The effects of ACE inhibitor Enalapril on Mytilus galloprovincialis: Insights into morphological and functional responses.

In the last decades, pharmaceuticals have emerged as a new class of environmental contaminants. Antihypertensives, including angiotensin-converting enzyme (ACE) inhibitors, are of special concern due to their increased consumption over the past years. However, the available data on their putative effects on the health of aquatic animals, as well as the possible interaction with biological systems are still poorly understood. This study analysed whether and to which extent the exposure to Enalapril, an ACE inhibitor commonly used for treating hypertension and heart failure, may induce morpho-functional alterations in the mussel Mytilus galloprovincialis, a sentinel organism of water pollution. By mainly focusing on the digestive gland (DG), a target tissue used for analysing the effects of xenobiotics in mussels, the effects of 10-days exposure to 0.6 ng/L (E1) and 600 ng/L (E2) of Enalapril were investigated in terms of cell viability and volume regulation, morphology, oxidative stress, and stress protein expression and localization. Results indicated that exposure to Enalapril compromised the capacity of DG cells from the E2 group to regulate volume by limiting the ability to return to the original volume after hypoosmotic stress. This occurred without significant effects on DG cell viability. Enalapril unaffected also haemocytes viability, although an increased infiltration of haemocytes was histologically observed in DG from both groups, suggestive of an immune response. No changes were observed in the two experimental groups on expression and tissue localization of heat shock proteins 70 (HSPs70) and HSP90, and on the levels of oxidative biomarkers. Our results showed that, in M. galloprovincialis the exposure to Enalapril did not influence the oxidative status, as well as the expression and localization of stress-related proteins, while it activated an immune response and compromised the cell ability to face osmotic changes, with potential consequences on animal performance.

Identification of anoikis-related gene signatures and construction of the prognosis model in prostate cancer.

Background: One of the primary reasons for tumor invasion and metastasis is anoikis resistance. Biochemical recurrence (BCR) of prostate cancer (PCa) serves as a harbinger of its distant metastasis. However, the role of anoikis in PCa biochemical recurrence has not been fully elucidated. Methods: Differential expression analysis was used to identify anoikis-related genes based on the TCGA and GeneCards databases. Prognostic models were constructed utilizing LASSO regression, univariate and multivariate Cox regression analyses. Moreover, Gene Expression Omnibus datasets (GSE70770 and GSE46602) were applied as validation cohorts. Gene Ontology, KEGG and GSVA were utilized to explore biological pathways and molecular mechanisms. Further, immune profiles were assessed using CIBERSORT, ssGSEA, and TIDE, while anti-cancer drugs sensitivity was analyzed by GDSC database. In addition, gene expressions in the model were examined using online databases (Human Protein Atlas and Tumor Immune Single-Cell Hub). Results: 113 differentially expressed anoikis-related genes were found. Four genes (EEF1A2, RET, FOSL1, PCA3) were selected for constructing a prognostic model. Using the findings from the Cox regression analysis, we grouped patients into groups of high and low risk. The high-risk group exhibited a poorer prognosis, with a maximum AUC of 0.897. Moreover, larger percentage of immune infiltration of memory B cells, CD8 Tcells, neutrophils, and M1 macrophages were observed in the high-risk group than those in the low-risk group, whereas the percentage of activated mast cells and dendritic cells in the high-risk group were lower. An increased TIDE score was founded in the high-risk group, suggesting reduced effectiveness of ICI therapy. Additionally, the IC50 results for chemotherapy drugs indicated that the low-risk group was more sensitive to most of the drugs. Finally, the genes EEF1A2, RET, and FOSL1 were expressed in PCa cases based on HPA website. The TISCH database suggested that these four ARGs might contribute to the tumor microenvironment of PCa. Conclusion: We created a risk model utilizing four ARGs that effectively predicts the risk of BCR in PCa patients. This study lays the groundwork for risk stratification and predicting survival outcomes in PCa patients with BCR.

TCBIR/CD320: a potential therapeutic target upregulated in endothelial cells and associated with immune cell infiltration in liver hepatocellular carcinoma.

