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A New Ferroptosis-Related lncRNA Signature Predicts the Prognosis of Bladder Cancer Patients.
Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients. Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed. Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel. Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.
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The Expression of the LDLR, LDLRAP1, and PCSK9 Genes has Prognostic Significance in Triple-negative Breast Cancer.
AIMS: The purpose of this study was to investigate the prognostic significance of cholesterol uptake genes in predicting the survival of breast cancer patients. BACKGROUND: Cholesterol plays a crucial role in the homeostasis of tumor cells. It is known that cholesterol levels can influence important parameters of the disease, such as sensitivity to therapy, progression, and metastasis of cancer. Previous studies suggest that breast cancer subtypes exhibit differences in metabolism. OBJECTIVE: The objectives of this study were to determine whether cholesterol uptake genes have prognostic significance for overall survival in breast cancer patients, evaluate if this prognostic significance varies between breast cancer subtypes, and identify differences in the expression of cholesterol uptake genes among these subtypes. METHODS: Data from mRNA sequencing of tumors from the Cancer Genome Atlas (TCGA) portal were analyzed. Tumors were classified into molecular subtypes, and the prognostic significance of cholesterol uptake gene expression levels was evaluated for each subtype. DESeq2 and Fisher's test were used to assess differences in gene expression. RESULTS: High expression levels of genes involved in de novo cholesterol synthesis were associated with poor prognosis for the Basal-like and Luminal A breast cancer subtypes. The prognostic significance of low-density lipoprotein receptor (LDLR), LDLR adapter protein 1 (LDLRAP1), and proprotein convertase subtilisin/kexin type 9 (PCSK9), which are responsible for exogenous cholesterol uptake, varied across subtypes. Specifically, low expression of LDLR was associated with a favorable prognosis for the luminal A (OR = 2.17; FDR = 0.0048) and luminal B (OR = 2.21; FDR = 0.015) subtypes but indicated poor prognosis in the basal-like subtype (OR = 0.48; FDR = 0.05). No genes were significant for prognosis prediction in the HER2-positive subtype. The HER2+ subtype exhibited higher expression of cholesterol uptake genes compared to the basal-like subtype based on the analysis of tumor mRNA sequencing (OR = 6.45, p-value = 3.07E-05). This finding was also confirmed through the study of publicly available single-cell sequencing data (OR = 40.3, p-value = 2.19e-07), which may contribute to the differences in their prognostic significance. CONCLUSION: The prognostic significance of cholesterol uptake gene expression varies among breast cancer subtypes. Precise fitting of biomarkers into breast cancer subtypes may aid in more accurate patient stratification and improve treatment approaches.
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Single-cell eQTL Mapping Reveals Cell Subtype-specific Genetic Control and Mechanism in Malignant Transformation of Colorectal Cancer.
UNLABELLED: Colorectal cancer is a heterogeneous disease that develops through a stepwise accumulation, yet the underlying mechanisms at single-cell resolution remain unclear. In this study, we profiled 751,531 single-cell transcriptomes, spatial transcriptomics, and snMultiomes from 142 multistage samples, revealing the cellular and molecular alterations and dynamic intercellular cross-talk during colorectal cancer development. Additionally, we created a colorectal cancer single-cell expression quantitative trait locus (sc-eQTL) map identifying 16,833 significant pairs across 28 cell subtypes, with more than 76% of sc-eQTLs being cell type-specific and fewer than 15% detectable in bulk datasets. A polygenic risk score derived from sc-eQTLs substantially improved colorectal cancer risk prediction. We prioritized rs4794979 that is associated with an increased colorectal cancer risk (OR = 1.11, P = 2.04 × 10-12) by promoting LGALS9 expression mediated by ELK1. Elevated LGALS9 in epithelia interacts with SLC1A5 on fibroblasts, promoting transformation into cancer-associated fibroblasts and simultaneously inducing CD8+ T-cell exhaustion via the LGALS9-TIM3 axis, thereby facilitating colorectal cancer development. Blocking the LGALS9-TIM3 axis enhanced anti-PD-1 therapy to inhibit colorectal cancer progression. SIGNIFICANCE: Our study provides a valuable resource, including a dynamic single-cell landscape and a robust colorectal cancer sc-eQTL atlas, and elucidates the cell type-specific regulation and important cross-talk mechanisms between cell types in the tumor microenvironment, offering deep insights into colorectal cancer tumorigenesis and targeted therapies.
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Identification and characterization of aging/senescence-induced genes in osteosarcoma and predicting clinical prognosis.
