Gene Ontology Consortium: going forward

Identification of a pro-protein synthesis osteosarcoma subtype for predicting prognosis and treatment

Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor that is aggressive and has a poor prognosis. Although combining surgery and chemotherapy has significantly improved patient outcomes, the prognosis for OS patients with metastatic or recurrent OS has remained unsatisfactory. Therefore, it is imperative to gain a fresh perspective on OS development mechanisms and treatment strategies. After studying single-cell RNA sequencing (scRNA-seq) data in public databases, we identified seven OS subclonal types based on intra-tumor heterogeneity. Subsequently, we constructed a prognostic model based on pro-protein synthesis osteosarcoma (PPS-OS)-associated genes. Correlation analysis showed that the prognostic model performs extremely well in predicting OS patient prognosis. We also demonstrated that the independent risk factors for the prognosis of OS patients were tumor primary site, metastatic status, and risk score. Based on these factors, nomograms were constructed for predicting the 3- and 5-year survival rates. Afterward, the investigation of the tumor immune microenvironment (TIME) revealed the vital roles of γδ T-cell and B-cell activation. Drug sensitivity analysis and immune checkpoint analysis identified drugs that have potential application value in OS. Finally, the jumping translocation breakpoint (JTB) gene was selected for experimental validation. JTB silencing suppressed the proliferation, migration, and invasion of OS cells. Therefore, our research suggests that PPS-OS-related genes facilitate the malignant progression of OS and may be employed as prognostic indicators and therapeutic targets in OS.

Zebrafish myo7aa affects congenital hearing by regulating Rho-GTPase signaling

Introduction

myo7aa, the homolog of the human Usher 1B syndrome pathogenic gene, myo7A, plays an important role in stereociliary development and maintenance, therefore, is critical for hearing and balance. However, the molecular mechanisms that myo7aa regulate hearing and balance still need to be studied.

Methods

In this study, we generated two independent zebrafish myo7aa knockout lines using CRISPR/Cas9 technology. To investigate the effects of myo7aa on hearing, YO-PRO-1 staining and startle response assay were used. To gain insight into the specific molecular mechanisms by which myo7aa affects hearing, transcriptome sequencing and bioinformatics analysis were employed.

Results

Our study showed that hair cells of myo7aa-/- zebrafish can not take up YO-PRO-1 fluorescent dye and are insensitive to acoustic stimulation in myo7aa-/- zebrafish compared to wild type. Genes related to the Rho GTPase signaling pathway, such as arhgap33, dab2ip, and arghef40, are significantly down-regulated in myo7aa-/- zebrafish embryos at 3 dpf. GTP and ATP compensation can partially rescue the hair cell defects in myo7aa knockout zebrafish.

Discussion

Our findings suggest that zebrafish myo7aa affects congenital hearing by regulating Rho GTPase signaling, and loss of myo7aa leads to abnormal Rho GTPase signaling and impairs hair cell function. myo7aa, myo7A, arhgap33, dab2ip, arghef40 and myo7aa-/- fonts in the abstract are italicized. -/- is a superscript format.

A Mouse Model of Sporadic Alzheimer's Disease with Elements of Major Depression

After olfactory bulbectomy, animals are often used as a model of major depression or sporadic Alzheimer's disease and, hence, the status of this model is still disputable. To elucidate the nature of alterations in the expression of the genome after the operation, we analyzed transcriptomes of the cortex, hippocampus, and cerebellum of the olfactory bulbectomized (OBX) mice. Analysis of the functional significance of genes in the brain of OBX mice indicates that the balance of the GABA/glutamatergic systems is disturbed with hyperactivation of the latter in the hippocampus, leading to the development of excitotoxicity and induction of apoptosis in the background of severe mitochondrial dysfunction and astrogliosis. On top of this, the synthesis of neurotrophic factors decreases leading to the disruption of the cytoskeleton of neurons, an increase in the level of intracellular calcium, and the activation of tau protein hyperphosphorylation. Moreover, the acetylcholinergic system is deficient in the background of the hyperactivation of acetylcholinesterase. Importantly, the activity of the dopaminergic, endorphin, and opiate systems in OBX mice decreases, leading to hormonal dysfunction. On the other hand, genes responsible for the regulation of circadian rhythms, cell migration, and innate immunity are activated in OBX animals. All this takes place in the background of a drastic downregulation of ribosomal protein genes in the brain. The obtained results indicate that OBX mice represent a model of Alzheimer's disease with elements of major depression.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Ferroptosis-Associated Extracellular Matrix Remodeling in Radiation-Induced Lung Fibrosis Progression

