ssGSEA Analysis Research Articles

Pancancer analysis of NDUFA4L2 with focused role in tumor progression and metastasis of colon adenocarcinoma.

Colon adenocarcinoma (COAD) is a prevalent gastrointestinal malignant disease with a high mortality rate, and identification of novel prognostic biomarkers and therapeutic targets is urgently needed. Although NDUFA4L2 has high expressions in various tumors and affects tumor progression, its role in COAD remains unclear. The role of NDUFA4L2 in COAD was analyzed utilizing datasets available from public databases including The Cancer Genome Atlas, The Genotype-Tissue Expression (GTEx), Gene Expression Omnibus, Alabama Cancer Database (UALCAN), and The Human Protein Atlas databases. The prognostic value of NDUFA4L2 was determined using Kaplan-Meier analysis and Cox regression analysis. To investigate the possible mechanism underlying the role of NDUFA4L2 in COAD, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were employed. The correlation between NDUFA4L2 expression and immune cell infiltration levels was examined through single-sample gene set enrichment analysis (ssGSEA). The NDUFA4L2 expression levels in COAD patients and cell lines were validated through immunohistochemistry, immunofluorescence, qRT-PCR, and Western blot. Wound healing assay was also performed to evaluate the effect of NDUFA4L2 on COAD metastasis. Furthermore, the NDUFA4L2 mediated competing endogenous RNA (ceRNA) regulatory network was predicted and constructed through a variety of databases. The comprehensive pan-cancer analysis showed that NDUFA4L2 possesses diagnostic and prognostic value in many cancers, especially in COAD. GO-KEGG and GSEA analyses indicated that NDUFA4L2 was associated with multiple biological functions including epithelial-mesenchymal transition and adaptation to hypoxia. The ssGSEA analysis showed that NDUFA4L2 expression was associated with immune infiltration. In vitro experiments confirmed upregulation of NDUFA4L2 in COAD tissues and cell lines, and NDUFA4L2 overexpression significantly promoted migration of COAD cells. In addition, the C9orf139 /miR-194-3p axis was speculated as the possible upstream regulators of NDUFA4L2 in COAD. This study demonstrated that NDUFA4L2 upregulation was correlated with tumor progression, relapsed prognosis and aggressive migration of COAD, suggesting that NDUFA4L2 can act as an effective prognostic biomarker and a promising therapeutic target for COAD treatment.

Elucidating the molecular interactions and immune modulation of bisphenols exposure in the pathogenesis of polycystic ovary syndrome

Bisphenols (BPs) are known endocrine disruptors potentially contributing to the pathogenesis of Polycystic Ovary Syndrome (PCOS). This study aims to elucidate the molecular interactions between BPs and PCOS-related genes and their combined effects on PCOS development. We identified common genes associated with BPs and PCOS using the CTD. Differential expression analysis was performed on three GEO datasets, leading to the identification of differentially expressed genes (DEGs). Protein-Protein Interaction (PPI) network construction, enrichment analysis, single-gene Gene Set Enrichment Analysis (GSEA), and immune cell infiltration analysis were carried out. A nomogram was developed for PCOS risk prediction, and molecular docking studies were performed using AutoDock Vina, with interaction visualizations via PyMOL. We identified 139 common genes between BPs exposure and PCOS, enrichment analysis highlighted pathways related to hormone metabolism, ovarian steroidogenesis, and p53 signaling. Four hub DEGs (PBK, CCNE2, LPCAT2, S100P) were identified, and a nomogram incorporating these genes demonstrated excellent predictive accuracy. GSEA revealed roles in cell adhesion, immune response, and metabolism. ssGSEA analysis showed significant differences in immune cell infiltration between PCOS and control groups, with notable correlations between hub DEGs and immune cells. Molecular docking indicated strong binding affinities between the hub DEGs and BPAF, suggesting potential disruptions induced by BPs. BPs exposure is associated with significant molecular and immunological changes in PCOS, impacting genes involved in hormone regulation, immune response, and metabolic pathways. The strong binding affinities between BPs and key PCOS-related genes reveal their potential role in exacerbating PCOS, providing insights for targeted therapeutic strategies.

