Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Signature”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34Linked to original sources

Proteomic and machine learning analysis predicts treatment response signatures in Myasthenia Gravis.

BACKGROUND: Myasthenia gravis (MG) is a prototypical antibody-mediated autoimmune disease with variable treatment responses with a need for biomarkers to guide therapeutic decision making. Proteomic profiling, coupled with machine learning, offers a hypothesis-free approach to identify multi-protein signatures associated with treatment response. METHODS: We analyzed sera collected at entry (baseline) from participants in a phase 3 trial randomized trial comparing thymectomy plus prednisone versus prednisone alone, along with matched controls using liquid chromatography-mass spectrometry. We derived disease-specific proteomic signatures and evaluated associations between baseline proteins and 6-month clinical outcomes using multiple machine-learning approaches with internal validation. RESULTS: Baseline serum proteomes distinguished MG from controls, with pathway enrichment implicating complement activation, immunoglobulin production, and T-cell receptor signaling. Distinct protein panels predicted 6-month clinical improvement within each treatment arm. In the thymectomy-plus-prednisone group, models captured non-linear relationships of predictive proteins in contrast with the predominant additive patterns observed in the prednisone-alone group. Predictive proteins were enriched for T-cell signaling and leukocyte trafficking functions, providing insight into treatment-specific biology. CONCLUSIONS: Baseline serum proteomics captures core disease characteristics of MG and predicts short-term clinical response in a treatment-specific manner. While our results require validation in independent cohorts, these findings could enable biomarker-guided selection of thymectomy, refine risk stratification, and furnish mechanistic readouts for future MG trials and clinical care. We aim to conduct future studies using -omic approaches to validate these baseline predictive biomarkers and pathways of treatment response in patients with MG.

Adult↗

Multi-omics signature of healthy versus unhealthy lifestyles reveals associations with diseases.

This multi-omics cross-sectional study investigated differences in metabolomics, proteomics, and epigenomics profiles between two groups of adults matched for age but differing in lifestyle factors such as body composition, diet, and physical activity patterns. Data from prior studies were utilized for a comprehensive integrative analysis. The study included 52 participants in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). Using multi-omics integration software (OmicsNet and Pathview), 96 significantly (p&#x2009;<&#x2009;0.05) enriched pathways were identified that differentiated the LIFE and CON groups. Top pathways significantly (p&#x2009;<&#x2009;2.63&#x2009;&#xd7;&#x2009;10-5) influenced by group status included fatty acid degradation, fatty acid elongation, glutathione metabolism, Parkinson disease, and central carbon metabolism in cancer. This study identified a distinct metabolic signature comprised of metabolites, proteins, and gene methylation sites associated with a healthy lifestyle. These findings provide unique, but complementary, results to previous single-omics analyses using metabolomics and proteomics procedures which showed that the LIFE group exhibited lower plasma bile acid levels, higher levels of beneficial fatty acids, reduced innate immune activation, enhanced lipoprotein metabolism, and increased HDL remodeling. The current multi-omics analysis builds on these previous results by providing a more holistic view of how metabolites, proteins, and methylation sites associated with a healthy lifestyle, providing a larger, more comprehensive list of altered pathways. Additionally, the integrated analysis revealed connections between lifestyle factors and conditions such as cancer and insulin resistance beyond what identified in the single-omics approaches, highlighting the broader metabolic impact of lifestyle on health. Overall, the signatures identified by this multi-omics approach provide a basis for developing more translational biomarkers, such as those that defined the cancer and insulin resistance pathways that can be used to assess one's state of health and provide guidance on behavior modifications that should be taken to lower disease risk.

Humans↗

Current strategies in treatment of oligodendroglioma: evolution of molecular signatures of response.

