GPC2 Is a Potential Diagnostic, Immunological, and Prognostic Biomarker in Pan-Cancer

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

Pan-Cancer Analysis and Experimental Validation of CEND1 as a Prognostic and Immune Infiltration-Associated Biomarker for Gliomas

Cell cycle exit and neuronal differentiation 1 (CEND1), highly expressed in the brain, is a specific transmembrane protein which plays a tumor suppressor role. This study is performed to investigate the role of CEND1 in various cancers through pan-cancer analysis, and further investigate its functions in gliomas by cell experiments. The expression and subcellular localization of CEND1 in different cancer types were analyzed utilizing the data from the GEPIA, UCSC, UALCAN and HPA databases. Relationships of CEND1 expression with prognosis, immunomodulation-related genes, immune checkpoint genes, microsatellite instability (MSI), tumor mutation burden (TMB) and RNA modifications were analyzed based on the TCGA database. The ESTIMATE algorithm was utilized to evaluate tumors' StromalScore, Immune Score, and ESTIMATES Score. The cBioPortal database was employed to analyze the categories and frequencies of CEND1 gene alterations. Biological functions and co-expression patterns of CEND1 in gliomas were explored using the LinkedOmics database, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. The interactions between CEND1 and drugs were explored employing the Comparative Toxicogenomics Database and molecular docking technology. Cell experiments were conducted to analyze triptonide's effects on glioma cells through CCK-8, flow cytometry and qRT-PCR. CEND1 was lowly expressed in gliomas, and high CEND1 expression was correlated to better overall survival of glioma patients (HR = 0.65, P = 0.02). Deep deletion was the main type of hereditary change of CEND1 mutation. CEND1 expression was markedly associated with immune infiltration, TMB, MSI, and RNA modification in various tumors (r > 0.3, P < 0.05). CEND1 co-expressed genes in gliomas were markedly correlated with immune responses and cell cycle (FDR < 0.05). Triptonide could bind well to CEND1 (-5.0 kcal/mol), and triptonide could facilitate CEND1 expression in glioma cells and cell apoptosis, and block the cell cycle progression (P < 0.05). CEND1 serves as a potential biomarker for pan-cancer. Particularly in gliomas, CEND1 is a key regulator of cell apoptosis and cell cycle, and a potential target for glioma treatment.

The potential and promise for clinical application of adoptive T cell therapy in cancer

Adoptive cell therapy has revolutionized cancer treatment, especially for hematologic malignancies. T cells are the most extensively utilized cells in adoptive cell therapy. Currently, tumor-infiltrating lymphocytes, T cell receptor-transgenic T cells and chimeric antigen receptor T cells are the three main adoptive T cell therapies. Tumor-infiltrating lymphocytes kill tumors by reinfusing enlarged lymphocytes that naturally target tumor-specific antigens into the patient. T cell receptor-transgenic T cells have the ability to specifically destroy tumor cells via the precise recognition of exogenous T cell receptors with major histocompatibility complex. Chimeric antigen receptor T cells transfer genes with specific antigen recognition structural domains and T cell activation signals into T cells, allowing T cells to attack tumors without the assistance of major histocompatibility complex. Many barriers have been demonstrated to affect the clinical efficacy of adoptive T cell therapy, such as tumor heterogeneity and antigen loss, hard trafficking and infiltration, immunosuppressive tumor microenvironment and T cell exhaustion. Several strategies to improve the efficacy of adoptive T cell therapy have been explored, including multispecific chimeric antigen receptor T cell therapy, combination with immune checkpoint blockade, targeting the immunosuppressive tumor microenvironment, etc. In this review, we will summarize the current status and clinical application, followed by major bottlenecks in adoptive T cell therapy. In addition, we will discuss the promising strategies to improve adoptive T cell therapy. Adoptive T cell therapy will result in even more incredible advancements in solid tumors if the aforementioned problems can be handled.

GTSE1: A potential prognostic and diagnostic biomarker in various tumors including lung adenocarcinoma

OBJECTIVE

This research was aimed to comprehensively investigate the expression levels, diagnostic and prognostic implications, and the relationship with immune infiltration of G2 and S phase-expressed-1 (GTSE1) across 33 tumor types, including lung adenocarcinoma (LUAD), through gene expression profiling.

METHODS

GTSE1 mRNA expression data together with clinical information were acquired from Xena database of The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) database for this study. The Wilcoxon rank-sum test was used to detect differences in GTSE1 expression between groups. The ability of GTSE1 to accurately predict cancer status was evaluated by calculating the area under the curve (AUC) value for the receiver operating characteristic curve. Additionally, we investigated the predictive value of GTSE1 in individuals diagnosed with neoplasms using univariate Cox regression analysis as well as Kaplan-Meier curves. Furthermore, the correlation between GTSE1 expression and levels of immune infiltration was assessed by utilizing the Tumor Immune Estimate Resource (TIMER) database to calculate the Spearman rank correlation coefficient. Finally, the pan-cancer analysis findings were validated by examining the association between GTSE1 expression and prognosis among patients with LUAD.

