Biomedical subjects

Ye Chen

Publications and source records attributed to Ye Chen.

5 recordsLinked to original sources

PubMed2026

Driver genomic lesions in MDM2, CDK4, and JUN co-opt targetable super-enhancer networks to impose liposarcomagenic core regulatory circuitry.

INTRODUCTION: Amplification of chromosome 12q13-15 spanning MDM2 and CDK4 genes serves as a molecular diagnostic hallmark of dedifferentiated liposarcoma (DDLPS), an aggressive soft-tissue sarcoma. Epigenetic activation of master transcription factors (RUNX proteins, FOSL2, and MYC) establishes a self-reinforcing oncogenic transcriptional circuitry in DDLPS. Nevertheless, the collaborative interplay between genomic alterations and epigenetic dysregulation in defining DDLPS cell identity remains elusive. OBJECTIVES: This work aimed to elucidate the primary genetic drivers and mechanistic basis of DDLPS-specific core transcriptional regulatory circuitry. METHODS: We performed integrative chromatin profiling analysis of DDLPS clinical specimens and cell lines to map cis-regulatory landscapes. Cistromes of MDM2, JUN, and E2F1 were delineated through chromatin immunoprecipitation sequencing in two DDLPS models. Essential driver functions and transcriptional regulatory effects of key regulators were assessed via various genetic manipulation approaches. Synergistic interactions between BET-targeting agents and MDM2/p53 or CDK4 inhibitors were quantified by cell viability assays. In vivo xenograft assays evaluated the oncogenic potential of key regulators and the therapeutic efficacy of novel strategies. RESULTS: Co-amplification of MDM2, CDK4, and JUN during sarcomagenesis converges with BET protein-dependent chromatin remodeling to fuel feed-forward transcriptional circuits among master transcription factors. Mechanistically, excessively expressed MDM2 stabilizes the core regulatory circuitry by forming chromatin-bound complexes with JUN/FOSL2 at cis-regulatory elements, especially super-enhancers across DDLPS genome. Concurrently, CDK4 maintains expression of E2F1 which further fosters transcriptional output of master transcription factors in DDLPS cells. Leveraging DDLPS-selective overexpression of MDM2 and its E3 ligase activity, targeted degradation of BET proteins by MDM2-recruiting proteolysis targeting chimera selectively disrupted the core regulatory circuitry, suppressing DDLPS growth and exhibiting strong synergy with CDK4 inhibitor. CONCLUSION: DDLPS-associated genomic lesions collaborate with BET-dependent chromatin regulation to establish disease-sustaining transcriptional circuitry. Our findings also provide a mechanistic rationale for harnessing MDM2's E3 ligase activity to therapeutically degrade oncoproteins in MDM2-amplified malignancies.

Core transcriptional regulatory circuitry↗

PubMed2026

Screening of molecular biomarkers ASPN and LBH and construction of a prediction nomogram for the progression of esophagogastric junction adenocarcinoma.

BACKGROUND: Esophagogastric junction adenocarcinoma (EGJA) is an aggressive malignancy of the digestive system with poor prognosis. Early diagnosis and accurate prediction of tumor progression remain major clinical challenges. This study aimed to identify and validate molecular biomarkers and construct a precise diagnostic model, providing a scientific basis for individualized treatment. METHODS: Differentially expressed genes (DEGs) associated with EGJA were identified using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was then performed for further screening. The protein expression levels of ASPN and LBH were validated by immunohistochemistry in both tumor and adjacent non-tumor tissues. A nomogram was constructed by integrating clinical and pathological features, and its performance and clinical utility were assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). RESULTS: Immunohistochemistry demonstrated that the protein expression of ASPN was significantly upregulated in tumor tissues, with expression levels increasing with tumor stage. Conversely, LBH was downregulated in tumor tissues and decreased with advancing stages. The predictive model achieved an area under the curve (AUC) value of 0.977, indicating excellent diagnostic and prognostic performance. DCA confirmed the clinical net benefit of the model. CONCLUSIONS: ASPN and LBH are critical molecular biomarkers for EGJA. The nomogram combining these two markers enables accurate distinction between early and advanced-stage tumors, offering significant support for early diagnosis of EGJA.

ASPN↗

PubMed2026

Phase Ib/II Study of Zanidatamab in Combination with Tislelizumab and Chemotherapy in First-Line HER2-Positive Gastric/Gastroesophageal Junction Adenocarcinoma.

PURPOSE: This phase Ib/II trial (NCT04276493) assessed the antitumor activity, safety, and pharmacokinetics (PK) of zanidatamab in combination with tislelizumab and chemotherapy in patients with advanced HER2-positive (HER2+) gastric cancer/gastroesophageal junction cancer (GEJC). PATIENTS AND METHODS: Adult patients with previously untreated, unresectable, locally advanced/metastatic HER2+ gastric cancer/GEJC received zanidatamab 30 mg/kg i.v. (cohort A) or zanidatamab 1800 mg i.v. (weight <70 kg)/2,400 mg i.v. (weight ≥70 kg; cohort B) once every 3 weeks (Q3W). Both cohorts received tislelizumab 200 mg i.v. once every 3 weeks and standard chemotherapy [capecitabine and oxaliplatin (CAPOX)] once every 3 weeks. Primary endpoints were investigator-assessed confirmed objective response rate (cORR) per RECIST v1.1, in addition to the frequency and severity of adverse events (AE) and serious AEs. Secondary endpoints included investigator-assessed progression-free survival (PFS), duration of response (DoR), overall survival (OS), PK, and immunogenicity of zanidatamab. RESULTS: As of December 7, 2023, 33 patients (cohort A, n = 19; cohort B, n = 14) received treatment. The confirmed objective response rate was 75.8%; the median duration of response, progression-free survival, and overall survival were 23.3, 16.7, and 32.4 months, respectively. The most common treatment-related AEs (TRAEs) were diarrhea (100%), nausea (63.6%), and decreased appetite (48.5%). Treatment-related AEs of grade ≥3 were reported in 22 (66.7%) patients; diarrhea was the most common (27.3%). CONCLUSIONS: Zanidatamab, in combination with tislelizumab and CAPOX, demonstrated clinically meaningful antitumor activity with a manageable safety profile as first-line therapy for patients with HER2+ gastric cancer/GEJC. These results support a further development of zanidatamab and tislelizumab with chemotherapy in this patient population in the ongoing phase III HERIZON-GEA-01 trial (NCT05152147).

