Biology subjects

Sung, M.

Publications and source records attributed to Sung, M..

8 recordsLinked to original sources

bioRxiv2025

CRISPR-Induced NUT Suppression Promotes Differentiation and Enhances Trop2-Targeted Immunocytokine Response in NUT Carcinoma

NUT carcinoma (NC) is an aggressive malignancy driven by NUTM1 gene rearrangements with limited therapeutic options. Here, we show that direct suppression of NUTM1 using CRISPR/Cas9 induces squamous-like differentiation and upregulates TROP2 expression in NC cells. Building on this finding, we developed a TROP2-interferon beta (IFN-{beta}) mutein immunocytokine that selectively targets TROP2-expressing tumors. Combined NUTM1 suppression and TROP2-targeted immunotherapy synergistically enhanced cytotoxic and immune-mediated responses in vitro. Transcriptomic and spatial analyses of NC patient tumors revealed that differentiation status correlates with TROP2 expression, upregulated immune pathways, and favorable clinical outcomes. Our results suggest that overcoming differentiation blockade not only alters tumor phenotype but also creates a more immune-permissive microenvironment. These findings highlight the therapeutic potential of sequential tumor reprogramming followed by targeted immunotherapy in treating NC and propose a broader strategy for overcoming differentiation blockade in fusion-driven cancers.

cancer biology↗

bioRxiv2025

Bimodality in pan-cancer proteomics reveals new opportunities for biomarker discovery

Bimodal protein expression, characterized by the distribution of protein expression with two modes, is linked to phenotypic variation across various biological systems. Whereas previous studies focused on RNA expression data, we developed a bimodality model tailored for proteomics to enhance the identification of cancer-associated biomarkers and targets, facilitating precision oncology. We analyzed proteomics data from various cancer types and identified 2401 tumor-associated bimodal proteins. These proteins were evaluated for pathway enrichment, revealing significant associations with critical cancer pathways, such as metabolism of non-essential amino acids, interaction between the extracellular matrix and its receptors on the cell surface, and central carbon metabolism in cancer. Utilizing an AI-enhanced knowledge graph, we further delineated common patterns among pan-cancer tumor-associated bimodal proteins. A case study on the bimodal expression of TROP2 in colon adenocarcinoma highlighted upregulation of MYC and WNT/{beta}-catenin signaling pathways and down-regulation of inflammatory and interferon-related pathways in the TROP2-high group. The biological difference between TROP2-high and TROP2-low groups underscored its significance in determining cancer heterogeneity and differences in cancer vulnerability, which can inform treatment decisions. Our findings show the value of proteomics in uncovering novel biomarkers and advancing precision medicine, setting a precedent for further multi-omics integration and clinical validation.

bioinformatics↗

bioRxiv2024

An endothelial SOX18-mevalonate pathway axis enables repurposing of statins for infantile hemangioma

Infantile hemangioma (IH) is the most common tumor in children and a paradigm for pathological vasculogenesis, angiogenesis and regression. Propranolol is the mainstay of treatment for IH. It inhibits hemangioma vessel formation via a {beta}-adrenergic receptor independent off-target effect of its R(+) enantiomer on the endothelial specific transcription factor sex-determining region Y (SRY) box transcription factor 18 (SOX18). Transcriptomic profiling of patient-derived hemangioma stem cells uncovered the mevalonate pathway (MVP) as a target of R(+) propranolol. Loss of SOX18 function confirmed R(+) propranolol mode of action on the MVP. Functional validation in preclinical IH models revealed that statins - targeting the MVP - are potent inhibitors of hemangioma vessel formation. We propose a novel SOX18-MVP-axis as a central regulator of IH pathogenesis and suggest statin repurposing to treat IH. Our findings reveal novel pleiotropic effects of beta-blockers and statins acting on the SOX18-MVP axis to disable an endothelial specific program in IH, which may impact other scenarios involving pathological vasculogenesis and angiogenesis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/577829v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@f02b2corg.highwire.dtl.DTLVardef@1a2790forg.highwire.dtl.DTLVardef@1ba0318org.highwire.dtl.DTLVardef@1213522_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2024

Exploring Mechanisms of Lipid Nanoparticle-Mucus Interactions in Healthy and Cystic Fibrosis Conditions

