A prognostic biomarker of disulfidptosis constructed by machine learning framework model as potential reporters of pancreatic adenocarcinoma.

BACKGROUND: Pancreatic adenocarcinoma (PAAD), known for its high lethality, has not been thoroughly explored in terms of its mechanisms and patterns of immune infiltration. Disulfidptosis, a newly identified mode of cell death, is likely associated with tumorigenesis and progression but remains poorly understood in PAAD at the genetic and mechanistic levels. METHODS: Sixteen PAAD samples from the GSE154778 scRNA-seq dataset were subjected to single-cell analysis. Disulfidptosis grouping and scores were established across various immune cell populations. Using the TCGA-PAAD database, LASSO regression was employed to construct prognostic markers linked to disulfidptosis. The performance of this model was assessed in both training and independent validation cohorts. Subsequent analyses explored the correlations between disulfidptosis scores, immune infiltration, and drug sensitivity. Cellular experiments further confirmed the significant positive relationship of the gene MET with disulfidptosis and its role in influencing the invasion and metastasis of PAAD. RESULTS: WGCNA identified Disulf-High and Disulf-Low as modules strongly correlated with disulfidptosis. Five prognostically significant genes were selected to construct prognostic models. Survival analysis demonstrated that the disulfidptosis-related biological model successfully achieved prognostic stratification in PAAD patients. Additionally, the disulfidptosis score was significantly correlated with both immune infiltration and drug sensitivity. Knockdown of the MET gene substantially inhibited cell multiplication and cell cycle progression in two PAAD cell lines, effects potentially induced by the activation of the PI3K/AKT signalling pathway in the tumour. CONCLUSION: Key genes associated with disulfidptosis significantly correlate with immune infiltration and the development of PAAD. Biomarkers based on disulfidptosis present potential avenues for novel therapies and clinical treatments in PAAD.

Deciphering the role of oxidative stress genes in idiopathic pulmonary fibrosis: a multi-omics mendelian randomization approach.

Oxidative stress (OS) is crucial in idiopathic pulmonary fibrosis (IPF) pathogenesis, with its genes potentially acting as both causes and consequences of the disease. We identified OS-related genes from GeneCards and performed a meta-analysis on pulmonary transcriptome datasets to discover differentially expressed genes (DEGs) related to OS in IPF. We integrated this data with the largest available IPF GWAS summaries, expression quantitative trait loci (eQTLs), and DNA methylation QTLs (mQTLs) from blood. This approach aimed to identify blood OS genes and regulatory elements linked to IPF risk, incorporating the latest pulmonary eQTLs and bronchoalveolar lavage fluid microbial QTLs (bmQTLs) for a comprehensive view of gene-lung microbiota interactions through SMR and colocalization analyses. Sensitivity analyses were conducted using two additional mendelian randomization (MR) methods. Meta-analysis revealed 1090 differentially expressed OS genes between IPF patients and controls. Integration with IPF GWAS, eQTL, and mQTL data identified key genes and regulatory elements involved in IPF pathogenesis, highlighting the role of specific genes such as KCNMA1 and SLC22A5 in modulating IPF risk through epigenetic mechanisms. Colocalization analysis further identified potential interactions between gene expression and lung microbiota. Our findings elucidate the complex interplay between OS genes and IPF, suggesting potential therapeutic targets and highlighting the importance of considering epigenetic and microbial interactions in the disease's etiology and progression.

Integrated machine learning survival framework to decipher diverse cell death patterns for predicting prognosis in lung adenocarcinoma.

Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and metastasis of tumors. Nevertheless, a comprehensive analysis of the diverse types of PCD in lung adenocarcinoma (LUAD) is currently lacking. The study encompassed a total of 1481 genes associated with the regulation of 13 distinct PCD patterns. Ten machine learning algorithms were amalgamated into 101 combinations, from which the optimal algorithm was chosen to formulate an artificial intelligence-derived prognostic signature based on the average C-index across four multicenter cohorts. The established optimal cell death index (CDI) model emerged as an independent risk factor for overall survival, demonstrating robust and consistent performance. Notably, CDI exhibited significantly higher accuracy compared to traditional clinical variables and molecular features. It exhibited superior performance than other published models. By integrating CDI with relevant clinical features, a nomogram with excellent predictive performance was developed. LUAD patients with low CDI score had a higher immune modulators, TIDE scores and immune scores, indicating a better immunotherapy benefit. More importantly, we found that the regulation of antigen presentation is the crucial mechanism of PCD. SCG2 is a key molecule that inhibits the malignant progression of LUAD. CDI holds great potential as a robust and promising tool for enhancing clinical outcomes in patients with LUAD.

Molecular Landscape and Prognostic Value in the Post-Translational Ubiquitination, SUMOylation and Neddylation in Osteosarcoma: A Transcriptome Study.

Background: Post-translational modifications (PTM) significantly influence the pathogenesis and progression of diverse neoplastic conditions. Nevertheless, there has been limited research focusing on the potential of PTM-related genes (PTMRGs) as tumor biomarkers for predicting the survival of specific patients. Methods: The datasets utilized in this research were obtained from the TARGET and GEO repositories, respectively. The gene signature was constructed through the utilization of LASSO Cox regression method. GSEA and GO was used to identify hub pathways associated with risk genes. The functionality of risk genes in osteosarcoma (OS) cell lines was verified through the implementation of the CCK-8 assay, cell cycle analysis, and immunofluorescence assay. Results: Two distinct PTM patterns and gene clusters were finally determined. Significant differences in the prognosis of patients were found among two different PTM patterns and gene clusters, so were in the function enrichment and the landscape of TME immune cell infiltration. Moreover, we examined two external immunotherapy cohorts and determining that patients in the low-risk group was more likely to profit from immunotherapy. In addition, we mapped the expression of the genes in the signature in distinct cells using single-cell analysis. Finally, CCK-8 assay, cell cycle analysis, and immunofluorescence assay were utilized to confirm that RAD21 was expressed and functioned in OS. Conclusion: In conclusion, this study elucidated the potential link between PTM and immune infiltration landscape of OS for the first time and provided a new assessment protocol for the precise selection of treatment strategies for patients with advanced OS.

Comparative Analysis of Bacterial Information of Biofilms and Activated Sludge in Full-Scale MBBR-IFAS Systems.

This study extensively analyzed the bacterial information of biofilms and activated sludge in oxic reactors of full-scale moving bed biofilm reactor-integrated fixed-film activated sludge (MBBR-IFAS) systems. The bacterial communities of biofilms and activated sludge differed statistically (R = 0.624, p < 0.01). The denitrifying genera Ignavibacterium, Phaeodactylibacter, Terrimonas, and Arcobacter were more abundant in activated sludge (p < 0.05), while comammox Nitrospira was more abundant in biofilms (p < 0.05), with an average relative abundance of 8.13%. Nitrospira and Nitrosomonas had weak co-occurrence relationships with other genera in the MBBR-IFAS systems. Potential function analysis revealed no differences in pathways at levels 1 and 2 based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) between biofilms and activated sludge. However, in terms of pathways at level 3, biofilms had more potential in 26 pathways, including various organic biodegradation and membrane and signal transportation pathways. In comparison, activated sludge had more potential in only five pathways, including glycan biosynthesis and metabolism. With respect to nitrogen metabolism, biofilms had greater potential for nitrification (ammonia oxidation) (M00528), and complete nitrification (comammox) (M00804) concretely accounted for methane/ammonia monooxygenase (K10944, K10945, and K10946) and hydroxylamine dehydrogenase (K10535). This study provides a theoretical basis for MBBR-IFAS systems from the perspective of microorganisms.

Innovative inbuilt moving bed biofilm reactor for nitrogen removal applied in household aquarium.