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Comprehensive analysis of Epha10 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in non-small cell lung cancer

The EphA family belongs to a large group of membrane receptor tyrosine kinases. Emerging evidence indicates that the EphA family participates in tumour occurrence and progression. Nonetheless, the expression patterns and prognostic values of the nine EphAs in non-small cell lung cancer (NSCLC) have rarely been studied before. In the current study, we comprehensively analysed the expression and prognostic role of EphA family members by different means. The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases were used to investigate the expression of EphAs in NSCLC. The cBioPortal database was applied to analyse the prognostic values and genetic mutations of EphAs.We discovered that the expression of EphA10 was significantly higher in NSCLC tissues than in adjacent noncancerous tissues, and survival analyses showed that a higher level of EphA10 predicted poor prognosis. Further exploration into the role of EphA10 by ESTIMATE, CIBERSORT, and ssGSEA analysis found that it was also related to immune infiltration and higher expression of targets of ICI targets. In conclusion, this study revealed that among the EphA family members, EphA10 played an oncogenic role and was a promising biomarker for poor prognosis and better immunotherapy response in NSCLC.

Development and validation of a hypoxia- and mitochondrial dysfunction- related prognostic model based on integrated single-cell and bulk RNA sequencing analyses in gastric cancer.

Gastric cancer (GC) remains a major global health threat ranking as the fifth most prevalent cancer. Hypoxia, a characteristic feature of solid tumors, significantly contributes to the malignant progression of GC. Mitochondria are the major target of hypoxic injury that promotes mitochondrial dysfunction during the development of cancers including GC. However, the gene signature and prognostic model based on hypoxia- and mitochondrial dysfunction-related genes (HMDRGs) in the prediction of GC prognosis have not yet been established. The gene expression profile datasets of stomach cancer patients were retrieved from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Prognostic genes were selected using Least Absolute Shrinkage andSelection Operator Cox (LASSO-Cox) regression analysis to construct a prognostic model. Immune infiltration was evaluated through ESTIMATE, CIBERSORT, and ssGSEA analyses. Tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were utilized to explore implications for immunotherapy. Furthermore, in vitro experiments were conducted to validate the functional roles of HMDRGs in GC cell malignancy. In this study, five HMDRGs (ZFP36, SERPINE1, DUSP1, CAV1, and AKAP12) were identified for developing a prognostic model in GC. This model stratifies GC patients into high- and low-risk groups based on median risk scores. A nomogram predicting overall survival (OS) was constructed and showed consistent results with observed OS. Immune infiltration analysis indicated that individuals in the high-risk group tend to exhibit increased immune cell infiltration. Additionally, analysis of cancer immunotherapy responses revealed that high-risk group patients exhibit poorer responses to cancer immunotherapy compared to the low-risk group. Immunohistochemistry (IHC) staining indicated that the expression levels of HMDRGs were remarkably correlated with GC, of which, SERPINE1 displayed the most pronounced up-regulation, while ZFP36 exhibited the most notable down-regulation in GC patients. Furthermore, in vitro investigation validated that SERPINE1 and ZFP36 contribute to the malignant processes of GC cells correlated with mitochondrial dysfunction. This study presents a novel and efficient approach to evaluate GC prognosis and immunotherapy efficacy, and also provides insights into understanding the pathogenesis of GC.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1.

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Association of GATA3 expression in triple-positive breast cancer with overall survival and immune cell infiltration

Breast cancer remains a leading cause of cancer-related mortality among women, with triple-positive breast cancer (TPBC) being a particularly aggressive subtype. GATA binding protein 3 (GATA3) plays a crucial role in the luminal differentiation of breast epithelium and T-cell differentiation. However, the relationship between GATA3 and immune infiltration in TPBC remains unclear. This study collected and analyzed TPBC data from The Cancer Genome Atlas (TCGA), METABRIC, and GSE123845 databases. Univariate and multivariate Cox regression analyses, along with Kaplan–Meier survival analyses, were employed to assess the prognostic value of GATA3 and other clinical features. Subsequently, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and regulatory mechanisms of GATA3 in TPBC. Additionally, ssGSEA analysis revealed the connection between GATA3 and immune infiltration. And the effects of neoadjuvant chemotherapy and immunotherapy on GATA3 expression were also explored. Finally, clinical samples were used to detect the relationship between GATA3 expression and tumor infiltrating lymphocyte (TIL) levels. Our results demonstrated that GATA3 was significantly overexpressed in TPBC tissues compared to normal tissues (P < 0.05). A positive correlation between GATA3 mRNA and protein levels was observed (R = 0.55, P < 0.05). Notably, high GATA3 expression was associated with poor overall survival (HR = 1.24, 95% confidence interval (CI) 1.25–11.76, P < 0.05). GSEA indicated significant enrichment of immune-related gene sets in low GATA3 expression groups. Furthermore, pathologic complete response (pCR) patients exhibited significantly lower GATA3 expression compared to residual disease (RD) patients. Mutation analysis revealed higher PIK3CA and TP53 mutation rates in high GATA3 expression groups. Finally, clinical validation data showed that the degree of TILs was significantly higher in the low GATA3 expression group. In conclusion, this study suggests that high GATA3 expression may be associated with poor prognosis and may reduce immune infiltration in TPBC.

