Search

Abstract Introduction Three randomised controlled trials (RCTs) have demonstrated that first-line cryoballoon pulmonary vein isolation decreases atrial tachycardia in patients with symptomatic paroxysmal atrial fibrillation (PAF) compared with antiarrhythmic drugs (AADs). The aim of this study was to develop a cost-effectiveness model (CEM) for first-line cryoablation compared with first-line AADs for the treatment of PAF. The model used a Danish healthcare perspective. Methods Individual patient-level data from the Cryo-FIRST, STOP AF and EARLY-AF RCTs were used to parameterise the CEM. The model structure consisted of a hybrid decision tree (one-year time horizon) and a Markov model (40-year time horizon, with a three-month cycle length). Health-related quality of life was expressed in quality-adjusted life years (QALYs). Costs and benefits were discounted at 3% per year. Model outcomes were produced using probabilistic sensitivity analysis. Results First-line cryoablation is dominant, meaning it results in lower costs (-€2,663) and more QALYs (0.18) when compared to first-line AADs. First-line cryoablation also has a 99.96% probability of being cost-effective, at a cost-effectiveness threshold of €23,200 per QALY gained. Regardless of initial treatment, patients were expected to receive ∼ 1.2 ablation procedures over a lifetime horizon. Conclusion First-line cryoablation is both more effective and less costly (i.e. dominant), when compared with AADs for patients with symptomatic PAF in a Danish healthcare system.

Abstract Background Skeletal muscle dysfunction is a common extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD). Alterations in skeletal muscle myosin heavy chain expression, with reduced type I and increased type II myosin heavy chain expression, are associated with COPD severity when studied in largely male cohorts. The objectives of this study were (1) to define an abnormal myofibre proportion phenotype in both males and females with COPD and (2) to identify transcripts and transcriptional networks associated with abnormal myofibre proportion in COPD. Methods Forty‐six participants with COPD were assessed for body composition, strength, endurance and pulmonary function. Skeletal muscle biopsies from the vastus lateralis were assayed for fibre‐type distribution and cross‐sectional area via immunofluorescence microscopy and RNA‐sequenced to generate transcriptome‐wide gene expression data. Sex‐stratified k‐means clustering of type I and IIx/IIax fibre proportions was used to define abnormal myofibre proportion in participants with COPD and contrasted with previously defined criteria. Single transcripts and weighted co‐expression network analysis modules were tested for correlation with the abnormal myofibre proportion phenotype. Results Abnormal myofibre proportion was defined in males with COPD (n = 29) as 22% type IIx/IIax fibres and in females with COPD (n = 17) as 12% type IIx/IIax fibres. Half of the participants with COPD were classified as having an abnormal myofibre proportion. Participants with COPD and an abnormal myofibre proportion had lower median handgrip strength (26.1 vs. 34.0 kg, P = 0.022), 6‐min walk distance (300 vs. 353 m, P = 0.039) and forced expiratory volume in 1 s‐to‐forced vital capacity ratio (0.42 vs. 0.48, P = 0.041) compared with participants with COPD and normal myofibre proportions. Twenty‐nine transcripts were associated with abnormal myofibre proportions in participants with COPD, with the upregulated NEB, TPM1 and TPM2 genes having the largest fold differences. Co‐expression network analysis revealed that two transcript modules were significantly positively associated with the presence of abnormal myofibre proportions. One of these co‐expression modules contained genes classically associated with muscle atrophy, as well as transcripts associated with both type I and type II myofibres, and was enriched for genetic loci associated with bone mineral density. Conclusions Our findings indicate that there are significant transcriptional alterations associated with abnormal myofibre proportions in participants with COPD. Transcripts canonically associated with both type I and type IIa fibres were enriched in a co‐expression network associated with abnormal myofibre proportion, suggesting altered transcriptional regulation across multiple fibre types.

