[Management of the cut-out of various forms of osteosynthesis for proximal femoral fractures]

Proximal femoral fractures are a common type of injury in older people. A cut-out of the femoral neck screw after initial osteosynthetic surgery of proximal femoral fractures is a frequent and feared complication. There could be different causes for cut-outs. Osteoporosis and necrosis of the femoral head could be biological reasons for cut-outs; however, mechanical factors, such as reduction, implant position and morphological characteristics of fractures also have a major influence on the cut-out rate. The treatment of the cut-out is often complex and depends on the destruction of the femoral head and the acetabulum. If the bone quality is still good and the head is not completely destroyed, a reosteosynthesis can be performed. Conversion to an endoprosthetic replacement is often the only possibility. Endoprosthetic treatment is often complex and associated with a high morbidity.

Stem-loop-induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control

Activating transcription factor 4 (ATF4) is a master transcriptional regulator of the integrated stress response, leading cells toward adaptation or death. ATF4's induction under stress was thought to be due to delayed translation reinitiation, where the reinitiation-permissive upstream open reading frame 1 (uORF1) plays a key role. Accumulating evidence challenging this mechanism as the sole source of ATF4 translation control prompted us to investigate additional regulatory routes. We identified a highly conserved stem-loop in the uORF2/ATF4 overlap, immediately preceded by a near-cognate CUG, which introduces another layer of regulation in the form of ribosome queuing. These elements explain how the inhibitory uORF2 can be translated under stress, confirming prior observations but contradicting the original regulatory model. We also identified two highly conserved, potentially modified adenines performing antagonistic roles. Finally, we demonstrated that the canonical ATF4 translation start site is substantially leaky scanned. Thus, ATF4's translational control is more complex than originally described, underpinning its key role in diverse biological processes.

Identification of molecular signatures defines the differential proteostasis response in induced spinal and cranial motor neurons

Amyotrophic lateral sclerosis damages proteostasis, affecting spinal and upper motor neurons earlier than a subset of cranial motor neurons. To aid disease understanding, we exposed induced cranial and spinal motor neurons (iCrMNs and iSpMNs) to proteotoxic stress, under which iCrMNs showed superior survival, quantifying the transcriptome and proteome for >8,200 genes at 0, 12, and 36 h. Two-thirds of the proteome showed cell-type differences. iSpMN-enriched proteins related to DNA/RNA metabolism, and iCrMN-enriched proteins acted in the endoplasmic reticulum (ER)/ER chaperone complex, tRNA aminoacylation, mitochondria, and the plasma/synaptic membrane, suggesting that iCrMNs expressed higher levels of proteins supporting proteostasis and neuronal function. When investigating the increased proteasome levels in iCrMNs, we showed that the activity of the 26S proteasome, but not of the 20S proteasome, was higher in iCrMNs than in iSpMNs, even after a stress-induced decrease. We identified Ublcp1 as an iCrMN-specific regulator of the nuclear 26S activity.

Complex changes in serum protein levels in COVID-19 convalescents

The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.

Stem-loop induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control

ATF4 is a master transcriptional regulator of the integrated stress response leading cells towards adaptation or death. ATF4's induction under stress was thought to be mostly due to delayed translation reinitiation, where the reinitiation-permissive uORF1 plays a key role. Accumulating evidence challenging this mechanism as the sole source of ATF4 translation control prompted us to investigate additional regulatory routes. We identified a highly conserved stem-loop in the uORF2/ATF4 overlap, immediately preceded by a near-cognate CUG, which introduces another layer of regulation in the form of ribosome queuing. These elements explain how the inhibitory uORF2 can be translated under stress, confirming prior observations, but contradicting the original regulatory model. We also identified two highly conserved, potentially modified adenines performing antagonistic roles. Finally, we demonstrate that the canonical ATF4 translation start site is substantially leaky-scanned. Thus, ATF4's translational control is more complex than originally described underpinning its key role in diverse biological processes.

Atomic diffusion in liquid gallium and gallium-nickel alloys probed by quasielastic neutron scattering and molecular dynamic simulations

The atomic mobility in liquid pure gallium and a gallium-nickel alloy with 2 at% of nickel is studied experimentally by incoherent quasielastic neutron scattering. The integral diffusion coefficients for all-atom diffusion are derived from the experimental data at different temperatures. DFT-basedab-initiomolecular dynamics (MD) is used to find numerically the diffusion coefficient of liquid gallium at different temperatures, and numerical theory results well agree with the experimental findings at temperatures below 500 K. Machine learning force fields derived fromab-initiomolecular dynamics (AIMD) overestimate within a small 6% error the diffusion coefficient of pure gallium within the genuine AIMD. However, they better agree with experiment for pure gallium and enable the numerical finding of the diffusion coefficient of nickel in the considered melted alloy along with the diffusion coefficient of gallium and integral diffusion coefficient, that agrees with the corresponding experimental values within the error bars. The temperature dependence of the gallium diffusion coefficientDGa(T)follows the Arrhenius law experimentally for all studied temperatures and below 500 K also in the numerical simulations. However,DGa(T)can be well described alternatively by an Einstein-Stokes dependence with the metallic liquid viscosity following the Arrhenius law, especially for the MD simulation results at all studied temperatures. Moreover, a novel variant of the excess entropy scaling theory rationalized our findings for gallium diffusion. Obtained values of the Arrhenius activation energies are profoundly different in the competing theoretical descriptions, which is explained by different temperature-dependent prefactors in the corresponding theories. The diffusion coefficient of gallium is significantly reduced (at the same temperature) in a melted alloy with natural nickel, even at a tiny 2 at% concentration of nickel, as compared with its pure gallium value. This highly surprising behavior contradicts the existing excess entropy scaling theories and opens a venue for further research.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Fractionation of Native Protein Complexes from Mammalian Cells to Determine the Differential Proteasome Activity and Abundance

