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Development and evaluation of a disulfidoptosis-related lncRNA index for prognostication in clear cell renal cell carcinoma.
BACKGROUND: This study introduces a novel prognostic tool, the Disulfidoptosis-Related lncRNA Index (DRLI), integrating the molecular signatures of disulfidoptosis and long non-coding RNAs (lncRNAs) with the cellular heterogeneity of the tumor microenvironment, to predict clinical outcomes in patients with clear cell renal cell carcinoma (ccRCC). METHODS: We analyzed 530 tumor and 72 normal samples from The Cancer Genome Atlas (TCGA), employing k-means clustering based on disulfidoptosis-associated gene expression to stratify ccRCC samples into prognostic groups. lncRNAs correlated with disulfidoptosis were identified and used to construct the DRLI, which was validated by Kaplan-Meier and receiver operating characteristic curves. We utilized single-cell deconvolution analysis to estimate the proportion of immune cell types within the tumor microenvironment, while the ESTIMATE and TIDE algorithms were employed to assess immune infiltration and potential response to immunotherapy. RESULTS: The Disulfidoptosis-Related lncRNA Index (DRLI) effectively stratified ccRCC patients into high and low-risk groups, significantly impacting survival outcomes (P < 0.001). High-risk patients, marked by a unique lncRNA profile associated with disulfidoptosis, faced worse prognoses. Single-cell analysis revealed marked tumor microenvironment heterogeneity, especially in immune cell makeup, correlating with patient risk levels. In prognostic predictions, DRLI outperformed traditional clinical indicators, achieving AUC values of 0.779, 0.757, and 0.779 for 1-year, 3-year, and 5-year survival in the training set, and 0.746, 0.734, and 0.750 in the validation set. Notably, while the constructed nomogram showed exceptional predictive capability for short-term prognosis (AUC = 0.877), the DRLI displayed remarkable long-term predictive accuracy, with its AUC value reaching 0.823 for 10-year survival, closely approaching the nomogram's performance. CONCLUSIONS: The study introduces the DRLI as a groundbreaking molecular stratification tool for ccRCC, enhancing prognostic precision and potentially guiding personalized treatment strategies. This advancement is particularly significant in the context of long-term survival predictions. Our findings also elucidate the complex interplay between disulfidoptosis, lncRNAs, and the immune microenvironment in ccRCC, offering a comprehensive perspective on its pathogenesis and progression. The DRLI and the nomogram together represent significant strides in ccRCC research, highlighting the importance of molecular-based assessments in predicting patient outcomes.
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Exploring the pathogenesis, biomarkers, and potential drugs for type 2 diabetes mellitus and acute pancreatitis through a comprehensive bioinformatic analysis.
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that accounts for > 90% of all diabetes cases. Acute pancreatitis (AP) can be triggered by various factors and is a potentially life-threatening condition. Although T2DM has been shown to have a close relationship with AP, the common mechanisms underlying the two conditions remain unclear. METHODS: We identified common differentially expressed genes (DEGs) in T2DM and AP and used functional enrichment analysis and Mendelian randomization to understand the underlying mechanisms. Subsequently, we used several machine learning algorithms to identify candidate biomarkers and construct a diagnostic nomogram for T2DM and AP. The diagnostic performance of the model was evaluated using ROC, calibration, and DCA curves. Furthermore, we investigated the potential roles of core genes in T2DM and AP using GSEA, xCell, and single-cell atlas and by constructing a ceRNA network. Finally, we identified potential small-molecule compounds with therapeutic effects on T2DM and AP using the CMap database and molecular docking. RESULTS: A total of 26 DEGs, with 14 upregulated and 12 downregulated genes, were common between T2DM and AP. According to functional and DisGeNET enrichment analysis, these DEGs were mainly enriched in immune effector processes, blood vessel development, dyslipidemia, and hyperlipidemia. Mendelian randomization analyses further suggested that lipids may be a potential link between AP and T2DM. Machine learning algorithms revealed ARHGEF9 and SLPI as common genes associated with the two diseases. ROC, calibration, and DCA curves showed that the two-gene model had good diagnostic efficacy. Additionally, the two genes were found to be closely associated with immune cell infiltration. Finally, imatinib was identified as a potential compound for the treatment of T2DM and AP. CONCLUSION: This study suggests that abnormal lipid metabolism is a potential crosstalk mechanism between T2DM and AP. In addition, we established a two-gene model for the clinical diagnosis of T2DM and AP and identified imatinib as a potential therapeutic agent for both diseases.
