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PubMed2026

Stratifying lung adenocarcinoma: a novel prognostic model based on mitochondrial outer membrane permeabilization activity.

UNLABELLED: Mitochondrial outer membrane permeabilization (MOMP) is a core apoptotic regulatory event that dictates mitochondrial integrity, where full activation drives cell death and sublethal dysregulation contributes to tumor genomic instability. We used the Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD) as the training cohort and the Gene Expression Omnibus dataset GSE42127 as the validation cohort to identify prognostic genes related to MOMP activity in lung adenocarcinoma (LUAD) and to evaluate their potential biological significance. By intersecting MOMP-related genes with differentially expressed genes, combined with survival analysis, Mendelian randomization analysis, and 101 machine-learning algorithm combinations, seven prognostic genes, namely BIRC5, PSMD11, TNFRSF13C, YWHAZ, YWHAG, CYCS, and LTB, were identified. Next, an optimal prognostic model was constructed based on the gradient boosting machine (GBM) algorithm. Based on the risk score, LUAD patients were stratified into high- and low-risk groups, and patients in the high-risk group exhibited poorer overall survival in both the training and validation cohorts. Furthermore, a nomogram integrating the risk score and clinicopathological factors was developed and showed favorable predictive performance for 1-, 3-, and 5-year survival. Meanwhile, functional and immune analyses revealed that the high-risk group was enriched in DNA replication-related pathways and demonstrated a higher tumor mutation burden (TMB). Correlation analysis indicated that TNFRSF13C was positively correlated with activated B cells, whereas BIRC5 was negatively correlated with eosinophils, suggesting that MOMP-related genes might be involved in remodeling the immune microenvironment of LUAD. Drug sensitivity analysis showed differences in predicted half-maximal inhibitory concentration (IC50) values between the risk groups, suggesting the potential value of this model in assisting therapeutic stratification. Single-cell RNA sequencing (scRNA-seq) further identified T lymphocytes as a key cell type, with numerous prognostic genes exhibiting differential expression in T cells or dynamic changes during differentiation. We suggest that the MOMP-related signature established in this study may provide a reference for prognostic stratification in LUAD and offers candidate prognostic genes for subsequent experimental and clinical validation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13205-026-05058-6.

Lung adenocarcinoma↗

PubMed1996

Sequence specificity in CpG mutation hotspots.

CpG dinucleotides are efficiently methylated in vertebrate genomes except in the CpG islands having a high C+G content. Methylated CpGs are the single most mutated dinucleotide. Sequences surrounding disease causing CpG mutation sites were analyzed from locus-specific mutation databases. Both tetra- and heptanucleotide analyses indicated clear overall sequence preference for having pyrimidines 5' and purines 3' to the mutated 5-methylcytosine. The most mutated tetranucleotides are TCGA and TCGG, the former being also a frequent restriction and modification site. The results will help in elucidating the still controversial mutation mechanism of CpG doublets.

Agammaglobulinaemia Tyrosine Kinase↗

PubMed1992

Adenovirus VARNA1 gene B block promoter element sequences required for transcription and for interaction with transcription factors.

We constructed mutants with a deletion of either half of the 18 base-pair B block palindrome in the VARNA1 gene, mutants with different intra-palindromic spacings, a complete set of mutants with single base substitutions, and mutants with double and triple base substitutions in the palindrome. The transcription efficiencies of these mutants were determined in human KB cell-free cytoplasmic S100 extracts. The relative competing strength of each mutant, as determined by a sequential competition experiment, was used to assess each mutant's ability to sequester factors into formation of a stable preinitiation complex. The ability of each mutant to assemble transcriptionally active preinitiation complexes was also determined by direct transcription of the isolated complexes. Finally, the ability of each mutant to interact with the transcription factor(s) TFIIIC and form a distinct gel-resolved complex was also determined. From the results of the above assays, we concluded that the two seemingly identical halves of the palindrome did not contribute equally to transcription, or to assembly of the functional preinitiation complex, nor to interaction with TFIIIC. The anterior half (B1) of the B block palindrome, which is proximal to the A block promoter element, played a stronger role in transcription and in assembly of the functional preinitiation complex than the posterior half (B2) of the palindrome. Consistent with this observation, the point mutations in four base-pairs, GTTC, from +60 to +63 in the anterior half of the B block palindrome, has the most severe effect on transcription. In contrast, we showed that the central sequence and the posterior half (B2) played a stronger role than the anterior half (B1) of the B block palindrome in the interaction of the promoter with TFIIIC. This was corroborated by the observation that base substitutions in the central four base-pair sequence of the palindrome, TCGA, from +62 to +65, had the most severe effect on interaction with TFIIIC, and that mutations in most of the sequences in the posterior half of the B block palindrome had more drastic effects than mutations in the anterior half of the palindrome in this interaction. Furthermore, the spacing between the two halves of the B block palindrome had a drastic effect on the overall transcription efficiency and the interaction of the promoter with TFIIIC, suggesting that the interaction between the two halves of the B block palindrome is not only essential, but also synergistic for the interaction with TFIIIC as well as the assembly of a transcriptionally active preinitiation complex and efficient transcription.