Eukaryotic cells have different types of proteasomes that differ in size. The smallest proteolytically active particle is the 20S proteasome, which degrades damaged and oxidized proteins; the most common larger particle is the 26S proteasome, which degrades ubiquitylated proteins. The 26S proteasome is formed by a 20S particle capped with one or two regulatory particles, named 19S. While proteasome particles function in the cytoplasm, endoplasmic reticulum, and nucleus, our understanding of their abundance and activity in different cellular compartments is still limited. We provide a three-step protocol that first involves detergent-based fractionation of the cytoplasmic and nuclear compartments, maintaining the integrity and activity of proteasome complexes. Second, the protocol employs native gel separation of large multiprotein complexes in the fractions and a fluorescence-based in-gel quantitation of the activity and different proteasome particles. Finally, the protocol involves protein in-gel denaturation and transfer to a PVDF membrane. Western blotting then detects and quantifies the different proteasome particles. Therefore, the protocol allows for sensitive measurements of activity and abundance of individual proteasome particles from different cellular compartments. It has been optimized for motor neurons induced from mouse embryonic stem cells but can be applied to a variety of mammalian cell lines. Key features • Protocol for fractionation of active nuclear and cytoplasmic proteasome complexes. • Native electrophoresis and fluorescence-based in-gel activity assay, which allows the visualization and quantification of active complexes within the acrylamide gel matrix. • In-gel protein denaturation followed by transfer of complexes to PVDF membrane, which allows the analysis of complexes' abundance using antibodies.

Ring Finger 149-Related Is an FGF/MAPK-Independent Regulator of Pharyngeal Muscle Fate Specification

During embryonic development, cell-fate specification gives rise to dedicated lineages that underlie tissue formation. In olfactores, which comprise tunicates and vertebrates, the cardiopharyngeal field is formed by multipotent progenitors of both cardiac and branchiomeric muscles. The ascidian Ciona is a powerful model to study cardiopharyngeal fate specification with cellular resolution, as only two bilateral pairs of multipotent cardiopharyngeal progenitors give rise to the heart and to the pharyngeal muscles (also known as atrial siphon muscles, ASM). These progenitors are multilineage primed, in as much as they express a combination of early ASM- and heart-specific transcripts that become restricted to their corresponding precursors, following oriented and asymmetric divisions. Here, we identify the primed gene ring finger 149 related (Rnf149-r), which later becomes restricted to the heart progenitors, but appears to regulate pharyngeal muscle fate specification in the cardiopharyngeal lineage. CRISPR/Cas9-mediated loss of Rnf149-r function impairs atrial siphon muscle morphogenesis, and downregulates Tbx1/10 and Ebf, two key determinants of pharyngeal muscle fate, while upregulating heart-specific gene expression. These phenotypes are reminiscent of the loss of FGF/MAPK signaling in the cardiopharyngeal lineage, and an integrated analysis of lineage-specific bulk RNA-seq profiling of loss-of-function perturbations has identified a significant overlap between candidate FGF/MAPK and Rnf149-r target genes. However, functional interaction assays suggest that Rnf149-r does not directly modulate the activity of the FGF/MAPK/Ets1/2 pathway. Instead, we propose that Rnf149-r acts both in parallel to the FGF/MAPK signaling on shared targets, as well as on FGF/MAPK-independent targets through (a) separate pathway(s).

Re-mining serum proteomics data reveals extensive post-translational modifications upon Zika and dengue infection

Zika virus (ZIKV) and dengue virus (DENV) are two closely related flaviviruses with similar symptoms. However, due to the implications of ZIKV infections for pregnancy outcomes, understanding differences in their molecular impact on the host is of high interest. Viral infections change the host proteome, including post-translational modifications. As modifications are diverse and of low abundance, they typically require additional sample processing which is not feasible for large cohort studies. Therefore, we tested the potential of next-generation proteomics data in its ability to prioritize specific modifications for later analysis. We re-mined published mass spectra from 122 serum samples from ZIKV and DENV patients for the presence of phosphorylated, methylated, oxidized, glycosylated/glycated, sulfated, and carboxylated peptides. We identified 246 modified peptides with significantly differential abundance in ZIKV and DENV patients. Amongst these, methionine-oxidized peptides from apolipoproteins and glycosylated peptides from immunoglobulin proteins were more abundant in ZIKV patient serum and generate hypotheses on the potential roles of the modification in the infection. The results demonstrate how data-independent acquisition techniques can help prioritize future analyses of peptide modifications.

Extracellular matrix stiffness regulates degradation of MST2 via SCF βTrCP

The Hippo pathway plays central roles in relaying mechanical signals during development and tumorigenesis, but how the proteostasis of the Hippo kinase MST2 is regulated remains unknown. Here, we found that chemical inhibition of proteasomal proteolysis resulted in increased levels of MST2 in human breast epithelial cells. MST2 binds SCFβTrCP E3 ubiquitin ligase and silencing βTrCP resulted in MST2 accumulation. Site-directed mutagenesis combined with computational molecular dynamics studies revealed that βTrCP binds MST2 via a non-canonical degradation motif. Additionally, stiffer extracellular matrix, as well as hyperactivation of integrins resulted in enhanced MST2 degradation mediated by integrin-linked kinase (ILK) and actomyosin stress fibers. Our study uncovers the underlying biochemical mechanisms controlling MST2 degradation and underscores how alterations in the microenvironment rigidity regulate the proteostasis of a central Hippo pathway component.

Proteomic Signatures of the Serological Response to Influenza Vaccination in a Large Human Cohort Study

The serological response to the influenza virus vaccine is highly heterogeneous for reasons that are not entirely clear. While the impact of demographic factors such as age, body mass index (BMI), sex, prior vaccination and titer levels are known to impact seroconversion, they only explain a fraction of the response. To identify signatures of the vaccine response, we analyzed 273 protein levels from 138 serum samples of influenza vaccine recipients (2019-2020 season). We found that levels of proteins functioning in cholesterol transport were positively associated with seroconversion, likely linking to the known impact of BMI. When adjusting seroconversion for the demographic factors, we identified additional, unexpected signatures: proteins regulating actin cytoskeleton dynamics were significantly elevated in participants with high adjusted seroconversion. Viral strain specific analysis showed that this trend was largely driven by the H3N2 strain. Further, we identified complex associations between adjusted seroconversion and other factors: levels of proteins of the complement system associated positively with adjusted seroconversion in younger participants, while they were associated negatively in the older population. We observed the opposite trends for proteins of high density lipoprotein remodeling, transcription, and hemostasis. In sum, careful integrative modeling can extract new signatures of seroconversion from highly variable data that suggest links between the humoral response as well as immune cell communication and migration.