BACKGROUND: Aging is an influential risk factor for progression of both degenerative and oncological diseases of the bone. Osteosarcoma, considered the most common primary mesenchymal tumor of the bone, is a worldwide disease with poor 5-year survival. This study investigated the role of aging-/senescence-induced genes (ASIGs) in contributing to osteosarcoma diagnosis, prognosis, and therapeutic agent prediction. METHODS: Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used to collect relevant gene expression and clinical data of osteosarcoma and paracancerous tissues. Patients were clustered by consensus using prognosis-related ASIGs. ssGSEA, ESTIMATE, and TIMER were used to determine the tumor immune microenvironment (TIME) of subgroups. Functional analysis of differentially expressed genes between subgroups, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVAs), was performed to clarify functional status. Prognostic risk models were constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. SCISSOR was used to identify relevant cells in osteosarcoma single-cell data for different risk groups. The effect of immunotherapy was predicted based on TIDE scores and chemotherapy drug sensitivity using CTRP and PRISM. RESULTS: Three molecular subgroups were identified based on prognostic differentially expressed ASIGs. Immunological infiltration levels of the three groups differed significantly. Based on GO and KEGG analyses, differentially expressed genes between the three subgroups mainly relate to immune and aging regulation pathways; GSVA showed substantial variations in multiple Hallmark pathways among the subgroups. The ASIG risk score built based on differentially expressed genes can predict patient survival and immune status. We also developed a nomogram graph to accurately predict prognosis in combination with clinical characteristics. The correlation between the immune activation profile of patients and the risk score is discussed. Through single-cell analysis of the tumor microenvironment, we identified distinct risk-group-associated cells with significant differences in immune signaling pathways. Immunotherapeutic efficacy and chemotherapeutic agent screening were evaluated based on risk score. CONCLUSION: Aging-related prognostic genes can distinguish osteosarcoma molecular subgroups. Our novel aging-associated gene signature risk score can be used to predict the osteosarcoma immune landscape and prognosis. Moreover, the risk score correlates with the TIME and provides a reference for immunotherapy and chemotherapy in terms of osteosarcoma.
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The mechanism of fibronectin 1 promoting papillary thyroid cancer progression by regulating anoikis resistance.
Background: Papillary thyroid cancer is a common head and neck malignancy with a globally rising incidence. While most patients attain favorable prognosis following standard treatment, a subset develops recurrence and metastasis—two key factors that compromise clinical outcomes. Anoikis resistance is a prerequisite for tumor metastasis; however, the role and mechanism of Fibronectin 1 (FN1)—a molecule overexpressed in multiple cancers and linked to tumor progression—in papillary thyroid cancer anoikis resistance remain undefined. Objective: This study therefore investigated the function and regulatory mechanism of FN1 in papillary thyroid cancer anoikis resistance using a combination of bioinformatics analyses and experimental validation. Methods: First, using The Cancer Genome Atlas (TCGA) dataset and anoikis-related genes from GeneCards, we identified FN1 as an anoikis-related hub gene in thyroid cancer through bioinformatics analyses, including consensus clustering, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network analysis. Its clinical relevance was further analyzed from the perspectives of pathological typing, survival prognosis, immune cell infiltration (via xCell) and single-cell expression patterns. Next, we performed validation using papillary thyroid cancer tissues, adjacent normal tissues, and cell lines (8305c, BCPAP, Nthy-ori 3 − 1): FN1 expression and cancer cell anoikis were detected by immunohistochemistry (IHC) and TUNEL staining; FN1 mRNA and protein levels were quantified via qRT-PCR and Western blot. Finally, we modulated FN1 expression through RNA interference (for knockdown). Cell proliferation, migration, and invasion were assessed using CCK-8 and Transwell assays, while Western blot was applied to measure the expression of apoptosis-related proteins. Results: FN1 is highly expressed in papillary thyroid cancer tissues and cell lines and is associated with poor tumor prognosis. Silencing FN1 can inhibit the proliferation, migration and invasion of papillary thyroid cancer cells and increase the anoikis rate. Overexpression of FN1 showed the opposite effect. Mechanistically, FN1 can up-regulate anti-apoptotic proteins BCL2L1 and Caspase-3, and down-regulate pro-apoptotic protein BAD, thereby enhancing anoikis resistance. Conclusions: FN1 is highly expressed in papillary thyroid cancer and correlates with poor prognosis. Mechanistically, FN1 enhances papillary thyroid cancer cell tumorigenic potential by regulating proliferation, migration, invasion and apoptotic progression via the BCL2L1/BAD axis, thus driving tumor development. FN1 may act as a promising therapeutic target for advanced papillary thyroid cancer.
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Integrative Analysis of Glycine, Serine, and Threonine Metabolism and the Immune Microenvironment in Endometrial Cancer: A Prognostic Model and Metabolic-Immune Framework for Precision Oncology.