An innovative inbuilt moving bed biofilm reactor (MBBR) was created to protect fish from nitrogen in a household aquarium. During the 90 experimental days, the ammonia nitrogen (NH4+-N) concentration in the aquarium with the inbuilt MBBR was always below 0.5 mg/L, which would not threaten the fish. Concurrently, nitrite and nitrate nitrogen concentrations were always below 0.05 mg/L and 4.5 mg/L, respectively. However, the blank contrast aquarium accumulated 1.985 mg/L NH4+-N on the 16th day, which caused the fish to die. The suspended biofilms could achieve the specific NH4+-N removal rate of 45.43 g/m3/d. Biofilms presented sparsely with filamentous structures and showed certain degrees of roughness. The bacterial communities of the suspended biofilms and the sediment were statistically different (p < 0.05), reflected in denitrifying and nitrifying bacteria. In particular, the relative abundance of Nitrospira reached 1.4%, while the genus was barely found in sediments. The suspended biofilms showed potentials for nitrification function with the predicted sequence numbers of ammonia monooxygenase [1.14.99.39] and hydroxylamine dehydrogenase [EC:1.7.2.6] of 220 and 221, while the values of the sediment were only 5 and 1. This study created an efficient NH4+-N removal inbuilt MBBR for household aquariums and explored its mechanism to afford a basis for its utilization.

Exploring the relationship between Treg-mediated risk in COPD and lung cancer through Mendelian randomization analysis and scRNA-seq data integration.

BACKGROUND: Evidence from observational studies suggests an association between chronic obstructive pulmonary disease (COPD) and lung cancer. The potential interactions between the immune system and the lungs may play a causative role in COPD and lung cancer and offer therapeutic prospects. However, the causal association and the immune-mediated mechanisms between COPD and lung cancer remain to be determined. METHODS: We employed a two-sample Mendelian randomization (MR) approach to investigate the causal association between COPD and lung cancer. Additionally, we examined whether immune cell signals were causally related to lung cancer, as well as whether COPD was causally associated with immune cell signals. Furthermore, through two-step Mendelian randomization, we investigated the mediating effects of immune cell signals in the causal association between COPD and lung cancer. Leveraging publicly available genetic data, our analysis included 468,475 individuals of European ancestry with COPD, 492,803 individuals of European ancestry with lung cancer, and 731 immune cell signatures of European ancestry. Additionally, we conducted single-cell transcriptome sequencing analysis on COPD, lung cancer, and control samples to validate our findings. FINDINGS: We found a causal association between COPD and lung cancer (odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.31-2.02, P-value < 0.001). We also observed a causal association between COPD and regulatory T cells (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.01-1.40, P-value < 0.05), as well as a causal association between regulatory T cells and lung cancer (odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.002-1.045, P-value < 0.05). Furthermore, our two-step Mendelian randomization analysis demonstrated that COPD is associated with lung cancer through the mediation of regulatory T cells. These findings were further validated through single-cell sequencing analysis, confirming the mediating role of regulatory T cells in the association between COPD and lung cancer. INTERPRETATION: As far as we are aware, we are the first to combine single-celled immune cell data with two-sample Mendelian randomization. Our analysis indicates a causal association between COPD and lung cancer, with regulatory T cells playing an intermediary role.

Comprehensive single-cell transcriptomic profiling reveals molecular subtypes and prognostic biomarkers with implications for targeted therapy in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a genetically heterogeneous disease with poor clinical outcomes. Identification of biomarkers linked to DNA replication stress may enable improved prognostic risk stratification and guide therapeutic decision making. We performed integrated single-cell RNA sequencing and computational analyses to define the molecular determinants and subtypes underlying ESCC heterogeneity. METHODS: Single-cell RNA sequencing was performed on ESCC samples and analyzed using Seurat. Differential gene expression analysis was used to identify esophageal cell phenotypes. DNA replication stress-related genes were intersected with single-cell differential expression data to identify potential prognostic genes, which were used to generate a DNA replication stress (DRS) score. This score and associated genes were evaluated in survival analysis. Putative prognostic biomarkers were evaluated by Cox regression and consensus clustering. Mendelian randomization analyses assessed the causal role of PRKCB. RESULTS: High DRS score associated with poor survival. Four genes (CDKN2A, NUP155, PPP2R2A, PRKCB) displayed prognostic utility. Three molecular subtypes were identified with discrete survival and immune properties. A 12-gene signature displayed robust prognostic performance. PRKCB was overexpressed in ESCC, while PRKCB knockdown reduced ESCC cell migration. CONCLUSIONS: This integrated single-cell sequencing analysis provides new insights into the molecular heterogeneity and prognostic determinants underlying ESCC. The findings identify potential prognostic biomarkers and a gene expression signature that may enable improved patient risk stratification in ESCC. Experimental validation of the role of PRKCB substantiates the potential clinical utility of our results.