Meiotic DNA breaks activate a streamlined phospho-signaling response that largely avoids protein-level changes

Meiotic cells introduce a numerous programmed DNA breaks into their genome to stimulate meiotic recombination and ensure controlled chromosome inheritance and fertility. A checkpoint network involving key kinases and phosphatases coordinates the repair of these DNA breaks, but the precise phosphorylation targets remain poorly understood. It is also unknown whether meiotic DNA breaks change gene expression akin to the canonical DNA-damage response. To address these questions, we analyzed the meiotic DNA break response in Saccharomyces cerevisiae using multiple systems-level approaches. We identified 332 DNA break-dependent phosphorylation sites, vastly expanding the number of known events during meiotic prophase. Less than half of these events occurred in recognition motifs for the known meiotic checkpoint kinases Mec1 (ATR), Tel1 (ATM), and Mek1 (CHK2), suggesting that additional kinases contribute to the meiotic DNA-break response. We detected a clear transcriptional program but detected only very few changes in protein levels. We attribute this dichotomy to a decrease in transcript levels after meiotic entry that dampens the effects of break-induced transcription sufficiently to cause only minimal changes in the meiotic proteome.

PL01.5.A Towards modernizing intraoperative histopathological assessment in brain and spinal tumors - Comparison of the novel Stimulated Raman Histology with conventional H&E staining

Background

By intraoperative analysis of fresh frozen sections, neuropathologists provide important information of different brain and spinal tumors to the neurosurgeon during surgery. This facilitates characterization of these tumors intraoperatively to optimize the surgical strategy and patient management. However, preparation and staining are time consuming using conventional techniques of intraoperative fresh frozen section. Stimulated Raman Histology (SRH) was introduced as novel technique providing high-resolution digital images of unprocessed tissue samples directly in the operating room comparable to conventional histopathological images. Additionally, SRH images are fast and easily accessible by neuropathologists. Recently, first data showed promising results on the accuracy and feasibility of SRH in comparison to conventional H&E staining.

Material and Methods

In a time period of 4 months, patients with different brain or spinal tumors who underwent neurosurgical resection or open/stereotactic biopsy at the Dept. of Neurosurgery, Medical University Vienna were included in this study. Tumor tissue samples were collected intraoperatively whenever safely possible for analysis with SRH. Subsequently, unprocessed tissue samples were scanned by SRH, and intraoperative histopathological images were created directly in the operating room within a few minutes. All collected tissue samples were then sent for routine neuropathological workup. In an overall analysis, SRH images and H&E staining of all patients were analyzed separately by two board certified neuropathologists. Information on age, localization and suspected diagnosis was provided in each case in order to simulate the situation of intraoperative fresh frozen section. In a next step the technical feasibility and diagnostic accuracy of SRH was calculated.

Results

In this study, tissue samples of 95 patients who underwent neurosurgical resection or open/stereotactic biopsy of different brain and spinal tumors were collected intraoperatively and analyzed by SRH. In total, 31 gliomas, 30 meningiomas, 19 metastases, 7 neurinomas and 8 rare tumors were analyzed. In the present study the use of SRH was technically feasible in all cases and could be easily integrated in the neurosurgical workflow to provide rapid digital histopathological images for the analyzing neuropathologists. According to our data, SRH provided high diagnostic accuracy (>95%) in the investigated different brain and spinal tumors.

Conclusion

Based on our preliminary data the technical use of SRH is feasible and showed a high rate of diagnostic accuracy in a large series of different brain and spinal tumors. By using this promising technique, we intend to modernize intraoperative histopathological assessment by providing rapid digital images of brain and spinal tumors to optimize the management of these patients.

Prevaccination Glycan Markers of Response to an Influenza Vaccine Implicate the Complement Pathway

A key to improving vaccine design and vaccination strategy is to understand the mechanism behind the variation of vaccine response with host factors. Glycosylation, a critical modulator of immunity, has no clear role in determining vaccine responses. To gain insight into the association between glycosylation and vaccine-induced antibody levels, we profiled the pre- and postvaccination serum protein glycomes of 160 Caucasian adults receiving the FLUZONE influenza vaccine during the 2019-2020 influenza season using lectin microarray technology. We found that prevaccination levels of Lewis A antigen (Lea) are significantly higher in nonresponders than responders. Glycoproteomic analysis showed that Lea-bearing proteins are enriched in complement activation pathways, suggesting a potential role of glycosylation in tuning the activities of complement proteins, which may be implicated in mounting vaccine responses. In addition, we observed a postvaccination increase in sialyl Lewis X antigen (sLex) and a decrease in high mannose glycans among high responders, which were not observed in nonresponders. These data suggest that the immune system may actively modulate glycosylation as part of its effort to establish effective protection postvaccination.

New Views of Old Proteins: Clarifying the Enigmatic Proteome

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

Evaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine

The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.

New horizons in the stormy sea of multimodal single-cell data integration

While measurements of RNA expression have dominated the world of single-cell analyses, new single-cell techniques increasingly allow collection of different data modalities, measuring different molecules, structural connections, and intermolecular interactions. Integrating the resulting multimodal single-cell datasets is a new bioinformatics challenge. Equally important, it is a new experimental design challenge for the bench scientist, who is not only choosing from a myriad of techniques for each data modality but also faces new challenges in experimental design. The ultimate goal is to design, execute, and analyze multimodal single-cell experiments that are more than just descriptive but enable the learning of new causal and mechanistic biology. This objective requires strict consideration of the goals behind the analysis, which might range from mapping the heterogeneity of a cellular population to assembling system-wide causal networks that can further our understanding of cellular functions and eventually lead to models of tissues and organs. We review steps and challenges toward this goal. Single-cell transcriptomics is now a mature technology, and methods to measure proteins, lipids, small-molecule metabolites, and other molecular phenotypes at the single-cell level are rapidly developing. Integrating these single-cell readouts so that each cell has measurements of multiple types of data, e.g., transcriptomes, proteomes, and metabolomes, is expected to allow identification of highly specific cellular subpopulations and to provide the basis for inferring causal biological mechanisms.

