Profile

Biography

I obtained my PhD in the Bone Oncology group of Prof. Ingunn Holen and Prof. Penelope Ottewell in the Department of Oncology & Metabolism at The University of Sheffield Medical School, which was awarded in October 2017. My PhD project focussed on developing novel models of mitotic quiescence in human breast cancer cells in vitro and metastatic dormancy in vivo. My early postdoctoral work was focussed on characterising the cellular sub-populations isolated from these models using a multitude of approaches, including next-generation sequencing.

In early 2019, I undertook a three-month training placement in high-performance computing (HPC) and bioinformatic analysis of RNA sequencing (RNA-Seq) data at the Kinghorn Centre for Clinical Genomics at the Garvan Institute of Medical Research in Sydney, Australia working under Dr Nenad Bartonicek.

Beginning in September 2019, I transitioned to a two-year position as a postdoctoral cancer bioinformatician and in June 2022 moved to a full-time role as cancer bioinformatician embedded within the Sheffield Bioinformatics Core Facility working in the group of Prof. James Catto on several clinical projects involving large-scale next-generation sequencing and clinical data analysis.

In May 2023 I was appointed as a Senior Lecturer in Data Science and Analytics in the Department of Computing at Sheffield Hallam University and awarded a three-year honorary post as Senior Lecturer in Bioinformatics in the Department of Oncology and Metabolism at the University of Sheffield.

My current research activity is centred on numerous cancer types, including projects aiming to create a mutational map of the 100,000 Genomes Project bladder cancer and ovarian cancer cohorts, a project aiming to develop a model to predict response to therapy in gestational trophoblastic disease, and a project aiming to identify molecular drivers of metastatic dormancy in breast cancer. I am also contributing bioinformatics capability to the Genotype of Urothelial Cancer - Stratified Treatment and Oncological outcomes (GUSTO) phase II clinical study, as well as supporting several smaller clinical, basic science and student-led projects in a diverse range of areas including public healthcare data, text mining and sentiment analysis, and predictive modelling.

Publications

This section contains an up-to-date list of publications that I have authored.

Original Manuscripts

Morita, M., Arshad, F., Quayle, L.A., George, C.N., Lefley, D.V., Kalajzic, I., Balsubramanian, M., Cebe, T., Reilly, G., Bishop, N.J., Ottewell, P.D. (2024). Losartan Alters Osteoblast Differentiation and Increases Bone Mass Through Inhibition of TGFB Signalling In Vitro and in an OIM Mouse Model. Bone Reports, 101795: 2352-1872.

Griffin, J., Down, J., Quayle, L.A., Heath, P., Gibb, E.A., Davicioni, E., Liu, Y., Zhao, X., Swain, J., Wang, D., Hussain, S., Crabb, S., Catto, JWF. on behalf of the GUSTO Trial Management Group (2024) Verification of Molecular Subtyping of Bladder Cancer in the GUSTO Clinical Trial. J Pathol Clin Res, 1;10(2):e12363.

Catto, J.W.F., Mandrik, O., Quayle, L.A., Hussain, S.A., McGrath, J., Cresswell, J., Birtle, A.J., Jones, R.J., Mariappan, P., Makaroff, L.E., Knight, A., Mostafid, H., Chilcott, J., Sasieni, P., Cumberbatch M. (2023). Diagnosis, Treatment and Survival from Bladder, Upper Urinary Tract and Urethral Cancers: Real World Findings from NHS England Between 2013 and 2019. BJU Int, 131(6): 734-744.

Quayle, L.A., Spicer, A., Ottewell, P.D., Holen, I. (2021). Transcriptomic Profiling Reveals Novel Candidate Genes and Signalling Programs in Breast Cancer Quiescence and Dormancy. Cancers, 13(16): 3922.

