10 research outputs found
A roadmap for patient-public involvement and engagement (PPIE) : recounting the untold stories of breast cancer patient experiences
Introduction Breast cancer remains a prevalent disease in women worldwide. Though significant advancements in the standard of care for breast cancer have contributed to improved patient survival and quality of life, a breast cancer diagnosis and subsequent treatment interventions have a long-lasting impact on patients’ lived experiences. A high-quality healthcare system uses a patient-centred approach to healthcare, with patient engagement being a central pillar in the delivery of patient-centred care. However, the disconnect between patients and researchers can translate into research lacking real-world relevance to patient health needs. Here, we report a patient and stakeholder engagement workshop series that was conceptualized with the goal of promoting dialogue between patients with breast cancer, breast cancer researchers and the clinician involved in their care. We present the collaborative learning process and emerging opportunities from this patient engagement workshop series as a community-academic partnership. Method We report on a three-part storytelling workshop, with the scope of the workshops including topics related to raising awareness of the patient lived experience following a breast cancer diagnosis, breast cancer research activities undertaken by researchers, and the approach used by multidisciplinary healthcare teams in the management of breast cancer using storytelling as a tool. We used an iterative approach to cohort trust and relationship building, narrative development, and the use of multiple media formats to capture patient stories. This included the use of object memories, storytelling prompt cards and open-mic audio format to capture patient stories from diagnosis to treatment, and remission. Results 20 patients shared their stories with key themes emerging from the qualitative analysis of audio recordings. For many, this was the first time they had spoken about their breast cancer experience beyond family and friends. Emerging themes included common public misconceptions about a breast cancer diagnosis, the importance of self-advocacy in patient decision making about treatment, and the complex emotional journey experienced by patients diagnosed with breast cancer. The group-based storytelling approach provided collective empowerment to share personal experiences and connect meaningfully across the peer community. Conclusion While a breast cancer diagnosis can be overwhelming from a physical, social, emotional and cognitive perspective, storytelling as a patient engagement approach can build patient trust in researchers, ensuring that as key stakeholders they are involved in the process of research. Understanding the patient perspective of a breast cancer diagnosis and subsequent experiences can support healthcare professionals in developing an empathetic approach to sharing information, and involving patients in shared decision making about their healthcare
Mitochondrial hyperfusion via metabolic sensing of regulatory amino acids
The relationship between nutrient starvation and mitochondrial dynamics is poorly understood. We find that cells facing amino acid starvation display clear mitochondrial fusion as a means to evade mitophagy. Surprisingly, further supplementation of glutamine (Q), leucine (L), and arginine (R)Â did not reverse, but produced stronger mitochondrial hyperfusion. Interestingly, the hyperfusion response to QÂ + LÂ + R was dependent upon mitochondrial fusion proteins Mfn1 and Opa1 but was independent of MTORC1. Metabolite profiling indicates that QÂ + LÂ + R addback replenishes amino acid and nucleotide pools. Inhibition of fumarate hydratase, glutaminolysis, or inosine monophosphate dehydrogenase all block QÂ + LÂ + R-dependent mitochondrial hyperfusion, which suggests critical roles for the tricarboxylic acid (TCA) cycle and purine biosynthesis in this response. Metabolic tracer analyses further support the idea that supplemented Q promotes purine biosynthesis by serving as a donor of amine groups. We thus describe a metabolic mechanism for direct sensing of cellular amino acids to control mitochondrial fusion and cell fate
High-throughput metabolic screening of microalgae genetic variation in response to nutrient limitation
Metabolic analysis of the response of Pseudomonas putida DOT-T1E strains to toluene using Fourier transform infrared spectroscopy and gas chromatography mass spectrometry
Development of an accessible gene expression bioinformatics pipeline to study driver mutations of colorectal cancer
Colorectal cancer (CRC) is a global cause of cancer-related mortality driven by genetic and environmental factors which influence therapeutic outcomes. The emergence of next-generation sequencing technologies enables the rapid and extensive collection and curation of genetic data for each cancer type into clinical gene expression biobanks. In this study we used a combination of bioinformatics tools to investigate the expression patterns and prognostic significance of two genes, adenomatous polyposis coli (APC) and B-Raf proto-oncogene (BRAF), that are commonly dysregulated in colon cancer. Subsequently, we investigated the pathways and biomolecular effectors implicated in APC and BRAF function. Our results show mutation types, frequency, anatomical location and differential expression patterns for APC and BRAF between colorectal tumour and matched healthy tissue. The prognostic values of APC and BRAF was investigated as a function of expression level in CRC and other cancer types. In the era of precision medicine and with significant advancements in biobanking and data curation, there is significant scope to use existing clinical datasets for evaluating the role of mutational drivers in carcinogenesis. This offers the potential for studying combinations of less well-known genes and the discovery of novel biomarkers or studying the association between various effector proteins and pathways
