Gene Set Enrichment Research Articles

Single-Cell Proteomics Uncovers Dual Traits of Dermal Sheath Cells in Wound Repair.

Wound healing is a dynamic process involving multiple cell types and signaling pathways. Dermal sheath cells (DSCs), residing surrounding hair follicles, play a critical role in tissue repair, yet their regulatory mechanisms remain unclear. This study used single-cell proteomics with the AcanCreER;R26LSL-tdTomato-DTR mouse model to explore DSC function across different healing stages. All animal procedures were conducted in accordance with the Animal Research: Reporting of In Vivo Experiments guidelines. Gene set enrichment analysis (GSEA) and temporal clustering (Mfuzz) were employed to reveal dynamic functional shifts. GSEA identified enriched gene sets related to interferon-gamma response, inflammatory response, ultraviolet response, myogenesis, and xenobiotic metabolism. Temporal clustering revealed eight distinct clusters: clusters associated with the early contracting and proliferative phases were linked to metabolic activation and oxidative stress, while clusters from the later remodeling phase emphasized extracellular matrix remodeling and structural reorganization. The dynamic expression of epithelial-mesenchymal transition-related genes and keratins supported DSCs' dual epithelial and mesenchymal traits. Additionally, keratins, collagens, integrins, and actin proteins emerged as promising markers or signature molecules for DSCs. This study reveals DSCs' dual traits during wound repair, providing a basis for therapies to enhance healing.

NIPAL1 as a prognostic biomarker associated with pancreatic adenocarcinoma progression and immune infiltration

Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor in the digestive system, with an increasing incidence and mortality rate globally. Recent genetic studies have revealed that the abnormal expression and functional dysregulation of various genes are involved in the occurrence and progression of pancreatic cancer. NIPA-like proteins (NIPAs) are expressed in a variety of cancer types, yet the role of NIPAL1 in cancer remains unclear. Therefore, further research is required to determine its diagnostic significance and understand its biological functions in cancer. Primitive RNA sequencing (RNA-seq) data of PAAD from The Cancer Genome Atlas (TCGA) was utilized for bioinformatics analysis to characterize the expression levels of NIPAL1 in tumor and normal tissues. Differentially expressed genes (DEGs) were identified, and Gene Set Enrichment Analysis (GSEA) was performed to elucidate potential biological mechanisms of NIPAL1 involved in PAAD development. Additionally, we analyzed the correlation between NIPAL1 expression, immune cell infiltration, and PAAD progression. The Genomics of Drug Sensitivity in Cancer (GDSC) database was utilized to investigate the relationship between NIPAL1 expression and the efficacy of common drugs used in chemotherapy and targeted therapy in patients with pancreatic cancer. Subsequently, we predicted five small-molecule drugs targeted at NIPAL1 using molecular docking. Finally, high expression of NIPAL1 in tumor tissues was validated through immunohistochemistry. In pancreatic cancer cell lines, changes in phenotypes such as proliferation, migration, and invasion following the knockdown of NIPAL1 were assessed. Finally, we established a subcutaneous tumor-bearing mouse model to further validate its therapeutic significance in vivo.

Predictive role of SLC1A5 in neuroblastoma prognosis and immunotherapy

BackgroundNeuroblastoma, a prevalent extracranial solid tumor in pediatric patients, demonstrates significant clinical heterogeneity, ranging from spontaneous regression to aggressive metastatic disease. Despite advances in treatment, high-risk neuroblastoma remains associated with poor survival. SLC1A5, a key glutamine transporter, plays a dual role in promoting tumor growth and immune modulation. However, its contributions to neuroblastoma biology remain largely unexplored.MethodsThis study utilized clinical neuroblastoma samples from 20 patients and 1310 cases from four public datasets to investigate SLC1A5 expression, biological function, and prognostic significance. Differential expression, Kaplan–Meier survival analysis, gene set enrichment analysis, and weighted correlation network analysis were conducted. Functional validation included qPCR, immunohistochemistry, Western blotting, and cell proliferation assays using the SLC1A5 inhibitor V-9302. A prognostic signature, SRPS, was constructed and validated using machine-learning approaches. Immune infiltration analysis was performed to evaluate the tumor immune microenvironment.ResultsSLC1A5 expression was significantly elevated in high-risk neuroblastoma and correlated with advanced stages and poor prognosis. GSEA revealed mTORC1 signaling enrichment in high SLC1A5 expression groups, validated by increased p-p70S6K levels in tumor samples and neuroblastoma cells. V-9302 treatment suppressed mTORC1 signaling and inhibited cell proliferation. Hub-genes were identified to form the SRPS model, which demonstrated superior prognostic performance compared to existing models. Immune infiltration analysis revealed a more immunosuppressive tumor microenvironment associated with high SLC1A5 expression. Additionally, SLC1A5 negatively regulated ST8SIA1, a gene crucial for GD2 biosynthesis, suggesting that SLC1A5 inhibition may enhance GD2-directed immunotherapies.ConclusionSLC1A5 plays a pivotal role in neuroblastoma by promoting tumor progression and shaping an immunosuppressive microenvironment. The SRPS model, incorporating SLC1A5-associated genes, offers robust prognostic utility. Targeting SLC1A5 through advanced drug delivery systems and combined metabolic-immunotherapeutic strategies may enhance treatment specificity and efficacy. These findings provide a foundation for novel therapeutic approaches to improve outcomes in high-risk neuroblastoma patients.

Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn’s disease by bioinformatics analysis and machine learning

Crohn’s disease (CD) is a chronic inflammatory bowel disease with an unknown etiology. Ubiquitination plays a significant role in the pathogenesis of CD. This study aimed to explore the functional roles of ubiquitination-related genes in CD. Differentially expressed ubiquitination-related genes were identified by intersecting differentially expressed genes (DEGs) from the GSE95095 dataset in the Gene Expression Omnibus (GEO) database with a set of ubiquitination-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Key genes were selected by combining hub genes from the protein-protein interaction (PPI) network with feature genes identified by Lasso and Random Forest (RF) algorithms. Additionally, the correlation between key genes and immune infiltration was assessed, and Gene Set Enrichment Analysis (GSEA) of key genes was conducted. The efficacy of key genes was validated using ROC curves in an external dataset, and their expression was confirmed in LPS-induced Caco-2 cells through RT-qPCR. A total of 32 ubiquitination-related DEGs were identified, and two key genes (UBE2R2, NEDD4L) were selected. The infiltration of M2 macrophages was reduced in CD patients, with UBE2R2 expression negatively correlated and NEDD4L expression positively correlated with M2 macrophage infiltration. GSEA indicated that UBE2R2 was enriched in terpenoid backbone biosynthesis, regulation of autophagy, and limonene and pinene degradation, while NEDD4L was enriched in lysosome, Wnt signaling, and calcium signaling pathways. ROC curves demonstrated superior efficacy for NEDD4L. In LPS-induced Caco-2 cells, UBE2R2 expression increased, while NEDD4L expression decreased. A comprehensive analysis of the functional relationship between ubiquitination-related genes and CD can enhance understanding of CD pathogenesis and suggest potential therapeutic targets.

METTL5 Promotes Tumor Progression in Oral Squamous Cell Carcinoma by Activating the Myc Pathway.

It has been observed that methyltransferases-like 5 (METTL5) is a key mediator underlying tumorigenesis in humans. This study aimed to investigate the biological function, expression pattern, and clinical significance of METTL5 in oral squamous cell carcinoma (OSCC). Bioinformatics interrogations and immunohistochemical staining were utilized for determining the expression and localization of METTL5 in OSCC, and revealing the relationship between the expression of METTL5 and prognosis. Cell phenotype experiments and xenograft models were used to detect the impact of METTL5 silencing on OSCC. Gene Set Enrichment Analysis, Spearman correlation, and c-Myc overexpression plasmid was utilized for exploring the regulatory effects of METTL5 on the Myc pathway. METTL5 was overexpressed in OSCC and correlated with reduced survival. Cell proliferation, migration, and invasion were significantly inhibited by METTL5 knockdown invitro, and tumor growth was impaired invivo. Moreover, METTL5 was capable of activating the Myc pathway. The influences of knockdown of METTL5 on Cal27 cell biological behaviors were reversed by overexpression of c-Myc. Our data suggested that METTL5 may act as a putative oncogene and prognostic biomarker in OSCC. The Myc pathway appears to be involved in cell proliferation, migration, invasion, and apoptosis in OSCC mediated by METTL5.

HMOX1 as a potential drug target for upper and lower airway diseases: insights from multi-omics analysis

Background Oxidative stress is key in inflammatory airway diseases. Heme oxygenase 1 (HMOX1) regulates oxidative stress, but its role in airway diseases needs exploration.MethodsDifferentially expressed genes (DEGs) between healthy nasal mucosa and chronic rhinosinusitis with nasal polyps (CRSwNP) were identified from Gene Expression Omnibus (GEO). Candidate genes were further screened using Gene Set Enrichment Analysis (GSEA) and Random Forest (RF) algorithms. Causal inference between candidate genes and upper and lower airway diseases (CRSwNP, allergic rhinitis (AR), and asthma (AS)) was conducted using bidirectional two-sample Mendelian randomization (TwoSampleMR) analysis. Single-cell RNA sequencing (scRNA-seq) data were used to determine the cellular localization and intercellular interactions of candidate genes. Molecular docking was used to identify potential therapeutic agents.ResultsHMOX1 expression was significantly elevated in CRSwNP. TwoSampleMR analysis indicated a negative causal relationship between HMOX1 exposure and the occurrence of upper and lower airway diseases (CRSwNP [(odds ratio (OR)/95% confidence interval (CI): 0.945/(0.893–0.999), P = 0.044], AR [OR/95% CI: 0.997/(0.994–0.999), P = 0.007], and AS [OR/95% CI: 0.935/(0.895–0.977), P = 0.003]). scRNA-seq data revealed HMOX1 localization in M2 macrophages. Molecular docking identified 15 antioxidants, including Acetylcysteine and Quercetin, that can upregulate HMOX1 expression.ConclusionHMOX1 may have a protective role in the pathogenesis of upper and lower airway diseases (CRSwNP, AR, and AS) by modulating oxidative stress. Antioxidants that increase HMOX1 expression could offer new therapeutic avenues for these diseases.Clinical trialNot applicable.

