Development and Validation of a Prognostic Index Based on Genes Participating in Autophagy in Patients With Lung Adenocarcinoma

Deciphering the SOX4/MAPK1 regulatory axis: a phosphoproteomic insight into IQGAP1 phosphorylation and pancreatic Cancer progression

OBJECTIVE

This study aims to elucidate the functional role of IQGAP1 phosphorylation modification mediated by the SOX4/MAPK1 regulatory axis in developing pancreatic cancer through phosphoproteomics analysis.

METHODS

Proteomics and phosphoproteomics data of pancreatic cancer were obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Differential analysis, kinase-substrate enrichment analysis (KSEA), and independent prognosis analysis were performed on these datasets. Subtype analysis of pancreatic cancer patients was conducted based on the expression of prognostic-related proteins, and the prognosis of different subtypes was evaluated through prognosis analysis. Differential analysis of proteins in different subtypes was performed to identify differential proteins in the high-risk subtype. Clinical correlation analysis was conducted based on the expression of prognostic-related proteins, pancreatic cancer typing results, and clinical characteristics in the pancreatic cancer proteomics dataset. Functional pathway enrichment analysis was performed using GSEA/GO/KEGG, and most module proteins correlated with pancreatic cancer were selected using WGCNA analysis. In cell experiments, pancreatic cancer cells were grouped, and the expression levels of SOX4, MAPK1, and the phosphorylation level of IQGAP1 were detected by RT-qPCR and Western blot experiments. The effect of SOX4 on MAPK1 promoter transcriptional activity was assessed using a dual-luciferase assay, and the enrichment of SOX4 on the MAPK1 promoter was examined using a ChIP assay. The proliferation, migration, and invasion functions of grouped pancreatic cancer cells were assessed using CCK-8, colony formation, and Transwell assays. In animal experiments, the impact of SOX4 on tumor growth and metastasis through the regulation of MAPK1-IQGAP1 phosphorylation modification was studied by constructing subcutaneous and orthotopic pancreatic cancer xenograft models, as well as a liver metastasis model in nude mice.

RESULTS

Phosphoproteomics and proteomics data analysis revealed that the kinase MAPK1 may play an important role in pancreatic cancer progression by promoting IQGAP1 phosphorylation modification. Proteomics analysis classified pancreatic cancer patients into two subtypes, C1 and C2, where the high-risk C2 subtype was associated with poor prognosis, malignant tumor typing, and enriched tumor-related pathways. SOX4 may promote the occurrence of the high-risk C2 subtype of pancreatic cancer by regulating MAPK1-IQGAP1 phosphorylation modification. In vitro cell experiments confirmed that SOX4 promoted IQGAP1 phosphorylation modification by activating MAPK1 transcription while silencing SOX4 inhibited the proliferation, migration, and invasion of pancreatic cancer cells by reducing the phosphorylation level of MAPK1-IQGAP1. In vivo, animal experiments further confirmed that silencing SOX4 suppressed the growth and metastasis of pancreatic cancer by reducing the phosphorylation level of MAPK1-IQGAP1.

CONCLUSION

The findings of this study suggest that SOX4 promotes the phosphorylation modification of IQGAP1 by activating MAPK1 transcription, thereby facilitating the growth and metastasis of pancreatic cancer.

Validation of biomarkers and immunotherapy in head and neck squamous cell carcinoma using bioinformatics and Mendelian randomization

BACKGROUND

To promote carcinogenesis through diverse molecular pathways involving dysregulation of gene expression and abnormalities.

METHODS

We employed Mendelian randomization (MR) to uncover causal relationships between genetic factors and HNSCC. We used the Inverse Variance Weighted (IVW) method as the primary MR analysis, and validated the results through complementary approaches like MR-Egger regression, weighted median, and mode analyses.