CD320, which is a transmembrane protein responsible for facilitating the absorption of vitamin B12, plays a key role in this process. However, the relationships between CD320 and immune cell infiltration levels remain unclear, with limited studies investigating the diagnostic and prognostic significance of CD320 in hepatocellular carcinoma. We used various databases, including the TIMER, GEPIA, UALCAN and TCGA databases to investigate the expression levels of CD320 in hepatocellular carcinoma. Subsequently, we analyzed the prognosis of hepatocellular carcinoma patients with different expression levels of CD320. Furthermore, we also performed Western blot, immunohistochemistry, and immunofluorescence analyses to validate the results of the database analysis. Finally, the functions of CD320 in hepatocellular carcinoma were also confirmed via relevant cell experiments and angiogenesis assays. We found that CD320 expression was significantly upregulated in tumor vascular endothelial cells. Moreover, the knockdown of CD320 led to a reduction in angiogenesis in endothelial cells. Increased expression of CD320 was also correlated with a poor prognosis in patients with hepatocellular carcinoma, which suggested that CD320 may be a potential prognostic marker. Finally, TIMER analysis demonstrated that the infiltration of six immune cell types was significantly associated with high expression levels of CD320 in hepatocellular carcinoma. Herein, we demonstrated that CD320 may play an important role in angiogenesis in hepatocellular carcinoma. These findings suggested that CD320 may be a potential clinical prognostic marker and immunotherapy target for hepatocellular carcinoma.

JARID2, a novel regulatory factor, promotes cell proliferation, migration, and invasion in oral squamous cell carcinoma.

BACKGROUND: Accurate regulation of gene expression is crucial for normal development and function of cells. The prognostic significance and potential carcinogenic mechanisms of the related gene JARID2 in OSCC are not yet clear, but existing research has indicated a significant association between the two. METHODS AND MATERIALS: The relationship between the expression of the JARID2 gene in tumor samples of OSCC patients and clinical pathological factors was analyzed using immunohistochemistry experiments and RT-qPCR analysis. Based on the clinical pathological data of patients, bioinformatics analysis was conducted using public databases to determine the function of JARID2 in OSCC. Knockdown OSCC cell lines were constructed, and the impact of JARID2 on the biological behavior of OSCC cell lines was assessed through CCK-8, wound healing assay, and transwell analysis. RESULTS: Immunohistochemistry experiments confirmed the correlation between JARID2 and the prognosis of OSCC patients, while RT-qPCR experiments demonstrated its expression levels in tissue and cells. CKK-8 experiments, wound healing assays, and Transwell experiments indicated that knocking down JARID2 had a negative impact on the proliferation, invasion, and migration of OSCC cells. Bioinformatics analysis results showed that the expression of JARID2 in OSCC is closely associated with patient gene co-expression, gene function enrichment, immune infiltration, and drug sensitivity. CONCLUSION: Our study indicates that JARID2 is a novel prognostic biomarker and potential therapeutic target for OSCC.

Comprehensive analysis of clinical and biological value of ING family genes in liver cancer.

BACKGROUND: Liver cancer (LIHC) is a malignant tumor that occurs in the liver and has a high mortality in cancer. The ING family genes were identified as tumor suppressor genes. Dysregulated expression of these genes can lead to cell cycle arrest, senescence and/or apoptosis. ING family genes are promising targets for anticancer therapy. However, their role in LIHC is still not well understood. AIM: To have a better understanding of the important roles of ING family members in LIHC. METHODS: A series of bioinformatics approaches (including gene expression analysis, genetic alteration analysis, survival analysis, immune infiltration analysis, prediction of upstream microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) of ING1, and ING1-related gene functional enrichment analysis) was applied to study the expression profile, clinical relationship, prognostic significance and immune infiltration of ING in LIHC. The relationship between ING family genes expression and tumor associated immune checkpoints was investigated in LIHC. The molecular mechanism of ING1 mediated hepatocarcinogenesis was preliminarily discussed. RESULTS: mRNA/protein expression of different ING family genes in LIHC was analyzed in different databases, showing that ING family genes were highly expressed in LIHC. In 47 samples from 366 LIHC patients, the ING family genes were altered at a rate of 13%. By comprehensively analyzing the expression, clinical pathological parameters and prognostic value of ING family genes, ING1/5 was identified. ING1/5 was related to poor prognosis of LIHC, suggesting that they may play key roles in LIHC tumorigenesis and progression. One of the target miRNAs of ING1 was identified as hsa-miR-214-3p. Two upstream lncRNAs of hsa-miR-214-3p, U91328.1, and HCG17, were identified. At the same time, we found that the expression of ING family genes was correlated with immune cell infiltration and immune checkpoint genes. CONCLUSION: This study lays a foundation for further research on the potential mechanism and clinical value of ING family genes in the treatment and prognosis of LIHC.