A Risk Score Based on Immune- and Oxidative Stress-Related LncRNAs Predicts Prognosis in Lung Adenocarcinoma: Insights from in vitro Experiments and Large-Scale Transcriptome Analysis.

Background: Long non-coding RNAs (lncRNAs) were demonstrated to be key to cancer progression and highly associated with the tumor immune microenvironment. Oxidative stress and immune may modulate the biological behaviors of tumors. Therefore, biomarkers that combined oxidative stress, immune, and lncRNA can be a promising candidate bioindicator in clinical therapy of cancers. Methods: Immune-related genes (IRGs) and oxidative stress-related genes (ORGs) were identified based on a detailed review of published literatures. The transcriptome data and clinical information of lung adenocarcinoma (LUAD) patients were obtained from TCGA database. Lasso and Cox regression analyses were conducted to develop a prognostic model. Additionally, the link between immune checkpoints, immune cells, and the prognostic model was investigated, and predict the sensitivity of immunotherapy. Results: 2498 IRGs and 809 ORGs were extracted from previous studies, and 190 immune- and oxidative stress-related genes (IOGs) were acquired by overlapping the above genes. 658 immune- and oxidative stress-related lncRNAs (IOLs) were screened by Pearson correlation analysis. A total of 25 prognosis-related IOLs were screened by univariate regression analysis. Finally, LASSO Cox regression analysis was adopted for determining a 12-IOLs prognostic risk signature. The signature performance was confirmed in the training cohort and the testing cohort, and cases were classified into low- and high-risk groups by the risk score calculated from the signature. Patients in the high-risk group had poor prognoses and immunosuppression, while the risk score was significantly associated with tumor-infiltrating immune cells, immune checkpoint expression, and immunotherapy responses. In vitro experiments further confirmed the expression of key signature gene. Conclusion: Our new IOLs-related prognostic signature can be reliable prognostic tools and therapeutic targets for LUAD patients.

Illuminating Shared Genetic Associations Between Oesophageal Carcinoma and Pulmonary Carcinoma Risk.

Background: Lung cancer and oesophageal cancer are prevalent malignancies with rising incidence and mortality worldwide. While some environmental and behavioural risk factors for these cancers are established, the contribution of genetic factors to their pathogenesis remains incompletely defined. This study aimed to interrogate the intricate genetic relationship between lung cancer and oesophageal cancer and their potential comorbidity. Methods: We utilised linkage disequilibrium score regression (LDSC) to analyse the genetic correlation between oesophageal carcinoma and lung carcinoma. We then employed several approaches, including pleiotropic analysis under the composite null hypothesis (PLACO), multi-marker analysis of genomic annotation (MAGMA), cis-expression quantitative trait loci (eQTL) analysis, and a pan-cancer assessment to identify pleiotropic loci and genes. Finally, we performed bidirectional Mendelian randomisation (MR) to evaluate the causal relationship between these malignancies. Results: LDSC revealed a significant genetic correlation between oesophageal carcinoma and lung carcinoma. Further analysis identified shared gene loci including PGBD1, ZNF323, and WNK1 using PLACO. MAGMA identified enriched pathways and 9 pleiotropic genes including HIST1H1B, HIST1H4L, and HIST1H2BL. eQTL analysis integrating oesophageal, lung, and blood tissues revealed 26 shared genes including TERT, NKAPL, RAD52, BTN3A2, GABBR1, CLPTM1L, and TRIM27. A pan-cancer exploration of the identified genes was undertaken. MR analysis showed no evidence for a bidirectional causal relationship between oesophageal carcinoma and lung carcinoma. Conclusions: This study provides salient insights into the intricate genetic links between lung carcinoma and oesophageal carcinoma. Utilising multiple approaches for genetic correlation, locus and gene analysis, and causal assessment, we identify shared genetic susceptibilities and regulatory mechanisms. These findings reveal new leads and targets to further elucidate the genetic basis of lung and oesophageal carcinoma, aiding development of preventive and therapeutic strategies.

