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Cellular dynamics in cerebrospinal fluid unveils the key regulators of intracranial response to immune checkpoint inhibitors in NSCLC brain metastases.
BACKGROUND: Brain metastases (BrM) in non-small cell lung cancer (NSCLC) present a significant challenge due to poor prognosis. While immune checkpoint inhibitors (ICIs) have been standard treatments for NSCLC, their efficacy in BrM is variable, emphasizing the urgent need for predictive biomarkers and fundamental mechanisms. METHODS: Patients with NSCLC and BrM planning to receive ICI therapy were enrolled in the prospective cohort, dynamic cerebrospinal fluid (CSF) samples (n=20) were collected through lumbar puncture and used for single-cell RNA sequencing (scRNA-seq), and BrM tumors were collected if they have the indications of surgery, with integrating scRNA-seq data from external database (total n=20). Three independent cohorts underwent flow cytometry (n=8), proteomics analysis (n=31), and multiplex immunohistochemistry (n=25) for validation. RESULTS: Our study provided a high-resolution atlas of cellular dynamics in the CSF and BrM during ICI therapy in patients with NSCLC and BrM. Notably, we identified a key immune cell subset, CD4+PDCD1+CXCR6+ T cells, as a positive predictor of ICI intracranial tumor responses, which presented highly functional and transcriptomic similarities in both CSF and BrM tumor environment. Moreover, CXCR6 could serve as a specific marker for CD4+PDCD1+ T cells linked to ICI response. Further, we revealed that the novel cluster of CD4+PDCD1+CXCR6+ T cells was closely associated with lymphocyte activation and aggregation in CSF and BrM of ICI responders, and classical dendritic cells of ICI responders interacted with CD4+PDCD1+CXCR6+ T cells for enhanced antigen presentation and inflammatory activation. CONCLUSION: Our findings revealed critical insights into the immune landscape of NSCLC BrM under ICI therapy, highlighting CD4+PDCD1+CXCR6+ T cells in CSF as a promising biomarker and illuminating fundamental mechanisms underlying ICI efficacy.
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Blood DNA methylation markers are associated with diabetic kidney disease progression in type 1 diabetes.
AIMS/HYPOTHESIS: DNA methylation has been shown to be associated with kidney function and diabetic kidney disease (DKD), but prospective studies are scarce. Therefore, we conducted epigenome-wide association studies (EWASs) on early- and late-stage DKD progression using DNA methylation data obtained by analysing baseline blood samples from participants in the Finnish Diabetic Nephropathy Study type 1 diabetes cohort. METHODS: We included 403 individuals with normal AER (early-stage progression group) and 372 individuals with severe albuminuria (late-stage progression group), and followed up DKD progression, defined as a decrease in eGFR to <60 ml/min per 1.73 m2 in the early-stage progression group, and end-stage kidney disease (ESKD) in the late-stage group. Replication was conducted in two type 1 diabetes cohorts in addition to publicly available EWAS summary statistics from diabetes and general population cohorts. Significant loci were further characterised by integration with genetic and proteomic data. RESULTS: We identified 11 methylation sites associated with DKD progression (p<9.4 × 10-8). Methylation at cg01730944 near the podocyte-specific gene CDKN1C and three other CpGs associated with early-stage DKD progression were independent of baseline eGFR, whereas late-stage progression CpGs were strongly associated with eGFR. The identified lead ESKD risk locus cg17944885 (chr19p13.2, p=2.6 × 10-17) and several novel methylation sites associated with late-stage DKD progression were supported by the results of previous studies. Proteomic analysis of cis proteins identified potential target genes for two CpGs: cg14999724 methylation was associated with PRG3 and PRG2, and cg12272104 was associated with BSG, FSTL3 and PALM. Furthermore, UK Biobank data show associations between these proteins and severe kidney endpoints. Finally, survival models that included methylation markers in addition to clinical risk factors significantly improved the identification of individuals at risk of early-stage DKD progression. CONCLUSIONS/INTERPRETATION: The current study detected 11 loci associated with DKD progression, identifying methylation changes predictive of early-stage DKD progression in type 1 diabetes for the first time. Future research is needed to establish prognostic DNA methylation markers for DKD progression.
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Exploring the potential mechanisms of Yi-Yi-Fu-Zi-Bai-Jiang-San therapy on the immune-inflamed phenotype of colorectal cancer via combined network pharmacology and bioinformatics analyses.