Oligodendroglioma frequently (> or = 70%) responds to radiation and chemotherapy, and is the first CNS neoplasm in which a genetic signature (1p and 19q deletion) has been associated with outcome within the context of large clinical trials. Current translational investigations focus on deletions or mutations of potential tumor suppressor genes, epigenetic alterations, amplification or mutation of growth factor and regulatory genes, and characterization of signaling events and regulatory protein expression. The most compelling data has involved 1p and 19q loss, which is observed in over 50% of anaplastic oligodendrogliomas. In two randomized phase III trials (Radiation Therapy Oncology Group 9402 and European Organisation for Research and Treatment of Cancer 26951), the addition of neoadjuvant or adjuvant procarbazine, lomustine, and vincristine (PCV; respectively) to radiotherapy did not produce superior survival as compared with radiotherapy alone. A modest increase in progression-free survival was observed with the addition of PCV, but at the cost of increased toxicity. Combined 1p and 19q loss identified a favorable prognostic group in both studies, which appeared to be independent of treatment arms. However, it is unclear whether these deletions represent surrogate markers of a favorable biologic tumor behavior, or are predictive of outcome after specific treatment. Currently, there is insufficient data to allow therapeutic decisions to be made solely on the basis of 1p and 19q gene deletion status. Future phase III trials are evaluating other chemotherapeutic and targeted agents, including temozolomide, and include correlative investigations of aberrant molecular events in these neoplasms, which may lead to future therapeutic strategies that are based on specific molecular signatures.

Central Nervous System Neoplasms↗

Gene expression profiling identifies a unique androgen-mediated inflammatory/immune signature and a PTEN (phosphatase and tensin homolog deleted on chromosome 10)-mediated apoptotic response specific to the rat ventral prostate.

Understanding androgen regulation of gene expression is critical for deciphering mechanisms responsible for the transition from androgen-responsive (AR) to androgen-independent (AI) prostate cancer (PCa). To identify genes differentially regulated by androgens in each prostate lobe, the rat castration model was used. Microarray analysis was performed to compare dorsolateral (DLP) and ventral prostate (VP) samples from sham-castrated, castrated, and testosterone-replenished castrated rats. Our data demonstrate that, after castration, the VP and the DLP differed in the number of genes with altered expression (1496 in VP vs. 256 in DLP) and the nature of pathways modulated. Gene signatures related to apoptosis and immune response specific to the ventral prostate were identified. Microarray and RT-PCR analyses demonstrated the androgen repression of IGF binding protein-3 and -5, CCAAT-enhancer binding protein-delta, and phosphatase and tensin homolog deleted on chromosome 10 (PTEN) genes, previously implicated in apoptosis. We show that PTEN protein was increased only in the luminal epithelial cells of the VP, suggesting that it may be a key mediator of VP apoptosis in the absence of androgens. The castration-induced immune/inflammatory gene cluster observed specifically in the VP included IL-15 and IL-18. Immunostaining of the VP, but not the DLP, showed an influx of T cells, macrophages, and mast cells, suggesting that these cells may be the source of the immune signature genes. Interestingly, IL-18 was localized mainly to the basal epithelial cells and the infiltrating macrophages in the regressing VP, whereas IL-15 was induced in the luminal epithelium. The VP castration model exhibits immune cell infiltration and loss of PTEN that is often observed in progressive PCa, thereby making this model useful for further delineation of androgen-regulated gene expression with relevance to PCa.

Androgens↗

Aequorin-based measurements of intracellular Ca2+-signatures in plant cells.

Due to the involvement of calcium as a main second messenger in the plant signaling pathway, increasing interest has been focused on the calcium signatures supposed to be involved in the patterning of the specific response associated to a given stimulus. In order to follow these signatures we described here the practical approach to use the non-invasive method based on the aequorin technology. Besides reviewing the advantages and disadvantages of this method we report on results showing the usefulness of aequorin to study the calcium response to biotic (elicitors) and abiotic stimuli (osmotic shocks) in various compartments of plant cells such as cytosol and nucleus.

