Biology subjects

McInnes, G.

Publications and source records attributed to McInnes, G..

5 recordsLinked to original sources

bioRxiv2025

Time-dependent chromatin maturation during 3D spheroid culture improves preclinical modeling of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the deadliest cancer worldwide. Therapeutic progress stagnate, highlighting the complexity to replicate NSCLC in preclinical models. Drug discovery studies rely mostly on cancer cells in two-dimension (2D), which poorly predict drug efficacy in patients. There is a growing interest in three-dimensional (3D) preclinical models, such as 3D spheroids, to better model tumor phenotype and improve therapeutic prediction. However, a comprehensive view of 3D culture methods impact on transcriptomes, epigenomes and pharmacological responses and their correlations to NSCLC tumors is still missing. Here, we demonstrate that NSCLC spheroids undergo time-dependent transcriptomic and epigenomic changes, which peak after 3 weeks of culture. While DNA methylome remained stable, chromatin methylation and acetylation marks gained features of advanced NSCLC in a time-dependent manner. Single-cell transcriptomic profiling of spheroids demonstrated that time of 3D culture improved the correlation to NSCLC tumors. Moreover, long-term culture of 3D spheroids increased drug screening predictability, by showing resistance to drugs that failed in NSCLC patients (such as HDAC inhibitors) while demonstrating novel pharmacological vulnerabilities and synergistic interactions (such as combination of PRMT and HDAC inhibitors). Strikingly, reverting 3D spheroids back to 2D culture rapidly reversed transcriptomic, epigenetic and pharmacological signatures acquired after 3 weeks of 3D culture, highlighting the critical impact of cell culture conditions on NSCLC phenotype. Collectively, our findings demonstrate that implementing a time-dependent maturation process into 3D spheroid culture induces chromatin and transcriptomic changes that enhance NSCLC preclinical modeling.

cancer biology↗

bioRxiv2019

Hubble2D6: A deep learning approach for predicting drug metabolic activity

Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene whose protein product metabolizes more than 20% of clinically used drugs. Genetic variations in CYP2D6 are responsible for interindividual heterogeneity in drug response that can lead to drug toxicity and ineffective treatment, making CYP2D6 one of the most important pharmacogenes. Prediction of CYP2D6 phenotype relies on curation of literature-derived functional studies to assign a functional status to CYP2D6 haplotypes. As the number of large-scale sequencing efforts grows, new haplotypes continue to be discovered, and assignment of function is challenging to maintain. To address this challenge, we have trained a deep learning model to predict functional status of CYP2D6 haplotypes, called Hubble.2D6. We find that Hubble.2D6 predicts CYP2D6 haplotype functional status with 88% accuracy in a held out test set and explains a significant amount of the variability in in vitro functional data. Hubble.2D6 may be a useful tool for assigning function to haplotypes with uncurated function, which may be used for screening individuals who are at risk of being poor metabolizers.

bioinformatics↗

bioRxiv2018

Targeting MYC Overexpressing Leukemia with Cardiac Glycoside Proscillaridin Through Downregulation of Histone Acetyltransferases

Targeting MYC oncogene remains a major therapeutic goal in cancer chemotherapy. Here, we demonstrate that proscillaridin, a cardiac glycoside approved for heart failure treatment exhibit anticancer selectivity towards high MYC expressing leukemic cell lines and leukemia stem cells. At a clinically relevant concentration, proscillaridin induced a rapid downregulation of MYC protein level, due to a significant decrease in MYC protein half-life. Proscillaridin treatment induced a downregulation of gene sets involved in MYC pathway, and a concomitant upregulation of genes involved in hematopoietic differentiation. Proscillaridin induced a significant loss of lysine acetylation in histone H3 (K9, K14, K18 and K27) and in non-histone proteins such as MYC, MYC target proteins, and a series of histone acetylation regulators. Loss of lysine acetylation correlated with a rapid downregulation of histone acetyltransferase protein levels, involved in histone and MYC acetylation (CBP, P300, GCN5, TIP60, and MOZ), preferentially in MYC overexpressing leukemia as compared to other cancer cells. These results support the repurposing of proscillaridin in MYC overexpressing leukemia and propose a novel strategy to target MYC in cancer.

pharmacology and toxicology↗

bioRxiv2018

Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics

Large biobanks linking phenotype to genotype have led to an explosion of genetic association studies across a wide range of phenotypes. Sharing the knowledge generated by these resources with the scientific community remains a challenge due to patient privacy and the vast amount of data. Here we present Global Biobank Engine (GBE), a web-based tool that enables the exploration of the relationship between genotype and phenotype in large biobank cohorts, such as the UK Biobank. GBE supports browsing for results from genome-wide association studies, phenome-wide association studies, gene-based tests, and genetic correlation between phenotypes. We envision GBE as a platform that facilitates the dissemination of summary statistics from biobanks to the scientific and clinical communities. GBE currently hosts data from the UK Biobank and can be found freely available at biobankengine.stanford.edu.

bioinformatics↗

bioRxiv2017

Medical relevance of protein-truncating variants across 337,208 individuals in the UK Biobank study

Protein-truncating variants can have profound effects on gene function and are critical for clinical genome interpretation and generating therapeutic hypotheses, but their relevance to medical phenotypes has not been systematically assessed. We characterized the effect of 18,228 protein-truncating variants across 135 phenotypes from the UK Biobank and found 27 associations between medical phenotypes and protein-truncating variants in genes outside the major histocompatibility complex. We performed phenome-wide analyses and directly measured the effect of homozygous carriers, commonly referred to as \"human knockouts,\" across medical phenotypes for genes implicated to be protective against disease or associated with at least one phenotype in our study and found several genes with strong pleiotropic or non-additive effects. Our results illustrate the importance of protein-truncating variants in a variety of diseases.

genetics↗