Identification of hub genes and pathways in mouse with cold exposure

Abstract Background Cold exposure is linked to numerous diseases, yet the changes in key genes and pathways in mice under cold exposure remain unexplored. Understanding these alterations could offer insights into the mechanisms of cold resistance and contribute valuable ideas for treating cold-related diseases. Methods The dataset GSE148361 was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the “limma” package in R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on DEGs. The STRING (Search Tool for the Retrieval of Interacting Genes) database was used to construct a protein-protein interaction (PPI) network. Additionally, gene set enrichment analysis (GSEA) was conducted to identify pathways associated with key genes. miRNAs and upstream transcription factors (TFs) were predicted using the miRNet database. Results A total of 208 DEGs were identified, with 137 upregulated and 71 downregulated. In biological processes, DEGs were enriched in nucleotide and purine-containing compound metabolism. For cellular components, DEGs were involved in condensed chromosomes and mitochondrial protein complexes. In molecular functions, proton transmembrane transporter activity was enriched. KEGG pathway analysis showed significant enrichment in biosynthesis of unsaturated fatty acids, fatty acids, and pyruvate metabolism. From the PPI network, 12 hub genes were identified using MCODE. Four hub genes (Col3a1, fi203, Rtp4, Vcan) demonstrated similar trends in a validation set (GSE110420) and were significantly differentially expressed. GSEA analysis indicated that these four genes were enriched in pathways such as ECM-receptor interaction and cytokinecytokine receptor interaction. The hub gene network included 93 miRNAs and one TF Conclusion This study identified four hub genes as potential diagnostic biomarkers for cold exposure, providing insights for further research on the effects of cold on gene expression and disease.

High expression of tetraspanin CD63 predicts poor prognosis in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) has one of the poorest cancer prognosis rates; there is an urgent need to develop new drug therapies and biomarkers. CD63, a tetraspanin protein and well-known exosomal marker, is implicated in cancer progression; however, the significance of CD63 expression in ESCC remains unclear. Herein, we report the significance of CD63 expression by analyzing ESCC patient samples and ESCC cell lines. ESCC patient samples (n=86) were evaluated for CD63 expression by immunostaining; univariate and multivariate analysis using Cox proportional hazards were used to evaluate CD63 expression and clinicopathological features as prognostic factors for survival. For in vitro analysis, CD63 knockdown was performed in human ESCC cell lines (TE2 and TE15) using siRNA, and changes in proliferative potential. The gene expression change were also analyzed by microarray and gene set enrichment analysis. Overall survival was significantly worse in the CD63 high group (P=0.031, log-rank test). Five-year overall survival univariate analysis identified positive lymph nodes, pStage 3 or higher, and CD63 high expression as poor prognostic factors, while multivariate analysis showed that CD63 high expression was an independent poor prognostic factor (P=0.009, HR 2.56, 95%CI 1.269-5.167). CD63 knockdown in ESCC cell lines resulted in a phenotype of decreased proliferative potential. CD63 knockdown increased the expression of genes involved in cell adhesion and suppressed the expression of genes involved in granule secretion. CD63 also shown to affect nuclear import, protein complex localization, and ERBB-signaling pathways. In conclusion, CD63 affects gene expression in ESCC, and high tissue expression of CD63 predicts poor prognosis in ESCC patients.

A dynamic co-expression approach reveals Gins2 as a potential upstream modulator of HNSCC metastasis

Head and neck squamous cell carcinoma (HNSCC) is an aggressive cancer that is notably associated with a high risk of lymph node metastasis, a major cause of cancer mortality. Current therapeutic options remain limited to surgery supplemented by radio- or chemotherapy; however, these interventions often result in high-grade toxicities. Distant metastasis significantly contributed to the poor prognosis and decreased survival rates. However, the underlying molecular mechanisms remain poorly understood. Disease-related “omics” data provide a comprehensive overview of gene relationships, helping to decode the complex molecular mechanisms involved. Interactions between biological molecules are complex and highly dynamic across various cellular conditions, making traditional co-expression methods inadequate for understanding these intricate relationships. In the present study, a novel three-way interaction approach was employed to uncover dynamic co-expression relationships underlying the metastatic nature of HNSCC. Subsequently, the biologically relevant triples from statistically significant ones were defined through gene set enrichment analysis and reconstruction of the gene regulatory network. Finally, the validity of biologically relevant triplets was assessed at the protein level. The results highlighted the “PI3K/AKT/mTOR (PAM) signaling pathway” as a disrupted pathway involved in the metastatic nature of HNSCC. Notably, Gins2, identified as a switch gene, along with the gene pair {Akt2, Anxa2}, formed a statistically significant and biologically relevant triplet. It suggests that Gins2 could serve as a potential upstream modulator in the PAM signaling pathway, playing a crucial role in the distant metastasis of HNSCC. In addition, survival analysis of significant switch genes indicated that two genes, C19orf33 and Usp13, may be especially important for prognostic purposes in HNSCC.