Background: Radiation-induced lung fibrosis (RILF) is a life-threatening complication of thoracic radiotherapy. Ferroptosis, a recently discovered type of cell death, is believed to contribute to RILF, though the associated mechanisms are unknown. This study aimed to investigate the potential mechanism of ferroptosis in RILF and examine the contribution of different cell types to ferroptosis during RILF progression. Methods: Histopathological changes in RILF lung tissue were assessed through H&E and Masson staining. IHC staining investigated ferroptosis markers (GPX4, ACSL4, NCOA4). Ferroptosis-related genes (FRG) and pathway scores were derived from RILF transcriptome microarray data. The sc-RNAseq analysis detected FRG score dynamics across cell types, validated by IF staining for PDGFR-α and ACSL4. Results: ACSL4 and NCOA4 protein levels were significantly higher and GPX4 lower in IR than control. FRG scores were positively correlated with fibrosis-related pathway scores in the RILF transcriptome data. FRG and ECM scores were concurrently upregulated in myofibroblasts. Enhanced co-staining of PDGFR-α and ACSL4 were observed in the fibrotic areas of RILF lungs. Conclusions: Our research indicated that in RILF, fibroblasts undergoing ferroptosis may release increased levels of ECM, potentially accelerating the progression of lung fibrosis. This finding presents ferroptosis as a potential therapeutic target in RILF.

Crosstalk among proximal tubular cells, macrophages, and fibroblasts in acute kidney injury: single-cell profiling from the perspective of ferroptosis

The link between ferroptosis, a form of cell death mediated by iron and acute kidney injury (AKI) is recently gaining widespread attention. However, the mechanism of the crosstalk between cells in the pathogenesis and progression of acute kidney injury remains unexplored. In our research, we performed a non-negative matrix decomposition (NMF) algorithm on acute kidney injury single-cell RNA sequencing data based specifically focusing in ferroptosis-associated genes. Through a combination with pseudo-time analysis, cell-cell interaction analysis and SCENIC analysis, we discovered that proximal tubular cells, macrophages, and fibroblasts all showed associations with ferroptosis in different pathways and at various time. This involvement influenced cellular functions, enhancing cellular communication and activating multiple transcription factors. In addition, analyzing bulk expression profiles and marker genes of newly defined ferroptosis subtypes of cells, we have identified crucial cell subtypes, including Egr1 + PTC-C1, Jun + PTC-C3, Cxcl2 + Mac-C1 and Egr1 + Fib-C1. All these subtypes which were found in AKI mice kidneys and played significantly distinct roles from those of normal mice. Moreover, we verified the differential expression of Egr1, Jun, and Cxcl2 in the IRI mouse model and acute kidney injury human samples. Finally, our research presented a novel analysis of the crosstalk of proximal tubular cells, macrophages and fibroblasts in acute kidney injury targeting ferroptosis, therefore, contributing to better understanding the acute kidney injury pathogenesis, self-repairment and acute kidney injury-chronic kidney disease (AKI-CKD) progression.

CircABHD2 Inhibits Malignant Progression of Endometrial Cancer by Regulating NAD+/NAMPT Metabolism Axis

Circular RNAs (circRNAs) perform important functions in the regulation of diverse physiological and pathological processes. CircABHD2 exhibits down-regulation in both endometrial cancer (EC) cells and tissues, but the biological roles and mechanisms of action in EC are still unclear. This study aims to provide a theoretical basis for the role of circABHD2 in EC and potential targets for individualized precision therapy. Dysregulated circRNAs were identified using RNA sequencing (RNA-Seq) from EC tissues and validated using RT-qPCR. CCK-8, colony formation assay, wound healing assay, transwell assay, cell cycle, and apoptosis assay were used to evaluate the effects of circABHD2 on EC cells. Metabolomics assay and western blot analyses were used to investigate the potential mechanisms of circABHD2. From sequencing of RNA (RNA-Seq) analysis of EC tissues, we obtained 19 dysregulated circRNAs, including 8 upregulated ones and 11 downregulated ones. Using RT-qPCR on 32 EC tissues and 19 normal endometrial tissues, we confirmed that circABHD2 was downregulated in EC tissues. The expression levels of circABHD2 were closely relevant to the International Federation of Gynecology and Obstetrics (FIGO) stage and differentiation degree of EC. Functional experiments demonstrated that overexpression of circABHD2 decreased proliferation, migration, invasion, and promoted cell apoptosis. Un-targeted metabolomic assay revealed 31 differential metabolites in EC cells overexpressing circABHD2. KEGG analysis of differential metabolites indicated that NAD+ is the core metabolite regulated by circABHD2. NAMPT is one key enzyme involved in the synthetic pathway responsible for NAD+. Subsequent experiments confirmed that by inhibiting NAMPT protein expression in EC cells, cirABHD2 can inhibit NAD+ level, suggesting that circABHD2 may inhibit EC by regulating the metabolic axis of NAD+/NAMPT. CircABHD2, a downregulated circRNA in EC cells and tissues, inhibits the malignant progression of EC via the NAD+/NAMPT metabolic axis. This discovery presents a promising diagnostic biomarker and potential therapeutic target for EC.