Adenoviruses, Human↗

PubMed1980

Single-strand and double-strand cleavage at half-modified and fully modified recognition sites for the restriction nucleases Sau3a and Taqi.

The influence of cytosine methylation on the cleavage of DNA by the restriction nucleases Sau3A and TaqI has been investigated. Bovine satellite DNA fragments containing a GATCGA sequence, i.e. a Sau3A site overlapping with a TaqI site have been used in this study. The methylation of these fragments has been determined by sequence analysis. It has been found that a TaqI site (TCGA) methylated at cytosine in both DNA strands is still sensitive to double-strand cleavage. A Sau3A site (GATC), however, is rendered resistant to double-strand cleavage by methylation of a single cytosine. Fragments containing the "half-modified" Sau3A site are nicked in the unmethylated DNA strand. It has been shown by sequence analysis of nicked DNA that the single-strand break occurs at the same position which is cleaved in unmodified DNA.

Animals↗

PubMed1992

The corrected nucleotide sequences of the TaqI restriction and modification enzymes reveal a thirteen-codon overlap.

The nucleotide sequence of the genes encoding methyltransferase TaqI (M.TaqI) and restriction endonuclease TaqI (R.TaqI) with the recognition sequence, TCGA, were analyzed in clones isolated from independent libraries. The genes, originally reported as 363 and 236 codons long [Slatko et al., Nucleic Acids Res. 15 (1987) 9781-9796] were redetermined as 421 and 263 codons long, respectively. The C terminus of the taqIM gene overlaps the N terminus of the taqIR gene by 13 codons, as observed with the isoschizomeric TthHB8I restriction-modification system [Barany et al., Gene 112 (1992) 13-20]. Removal of the overlapping codons did not interfere with in vivo M.TaqI activity. We postulate the overlap plays a role in regulating taqIR expression.

Amino Acid Sequence↗

PubMed1994

Evidence for adenine methylation within the mouse myogenic gene Myo-D1.

Previous studies have indicated that there may be uncleavable TaqI sites (TCGA) within the mouse myogenic gene, Myo-D1. Fragments of DNA bearing most of the presumed insensitive TaqI sites have been reproduced using PCR. The presence of each of the originally uncleavable TaqI sites has been confirmed and each TaqI site has been shown to be sensitive to TaqI hydrolysis in PCR-synthesized genomic DNA. Since TaqI is inhibited by methylation of the adenine residue within its recognition sequence (but not by cytosine methylation), it is suggested that specific adenine bases are methylated in the coding region of Myo-DI and maintained throughout cell division. The same TaqI recognition sequences are insensitive to digestion in genomic DNA isolated from various mouse tissues including fetus, regenerating skeletal muscle and a myogenic cell line, all of which express Myo-D1. Thus, adenine methylation is not a modification of DNA following gametic fusion nor does it appear to play a major role in regulation of Myo-D1 expression.

Adenine↗

PubMed2025

Identification and external validation of a prognostic signature based on myeloid-derived suppressor cells-related LncRNAs to evaluate survival prognosis and treatment efficacy in invasive breast carcinoma.