BACKGROUND: The development and progression of colorectal cancer (CRC) is closely associated with its complex tumor microenvironment (TME). Assessment of the modified pattern of immune cell infiltration (ICI) will help increase knowledge regarding the characteristics of TME infiltration. Yi-Yi-Fu-Zi-Bai-Jiang-San (YYFZBJS) has been shown to have positive effects on the regulation of the immune microenvironment of CRC. However, its pharmacological targets and molecular mechanisms remain to be elucidated. METHODS: Network pharmacological analysis was used to identify the target of YYFZBJS in the TME of CRC. Patients with the immune-inflamed phenotype (IIP) were identified using CRC samples from The Cancer Genome Atlas (TCGA) database. Consensus genes were identified by intersecting YYFZBJS targets, CRC disease targets and differentially expressed genes in the CRC microenvironment. Then, least absolute shrinkage and selection operator (LASSO) Cox analyses were used to identify a prognostic signature from the consensus genes. Cytoscape software was further used to build a unique herb-compound-target network diagram of the important components of YYFZBJS and prognostic gene targets. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed using the prognostic gene sets to explore the molecular mechanism of the prognostic genes in drug therapy for CRC IIP patients. Finally, single-cell analysis was performed to validate the expression of the prognostic genes in the TME of CRC using the TISCH2 database. RESULTS: A total of 284 IIP patients were identified from 480 patients with CRC. A total of 35 consensus genes were identified as targets of YYFZBJS in the TME of CRC patients. An eleven-gene prognostic signature, including PIK3CG, C5AR1, PRF1, CAV1, HPGDS, PTGS2, SERPINE1, IDO1, TGFB1, CXCR2 and MMP9, was identified from the consensus genes, with areas under the receiver operating characteristic (ROC) curve (AUCs) values of 0.84 and 0.793 for the training and test cohorts, respectively. In the herb-compound-target network, twenty-four compounds were shown to interact with the 11 prognostic genes, which were significantly enriched in the IL-17 signaling, arachidonic acid metabolism and metabolic pathways. Single-cell analysis of the prognostic genes confirmed that their abnormal expression was associated with the TME of CRC. CONCLUSION: This study organically integrated network pharmacology and bioinformatics analyses to identify prognostic genes in CRC IIP patients from the targets of YYFZBJS. Although this data mining work was limited to the study of mechanisms related to prognosis based on the immune microenvironment, the methodology provides new perspectives in the search for novel therapeutic targets of traditional Chinese medicines (TCMs) and accurate diagnostic indicators of cancers targeted by TCMs.
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Expression of Bruton's Tyrosine Kinase Reflects Immune Cells Infiltration and Cell Proliferation in Breast Cancer.
BACKGROUND: Bruton's tyrosine kinase (BTK) is a downstream mediator in B-cell receptor (BCR) signaling and is essential for B-cell differentiation and proliferation. BTK inhibitors are approved and in clinical use for hematological cancers such as lymphoma and leukemia, with testing underway in solid tumors. Because BTK is expressed in myeloid-derived suppressor cells (MDSCs) known to worsen breast cancer (BC) outcomes, we investigated the clinical relevance of BTK expression in multiple BC subtypes as a predictor of progression and/or response to treatment. METHODS: We performed an integrative transcriptomic analysis of tumor BTK expression across three large BC cohorts (The Cancer Genome Atlas (TCGA), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and Sweden Cancerome Analysis Network-Breast (SCAN-B); total n = 5,240), 10 neoadjuvant chemotherapy (NAC) datasets, and the I-SPY2 neoadjuvant immunotherapy trial cohort. Gene set enrichment analysis (GSEA) and xCell deconvolution were used to evaluate associations with cell proliferation, immune infiltration, and tumor microenvironment (TME) composition while single-cell sequencing datasets (SCP1039, SCP1106) were used to identify BTK-expressing cell populations. Survival analyses were performed using Kaplan-Meier and log-rank tests. RESULTS: BTK levels were the highest in triple-negative BC (TNBC) among the subtypes and unexpectedly drove stronger proliferation gene set enrichment in estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) tumors (e.g., MITOTIC_SPINDLE, G2M_CHECKPOINT). However, BTK expression did not correlate with American Joint Committee on Cancer (AJCC) stage or overall, disease-free, or disease-specific survival across cohorts or molecular subtypes. Notably, BTK-high tumors showed robust enrichment of immune pathways (interferon gamma (IFN-γ) response, interleukin-6 (IL-6)/Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3), tumor necrosis factor-α (TNF-α) signaling) and exhibited elevated tumor-infiltrating leukocyte and lymphocyte fractions, increased cytolytic activity, and greater abundance of myeloid and lymphoid cell populations. BTK expression was not consistently associated with NAC response as only one of 10 datasets (GSE25066) showed a weak association within ER+ and HER2-positive subtypes. Similarly, BTK levels did not predict response in I-SPY2 patients receiving durvalumab plus olaparib, despite strong correlations with programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) expression. Single-cell analysis localized BTK transcripts primarily to myeloid and B cells. CONCLUSION: BTK expression in BC reflects a proliferative and immune-active TME, particularly in TNBC and HER2-positive subtypes, but lacks prognostic or predictive value for NAC or PD-L1-based immunotherapy response.
