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PubMed2026

Integrated analysis of amide proton transfer weighted MRI and proteomics uncovers altered protein dynamics in glioblastoma.

PURPOSE: Elevated amide proton transfer-weighted (APTw) MRI signals in glioblastoma (GBM) are often linked to increased intracellular mobile proteins, but the associated molecular patterns in human tissue remain unclear. We examined the relationship between regional APTw features and cellular protein composition and profiled proteomic differences between tumor and peritumoral tissue. METHODS: In this single-center prospective study, preoperative MRI data were integrated with intraoperative neuronavigation for 12 image-guided tissue samples (8 tumor and 4 peritumoral). Total, cytoplasmic, and nuclear proteins were quantified using bicinchoninic acid (BCA) assay. Data-independent acquisition (DIA) proteomics identified exploratory differentially expressed proteins (DEPs), followed by functional enrichment and protein-protein interaction (PPI) network analyses. Transcript-level expression patterns and survival associations were queried in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets to provide indirect external clinical context. RESULTS: Tumor regions showed higher APTw signals than peritumoral regions (p < 0.001) and increased cytoplasmic protein concentration (p < 0.05), without a corresponding increase in total or nuclear protein levels. DIA identified 654 DEPs. Further analysis highlighted 36 higher-significance DEPs, and prioritized 12 hub proteins in the PPI network. In public transcriptomic datasets, ERBB2, RUNX1, and SHC1 showed higher expression in GBM and were associated with poorer overall survival. CONCLUSION: These findings suggest that elevated APTw signal in GBM may be associated with increased cytoplasmic protein content and distinct proteomic alterations. This imaging-proteomic framework provides exploratory regional context for future mechanistic and follow-up studies, but larger, spatially matched and independently validated cohorts are required to confirm the molecular contributors to APTw contrast.

Humans↗

PubMed2025

Comprehensive proteomic and pathological profiling identifies PRAS40 as a novel biomarker and mediator of primary immune checkpoint blockade resistance in non-small cell lung cancer.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment landscape of non-small cell lung cancer (NSCLC), yet primary resistance remains a significant clinical challenge. Recent evidence implicates PRAS40 (AKT1S1) in regulating cellular survival and immune responses, but its role in immunotherapy resistance is not fully understood. METHODS: Transcriptomic data from TCGA and GTEx cohorts were analyzed to assess PRAS40 expression. Prognostic value was evaluated using Cox regression. Immune microenvironment features were characterized with CIBERSORT and TIMER. Predictive efficacy for ICB response was examined using TIDE and IPS. Plasma PRAS40 levels in 66 NSCLC patients receiving ICB were quantified by proximity extension assay (PEA), and multiplex immunohistochemistry assessed associations among PRAS40, PD-L1, and CD8+ T cells in tumor tissues. RESULTS: High PRAS40 expression was associated with poor prognosis, reduced CD8+ T cell infiltration, and downregulation of immune checkpoint genes. Elevated circulating PRAS40 predicted primary ICB resistance and shorter progression-free survival, independent of PD-L1 or CD8+ T cell status. CONCLUSION: PRAS40 is strongly associated with primary ICB resistance in NSCLC and may serve as a novel predictive biomarker. These findings support its potential to guide personalized immunotherapy in lung cancer.

Humans↗

PubMed2025

Intratumoral B cell and interferon signatures in newly diagnosed glioblastoma are associated with longer survival in patients treated with SurVaxM.

Glioblastoma (GBM) has proved difficult to treat, and there is dire need for more effective therapies. In a single arm phase IIa trial (NCT02455557), treatment of newly diagnosed GBM patients with the peptide vaccine SurVaxM resulted in promising median progression-free and overall survival. To investigate molecular features that associate with GBM responsiveness to SurVaxM, retrospective whole exome and RNA sequencing was performed on patient tumors (n = 34) collected prior to standard of care treatment plus SurVaxM. Differential gene expression and mutational profiles were characterized between patients with short-term (OS < 18 months) or long-term (OS ≥ 18 months) overall survival. Greater expression of interferon, complement, and humoral immunity signatures were associated with long-term survival. Deconvolution of transcriptomes identified enrichment of intratumoral memory B cell populations in long-term survivors that were validated by CD20 staining in matched samples. A five-gene expression signature and a B cell specific signature predicted survival within the SurVaxM-treated cohort, however, these signatures were not associated with improved outcomes in a similarly treated population obtained from The Cancer Genome Atlas (TCGA) that did not receive immunotherapeutic intervention. Although prospective validation is ongoing, the findings in this discovery cohort specify molecular features of GBM associated with better overall survival and potential responsiveness to immunotherapy with SurVaxM.

