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PubMed2026

Integrative Pan-Cancer Characterization of lncRNA UPK1A-AS1 and Its Role in Hypoxia-Associated Sorafenib Resistance in Hepatocellular Carcinoma.

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of tumor initiation and progression through transcriptional and posttranscriptional mechanisms. UPK1A antisense RNA 1 (UPK1A-AS1), a cancer-associated lncRNA, has been reported to participate in oncogenic processes; however, its overall landscape across human malignancies and its biological role in therapy resistance remain poorly understood. Given the increasing importance of identifying functional lncRNAs with prognostic and therapeutic potential, this study presents a comprehensive multiomics characterization of UPK1A-AS1 and its experimental validation in hepatocellular carcinoma (HCC). We integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), the cancer immunology data engine (CIDE), and the cBioPortal for cancer genomics (cBioPortal) to systematically assess its expression pattern, genomic alterations, clinical significance, and immunological associations. Our analyses revealed that UPK1A-AS1 is significantly upregulated in multiple tumor types, with copy-number amplification as the predominant genomic alteration driving its overexpression. Elevated UPK1A-AS1 expression was correlated with advanced disease stage, poor differentiation, immune exclusion, and unfavorable prognosis, supporting its potential as a cancer type-dependent biomarker. In parallel, functional studies demonstrated that hypoxia transcriptionally induces UPK1A-AS1 in HCC, where it promotes sorafenib resistance by suppressing apoptosis. Silencing UPK1A-AS1 restored apoptotic and enhanced sorafenib efficacy both in vitro and in vivo. Collectively, our findings suggest that UPK1A-AS1 is a hypoxia-inducible oncogenic lncRNA that plays dual roles in cancer, with cancer type-dependent associations with progression and immune modulation across malignancies and mechanistically mediating hypoxia-associated drug resistance in HCC.

Humans↗

PubMed2026

IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.

BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.

IL1RAP↗

PubMed2026

Virtual Tumors Enable Prediction of Personalized Therapeutic Combinations for Non-Small Cell Lung Cancer.

UNLABELLED: The disease burden from non-small cell lung cancer (NSCLC) adenocarcinoma is substantial, with a million new cases diagnosed globally each year and a 5-year survival rate of less than 20%. The lack of therapeutic options personalized to individual patients leads to high variation in survival. The combination of patient stratification with personalized treatment has the potential to improve outcomes; however, the variation in mutations found in patients with NSCLC adenocarcinoma makes experimentally determining treatment combinations time-consuming and expensive. In this study, we developed an interpretable mechanistic model to decipher complex signaling interplay and guide personalized therapy in NSCLC adenocarcinoma. This "virtual tumor" model encompassed key tumor-intrinsic oncogenic signaling pathways for efficiently predicting rational drug-drug and drug-radiotherapy combination therapies in NSCLC. Diverse genetic profiles were simulated for testing more than 10,000 therapeutic strategies to identify optimal approaches to overcome resistance mechanisms specific to genetic profiles and p53 status. The virtual tumor model reproduced drug additivity screens, predicted radiosensitizing genes validated in a CRISPR screen, and identified 53BP1 as a potential drug target that improved the therapeutic window during radiotherapy. A 19-gene signature derived from the virtual tumor framework stratified patients most likely to benefit from radiotherapy, which was validated using The Cancer Genome Atlas (TCGA) data. These results show the utility of virtual tumors to predict effective therapeutic combinations and present a computational resource for large-scale screening of personalized therapies to guide clinical decision-making in patients with NSCLC. SIGNIFICANCE: A computational framework that simulates thousands of personalized treatment strategies offers a scalable, cost-effective way to tailor therapies and improve outcomes for patients with genetically diverse NSCLC.

Humans↗

PubMed2026

Deficiency in POLE Exonuclease Causes Synthetic Lethality in Highly Aneuploid Cancer Cells.