BACKGROUND: Originating in the hematopoietic tissue, myeloid-derived suppressor cells (MDSCs) significantly contribute to tumor-related immunological processes. However, their relationship with long noncoding RNAs (lncRNAs) and breast cancer remains incompletely understood. In this study, we introduced MDSCs-associated lncRNAs as novel prognostic biomarkers to assess outcomes in patients with invasive breast carcinoma (BRCA). METHODS: Information regarding BRCA cases, including clinical and genomic details, was obtained from the TCGA repository. Predictive indicators were discovered, and their reliability underwent thorough verification. A clinically useful nomogram was developed following application-based validation. Additional investigations encompassed functional analysis, TMB assessment, TME profiling, immunotherapy efficacy forecasting, and drug sensitivity testing along with target identification. Long non-coding RNA expression was measured using reverse transcription quantitative PCR. RESULTS: A risk stratification model incorporating eight MDSCs-related lncRNAs effectively predicted patient outcomes. Kaplan-Meier (K-M) survival analysis clearly indicated a much worse prognosis among patients classified as high-risk (p < 0.001). The nomogram accurately forecasted overall survival (OS). Analysis of functional enrichment revealed that pathways associated with epithelial cells showed activity among patients at higher risk. Characterization of the tumor microenvironment showed increased immune cell presence in those classified as low-risk. Conversely, individuals with greater risk displayed higher tumor mutational burden. TIDE and IPS analyses indicated superior immunotherapy responsiveness in the low-risk BRCA subgroup. Among 47 drugs with notable IC50 variations, Ribociclib, PD173074, KU-55933, NU7441, and nutlin-3a exhibited lower IC50 values within the low-risk group, whereas Lapatinib demonstrated greater efficacy among the high-risk group. Moreover, 10 potential therapeutic agents and their targets were predicted for high-risk patients. RT-qPCR validation confirmed the robustness of the model. CONCLUSIONS: We successfully verified a new model of molecular markers of MDSCs-related lncRNAs, offering critical insights for predicting outcomes and guiding therapeutic decisions in BRCA cases.

Bioinformatics↗

PubMed2025

Integrated multi-omics analysis reveals TMEM147 as an immunosuppressive prognostic biomarker in LUAD.

TMEM147, an endoplasmic reticulum (ER) membrane protein, is implicated in lung adenocarcinoma (LUAD) progression, although its precise role remains unclear. To elucidate its function, this study integrated bioinformatics analyses with experimental validation. First, TMEM147 expression was assessed using TCGA and GEO datasets, with validation performed in LUAD cell lines. Survival analysis evaluated its prognostic significance. Subsequently, Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and single-sample gene set enrichment analysis (ssGSEA) were employed to identify associated functional pathways and interactions within the tumor immune microenvironment. Transcription factor binding predictions and in vitro functional assays (migration, invasion, proliferation) further characterized TMEM147's role. Results indicated that TMEM147 was significantly upregulated in LUAD and correlated with poor outcomes in patients. FLI1 was predicted as a key transcriptional regulator of TMEM147. Furthermore, TMEM147 expression influenced immune cell infiltration profiles and was associated with pathways involved in ribonucleoprotein biogenesis and oxidative phosphorylation (OXPHOS). Importantly, silencing TMEM147 significantly reduced cancer cell migration, invasion, and proliferation. These findings collectively suggest that TMEM147 promotes LUAD progression and holds potential as both a prognostic biomarker and a therapeutic target.

Bioinformatics analysis↗

PubMed2026

KRAS Expression Complements Genomic Profiling in Identifying Therapeutic Vulnerability in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) remains a major therapeutic challenge. Although alterations in the RAS pathway occur in over 50% of tumors, only a limited proportion are clinically actionable. We investigated whether KRAS expression complements genomic profiling for patient stratification and therapeutic vulnerability in GC. METHODS: Comprehensive genomic profiling was performed in 19 Taiwanese GC patients and compared with TCGA-STAD data (n = 434). KRAS mRNA expression and overall survival were evaluated by meta-analysis of 13 independent cohorts (n = 2,521). Protein-level validation was performed by immunohistochemistry in an independent cohort (n = 121). Functional KRAS dependency and response to combined MEK/SHP2 inhibition were assessed in eight GC cell lines. RESULTS: KRAS amplification was entirely contained within the KRAS-high population, whereas most KRAS-high tumors lacked detectable amplification. High KRAS expression was associated with poorer overall survival (HR 1.23, p = 0.001) and remained an independent prognostic factor after multivariable adjustment (adjusted HR 1.24, p = 0.003). Protein-level analysis showed a concordant trend. KRAS expression correlated strongly with functional dependency (R2 = 0.88, p = 0.005), was enriched in MSI and CIN subtypes, and identified cell lines with enhanced sensitivity to combined MEK/SHP2 inhibition. CONCLUSIONS: KRAS expression complements genomic profiling by identifying biologically relevant KRAS-dependent GCs beyond mutation or amplification alone. Integrating expression-based stratification with genomic profiling may improve patient selection for RAS pathway-directed combination therapies.