Humans↗

PubMed2025

CD40 transcriptomic expression patterns across malignancies: implications for clinical trials of CD40 agonists.

BACKGROUND: CD40 is a T-cell co-stimulatory receptor targeted by next-generation immunotherapies. We conducted a pan-cancer transcriptome analysis of CD40, its ligand, and related immune markers to evaluate co-expression patterns and clinical outcomes. METHODS: We analyzed transcriptome data for CD40, its ligand, and other common checkpoints and co-stimulators (PD-1, PD-L1, PD-L2, CTLA-4, LAG-3, ICOS, CD27, CD28, OX40, and GITR). RNA expression was classified as high (75-100th percentile), moderate (25-74th), or low (0-24th) against a reference population of 735 previously tested solid tumors. RESULTS: Of 514 patients, 114 (22%) showed high, 247 (48%) moderate, and 153 (30%) low CD40 RNA expression. High CD40 expression was most frequent in liver and bile duct (42%), pancreatic (42%), and ovarian (40%) cancers. Both high CD40 and low-moderate CD40 ligand expression-potentially conducive to CD40 agonist therapy-was most frequent in ovarian (33%) and pancreatic (24%) cancer. In both UCSD (N = 514) and TCGA (N = 10,953) cohorts, high CD40 expression significantly correlated with high CD28 and GITR. High CD40 RNA levels were not prognostic for overall survival (OS) from metastatic disease (P = 0.2) (n = 272 immune checkpoint inhibitor (ICI)-naïve patients). High CD40 expression correlated with longer OS from immunotherapy initiation (n = 217 ICI-treated patients; P = 0.04, univariable analysis), but not multivariable analysis, suggesting it may not be an independent predictive biomarker. CONCLUSION: High CD40 expression correlated with liver and bile duct, pancreatic, and ovarian cancers, as well as with CD28 and GITR transcripts. Immune marker co-expression in individual patients merits further exploration for the development of CD40-based and other immunotherapy interventions.

Humans↗

PubMed2026

Targeting ALDH2 with Alda-1 to reverse cisplatin resistance in lung adenocarcinoma.

BACKGROUND: Cisplatin resistance remains a major obstacle in lung adenocarcinoma (LUAD) treatment. The role of Aldehyde dehydrogenase 2 (ALDH2), a detoxifying enzyme, in LUAD prognosis and chemoresistance is poorly understood. METHODS: We analyzed ALDH2's prognostic value using clinical cohorts, TCGA, and proteomic data. Cisplatin-resistant cell lines and xenograft models were used to assess the effect of the ALDH2 agonist Alda-1. Molecular mechanisms were investigated via gain/loss-of-function studies. RESULTS: High ALDH2 expression was significantly associated with improved survival in univariate analysis and correlated with a favorable genomic instability profile in LUAD. Pharmacological activation of ALDH2 with Alda-1 restored cisplatin sensitivity in resistant cells and potently enhanced cisplatin's efficacy in vivo. Mechanistically, ALDH2 activation upregulated PKC-ζ, leading to downregulation of the drug efflux pump MDR1. Proteomic analysis further linked low ALDH2 expression to a pro-chemoresistance signature. CONCLUSION: ALDH2 represents a potential prognostic biomarker associated with favorable outcomes in LUAD, particularly in patients receiving chemotherapy. Its activation via Alda-1 overcomes cisplatin resistance by targeting the PKC-ζ/MDR1 axis, presenting a novel therapeutic strategy.

Cisplatin↗

PubMed1999

Specific detection of Xylella fastidiosa Pierce's disease strains.

Pierce's disease (PD, Xylella fastidiosa) of grapevine is the primary pathogen limiting vinifera grape production in Florida and other regions of the southeastern United States. Quick and accurate detection of PD strains is essential for PD studies and control. A unique random amplified polymorphic DNA (PD1-1-2) was isolated from a PD strain from Florida. Fragment PD1-1-2 was cloned, sequenced, and found to be 1005 bp in length. PCR primers were designed to utilize these sequence data for PD strain detection. One primer set (XF176f-XF954r) amplified a 779-bp DNA fragment from 34 PD strains including seven pathotypes of X. fastidiosa, but not from strains of Xanthomonas campestris pv. campestris, Xan. vesicatoria or Escherichia coli. A second primer set (XF176f and XF686r) amplified a 511-bp fragment specific to 98 PD strains, but not from strains of citrus variegated chlorosis, mulberry leaf scorch, oak leaf scorch, periwinkle wilt, phony peach, or plum leaf scald. Sequence analysis indicated that RAPD fragment PD1-1-2 contains a Ser-tRNA gene. The PD-specific region includes a TaqI restriction site (TCGA) and is 150 bp downstream of the Ser-tRNA gene.

