A multi-omics integrative analyses reveals CYBB-mediated apoptotic and immune dysregulation as a key target of berberine in diffuse large B-cell lymphoma
Aug 2026· Frontiers in Pharmacology· Vol 17· 0 citations· 71 references
Medicine
TL;DR
This integrative study identifies berberine-related genes with potential causal relevance to DLBCL and prioritizes CYBB as a functionally relevant target linked to apoptosis, immune regulation, and prognosis, highlighting the potential involvement of berberine–CYBB axis underlying berberine activity in DLBCL.
Abstract
Background Berberine has shown antitumor activity across multiple malignancies, yet its molecular targets and mechanisms of action in diffuse large B-cell lymphoma (DLBCL) remain incompletely defined. We integrated genetic causality, multi-omics data, and functional validation to identify berberine-related molecular pathways relevant to DLBCL. Methods We identify bioinformatic screening and Mendelian randomization (MR) on 760 candidate berberine-related genes; 315 with adequate instruments underwent MR for causal links to DLBCL. Follow-up analyses included pathway enrichment, Protein-Protein Interaction (PPI) networks, machine-learning prognostic modeling, molecular docking and dynamics, single-cell RNA sequencing, cell–cell communication inference, bulk transcriptomic validation, and in vitro assays. Results MR identified several berberine-related genes with putative causal associations with DLBCL. ABCA1, ITK, MAPK3, TGM2, and DAPK1 were associated with decreased DLBCL risk, whereas CYBB, RAC1, JUN, and CPT1A were associated with increased risk. Enriched pathways encompassed B-cell receptor signaling, immune checkpoints, apoptosis, and MAPK signaling. Apoptosis pathway activity correlated with favorable prognosis across cohorts. Integrative analyses prioritized CYBB as a central hub. Molecular docking and dynamics indicated stable berberine–CYBB binding. Single-cell analyses showed CYBB + B cells had distinct apoptotic, immunoregulatory, and communication features, including BTLA–TNFRSF14 signaling. Bulk deconvolution linked high CYBB to worse prognosis, proliferation, and an immunosuppressive microenvironment. Functionally, CYBB knockdown reduced DLBCL cell viability and increased apoptosis; berberine inhibited growth dose-dependently, and cellular thermal shift assays supported berberine–CYBB target engagement in cells. Conclusion This integrative study identifies berberine-related genes with potential causal relevance to DLBCL and prioritizes CYBB as a functionally relevant target linked to apoptosis, immune regulation, and prognosis, highlighting the potential involvement of berberine–CYBB axis underlying berberine activity in DLBCL, although rescue experiments are needed to confirm its specificity and relative contribution.
Background Clear cell renal cell carcinoma (ccRCC) is metabolically primed for ferroptosis, yet the prognostic relevance and mechanistic contribution of ferroptosis-related genes remain incompletely defined. This study aimed to identify ferroptosis-associated biomarkers with prognostic value and to clarify their functional relevance in ccRCC progression. Methods We integrated single-cell RNA sequencing, bulk RNA-seq, spatial transcriptomics, and machine-learning-based feature selection to identify ferroptosis-related prognostic genes in ccRCC. A four-gene risk model and an integrated nomogram were constructed and evaluated in independent cohorts. PANX2 was prioritized for experimental validation using stable knockdown models, RNA sequencing, lipid peroxidation and iron probes, redox assays, Western blot, luciferase reporter assays, xenografts, and an immunocompetent murine renal carcinoma model. Results A four-gene prognostic signature (CA9, PVT1, RRM2, and PANX2) was identified and used to construct a risk model with consistent predictive performance in the training and external validation cohorts. Among these genes, PANX2 was predominantly enriched in epithelial tumor compartments and had not been functionally characterized in ccRCC. PANX2 knockdown inhibited ccRCC cell proliferation, reduced antioxidant capacity, increased intracellular Fe2+ accumulation and lipid peroxidation, and sensitized cells to erastin-induced ferroptotic death. Mechanistically, PANX2 loss was associated with reduced Akt/mTOR pathway activity and diminished SLC7A11 expression; rescue with an Akt activator or SLC7A11 overexpression attenuated ferroptosis-associated phenotypes. In an immunocompetent murine renal carcinoma model, PANX2 knockdown was accompanied by increased infiltration of CD45+ leukocytes, CD3+ T cells, and CD8+ T cells, supporting a potential link between PANX2-dependent ferroptosis resistance and the tumor immune contexture. Conclusions This study identifies PANX2 as a ccRCC-relevant suppressor of ferroptosis and supports the involvement of a PANX2-Akt/mTOR-SLC7A11-associated signaling axis in redox homeostasis and tumor progression. The ferroptosis-related prognostic model and nomogram may support risk stratification, while PANX2 represents a candidate therapeutic vulnerability that warrants further mechanistic and translational validation.
