Andrew David Beggs

This paper develops a low-matrix co-culture platform to evaluate T cell engager activity in patient-derived CRC organoids, showing dose-dependent cytotoxicity and immune activation across diverse models.

This study identifies PBF/PTTG1IP as an endogenous regulator of cell adhesion, polarity, and directional motility by analyzing knockout models and phosphoproteomic data.

This paper develops an embryonic zebrafish xenograft model to assess the efficacy of multi-receptor tyrosine kinase inhibitors in rhabdomyosarcoma, identifying VEGF-A as a potential biomarker for Regorafenib response.

The paper identifies a 101-biomarker signature predicting radiotherapy response in colorectal cancer using multi-omics and supervised learning, achieving 89% accuracy.

This study shows that HPV18 infection reprograms host transcription by altering CTCF binding and promoter-enhancer interactions, leading to repression of the tumor suppressor CADM1.

The paper investigates how CDKN2A and other 9p21 gene losses influence oesophageal cancer progression, finding context-dependent effects on survival and immune infiltration.

The paper identifies a high-density miR-430 promoter cluster that forms a transcription body, enabling early gene activation during the minor wave of zygotic genome activation in zebrafish.

The paper identifies RAD52 as the mediator of synthetic-lethal interactions between BRCA1/2, 53BP1 deficiencies, and DNA polymerase theta loss in murine cells.

The paper uses clinical-grade whole genome sequencing and 3' transcriptome analysis to identify targetable genomic alterations in colorectal cancer patients.

This study demonstrates that the Illumina Infinium HD methylation assay can reliably detect methylation and copy number variants in low-input DNA samples, including circulating tumour DNA.

The paper evaluates the TruSight Oncology 500 assay for measuring tumour mutational burden and detecting clinically actionable variants, showing strong correlation with whole genome sequencing and orthogonal methods.

This paper introduces a method to predict cancer driver genes using ontology-based features and validates it in nasopharyngeal and colorectal cancers.

The paper introduces conliga, a method for inferring high-resolution SCNA profiles from a low-cost and simple assay, addressing the need for affordable SCNA analysis in clinical settings.

Nanopore-only sequencing of GM12878 across 39 MinION flowcells (91.2 Gb) yielded an assembly with NG50 ∼3 Mb; adding 5× ultra-long reads raised NG50 to 6.4 Mbp.

The paper identifies methylation markers that distinguish non-dysplastic Barrett's oesophagus patients who progress to cancer from those that do not.