Novel histone acetylation-related lncRNA signature for predicting prognosis and tumor microenvironment in esophageal carcinoma.

Histone acetylation is one of the most common epigenetic modifications and plays a crucial role in tumorigenesis. However, the prognostic significance of histone acetylation-related lncRNAs (HARlncRNAs) in esophageal carcinoma (ESCA) is not well understood. A total of 653 differentially expressed lncRNAs (DElncRNAs) were identified between 162 ESCA tissues and 11 normal tissues in the TCGA database, and 7 of them were correlated with acetylation regulators. We employed univariate Cox regression analysis, combining it with clinical prognosis information, to select 3 prognostic-related HARlncRNAs for further analysis. Subsequently, we used LASSO regression analysis to construct a risk signature for ESCA and identified C21orf62-AS1 and SSTR5.AS1 as potential biomarkers for the prognosis of ESCA patients. Based on the risk score calculated using the risk signature, we categorized patients into high- and low-risk groups. We identified the risk score as an independent risk factor and validated it in the training, test, and GSE53624 datasets. Additionally, patients categorized by their risk scores exhibited distinct immune statuses, tumor mutation burdens, responses to immunotherapy, and drug sensitivities.

Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis.

BACKGROUND: Disulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification. METHODS: This study systematically explores the genetic and transcriptional variability, prognostic relevance, and expression profiles of DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis and ESTIMATE to assess the tumor microenvironment (TME) in different subgroups. We conducted a functional analysis of differentially expressed genes between subgroups, which involved gene ontology, the Kyoto encyclopedia of genes and genomes, and gene set variation analysis, in order to elucidate their functional status. Prognostic risk models were developed using univariate Cox regression and the least absolute shrinkage and selection operator regression. Additionally, single-cell clustering and cell communication analysis were conducted to enhance the understanding of the importance of signature genes. Lastly, qRT-PCR was employed to validate the prognostic model. RESULTS: Two clearly defined DRG clusters were identified through a consensus-based, unsupervised clustering analysis. Observations were made concerning the correlation between changes in multilayer DRG and various clinical characteristics, prognosis, and the infiltration of TME cells. A well-executed risk assessment model, known as the DRG score, was developed to predict the prognosis of LUAD patients. A high DRG score indicates increased TME cell infiltration, a higher mutation burden, elevated TME scores, and a poorer prognosis. Additionally, the DRG score showed a significant correlation with the tumor mutation burden score and the tumor immune dysfunction and exclusion score. Subsequently, a nomogram was established for facilitating the clinical application of the DRG score, showing good predictive ability and calibration. Additionally, crucial DRGs were further validated by single-cell sequencing data. Finally, crucial DRGs were further validated by qRT-PCR and immunohistochemistry. CONCLUSION: Our new DRG signature risk score can predict the immune landscape and prognosis of LUAD. It also serves as a reference for LUAD's immunotherapy and chemotherapy.

Integrative analysis of single-cell and bulk RNA-sequencing data revealed disulfidptosis genes-based molecular subtypes and a prognostic signature in lung adenocarcinoma.

