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CAFs activated by YAP1 upregulate cancer matrix stiffness to mediate hepatocellular carcinoma progression.
BACKGROUND: The stiffness of the matrix is closely related to the progression of hepatocellular carcinoma (HCC). Although direct targeting of stromal rigidity in HCC remains a clinical challenge, cancer-associated fibroblasts (CAFs) are considered key contributors to this process. Given the heterogeneity of CAFs, this study explored the relationship between specific CAF subsets and liver cancer matrix stiffness, aiming to identify novel therapeutic targets for HCC patients. METHODS: Single-cell sequencing datasets were leveraged to identify cell types within liver cancer and characterize the transcriptomic profiles of CAFs. Prognostic analysis, utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) liver cancer datasets, assessed the correlation between matrix stiffness-related genes and HCC patient outcomes. Pseudo-time analysis was applied to trace the developmental trajectories of CAFs. By calculating intercellular communication probabilities and analyzing transcription factor activity, the functions and interactions of different CAF subsets were elucidated. Gene Ontology (GO) analysis was used to explore the functional roles of CAFs in distinct Yes-associated protein 1 (YAP1) groups. Finally, cellular experiments and animal experiments were further conducted to validate the hypotheses of this study. RESULTS: This study identified CAF subpopulations based on single-cell sequencing data and analyzed transcriptional changes within these subpopulations. Key findings include the identification of collagen type I alpha 1 (COL1A1), collagen type III alpha 1 (COL3A1), and lysyloxidase (LOX) as pivotal node genes during CAF development. Moreover, the expression of matrix stiffness-related genes was inversely correlated with the prognosis of HCC patients. Notably, the YAP1-positive CAF subpopulation emerged as the primary contributor to matrix stiffness in liver cancer. This subpopulation upregulates the expression of matrix stiffness-related genes and promotes tumor progression by activating signaling pathways such as autophagy and GTPase activity regulation. Cellular experiments and animal studies further validated this conclusion. CONCLUSION: This single-cell analysis uncovered the functional roles of CAFs in liver cancer. The YAP1-positive CAF subpopulation, in particular, was shown to contribute to matrix stiffness by upregulating the expression of relevant genes and promoting tumor progression through the activation of specific signaling pathways.
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Spatial mapping, isolation, and culture of primary human microglia and astrocytes: A systematic review and framework for glial cell-based models.
Microglia and astrocytes are essential glial cells in the CNS that play key roles in brain development, homeostasis, and disease. While immortalized cell lines are convenient, they lack the physiological relevance of primary cells, highlighting the need for reliable human-based isolation protocols. This systematic review synthesizes 21 studies describing methods for isolating and culturing primary human microglia and astrocytes from adult surgical resections, postmortem tissues, and fetal brains. Using the Human Brain Cell Atlas v1.0 single-nuclei RNA-Seq dataset and voxel-wise mapping on the MNI152 template, we provide a spatial transcriptomic context for region-specific glial isolation. We critically assess tissue dissociation techniques, enrichment strategies, and culture conditions, including substrate coatings and growth factors. Additionally, we summarize phenotypic and functional assays used for characterization including surface marker expression, phagocytosis, and cytokine profiling. Despite variability across protocols, we propose an optimized, spatially informed workflow to reproducibly isolate viable, pure glial populations from human brain tissues. This approach supports New Approach Methodologies and the 3Rs-Replacement, Reduction, and Refinement by promoting ethical, human-relevant in vitro models. Our framework advances glial cell-based systems, improving the translational relevance of neurodegenerative and neuroinflammatory disease research and aligns with multiple United Nations Sustainable Development Goals through responsible scientific practices.
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The role of KIAA1467 in breast cancer: insights from pan-cancer and single-cell sequencing analysis.
