Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a severe lung condition, and finding better ways to diagnose and treat the disease is crucial for improving patient outcomes. Our study sought to develop an artificial neural network (ANN) model for IPF and determine the immune cell types that differed between the IPF and control groups. METHODS: From the Gene Expression Omnibus (GEO) database, we first obtained IPF microarray datasets. To conduct protein-protein interaction (PPI) networks and enrichment analyses, differentially expressed genes (DEGs) were screened between tissues of patients with IPF and tissues of controls. Afterward, we identified the important feature genes associated with IPF using random forest (RF) analysis, and then constructed and validated a prediction ANN mode. In addition, the proportions of immune cells were quantified using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) analysis, which was performed on microarray datasets based on gene expression profiling. RESULTS: A total of 11 downregulated and 36 upregulated DEGs were identified. PPI networks and enrichment analyses were carried out; the immune system and extracellular matrix were the subjects of the enrichments. Using RF analysis, the significant feature genes LRRC17, COMP, ASPN, CRTAC1, POSTN, COL3A1, PEBP4, IL13RA2, and CA4 were identified. The nine feature gene scores were integrated into the ANN to develop a diagnostic prediction model. The receiver operating characteristic (ROC) curves demonstrated the strong diagnostic ability of the ANN in predicting IPF in the training and testing sets. An analysis of IPF tissues in comparison to normal tissues revealed a reduction in the infiltration of natural killer cells resting, monocytes, macrophages M0, and neutrophils; conversely, the infiltration of T cells CD4 memory resting, mast cells, and macrophages M0 increased. CONCLUSION: LRRC17, COMP, ASPN, CRTAC1, POSTN, COL3A1, PEBP4, IL13RA2, and CA4 were determined as key feature genes for IPF. The nine feature genes in the ANN model will be extremely important for diagnosing IPF. It may be possible to use differentiated immune cells from IPF samples in comparison to normal samples as targets for immunotherapy in patients with IPF.

Prognosis and immunotherapeutic implications of molecular classification of cervical cancer based on immunophenoscore-related genes.

The immunophenoscore (IPS) is an important indicator for evaluating immunotherapy response. This work was designed to establish a prognostic model based on IPS-related genes in cervical cancer. Weighted correlation network analysis (WGCNA) was utilized to identify key modules related to IPS in cervical cancer data from The Cancer Genome Atlas (TCGA). The results show that the yellow module (158 genes) had a high correlation with both IPS_CTLA4_blocker and IPS_CTLA4_and PC1/PDL1/PDL2 blocker. Univariate cox regression analysis and LASSO regression analysis were performed based on 158 genes, and 9 characteristic genes were finally identified to construct the model. According to the differentially expressed genes, cervical cancer samples were divided into high-risk and low-risk groups and cluster 1.2.3. Higher risk scores associated with poorer prognosis. cluster2 and cluster3 were identified as cervical cancer subtypes with significant survival differences. cluster2 had higher immune cell infiltration levels and better prognosis, with greater sensitivity to Cyclopamine, Imatinib, MG-13, Paclitaxel, PHA-665752, Rapamycin, Sorafenib, Sunitinib, and VX-680. In contrast, cluster3 had higher TTN and PIK3CA mutations and greater sensitivity to AZ628, Dasatinib, Doxorubicin, HG-6-64-1, JQ12, Midostaurin, PF-562271, TAE684, and WH-4-023. In conclusion, we developed a feasible risk score model based on IPS-related genes for cervical cancer prognosis and identified potential drugs for different cervical cancer subtypes.

Investigation of TMEM41A's function in breast cancer prognosis and its connection to immune cell infiltration.

BACKGROUND: Globally, breast cancer is the most common type of malignant tumor. It has been demonstrated that TMEM41A is abnormally expressed in a number of cancers and is linked to a dismal prognosis. TMEM41A's involvement in breast cancer remains unknown, though. METHODS: Data from databases such as TCGA were used in this study. Expression differences were compared using non-parametric tests. Cox regression analysis was employed, and analyses such as Nomogram were used to assess the significance of TMEM41A in predicting the prognosis of breast cancer. Lastly, it was looked into how immune cell infiltration in breast cancer is related to TMEM41A expression levels. RESULTS: The results suggest that TMEM41A is overexpressed in breast cancer and correlates with poor prognosis (P = 0.01), particularly in early-stage and ductal A breast cancer (P < 0.01). Breast cancer patients' expression of TMEM41A was found to be an independent risk factor (HR = 1.132, 95% CI 1.036-1.237) by multifactorial Cox regression analysis. The Nomogram prediction model's c-index was 0.736 (95% CI 0.684-0.787). The results of GSEA biofunctional enrichment analysis included the B cell receptor signaling pathway (P < 0.05). Ultimately, there was a significant correlation (P < 0.05) between TMEM41A expression in breast cancer and an infiltration of twenty immune cells. CONCLUSIONS: Breast cancer tissues overexpress TMEM41A, which is linked to immune cell infiltration and prognosis (particularly in early stage and luminal A breast cancer). Overexpression of TMEM41A is anticipated to serve as a novel prognostic indicator and therapeutic target for breast cancer.