Base Sequence↗

PubMed2026

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and potential therapeutic targets. Multi-source transcriptomic datasets (TCGA-COAD, GSE39582, GSE17536) and single-cell RNA-seq data were analyzed. Ten machine learning algorithms were integrated to construct an acRG-based prognostic signature (acRGBS). Immune microenvironment (TME) and genomic profiling were performed, with in vitro functional experiments validating TUBA1C's role. acRGBS, comprising four hub genes (SARAF, CDC42SE2, TSPYL2, TUBA1C), effectively stratified COAD patients into high- and low-risk groups with distinct survival outcomes and was an independent prognostic factor. High-risk patients exhibited increased genomic instability and immunosuppressive TME, while low-risk patients had favorable immunotherapy response. TUBA1C was overexpressed in COAD cells, and its knockdown inhibited proliferation/migration and induced apoptosis. The acRGBS is a robust prognostic tool for COAD, and TUBA1C serves as a candidate therapeutic target, providing new insights for personalized COAD management.

Humans↗

PubMed2026

Gastric carcinoma classification in the WHO 6th edition (2026): Updated framework and emerging entities.

The sixth edition of the WHO Classification of Digestive System Tumours (2026) represents an important step in the continuing evolution of gastric carcinoma classification. While preserving morphology as the foundation of diagnosis, it incorporates advances in molecular pathology, genotype-phenotype correlations, tumour evolution, and predictive biomarker assessment. This review summarizes the development of the WHO classification from the third edition (2000) to the sixth edition (2026) and highlights its relationship with other major classification systems, including those of Laurén, Nakamura, and the Japanese Gastric Carcinoma Association (JGCA). Major histological categories remain largely unchanged; however, several important conceptual and diagnostic refinements have been introduced. These include recognition of crawling-type adenocarcinoma as a distinctive variant of tubular adenocarcinoma, subclassification of poorly cohesive carcinoma into signet-ring cell and non-signet-ring cell subtypes, introduction of the concept of pure signet-ring cell carcinoma, and increased emphasis on tumour evolution. The sixth edition also expands and refines the spectrum of uncommon gastric carcinoma subtypes, including gastric carcinoma with lymphoid stroma, AFP-producing carcinoma, micropapillary adenocarcinoma, gastric adenocarcinoma of fundic-gland type, and gastric sarcomatoid carcinoma. Crucially, molecular subgroups originally proposed by The Cancer Genome Atlas (TCGA) and actionable biomarkers-including HER2 (ERBB2), Claudin 18.2, mismatch repair deficiency/microsatellite instability (dMMR/MSI), and programmed death-ligand 1 (PD-L1)-have transitioned from research-based categories into essential tools for precision oncology. Rather than providing exhaustive diagnostic criteria, this review offers a conceptual framework and encourages consultation of the original WHO text for full details. These advances illustrate the transition of gastric carcinoma classification from a predominantly morphology-based system toward an integrated histomolecular framework that more closely links pathological diagnosis with tumour biology, prognostication, and therapeutic stratification.

Crawling-type adenocarcinoma↗

PubMed2026

Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.

BACKGROUND: Neoadjuvant therapy (NAT) is recommended for locally advanced gastric cancer (LAGC), but some patients respond poorly. We aimed to construct a multimodal model integrating CT images, transcriptomic sequencing, and clinicopathological data to assess prognosis in LAGC patients receiving NAT. MATERIALS AND METHODS: This multicenter study included 505 LAGC patients who underwent NAT. Radiomic features were extracted from preoperative CT images of 505 patients. RNA-seq was performed on 277 post-NAT specimens, with additional data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (n = 804). Patients were divided into training (168 cases), internal validation (72 cases), and external validation cohorts. Machine learning algorithms identified key radiomic, molecular, and clinical features associated with NAT response, which were then integrated into a multimodal model to predict overall survival (OS) and disease-free survival (DFS). RESULTS: Six radiomic and three molecular features significantly associated with NAT response were selected. Radiomic risk (hazard ratio [HR]: 4.0, P < 0.001) and molecular risk (HR: 7.1, P < 0.001) were independent prognostic factors. By integrating radiomic risk, molecular risk, and clinical characteristics, a multimodal model (MuMo) was constructed.The C-index results (OS, C-index = 0.855; DFS, C-index = 0.786) demonstrated that MuMo outperformed the single-modality models and ypTNM staging.Mechanistic analysis suggested that the efficacy of neoadjuvant therapy was significantly enriched in immune-inflammatory pathways. CONCLUSIONS: MuMo can effectively predict postoperative survival risk in LAGC patients receiving NAT, serving as a powerful tool for optimizing prognostic assessment.