RESULTS

GTSE1 exhibited significantly increased expression levels in a wide range of tumor tissues in contrast with normal tissues (p < 0.05). The expression of GTSE1 in various tumors was associated with clinical features, overall survival, and disease-specific survival (p < 0.05). In immune infiltration analyses, a strong correlation of the level of immune infiltration with the expression of GTSE1 was observed. Furthermore, GTSE1 demonstrated good discriminative and diagnostic value for most tumors. Additional experiments confirmed the relationship between elevated GTSE1 expression and unfavorable prognosis in individuals diagnosed with LUAD. These findings indicated the crucial role of GTSE1 expression level in influencing the development and immune infiltration of different types of tumors.

CONCLUSIONS

GTSE1 might be a potential biomarker for the prognosis of pan-cancer. Meanwhile, it represented a promising target for immunotherapy.

Exploring the role of Prx II in mitigating endoplasmic reticulum stress and mitochondrial dysfunction in neurodegeneration

BACKGROUND

Neurodegenerative diseases are increasingly recognized for their association with oxidative stress, which leads to progressive dysfunction and loss of neurons, manifesting in cognitive and motor impairments. This study aimed to elucidate the neuroprotective role of peroxiredoxin II (Prx II) in counteracting oxidative stress-induced mitochondrial damage, a key pathological feature of neurodegeneration.

METHODS

We investigated the impact of Prx II deficiency on endoplasmic reticulum stress and mitochondrial dysfunction using HT22 cell models with knocked down and overexpressed Prx II. We observed alcohol-treated HT22 cells using transmission electron microscopy and monitored changes in the length of mitochondria-associated endoplasmic reticulum membranes and their contact with endoplasmic reticulum mitochondria contact sites (EMCSs). Additionally, RNA sequencing and bioinformatic analysis were conducted to identify the role of Prx II in regulating mitochondrial transport and the formation of EMCSs.

RESULTS

Our results indicated that Prx II preserves mitochondrial integrity by facilitating the formation of EMCSs, which are essential for maintaining mitochondrial Ca2+ homeostasis and preventing mitochondria-dependent apoptosis. Further, we identified a novel regulatory axis involving Prx II, the transcription factor ATF3, and miR-181b-5p, which collectively modulate the expression of Armcx3, a protein implicated in mitochondrial transport. Our findings underscore the significance of Prx II in protecting neuronal cells from alcohol-induced oxidative damage and suggest that modulating the Prx II-ATF3-miR-181b-5p pathway may offer a promising therapeutic strategy against neurodegenerative diseases.

CONCLUSIONS

This study not only expands our understanding of the cytoprotective mechanisms of Prx II but also offers necessary data for developing targeted interventions to bolster mitochondrial resilience in neurodegenerative conditions.

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD.

Methods

Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases.

Results

A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1.

Conclusions

Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Dichotomous Effects of Glypican-4 on Cancer Progression and Its Crosstalk with Oncogenes

Glypicans are linked to various aspects of neoplastic behavior, and their therapeutic value has been proposed in different cancers. Here, we have systematically assessed the impact of GPC4 on cancer progression through functional genomics and transcriptomic analyses across a broad range of cancers. Survival analysis using TCGA cancer patient data reveals divergent effects of GPC4 expression across various cancer types, revealing elevated GPC4 expression levels to be associated with both poor and favorable prognoses in a cancer-dependent manner. Detailed investigation of the role of GPC4 in glioblastoma and non-small cell lung adenocarcinoma by genetic perturbation studies displays opposing effects on these cancers, where the knockout of GPC4 with CRISPR/Cas9 attenuated proliferation of glioblastoma and augmented proliferation of lung adenocarcinoma cells and the overexpression of GPC4 exhibited a significant and opposite effect. Further, the overexpression of GPC4 in GPC4-knocked-down glioblastoma cells restored the proliferation, indicating its mitogenic effect in this cancer type. Additionally, a survival analysis of TCGA patient data substantiated these findings, revealing an association between elevated levels of GPC4 and a poor prognosis in glioblastoma, while indicating a favorable outcome in lung carcinoma patients. Finally, through transcriptomic analysis, we attempted to assign mechanisms of action to GPC4, as we find it implicated in cell cycle control and survival core pathways. The analysis revealed upregulation of oncogenes, including FGF5, TGF-β superfamily members, and ITGA-5 in glioblastoma, which were downregulated in lung adenocarcinoma patients. Our findings illuminate the pleiotropic effect of GPC4 in cancer, underscoring its potential as a putative prognostic biomarker and indicating its therapeutic implications in a cancer type dependent manner.