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Systems pharmacology: a combination strategy for improving efficacy of PD-1/PD-L1 blockade.
Targeting tumor microenvironment (TME), such as immune checkpoint blockade (ICB), has achieved increased overall response rates in many advanced cancers, such as non-small cell lung cancer (NSCLC), however, only in a fraction of patients. To improve the overall and durable response rates, combining other therapeutics, such as natural products, with ICB therapy is under investigation. Unfortunately, due to the lack of systematic methods to characterize the relationship between TME and ICB, development of rational immune-combination therapy is a critical challenge. Here, we proposed a systems pharmacology strategy to identify resistance regulators of PD-1/PD-L1 blockade and develop its combinatorial drug by integrating multidimensional omics and pharmacological methods. First, a high-resolution TME cell atlas was inferred from bulk sequencing data by referring to a high-resolution single-cell data and was used to predict potential resistance regulators of PD-1/PD-L1 blockade through TME stratification analysis. Second, to explore the drug targeting the resistance regulator, we carried out the large-scale target fishing and the network analysis between multi-target drug and the resistance regulator. Finally, we predicted and verified that oxymatrine significantly enhances the infiltration of CD8+ T cells into TME and is a powerful combination agent to enhance the therapeutic effect of anti-PD-L1 in a mouse model of lung adenocarcinoma. Overall, the systems pharmacology strategy offers a paradigm to identify combinatorial drugs for ICB therapy with a systems biology perspective of drug-target-pathway-TME phenotype-ICB combination.
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A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma.
Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.
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Uncovering the regulatory landscape of early human B cell lymphopoiesis and its implications in the pathogenesis of B-ALL.
Dysregulation of early B cell lymphopoiesis-the process guiding cellular immunity development-can lead to malignancy, making it crucial to understand its regulatory mechanisms. We generated a multiomics resource comprising paired chromatin accessibility and gene expression profiles across eight human B cell precursor populations, providing a detailed characterization of early human B cell development. Integrative analysis revealed highly cell type-specific regulatory elements and enabled the reconstruction of the gene regulatory network governing differentiation. We identified putative candidate regulons, such as ELK3, enriched in pro-B cells and potentially involved in cell cycle progression. Regulons from bulk data were projected onto single-cell data, validating their activity and refining the regulatory landscape. This resource enabled identification of active regulatory programs and transformation-associated states in B cell acute lymphoblastic leukemia. The publicly available atlas provides a valuable resource for understanding B cell development and disease, supporting future efforts to decode regulatory programs in immunity and hematologic malignancies.
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Spatially Resolved Molecular Subtyping Uncovers Tumor Progression and Immune Evasion Mechanisms in High-grade Serous Ovarian Cancer.
UNLABELLED: High-grade serous ovarian cancer (HGSOC) is a lethal malignancy characterized by profound intratumoral heterogeneity and immune evasion. Although previous research has identified 4 molecular subtypes of HGSOC, defining their spatial distribution across anatomic sites could help identify functional mediators of progression and immune evasion. In this study, we performed single-cell and spatial transcriptomic sequencing on 66 anatomically paired samples across 5 sites from 8 patients and conducted an integrated analysis on the generated datasets. Five distinct gene programs (GP) with specific spatial distributions and functional roles were identified: GP1 (differentiated-invasive), GP2 (differentiated-proliferative), GP3 (immunoreactive), GP4 (mesenchymal), and GP5 (proliferative). Interestingly, molecular subtypes exhibited dynamic spatial transitions that promote HGSOC progression. The differentiated-proliferative subtype dominated tumor cores, whereas the differentiated-invasive subtype localized to the invasive front driven by SDC4-expressing epithelial cells (c40) that were functionally validated to promote migration/invasion. Concurrently, immune evasion operated through distinct mechanisms. Differentiated-invasive and immunoreactive subtype co-localization established immunosuppression via the TNFα-SAA1/2-APOE signaling axis that recruits immunosuppressive myeloid cells across primary and metastatic sites, whereas fibroblast-derived collagen barriers were constructed at the interfaces between mesenchymal and immunoreactive subtypes in omental metastases along with dysregulated chemokines to exclude immune infiltration. This spatially resolved atlas directly links subtype spatial transitions to tumor progression and subtype co-localization to immune evasion, providing a mechanistic framework for targeting spatially organized tumor-immune interactions in HGSOC. SIGNIFICANCE: Spatially resolved transcriptomic analysis reveals tumor subtype transitions and niche-specific immune evasion mechanisms in ovarian cancer.