UNLABELLED: Aneuploidy is a hallmark of cancer and is associated with drug resistance and poor clinical outcomes across diverse cancer types. However, no therapies have been clinically established to target highly aneuploid tumors. By analyzing nearly half a million tumor samples subjected to comprehensive genomic profiling, we identified a striking mutual exclusivity between POLE exonuclease domain mutations and high aneuploidy burden. This observation was independently validated using data from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE). Probabilistic modeling revealed that the elevated quantity and unique spectrum of mutations induced by POLE exonuclease deficiency increase the likelihood of inactivating essential genes on chromosome arms harboring losses, leading to a synthetic lethal phenotype in highly aneuploid cells. Functional experiments demonstrated that POLE exonuclease activity is essential for the viability of highly aneuploid cancer cell lines but dispensable in diploid cells. These findings suggest that selective inhibition of POLE exonuclease activity may represent a promising therapeutic strategy for targeting highly aneuploid tumors. SIGNIFICANCE: An integrated approach using large-scale genomic analyses, probabilistic modeling and functional validation identified POLE exonuclease as a potential synthetic lethal target to overcome cancer aneuploidy.

Humans↗

PubMed2026

Multinucleated Giant Cells in Human Pancreatic Cancer Are a Distinct Macrophage Population Undergoing a DNA Damage Response and Associated with an Aggressive Tumor Microenvironment.

Macrophages (Mϕ) constitute a dominant and functionally diverse immune population within the microenvironment of pancreatic ductal adenocarcinoma (PDAC), yet how Mϕ heterogeneity contributes to the tumor remains poorly defined. In an institutional cohort of 145 PDAC specimens, we identified a population of multinucleated giant cells (MGC) of Mϕ origin, an entity previously described in chronic inflammation but rarely in cancer. CD68+ MGCs were present in 28% of tumors, enriched in squamous, nonglandular regions, and more frequent after neoadjuvant chemotherapy. By integrating spatial transcriptomics and quantitative imaging, we defined the features of these cells, which, compared with MGCs in nonneoplastic inflammatory lesions, lacked canonical polarization markers (HLA-DR and CD163) and displayed a distinctive transcriptional program characterized by upregulation of the POLR2K, TUBA8, COX5B, and VDAC1 genes, which encode proteins involved in DNA repair, oxidative stress, and MYC signaling. Spatial analyses revealed activation of hypoxia and extracellular matrix-remodeling pathways in MGC-associated niches, and experimental hypoxia promoted MGC formation in vitro. Consistent with these data, we found that in the The Cancer Genome Atlas (TCGA) Pancreatic Adenocarcinoma (PAAD) dataset a Mϕ MGC gene signature was enriched in the squamous PDAC subtype and correlated with poorer overall survival (P = 0.018). Morphometric and immunofluorescence analyses further showed increased 53BP1+Ki67+ nuclei and nuclear atypia in MGCs, indicating ongoing proliferation despite DNA damage. Together, these data identify MGCs of Mϕ origin as an immune cell state shaped by hypoxia and stress signaling, associated with aggressive tumor phenotypes, and potentially exploitable as an immune classifier in PDAC.

Humans↗

PubMed1991

Longitudinal differentiation of the human Yq heterochromatin as revealed by the restriction enzyme TaqI.

The restriction endonuclease TaqI cleaves DNA at TCGA sites which are very common in human satellite DNAs. However, this enzyme was not used successfully up to now to digest constitutive heterochromatin of human chromosomes, where those highly repetitive DNAs are preferentially located. In this work, we show that TaqI is able to cut and extract DNA from the major heterochromatic regions on chromosomes 1, 9, 15, and 16 which appear as unstained gaps. Yq heterochromatin displays moderate digestion along its entire length but a middle region can be distinguished which is usually more affected. Complete digestion of Yq heterochromatin can be achieved when this block has been previously undercondensed by treating cell cultures with the cytidine analog, 5-azacytidine. Thus, it may be deduced that some factors related to chromatin organization might be involved in the action of TaqI. These results come to reinforce previous data about heterogeneity of Yq heterochromatin, and allow us to subdivide it into three different regions according to their differential response to TaqI digestion.