Xing-Lin Li, Yiqi Xiong, Ji-Yin Wang et al.· Frontiers in Immunology· 0 citations
Introduction Head and neck cancer (HNC) is characterized by substantial immune heterogeneity and limited availability of clinically actionable molecular targets. Here, we developed an integrative single-cell eQTL-driven multi-omics framework to identify immune cell-specific causal genes and prioritize drug-repurposing candidates for HNC. Methods Single-cell eQTL data from the OneK1K cohort were integrated with European HNC GWAS summary statistics through two-sample Mendelian randomization, followed by transcriptomic differential expression analysis and weighted gene co-expression network analysis. Candidate targets were further evaluated using diagnostic modeling, immune infiltration analysis, single-cell and spatial transcriptomics, Bayesian colocalization, Western blot validation, molecular docking, molecular dynamics simulations, and FAERS-based safety profiling. Results We identified 494 immune cell-specific eGenes causally associated with HNC risk. Multi-layered target prioritization highlighted AIM1 and ANXA1 as protective immune-related genes, both of which were downregulated in HNC tissues and showed cell-type-preferential expression in T cells and monocytes, respectively. A dual-gene diagnostic model achieved strong discrimination performance with an AUC of 0.917. Colocalization analysis supported shared genetic signals between AIM1 or ANXA1 loci and HNC susceptibility, while Western blotting confirmed reduced AIM1 and ANXA1 protein expression in SCC-9 cells compared with normal HOK cells. Drug screening and molecular docking identified topotecan as a candidate ligand for AIM1 and terbutaline as a candidate ligand for ANXA1. Subsequent molecular dynamics simulations demonstrated stable drug–target complexes with favorable binding free energies. FAERS analysis further characterized the adverse-event spectrum and potential safety considerations for both compounds. Discussion Collectively, this study provides a single-cell genetic and pharmacological framework for defining immune-related causal targets in HNC and supports AIM1 and ANXA1 as promising biomarkers and therapeutic entry points for precision drug development.
Zhangwei Xue, Guo-Hang Shen, Gongbiao Lin et al.· Frontiers in Oncology· 0 citations
BACKGROUND
Burkitt lymphoma (BL) is a highly aggressive malignancy with limited effective treatments due to toxicity/resistance. Identifying and prioritizing candidate biomarkers and potential therapeutic targets from complex transcriptomic data, ahead of functional validation, remains a major unmet need.
METHODS
We integrated differential gene expression analysis across BL vs. control cohorts (Gene Expression Omnibus [GEO] datasets GSE43677/GSE12453) with Random Forest machine learning to prioritize candidates. Validated top genes via immunohistochemistry in an independent cohort (n = 10 BL, n = 10 reactive lymphoid hyperplasia [RLH] controls), followed by immune cell infiltration analysis.
RESULTS
This approach identified four candidate genes; only Chromatin Assembly Factor 1 Subunit A (CHAF1A) showed profound protein-level overexpression in BL tumors vs. RLH. In a single-dataset CIBERSORT analysis, CHAF1A expression showed exploratory correlational associations with several immune-cell fractions, most strongly a positive association with M0 macrophages; these in silico associations are hypothesis-generating and do not by themselves establish a mechanistic role in the tumor immune microenvironment.
CONCLUSION
CHAF1A is identified as a candidate biomarker associated with BL that, in exploratory single-dataset analysis, also correlates with immune-cell infiltration; these findings nominate it as a potential therapeutic target that warrants functional validation in future studies.
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma in adults and is characterized by aggressive progression and substantial molecular and clinical heterogeneity. Despite advances in immunochemotherapy, a considerable proportion of patients develop relapsed or refractory disease, highlighting the need to better understand the molecular mechanisms underlying DLBCL. Nei-Xiao-Luo-Li-San (NXLLS), a traditional herbal formulation historically used for nodules and tumor-like masses, provides a pharmacological model for investigating molecular responses and candidate regulatory mechanisms in DLBCL. Methods: NXLLS was chemically characterized to assess its compositional profile and compositional similarity among batches. Its biological effects were evaluated by assessing cell viability, migration, invasion, and cell-cycle progression in Toledo DLBCL cells. Molecular responses to NXLLS were investigated through an integrated approach combining transcriptomic analysis, network pharmacology, and molecular assays. The functional role of ATF5 was further evaluated using lentiviral overexpression and knockdown. Results: Chromatographic profiling provided an exploratory assessment of compositional similarity among NXLLS samples and supported the selection of eight representative compounds using liquid chromatography–mass spectrometry (LC–MS) annotation and high-performance liquid chromatography (HPLC) authentic-standard confirmation. NXLLS reduced cell viability, migration, and invasion in Toledo DLBCL cells within the tested concentration range. At the molecular level, NXLLS was associated with altered cell-cycle distribution and potential G1-phase accumulation at later time points, reduced vascular endothelial growth factor (VEGF)-associated enzyme-linked immunosorbent assay (ELISA) signal, and modulated stress-response genes. RNA sequencing (RNA-seq) revealed transcriptional changes involving stress-response and histone deacetylase (HDAC)-associated epigenetic pathways. Correspondingly, HDAC expression was reduced, whereas acetylated histone H3 lysine 9 (Ac-H3K9) and acetylated histone H3 lysine 27 (Ac-H3K27) levels were increased. ATF5 knockdown recapitulated several cellular and epigenetic changes observed following NXLLS treatment, supporting ATF5 as a potential downstream mediator of the NXLLS response. Conclusions: This study identified potential molecular targets associated with the response to NXLLS in Toledo DLBCL cells, with ATF5 further investigated as a potential downstream mediator. The findings also suggest an association between the NXLLS response and HDAC-related epigenetic changes, providing a basis for further investigation of their mechanistic relationships.