Immune infiltration landscape and potential drug-targeted implications for hepatocellular carcinoma with ‘progression/hyper-progression’ recurrence

Background and aims Hepatocellular carcinoma (HCC) recurrence was previously characterized into four types, and patients with progression/hyper-progression recurrence (type III–IV) have an extremely poor prognosis. However, the immune background of resectable HCC, particularly in patients who experience recurrence, remains underexplored. Therefore, this study aimed to describe the immune landscape of resectable HCC, especially postoperative type III–IV recurrent HCC, and explore potential immune-targeted anti-relapse strategies for treated populations. Methods The differences in gene expression in patients with recurrent HCC (type I–II (solitary or multi-intrahepatic oligo recurrence) vs. type III–IV) were investigated using bulk sequencing. Multiple immune infiltration methods (single-sample gene set enrichment analysis (GSEA), Microenvironment Cell Populations-counter and ESTIMATE) were used, and patients were divided into four groups to identify four distinct immune subtypes: immune-enrichment/matrix-poor (IE1), immune-enrichment/matrix-rich (IE2), immune intermediate/matrix-rich (ITM) and immune desert/matrix-poor (ID). Co-expression and protein interaction analyses were used to identify characteristic genes in ITM closely associated with type III–IV recurrence, which was matched with drug targets for Huaier granules (HG) and lenvatinib. Virtual docking was used to identify potential therapeutic targets, and the results were verified using single-nuclei RNA sequencing and histological analysis. Results ITM was closely related to type III–IV recurrence and exhibited immunotherapy potential. The potential efficacy of inhibiting CCNA2, VEGFA, CXCL8, PLK2, TIMP1, ITGB2, ALDOA, ANXA5 and CSK in ITM reversal was determined. Molecular docking demonstrated that the proteins of these genes could bind to HG or lenvatinib. The immunohistochemical findings demonstrated differential VEGFA (p < .01) and PLK2 (p < .001) expression in ITM type and ID in type III–IV recurrent HCC. Conclusions Three primary immunotypes of resectable HCC (IE2, ITM and ID) were identified, and HG and lenvatinib could potentially overcome immune checkpoint blockade (ICB) resistance in ITM patients with HCC, particularly those classified as type III–IV.

UHRF1 promotes epithelial-mesenchymal transition mediating renal fibrosis by activating the TGF-β/SMAD signaling pathway

Renal fibrosis is widely recognized as the ultimate outcome of many chronic kidney diseases. The process of epithelial-mesenchymal transition (EMT) plays a critical role in the progression of fibrosis following renal injury. UHRF1, as a critical epigenetic regulator, may play an essential role in the pathogenesis and progression of renal fibrosis and EMT. However, the potential mechanisms remain to be elucidated. We aim to investigate the role of UHRF1 in EMT and renal fibrosis and to evaluate the potential benefits of Hinokitiol in preventing renal fibrosis. Based on data from the GEO and Nephroseq databases, UHRF1 exhibited high expression levels in the unilateral ureteral obstruction (UUO) model and in patients with nephropathy. Gene set enrichment analysis predicted that UHRF1 may function through the TGF-β signaling pathway in fibrosis. By establishing a TGF-β1-stimulated HK2 cell model and animal models of renal fibrosis induced by UUO and folic acid, we confirmed that UHRF1 was highly expressed in both in vitro and in vivo models of renal fibrosis. After knockdown of UHRF1 in vitro, we found that the TGF-β/SMAD signaling pathway was inhibited, renal tubular epithelial cell EMT was reduced and renal fibrosis was attenuated. Hinokitiol has been reported to reduce the expression of UHRF1 mRNA and protein. We observed that inhibition of UHRF1 with Hinokitiol ameliorated induced EMT and renal fibrosis by reducing SMAD2/3 phosphorylation in vivo and in vitro. Taken together, our data demonstrated that the upregulation of UHRF1 accelerated the EMT of renal tubular cells and renal fibrosis through the TGF-β/SMAD signaling pathway. Hinokitiol may ameliorate renal fibrosis by suppressing the expression of UHRF1 in the kidney.

Abstract B031: Proteomic profiling of oligometastatic castration-sensitive prostate cancer treated with stereotactic ablative radiotherapy

