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Unveiling the role of RARs in stomach adenocarcinoma: clinical implications and prognostic biomarkers.
BACKGROUND: Retinoic acid receptors (RARs) family are known to play a significant role in the occurrence and development of tumors. However, the relationship between RARs and stomach adenocarcinoma (STAD) has not yet been clearly identified. The aim of this study is to evaluate the expression profile and clinical value of the RARs family in STAD. METHODS: The expression level, clinical characteristics, prognostic value, immunity-related evaluations, genetic alteration and methylation site of RARs in STAD were explored using a series of online databases including gene expression profiling interactive analysis (GEPIA), tumor immune estimation resource (TIMER), University of Alabama at Birmingham cancer data (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter, gene set cancer analysis (GSCA), cBioPortal, MethSurv, GeneMANIA, LinkedOmics, Metascape, Search tool for the retrieval of interacting genes (STRING), tumor immune single-cell hub (TISCH) and cancer cell line encyclopedia (CCLE). RESULTS: We discovered dramatically increased expression of RARA and decreased expression of RARB in STAD tissues, and many clinical variables were closely related to RARs. Notably, higher expressions of RARA and RARB as well as lower expression of RARG correlated with worse overall survival (OS) for STAD patients. The clinical value of prognostic model indicated that RARs were identified to be potential prognostic biomarkers for STAD patients. Moreover, RARB was closely related to immune cell infiltration, which had effect on the role of RARB in STAD prognosis. And the genetic alteration of RARB was significantly associated with the longer disease-free survival (DFS) of STAD patients. Additionally, some CpG sites of the RARs family were related with the prognosis of STAD patients. Functional enrichment analyses indicated that several pathways in STAD might be pivotal pathways regulated by RARs. At the single-cell level, there was some extent of infiltration of tumor microenvironment-related cells in the RARs expression in STAD. CONCLUSIONS: Our results evaluated the expression profile and clinical values of RARs in patients with STAD, which provided a basis for future in-depth exploration of the specific mechanisms of each member of RARs in STAD.
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Construction and validation of an EGFR-related risk signature identified SHC1 as a prognostic biomarker for lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) is a significant subtype of lung cancer, contributing to high mortality rates and posing substantial challenges to public health. This study aims to explore the significance of the epidermal growth factor receptor (EGFR)-related gene SHC1 in the progression and prognosis of LUAD. METHODS: Patient RNA sequencing (RNA-seq) and clinical data were acquired from The Cancer Genome Atlas (TCGA) database. Using the least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of EGFR signaling-related genes (ESRGs) for the prognostic prediction of LUAD. We investigated the relationship between SHC1 gene expression and immune cell infiltration by employing single-sample gene set enrichment analysis (ssGSEA). The potential functional role of the SHC1 gene was evaluated through GSEA. Additionally, the association between SHC1 expression and clinical data was investigated. Immunohistochemistry was utilized to assess SHC1 expression in 88 cases of invasive pulmonary adenocarcinoma. RESULTS: Univariate Cox regression analysis identified that increased expression of SHC1 correlated with poorer overall survival (OS). SHC1 exhibited significantly elevated expression levels in LUAD tissues. Moreover, elevated levels of SHC1 gene expression correlated strongly with advanced tumor (T), node (N), and metastasis (M) stages and were significantly associated with immune cell infiltration in LUAD. Furthermore, marked increases in SHC1 protein expression were observed in patients diagnosed with invasive pulmonary adenocarcinoma. CONCLUSIONS: These findings suggest that SHC1 plays a crucial oncogenic role in LUAD. Increased SHC1 expression in LUAD was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration.
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Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs.