Transcriptomic Analysis of Metastatic Uveal Melanoma and Differences in Male and Female Patients

BACKGROUND/AIM

Uveal melanoma is an ocular malignancy whose prognosis severely worsens following metastasis. In order to improve the understanding of molecular physiology of metastatic uveal melanoma, we identified genes and pathways implicated in metastatic vs non-metastatic uveal melanoma.

PATIENTS AND METHODS

A previously published dataset from Gene Expression Omnibus (GEO) was used to identify differentially expressed genes between metastatic and non-metastatic samples as well as to conduct pathway and perturbagen analyses using Gene Set Enrichment Analysis (GSEA), EnrichR, and iLINCS.

RESULTS

In male metastatic uveal melanoma samples, the gene LOC401052 is significantly down-regulated and FHDC1 is significantly up-regulated compared to non-metastatic male samples. In female samples, no significant differently expressed genes were found. Additionally, we identified many significant up-regulated immune response pathways in male metastatic uveal melanoma, including "T cell activation in immune response". In contrast, many top up-regulated female pathways involve iron metabolism, including "heme biosynthetic process". iLINCS perturbagen analysis identified that both male and female samples have similar discordant activity with growth factor receptors, but only female samples have discordant activity with progesterone receptor agonists.

CONCLUSION

Our results from analyzing genes, pathways, and perturbagens demonstrate differences in metastatic processes between sexes.

Species-specific duplicated FMRFaR-like gene A62 regulates spontaneous locomotion in Apolygus lucorum

BACKGROUND

Apolygus lucorum, a major cotton pest, has undergone a significant expansion of the FMRFaR gene within the GPCR superfamily, resulting in two classes of GPCR, namely FMRFaR (A54-55) and newly duplicated FMRFaR-like (A56-62). Notably, FMRFaR-like genes, particularly A62, show enhanced expression in the legs and wings of adults, indicating their potential role in locomotion. Employing A62 as a representative of FMRFaR-like, our study investigates the influence of FMRFa, FMRFaR, and FMRFaR-like on locomotion and development of A. lucorum.

RESULTS

FMRFaR and FMRFa exhibit comparable temporal and tissue expression patterns, whereas the FMRFaR-like genes within A. lucorum exhibit completely distinct evolutionary and expression patterns compared to classical FMRFaR. RNA interference (RNAi) experiments revealed that suppressing FMRFa expression results in complete lethality in A. lucorum, but neither FMRFaR nor A62 exhibit the same effect after RNAi. Suppressing the expression of FMRFa only decreases the expression of the A54 gene simultaneously, suggesting that A54 may function as a classical FMRFaR activated by FMRFa. RNAi of A62 leads to wing malformation and a significant reduction in spontaneous movement behavior in A. lucorum. Further transcriptomic analysis revealed that A62 affects the A. lucorum's movement behavior through energy metabolism pathways and motor protein pathways.

CONCLUSION

Our study unveils the unique and complex roles of FMRFa and its receptor in A. lucorum. These findings provide valuable insights into potential targets for pest control strategies aimed at managing A. lucorum populations in cotton fields. © 2024 Society of Chemical Industry.

Giardia intestinalis extracellular vesicles induce changes in gene expression in human intestinal epithelial cells in vitro

Giardiasis is a common waterborne zoonotic disease caused by Giardia intestinalis. Upon infection, Giardia releases excretory and secretory products (ESPs) including secreted proteins (SPs) and extracellular vesicles (EVs). Although the interplay between ESPs and intestinal epithelial cells (IECs) has been previously described, the functions of EVs in these interactions and their differences from those of SPs require further exploration. In the present study, EVs and EV-depleted SPs were isolated from Giardia ESPs. Proteomic analyses of isolated SPs and EVs showed 146 and 91 proteins, respectively. Certain unique and enriched proteins have been identified in SPs and EVs. Transcriptome analysis of Caco-2 cells exposed to EVs showed 96 differentially expressed genes (DEGs), with 56 upregulated and 40 downregulated genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) indicated that Caco-2 genes related to metabolic processes, the HIF-1 signaling pathway, and the cAMP signaling pathway were affected. This study provides new insights into host-parasite interactions, highlighting the potential significance of EVs on IECs during infections.

