Biology subjects

Chow, K.-H.

Publications and source records attributed to Chow, K.-H..

5 recordsLinked to original sources

bioRxiv2026

Reactivation of a TAL1 progenitor cell enhancer region by non-coding somatic variants in T-lineage acute lymphoblastic leukemia

Aberrant activation of TAL1, a key oncogenic driver, defines a major subgroup comprising [~]30% of childhood T-lineage acute lymphoblastic leukemias (T-ALLs). We and others have shown that somatic non-coding mutations within upstream and intronic cis-regulatory regions of TAL1 contribute to transformation by creating binding sites for MYB and other transcription factors. Here we investigated cis-regulatory mechanisms mediated by somatic mutations occurring in an intergenic region located 29 kilobase pairs downstream of the canonical TAL1 transcription initiation site, implicated in 6% of TAL1-expressing T-ALLs. These somatic variants include i) complex indels resulting in de novo MYB transcription factor binding sites (TFBSs) and ii) internal tandem duplications (ITDs) encompassing canonical MYB TFBSs. Chromatin immunoprecipitation sequencing (ChIP-seq) revealed binding of the TAL1 core regulatory circuit (CRC) transcription factors MYB, GATA3, and RUNX1, resulting in enhancer activity mediated by sequences with the mutant allele. Strikingly, ChIP-seq peaks for the repressive H3K27me3 mark and the active H3K27ac mark co-existed across TAL1 regulatory sequences but enriched for different haplotypes. TAL1 transcription from the mutant haplotype initiated from a promoter located within exon 4 of the canonical TAL1 transcript, resulting in a short isoform normally expressed by hematopoietic stem cells (HSC). Interestingly, neither the isoform expression nor the enhancer activity could be predicted by the sequence-to-function deep learning artificial intelligence (AI) model AlphaGenome, emphasizing the importance of experimental validation. Our findings indicate that selection for cis-regulatory, non-coding variants leads to reactivation of enhancers normally active in HSC but silenced in differentiated lineages during normal hematopoietic cell development.

cancer biology↗

bioRxiv2024

Towards a new standard in genomic data privacy: a realization of owner-governance

With the rapid developments in sequencing technologies, individuals now have unprecedented access to their genomic data. However, existing data management systems or protocols are inadequate for protecting privacy, limiting individuals control over their genomic information, hindering data sharing, and posing a challenge for biomedical research. To fill the gap, an owner-governed system that fulfills owner authority, lifecycle data encryption, and verifiability at the same time is prompted. In this paper, we realized Governome, an owner-governed data management system designed to empower individuals with absolute control over their genomic data during data sharing. Governome uses a blockchain to manage all transactions and permissions, enabling data owners with dynamic permission management and to be fully informed about every data usage. It uses homomorphic encryption and zero-knowledge proofs to enable genomic data storage and computation in an encrypted and verifiable form for its whole lifecycle. Governome supports genomic analysis tasks, including individual variant query, cohort study, GWAS analysis, and forensics. Query of a variants genotype distribution among 2,504 1kGP individuals in Governome can be efficiently completed in under 18 hours on an ordinary server. Governome is an open-source project available at https://github.com/HKU-BAL/Governome.

bioinformatics↗

bioRxiv2024

Measuring single-cell density with high throughput enables dynamic profiling of immune cell and drug response from patient samples

Cell density, the ratio of cell mass to volume, is an indicator of molecular crowding and therefore a fundamental determinant of cell state and function. However, existing density measurements lack the precision or throughput to quantify subtle differences in cell states, particularly in primary samples. Here we present an approach for measuring the density of 30,000 single cells per hour with a precision of 0.03% (0.0003 g/mL) by integrating fluorescence exclusion microscopy with a suspended microchannel resonator. Applying this approach to human lymphocytes, we discovered that cell density and its variation decrease as cells transition from quiescence to a proliferative state, suggesting that the level of molecular crowding decreases and becomes more regulated upon entry into the cell cycle. Using a pancreatic cancer patient-derived xenograft model, we found that the ex vivo density response of primary tumor cells to drug treatment can predict in vivo tumor growth response. Our method reveals unexpected behavior in molecular crowding during cell state transitions and suggests density as a new biomarker for functional precision medicine.

bioengineering↗

bioRxiv2021

FGFR inhibitor mediated dismissal of SWI/SNF complexes from YAP-dependent enhancers induces adaptive therapeutic resistance

How cancer cells adapt to evade the therapeutic effects of drugs targeting oncogenic drivers is poorly understood. Here we report an epigenetic mechanism leading to the adaptive resistance of triple-negative breast cancer (TNBC) to fibroblast growth factor receptor (FGFR) inhibitors. Prolonged FGFR inhibition suppresses the function of BRG1-dependent chromatin remodeling leading to an epigenetic state that derepresses YAP-associated enhancers. These chromatin changes induce the expression of several amino acid transporters resulting in increased intracellular levels of specific amino acids that reactivate mTORC1. Collectively, these findings reveal a novel feedback loop involving an epigenetic state transition and metabolic reprogramming that leads to adaptive therapeutic resistance.

cancer biology↗

bioRxiv2020

Functional drug susceptibility testing based on biophysical measurements predicts patient outcome in glioblastoma patient-derived neurosphere models

Functional precision medicine aims to match each cancer patient to the most effective treatment by performing ex vivo drug susceptibility testing on the patients tumor cells. Despite promising feasibility studies, functional drug susceptibility testing is not yet used in clinical oncology practice to make treatment decisions. Often, functional testing approaches have measured ex vivo drug response using metabolic assays such as CellTiter-Glo, which measures ATP as a proxy for numbers of viable cells. As a complement to these existing metabolic drug response assays, we evaluated whether biophysical assays based on cell mass (the suspended microchannel resonator mass assay) or size as measured by microscopy (the IncuCyte assay) could be used as a readout for ex vivo drug response. Using these biophysical assays, we profiled the ex vivo temozolomide responses of a retrospective cohort of 70 glioblastoma patient-derived neurosphere models with matched clinical outcomes and found that both biophysical assays predicted patients overall survival with similar power to MGMT promoter methylation, the clinical gold standard biomarker for predicting temozolomide response in glioblastoma. These findings suggest that biophysical assays could be a useful complement to existing metabolic approaches as "universal biomarkers" to measure sensitivity or resistance to anti-cancer drugs with a wide variety of cytostatic or cytotoxic mechanisms. One-sentence summaryBy using biophysical assays to perform ex vivo drug susceptibility testing on 70 glioblastoma patient-derived neurosphere models, we find that functional testing predicts the duration that patients survive when treated with temozolomide, the standard of care chemotherapy.

cancer biology↗