BACKGROUND: The decline in organ function due to aging significantly impacts the health and quality of life of the elderly. Assessing and delaying aging has become a major societal concern. Previous studies have largely focused on differences between young and old individuals, often overlooking the complexity and gradual nature of aging. METHODS: In this study, we constructed a comprehensive multi-organ aging atlas in mice and systematically analyzed the aging trajectories of 16 organs to elucidate their functional specificity and identify organ-specific aging trend genes. Cross-organ association analysis was employed to identify global aging regulatory genes, leading to the development of a multi-organ aging assessment model, hereafter referred to as the 2A model. The model's validity was confirmed using single-cell RNA sequencing data from aging mouse lungs, cross-species gene expression profiles, and pharmacogenomic data. Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging. RESULTS: The 2A model effectively assessed aging states in both human and mouse tissues and demonstrated predictive capability for senescent cell clearance rates. Compared to the sc-ImmuAging and SCALE clocks, the 2A model exhibited superior predictive accuracy at the single-cell level. Organ-specific analyses identified the lungs and kidneys as particularly susceptible to aging, with immune dysfunction and programmed cell death emerging as key contributors. Notably, single-cell data confirmed that plasma cell accumulation and naive-like cell reduction showed linear changes during organ aging. Aging trend genes identified in each organ were significantly enriched in aging-related functional pathways, enabling precise assessment of the aging process and determination of organ-specific aging milestones. Additionally, drug screening identified Fostamatinib, Ranolazine, and Metformin as potential modulators of multi-organ aging, with mechanisms involving key pathways such as longevity regulation and circadian rhythm. CONCLUSIONS: The 2A model represents a significant advancement in aging assessment by integrating multi-dimensional validation strategies, enhancing its accuracy and applicability. The identification of organ-specific aging pathways and candidate pharmacological interventions provides a theoretical foundation and translational framework for precision anti-aging therapies.
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STEA: Histologically Validated and Reference-Independent Major Cell-Type Annotation for Spatial Transcriptomics Reveals Relevant Cellular Organization and Architecture of Tumor Microenvironment.
BACKGROUND: Recent advances in spatial transcriptomic technologies enable in situ gene expression profiling while preserving spatial context. This capability is particularly important for studying the tumor microenvironment (TME), where diverse and admixed cell populations interact within highly organized spatial niches that influence tumor progression and therapeutic response. However, the limited resolution of early spatial transcriptomic platforms results in each spatial spot capturing transcripts from multiple cell types, making accurate spot deconvolution or annotation a critical yet challenging step in downstream data analysis. The level of complexity will be particularly prominent in heterogeneous samples like the tumor microenvironments where multiple cell types are highly admixed and reliable single-cell reference atlases may usually be unavailable. METHODS: In this paper, we developed our method called STEA, which is a novel and accurate reference-independent enrichment-based annotation algorithm for major cell type. Unlike the existing approaches, STEA does not require single-cell RNA sequencing datasets as reference, offering both flexibility and computational efficiency in execution. RESULTS: We performed comprehensive benchmarking using a variety of simulated datasets across different platforms and scenarios and demonstrated the superior accuracy of STEA. Apart from synthetic data, we also evaluated multiple real datasets to further exemplify its practical applicability on both oncology-related and oncology-unrelated data. More importantly, we could confidently demonstrate the high concordance between prediction of STEA and histological classification by experienced pathologist. CONCLUSION: Our STEA algorithm provides a practical reference-independent framework to complement the cutting-edge spatial transcriptomics in genomics studies, facilitating accurate downstream high-dimensional spatial characterization of cellular and molecular landscapes, reconstruction of tissue architecture as well as cell-cell communication in malignant and non-malignant scenarios. Taken together, our comprehensive evaluation demonstrates the robustness and reliability of STEA, highlighting its potential as a valuable tool for studying complex tissue organization, particularly within heterogeneous TME.
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Unveiling a unique microglial phenotype promoting oxidation in the iBRB: insights from single-cell transcriptomics in the NPDR rat model.
