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The role of IQCB1 in liver cancer: a bioinformatics analysis.
BACKGROUND: Liver hepatocellular carcinoma (LIHC) is a prevalent malignancy globally, exhibiting substantial incidence and mortality rates. Early diagnosis and prevention of metastasis are crucial for the benefit of patients with liver cancer. The present study aimed to elucidate the involvement of IQCB1 in liver cancer through the utilization of bioinformatics. METHODS: The samples utilized in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Initially, the TCGA-LIHC dataset was employed to examine the expression of IQCB1, and its validation was performed on the GSE25097 dataset. Subsequently, Kaplan-Meier (KM) analysis was conducted to evaluate the prognostic significance of IQCB1 in LIHC, and its correlation with clinical pathological features was also investigated. Furthermore, a protein-protein interaction (PPI) network consisting of 20 proteins associated with IQCB1 was constructed using data from the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out. A risk model was formulated to assess the prognostic significance and its prognostic value was compared to that of IQCB1 in isolation. Furthermore, an examination was conducted to explore the correlation between IQCB1 and immune infiltration, along with the involvement of immunological checkpoints. A drug sensitivity assessment of IQCB1 was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Additionally, the Tumor Immune Single-cell Hub (TISCH) database was utilized to investigate the association between IQCB1 and the tumor microenvironment (TME). RESULTS: The expression of IQCB1 was observed to be significantly elevated in tumor samples. Furthermore, patients with high expression levels of IQCB1 demonstrated a poorer prognosis. Additionally, IQCB1 exhibited significant correlations with MKI67, hepatitis B virus (HBV), hepatitis C virus (HCV), and alpha-fetoprotein (AFP). GO and KEGG analyses revealed enrichment of multiple signaling pathways. Subsequently, an investigation was conducted to examine the association between IQCB1 and the activity of ten signaling pathways related to tumor development. A positive correlation was observed between IQCB1 expression and T-helper 2 (Th2) cells, whereas a negative correlation was observed between IQCB1 expression and Th17 cells. Furthermore, a positive association was found between IQCB1 and immune checkpoints, particularly with CD276. Analysis of single-cell data from the TISCH database revealed widespread expression of IQCB1 in the TME. Additionally, screening revealed that among 12 drugs related to IQCB1, a subset of 10 drugs demonstrated negative correlations, whereas two drugs exhibited positive correlations. CONCLUSIONS: IQCB1 has the potential to function as a diagnostic and prognostic molecular marker, and its association with immune infiltration and checkpoint mechanisms has been observed.
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Distinct identities of leaf phloem cells revealed by single cell transcriptomics.
The leaf vasculature plays a key role in solute translocation. Veins consist of at least seven distinct cell types, with specific roles in transport, metabolism, and signaling. Little is known about leaf vascular cells, in particular the phloem parenchyma (PP). PP effluxes sucrose into the apoplasm as a basis for phloem loading, yet PP has been characterized only microscopically. Here, we enriched vascular cells from Arabidopsis leaves to generate a single-cell transcriptome atlas of leaf vasculature. We identified at least 19 cell clusters, encompassing epidermis, guard cells, hydathodes, mesophyll, and all vascular cell types, and used metabolic pathway analysis to define their roles. Clusters comprising PP cells were enriched for transporters, including SWEET11 and SWEET12 sucrose and UmamiT amino acid efflux carriers. We provide evidence that PP development occurs independently from ALTERED PHLOEM DEVELOPMENT, a transcription factor required for phloem differentiation. PP cells have a unique pattern of amino acid metabolism activity distinct from companion cells (CCs), explaining differential distribution/metabolism of amino acids in veins. The kinship relation of the vascular clusters is strikingly similar to the vein morphology, except for a clear separation of CC from the other vascular cells including PP. In summary, our single-cell RNA-sequencing analysis provides a wide range of information into the leaf vasculature and the role and relationship of the leaf cell types.
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LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.
Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.
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Hepatitis B virus X protein (HBx)-mediated immune modulation and prognostic model development in hepatocellular carcinoma.
Hepatitis B virus (HBV) X protein (HBx) is critical in hepatocellular carcinoma (HCC) development, but its influence on tumor immunity and the tumor microenvironment (TME) remains unclear. This study aimed to construct a prognostic model based on HBx-related genes and explore their relationship with immune infiltration and immunotherapy response. Through transcriptome sequencing of our HBx-expressing HepG2 cells and analysis of HCC patient data from the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx), we identified seven HBx-related genes, nuclear VCP-like (NVL), WD repeat domain 75 (WDR75), NOP58 nucleolar protein (NOP58), Brix domain-containing protein 1 (BRIX1), deoxynucleotidyltransferase terminal interacting protein 2 (DNTTIP2), MKI67 FHA domain interacting nucleolar phosphoprotein (NIFK), and ribosome production factor 2 (RPF2), associated with poor prognosis. LASSO Cox regression narrowed these to four key genes (BRIX1, RPF2, DNTTIP2, and WDR75), which were used to develop a prognostic riskscore signature. High-risk patients exhibited lower survival rates, decreased infiltration of anti-tumor immune cells, poorer responses to immunotherapy, and increased immune evasion. Among the four genes, DNTTIP2 showed higher expression in single-cell data, was linked to migration inhibitory factor (MIF) signaling, and may play a pivotal role in shaping an immunosuppressive TME. Elevated DNTTIP2 expression was confirmed in HBx-expressing HepG2 cells and HBV-infected HCC samples. This study highlights a novel HBx-related four-gene prognostic model that predicts clinical outcomes, immune infiltration, and immunotherapy response, offering insights into HCC progression and potential therapeutic targets.
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CD90 Marks a Mesenchymal Program in Human Thymic Epithelial Cells In Vitro and In Vivo.
Thymic epithelium is critical for the structural integrity of the thymus and for T cell development. Within the fully formed thymus, large numbers of hematopoietic cells shape the thymic epithelium into a scaffold-like structure which bears little similarity to classical epithelial layers, such as those observed in the skin, intestine or pancreas. Here, we show that human thymic epithelial cells (TECs) possess an epithelial identity that also incorporates the expression of mesenchymal cell associated genes, whose expression levels vary between medullary and cortical TECs (m/cTECs). Using pluripotent stem cell (PSC) differentiation systems, we identified a unique population of cells that co-expressed the master TEC transcription factor FOXN1, as well as the epithelial associated marker EPCAM and the mesenchymal associated gene CD90. Using the same serum free culture conditions, we also observed co-expression of EPCAM and CD90 on cultured TECs derived from neonatal human thymus in vitro. Single cell RNA-sequencing revealed these cultured TECs possessed an immature mTEC phenotype and expressed epithelial and mesenchymal associated genes, such as EPCAM, CLDN4, CD90 and COL1A1. Importantly, flow cytometry and single cell RNA-sequencing analysis further confirmed the presence of an EPCAM+CD90+ population in the CD45- fraction of neonatal human thymic stromal cells in vivo. Using the human thymus cell atlas, we found that cTECs displayed more pronounced mesenchymal characteristics than mTECs during embryonic development. Collectively, these results suggest human TECs possess a hybrid gene expression program comprising both epithelial and mesenchymal elements, and provide a basis for the further exploration of thymus development from primary tissues and from the in vitro differentiation of PSCs.
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Prognostic and Immunological Value of CTNNB1 in Pancreatic Adenocarcinoma: A Comprehensive NGS and Multicomponent Analysis.
BACKGROUND: To explore the prognostic value and immunomodulatory role of CTNNB1 in pancreatic ductal adenocarcinoma (PDAC), so as to provide evidence for the diagnosis and individualized treatment of PDAC. METHODS: Next-generation sequencing (NGS) was performed to detect 425 cancer-associated genes in PDAC specimens and matched normal pancreatic tissues. Integrative transcriptome analysis based on TCGA, GTEx, and multiple GEO datasets was conducted to identify the differential expression of CTNNB1 between PDAC and normal pancreatic tissues. The Human Protein Atlas (HPA, https://www.proteinatlas.org/) database was used to verify the protein expression and subcellular localization of CTNNB1 in normal pancreatic tissues and pancreatic ductal adenocarcinoma (PDAC) tissues. Single-cell RNA-sequencing and spatial transcriptomic data were further supplemented to delineate its cellular expression landscape. Forest plot, Kaplan-Meier survival analysis, and ROC curve analysis were applied to evaluate the correlations between CTNNB1 expression and prognostic and to verify its prognostic accuracy. The prognostic reliability was further validated using the independent cohort GSE57495. Immune cell infiltration and immune regulatory factors were quantified via TIMER, EPIC, MCPcounter, CIBERSORT, and xCell algorithms, and TMEscore was calculated to predict the responsiveness to immune checkpoint blockade (ICB). Pharmacogenomic datasets including GDSC1, GDSC2, PRISM, and CTRP were utilized to screen optimal candidate drugs for CTNNB1-high PDAC patients. RESULTS: CTNNB1 was significantly overexpressed in PDAC compared with normal pancreatic tissues. HPA