"Structuromics": another step toward a holistic view of the cell

Large-scale mapping of protein structures and their different states is crucial for gaining a mechanistic understanding of proteome function and regulation. In this issue of Cell, Cappelletti et al. achieve such a feat and identify hundreds of protein structural changes in response to outside stressors, providing a rich "structuromics" resource characterizing cellular adaptation.

Integrated multi-omics analysis of RB-loss identifies widespread cellular programming and synthetic weaknesses

Inactivation of RB is one of the hallmarks of cancer, however gaps remain in our understanding of how RB-loss changes human cells. Here we show that pRB-depletion results in cellular reprogramming, we quantitatively measured how RB-depletion altered the transcriptional, proteomic and metabolic output of non-tumorigenic RPE1 human cells. These profiles identified widespread changes in metabolic and cell stress response factors previously linked to E2F function. In addition, we find a number of additional pathways that are sensitive to RB-depletion that are not E2F-regulated that may represent compensatory mechanisms to support the growth of RB-depleted cells. To determine whether these molecular changes are also present in RB1^-/- tumors, we compared these results to Retinoblastoma and Small Cell Lung Cancer data, and identified widespread conservation of alterations found in RPE1 cells. To define which of these changes contribute to the growth of cells with de-regulated E2F activity, we assayed how inhibiting or depleting these proteins affected the growth of RB1^-/- cells and of Drosophila E2f1-RNAi models in vivo. From this analysis, we identify key metabolic pathways that are essential for the growth of pRB-deleted human cells.

Meeting the UK Government's prevention agenda: primary care practitioners can be trained in skills to prevent disease and support self-management

Aims:

The NHS Long Term Plan has a prevention focus and ambition to support patients to self-manage disease through improving health behaviours. An essential requirement of self-management is behaviour change, but many practitioners have not been trained in skills to support behaviour change. ‘Healthy Conversation Skills’ (HCS) training was developed at the University of Southampton for this purpose. This article reports on a pilot study that aimed to assess the feasibility of primary care practitioners adopting HCS in their routine practice. It describes their experiences and level of competence post-training.

Methods:

Health Education England (Wessex) commissioned HCS training for 18 primary care practitioners. Fifteen of these practitioners were subsequently observed in their consultations at one or two time points; face-to-face semi-structured, reflective feedback interviews were conducted immediately following the observations. Practitioners’ HCS competence was assessed from the observations and interviews using a previously developed and published coding rubric. The interview data were analysed thematically to understand practitioners’ experiences of using the new skills.

Results:

Practitioners demonstrated competence in embedding the skills into their routine practice following HCS training. They reflected on how patients liked being asked questions, the usefulness of setting SMARTER (Specific, Measured, Action-oriented, Realistic, Timed, Evaluated and Reviewed) goals and the power of listening. They could also identify facilitators of skill use and ways to overcome challenges such as patients with competing priorities and organisational constraints. They found the skills valuable as a way of empowering patients to make changes to manage their own health.

Conclusions:

HCS are acceptable to primary care practitioners, can be readily adopted into their routine consultations and are a helpful strategy for supporting patients to make changes. HCS training has the potential to be a sustainable, scalable and effective way of contributing to the prevention agenda by supporting disease self-management, and hence of addressing today’s epidemic of lifestyle-related conditions.

Simple Method to Quantify Protein Abundances from 1000 Cells

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

Improving pregnant women's diet and physical activity behaviours: the emergent role of health identity

Background

Women who gain too much weight in pregnancy are at increased risk of disease and of having children with increased risk. Interventions to improve health behaviours are usually designed for a general population of pregnant women, and trial outcomes show an average impact that does not represent the differences between individuals. To inform the development of future interventions, this study explored the factors that influenced women’s diet and physical activity during pregnancy and aimed to identify the needs of these women with regards to lifestyle support.

Methods

Women who completed a trial of vitamin D supplementation and nurse support in pregnancy were invited to take part in an interview. Seventeen women were interviewed about their lifestyles during pregnancy, the support they had, and the support they wanted. Interview transcripts were coded thematically and analysed to understand the factors that influenced the diets and physical activity levels of these women and their engagement with resources that could provide support.

Results

Women identified barriers to eating well or being physically active, and pregnancy-specific issues like nausea and pain were common. Women’s interest in maintaining a healthy lifestyle and their engagement with lifestyle support was related to the extent to which they self-identified as healthy people. Health-disengaged women were disinterested in talking about their lifestyles while health-focused women did not feel that they needed extra support. Women between these ends of the ‘health identity’ spectrum were interested in improving their health, and were able to identify barriers as well as sources of support.

Conclusions

Lifestyle interventions in pregnancy should be adapted to meet the needs of individuals with different health identities, and encouraging a change in health identity may be one way of supporting sustained change in health behaviours.

Chemical chaperones reverse early suppression of regulatory circuits during unfolded protein response in B cells from common variable immunodeficiency patients

B cells orchestrate pro-survival and pro-apoptotic inputs during unfolded protein response (UPR) to translate, fold, sort, secrete and recycle immunoglobulins. In common variable immunodeficiency (CVID) patients, activated B cells are predisposed to an overload of abnormally processed, misfolded immunoglobulins. Using highly accurate transcript measurements, we show that expression of UPR genes and immunoglobulin chains differs qualitatively and quantitatively during the first 4 h of chemically induced UPR in B cells from CVID patients and a healthy subject. We tested thapsigargin or tunicamycin as stressors and 4-phenylbutyrate, dimethyl sulfoxide and tauroursodeoxycholic acid as chemical chaperones. We found an early and robust decrease of the UPR upon endoplasmic reticulum (ER) stress in CVID patient cells compared to the healthy control consistent with the disease phenotype. The chemical chaperones increased the UPR in the CVID patient cells in response to the stressors, suggesting that misfolded immunoglobulins were stabilized. We suggest that the AMP-dependent transcription factor alpha branch of the UPR is disturbed in CVID patients, underlying the observed expression behavior.