BACKGROUND: Early diagnosis and targeted treatment of inner blood-retinal barrier (iBRB) impairment in non-proliferative diabetic retinopathy (NPDR) present significant challenges. This study investigates the cellular heterogeneity and early lesions in the iBRB microenvironment. METHODS: We created a single-cell transcriptional atlas of NPDR using retinas from Zucker Diabetic Fatty rats, focusing on the expression of cells within the iBRB microenvironment, particularly microglia. We performed cell-cell gene interaction analyses to investigate intercellular communications among different cell types in the iBRB. Additionally, we conducted differentiation potential and trajectory analysis, transcription factor regulatory network characterization, and enrichment analysis of microglia. We also employed transmission electron microscopy, immunofluorescence, and histological analysis to validate the hypothesis. RESULTS: Based on retinal samples from NPDR rats which had retinal edema and kidney damage, and normal rats, we selected 36,821 cells for subsequent analysis using single-cell sequencing. We identified 669 cells in iBRB and microglia had the highest connectivity value by enrichment analysis. 980 differentially expressed genes related to microglia divide it into 4 subtypes. Among them, Spp1 highly expressed microglia subtype 2 had the highest differentiation potential and was significantly upregulated after NPDR lesions. By integrating histological and biochemical analysis results, the roles of the subtype in the differentiation of microglia in the iBRB microenvironment, such as oxidative stress and apoptosis, were well validated. CONCLUSION: This study identified a novel microglia type in NPDR rats, offering valuable insight into targeted therapeutic strategies for NPDR patients and enhancing our understanding of microglial regulation within the iBRB.
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High Expression of CISD2 in Relation to Adverse Outcome and Abnormal Immune Cell Infiltration in Glioma.
Glioma is a serious disease burden globally, with high mortality and recurrence rates. CDGSH iron sulfur domain 2 (CISD2) is an evolutionarily conserved protein that is involved in several cancers. However, its role in the prognosis and immune infiltration in glioma remains unclear. In our research, RNA-seq matrix and clinicopathological relevant data for CISD2 were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Human Protein Atlas was used to verify the CISD2 protein level in glioma, and STRING was used to establish relative coexpression gene network. The Kaplan-Meier plotter was adopted to analyze the effect of CISD2 on prognosis. The connection between CISD2 expression and immune infiltration was analyzed using single-sample GSEA (ssGSEA), TIMER, and GEPIA. In contrast to normal tissues, CISD2 expression was significantly higher in glioma tissues, and CISD2 presented a certain diagnostic value in distinguishing glioma tissues from normal tissues. Furthermore, the CISD2 level was correlated with age, histologic grade, histological type, isocitrate dehydrogenase (IDH) status, 1p/19q codeletion status, and primary therapy outcome of glioma, while high CISD2 mRNA expression was correlated with grave overall survival. Multivariate analysis demonstrated that CISD2 was an independent risk factor for patients with glioma. Functional enrichment analysis indicated that CISD2 could regulate proliferation, immune reaction, and mitochondrial function. The results from the ssGSEA and TIMER databases confirmed that CISD2 acts a prominent role in immune cell infiltration in the tumor microenvironment, especially in low-grade glioma (LGG). Furthermore, CISD2 expression was observably correlated to M2 polarization in macrophages with glioma progression. This is the first research to investigate the immune role of CISD2 in glioma. CISD2 may be an innovative prognostic biomarker and can act as a potential target for future therapy for glioma.
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A PTN+ glioblastoma subclone orchestrates immune reprogramming to drive distant recurrence.