Bioinformatics analysis highlights CCNB1 as a potential prognostic biomarker and an anti-kidney renal papillary cell carcinoma drug target

Kidney renal papillary cell carcinoma (KIRP) is a common urinary tumor that causes lymph node invasion. Once metastatic, the prognosis is poor and there is a lack of effective early diagnostic markers for this tumor. The expression of CCNB1 in KIRP tumor tissues was significantly higher than that in normal tissues in The Cancer Genome Atlas database with or without the genotype-tissue expression database, and a consistent result was obtained in 32 paired tissues. In addition, CCNB1 expression increased remarkably with the progression of the T and M stages. Moreover, using the online HPA database, we verified that the immunohistochemical scores of CCNB1 in KIRP were higher than those in the normal kidney tissues. The higher expression group of CCNB1 showed a worse prognosis in KIRP. Moreover, the receiver operating characteristic curve, univariate and multivariate analyses, and construction of the column diagram further illustrated that CCNB1 was an independent prognostic factor for KIRP. Meanwhile, CCNB1 could better predict the 1- and 3-year survival rates of KIRP. Six genes were significantly and positively co-expressed with CCNB1. We also found that the CCNB1 high-expression group was enriched in the ECM_RECEPTOR_INTERACTION and FOCAL_ADHESION pathways. Finally, drug sensitivity analysis combined with molecular docking identified 5 targeting drugs with the strongest binding activity to CCNB1. CCNB1 is a potential and reliable biomarker for KIRP diagnosis and can be used to predict the survival of patients with KIRP. The 5 selected drugs targeting CCNB1 may provide new hopes for patients with KIRP metastasis.

Integrative analysis confirms TPX2 as a novel biomarker for clinical implication, tumor microenvironment, and immunotherapy response across human solid tumors

Targeting Protein for Xenopus Kinesin Like Protein 2 (TPX2) serves as a microtubule associated protein for the regulation of spindle assembly and tumorigenesis. We aim to investigate the prognostic and immunological role of TPX2 in pan-cancer. TCGA database, Tumor Immune Single-cell Hub (TISCH), and Human Protein Atlas (HPA) were retrieved to evaluate the expression pattern of TPX2 as well as its diagnostic and prognostic value in solid tumors. Genomic alterations of TPX2 were assessed with cBioPortal database. In vitro experiments in lung adenocarcinoma (LUAD) were performed to confirm the potential role of TPX2. Overexpression of TPX2 was found in 22 types of cancers, and was positively related with copy number variations (CNV) and negative with methylation. Up-regulated TPX2 could predict worse outcomes in the majority of cancers. Single-cell analysis revealed that TPX2 was mainly distributed in malignant cells (especially in glioma) and proliferating T cells. Genomic alteration of TPX2 was common in different types of tumors, while with prognostic value in two types of cancers. Additionally, significant correlations were found between TPX2 expression and tumor microenvironment (including stromal cells and immune cells) as well as immune related genes across cancer types. Drug sensitivity analysis revealed that TPX2 could predict response to chemotherapy and immunotherapy. Functional analyses demonstrated close relationship of TPX2 with immune function and malignant phenotypes. Finally, it was confirmed that knockdown of TPX2 could reduce proliferation and migration ability of LUAD cells. In summary, TPX2 could serve as a diagnostic and prognostic biomarker and a potential immunotherapy marker.

Metabolic reprogramming based on RNA sequencing of gemcitabine-resistant cells reveals the FASN gene as a therapeutic for bladder cancer

Bladder cancer (BLCA) is the most frequent malignant tumor of the genitourinary system. Postoperative chemotherapy drug perfusion and chemotherapy are important means for the treatment of BLCA. However, once drug resistance occurs, BLCA develops rapidly after recurrence. BLCA cells rely on unique metabolic rewriting to maintain their growth and proliferation. However, the relationship between the metabolic pattern changes and drug resistance in BLCA is unclear. At present, this problem lacks systematic research. In our research, we identified and analyzed resistance- and metabolism-related differentially expressed genes (RM-DEGs) based on RNA sequencing of a gemcitabine-resistant BLCA cell line and metabolic-related genes (MRGs). Then, we established a drug resistance- and metabolism-related model (RM-RM) through regression analysis to predict the overall survival of BLCA. We also confirmed that RM-RM had a significant correlation with tumor metabolism, gene mutations, tumor microenvironment, and adverse drug reactions. Patients with a high drug resistance- and metabolism-related risk score (RM-RS) showed more active lipid synthesis than those with a low RM-RS. Further in vitro and in vivo studies were implemented using Fatty Acid Synthase (FASN), a representative gene, which promotes gemcitabine resistance, and its inhibitor (TVB-3166) that can reverse this resistance effect.

