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An atlas of genetic effects on cellular composition of the tumor microenvironment.
Deciphering the composition of the tumor microenvironment (TME) is critical for understanding tumorigenesis and to design immunotherapies. In the present study, we mapped genetic effects on cell-type proportions using single-cell and bulk RNA sequencing data, identifying 3,494 immunity quantitative trait loci (immunQTLs) across 23 cancer types from The Cancer Genome Atlas. Functional annotation revealed regulatory potential and we further assigned 1,668 genes that regulate TME composition. We constructed a combined immunQTL map by integrating data from European and Chinese colorectal cancer (CRC) samples. A polygenic risk score that incorporates these immunQTLs and hits on a genome-wide association study outperformed in CRC risk stratification within 447,495 multiethnic individuals. Using large-scale population cohorts, we identified that the immunQTL rs1360948 is associated with CRC risk and prognosis. Mechanistically, the rs1360948-G-allele increases CCL2 expression, recruiting regulatory T cells that can exert immunosuppressive effects on CRC progression. Blocking the CCL2-CCR2 axis enhanced anti-programmed cell death protein 1 ligand therapy. Finally, we have established a database (CancerlmmunityQTL2) to serve the research community and advance our understanding of immunogenomic interactions in cancer pathogenesis.
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Single-cell transcriptome analyses reveal novel targets modulating cardiac neovascularization by resident endothelial cells following myocardial infarction.
AIMS: A better understanding of the pathways that regulate regeneration of the coronary vasculature is of fundamental importance for the advancement of strategies to treat patients with heart disease. Here, we aimed to investigate the origin and clonal dynamics of endothelial cells (ECs) associated with neovascularization in the adult mouse heart following myocardial infarction (MI). Furthermore, we sought to define murine cardiac endothelial heterogeneity and to characterize the transcriptional profiles of pro-angiogenic resident ECs in the adult mouse heart, at single-cell resolution. METHODS AND RESULTS: An EC-specific multispectral lineage-tracing mouse (Pdgfb-iCreERT2-R26R-Brainbow2.1) was used to demonstrate that structural integrity of adult cardiac endothelium following MI was maintained through clonal proliferation by resident ECs in the infarct border region, without significant contributions from bone marrow cells or endothelial-to-mesenchymal transition. Ten transcriptionally discrete heterogeneous EC states, as well as the pathways through which each endothelial state is likely to enhance neovasculogenesis and tissue regeneration following ischaemic injury were defined. Plasmalemma vesicle-associated protein (Plvap) was selected for further study, which showed an endothelial-specific and increased expression in both the ischaemic mouse and human heart, and played a direct role in regulating human endothelial proliferation in vitro. CONCLUSION: We present a single-cell gene expression atlas of cardiac specific resident ECs, and the transcriptional hierarchy underpinning endogenous vascular repair following MI. These data provide a rich resource that could assist in the development of new therapeutic interventions to augment endogenous myocardial perfusion and enhance regeneration in the injured heart.
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Identification of prognostic biomarkers in colorectal cancer through multi-omics profiling of programmed cell death pathways.
BACKGROUND: Programmed cell death (PCD) pathways, including autophagy, ferroptosis, cuproptosis, neutrophil extracellular trap formation (NETosis), and paraptosis, are central to tumor biology and hold potential as therapeutic targets in colorectal cancer (CRC). The aim of this study is to use multi-omics data to analyze the role of PCD in CRC. METHODS: We conducted a multi-omics analysis using data from The Cancer Genome Atlas (TCGA), single-cell sequencing, and spatial transcriptomics to investigate the expression profiles, prognostic significance, and functional effects of PCD-associated genes in CRC. Key prognostic genes were identified through gene set variation analysis (GSVA), single-sample gene set enrichment analysis (ssGSEA), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression modeling. RESULTS: Our analysis identified five PCD pathways with significant prognostic relevance in CRC, particularly autophagy and cuproptosis. Pan-cancer analyses highlighted unique and shared expression patterns of PCD-related genes across diverse cancer types, revealing their differential roles in cancer progression. Dynamic network biomarker (DNB) modeling pinpointed stage-specific critical transitions in PCD pathway activity, suggesting temporal variations in pathway influence on tumor progression. Functional assays demonstrated that overexpression of nuclear receptor coactivator 4 (NCOA4), an autophagy-related gene, suppressed CRC cell migration and invasion while promoting apoptosis, validating its anti-tumor role in CRC. CONCLUSIONS: This study underscores the prognostic significance of PCD pathways in CRC, highlighting their potential as biomarkers and therapeutic targets. By identifying core genes within these pathways and elucidating their temporal effects on tumor progression, we provide a comprehensive foundation for future research into PCD-targeted therapies in CRC, aiming to enhance personalized treatment strategies.