Humans↗

PubMed2025

MED12-STAT1-TAP2 axis regulates CD8 + T cell cytotoxicity and mediates immunotherapy outcome in non-small cell lung cancer.

Although immunotherapy for late-stage non-small cell lung carcinoma (NSCLC) has been clinically utilized, its prognosis remains highly heterogeneous, prompting us to investigate novel predictive immunotherapy biomarkers for NSCLC. We analyzed the correlations between MED12 nonsynonymous mutations and survival, clinical, genomic, transcriptomic information, and immune infiltration information through data mining across multiple datasets. We also investigated the mechanism of MED12 using luciferase assay, Western blot, ChIP-PCR, and siRNA. MED12 is significantly associated with survival in completely independent immunotherapy datasets, including MSKCC (N = 350), Naiyer2015 (N = 34), our own (N = 295) and the pan-cancer dataset, but not in the TCGA dataset, where patients received non-immunotherapy regimens. Mutations in MED12 showed no significant correlation with known metrics (TMB, IPS/CTLA4/PD1 status, PD-1/PD-L1 expression, and TCR/BCR status) or DNA Damage Repair (DDR) pathway mutations, yet they carried independent prognostic information according to the Cox multivariate regression. On the other hand, MED12 mutation is significantly associated with multiple immune-related pathways and immune infiltration of CD8 + T cells and activated NK cells. Lactate dehydrogenase assay revealed that knockdown of TAP2 restored the upregulation of CD8 + T cell cytotoxicity triggered by MED12 knockdown. ChIP-PCR, luciferase assay and siRNA knock down assay indicate that MED12 binds to the promoter region of STAT1 to suppress its transcription, while the transcription factor STAT1 promotes the transcription of TAP2, thus inhibiting the antigen processing and presentation. Collectively, MED12 mutation is an independent and valuable biomarker for predicting the response to immune checkpoint inhibitor (ICI)therapy in NSCLC by modulating CD8 + T cell cytotoxicity via the STAT1/TAP2 axis.

Humans↗

PubMed2026

Integrative transcriptomic, spatial and functional-genomic analysis identifies a UFMylation-related vascular-stromal program and prioritizes WWTR1 in glioblastoma.

Glioblastoma (GBM) contains spatially organized stress-adaptive and vascular niches. Because transcript abundance does not measure UFM1 conjugation, we asked whether a UFMylation-related transcriptional axis identifies a reproducible tissue program and alters candidate prioritization. In 518 unique primary TCGA-GBM tumors profiled on the Affymetrix HT Human Genome U133A array, weighted gene co-expression network analysis of 8,000 variable genes yielded 12 modules. The 278-gene green module ranked first across nine prespecified traits (mean |r|=0.637). Direct overlap comprised 1/3 measurable UFMylation-core, 5/19 ER-stress/UPR, and 2/15 proteostasis genes; after excluding overlapping genes, correlations with the green eigengene remained significant (r = 0.373, 0.831, 0.639, and 0.699 for UFMylation-core, ER-stress/UPR, proteostasis, and composite scores, respectively). The green score was associated with overall survival per standard-deviation increase (HR 1.17, 95% CI 1.07-1.28), although clinical adjustment attenuated the estimate. In a 10-sample single-cell dataset, sample-level scores were higher in pericytes and endothelial cells than in malignant cells. Donor-aware IvyGAP analysis supported regional organization, whereas one Visium section showed stronger concordance with ER-stress/UPR and mesenchymal scores than with the UFMylation-core score. CellChat indicated pathway-selective rather than global remodeling of inferred vascular communication. Layer ablation moved WWTR1 from rank 48 using WGCNA alone to rank 4 overall and rank 1 among non-common-essential genes after cross-platform integration. These findings define an ER-stress/mesenchymal-weighted, UFMylation-related vascular-stromal transcriptional association and nominate WWTR1 for experimental testing.