Immune-Related Long Non-Coding RNA Signature Determines Prognosis and Immunotherapeutic Coherence in Esophageal Cancer.

Objectives: Aim of this study was to explore the immune-related lncRNAs having prognostic role and establishing risk score model for better prognosis and immunotherapeutic coherence for esophageal cancer (EC) patients. Methods: To determine the role of immune-related lncRNAs in EC, we analyzed the RNA-seq expression data of 162 EC patients and 11 non-cancerous individuals and their clinically relevant information from the cancer genome atlas (TCGA) database. Bioinformatic and statistical analysis such as Differential expression analysis, co-expression analysis, Kaplan Meier survival analysis, Cox proportional hazards model, ROC analysis of risk model was employed. Results: Utilizing a cutoff criterion (log2FC > 1 + log2FC < -1 and FDR < 0.01), we identified 3737 RNAs were significantly differentially expressed in EC patients. Among these, 2222 genes were classified as significantly differentially expressed mRNAs (demRNAs), and 966 were significantly differentially expressed lncRNAs (delncRNA). Through Pearson correlation analysis between differentially expressed lncRNAs and immune related-mRNAs, we identified 12 immune-related lncRNAs as prognostic signatures for EC. Notably, through Kaplan-Meier analysis on these lncRNAs, we found the low-risk group patients showed significantly improved survival compared to the high-risk group. Moreover, this prognostic signature has consistent performance across training, testing and entire validation cohort sets. Using ESTIMATE and CIBERSORT algorithm we further observed significant enriched infiltration of naive B cells, regulatory T cells resting CD4+ memory T cells, and, plasma cells in the low-risk group compared to high-risk EC patients group. On the contrary, tumor-associated M2 macrophages were highly enriched in high-risk patients. Additionally, we confirmed immune-related biological functions and pathways such as inflammatory, cytokines, chemokines response and natural killer cell-mediated cytotoxicity, toll-like receptor signaling pathways, JAK-STAT signaling pathways, chemokine signaling pathways significantly associated with identified IRlncRNA signature and their co-expressed immune genes. Furthermore, we assessed the predictive potential of the lncRNA signature in immune checkpoint inhibitors; we found that programed cell death ligand 1 (PD-L1; P-value = .048), programed cell death ligand 2 (PD-L2; P-value = .002), and T cell immunoglobulin and mucin-domain containing-3 (TIM-3; P-value = .045) expression levels were significantly higher in low-risk patients compared to high-risk patients. Conclusion: We believe this study will contribute to better prognosis prediction and targeted treatment of EC in the future.

Analyzing the role of TM4SF1 expression in pancreatic adenocarcinoma: understanding prognostic implications and therapeutic opportunities.

Background: Pancreatic adenocarcinoma (PAAD) is a highly lethal malignancy characterized by aggressive growth and poor prognosis. Understanding the molecular mechanisms underlying PAAD is crucial for developing effective therapies. This study aimed to explore the role of TM4SF1 and other key genes in PAAD progression, their prognostic implications, and therapeutic opportunities. Methods: Differential gene expression analysis was performed using PAAD and normal tissue samples to identify upregulated genes, with TM4SF1 emerging as significantly elevated in PAAD. Functional enrichment analysis elucidated associated signaling pathways. A prognostic model comprising BPIFB4, PLEKHN1, CPTP, DVL1, and DDR1 was developed using least absolute shrinkage and selection operator (LASSO) regression and validated in an independent cohort. Genetic mutation analysis provided insights into the functional significance of identified genes. Pharmacogenomic analysis examined associations between gene expression and drug sensitivity. Experimental validation included quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot analyses to confirm gene expression patterns and protein levels. Results: Lower TM4SF1 expression correlated with enhanced anti-tumor immune activity in PAAD, suggesting a complex interplay between genetic expression and immune response. The prognostic model showed robust associations with patient survival outcomes, validated across diverse patient cohorts. Genetic mutation analysis highlighted potential therapeutic targets. Pharmacogenomic analysis revealed correlations between gene expression profiles and drug responsiveness, suggesting personalized treatment strategies. Experimental validation confirmed elevated TM4SF1 levels in tumor tissues and demonstrated its role in promoting cancer cell proliferation and colony formation. Conclusions: This study advances understanding of the molecular landscape of PAAD, emphasizing TM4SF1 as a key regulator and potential therapeutic target. The integration of genetic expression, immune response dynamics, and pharmacogenomics offers a multifaceted approach to personalized treatment strategies for PAAD, paving the way for improved patient outcomes and novel therapeutic interventions. Further research is warranted to elucidate the clinical utility of targeting TM4SF1 and other identified genes in PAAD management.