Correlation between Complement C1q A Chain (C1QA) and Macrophages in the Progression of Carotid Atherosclerosis.

There is increasing evidence that macrophages are involved in the development of carotid atherosclerosis (CAS), but the specific mechanism is still unclear. We aimed to explore the key genes that play a regulatory role on macrophages in the progression of CAS. From 2021 August to 2023 August, GEO datasets GSE100927 and GSE43292 were downloaded and the key gene modules related to CAS were identified by weighted Gene co-expression network analysis (WGCNA). Kyoto Encyclopedia of Genes and Genes (KEGG) pathway analysis was performed on the genes of the key modules to identify common gene enrichment pathways. Differential expression analysis of pathway-related genes was performed by the "limma" package of R software. Case groups were categorized into high and low expression groups based on the expression levels of key genes, and ssGSEA immune infiltration analysis was performed. The turquoise module of GSE100924 (threshold=12) and the brown module of GSE43292 (threshold=7) were obtained through WGCNA analysis. The analysis of KEGG showed that the differentially expressed genes in the turquoise and brown modules were co-enriched in the staphylococcus aureus infection signaling pathway. Differential expression analysis identified 18 common differentially expressed genes, all of which were highly expressed in the case group. C1QA is the gene of interest. According to ssGSEA analysis, the high expression group of C1QA showed a significant increase in the number of macrophages (GSE43292, P=0.0011; GSE100927, P=0.025). This study identified the key gene C1QA involved in regulating macrophage functional activity during the CAS process, providing new ideas for effective control of CAS.

TICRR as a potential prognostic biomarker for lung adenocarcinoma: A comprehensive analysis using TCGA database.

To investigate the role of TopBP1-interacting checkpoint and replication regulator (TICRR) in the tumorigenesis and prognosis of lung adenocarcinoma (LUAD) patients. Wilcoxon signed-rank test and logistic regression were utilized to analyze the relationship between clinical characteristics and TICRR expression in LUAD from TCGA dataset. Kaplan-Meier plots and Cox regressions were used to assess the impact of TICRR impact on prognosis. ROC curves and nomograms were generated to further evaluate the relationship between TICRR expression and the risk of LUAD. Gene set enrichment analysis (GSEA) was conducted on TCGA dataset, and ssGSEA was employed to investigate the association between TICRR and immune infiltrates. The results showed that high TICRR expression was significantly associated with various clinical factors including gender, age, pathological stage, T stage, N stage, M stage, outcome of primary therapy and smoking status. ROC curves also demonstrated that TICRR was a promising biomarker for molecular pathology diagnosis in LUAD patients (AUC = 0.952). Further analysis using gene ontology (GO) term enrichment and GSEA revealed an abnormal correlation between TICRR expression and cell division. Interestingly, ssGSEA analysis showed that TICRR expression correlated with multiple immune cell types, such as Th2 cell, TFH cell, mast cell, iDC, eosinophils, and dendritic cell. Lastly, the KM-plotters indicated that LUAD patients with high TICRR expression obtained worse life expectancy (P < .001). TICRR has proven to be a valuable tool in predicting disease progression and prognosis in patients with LUAD, thereby establishing itself as a fitting biomarker for forecasting overall survival (OS) of LUAD patients.

Unraveling Crucial Mitochondria-Related Genes in the Transition from Ulcerative Colitis to Colorectal Cancer.