Abstract Background: The trajectory of metastatic castration-sensitive prostate cancer varies based on disease presentation and biology. While proteomic profiling studies of primary prostate tissue have linked protein expression with metastatic progression and prognosis, few studies have explored biological changes after treatment and their associations with response. Therefore, we conducted proteomic profiling of patients with oligometastatic castration-sensitive prostate cancer (omCSPC) treated with stereotactic ablative radiotherapy (SABR) or observation in the ORIOLE phase 2 randomized clinical trial (RCT). Methods Plasma from omCSPC patients in the ORIOLE trial was collected at baseline (day 1), day 90, and day 180. Protein abundance was quantified using the Olink Explore Assay. Differential expression from baseline to day 90 or 180 in each treatment arm was analyzed using a 2-sided t-test with Benjamini-Hochberg correction. Changes in protein expression at day 90 and 180 were compared with a Pearson correlation. Pathway enrichment was performed via gene set enrichment analysis (GSEA) using Reactome, KEGG, and Hallmark gene sets. Associations with progression-free survival (PFS) were analyzed using Kaplan-Meier and log-rank tests. Results In total, 1,472 proteins were assayed across 130 samples from 46 patients over 3 time points. Significant changes in expression post-SABR were noted at day 90 and 180 compared to baseline (using adjusted p-value cutoff of 0.05). At day 90, four proteins (FCRL1, CD22, TCL1A, FCER2) were downregulated; at day 180, only FCRL1, a Fc receptor-like gene family preferentially expressed in B cells, remained downregulated. No significant expression changes were found in the observation arm. Differential expression of proteins during follow-up were associated with PFS. In particular, LTO1, a maturation factor of ABCE1 important for ribosomal biogenesis and translation, was overexpressed at both day 90 and 180 post-SABR, and overexpression was associated with improved PFS at day 90 (median 24.5 mo vs 6 mo; p=0.017) and day 180 (median 33 mo vs 6 mo; p=0.043). These associations were absent in the observation arm. For proteins differentially expressed in the SABR arm at day 90, several signaling pathways were significantly enriched for patients with prolonged PFS, including positive enrichment of unfolded protein response (UPR) (p=0.008) and IL-4/IL-13 (p=0.009). At 180 days, several pathways were enriched for patients with prolonged PFS including negative enrichment of CTLA4 inhibitory signaling (p=0.005) and CD28 co-stimulation (p=0.008). Conclusion Proteomic analysis in omCSPC patients from the ORIOLE trial reveals significant expression changes at days 90 and 180 after SABR. B-cell signaling proteins were selectively downregulated in the SABR arm, and pathways associated with protein translation and immune response were enriched post-SABR for patients with prolonged PFS. Further research will explore connections to genomic and transcriptomic changes, with additional validation needed. Citation Format: Jarey H. Wang, Amol Shetty, Yang Song, Noura Radwan, Soha Bazyar, Xiaolei Shi, Theodore L. DeWeese, Daniel Y. Song, Ryan M. Phillips, Matthew P. Deek, Philip Sutera, Ana P. Kiess, Phuoc T. Tran. Proteomic profiling of oligometastatic castration-sensitive prostate cancer treated with stereotactic ablative radiotherapy. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B031.

Abstract P007: A digital pathology multimodal artificial intelligence algorithm is associated with pro-metastatic genomic pathways in oligometastatic prostate cancer

Abstract Purpose Oligometastatic castration-sensitive prostate cancer (omCSPC) is a clinically and biologically heterogeneous disease. A multimodal artificial intelligence (MMAI) algorithm (ArteraAI Prostate Test), which incorporates digital histopathology and clinical information, is prognostic for outcomes in localized prostate cancer. We hypothesized MMAI algorithms are also prognostic in omCSPC and correlate with tumor biology. Thus, we aimed to evaluate the association between MMAI score vector features (VF) with outcomes and genomics of omCSPC. Materials/Methods We correlated somatic pathogenic mutations and ArteraAI MMAI scores from 168 omCSPC patients. RNAseq profiling was performed on a subset of 65 metachronous patients. Somatic nonsynonymous pathogenic mutations from panel DNAseq were identified using Mutect2 and ClinVAR database. Pair-end reads of RNAseq were aligned to Human reference (hg38) using HISAT2. To identify the differentially mutated genes associated with MMAI scores, samples were binned separately based on the median or quartile MMAI scores, and Fisher’s exact test were used to evaluate differentially mutated genes between bins. Differential expression of genes were evaluated using DEseq2 and gene set enrichment analysis. VFs from the MMAI scores and correlated with mutations using Wilcoxon test. Results Median follow-up was 34.7 months. Overall survival was shorter in patients with high MMAI scores (top quartile) compared to those with low MMAI scores (bottom three quartiles, p=0.017). MMAI scores were significantly higher in synchronous compared to metachronous omCSPC (p&amp;lt;0.05). DNAseq demonstrated high MMAI scores were associated with higher incidence of BRCA2/ATM (p=0.008) and WNT pathway (APC/CTNNB1) mutations (p=0.13). Conversely, high MMAI scores were associated with lower incidence of SPOP mutations (p=0.03). RNAseq revealed differential gene expression based on MMAI score, with higher scores being enriched for epithelial-mesenchymal transition (EMT) pathway expression (p&amp;lt;0.01). Of the 128 VFs that contribute to MMAI scores, 32 were associated with somatic mutations. Specifically, 15 VFs associated with mutations in DNA damage response (p&amp;lt;0.01); 8 VFs associated with mutated genes of PIK3 pathway(p&amp;lt;0.01); 4 VFs associated with mutated genes of TP53 pathway(p&amp;lt;0.01); and 1 VF associated with genomic alteration in WNT pathway genes. Conclusions We demonstrate digital histopathology features using MMAI algorithms are prognostic for outcomes in omCSPC. We directly correlated MMAI scores with DNA mutations and transcriptional programs involved in metastatic propagation with higher scores associated with aggressive alterations (WNT, BRCA2/ATM, EMT) and lower scores associated with more indolent alterations (SPOP). Furthermore, VF were able to be directly correlated with DNA mutations. This suggests digital histopathology-based MMAI algorithms identify phenotypic pathologic features correlated with underlying biological genomic and transcriptomic processes and can be leveraged to better understand the heterogeneity of omCSPC. Citation Format: Matthew P. Deek, Yang Song, Amol Shetty, Philip Sutera, Adrianna A. Mendes, Kim Van der Eecken, Emmalyn Chen, Timothy Showalter, Trevor J Royce, Tamara Todorovic, Huei-Chung Huang, Scott A. Houck, Rikiya Yamashita, Ana Ponce Kiess, Daniel Y. Song, Tamara Lotan, Andre Esteva, Felix Y. Feng, Piet Ost, Phuoc T. Tran.A digital pathology multimodal artificial intelligence algorithm is associated with pro-metastatic genomic pathways in oligometastatic prostate cancer.[abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr P007