Key Disease-Related Genes and Immune Cell Infiltration Landscape in Inflammatory Bowel Disease: A Bioinformatics Investigation.

Inflammatory Bowel Diseases (IBD), which encompass ulcerative colitis (UC) and Crohn's disease (CD), are characterized by chronic inflammation and tissue damage of the gastrointestinal tract. This study aimed to uncover novel disease-gene signatures, dysregulated pathways, and the immune cell infiltration landscape of inflamed tissues. Eight publicly available transcriptomic datasets, including inflamed and non-inflamed tissues from CD and UC patients were analyzed. Common differentially expressed genes (DEGs) were identified through meta-analysis, revealing 180 DEGs. DEGs were implicated in leukocyte transendothelial migration, PI3K-Akt, chemokine, NOD-like receptors, TNF signaling pathways, and pathways in cancer. Protein-protein interaction network and cluster analysis identified 14 central IBD players, which were validated using eight external datasets. Disease module construction using the NeDRex platform identified nine out of 14 disease-associated genes (CYBB, RAC2, GNAI2, ITGA4, CYBA, NCF4, CPT1A, NCF2, and PCK1). Immune infiltration profile assessment revealed a significantly higher degree of infiltration of neutrophils, activated dendritic cells, plasma cells, mast cells (resting/activated), B cells (memory/naïve), regulatory T cells, and M0 and M1 macrophages in inflamed IBD tissue. Collectively, this study identified the immune infiltration profile and nine disease-associated genes as potential modulators of IBD pathogenesis, offering insights into disease molecular mechanisms, and highlighting potential disease modulators and immune cell dynamics.

A novel tumor-derived exosomal gene signature predicts prognosis in patients with pancreatic cancer.

Background: Pancreatic cancer is a devastating disease with poor prognosis. Accumulating evidence has shown that exosomes and their cargo have the potential to mediate the progression of pancreatic cancer and are promising non-invasive biomarkers for the early detection and prognosis of this malignancy. This study aimed to construct a gene signature from tumor-derived exosomes with high prognostic capacity for pancreatic cancer using bioinformatics analysis. Methods: Gene expression data of solid pancreatic cancer tumors and blood-derived exosome tissues were downloaded from The Cancer Genome Atlas (TCGA) and ExoRBase 2.0. Overlapping differentially expressed genes (DEGs) in the two datasets were analyzed, followed by functional enrichment analysis, protein-protein interaction networks, and weighted gene co-expression network analysis (WGCNA). Using the least absolute shrinkage and selection operator (LASSO) regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was constructed based on the TCGA dataset, which was validated by an external validation dataset, GSE62452. The prognostic power of this gene signature and its relationship with various pathways and immune cell infiltration were analyzed. Results: A total of 166 overlapping DEGs were identified from the two datasets, which were markedly enriched in functions and pathways associated with the cell cycle. Two key modules and corresponding 70 exosomal DEGs were identified using WGCNA. Using LASSO Cox regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was built using six exosomal DEGs (ARNTL2, FHL2, KRT19, MMP1, CDCA5, and KIF11), which showed high predictive performance for prognosis in both the training and validation datasets. In addition, this prognostic signature is associated with the differential activation of several pathways, such as the cell cycle, and the infiltration of some immune cells, such as Tregs and CD8+ T cells. Conclusions: This study established a six-exosome gene signature that can accurately predict the prognosis of pancreatic cancer.