RESULTS

Our analysis identified 2210 genes that are differentially expressed in head and neck cancer (HNSCC) compared to normal tissues. Within the protein interaction network, the genes IL1B, CXCL8, CXCL1, and CCL2 stood out as central hubs. Further investigation revealed that these key genes are involved in important biological processes like skin development, wound healing, and fat metabolism. Notably, our Mendelian randomization analysis provided evidence for a causal relationship between the expression of the IL1B gene and the development of HNSCC.

CONCLUSIONS

Our analysis identified 5 key genes - IL1B, CXCL8, CXCL1, CCL2, and IL1B - that show significant changes in expression in head and neck cancer. These genes could serve as important new biomarkers to help diagnose this disease and track how it progresses over time. Importantly, these genes are involved in regulating the immune system, suggesting that the body's immune response plays a critical role in head and neck cancer. This provides new avenues for future research to better understand the complex gene expression patterns underlying this type of cancer. Further investigation of these key genes and their regulatory networks could lead to important insights and potential new treatment approaches.

Downregulated expression of plakophilin-2 gene in patients with colon adenocarcinoma predicts an unfavorable prognosis and immune infiltrate

BACKGROUND

Plakophilin 2 gene (PKP2) has been revealed to be differentially expressed in various cancer types and is correlated with prognosis. However, the role of PKP2 in colon adenocarcinoma remains indistinct.

METHODS

Differences in transcriptional expression of PKP2 between colon adenocarcinoma tissues and normal adjacent tissues were acquired from the publicly available dataset-the Cancer Genome Atlas. A receiver operating curve (ROC) was constructed to differentiate colon adenocarcinoma tissues from adjacent normal tissues. The Kaplan-Meier plot method was performed to evaluate the effect of PKP2 on survival. The correlation between mRNA expression of PKP2 and immune infiltrating was determined by the Tumor Immune Estimation Resource and Tumor-Immune System Interaction databases.

RESULTS

The expression of PKP2 in colon adenocarcinoma tissues was significantly downregulated compared with corresponding adjacent normal tissues. Decreased PKP2 mRNA expression was associated with lymph node metastases and advanced pathological stage. The ROC curve analysis indicated that with a cutoff value of 6.034, the sensitivity and specificity for PKP2 differentiating the colon adenocarcinoma tissues from the adjacent normal tissues were 90.2 and 66.5% respectively. Kaplan-Meier plot survival analysis revealed that colon adenocarcinoma patients with low-PKP2 had a worse prognosis than those with high-PKP2 (68.2 vs. 101.4 months, p = 0.028). Correlation analysis showed that mRNA expression of PKP2 was correlative with immune infiltrates.

CONCLUSIONS

Downregulated PKP2 is significantly correlated with unfavorable immune infiltrating and survival in colon adenocarcinoma. This research indicates that PKP2 can be selected as a novel biomarker of potential immunotherapy targets and unfavorable prognosis in colon adenocarcinoma.

Comprehensive analysis of Cuproplasia and immune microenvironment in lung adenocarcinoma

Background: Trace elements such as copper are essential for human health. Recently the journal Nat Rev Cancer has put forward the concept of Cuproplasia, a way of promoting tumor growth through reliance on copper. We attempted to conduct a comprehensive analysis of Cuproplasia-related genes in lung adenocarcinoma (LUAD) to explore the mechanism of action of Cuproplasia-related genes in LUAD. Method: Transcriptome data and clinical information of LUAD were obtained from TCGA-LUAD and GSE31210, and prognostic models of Cuproplasia-related genes were constructed and verified by regression analysis of GSVA, WGCNA, univariate COX and lasso. The signal pathways affected by Cuproplasia-related genes were analyzed by GO, KEGG and hallmarK pathway enrichment methods. Five immunocell infiltration algorithms and IMVIGOR210 data were used to analyze immune cell content and immunotherapy outcomes in the high-low risk group. Results: In the results of WGCNA, BROWN and TURQUOISE were identified as modules closely related to Cuproplasia score. In the end, lasso regression analysis established a Cuproplasia-related signature (CRS) based on 24 genes, and the prognosis of high-risk populations was worse in TCGA-LUAD and GSE31210 datasets. The enrichment analysis showed that copper proliferation was mainly through chromosome, cell cycle, dna replication, g2m checkpoint and other pathways. Immunoinfiltration analysis showed that there were differences in the content of macrophages among the four algorithms. And IMVIGOR210 found that the lower the score, the more effective the immunotherapy was. Conclusion: The Cuproplasia related gene can be used to predict the prognosis and immunotherapy outcome of LUAD patients, and may exert its effect by affecting chromosome-related pathways and macrophages.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