BACKGROUND: Disulfidoptosis is an unconventional form of programmed cell death that distinguishes itself from well-established cell death pathways like ferroptosis, pyroptosis, and necroptosis. METHODS: Initially, we conducted a single-cell analysis of the GSE131907 dataset from the GEO database to identify disulfidoptosis-related genes (DRGs). We utilized differentially expressed DRGs to classify TCGA samples with an unsupervised clustering algorithm. Prognostic models were built using Cox regression and LASSO regression. RESULTS: Two DRG-related clusters (C1 and C2) were identified based on the DEGs from single-cell sequencing data analysis. In comparison to C1, C2 exhibited significantly worse overall prognosis, along with lower expression levels of immune checkpoint genes (ICGs) and chemoradiotherapy sensitivity-related genes (CRSGs). Furthermore, C2 displayed a notable enrichment in metabolic pathways and cell cycle-associated mechanisms. C2 was also linked to the development and spread of tumors. We created a prognostic risk model known as the DRG score, which relies on the expression levels of five DRGs. Patients were categorized into high-risk and low-risk groups depending on their DRG score, with the former group being linked to a poorer prognosis and higher TMB score. Moreover, the DRG score displayed significant correlations with CRSGs, ICGs, the tumor immune dysfunction and exclusion (TIDE) score, and chemotherapeutic sensitivity. Subsequently, we identified a significant correlation between the DRG score and monocyte macrophages. Additionally, crucial DRGs were additionally validated using qRT-PCR. CONCLUSIONS: Our new DRG score can predict the immune landscape and prognosis of LUAD, serving as a reference for immunotherapy and chemotherapy.

Occurrence and Prognosis of Mixed Subtype Adenocarcinoma and Adeno-Squamous Carcinoma in Esophageal Cancer.

Purpose: To gain a deeper understanding of the incidence and survival rates of rare esophageal mixed adenoacanthoma (EAM) and esophageal mixed adeno-squamous carcinoma (EASC) to promote a more comprehensive understanding of these two subtypes. Background: EAM and EASC are rare subtypes of esophageal cancer with limited literature available. Extensive research has been conducted on the clinical and pathological characteristics of gastric and colorectal mixed adenoacanthomas, but there is relatively little literature on esophageal mixed adenoacanthomas. Therefore, this study aims to investigate the incidence and survival rates of these two subtypes in depth. Methods: Patients diagnosed with EAM and EASC between 2000 and 2019 were selected from the SEER database for the study. Joinpoint software was used to calculate the incidence rates of esophageal AM and ASC patients, and differences in cancer overall survival (OS) and cancer-specific survival (CSS) based on Kaplan-Meier curves were compared. Multivariate Cox regression analysis was employed to identify independent prognostic factors for OS and CSS, and a prognostic model was established and validated for accuracy. Results: The study found that the incidence of EAM increased until 2014, followed by a decline, while the incidence of EASC decreased until 2017, followed by an increase. Both of these subtypes were more common in male patients and those over the age of 65. For EAM patients, preoperative chemoradiotherapy was associated with better survival rates, while for EASC patients, preoperative radiotherapy combined with adjuvant chemotherapy improved survival. Finally, we constructed nomograms for predicting the overall survival of EAM and EASC patients by incorporating identified risk factors, which demonstrated good sensitivity and specificity. Conclusion: EAM and EASC are rare subtypes of esophageal cancer, and an in-depth exploration of their incidence and survival rates provides valuable data and insights for understanding these rare esophageal cancer subtypes. This information can assist clinical decision-making for healthcare professionals.

Molecular map of cGAS-STING pathway-related genes in bladder cancer: the perspective toward immune microenvironment and prognosis.