Anoikis-related subtype and prognosis analyses based on bioinformatics, and an expression verification of ANGPTL4 based on experiments of lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high mortality. Anoikis resistance is an important mechanism of tumor cell proliferation and migration. Our research is devoted to exploring the role of anoikis in the diagnosis, classification, and prognosis of LUAD. Methods: We downloaded the expression profile, mutation, and clinical data of LUAD from The Cancer Genome Atlas (TCGA) database. The "ConsensusClusterPlus" package was then used for the cluster analysis, and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were used to establish the prognostic model. We verified the reliability of the model using a Gene Expression Omnibus (GEO) data set. A gene set variation analysis (GSVA) was conducted to investigate the functional enrichment differences in the different clusters and risk groups. The CIBERSORT algorithm and a single-sample gene set enrichment analysis (ssGSEA) were used to analyze immune cell infiltration. The tumor mutation burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the patients' sensitivity to immunotherapy. Immunohistochemical staining of tissue microarrays was used to verify the correlation between ANGPTL4 expression and the clinicopathological characteristics and prognosis of LUAD patients. Results: First, we screened 135 differentially expressed anoikis-related genes (ARGs) and 23 prognosis-related ARGs from TCGA-LUAD data set. Next, 494 LUAD samples were allocated to cluster A and cluster B based on the 23 prognosis-related ARGs. The Kaplan-Meier (K-M) analysis showed the overall survival (OS) of cluster B was better than that of cluster A. The clinicopathological characteristics and functional enrichment analyses revealed significant differences between clusters A and B. The tumor microenvironment (TME) analysis showed that cluster B had more immune cell infiltration and a higher TME score than cluster A. Subsequently, a LASSO Cox regression model of LUAD was constructed with ten ARGs. The K-M analysis showed that the low-risk patients had longer OS than the high-risk patients. The receiver operating characteristic curve, nomogram, and GEO data set verification results showed that the model had high accuracy and reliability. The level of immune cell infiltration and TME score were higher in the low-risk group than the high-risk group. The high-risk group had stronger sensitivity to immune checkpoint block therapy and weaker sensitivity to chemotherapy drugs than the low-risk group. ANGPTL4 expression was correlated with stage, tumor differentiation, tumor size, lymph node metastasis, and OS. Conclusions: We discovered novel molecular subtypes and constructed a novel prognostic model of LUAD. Our findings provide important insights into subtype classification and the accurate survival prediction of LUAD. We also identified ANGPTL4 as a prognostic indicator of LUAD.

Pan-Cancer Analysis Confirms the Prognostic and Immunological Implications of the 1,25-Dihydroxy Vitamin D3 Receptor in Cervical Squamous Cell Carcinoma.

Vitamin D receptor (VDR), specifically the 1,25-dihydroxy form, holds significant importance in various types of cancer, including cervical squamous cell carcinoma (CESC), which poses a significant public health challenge. A pan-cancer analysis was conducted on VDR in CESC, with a focus on its expression and relationship with immune infiltration and genetic alterations. Bioinformatics databases, including TIMER, GEPIA, UALCAN, cBioportal, and Kaplan-Meier Plotter, have been utilized. VDR expression in CESC has been validated using publicly available data. Results were significantly upregulated (P=0.05) in THCA, BRCA, KICH, LUAD, LIHC, STAD, UCEC, CESC, CHOL, ESCA, and HNSC samples. We analyzed the correlation between VDR expression and various clinicopathological factors such as age, race, and cancer stage. VDR expression was significantly upregulated across all age groups, with the highest levels observed in older adults followed by young and middle-aged adults. VDR gene expression was significantly elevated across all races, including Caucasians, African-Americans, and Asians, compared to that in the normal group. Furthermore, VDR expression was significantly upregulated in cancer stages 1, 2, 3, and 4, with the highest increase observed in stage 3 compared to that in normal individuals. We analyzed the expression of the VDR in relation to immune cell type and tumor cell purity in CESC. Our results indicated that VDR expression was positively correlated with neutrophils and dendritic cells and negatively correlated with tumor cell purity in CESC patients. There was no significant correlation between VDR expression and the abundance of B cells, CD8+ T cells, CD4+ T cells, and macrophages. Our study found no significant effect of VDR expression on patient prognosis, although it was positively correlated with CD4+ T cells. The Cox proportional hazards model indicated that age and immune cells did not significantly affect prognosis. Most VDR mutations are concentrated in diffuse large B-cell lymphoma, with an amplification frequency of 4% and a deep deletion frequency of 2.2%. GEO confirmed VDR expression in CESC, identifying 1515 upregulated and 1877 downregulated genes, with volcano plots showing CESC downregulation in patients.

MCT4 is an independent prognostic factor and affects immune cell infiltration in patients with colorectal liver oligometastases.

