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A risk score model based on glycosylation-related genes for predicting radioresistance and prognosis of lung adenocarcinoma.
BACKGROUND: Radiotherapy resistance (RR) is the main cause of radiotherapy failure in lung cancer patients, and its mechanisms are still unrevealed. Glycosylation, as a type of post-translational modification of proteins, plays a key role in tumor progression. Some studies have shown a strong link between glycosylation and RR. However, the absence of a systematic glycosylation-related genes (GRGs) model to predict radiotherapy efficacy in lung adenocarcinoma (LUAD) patients highlights a significant clinical and research gap. The aim of the research was to investigate the prognostic characteristics of GRGs in LUAD treated with radiotherapy. METHODS: RNA sequencing data of LUAD were obtained from The Cancer Genome Atlas (TCGA) database. The expression and prognostic significance of GRGs in patients who underwent radiotherapy were analyzed with bioinformatics tools, and the Gene Expression Omnibus (GEO) database was used for verification. Gene set enrichment analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), etc. were used to analyze the potential mechanism of risk model constructed by GRGs in LUAD. The predictive significance of risk model was investigated by immune infiltration analysis, somatic mutations, and drug susceptibility analysis, etc. Single-cell sequencing and molecular docking were used to find new potential targets for LUAD patients. Finally, our bioinformatics analysis results were verified by wet experiments. RESULTS: GO and KEGG analyses found that glycosylation played a pivotal role in LUAD RR. Forty-four differentially expressed radiotherapy-related glycosylation genes (DERRGGs) were identified in LUAD. KREMEN2, NRARP, QSOX2, GOLGA3, CELSR2, and SRI were screened out by least absolute shrinkage and selection operator (LASSO) analysis. A new risk model was constructed by these six DERRGGs, which showed good predictive power. Multivariate regression found that RiskScore was an independent prognostic factor. Immune infiltration analysis suggested that patients in the high-risk group were more susceptible to suffer from immunosuppression. Single-cell sequencing analysis showed the six genes were mainly distributed in malignant tumors. Drug sensitivity analysis found that the patients in the high-risk group were more sensitive to the clinical drugs, such as afatinib, cytarabine, gemcitabine and so on. Molecular docking demonstrated that tretinoin showed good binding affinity with NRARP, KREMEN2 and QSOX2. Our wet experiment results not only demonstrated that NRARP, KREMEN2 and QSOX2 were more abundant in LUAD irradiation-resistance cells and NRARP protein was significantly up-regulated in radiation-resistant samples, but also showed that tretinoin inhibited the survival of the irradiation-resistance cell obviously. CONCLUSIONS: This study constructed glycosylation related RiskScore to predict the prognosis of LUAD patients, specifically in the context of radiotherapy. We explored the relationship between radiotherapy efficacy, glycosylation and prognosis of LUAD patients, which provides new ideas for personalized treatment of LUAD patients. And we suggested that tretinoin may be a potential radiotherapy sensitizer for LUAD, providing a foundation for future investigations.
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Genetic and genomic insights into male reproductive tract development.
Genetic and genomic analysis continues to drive important insights into male reproductive tract (MRT) development. Here, we briefly review normal MRT development, highlighting recent discoveries of cell types and cellular processes delivered by single-cell sequencing. We report a systematic review of phenotype terms and genes linked to MRT development, identifying 35 terms from the Human Phenotype Ontology associated with 269 unique genes. A parallel review of mouse data revealed differences in the phenotype terms available and the number and identity of genes linked to MRT defects, indicating opportunities for harmonization of knowledge. We used a published single-cell atlas of the developing testis to characterize the regulation of MRT genes across cell types and stages of fetal testis development. Single-cell RNA sequencing data support the conclusion that Leydig cells and Sertoli cells are the primary testicular cell types expressing MRT genes. Furthermore, we find post-conception weeks 6, 8, and 16 to be the key points of upregulation of testicular MRT genes. New advances, especially in imaging and spatially resolved molecular measurements, provide exciting prospects for MRT research and diagnosis, and we expect rapid progress in the coming years. Continued investigation in this space is essential to understand the genetic basis of MRT development and how MRT defects are related to medical outcomes in adult life.
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Identification of mitochondrial-related subtypes and development of a prognostic model for pancreatic ductal adenocarcinoma.