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Ferroptosis-associated gene CISD2 suppresses colon cancer development by regulating tumor immune microenvironment.
BACKGROUND: Despite the association of ferroptosis with various tumors, the specific mechanism by which it influences colon adenocarcinoma (COAD) microenvironmental equilibrium remains elusive. This study aims to elucidate how ferroptosis affects COAD microenvironmental homeostasis and its potential impact on COAD research. OBJECTIVE: By employing genetic screening and single-cell analysis of tumor data, we investigated the role of ferroptosis genes in COAD microenvironmental homeostasis. The genes were correlated with immune cell infiltration in tissue samples and patient outcomes. METHODS: Ferroptosis-associated genes were initially identified through the FerrDb database. Utilizing the tidyverse and Seurat packages, genes with substantial expression differences were extracted, and clustering analysis was performed on the single-cell data. A Venn diagram depicted shared differential genes for ferroptosis and tumors. To screen key ferroptosis genes, further enrichment analysis and immune cell infiltration analysis were conducted. Lastly, human COAD cell lines were employed to overexpress CDGSH iron sulfur domain 2 (CISD2) through cellular assays to validate its function in COAD. RESULTS: Following screening of The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, 414 COAD patient samples and 341 normal samples were included. Through the FerrDb database, 259 ferroptosis genes were identified. Clustering the single-cell data revealed 911 tumor marker genes, of which 18 were ferroptosis genes. Analysis of variance (ANOVA) and univariate regression analysis determined that only CISD2 was statistically significantly associated with clinical outcomes. Additionally, CISD2 was found to positively correlate with activated memory T cells and negatively correlate with regulatory T cells (Tregs) and plasma cells in COAD, as well as being significantly associated with several immune-related and cancer-related pathways. CISD2 expression was elevated in most tumors, likely due to cell cycle regulation and immune system activation. Moreover, CISD2 upregulation inhibited COAD cell proliferation and enhanced 5-fluorouracil (5-FU) sensitivity. Our findings indicate, for the first time, that CISD2 governs the cell cycle and stimulates the immune system to impede COAD progression. CONCLUSION: By modulating the cell cycle and mediating immune infiltration, CISD2 may inhibit COAD development by influencing tumor immune microenvironment equilibrium, providing valuable insights into the relevance and potential impact of the research results on the COAD research field.
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Integrating Transcriptomic Data with Mechanistic Systems Pharmacology Models for Virtual Drug Combination Trials.
Monotherapy clinical trials with mutation-targeted kinase inhibitors, despite some success in other cancers, have yet to impact glioblastoma (GBM). Besides insufficient blood-brain barrier penetration, combinations are key to overcoming obstacles such as intratumoral heterogeneity, adaptive resistance, and the epistatic nature of tumor genomics that cause mutation-targeted therapies to fail. With now hundreds of potential drugs, exploring the combination space clinically and preclinically is daunting. We are building a simulation-based approach that integrates patient-specific data with a mechanistic computational model of pan-cancer driver pathways (receptor tyrosine kinases, RAS/RAF/ERK, PI3K/AKT/mTOR, cell cycle, apoptosis, and DNA damage) to prioritize drug combinations by their simulated effects on tumor cell proliferation and death. Here we illustrate a first step, tailoring the model to 14 GBM patients from The Cancer Genome Atlas defined by an mRNA-seq transcriptome, and then simulating responses to three promiscuous FDA-approved kinase inhibitors (bosutinib, ibrutinib, and cabozantinib) with evidence for blood-brain barrier penetration. The model captures binding of the drug to primary targets and off-targets based on published affinity data and simulates responses of 100 heterogeneous tumor cells within a patient. Single drugs are marginally effective or even counterproductive. Common copy number alterations (PTEN loss, EGFR amplification, and NF1 loss) have a negligible correlation with single-drug or combination efficacy, reinforcing the importance of postgenetic approaches that account for kinase inhibitor promiscuity to match drugs to patients. Drug combinations tend to be either cytostatic or cytotoxic, but seldom both, highlighting the need for considering targeted and nontargeted therapy. Although we focus on GBM, the approach is generally applicable.