Kynureninase Promotes Immunosuppression and Predicts Survival in Glioma Patients: In Silico Data Analyses of the Chinese Glioma Genome Atlas (CGGA) and of the Cancer Genome Atlas (TCGA)

Kynureninase (KYNU) is a kynurenine pathway (KP) enzyme that produces metabolites with immunomodulatory properties. In recent years, overactivation of KP has been associated with poor prognosis of several types of cancer, in particular by promoting the invasion, metastasis, and chemoresistance of cancer cells. However, the role of KYNU in gliomas remains to be explored. In this study, we used the available data from TCGA, CGGA and GTEx projects to analyze KYNU expression in gliomas and healthy tissue, as well as the potential contribution of KYNU in the tumor immune infiltrate. In addition, immune-related genes were screened with KYNU expression. KYNU expression correlated with the increased malignancy of astrocytic tumors. Survival analysis in primary astrocytomas showed that KYNU expression correlated with poor prognosis. Additionally, KYNU expression correlated positively with several genes related to an immunosuppressive microenvironment and with the characteristic immune tumor infiltrate. These findings indicate that KYNU could be a potential therapeutic target for modulating the tumor microenvironment and enhancing an effective antitumor immune response.

Identification of Clinical Prognostic Regulators and Analysis of Ferroptosis-Related Signatures in the Tumor Immune Microenvironment in Lung Squamous Cell Carcinoma

Objective

Lung squamous cell carcinoma (LUSC) is a common respiratory malignancy and presents an increasing prevalence. Ferroptosis is a newly identified controlled cell death that has captured clinical attention worldwide. However, the ferroptosis-related lncRNA expression in LUSC and its relevance to prognosis remain elusive.

Methods

The research measured predictive ferroptosis-related lncRNAs in LUSC samples from the TCGA datasets. Data on the stemness indices (mRNAsi) and corresponding clinical characteristics were obtained from TCGA. A prognosis model was established using the LASSO regression. Changes within the neoplasm microenvironment (TME) and medicine association were examined to grasp higher immune cell infiltration in numerous risk teams. In line with coexpression studies, the expression of lncRNAs is closely associated with that of ferroptosis. They were overexpressed in unsound people in the absence of alternative clinical symptoms.

Results

The low-risk and speculative teams were considered to have substantial differences in CCR and inflammation-promoting genes. C10orf55, AC016924.1, AL161431.1, LUCAT1, AC104248.1, and MIR3945HG were highly expressed in the high-risk group, suggesting their involvement in the oncology process of LUSC. Moreover, AP006545.2 and AL122125.1 were considerably higher in the low-risk group, implying the potential of these genes as LUSC tumor suppressor genes. The biomarkers listed above may serve as therapeutic targets for LUSC. lncRNAs were also linked to patient outcomes in the LUSC trial.

Conclusion

lncRNAs of ferroptosis were overexpressed in the high-risk cohort without other clinical signs, implying their potential to predict BLCA prognosis. GSEA highlighted immunological and tumor-related pathways in the high-risk group. LUSC occurrence and progression are linked to lncRNAs of ferroptosis. Corresponding prognostic models help forecast the prognosis of LUSC patients. lncRNAs of ferroptosis and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in LUSC, which requires further trials. In addition, the lncRNAs of ferroptosis signature offer a viable alternative to predict LUSC, and these ferroptosis-lncRNAs show a prospective research area for LUSC-targeted treatment in the future.