Humans↗

PubMed2025

Elevated expression of transferrin receptor-1 in pancreatic cancer: clinical implications and prognostic significance.

PURPOSE: Many advanced-stage pancreatic cancers are fatal, highlighting the need for solid prognostic indicators. This study evaluates transferrin receptor-1 (TfR1) expression in pancreatic cancer tissues and cell lines for clinical and therapeutic potential. METHOD: The GuangRe database, which integrates mRNA data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project, was used to assess TFRC gene expression in pancreatic cancer and normal tissues. ROC curves and Kaplan-Meier and Log-rank tests were used to evaluate TFRC gene expression's diagnostic and survival efficacy. In vitro Western blotting and immunofluorescence experiments on pancreatic cancer cell lines assessed TfR1 expression. IHC staining was done on tissue samples from 90 patients to determine TfR1's clinical importance. RESULTS: The study found that TFRC mRNA levels were significantly higher in pancreatic cancer tissues compared to nearby normal tissues (P < 0.05), with an AUC of 0.936. We found higher TfR1 protein levels in pancreatic cancer cell lines (P < 0.01) using western blot and immunofluorescence studies. Immunohistochemistry showed that pancreatic cancer tissues expressed 30.1% TfR1 compared to paracancer (11.1%) (P = 0.003). In COX regression analysis, increased TfR1 expression was related with lower overall survival (OS) and progression-free survival (PFS), making it an independent prognostic factor. CONCLUSION: Higher TfR1 expression is associated with poor pancreatic cancer outcomes, suggesting its potential as a prognostic biomarker and therapeutic target.

Humans↗

PubMed2025

The MTORC1 signaling pathway related gene POLR3G serves as a potential prognostic biomarker in Hepatocellular Carcinoma.

This study aims to investigate the prognostic significance and potential biological functions of the MTORC1 signaling pathway-associated gene POLR3G in Hepatocellular carcinoma (HCC). A prognostic risk model for HCC was developed by integrating HCC-related datasets and associated clinical data obtained from The Cancer Genome Atlas (TCGA) database. The GSVA website was employed to analyze the model genes across pan-cancer datasets, focusing on copy number variations (CNV), single nucleotide variations (SNV), methylation differences, drug sensitivity and immune cell infiltration profiles. Subsequently, we examined the expression levels and prognostic significance of POLR3G in HCC. Utilizing Spearman correlation analysis, we identified genes associated with POLR3G. Furthermore, Gene Set Enrichment Analysis (GSEA) was employed to elucidate the potential signaling pathways in which POLR3G may be involved. The relationship between POLR3G expression and immune cell abundance in HCC samples was assessed using the ssGSEA algorithm. Finally, the impact of POLR3G on HCC cell proliferation was validated through CCK-8 and EDU cell proliferation assays. Through univariate Cox regression analysis and LASSO regression analysis, we established a prognostic risk model for HCC comprising 13 genes. The analysis revealed that individuals categorized in the low-risk group had a markedly improved overall survival probability relative to those in the high-risk group. POLR3G exhibited a markedly elevated expression in HCC tissues when compared to adjacent normal tissues. The expression of POLR3G was correlated with tumor grade, and elevated POLR3G expression was associated with poor prognosis in HCC patients. Furthermore, the expression level of POLR3G was found to be correlated with the level of immune cell infiltration. Knockdown of POLR3G significantly inhibited the proliferative capacity of hepatocellular carcinoma cells. The findings suggest that POLR3G may serve as a potential biomarker influencing the prognosis of hepatocellular carcinoma patients by modulating the tumor immune microenvironment.

Humans↗

PubMed2026

PYCR1 promotes glutamine metabolism and the progression of lung adenocarcinoma by regulating the expression of OPLAH.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Glutamine plays a critical role in the progression of LUAD. However, the function of pyrroline-5-carboxylate reductase 1 (PYCR1) and its regulatory role in glutamine metabolism remain unclear. Transcriptomic and clinical data for LUAD were obtained from The Cancer Genome Atlas (TCGA) and validated using Gene Expression Omnibus (GEO) datasets (GSE19188, GSE13213). Glutamine metabolism-related genes were analyzed for differential expression and prognostic significance. Functional enrichment was performed via gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses. Single-cell RNA-seq data (GSE117570) were processed using Seurat, and cell-cell communication was inferred with CellChat. In vitro, lentiviral overexpression, Western blotting, EdU, CCK-8, and glutamine uptake assays were conducted. An orthotopic xenograft model was established in nude mice to assess tumor growth in vivo. Six glutamine-metabolism-related genes were found significantly overexpressed in LUAD tissues and associated with poor overall survival. Single-cell sequencing revealed predominant PYCR1 expression in malignant cells. Functional assays demonstrated that PYCR1 overexpression enhanced glutamine uptake, proliferation, and inhibited apoptosis in LUAD cells, effects mediated via suppression of the P53 pathway. PYCR1 promoted tumor growth in a xenograft model and was found to transcriptionally upregulate 5-oxoprolinase (OPLAH), which augmented its oncogenic effects. Our findings identify the PYCR1/OPLAH axis as a key driver of LUAD progression via p53 signaling, revealing a promising therapeutic target.