Base Sequence↗

PubMed1994

Regulation of the alpha 1-antitrypsin gene and a disease-associated mutation in a related enhancer sequence.

Ten years ago a search was initiated for DNA variation in the alpha-1-antitrypsin gene (alpha 1-AT) to determine whether there were mutations more commonly associated with patients who had chronic obstructive airways disease (COAD) than with healthy individuals. Using the conventional approach of Southern blotting and searching for restriction fragment length polymorphisms, we identified a potentially useful polymorphism that resulted in the loss of a recognition site for the restriction enzyme, Taq I. The polymorphism occurred in about 17% of patients with COAD and about 5% of the general population (p = 0.0016). The normal sequence in the 3' flanking region of the alpha 1-antitrypsin gene had to be characterized, as it was not known. On the basis of homology, a number of closely clustered sequence motifs demonstrating the characteristics of an enhancer were identified that would potentially increase the transcription and expression of alpha 1-antitrypsin. The normal Taq I sequence occurred in a motif that demonstrated homology to a DNA sequence for octamer transcription factors. The mutation was characterized by in vitro amplification of the region and direct sequencing as a G to A transition (Taq I site TCGA < TCAA). Specific binding of nuclear proteins by gel-shift analysis and DNase I footprinting and increased in vivo transcriptional activity were demonstrated by transfection of mammalian cells containing DNA fragments corresponding to the region of interest. In contrast, the mutant sequence demonstrated loss of binding to nuclear proteins and reduced transcriptional activity. The latter finding was not confined to tissues known to express alpha 1-antitrypsin.(ABSTRACT TRUNCATED AT 250 WORDS)

Base Sequence↗

PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗

PubMed2026

Identification of a necroptosis-related lncRNA prognostic signature and the hub RBP HNRNPK in esophageal squamous cell carcinoma.

ObjectiveEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with poor prognosis. Necroptosis is important for tumor immunity, but its role in ESCC remains unclear. This retrospective bioinformatics study aimed to investigate the prognostic value of necroptosis-related long non-coding RNAs (lncRNAs) and to identify key lncRNA-binding proteins (RBPs) in ESCC patients.MethodsRNA transcriptome and clinical data of ESCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Necroptosis-related lncRNAs were identified through correlation analysis with necroptosis-related genes, subjected to consensus cluster analysis, and used to construct a prognostic risk model via least absolute shrinkage and selection operator (LASSO) regression. The hub RBP was experimentally validated by quantitative polymerase chain reaction (qPCR) using 30 pairs of ESCC and adjacent normal tissues from patients who underwent surgical resection.ResultsA total of 30 necroptosis-related lncRNAs were significantly correlated with overall survival (OS). The upregulated lncRNAs in the risk model were associated with high immune scores, innate immune cell infiltration, cluster 2 classification, and advanced T-stage disease (p < 0.05). Three hub RBPs (HNRNPA1, HNRNPC, and HNRNPK) were identified through protein-protein interaction network analysis. qPCR confirmed that HNRNPK was significantly overexpressed in ESCC tissues compared to adjacent normal tissues (p < 0.05).ConclusionsThe necroptosis-related lncRNA risk model is an independent prognostic factor for ESCC patients. HNRNPK was identified as a hub RBP significantly overexpressed in ESCC tissues. We hypothesize that HNRNPK may promote tumor progression through regulating proto-oncogene expression or modulating the immune microenvironment, though this requires further mechanistic validation.

Humans↗

PubMed2026

Integrative genetic and transcriptomic analyses prioritize CDC16 as a candidate marker for gastric cancer.