A protein-centric approach for exome variant aggregation enables sensitive association analysis with clinical outcomes

Somatic mutations are early drivers of tumorigenesis and tumor progression. However, the mutations typically occur at variable positions across different individuals, resulting in the data being too sparse to test meaningful associations between variants and phenotypes. To overcome this challenge, we devised a novel approach called Gene-to-Protein-to-Disease (GPD) which accumulates variants into new sequence units as the degree of genetic assault on structural or functional units of each protein. The variant frequencies in the sequence units were highly reproducible between two large cancer cohorts. Survival analysis identified 232 sequence units in which somatic mutations had deleterious effects on overall survival, including consensus driver mutations obtained from multiple calling algorithms. By contrast, around 76% of the survival predictive units had been undetected by conventional gene-level analysis. We demonstrate the ability of these signatures to separate patient groups according to overall survival, therefore, providing novel prognostic tools for various cancers. GPD also identified sequence units with somatic mutations whose impact on survival was modified by the occupancy of germline variants in the surrounding regions. The findings indicate that a patient's genetic predisposition interacts with the effect of somatic mutations on survival outcomes in some cancers.

Polyubiquitin Chains Linked by Lysine Residue 48 (K48) Selectively Target Oxidized Proteins In Vivo

Aims: Ubiquitin is a highly conserved protein modifier that heavily accumulates during the oxidative stress response. Here, we investigated the role of the ubiquitination system, particularly at the linkage level, in the degradation of oxidized proteins. The function of ubiquitin in the removal of oxidized proteins remains elusive because of the wide range of potential targets and different roles that polyubiquitin chains play. Therefore, we describe in detail the dynamics of the K48 ubiquitin response as the canonical signal for protein degradation. We identified ubiquitin targets and defined the relationship between protein ubiquitination and oxidation during the stress response. Results: Combining oxidized protein isolation, linkage-specific ubiquitination screens, and quantitative proteomics, we found that K48 ubiquitin accumulated at both the early and late phases of the stress response. We further showed that a fraction of oxidized proteins are conjugated with K48 ubiquitin. We identified ∼750 ubiquitinated proteins and ∼400 oxidized proteins that were modified during oxidative stress, and around half of which contain both modifications. These proteins were highly abundant and function in translation and energy metabolism. Innovation and Conclusion: Our work showed for the first time that K48 ubiquitin modifies a large fraction of oxidized proteins, demonstrating that oxidized proteins can be targeted by the ubiquitin/proteasome system. We suggest that oxidized proteins that rapidly accumulate during stress are subsequently ubiquitinated and degraded during the late phase of the response. This delay between oxidation and ubiquitination may be necessary for reprogramming protein dynamics, restoring proteostasis, and resuming cell growth.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery

Computational tools for multiomics data integration have usually been designed for unsupervised detection of multiomics features explaining large phenotypic variations. To achieve this, some approaches extract latent signals in heterogeneous data sets from a joint statistical error model, while others use biological networks to propagate differential expression signals and find consensus signatures. However, few approaches directly consider molecular interaction as a data feature, the essential linker between different omics data sets. The increasing availability of genome-scale interactome data connecting different molecular levels motivates a new class of methods to extract interactive signals from multiomics data. Here we developed iOmicsPASS, a tool to search for predictive subnetworks consisting of molecular interactions within and between related omics data types in a supervised analysis setting. Based on user-provided network data and relevant omics data sets, iOmicsPASS computes a score for each molecular interaction, and applies a modified nearest shrunken centroid algorithm to the scores to select densely connected subnetworks that can accurately predict each phenotypic group. iOmicsPASS detects a sparse set of predictive molecular interactions without loss of prediction accuracy compared to alternative methods, and the selected network signature immediately provides mechanistic interpretation of the multiomics profile representing each sample group. Extensive simulation studies demonstrate clear benefit of interaction-level modeling. iOmicsPASS analysis of TCGA/CPTAC breast cancer data also highlights new transcriptional regulatory network underlying the basal-like subtype as positive protein markers, a result not seen through analysis of individual omics data.

Stem cell-derived cranial and spinal motor neurons reveal proteostatic differences between ALS resistant and sensitive motor neurons

In amyotrophic lateral sclerosis (ALS) spinal motor neurons (SpMN) progressively degenerate while a subset of cranial motor neurons (CrMN) are spared until late stages of the disease. Using a rapid and efficient protocol to differentiate mouse embryonic stem cells (ESC) to SpMNs and CrMNs, we now report that ESC-derived CrMNs accumulate less human (h)SOD1 and insoluble p62 than SpMNs over time. ESC-derived CrMNs have higher proteasome activity to degrade misfolded proteins and are intrinsically more resistant to chemically-induced proteostatic stress than SpMNs. Chemical and genetic activation of the proteasome rescues SpMN sensitivity to proteostatic stress. In agreement, the hSOD1 G93A mouse model reveals that ALS-resistant CrMNs accumulate less insoluble hSOD1 and p62-containing inclusions than SpMNs. Primary-derived ALS-resistant CrMNs are also more resistant than SpMNs to proteostatic stress. Thus, an ESC-based platform has identified a superior capacity to maintain a healthy proteome as a possible mechanism to resist ALS-induced neurodegeneration.

