Biology subjects

Hoon, D. S. B.

Publications and source records attributed to Hoon, D. S. B..

4 recordsLinked to original sources

bioRxiv2026

CRTC, not phosphorylated CREB1, drives cAMP-induced transcription across diverse cell types

Specialized cell types layer cell-type-restricted proteins, metabolites, and organelles onto a shared foundation of core cellular processes. How this ubiquitous machinery generates lineage-specific outputs is central to both cell biology and therapeutic development. G-protein-coupled receptors (GPCRs) respond to receptor-restricted ligands to drive cell-type-specific transcription through cAMP-mediated activation of protein kinase A (PKA), which activates the transcription factor CREB1 through two parallel modes: direct phosphorylation at serine 133, and inhibition of salt-inducible kinases (SIK) that restrain the CRTC coactivators. How these modes integrate and contribute to signaling across cell types has remained unresolved, obscured by genetic redundancy and essentiality. Here we combine focused genetic analyses with a cross-lineage transcriptomic survey to dissect these parallel inputs. In Creb1/Atf1/Crem triple-knockout cells, a non-phosphorylatable mutant CREB1S133A fully rescued endogenous target gene activation, while Crtc1/Crtc2/Crtc3 ablation abolished transcription even with intact CREB1 serine 133 phosphorylation. As part of this mechanism, we found the annotated repressor ICER can instead act as a positive regulator, substituting for full-length CREB1 paralogs to drive a feedforward loop. Across melanocytes, hepatocytes, osteocytes, macrophages, and neurons, SIK inhibition recapitulated cAMP-PKA-driven transcription across both shared and cell-type-specific gene expression programs, with neurons a notable exception. These results invert the canonical model, placing CRTC recruitment as the dominant driver of CREB1-mediated transcription across diverse lineages, reframing how cAMP-PKA signaling can be interpreted and therapeutically targeted.

cell biology↗

bioRxiv2026

Single-cell lineage tracing maps clonal and transcriptional dynamics in melanoma metastasis

Melanoma metastasis is driven by extensive intratumoral heterogeneity and phenotypic plasticity, yet how clonal identity relates to transcriptional programs during metastasis remains unclear. Here, we applied MeRLin, a single-cell lineage tracing platform, to dissect the clonal and transcriptional heterogeneity of metastatic melanoma in a patient-derived spontaneous metastasis model. Clonal analyses revealed hierarchical structures during tumor progression, with a subset of lineages from primary tumors consistently enriched across metastatic sites, supporting a model of polyclonal seeding followed by selective expansion of pre-existing highly metastatic subpopulations. Single-cell transcriptomic profiling identified two major metastatic subpopulations of distinct transcriptional programs, characterized by neural crest stem cell-like and lipid metabolism signatures. Both programs were enriched for invasion-associated genes and maintained across organs through distinct regulatory networks. Spatial mapping by barcode RNA-FISH linked these transcriptional states to their tissue context and showed that OLFML3 expression partially co-localized with a dominant subpopulation at the tumor-liver interface, marking the invasive fronts of metastatic growth. Together, these findings establish a framework in which clonal identity, transcriptional state, and spatial organization jointly shape metastatic melanoma progression.

cancer biology↗

bioRxiv2022

DNA methylome combined with chromosome cluster-oriented analysis provides an early signature for cutaneous melanoma aggressiveness

Aberrant DNA methylation is a well-known feature of tumours and has been associated with metastatic melanoma. However, since melanoma cells are highly heterogeneous, it has been challenging to use affected genes to predict tumour aggressiveness, metastatic evolution, and patients outcomes. We hypothesized that common aggressive hypermethylation signatures should emerge early in tumorigenesis and should be shared in aggressive cells, independent of the physiological context under which this trait arises. We compared paired melanoma cell lines with the following properties: (i) each pair comprises one aggressive counterpart and its parental cell line, and (ii) the aggressive cell lines were each obtained from different host and their environment (human, rat, and mouse), though starting from the same parent cell line. Next, we developed a multi-step genomic pipeline that combines the DNA methylome profile with a chromosome cluster-oriented analysis. A total of 229 differentially hypermethylated genes were commonly found in the aggressive cell lines. Genome localization analysis revealed hypermethylation peaks and clusters, identifying eight hypermethylated gene promoters for validation in tissues from melanoma patients. Five CpG identified in primary melanoma tissues were transformed into a DNA methylation score that can predict survival (Log-rank test, p=0.0008). This strategy is potentially universally applicable to other diseases involving DNA methylation alterations.

cancer biology↗

bioRxiv2018

Epigenetic Profiling for the Molecular Classification of Metastatic Brain Tumors

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet these challenges, we generated genome-scale DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n=96). Using supervised machine learning and integration of multiple DNA methylomes from normal, primary, and metastatic tumor specimens (n=1,860), we unraveled epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically-relevant subtypes. BrainMETH predictions were supported by routine histopathologic evaluation. We further characterized and validated the most predictive genomic regions in a large cohort of brain tumors (n=165) using quantitative methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

cancer biology↗