Tulotta, C., Lefley, D., Moore, C., Amariutei, A., Spicer, A., Quayle, L., Hughes, R., Ahmed, K., Cookson, V., Evans, C., Vadakekolathu, J., Heath, P., Francis, F., Pinteaux, E., Pockley, A., Ottewell, P.D. (2021). IL-1B Drives Opposing Responses in Primary Tumours and Bone Metastases: Harnessing Combination Therapies to Improve Outcome in Breast Cancer. NPJ Breast Cancer, 7(1): 95.

Quayle, L.A., Ottewell, P.D., Holen, I. (2018). Chemotherapy Resistance and Stemness in Mitotically Quiescent Human Breast Cancer Cells Identified by Fluorescent Dye Retention. Clin Exp Metastasis, 35(8): 831-846.

Quayle, L.A., Pereira, M.G., Scheper, G., Wiltshire, T., Peake, R.E., Hussain, I., Rea, C.A. & Bates, T.E. (2017). Anti-Angiogenic Drugs: Direct Anti-Cancer Agents with Mitochondrial Mechanisms of Action. Oncotarget, 8 (51): 88670-88688.

Quayle, L., Ottewell, P.D., Holen, I. (2015). Bone Metastasis: Molecular Mechanisms Implicated in Tumour Cell Dormancy in Breast and Prostate Cancer. Curr Cancer Drug Targets. 15: 469-480.

Book Chapters

Holen, I. and Quayle, L.A. (2020). Stem Cell Niches in Bone and Their Roles in Cancer Metastasis. Advances in Stem Cells and their Niches. Elsevier. 5: 35-62.

Ottewell, P.D. and Quayle, L.A. (2019) Tumor Dormancy in the Bone. Encyclopaedia of Bone Biology. Elsevier. 166 - 179.

Conference Proceedings

Crabb, S.J., Hussain, S.A., Oughton, J.B., Swain, J., Cairns, D.A., Collinson, M., Ainsworth, G., McCready, D., Griffin, J., Heath, P., Quayle, L., Down, J., Wang, D., Knight, A., Gibb, E., Davicioni, E., Liu, Y., Catto, J.W.F. (2024) Use of Gene Expression Patterns to Identify Unique Molecular Subtypes in Muscle Invasive Bladder Cancer: GUSTO. 2024 ASCO Annual Meeting, J. Clin. Oncol. 42:16(Suppl): Abstract TPS4621.

Griffin, J., Down, J., Quayle, L., Heath, P., Catto, J. (2023) Pathology Against the Clock: Verification of Gene Expression Subtyping for the GUSTO Clinical Trial. Liverpool Pathology 2023. 14th Joint Meeting of the BDIAP and The Pathological Society, 27-29 June 2023. J Pathol. 261 Suppl 1:S3-S69: Abstract P85.

Quayle, L., Ottewell, P.D., Holen, I. (2018) Therapeutic Resistance and Stemness in Mitotically Quiescent Human Breast Cancer Cells. 1st UK Interdisciplinary Breast Cancer Symposium 15th – 16th January 2018; Manchester, U.K. Breast Cancer Res Treat. 167:309–405: Abstract P10.12.

Quayle, L., Park, S., McDonnell, D.P., Ottewell, P.D., Holen, I. (2017) Targeting ERR-α Regulated Lactate Metabolism Eliminates Drug-Resistant Breast Cancer Cells. Proceedings of the 2016 San Antonio Breast Cancer Symposium 6th – 10th December 2016; San Antonio, TX, U.S.A. Cancer Res. 77(4 Suppl): Abstract P3-07-14.

Peer Review

Acta Pharmaceutica Sinica B
Cancer Chemotherapy and Pharmacology
Clinical & Experimental Metastasis
Discover Oncology
Journal of Cellular Biochemistry
Journal of Tissue Engineering and Regenerative Medicine
Scientific Reports

Editorial Board Membership

Clinical & Experimental Metastasis (2023 - Present)

Professional Memberships

British Association for Cancer Research (2014 - Present)
European Association for Cancer Research (2014 - Present)
Institute of Biomedical Science (2011 - 2017)
Royal Society of Biology (2011 - 2017)

Teaching Qualifications

I have been awarded the Advance HE Fellowship. This award demonstrates a personal and institutional commitment to professionalism in learning and teaching in higher education, and that my higher education (HE) teaching and/or support for learning practice meets all 15 points of the Professional Standards Framework 2023.

