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KeyPathwayMineR: De Novo Pathway Enrichment in the R Ecosystem.
De novo pathway enrichment is a systems biology approach in which OMICS data are projected onto a molecular interaction network to identify subnetworks representing condition-specific functional modules and molecular pathways. Compared to classical pathway enrichment analysis methods, de novo pathway enrichment is not limited to predefined lists of pathways from (curated) databases and thus particularly suited for discovering novel disease mechanisms. While several tools have been proposed for pathway enrichment, the integration of de novo pathway enrichment in end-to-end OMICS analysis workflows in the R programming language is currently limited to a single tool. To close this gap, we have implemented an R package KeyPathwayMineR (KPM-R). The package extends the features and usability of existing versions of KeyPathwayMiner by leveraging the power, flexibility and versatility of R and by providing various novel functionalities for performing data preparation, visualization, and comparison. In addition, thanks to its interoperability with a plethora of existing R packages in e.g., Bioconductor, CRAN, and GitHub, KPM-R allows carrying out the initial preparation of the datasets and to meaningfully interpret the extracted subnetworks. To demonstrate the package's potential, KPM-R was applied to bulk RNA-Seq data of nasopharyngeal swabs from SARS-CoV-2 infected individuals, and on single cell RNA-Seq data of aging mice tissue from the Tabula Muris Senis atlas.
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Temporal transcriptomic dynamics in developing macaque neocortex.
Despite intense research on mice, the transcriptional regulation of neocortical neurogenesis remains limited in humans and non-human primates. Cortical development in rhesus macaque is known to recapitulate multiple facets of cortical development in humans, including the complex composition of neural stem cells and the thicker supragranular layer. To characterize temporal shifts in transcriptomic programming responsible for differentiation from stem cells to neurons, we sampled parietal lobes of rhesus macaque at E40, E50, E70, E80, and E90, spanning the full period of prenatal neurogenesis. Single-cell RNA sequencing produced a transcriptomic atlas of developing parietal lobe in rhesus macaque neocortex. Identification of distinct cell types and neural stem cells emerging in different developmental stages revealed a terminally bifurcating trajectory from stem cells to neurons. Notably, deep-layer neurons appear in the early stages of neurogenesis, while upper-layer neurons appear later. While these different lineages show overlap in their differentiation program, cell fates are determined post-mitotically. Trajectories analysis from ventricular radial glia (vRGs) to outer radial glia (oRGs) revealed dynamic gene expression profiles and identified differential activation of BMP, FGF, and WNT signaling pathways between vRGs and oRGs. These results provide a comprehensive overview of the temporal patterns of gene expression leading to different fates of radial glial progenitors during neocortex layer formation.
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Systems mapping of intra-donor, cross-tissue T cell clonal expansion and tissue adaptation in the gut-liver-blood axis.
The human gut-liver axis is a critical immunological interface, yet factors that shape T cell adaptation and clonal expansion across tissues remain unclear. We performed integrated single-cell RNA and T cell receptor sequencing on T cells from matched colon epithelium, lamina propria, liver, and blood of the same donors, enabling clonal tracking and tissue-specific transcriptional profiling without inter-individual confounders. Colonic intraepithelial lymphocytes were largely clonally distinct from lamina propria T cells. Tissue-resident T cells in colon vs. liver displayed marked transcriptional divergence, with colonic lamina propria tissue-resident memory T cells (TRMs) enriched for interferon-stimulated genes (e.g., ISG15 and IFITM3). Ligand-receptor analysis implicated liver-derived factors, including fibrinogen gamma chain, in shaping colon TRM states. Across tissues, highly expanded clones of the same cell type shared a core upregulated gene set, suggesting common determinants of clonal success. These data provide a same-donor single-cell atlas of T cell diversity and adaptation across the human gut-liver-blood axis.
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Prognostic biomarkers related to PANoptosis in esophageal cancer and their immune microenvironment: multi-omics analysis and therapeutic significance.