A Comprehensive Pan-cancer Analysis of the Biological Immunomodulatory Function and Clinical Value of CD27

Background: CD27 is an immunological checkpoint gene, plays a critical function inInhibition or activation of cancer immunity. The CD27/CD27L axis is its pathway of action. Therefore, our goal was to examine the predictive role of CD27 in the clinical prognosis of 33 cancer types and its functions in cancer progression, as well as explore the link between pan-cancer CD27 gene expression and immune infiltration. Methods: By comprehensive use of datasets and methods from TCGA, cBioPortal, GTEx, HPA, KM-plotter, Spearman, CellMinerTM, R packages and RT-qPCR, we delved deeper into the potential impact of the CD27 on cancer development. These include expression differences, immune infiltration, matrix infiltration, gene mutations, DNA methylation, signaling pathways, TMB, MSI, and prognosis. Also, we explored CD27 interactions with different drugs. Results: The results showed that, mutated CD27 was highly expressed in most cancers. The CD27 showed strong diagnostic value in 4 cancers and marked a positive prognosis for CESC, intracervical adenocarcinoma, HNSC, and endometrial cancer, and a poor prognosis for UVM. In addition, CD27 affects multiple immune and inflammatory signaling pathways and is positively correlated with immune cell infiltration, T cell differentiation, macrophage M1 polarization, stromal infiltration, and drug sensitivity. DNA methylation is involved in CD27 expression in cancer. Conclusion: CD27, which is mutated in cancers and appears widely highly expressed and altered tumor immune invasion and stromal invasion by affecting multiple immune-related and inflammation signaling pathways, plays a significant role in CESC, HNSC, UCEC and UVM, and may be used as a therapeutic target for related cancers.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis

BACKGROUND

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC.

METHODS

We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics.

RESULTS

In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively.

CONCLUSION

Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA-miRNA-lncRNA/circRNA networks

OBJECTIVE

The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA-miRNA-lncRNA/circRNA network.

METHODS

The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT-PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA-miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database.

RESULTS

A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT-PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs.

CONCLUSIONS

PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS.

Optimal combination of MYCN differential gene and cellular senescence gene predicts adverse outcomes in patients with neuroblastoma

Introduction

Neuroblastoma (NB) is a common extracranial tumor in children and is highly heterogeneous. The factors influencing the prognosis of NB are not simple.

Methods

To investigate the effect of cell senescence on the prognosis of NB and tumor immune microenvironment, 498 samples of NB patients and 307 cellular senescence-related genes were used to construct a prediction signature.

Results

A signature based on six optimal candidate genes (TP53, IL-7, PDGFRA, S100B, DLL3, and TP63) was successfully constructed and proved to have good prognostic ability. Through verification, the signature had more advantages than the gene expression level alone in evaluating prognosis was found. Further T cell phenotype analysis displayed that exhausted phenotype PD-1 and senescence-related phenotype CD244 were highly expressed in CD8+ T cell in MYCN-amplified group with higher risk-score.

Conclusion

A signature constructed the six MYCN-amplified differential genes and aging-related genes can be used to predict the prognosis of NB better than using each high-risk gene individually and to evaluate immunosuppressed and aging tumor microenvironment.

Prognostic significance of the rho GTPase RHOV and its role in tumor immune cell infiltration: a comprehensive pan-cancer analysis

Ras homolog gene family member V (RHOV) is an atypical Rho GTPase that participates in various important cellular processes. Although RHOV has been identified to play an oncogenic role in lung cancer and triple-negative breast cancer, its role in other types of tumors remains unknown. In this study, we investigated the expression of RHOV in pan-cancer analysis using The Cancer Genome Atlas (TCGA) and Gene-Tissue Expression datasets. RHOV mRNA levels were dysregulated in several types of tumors. RHOV expression was identified as an independent prognostic factor in 7 of 33 types of tumors; however, the relationship varied according to tumor type. Higher RHOV expression was associated with a favorable prognosis in kidney renal cell carcinoma and prostate adenocarcinoma, for which RHOV expression was downregulated, whereas RHOV expression was associated with a poor prognosis for patients with adenoid cystic carcinoma, lung adenocarcinoma, pancreatic ductal adenocarcinoma, skin cutaneous melanoma, and uveal melanoma with upregulated RHOV expression. Furthermore, RHOV expression was associated with various clinicopathological parameters in these tumors. RHOV expression showed varied associations with different types of tumor-infiltrating immune cells and demonstrated a potential impact on the response to immunotherapy depending on the cancer type. Additionally, functional enrichment analysis of RHOV-related genes demonstrated a role in a wide range of developmental and immune-related processes. This study provides valuable insights into the role of RHOV in pan-cancer development, indicating its role as a tumor suppressor or oncogene according to the cancer type and tumor microenvironment.

