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Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer.
Recent studies have proposed that pyruvate dehydrogenase E1 component subunit alpha (PDHA1), a cuproptosis-key gene, is crucial to the glucose metabolism reprogram of tumor cells. However, the functional roles and regulated mechanisms of PDHA1 in multiple cancers are largely unknown. The Cancer Genome Atlas (TCGA), GEPIA2, and cBioPortal databases were utilized to elucidate the function of PDHA1 in 33 tumor types. We found that PDHA1 was aberrantly expressed in most cancer types. Lung adenocarcinoma (LUAD) patients with high PDHA1 levels were significantly correlated with poor prognosis of overall survival (OS) and first progression (FP). Kidney renal clear cell carcinoma (KIRC) patients with low PDHA1 levels displayed poor OS and disease-free survival (DFS). However, for stomach adenocarcinoma (STAD), the downregulated PDHA1 expression predicted a good prognosis in patients. Moreover, we evaluated the mutation diversity of PDHA1 in cancers and their association with prognosis. We also analyzed the protein phosphorylation and DNA methylation of PDHA1 in various tumors. The PDHA1 expression was negatively correlated with tumor-infiltrating immune cells, such as myeloid dendritic cells (DCs), B cells, and T cells in pan-cancers. Mechanically, we used single-cell sequencing to discover that the PDHA1 expression had a close link with several cancer-associated signaling pathways, such as DNA damage, cell invasion, and angiogenesis. At last, we conducted a co-expressed enrichment analysis and showed that aberrantly expressed PDHA1 participated in the regulation of mitochondrial signaling pathways, including oxidative phosphorylation, cellular respiration, and electron transfer activity. In summary, PDHA1 could be a prognostic and immune-associated biomarker in multiple cancers.
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Gene expression and immune cell heterogeneity in inbred Amur tiger.
Inbreeding leads to a reduction in genetic diversity and an elevated likelihood of expressing recessive defective genes, which adversely affect the development of the immune system and render individuals and populations more susceptible to carcinogenic factors, consequently heightening the risk of cancer. Through investigating the function and extent of immune cell interaction in peripheral blood mononuclear cells (PBMCs) of inbred individual, a comprehensive understanding can be gained regarding the impact of inbreeding on various aspects of the immune system, including diversity, self-tolerance, immune responsiveness, susceptibility to diseases, and other related areas. Currently, the wild Amur tiger population in China exhibits a moderate degree of inbreeding, with a probability exceeding 90% that it will be deemed extinct within the forthcoming century. However, the impact of inbreeding on the immune system remains ambiguous, presenting numerous challenges for the development and implementation of conservation strategies. Here, for the first time, a detailed single-cell sequencing atlas of peripheral blood samples obtained from Amur tigers is presented, delineating eight distinct cell types. Our study demonstrates that the inbred tiger exhibits a relatively lower proportion of lymphocytes and cDC2 cells, along with reduced intercellular interactions. We also observed elevated activity in several signaling pathways (e.g., TGFb, APRIL, BAG, GRN, VISFATIN) that have been linked to inflammation and cancer in other species. The WGCNA analysis analysis further suggested a candidate regulatory network in inbred tiger, with the cancer-associated gene YTHDC2 emerging as a hub gene. Together, our exploratory study offers preliminary insights into the immune heterogeneity in inbred Amur tigers and can potentially guide future studies aimed at enabling timely health interventions for this endangered species.
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Single-nucleus profiling highlights the all-brain echinoderm nervous system.
Metazoans comprise diverse tissues and cell types, each essential for the organismal survival. Most of these types are established early in embryogenesis and persist into adulthood. In indirectly developing sea urchins, however, the continuity between embryonic and adult stages is interrupted by a planktonic larval stage that undergoes complete metamorphosis. While gene regulatory networks controlling embryonic and larval lineages are well studied, the molecular and morphological identities of postmetamorphic cell types remain poorly understood. Here, we reconstructed the cell atlas of postmetamorphic Paracentrotus lividus juveniles using single-nucleus transcriptomics, revealing conservation of regulatory mechanisms. We identified signatures of eight distinct cell type groups and analyzed 29 neuronal families, including 15 unique photoreceptor types. By combining transcriptomics, spatial analysis, and ultrastructure, we identified vertebrate neuronal and opsin homologs expressed across the juvenile. These findings show that the echinoderm body plan is predominantly head-like and exhibits an "all-brain" organization.
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Spinster homolog 2 reduces malignancies of glioblastoma via PTEN/PI3K/AKT pathway.