Abstract Urinary incontinence (UI) is a disorder of micturition that can occur in dogs of any age, sex, and breed depending on the underlying cause and time of onset. Diagnosis and treatment for various causes of UI in dogs have been described by multiple comprehensive single author review articles, but large prospective clinical trials comparing treatment outcomes in veterinary medicine are lacking. The objectives of this consensus statement therefore are to provide guidelines on both recommended diagnostic testing and treatment for various causes of UI in dogs. Specifically, pathophysiology directly related to the canine urinary system will be reviewed and diagnostic and therapeutic challenges will be addressed. A panel of 12 experts in the field (8 small animal internists [L. Adams, J. Bartges, A. Berent, J. Byron, J. Foster, A. Kendall, S. Vaden, J. Westropp], 2 neurologists [J. Coates, N. Olby], 1 radiologist [G. Oetelaar], and 1 surgeon [C. Adin]) was formed to assess and summarize evidence in the peer‐reviewed literature and to complement it with consensus recommendations using the Delphi method. Some statements were not voted on by all panelists. This consensus statement aims to provide guidance for management of both male and female dogs with underlying storage or voiding disorders resulting in UI.

Abstract Background Ocular complaints, including acute or subacute vision loss, are commonly encountered in emergency departments (ED). These potentially time-sensitive complaints are difficult to diagnose and evaluate without adequate, specialized equipment and expertise. Additionally, a thorough evaluation often requires a more extensive and specialized physical exam, imaging, and ophthalmologic consultation, all of which may not be readily available in the acute setting. Case presentation This case report presented a patient in the emergency department with the chief complaint of vision loss. Point-of-care ultrasound (POCUS) using the 10-MHz-linear-array probe, in the ocular setting, demonstrated calcification of the lens, a finding consistent with cataract in the right eye. Conclusions The use of POCUS can expedite the accurate identification of vision threatening pathology, such as cataracts, and streamline ED disposition and plan of care.

Hematopoiesis is a finely orchestrated process, whereby hematopoietic stem cells give rise to all mature blood cells. Crucially, they maintain the ability to self-renew and/or differentiate to replenish downstream progeny. This process starts at an embryonic stage and continues throughout the human lifespan. Blood cancers such as leukemia occur when normal hematopoiesis is disrupted, leading to uncontrolled proliferation and a block in differentiation of progenitors of a particular lineage (myeloid or lymphoid). Although normal stem cell programs are crucial for tissue homeostasis, these can be co-opted in many cancers, including leukemia. Myeloid or lymphoid leukemias often display stem cell-like properties that not only allow proliferation and survival of leukemic blasts but also enable them to escape treatments currently employed to treat patients. In addition, some leukemias, especially in children, have a fetal stem cell profile, which may reflect the developmental origins of the disease. Aberrant fetal stem cell programs necessary for leukemia maintenance are particularly attractive therapeutic targets. Understanding how hijacked stem cell programs lead to aberrant gene expression in place and time, and drive the biology of leukemia, will help us develop the best treatment strategies for patients.

Cotton ginning generates millions of tons of byproducts every year. If not properly managed, these materials become waste, which may constitute significant environmental, economic, and logistical issues. The objectives of this study were to characterize fresh and composted cotton gin byproducts (CGBs) for utilization as animal feed supplements and investigate the effects of composting on the forage properties. The study analyzed and compared the nutrients and energy contents of fresh and composted CGB from four commercial cotton gins in Arkansas, Mississippi, Missouri, and Tennessee states, USA. The results suggest that composting CGB may result in more than a 47% increase in fiber and crude protein and at least a 25% decrease in total digestible nutrients and net energy estimations. The differences in macro- and micro-nutrient contents and feed properties suggest that composting CGB may improve the potential for utilization as an animal feed supplement. Establishing the forage properties of CGB is crucial for determining animal feed formulations using CGB as supplements.

Abstract Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.

Abstract Integrins are a highly complex family of receptors that, when expressed on the surface of cells, can mediate reciprocal cell-to-cell and cell-to-extracellular matrix (ECM) interactions leading to assembly of integrin adhesion complexes (IACs) that initiate many signaling functions both at the membrane and deeper within the cytoplasm to coordinate processes including cell adhesion, migration, proliferation, survival, differentiation, and metabolism. All metazoan organisms possess integrins, and it is generally agreed that integrins were associated with the evolution of multicellularity, being essential for the association of cells with their neighbors and surroundings, during embryonic development and many aspects of cellular and molecular biology. Integrins have important roles in many aspects of embryonic development, normal physiology, and disease processes with a multitude of functions discovered and elucidated for integrins that directly influence many areas of biology and medicine, including mammalian pregnancy, in particular implantation of the blastocyst to the uterine wall, subsequent placentation and conceptus (embryo/fetus and associated placental membranes) development. This review provides a succinct overview of integrin structure, ligand binding, and signaling followed with a concise overview of embryonic development, implantation, and early placentation in pigs, sheep, humans, and mice as an example for rodents. A brief timeline of the initial localization of integrin subunits to the uterine luminal epithelium (LE) and conceptus trophoblast is then presented, followed by sequential summaries of integrin expression and function during gestation in pigs, sheep, humans, and rodents. As appropriate for this journal, summaries of integrin expression and function during gestation in pigs and sheep are in depth, whereas summaries for humans and rodents are brief. Because similar models to those illustrated in Fig. 1, 2, 3, 4, 5 and 6 are present throughout the scientific literature, the illustrations in this manuscript are drafted as Viking imagery for entertainment purposes.

