Biology subjects

Walker, R. C.

Publications and source records attributed to Walker, R. C..

7 recordsLinked to original sources

bioRxiv2024

Comparative analysis of protein expression between oesophageal adenocarcinoma and normal adjacent tissue

Oesophageal adenocarcinoma (OAC) is the 7th most common cancer in the United Kingdom and remains a significant health challenge. This study presents a proteomic analysis of seven OAC donors complementing our previous neoantigen identification study of their human leukocyte antigen (HLA) immunopeptidomes. Using label-free mass spectrometry proteomics, we compared OAC tumour tissue to matched normal adjacent tissue (NAT) to identify differentially expressed proteins. We identified differential expression of a number of proteins previously linked to OAC and other cancers. We observed enrichment of processes and pathways relating RNA processing and the immune system. Our findings also offer insight into the role of the protein stability in the generation of the neoantigen we previously identified. These results provide independent corroboration of existing oesophageal adenocarcinoma biomarker studies that may inform future diagnostic and therapeutic research.

cancer biology↗

bioRxiv2022

Identification of neoantigens in esophageal adenocarcinoma

Esophageal adenocarcinoma (EAC) has a relatively poor long-term survival and limited treatment options. Promising targets for immunotherapy are short peptide neoantigens containing tumor mutations, presented to cytotoxic T-cells by human leukocyte antigen molecules (HLA). Despite an association between putative neoantigen abundance and therapeutic response across cancers, immunogenic neoantigens are challenging to identify. Here we characterized the mutational and immunopeptidomic landscapes of tumors from a cohort of seven patients with EAC. We directly identified one HLA-I presented neoantigen from one patient, and report functional T-cell responses from a predicted HLA-II neoantigen in a second patient. The predicted class II neoantigen contains both HLA I and II binding motifs. Our exploratory observations are consistent with previous neoantigen studies in finding that neoantigens are rarely directly observed, and an identification success rate following prediction in the order of 10%. However, our identified putative neoantigen is capable of eliciting strong T-cell responses, emphasizing the need for improved strategies for neoantigen identification.

cancer biology↗

bioRxiv2021

RNA folding using quantum computers

The 3-dimensional fold of an RNA molecule is largely determined by patterns of intramolecular hydrogen bonds between bases. Predicting the hydrogen bonding network from the sequence, also referred to as RNA secondary structure prediction or RNA folding, is a nondeterministic polynomial-time (NP)-complete computational problem. The structure of the molecule is strongly predictive of its functions and biochemical properties, and therefore the ability to accurately predict the structure is a crucial tool for biochemists. Many methods have been proposed to efficiently sample possible secondary structure patterns. Classic approaches employ dynamic programming, and recent studies have explored approaches inspired by evolutionary algorithms. This work demonstrates leveraging quantum computing hardware to predict the secondary structure of RNA. A Hamiltonian written in the form of a Binary Quadratic Model (BQM) is derived to drive the system toward maximizing the number of base pairs while simultaneously maximizing the average length of the stems. An Adiabatic Quantum Computer (AQC) is compared to a Replica Exchange Monte Carlo (REMC) algorithm programmed with the same objective function, with the AQC being shown to be highly competitive at rapidly identifying low energy solutions. The method proposed in this study was compared to three algorithms from literature and was found to have the highest success rate.

bioinformatics↗

bioRxiv2021

Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma

Neoadjuvant therapy followed by surgery is the standard of care for locally advanced esophageal adenocarcinoma (EAC). Unfortunately, response to neoadjuvant chemotherapy (NAC) is poor (<20%), as is the overall survival benefit at 5 years (5%). The EAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. To identify associations between genomic events and response to NAC in EAC, a comparative genomic analysis was performed in 65 patients with extensive clinical and pathological annotation using whole-genome sequencing (WGS). We defined response using Mandard Tumor Regression Grade (TRG), with responders classified as TRG1-2 (n=27) and non-responders classified as TRG4-5 (n=38). We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P=0.036) and elevated copy number variation in non-responders (282 vs 136/patient, P<0.001). We identified copy number variants unique to each group in our cohort, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of note, NAV3 mutations were exclusively present in the non-responder group with a frequency of 22%. Thus, lower mutation burden, higher chromosomal instability and specific copy number alterations are associated with resistance to NAC.

genomics↗

bioRxiv2021

mRNA codon optimization on quantum computers

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. An adiabatic quantum computer (AQC) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The AQC is found to be competitive in identifying optimal solutions and future generations of AQCs may be able to outperform classical GAs. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

bioinformatics↗

bioRxiv2020

SARS-CoV-2 infection of African green monkeys results in mild respiratory disease discernible by PET/CT imaging and prolonged shedding of infectious virus from both respiratory and gastrointestinal tracts

Vaccines are urgently needed to combat the global coronavirus disease 2019 (COVID-19) pandemic, and testing of candidate vaccines in an appropriate non-human primate (NHP) model is a critical step in the process. Infection of African green monkeys (AGM) with a low passage human isolate of SARS-CoV-2 by aerosol or mucosal exposure resulted in mild clinical infection with a transient decrease in lung tidal volume. Imaging with human clinical-grade 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET) co-registered with computed tomography (CT) revealed pulmonary lesions at 4 days post-infection (dpi) that resolved over time. Infectious virus was shed from both respiratory and gastrointestinal (GI) tracts in all animals in a biphasic manner, first between 2-7 dpi followed by a recrudescence at 14-21 dpi. Viral RNA (vRNA) was found throughout both respiratory and gastrointestinal systems at necropsy with higher levels of vRNA found within the GI tract tissues. All animals seroconverted simultaneously for IgM and IgG, which has also been documented in human COVID-19 cases. Young AGM represent an excellent species to study mild/subclinical COVID-19 disease and have shed light on unknown aspects of long-term virus shedding. They are ideally suited for preclinical evaluation of candidate vaccines and therapeutic interventions. One Sentence SummarySubclinical infection of African green monkeys infected with SARS-CoV-2 results in prolonged shedding of infectious virus from both respiratory and gastrointestinal tracts.

microbiology↗

bioRxiv2018

Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package

Alchemical free energy calculations (AFE) based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability, and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER.

biophysics↗