Nucleobindins and encoded peptides: From cell signaling to physiology

Nucleobindins (NUCBs) are DNA and calcium binding, secreted proteins with various signaling functions. Two NUCBs, nucleobindin-1 (NUCB1) and nucleobindin-2 (NUCB2), were discovered during the 1990s. These two peptides are shown to have diverse functions, including the regulation of inflammation and bone formation, among others. In 2006, Oh-I and colleagues discovered that three peptides encoded within the NUCB2 could be processed by prohormone convertases. These peptides were named nesfatin-1, 2 and 3, mainly due to the satiety and fat influencing properties of nesfatin-1. However, it was found that nesfatin-2 and -3 have no such effects. Nesfatin-1, especially its mid-segment, is very highly conserved across vertebrates. Although the receptor(s) that mediate nesfatin-1 effects are currently unknown, it is now considered an endogenous peptide with multiple functions, affecting central and peripheral tissues to regulate metabolism, reproduction, endocrine and other functions. We recently identified a nesfatin-1-like peptide (NLP) encoded within the NUCB1. Like nesfatin-1, NLP suppressed feed intake in mice and fish, and stimulated insulin secretion from pancreatic beta cells. There is considerable evidence available to indicate that nucleobindins and its encoded peptides are multifunctional regulators of cell biology and whole animal physiology. This review aims to briefly discuss the structure, distribution, functions and mechanism of action nucleobindins and encoded peptides.

Abstract P4-01-07: A comprehensive liquid biopsy in patients undergoing neoadjuvant therapy

Background: Precision medicine is revolutionizing breast cancer (BC) care. Comprehensive liquid biopsies are a tool for personalized care in patients with locally advanced breast cancer (LABC). Identifying robust biomarkers as part of a comprehensive liquid biopsy to predict response to treatment is of immense clinical interest.

Methods: After obtaining IRB approval, serial blood samples were collected from patients with LABC undergoing neoadjuvant therapy. Paired biopsies were collected prior to treatment and were sent to Foundation Medicine for next-generation sequencing (NGS). We used a sized-base microfilter technology to capture circulating tumor cells (CTCs) and circulating cancer associated fibroblasts (cCAFs). Patients with one or more CTCs or cCAFs were deemed positive for these tests. Additionally, in collaboration with Foundation Medicine, we extracted circulating tumor DNA (ctDNA) and we analyzed it using the FoundationACT platform. Patients with a detectable genomic alteration in their plasma were considered as having a positive ctDNA test. Our primary objective is to determine if a comprehensive liquid biopsy can serve as a prognostic marker of pathologic complete response (pCR).

Results: For this analysis we describe our findings in the initial blood draw of the first 18 patients enrolled. The mean age is 54 years (38-70). All patients who had their tumors sequenced had a detectable mutation. Consistent with the findings of others, we found TP53 mutations to be the most prevalent at 83.3%. We found that 44% of patients had ctDNA, 68.4% had cCAFs and 78.9% had CTCs. Many patients also had clusters of cells, consisting of one cell type, or co-clusters, consisting of both. 38.9% had CTC clusters, 16.7% had cCAF clusters and 16.7% had co-clusters (CTCs and cCAFs together). Some patients with CTCs did not have cCAFs and vice versa. The number of CTCs and cCAFS did not correlate with stage of disease or receptor status.

Conclusions: We describe a comprehensive liquid biopsy combining a sized-based microfilter technology for CTC and cCAFs identification and the FoundationACT platform for ctDNA analysis is feasible and these biomarkers can be detected in patients with LABC prior to the initiation of neoadjuvant therapy. Our study is accruing rapidly, and we will update our results with the longitudinal collection and the prognostic value of a comprehensive liquid biopsy at the time of the meeting.

Citation Format: Sandoval Leon AC, Medina Saenz K, Miller P, Benson A, Calfa C, Mahtani R, Slingerland J, Perez A, Vogel C, Valdes-Albini F, El-Ashry D, Lippman M. A comprehensive liquid biopsy in patients undergoing neoadjuvant therapy [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-01-07.

Identical and Nonidentical Twins: Risk and Factors Involved in Development of Islet Autoimmunity and Type 1 Diabetes

OBJECTIVE

There are variable reports of risk of concordance for progression to islet autoantibodies and type 1 diabetes in identical twins after one twin is diagnosed. We examined development of positive autoantibodies and type 1 diabetes and the effects of genetic factors and common environment on autoantibody positivity in identical twins, nonidentical twins, and full siblings.

RESEARCH DESIGN AND METHODS

Subjects from the TrialNet Pathway to Prevention Study (N = 48,026) were screened from 2004 to 2015 for islet autoantibodies (GAD antibody [GADA], insulinoma-associated antigen 2 [IA-2A], and autoantibodies against insulin [IAA]). Of these subjects, 17,226 (157 identical twins, 283 nonidentical twins, and 16,786 full siblings) were followed for autoantibody positivity or type 1 diabetes for a median of 2.1 years.

RESULTS

At screening, identical twins were more likely to have positive GADA, IA-2A, and IAA than nonidentical twins or full siblings (all P < 0.0001). Younger age, male sex, and genetic factors were significant factors for expression of IA-2A, IAA, one or more positive autoantibodies, and two or more positive autoantibodies (all P ≤ 0.03). Initially autoantibody-positive identical twins had a 69% risk of diabetes by 3 years compared with 1.5% for initially autoantibody-negative identical twins. In nonidentical twins, type 1 diabetes risk by 3 years was 72% for initially multiple autoantibody-positive, 13% for single autoantibody-positive, and 0% for initially autoantibody-negative nonidentical twins. Full siblings had a 3-year type 1 diabetes risk of 47% for multiple autoantibody-positive, 12% for single autoantibody-positive, and 0.5% for initially autoantibody-negative subjects.

CONCLUSIONS

Risk of type 1 diabetes at 3 years is high for initially multiple and single autoantibody-positive identical twins and multiple autoantibody-positive nonidentical twins. Genetic predisposition, age, and male sex are significant risk factors for development of positive autoantibodies in twins.