Journal Article↗

Mass spectrometry-based detection of transfer RNAs by their signature endonuclease digestion products.

The separation of biologically active, pure, and specific tRNAs is difficult due to the overall similarity in secondary and tertiary structures of different tRNAs. Because prior methods do not facilitate high-resolution separations of the extremely complex mixture represented by a cellular tRNA population, global studies of tRNA identity and/or abundance are difficult. We have discovered that the enzymatic digestion of an individual tRNA by a ribonuclease (e.g., RNase T1) will generate digestion products unique to that particular tRNA, and we show that a comparison of an organism's complete complement of tRNA RNase digestion products yields a set of unique or "signature" digestion product(s) that ultimately enable the detection of individual tRNAs from a total tRNA pool. Detection is facilitated by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and proof-of-principle is demonstrated on the whole tRNA pool from Escherichia coli. This method will enable the individual identification of tRNA isoacceptors without requiring specific affinity purification or extensive chromatographic and/or electrophoretic purification. Further, experimental identifications of tRNAs or other RNAs will now be possible using this signature digestion product approach in a manner similar to peptide mass fingerprinting used in proteomics, allowing RNomic studies of RNA at the post-transcriptional level.

Escherichia coli↗

Adaptive polarimetric sensing for optimum radar signature classification using a genetic search algorithm.

An automated technique for adaptive radar polarimetric pattern classification is described. The approach is based on a genetic algorithm that uses a probabilistic pattern separation distance function and searches for those transmit and receive states of polarization sensing angles that optimize this function. Seven pattern separation distance functions--the Rayleigh quotient, the Bhattacharyya, divergence, Kolmogorov, Matusta, Kullback-Leibler distances, and the Bayesian probability of error--are used on real, fully polarimetric synthetic aperture radar target signatures. Each of these signatures is represented as functions of transmit and receive polarization ellipticity angles and the angle of polarization ellipse. The results indicate that, based on the majority of the distance functions used, there is a unique set of state of polarization angles whose use will lead to improved classification performance.

Journal Article↗

Characterization of the signature of subwavelength variation from far-field irradiance.

The dynamic signature of the subwavelength variation of a slit is shown to be determinable from far-field irradiance with a precision of better than 1 nm. One can increase the efficiency of measurement of the subwavelength's signature by adjusting the detection width over which the subwavelength variation is detected. The subwavelength variation of a rectangular aperture was also examined to show the general feasibility.

Journal Article↗

Phase signature for particle detection with digital in-line holography.

The spatial phase resulting from the digital reconstruction of an in-line hologram of a particle field is shown to yield a unique pattern that can be used for particle detection. This phase signature is present only when viewed along with the reference light. The existence of the phase pattern is verified computationally and confirmed in laboratory experiments with holograms of calibrated glass spheres. The phase signature provides an alternative to the widely used intensity method for particle detection.

Journal Article↗

Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds.

Cancer invasion and metastasis have been likened to wound healing gone awry. Despite parallels in cellular behavior between cancer progression and wound healing, the molecular relationships between these two processes and their prognostic implications are unclear. In this study, based on gene expression profiles of fibroblasts from ten anatomic sites, we identify a stereotyped gene expression program in response to serum exposure that appears to reflect the multifaceted role of fibroblasts in wound healing. The genes comprising this fibroblast common serum response are coordinately regulated in many human tumors, allowing us to identify tumors with gene expression signatures suggestive of active wounds. Genes induced in the fibroblast serum-response program are expressed in tumors by the tumor cells themselves, by tumor-associated fibroblasts, or both. The molecular features that define this wound-like phenotype are evident at an early clinical stage, persist during treatment, and predict increased risk of metastasis and death in breast, lung, and gastric carcinomas. Thus, the transcriptional signature of the response of fibroblasts to serum provides a possible link between cancer progression and wound healing, as well as a powerful predictor of the clinical course in several common carcinomas.