Complement factor I knockdown inhibits colon cancer development by affecting Wnt/ß-catenin/c-Myc signaling pathway and glycolysis.

BACKGROUND: Colon cancer (CC) occurrence and progression are considerably influenced by the tumor microenvironment. However, the exact underlying regulatory mechanisms remain unclear. AIM: To investigate immune infiltration-related differentially expressed genes (DEGs) in CC and specifically explored the role and potential molecular mechanisms of complement factor I (CFI). METHODS: Immune infiltration-associated DEGs were screened for CC using bioinformatics. Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines. Stable CFI-knockdown HT29 and HCT116 cell lines were constructed, and the diverse roles of CFI in vitro were assessed using CCK-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice. Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting. RESULTS: Six key immune infiltration-related DEGs were screened, among which the expression of CFI, complement factor B, lymphoid enhancer binding factor 1, and SRY-related high-mobility-group box 4 was upregulated, whereas that of fatty acid-binding protein 1, and bone morphogenic protein-2 was downregulated. Furthermore, CFI could be used as a diagnostic biomarker for CC. Functionally, CFI silencing inhibited CC cell proliferation, migration, invasion, and tumor growth. Mechanistically, CFI knockdown downregulated the expression of key glycolysis-related proteins (glucose transporter type 1, hexokinase 2, lactate dehydrogenase A, and pyruvate kinase M2) and the Wnt pathway-related proteins (ß-catenin and c-Myc). Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/ß-catenin/c-Myc pathway. CONCLUSION: The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/ß-catenin/c-Myc pathway, indicating that it could serve as a promising target for therapeutic intervention in CC.

Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

Background: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidative stress and dysfunction, which play critical roles in cuproptosis. Here, we explored the potential role of cuproptosis-related genes (CRGs) in AILI. Methods: The gene expression profiles were obtained from the Gene Expression Omnibus database. The differential expression of CRGs was determined between the AILI and control samples. Protein protein interaction, correlation, and functional enrichment analyses were performed. Machine learning was used to identify hub genes. Immune infiltration was evaluated. The AILI mouse model was established by intraperitoneal injection of APAP solution. Quantitative real-time PCR and western blotting were used to validate hub gene expression in the AILI mouse model. The copper content in the mouse liver samples and AML12 cells were quantified using a colorimetric assay kit. Ammonium tetrathiomolybdate (ATTM), was administered to mouse models and AML12 cells in order to investigate the effects of copper chelator on AILI. Results: The analysis identified 7,809 differentially expressed genes, 4,245 of which were downregulated and 3,564 of which were upregulated. Four optimal feature genes (OFGs; SDHB, PDHA1, NDUFB2, and NDUFB6) were identified through the intersection of two machine learning algorithms. Further nomogram, decision curve, and calibration curve analyses confirmed the diagnostic predictive efficacy of the four OFGs. Enrichment analysis indicated that the OFGs were involved in multiple pathways, such as IL-17 pathway and chemokine signaling pathway, that are related to AILI progression. Immune infiltration analysis revealed that macrophages were more abundant in AILI than in control samples, whereas eosinophils and endothelial cells were less abundant. Subsequently, the AILI mouse model was successfully established, and histopathological analysis using hematoxylin-eosin staining along with liver function tests revealed a significant induction of liver injury in the APAP group. Consistent with expectations, both mRNA and protein levels of the four OFGs exhibited a substantial decrease. The administration of ATTAM effectively mitigates copper elevation induced by APAP in both mouse model and AML12 cells. However, systemic administration of ATTM did not significantly alleviate AILI in the mouse model. Conclusion: This study first revealed the potential role of CRGs in the pathological process of AILI and offered novel insights into its underlying pathogenesis.

Identification of hub glycolysis-related genes in acute myocardial infarction and their correlation with immune infiltration using bioinformatics analysis.