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Cross-Species Transcriptomic and Metabolomic Analysis Reveals Conserved and Divergent Fatty Acid Metabolic Regulatory Strategies During Mammalian Oocyte Maturation.
Mammalian oocyte maturation is a metabolically demanding process relying on lipid metabolism that supplies energy, structural substrates, and signaling mediators. However, a comprehensive cross-species understanding of the dynamic requirement for lipids during this process remains elusive, hindering the optimization of assisted reproductive technologies. Utilizing an integrated single-cell transcriptomic and targeted lipidomic approach, we mapped the metabolic landscape of bovine oocyte maturation. Our analysis uncovered a global transcriptional downregulation, with 3259 genes suppressed during the transition from the germinal vesicle (GV) to the metaphase II (MII) stage. This was particularly apparent in lipid catabolism pathways (e.g., for ACAA1), while mitochondrial energy production genes (ATP6) were upregulated. Lipidomics indicated a selective depletion of saturated fatty acids (SFAs; e.g., C16:0, C18:0) in MII oocytes, while monounsaturated (MUFAs) and polyunsaturated fatty acids (PUFAs) were preferentially retained. Integrated network analysis specified hexadecanoic acid (C16:0) as a central metabolic hub, which rewires its interactions from biosynthetic genes (FASN, ELOVL6) in GV oocytes to degradative enzymes (ACADVL, HADH) in MII oocytes. Expanding to a cross-species transcriptomic atlas, we identified a core set of 59 lipid metabolism genes conserved across bovine, mouse, and human oocytes. Despite this conservation, we discovered stark species-specific regulatory strategies: bovine and human oocytes significantly downregulated fatty acid degradation and elongation post-maturation, whereas murine oocytes maintain pathway activity, upregulating key regulators like Acsl3. Our work unveils an evolutionarily conserved core lipid metabolic program in mammalian oocytes that is adaptively tuned to meet species-specific physiological demands. Bovine and human oocytes prioritize catabolic flexibility, using SFAs for energy, while mouse oocytes maintain their anabolic capacity for membrane biosynthesis. These findings provide a transformative resource for the field, offering biomarkers for oocyte quality and a rationale for enhancing species-tailored lipid formulations to develop in vitro maturation systems and amend reproductive outcomes in both agriculture and medicine.
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A comprehensive evaluation of spontaneous pelvic organ prolapse in rhesus macaques as an ideal model for the study of human pelvic organ prolapse.
Pelvic organ prolapse (POP) seriously affects a woman's quality of life, and the treatment complications are severe. Although new surgical treatments are being developed, the host tissue responses and safety need to be evaluated in preclinical trials. However, there is a lack of suitable animal models, as most quadrupeds exhibit different structural and pathological changes. In this study, 72 elderly rhesus macaques (Macaca mulatta) were physically examined, and the incidence of spontaneous POP was similar to that in humans. The vaginal wall from five control monkeys and four monkeys with POP were selected for further analysis. Verhoeff-van Gieson staining showed that elastin content decreased significantly in monkeys with POP compared with control samples. Immunohistological staining revealed that the smooth muscle bundles in monkey POP appeared disorganized, and the number of large muscle bundles decreased significantly. The collagen I/III ratio in monkey POP also significantly decreased, as revealed by Sirius Red staining. These histological and biochemical changes in monkeys with POP were similar to those in humans with POP. Moreover, we generated a single-cell transcriptomic atlas of the prolapsed monkey vagina. Cross-species analysis between humans and monkeys revealed a comparable cellular composition. Notably, a differential gene expression analysis determined that dysregulation of the extracellular matrix and an immune disorder were the conserved molecular mechanisms. The interplay between fibroblasts and macrophages contributed to human and monkey POP. Overall, this study represents a comprehensive evaluation of spontaneous POP in rhesus macaques and demonstrates that monkeys are a suitable animal model for POP research.