Pterostilbene exerts anti-lung squamous cell carcinoma function by suppressing the level of KANK3

Early detection of lung squamous cell carcinoma (LUSC) has a significant impact on clinical outcomes, and pterostilbene (PT) is a natural compound with promising anti-oncogenic activities. This study aimed to identify potential LUSC biomarkers through a series of bioinformatic analyses and clinical verification and explored the interaction between PT and selected biomarkers during the treatment of LUSC. The analysis of the expression profile of the clinical samples of LUSC was performed to identify dysexpressed genes (DEGs) and validated by IHC. The role of KANK3 in the anti-LUSC effects of PT was assessed with a series of in vitro and in vivo assays. 4335 DEGs were identified, including 1851 upregulated genes and 2484 downregulated genes. Survival analysis showed that KANK3 was significantly higher in patients with LUSC with an advanced tumor stage. In in vitro assays, PT suppressed cell viability, induced apoptosis, and inhibited migration and invasion in LUSC cell lines, which was associated with downregulation of KANK3. After the reinduction of the KANK3 level in LUSC cells, the anti-LUSC function of PT was impaired. In mice model, reinduction of KANK3 increased tumor growth and metastasis even under the treatment of PT. The findings outlined in the current study indicated that PT exerted anti-LUSC function in a KANK3 inhibition-dependent manner.

The prognostic and clinical value of genes associate with immunity and amino acid Metabolism in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the commonest subtype of primary lung cancer. A comprehensive analysis of the association of immunity with amino acid metabolism in LUAD is critical for understanding the disease.

Methods

The present study examined LUAD and noncancerous cases from the TCGA database. Differentially expressed genes (DEGs) between LUAD and noncancerous tissues were detected by analyzing processed expression profiles. We cross-referenced the up-regulated DEGs with Immune and Amino Acid Metabolism-related genes (I&AAMGs), resulting in Immune and Amino Acid Metabolism related differentially expressed genes (IAAAMRDEGs). The STRING database was employed to analyze PPI on IAAAMRDEGs, obtaining excavated hub genes, whose biological processes, molecular functions and cellular components were examined with GO/KEGG. Potential mechanisms related to LUAD were investigated by GSEA and GSVA. A prognostic model was built by LASSO-COX analysis, taking into consideration risk scores and prognostic factors to determine biomarkers affecting LUAD occurrence and prognosis.

Results

Totally 377 genes were detected at the intersection of upregulated DEGs and I&AAMGs. Analysis of PPI on these 377 IAAAMRDEGs yielded 17 hub genes. A LASSO regression analysis was utilized to assess the prognostic values of the 17 hub genes. Validation using the combined dataset confirmed 4 genes, e.g., polo-like kinase (PLK1), Ribonucleotide Reductase Subunit M2 (RRM2), Thyroid Hormone Receptor Interactor 13 (TRIP13), and Hyaluronan-Mediated Motility Receptor (HHMR). The model's accuracy was further assessed by ROC curve analysis and the COX model. In addition, immunohistochemical staining obtained from the HPA database, revealed enhanced PLK1 expression in LUAD samples.

Conclusion

LUAD pathogenesis is highly associated with immunity and amino acid metabolism. The PLK1, RRM2, TRIP13, and HMMR genes have prognostic values for LUAD. PLK1 upregulation in LUAD might be involved in tumorigenesis by modulating the cell cycle and represents a potential prognostic factor in clinic.

Comprehensive Analysis of angiogenesis associated genes and tumor microenvironment infiltration characterization in cervical cancer

Background

Cervical cancer is among the most prevalent malignancies worldwide. This study explores the relationships between angiogenesis-related genes (ARGs) and immune infiltration, and assesses their implications for the prognosis and treatment of cervical cancer. Additionally, it develops a diagnostic model based on angiogenesis-related differentially expressed genes (ARDEGs).

Methods

We systematically evaluated 15 ARDEGs using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Immune cell infiltration was assessed using a single-sample gene-set enrichment analysis (ssGSEA) algorithm. We then constructed a diagnostic model for ARDEGs using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and evaluated the diagnostic value of this model and the hub genes in predicting clinical outcomes and immunotherapy responses in cervical cancer.

Results

A set of ARDEGs was identified from the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UCSC Xena database. We performed KEGG, GO, and GSEA analyses on these genes, revealing significant involvement in cell proliferation, differentiation, and apoptosis. The ARDEGs diagnostic model, constructed using LASSO regression analysis, showed high predictive accuracy in cervical cancer patients. We developed a reliable nomogram and decision curve analysis to evaluate the clinical utility of the ARDEG diagnostic model. The 15 ARDEGs in the model were associated with clinicopathological features, prognosis, and immune cell infiltration. Notably, ITGA5 expression and the abundance of immune cell infiltration (specifically mast cell activation) were highly correlated.

Conclusion

This study identifies the prognostic characteristics of ARGs in cervical cancer patients, elucidating aspects of the tumor microenvironment. It enhances the predictive accuracy of immunotherapy outcomes and establishes new strategies for immunotherapeutic interventions.