BACKGROUND: Monocarboxylate transporter 4 (MCT4) is a novel biomarker related to the level of immune cell infiltration, but its impact on tumor immune microenvironment (TIME) of colorectal liver oligometastases (CLO) remains unclear. The aim of this study was to assess MCT4 expression in primary tumor and liver oligometastases, investigate its impact on immune cell infiltration and its prognostic value for CLO patients undergoing liver resection. METHODS: We retrospectively selected 135 CLO patients who underwent curative liver resection between June 1999 and December 2016, and samples included 74 primary tumor tissues and 122 liver metastases. Immunohistochemistry (IHC) was performed to detect MCT4 expression in paraffin-embedded specimens and tyramine signal amplification (TSA) was used to detect the density of tumor-infiltrating lymphocytes, including CD3 + , CD8 + and Foxp3 + . Recurrence-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and log-rank test, and independent prognostic factors were identified with Cox regression modeling. RESULTS: Survival analysis indicated that CLO patients with low MCT4 expression had better 3-year RFS and 3-year OS rates than those with high MCT4 expression. Multivariate analysis indicated that high MCT4 expression was independently associated with poor RFS and OS. High MCT4 expression was associated with a lower number of intratumoral CD3 + /CD8 + T cells and was associated with higher Foxp3 + T cells infiltration. Patients with low MCT4 expression and high levels of differential immune infiltration had longer survival. CONCLUSIONS: MCT4 overexpression was associated with an unfavorable prognosis in patients with CLO and MCT4 expression level had an impact on intratumoral immune infiltration degree. A novel parameter that combined MCT4 expression level and differential immune infiltration level was constructed to stratify patients with CLO into different risk groups.

Ferroptosis-related gene transferrin receptor protein 1 expression correlates with the prognosis and tumor immune microenvironment in cervical cancer.

Background: Ferroptosis is a non-apoptotic iron-dependent form of cell death implicated in various cancer pathologies. However, its precise role in tumor growth and progression of cervical cancer (CC) remains unclear. Transferrin receptor protein 1 (TFRC), a key molecule associated with ferroptosis, has been identified as influencing a broad range of pathological processes in different cancers. However, the prognostic significance of TFRC in CC remains unclear. The present study utilized bioinformatics to explore the significance of the ferroptosis-related gene TFRC in the progression and prognosis of CC. Methods: We obtained RNA sequencing data and corresponding clinical information on patients with CC from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases. Using least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of five ferroptosis-related genes (FRGs) for the prognostic prediction of CC. We investigated the relationship between TFRC gene expression and immune cell infiltration by employing single-sample GSEA (ssGSEA) analysis. The potential functional role of the TFRC gene was evaluated through gene set enrichment analysis (GSEA). Immunohistochemistry and qPCR was employed to assess TFRC mRNA and protein expression in 33 cases of cervical cancer. Furthermore, the relationship between TFRC mRNA expression and overall survival (OS) was investigated in patients. Results: CC samples had significantly higher TFRC gene expression levels than normal tissue samples. Higher TFRC gene expression levels were strongly associated with higher cancer T stages and OS events. The findings of multivariate analyses illustrated that the OS in CC patients with high TFRC expression is shorter than in patients with low TFRC expression. Significant increases were observed in the levels of TFRC mRNA and protein expression in patients diagnosed with CC. Conclusion: Increased TFRC expression in CC was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration. In addition, it highlights ferroptosis as a promising therapeutic target for CC.

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma.

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

P53-associated lncRNAs regulate immune functions and RNA-modifiers in gastric cancer.

TP53, a guardian of the genome, suppresses or enhances tumors through various regulatory pathways. However, the role of p53-related long non-coding RNAs (lncRNAs) in immune regulation of tumor microenvironment and prognosis of gastric cancer (GC) is so far unelucidated. We analyzed the role of TP53-associated lncRNAs (obtained from the TP53LNC-DB database) in immune regulation, immune cell infiltration and RNA modification in gastric cancer. Firstly, using multivariate COX regression analysis, we identified eight lncRNAs related to the prognosis of GC. Furthermore, based on the expression of the lncRNA signature and risk score, the GC patients were divided into high-risk and low-risk groups. We found that M2-macrophages have significantly higher infiltration in the high-risk group. Similarly, significant differences in immune function (APC_co_stimulation, CCR, and checkpoint) and m6A modification (FTO, ZC3H13, YTHDC1, and RBM15), and m5C modification (NOP2 and TET1) between both groups were also observed. These signature lncRNAs were also positively associated with oxidative stress-related genes (MPO, MAPK14, HMOX1, and APP). Additionally, we found that high expression of GAS5 and low expression of MALAT1 in Helicobacter pylori (H-pylori) positive GC patients. Finally, GC patients in the low-risk group showed higher resistance to immunotherapy while patients in the high-risk group were more sensitive to various chemotherapy drugs. Based on these findings, we conclude that p53-associated lncRNAs signature could potentially predict the immune status and overall survival, and may also be used for risk management and planning immunotherapy for gastric cancer patients.

Timing, initiation and function: An in-depth exploration of the interaction network among neutrophil extracellular traps related genes in acute pancreatitis.