Humans↗

PubMed2025

A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.

BACKGROUND: A wide range of epidemiological modeling approaches have been applied to the SARS-CoV-2 pandemic, which presents an opportunity to assess common approaches applied to specific research questions. Spatial models interrogate how heterogeneities and host movement dynamics influence local and regional patterns of disease, issues that were of great interest for understanding and controlling SARS-CoV-2. OBJECTIVE: Here we present a systematic review of spatial epidemiological modeling approaches of SARS-CoV-2. We describe common themes and highlight unique strategies, providing a foundation for researchers to devise spatial models most appropriate for future pathogens and epidemics. Our review also categorizes the research questions that were addressed with spatial models, highlights parameter estimation techniques, and describes the cyber infrastructure used for model development. METHODS: We conducted a systematic review using Web of Science and a standardized set of keywords, followed by thorough examination of abstracts and full texts to determine which studies met our inclusion criteria. To guide our description and comparisons of models, we developed a Geography, Population, Movement (GPM) framework that conceptualizes the interactions between three distinct subcomponents of any spatial model. The geographic model represents the physical arena in which the model is implemented, the intra-population model describes the transmission and disease processes that occur within distinct spatial units of the geography, and the movement model describes the algorithms that dictate how hosts move among spatial units within the geography. RESULTS: The search identified a total of 193 articles, of which 109 were included in our review. The most abundant intra-population modeling methods were agent-based (47.7%) and compartmental modeling (29.4%) approaches. Movement models ranged in complexity, with the most complex models implementing commuter movement among many points of interest in the geographic arena, which were sometimes parameterized by fine-scale mobility data. Geographic models ranged from describing microcosms, such as single classrooms, all the way up to multi-country models. Of the 63.3% of models studies that specified the programming language used, we detected ten different languages, with Matlab and Python being the most frequent, although only 30.6% of studies provided open-access code for their models. We also described eight specialized software systems that were used to construct agent-based or compartment models of COVID-19. CONCLUSIONS: Our review identified and characterized a variety of spatial modeling strategies and software that were usefully employed to address many relevant epidemiological questions for COVID-19. Future research is needed to quantitatively assess which modeling approaches are most appropriate in specific situations, to answer specific questions, or to apply to certain disease systems. Moreover, future cyberinfrastructure could help to modularize and standardize modeling approaches, which would increase transparency and reproducibility, and which would facilitate a detailed examination of which model attributes relate to model performance in a variety of contexts.

COVID-19↗

PubMed2025

Redistribution of super-enhancers promotes malignancy in human hepatocellular carcinoma.

INTRODUCTION: Super-enhancers (SEs) are defined as the regulatory region where intensive transcriptional cofactors bind. Dysregulation of SEs is related to multiple diseases, however, its role in hepatocellular carcinoma (HCC) remains elusive. OBJECTIVES: This work aimed to reveal the dysregulation of SEs in HCC and the therapeutic potential for HCC treatment. METHODS: Fifteen HCC and twelve paracancerous samples underwent chromatin immunoprecipitation (ChIP) sequencing targeting H3K27ac, and subsequently the SEs were identified by the Rank Ordering of Super-Enhancers algorithm. Differential SEs featured by tumor or paracancerous tissues were identified, and cross-referenced with the differential expression genes and prognosis-related genes in 2 independent public or in-house HCC cohorts. The SE region of HSPA4 was deleted in the genome of HCCLM3 cell by CRISPR-Cas9, named HSPA4-SE-KO cells. The potential druggable transcriptional factors were identified by CRCmapper, GeneMANIA and Drug Gene Interaction Database (DGID). RESULTS: Five targets, including CDKN2C, HSPA4, GGH, PDGFA, and CAP2, were identified as HCC-gain SEs with oncogenic potential, which were further validated experimentally by SE inhibitors and ChIP targeting H3K27ac and BRD4. Cell proliferation and migration assays further confirmed that silencing of these HCC-gain SEs significantly suppressed the malignant phenotype of HCC cell lines. HSPA4 appeared strongest oncogenic functions among these targets, which was further verified by HCC mouse xenograft models and clinical sample investigation. Moreover, HSPA4-SE-KO cells obtained significantly suppressed HSPA4 expression and retarded tumorigenic capability. Finally, dysregulation of transcriptional factors engaged in the oncogenic role of SEs, and Danthron that targeting RXRA were identified from DGID for HCC treatment. CONCLUSION: The dysregulated SE landscape of HCC promoted the malignancy phenotype by the upregulation of oncogenes, and SE-regulatory network might be potential drug targets for HCC treatment. Our study deepened the insight of epigenetic dysregulation in HCC, offering the groundwork for SEs as potential therapeutic targets of HCC treatment.

Humans↗