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Novel prognostic alternative splicing events in colorectal Cancer: Impact on immune infiltration and therapy response.
OBJECTIVE: This study aims to comprehensively analyze alternative splicing (AS) features in colorectal cancer (CRC) using integrative multi-omics and to elucidate their relationship with the CRC immune microenvironment. METHODS: Transcriptomic data, clinical information, and Percent Spliced In (PSI) values of AS events for CRC patients were obtained from The Cancer Genome Atlas (TCGA) and TCGA SpliceSeq databases. Differentially expressed AS events were identified. Univariate Cox analysis was used to pinpoint prognosis-related AS events. A prognostic risk model was developed and validated using multivariate Cox analysis, patient survival analysis, and the area under the receiver operating characteristic (ROC) curve (AUC). Gene Set Enrichment Analysis (GSEA), immune infiltration, immunotherapy, chemotherapy sensitivity analyses, and regulatory relationships between AS events and splicing factors (SFs) were conducted. Single-cell sequencing was used to study the distribution of key factors. siRNA and overexpression vectors were utilized to silence/overexpress BCAS1 in CRC cells and evaluate their effects on cell growth, migration, and invasion. Furthermore, the interaction between BCAS1 and ANO7 pre-mRNA was investigated using RIP-PCR. RESULTS: 82 prognosis-related AS events were identified in CRC patients. A 15-AS prognostic model was constructed, which correlated with immune cell infiltration and showed differences in immunotherapy and chemotherapy sensitivity. BCAS1 was identified as a potential regulator of the ANO7|58341|AT splicing event in CRC. Single-cell sequencing analysis revealed the distribution of BCAS1 and ANO7 in cancer stem cells. In vitro experiments demonstrated that overexpression of BCAS1 and silencing of ANO7 inhibit the proliferation, migration, and invasion of CRC cells. Moreover, BCAS1 suppresses the progression of CRC by modulating ANO7 alternative splicing. CONCLUSION: This study provides new insights into the role of alternative splicing in colorectal cancer, particularly the potential regulatory action of BCAS1 on the ANO7|58341|AT splicing event. It also identifies the impact of alternative splicing on the tumor microenvironment and potential implications for immunotherapy, highlighting its relevance for the in-depth study and treatment of CRC.
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Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma.
Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation (RRA) method between tumor and normal tissues from six Gene Expression Omnibus databases (GSE43458, GSE62949, GSE68465, GSE115002, GSE116959, and GSE118370), followed by a selection of prognostic modules using weighted gene co-expression network analysis. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were applied to identify nine hub genes (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) that constructed a prognostic risk model. The RNA expressions of nine hub genes were validated in tumor and normal tissues by RNA-sequencing and single-cell RNA-sequencing, while immunohistochemistry staining from the Human Protein Atlas database showed consistent results in the protein levels. The risk model revealed that high-risk patients were associated with poor prognoses, including advanced stages and low survival rates. Furthermore, a multivariate Cox regression analysis suggested that the prognostic risk model could be an independent prognostic factor for LUAD patients. A nomogram that incorporated the signature and clinical features was additionally built for prognostic prediction. Moreover, the levels of hub genes were related to immune cell infiltration in LUAD microenvironments. A CMap analysis identified 13 small molecule drugs as potential agents based on the risk model for LUAD treatment. Thus, we identified a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 as novel biomarkers and validated their prognostic and predicted values for LUAD.
