Biology subjects

Duong, B.

Publications and source records attributed to Duong, B..

5 recordsLinked to original sources

bioRxiv2026

X-SPEAR: An Extensible Framework for Spatial Panel Evaluation and Refinement

Targeted spatial transcriptomics platforms such as Xenium require a predefined gene panel, and the genes in that panel are detected less efficiently, and to gene-specific degrees, in the spatial assay than in the single-cell reference used to choose them. We present X-SPEAR, a framework that couples DART marker selection with probe-level off-target assessment. DART learns short, interpretable Boolean gene rules and assembles several gene-disjoint rules per cell type. Its detection-aware training thins the reference to per-gene detection rates measured in a different, already completed experiment, so no Xenium data from the target tissue are needed before the panel is ordered. On held-out Xenium data from ovarian cancer, mouse brain and cervical cancer, DART substantially outperformed existing marker-selection methods at matched panel size, by 0.04-0.11 macro-F1 over Wilcoxon rank-sum, 0.04-0.08 over COSG and 0.10-0.18 over NS-Forest, and it reached Wilcoxon's best accuracy with 42-69% fewer genes. Ablations show that most of this gain comes from detection-aware training, which also improves other rank-based selectors and requires a detection profile measured with the same assay chemistry. At similar accuracy, DART's rule structure adds rules that faithfully summarise the downstream classifier, robustness to single-probe loss across 45 retinal ganglion cell subtypes, and better resolution of closely related cell states. We are applying X-SPEAR to design a Xenium panel for mouse retinal ganglion cell subtypes, and its in situ evaluation is in progress. X-SPEAR is available as an open-source Python package.

genomics↗

bioRxiv2026

A phylogeny-guided framework for decoding mechanisms of human endogenous retrovirus regulation in health and disease

Human endogenous retroviruses (HERVs) are remmants of ancient infections which make up to [~]8% of the human genome. Their activity influences development, immunity, and cancer, but studying them has been limited by a key technical challenge: short-read sequencing cannot uniquely assign reads to these highly repetitive elements. Here, we present ERVmancer, a phylogeny-informed method that resolves the read-mapping ambiguity and quantifies HERV expression across scales, from individual loci to entire retroviral clades, depending on mapping confidence. Benchmarking with sample-matched long- and short-read data generated in this study demonsrates that ERVmancer outperforms existing approaches in both sensitivity and specificity. Application of ERVmancer recapitulates known HERV expression patterns in multiple sclerosis and uncovers new biology in breast cancer, including suppression of HERVH-LTR7 by p53. By enabling accurate and scalable quantification of integrated retroviral elements, ERVmancer provides a broadly applicable resource for investigating retroviral mechanisms in health and disease.

bioinformatics↗

bioRxiv2025

Taxonomy-free fecal microbiome profiles enable robust prediction of immunotherapy response and toxicity in melanoma

The gut microbiome has been causally linked to the efficacy of immune-checkpoint inhibitor therapy (ICI), prompting numerous clinical trials of microbiome-targeting strategies. Yet, mechanisms by which gut microbiota shape immune responses remain elusive as taxonomic biomarkers have failed to generalize across multiple cohorts. In this study, we develop a taxonomy-agnostic framework to identify microbial biomarkers of ICI response and immune-related adverse event (irAE) occurrence from metagenomic sequencing. Applying this approach to four independent melanoma cohorts from clinical centers across the United States, we uncover gut microbial proteins produced by diverse bacterial taxa that consistently predict ICI response. Notably, we uncover a previously uncharacterized operon involved in cellular redox homeostasis that is encoded by different bacteria and reliably predicts irAE occurrence. We further validated the predictive power of this operon in a prospectively sequenced melanoma cohort. Our results demonstrate that taxa-agnostic microbial protein biomarkers are robust, generalizable, and provide a path towards pretreatment risk stratification for melanoma patients initiating ICI therapy.

cancer biology↗

bioRxiv2025

LRH-1 is a novel regulator of neutrophil-driven immune responses within the tumor microenvironment.

Elevated plasma cholesterol levels have been linked to worse outcomes in breast and ovarian cancer. Prior work including our own has demonstrated that myeloid immune cells are highly responsive to cholesterol fluctuations and to proteins involved in cholesterol regulation. However, the specific roles of Liver Receptor Homolog-1 (LRH-1, or NR5A2), a key transcriptional regulator of cholesterol homeostasis, within myeloid cells remains largely undefined. Interestingly, LRH-1 mRNA levels are reduced in both breast and ovarian tumors compared to normal tissue. Its elevated expression within tumors is associated with increased survival time. These clinical correlations prompted us to explore the role of LRH-1 in myeloid cells particularly in the context of breast and ovarian cancer progression. Initial analyses confirmed LRH-1 expression in various myeloid cell types, with particularly high levels in neutrophils. We therefore focused on how LRH-1 influences neutrophil behaviors relevant to cancer, including migration, NETosis, phagocytosis, and interactions with T cells. Small molecule ligands for LRH-1 regulated neutrophil migration towards cancer cells. Phagocytosis was also regulated by LRH-1 small molecule ligands, the extent being dependent on type of bait (e. coli vs. cancer cells). In T cell co-cultures, neutrophils pretreated with an LRH-1 agonist promoted greater T cell expansion - particularly in CD4 cells - while LRH-1 inhibition suppressed this response. Moreover, LRH-1 activation reduced NETosis, while treatment with an antagonist or inverse agonist enhanced NETosis. Treatment of mice with an inverse agonist of LRH-1 increased the growth of 4T1 and E0771 mammary tumors. Given prior evidence that neutrophils contribute to the recurrence of dormant lesions, we further examined the role of LRH-1 in this context. Mice harboring dormant D2.0R mammary cancer lesions treated with an LRH-1 inverse agonist exhibited earlier tumor recurrence and enhanced metastatic progression compared to vehicle-treated controls. In contrast, treatment with BL001, a small chemical LRH-1 agonist, delayed recurrence in D2.0R-grafted mice. Collectively, these findings reveal that LRH-1 is a novel regulator of neutrophil-driven immune responses within the tumor microenvironment. LRH-1 thus remerges as a promising therapeutic target to suppress metastasis or prevent recurrence in breast cancer.

cancer biology↗

bioRxiv2021

Genome-wide in vivo screen of circulating tumor cells identifies SLIT2 as a regulator of metastasis

Circulating tumor cells (CTCs) break free from primary tumors and travel through the bloodstream and lymphatic system to seed metastatic tumors, which are the major cause of death from cancer. The identification of the major genetic factors that enhance production and persistence of CTCs in the bloodstream at a whole genome level would enable more comprehensive molecular mechanisms of metastasis to be elucidated and the identification of novel therapeutic targets, but this remains a challenging task due to the heterogeneity and extreme rarity of CTCs. Here, we describe the first in vivo genome-wide CRISPR KO screen using CTCs directly isolated from a mouse xenograft. This screen elucidated SLIT2 - a gene encoding a secreted protein acting as a cellular migration cue - as the most significantly represented gene knockout in the CTC population. SLIT2 knockout cells are highly metastatic with hypermigratory and mesenchymal phenotype. Reduced expression of SLIT2 is observed in human tumors, indicating its role as a negative modulator of tumor progression and metastasis.

cancer biology↗