PURPOSE: Glycolysis and immune metabolism play important roles in acute myocardial infarction (AMI). Therefore, this study aimed to identify and experimentally validate the glycolysis-related hub genes in AMI as diagnostic biomarkers, and further explore the association between hub genes and immune infiltration. METHODS: Differentially expressed genes (DEGs) from AMI peripheral blood mononuclear cells (PBMCs) were analyzed using R software. Glycolysis-related DEGs (GRDEGs) were identified and analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) for functional enrichment. A protein-protein interaction network was constructed using the STRING database and visualized using Cytoscape software. Immune infiltration analysis between patients with AMI and stable coronary artery disease (SCAD) controls was performed using CIBERSORT, and correlation analysis between GRDEGs and immune cell infiltration was performed. We also plotted nomograms and receiver operating characteristic (ROC) curves to assess the predictive accuracy of GRDEGs for AMI occurrence. Finally, key genes were experimentally validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting using PBMCs. RESULTS: A total of 132 GRDEGs and 56 GRDEGs were identified on the first day and 4-6 days after AMI, respectively. Enrichment analysis indicated that these GRDEGs were mainly clustered in the glycolysis/gluconeogenesis and metabolic pathways. Five hub genes (HK2, PFKL, PKM, G6PD, and ALDOA) were selected using the cytoHubba plugin. The link between immune cells and hub genes indicated that HK2, PFKL, PKM, and ALDOA were significantly positively correlated with monocytes and neutrophils, whereas G6PD was significantly positively correlated with neutrophils. The calibration curve, decision curve analysis, and ROC curves indicated that the five hub GRDEGs exhibited high predictive value for AMI. Furthermore, the five hub GRDEGs were validated by RT-qPCR and western blotting. CONCLUSION: We concluded that HK2, PFKL, PKM, G6PD, and ALDOA are hub GRDEGs in AMI and play important roles in AMI progression. This study provides a novel potential immunotherapeutic method for the treatment of AMI.

A comprehensive pan-cancer analysis revealing SPAG6 as a novel diagnostic, prognostic and immunological biomarker in tumor.

Background: There have been studies on the role of sperm-associated antigen 6 (SPAG6) in cytoskeleton formation and growth cone stability, but it is also unknown how spag6 affect tumor growth and development. The aim of this study was to clarify the role of SPAG6 in pan-cancer, with some findings about thyroid carcinoma (THCA) validated through experiments. Methods: We examined the role of SPAG6 in pan-cancer, with the data being collected from databases. Further analysis was conducted to assess its correlations with prognosis, gene heterogeneity, stemness, and tumor immunity. The interacting proteins of SPAG6 were also identified, and gene ontology enrichment analysis was performed to determine its biological function. We preliminarily confirmed the role of SPAG6 via in vitro experiments and immunofluorescence staining. Results: This study found that SPAG6 expression was differentially expressed in cancers and at various tumor stages and grades. In stomach and esophageal carcinoma (STES), stomach adenocarcinoma (STAD), kidney renal clear cell carcinoma (KIRC), lung squamous cell carcinoma (LUSC), and adrenocortical carcinoma (ACC), SPAG6 expression was correlated with gender. SPAG6 expression was also found to be correlated with prognostic value, with low expression being associated with poor prognosis. Furthermore, SPAG6 expression was positively linked with immune-related cells in HNSC, chemokine receptors in LUSC, and immune checkpoint genes in THCA. Furthermore, SPAG6 overexpression suppressed the malignant phenotypes of THCA cells, manifested by slower proliferation and decreased migration. The different SPAG6 expression in THCA led to different malignant phenotypes, which are involved in the upregulation of DNA repair, MYC targets, peroxisome, and G2M checkpoint. Conclusions: SPAG6 plays a significant role as an oncogene and can be used as a marker to predict the prognosis of cancer. SPAG6 influences both the tumor immune infiltration and microenvironment, making it a promising immunotherapeutic target for tumor therapy.

A novel mitochondrial function-associated programmed cell death-related prognostic signature for predicting the prognosis of early breast cancer.