To clarify the significance of mitochondria-related differentially expressed genes (MTDEGs) in UC carcinogenesis through a bioinformatics analysis and provide potential therapeutic targets for patients with UC associated colorectal cancer. Microarray GSE37283 was utilized to investigate differentially expressed genes (DEGs) in UC and UC with neoplasia (UCN). MTDEGs were identified by intersecting DEGs with human mitochondrial genes. Utilizing LASSO and random forest analyses, we identified three crucial genes. Subsequently, using ROC curve to investigate the predictive ability of three key genes. Following, three key genes were confirmed in AOM/DSS mice model by Real-time PCR. Finally, single-sample gene set enrichment analysis (ssGSEA) was employed to explore the correlation between the hub genes and immune cells infiltration in UC carcinogenesis. The three identified hub MTDEGs (HMGCS2, MAVS, RDH13) may exhibit significant diagnostic specificity in the transition from UC to UCN. Real-time PCR assay further confirmed that the expressions of HMGCS2 and RDH13 were significantly downregulated in UCN mice than that in UC mice. ssGSEA analysis revealed the hub genes were highly associated with CD56dim natural killer cells. RDH13, HMGCS2, and MAVS may become diagnostic indicators and potential biomarkers for UCN. Our research has the potential to enhance our understanding of the mechanisms underlying carcinogenesis in UC.

FKBP3, a poor prognostic indicator, promotes the progression of LUAD via regulating ferroptosis and immune infiltration.

Ferroptosis was reported to possess the therapeutic potentials in various human cancers. In the present study, we explored the expression, clinical significance and the molecular mechanism of FK506 binding protein 3 (FKBP3) in the progression of lung adenocarcinoma (LUAD). Cox regression was performed to obtain the prognosis related to differentially expressed genes (DEGs) in LUAD datasets from TCGA. We also downloaded the ferroptosis-related gene datasets from GeneCards. Venn diagram was performed to find the intersecting genes and FKBP3 was selected as the targeted gene by analyzing the diagnostic and prognostic values of Top10 intersecting genes. Moreover, univariate and multivariate analyses were performed to evaluate the association between clinicopathological factors and survival rates. GO/KEGG and GSEA analysis was performed to explore the function of FKBP3 in LUAD progression. Protein-protein interaction (PPI) network was performed via STRING database and the top10 hub genes were selected. Finally, the relationship between FKBP3 and immune infiltration was explored by ssGSEA analysis. Firstly, 184 genes associated with the prognosis of LUAD and ferroptosis were obtained. FKBP3 was found to be significantly associated with a poor overall survival rate of LUAD patients. Immunohistochemical staining results showed that FKBP3 was highly located in cytoplasm and membrane of cells in LUAD tissues. PPI network analysis results showed that HDAC1, YY1, HDAC2, MTOR, PSMA3, PIN1, NCL, C14orf166, PIN4, and LARP6 were the top10 hub genes. Furthermore, spearman analysis results showed that the expression of FKBP3 was positively correlated with the abundance of Th2 cells and T helper cells. High level of FKBP3 was associated with poor prognostic outcomes of LUAD patients, which also inhibited immune infiltration in LUAD tissues. Additionally, FKBP3 was involved in regulating the ferroptosis process in LUAD patients. Thus, FKBP3 possessed the tumor promotion role might be involving in regulating ferroptosis and immune infiltration in LUAD progression.