AIMS: Distant recurrence (DR) represents a distinct and lethal trajectory in glioblastoma (GBM), characterized by the colonization of spatially isolated neural niches. The mechanisms by which disseminated tumor cells remodel the microenvironment to overcome anatomical and immunological barriers remain poorly understood. This study aimed to decode the immune ecosystem of DR and elucidate the intercellular crosstalk driving this lethal dissemination. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on paired primary and DR tumor specimens from GBM patients, alongside an independent local recurrence (LR) control cohort, to map dynamic cellular shifts. Bioinformatic analyses, including differential abundance testing (Milo), cell-cell communication inference (CellChat), and copy number variation (CNV) analysis, were integrated with clinical co-immunoprecipitation (Co-IP) validation, bidirectional in vitro co-culture assays, and an orthotopic xenograft mouse model. RESULTS: Our high-resolution atlas revealed a profound remodeling of the microenvironment in DR lesions, characterized by a specific expansion of anti-inflammatory monocyte-derived tumor-associated macrophages (Anti_infl-TAM) and a paradoxical co-enrichment of CD8 + T cells and Tregs. Mechanistically, an OPC-like subpopulation of PTN+ tumor cells acted as a "paracrine architect," promoting Anti_infl-TAM polarization through the interaction between PTN and NCL. Co-IP assays confirmed direct physical binding of these two proteins in human DR tissues. Functional and bidirectional knockdown assays demonstrated that decoupling this cellular communication, achieved by targeting either PTN in tumor cells or NCL in macrophages, significantly attenuated glioma cell proliferation, migration, invasion, and macrophage polarization. In vivo, silencing PTN markedly reduced Anti_infl-TAM infiltration, suppressed intracranial tumor burden, and prolonged overall survival in tumor-bearing mice. CONCLUSION: This study establishes that DR GBM is defined by a reconfigured immune niche rather than mere genetic drift. The paracrine crosstalk between PTN+ tumor cells and Anti_infl-TAM serves as a critical engine of this permissive soil, offering a promising therapeutic target to disrupt the supportive microenvironment in distant recurrent GBM.
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Pan-cancer analysis of the prognostic and immunological role of RPL4.
Ribosomal proteins (RPs) play an important role in the overall stability, function, and integrity of ribosomes. Ribosomal protein L4 (RPL4), which is encoded by RPL4, is assumed to play different roles in different cancers due to the strong correlation between them. However, research based on the underlying mechanisms of this correlations is limited. Therefore, this study investigated the biological role of RPL4 in various cancers. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to compare the differential expression of RPL4 in tumor and normal tissues. The Sangerbox database and Kaplan-Meier method were employed to assess RPL4's impact on the prognosis of pan-cancer. Analyses using the cBioPortal tool, Shiny Methylation Analysis Resource Tool (SMART), and MethSurv provided insights into the methylation and epigenetic alterations of RPL4. Gene enrichment analysis revealed that RPL4 is involved in ribosome biogenesis through multiple pathways, and its enrichment in signaling pathways directly or indirectly influence tumor development. Tumor Immune Single-cell Hub (TISCH) was used to analyze RPL4 expression levels and cellular functions in the tumor microenvironment. Tumor Immune Estimation Resource Database 2.0 (TIMER2.0) and Tumor-Immune System Interactions Database (TISIDB) tools revealed that RPL4 affected the immune infiltration potential of tumors. Furthermore, the application of the ROC mapper and CellMiner databases indicated an association between RPL4 and sensitivity to multiple antitumor drugs. Additionally, RPL4 was found to remodel the tumor immune microenvironment, leading to the development of chemoresistance. In conclusion, the findings suggest that RPL4 can be used as a potential tumor biomarker and may serve as a target for immunotherapy in various cancers. Genetic testing of RPL4 provides a foundation for the diagnosis, prognosis, and treatment of clinical tumors.
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Prognostic value of FUBP1 in Colorectal cancer and association with immune microenvironment characteristics.