BACKGROUND: Exogenous inhibition of neutrophil extracellular traps (NETs) was believed to alleviate acute pancreatitis (AP). This study aimed to comprehensively explore the key biological behavior of NETs including timing and pathogenesis in AP by integrating of single cell RNA sequencing(scRNA-seq) and bulk RNA-seq. METHODS: Differentially expressed NETs-related genes and the hub genes of NETs were screened by bulk RNA-seq. ScRNA-seq was used to identify the cell types in pancreas of AP mice and to depict the transcriptomic maps in neutrophils. The mouse AP models were build to verify the timing of initiation of NETs and underlying pathogenesis of damage on pancreas acinar cells. RESULTS: Tlr4 and Ccl3 were screened for hub genes by bulk RNA-seq. The trajectory analysis of neutrophils showed that high expression of Ccl3, Cybb and Padi4 can be observed in the middle stage during AP. Macrophages might be essential in the biological behavior of neutrophils and NETs. Through animal models, we presented that extensive NETs structures were formed at mid-stage of inflammation, accompanied by more serious pancreas and lung damage. NETs might promote necroptosis and macrophage infiltration in AP, and the damage on pancreatic injury could be regulated by Tlr4 pathway. Ccl3 was considered to recruit neutrophils and promote NETs formation. CONCLUSION: The findings explored the underlying timing and pathogenesis of NETs in AP for the first time, which provided gene targets for further studies.

WTAP promotes the progression of ulcerative colitis by silencing the expression of CES2 through m6A modification.

OBJECTIVE: This study will explore the function of WTAP, the critical segment of m6A methyltransferase complex, in UC and its regulation on immune response. METHODS: The expression levels of key proteins were detected in colon tissues which were derived from UC patients and mice. Macrophage polarization and CD4+ T cell infiltration were detected by flow cytometry and IF staining. ELISA assay was utilized to analyze the level of the inflammatory cytokines. m6A-RIP-PCR, actinomycin D test, and RIP assays were utilized to detect the m6A level, stability, and bound proteins of CES2 mRNA. A dual luciferase reporter assay was conducted to confirm the transcriptional interactions between genes. A co-culture system of intestinal epithelium-like organs was constructed to detect the primary mouse intestinal epithelial cells (PMIEC) differentiation. The interaction between proteins was detected via Co-IP assay. RESULTS: The expression of WTAP and CES2 in UC tissues was increased and decreased, respectively. Knockdown of WTAP inhibited the progression of UC in mice by inhibiting M1 macrophage polarization and CD4+ T cell infiltration. WTAP combined YTHDF2 to promote the m6A modification of CES2 mRNA and inhibited its expression. CES2 co-expressed with EPHX2 and overexpression of CES2 promoted the differentiation of PMIEC. The inhibitory effect of WTAP knockdown on the progress of UC was partially abrogated by CES2 knockdown. CONCLUSION: WTAP/YTHDF2 silences CES2 by promoting its m6A modification and then promotes the progression of UC. WTAP could be a promoting therapy target of UC.

UBR1 is a prognostic biomarker and therapeutic target associated with immune cell infiltration in gastric cancer.