BackgroundGastric cancer (GC) remains a major cause of cancer-related mortality, and biomarkers for early detection are needed.MethodsStomach and blood expression quantitative trait loci were integrated with two GC genome-wide association studies using Mendelian randomization (MR), Bayesian colocalization, and summary-data-based MR/heterogeneity in dependent instruments (SMR/HEIDI) testing. Bulk and single-cell transcriptomic analyses characterized candidate expression and lesion-associated patterns. CDC16 protein expression was evaluated by immunohistochemistry in 53 paired GC and non-neoplastic tissues, followed by paired and exploratory receiver operating characteristic analyses.ResultsMR prioritized PILRB, CDC16, and GABPB1-AS1; SMR/HEIDI provided complementary support, while colocalization for CDC16 and GABPB1-AS1 was suggestive and model-dependent. Bulk-tissue CDC16 abundance was higher in GC, but the modest TCGA-STAD tumor-normal difference (log2FC = 0.210, FDR = 0.019) was attenuated after proliferation adjustment (log2FC = -0.002, FDR = 0.987), indicating close coupling with proliferative activity. Single-cell analysis localized CDC16 predominantly to epithelial populations, and the proportion of CDC16-detectable epithelial cells increased across lesion categories (ρ = 0.735; permutation P = 0.031). CDC16 H-scores were higher in GC than in paired non-neoplastic tissues (161.15 ± 45.11 vs 102.15 ± 54.50; P < 0.001), with higher cancer-tissue scores in 41 of 53 cases. Exploratory AUC was 0.794 (95% CI, 0.704-0.874; sensitivity, 66.0%; specificity, 79.2%).ConclusionsConvergent genetic, transcriptomic, and protein-level evidence prioritizes CDC16 as a GC-associated candidate tissue marker whose expression is closely linked to proliferative activity. Prospective validation in independent cohorts, including appropriate disease controls and blood-based evaluation, is warranted.

Stomach Neoplasms↗

PubMed2026

Integrated transcriptomic and immunogenomic analysis unravels the immunological functions and prognostic landscape of WD repeat domain 76.

BackgroundWD Repeat Domain 76 (WDR76) plays a potential role in cellular regulation; however, its comprehensive landscape across human malignancies and its specific biological function in hepatocellular carcinoma (HCC) remain largely unexplored.MethodsWe conducted a systematic pan-cancer analysis utilizing multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) atabases to evaluate WDR76 expression, subcellular localization, and its correlation with clinicopathologic features, genomic instability, and immune infiltration. Diagnostic and prognostic values were assessed via Receiver operating characteristic (ROC) and Kaplan-Meier analyses. Furthermore, the functional role of WDR76 in HCC was validated in vitro using Hep-3B and Huh7 cell lines through siRNA-mediated knockdown, followed by CCK-8, wound-healing, and transwell assays.ResultsWDR76 was significantly upregulated in the majority of tumor types, including LIHC, LUAD, and COAD, while exhibiting nuclear localization. Elevated WDR76 expression correlated with advanced tumor staging, metastasis, and poor clinical outcomes across multiple cohorts, particularly in ACC, KIRP, and LIHC. ROC analysis highlighted its exceptional diagnostic precision in cancers such as GBM and LIHC. Immunologically, WDR76 expression was intricately linked to immune cell infiltration, immune checkpoint markers, and genomic instability parameters, suggesting a role in shaping the tumor microenvironment. Drug sensitivity profiling revealed that high WDR76 levels correlate with resistance to specific chemotherapeutic agents. Experimentally, silencing WDR76 in HCC cells significantly suppressed cell proliferation, migration, and invasion capabilities.ConclusionOur study establishes WDR76 as a robust pan-cancer prognostic biomarker and a potential immunotherapeutic target. Specifically, we provide experimental evidence that WDR76 functions as an oncogenic driver in liver cancer, promoting malignant phenotypes and offering a novel avenue for targeted therapeutic intervention.

Humans↗

PubMed2026

First-in-Class Small Molecule Inhibitor of Oncogene AVIL in Glioblastoma.

