomes showed up to 6-fold greater intracellular uptake in cancer cells due to targeting. Thus, in contrast to nontargeted liposomes, anti-HER2 immunoliposomes achieved intracellular drug delivery via MAb-mediated endocytosis, and this, rather than increased uptake in tumor tissue, was correlated with superior antitumor activity. Immunoliposomes capable of selective internalization in cancer cells in vivo may provide new opportunities for drug delivery.

Tumor necrosis factor (TNF) is a proinflammatory cytokine that induces conflicting pro- and antiapoptotic signals whose relative strengths determine the extent of cell death. TNF receptor (TNFR) has been studied in considerable detail, but it is not known how crosstalk among antagonistic pro- and antiapoptotic signals is achieved. Here we report an experimental and computational analysis of crosstalk between prodeath TNF and prosurvival growth factors in human epithelial cells. By applying classifier-based regression to a cytokine-signaling compendium of approximately 8000 intracellular protein measurements, we demonstrate that cells respond to TNF both directly, via activated TNF receptor, and indirectly, via the sequential release of transforming growth factor-alpha (TGF-alpha), interleukin-1alpha (IL-1alpha), and IL-1 receptor antagonist (IL-1ra). We refer to the contingent and time-varying series of extracellular signals induced by TNF as an "autocrine cascade." Time-dependent crosstalk of synergistic and antagonistic autocrine circuits may serve to link cellular responses to the local environment.

Signal transduction networks are often described by qualitative models that incorporate experimental findings from different cell types. However, a large body of evidence suggests that cell signaling differs substantially from one cell type to the next. Even in cases in which the topology of signaling networks is conserved, different cell types respond differently under the same experimental conditions. In this work we address the problem of developing quantitative and cell-type specific models of cells signaling that incorporate experimental data obtained from protein arrays and mathematical modeling. As a biological system we examine signaling mediated ErbB receptor family as the current literature is very controversial.

Computational biology is impacting drug design and has the potential to revolutionize the drug development process. Here, we describe how data-driven computational models can optimize the design of targeted therapeutics to yield improved safety and efficacy. We propose that, in the future, this approach will improve drug discovery, clinical development, diagnosis and treatment.

Antibody arrays have evolved into powerful tools for quantifying proteins and qualifying their state of activation in complex biological samples. This level of analysis holds tremendous promise as part of a diagnostic or prognostic platform. In particular, multiplex sandwich ELISA assays performed with microarrays in the wells of multi-well plates enable high-throughput analysis of multiple samples with multivariate readouts. Here, we compare and review recent advances in antibody microarray technology and describe its promises towards the systematic analysis of complex biological samples, ranging from profiling patient sera to studying intracellular signaling.

Signal transduction in mammalian cells is mediated by complex networks of interacting proteins. Understanding these networks at a circuit level requires devices to measure the amounts and activities of multiple proteins in a rapid and accurate manner. Ab microarrays have previously been applied to the quantification of labeled recombinant proteins and proteins in serum. The development of methods to analyze intracellular signaling molecules on microarrays would make Ab arrays widely useful in systems biology. Here we describe the fabrication of multiplex Ab arrays sensitive to the amounts and modification states of signal transduction proteins in crude cell lysates and the integration of these arrays with 96-well microtiter plate technology to create microarrays in microplates. We apply the Ab arrays to monitoring the activation, uptake, and signaling of ErbB receptor tyrosine kinases in human tumor cell lines. Data obtained from multicolor ratiometric microarrays correlate well with data obtained by using traditional approaches, but the arrays are faster and simpler to use. The integration of microplate and microarray methods for crude cell lysates should make it possible to identify and analyze small molecule inhibitors of signal transduction processes with unprecedented speed and precision. We demonstrate the future potential of this approach by characterizing the action of the epidermal growth factor receptor inhibitor PD153035 on cells by using Ab arrays; direct scale-up to array-based screening in 96- and 384-well plates should allow small molecules to be identified with specific inhibitory profiles against a signaling network.

Many targeted cancer therapies require endocytosis of the targeting molecule and delivery of the therapeutic agent to the interior of the tumor cell. To generate single chain Fv (scFv) antibodies capable of triggering receptor-mediated endocytosis, we previously developed a method to directly select phage antibodies for internalization by recovering infectious phage from the cytoplasm of the target cell. Using this methodology, we reported the selection of a panel of scFv that were internalized into breast cancer cells from a nonimmune phage library. For this work, an immunotherapeutic was generated from one of these scFv (F5), which bound to ErbB2 (HER2/neu). The F5 scFv was reengineered with a C-terminal cysteine, expressed at high levels in Escherichia coli, and coupled to sterically stabilized liposomes. F5 anti-ErbB2 immunoliposomes were immunoreactive as determined by surface plasmon resonance (SPR) and were avidly internalized by ErbB2-expressing tumor cell lines in proportion to the levels of ErbB2 expression. F5-scFv targeted liposomes containing doxorubicin had antitumor activity and produced significant reduction in tumor size in xenografted mice compared to nontargeted liposomes containing doxorubicin. This strategy should be applicable to generate immunotherapeutics for other malignancies by selecting phage antibodies for internalization into other tumor types and using the scFv to target liposomes or other nanoparticles.

Purpose: Anti-HER2 immunoliposomes combine the tumor-targeting of certain anti-HER2 monoclonal antibodies (MAbs) with the pharmacokinetic and drug delivery capabilities of sterically stabilized liposomes. We previously showed that anti-HER2 immunoliposomes bind efficiently to and internalize in HER2-overexpressing cells in vitro, resulting in intracellular drug delivery., Experimental Design: Here we describe the pharmacokinetics and therapeutic efficacy of anti-HER2 immunoliposomes containing doxorubicin (dox) in a series of animal models., Results: Immunoliposomes displayed long circulation that was identical to that of sterically stabilized liposomes in single- and multiple-dose studies in normal rats. Anti-HER2 immunoliposome-dox produced marked therapeutic results in four different HER2-overexpressing tumor xenograft models, including growth inhibition, regression, and cures. These results demonstrated that encapsulation of dox in anti-HER2 immunoliposomes greatly increased its therapeutic index, both by increasing antitumor efficacy and by reducing systemic toxicity. Immunoliposome-dox was significantly superior to all other treatment conditions tested, including free dox, liposomal dox, and anti-HER2 MAb (trastuzumab). When compared with liposomal dox in eight separate therapy studies in HER2-overexpressing models, immunoliposome delivery produced significantly superior antitumor efficacy in each study (P < 0.0001 to 0.04). Anti-HER2 immunoliposome-dox containing either recombinant human MAb HER2-Fab' or scFv C6.5 yielded comparable therapeutic efficacy. Cure rates for immunoliposome-dox reached 50% (11 of 21) with optimized immunoliposomes and Matrigel-free tumors and overall was 16% (18 of 115) versus no cures (0 of 124) with free dox or liposomal dox. Finally, anti-HER2 immunoliposome-dox was also superior to combinations consisting of free MAb plus free dox or free MAb plus liposomal dox., Conclusions: Anti-HER2 immunoliposomes produced enhanced antitumor efficacy via targeted delivery.