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Multi-omics characterization of the unsaturated fatty acid biosynthesis pathway in colon cancer.
The biosynthesis of unsaturated fatty acids is involved in the initiation and progression of colon adenocarcinoma (COAD). In this study, we aimed to investigate the multi-omics characteristics of unsaturated fatty acid biosynthesis-related genes and explore their prognostic value in colon cancer by analyzing the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. An unsaturated fatty acid biosynthesis pathway related-genes enrichment score (BUFAS) was constructed utilizing the single sample gene set enrichment analysis (ssGSEA). We discovered that a high BUFAS was associated with longer overall survival (OS) in both the training and the validation sets. Multivariable analysis including the clinical characteristics further verified the independent prognostic value of the BUFAS in both the TCGA-COAD and the GSE39582 datasets. In addition, GSEA analysis revealed that BUFAS was positively associated with several signaling pathways, including MTORC1, peroxisome, and pathways related to fatty acid metabolism, while was negatively associated with other signaling pathways, such as hedgehog, NOTCH, and Wnt/beta-catenin pathway. Furthermore, in the COAD cell lines of the Genomics of Drug Sensitivity in Cancer (GDSC) database, we found that BUFAS was positively correlated with the drug sensitivities of cisplatin, gemcitabine, camptothecin, lapatinib, and afatinib, while was negatively correlated with that of ponatinib. Moreover, in the COAD single-cell transcriptomic dataset (GSE146771), the BUFAS varied among different cell types and was enriched in mast cells and fibroblasts. Taken together, the BUFAS we constructed could be used as an independent prognostic signature in predicting the OS and drug resistance of colon cancer. Unsaturated fatty acid biosynthesis pathway might serve as potential therapeutic targets for cancer treatment.
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Characterization of the treatment-naive immune microenvironment in melanoma with BRAF mutation.
BACKGROUND: Patients with BRAF-mutant and wild-type melanoma have different response rates to immune checkpoint blockade therapy. However, the reasons for this remain unknown. To address this issue, we investigated the precise immune composition resulting from BRAF mutation in treatment-naive melanoma to determine whether this may be a driver for different response to immunotherapy. METHODS: In this study, we characterized the treatment-naive immune context in patients with BRAF-mutant and BRAF wild-type (BRAF-wt) melanoma using data from single-cell RNA sequencing, bulk RNA sequencing, flow cytometry and immunohistochemistry (IHC). RESULTS: In single-cell data, BRAF-mutant melanoma displayed a significantly reduced infiltration of CD8+ T cells and macrophages but also increased B cells, natural killer (NK) cells and NKT cells. We then validated this finding using bulk RNA-seq data from the skin cutaneous melanoma cohort in The Cancer Genome Atlas and deconvoluted the data using seven different algorithms. Interestingly, BRAF-mutant tumors had more CD4+ T cells than BRAF-wt samples in both primary and metastatic cohorts. In the metastatic cohort, BRAF-mutant melanoma demonstrated more B cells but less CD8+ T cell infiltration when compared with BRAF-wt samples. In addition, we further investigated the immune cell infiltrate using flow cytometry and multiplex IHC techniques. We confirmed that BRAF-mutant melanoma metastases were enriched for CD4+ T cells and B cells and had a co-existing decrease in CD8+ T cells. Furthermore, we then identified B cells were associated with a trend for improved survival (p=0.078) in the BRAF-mutant samples and Th2 cells were associated with prolonged survival in the BRAF-wt samples. CONCLUSIONS: In conclusion, treatment-naive BRAF-mutant melanoma has a distinct immune context compared with BRAF-wt melanoma, with significantly decreased CD8+ T cells and increased B cells and CD4+ T cells in the tumor microenvironment. These findings indicate that further mechanistic studies are warranted to reveal how this difference in immune context leads to improved outcome to combination immune checkpoint blockade in BRAF-mutant melanoma.