The molecular mechanisms of glioblastoma (GBM) are unclear, and the prognosis is poor. Spinster homolog 2 (SPNS2) is reportedly involved in pathological processes such as immune response, vascular development, and cancer. However, the biological function and molecular role of SPNS2 in GBM are unclear. SPNS2 is aberrantly low expressed in glioma. Survival curves, risk scores, prognostic nomograms, and univariate and multifactorial Cox regression analyses showed that SPNS2 is an independent prognostic indicator significantly associated with glioma progression and prognosis. Cell function assays and in vivo xenograft transplantation were performed that downregulation of SPNS2 promoted GBM cell growth, migration, invasion, epithelial-mesenchymal transition (EMT), anti-apoptosis, drug resistance, and stemness, while overexpression of SPNS2 had the opposite effect. Meanwhile, the functional enrichment and signaling pathways of SPNS2 in the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and RNA sequencing were analyzed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA). The above results were related to the inhibition of the PTEN/PI3K/AKT pathway by SPNS2. In addition, we predicted that SPNS2 is closely associated with immune infiltration in the tumor microenvironment by four immune algorithms, ESTIMATE, TIMER, CIBERSORT, and QUANTISEQ. In particular, SPNS2 was negatively correlated with the infiltration of most immune cells, immunomodulators, and chemokines. Finally, single-cell sequencing analysis also revealed that SPNS2 was remarkably correlated with macrophages, and downregulation of SPNS2 promotes the expression of M2-like macrophages. This study provides new evidence that SPNS2 inhibits malignant progression, stemness, and immune infiltration of GBM cells through PTEN/PI3K/AKT pathway. SPNS2 may become a new diagnostic indicator and potential immunotherapeutic target for glioma.
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Identification of anoikis-related gene signatures and construction of the prognosis model in prostate cancer.
BACKGROUND: One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated. METHODS: Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub). RESULTS: 113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa. CONCLUSION: We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.
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Identification and validation of a fatty acid metabolism gene signature for the promotion of metastasis in liver cancer.
Metastasis is a fatal status for liver cancer, and the identification of an effective prediction model and promising therapeutic target is essential. Given the known relationship between fatty acid (FA) metabolism and the liver, the present study aimed to investigate dysregulation of genes associated with FA metabolism in liver cancer. Bioinformatics analyses were performed on data from patients with hepatocellular carcinoma (HCC) obtained from The Cancer Genome Atlas database using R software packages. Online public tools such as the Human Protein Atlas, Tumor Immune Single-Cell Hub and the University of Alabama at Birmingham Cancer Data Analysis portal were also utilized. Some essential results were further verified using in vitro experiments using HepG2 liver cancer cells. A signature consisting of three genes associated with the progression and prognosis of HCC and FA metabolism was identified. When samples were scored based on the expression of these genes and divided according to the median value, the higher score group showed a worse outcome and repressive immune microenvironment than the lower score group. Downstream pathways such as hypoxia, IL6/JAK/STAT3 and epithelial-mesenchymal transition were found to be significantly activated in the higher score group. As the core factor in the signature, mitochondrial ribosomal protein L35 (MRPL35) was found to be upregulated in HCC and to have certain impacts on the dysregulation of effective immunity. Further investigations and in vitro experiments indicated that MRPL35 facilitates the migration and invasion abilities of liver cancer, and the resistance of HCC to treatment. These findings have important implications regarding the characteristics and mechanisms of metastasis in liver cancer, and provide a promising signature based on FA metabolism-related genes that may be used to predict outcomes and explored as a novel therapeutic target in liver cancer.
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SOX11 and GLIS2: Novel Biomarkers for Understanding the Progression of Oral Leukoplakia.
BACKGROUND: Oral leukoplakia (LP) is a common precancerous lesion that can progress to oral squamous cell carcinoma (OSCC). Although various risk factors have been identified, the molecular mechanisms and biomarkers of LP remain insufficiently understood. METHODS: This study integrated single-cell RNA sequencing with bulk RNA sequencing data from leukoplakia tissues to investigate the transcriptional regulatory mechanisms within LPtissues. Our aim is to identify key molecular markers and their associated pathways. Furthermore, by analyzing survival data from OSCC in the The Cancer Genome Atlas(TCGA) database, we assessed the prognostic significance of these molecular markers in tumors. Finally, we validated the potential roles of relevant molecular markers in the progression of leukoplakia using patient LP tissue samples. RESULTS: The analysis revealed that single-cell RNA sequencing data indicated that fibroblasts in LP tissues possess a unique gene regulatory network, exhibiting significantly different transcriptional characteristics compared to normal tissues. We identified SOX11 and GLIS2 as LP-specific molecular markers, with their expression significantly elevated in LP tissues compared to normal tissues. Transcriptomic profiling of LP reveals that SOX11 and GLIS2 positively correlate with the activation of epithelial-mesenchymal transition (EMT) and angiogenesis. Additionally, analysis of OSCC samples demonstrated that high expression levels of SOX11 and GLIS2 were associated with poor prognosis. Immunohistochemical staining further showed a gradual increase in the expression of SOX11 and GLIS2 during the progression of leukoplakia, supporting their potential application as biomarkers. CONCLUSION: As key transcription factors in LP, SOX11 and GLIS2 may influence the occurrence and development of lesions by regulating EMT and angiogenesis biological processes. They have the potential to serve as biomarkers and therapeutic targets for LP and OSCC, providing new insights into understanding the mechanisms of LP and developing treatment strategies.