BACKGROUND: Improving the response rate of single-agent immune checkpoint blockade (ICB) urgently requires the discovery of new therapeutic targets for combinatorial regimens. Analyses of tumor microenvironment (TME)-associated biomarkers have verified that KIAA1467 drives the formation of an immune-excluded, non-inflamed TME in breast cancer (BRCA). This study systematically explores the expression pattern, prognostic value, immune regulatory function, biological effects, and drug resistance relevance of FAM234B (also known as KIAA1467) in BRCA. METHODS: We performed pan-cancer survival analysis using The Cancer Genome Atlas (TCGA) datasets. Multi-omics bioinformatics analyses were conducted to evaluate KIAA1467 expression across malignancies. Single-cell RNA sequencing (scRNA-seq) data from GSE176078 was utilized to localize KIAA1467 expression at the cellular level. Immunohistochemistry and western blot assays validated KIAA1467 expression in BRCA clinical specimens. Correlation analyses were implemented to assess relationships between KIAA1467 expression, clinicopathological features, immune modulators, tumor-infiltrating immune cells, and p53 mutation status. Functional enrichment analysis uncovered relevant signaling pathways. Bioinformatic half maximal inhibitory concentration (IC50) prediction and in vitro cellular experiments were applied to evaluate associations between KIAA1467 and chemotherapeutic drug sensitivity. RESULTS: TCGA pan-cancer survival analysis demonstrated that elevated KIAA1467 expression significantly predicted shortened overall survival in BRCA and multiple other tumor types. KIAA1467 displayed distinct expression patterns across cancers, with prominent upregulation in BRCA. scRNA-seq confirmed enriched KIAA1467 expression within BRCA cells, and its upregulation in BRCA tissues was further verified by immunohistochemistry and western blot. High KIAA1467 expression was positively correlated with advanced tumor grade and lymphatic metastasis. KIAA1467 showed negative correlations with most immune modulators and core immune checkpoint molecules, as well as tumor-infiltrating immune cells in the TME, implying its potential function in tumor immune evasion. Low KIAA1467 expression was tightly linked to p53 mutations. Enrichment analysis indicated participation of KIAA1467 in epithelial-mesenchymal transition, apoptosis and cell cycle arrest. Furthermore, high KIAA1467 expression corresponded to higher estimated IC50 values of cisplatin, gefitinib, paclitaxel and gemcitabine, consistent with reduced chemosensitivity observed in vitro. CONCLUSIONS: This study reveals the multifaceted oncogenic role of KIAA1467 in BRCA. KIAA1467 participates in remodeling an immunosuppressive TME, correlates with malignant progression and chemoresistance, and may serve as a promising candidate target to optimize ICB-based combination therapy for BRCA. These findings offer new perspectives for the clinical treatment and comprehensive management of BRCA.
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Establishment of a new prognostic risk model of MAPK pathway-related molecules in kidney renal clear cell carcinoma based on genomes and transcriptomes analysis.
PURPOSE: The mitogen-activated protein kinase (MAPK) signaling pathway is often studied in oncology as the most easily mentioned signaling pathway. This study aims to establish a new prognostic risk model of MAPK pathway related molecules in kidney renal clear cell carcinoma (KIRC) based on genome and transcriptome analysis. METHODS: In our study, RNA-seq data were acquired from the KIRC dataset of The Cancer Genome Atlas (TCGA) database. MAPK signaling pathway-related genes were obtained from the gene enrichment analysis (GSEA) database. We used "glmnet" and the "survival" extension package for LASSO (Least absolute shrinkage and selection operator) regression curve analysis and constructed a prognosis-related risk model. The survival curve and the COX regression analysis were used the "survival" expansion packages. The ROC curve was plotted using the "survival ROC" extension package. We then used the "rms" expansion package to construct a nomogram plot. We performed a pan-cancer analysis of CNV (copy number variation), SNV (single nucleotide variant), drug sensitivity, immune infiltration, and overall survival (OS) of 14 MAPK signaling pathway-related genes using several analysis websites, such as GEPIA website and TIMER database. Besides, the immunohistochemistry and pathway enrichment analysis used The Human Protein Atlas (THPA) database and the GSEA method. Finally, the mRNA expression of risk model genes in clinical renal cancer tissues versus adjacent normal tissues was further verified by real-time quantitative reverse transcription (qRT-PCR). RESULTS: We performed Lasso regression analysis using 14 genes and created a new KIRC prognosis-related risk model. High-risk scores suggested that KIRC patients with lower-risk scores had a significantly worse prognosis. Based on the multivariate Cox analysis, we found that the risk score of this model could serve as an independent risk factor for KIRC patients. In addition, we used the THPA database to verify the differential expression of proteins between normal kidney tissues and KIRC tumor tissues. Finally, the results of qRT-PCR experiments suggested large differences in the mRNA expression of risk model genes. CONCLUSIONS: This study constructs a KIRC prognosis prediction model involving 14 MAPK signaling pathway-related genes, which is essential for exploring potential biomarkers for KIRC diagnosis.
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Brain-based gene expression and corresponding behavioural relevance of risk genes for broad antisocial behaviour.
Antisocial behaviour (ASB) involves persistent irresponsible, delinquent activities violating rights and safety of others. A meta-analysis of genome-wide association studies revealed significant genetic associations with ASB, yet their brain expression patterns and behavioural relevance remain unclear. Our investigation of fifteen genes associated with ASB examined their biological role and distribution across tissues, integrating post-mortem brain sample data from the Allen-Human-Brain Atlas and the Genotype-Tissue Expression project. We found that these genes were differentially expressed in the brain, particularly in regions like the cerebellum, putamen, and caudate, and were notably downregulated in the pancreas. Single cell type expression analysis revealed that ASB-associated genes had strong correlations with ductal and endothelial cells in the pancreas, indicating a possible metabolic influence on ASB. Certain genes like NTN1, SMAD5, NCAM2, and CDC42EP3 displayed specificity for cognitive terms including chronic pain, heart rate, and aphasia. These expression patterns aligned with neurocognitive domains related to thinking, and learning, distress, motor skills, as determined by fMRI analysis. This study connects specific brain gene expression with potential genetic and metabolic factors in ASB, offering novel insights into its biological basis and possible interdisciplinary approaches to understanding and addressing aggressive behaviours.
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Comprehensive Investigation Illustrates the Role of M2 Macrophages and Its Related Genes in Pancreatic Cancer.
Background and Objectives: M2 macrophages play an important role in cancers. Our study aimed to illustrate the effect of M2 macrophages in pancreatic cancer (PC). Materials and Methods: The open-access data used for analysis were downloaded from The Cancer Genome Atlas Program database, as well as some online databases. R software was mainly used for data analysis based on the specific packages. Results: Here, we comprehensively investigated the role of M2 macrophages and their related genes in PC. We performed the biological enrichment of M2 macrophages in PC. Meanwhile, we identified adenosine A3 receptor (TMIGD3) as the interest gene for further analysis. The single-cell analysis showed that was mainly expressed in the Mono/Macro cells based on the data from multiple data cohorts. Biological investigation showed that TMIGD3 was primarily enriched in angiogenesis, pancreas-beta cells and TGF-beta signaling. Tumor microenvironment analysis indicated that TMIGD3 was positively correlated with monocyte_MCPCOUNTER, NK cell_MCPCOUNTER, macrophages M2_CIBERSORT, macrophage_EPIC, neutrophil_TIMER and endothelial cell_MCPCOUNTER. Interestingly, we determined that all the immune functions quantified by single sample gene set enrichment analysis algorithms were activated in the patients with high TMIGD3 expression. Conclusions: Our results provide a novel direction for the research focused on the M2 macrophages in PC. Meanwhile, TMIGD3 was identified as an M2 macrophage-related biomarker for PC.
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Upregulation of GOLPH3 mediated by Bisphenol a promotes colorectal cancer proliferation and migration: evidence based on integrated analysis.