The gin stand power is measurable using common tools; however, such tools typically do not detect active ginning. Detecting active ginning is important when trying to separate out the energy going to the moving parts of the gin stand (i.e., the baseline energy) versus the active energy doing work to remove the cotton fibers from the seed. Studies have shown that the gin stand is the second largest consumer of electricity in the ginning operation, while electricity accounts for nearly 17% of the average expense per bale. If active energy differences exist between cotton cultivars, there may be room to optimize and lower these expenses. The goal of the current work is to provide a method (and software tool) to analyze typical power logger data, and extract periods of active ginning, along with the energy consumed and ginning times, in a semi-automated way. The new method presented allows multiple periods of active ginning in a single file, and can separate the total energy into the active and baseline components. Other metrics of interest that the software calculates include the ginning time, and average power. Software validation using a simulated test signal showed that a 2%-or-lower error is possible with a noisy signal.

By controlling for size and existence of a religious affiliation and gender, this study adds to the literature regarding opinions of undergraduate business students about the ethical nature of both academic and business related actions. Analysis of student survey data from two institutions similar in these characteristics continues in this longitudinal study. After the data were separated by gender, ethical perceptions of male students significantly differed for business-related dishonest acts for those male students who had taken two or more courses in religion, but church service attendance did not seem to have any effect. This may suggest that taking more courses (or having more dialogs) in which moral issues beyond academics are discussed may affect male student perceptions of ethical issues outside the institution.

Electron microscopy (EM) enables imaging at a resolution of nanometers and can shed light on how cancer evolves to develop resistance to therapy. Acquiring these images has become a routine task.However, analyzing them is now a bottleneck, as manual structure identification is very time-consuming and can take up to several months for a single sample. Deep learning approaches offer a suitable solution to speed up the analysis. In this work, we present a study of several state-of-the-art deep learning models for the task of segmenting nuclei and nucleoli in volumes from tumor biopsies. We compared previous results obtained with the ResUNet architecture to the more recent UNet++, FracTALResNet, SenFormer, and CEECNet models. In addition, we explored the utilization of unlabeled images through semi-supervised learning with Cross Pseudo Supervision. We have trained and evaluated all of the models on sparse manual labels from three fully annotated in-house datasets that we have made available on demand, demonstrating improvements in terms of 3D Dice score. From the analysis of these results, we drew conclusions on the relative gains of using more complex models, and semi-supervised learning as well as the next steps for the mitigation of the manual segmentation bottleneck.

Focused ion beam-scanning electron microscopy (FIB-SEM) images can provide a detailed view of the cellular ultrastructure of tumor cells. A deeper understanding of their organization and interactions can shed light on cancer mechanisms and progression. However, the bottleneck in the analysis is the delineation of the cellular structures to enable quantitative measurements and analysis. We mitigated this limitation using deep learning to segment cells and subcellular ultrastructure in 3D FIB-SEM images of tumor biopsies obtained from patients with metastatic breast and pancreatic cancers. The ultrastructures, such as nuclei, nucleoli, mitochondria, endosomes, and lysosomes, are relatively better defined than their surroundings and can be segmented with high accuracy using a neural network trained with sparse manual labels. Cell segmentation, on the other hand, is much more challenging due to the lack of clear boundaries separating cells in the tissue. We adopted a multi-pronged approach combining detection, boundary propagation, and tracking for cell segmentation. Specifically, a neural network was employed to detect the intracellular space; optical flow was used to propagate cell boundaries across the z-stack from the nearest ground truth image in order to facilitate the separation of individual cells; finally, the filopodium-like protrusions were tracked to the main cells by calculating the intersection over union measure for all regions detected in consecutive images along z-stack and connecting regions with maximum overlap. The proposed cell segmentation methodology resulted in an average Dice score of 0.93. For nuclei, nucleoli, and mitochondria, the segmentation achieved Dice scores of 0.99, 0.98, and 0.86, respectively. The segmentation of FIB-SEM images will enable interpretative rendering and provide quantitative image features to be associated with relevant clinical variables.