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Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation.
Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.
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A multi-scale integrated analysis identifies KRT8 as a pan-cancer early biomarker.
An early biomarker would transform our ability to screen and treat patients with cancer. The large amount of multi-scale molecular data in public repositories from various cancers provide unprecedented opportunities to find such a biomarker. However, despite identification of numerous molecular biomarkers using these public data, fewer than 1% have proven robust enough to translate into clinical practice. One of the most important factors affecting the successful translation to clinical practice is lack of real-world patient population heterogeneity in the discovery process. Almost all biomarker studies analyze only a single cohort of patients with the same cancer using a single modality. Recent studies in other diseases have demonstrated the advantage of leveraging biological and technical heterogeneity across multiple independent cohorts to identify robust disease biomarkers. Here we analyzed 17149 samples from patients with one of 23 cancers that were profiled using either DNA methylation, bulk and single-cell gene expression, or protein expression in tumor and serum. First, we analyzed DNA methylation profiles of 9855 samples across 23 cancers from The Cancer Genome Atlas (TCGA). We then examined the gene expression profile of the most significantly hypomethylated gene, KRT8, in 6781 samples from 57 independent microarray datasets from NCBI GEO. KRT8 was significantly over-expressed across cancers except colon cancer (summary effect size=1.05; p < 0.0001). Further, single-cell RNAseq analysis of 7447 single cells from lung tumors showed that genes that significantly correlated with KRT8 (p < 0.05) were involved in p53-related pathways. Immunohistochemistry in tumor biopsies from 294 patients with lung cancer showed that high protein expression of KRT8 is a prognostic marker of poor survival (HR = 1.73, p = 0.01). Finally, detectable KRT8 in serum as measured by ELISA distinguished patients with pancreatic cancer from healthy controls with an AUROC=0.94. In summary, our analysis demonstrates that KRT8 is (1) differentially expressed in several cancers across all molecular modalities and (2) may be useful as a biomarker to identify patients that should be further tested for cancer.
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Macrophage migration inhibitory factor-CD74 axis drives vascular smooth muscle cell-induced M1 macrophage polarization to exacerbate intracranial aneurysm inflammation.
BACKGROUND: Intracranial aneurysms (IAs) develop and progress through pathological processes, including inflammation and abnormal changes in the vascular structure. The cytokine Macrophage Migration Inhibitory Factor (MIF) is implicated in the pathology of vascular diseases. However, the role of MIF in IAs remains to be elucidated. METHODS: Transcriptomic data from IA and normal arteries were analyzed to quantify MIF expression and immune infiltration (CIBERSORT). Methylation sequencing assessed MIF promoter methylation. Single-cell RNA sequencing (scRNA-seq) defined secretory vascular smooth muscle cell (sVSMC) and M1-like macrophage proportions and MIF expression. Intercellular communication via the MIF-CD74 axis was evaluated using CellChat. In vitro functional experiments validated sVSMC-induced macrophage M1 polarization mechanisms. RESULTS: MIF mRNA was significantly upregulated in IAs (diagnostic AUC = 0.89) and correlated with increased M1-like macrophage infiltration (r = 0.783, p = 0.008). Hypomethylation of MIF was observed in IAs. scRNA-seq revealed expanded secretory VSMCs and M1-like macrophages, with elevated MIF in secretory VSMCs. CellChat confirmed enhanced MIF-CD74 signaling. In vitro, secretory VSMCs induced M1 polarization (iNOS/CD86↑, Arg1↓) via MIF-CD74; this effect was reversed by MIF knockdown or CD74 inhibition. CONCLUSION: We provide a comprehensive single-cell atlas of IAs and identify the sVSMC-derived MIF-CD74 axis as a novel mechanism driving macrophage M1 polarization and IA inflammation. This uncovers previously unrecognized sVSMC-macrophage crosstalk, establishing the MIF-CD74 axis as a promising immunomodulatory target for IA therapy.
