Biology subjects

Chan, A. S.

Publications and source records attributed to Chan, A. S..

4 recordsLinked to original sources

bioRxiv2024

Divergent lineage trajectories and genetic landscapes in human gastric intestinal metaplasia organoids associated with early neoplastic progression

ObjectiveGastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. DesignA large human gastric IM organoid (IMO) cohort (n=28) was established, along with normal gastric organoids (n=42) for comparison, and comprehensive multi-omics profiling and functional characterization were performed. ResultsSingle-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation, and unveiled lineage trajectories that connected different cycling and quiescent stem and progenitors, highlighting their differences in gastric to IM transition. The hybrid IMO cells showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were found to be highly similar to those derived from IMOs and exhibited fetal signature. Genomically, IMOs showed an elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs downregulated FGFR2 and became independent of FGF10 for survival. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, which could represent the earliest neoplastic precursor of IM-induced gastric cancer. ConclusionsOverall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and its neoplastic progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

cancer biology↗

bioRxiv2023

Benchmarking the translational potential of spatial gene expression prediction from histology

Spatial transcriptomics has enabled the quantification of gene expression at spatial coordinates, offering crucial insights into molecular underpinnings of diseases. In light of this, several methods predicting spatial gene expression from paired histology images have offered the opportunity of enhancing the utility of readily obtainable and cost-effective haematoxylin-and-eosin-stained histology images. To this end, we conducted a comprehensive benchmarking study encompassing six developed methods. These methods were reproduced and evaluated using HER2-positive breast tumour and human cutaneous squamous cell carcinoma datasets, followed by external validation using The Cancer Genome Atlas data. Our evaluation incorporates diverse metrics which capture the performance of predicted gene expression, model generalisability, translational potential, usability and computational efficiency of each method. Our findings demonstrate the capacity of methods to spatial gene expression from histology and highlight key areas that can be addressed to support the advancement of this emerging field.

bioinformatics↗

bioRxiv2021

Identifying cellular-to-phenotype associations by elucidating hierarchical relationships in high-dimensional cytometry data

High-throughput single cell technologies hold the promise of discovering novel cellular relationships with disease. However, analytical workflows constructed for these technologies to associate cell proportions with disease often employ unsupervised clustering techniques that overlook the valuable hierarchical structures that have been used to define cell types. We present treekoR, a framework that empirically recapitulates these structures, facilitating multiple quantifications and comparisons of cell type proportions. Our results from twelve case studies reinforce the importance of quantifying proportions relative to parent populations in the analyses of cytometry data -- as failing to do so can lead to missing important biological insights.

bioinformatics↗

bioRxiv2019

Transcription-driven cohesin repositioning rewires chromatin loops in cellular senescence

Senescence is a phenotypic state of stable proliferative arrest, typically occurring in lineage-committed cells and triggered by various stimuli. It is generally accompanied by activation of a secretory program (senescence-associated secretory phenotype, SASP), which modulates both local (tissue microenvironment) and systemic (ageing) homeostasis1,2. Enhancer-promoter interactions play a key role in gene regulation3-5, facilitated by chromatin loops, mostly formed via CCCTC binding factor (CTCF) and cohesin tethering6-8. The three-dimensional chromatin structure of senescent cells has been characterised9-11 mostly in terms of macro-domain structures, but its relevance in gene expression remains elusive. Here, we use Hi-C and capture Hi-C12,13 to show that oncogenic HRAS-induced senescence (RIS) in human diploid fibroblasts (HDFs) is accompanied by extensive enhancer-promoter rewiring, which is closely connected with dynamic cohesin binding to the genome. We find de novo cohesin peaks at the 3 end of a subset of active genes, reminiscent of the transcription-driven cohesin islands recently discovered in mouse embryonic fibroblasts deficient in both CTCF and the cohesin release factor Wings apart-like (Wapl)14. RIS de novo cohesin peaks are also transcription-dependent and enriched for SASP genes, as exemplified by IL1B, where de novo cohesin binding is involved in new loop formation. Cytokine induction is associated with similar cohesin islands appearance and enhancer-promoter rewiring during the terminal differentiation of monocytes to macrophages15, but not upon acute TNF treatment of HDFs16. These results suggest that RIS represents a fate-determined process in which gene expression is regulated beyond the cell type specific 3D chromatin framework, in part through cohesin redistribution.

molecular biology↗