Kai-Xuan Zou, Jong Hyuk Kim, Sahana Arunasalam et al.· Biomedicines· 0 citations
TOP2A
is universally upregulated in human cancers, yet its negative correlation with immune infiltration in bulk transcriptomes remains mechanistically unresolved at single-cell resolution.
We integrated multi-omics data across 34 cancer types with external prognostic validation in 59 independent datasets. Single-cell deconvolution resolved cell-type-specific expression, and confounder-adjusted analyses distinguished proliferation-dependent from
TOP2A
-specific phenotypes. Pharmacogenomic profiling employed bidirectional Connectivity Map screening with cross-validation across four drug sensitivity databases.
TOP2A
was broadly upregulated at mRNA and protein levels across cancers, with high expression associated with shorter survival in most malignancies yet a protective effect in THYM and READ. Copy-number amplification, rather than somatic mutation, emerged as the predominant genomic correlate of
TOP2A
overexpression.
TOP2A
expression correlated positively with tumor mutation burden, homologous recombination deficiency, aneuploidy, and loss of heterozygosity, indicating widespread genomic instability. Single-cell analysis revealed that
TOP2A
expression is stringently restricted to malignant epithelial cells and proliferating immune subsets. Tumor purity and proliferation-adjusted analyses demonstrated that the bulk-level immune exclusion signature reflects stoichiometric dilution driven by malignant cell expansion rather than direct immunosuppression, whereas associations with genomic instability were largely proliferation-independent. Pharmacogenomic cross-validation revealed enhanced sensitivity of
TOP2A
-high tumors to topoisomerase, Aurora kinase, and microtubule inhibitors, but intrinsic resistance to MEK and EGFR inhibitors. CMap screening prioritized the HDAC inhibitor MS-275 as a candidate with pan-cancer reversal potential across 22 cancer types.
This study clarifies that
TOP2A
functions as a pan‑cancer barometer of proliferative burden and genomic instability rather than a direct immune suppressor. Resolving the bulk-level immune paradox as a non-cell-autonomous dilution effect through single-cell deconvolution and confounder-adjusted analyses, and identifying putative therapeutic vulnerabilities, we provide a framework for deploying
TOP2A
as a prognostic biomarker and a hypothesis-generating therapeutic target.
Background Breast cancer remains a leading cause of female mortality worldwide, with therapeutic benefit limited by tumor heterogeneity and drug resistance. Identification of novel therapeutic targets through integration of genetic causality inference and functional validation is urgently needed. Methods Plasma protein quantitative trait loci (pQTL) from the Fenland cohort (~10,700 individuals) and the FinnGen R10 SomaScan subset (n = 828) were integrated with breast cancer genome-wide association study data from the Breast Cancer Association Consortium (122,977 cases and 105,974 controls). Causal protein-disease relationships were inferred using summary-data-based Mendelian randomization (SMR), with colocalization and HEIDI tests. Multi-level validation was performed using TCGA-BRCA transcriptomic data. Functional validation included CCK-8, EdU, wound healing, Transwell invasion, and flow cytometry apoptosis analysis evaluated CPNE1 knocdown and/or overexpression of the MST1 gene which encodes macrophage-simulating protein (MSP). Results SMR identified 23 proteins in Fenland and 10 in FinnGen at FDR < 0.05. MST1/MSP and CPNE1 were supported in both datasets with PP.H4 ≥ 0.80 and non-significant HEIDI tests. Genetically predicted circulating MSP was positively associated with breast cancer risk, whereas circulating CPNE1 showed an inverse association. TCGA-BRCA showed higher CPNE1 mRNA in tumors (P = 2.57×10⁻25) and lower MST1 mRNA (P = 3.04×10⁻23). CPNE1 expression was highest in triple-negative breast cancer and correlated positively with clinical stage (ρ = 0.211), whereas MST1 expression was lowest in triple-negative breast cancer and correlated inversely with stage (ρ = −0.164). In T47D and MDA-MB-231 cells, CPNE1 knockdown and MST1 overexpression each reduced proliferation, migration, and invasion and increased apoptosis; the combined group showed greater changes than either single intervention. Conclusion This study prioritizes the MST1 gene, which encodes MSP, and CPNE1 as candidate proteins for further investigation in breast cancer. However, the circulating-protein associations, tumor-mRNA patterns, and cell-autonomous perturbations represent distinct and directionally discordant biological contexts. The findings therefore support context-dependent candidate roles and justify mechanistic, in vivo, and formal interaction studies, but do not yet establish therapeutic efficacy or synergy.
Meng Jiang, Qilong Wang, Hong Xu· Breast Cancer· 0 citations
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