OBJECTIVE: To investigate FUBP1 expression, its prognostic value, impact on the tumor microenvironment (TME), and drug sensitivity in colorectal cancer (CRC), and to explore its potential underlying mechanisms. METHODS: Using data from The Cancer Genome Atlas (TCGA), we analyzed FUBP1 expression in CRC, evaluated its prognostic value via survival analysis and nomogram construction, performed pathway enrichment analysis, and assessed immune cell infiltration and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) scores. We further conducted immunohistochemistry (IHC) validation on an independent institutional cohort and analyzed the Gene Expression Omnibus (GEO) single-cell RNA sequencing dataset GSE132465 (n = 63,689 cells) to examine the association between FUBP1 expression and the tumor immune microenvironment at single-cell resolution. RESULTS: FUBP1 was highly expressed in CRC (P < 0.001), particularly in younger patients. High FUBP1 expression was associated with improved overall survival in univariate analysis (HR = 0.68, P = 0.028), yet this association was not maintained as an independent prognostic factor after adjustment for other clinical covariates (HR = 0.722, P = 0.098). Immunohistochemistry results from the independent cohort confirmed upregulated FUBP1 protein in 90% of CRC specimens. Single-cell analysis revealed that FUBP1-high cell clusters exhibited markedly reduced immune cell infiltration (35.97%vs 62.96%, P < 0.001), indicating an immunosuppressive "cold" tumor microenvironment. Tumors with high FUBP1 expression also displayed elevated PD-L1, PD-1, and CTLA4 expression, lower half-maximal inhibitory concentration (IC50) values for oxaliplatin, irinotecan, and 5-fluorouracil, and higher Immune Phenotype Score (IPS) for anti-PD-1 monotherapy or combined anti-CTLA-4 immunotherapy. FUBP1 expression was correlated with increased expression of MYC, TP53, and their downstream target genes (CCND1, CDK4, BAX, CDKN1A). CONCLUSION: FUBP1 is highly expressed in CRC and associated with an immunosuppressive "cold" tumor microenvironment characterized by decreased immune cell infiltration, while it correlates with favorable chemotherapeutic sensitivity. FUBP1 may serve as a potential predictive biomarker for responses to chemotherapy and immunotherapy, rather than an independent prognostic indicator for survival. Its linkage to MYC and TP53 signaling pathways warrants further mechanistic investigation.
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Development and verification of a manganese metabolism- and immune-related genes signature for prediction of prognosis and immune landscape in gastric cancer.
BACKGROUND: Gastric cancer (GC) poses a global health challenge due to its widespread prevalence and unfavorable prognosis. Although immunotherapy has shown promise in clinical settings, its efficacy remains limited to a minority of GC patients. Manganese, recognized for its role in the body's anti-tumor immune response, has the potential to enhance the effectiveness of tumor treatment when combined with immune checkpoint inhibitors. METHODS: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases was utilized to obtain transcriptome information and clinical data for GC. Unsupervised clustering was employed to stratify samples into distinct subtypes. Manganese metabolism- and immune-related genes (MIRGs) were identified in GC by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analysis. We conducted gene set variation analysis, and assessed the immune landscape, drug sensitivity, immunotherapy efficacy, and somatic mutations. The underlying role of NPR3 in GC was further analyzed in the single-cell RNA sequencing data and cellular experiments. RESULTS: GC patients were classified into four subtypes characterized by significantly different prognoses and tumor microenvironments. Thirteen genes were identified and established as MIRGs, demonstrating exceptional predictive effectiveness in GC patients. Distinct enrichment patterns of molecular functions and pathways were observed among various risk subgroups. Immune infiltration analysis revealed a significantly greater abundance of macrophages and monocytes in the high-risk group. Drug sensitivity analysis identified effective drugs for patients, while patients in the low-risk group could potentially benefit from immunotherapy. NPR3 expression was significantly downregulated in GC tissues. Single-cell RNA sequencing analysis indicated that the expression of NPR3 was distributed in endothelial cells. Cellular experiments demonstrated that NPR3 facilitated the proliferation of GC cells. CONCLUSION: This is the first study to utilize manganese metabolism- and immune-related genes to identify the prognostic MIRGs for GC. The MIRGs not only reliably predicted the clinical outcome of GC patients but also hold the potential to guide future immunotherapy interventions for these patients.