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a poor prognosis. Mitochondrial dysfunction, including alterations in metabolism, dynamics, and DNA, is increasingly recognized as a critical factor in the initiation and progression of pancreatic cancer. This study aimed to systematically investigate the role of mitochondrial dysfunction in PDAC to identify mitochondria-related genes (MitoRGs) of prognostic significance, explore associated molecular subtypes, and examine their effects on the tumor immune microenvironment. METHODS: We integrated transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify a set of MitoRGs with significant prognostic value for PDAC. Their expression was further validated in PDAC cells and using single-cell RNA-sequencing data. Unsupervised clustering was employed to classify PDAC patients into distinct subtypes based on MitoRG expression patterns. A robust prognostic model was subsequently constructed using least absolute shrinkage and selection operator-Cox regression analysis. The predictive accuracy of the model for 1-, 3-, and 5-year overall survival (OS) was assessed. The immune cell infiltration and genomic features of the risk groups defined by the model were also analyzed. Finally, a clinically applicable nomogram was developed to facilitate prognostic prediction. RESULTS: Based on MitoRG expression, PDAC patients were classified into two distinct subtypes (clusters A and B). Patients in cluster A exhibited significantly better OS than those in cluster B. A prognostic model based on a seven-MitoRG signature was established, which demonstrated high predictive accuracy. The high-risk group, as defined by the model, was characterized by an immunosuppressive tumor microenvironment, featuring reduced cytotoxic T-cell activity and increased stromal components. This group also showed significant enrichment of driver mutations such as KRAS and TP53. CONCLUSIONS: This study established a significant link between mitochondrial dysfunction and PDAC molecular subtypes, immune microenvironment remodeling, and clinical prognosis. The developed seven-MitoRG signature and nomogram could serve as reliable prognostic tools. These findings provide insights into the role of mitochondria in the pathogenesis of PDAC and offer potential targets for developing personalized therapeutic strategies.
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Global characterization of megakaryocytes in bone marrow, peripheral blood, and cord blood by single-cell RNA sequencing.
Megakaryocytes (MK) are mainly derived from bone marrow and are mainly involved in platelet production. Studies have shown that MK derived from bone marrow may have immune function, and that MK from peripheral blood are associated with prostate cancer. Single-cell transcriptome sequencing can help us better understand the heterogeneity and potential function of MK cell populations in bone marrow (BM), peripheral Blood (PB), and cord blood (CB) of healthy and diseased people.We integrated more than 1.2 million single-cell transcriptome data from 132 samples of PB, BM, and CB from healthy individuals and patients from different dataset. We examined the MK (including MK and product of MK) by single-cell RNA sequencing data analysis methods and identification of MK-related protein expression by the Human Protein atlas. We investigate the relationship between the MK subtype and Non-Small Cell Lung Cancer (NSCLC) in 77 non-cancer and 402 NSCLC. We found that MK were widely distributed and the amount of MK in peripheral blood was more than that in bone marrow and there were specificity MK subtypes in peripheral blood. We found classical MK1 with typical MK characteristics and non-classical MK2 closely related to immunity which was the most common subtype in bone marrow and cord blood. Classical MK1 was closely related to Non-Small Cell Lung Cancer (NSCLC) and can be used as a diagnostic marker. MK2 may have potential adaptive immune function and play a role in tumor NSCLC and autoimmune diseases Systemic Lupus Erythematosus. MK have 14 subtypes and are widely distributed in PB, CB, and BM. MK subtypes are closely related to immunity and have potential to be a diagnostic indicator of NSCLC.
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Alternative polyadenylation drives oncogenic gene expression in pancreatic ductal adenocarcinoma.
Alternative polyadenylation (APA) is a gene regulatory process that dictates mRNA 3'-UTR length, resulting in changes in mRNA stability and localization. APA is frequently disrupted in cancer and promotes tumorigenesis through altered expression of oncogenes and tumor suppressors. Pan-cancer analyses have revealed common APA events across the tumor landscape; however, little is known about tumor type-specific alterations that may uncover novel events and vulnerabilities. Here, we integrate RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA) to comprehensively analyze APA events in 148 pancreatic ductal adenocarcinomas (PDACs). We report widespread, recurrent, and functionally relevant 3'-UTR alterations associated with gene expression changes of known and newly identified PDAC growth-promoting genes and experimentally validate the effects of these APA events on protein expression. We find enrichment for APA events in genes associated with known PDAC pathways, loss of tumor-suppressive miRNA binding sites, and increased heterogeneity in 3'-UTR forms of metabolic genes. Survival analyses reveal a subset of 3'-UTR alterations that independently characterize a poor prognostic cohort among PDAC patients. Finally, we identify and validate the casein kinase CSNK1A1 (also known as CK1alpha or CK1a) as an APA-regulated therapeutic target in PDAC. Knockdown or pharmacological inhibition of CSNK1A1 attenuates PDAC cell proliferation and clonogenic growth. Our single-cancer analysis reveals APA as an underappreciated driver of protumorigenic gene expression in PDAC via the loss of miRNA regulation.