Biomarker↗

PubMed2025

HnRNPR promotes non-small cell lung cancer progression by protecting XB130 mRNA from XRN1- and DIS3L2-mediated degradation.

The adaptor protein XB130 is critically implicated in tumorigenesis. However, the mechanisms regulating its expression in tumors are not well understood. Our previous studies have identified hnRNPR as a potential binding protein of XB130 3'UTR in non-small cell lung cancer (NSCLC). This study aimed to clarify hnRNPR's role in NSCLC progression and its specific mechanisms regulating XB130 expression. The expression of hnRNPR in NSCLC and normal tissues was assessed using NSCLC tissue microarray and the TCGA database. Subsequently, in vitro and in vivo experiments were conducted to investigate the impact of hnRNPR on NSCLC cell proliferation and epithelial-mesenchymal transition (EMT) by modulating XB130 expression. The underlying molecular mechanisms of hnRNPR regulating XB130 expression were explored utilizing a range of molecular biology techniques including Western blotting, Real-time quantitative PCR, Immunohistochemistry, Dual-luciferase reporter assay, RNA pull-down assay, and RNA immunoprecipitation. We identified the overexpression of hnRNPR in NSCLC, with heightened hnRNPR levels significantly associated with poor prognosis in patients with lung adenocarcinoma. Functionally, hnRNPR overexpression promoted NSCLC cell proliferation and EMT and activated the Akt signaling pathway. Mechanistically, hnRNPR protected XB130 mRNA from XRN1- and DIS3L2-mediated degradation by binding to specific regions within XB130 3'UTR, consequently elevating XB130 expression. Lastly, XB130 overexpression counteracted the effects of hnRNPR silencing on NSCLC cells. Overall, our study unveils the potential of targeting the hnRNPR/XB130 axis as a promising therapeutic strategy for NSCLC.

Humans↗

PubMed2026

CTSG Suppresses Breast Cancer Progression by Inhibiting the EGFR/ERK Signaling Pathway and Enhancing CD8⁺ T Cell Activation.

BACKGROUND: Breast cancer (BC), the most common female malignancy, has metastasis as its main cause of mortality. Cathepsin G (CTSG) is involved in tumorigenesis and immunity. This study explores the role of CTSG in BC progression and CD8 + T cell regulation. METHODS: Differentially expressed genes and proteins (DEGs/DEPs) were analyzed using Limma, and core genes were screened using Random Forest (RF) and Least absolute shrinkage and selection operator (LASSO). CTSG expression was analyzed using GSE36295, the Cancer Genome Atlas (TCGA), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and western blot. Cell viability, proliferation, cell cycle, migration, and invasion were detected using Cell Counting Kit-8 (CCK8), 5‑Ethynyl‑2'‑deoxyuridine (EdU), flow cytometry, and Transwell assays, respectively. Sphere diameter was analyzed via sphere formation assay. Downstream mechanisms were examined using western blot, CCK8, flow cytometry, and Transwell assays. CD8 + T cell activity was examined using EdU, western blot, and flow cytometry. RESULTS: A total of 177 genes overlapped between GSE36295 DEGs and PDC000173 DEPs. CTSG was the hub gene identified by RF and LASSO. CTSG expression was significantly reduced in BC (P < 0.01). CTSG overexpression suppressed cell viability, proliferation, migration, invasion, sphere formation, and CD44 and CD133 expression (P < 0.01). CTSG up-regulation inhibited epidermal growth factor receptor (EGFR)/extracellular signal-regulated kinase (ERK) signaling axis and reduced cancer cell malignancy (P < 0.01). CTSG overexpression activated CD8 + T cells via EGFR/ERK inhibition, enhancing their cytotoxic effect on cancer cells (P < 0.01). CONCLUSION: CTSG inhibits BC malignancy and enhances CD8 + T cell function via EGFR/ERK inhibition.

Humans↗

PubMed2026

Pan-cancer multi-omics machine learning defines a lactylation-associated immune-excluded tumor state with proteomic and experimental corroboration.