BACKGROUND: The interaction between environmental endocrine-disrupting chemicals, such as Bisphenol A (BPA), and their influence on cancer progression, particularly regarding the GOLPH3 gene in colorectal cancer, remains unclear. METHODS: We performed an integrated analysis of transcriptional profiling, clinical data, and bioinformatics analyses utilizing data from the Comparative Toxicogenomics Database and The Cancer Genome Atlas. The study employed ClueGO, Gene Set Enrichment Analysis, and Gene Set Variation Analysis for functional enrichment analysis, alongside experimental assays to examine the effects of BPA exposure on colorectal cancer cell lines, focusing on GOLPH3 expression and its implications for cancer progression. RESULTS: Our findings demonstrated that BPA exposure significantly promoted the progression of colorectal cancer by upregulating GOLPH3, which in turn enhanced the malignant phenotype of colorectal cancer cells. Comparative analysis revealed elevated GOLPH3 protein levels in cancerous tissues versus normal tissues, with single-cell analysis indicating widespread GOLPH3 presence across various cell types in the cancer microenvironment. GOLPH3 was also associated with multiple carcinogenic pathways, including the G2M checkpoint. Furthermore, our investigation into the colorectal cancer microenvironment and genomic mutation signature underscored the oncogenic potential of GOLPH3, exacerbated by BPA exposure. CONCLUSION: This study provides novel insights into the complex interactions between BPA exposure and GOLPH3 in the context of colorectal cancer, emphasizing the need for heightened awareness and measures to mitigate BPA exposure risks. Our findings advocate for further research to validate these observations in clinical and epidemiological settings and explore potential therapeutic targets within these pathways.
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Cancer Stemness Associated With Prognosis and the Efficacy of Immunotherapy in Adrenocortical Carcinoma.
BACKGROUND: Cancer stem cells (CSCs) have been proven to influence drug resistance, recurrence, and metastasis in tumors. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in adrenocortical carcinoma. METHODS: RNA-seq data and clinical characteristics were downloaded from The Cancer Genome Atlas (TCGA). The stemness indexes, mDNAsi and mRNAsi, were calculated to classify all samples into low-score and high-score groups. Two algorithms, based on the R language, ESTIMATE and single-sample Gene Set Enrichment Analysis (ssGSEA) were used to assess the immune cell infiltration states of adrenocortical carcinoma patients. Weighted Gene Co-expression Network Analysis (WGCNA) was used to find genes that were related to the stemness of cancer. By bioinformatics methods, the correlations between biomarkers capable of predicting immune checkpoint inhibitors (ICIs) responses and stemness of cancer were explored. RESULTS: High-mRNAsi predicted shorter overall survival (OS) and a higher metastatic trend in adrenocortical carcinoma (ACC) patients. Compared with the low-mRNAsi group, the high-mRNAsi group had a lower ImmuneScore and StromalScroe. Twenty-two stemness-related prognostic genes were obtained by WGCNA, which focused on the function of the cell cycle and cell mitosis. Immune cell infiltration, especially CD8+T cell, increased in the low-mRNAsi group compared with the high-mRNAsi group. Lower expression of PD-L1, CTLA-4, and TIGHT was evaluated in the high-mRNAsi group. CONCLUSIONS: ACC patients with high-mRNAsi have poor prognosis and less immune cell infiltration. Combined with the finding of lower expression of CTLA-4, TIGHT, and PD-L1 in the high-mRNAsi group, we came to the conclusion that stemness index is a potential biomarker to predict the effectiveness of ICIs.
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Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis.
BACKGROUND: The treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancer-associated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma. METHODS: The Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated. RESULTS: Using the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma. CONCLUSION: COL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics.
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EDomics: a comprehensive and comparative multi-omics database for animal evo-devo.
Evolutionary developmental biology (evo-devo) has been among the most fascinating interdisciplinary fields for decades, which aims to elucidate the origin and evolution of diverse developmental processes. The rapid accumulation of omics data provides unprecedented opportunities to answer many interesting but unresolved evo-devo questions. However, the access and utilization of these resources are hindered by challenges particularly in non-model animals. Here, we establish a comparative multi-omics database for animal evo-devo (EDomics, http://edomics.qnlm.ac) containing comprehensive genomes, bulk transcriptomes, and single-cell data across 40 representative species, many of which are generally used as model organisms for animal evo-devo study. EDomics provides a systematic view of genomic/transcriptomic information from various aspects, including genome assembly statistics, gene features and families, transcription factors, transposable elements, and gene expressional profiles/networks. It also exhibits spatiotemporal gene expression profiles at a single-cell level, such as cell atlas, cell markers, and spatial-map information. Moreover, EDomics provides highly valuable, customized datasets/resources for evo-devo research, including gene family expansion/contraction, inferred core gene repertoires, macrosynteny analysis for karyotype evolution, and cell type evolution analysis. EDomics presents a comprehensive and comparative multi-omics platform for animal evo-devo community to decipher the whole history of developmental evolution across the tree of life.