Disease Progression↗

Molecular signatures of proliferation and quiescence in hematopoietic stem cells.

Stem cells resident in adult tissues are principally quiescent, yet harbor enormous capacity for proliferation to achieve self renewal and to replenish their tissue constituents. Although a single hematopoietic stem cell (HSC) can generate sufficient primitive progeny to repopulate many recipients, little is known about the molecular mechanisms that maintain their potency or regulate their self renewal. Here we have examined the gene expression changes that occur over a time course when HSCs are induced to proliferate and return to quiescence in vivo. These data were compared to data representing differences between naturally proliferating fetal HSCs and their quiescent adult counterparts. Bioinformatic strategies were used to group time-ordered gene expression profiles generated from microarrays into signatures of quiescent and dividing stem cells. A novel method for calculating statistically significant enrichments in Gene Ontology groupings for our gene lists revealed elemental subgroups within the signatures that underlie HSC behavior, and allowed us to build a molecular model of the HSC activation cycle. Initially, quiescent HSCs evince a state of readiness. The proliferative signal induces a preparative state, which is followed by active proliferation divisible into early and late phases. Re-induction of quiescence involves changes in migratory molecule expression, prior to reestablishment of homeostasis. We also identified two genes that increase in both gene and protein expression during activation, and potentially represent new markers for proliferating stem cells. These data will be of use in attempts to recapitulate the HSC self renewal process for therapeutic expansion of stem cells, and our model may correlate with acquisition of self renewal characteristics by cancer stem cells.

Analysis of Variance↗

Transcriptional profiling of aging in human muscle reveals a common aging signature.

We analyzed expression of 81 normal muscle samples from humans of varying ages, and have identified a molecular profile for aging consisting of 250 age-regulated genes. This molecular profile correlates not only with chronological age but also with a measure of physiological age. We compared the transcriptional profile of muscle aging to previous transcriptional profiles of aging in the kidney and the brain, and found a common signature for aging in these diverse human tissues. The common aging signature consists of six genetic pathways; four pathways increase expression with age (genes in the extracellular matrix, genes involved in cell growth, genes encoding factors involved in complement activation, and genes encoding components of the cytosolic ribosome), while two pathways decrease expression with age (genes involved in chloride transport and genes encoding subunits of the mitochondrial electron transport chain). We also compared transcriptional profiles of aging in humans to those of the mouse and fly, and found that the electron transport chain pathway decreases expression with age in all three organisms, suggesting that this may be a public marker for aging across species.

Adolescent↗

Whole-genome sequencing reveals divergent and shared selection signatures of heat stress adaptation in indigenous Ethiopian zebu cattle from dry-hot and humid-hot&#xa0;environments.

African zebu cattle (Bos indicus) exhibit remarkable adaptations to extreme thermal conditions, yet the genomic basis of this resilience remains incompletely characterized. Ethiopia provides a unique natural setting in which closely related zebu populations have adapted divergently to dry-hot (DHETZ) and humid-hot (HHETZ) climates. In this study, we reanalyzed publicly available whole-genome sequencing datasets from 46 Ethiopian zebu cattle from five populations and compared them with Asian zebu, Sudanese zebu, African taurine, and European taurine breeds. By integrating genome-wide SNP analysis, population genetic structure assessment, and multiple selection scans (iHS, Hp, XP-EHH, and XP-CLR), we identified distinct and shared selection signatures between DHETZ and HHETZ. We detected 33.7 million and 34.2 million biallelic autosomal SNPs in DHETZ and HHETZ, respectively. Ethiopian zebu clustered closely with Sudanese zebu but showed clear divergence from Asian zebu and taurine breeds. DHETZ and HHETZ exhibited very low genetic differentiation (FST&#x2009;=&#x2009;0.0063), consistent with their shared ancestry; however, each group displayed unique selection signals. In DHETZ, iHS and Hp detected 298 and 113 candidate regions, respectively, whereas in HHETZ, they detected 244 and 138 regions, respectively. Cross-population XP-EHH and XP-CLR analyses identified 163 and 227 divergent regions between DHETZ and HHETZ, respectively. Integration of the four selection scans identified 19 high-confidence candidate regions in DHETZ and 13 in HHETZ. DHETZ showed strong selection in genes involved in oxidative stress regulation, protein folding, mitochondrial function, and vascular remodeling, including SESN2, DNAJC8, GRPEL2, ABLIM3, and AFAP1L1. In contrast, HHETZ displayed signatures in genes associated with immune responses, energy metabolism, and angiogenesis inhibition, including MYD88, PRKACA, PRKACB, and WIF1. Several genes, including VEGFC, TNIP3, and DMXL2, were under selection in both groups, suggesting conserved mechanisms of thermotolerance and reproductive adaptation. The shared VEGFC signal and the HHETZ-specific WIF1 signal may indicate a distinct vascular regulatory mechanism in the dry-hot and humid-hot environments. Our results reveal a dual pattern of genomic adaptation in Ethiopian zebu cattle and provide candidate loci for future validation and climate-resilient livestock breeding.