BACKGROUND: Metabolic reprogramming is a hallmark of the pathogenesis and progression of endometrial carcinoma (EC). This study comprehensively analyzed the expression profiles of glycine, serine, and threonine (Gly/Ser/Thr) metabolism-related genes in EC. We also established a robust prognostic model and developed a molecular subtyping framework that integrates metabolic and immune characteristics based on the identified prognostic genes. The aims of this work are to enhance diagnostic precision and improve clinical management strategies for patients with EC. METHODS: Untargeted metabolomic analysis was performed on 35 EC and 15 normal tissues. The Cancer Genome Atlas (TCGA) transcriptomic data were integrated with weighted gene co-expression network analysis (WGCNA) to identify EC-related metabolic genes and construct a prognostic model using Cox proportional hazards and least absolute shrinkage and selection operator (LASSO) regression analyses. The model was validated using an independent proteomic and single-cell dataset from our institution. Consensus clustering classified patients into three molecular subtypes, which were further characterized by gene set variation analysis (GSVA) and profiling of immune infiltration. Finally, key prognostic genes were validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in EC and normal endometrial epithelial cells. RESULTS: Metabolomic analysis revealed significant enrichment of the Gly/Ser/Thr metabolic pathways. WGCNA identified a tumor-associated metabolic module among 1741 pathway-related genes. A prognostic model comprising methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), ribosomal protein S6 kinase A1 (RPS6KA1), and cyclin-dependent kinase inhibitor 2A (CDKN2A) was subsequently established. Consensus clustering based on risk scores stratified EC patients into three molecular subtypes: immunometabolic-suppressed (C1), proliferative-immunobalanced (C2), and immune-activated (C3). The C1 subtype had the poorest prognosis and was characterized by metabolic suppression and immune evasion. The C2 subtype showed a favorable prognosis and was defined by a "proliferation-immune balance" in which high proliferative activity coexisted with strong anti-tumor immunity. The C3 subtype was also associated with a favorable outcome, driven by upregulated DNA repair and oxidative phosphorylation pathways alongside infiltration of immune-active cells. RT-qPCR confirmed significant differences in the mRNA expression of MTHFD2, RPS6KA1, and CDKN2A between normal and EC cells (p < 0.05). CONCLUSION: This study developed a Gly/Ser/Thr pathway-based prognostic model for EC, based on the expression of MTHFD2, RPS6KA1, and CDKN2A as novel biomarkers. The resulting patient stratification framework holds significant clinical potential for guiding precise and personalized management of EC.
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Notch1 supports proliferation and bioenergetic activity in a pancreatic neuroendocrine neoplasm cell line.
BACKGROUND: Pancreatic neuroendocrine neoplasms (PNENs) arise from neuroendocrine cells of the pancreas. Therapeutic options are limited for patients with advanced disease and the molecular mechanisms that drive PNEN progression remain elusive. The Notch pathway regulates cell fate, proliferation, cell-cell communication, and survival in multicellular organisms. Dysregulation of one pathway member, Notch1, has been linked to the development and growth of several cancers; however, the role of Notch1 signaling in PNENs is not defined. METHODS: Notch1 expression was evaluated in normal adult pancreas and PNENs using publicly available single-cell RNA sequencing data from the Human Protein Atlas and immunohistochemistry on PNEN tissue microarrays. A CRISPR/Cas9-mediated knockout of Notch1 was generated in a PNEN cell line ('BON'). The functional impact of Notch1 loss was assessed through proliferation assays, cell cycle analysis, bulk transcriptomics, and Seahorse metabolic flux assays. In vivo tumor growth was evaluated using subcutaneous xenografts, and global proteomic profiling was performed on resected tumors. RESULTS: Notch1 was found to be absent in normal adult pancreatic neuroendocrine cells but was re-expressed in 39-45% of primary and metastatic PNENs. Genetic deletion of Notch1 significantly reduced PNEN cell proliferation in both 2D and 3D conditions, induced G1 cell cycle arrest, and slowed xenograft tumor growth. We also found that Notch1 regulates proliferation and cellular bioenergetic pathways in PNEN cells. CONCLUSIONS: Our findings reveal a role for Notch1 in supporting proliferation and bioenergetics in a PNEN cell line, providing new insights into its potential oncogenic function and contribution to PNEN pathobiology.
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Colorectal Cancer Cell's Weapon: RNF32 Engages SPP1+ Macrophages to Foster Liver Metastasis, Targeted by Indole-3-Acetic Acid.