Expression Pattern of Tumor-associated Antigens in Neuroblastoma: Association With Cytogenetic Features and Survival

Background/Aim

The prognosis of high-risk and relapsed neuroblastoma (NB) patients remains poor. The identification of tumor-associated markers is important for differential diagnosis, prognosis, and the development of targeted therapies. The aim of the study was to determine the expression profile of nine most common NB antigens and assess their association with clinicopathological characteristics and patient survival.

Patients and Methods

Tumor samples from 86 patients with NB were evaluated for the expression of tumor-associated antigen (TAA) using quantitative PCR. Twenty-one patients with benign tumors and 17 healthy donors were assigned as controls.

Results

Overexpression of tyrosine hydroxylase (TH), PHOX2B, PRAME, GPC2, B7-H3, and Survivin is the most typical for NB. Positive expression of MAGEA3, MAGEA1, and NY-ESO-1 at low levels was detected in 54%, 48%, and 52%, respectively, and was not NB specific. Higher TH expression was observed in samples without MYCN-amplification, while higher expression of Survivin, PHOX2B, and GPC2 was significantly associated with the presence of 1p.36 deletion. Overexpression of TH, PHOX2B, and MAGEA1 was associated with better event-free (EFS) and overall survival (OS). Survivin overexpression was associated with poor EFS but had no impact on OS. Multivariate analysis confirmed Survivin as independent marker for poor survival, and PHOX2B and MAGEA1 for better survival.

Conclusion

High expression of TH, PHOX2B, and MAGEA1 genes are favorable prognostic factors for OS and EFS, whereas high expression of Survivin is associated with an increased risk of relapse or progression.

Pan-cancer analysis and experimental validation identify ndc1 as a potential immunological, prognostic and therapeutic biomarker in pancreatic cancer

NDC1 is a transmembrane nucleoporin that participates in cell mitosis. In the field of oncology, NDC1 has shown its potential as a prognostic marker for multiple tumors. However, pan-cancer analysis of NDC1 to fully explore its role in tumors has not been performed and little is reported on its role in pancreatic cancers. In the present study, a pan-cancer analysis of NDC1 was performed using a bioinformatic approach. Survival analysis was performed by univariate Cox regression analysis and Kaplan-Meier survival analysis. Subsequently, the relationship between NDC1 and immune cell infiltration, TMB/MSI and drug sensitivity was analyzed. Moreover, the mechanism of NDC1 in pancreatic cancer were further analyzed by GSEA, GSVA. Finally, we conducted in vitro experiments including MTT, scratch, EdU, and apoptosis assays to explore the function of NDC1 in pancreatic cancer cells. High expression of NDC1 was demonstrated in 28 cancer types. Univariate Cox regression analysis revealed that NDC1 expression was closely associated with the survival outcome of 15 cancer types, and further Kaplan-Meier survival analysis showed negative associations with the progression-free survival in 14 cancers. In addition, a significant association between the NDC1 expression and immune cell infiltration in tumor microenvironment, immune-related genes, common tumor-regulatory and drug sensitivity was observed. Furthermore, NDC1 is abnormally expressed in pancreatic cancer, and is closely related to the prognosis of pancreatic cancer patients and chemosensitivity. The study reveals that NDC1 could be used as a potential immunological, prognostic and therapeutic target for pancreatic cancer.

Pan-Cancer Analysis of the Prognostic and Immunological Role of SMG5: A Biomarker for Cancers

INTRODUCTION

SMG5 is involved in tumor cell development and viewed as a potential target for immunotherapy. The purpose of this study was to systematically analyze the expression level, function, and prognostic value of SMG5 in pan-cancers.

METHODS

Differential expression of SMG5 in normal and tumor tissues was analyzed using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Database (GTEx) data. Survival analysis was performed by Kaplan-Meier method and Cox risk regression. The relationship between SMG5 expression and lymphocyte abundance, tumor cell immune infiltration level, molecular and immune subtypes as well as immune checkpoints was analyzed by tumor-immune system interactions database (TISIDB), Tumor Immune Estimation Resource (TIMER), and Sangerbox databases. The correlation between SMG5 and immune scores was studied using the Estimation of Stromal and Immune Cells in Malignant Tumours using Expression (ESTIMATE) data algorithm. Further, drug sensitivity analysis of SMG5 with low-grade glioma (LGG) was conducted using the CellMiner database.