Animals↗

Development of rationally designed nucleic acid signatures for microbial pathogens.

The detection and identification of microbial pathogens are critical challenges in clinical medicine and public health surveillance. Advances in genome analysis technology are providing an unprecedented amount of information about bacterial and viral organisms, and hold great potential for pathogen detection and identification. In this paper, a rational approach to the development and application of nucleic acid signatures is described based on phylogenetically informative sequence features, especially single nucleotide polymorphisms. The computational tools that are available to enable the development of the next generation of microbial molecular signatures for clinical diagnostics and infectious disease surveillance are reviewed and the impact on public health and national security will be discussed.

Bacteria↗

Quantitative measurement of fathead minnow vitellogenin by liquid chromatography combined with tandem mass spectrometry using a signature peptide of vitellogenin.

Vitellogenin (VTG) has been proposed as a sensitive biomarker of exposure to environmental estrogenic contaminants that induce VTG production in oviparous species. Enzyme-linked immunosorbent assay (ELISA) methods are currently widely used to measure the VTG levels. In this paper, a new liquid chromatography combined with tandem mass spectrometry (LC/ESI-MS/MS) method for the quantitative analysis of VTG in the plasma of fathead minnows exposed to 17alpha-ethinylestradiol (EE2) has been developed. This method includes, first, the selection of the signature peptide, which involves sodium dodecyl sulfate-polyarylamide gel electrophoresis separation, in-gel digestion, LC/ESI-MS/MS analysis with an ion trap mass spectrometer, and sequence determination with the TurboSEQUEST MS/MS database application; second, optimization of the selected signature peptide in multireaction monitor (MRM) mode with a triple quadrupole mass spectrometer; and third, trypsin digestion of plasma and VTG quantitation via MRM-mode LC/ESI-MS/MS. A series of plasma samples from fathead minnows following exposure to EE2 was assayed. A good correlation was found when EE2-induced plasma samples from fathead minnows were analyzed with ELISA and the described new method. Although used here with fathead minnow, the new LC/ESI-MS/MS method could be easily applied to the analysis of VTG expressed in any other fish species. Quantitation of VTG by this method was found to be highly specific and linear. The absence of potential artifactual measurements of VTG at low exposure levels could also be critical in future studies that evaluate weakly estrogenic compounds in aquatic species.