INTRODUCTION: Esophageal squamous cell carcinoma (ESCA) is one of the most common cancers worldwide. PANoptosis is an inflammatory programmed cell death pathway event regulated by the PANoptosome complex. Currently, there is limited research on the PANoptosis-related genes (PORGs) in ESCA. We aim to explore the prognostic biomarkers of PANoptosis in ESCA and their underlying mechanisms through comprehensive bioinformatics analysis. METHODS: In this study, we analyzed transcriptome and single-cell RNA sequencing (scRNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) and differential expression analysis were used to identify PANoptosis-related differentially expressed genes (POR-DEGs) in esophageal cancer. Hub genes were screened by univariate and multivariate Cox regression combined with machine learning models to construct diagnostic and prognostic models. The potential mechanisms of hub genes in esophageal cancer were preliminarily explored through gene immune infiltration and functional enrichment analysis. The differences and driving factors between high- and low-risk subgroups, as well as the regulation of PANoptosis by hub genes related to macrophages, were further revealed by immune assessment, drug sensitivity analysis, single-cell analysis, and molecular docking. Finally, the accuracy of model genes was verified by immunohistochemistry in clinical samples. RESULTS: Firstly, 74 PANoptosis-related differentially expressed genes (POR-DEGs) were identified for further analysis. Among the 74 genes, CCT6A, GMNN, and HSPB6 were identified as hub genes, and the constructed diagnostic and prognostic models were valuable. The high-risk subgroup showed poor prognosis, immune exhaustion, significant activation of pDC-LILRA4 cells, poor response to immunotherapy, and moderate sensitivity to chemotherapy. Further exploration of the immune regulatory mechanism of prognostic biomarkers revealed that the three hub genes, CCT6A, GMNN, and HSPB6, were closely related to the ESCA immune microenvironment. The CCT6A targeted by the traditional Chinese medicine component quercetin may inhibit PANoptosis by promoting the differentiation of Mono-CD14 cells into TAM-SPP1 macrophages. DISCUSSION: We constructed prognostic and diagnostic models using PANoptosis-related prognostic biomarkers, analyzed the differences and treatments between high-risk and low-risk groups, and revealed a new mechanism by which CCT6A may inhibit PANoptosis by promoting TAM-SPP1 differentiation, providing new targets and biomarkers for ESCA treatment.
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Actin-like Protein 6A Expression Correlates with Cancer Stem Cell-like Features and Poor Prognosis in Ovarian Cancer.
Ovarian cancer has the highest mortality rate among gynecological cancers, often diagnosed at the late stage and lacking an effective targeted therapy. Although the study of malignant features of cancer, considered to be cancer stem cells (CSCs), is emerging, the aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of ovarian cancer from a combined database with CSCs features. The common differentially expressed genes (DEGs) were selected in GSE185833 and GSE176246 datasets from the Gene Expression Omnibus (GEO). The GSE185833 dataset was created to reveal gene expression profiles of peritoneal metastasis tissues using single-cell sequencing, and the GSE176246 dataset was determined from gene expression profiles of chemotherapy-refractory ovarian cancer cell lines compared with ovarian cancer cell lines by RNA-seq analysis. By analyzing the correlation between common DEGs and prognosis of ovarian cancer and its possible pathways and functions were predicted by The Cancer Genome Atlas (TCGA) database. The expression levels of 11 genetic markers were significantly elevated in highly invasive and chemoresistant ovarian cancer. The expression of Actin-like protein 6A (ACTL6A) was found to be correlated with survival prognosis, and the total survival time of the patients with high expression of ACTL6A was shorter than those with low expression. Gene set enrichment analysis (GSEA) showed that ACTL6A positively enriched the gene set of 'Cell cycle' and ACTL6A negatively enriched the gene set of focal adhesion. CP724714, a human epidermal growth factor receptor 2 (HER2) inhibitor, could serve as a therapeutic option when ACTL6A levels are high in ovarian cancer cells. The high expression of ACTL6A is a poor prognostic factor in ovarian cancer and may serve as an effective biomarker for predicting treatment-refractory, metastasis, and prognosis of patients with ovarian cancer. The use of HER2 inhibitors is a promising therapeutic strategy against chemoresistant ovarian cancer.