RESULTS

SMG5 was highly expressed in 23 tumors and only had a significant impact on the prognosis of patients with LGG only. In addition, in tumor microenvironment and tumor immune analysis, we found that the level of immune infiltration, tumor mutational load, microsatellite instability, and immune checkpoints of LGG were significantly correlated with SMG5 expression. Furthermore, SMG5 was significantly associated with immune scores, stromal scores, and sensitivity of some drugs in LGG.

CONCLUSION

SMG5 is differentially expressed in several cancers and is significantly associated with prognosis, immune microenvironment, and immune checkpoints in LGG patients. Therefore, SMG5 could be a potential pan-cancer biomarker and an immunotherapeutic target for LGG.

Integrative profiling analysis reveals prognostic significance, molecular characteristics, and tumor immunity of angiogenesis-related genes in soft tissue sarcoma

Background

Soft tissue sarcoma (STS) is a class of malignant tumors originating from mesenchymal stroma with a poor prognosis. Accumulating evidence has proved that angiogenesis is an essential hallmark of tumors. Nevertheless, there is a paucity of comprehensive research exploring the association of angiogenesis-related genes (ARGs) with STS.

Methods

The ARGs were extracted from previous literature, and the differentially expressed ARGs were screened for subsequent analysis. Next, the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were conducted to establish the angiogenesis-related signature (ARSig). The predictive performance of the novel ARSig was confirmed using internal and external validation, subgroup survival, and independent analysis. Additionally, the association of the ARSig with the tumor immune microenvironment, tumor mutational burden (TMB), and therapeutic response in STS were further investigated. Notably, we finally conducted in vitro experiments to verify the findings from the bioinformatics analysis.

Results

A novel ARSig is successfully constructed and validated. The STS with a lower ARSig risk score in the training cohort has an improved prognosis. Also, consistent results were observed in the internal and external cohorts. The receiver operating characteristic (ROC) curve, subgroup survival, and independent analysis further indicate that the novel ARSig is a promising independent prognostic predictor for STS. Furthermore, it is proved that the novel ARSig is relevant to the immune landscape, TMB, immunotherapy, and chemotherapy sensitivity in STS. Encouragingly, we also validate that the signature ARGs are significantly dysregulated in STS, and ARDB2 and SRPK1 are closely connected with the malignant progress of STS cells.

Conclusion

In sum, we construct a novel ARSig for STS, which could act as a promising prognostic factor for STS and give a strategy for future clinical decisions, immune landscape, and personalized treatment of STS.

Exploring Artificial Intelligence in Anesthesia: A Primer on Ethics, and Clinical Applications

The field of anesthesia has always been at the forefront of innovation and technology, and the integration of Artificial Intelligence (AI) represents the next frontier in anesthesia care. The use of AI and its subtypes, such as machine learning, has the potential to improve efficiency, reduce costs, and ameliorate patient outcomes. AI can assist with decision making, but its primary advantage lies in empowering anesthesiologists to adopt a proactive approach to address clinical issues. The potential uses of AI in anesthesia can be schematically grouped into clinical decision support and pharmacologic and mechanical robotic applications. Tele-anesthesia includes strategies of telemedicine, as well as device networking, for improving logistics in the operating room, and augmented reality approaches for training and assistance. Despite the growing scientific interest, further research and validation are needed to fully understand the benefits and limitations of these applications in clinical practice. Moreover, the ethical implications of AI in anesthesia must also be considered to ensure that patient safety and privacy are not compromised. This paper aims to provide a comprehensive overview of AI in anesthesia, including its current and potential applications, and the ethical considerations that must be considered to ensure the safe and effective use of the technology.

Identification of the cell cycle characteristics of non-small cell lung cancer and its relationship with tumor immune microenvironment, cell death pathways, and metabolic reprogramming

Background

The genes related to the cell cycle progression could be considered the key factors in human cancers. However, the genes involved in cell cycle regulation in non-small cell lung cancer (NSCLC) have not yet been reported. Therefore, it is necessary to evaluate the genes related to the cell cycle in all types of cancers, especially NSCLC.

Methods

This study constituted the first pan-cancer landscape of cell cycle signaling. Cluster analysis based on cell cycle signaling was conducted to identify the potential molecular heterogeneity of NSCLC. Further, the discrepancies in the tumor immune microenvironment, metabolic remodeling, and cell death among the three clusters were investigated. Immunohistochemistry was performed to validate the protein levels of the ZWINT gene and examine its relationship with the clinical characteristics. Bioinformatics analyses and experimental validation of the ZWINT gene were also conducted.

