Biology subjects

Chen, H.-Z.

Publications and source records attributed to Chen, H.-Z..

6 recordsLinked to original sources

bioRxiv2026

Hepatobiliary Progenitor-like Reprogramming in Liver Metastases

Metastatic progression requires cancer cells to adapt to the unique constraints of distant organ microenvironments, yet the mechanisms that drive organ-specific adaptations remain poorly understood. Here, we show that the liver actively rewrites metastatic cancer cell identity, driving tumor cells toward a hepatobiliary progenitor-like state. Through integrated transcriptomic, proteomic, metabolomic, and epigenomic analyses of patient-derived rapid-autopsy samples and experimental models, we identify this state as selectively enriched in liver metastases. It is characterized by co-activation of hepatic and biliary/progenitor regulators HNF4A and SOX9 and is observed across multiple epithelial cancers, indicating a conserved response to the hepatic niche. Mechanistically, hepatocyte-derived TGF-{beta} and hypoxia converge to activate a HIF-1-ACLY axis, increasing nuclear acetyl-coenzyme A availability and histone acetylation at hepatic lineage regulatory elements to drive hepatobiliary reprogramming. This coordinated niche-response program can be captured transcriptionally and is associated with inferior overall survival. Disruption of this pathway suppresses hepatic reprogramming and impairs liver metastatic fitness. These findings identify the liver as an active determinant of metastatic cell fate, linking microenvironmental signaling to metabolic and chromatin remodeling programs that enable lineage plasticity. More broadly, they reveal organ-specific reprogramming as a fundamental principle of metastasis and a therapeutic vulnerability in liver metastases.

cancer biology↗

bioRxiv2026

EZH2 Inhibition Reshapes 3D Chromatin Architecture to Induce Immunogenic Phenotype in Small Cell Lung Cancer

BackgroundThe histone methyltransferase EZH2, enzymatic core of the trimeric polycomb repressive complex 2 (PRC2), has been shown to promote small cell lung cancer (SCLC) survival through epigenetic silencing of multiple targets including Class I MHC molecules (HLA-A/B) and DNA repair factors (SLFN11). Treatment of SCLC cells with EZH2 inhibitors in vitro can reactivate expression of these genes and result in therapeutic response to immune checkpoint inhibition (ICI) and chemotherapy. Here, we investigate the impact of EZH1/2 dual inhibition on 3D chromatin structure and its relationship to transcriptional regulation in neuroendocrine (NE) SCLC. ResultsEmploying Micro-C, a micrococcal nuclease-based 3D genome mapping technique, we show that EZH1/2 inhibition with Valemetostat induced significant changes at multiple genome organizational levels (compartment, topological associated domain, and chromatin loop) without incurring cell death in NE SCLC. Alterations in 3D genome permissive for transcriptional activation were correlated with increased chromatin accessibility (ATAC-sequencing) and expression of target genes (transcriptome profiling). Known transcription factor motif discovery revealed enrichment of non-NE motifs (e.g., REST) in regions with gained chromatin accessibility in Valemetostat-treated cells, consistent with results from gene set enrichment analysis demonstrating NE to non-neuroendocrine lineage shift. Notably, EZH1/2 inhibition reactivated Class I MHC expression by facilitating enhancer-promoter looping. ConclusionOur results demonstrate that repression of a subset of EZH2 targets including Class I MHC genes is affected through modulation of 3D genome structure to the level of chromatin looping and further support clinical investigation of EZH2 inhibition in boosting therapeutic efficacy of ICI in SCLC patients.

genomics↗

bioRxiv2025

Plasma Ficolins Enable Liver Macrophages to Capture Blood-Borne Bacteria by Recognizing Capsular Polysaccharides

Ficolins are evolutionarily conserved glycan-binding lectins in plasma or on cell membranes of immune cells, yet their physiological functions remain to be defined. Here we demonstrate that plasma ficolins drives the capture of diverse encapsulated bacteria in the blood circulation by the liver resident macrophages (Kupffer cells). Ficolin-activated immunity in the liver sinusoids provides swift and sterilizing immunity in mice. Mice lacking ficolin-A (the only plasma ficolin) became hypersusceptible to the blood infections of the ficolin-A-recognizable bacterial serotypes. Mechanistically, plasma ficolins activate complement C3 on bacterial surfaces by pattern recognition of acetylated monosaccharides on polysaccharide capsules, and thereby deliver the opsonized bacteria to C3 receptors on Kupffer cells for phagocytic elimination. These findings reveal that plasma ficolins serve as pattern-recognition receptors that are essential for maintaining the bloodstream sterile.

microbiology↗

bioRxiv2025

Moving Beyond Binary Biomarkers: Machine Learning Model Resolves Concurrent and Molecularly Heterogeneous Mismatch Repair and Homologous Recombination Deficiencies in Prostate Cancer

Current DNA damage repair (DDR) biomarkers employ binary classifications that fail to capture the molecular complexity of tumors with concurrent repair deficiencies. We used genomics analysis to stratify 672 metastatic prostate cancer patients into 11 DDR subgroups, identifying 51 molecular signatures with weighted roles in class identity. We identified a tumor-mutational-burden very-high subset, characterized by 19 mutations/Mb or more, as a molecularly distinct group characterized by preserved genomic integrity and enhanced immunogenicity. Critically, 2.3 percent of tumors exhibited concurrent TMB-High and HRR mutant phenotypes, while 1.5 percent harbored MMR bi-allelic loss without MMRd (mismatch-repair-deficiency) signatures. Clinical validation in 130 patients demonstrated superior immunotherapy responses in tumors with very high TMB levels. We developed CHIMERA DDR, a probabilistic machine learning tool that integrates these 51 genomic features using a nested Random Forest architecture to infer seven clinically relevant DDR subgroups. After negating model overfit concerns, CHIMERA-DDR showed exceptional classification performance (AUCs 0.919-0.999) to accurately detect MMRd and HRR mutant molecular subtypes with or without concurrent DDR deficiencies, resolving admixed phenotypes to enable precision therapeutic stratification beyond binary methods.

genomics↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2021

Cancer cell-autonomous cGAS-STING response confers drug resistance

As an evolutionarily conserved DNA-sensing machinery in innate immunity, the cGAS-STING pathway has been reported to play an important role in immune surveillance and tumor suppression. Recent evidence suggests an intriguing tumor- and metastasis-promoting effect of this signaling pathway, either in a cancer cell-autonomous or a cancer cell-nonautonomous, bystander cell-mediated manner. Here, we show a new face of cGAS-STING signaling whose activation in a cancer-cell-autonomous response manner confers drug resistance. Targeted or conventional chemotherapy drug treatment induced cancer cell cytosolic DNA accumulation and triggered subsequent cGAS-STING signaling activation in cancer cell lines and the human cell-derived xenograft tumors. This activation promoted an acquisition and maintenance of drug resistance which was prevented and overcome in vitro and in vivo by blockade of STING signaling. This finding highlights a new face of cGAS-STING signaling and an ability of cancer cells to hijack the evolutionarily conserved inflammatory signaling to counteract drug stress and warrants a caution in combining STING agonist with targeted or conventional chemotherapy drug treatment, a strategy prevailing in current clinical trials. Statement of significancecGAS-STING signaling has long been recognized as playing a key role in triggering antitumor immunity. We reveal a new face of cGAS-STING signaling and an ability of cancer cells autonomously to hijack the evolutionarily conserved inflammatory signaling to counteract drug stress.

cancer biology↗