SPACA6P-AS: a trailblazer in breast cancer pathobiology and therapeutics

ObjectiveThe primary objective of this investigation is to delve into the involvement of the long noncoding RNA (lncRNA) SPACA6P-AS in breast cancer (BC) development, focusing on its expression pattern, association with clinical-pathological features, impact on prognosis, as well as its molecular and immunological implications.MethodsBioinformatics analysis was conducted utilizing RNA sequencing data of 1083 BC patients from the TCGA database. Functional exploration of SPACA6P-AS was carried out through the construction of survival curves, GO and KEGG enrichment analysis, and single-sample gene set enrichment analysis (ssGSEA). Furthermore, its functionality was validated through in vitro cell experiments and in vivo nude mouse model experiments.ResultsSPACA6P-AS showed a remarkable increase in expression levels in BC tissues (p < 0.001) and demonstrated a close relationship to poor prognosis (overall survival HR = 1.616, progression-free interval HR = 1.40, disease-specific survival HR = 1.54). Enrichment analysis revealed that SPACA6P-AS could impact biological functions such as protease regulation, endopeptidase inhibitor activity, taste receptor activity, taste transduction, and maturity-onset diabetes of the young pathway. ssGSEA analysis indicated a negative correlation between SPACA6P-AS expression and immune cell infiltration like dendritic cells and neutrophils, while a positive correlation was observed with central memory T cells and T helper 2 cells. Results from in vitro and in vivo experiments illustrated that silencing SPACA6P-AS significantly inhibited the proliferation, migration, and invasion capabilities of BC cells. In vitro experiments also highlighted that dendritic cells with silenced SPACA6P-AS exhibited enhanced capabilities in promoting the proliferation of autologous CD3 + T cells and cytokine secretion. These discoveries elucidate the potential multifaceted roles of SPACA6P-AS in BC, including its potential involvement in modulating immune cell infiltration in the tumor microenvironment.ConclusionThe high expression of lncRNA SPACA6P-AS in BC is closely linked to poor prognosis and may facilitate tumor progression by influencing specific biological processes, signaling pathways, and the immune microenvironment. The regulatory role of SPACA6P-AS positions it as a prospective biomarker and target for therapeutic approaches for BC diagnosis and intervention.

SFXN3 is a Prognostic Marker and Promotes the Growth of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a heterogeneous disease with rapid progression and frequent mutations. Sideroflexin3 (SFXN3) has been shown to be involved in various neurodegenerative diseases. However, the role of SFXN3 in AML remains unclear. The level and prognostic value of SFXN3 were assessed in pan-cancer, especially AML, based on the data obtained from the TCGA database. The effect and mechanism of SFXN3 in AML were measured by fluorescence-activated cell sorting (FACS), qRT-PCR, western blotting in vitro and in vivo. The correlation between SFXN3 and the infiltration of immune cells in AML was assessed via cibersort and ssGSEA analyses. SFXN3 is expressed at higher levels in AML, and high SFXN3 level is associated with decreased overall survival rate (OSR) in AML. Next, knockdown of SFXN3 results in enhanced cell apoptosis and dropped cell proliferation. Then, knockdown of SFXN3 caused a reduction in the expression of CyclinD1 (CCND1) and nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1). Finally, SFXN3 may related to the immunosuppressive state of AML. Increased SFXN3 expression is detected in AML, which indicates a poor prognosis and may link to immunosuppressive state of AML. In addition, SFXN3 can inhibit AML cells apoptosis and promote cell proliferation via enhancing CCND1 and NFKB1 levels.

#971 Effects of arsenic trioxide on MMP9/IL-17A expression in lupus nephritis—results from bioinformatics analysis and in vitro studies

Abstract Background and Aims Previous research has indicated that ATO treatment at low doses may decrease the likelihood of flares in active systemic lupus erythematosus (SLE) patients, but the pharmacological mechanisms of such effect have not been studied. Method Machine learning and network pharmacology analysis were employed to explore the potential targets from differentially expressed genes (DEGs) of human SLE and LN peripheral blood mononuclear cells (PBMCs) microarray datasets and pharmacological databases. GO and KEGG analyses were performed, and the protein-protein interaction (PPI) network was constructed. The association of these characteristic genes and immune cells were further examined and validated. Results Three machine learning models (RF, SVM, and XGB) were utilized to identify five immunoregulatory genes in SLE among twelve intersection DEGs. Among these genes, MMP9 exhibited the highest ROC AUC (0.92) in predicting disease development. KEGG analysis revealed significant associations with the IL-17 signaling pathway (p = 1.67E-18). Furthermore, ssGSEA analysis indicated positive correlations between MMP9 and macrophages (correlation coefficient 0.88) as well as neutrophils (correlation coefficient 0.66). In vitro treatment of PBMCs from lupus nephritis (LN) patients with ATO resulted in downregulation of MMP9 and IL-17A, validating our bioinformatics findings. Conclusion ATO has the potential to mitigate the MMP/IL-17A pathways in PBMCs in LN patients, and hence maybe a promising and innovative therapeutic alternative.

Integrated Analysis of CD1A Immune Infiltration and Competing Endogenous RNA Networks in COAD.