Introduction: Tissue-based sampling and diagnosis are defined as the extraction of information from certain limited spaces and its diagnostic significance of a certain object. Pathologists deal with issues related to tumor heterogeneity since analyzing a single sample does not necessarily capture a representative depiction of cancer, and a tissue biopsy usually only presents a small fraction of the tumor. Many multiplex tissue imaging platforms (MTIs) make the assumption that tissue microarrays (TMAs) containing small core samples of 2-dimensional (2D) tissue sections are a good approximation of bulk tumors although tumors are not 2D. However, emerging whole slide imaging (WSI) or 3D tumor atlases that use MTIs like cyclic immunofluorescence (CyCIF) strongly challenge this assumption. In spite of the additional insight gathered by measuring the tumor microenvironment in WSI or 3D, it can be prohibitively expensive and time-consuming to process tens or hundreds of tissue sections with CyCIF. Even when resources are not limited, the criteria for region of interest (ROI) selection in tissues for downstream analysis remain largely qualitative and subjective as stratified sampling requires the knowledge of objects and evaluates their features. Despite the fact TMAs fail to adequately approximate whole tissue features, a theoretical subsampling of tissue exists that can best represent the tumor in the whole slide image.Methods: To address these challenges, we propose deep learning approaches to learn multi-modal image translation tasks from two aspects: 1) generative modeling approach to reconstruct 3D CyCIF representation and 2) co-embedding CyCIF image and Hematoxylin and Eosin (H&E) section to learn multi-modal mappings by a cross-domain translation for minimum representative ROI selection.Results and discussion: We demonstrate that generative modeling enables a 3D virtual CyCIF reconstruction of a colorectal cancer specimen given a small subset of the imaging data at training time. By co-embedding histology and MTI features, we propose a simple convex optimization for objective ROI selection. We demonstrate the potential application of ROI selection and the efficiency of its performance with respect to cellular heterogeneity.

Comprehensive profiling of ligand-induced perturbation responses of the MCF10A mammary epithelial cell line provides an exhaustive resource for identification of the molecular basis of cellular phenotypes.

Only a minority of patients with non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitors. Here the authors design a nanosystem for the co-delivery of a PLK1 inhibitor and PD-L1 antibody, showing anti-tumor immune responses in preclinical lung cancer models.

An approach for tissue image analysis applicable to highly multiplexed immunofluorescence imaging of the spatial distribution of multiple protein biomarkers is proposed, here applied to the analysis of multiplex IF using the multiplex imaging platform, CyCIF.

Objectives: The excessive release of the antidiuretic hormone vasopressin is implicated in many diseases including cardiovascular disease, diabetes, obesity, and metabolic syndrome. Once thought to be elevated as a consequence of diseases, data now supports a more causative role. We have previously identified CREB3L1 as a transcription factor that co-ordinates vasopressin synthesis and release in the hypothalamus. The objective here was to identify mechanisms orchestrated by CREB3L1 that co-ordinate vasopressin release. Methods: We mined Creb3l1 knockdown SON RNA-seq data to identify downstream target genes. We proceeded to investigate the expression of these genes and associated pathways in the supraoptic nucleus of the hypothalamus in response to physiological and pharmacological stimulation. We used viruses to selectively knockdown gene expression in the supraoptic nucleus and assessed physiological and metabolic parameters. We adopted a phosphoproteomics strategy to investigate mechanisms that facilitate hormone release by the pituitary gland. Results: We discovered glucagon like peptide 1 receptor (Glp1r) as a downstream target gene and found increased expression in stimulated vasopressin neurones. Selective knockdown of supraoptic nucleus Glp1rs resulted in decreased food intake and body weight. Treatment with GLP-1R agonist liraglutide decreased vasopressin synthesis and release. Quantitative phosphoproteomics of the pituitary neurointermediate lobe revealed that liraglutide initiates hyperphosphorylation of presynapse active zone proteins that control vasopressin exocytosis. Conclusion: In summary, we show that GLP-1R signalling inhibits the vasopressin system. Our data advises that hydration status may influence the pharmacodynamics of GLP-1R agonists so should be considered in current therapeutic strategies.