Constructing and validating of m6a-related genes prognostic signature for stomach adenocarcinoma and immune infiltration: Potential biomarkers for predicting the overall survival

Background

Stomach adenocarcinoma (STAD) arises from the mutations of stomach cells and has poor overall survival. Chemotherapy is commonly indicated for patients with stomach cancer following surgical resection. The most prevalent alteration that affects cancer growth is N6-methyladenosine methylation (m6A), although the possible function of m6A in STAD prognosis is not recognized.

Method

The research measured predictive FRGs in BLCA samples from the TCGA and GEO datasets. Data on the stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and corresponding clinical characteristics were obtained from TCGA and GEO. STAD from TCGA and GEO at 24 m6A was investigated. Lasso regression was used to construct the prediction model to assess the m6A prognostic signals in STAD. In addition, the correlation between m6a and immune infiltration in STAD patients was discussed using GSVA and ssGSEA analysis. Based on these genes, GO and KEGG analyses were performed to identify key biological functions and key pathways.

Result

A significant relationship was discovered between numerous m6A clusters and the tumor immune microenvironment, as well as three m6A alteration patterns with different clinical outcomes. Furthermore, GSVA and ssGSEA showed that m6A clusters were significantly associated with immune infiltration in the STAD. The low-m6Ascore group had a lower immunotherapeutic response than the high-m6Ascore group. ICIs therapy was more effective in the group with a higher m6Ascore. Three writers (VIRMA, ZC3H13, and METTL3) showed significantly lower expression, whereas five authors (METTL14, METTL16, WTAP, RBM15, and RBM15B) showed considerably higher expression. Three readers (YTHDC2, YTHDF2, and LRPPRC) had higher levels of expression, whereas eleven readers (YTHDC1, YTHDF1, YTHDF3, HNRNPC, FMR1, HNRNPA2B1, IGFBP1, IGFBP2, IGFBP3, and RBMX) had lower levels. As can be observed, the various types of m6 encoders have varied ramifications for STAD control.

Conclusion

STAD occurrence and progression are linked to m6A-genes. Corresponding prognostic models help forecast the prognosis of STAD patients. m6A-genes and associated immune cell infiltration in the tumor microenvironment (TME) may serve as potential therapeutic targets in STAD, which requires further trials. In addition, the m6a-related gene signature offers a viable alternative to predict bladder cancer, and these m6A-genes show a prospective research area for STAD targeted treatment in the future.

Constructing and Validating a Pyroptosis-Related Genes Prognostic Signature for Stomach Adenocarcinoma and Immune Infiltration: Potential Biomarkers for Predicting the Overall Survival

Background

Stomach adenocarcinoma (STAD) is a kind of cancer that begins in the stomach cells and has a poor overall survival rate. Following resection surgery, chemotherapy has been suggested as a curative method for stomach cancer. However, it is ineffective. Pyroptosis, a kind of inflammatory programmed cell death, has been shown to play a significant role in the development and progression of STAD. However, whether pyroptosis-related genes (PRGs) can be utilized to predict the diagnosis and prognosis of gastric cancer remains unknown.

Method

The research measured at predictive PRGs in STAD samples from TCGA and GEO. Lasso regression was used to build the prediction model. Coexpression analysis revealed that gene expression was linked to pyroptosis. PRGs were found to be overexpressed in high-risk individuals, implying that they could be used in a model to predict STAD prognosis.

Result

Immunological and tumor-related pathways were discovered using GSEA. In STAD patients, the genes GPX3, PDGFRL, RGS2, and SERPINE1 may be connected to the cancer process. The levels of expression also differed between the two risk groups.

Conclusion

The purpose of this study is to identify and verify STAD-associated PRGs that can effectively guide prognosis and the immunological milieu in STAD patients as well as offer evidence for the development of pyroptosis-related molecularly targeted therapeutics. Therefore, PRGs and the link between immunological and PRGs in STAD may be therapeutic targets.

Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer

Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear.

Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan–Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC.

Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4⁺ T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC.

Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting.