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Biology subjects

Kuo, D. J.

Publications and source records attributed to Kuo, D. J..

2 recordsLinked to original sources

Heterogeneity in chromatin structure drives core regulatory pathways in B-cell Acute Lymphoblastic Leukemia

B-cell acute lymphoblastic leukemia (B-ALL) is the most common pediatric malignancy. Based on gene expression profiling, B-ALL can be classified into distinct transcriptional subtypes with differing disease outcomes. Many of these transcriptional subtypes are defined by mutations in transcription factors and chromatin-modifying enzymes, but how such diverse mutations lead to distinct transcriptional subtypes remains unclear. To illuminate the chromatin regulatory landscape in B-ALL, we analyzed 3D genome organization, open chromatin, and gene expression in 53 primary patient samples. At the level of 3D genome organization, we identified chromatin interactions that vary across transcriptional subtypes. These sites of variable 3D chromatin interactions correlate with local gene expression changes and are enriched for core drivers of B-ALL observed in genome-wide CRISPR knock-out screens. Sites of variable 3D genome interactions are frequently shared across multiple transcriptional subtypes and are enriched for open chromatin sites found in normal B-cell development but repressed in mature B-cells. Within an individual patient sample, the chromatin landscape can resemble progenitor chromatin states at some loci and mature B-cell chromatin at others, suggesting that the chromatin in B-ALL patient tumor cells is in a partially arrested immature state. By analyzing transcriptomic data from large cohorts of B-ALL patients, we identify gene expression programs that are shared across transcriptional subtypes, associated with B-cell developmental stages, and predictive of patient survival. In combination, these results show that the 3D genome organization of B-ALL reflects B-cell developmental stages and helps illustrate how B-cell developmental arrest interacts with transcriptional subtypes to drive B-ALL.

cancer biology↗

Molecular Signatures for Microbe-Associated Colorectal Cancers

BackgroundGenetic factors and microbial imbalances play crucial roles in colorectal cancers (CRCs), yet the impact of infections on cancer initiation remains poorly understood. While bioinformatic approaches offer valuable insights, the rising incidence of CRCs creates a pressing need to precisely identify early CRC events. We constructed a network model to identify continuum states during CRC initiation spanning normal colonic tissue to pre-cancer lesions (adenomatous polyps) and examined the influence of microbes and host genetics. MethodsA Boolean network was built using a publicly available transcriptomic dataset from healthy and adenoma affected patients to identify an invariant Microbe-Associated Colorectal Cancer Signature (MACS). We focused on Fusobacterium nucleatum (Fn), a CRC-associated microbe, as a model bacterium. MACS-associated genes and proteins were validated by RT-qPCR, RNA seq, ELISA, IF and IHCs in tissues and colon-derived organoids from genetically predisposed mice (CPC-APCMin+/-) and patients (FAP, Lynch Syndrome, PJS, and JPS). ResultsThe MACS that is upregulated in adenomas consists of four core genes/proteins: CLDN2/Claudin-2 (leakiness), LGR5/leucine-rich repeat-containing receptor (stemness), CEMIP/cell migration-inducing and hyaluronan-binding protein (epithelial-mesenchymal transition) and IL8/Interleukin-8 (inflammation). MACS was induced upon Fn infection, but not in response to infection with other enteric bacteria or probiotics. MACS induction upon Fn infection was higher in CPC-APCMin+/- organoids compared to WT controls. The degree of MACS expression in the patient-derived organoids (PDOs) generally corresponded with the known lifetime risk of CRCs. ConclusionsComputational prediction followed by validation in the organoid-based disease model identified the early events in CRC initiation. MACS reveals that the CRC-associated microbes induce a greater risk in the genetically predisposed hosts, suggesting its potential use for risk prediction and targeted cancer prevention.

microbiology↗