The CD1A gene, a key component of the human immune system and part of the CD1 family, plays a crucial role in presenting lipid antigens to T cells. Abnormal CD1A expression is associated with various immune-related diseases and tumors. However, the biological function of CD1A in COAD is unclear. Multiple databases were systematically employed to conduct an analysis of CD1A expression in pan-cancer and COAD, along with its clinical-pathological features. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of CD1A were performed using the 'clusterProfiler' package. The Protein-protein interaction (PPI) analysis of CD1A was used the STRING database. Additionally, TIMER and ssGSEA tools were used to explore the relationship between CD1A expression in COAD and immune cell infiltration. The study also investigated the association between CD1A expression and N6-methyladenosine (m6A) modification genes in the TCGA COAD cohort and constructed a CD1A-centric competing endogenous RNA (ceRNA) regulatory network. CD1A displays varying expression levels in various tumors, including COAD, and is closely linked to clinical-pathological characteristics. GO analysis suggests that CD1A plays a role in important processes like antigen processing and presentation, leukocyte-mediated immunity, and lymphocyte-mediated immunity. KEGG analysis identifies CD1A's involvement in key pathways such as the Chemokine signaling pathway and Cytokine-cytokine receptor interaction. PPI analysis highlights CD1A's interactions with CD207, CD1C, CD1E, FOXP3, and ITGB2. ssGSEA analysis indicates a significant relationship between CD1A expression and the infiltration of various immune cells in COAD. Significant associations were found between CD1A and m6A modification genes in COAD. Furthermore, a CD1A-centered ceRNA regulatory network has been constructed. CD1A emerges as a potential biomarker for the diagnosis and treatment of COAD, showing a strong association with tumor immune infiltration, m6A modification, and the ceRNA network.

Machine Learning-derived Multi-omics Prognostic Signature of Pyroptosis-related lncRNA with Regard to ZKSCAN2-DT and Tumor Immune Infiltration in Colorectal Cancer.

Colorectal cancer (CRC) has become the most prevalent gastrointestinal malignant tumor, ranking third (10.2%) in incidence and second (9.2%) in death among all malignancies globally. The most common histological subtype of CRC is colon adenocarcinoma (COAD), although the cause of CRC remains unknown, as there are no valid biomarkers. A thorough investigation was used to build a credible biomolecular risk model based on the pyroptosis-associated lncRNAs discovered for COAD prediction. Furthermore, Cibersort and Tumor Immune Dysfunction and Exclusion (TIDE), the methods of exploring tumor immune infiltration, were adopted in our paper to detect the effects of differential lncRNAs on the tumor microenvironment. Finally, quantitative real-time polymerase chain reaction (qPCR), as the approach of exploring expressions, was utilized on four different cell lines. Seven pyroptosis-related lncRNAs have been identified as COAD predictive risk factors. Cox analysis, both univariate and multivariate, revealed that the established signature might serve as a novel independent factor with prognostic meaning in COAD patients. ZKSCAN2-DT was shown to be considerably overexpressed in the COAD cell line when compared to normal human colonic epithelial cells. Furthermore, ssGSEA analysis results revealed that the immune infiltration percentage of most immune cells dropped considerably as ZKSCAN2-DT expression increased, implying that ZKSCAN2-DT may play an important role in COAD immunotherapy. Our research is the first to identify pyroptosis-related lncRNAs connected with COAD patient prognosis and to construct a predictive prognosis signature, directing COAD patient prognosis in therapeutic interventions.

Characterization of macrophages in head and neck squamous cell carcinoma and development of MRG-based risk signature