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Spatiotemporal cellular map of the developing human reproductive tract.
The human reproductive tract is essential for species perpetuation and overall health. Its development involves complex processes of sex specification, tissue patterning and morphogenesis, the disruption of which can cause lifelong issues, including infertility1-5. Here we present an extensive single-cell and spatial multi-omic atlas of the human reproductive tract during prenatal development to provide insights beyond those that are possible with smaller-scale, organ-focused studies. We describe potential regulators of sexual dimorphism in reproductive organs and pinpoint previously unknown genes involved in Müllerian duct emergence and regression and urethral canalization of the penis. By combining histological features with gene expression and chromatin accessibility data, we define transcription factors and signalling events potentially involved in the regionalization of the Müllerian and Wolffian ducts. We also refine how the HOX code is established in distinct reproductive organs and reveal that the expression of thoracic HOX genes is increased in the rostral mesenchyme of the fallopian tube and epididymis. Our findings further indicate that epithelial regionalization of the fallopian tube and epididymis, which probably contribute to sperm maturation and capacitation, is established during development. By contrast, later events are necessary for regionalization of the uterocervical canal epithelium. Finally, on the basis of single-cell data and fetal-derived organoids, we show that the fetal uterine epithelium is vulnerable to oestrogen-mimicking endocrine disruptors. By mapping sex-specific reproductive tract regionalization and differentiation at the cellular level, our study provides valuable insights into causes and potential treatments of developmental reproductive disorders.
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Role of CALCR expression in liver cancer: Implications for the immunotherapy response.
Liver hepatocellular carcinoma (LIHC) is a prevalent and lethal malignancy with a complex molecular landscape. Fibrosis and ferroptosis are implicated in LIHC progression, yet their roles remain to be elucidated. The present study investigated the expression and prognostic significance of calcitonin receptor (CALCR), a gene that intersects the pathways of fibrosis and ferroptosis, across LIHC and other types of cancer. Data were obtained from The Cancer Genome Atlas and the Molecular Signatures Database. LIHC patients were classified into two clusters based on fibrosis‑related gene expression using ConsensusClusterPlus. Single‑sample gene set enrichment analysis was employed to quantify fibrosis and ferroptosis levels. Correlation, survival and nomogram analyses were performed to assess the prognostic value of CALCR. Additionally, single‑cell RNA sequencing data from the Tumor Immune Single Cell Hub 2 (TISCH2) and pan‑cancer analyses of genomic heterogeneity features were incorporated. The present study also identified a putative regulatory role for CALCR in LIHC cell migration, proliferation and apoptosis. CALCR was identified as a significant prognostic marker for LIHC. Patients with high CALCR expression exhibited shortened overall survival (OS) and disease‑specific survival (DSS). Specifically, the hazard ratios (HRs) for OS and DSS were 1.76 [95% confidence interval (CI): 1.23=2.49) and 1.77 (95% CI: 1.13=2.78], respectively, with corresponding P‑values of 0.002 for OS and 0.013 for DSS. Analyses of immune cell infiltration revealed a more complex immune environment in patients with low CALCR expression, suggesting differential responses to immunotherapy. Furthermore, in HepG‑2 and HuH‑7 cells, small interfering (si)‑CALCR increased apoptosis while reducing proliferation and migration compared with si‑negative control. CALCR serves as a significant prognostic biomarker for LIHC, influencing both molecular pathways and the immune landscape. Its expression is associated with improved survival outcomes and distinct genomic features, positioning it as a potential therapeutic target and predictor of immunotherapy efficacy.