Glioblastoma multiforme (GBM) is the most prevalent and aggressive malignant primary brain tumor, marked by rapid growth, extensive invasiveness, and a median survival of only ∼15 months despite current multimodal therapy. To identify new therapeutic vulnerabilities, we investigated the actin-regulatory protein AVIL, previously implicated through a MARS-AVIL gene fusion in rhabdomyosarcoma. Comprehensive genomic and transcriptomic analyses across REMBRANDT, TCGA, and CGGA datasets revealed recurrent AVIL amplification and consistently elevated AVIL expression in GBM compared with normal brain tissue. AVIL was overexpressed across all GBM molecular subtypes and glioma stem cell (GSC) states but was nearly undetectable in normal astrocytes, neural stem cells, and brain tissues. Functional studies demonstrated that AVIL is both necessary and sufficient for glioma genesis: AVIL silencing eradicated GBM cells in vitro and suppressed xenograft growth in vivo, while AVIL overexpression enhanced proliferation, migration, and transformation. Mechanistically, AVIL drives tumor progression through actin cytoskeleton remodeling and activation of the FOXM1-LIN28B oncogenic pathway. Using a small molecule microarray screen, we identified a selective AVIL-binding compound (compound A) that potently inhibited GBM cell growth with minimal toxicity to normal astrocytes. Gene expression changes induced by compound A mirrored those following AVIL knockdown, indicating on-target activity. Compound A demonstrated robust antitumor efficacy in multiple preclinical GBM models, including orthotopic xenografts, GSC-derived tumors, patient-derived xenografts, and temozolomide-resistant GBM with favorable pharmacokinetics and blood-brain barrier penetration. The minimal AVIL expression in normal tissues and lack of phenotype in AVIL-deficient mice underscore its potential as a low-toxicity therapeutic target. Together, these findings establish AVIL as a critical oncogenic driver in GBM and introduce a first-in-class AVIL inhibitor with strong translational promise for precision neuro-oncology.

Glioblastoma↗

PubMed2026

RCoxNet: A Deep Learning Framework Integrating Random Walk with Restart, Mutation, and Clinical Data for Cancer Survival Prediction.

Accurate survival prediction in cancer remains challenging due to the sparsity of somatic mutation profiles and the failure of existing models to capture higher-order gene-gene dependencies. Network diffusion methods such as Random Walk with Restart (RWR) can propagate mutation signals across protein-protein interaction (PPI) networks to address sparsity, yet their integration within a deep learning Cox survival framework has not been comprehensively benchmarked across multiple cancer cohorts. We present RCoxNet, a deep learning framework that maps somatic mutation profiles onto a ConsensusPathDB-derived PPI network via RWR, selects prognostic genes by log-rank filtering, and processes network-informed mutation scores through three fully connected hidden layers feeding into a Cox proportional hazards output. RCoxNet was evaluated on The Cancer Genome Atlas (TCGA) cohorts for four cancer types (breast invasive carcinoma [BRCA], lung adenocarcinoma [LUNG], glioblastoma multiforme [GBM], and ovarian serous cystadenocarcinoma [OV]) using 20 independent random splits. The model achieved mean C-index values of 0.807 ± 0.044 (BRCA), 0.750 ± 0.039 (LUNG), 0.704 ± 0.041 (GBM), and 0.668 ± 0.036 (OV), consistently outperforming DeepSurv, Cox-nnet, SurvivalNet, Cox Elastic-Net (Cox-EN), and DeepHit, with statistically significant gains over Cox-EN, Cox-nnet, SurvivalNet, and DeepHit across the majority of cohorts. RCoxNet demonstrates that embedding sparse mutation profiles into a PPI network context substantially improves cancer survival prediction and yields biologically interpretable prognostic features relevant to precision oncology.

cancer survival prediction↗

PubMed2025

TMSB10 drives prostate cancer aggressiveness via immune microenvironment regulation.