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Expression of OLR1 gene on tumor-associated macrophages of head and neck squamous cell carcinoma, and its correlation with clinical outcome.
Head and neck squamous cell carcinoma (HNSCC) is one of the most heavily immune infiltrated human tumors, having distinct immune subtypes associated with different molecular characteristics and clinical outcomes. The tumor microenvironment (TME) of HNSCC which was dominated by tumor-associated macrophages (TAMs) had a relatively inferior prognosis. High levels of oxidized low-density lipoprotein receptor 1 (OLR1) expression are associated with more aggressive and metastatic characteristics in multiple cancers. However, the link between the OLR1 expression and immunosuppression of TME, and the molecular mechanisms which govern intratumoral TAMs behavior are unclear. Here, we performed the transcriptional analysis based on a single-cell RNA-sequencing (scRNA-seq) dataset of HNSCC, and found that the OLR1 expression was specifically enriched on the TAMs. Evaluation of protein expression within histologic sections of primary HNSCC patient samples showed a co-expression pattern of OLR1 and CD68 on macrophages. A total of 498 tumor samples of HNSCC patients from The Cancer Genome Atlas (TCGA) database were also analyzed. Remarkably, OLR1 expression was dramatically higher in HNSCC tissues than that in adjacent normal tissues, and the patients with high levels of OLR1 expression had significantly unfavorable overall survival (Hazard Ratio = 1.724, log-rank P-value = 0.0066) when compared to patients harboring low expression levels of OLR1. In summary, we reported that the specific expression of OLR1 on the TAMs was significantly correlated with poor survival outcomes, revealing that OLR1 could serve as a potential prognosis marker and promising target for immunotherapy in HNSCC.
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Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma.
BACKGROUND: Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration. The study was conducted to elucidate the association of TAP1 expression with immunological characteristics, and sought to exploit the value of TAP1 as a biomarker reflecting the inflamed TME and immunotherapeutic response. METHODS: RNA-sequencing profiles and clinical annotations were obtained from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort and Gene Expression Omnibus (GEO) portal. Preprocessing was conducting using the limma package. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules and TAP1 co-expressed genes (CEGs) based on correlation patterns. Consensus clustering and silhouette analysis determined the optimal number of TAP1-related groups. Gene expression profiles were integrated and classified using the pamr package. The Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate immunological characteristics. Differential expression analysis was conducted using the limma package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Single-cell RNA sequencing (scRNA-seq) datasets were analyzed using the Seurat toolkit to characterize cell types. RESULTS: Within this investigation, no significant differences in TAP1 expression were observed among patients exhibiting various clinicopathological features, indicating that TAP1 expression was not specific to molecular subtypes. Subsequent analysis revealed a positive correlation between TAP1 and diverse immunological traits, encompassing immunomodulators, tumor-infiltrating immune cells, as well as immune checkpoints across multiple datasets. Besides, within a GC immunotherapy cohort, individuals displaying high TAP1 expression demonstrated an increased likelihood of achieving complete remission (CR) post-treatment, suggesting heightened sensitivity to immunotherapy. In the clinical cohort, TAP1 overexpression in GC patients was positively correlated with CD8. CONCLUSIONS: TAP1 appears linked to an inflamed TME and serves as a prospective biomarker for discerning immunological attributes and gauging immunotherapeutic responses in GC, particularly in identifying immune-reactive tumors.
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Identification and verification of SPP1 in anoikis as a prognostic biomarker for intestinal metaplasia and gastric cancer.