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Circulating immune cells exhibit distinct traits linked to metastatic burden in breast cancer.
BACKGROUND: Circulating immune cells play a crucial role in the anti-tumour immune response, yet the systemic immune system in metastatic breast cancers is not fully characterised. Investigating the cellular and molecular changes in peripheral blood mononuclear cells (PBMCs) from breast cancer patients could elucidate the role of circulating immune cells in metastasis and aid in identifying biomarkers for disease burden and progression. METHODS: In this study, we characterised the systemic immune landscape associated with varying levels of metastatic burden by analysing the single-cell transcriptomes of PBMCs from breast cancer patients and healthy controls. Our research focused on identifying changes in immune cell composition, transcriptional programs, and immune-cell communication networks linked to metastatic burden. Additionally, we compared these PBMC features onto a single-cell atlas of primary breast tumours to study corresponding traits in tumour-infiltrating immune cells. RESULTS: In metastatic breast cancer, PBMCs exhibit a significant downregulation of the adaptive immune system and a decreased number and activity of unconventional T cells, such as γδ T cells. Additionally, metastatic burden is associated with impaired cell communication pathways involved in immunomodulatory functions. We also identified a gene signature derived from myeloid cells shared between tumour immune infiltrates and circulating immune cells in breast cancer patients. CONCLUSIONS: Our study provides a comprehensive single-cell molecular profile of the peripheral immune system in breast cancer, offering a valuable resource for understanding metastatic disease in terms of tumour burden. By identifying immune traits linked to metastasis, we have unveiled potential new biomarkers of metastatic disease.
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Multi-stage transcriptome analysis reveals genetic orchestration of rat testis development.
BACKGROUND: Testicular development is a highly orchestrated process essential for male fertility, but its temporal genetic regulation remains incompletely resolved in many mammalian models. This study re-analyses rat testis transcriptomes across 15 stages from embryonic day 12 to postnatal week 16 using bulk RNA-sequencing data from a multispecies organ development atlas, generating a continuous, testis-focused temporal framework, and pinpointing key developmental transition windows and regulatory modules. RESULTS: Of 23,748 annotated genes, 17,717 were differentially expressed (DEGs), and hierarchical plus co-expression analyses identified four principal expression modules and five clusters capturing spermatogenic, morphogenetic, immune, and neurone-like programs. Four major transcriptional transition windows, embryonic day 14, embryonic day 19, postnatal week 2, and postnatal week 6, were defined, with the largest remodeling between 2 and 6 weeks coinciding with the onset of robust spermatogenesis and marking a particularly vulnerable window for environmental or toxicant-induced perturbation. Stage-specific spermatogenesis-associated gene sets at embryonic day 19 (n = 28), postnatal week 2 (n = 61), and week 6 (n = 735) showed minimal overlap, supporting sequential regulatory waves driving germ cell commitment, early meiosis, and terminal differentiation. Target enrichment analyses highlighted five conserved microRNAs (rno-miR-151-5p, rno-miR-29b-3p, rno-miR-384-5p, rno-miR-500-5p, rno-miR-672-5p) whose predicted and validated targets form modules related to extracellular matrix remodeling, apoptosis and cell-cycle control, ion-channel signaling, and neuronal-like pathways, with high sequence conservation to human homologs. Immune-related genes and blood-testis barrier components displayed coordinated expression dynamics, and a conserved core of 487 spermatogenesis genes showed strong cross-mammalian orthology, indicating a deeply shared transcriptional backbone on which species-specific regulatory nuances are layered. CONCLUSIONS: This multistage transcriptomic analysis delineates major developmental transitions, co-expression modules, and regulatory miRNA-mRNA networks that orchestrate rat testis maturation and highlight a critical P2W-P6W transition window. The resource complements existing multiorgan and single-cell datasets by providing a testis-focused temporal framework and identifies conserved gene sets and regulatory candidates of direct relevance to male infertility, toxicology, and cross-species translational studies.