Animals↗

A CFH- and SPINT2-based prognostic signature for cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant tumor with a poor prognosis, and reliable biomarkers for postoperative risk stratification remain limited. This study aimed to develop and validate a CFH- and SPINT2-based prognostic signature to support postoperative risk stratification and inform adjuvant therapy selection in CCA through integrative machine learning and single-cell transcriptomics. METHODS: Differentially expressed genes were screened from GSE26566. Integrative machine learning (least absolute shrinkage and selection operator-Cox, random forest, and univariate Cox regression) was performed in the training cohort (GSE89749; n=115) to construct a risk model, which was externally validated in two independent cohorts: cohort 1 (E-MTAB-6389; n=75) and cohort 2 [The Cancer Genome Atlas Cholangiocarcinoma (TCGA-CHOL) data set; n=36]. Systematic analysis was conducted and included examinations of immune infiltration [via single-sample gene set enrichment analysis (ssGSEA)], pathway enrichment (via hallmark GSEA), cellular localization (via single-cell RNA sequencing), and drug sensitivity (via the Genomics of Drug Sensitivity in Cancer 2 database). RESULTS: Two genes, CFH and SPINT2, were identified and incorporated into a prognostic risk score. High-risk patients in the training cohort had a significantly worse overall survival (log-rank P=0.02). External validation was performed in two independent cohorts. In validation cohort 1, the risk group was an independent prognostic factor [hazard ratio =2.27, 95% confidence interval (CI): 1.18-4.37; P=0.01]. In validation cohort 2, the model demonstrated acceptable discriminative ability (concordance index =0.721; 3-year area under the curve =0.692). The high-risk group exhibited an immunosuppressive microenvironment characterized by increased infiltration of macrophages and myeloid-derived suppressor cells, along with the activation of epithelial-mesenchymal transition, inflammatory response, and NF-&#x3ba;B signaling pathways. Single-cell analysis revealed a cell-type-specific expression pattern: CFH was predominantly expressed in fibroblasts, while SPINT2 was mainly expressed in malignant cells. Drug sensitivity analysis demonstrated that the high-risk group was more sensitive to gemcitabine, cisplatin, poly(ADP-ribose) polymerase (PARP) inhibitors, and mammalian target of rapamycin (mTOR) inhibitors, whereas the low-risk group was more sensitive to lapatinib. CONCLUSIONS: The CFH- and SPINT2-based prognostic signature may serve as an independent biomarker for postoperative risk stratification in CCA. High-risk patients, characterized by fibroblast-derived CFH enrichment and malignant-cell SPINT2 loss, exhibit an immunosuppressive microenvironment and may be more suitable for gemcitabine-based chemotherapy or PARP/mTOR inhibitors, whereas low-risk patients may benefit from less intensive adjuvant strategies or HER2/EGFR-targeted lapatinib. Prospective validation is warranted before clinical implementation.

Cholangiocarcinoma (CCA)↗

Integrative analysis identifies a glycosylation-related lncRNA signature associated with prognosis in kidney renal clear cell carcinoma.