Pyrroline Carboxylate Reductases↗

PubMed2026

Pan-cancer analysis identifies KANSL2 as a cell-cycle-associated regulator of tumor progression and immunity in liver hepatocellular carcinoma.

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

Carcinoma, Hepatocellular↗

PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (ΔAUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗

PubMed2024

RNF115 aggravates tumor progression through regulation of CDK10 degradation in thyroid carcinoma.

BACKGROUND: RING Finger Protein 115 (RNF115), a notable E3 ligase, is known to modulate tumorigenesis and metastasis. In our investigation, we endeavor to unravel the putative function and inherent mechanism through which RNF115 influences the evolution of thyroid carcinoma (THCA). METHODS: We analyzed RNF115 expression in THCA using the Cancer Genome Atlas (TCGA) database. The influence of RNF115 on the progression of THCA was evaluated using both in vitro and in vivo experimental approaches. The protein regulated by RNF115 was identified through bioinformatics analysis, and its biological significance was further explored. RESULTS: In both THCA tissues and cells, RNF115 showed elevated expression levels. Enhanced expression of RNF115 fostered cell proliferation, tumor growth, and the exacerbation of epithelial-mesenchymal transition (EMT) in THCA, while also promoting tumor lung metastasis. Bioinformatics analysis identified cyclin-dependent kinase 10 (CDK10) as a downstream target of RNF115, which was found to be ubiquitinated and degraded by RNF115 in THCA cells. Functionally, overexpression of CDK10 was found to counteract the promotion of malignant phenotype in THCA induced by RNF115. From a mechanistic perspective, RNF115 activated the Raf-1 pathway and enhanced cancer cell cycle progression by degrading CDK10 in THCA cells. CONCLUSION: RNF115 triggers cell proliferation, EMT, and tumor metastasis by ubiquitinating and degrading CDK10. The regulation of the Raf-1 pathway and cell cycle progression in THCA may be profoundly influenced by this process.

Humans↗

PubMed2026

MYBL2 promotes malignant phenotypes and M2-like macrophage polarization through CCL2 in non-small cell lung cancer.

Hub genes associated with non-small cell lung cancer (NSCLC) were identified through bioinformatics screening. In vitro experiments analyzed the potential mechanisms by which these genes regulate tumor malignant phenotypes and macrophage polarization. Differentially expressed genes were identified from The Cancer Genome Atlas (TCGA)-NSCLC and GSE32175 datasets, followed by protein-protein interaction (PPI) network analysis to screen hub genes. The effects of MYB Proto-Oncogene Like 2 (MYBL2) on NSCLC progression and macrophage polarization were evaluated using in vitro models. The regulatory relationship between MYBL2 and C-C motif chemokine ligand 2 (CCL2) was investigated by Chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays, and rescue experiments were performed to validate the role of the MYBL2-CCL2 axis. Bioinformatics screening identified BUB1B, CDCA2 and MYBL2 as key hub genes with high expression in NSCLC, among which MYBL2 was significantly upregulated in NSCLC cells. Functional experiments confirmed that MYBL2 silencing markedly inhibited the malignant proliferation, migration and invasion of NSCLC cells. Tumor cell MYBL2 knockdown effectively reversed M2-like polarization and promoted M1-like polarization in the co-culture system. Mechanistically, MYBL2 directly bound to the CCL2 promoter region to enhance CCL2 transcriptional activity and upregulate CCL2 expression in NSCLC cells. Exogenous CCL2 supplementation significantly rescued the inhibitory effect of MYBL2 knockdown on macrophage M2-like polarization, verifying the mediating role of CCL2 in this regulatory axis. MYBL2 is strongly expressed in NSCLC cells and is associated with enhanced malignant phenotypes. It may affect macrophage M2-like polarization by upregulating CCL2, thus participating in NSCLC immune microenvironment remodeling.

CCL2↗