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The landscape in telomere related gene prognostic signature for survival and medication treatment effectiveness prediction in hepatocellular carcinoma.
OBJECTIVE: Telomeres, made of repetitive DNA sequences and shelterin complexes, which were found at the ends of chromosomes and had been extensively studied in cancer research. However, in hepatocellular carcinoma (HCC) was still relatively scarce. In this study, we investigated the correlation between telomerase-related genes (TRGs) and the prognosis and immunotherapy of HCC patients to enhance clinical outcomes. METHODS: In this work, TRGs were gathered using TelNet, while clinical information and gene expression data for HCC patients were retrieved from the Cancer Genome Atlas (TCGA) database. A risk prediction model based on TRGs was created using COX and Lasso regression analyses, with ROC curves used to assess prognostic efficacy. Univariate and multifactorial COX regression analyses were used to determine if the risk model had an independent impact on prognosis. Nomograms were created to enhance clinical usability, and calibration curves were used to assess predictive ability at various time points. The Tumor Immune Dysfunction and Exclusion (TIDE) score was used to analyze differences in immune infiltrating cells between risk groups. The study analyzed the relationship between risk ratings and drug treatment effectiveness using data from the CellMiner database. The hub gene was identified and its relationship to prognostic markers of HCC patients was examined. The expression of hub genes in immune cell subpopulations was also investigated by single-cell data. RESULTS: 2093 TRGs were identified, with 949 showing significant differences in expression between HCC and paracancerous tissues. Seven risk genes were overexpressed in tumor tissues, leading to lower survival rates in high-risk patients. Risk model could independently predict the prognosis of HCC patients. Analysis of tumor immune infiltrating cells revealed significant differences in cell abundance between risk groups, with notable variations in immune subset enrichment between subgroups. Higher risk scores correlated with increased sensitivity to sorafenib, mitoxantrone, oxaliplatin, gemcitabine, and entinostat, while sensitivity decreased for vincristine, etc. CDCA8 was identified as a key gene in the Protein Interaction Network, while high expression associated with poorer overall survival, tumor proliferation and metastasis. The results of single-cell data analysis suggest that CDCA8 may promote the development of HCC by affecting T lymphocytes. CONCLUSION: The TRG-based risk model could predict HCC patient prognosis and closely linked to tumor immune environment, which could offer new possibilities for clinical treatment.
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Multi-omics analyses related to unfolded protein response in prostate cancer implicate pro-tumor role of IFRD1.
INTRODUCTION: The unfolded protein response (UPR) promotes prostate cancer (PCa) progression, yet its multi-omics landscape and clinical utility remain undefined. METHODS: We integrated single-cell and bulk transcriptomic datasets, and identified UPR-related genes (UPRRGs) through a combination of differential expression analysis and weighted gene co-expression network analysis (WGCNA), based on which we further developed a consensus UPR-related signature (UPRRS) using a machine learning framework. The UPRRGs were further characterized by functional enrichment, cell-cell communication, and survival analyses. A clinically applicable nomogram integrating UPR-related prognostic genes was constructed for prognostic prediction. Through in silico and in vitro analyses, we validated the clinical relevance between the hub UPRRGs and PCa progression. RESULTS: Single-cell analyses revealed elevated UPR activity in prostate epithelial cells, most prominently within the LE-KLK3 subpopulation. These cells exhibited enhanced ligand-receptor interactions in TNF, VEGF and NOTCH signaling axes. A seven-UPRRG signature (including IFRD1, DDIT3, HSPA5) demonstrated robust prognostic performance in the TCGA training set and three external validation cohorts (C-index > 0.82; AUC > 0.80). Multivariate Cox analysis confirmed UPRRS as an independent prognostic factor beyond clinical stage and Gleason score. Mechanistically, the UPRRS-high subgroup displayed an immunosuppressive microenvironment and reduced sensitivity to multiple chemotherapeutics. In vitro knock-down of IFRD1 markedly attenuated PCa cell proliferation and migration. CONCLUSION: We provide the first systematic single-cell atlas of UPR heterogeneity in PCa and develop a clinically translatable UPRRS prognostic model. IFRD1, a key driver, emerges as a dual diagnostic and therapeutic target, offering both theoretical and experimental foundations for precision stratification and individualized management of PCa.
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An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics.
Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung.