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T-cell exhaustion: A potential target biomarker of the tumour microenvironment affecting oesophageal adenocarcinoma.
BACKGROUND: Oesophageal adenocarcinoma (EAC) is one of the most common malignant tumours, and the number of patients is increasing year by year. T-cell exhaustion (TEX) is an important risk factor for tumour immunosuppression and invasion, but its underlying mechanism in the pathogenesis of EAC is not clear. METHODS: Unsupervised clustering was performed to screen relevant genes based on Gene Set Variation Analysis scores of the three pathways of the HALLMARK gene set IL2/IFNG/TNFA. Multiple enrichment analyses and data combinations were used to depict the relationship between TEX-related risk models and CIBERSORTx immune infiltrating cells. In addition, to explore the impact of TEX on EAC therapeutic resistance, we assessed the impact of TEX risk models on the therapeutic sensitivity of various novel drugs using single-cell sequencing and searched for their potential therapeutic targets and cellular communication. RESULTS: Four risk clusters of EAC patients were identified by unsupervised clustering and searched for potential TEX-related genes. Based on this, LASSO regression and decision trees were used to construct risk prognostic models containing a total of three TEX-associated genes in EAC. The results showed that TEX risk scores were significantly associated with the survival prognosis of EAC patients in both the Cancer Genome Atlas dataset and the independent validation set of Gene Expression Omnibus. Immune infiltration and cell communication analyses identified mast cell resting as a protective factor in TEX, and pathway enrichment analyses showed that the TEX risk model was highly associated with multiple chemokines as well as inflammation-associated pathways. In addition, higher TEX risk scores were associated with a weak responsiveness to immunotherapy. CONCLUSION: We describe the immune infiltration, prognostic significance and potential possible mechanisms of TEX in the EAC patient population. This is a novel attempt to promote the development of novel therapeutic modalities and immunological target construction for oesophageal adenocarcinoma. It is expected to make a potential contribution to advancing the exploration of immunological mechanisms and the opening of target drugs in EAC.
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Clinical Implications of the Novel Genetic Polymorphism Associated With Retinal Vein Occlusion: The East Asian GWAS Survey in a Single-Center Taiwanese Cohort.
PURPOSE: To explore the single-nucleotide polymorphic features in an East Asian cohort of retinal venous occlusion (RVO) patients, to map pathogenic genes, and to analyze potential pathophysiological associations. METHODS: This was a cross-sectional monocentric cohort study involving 172 patients with RVO and 1720 control participants from the Taiwanese population from a single center, Taichung Veterans General Hospital, under the framework of the Taiwan Precision Medicine Initiative (TPMI). DNA samples were collected from a Taiwanese population under the framework of the TPMI. Single nucleotide polymorphism (SNP) exploration was performed using PLINK 2.0. Gene mapping for the selected SNPs and functional analysis were conducted via the SNPXplorer online platform with the R packages biomaRt and clusterProfiler. Single-cell transcriptome mapping was achieved using the published Human Eye Transcriptome Atlas. RESULTS: We report several novel RVO-associated SNPs with suggestive genome-wide association (P < 1 × 10-5), including rs16938701 (STAU2), rs76802456 (FAM189A1), rs995014 (N6AMT1), rs933813, rs6991412 (STAU2), rs79040889, and rs12524176. Among them, the STAU2 single-nucleotide variant, rs16938701, had the most remarkable association (P = 3.19 × 10-7). After mapping to the published human retina single-cell transcriptome atlas, STAU2 exhibited relatively high expression levels in retinal pigment epithelium/choroid complex, microglia, and hyalocyte among all ocular cell types. CONCLUSIONS: We identified several novel risk loci significantly associated with the occurrence of RVO and examined potential mechanistic links between specific biological processes and the pathophysiology of RVO. TRANSLATIONAL RELEVANCE: These findings provide novel insights into the genetic basis of RVO and highlight key pathways that may inform future research and therapeutic strategies.
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Integrated bioinformatics, machine learning, and experimental validation identify a four-gene diagnostic signature for cervical cancer associated with PI3K/AKT signaling.
Early and accurate diagnosis remains a major challenge in cervical cancer management. This study aimed to identify reliable diagnostic biomarkers for cervical cancer by integrating bioinformatics and machine learning approaches and to further validate their biological relevance experimentally. Transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas were analyzed using differential expression analysis, weighted gene co-expression network analysis, and three machine learning algorithms to identify core genes. Diagnostic performance was evaluated using receiver operating characteristic curves and a nomogram model. Functional relevance was explored by drug sensitivity analysis, ssGSEA, immune infiltration analysis, and single-cell RNA sequencing. RT-qPCR validation was performed in 10 paired cervical cancer and adjacent normal tissues, while Western blotting was performed in three paired tissue samples. In vitro validation was conducted using SiHa and HeLa cells. Four genes, CCND1, TRIP13, MYBL2, and GNB4, were identified as potential diagnostic biomarkers, and the combined model showed superior diagnostic performance compared with any single gene (AUC = 0.989). Treatment with 3-methyladenine altered the expression of these genes, suggesting their potential association with PI3K/AKT-related pathway activity. Moreover, siRNA-mediated GNB4 knockdown suppressed cervical cancer cell proliferation and reduced PI3K and AKT phosphorylation, providing preliminary evidence for the functional involvement of GNB4 in PI3K/AKT pathway activation. CCND1, TRIP13, MYBL2, and GNB4 may serve as promising diagnostic biomarkers for cervical cancer. Their dysregulation was associated with PI3K/AKT pathway activity and may reflect molecular alterations involved in cervical cancer progression. In particular, GNB4 showed potential diagnostic relevance and preliminary functional significance, suggesting that it may represent a candidate biomarker and molecular target for further investigation.
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New insight into RNA biomarkers in neuropathic pain: a clinician-neuroscientist roadmap to translational testing and treatment monitoring a clinical review.
Neuropathic pain affects an estimated 7%-10% of the global population and imposes an annual economic burden exceeding $600 billion in the United States alone. It lacks robust objective biomarkers; current diagnosis relies heavily on subjective reporting and heterogeneous phenotypes. Currently utilized pain assessment tools include the brief pain inventory (BPI), numerical rating scales (0-10 pain scores), and the visual analog score (VAS), which depend on patient-reported outcomes and are influenced by social, psychological and contextual factors. This subjectivity contributes to heterogeneous phenotyping and variability (>30%) towards the treatment response. Emerging transcriptomic and epitranscriptomic evidence suggests that RNA-based biomarkers may offer a biologically sound and objective approach to understanding and managing pain by capturing underlying molecular mechanisms. Therefore, the present clinical review focused on RNA biomarker classes (mRNA, miRNA, lncRNA, RNA editing, RNA modifications) and proposes a clinically deployable testing system for diagnosis, stratification, and treatment monitoring, since there are no FDA-approved RNA-based biomarkers for pain. Therefore, this review synthesizes evidence from immune-cell transcriptomic meta-analysis (TCL1A/ERAP2), dorsal root ganglion (DRG) and central nervous system gene expression patterns (EFNB2, GABBR1, NCAM1, SCN11A)/brain genetic architecture via single-cell omics integration, and atlas-driven frameworks, like iPain single-cell atlas of pain chronification and nociceptor senescence. Additional sources include studies on RNA editing mediator adenosine deaminase acting on RNA2 (ADAR2), clinical and translational evidence supporting miRNA biomarkers, and lncRNA axes (NEAT1/miR-183-5p; H19/miR-141) as tissue-specific regulatory nodes. Additionally, m6A epitranscriptomic modifications regulated by the METTL3/METTL14 writer complex and FTO/ALKBH5 erasers, with site-specific methylation of GRIN2B mRNA shown to upregulate GluN2B in dorsal horn neurons and augment central sensitization. These biomarkers also demonstrate potential utility as pharmacodynamic readouts in drug and neuro-modulation trials. Additionally, an emerging RNA workflow technology pathway leveraging rapid low-input RNA based assays was also explained. All evidence supports the idea that these biomarkers can provide complementary insight into the mechanisms underlying pain. Although current evidence supports the feasibility of RNA-based biomarkers as indicators of key biological processes, however, the current pain biology score remains at the theoretical model stage and has not been validated through in vivo, in vitro or clinical trials.
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IL18BP links antigen processing and presentation programs to a dendritic cell-enriched immunoregulatory state in colorectal cancer.
BACKGROUND: Antigen processing and presentation (APP) is required for tumor immune recognition, but its relationship with the immune landscape in colorectal cancer (CRC) remains incompletely defined. In this study, APP-related transcriptional programs were used as the starting point to identify immune-cell-associated biomarkers with prognostic and immunotherapeutic relevance in CRC. METHODS: Six public CRC bulk cohorts were analyzed to define APP-related molecular states. Weighted gene co-expression network analysis and four machine-learning frameworks, including Boruta, LassoLR, Pamr, and XGBoost, were applied to prioritize genes linked to APP activity. Single-cell analysis was performed with an atlas of 121 samples and 169,427 cells to identify the cellular origin of the candidate gene. Immune infiltration, cancer-immunity-cycle activity, immune checkpoint blockade (ICB) response, predicted drug response, somatic mutation patterns, and in vitro function were then evaluated. RESULTS: Two APP-associated patterns were identified and showed different survival outcomes and immune landscapes. Network- and machine-learning-based screening prioritized IL18BP as the main APP-associated candidate. Higher IL18BP expression was associated with longer survival and an immune-active phenotype, including stronger antigen-presentation signals, increased immune infiltration, checkpoint-related signatures, and cancer-immunity-cycle activation. Single-cell profiling showed that IL18BP was preferentially enriched in dendritic cells (DCs), linking the APP-derived bulk signature to a DC-centered immunoregulatory compartment. Across nine external ICB-treated cohorts, IL18BP showed response-classification performance. Drug-response prediction and somatic mutation analyses identified additional features associated with IL18BP-defined groups. In CRC cell lines, IL18BP knockdown increased proliferation, migration, and invasion. CONCLUSION: These findings identify IL18BP as a DC-enriched, APP-associated biomarker in CRC. By connecting APP programs in bulk tumors with DC-level expression patterns at single-cell resolution, this study positions IL18BP as an APP-associated marker of a DC-enriched immune state. These findings support further evaluation of IL18BP for prognostic and immunotherapy stratification in colorectal cancer but do not establish a causal APP-DC-IL18BP pathway.
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High LYRM4-AS1 predicts poor prognosis in patients with glioma and correlates with immune infiltration.
BACKGROUND: Many researches proved that non-coding RNAs are important in glioma development. We screened the differentially expressed genes through The Cancer Genome Atlas (TCGA) database and identified the molecule LYRM4-AS1 associated with prognosis. As a lncRNA, the expression level and role of LYRM4-AS1 in glioma are inconclusive. Therefore, we attempted to assess the clinical significance, expression and related mechanisms of LYRM4-AS1 in glioma by employing cell experiments and an integrative in silico methodology. METHODS: RNA-seq data were obtained from UCSC XENA and TCGA datasets. The Gene Expression Omnibus (GEO) database was used to download glioma-related expression profile data. The LYRM4-AS1 expression level was evaluated. Survival curves were constructed by the Kaplan-Meier method. Cox regression analysis was used to analyze independent variables. Patients were divided into high and low expression group base on the median LYRM4-AS1 expression value in glioma tissues. The DESeq2 R package was used to identify differentially expressed genes (DEGs) between two different expression LYRM4-AS1 groups. Gene set enrichment analysis (GSEA) was conducted. Next, the single-sample Gene Set Enrichment Analysis (ssGSEA) was done to quantify the immune infiltration of immune cells in glioma tissues. Gene expression profiles for glioma tumor tissues were used to quantify the relative enrichment score for each immune cell. Spearman correlation analysis was used to analyze the correlation between LYRM4-AS1 and biomarkers of immune cells as well as immune checkpoints in glioma. Finally, assays for cell apoptosis, cell viability and wound healing were conducted to evaluate the function on U87 MG and U251 cells after knocking down LYRM4-AS1. RESULTS: We found that LYRM4-AS1 was upregulated and related to the grade and malignancy of glioma. Survival analyses showed that high expression LYRM4-AS1 patients had poor clinical outcomes (P < 0.01). Cox regression analyses demonstrated that LYRM4-AS1 was an independent risk factor for overall survival (OS) in glioma (HR: 274 1.836; CI [1.278-2.639]; P = 0.001). Enrichment and immune infiltration analysis showed interferon signaling and cytokine-cytokine receptor interaction enriched in the LYRM4-AS1 high-expression phenotype, and LYRM4-AS1 showed significantly positively related to immune infiltration as well as immune checkpoints (P < 0.01). The knockdown of LYRM4-AS1 in U87 MG and U251 cells can inhibit migration and proliferation of cells (P < 0.05). CONCLUSIONS: These findings indicated that the increased LYRM4-AS1 may be useful for the diagnosis and prognosis of glioma and might participate in the immune infiltration.
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Lactylation prognostic signature identifies DHCR7 as a modulator of chemoresistance and immunotherapy efficacy in bladder cancer.
BACKGROUND: Bladder cancer (BLCA), the 10th most common cancer worldwide, presents a worsening prognosis as the disease progresses. Reliable tools for predicting BLCA prognosis and treatment efficacy remain urgently needed. METHODS: Expression profiles of lactylation related genes were analyzed utilizing the Cancer Genome Atlas (TCGA) database and BLCA data from the GSE13507 dataset. Two distinct clusters were identified through unsupervised clustering analysis. Lactylation associated gene signatures were established and subsequently validated using training cohort and different validation cohorts. Immune cell infiltration patterns and drug response profiles were systematically evaluated. Parallel analyses of lactylation related genes were conducted at the single-cell resolution. A series of in vivo and in vitro experiments were subsequently performed to validate the findings. RESULTS: We examined the mRNA expression profiles of 22 lactylation related genes in BLCA tissues. Through comprehensive analysis, we identified two distinct lactylation clusters that exhibited significantly different clinical outcomes and tumor immune microenvironment characteristics. Building upon these findings, we subsequently stratified patients into two molecular subtypes according to the lactylation clusters and established a robust genetic signature for predicting survival outcomes in BLCA patients. The lactylation risk score showed a strong connection with survival outcomes and correlated with the tumor microenvironment (TME) immunosignature and predicted immunotherapy efficacy. DHCR7 emerged as a pivotal prognostic gene from the nine gene model, prompting subsequent focused analyses. Single-cell analysis confirmed that DHCR7 reached peak expression in tumor epithelial cells, whereas TCGA data and single-cell data demonstrated strong associations between DHCR7 and diverse immune-cell populations. For the first time, we identified that knockdown of DHCR7 enhances the efficacy of both cisplatin chemotherapy and immunotherapy, highlighting DHCR7 as a key player in cisplatin resistance and its influence on immunotherapy effectiveness in BLCA. These findings offer valuable insights into potential combined therapeutic strategies. CONCLUSIONS: We developed a robust lactylation risk prediction model for accurately forecasting BLCA prognosis and identified DHCR7 as a pivotal biomarker involved in cisplatin resistance and influencing immunotherapy efficacy in BLCA.
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INHBA: a mitochondrial-related pan-cell death gene associated with the prognosis and immunity of OSCC.
Oral squamous cell carcinoma (OSCC) is a malignant tumor characterized by both clinical and molecular heterogeneity. Its rising global incidence and mortality rates pose considerable clinical challenges. Accumulating evidence suggests that dysregulation of mitochondria-associated pan-cell death, a process integrating multiple mitochondrial-related cell death modalities, is closely linked to tumor initiation and progression. Nevertheless, the identification of key therapeutic targets among mitochondria-associated pan-cell death-related genes (MAPGs) in OSCC remains an unresolved issue, underscoring the need for further investigation. We systematically investigated the expression patterns, prognostic relevance, and immune microenvironmental features of mitochondria-associated pan-cell death-related genes (MAPGs) in OSCC by integrating data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) datasets (GSE42743, GSE41613, GSE75538, GSE164241, GSE172577, and GSM6339633), and the MitoCarta3.0 database. Using nine machine learning algorithms, we compared the importance and prognostic value of MAPGs and identified INHBA as the most pivotal MAPG. Its predictive power and functional relevance were further explored through enrichment analysis. We validated INHBA mRNA expression levels in clinical OSCC samples using quantitative real-time PCR (qRT‑PCR). Pan-cancer analysis was performed to assess the potential of INHBA as a therapeutic target across multiple cancer types. Single-cell RNA sequencing, spatial transcriptomics, and cell-cell communication analyses were integrated to elucidate the spatial distribution of INHBA in OSCC and its crosstalk with the immune microenvironment. Finally, drug sensitivity profiling was conducted using the GDSC and PRISM databases. A total of 19 MAPGs with the greatest prognostic value were screened out. Among them, INHBA emerged as the most critical MAPG, which was overexpressed in HNSCC and strongly correlated with poor prognosis in OSCC patients (p < 0.05). Meanwhile, INHBA expression was elevated in cancer-associated fibroblasts (CAFs). Spatial transcriptomic analysis further revealed strong spatial colocalization between INHBA and CAF-localized regions. These results indicated that INHBA primarily functioned within CAFs, especially myCAFs, and may promote OSCC progression through modulation of the immune microenvironment. Elevated INHBA expression served as a prognostic indicator in OSCC, a finding consistent with its prognostic relevance in broader HNSCC analyses. Selumetinib and naltrexone showed high sensitivity in INHBA-high contexts. INHBA is a crucial MAPG that is upregulated in OSCC and mainly functions in CAFs. It likely affects the poor prognosis of OSCC by regulating the immune microenvironment. Selumetinib and naltrexone hold promise as innovative therapeutic agents, potentially opening up new treatment avenues for OSCC patients.
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Integrating tertiary lymphoid structure-associated genes into computational models to evaluate prognostication and immune infiltration in pancreatic cancer.
Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor response to all therapeutic modalities and dismal prognosis. The presence of tertiary lymphoid structures (TLSs) in various solid cancers is of crucial prognostic significance, highlighting the intricate interplay between the tumor microenvironment and immune cells aggregation. However, the extent to which TLSs and immune status affect PDAC prognosis remains incompletely understood. Here, we sought to unveil the unique properties of TLSs in PDAC by leveraging both single-cell and bulk transcriptomics, culminating in a risk model that predicts clinical outcomes. We used TLS scores based on a 12-gene (CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, and CXCL13) and 9-gene (PTGDS, RBP5, EIF1AY, CETP, SKAP1, LAT, CCR6, CD1D, and CD79B) signature, respectively, and examined their distribution in cell clusters of single-cell data from PDAC samples. The markers involved in these clusters were selected to develop a prognostic model using The Cancer Genome Atlas Program database as the training cohort and Gene Expression Omnibus database as the validation cohort. Further, we compared the immune infiltration, drug sensitivity, and enriched and differentially expressed genes between the high- and low-risk groups in our model. Therefore, we established a risk model that has significant implications for the prognostic assessment of PADC patients with remarkable differences in immune infiltration and chemosensitivity between the low- and high-risk groups. This paradigm established by TLS-related cell marker genes provides a prognostic prediction and a panel of novel therapeutic targets for exploring potential immunotherapy.
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Overexpression of LIMA1 Indicates Poor Prognosis and Promotes Epithelial-Mesenchymal Transition in Head and Neck Squamous Cell Carcinoma.
BACKGROUND: LIMA1 encodes LIM domain and actin binding 1, a cytoskeleton-associated protein whose loss has been linked to migration and invasion behavior of cancer cells. However, the roles of LIMA1 underlying the malignant behavior of tumors in head and neck squamous cell carcinoma (HNSC) are not fully understood. METHODS: We conducted a multi-omics study on the role of LIMA1 in HNSC based on The Cancer Genome Atlas data. Subsequent in vitro experiments were performed to validate the results of bioinformatic analysis. We first identified the correlation between LIMA1 and tumor cell functional states according to single-cell sequencing data in HNSC. The potential downstream effects of LIMA1 were explored for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathways through functional enrichment analysis of the gene sets that correlated with LIMA1 in HNSC. The prognostic role of LIMA1 was assessed using the log rank test to compare difference in survival between LIMA1High and LIMA1Low patients. Univariate Cox regression and multivariate Cox regression were further carried out to identify the prognostic value of LIMA1 in HNSC. RESULTS: LIMA1 was identified as a prognostic biomarker and is associated with epithelial-mesenchymal transition (EMT) progress in HNSC. In vitro silencing of LIMA1 suppressed EMT and related pathways in HNSC. CONCLUSIONS: LIMA1 promotes EMT and further leads to tumor invasion and metastasis. Increased expression of LIMA1 indicates poor survival, identifying it as a prognostic biomarker in HNSC.