BACKGROUND: The cGAS-STING pathway emerges as a pivotal innate immune pathway with the potential to profoundly influence all facets of tumor initiation and progression. The prognostic significance and immunological role of cGAS-STING pathway-related genes (CRGs) in individuals diagnosed with bladder cancer (BLCA) have not yet been fully elucidated. METHODS: Performed unsupervised cluster analysis to identify distinct clusters. Utilizing LASSO and multivariate Cox regression analysis to construct a prognostic risk model. The IMvigor210, GSE13507 and GSE78220 cohorts were utilized to explore the potential value of risk score in immune therapy response and survival prediction. RESULTS: A risk model was developed utilizing four CRGs in order to forecast the overall survival (OS) of BLCA patients. The risk score to be a standalone risk factor, which was further corroborated by the external validation set obtained from the GEO database (GSE13507). We established an integrated nomogram that combined risk scoring and clinical information, exhibiting commendable clinical practicality in predicting the overall survival period of BLCA patients. It is noteworthy that risk score could differentiate tumor microenvironments among different risk groups and individuals who were more responsive to immunotherapy in IMvigor210 and GSE13507 cohorts. In vitro experiments, we noted an up-regulation of IRF3 and IKBKB upon the activation of the cGAS-STING pathway. Conversely, the activation of the cGAS-STING pathway resulted in a down-regulation of POLR3G and CTNNB1. CONCLUSIONS: CRG risk model shows promise as a potential stratification approach for bladder cancer patients.

FABP6 serves as a new therapeutic target in esophageal tumor.

BACKGROUND: Esophageal cancer is one of the most common malignant tumors with high incidence and mortality rates. Despite the continuous development of treatment options, the prognosis for esophageal cancer patients remains poor. Therefore, there is an urgent need for new diagnostic and therapeutic targets in clinical practice to improve the survival of patients with esophageal cancer. METHODS: In this study, we conducted a comprehensive scRNA-seq analysis of the tumor microenvironment in primary esophageal tumors to elucidate cell composition and heterogeneity. Using Seurat, we identified eight clusters, encompassing non-immune cells (fibroblasts, myofibroblasts, endothelial cells, and epithelial cells) and immunocytes (myeloid-derived cells, T cells, B cells, and plasma cells). Compared to normal tissues, tumors exhibited an increased proportion of epithelial cells and alterations in immune cell infiltration. Analysis of epithelial cells revealed a cluster (cluster 0) with a high differentiation score and early distribution, suggesting its importance as a precursor cell. RESULTS: Cluster 0 was characterized by high expression of FABP6, indicating a potential role in fatty acid metabolism and tumor growth. T cell analysis revealed shifts in the balance between Treg and CD8+ effector T cells in tumor tissues. Cellular communication analysis identified increased interactions between FABP6+ tumor cells and T cells, with the involvement of the MIF-related pathway and the CD74-CD44 interaction. This study provides insights into the cellular landscape and immune interactions within esophageal tumors, contributing to a better understanding of tumor heterogeneity and potential therapeutic targets.

Integrated analysis identities Rho GTPases related molecular map in patients with gastric carcinoma.

The intricate involvement of Rho GTPases in a multitude of human malignancies and their diverse array of biological functions has garnered substantial attention within the scientific community. However, their expression pattern and potential role in gastric cancer (GC) remain unclear. In this study, we successfully identified two distinct subtypes associated with Rho GTPase-related gene (RGG) through consensus clustering analysis, which exhibited significant disparities in overall survival and the tumor microenvironment. Subsequently, an extensively validated risk model termed RGGscore was meticulously constructed to prognosticate the outcomes of GC patients. This model was further assessed and validated using an external cohort. Notably, the high RGGscore group was indicative of a poorer prognosis. Univariate and multivariate Cox regression analyses unveiled the RGGscore as an autonomous prognostic indicator for GC patients. Subsequent external validation, utilizing two cohorts of patients who underwent immunotherapy, demonstrated a significant correlation between a low RGGscore and improved response to immunotherapy. Additionally, the expression levels of three genes associated with RGGscore were examined using qRT-PCR. Taken together, a pioneering RGGscore model has been successfully established, showcasing its potential efficacy in offering valuable therapeutic guidance for GC.

Potential impact of cuproptosis-related genes on tumor immunity in esophageal carcinoma.