Purpose: To screen mitochondrial function-associated PCD-related biomarkers and construct a risk model for predicting the prognosis of early breast cancer. Methods: Data on gene expression levels and clinical information were obtained from the TCGA database, and GSE42568 and GSE58812 datasets were obtained from GEO database. The mitochondrial function-associated programmed cell death (PCD) related genes in early breast cancer were identified, then LASSO logistic regression, SVM-RFE, random forest (RF), and multiple Cox logistic regression analysis were employed to construct a prognostic risk model. Differences in immune infiltration, drug sensitivity, and immunotherapy response were evaluated between groups. Lastly, the qRT-PCR was employed to confirm the key genes. Results: Total 1,478 DEGs were screened between normal and early breast cancer groups, and these DEGs were involved in PI3K-Akt signaling pathway, focal adhesion, and ECM-receptor interaction pathways. Then total 178 mitochondrial function-associated PCD related genes were obtained, followed by a four mitochondrial function-associated PCD related genes prognostic model and nomogram were built. In addition, total 2 immune checkpoint genes were lowly expressed in the high-risk group, including CD47 and LAG3, and the fraction of some immune cells in high- and low-risk groups had significant difference, such as macrophage, eosinophil, mast cell, etc., and the Top3 chemotherapeutics with significant differences were included FH535, MK.2206, and bicalutamide. Finally, the qRT-qPCR results shown that the CREB3L1, CAPG, SPINT1 and GRK3 mRNA expression were in line with the bioinformatics analysis results. Conclusion: Four mitochondrial function-associated PCD-related genes were identified, including CREB3L1, CAPG, SPINT1, and GRK3, and the prognostic risk model and nomogram were established for predicting the survival of early breast cancer patient. The chemotherapeutics, containing FH535, MK.2206, and bicalutamide, might be used for early breast cancer.

Fatty infiltration in paraspinal muscles: Predicting the outcome of lumbar surgery and postoperative complications.

Lumbar spine disorders often cause lower back pain, lower limb radiating pain, restricted movement, and neurological dysfunction, which seriously affect the quality of life of middle-aged and older people. It has been found that pathological changes in the spine often cause changes in the morphology and function of the paraspinal muscles (PSMs). Fatty infiltration (FI) in PSMs is closely associated with disc degeneration and Modic changes. And FI causes inflammatory responses that exacerbate the progression of lumbar spine disease and disrupt postoperative recovery. Magnetic resonance imaging (MRI) can better distinguish between fat and muscle tissue with the threshold technique. Three-dimensional-MRI multi-echo imaging techniques such as water-fat separation and proton density are currently popular for studying FI. Muscle fat content obtained based on these imaging sequences has greater accuracy, visualization, acquisition speed, and utility. The proton density fat fraction calculated from these techniques has been shown to evaluate more subtle changes in PSMs. Magnetic resonance spectroscopy can accurately reflect the relationship between FI and the degeneration of PSMs by measuring intracellular and extracellular lipid values to quantify muscle fat. We have pooled and analyzed published studies and found that patients with spinal disorders often exhibit FI in PSMs. Some studies suggest an association between FI and adverse surgical outcomes, although conflicting results exist. These suggests that clinicians should consider FI when assessing surgical risks and outcomes. Future studies should focus on understanding the biological mechanisms underlying FI and its predictive value in spinal surgery, providing valuable insights for clinical decision-making.

Development of a Cancer-associated Fibroblast Signature for Evaluating Immunotherapy Response and Prognosis of Hepatocellular Carcinoma.