Rationale: Body mass index (BMI) is associated with chronic obstructive pulmonary disease (COPD) mortality, but the underlying mechanisms are unclear. The effect of genetic variants aggregated into a polygenic score may elucidate the causal mechanisms and predict risk. Objectives: To examine the associations of genetically predicted BMI with all-cause and cause-specific mortality in COPD. Methods: We developed a polygenic score (PGS) for BMI (PGSBMI) and tested for associations of the PGSBMI with all-cause, respiratory, and cardiovascular mortality in participants with COPD from the COPDGene (Genetic Epidemiology of COPD), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), and Framingham Heart studies. We calculated the difference between measured BMI and PGS-predicted BMI (BMIdiff) and categorized participants into groups of discordantly low (BMIdiff <20th percentile), concordant (BMIdiff between the 20th and 80th percentiles), and discordantly high (BMIdiff >80th percentile) BMI. We applied Cox models, examined potential nonlinear associations of the PGSBMI and BMIdiff with mortality, and summarized results with meta-analysis. Measurements and Main Results: We observed significant nonlinear associations of measured BMI and BMIdiff, but not PGSBMI, with all-cause mortality. In meta-analyses, a one–standard deviation increase in the PGSBMI was associated with an increased hazard for cardiovascular mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.12–1.49), but not for respiratory or all-cause mortality. Compared with participants with concordant measured and genetically predicted BMI, those with discordantly low BMI had higher risks for all-cause mortality (HR, 1.57; 95% CI, 1.41–1.74) and respiratory death (HR, 2.01; 95% CI, 1.61–2.51). Conclusions: In people with COPD, a higher genetically predicted BMI is associated with higher cardiovascular mortality but not respiratory mortality. Individuals with a discordantly low BMI have higher all-cause and respiratory mortality rates than those with a concordant BMI. [ABSTRACT FROM AUTHOR]

Expression of the classical interferon (IFN) stimulated genes (ISGs) increases in the endometrial stroma and glandular epithelium (GE) through activation of signal transducer and activator of transcription (STAT) signaling in response to the secretion of IFN tau (IFNT) and IFN gamma (IFNG) by the conceptuses of ruminants, including cattle and sheep, and pigs, respectively. The first of the classical ISGs to be characterized was ISG15 in cattle. Classical ISGs are not expressed by the endometrial luminal epithelium (LE) due to the expression of interferon regulatory factor 2 (IRF2) in the LE that prevents the expression of ISGs in the LE. Classical ISG expression in the endometrium serves as a reliable indicator of conceptus health and elongation in cattle. There are also nonclassical ISGs that are upregulated in endometrial LE in response to progesterone (P4) that are further stimulated by IFNT in sheep, the intracellular signaling pathway responsible for IFN effects on expression is unknown. ISGs are also upregulated in extrauterine tissues including CL and peripheral blood mononuclear cells (PBMCs). The expression of ISGs by the PBMCs of cattle serves as an early prognosticator of pregnancy. The physiological roles of ISGs remain obscure, but evidence suggests that they are at least in part involved in modifying the immune system to support endometrial remodeling necessary for the successful implantation of the conceptus. Our understanding of these ISGs is primarily the result of work from the laboratories of Drs Fuller Bazer, Thomas (Tod) Hansen, Gregory Johnson, Hakhyun Ka, Patrick Lonergan, Troy Ott, and Thomas Spencer. [ABSTRACT FROM AUTHOR]

The 90 kDa ribosomal S6 kinases (RSKs) are serine threonine kinases comprising four isoforms. The isoforms can have overlapping functions in regulation of migration, invasion, proliferation, survival, and transcription in various cancer types. However, isoform specific differences in RSK1 versus RSK2 functions in gene regulation are not yet defined. Here, we delineate ribosomal S6 kinases isoform-specific transcriptional gene regulation by comparing transcription programs in RSK1 and RSK2 knockout cells using microarray analysis. Microarray analysis revealed significantly different mRNA expression patterns between RSK1 knockout and RSK2 knockout cell lines. Importantly some of these functions have not been previously recognized. Our analysis revealed RSK1 has specific roles in cell adhesion, cell cycle regulation and DNA replication and repair pathways, while RSK2 has specific roles in the immune response and interferon signaling pathways. We further validated that the identified gene sets significantly correlated with mRNA datasets from cancer patients. We examined the functional significance of the identified transcriptional programs using cell assays. In alignment with the microarray analysis, we found that RSK1 modulates the mRNA and protein expression of Fibronectin1, affecting cell adhesion and CDK2, affecting S-phase arrest in the cell cycle, and impairing DNA replication and repair. Under similar conditions, RSK2 showed increased ISG15 transcriptional expression, affecting the immune response pathway and cytokine expression. Collectively, our findings revealed the occurrence of RSK1 and RSK2 specific transcriptional regulation, defining separate functions of these closely related isoforms.