Site-Specific K63 Ubiquitinomics Provides Insights into Translation Regulation under Stress

During oxidative stress, K63-linked polyubiquitin chains modify a variety of proteins including ribosomes. Knowledge of the precise sites of K63 ubiquitin is key to understand its function during the response to stress. To identify the sites of K63 ubiquitin, we developed a new mass spectrometry based method that quantified >1100 K63 ubiquitination sites in yeast that responded to oxidative stress induced by H₂O₂. We determined that under stress, K63 ubiquitin-modified proteins were involved in several cellular functions including ion transport, protein trafficking, and translation. The most abundant ubiquitin sites localized to the head of the 40S subunit of the ribosome, modified assembled polysomes, and affected the binding of translation factors. The results suggested a new pathway of post-initiation control of translation during oxidative stress and illustrated the importance of high-resolution mapping of noncanonical ubiquitination events.

EBprotV2: A Perseus Plugin for Differential Protein Abundance Analysis of Labeling-Based Quantitative Proteomics Data

We present EBprotV2, a Perseus plugin for peptide-ratio-based differential protein abundance analysis in labeling-based proteomics experiments. The original version of EBprot models the distribution of log-transformed peptide-level ratios as a Gaussian mixture of differentially abundant proteins and nondifferentially abundant proteins and computes the probability score of differential abundance for each protein based on the reproducible magnitude of peptide ratios. However, the fully parametric model can be inflexible, and its R implementation is time-consuming for data sets containing a large number of peptides (e.g., >100 000). The new tool built in the C++ language is not only faster in computation time but also equipped with a flexible semiparametric model that handles skewed ratio distributions better. We have also developed a Perseus plugin for EBprotV2 for easy access to the tool. In addition, the tool now offers a new submodule (MakeGrpData) to transform label-free peptide intensity data into peptide ratio data for group comparisons and performs differential abundance analysis using mixture modeling. This approach is especially useful when the label-free data have many missing peptide intensity data points.

New insights into the cellular temporal response to proteostatic stress

Maintaining a healthy proteome involves all layers of gene expression regulation. By quantifying temporal changes of the transcriptome, translatome, proteome, and RNA-protein interactome in cervical cancer cells, we systematically characterize the molecular landscape in response to proteostatic challenges. We identify shared and specific responses to misfolded proteins and to oxidative stress, two conditions that are tightly linked. We reveal new aspects of the unfolded protein response, including many genes that escape global translation shutdown. A subset of these genes supports rerouting of energy production in the mitochondria. We also find that many genes change at multiple levels, in either the same or opposing directions, and at different time points. We highlight a variety of putative regulatory pathways, including the stress-dependent alternative splicing of aminoacyl-tRNA synthetases, and protein-RNA binding within the 3’ untranslated region of molecular chaperones. These results illustrate the potential of this information-rich resource.

Integration of large-scale multi-omic datasets: a protein-centric view

Innovative mass spectrometry-based proteomics has enabled routine measurements of protein abundance, localization, interactions, and modifications, covering unique aspects of gene expression regulation and function. It is now time to move from isolated analyses of these datasets toward true integration of proteomics with other data types to gain insights from the interactions and interdependencies of biomolecules. When combined with genomic or transcriptomic data, proteomics expands genome annotation to identify variant or missing genes. Dynamic proteomic measurements can move analysis from predominantly concentration-based framework to that of synthesis and degradation of proteins. Proteomic data from thousands of cancer patients can foster identification of novel pathogenic mutations via detection of protein sequence changes that lead to dysregulated pathways in various tumors. Such comprehensive efforts can exploit the synergy arising from large and complex datasets to advance virtually every field of biology.

Implications of Nondifferential Misclassification on Estimates of Attributable Risk

Objectives: Only the effects of isolated nondifferential misclassification of exposure or disease on the estimates of attributable risk have been discussed in the literature. The aim of this paper is to broaden the spectrum of scenarios for which implications of misclassification are available.

Methods: For this purpose, a matrix-based approach allowing a comprehensive, unified analysis of various structures of misclassification is introduced. The relative bias or – in the situation of covariate misclassification – the relative adjustment are presented for the different misclassification scenarios.

Results: Under nondifferential misclassification of exposure or disease, the attributable risk is biased towards the null with the only exception of perfect sensitivity of exposure classification or perfect specificity of disease classification both leading to an unbiased attributable risk. From these two marginal effects, the consequences of simultaneous nondifferential independent misclassification of exposure and disease on the attributable risk are derived in the matrix-based approach. Misclassification of a dichotomous covariate leads to partial adjustment.

Conclusions: To a large extent, the results for the attributable risk are in accordance with the well-known results for the relative risk. The algebraic differences between the two risk measures, however, make it necessary to repeat the methodological considerations for the attributable risk.

PTMscape: an open source tool to predict generic post-translational modifications and map modification crosstalk in protein domains and biological processes

PTMscape predicts PTM sites using descriptors of sequence and physico-chemical microenvironment, and tests enrichment of single or pairs of PTMs in protein domains.

While tandem mass spectrometry can detect post-translational modifications (PTM) at the proteome scale, reported PTM sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools use prediction models pre-trained for single PTM type by the developers and it remains a difficult task to perform large-scale batch prediction for multiple PTMs with flexible user control, including the choice of training data. We developed an R package called PTMscape which predicts PTM sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of PTMs in protein domains. PTMscape is flexible in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Applying this framework, we expanded proteome-wide coverage of five major PTMs affecting different residues by prediction, especially for lysine and arginine modifications. Using a combination of experimentally acquired sites (PSP) and newly predicted sites, we discovered that the crosstalk among multiple PTMs occur more frequently than by random chance in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other types of PTM.

Abstract P6-11-03: A phase 2 open-label study of lucitanib in patients (pts) with FGF aberrant metastatic breast cancer (MBC)

BACKGROUND: Lucitanib is a potent, oral antiangiogenic tyrosine kinase inhibitor of Vascular Endothelial Growth Factor Receptors 1-3 (VEGFR1-3), Platelet-Derived Growth Factor Receptors alpha and beta (PDGFRα/β), and Fibroblast Growth Factor Receptors 1-3 (FGFR1-3). FGF aberrancies (amplification of FGFR1,or 11q[amplicon containing FGF ligands 3, 4, and 19]), are genomic alterations observed in over 20% of breast cancer pts and promote cancer proliferation and survival.