The role of KPNA2 mutations in breast cancer prognosis : a survey of publicly available databases
Breast cancer, comprising of several sub-phenotypes, is a leading cause of female cancer-related mortality in the UK and accounts for 15% of all cancer cases. Chemoresistant sub phenotypes of breast cancer remain a particular challenge. However, the rapidly-growing availability of clinical datasets, presents the scope to underpin a data driven precision medicine-based approach exploring new targets for diagnostic and therapeutic interventions. We report a survey of several publicly available databases probing the expression and prognostic role of Karyopherin-2 alpha (KPNA2) in breast cancer prognosis. Aberrant KPNA2 overexpression is directly correlated with aggressive tumour phenotypes and poor patient survival outcomes. We examined the existing information available on a range of commonly occurring mutations of KPNA2 and their correlation with patient survival. Our analysis of clinical gene expression datasets show that KPNA2 is frequently amplified in breast cancer, with differences in expression levels observed as a function of patient age and clinicopathologic parameters. We also found that aberrant KPNA2 overexpression is directly correlated with poor patient prognosis, warranting further investigation of KPNA2 as an actionable target for patient stratification or the design of novel chemotherapy agents. In the era of big data, the wealth of datasets available in the public domain can be used to underpin proof of concept studies evaluating the biomolecular pathways implicated in chemotherapy resistance in breast cancer
Nanoparticle isolation from biological media for protein corona analysis: The impact of incubation and recovery protocols on nanoparticle attributes
The use of nanoparticles has increasingly been implemented in biomedical applications including the diagnosis and treatment of disease. When administered to a biological system, nanoparticles spontaneously interact with their surrounding environment, leading to the surface-adsorption of small molecules and biomacromolecules. The protein component of the surface-adsorbed species, is often referred to as the “protein corona”. The composition of the protein corona is governed by nanoparticle properties, incubation media and parameters related to the environment in which nanoparticle incubations are performed. In this study, we investigated the formation of protein corona on polystyrene nanoparticles which have different surface chemistries and the impact of experimental incubation parameters, including centrifugation-resuspension protocols, incubation duration and shear flow rate conditions. The particle characteristics measured include size distribution, zeta potential and total protein content.
Our findings show significant differences in nanoparticle size following exposure to media containing proteins across the three different nanoparticle surface chemistries. These findings were also confirmed by total protein concentration measurements performed on nanoparticles recovered from bulk media, and measurements of the composition of surface-adsorbed proteins by gel electrophoresis. We also found that exposure to different shear flow conditions alters both the thickness and the composition of surface-adsorbed protein coronas. In parallel to analysis of nanoparticles isolated using the centrifugation-resuspension protocol, we performed in situ analysis of nanoparticle size in media containing proteins. Results obtained from these measurements highlight that the recovery procedure is disruptive to the protein corona and therefore the need for investigative methods that do not alter the properties of the nanoparticle coronas.
Nanomedicines are generally intended for administration via injection, and our findings show that parameters such as shear flow and media composition can significantly alter nanoparticle physicochemical parameters. Overall, we show that the recovery protocol can significantly alter particle parameters in addition to the overall protein composition of surface-adsorbed proteins. We recommend that nanoparticle characterization pipelines studying bio-nano interactions during early nanomedicine development consider experimental design in the context of biologically-relevant shear flow conditions and media composition because these parameters can significantly alter particle physical parameters and the subsequent conclusions drawn from such studies
Molecular Analysis of Exhaled Breath as a Diagnostic Test for Ventilator--Associated Lower 3 Respiratory Tract Infections (BreathDx)--an international multicentre observational study 4
Patients suspected of ventilator-associated lower respiratory tract infections (VA-LRTIs) commonly receive broad-spectrum antimicrobial therapy unnecessarily. We tested whether exhaled breath analysis can discriminate between patients suspected of VA-LRTI with confirmed infection, from patients with negative cultures. Breath from 108 patients suspected of VA-LRTI was analysed by gas chromatography-mass spectrometry. The breath test had a sensitivity of 98% at a specificity of 49%, confirmed with a second analytical method. The breath test had a negative predictive value of 96% and excluded pneumonia in half of the patients with negative cultures. Trial registration number: UKCRN ID number 19086, registered May 2015