BACKGROUND: Glycosylation and long non-coding RNAs (lncRNAs) play critical roles in tumor progression. However, the prognostic significance of glycosylation-related lncRNAs (GRLncs) in kidney renal clear cell carcinoma (KIRC) remains largely unclear. This study aimed to identify prognostic GRLncs and construct a predictive model for KIRC prognosis. METHODS: Transcriptomic and clinical data of KIRC patients were analyzed to identify GRLncs associated with overall survival (OS). A prognostic model was constructed based on selected GRLncs, and its predictive performance was evaluated using Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) curves, and univariate and multivariate Cox regression analyses. Patients were stratified into high- and low-risk groups according to the median risk score, and internal validation was performed using training and testing cohorts to assess the stability of the model. Tumor microenvironment characteristics, immune checkpoint expression, immunotherapy response, and drug sensitivity were further analyzed. In addition, the expression of three signature lncRNAs was validated by real-time quantitative polymerase chain reaction (RT-qPCR) in 10 paired KIRC tumor and adjacent normal tissues. Functional roles of selected lncRNAs were investigated using antisense oligonucleotides (ASOs)-mediated knockdown in KIRC cell lines, followed by Cell Counting Kit 8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) incorporation, colony formation, and migration assays. RESULTS: Five GRLncs (AC093278.2, EPB41L4A-DT, DLGAP1-AS2, AC084876.1, and AC005261.3) were identified and used to construct a prognostic model. AC093278.2 and EPB41L4A-DT were protective factors, whereas DLGAP1-AS2, AC084876.1, and AC005261.3 were risk factors. KM analysis on GRLncs-based risk score stratification revealed patients in the high-risk group had significantly poorer OS than those in the low-risk group. ROC analysis and Cox regression demonstrated that the GRLnc-based risk score served as an independent predictor of KIRC prognosis and exhibited favorable predictive performance compared with conventional clinical variables. High- and low-risk groups also exhibited distinct immune microenvironment characteristics, immune checkpoint expression patterns, and predicted drug sensitivities. RT-qPCR detected significant downregulation of protective factor-EPB41L4A-DT in KIRC tissues, while risk factors-DLGAP1-AS2 and AC084876.1 showed expression trends consistent with their predicted risk attributes. Functional experiments further revealed that knockdown of DLGAP1-AS2 and AC084876.1 suppressed proliferation and migration of KIRC cells, whereas knockdown of EPB41L4A-DT promoted these processes, supporting the biological relevance of these three signature lncRNAs. CONCLUSIONS: This study establishes a novel prognostic model based on five GRLncs that showed promising performance in The Cancer Genome Atlas (TCGA)-based analyses of KIRC. The combined clinical expression analysis and functional validation of three constituent GRLncs (DLGAP1-AS2, EPB41L4A-DT, and AC084876.1) supports the biological plausibility of the model and suggest that GRLncs may serve as potential prognostic biomarkers and therapeutic targets for KIRC.

Kidney renal clear cell carcinoma (KIRC)↗

A cuproptosis-related lncRNAs-based risk signature for predicting prognosis and immune status in glioma.

BACKGROUND: Glioma is one of the most prevalent primary malignant brain tumors, characterized by poor prognosis and limited treatment options. Recent studies have identified cuproptosis, a novel copper-dependent form of regulated cell death, as a critical mechanism involved in tumor progression. However, the role of cuproptosis-related long non-coding RNAs (lncRNAs) in glioma remains not fully clarified. This study aimed to develop and validate a prognostic model based on cuproptosis-associated lncRNAs to predict patient outcomes and guide individualizing therapeutic strategies. METHODS: Transcriptomic profiles and clinical data were obtained from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and the Chinese Glioma Genome Atlas (CGGA) databases. Cuproptosis -related prognostic lncRNAs were filtered via univariate and multivariate Cox and Least absolute shrinkage and selection operator (LASSO) regression analyses, which were selected to establish a prognostic model for glioma. Samples were divided into high- and low-risk groups, and the predictive performance of the prognostic model was evaluated based on receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) survival curves, and a nomogram. In addition, immune cell infiltration, tumor mutational burden (TMB), immunophenoscore (IPS), Tumor Immune Dysfunction and Exclusion (TIDE) and drug sensitivity were analyzed. Expression levels of selected lncRNAs and proteins were validated using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: An 11-lncRNA signature associated with cuproptosis was established, and the risk score derived from this model was identified as an independent prognostic factor for glioma. The model exhibited excellent predictive ability, with area under the curve (AUC) values of 0.880, 0.913, and 0.866 for 1-, 3-, and 5-year survival, respectively. Higher TMB, immune checkpoint expression, and IPS were observed in the high-risk group and no significant difference was observed in TIDE between risk groups. Drug sensitivity analysis identified TPCA-1, KIN001-135, and ispinesib mesylate as potential therapeutic agents. Expression validation in glioma cells further supported the biological relevance of the selected lncRNAs. CONCLUSIONS: This cuproptosis-related lncRNA-based signature demonstrates strong prognostic value and may serve as a promising tool for glioma risk stratification and personalized treatment selection.

Glioma↗