Abstract B017: Combining baseline microenvironment biomarkers with hypoxia imaging to predict radiochemotherapy outcomes in head and neck cancer

Abstract Background: Hypoxia contributes to tumor therapy resistance and it can be evaluated through imaging, such as [18F]fluoromisonidazole (FMISO)-PET, or hypoxia-associated gene expression profiling, among other modalities. Integrating imaging with tumor microenvironment features may provide a more comprehensive prognostic assessment. This study evaluates the prognostic value of combining FMISO-PET hypoxia imaging with baseline gene expression profiles in head and neck squamous cell carcinoma (HNSCC) patients undergoing radiochemotherapy (RCTx). Methods FMISO-PET images were obtained at baseline and at weeks 1, 2, and 5 during RCTx to assess tumor-to-background ratios (TBR) and hypoxic volumes (HV). Gene expression from pre-treatment biopsies was analyzed using Affymetrix microarrays. Gene set enrichment analysis of cancer hallmarks was conducted, and cell type fractions were imputed using CIBERSORTx. Correlation and LASSO analyses were conducted to identify baseline gene expression and cell type fractions associated with hypoxia imaging at baseline and during RCTx. Cox regression models were used to integrate imaging and gene expression data for predicting loco-regional tumor control (LRC). Results Baseline Epithelial to Mesenchymal Transition and Hypoxia gene sets were strongly correlated with hypoxia imaging parameters at week 2. A LASSO model identified baseline gene expression associated with FMISO-PET parameters (TBRpeak, HV16, and residual hypoxia) at week 2, indicating a predisposition for hypoxia persistence. AKR1A1, PITPNB, CTSK, and PEF1 gene expression levels were associated with LRC. In the tumor microenvironment, CD4 memory resting T cells and fibroblasts at baseline correlated with hypoxia imaging at weeks 1 and 2, with high levels of these cell fractions linked to decreased LRC. The fibroblast cell fraction positively correlated with CTSK transcript levels (Spearman ρ = 0.59, p &amp;lt; 0.05). K-means clustering based on CTSK and fibroblast levels identified patient subgroups with distinct LRC outcomes (HR [95% CI]: 3.491 [1.165-10.46], p = 0.0256). Importantly, clustering remained an independent predictor of LRC when analyzed with baseline FMISO TBRpeak and HV16 in multivariate Cox regression (HR [95% CI]: 3.883 [1.224-12.321], p = 0.0213). However, when TBRpeak and HV16 at week 2 were included in the model, the impact of the fibroblast cell fraction/CTSK clustering was attenuated (HR [95% CI]: 2.899 [0.918-9.156], p = 0.0697). Conclusion This study highlights the potential for integrating baseline tumor microenvironment markers, such as fibroblast fraction and CTSK expression, with dynamic hypoxia imaging to improve HNSCC prognostic accuracy. High fibroblast cell fraction and CTSK levels at baseline may predispose tumors to treatment-resistant hypoxia, confirmed by persistent hypoxia measured by FMISO-PET at week 2 . By capturing both predisposition to and hypoxia imaging, this approach may enhance the personalization of radiochemotherapy for high-risk HNSCC patients. Citation Format: María J. Besso, Verena Bitto, Cristina Conde-Lopez, Mareike Roscher, Steffen Löck, Annett Linge, Mechthild Krause, Michael Baumann, Ina Kurth. Combining baseline microenvironment biomarkers with hypoxia imaging to predict radiochemotherapy outcomes in head and neck cancer. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B017.

Identification of Ferroptosis-related Genes for Diabetic Nephropathy by Bioinformatics and Experimental Validation.

The present study delves into the exploration of diagnostic biomarkers linked with ferroptosis in the context of diabetic nephropathy, unraveling their underlying molecular mechanisms. In this study, we retrieved datasets GSE96804 and GSE30529 as the training cohort, followed by screening for Differentially Expressed Genes (DEGs). By intersecting these DEGs with known ferroptosisrelated genes, we obtained the differentially expressed genes related to ferroptosis (DEFGs). Subsequently, Weighted Correlation Network Analysis (WGCNA) was carried out to identify key modules associated with Diabetic Nephropathy (DN), culminating in the identification of a significant gene. Enrichment analysis and Gene Set Enrichment Analysis (GSEA) were then carried out on the DEFGs and genes linked to the significant gene. To validate our findings, we employed cohorts GSE30528 and GSE43950, utilizing ROC curve analysis to assess diagnostic efficacy for DN, as measured by the area under the curve (AUC). Immune cell infiltration was analyzed and compared between groups using the CIBERSORT algorithm. Bayesian colocalization analysis was performed to examine the co-location of DEFGs and DN. Finally, to validate the hub genes identified, we conducted quantitative real-time polymerase chain reaction (qRT-PCR) experiments in vitro. FUZ, GLI1, GLI2, GLI3, and DVL2 were identified as the hub genes. Functional enrichment analysis demonstrated that ferroptosis and immune response play an important role in DN. ROC analysis showed that the identified genes had good diagnostic efficiency in DN. The results of the immune infiltration analysis showed that there may be crosstalk between ferroptosis and immune cells in DN. Bayesian co-localization analysis revealed the genetic correlation between the hub genes and DN. The outcomes of the qRT-PCR analyses corroborated the reliability of the identified hub genes as robust molecular markers for targeted therapy in DN. The interplay between immune inflammatory reactions and ferroptosis emerges as a crucial pathogenic mechanism, offering novel insights into the molecular therapy of DN. Furthermore, the identification of FUZ, GLI1, GLI2, GLI3, and DVL2 as potential targets holds promise for future therapeutic interventions aimed at treating DN.