Coordinated inflammation and immune response transcriptional regulation in breast cancer molecular subtypes

Breast cancer, characterized by its complexity and diversity, presents significant challenges in understanding its underlying biology. In this study, we employed gene co-expression network analysis to investigate the gene composition and functional patterns in breast cancer subtypes and normal breast tissue. Our objective was to elucidate the detailed immunological features distinguishing these tumors at the transcriptional level and to explore their implications for diagnosis and treatment. The analysis identified nine distinct gene module clusters, each representing unique transcriptional signatures within breast cancer subtypes and normal tissue. Interestingly, while some clusters exhibited high similarity in gene composition between normal tissue and certain subtypes, others showed lower similarity and shared traits. These clusters provided insights into the immune responses within breast cancer subtypes, revealing diverse immunological functions, including innate and adaptive immune responses. Our findings contribute to a deeper understanding of the molecular mechanisms underlying breast cancer subtypes and highlight their unique characteristics. The immunological signatures identified in this study hold potential implications for diagnostic and therapeutic strategies. Additionally, the network-based approach introduced herein presents a valuable framework for understanding the complexities of other diseases and elucidating their underlying biology.

Potential diagnostic biomarkers for immunogenic cell death in elderly female patients with ischemic stroke: identification and analysis

Ischemic stroke (IS) is of increasing concern given the aging population and prevalence of unhealthy lifestyles, with older females exhibiting higher susceptibility. This study aimed to identify practical diagnostic markers, develop a diagnostic model for immunogenic cell death (ICD)-associated IS, and investigate alterations in the immune environment caused by hub genes. Differentially expressed genes associated with ICD in IS were identified based on weighted gene co-expression network analysis and the identification of significant modules. Subsequently, machine learning algorithms were employed to screened hub genes, which were further assessed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis. A nomogram mode lwas then constructed for IS diagnosis, and its diagnostic value was assessed using a receiver operating characteristic curve. Finally, alterations in immune cell infiltration were assessed within patients with IS, and the pan-cancer expression patterns of hub genes were evaluated. Three hub genes associated with ICD (PDK4, CCL20, and FBL) were identified. The corresponding nomogram model for IS diagnosis could effectively identify older female patients with IS (area under the curve (AUC) = 0.9555). Overall, the three hub genes exhibit good diagnostic value (AUC > 0.8). CCL20 and FBL are significantly associated with the extent of immune cells infiltration. Moreover, a strong link exists between hub gene expression and pan-cancer prognosis. Cumulatively, these results indicate that ICD-related hub genes critically influence IS progression in older females, presenting novel diagnostic and therapeutic targets for personalized treatment.

CDK4/6 inhibition enhances T-cell immunotherapy on hepatocellular carcinoma cells by rejuvenating immunogenicity

Hepatocellular carcinoma (HCC) poses a significant clinical challenge, necessitating the integration of immunotherapeutic approaches. Palbociclib, a selective CDK4/6 inhibitor, has demonstrated promising efficacy in preclinical HCC models and is being evaluated as a novel therapeutic option in clinical trials. Additionally, CDK4/6 inhibition induces cellular senescence, potentially influencing the tumor microenvironment and immunogenicity of cancer cells. In this study, we conducted comprehensive bioinformatic analyses using diverse HCC transcriptome datasets, including bulk and single-cell RNA-sequencing data from public databases. We also utilized human and mouse HCC cells to investigate functional aspects. Primary T cells isolated from mouse blood were employed to assess T cell immunity against HCC cells. Results revealed that CD8+ T-cell infiltration correlates with improved outcomes in HCC patients with suppressed CDK4/6 expression. Moreover, CDK4/6 expression was associated with alterations in the immune landscape and immune checkpoint expression within the liver tumor microenvironment. Furthermore, we found that treatment with Palbociclib and Doxorubicin induces cellular senescence and a senescence-associated secretory phenotype in HCC cells. Notably, pretreatment with Palbociclib augmented T cell-mediated cytotoxicity against HCC cells, despite upregulation of PD-L1, surpassing the effects of Doxorubicin pretreatment. In conclusion, our study elucidates a novel mechanism by which CDK4/6 inhibition enhances T-cell-associated cancer elimination and proposes a potential therapeutic strategy to enhance T-cell immunotherapy on HCC.

Chromosome-level genome assembly of the cereal cyst nematode Heterodera flipjevi

As an economically important plant parasitic nematode (PPN), Heterodera filipjevi causes great damage on wheat, and now it was widely recorded in many countries. While multiple genomes of PPNs have been published, high-quality genome assembly and annotation on H. filipjevi have yet to be performed. This study presents a chromosome-scale genome assembly and annotation for H. filipjevi, utilizing a combination of Illumina short-read, PacBio long-read, and Hi-C sequencing technologies. The genome consists of 9 pseudo-chromosomes that contain 134.19 Mb of sequence, with a scaffold N50 length of 11.88 Mb. In total, 10,036 genes were annotated, representing 75.20% of the total predicted protein-coding genes. Our study provides the first chromosome-scale genome for H. filipjevi, which is also the inaugural high-quality genome of cereal cyst nematodes (CCNs). It provides a valuable genomic resource for further biological research and pest management of cereal cyst nematodes disease.