Colorectal cancer liver metastasis (CRLM) involves complex molecular mechanisms. By integrating The Cancer Genome Atlas (TCGA) data and employing Cox regression, Weighted Gene Co-expression Network Analysis (WGCNA), and single-cell RNA sequencing, this study identifies RNF32 as a key gene linking poor prognosis to metastasis. Functional assays demonstrate that RNF32 promotes tumor cell proliferation, invasion, and epithelial-mesenchymal transition (EMT) in vitro, and drives tumor growth and liver metastasis in vivo. Mechanistically, RNF32 catalyzes K48-linked ubiquitination at the K60 site of GSK3β, stabilizing β-catenin and activating the Wnt signaling pathway, thereby upregulating CCL2. Mass cytometry and other experiments further reveal that RNF32 recruits SPP1+ macrophages via CCL2 to remodel the metastatic niche, a process dependent on the CCR2/FABP1/PPARG axis. Macrophage depletion abrogates metastasis, while the FABP1 inhibitor orlistat reverses SPP1 upregulation in macrophages. Moreover, SPP1+ macrophages interact with tumor cell CD44, synergizing with RNF32 to enhance cancer stemness via Wnt signaling. Importantly, virtual screening identifies indole-3-acetic acid (IAA) as an RNF32 inhibitor that suppresses liver metastasis and reverses immunosuppression in vivo. This study establishes RNF32 as a dual-functional driver of metastasis and proposes IAA as a promising therapeutic agent, offering new hope for targeting both tumor-intrinsic EMT and the immune microenvironment in CRC liver metastasis.
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Transcriptomics Analysis Identifies the Decline in the Alveolar Type II Stem Cell Niche in Aged Human Lungs.
Aging poses a global public health challenge, which is linked to the rise of age-related lung diseases. The precise understanding of the molecular and genetic changes in the aging lung that elevate the risk of acute and chronic lung diseases remains incomplete. Alveolar type II (AT2) cells are stem cells that maintain epithelial homeostasis and repair the lung after injury. AT2 progenitor function decreases with aging. The maintenance of AT2 function requires niche support from other cell types, but little has been done to characterize alveolar alterations with aging in the AT2 niche. To systematically profile the genetic changes associated with age, we present a single-cell transcriptional atlas comprising nearly half a million cells from the healthy lungs of human subjects spanning various ages, sexes, and smoking statuses. Most annotated cell lineages in aged lungs exhibit dysregulated genetic programs. Specifically, the aged AT2 cells demonstrate loss of epithelial identities, heightened inflammaging characterized by increased expression of AP-1 (Activator Protein-1) transcription factor and chemokine genes, and significantly increased cellular senescence. Furthermore, the aged mesenchymal cells display a remarkable decrease in collagen and elastin transcription and a loss of support to epithelial cell stemness. The decline of the AT2 niche is further exacerbated by a dysregulated genetic program in macrophages and dysregulated communications between AT2 and macrophages in aged human lungs. These findings highlight the dysregulations observed in both AT2 stem cells and their supportive niche cells, potentially contributing to the increased susceptibility of aged populations to lung diseases.
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HDAC5 modulates PD-L1 expression and cancer immunity via p65 deacetylation in pancreatic cancer.
Rationale: Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with a dismal 5-year survival less than 10%. Most patients with PDAC exhibit poor response to single-agent immunotherapy. Multimodal therapies targeting mechanisms of resistance to immunotherapy are urgently needed. We found that the class IIa histone deacetylase (HDAC) member, HDAC5 is downregulated in multiple solid tumors and its level were associated with favorable prognosis in PDAC patients. Upregulated genes in patients harboring HDAC5 deletions were enriched in adaptive immune responses and lymphocyte-mediated immunity in The Cancer Genome Atlas (TCGA) pancreatic cancer dataset. Methods: Tissue microarray of pancreatic cancer were used to analysis the correlation between HDAC5 and PD-L1. RNA-seq, transcription factor motif analysis, drug screening and molecular biology assays were performed to identify the mechanism of HDAC5's repression on PD-L1. Allografts of pancreatic cancer in mouse were applied to test the efficiency of HDAC5 inhibition and anti-PD1 co-treatment. Results: HDAC5 regulated PD-L1 expression by directly interacting with NF-κB p65; this interaction was suppressed by p65 phosphorylation at serine-311. Additionally, HDAC5 diminished p65 acetylation at lysine-310, which is essential for the transcriptional activity of p65. Importantly, we demonstrated that HDAC5 silencing or inhibition sensitized PDAC tumors to immune checkpoint blockade (ICB) therapy in syngeneic mouse model and KPC mouse derived PDAC model. Conclusion: Our findings revealed a previously unknown role of HDAC5 in regulating the NF-κB signaling pathway and antitumor immune responses. These findings provide a strong rationale for augment the antitumor effects of ICB in immunotherapy-resistant PDAC by inhibiting HDAC5.