BACKGROUND: Alcohol abuse, non-alcoholic fatty liver disease (NAFLD), and hepatitis B and C are the main pathogenic factors of hepatocellular carcinoma (HCC). Though the current understanding of risk factors for HCC has been improved, patients with this type of cancer are normally diagnosed at advanced stages, posing significant challenges to effective treatment. METHODS: This study analyzed the HCC datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database (GSE14520 and GSE116174). Stromal and immune cell infiltration in the tumor microenvironment (TME) was quantified by the ESTIMATE algorithm. To identify gene modules associated with cancer-associated fibroblasts (CAFs), weighted gene co-expression network analysis (WGCNA) was performed to develop gene co-expression networks. A CAF prognosis score (CAFPS) model was established based on the prognostic CAF genes screened by univariate and multivariate Cox regression analyses. To determine the role of the genes in the vital module in HCC, we conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, the relationship between CAFPS and drug sensitivity was analyzed using Genomic Data for Cancer Drug Sensitivity (GDSC). RESULTS: In this study, we found significant differences in immune scores, stromal scores, CAFs scores, and CD4/8 T-cell scores between normal samples and samples with different TNM staging. In particular, the proportion of CAFs was higher than all other cells in normal samples. Gene modules related to CAFs were identified by developing a gene co-expression network using WGCNA analysis. The lightyellow and greenyellow modules showed the highest correlation with CAF scores. Univariate COX analysis identified 12 genes related to HCC prognosis from a total of 191 genes in the two modules. The Kaplan-Meier (KM) survival analysis revealed that a high expression of these genes was associated with a lower survival chance. Based on the 12 genes obtained by univariate COX analysis, multivariate COX analysis was performed to construct a risk score model for the characteristics of CAFs (CAFPS). The KM survival curves of patients in the high CAFPS and low CAFPS groups showed that patients in the low CAFPS group had better survival. CONCLUSION: CAFs played a crucial role in the pathogenesis and treatment response of HCC. Targeting the CAFs milieu may provide therapeutic benefits, highlighting the importance of CAFS in developing a personalized treatment for HCC patients. Further studies are required to verify the current findings and explore their implications in clinical settings.

Association of MRI findings with paraspinal muscles fat infiltration at lower lumbar levels in patients with chronic low back pain: a multicenter prospective study.

OBJECTIVE: In chronic low back pain (CLBP), the relationship between spinal pathologies and paraspinal muscles fat infiltration remains unclear. This study aims to evaluate the relationship between MRI findings and paraspinal muscles morphology and fat infiltration in CLBP patients by quantitative MRI. METHODS: All the CLBP patients were enrolled from July 2021 to December 2022 in four medical institutions. The cross-sectional area (CSA) and proton density fat fraction (PDFF) of the multifidus (MF) and erector spinae (ES) muscles at the central level of the L4/5 and L5/S1 intervertebral discs were measured. MRI findings included degenerative lumbar spondylolisthesis (DLS), intervertebral disc degeneration (IVDD), facet arthrosis, disc bulge or herniation, and disease duration. The relationship between MRI findings and the paraspinal muscles PDFF and CSA in CLBP patients was analyzed. RESULTS: A total of 493 CLBP patients were included in the study (198 females, 295 males), with an average age of 45.68 ± 12.91 years. Our research indicates that the number of MRI findings are correlated with the paraspinal muscles PDFF at the L4/5 level, but is not significant. Moreover, the grading of IVDD is the primary factor influencing the paraspinal muscles PDFF at the L4-S1 level (BES at L4/5=1.845, P < 0.05); DLS was a significant factor affecting the PDFF of MF at the L4/5 level (B = 4.774, P < 0.05). After including age, gender, and Body Mass Index (BMI) as control variables in the multivariable regression analysis, age has a significant positive impact on the paraspinal muscles PDFF at the L4-S1 level, with the largest AUC for ES PDFF at the L4/5 level (AUC = 0.646, cut-off value = 47.5), while males have lower PDFF compared to females. BMI has a positive impact on the ES PDFF only at the L4/5 level (AUC = 0.559, cut-off value = 24.535). CONCLUSION: The degree of paraspinal muscles fat infiltration in CLBP patients is related to the cumulative or synergistic effects of multiple factors, especially at the L4/L5 level. Although age and BMI are important factors affecting the degree of paraspinal muscles PDFF in CLBP patients, their diagnostic efficacy is moderate.

Endoplasmic reticulum stress promotes hepatocellular carcinoma by modulating immunity: a study based on artificial neural networks and single-cell sequencing.