Hepatocellular carcinoma: An analysis of the expression status of stress granules and their prognostic value

BACKGROUND

Hepatocellular carcinoma (HCC) is a global popular malignant tumor, which is difficult to cure, and the current treatment is limited.

AIM

To analyze the impacts of stress granule (SG) genes on overall survival (OS), survival time, and prognosis in HCC.

METHODS

The combined The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE25097, and GSE36376 datasets were utilized to obtain genetic and clinical information. Optimal hub gene numbers and corresponding coefficients were determined using the Least absolute shrinkage and selection operator model approach, and genes for constructing risk scores and corresponding correlation coefficients were calculated according to multivariate Cox regression, respectively. The prognostic model’s receiver operating characteristic (ROC) curve was produced and plotted utilizing the time ROC software package. Nomogram models were constructed to predict the outcomes at 1, 3, and 5-year OS prognostications with good prediction accuracy.

RESULTS

We identified seven SG genes (DDX1, DKC1, BICC1, HNRNPUL1, CNOT6, DYRK3, CCDC124) having a prognostic significance and developed a risk score model. The findings of Kaplan-Meier analysis indicated that the group with a high risk exhibited significantly reduced OS in comparison with those of the low-risk group (P < 0.001). The nomogram model’s findings indicate a significant enhancement in the accuracy of OS prediction for individuals with HCC in the TCGA-HCC cohort. Gene Ontology and Gene Set Enrichment Analysis suggested that these SGs might be involved in the cell cycle, RNA editing, and other biological processes.

CONCLUSION

Based on the impact of SG genes on HCC prognosis, in the future, it will be used as a biomarker as well as a unique therapeutic target for the identification and treatment of HCC.

Shared biomarkers and mechanisms in idiopathic pulmonary fibrosis and non-small cell lung cancer

BACKGROUND

Epidemiological evidence has indicated the occurrence of idiopathic pulmonary fibrosis (IPF) with coexisting lung cancer is not a coincidence. The pathogenic mechanisms shared between IPF and non-small cell lung cancer (NSCLC) at the transcriptional level remain elusive and need to be further elucidated.

METHODS

IPF and NSCLC datasets of expression profiles were obtained from the GEO database. Firstly, to detect the shared dysregulated genes positively correlated with both IPF and NSCLC, differentially expressed analysis and WGCNA analysis were carried out. Functional enrichment and the construction of protein-protein network were employed to reveal pathogenic mechanisms related to two diseases mediated by the shared dysregulated genes. Then, the LASSO regression was adopted for screening critical candidate biomarkers for two disorders. Moreover, ROC curves were applied to evaluate the diagnostic value of the candidate biomarkers in both IPF and NSCLC.

RESULTS

The 20 shared dysregulated genes positively correlated with both IPF and NSCLC were identified after intersecting differentially expressed analysis and WGCNA analysis. Functional enrichment revealed the 20 shared genes mostly enriched in extracellular region, which is critical in the organization of extracellular matrix. The protein-protein networks unrevealed the interaction of the 11 shared genes involving in collagen deposition and the connection between PYCR1 with PSAT1. PSAT1, PYCR1, COL10A1 and KIAA1683 were screened by the LASSO regression. ROC curves comprising area under the curve (AUC) verified the potential diagnostic value of PSAT1 and COL10A1 in both IPF and NSCLC.

CONCLUSIONS

We revealed dysregulated extracellular matrix through aberrant expression of the relevant genes, which provided further understanding for the common molecular mechanisms predisposing the occurrence of both IPF and NSCLC.

Identification of PANoptosis-related genes as prognostic indicators of thyroid cancer

Background

Thyroid cancer (THCA) has become a common malignancy in recent years, with the mortality rate steadily increasing. PANoptosis is a unique kind of programmed cell death (PCD), including pyroptosis, necroptosis, and apoptosis, and is involved in the proliferation and prognosis of numerous cancers. This paper demonstrated the connection between PANoptosis-related genes and THCA based on the analyses of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, which have not been evaluated yet.

Methods

We identified PANoptosis-related differentially expressed genes (PRDEGs) by multi-analyzing the TCGA-THCA and GEO datasets. To identify the significant PRDEGs, a prognostic model was constructed using least absolute shrinkage and selection operator regression (LASSO). The predictive values of the significant PRDEGs for THCA outcomes were determined using Cox regression analysis and nomograms. Gene enrichment analyses were performed. Finally, immunohistochemistry was carried out using the human protein atlas.

Results

A LASSO regression model based on nine PRDEGs was constructed, and the prognostic value of key PRDEGs was explored via risk score. Univariate and multivariate Cox regression were implemented to identify further three significant PRDEGs closely related to distant metastasis, lymph node metastasis, and tumor stage. Then, a nomogram was constructed, which presented high predictive accuracy for 5 years survival of THCA patients. Gene enrichment analyses in THCA were strongly associated with PCD pathways. CASP6 presented significantly differential expression during clinical T stage, N stage, and PFI events (P < 0.05 for all) and demonstrated the highest degree of diagnostic efficacy in PRDEGs (HR: 2.060, 95 % CI: 1.170-3.628, P < 0.05). Immunohistochemistry showed CASP6 was more abundant in THCA tumor tissue.