Identification of a metabolic-immune signature associated with prognosis in colon cancer and exploration of potential predictive efficacy of immunotherapy response

The role of metabolic reprogramming of the tumor immune microenvironment in cancer development and immune escape has increasingly attracted attention. However, the predictive value of differences in metabolism-immune microenvironment on the prognosis of colon cancer (CC) and the response to immunotherapy have not been elucidated. The aim of this study was to investigate changes in metabolism and immune profile of CC and to identify a reliable signature for predicting prognosis and therapeutic response. The metabolism and immune-related differential genes in CC were screened out by differential gene expression analysis. A metabolism and immune related prognostic signature was established by the least absolute shrinkage and selection operator (LASSO) Cox algorithm. The training cohort with 417 patients from The Cancer Genome Atlas (TCGA) database and the validation cohort of 232 patients from GSE17538 were used to confirm the robustness of the prognostic signature. Immunohistochemical staining scores were used to assess gene expression levels in our clinical samples. Gene ontology (GO) analysis, gene set enrichment analysis (GSEA), single nucleotide variation (SNV) analysis, immune infiltration and immune factors analysis were used to explore the characteristics of patients with different subtypes. Multiple cancer immunotherapy datasets were used to assess the response of patients with different subtypes to immune checkpoint inhibitors. We established the Metabolism and Immune-Related Prognostic Score (MIRPS) based on six genes (CD36, PCOLCE2, SCG2, CALB2, STC2, CLDN23) to predict the prognosis of CC patients. We found a correlation between MIRPS and the malignant phenotype, microsatellite subtype, mutation load, and immune escape in CC. Tumors with high MIRPS presented a higher tumor mutation load and a more prominent immunosuppressive microenvironment. This subset of patients may potentially respond well to immune checkpoint inhibitor therapy. MIRPS may be used as a novel prognostic tool for CC and have potential value for immunotherapy response prediction.

Pan-cancer and experimental analyses reveal the immunotherapeutic significance of CST2 and its association with stomach adenocarcinoma proliferation and metastasis

PurposeCystatin 2 (CST2) is a cysteine protease inhibitor, and recent research suggests its potential involvement in cancer development. However, its role in the occurrence, progression, and prognosis of pan-cancer has not been systematically investigated.Materials and methodsThis study comprehensively analyzes the differential expression of CST2 in pan-cancer. The expression distribution patterns of CST2 were examined using single-cell datasets. Furthermore, we conducted a comprehensive evaluation of the correlation between CST2 expression and various factors. These factors include prognosis, immune cell infiltration, immune-related genes, mutations, methylation, tumor mutation burden (TMB), and microsatellite instability (MSI). In addition, we analyzed the sensitivity of drugs dependent on CST2 expression. We utilized gene set enrichment analysis (GSEA) analysis to explore the biological functions of CST2 across different cancer types. Finally, in gastric cancer cell lines, we will investigate the impact of CST2 knockout on expression levels, clonal proliferation, cell apoptosis, and cell migration.ResultsCST2 exhibits abnormal overexpression in multiple tumors. Single-cell analysis reveals high expression of CST2 in fibroblasts. CST2 is closely associated with prognosis, immune cell infiltration, immune-related genes, mutations, methylation, TMB, and MSI. Enrichment analysis demonstrated a significant correlation between CST2 and immune-related pathways. In stomach adenocarcinoma (STAD), CST2-related risk models are associated with prognosis and demonstrate strong predictive capabilities, while also being closely linked to the immune microenvironment. Drug sensitivity analysis indicates the correlation between CST2 and 21 chemotherapy drugs. Finally, experimental validation revealed significantly elevated expression of CST2 in STAD, indicating its role as a driver gene in regulating malignant cell proliferation and migration.ConclusionCST2 serves as a potential tumor immune biomarker, playing a critical facilitating role in the proliferation and migration processes of STAD.

Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning

IntroductionType 2 diabetes (T2D) is a complex metabolic disorder with significant global health implications. Understanding the molecular mechanisms underlying T2D is crucial for developing effective therapeutic strategies. This study employs single-cell RNA sequencing (scRNA-seq) and machine learning to explore the the pathogenesis of T2D, with a particular focus on immune cell infiltration.MethodsWe analyzed scRNA-seq data from islet cells of T2D and nondiabetic (ND) patients, identifying differentially expressed genes (DEGs), especially those related to metal ion transport (RMITRGs). We employed 12 machine learning algorithms to develop predictive models and assessed immune cell infiltration using single-sample gene set enrichment analysis (ssGSEA). Correlations between immune cells and key RMITRGs were investigated, and the interactions among these genes were explored through protein-protein interaction (PPI) network analysis. Additionally, we performed a detailed cell-cell communication analysis to identify significant signaling pathways in T2D.ResultsOur analysis identified 1953 DEGs between T2D and ND patients, with the Stepglm[backward] plus GBM model demonstrating high predictive accuracy and identifying 13 hub RMITRGs. Twelve protein structures were predicted using AlphaFold 3, revealing potential functional conformations. We observed a strong correlation between hub RMITRGs and immune cells, and PPI network analysis revealed key interactions. Cell-cell communication analysis highlighted 16 active signaling pathways, with CXCL, MIF, and COMPLEMENT linked to immune and inflammatory responses, and WNT, KIT, LIFR, and HGF pathways uniquely activated in T2D.ConclusionOur analysis identified genes crucial for T2D, emphasizing ion transport, signaling, and immune cell interactions. These findings suggest therapeutic potential to enhance T2D management. The identified pathways and genes provide valuable insights into the disease mechanisms and potential targets for intervention.