INTRODUCTION: Hepatocellular carcinoma (HCC) is characterized by the complex pathogenesis, limited therapeutic methods, and poor prognosis. Endoplasmic reticulum stress (ERS) plays an important role in the development of HCC, therefore, we still need further study of molecular mechanism of HCC and ERS for early diagnosis and promising treatment targets. METHOD: The GEO datasets (GSE25097, GSE62232, and GSE65372) were integrated to identify differentially expressed genes related to HCC (ERSRGs). Random Forest (RF) and Support Vector Machine (SVM) machine learning techniques were applied to screen ERSRGs associated with endoplasmic reticulum stress, and an artificial neural network (ANN) diagnostic prediction model was constructed. The ESTIMATE algorithm was utilized to analyze the correlation between ERSRGs and the immune microenvironment. The potential therapeutic agents for ERSRGs were explored using the Drug Signature Database (DSigDB). The immunological landscape of the ERSRGs central gene PPP1R16A was assessed through single-cell sequencing and cell communication, and its biological function was validated using cytological experiments. RESULTS: An ANN related to the ERS model was constructed based on SRPX, THBS4, CTH, PPP1R16A, CLGN, and THBS1. The area under the curve (AUC) of the model in the training set was 0.979, and the AUC values in three validation sets were 0.958, 0.936, and 0.970, respectively, indicating high reliability and effectiveness. Spearman correlation analysis suggests that the expression levels of ERSRGs are significantly correlated with immune cell infiltration and immune-related pathways, indicating their potential as important targets for immunotherapy. Mometasone was predicted to be the most promising treatment drug based on its highest binding score. Among the six ERSRGs, PPP1R16A had the highest mutation rate, predominantly copy number mutations, which may be the core gene of the ERSRGs model. Single-cell analysis and cell communication indicated that PPP1R16A is predominantly distributed in liver malignant parenchymal cells and may reshape the tumor microenvironment by enhancing macrophage migration inhibitory factor (MIF)/CD74 + CXCR4 signaling pathways. Functional experiments revealed that after siRNA knockdown, the expression of PPP1R16A was downregulated, which inhibited the proliferation, migration, and invasion capabilities of HCCLM3 and Hep3B cells in vitro. CONCLUSION: The consensus of various machine learning algorithms and artificial intelligence neural networks has established a novel predictive model for the diagnosis of liver cancer associated with ERS. This study offers a new direction for the diagnosis and treatment of HCC.

Screening of genes related to programmed cell death in esophageal squamous cell carcinoma and construction of prognostic model based on transcriptome analysis.

OBJECTIVES: To screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value. METHODS: Differentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored using Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts. RESULTS: Fourteen DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion. CONCLUSION: A prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.

Systematic pan-cancer analysis insights into ICAM1 as an immunological and prognostic biomarker.

Intercellular adhesion molecule 1 (ICAM1) is a cell surface adhesion glycoprotein in the immunoglobulin supergene family. It is associated with several epithelial tumorigenesis processes, as well as with inflammation. However, the function of ICAM1 in the prognosis of tumor immunity is still unclear. This study aimed to examine the immune function of ICAM1 in 33 tumor types and to investigate the prognostic value of tumors. Using datasets from the Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Cancer Cell Lines Encyclopedia (CCLE), Human Protein Atlas (HPA), and cBioPortal, we investigated the role of ICAM1 in tumors. We explored the potential correlation between ICAM1 expression and tumor prognosis, gene mutations, microsatellite instability, and tumor immune cell levels in various cancers. We observed that ICAM1 is highly expressed in multiple malignant tumors. Furthermore, ICAM1 is negatively or positively associated with different malignant tumor prognoses. The expression levels of ICAM1 were correlated with the tumor mutation burden (TMB) in 11 tumors and with MSI in eight tumors. ICAM1 is a gene associated with immune infiltrating cells, such as M1 macrophages and CD8+ T cells in gastric and colon cancer. Meanwhile, the expression of ICAM1 is associated with several immune-related functions and immune-regulation-related signaling pathways, such as the chemokine signaling pathway. Our study shows that ICAM1 can be used as a prognostic biomarker in many cancer types because of its function in tumorigenesis and malignant tumor immunity.

PDK3 drives colorectal carcinogenesis and immune evasion and is a therapeutic target for boosting immunotherapy.