Conclusion

A potential prognostic role for PRDEGs in THCA was identified, providing a new direction for treatment. CASP6 may be a potential therapeutic target and a novel prognostic biomarker for THCA.

Hepatocellular carcinoma: An analysis of the expression status of stress granules and their prognostic value

BACKGROUND

Hepatocellular carcinoma (HCC) is a global popular malignant tumor, which is difficult to cure, and the current treatment is limited.

AIM

To analyze the impacts of stress granule (SG) genes on overall survival (OS), survival time, and prognosis in HCC.

METHODS

The combined The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE25097, and GSE36376 datasets were utilized to obtain genetic and clinical information. Optimal hub gene numbers and corresponding coefficients were determined using the Least absolute shrinkage and selection operator model approach, and genes for constructing risk scores and corresponding correlation coefficients were calculated according to multivariate Cox regression, respectively. The prognostic model's receiver operating characteristic (ROC) curve was produced and plotted utilizing the time ROC software package. Nomogram models were constructed to predict the outcomes at 1, 3, and 5-year OS prognostications with good prediction accuracy.

RESULTS

We identified seven SG genes (DDX1, DKC1, BICC1, HNRNPUL1, CNOT6, DYRK3, CCDC124) having a prognostic significance and developed a risk score model. The findings of Kaplan-Meier analysis indicated that the group with a high risk exhibited significantly reduced OS in comparison with those of the low-risk group (P < 0.001). The nomogram model's findings indicate a significant enhancement in the accuracy of OS prediction for individuals with HCC in the TCGA-HCC cohort. Gene Ontology and Gene Set Enrichment Analysis suggested that these SGs might be involved in the cell cycle, RNA editing, and other biological processes.

CONCLUSION

Based on the impact of SG genes on HCC prognosis, in the future, it will be used as a biomarker as well as a unique therapeutic target for the identification and treatment of HCC.

Identification of immune-related tumor antigens and immune subtypes in osteosarcoma

Purpose

The development of tumor vaccines has become a hot topic in immunotherapy for osteosarcoma (OS); however, more tumor antigens with stronger immunogenicity need to be identified.

Methods

We downloaded six sets of gene expression profile data from online databases. The overexpressed genes were analyzed, intersected, and used to calculate the immune infiltration abundance in the TARGET OS dataset based on their expression matrix. Potential tumor antigen genes were identified based on whether they exhibited a high correlation with the antigen-presenting cells (APCs). A total of 1330 immune-related genes (IRGs) from the ImmPort website were retrieved based on their expression, and the Consensus Cluster method was used to obtain immune subtypes of the OS samples. Prognosis, immune microenvironment, and sensitivity to drugs were compared among the immune subtypes.

Results

In total, 680 genes were overexpressed in at least two datasets, of which TREM2, TNFRSF12A, and THY1 were positively correlated with different APCs. Based on the expression matrix of 1330 IRGs in TARGET-OS, two immune subtypes, IS1 and IS2, were identified. The prognosis of the IS1 subtype was better than that of IS2, the expression of immune checkpoint (ICP)-related genes was higher in patients with the IS1 subtype, and immune cell infiltration and sensitivity to 16 drugs were generally higher in IS1 subtype patients.

Conclusion

We identified three APC-correlated genes that can be considered to code for potential novel tumor antigens for OS vaccines. Two immune subtypes in patients with OS were identified to implement personalized treatments using mRNA vaccines.

Genome-wide analyses of member identification, expression pattern, and protein-protein interaction of EPF/EPFL gene family in Gossypium

BACKGROUND

Epidermal patterning factor / -like (EPF/EPFL) gene family encodes a class of cysteine-rich secretory peptides, which are widelyfound in terrestrial plants.Multiple studies has indicated that EPF/EPFLs might play significant roles in coordinating plant development and growth, especially as the morphogenesis processes of stoma, awn, stamen, and fruit skin. However, few research on EPF/EPFL gene family was reported in Gossypium.