Macrophages are immune cells in the TME that can not only inhibit angiogenesis, extracellular matrix remodeling, cancer cell proliferation, and metastasis but also mediate the phagocytosis and killing of cancer cells after activation, making them key targets in anti-tumor immunotherapy. However, there is little research on macrophages and their relation to disease prognosis in HNSCC. Initially, we collected scRNA-seq, bulk RNA-seq, and clinical data. Subsequently, we identified macrophages and distinguished MRGs. Using the K-means algorithm, we performed consensus unsupervised clustering. Next, we used ssGSEA analysis to assess immune cell infiltration in MRG clusters. A risk model was established using multivariate Cox analysis. Then, Kaplan–Meier, ROC curves, univariate and multivariate COX analyses, and C-index was used to validate the predictive power of the signature. The TIDE method was applied to assess the response to immunotherapy in patients diagnosed with HNSCC. In addition, drug susceptibility predictions were made for the GDSC database using the calcPhenotype function. We found that 8 MRGs had prognostic potential. Patients in the MRG group A had a higher probability of survival, and MRG clusters A and B had different characteristics. Cluster A had a higher degree of expression and infiltration in MRG, indicating a closer relationship with MRG. The accuracy of the signature was validated using univariate and multivariate Cox analysis, C-index, and nomogram. Immune landscape analysis found that various immune functions were highly expressed in the low-risk group, indicating an improved response to immunotherapy. Finally, drugs with high sensitivity to HNSCC (such as 5-Fluorouracil, Temozolomide, Carmustine, and EPZ5676) were explored and analyze the malignant characteristics of HNSCC. We constructed a prognostic model using multivariate Cox analysis, consisting of 8 MRGs (TGM2, STC1, SH2D3C, PIK3R3, MAP3K8, ITGA5, ARHGAP4, and AQP1). Patients in the low-risk group may have a higher response to immunotherapy. The more prominent drugs for drug selection are 5-fluorouracil, temozolomide and so on. Malignant features associated with HNSCC include angiogenesis, EMT, and the cell cycle. This study has opened up new prospects for the prognosis, prediction, and clinical treatment strategy of HNSCC.

Proteomics Identifies LUC7L3 as a Prognostic Biomarker for Hepatocellular Carcinoma.

Alternative splicing has been shown to participate in tumor progression, including hepatocellular carcinoma. The poor prognosis of patients with HCC calls for molecular classification and biomarker identification to facilitate precision medicine. We performed ssGSEA analysis to quantify the pathway activity of RNA splicing in three HCC cohorts. Kaplan-Meier and Cox methods were used for survival analysis. GO and GSEA were performed to analyze pathway enrichment. We confirmed that RNA splicing is significantly correlated with prognosis, and identified an alternative splicing-associated protein LUC7L3 as a potential HCC prognostic biomarker. Further bioinformatics analysis revealed that high LUC7L3 expression indicated a more progressive HCC subtype and worse clinical features. Cell proliferation-related pathways were enriched in HCC patients with high LUC7L3 expression. Consistently, we proved that LUC7L3 knockdown could significantly inhibit cell proliferation and suppress the activation of associated signaling pathways in vitro. In this research, the relevance between RNA splicing and HCC patient prognosis was outlined. Our newly identified biomarker LUC7L3 could provide stratification for patient survival and recurrence risk, facilitating early medical intervention before recurrence or disease progression.

Bisphenol S enhances the cell proliferation ability of prostate cancer cells by regulating the expression of SDS

Recent times have witnessed an increase in both incidence and mortality rates of prostate cancer. While some individuals with localized or metastatic cancer may progress slowly with a lower mortality risk, those with intermediate or high-risk cancer often face a higher likelihood of death, despite treatment. Bisphenol A (BPA) has been linked to various cancers, including prostate and breast cancer, yet the relationship between bisphenol S (BPS) and human health remains underexplored. In our study, we employed ssGSEA analysis to evaluate the BPS-associated score in a prostate cancer cohort. Additionally, differential expression analysis identified BPS-related genes within the same group. Through COX and LASSO regression analyses, we developed and validated a BPS-related risk model using ROC curve and survival analyses. A nomogram, integrating clinical characteristics with this risk model, was established for improved predictive accuracy, further substantiated by calibration curve validation. Molecular docking analysis suggested potential binding between SDS and BPS. We also conducted cell proliferation assays on C4–2 and LNCaP prostate cancer cells, revealing increased cell growth at a BPS concentration of 10–7 M, as evidenced by CCK8 and EdU assays. In summary, our findings shed light on the BPS-prostate cancer linkage, identifying BPS-associated genes, establishing a validated risk model, exploring SDS-BPS binding potential, and assessing BPS's effect on prostate cancer cell growth. These insights underscore the need for further investigation into BPS and its impact on human diseases.

Identification of fibronectin type III domain containing 3B as a potential prognostic and therapeutic target for pancreatic cancer: a preliminary analysis

BackgroundFibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated.MethodsIn this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan–Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored.ResultsThe study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan–Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells.ConclusionDespite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.