immunohistochemistry confirmed CTNNB1 shifts from membranous to cytoplasmic localization in PDAC, indicating activated Wnt signaling and concordant dysregulation at mRNA and protein levels. CTNNB1 protein was mainly localized in malignant epithelial cells of PDAC, with elevated expression also observed in partial immune cell subsets by single-cell sequencing and spatial transcriptome assessment. Upregulated CTNNB1 was significantly linked to unfavorable clinical prognosis in PDAC. ROC analysis verified its good diagnostic efficiency for distinguishing PDAC from peritumoral tissues with favorable sensitivity and specificity. CTNNB1 expression was closely correlated with multiple immune biomarker molecules and ICB therapeutic efficacy; patients with low CTNNB1 expression tended to be more responsive to ICB treatment. Pharmacological prediction revealed that PDAC patients with high CTNNB1 expression exhibited enhanced sensitivity to clofibrate and several other small-molecule compounds. CONCLUSION: CTNNB1 may be remarkably effective as a suitable biomarker for the prognosis prediction of PDAC patients and is closely related to the tumor immune microenvironment. Such an association could provide novel thoughts for the therapy tactics and mechanistic studies toward PDAC.
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Data Mining for Identification of Targets and Repurposed Drugs to Eliminate Persistent Chronic Myeloid Leukaemia Stem Cells: Targeting RAS/RAF Signalling.
BACKGROUND: Persistent leukaemic stem cells (LSCs) in chronic myeloid leukaemia (CML) are insensitive to targeted tyrosine kinase inhibitors (TKIs). Identifying alternative molecular vulnerabilities may offer new therapeutic opportunities. This study aimed to identify active RAS/RAF signalling pathway components in persistent CML-LSCs using publicly available datasets to propose a novel drug combination that could synergise with TKI therapy. METHODS: EMBL-EBI Single Cell Expression Atlas and Stemformatics were used to analyse gene expression within the chosen signalling pathway using DESeq2 analysis in R Studio. Genes that showed statistically significant differences across three comparisons (CML vs. normal; post vs. pre TKI; post TKI vs. normal) were evaluated for gene dependency (Chronos scores), expression profiles, and inhibitor sensitivity using the DepMap platform, with a focus on CML cell lines. Candidate inhibitors were identified using DrugBank. RESULTS: PPP2CA demonstrated broad essentiality with negative Chronos scores consistent with strong gene dependency. Its expression was consistently high, reinforcing its biological relevance in CML. LB-100 was found as a PP2A inhibitor under trial. Sensitivity analysis revealed LB-100 affected 548 cancer cell lines broadly. CONCLUSION: PPP2CA represents a promising therapeutic vulnerability in CML, supported by both strong dependency and consistent expression in myeloid models, while BRAF showed limited relevance outside mutation-driven cancers. Variation in experimental platforms, sample representation, and data integration across public datasets is a recognised study limitation. Nonetheless, LB-100 may provide a novel therapeutic avenue in CML, provided further preclinical functional and clinical validation is performed in patient-derived samples to confirm translational applicability of the findings.
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LCLAT1 as a Potential Biomarker for Predicting Clinical Prognosis, Tumor Immunity, and Therapeutic Efficacy in Hepatocellular Carcinoma.
Lysocardiolipin acyltransferase 1 (LCLAT1) is a lipid acyltransferase that plays an important role in mitochondrial function maintenance and lipid metabolism. Nevertheless, there is scarce research regarding its involvement in tumors. This study sought to investigate the potential role of LCLAT1 in hepatocellular carcinoma (HCC). We obtained HCC expression profile data from The Cancer Genome Atlas and Gene Expression Omnibus databases; verified LCLAT1 expression in HCC by qRT-PCR, Western blotting, and immunohistochemical (IHC) staining; and analyzed the potential pathogenic mechanisms of LCLAT1 in HCC bioinformatically. The associations of the LCLAT1 expression level with HCC patient prognosis, immune escape, and treatment response were also explored using bioinformatics tools and IHC staining. LCLAT1 was significantly overexpressed in HCC cell lines and tissues, and its expression level was positively correlated with histologic grade, tumor status, fibrotic Ishak score, and poor patient prognosis in HCC patients. Gene set enrichment analysis suggested that patients with high LCLAT1 had significant enrichment for methylation-, immune-, and cell proliferation-related pathways. The prognosis of HCC was found to be linked to the DNA methylation status of the five CpG islands within the LCLAT1 gene. Immune infiltration and single-cell level analyses showed that LCLAT1 was closely associated with the tumor microenvironment. Moreover, high LCLAT1 expression may promote immune evasion in HCC, and the abundance of several immune cells correlated with HCC prognosis. Finally, HCC patients with low LCLAT1 responded better to treatment with transarterial chemoembolization, sorafenib, and immune checkpoint inhibitors. LCLAT1 might serve as a potential prognostic biomarker and as a multipathway target involved in the malignant progression of HCC. Importantly, LCLAT1 was related to immune infiltration and could aid in predicting treatment response in HCC.
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Multi-omics and spatial transcriptomics reveal that S100A10 drives CD8+ T-cell exhaustion and immune evasion in hepatocellular carcinoma through cPLA2-5-LOX-mediated arachidonic acid metabolism and ferroptosis.
Immune evasion in hepatocellular carcinoma (HCC) represents a major biological barrier limiting the efficacy of immunotherapy, yet its molecular basis remains incompletely understood. Increasing evidence indicates that tumor metabolic reprogramming and ferroptosis-related signaling play critical roles in shaping an immunosuppressive tumor microenvironment (TME); however, the specific regulatory factors involved remain unclear. This study aims to systematically elucidate the functional role of S100 calcium-binding protein A10 (S100A10) in immune evasion in HCC, with a particular focus on the molecular mechanisms by which S100A10 regulates CD8+ T-cell exhaustion through arachidonic acid (AA) metabolism and ferroptosis, as well as its potential therapeutic implications. To this end, data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort are integrated to analyze the expression patterns of S100A10, its prognostic value, and its association with the immune microenvironment. S100A10 overexpression and knockout models are established in HCCLM3 and MHCC97L cell lines, and S100A10-mediated metabolic pathway reprogramming is characterized using transcriptomic profiling, untargeted metabolomics, and ferroptosis-related functional assays. In parallel, single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics are employed to delineate the cell-type specificity and spatial distribution of S100A10. Furthermore, human CD8+ T-cell co-culture systems and orthotopic mouse HCC models are used to evaluate the impact of S100A10 on immune function and responsiveness to anti-programmed cell death protein 1 (anti-PD-1) therapy. The results demonstrate that S100A10 is significantly upregulated in HCC and is closely associated with poor prognosis and an immunosuppressive state. Mechanistically, S100A10 activates cytosolic phospholipase A2-arachidonate 5-lipoxygenase (cPLA2-5-LOX)-mediated AA oxidative metabolism, leading to the accumulation of lipid peroxidation products and ferroptosis-associated signals, thereby driving CD8+ T-cell exhaustion and promoting immune evasion. Significantly, inhibition of S100A10 reshapes the tumor immune microenvironment (TIME) and enhances the therapeutic efficacy of anti-PD-1 treatment. Collectively, these findings identify S100A10 as a critical regulator of metabolic-immune coupling in HCC and provide a theoretical basis for combinatorial strategies targeting metabolism and immunotherapy.
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Multi-omic analysis reveals the role of coagulation factor family genes and their predictive value for immune checkpoint inhibitors efficacy in gastric cancer.
Coagulation factor family genes play a pivotal role in tumor progression and immune modulation, but their relationship with tumor microenvironment and immunotherapy response in gastric cancer remains unclear. This study utilized single-cell and The Cancer Genome Atlas datasets to investigate the clinical and immune relevance of coagulation factor family genes in gastric cancer. Based on coagulation factor family genes, a risk score was constructed. The high-risk group was found to have a worse prognosis and exhibited an immunosuppressive state. Coagulation factor V (F5) emerged as a central gene, correlating negatively with immune cell recruitment and cytotoxic activity within the tumor immune cycle. In vitro knockdown experiments and in vivo 615 mouse liver metastasis models showed that F5 enhances metastasis and reduces CD8+ T cell infiltration. Immunohistochemistry (n = 64) and flow cytometry (n = 31) further confirmed F5 immunomodulatory effects. Among 37 patients receiving neoadjuvant immunotherapy, low F5 expression was associated with improved response. Finally, Gastrodin was identified via virtual screening and molecular dynamics as a potential small-molecule inhibitor of F5. These findings indicate that coagulation factor family genes, particularly F5, promote gastric cancer progression and immune evasion, and that targeting F5 may enhance immunotherapeutic outcomes.