BACKGROUND: Histone lactylation links lactate metabolism to chromatin regulation, but whether lactylation-program-associated transcriptional patterns delineate recurrent pan-cancer tumor states remains unclear. METHODS: We integrated mRNA, lncRNA, and miRNA profiles from 9712 TCGA tumors across 33 cancer types with GTEx references, six GEO cohorts, IMvigor210, and an institutional clear-cell renal cell carcinoma (ccRCC) cohort used for exploratory DIA-NN proteomic corroboration. Random-effects co-expression meta-analysis, multi-omics consensus clustering, regulon inference, immune deconvolution, TIDE, oncoPredict, and SHAP-based machine learning were applied. hsa-miR-431-5p was functionally evaluated as a proof-of-concept CS2-associated miRNA in bladder cancer models. RESULTS: LacCoEx-Atlas comprised 398,491 lactylation-related co-expression pairs across 24,667 RNA features under a random-effects framework (median I² = 88.6%). Consensus clustering identified two subtypes: CS2 showed glycolytic-mesenchymal-immune-excluded features, M2 macrophage enrichment, CD8⁺ T-cell depletion, elevated HDAC4/NSD3/KDM6B activity, and worse survival, whereas CS1 showed oxidative, sirtuin-active programs. CS2 had fewer predicted ICI responders (18.3% vs. 52.0%) and a lower observed ORR in IMvigor210 (15.3% vs. 24.0%). oncoPredict identified NU7441 as a hypothesis-generating CS2-associated sensitivity signal (Hedges' g = 1.17). DIA-NN proteomics in 50 ccRCC specimens provided exploratory support for CS2-associated hypoxia, ECM degradation, and metastasis programs. The 10-feature mRNA LARItools model achieved an apparent AUC of 0.9413, while a separate multi-omics model achieved 0.971; neither was independently validated. LARItools reproduced prognostic separation across six GEO cohorts. miR-431-5p promoted malignant phenotypes and EMT in bladder cancer cells, with concordant CMU4h expression findings. CONCLUSIONS: Lactylation-program-associated transcriptional patterns delineate a recurrent immune-excluded pan-cancer tumor state associated with adverse prognosis, reduced predicted immunotherapy responsiveness, exploratory single-cancer protein-level support, and testable DNA damage response-targeting hypotheses. LacCoEx-Atlas and LARItools provide open resources for lactylation-program-associated tumor-state stratification and future translational research.

Humans↗

PubMed2026

Machine learning-enabled multi-omics discovery of prognostic biomarkers and signaling targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains difficult to subtype using single omics layers. We conducted an exploratory investigation integrating reverse-phase protein array (RPPA) and DNA methylation data from the cancer genome atlas (TCGA)- pancreatic adenocarcinoma (PAAD) to assess the feasibility of multi-omics subtyping, alongside a supervised machine learning analysis of a small gene expression omnibus (GEO) transcriptomic cohort (n = 26) to identify candidate diagnostic genes. RPPA-based K-means clustering suggested a weak, possible two-subtype structure (silhouette ≈ 0.16) that remained unassociated with overall survival (log-rank p = 0.113) and lacked independent prognostic value. An independently performed similarity network fusion (SNF) analysis integrating RPPA and methylation data showed low concordance with RPPA-derived subtypes (Adjusted Rand Index (ARI) = 0.014), indicating limited convergence between molecular modalities. Supervised machine learning analysis of the GEO cohort using a fully nested leave-one-out cross-validation pipeline achieved a mean (area under the curve) AUC of 0.896 across four classifiers and identified four-fold-stable candidate genes (ESCO2, COL17A1, BCL2L14, and SOWAHB). However, this gene panel demonstrated limited external validity across two independent PDAC cohorts (log-rank p = 0.438 for both GSE62452 and GSE28735), indicating limited generalizability despite robust internal performance. Collectively, these findings provide limited evidence for a robust, prognostically significant multi-omics subtype or a validated diagnostic gene signature; instead, this study serves as a hypothesis-generating resource and highlights the importance of rigorous cross-validation and independent external validation in small-sample transcriptomic biomarker discovery.

Humans↗

PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗

PubMed2026

Comprehensive bioinformatics analysis identifies candidate ciliogenesis-related genes preferentially associated with N0-stage lung squamous cell carcinoma.