Thymosin β10 (TMSB10) has emerged as a key player in the progression of prostate cancer, significantly influencing the tumor immune microenvironment. Pan-cancer analysis from The Cancer Genome Atlas (TCGA) revealed that TMSB10 is upregulated across multiple cancer types, particularly in prostate cancer, where high TMSB10 expression correlates with poorer patient outcomes. Functional assays using prostate cancer cell lines LNCaP and DU145 showed that TMSB10 silencing suppresses cell proliferation, migration, and invasion, while overexpression enhances these oncogenic processes. Furthermore, co-culture experiments demonstrated that TMSB10 overexpression skews macrophage polarization, decreasing the population of M1-type macrophages while increasing M2-type macrophages. This shift reduces immune cell cytotoxicity and alters cytokine secretion, highlighting TMSB10's role in immune evasion. These findings establish TMSB10 as a pivotal factor in prostate cancer biology, promoting tumor aggressiveness and modulating the immune response within the tumor microenvironment. TMSB10 presents a promising therapeutic target for prostate cancer, offering new avenues for treatments aimed at altering the tumor immune landscape. This research also provides a foundation for further exploration of TMSB10's role in other cancers.

Male↗

PubMed2025

SNORA47 affects stemness and chemotherapy sensitivity via EBF3/RPL11/c-Myc axis in luminal A breast cancer.

Chemotherapy sensitivity is an important factor that restricts the prognosis of breast cancer, and breast cancer stem cells (BCSCs) are the root cause of chemotherapy sensitivity. SNORA47, a member of the small nucleolar RNAs, has not been documented in the context of breast cancer, although it has been reported in lung cancer. In this study, high SNORA47 expression was linked to unfavorable survival outcomes among patients with Luminal A breast cancer in The Cancer Genome Atlas (TCGA). Among Luminal A patients, an elevated expression of SNORA47 correlated with high TNM stage (P = 0.049). SNORA47 was strongly associated with breast cancer stemness phenotype and tumor sensitivity in vivo and in vitro. Our findings demonstrated that SNORA47, through its interaction with early B-cell factor 3(EBF3), facilitated the translocation of ribosomal protein L11(RPL11), which as a modulator that subsequently regulates the expression levels of the oncogene c-Myc. These discoveries provided novel insights into the molecular mechanisms of breast cancer progression and suggested potential therapeutic targets for overcoming drug sensitivity by disrupting the SNORA47-EBF3-RPL11 axis.

Humans↗

PubMed2025

The MYC/TXNIP axis mediates NCL-Suppressed CD8+T cell immune response in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a deadly malignancy with immune evasion playing a key role in tumor progression. Glucose metabolism is crucial for T cell function, and the nucleolar protein NCL may influence T cell glucose metabolism. This study aims to investigate NCL's role in T cell glucose metabolism and immune evasion by lung adenocarcinoma cells. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we analyzed cell clustering, annotation, and prognosis. In vitro experiments involved manipulating NCL expression in CD8+ T cells to study immune function and glucose metabolism. In vivo studies using an orthotopic transplant mouse model monitored NCL's impact on CD8+ T cell glucose metabolism and anti-tumor immune function. RESULTS: NCL was associated with T cell dysfunction and glucose metabolism. NCL silencing enhanced CD8+ T cell glucose metabolism, cytotoxicity, and infiltration, while NCL overexpression had the opposite effect. NCL overexpression relieved MYC-mediated transcriptional repression of TXNIP, reducing CD8+ T cell glucose metabolism. In vivo, NCL inhibited CD8+ T cell glucose metabolism through the MYC/TXNIP axis, hindering anti-tumor immune function. CONCLUSIONS: NCL overexpression suppresses CD8+ T cell glucose metabolism and anti-tumor immune function, promoting lung adenocarcinoma progression via the MYC/TXNIP axis.

CD8-Positive T-Lymphocytes↗

PubMed2025

ALDOC and PGK1 coordinately induce glucose metabolism reprogramming and promote development of colorectal cancer.