Mucus forms the first defense line of human lungs, and as such hampers the efficient delivery of therapeutics to the underlying epithelium. This holds particularly true for genetic cargo such as CRISPR-based gene editing tools which cannot readily surmount the mucosal barrier. While lipid nanoparticles (LNPs) emerged as versatile non-viral gene delivery systems that could help overcome the delivery challenge, many knowledge gaps remain, especially for diseased states such as cystic fibrosis (CF). This study provides fundamental insights into Cas9 mRNA or ribonucleoprotein-loaded LNP-mucus interactions in healthy and diseased states by assessing the impact of the genetic cargo, mucin sialylation, mucin concentration, ionic strength, pH, and polyethylene glycol (PEG) concentration and nature on LNP diffusivity leveraging experimental approaches and Brownian dynamics simulations. Taken together, this study identifies key mucus and LNP characteristics that are critical to enabling a rational LNP design for transmucosal delivery. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/575680v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@10b1c0dorg.highwire.dtl.DTLVardef@5ebce4org.highwire.dtl.DTLVardef@1c34c1corg.highwire.dtl.DTLVardef@b9eb2d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Live Malassezia strains isolated from the mucosa of patients with ulcerative colitis

The human gut is inhabited by a complex ecosystem of diverse microorganisms. While most studies on the gut microbiota have focused on bacteria, accumulating evidence has underscored the role of the mycobiota in inflammatory bowel disease (IBD). This study is the first to isolate and characterize live Malassezia globosa strains from the intestinal mucosa of patients with ulcerative colitis. Malassezia species primarily inhabit the human skin. We therefore compared the M. globosa gut isolates with the M. globosa skin isolates and noted a striking disparity between them. The gut isolates led to a greater exacerbation of colitis in mice. Transcriptome analysis revealed that the gut isolates were more sensitive to normoxia than the skin isolates, suggesting adaptation to hypoxia prevalent in the intestinal environment. These findings provide novel insights into the potential impact of M. globosa on the pathogenesis of IBD and the influence of niche-specific adaptations on its virulence.

microbiology↗

bioRxiv2023

Hypothesis-free phenotype prediction within a genetics-first framework

Cohort-wide sequencing studies have revealed that the largest category of variants is those deemed rare, even for the subset located in coding regions (99% of known coding variants are seen in less than 1% of the population1-3). Our understanding of how rare genetic variants influence disease and organism-level phenotypes has achieved limited progress, partly explained by the intrinsic difficulty in statistically evaluating the biological significance of rare events. Here we show that discoveries can instead be made through a knowledge-based approach using protein domains and ontologies (function and phenotype) that considers all coding variants regardless of allele frequency. We describe an ab initio, genetics-first method making molecular knowledge-based interpretations for exome-wide non-synonymous variants for phenotypes at the organism and cellular level. By using this reverse approach, we identify plausible novel genetic causes for developmental disorders that have eluded other established methods and present novel molecular hypotheses for the causal genetics of 40 phenotypes generated from a direct-to-consumer genotype cohort. This system offers a chance to extract further discovery from genetic data after standard tools have been applied.

genomics↗

bioRxiv2023

Pan-cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics

The National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data is suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolute quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody-drug conjugates and immunotherapeutic agents.

bioinformatics↗

bioRxiv2018

Co-expression of MDM2 and CDK4 in transformed human mesenchymal stem cells induces dedifferentiated liposarcoma potency

Amplification and overexpression of MDM2 and CDK4 are well-known diagnostic criteria of well-differentiated liposarcoma (WDLPS)/dedifferentiated liposarcoma (DDLPS). Although it was reported that depletion of MDM2 or CDK4 decreased proliferation in DDLPS cell lines, it remains unclear whether MDM2 and CDK4 induce WDLPS/DDLPS tumorigenesis. We examined whether MDM2 and/or CDK4 produce WDLPS/DDLPS using transformed human bone marrow stem cells (BMSCs), 2H and 5H, with five oncogenic hits (overexpression of hTERT, TP53 degradation, RB inactivation, c-MYC stabilization, and overexpression of HRASv12). In vitro functional experiments revealed that co-overexpression of MDM2 and CDK4 plays key roles in tumorigenesis by increasing cell growth and migration and inhibiting adipogenic differentiation potency compared to sole expression of MDM2 or CDK4. Using mouse xenograft models, we found that co-overexpression of MDM2 and CDK4 in 5H cells with five additional oncogenic mutations can develop proliferative DDLPS in vivo. Our results suggest that co-overexpression of MDM2 and CDK4 induces DDLPS tumour potency in transformed human BMSCs by accelerating cell growth and migration and blocking adipogenetic potential incooperation with multiple genetic factors.

cancer biology↗