Biology subjects

Van, C.

Publications and source records attributed to Van, C..

5 recordsLinked to original sources

bioRxiv2025

Myeloid-specific TFAM deficiency drives mitochondrial DNA stress and exacerbates allergic airway inflammation

Asthma is the most prevalent chronic inflammatory lung disease in adolescents and young adults, characterized by persistent airway inflammation and remodeling. Increasing evidence indicates that activated lung macrophages play a significant role in the initiation, intensity, progression, and resolution of allergic airway inflammation. However, the underlying mechanisms regulating macrophage-mediated inflammation in asthma remain incompletely understood. Our previous work revealed increased mitochondrial DNA (mtDNA) depletion and mitochondrial damages in the lungs of asthmatic mice, implicating mitochondrial dysfunction in disease pathogenesis. Given that mitochondrial transcription factor A (TFAM) is essential for mtDNA maintenance and integrity, we hypothesized that TFAM has a fundamental role in regulating mtDNA stress and downstream inflammtroy response in asthma. Using myeloid-specific TFAM knockout (TFAMfl/flLysMcre, TFAM KO) mice subjected to allergens sensitization and challenge, we observed pronounced mitochondrial dysfunction and accentuated asthmatic inflammation. This was accompanied by elevated expression of asthma-associated mediators, including il-13, muc5a/c, muc5b, and ccl17. In addition, TFAM deficiency was associated with increased eosinophilia and and cytosolic mtDNA release, contributing to exacerbated airway pathology. Together, we have identified a critical role of TFAM in myeloid cells that contributes to asthmatic airway inflammation. These results suggest that therapeutic restoration of TFAM function may offer a novel strategy to mitigate mitochondrial stress, reduce airway inflammation, and improve outcomes in patients with moderate to severe asthma.

immunology↗

bioRxiv2024

Colorectal Cancer Stem Cell Subtypes Orchestrate Distinct Tumor Microenvironments

SummarySeveral classification systems have been developed to define tumor subtypes in colorectal cancer (CRC). One system proposes that tumor heterogeneity derives in part from distinct cancer stem cell populations that co-exist as admixtures of varying proportions. However, the lack of single cell resolution has prohibited a definitive identification of these types of stem cells and therefore any understanding of how each influence tumor phenotypes. Here were report the isolation and characterization of two cancer stem cell subtypes from the SW480 CRC cell line. We find these cancer stem cells are oncogenic versions of the normal Crypt Base Columnar (CBC) and Regenerative Stem Cell (RSC) populations from intestinal crypts and that their gene signatures are consistent with the "Admixture" and other CRC classification systems. Using publicly available single cell RNA sequencing (scRNAseq) data from CRC patients, we determine that RSC and CBC cancer stem cells are commonly co-present in human CRC. To characterize influences on the tumor microenvironment, we develop subtype-specific xenograft models and we define their tumor microenvironments at high resolution via scRNAseq. RSCs create differentiated, inflammatory, slow growing tumors. CBCs create proliferative, undifferentiated, invasive tumors. With this enhanced resolution, we unify current CRC patient classification schema with TME phenotypes and organization. O_LITwo cancer stem cell subtypes are isolated and determined to be commonly found as mixed populations in human CRC C_LIO_LIThe heterogeneous SW480 cell line models and unifies two binary cancer stem cell classifications of colorectal cancer C_LIO_LIHigh resolution analysis of xenograft tumors reveals that CRC stem cells are dominant, context-independent organizers of their TME C_LIO_LIRSC/YAP/STAT3-positive CRC stem cells create differentiated tumors that attempt tissue generation via an inflammatory, angiogenic, oncofetal program C_LIO_LICBC/MYC-positive CRC stem cells create tumors that are proliferative, undifferentiated, and invasive C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/591144v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@166735aorg.highwire.dtl.DTLVardef@11f3e55org.highwire.dtl.DTLVardef@354a4forg.highwire.dtl.DTLVardef@a18ab1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Leveraging genetic correlation structure to target discrete signaling mechanisms across metabolic tissues

Abstract/IntroductionInter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Beginning with the discovery of insulin over a century ago, characterization of molecules responsible for signal between tissues has required careful and elegant experimentation where these observations have been integral to deciphering physiology and disease. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. For example, physiologic dissection of the actions of soluble proteins such as proprotein convertase subtilisin/kexin type 9 (PCSK9) and glucagon-like peptide 1 (GLP1) have yielded among the most promising therapeutics to treat cardiovascular disease and obesity, respectively1-4. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by "brute-force" surveys of all genes within RNA-sequencing measures across tissues within a population5-9. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. Variation of genes such as FGF21, ADIPOQ, GCG and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as Gene-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways and network architectures across metabolic organs.

physiology↗

bioRxiv2022

Genetic variation of human myokine signaling is dominated by biologic sex and sex hormones

Abstract/IntroductionProteins secreted from skeletal muscle, termed myokines, allow muscle to impact systemic physiology and disease. Myokines play critical roles in a variety of processes, including metabolic homeostasis, exercise improvements, inflammation, cancer and cognitive functions1-6. Despite the clear relevance of these factors in mediating a multitude of physiological outcomes, the genetic architecture, regulation and functions of myokines, as well as degree of conservation of these communication circuits remains inadequately understood. Given that biologic sex controls critical aspects of nearly every physiologic outcome, it is essential to consider when relating specific mechanisms to complex genetic and metabolic interactions. Specifically, many metabolic traits impacted by myokines show striking sex differences arising from hormonal7-10, genetic7,11 or gene-by-sex interactions12,13. In this study, we performed a genetic survey of myokine gene regulation and cross-tissue signaling in humans where sex as a biological variable was emphasized. While expression levels of a majority of myokines and cell proportions within skeletal muscle showed little differences between males and females, nearly all significant cross-tissue enrichments operated in a sex-specific or hormone-dependent fashion; in particular, with estrogens. These sex- and hormone-specific effects were consistent across key metabolic tissues: liver, pancreas, hypothalamus, intestine, heart, visceral and subcutaneous adipose tissue. Skeletal muscle estrogen receptor enrichments across metabolic tissues appeared stronger than androgen receptor and, surprisingly, ~3-fold higher in males compared to females. To define the causal roles of estrogen signaling on myokine gene expression and functions, we generated male and female mice which lack estrogen receptor (Esr1) specifically in skeletal muscle and integrated global RNA-Sequencing with human data. These analyses highlighted mechanisms of sex-dependent myokine signaling conserved between species, such as myostatin enriched for divergent substrate utilization pathways between sexes. Several other sex-dependent mechanisms of myokine signaling were uncovered, such as muscle-derived TNF exerting stronger inflammatory signaling in females compared to males and GPX3 as a male-specific link between glycolytic fiber abundance and hepatic inflammation. Collectively, we provide the first genetic survey of human myokines and highlight sex and estrogen receptor signaling as critical variables when assaying myokine functions and how changes in cell composition impact other metabolic organs.

physiology↗

bioRxiv2021

Genome-wide analysis of mitochondrial DNA copy number reveals multiple loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses were used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 x 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 x 10-8) and mtDNA replication (p = 1.2 x 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 x 10-4).

genetics↗