METHODS: MBC pts who had received at least 1 metastatic line of therapy were randomized 1:1 to 10 or 15 mg QD of lucitanib. Stratification was based on local assessment of FGF aberrancy; pts with both FGFR1 and 11q-amplified tumors were stratified as FGFR1 amplified. Central confirmation of FGFR1 or 11q amplification was done using Abbott FISH probes (FGFR1 or 11q copy number ≥ 6 and a ratio of FGFR1 or 11q to centromere ≥ 2). Investigator-assessed progression-free survival (PFS) was the primary endpoint. Secondary endpoints included objective response rate (ORR) per RECIST 1.1, disease control rate (DCR), duration of response (DR), and incidence of treatment-emergent adverse events (TEAE).

RESULTS: Enrollment completed in 3/2016; 178 pts that received at least 1 dose of lucitanib are included in this analysis (baseline characteristics in Table 1). Due to grade 3 hypertension in the 15 mg group (46% vs 37% in 10 mg group), enrollment to the 15 mg group was halted. Overall, most pts (97%) experienced at least 1 TEAE, with the most frequently (≥ 30%) occurring events being hypertension (73%), fatigue (48%), nausea (43%), hypothyroidism (40%), and headache (33%). Grade ≥ 3 TEAEs occurred in 66% of pts, with hypertension as the most frequent event (40%) followed by proteinuria and hyponatremia (both 6%). AEs were manageable with dose interruption or reduction, with approximately 8% of pts ending treatment due to an AE. Current median PFS is 3.5 mos (95% CI 2.8-4.6; range 0.62-12.95) and 2.6 mos (95% CI 1.8-2.9; range 0.82-18.87) respectively for the 10 mg and 15 mg treatment groups. No differences in clinical activity were observed by treatment group, FGF aberrancy, hormone receptor or HER2 status. Of the 168 evaluable pts, confirmed ORR was 3%; overall DCR was 27% (32% for pts in the 10 mg group compared to 20% for the 15 mg group); overall mean (standard deviation) DR of 3.3 (1.8) mos.

Baseline Characteristics 10 mg QD15 mg QD N=109N=69Age (years)Median5653Range27-8227-80SexFemale109 (100%)67 (97%)Male02 (3%)ECOG PSmissing5 (5%)2 (3%)051 (47%)30 (43%)153 (49%)37 (54%)Number of prior anticancer therapies in the metastatic setting&gt; 332 (29%)21 (30%)3-648 (44%)32 (46%)&gt; 629 (27%)16 (23%)Endocrine/HER2 statusmissing7 (6%)1 (1%)ER+ or PR+74 (68%)50 (73%)HER2+12 (11%)7 (10%)TNBC16 (15%)11 (16%)FGFR aberrancyFGFR1 amplified54 (49%)29 (42%)11q amplified31 (28%)24 (35%)FGFR1 and 11q amplified13 (12%)9 (13%)FGFR1 and 11q non-amplified11 (10%)7 (10%)

CONCLUSION: At 10 mg QD, lucitanib has modest activity with manageable toxicity in this heavily pretreated pt population. Future clinical development for lucitanib may focus on alternative biomarkers to identify sensitive tumors and rational combinations with other anti-cancer drugs.

Citation Format: Mayer IA, Arteaga CL, Nanda R, Miller KD, Jhaveri K, Brufsky AM, Rugo H, Yardley DA, Vahdat LT, Sadeghi S, Audeh MW, Rolfe L, Litten J, Knox A, Raponi M, Tankersley C, Isaacson J, Wride K, Morganstern DE, Vogel C, Connolly RM, Gradishar WJ, Patel R, Pusztai L, Abu-Khalaf M. A phase 2 open-label study of lucitanib in patients (pts) with FGF aberrant metastatic breast cancer (MBC) [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-11-03.

The relationship between maternal self-efficacy, compliance and outcome in a trial of vitamin D supplementation in pregnancy

In a randomised controlled trial of vitamin D during pregnancy, we demonstrated that women with lower self-efficacy were more likely to experience practical problems with taking the trial medication and that this was associated with lower compliance and achieved 25(OH)-vitamin D concentrations.

INTRODUCTION

The relationship between self-efficacy (the belief that one can carry out a behaviour), compliance with study protocol and outcome was explored within a randomised, double-blind, placebo-controlled trial of vitamin D supplementation in pregnancy.

METHODS

In the Maternal Vitamin D Osteoporosis Study (MAVIDOS) trial, women with circulating plasma 25(OH)-vitamin D of 25-100 nmol/l in early pregnancy were randomised to either 1000 IU cholecalciferol/day or matched placebo from 14 weeks until delivery. Circulating 25(OH)-vitamin D concentrations were assessed at 14 and 34 weeks' gestation. A sequential sub-sample completed Schwarzer's General Self-Efficacy Scale at 14 and 34 weeks and the Problematic Experiences of Therapy Scale at 34 weeks. Women were interviewed about their experiences of the trial and interview transcripts analysed thematically.

RESULTS

In 203 women, those with higher self-efficacy were less likely to experience practical problems taking the study medication (odds ratio (OR) 0.81 (95 % confidence interval (CI) 0.69-0.95), p = 0.01). Over half reported practical problems associated with poorer compliance with the protocol requiring women to take the medication daily. Compliance in women who experienced practical problems was 94 % compared with 98 % for those with no problems (p < 0.001). Poorer compliance was also associated with lower concentrations of 25(OH)-D in late pregnancy in the treatment group (β = 0.54 nmol/l (95 % CI 0.18-0.89), p = 0.003). Thematic analysis suggested common difficulties were remembering to take the medication every day and swallowing the large capsules.

CONCLUSIONS

These findings suggest that differences in self-efficacy influence trial outcomes. Such information may help clinicians anticipate responses to routine vitamin D supplementation in pregnancy and identify those who may need more support to comply.

TRIAL REGISTRATION

ISRCTN82927713, registered 11/04/2008.