Pyruvate Dehydrogenase Kinase 3 (PDK3) has emerged as a significant player in various cancer types, yet its specific impact on cancers including colon cancer remains ambiguous. Through pan-cancer analysis using TCGA data, we found that the expression of PDK3 and the composition of the immune microenvironment for different tumors were highly heterogeneous across tumors. PDK3 is highly expressed in colorectal cancer and may promote tumor proliferation by activating PI3K-AKT signaling. In addition, we found that PDK3 was able to inhibit tumor antigen presentation signals to suppress immune killing. High PDK3 expression predicts less CD8+ T cell infiltration and effector function. Moreover, inhibition of PDK3 expression bolstered CD8+ T cell-mediated cytotoxicity CD8+ T cell infiltration and activation in vivo. Notably, PDK3 was found to facilitate STAT1 activation and elevate programmed death-ligand 1 (PD-L1) expression in colon cancer cells. Importantly, PDK3 inhibition combination with PD-1 blockade significantly activates the infiltrated CD8+ T cells to suppress tumor growth and improves the survival benefit in several murine tumor models. In summary, these findings underscore PDK3's role in fueling colon cancer growth by orchestrating PI3K-AKT signaling and PD-L1 expression and dampening CD8+ T cell function.

Identification and validation of calcium extrusion-related genes prognostic signature in colon adenocarcinoma.

Background: Disruptions in calcium homeostasis are associated with a wide range of diseases, and play a pivotal role in the development of cancer. However, the construction of prognostic models using calcium extrusion-related genes in colon adenocarcinoma (COAD) has not been well studied. We aimed to identify whether calcium extrusion-related genes serve as a potential prognostic biomarker in the COAD progression. Methods: We constructed a prognostic model based on the expression of calcium extrusion-related genes (SLC8A1, SLC8A2, SLC8A3, SLC8B1, SLC24A2, SLC24A3 and SLC24A4) in COAD. Subsequently, we evaluated the associations between the risk score calculated by calcium extrusion-related genes and mutation signature, immune cell infiltration, and immune checkpoint molecules. Then we calculated the immune score, stromal score, tumor purity and estimate score using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm. The response to immunotherapy was assessed using tumor immune dysfunction and exclusion (TIDE). Finally, colorectal cancer cells migration, growth and colony formation assays were performed in RKO cells with the overexpression or knockdown SLC8A3, SLC24A2, SLC24A3, or SLC24A4. Results: We found that patients with high risk score of calcium extrusion-related genes tend to have a poorer prognosis than those in the low-risk group. Additionally, patients in high-risk group had higher rates of KRAS mutations and lower MUC16 mutations, implying a strong correlation between KRAS and MUC16 mutations and calcium homeostasis in COAD. Moreover, the high-risk group showed a higher infiltration of regulatory T cells (Tregs) in the tumor microenvironment. Finally, our study identified two previously unreported model genes (SLC8A3 and SLC24A4) that contribute to the growth and migration of colorectal cancer RKO cells. Conclusions: Altogether, we developed a prognostic risk model for predicting the prognosis of COAD patients based on the expression profiles of calcium extrusion-related genes, Furthermore, we validated two previously unreported tumor suppressor genes (SLC8A3 and SLC24A4) involved in colorectal cancer progression.

DPF2 overexpression correlates with immune infiltration and dismal prognosis in hepatocellular carcinoma.

Background: Double plant homeodomain finger 2 (DPF2), belonging to the d4 family of structural domains, has been associated with various human malignancies. However, its impact on hepatocellular carcinoma (HCC) remains unclear. The objective of this study is to elucidate the role of DPF2 in the diagnosis and prognosis of HCC. Methods: DPF2 gene expression in HCC and adjacent tissues was analyzed using Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, validated by immunohistochemical staining of Guangxi specimens and data from the Human Protein Atlas (HPA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genome (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to identify DPF2's potential pathways and functions in HCC. DPF2's mutation and methylation statuses were assessed via cBioPortal and MethSurv. The association between DPF2 and immune infiltration was investigated by TIMER. The prognostic value of DPF2 in HCC was established through Kaplan-Meier and Cox regression analyses. Results: DPF2 levels were significantly higher in HCC than normal tissues (p<0.001), correlating with more severe HCC features (p<0.05). Higher DPF2 expression predicted poorer overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). DPF2 involvement was noted in critical signaling pathways including the cell cycle and Wnt. It also correlated with T helper cells, Th2 cells, and immune checkpoints like CTLA-4, PD-1, and PD-L1. Conclusion: High DPF2 expression, associated with poor HCC prognosis, may disrupt tumor immune balance and promote immune evasion. DPF2 could potentially be utilized as a biomarker for diagnosing and prognosticating hepatocellular carcinoma.