Anoikis is a form of apoptosis induced by cell detachment from the extracellular matrix, and cancer cells must evade it to metastasize. Gastric cancer (GC) remains a leading global cause of cancer-related mortality, with intestinal metaplasia (IM) established as a key premalignant lesion. This study explored the multi-omics features of the anoikis-related gene SPP1 across the control-IM-GC cascade, focusing on its links to immunity and prognosis. Comprehensive transcriptome analyses were conducted using datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the GeneCards database via the R programming language. By integrating Weighted Gene Co-expression Network Analysis (WGCNA) and competing endogenous RNA (ceRNA) networks, alongside Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA), the study explored the immunological roles of Secreted Phosphoprotein 1 (SPP1) in GC. Furthermore, immune infiltration and immune checkpoint analyses were combined with single-cell RNA sequencing (scRNA-seq) to elucidate the tumor microenvironment. Finally, Cox proportional hazards regression and Receiver Operating Characteristic (ROC) curve analyses were utilized to assess the prognostic significance of SPP1 and to construct a predictive risk signature. RT-qPCR/Western blot (32 human tissues) and in vitro assays were conducted to validate SPP1's expression and function. SPP1 was significantly upregulated across the Correa cascade, with high predictive accuracy, and was associated with survival and potential immunotherapy relevance. Higher levels were associated with a poorer prognosis. In vitro, SPP1 inhibition reduced GC cell migration, enhanced apoptosis, and induced S/G2 phase arrest. To our knowledge, this is the first study to associate SPP1 with IM/GC. Our findings suggest that it may serve as a prognostic biomarker, with immunotherapeutic implications that require further study.
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Single-Cell Transcriptomic Analysis Reveals Multicellular Coordination and Signaling Rewiring During Fetal Goat Skeletal Muscle Development.
Fetal skeletal muscle development involves coordinated interactions among myogenic, stromal, vascular, and immune compartments, yet the cellular and molecular programs guiding tissue maturation remain incompletely understood. To address this, we generated a high-resolution single-cell atlas of fetal female goat skeletal muscle and performed trajectory analysis, transcription factor activity profiling, and intercellular communication mapping. Unsupervised clustering identified RUNX2 mesenchymal progenitors, fibro-adipogenic progenitors (FAPs), myofibroblasts, endothelial cells, macrophages, differentiating myocytes, and mature skeletal muscle fibers, revealing a heterogeneous ecosystem in which stromal populations support myogenic progression and vascular and immune cells contribute to tissue organization. Pseudotime analysis traced a maturation continuum from differentiation-competent myocytes to contractile fibers, marked by sequential activation of extracellular matrix remodeling, cytoskeletal stabilization, and sarcomere assembly. KEGG and GO enrichment highlighted stage-specific engagement of ErbB, Hedgehog, and Hippo signaling, as well as cell cycle and ubiquitin-mediated proteolysis pathways, linking proliferation, differentiation, and structural maturation. Transcription factor profiling revealed early-stage proliferative and morphogenetically permissive states driven by E2F4/5, HMGA2, and HAND2, transitioning to late-stage differentiation, ECM remodeling, and tissue stabilization orchestrated by CEBPB, CREB3L1, ELK1, and E2F2. Cell-cell communication analysis showed a developmental redistribution of signaling authority, from ECM-driven, progenitor-centered networks to modular, structurally stabilized interactions. These findings define the cellular, transcriptional, and signaling framework orchestrating fetal skeletal muscle maturation.
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A Single-Cell Transcriptome Atlas Characterizes the Immune Landscape of Human Testes During Aging.
Aging disrupts immune regulation, affecting tissue function and increasing vulnerability to various diseases. However, the effects of aging on immune cells within human testes are not well understood. In this study, we utilized single-cell RNA sequencing to profile immune cells from 33 human testis samples from individuals aged 21 to 69. Our analysis revealed key immune cell types, including CD8+ T cells, monocytes, cDC2 cells, and various macrophage subtypes within the testes. We observed an age-related change in monocytes and MRC1hi tissue-resident macrophage (TRM), a pattern consistent in both human and mouse testes. Individuals aged 40 and older showed notable shifts in pathways related to phagocytosis, cytokine signaling, and antigen presentation. Monocytes also exhibited pro-inflammatory characteristics, potentially contributing to the low-grade inflammation commonly associated with aging. Together, these findings provide insights into age-related immune cell alterations in human testes and uncover molecular mechanisms underlying these shifts, offering a valuable resource for understanding immune aging in the reproductive system.