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Characterization of a G2M checkpoint-related gene model and subtypes associated with immunotherapy response for clear cell renal cell carcinoma.
Clear cell renal cell carcinoma (ccRCC) presents challenges in early diagnosis and effective treatment. In this study, we aimed to establish a prognostic model based on G2M checkpoint-related genes and identify associated clusters in ccRCC through clinical bioinformatic analysis and experimental validation. Utilizing a single-cell RNA dataset (GSE159115) and bulk-sequencing data from The Cancer Genome Atlas (TCGA) database, we analyzed the G2M checkpoint pathway in ccRCC. Differential expression analysis identified 45 genes associated with the G2M checkpoint, leading to the construction of a predictive model with four key genes (E2F2, GTSE1, RAD54L, and UBE2C). The model demonstrated reliable predictive ability for 1-, 3-, and 5-year overall survival, with AUC values of 0.794, 0.790, and 0.794, respectively. Patients in the high-risk group exhibited a worse prognosis, accompanied by significant differences in immune cell infiltration, immune function, TIDE and IPS scores, and drug sensitivities. Two clusters of ccRCC were identified using the "ConsensusClusterPlus" package, cluster 1 exhibited a worse survival rate and was resistant to chemotherapeutic drugs of Axitinib, Erlotinib, Pazopanib, Sunitinib, and Temsirolimus, but not Sorafenib. Targeted experiments on RAD54L, a gene involved in DNA repair processes, revealed its crucial role in inhibiting proliferation, invasion, and migration in 786-O cells. In conclusion, our study offers valuable insights into the molecular mechanisms underlying ccRCC, identifying potential prognostic genes and molecular subtypes associated with the G2M checkpoint. These findings hold promise for guiding personalized treatment strategies in the management of ccRCC.
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First-in-human single-cell and TCR atlas reveals peripheral immune remodeling before and after irreversible electroporation in prostate cancer.
BACKGROUND: Prostate cancer (PCa) is the second most common malignancy in men worldwide. Although radical prostatectomy effectively controls tumor progression, it often causes complications such as urinary incontinence and sexual dysfunction. Irreversible electroporation (IRE), a non-thermal ablation technique that preserves neurovascular structures, has emerged as a promising focal therapy and may induce systemic antitumor immunity through immunogenic cell death. However, the mechanisms and temporal dynamics of systemic immune responses to IRE in humans remain unclear. METHODS: This prospective study enrolled five patients with localized PCa (T2a-T2c). Peripheral blood samples were collected before and 7 days after IRE treatment. Single-cell RNA sequencing and T-cell receptor (TCR) repertoire profiling (10x Genomics) were performed to construct a high-resolution immune landscape. Integrated bioinformatic analyses-including Seurat/Harmony clustering, differential expression, functional enrichment, Gene Set Variation Analysis, transcription factor analysis, cell-cell communication (CellChat), and clonal tracking (Immunarch/scRepertoire)-were used to characterize systemic immune modulation following IRE. RESULTS: IRE induced bidirectional remodeling of the peripheral immune landscape. Myeloid cells, especially non-classical monocytes, increased in proportion and exhibited activation of inflammatory (interleukin-27), antiviral, complement, and antigen presentation pathways. T cells declined and exhibited reduced activation-associated and proliferation-associated transcriptional programs alongside enhanced survival-related signaling, consistent with a relative quiescent state of peripheral adaptive immunity at day 7. Natural killer cells showed elevated cytotoxic activity. TCR profiling revealed increased diversity and antigen-driven clonal expansion, while cell-cell communication shifted toward proinflammatory (TNF/SELPLG) and away from antigen-presenting (major histocompatibility complex (MHC)-I/CD40) interactions, indicating coordinated innate-adaptive rebalancing. CONCLUSION: This study is the first to map systemic immune dynamics after IRE in prostate cancer using single-cell analysis. 1 week after IRE, peripheral blood mononuclear cells show robust innate activation with concomitant attenuation of circulating T-cell activation/proliferation and reduced MHC-I/CD40-related communication, consistent with a time-dependent systemic immune rebalancing phase rather than sustained peak adaptive activation in blood. These findings support time-resolved immune monitoring and may help optimize the timing of IRE-based combination immunotherapy.
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Immune regulatory genes impact the hot/cold tumor microenvironment, affecting cancer treatment and patient outcomes.
BACKGROUND AND AIMS: Immunologically hot tumors, characterized by an inflamed tumor microenvironment (TME), contrast significantly with immunologically cold tumors. The identification of these tumor immune subtypes holds clinical significance, as hot tumors may exhibit improved prognoses and heightened responsiveness to checkpoint blockade therapy. Nevertheless, as yet there is no consensus regarding the clinically relevant definition of hot/cold tumors, and the influence of immune genes on the formation of hot/cold tumors remains poorly understood. METHODS: Data for 33 different types of cancer were obtained from The Cancer Genome Atlas database, and their immune composition was assessed using the CIBERSORT algorithm. Tumors were categorized as either hot or cold based on their distinct immune composition, ongoing immune response, and overall survival. A customized immunogram was created to identify important immunological characteristics. Kyoto Encyclopedia of Genes and Genomes and Hallmark pathway enrichment were evaluated through gene set variation analysis. Additionally, hub genes that regulate the tumor microenvironment were identified, and their expression patterns were analyzed using single-cell RNA sequencing. Furthermore, drug sensitivity and molecular docking analyses were performed to identify potential drug candidates capable of transforming cold tumors into hot tumors. For validation, a clinical cohort of patients diagnosed with pancreatic adenocarcinoma was examined using multiplex immunohistochemistry. RESULTS: We were able to differentiate between hot and cold tumors in various types of cancer (bladder urothelial carcinoma, pancreatic adenocarcinoma, and cervical squamous cell carcinoma) by analyzing the presence of CD8+ T cells, activated natural killer cells, and M2-type macrophages, as well as the cytolytic activity and T cell proliferation. Hub genes that regulate the TME, including PDCD1, CD276, and NT5E, were discovered. The increased expression of NT5E and its prognostic significance were confirmed through multiplex immunohistochemistry in pancreatic adenocarcinoma. Finally, dasatinib and tozasertib were identified as drug candidates capable of converting cold pancreatic adenocarcinoma tumors into hot tumors. CONCLUSION: In this study, we developed a framework for discerning clinically significant immune subtypes across various cancer types, further identifying several potential targets for converting cold tumors into hot tumors to enhance anticancer treatment efficacy.
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Proteome Landscape of Epithelial-to-Mesenchymal Transition (EMT) of Retinal Pigment Epithelium Shares Commonalities With Malignancy-Associated EMT.
Stress and injury to the retinal pigment epithelium (RPE) often lead to dedifferentiation and epithelial-to-mesenchymal transition (EMT). These processes have been implicated in several retinal diseases, including proliferative vitreoretinopathy, diabetic retinopathy, and age-related macular degeneration. Despite the importance of RPE-EMT and the large body of data characterizing malignancy-related EMT, comprehensive proteomic studies to define the protein changes and pathways underlying RPE-EMT have not been reported. This study sought to investigate the temporal protein expression changes that occur in a human-induced pluripotent stem cell-based RPE-EMT model. We utilized multiplexed isobaric tandem mass tag labeling followed by high-resolution tandem MS for precise and in-depth quantification of the RPE-EMT proteome. We have identified and quantified 7937 protein groups in our tandem mass tag-based MS analysis. We observed a total of 532 proteins that are differentially regulated during RPE-EMT. Furthermore, we integrated our proteomic data with prior transcriptomic (RNA-Seq) data to provide additional insights into RPE-EMT mechanisms. To validate these results, we have performed a label-free single-shot data-independent acquisition MS study. Our integrated analysis indicates both the commonality and uniqueness of RPE-EMT compared with malignancy-associated EMT. Our comparative analysis also revealed that multiple age-related macular degeneration-associated risk factors are differentially regulated during RPE-EMT. Together, our integrated dataset provides a comprehensive RPE-EMT atlas and resource for understanding the molecular signaling events and associated biological pathways that underlie RPE-EMT onset. This resource has already facilitated the identification of chemical modulators that could inhibit RPE-EMT, and it will hopefully aid in ongoing efforts to develop EMT inhibition as an approach for the treatment of retinal disease.
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Transcriptional analysis of cystic fibrosis airways at single-cell resolution reveals altered epithelial cell states and composition.
Cystic fibrosis (CF) is a lethal autosomal recessive disorder that afflicts more than 70,000 people. People with CF experience multi-organ dysfunction resulting from aberrant electrolyte transport across polarized epithelia due to mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. CF-related lung disease is by far the most important determinant of morbidity and mortality. Here we report results from a multi-institute consortium in which single-cell transcriptomics were applied to define disease-related changes by comparing the proximal airway of CF donors (n = 19) undergoing transplantation for end-stage lung disease with that of previously healthy lung donors (n = 19). Disease-dependent differences observed include an overabundance of epithelial cells transitioning to specialized ciliated and secretory cell subsets coupled with an unexpected decrease in cycling basal cells. Our study yields a molecular atlas of the proximal airway epithelium that will provide insights for the development of new targeted therapies for CF airway disease.