Results

First, pan-cancer analysis provided an overview of cell cycle signaling and highlighted its crucial role in cancer. A majority of cell cycle regulators play risk roles in lung adenocarcinoma (LUAD); however, some cell cycle genes play protective roles in lung squamous cell carcinoma (LUSC). Cluster analysis revealed three potential subtypes for patients with NSCLC. LUAD patients with high cell cycle activities were associated with worse prognosis; while, LUSC patients with high cell cycle activities were associated with a longer survival time. Moreover, the above three subtypes of NSCLC exhibited distinct immune microenvironments, metabolic remodeling, and cell death pathways. ZWINT, a member of the cell signaling pathway, was observed to be significantly associated with the prognosis of LUAD patients. A series of experiments verified the higher expression levels of ZWINT in NSCLC compared to those in paracancerous tissues. The activation of epithelial-mesenchymal transition (EMT) induced by ZWINT might be responsible for tumor progression.

Conclusion

This study revealed the regulatory function of the cell cycle genes in NSCLC, and the molecular classification based on cell cycle-associated genes could evaluate the different prognoses of patients with NSCLC. ZWINT expression was found to be significantly upregulated in NSCLC tissues, which might promote tumor progression via activation of the EMT pathway.

Attenuation of cancer proliferation by suppression of glypican-1 and its pleiotropic effects in neoplastic behavior

Glypicans (GPC1-6) are associated with tumorigenic processes and their involvement in neoplastic behavior has been discussed in different cancer types. Here, a cancer-wide GPC expression study, using clinical cancer patient data in The Cancer Genome Atlas, reveals net upregulation of GPC1 and GPC2 in primary solid tumors, whereas GPC3, GPC5 and GPC6 display lowered expression pattern compared to normal tissues. Focusing on GPC1, survival analyses of the clinical cancer patient data reveal statistically significant correlation between high expression of GPC1 and poor prognosis in 10 particular cancer types i.e., bladder urothelial carcinoma, brain lower grade glioma, liver hepatocellular carcinoma, colon adenocarcinoma, kidney renal clear cell carcinoma, lung adenocarcinoma, mesothelioma, ovarian serous cystadenocarcinoma, uterine corpus endometrial carcinoma and uveal melanoma. In vitro studies targeting GPC1 expression by CRISPR/Cas9 or siRNA or treatment with an anti-GPC1 antibody resulted in attenuation of proliferation of cancer cells from bladder carcinoma, glioma and hepatocellular carcinoma patients (T24, U87 and HepG2 cells). Further, overexpression of GPC1 exhibited a significant and negative correlation between GPC1 expression and proliferation of T24 cells. Attempt to reveal the mechanism through which downregulation of GPC1 leads to attenuation of tumor growth using systematic Ingenuity Pathway Analysis indicate that suppression of GPC1 results in ECM-mediated inhibition of specific pro-cancer signaling pathways involving TGF-β and p38 MAPK. Identified differential expression and pleiotropic effects of GPCs in specific cancer types emphasize their potential of as novel diagnostic tools and prognostic factors and open doors for future GPC targeted therapy.

Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.

Association between GPC2 polymorphisms and neuroblastoma risk in Chinese children

BACKGROUND

The cell surface glycoprotein glypican 2 (GPC2) has been shown to increase susceptibility to neuroblastoma, which is the most common malignancy in children. However, associations between single nucleotide polymorphism(s) of GPC2 and neuroblastoma risk remain unclarified.

METHODS

We conducted a case-control study to investigate two GPC2 polymorphisms (rs1918353 G>A and rs7799441 C>T) in 473 healthy controls and 402 pediatric patients with neuroblastoma. Single nucleotide polymorphism (SNP) genotyping was conducted on the samples by the TaqMan technique, and the data were subsequently analyzed by the t test, chi-squared test, and logistic regression model. In addition, we further performed stratification analysis by age, sex, tumor site of origin, or clinical stage to control confounding factors.

RESULTS

According to the data of dominant models (GA/AA vs. GG: adjusted OR = 0.99, 95% CI = 0.76-1.29, p = 0.943; CT/TT vs. CC: adjusted OR = 0.91, 95% CI = 0.70-1.19, p = 0.498) or other comparisons, as well as the conjoint analysis (adjusted OR = 1.22, 95% CI = 0.93-1.59, p = 0.152), we unfortunately proved that the analysis of single or multiple loci did not support any significant association of GPC2 polymorphisms with susceptibility to neuroblastoma.

CONCLUSION

GPC2 polymorphisms (rs1918353 G>A and rs7799441 C>T) are unable to statistically affect neuroblastoma risk in Chinese children. Therefore, more samples, especially from patients of various ethnic backgrounds, are required to increase the sample size and verify the effect of GPC2 polymorphisms on neuroblastoma risk in the presence of ethnic factor.

Development of a basement membrane gene signature and identification of the potential candidate therapeutic targets for pancreatic cancer

Background

Pancreatic cancer is a deadly cancer with a poor prognosis. In light of mounting evidence that basement membrane genes (BMGs) play a role in the development of cancer, we sought to examine the prognostic importance and role of BMGs in pancreatic ductal adenocarcinoma (PDAC) patients.