Evolutionary constrained genes associated with autism spectrum disorder across 2,054 nonhuman primate genomes

BackgroundSignificant progress has been made in elucidating the genetic underpinnings of Autism Spectrum Disorder (ASD). However, there are still significant gaps in our understanding of the link between genomics, neurobiology and clinical phenotype in scientific discovery. New models are therefore needed to address these gaps. Rhesus macaques (Macaca mulatta) have been extensively used for preclinical neurobiological research because of remarkable similarities to humans across biology and behaviour that cannot be captured by other experimental animals.MethodsWe used the macaque Genotype and Phenotype (mGAP) resource consisting of 2,054 macaque genomes to examine patterns of evolutionary constraint in known human neurodevelopmental genes. Residual variation intolerance scores (RVIS) were calculated for all annotated autosomal genes (N = 18,168) and Gene Set Enrichment Analysis (GSEA) was used to examine patterns of constraint across ASD genes and related neurodevelopmental genes.ResultsWe demonstrated that patterns of constraint across autosomal genes are correlated in humans and macaques, and that ASD-associated genes exhibit significant constraint in macaques (p = 9.4 × 10− 27). Among macaques, many key ASD-implicated genes were observed to harbour predicted damaging mutations. A small number of key ASD-implicated genes that are highly intolerant to mutation in humans, however, showed no evidence of similar intolerance in macaques (CACNA1D, MBD5, AUTS2 and NRXN1). Constraint was also observed across genes associated with intellectual disability (p = 1.1 × 10− 46), epilepsy (p = 2.1 × 10− 33) and schizophrenia (p = 4.2 × 10− 45), and for an overlapping neurodevelopmental gene set (p = 4.0 × 10− 10).LimitationsThe lack of behavioural phenotypes among the macaques whose genotypes were studied means that we are unable to further investigate whether genetic variants have similar phenotypic consequences among nonhuman primates.ConclusionThe presence of pathological mutations in ASD genes among macaques, along with evidence of similar genetic constraints to those in humans, provides a strong rationale for further investigation of genotype-phenotype relationships in macaques. This highlights the importance of developing primate models of ASD to elucidate the neurobiological underpinnings and advance approaches for precision medicine and therapeutic interventions.

Comprehensive Analysis Reveals the Potential Diagnostic Value of Biomarkers Associated With Aging and Circadian Rhythm in Knee Osteoarthritis.

Knee osteoarthritis (KOA) is characterized by structural changes. Aging is a major risk factor for KOA. Therefore, the objective of this study was to examine the role of genes related to aging and circadian rhythms in KOA. This study identified differentially expressed genes (DEGs) by comparing gene expression levels between normal and KOA samples from the GEO database. Subsequently, we intersected the DEGs with aging-related circadian rhythm genes to obtain a set of aging-associated circadian rhythm genes differentially expressed in KOA. Next, we conducted Mendelian randomization (MR) analysis, using the differentially expressed aging-related circadian rhythm genes in KOA as the exposure factors, their SNPs as instrumental variables, and KOA as the outcome event, to explore the causal relationship between these genes and KOA. We then performed Gene Set Enrichment Analysis (GSEA) to investigate the pathways associated with the selected biomarkers, conducted immune infiltration analysis, built a competing endogenous RNA (ceRNA) network, and performed molecular docking studies. Additionally, the findings and functional roles of the biomarkers were further validated through experiments on human cartilage tissue and cell models. A total of 75 differentially expressed aging-circadian rhythm related genes between the normal group and the KOA group were identified by difference analysis, primarily enriched in the circadian rhythm pathway. Two biomarkers (PFKFB4 and DDIT4) were screened by MR analysis. Then, immune infiltration analysis showed significant differences in three types of immune cells (resting dendritic cells, resting mast cells, and M2 macrophages), between the normal and KOA groups. Drug prediction and molecular docking results indicated stable binding of PFKFB4 to estradiol and bisphenol_A, while DDIT4 binds stably to nortriptyline and trimipramine. Finally, cell lines with stable expression of the biomarkers were established by lentiviral infection and resistance screening, Gene expression was significantly elevated in overexpressing cells of PFKFB4 and DDIT4 and reversed the proliferation and migration ability of cells after IL-1β treatment. Two diagnostic and therapeutic biomarkers associated with aging-circadian rhythm in KOA were identified. Functional analysis, molecular mechanism exploration, and experimental validation further elucidated their roles in KOA, offering novel perspectives for the prevention and treatment of the disease.