PURPOSE: There is few research on which genes play an important role in tumors without lymph metastasis. This study aimed to identify candidate molecular alterations preferentially associated with N0-stage LUSC. METHODS: we conducted a comprehensive bioinformatics analysis using publicly available The Cancer Genome Atlas (TCGA) data. Differentially expressed genes (DEGs) were identified separately by comparing N0 tumors and N+ tumors with normal lung tissues. Genes dysregulated in both N0 and N+ tumors were excluded to identify candidate N0-associated genes PPI networks were constructed using STRING and Cytoscape, with module analysis performed via MCODE. Hub genes were identified using multiple Cytohubba algorithms. Functional enrichment analyses were conducted using GO, and KEGG pathways using DAVID. Gene interaction networks were further explored using GeneMANIA. Immune cell infiltration was evaluated with TIMER. Associations with pathological stage and patient survival were assessed using GEPIA and other relevant tools. RESULTS: A total of 1103 candidate N0-associated DEGs were identified, including 748 upregulated and 355 downregulated genes. The PPI network contained five major MCODE clusters. One cluster (MCODE 4) included TTC30A, TTC30B, BBS7, and KIF3B genes implicated in ciliogenesis. TTC30B showed significant differential expression across pathological stages in the overall LUSC cohort. Seven consensus hub genes (ERBB2, CHUK, CASP8, NOTCH1, HNF4A, CREBBP, and IRS1) were identified based on their consistent ranking across multiple CytoHubba algorithms. Upregulated candidate N0-associated genes were primarily enriched in immune-related processes, including B-cell-mediated immunity and humoral responses, whereas downregulated genes were enriched in lysosomal and trans-Golgi network-related pathways. Exploratory immune infiltration analyses identified associations between the four ciliogenesis-related genes and several immune cell populations. CONCLUSIONS: This study identified candidate molecular signatures preferentially associated with N0-stage LUSC, including ciliogenesis-related genes and consensus hub genes. These findings provide hypotheses regarding molecular features of N0-stage LUSC and warrant further validation in independent cohorts and experimental studies.

Humans↗

PubMed2026

Integrin α3 (ITGA3) expression across breast cancer subtypes: Prognosis and therapeutic relevance.

BACKGROUND: Integrin α3 (ITGA3), which heterodimerizes with integrin β1, has emerged as a potential biomarker and therapeutic target in several epithelial malignancies; however, its clinical relevance in breast cancer remains incompletely characterized. This study evaluated ITGA3 expression across breast cancer molecular subtypes and assessed its prognostic and predictive significance. METHODS: Immunohistochemistry (IHC) was performed on archival breast cancer specimens using tissue microarrays (n = 148) and whole-tissue sections (n = 21). Complete clinicopathologic and outcome data were available for 108 patients, including hormone receptor-positive/human epidermal growth factor receptor 2-negative, HER2-positive, and triple-negative breast cancer (TNBC) subtypes. ITGA3 expression was quantified using H-scores and correlated with clinicopathologic features and survival outcomes. Independent transcriptomic analyses were conducted using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) cohorts to evaluate ITGA3 mRNA expression, co-expressed signaling pathways, and associations with therapeutic response. RESULTS: ITGA3 protein expression was detected in 85.2% of breast cancer specimens and was significantly higher in HR-positive/HER2-negative and HER2-positive tumors compared with TNBC (p < 0.0050). High ITGA3 expression was associated with shorter recurrence-free survival (p < 0.0001). In the METABRIC cohort, tumors with ITGA3 alterations demonstrated significantly worse relapse-free survival (p < 0.0001) and overall survival (p < 0.0500). Transcriptomic analyses revealed that ITGA3 co-expressed with estrogen receptor 1(ESR1), erb-b2 receptor tyrosine kinase 2 (ERBB2), and luminal markers, along with enrichment of estrogen receptor and phosphoinositide 3-kinase-protein kinase B-mechanistic target of rapamycin (PI3K/AKT/mTOR) signaling pathways. ITGA3 expression was not predictive of response to tamoxifen or trastuzumab. CONCLUSION: Elevated ITGA3 expression is associated with breast cancer recurrence and poor clinical outcomes, supporting its potential role as a prognostic biomarker and candidate therapeutic target.