BACKGROUND: Ubiquitination is a targeted protein modification process mediated by intracellular molecules. UBR1 encodes a protein that binds to unstable N-terminal residues of substrate proteins and contributes to the formation of substrate-linked polyubiquitin chains. However, the function and cellular pathways of UBR1 in tumors have received inadequate attention. This study aimed to investigate the potential of UBR1 as a prognostic biomarker and immunotherapy target for stomach adenocarcinoma (STAD) as well as its biological function and molecular mechanism in relation to the disease. METHODS: Differential expression and pan-cancer gene set enrichment analysis (GSEA) were conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) datasets. The Human Protein Atlas (HPA) database was utilized to identify UBR1-enriched pathways in AGS cells and to compare immunohistochemical differences between cancerous and adjacent non-cancerous tissues in gastric cancer. Quantitative Polymerase Chain Reaction (QPCR) and Western blot (WB) analyses were employed to validate these findings in both cancerous and adjacent non-cancerous tissues of gastric cancer. UBR1 expression in GES-1 and four gastric cancer cell lines was assessed using QPCR and WB. Kaplan-Meier curves, univariate and multivariate Cox regression analyses, and receiver operating characteristic (ROC) curve analyses were performed to evaluate the prognostic and diagnostic roles of UBR1. Additionally, the correlation between UBR1 expression and clinical parameters was analyzed using TCGA and GEO databases. UBR1 mutation data were obtained from the cBioPortal database. The mutation landscape, mutation-associated genes, protein structure, tumor mutation burden (TMB), and microsatellite instability (MSI) correlations were analyzed and illustrated. The biological functions of UBR1 were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The correlation between UBR1 and immune infiltration was assessed using TIMER and EPIC computational methods. Protein expression levels of UBR1 in gastric cancer cell lines were determined by immunohistochemistry (IHC) and WB analysis. Quantitative real-time PCR (qRT-PCR) was employed to analyze mRNA expression. Immunoprecipitation (IP) assays were conducted to detect protein-protein interactions between UBR1 and PDL1, while cellular immunofluorescence was used to observe the co-localization of these proteins. Cell proliferation was evaluated using CCK8 and colony formation assays. Cell migration was assessed using Transwell and wound healing assays. Finally, apoptosis was analyzed using flow cytometry, and WB was used to detect changes in apoptotic proteins and NF-κB P65 pathway proteins. RESULTS: UBR1 was upregulated in 28 cancer types, including STAD, and its overexpression was validated in gastric cancer cell lines and tissues. UBR1 expression was associated with advanced pathological characteristics. High UBR1 expression was linked to poor prognostic outcomes, including overall survival (OS), progression-free interval (PFI), disease-specific survival (DSS), as well as responses to surgery, chemotherapy, and HER2 expression. UBR1 expression showed significant correlations with clinical parameters such as age, gender, TNM stage, pathological stage, tumor resection, and anti-reflux therapy. Amplifications and deletions were the most frequent genetic alterations associated with UBR1. According to KEGG and GSEA analyses, UBR1 was significantly associated with several cancer pathways, oxidative phosphorylation, and the TNF-NFκB pathway. UBR1 also exhibited a significant correlation with immune cell infiltration and immunotherapy, including a direct interaction with PDL1. Knockdown of UBR1 inhibited the proliferation, migration, and invasion of STAD cells and promoted apoptosis. CONCLUSIONS: UBR1 is overexpressed in STAD, promoting its progression and positively correlating with immune cell infiltration and immunotherapeutic responses. Therefore, UBR1 could be a promising biomarker for the prognosis and immunotherapy of STAD.

Prognostic Value of Insulin Growth Factor-Like Receptor 1 (IGFLR1) in Stage II and III Colorectal Cancer and Its Association with Immune Cell Infiltration.

IGFLR1 is a novel biomarker, and some evidences suggested that is involved in the immune microenvironment of CRC. Here, we explored the expression of IGFLR1 and its association with the prognosis as well as immune cell infiltration in CRC, with the aim to provide a basis for further studies on IGFLR1. Immunohistochemical staining for IGFLR1, TIM-3, FOXP3, CD4, CD8, and PD-1 was performed in eligible tissues to analyze the expression of IGFLR1 and its association with prognosis and immune cell infiltration. Then, we screened colon cancer samples from TCGA and grouped patients according to IGFLR1-related genes. We also evaluated the co-expression and immune-related pathways of IGFLR1 to identify the potential mechanism of it in CRC. When P < 0.05, the results were considered statistically significant. IGFLR1 and IGFLR1-related genes were associated with the prognosis and immune cell infiltration (P < 0.05). In stage II and III CRC tissue and normal tissue, we found (1) IGFLR1 was expressed in both the cell membrane and cytoplasm and which was differentially expressed between cancer tissue and normal tissue. IGFLR1 expression was associated with the expression of FOXP3, CD8, and gender but was not associated with microsatellite instability. (2) IGFLR1 was an independent prognostic factor and patients with high IGFLR1 had a better prognosis. (3) A model including IGFLR1, FOXP3, PD-1, and CD4 showed good prognostic stratification ability. (4) There was a significant interaction between IGFLR1 and GATA3, and IGFLR1 had a significant co-expression with related factors in the INFR pathway. IGFLR1 has emerged as a new molecule related to disease prognosis and immune cell infiltration in CRC patients and showed a good ability to predict the prognosis of patients.

Identification of Immune Gene Signature Associated with T Cells and Natural Killer Cells in Type 1 Diabetes.