Colorectal cancer (CRC) remains a significant health challenge globally, demanding a comprehensive understanding of its molecular underpinnings for effective management. In this study, we investigated the role of Aldolase C (ALDOC), a glycolytic enzyme, in CRC pathogenesis. Transcriptomic analysis of CRC tissues from The Cancer Genome Atlas (TCGA) revealed a substantial upregulation of ALDOC, correlating with adverse clinical outcomes. Immunohistochemical (IHC) staining of locally collected patient-derived tissues corroborated these findings, demonstrating elevated ALDOC expression in tumor tissues, particularly in advanced stages. Functional studies elucidated the regulatory role of ALDOC in CRC cell phenotypes. ALDOC knockdown significantly inhibited cell proliferation, induced apoptosis, arrested cell cycle progression, and suppressed cell migration in vitro. Moreover, in vivo studies using xenograft models confirmed that ALDOC knockdown attenuated tumor growth. Mechanistically, ALDOC was found to interact with hypoxia-inducible factor 1 alpha (HIF1A) and enhance its transcriptional activity on phosphoglycerate kinase 1 (PGK1), a key glycolytic enzyme. Dual-luciferase reporter assays and chromatin immunoprecipitation experiments validated the ALDOC-mediated transcriptional activation of PGK1. Further functional rescue experiments revealed a synergistic interplay between ALDOC and PGK1 in regulating CRC cell phenotypes. Additionally, ALDOC was implicated in promoting aerobic glycolysis in CRC cells, potentially through PGK1 regulation. Collectively, our findings unveil ALDOC as a critical regulator of CRC pathogenesis, offering insights into its potential as a therapeutic target and highlighting the ALDOC/PGK1 axis as a promising avenue for further investigation in CRC.

Humans↗

PubMed2026

LARS promotes hepatocellular carcinoma progression via the PI3K/AKT/mTOR pathway and interaction with RPS5, and serves as a prognostic biomarker.

BACKGROUND: Hepatocellular carcinoma (HCC) caused many cancer deaths around the world. Its progression involves complex mechanisms, creating an urgent need to identify new therapeutic targets. Leucine-tRNA synthetase (LARS) is a key enzyme for protein synthesis, but its specific role and mechanism in HCC are not well understood. PURPOSE: This research aims to investigate the biological function, molecular mechanism, and clinical relevance of the LARS gene in HCC progression, to assess its potential as a treatment target. METHODS: LARS expression was assessed in HCC cell lines (PLC-PRF-5, HCC-LM3) and in mouse subcutaneous tumor models using siRNA and adeno-associated virus (AAV). Techniques including Cell Counting Kit-8(CCK-8), colony formation, EdU, Transwell, wound healing, and flow cytometry were used to measure cell proliferation, migration, invasion, and apoptosis. RNA-seq, proteomics (TMT), western blot, co-immunoprecipitation (Co-IP) with mass spectrometry, molecular docking, and molecular dynamics simulation were employed to study the affected signaling pathway (PI3K/AKT/mTOR) and interacting protein (RPS5). The TCGA (The Cancer Genome Atlas) database and UALCAN platform were used to analyze links between LARS expression and clinicopathological features or prognosis in HCC patients. RESULTS: Reducing LARS expression significantly inhibited the proliferation, colony formation, migration, and invasion of HCC cells, while promoting apoptosis. In mice, LARS knockdown markedly slowed tumor growth. Mechanistic studies showed that reducing LARS expression levels affected the PI3K/AKT/mTOR signaling pathway and led to decreased levels of the key interacting protein RPS5. Overexpressing RPS5 partly reversed the proliferation inhibition caused by LARS depletion. Molecular docking and dynamics simulations suggested that the environmental contaminant triphenyl phosphate (TPP) might bind to the LARS protein. Clinical data analysis revealed that LARS expression is higher in HCC tissues. High LARS expression was significantly associated with shorter overall survival (OS) in patients and correlated positively with various clinical features like tumor stage, grade, and TP53 mutation status. CONCLUSION: LARS helped HCC become worse by affecting the PI3K/AKT/mTOR pathway and working with RPS5. High LARS meant a worse outcome for patients. This suggested LARS could be used to predict disease or as a treatment target in HCC.

Carcinoma, Hepatocellular↗