Cuproptosis involves a direct interaction with the tricarboxylic acid (TCA) lipid acylation components. This process intricately intersects with post-transcriptional lipid acylation (LA) and is linked to mitochondrial respiration and LA metabolism. Copper ions form direct bonds with acylated DLAT, promoting DLAT oligomerization, reducing Fe-S cluster proteins, and inducing a protein-triggered toxic stress response that culminates in cell demise. Simultaneously, the importance of immune contexture in cancer progression and treatment has significantly increased. We assessed the expression of cuproptosis-related genes (CRGs) across TCGA and validated our findings using the GEO data. Consensus clustering divided esophageal cancer (ESCA) patients into two clusters based on the expression of 7 CRGs. We evaluated the expression of immune checkpoint inhibitor (ICI) targets and calculated the elevated tumor mutational burden (TMB). Weighted gene co-expression network analysis (WGCNA) identified genes associated with the expression of CRGs and immunity. Cluster 1 exhibited increased immune infiltration, higher expression of ICI targets, higher TMB, and a higher incidence of deficiency in mismatch repair-microsatellite instability-high status. WGCNA analysis identified 14 genes associated with the expression of CRGs and immune scores. ROC analysis revealed specific hub genes with strong predictive capabilities. The expression levels of SLC6A3, MITD1, and PDHA1 varied across different pathological stages; CCS, LIPT2, PDHB, and PDHA1 showed variation in response to radiation therapy; MITD1 and PDHA1 exhibited differences related to the pathological M stages of ESCA. CRGs influence the immune contexture and can potentially transform cold tumors into hot tumors in ESCA patients.

A novel and robust pyroptosis-related prognostic signature predicts prognosis and response to immunotherapy in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a highly malignant gastrointestinal tumor, has a poor prognosis and high mortality rate. Pyroptosis could regulate tumor cell proliferation, invasion, and metastasis, thereby affecting the prognosis of cancer patients. However, the role of pyroptosis-related genes (PRGs) in ESCC remains unclear. This study selected 33 PRGs, and finally identified 29 PRGs that were differentially expressed between ESCC and normal esophageal tissues. The genetic mutation variation landscape of PRG in ESCC was also summarised. Based on consensus clustering for the 33 PRGs, all ESCC patients could be divided into two subtypes. Functional enrichment analysis revealed that these 33 PRGs were mainly involved in cytokine production, interleukin-1 production, and the NOD-like receptor signalling pathway. We created a prognostic PRG signature based on least absolute shrinkage and selection operator regression and Cox regression analysis with good survival prediction ability in both GEO and TCGA cohorts. Combined with the clinical characteristics, signature-based risk score was found to be an independent factor for predicting the OS of ESCC patients. A nomogram with enhanced precision for forecasting ESCC was established based on various independent prognostic elements. Significant correlation was observed between prognostic PRGs and immune-cell infiltration, tumor mutation burden, microsatellite instability, immune checkpoint, and drug sensitivity. Finally, we validated the expression of four PRGs in ESCC cell lines and tissues samples. In conclusion, the PRGs exerted significant effects on tumor immunity and prognosis of ESCC.

Gene set variation analysis-based aging and senescence score as a prognostic indicator and therapeutic guide in lung adenocarcinoma.

Accumulating evidence suggests that aging and senescence play crucial roles in tumorigenesis, cancer progression, and treatment. However, the influence of aging and senescence-related genes (ASRGs) on clinical outcomes and treatment options in lung adenocarcinoma (LUAD) patients remains unknown. Here, we developed an aging and senescence-related scoring system, ASRS, by integrating bulk transcriptome data from 22 LUAD datasets. In 3,243 LUAD samples, higher ASRS scores were associated with poor tumor stage and pathological grade, as well as shorter overall survival, disease-free survival, and recurrence-free survival. Additionally, ASRS was associated with different immune patterns in the tumor microenvironment (TME). Importantly, ASRS was found to predict therapeutic efficacy, with patients having a low ASRS benefiting from immunotherapy and those with a high ASRS responding better to chemotherapy. Therefore, ASRS represents a previously overlooked characteristic of LUAD that can influence patient outcomes and treatment success.