Biomarkers↗

PubMed2026

An immune exhaustion signature predicts prognosis and identifies patients with diffuse large B-cell lymphoma (DLBCL) who derive preferential benefit from chimeric antigen receptor (CAR)-T cell therapy.

BACKGROUND: The tumor microenvironment (TME) is a key determinant of prognosis in diffuse large B-cell lymphoma (DLBCL). While T-cell exhaustion is implicated in therapeutic failure, its precise molecular hallmarks and utility for predicting response to modern immunotherapies, such as chimeric antigen receptor (CAR)-T cell therapy, remain unclear. METHODS: We performed an integrative analysis of transcriptomic and clinical data from multiple DLBCL cohorts (The Cancer Genome Atlas [TCGA], GSE181063, GSE10846, GSE248835, GSE182434). We used unsupervised clustering, exploratory analysis of single-cell RNA sequencing data, and the least absolute shrinkage and selection operator for variable selection (LASSO-Cox) regression to characterize the exhausted TME, construct a prognostic model, and evaluate its predictive value for CAR-T cell therapy. The model's dynamic behavior was assessed in a proof-of-concept longitudinal cohort of patients treated with the T-cell-engaging bispecific antibody glofitamab. RESULTS: We identified a "high-exhaustion" subtype associated with significantly poorer overall survival (OS; log-rank P = 0.016). Based on this, we developed a five-gene immune exhaustion-Related Prognostic Score (IERPS) that served as a robust independent predictor of poor OS across multiple cohorts. Critically, in a cohort of 256 relapsed/refractory patients, the IERPS was strongly prognostic for event-free survival (EFS) in the standard-of-care (SOC) arm (HR = 2.02, 95% confidence interval [95% CI]: 1.07-3.81, P = 0.029) but lost prognostic significance in the CAR-T arm (HR = 0.70, 95 % CI: 0.35-1.40, P = 0.314). This significant interaction suggests that CAR-T cell therapy may abrogate the poor prognosis associated with a high IERPS. Biologically, exploratory single-cell analysis (n = 4 samples) defined the high-IERPS state by hallmarks of classical T-cell exhaustion, and a descriptive case study showed the score dynamically tracked clinical response to glofitamab. CONCLUSIONS: A state of active T-cell exhaustion and a suppressive TME drive the adverse immune phenotype in DLBCL. Our IERPS model captures this dysfunctional state, acting as a powerful prognostic tool and, more importantly, as a potential predictive biomarker to identify high-risk patients who appear to overcome their inherently poor prognosis through CAR-T cell therapy.

Biomarkers↗

PubMed2026

Linking MRI radiomics to transcriptomics-based radiosensitivity in lower-grade glioma: A radiogenomic framework.

BACKGROUND: RSI is a transcriptomics-based biomarker associated with radiotherapy outcomes, but its clinical application is constrained by the requirement for tumor tissue and RNA sequencing. This study investigates whether MRI-derived radiomic features can reflect RSI-defined intrinsic radiosensitivity in lower-grade glioma.This addresses a critical gap arising from the limited availability of matched imaging and genomic data in routine clinical practice. METHODS: MRI-derived radiomic features were extracted from FLAIR images of lower-grade glioma patients obtained from TCIA and matched with transcriptomic data from TCGA. A total of 107 patients with both MRI and RNA sequencing data were included in the radiogenomic analysis. Radiomic features were ranked using a Borda-based ensemble feature selection strategy. Five supervised machine-learning classifiers were trained to predict RSI-based radiosensitivity classification, and model interpretability was assessed using SHAP within radiogenomic framework. RESULTS: Classification performance increased with feature number and stabilized at compact subset of 13 radiomic features. Logistic regression showed stable performance with an AUC of 0.82 (95 % CI: 0.71-0.93). SHAP analysis indicated that heterogeneity-related texture features were dominant contributors to model predictions, with many associated with the RR phenotype, while others were linked to the RS phenotype. CONCLUSION: An MRI-based radiomic signature enables non-invasive prediction of RSI-defined radiosensitivity in lower-grade glioma. Rather than offering an immediately deployable clinical tool, this study establishes a proof-of-concept radiogenomic framework demonstrating that intrinsic radiosensitivity, traditionally assessed through invasive molecular assays, can be approximated using quantitative imaging features. These findings highlight the potential of imaging-based radiosensitivity assessment and provide a foundation for future radiogenomic investigations.

Lower-grade glioma↗