Abstract A number of highly multiplexed immunostaining and imaging methods have advanced spatial proteomics of cancer for improved treatment strategies. While a variety of methods have been developed, the most widely used methods are limited by harmful signal removal techniques, difficulties with reagent production and antigen sensitivity. Multiplexed immunostaining employing oligonucleotide (oligos)-barcoded antibodies is an alternative approach that is growing in popularity. However, challenges remain in consistent conjugation of oligos to antibodies with maintained antigenicity as well as non-destructive, robust and cost-effective signal removal methods. Herein, a variety of oligo conjugation and signal removal methods were evaluated in the development of a robust oligo conjugated antibody cyclic immunofluorescence (Ab-oligo cyCIF) methodology. Both non- and site-specific conjugation strategies were assessed to label antibodies, where site-specific conjugation resulted in higher retained binding affinity and antigen-specific staining. A variety of fluorescence signal removal methods were also evaluated, where incorporation of a photocleavable link (PCL) resulted in full fluorescence signal removal with minimal tissue disruption. In summary, this work resulted in an optimized Ab-oligo cyCIF platform capable of generating high dimensional images to characterize the spatial proteomics of the hallmarks of cancer.

Abstract In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Abstract Background HER2-amplified breast cancer is a clinically defined subtype of breast cancer for which there are multiple viable targeted therapies. Resistance to these targeted therapies is a common problem, but the mechanisms by which resistance occurs remain incompletely defined. One mechanism that has been proposed is through mutation of genes in the PI3-kinase pathway. Intracellular signaling from the HER2 pathway can occur through PI3-kinase, and mutations of the encoding gene PIK3CA are known to be oncogenic. Mutations in PIK3CA co-occur with HER2-amplification in ~ 20% of cases within the HER2-amplified subtype. Methods We generated isogenic knockin mutants of each PIK3CA hotspot mutation in HER2-amplified breast cancer cells using adeno-associated virus-mediated gene targeting. Isogenic clones were analyzed using a combinatorial drug screen to determine differential responses to HER2-targeted therapy. Western blot analysis and immunofluorescence uncovered unique intracellular signaling dynamics in cells resistant to HER2-targeted therapy. Subsequent combinatorial drug screens were used to explore neuregulin-1-mediated resistance to HER2-targeted therapy. Finally, results from in vitro experiments were extrapolated to publicly available datasets. Results Treatment with HER2-targeted therapy reveals that mutations in the kinase domain (H1047R) but not the helical domain (E545K) increase resistance to lapatinib. Mechanistically, sustained AKT signaling drives lapatinib resistance in cells with the kinase domain mutation, as demonstrated by staining for the intracellular product of PI3-kinase, PIP3. This resistance can be overcome by co-treatment with an inhibitor to the downstream kinase AKT. Additionally, knockout of the PIP3 phosphatase, PTEN, phenocopies this result. We also show that neuregulin-1, a ligand for HER-family receptors, confers resistance to cells harboring either hotspot mutation and modulates response to combinatorial therapy. Finally, we show clinical evidence that the hotspot mutations have distinct expression profiles related to therapeutic resistance through analysis of TCGA and METABRIC data cohorts. Conclusion Our results demonstrate unique intracellular signaling differences depending on which mutation in PIK3CA the cell harbors. Only mutations in the kinase domain fully activate the PI3-kinase signaling pathway and maintain downstream signaling in the presence of HER2 inhibition. Moreover, we show there is potentially clinical importance in understanding both the PIK3CA mutational status and levels of neuregulin-1 expression in patients with HER2-amplified breast cancer treated with targeted therapy and that these problems warrant further pre-clinical and clinical testing.