I have also reached certified The Carpentries Instructor status. This certification demonstrates my understanding of core evidence-based teaching practices and pedagogical concepts that qualify me to teach foundational coding and data science skills to researchers under the core curriculum of Data Carpentry, Library Carpentry, and Software Carpentry.

Skills Summary

Below is a brief overview of some of my analytical skills and competencies:

  • Programming in R, Python, SQL, and Unix (BASh)
  • Auxiliary tools such as Markdown, Git, Conda and Nextflow
  • Containerisation technologies Singularity (Apptainer) and Docker
  • Pipeline development and deployment on high-performance computing (HPC) or cloud-based infrastructure
  • Proteomics, Microarray, RNA-Seq (bulk, single-cell and spatial), Whole Genome (WGS) and Whole Exome (WES) sequencing data analysis
  • Relational database design, access and analysis
  • Large-scale clinical data cleaning and integration
  • Time-to-event (survival) analysis
  • Interaction network construction, validation, and analysis
  • Geospatial data analysis
  • Text mining
  • Unsupervised and supervised machine learning model development and deployment
  • Advanced data visualisation
  • Self-service interactive dashboard and web app development

Courses and Certificates

This section contains an up-to-date list of links (in alphabetical order) to certificates gained through my commitment to continuous professional development (CPD).

Bioinformatics Courses

Courses Run by Sheffield Bioinformatics Core and RSE Teams

Analysis of RNA-Seq Data in R
Best Practices for Data Management
High Performance Computing: Accessing Resources and Running Software
Introduction to RNA-Seq
Introduction to RNA-Seq in R
Introduction to the Command Line for Bioinformatics

Physalia Courses

Single-cell RNAseq with R/Bioconductor (5th - 9th June 2023)
Spatial Omics in R/Bioconductor (20th - 24th May 2024)
Metabolomics in R: From Study Design to Data Analysis (7th - 10th Oct 2024)

DataCamp Analysing Genomic Data in R Skills Track

Introduction to Bioconductor in R
RNA-Seq with Bioconductor in R
Differential Expression Analysis with Limma in R

Git

Introduction to Git

Python

Learn Python 3

Data Manipulation with Pandas
Intermediate Python
Introduction to Python

R Programming

Career and Skills Tracks

Data Scientist with R
Statistics Fundamentals with R

Courses

Building Web Applications with Shiny in R
Cleaning Data in R
Cluster Analysis in R
Data Manipulation with dplyr
Differential Expression Analysis with limma in R
Exploratory Data Analysis in R
Exploratory Data Analysis in R Applied
Feature Engineering in R
Hypothesis Testing in R
Intermediate Data Visualisation with ggplot2
Intermediate Importing Data in R
Intermediate R
Intermediate Regression in R
Introduction to Bioconductor in R
Introduction to Data Visualisation with ggplot2
Introduction to Importing Data in R
Introduction to R
Introduction to Regression in R
Introduction to Statistics in R
Introduction to the Tidyverse
Introduction to Writing Functions in R
Joining Data with dplyr
Machine Learning in the Tidyverse
Modelling with Tidymodels in R
Reporting with R Markdown
RNA-Seq with Bioconductor in R
Sampling in R
Supervised Learning in R: Classification
Supervised Learning in R: Regression
Unsupervised Learning in R
Working with Dates and Times in R

Unix Shell

Introduction to BASh Scripting
Introduction to Shell

SQL

Introduction to SQL

Other

Introduction to ChatGPT
Introduction to Data Warehousing
Understanding Data Engineering
Understanding Machine Learning

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