Purpose: This study aimed to investigate the abnormal infiltration of immune cells in type 1 diabetes mellitus (T1D) and elucidate their regulatory mechanisms. Methods: Public T1D-related gene expression data were obtained from the Gene Expression Omnibus database.The GSE123658 dataset analyzed whole blood RNA-seq data from type 1 diabetic patients and healthy volunteers. The GSE110914 dataset analyzed neutrophils purified from peripheral blood of patients with symptomatic and pre-symptomatic type 1 diabetes (T1D), at risk of T1D, and healthy controls. Immune cell infiltration analysis was performed to identify abnormally infiltrating immune cells. Differentially expressed immune genes (DEIGs) in T1D samples were identified, followed by the construction of an immune gene signature (IGS) using a protein-protein interaction (PPI) network and Least absolute shrinkage and selection operator Cox regression analyses (LASSO Cox regression analyses). The regulatory mechanisms underlying IGS were explored using gene set enrichment analysis. Furthermore, expression validation, diagnostic efficacy evaluation, and upstream miRNA prediction of hub signature genes were performed. We verified the miRNA expression of the key gene colony stimulating factor 1 (CSF1) and microRNA-326 (miR-326) by reverse transcription-quantitative PCR (RT‒qPCR). Results: The proportion of infiltrating T and natural killer (NK) cells differed between the T1D and control samples, and 207 immune genes (IGs) related to these immune cells were extracted. After differential expression, PPI, and LASSO Cox regression analyses, four signature DEIGs were identified for IGS construction: notch receptor 1 (NOTCH1), Janus kinase 3 (JAK3), tumor necrosis factor receptor superfamily member 4(TNFRSF4), and CSF1. Key pathways such as the Toll-like receptor signaling pathway were significantly activated in the high-risk group. Moreover, the upregulation of CSF1 in T1D samples was confirmed using a validation dataset, and CSF1 showed high diagnostic efficacy for T1D. Furthermore, CSF1 was targeted by miR-326.We used validated key genes in T1D patients, several of which were confirmed by RT‒qPCR. Conclusion: In conclusion, the identified key IGs may play an important role in T1D. CSF1 can be developed as a novel diagnostic biomarker for T1D.

A Mature Tertiary Lymphoid Structure with a Ki-67-Positive Proliferating Germinal Center Is Associated with a Good Prognosis and High Intratumoral Immune Cell Infiltration in Advanced Colorectal Cancer.

Tertiary lymphoid structures (TLSs) are complex lymphocyte clusters that arise in non-lymphoid tissues due to inflammation or cancer. A mature TLS with proliferating germinal centers is associated with a favorable prognosis in various cancers. However, the effect of TLS maturity on advanced colorectal cancer (CRC) remains unexplored. We analyzed the significance of TLS maturity and tumor Ki-67 expression in surgically resected tumors from 78 patients with pathological T4 CRC. Mature TLS was defined as the organized infiltration of T and B cells with Ki-67-positive proliferating germinal centers. We analyzed the relationship between TLS maturity and intratumoral immune cell infiltration. Mature TLS with germinal center Ki-67 expression was associated with microsatellite instability and improved survival; however, high tumor Ki-67 expression was associated with poor survival in the same cohort. Multivariate analysis identified the absence of mature TLS as an independent predictor of poor post-recurrence overall survival. Intratumoral infiltration of T lymphocytes and macrophages was significantly elevated in tumors with mature TLS compared to those lacking it. High Ki-67 levels and absent mature TLS were identified as poor prognostic factors in advanced CRC. Mature TLS could serve as a promising marker for patients at high-risk of CRC.

A prognostic model constructed by ferroptosis-associated genes (FAGs) in papillary renal cell carcinoma (PRCC) and its association with tumor mutation burden (TMB) and immune infiltration.

BACKGROUND: This study aimed to identify the prognostic-related differentially expressed ferroptosis-associated genes (DEFAGs) in papillary renal cell carcinoma (PRCC). METHODS: Data encompassing simple nucleotide variation, transcriptome profiles, and relevant clinical information of PRCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The expression matrix of ferroptosis-associated genes (FAGs) was analyzed using the "limma" package in R to identify differentially expressed DEFAGs. Lasso regression analysis, along with univariate and multivariate Cox proportional hazards regressions, was employed to identify independent prognostic-related DEFAGs and formulate a nomogram. Additionally, we examined potential independent survival-related clinical risk factors and compared immune cell infiltration and tumor mutation burden (TMB) differences between high- and low-risk patient groups. RESULTS: A cohort of 321 patients were analyzed, revealing twelve FAGs significantly influencing the overall survival (OS) of PRCC patients. Among them, two mRNAs (GCLC, HSBP1) emerged as independent prognostic-related DEFAGs. Smoking status, tumor stage, and risk score were identified as independent clinical risk factors for PRCC. Furthermore, notable disparities in immune cell infiltration and function were observed between high- and low-risk groups. GCLC and HSBP1 were associated with various immune cells and functions, TMB, and immune evasion. CONCLUSION: This finding revealed two independent prognostic-related DEFAGs in PRCC and established a robust prognostic model, offering potential therapeutic targets and promising insights for the management of this disease.