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Comprehensive big data analysis reveals SLC10A3 as a potential biomarker in head and neck cancer.
Head and neck cancer (HNC) continues to pose a significant global health challenge, highlighting the urgent need for discovering new therapeutic targets. Recent studies highlight the role of solute carrier (SLC) proteins in cancer progression. This study investigates the expression and potential role of SLC10A3 in HNC, aiming to determine its clinical significance and therapeutic relevance. Publicly available datasets, including The Cancer Genome Atlas (TCGA), Clinical Proteomics Tumor Analysis Consortium (CPTAC), and Gene Expression Omnibus (GEO), were analyzed to assess SLC10A3 expression in head and neck squamous cell carcinoma (HNSCC). The prognostic relevance of SLC10A3 was assessed using Kaplan-Meier (KM) survival and Receiver Operating Characteristic (ROC) curve analysis. Correlation analysis within TCGA, CPTAC, and GEO datasets identified genes associated with SLC10A3 expression. Protein-protein docking studies were performed to predict potential interactions between SLC10A3 and identified protein coding genes. SLC10A3 was found to be significantly upregulated in HNSCC tumor samples compared to normal tissues across TCGA and CPTAC datasets. Increased SLC10A3 expression correlated with poor survival outcomes in TCGA-HNSCC patients. Correlation analysis identified 26 genes positively associated with SLC10A3, where BCAP31, IRAK1, and UBL4A showed consistent correlation across TCGA, CPTAC, and GEO datasets. Computational protein interaction modeling using docking and AI/ML-based Evolutionary Scale Modelling (ESM) framework revealed significant binding affinities between SLC10A3 and identified protein-coding genes, suggesting potential functional interactions. These findings establish SLC10A3 as a promising therapeutic target in HNC. Its consistent upregulation, association with poor prognosis, and potential interactions with key regulatory proteins highlight its relevance for future therapeutic strategies.
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CD38+ Endothelial Remodeling Defines Spatially Diverse Vasculopathy Programs in Rapidly Advancing Oral Inflammation.
Oral inflammatory diseases affect nearly half of the global population. Among them, newly defined peri-implantitis and high-grade periodontitis represent rapidly advancing inflammatory disease types, marked by relatively rapid tissue destruction. Despite their prevalence, the cell mechanisms and spatial architecture driving this severity remain poorly understood. Focusing first on peri-implantitis versus low- and moderate-grade periodontitis, we applied microbial profiling, single-cell RNA sequencing (scRNA-seq), and spatial proteomics (sp-proteomics) to uncover shared pathogenic programs linked to accelerated niche breakdown. Furthermore, to preserve spatial fidelity, each tissue was anatomically orientated along the tooth- or implant-epithelial interface, analogous sites of disease origination. Laser capture microdissection followed by microbiome analysis of unique tissue compartments revealed reduced bacterial load and diversity in peri-implantitis stroma. We then expanded our version-1 Human Periodontal Atlas by integrating newly generated peri-implantitis scRNAseq data (36-total samples; 121395-cells), revealing widespread transcriptional alterations, including oxidative stress, hypoxic, and NAD+ metabolism-associated signatures, primarily in a subpopulation of TNFRSF6B +/ICAM1 + post-capillary venules. We then performed high-resolution sp-proteomics (15-total samples; 337260-cells) and analyzed VEC states and associated neighborhoods via AstroSuite using newly developed tri-wise spatial analysis. This revealed CD34+-VEC loss and CD38+-VEC expansion almost exclusively in peri-implantitis. We extended this analysis to high-grade periodontitis. Mucosal biopsies from four lesion-affected and four unaffected sites within the same individuals (1:1 matched; 8-samples; 225137-cells) again demonstrated spatially restricted CD38+-VEC remodeling exclusively in affected tissues, with similar vasculopathy front patterning. The findings nominate spatially distinct vasculopathy patterning as a hallmark of rapidly advancing oral inflammation and a targetable therapeutic axis.