Methods

BMGs were obtained from previous top research studies. The clinical and messenger ribonucleic acid expression data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets, respectively. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used for the PDAC risk modeling and gene identification. The Kaplan-Meier method was used to compare outcomes between the low- and high-risk groups. Finally, we analyzed small-molecule drugs that could be used to target BMGs for treatment using the Enrichr data set and validated the function of the tubulointerstitial nephritis antigen (TINAG) in pancreatic cancer.

Results

We successfully constructed and validated a 7 BMG-based model to predict PDAC patient outcomes. Additionally, we discovered that 7 BMG-based model was an independent predictive factor for PDAC. According to our functional analysis, the majority of the signaling pathways enriched in BMGs were those connected to malignancy. Immune cell infiltration and immunological checkpoints were also linked to the BMG-based model. Further, we identified 5 small-molecule drugs that may be useful in treating PDAC patients. We also found that TINAG promoted cell proliferation in pancreatic cancer.

Conclusions

Our study extended understandings of how BMGs work in PDAC. We identified a credible predictive biomarker for PDAC patients' survival.

In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis

Fluorosis is a serious global public health problem. Interestingly, so far, there is no specific drug treatment for the treatment of fluorosis. In this paper, the potential mechanisms of 35 ferroptosis-related genes in U87 glial cells exposed to fluoride were explored by bioinformatics methods. Significantly, these genes are involved in oxidative stress, ferroptosis, and decanoate CoA ligase activity. Ten pivotal genes were found by the Maximal Clique Centrality (MCC) algorithm. Furthermore, according to the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD), 10 possible drugs for fluorosis were predicted and screened, and a drug target ferroptosis-related gene network was constructed. Molecular docking was used to study the interaction between small molecule compounds and target proteins. Molecular dynamics (MD) simulation results show that the structure of the Celestrol-HMOX1 composite is stable and the docking effect is the best. In general, Celastrol and LDN-193189 may target ferroptosis-related genes to alleviate the symptoms of fluorosis, which may be effective candidate drugs for the treatment of fluorosis.

Aerobic exercise inhibits renal EMT by promoting irisin expression in SHR

To determine the effect of aerobic exercise in different intensities on renal injury and epithelial-mesenchymal transformation (EMT) in the kidney of spontaneously hypertensive rats (SHR) and explore possible mechanisms, we subjected SHR to different levels of 14-week aerobic treadmill training. We tested the effects of aerobic exercise on irisin level, renal function, and EMT modulators in the kidney. We also treated angiotensin II-induced HK-2 cells with irisin and tested the changes in EMT levels. The data showed low and moderate aerobic exercise improved renal function and inhibited EMT through promoting irisin expression in SHR. However, high-intensity exercise training had no effect on renal injury and EMT in SHR but did significantly activate STAT3 phosphorylation in the kidney. These results clarify the mechanisms of exercise in improving hypertension-related renal injury and suggest that irisin might be a therapeutic target for patients with kidney injury.

A 20-Gene Signature Predicting Survival in Patients with Clear Cell Renal Cell Carcinoma Based on Basement Membrane

Objectives

The most common subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC), has a high heterogeneity and aggressive nature. The basement membrane (BM) is known to play a vital role in tumor metastasis. BM-related genes remain untested in ccRCC, however, in terms of their prognostic significance.

Methods

BM-related genes were gleaned from the most recent cutting-edge research. The RNA-seq and clinical data of the ccRCC were obtained from TCGA and GEO databases, respectively. The multigene signature was constructed using the univariate Cox regression and the LASSO regression algorithm. Then, clinical features and prognostic signatures were combined to form a nomogram to predict individual survival probabilities. Using functional enrichment analysis and immune-correlation analysis, we investigated potential enrichment pathways and immunological characteristics associated with BM-related-gene signature.

Results

In this study, we built a model of 20 BM-related genes and classified them as high-risk or low-risk, with each having its anticipated risk profile. Patients in the high-risk group showed significantly reduced OS compared with patients in the low-risk group in the TCGA cohort, as was confirmed by the testing dataset. Functional analysis showed that the BM-based model was linked to cell-substrate adhesion and tumor-related signaling pathways. Comparative analysis of immune cell infiltration degrees and immune checkpoints reveals a central role for BM-related genes in controlling the interplay between the immune interaction and the tumor microenvironment of ccRCC.

Conclusions

We combined clinical characteristics known to predict the prognosis of ccRCC patients to create a gene signature associated with BM. Our findings may also be useful for forecasting how well immunotherapies would work against ccRCC. Targeting BM may be a therapeutic alternative for ccRCC, but the underlying mechanism still needs further exploration.