RESULTS

We separately identified 20 G. raimondii, 24 G. arboreum, 44 G. hirsutum, and 44 G. barbadense EPF/EPFL genes in the 4 representative cotton species, which were divided into four clades together with 11 Arabidopsis thaliana, 13 Oryza sativa, and 17 Selaginella moellendorffii ones based on their evolutionary relationships. The similar gene structure and common motifs indicated the high conservation among the EPF/EPFL members, while the uneven distribution in chromosomes implied the variability during the long-term evolutionary process. Hundreds of collinearity relationships were identified from the pairwise comparisons of intraspecifc and interspecific genomes, which illustrated gene duplication might contribute to the expansion of cotton EPF/EPFL gene family. A total of 15 kinds of cis-regulatory elements were predicted in the promoter regions, and divided into three major categories relevant to the biological processes of development and growth, plant hormone response, and abiotic stress response. Having performing the expression pattern analyses with the basic of the published RNA-seq data, we found most of GhEPF/EPFL and GbEPF/EPFL genes presented the relatively low expression levels among the 9 tissues or organs, while showed more dramatically different responses to high/low temperature and salt or drought stresses. Combined with transcriptome data of developing ovules and fibers and quantitative Real-time PCR results (qRT-PCR) of 15 highly expressed GhEPF/EPFL genes, it could be deduced that the cotton EPF/EPFL genes were closely related with fiber development. Additionally, the networks of protein-protein interacting among EPF/EPFLs concentrated on the cores of GhEPF1 and GhEPF7, and thosefunctional enrichment analyses indicated that most of EPF/EPFLs participate in the GO (Gene Ontology) terms of stomatal development and plant epidermis development, and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways of DNA or base excision repair.

CONCLUSION

Totally, 132 EPF/EPFL genes were identified for the first time in cotton, whose bioinformatic analyses of cis-regulatory elements and expression patterns combined with qRT-PCR experiments to prove the potential functions in the biological processes of plant growth and responding to abiotic stresses, specifically in the fiber development. These results not only provide comprehensive and valuable information for cotton EPF/EPFL gene family, but also lay solid foundation for screening candidate EPF/EPFL genes in further cotton breeding.

Construction and Bioinformatics Analysis of ceRNA Regulatory Networks in Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive form of pulmonary fibrosis of unknown etiology. Despite ongoing research, there is currently no cure for this disease. Recent studies have highlighted the significance of competitive endogenous RNA (ceRNA) regulatory networks in IPF development. Therefore, this study investigated the ceRNA network associated with IPF pathogenesis. We obtained gene expression datasets (GSE32538, GSE32537, GSE47460, and GSE24206) from the Gene Expression Omnibus (GEO) database and analyzed them using bioinformatics tools to identify differentially expressed messenger RNAs (DEmRNAs), microRNAs (DEmiRNAs), and long non-coding RNAs (DElncRNA). For DEmRNAs, we conducted an enrichment analysis, constructed protein-protein interaction networks, and identified hub genes. Additionally, we predicted the target genes of differentially expressed mRNAs and their interacting long non-coding RNAs using various databases. Subsequently, we screened RNA molecules with ceRNA regulatory relations in the lncACTdb database based on the screening results. Furthermore, we performed disease and functional enrichment analyses and pathway prediction for miRNAs in the ceRNA network. We also validated the expression levels of candidate DEmRNAs through quantitative real-time reverse transcriptase polymerase chain reaction and analyzed the correlation between the expression of these candidate DEmRNAs and the percent predicted pre-bronchodilator forced vital capacity [%predicted FVC (pre-bd)]. We found that three ceRNA regulatory axes, specifically KCNQ1OT1/XIST/NEAT1-miR-20a-5p-ITGB8, XIST-miR-146b-5p/miR-31-5p- MMP16, and NEAT1-miR-31-5p-MMP16, have the potential to significantly affect IPF progression. Further examination of the underlying regulatory mechanisms within this network enhances our understanding of IPF pathogenesis and may aid in the identification of diagnostic biomarkers and therapeutic targets.

Genome-wide enhancer RNA profiling adds molecular links between genetic variation and human cancers

BACKGROUND

Dysregulation of enhancer transcription occurs in multiple cancers. Enhancer RNAs (eRNAs) are transcribed products from enhancers that play critical roles in transcriptional control. Characterizing the genetic basis of eRNA expression may elucidate the molecular mechanisms underlying cancers.

METHODS

Initially, a comprehensive analysis of eRNA quantitative trait loci (eRNAQTLs) was performed in The Cancer Genome Atlas (TCGA), and functional features were characterized using multi-omics data. To establish the first eRNAQTL profiles for colorectal cancer (CRC) in China, epigenomic data were used to define active enhancers, which were subsequently integrated with transcription and genotyping data from 154 paired CRC samples. Finally, large-scale case-control studies (34,585 cases and 69,544 controls) were conducted along with multipronged experiments to investigate the potential mechanisms by which candidate eRNAQTLs affect CRC risk.

RESULTS

A total of 300,112 eRNAQTLs were identified across 30 different cancer types, which exert their influence on eRNA transcription by modulating chromatin status, binding affinity to transcription factors and RNA-binding proteins. These eRNAQTLs were found to be significantly enriched in cancer risk loci, explaining a substantial proportion of cancer heritability. Additionally, tumor-specific eRNAQTLs exhibited high responsiveness to the development of cancer. Moreover, the target genes of these eRNAs were associated with dysregulated signaling pathways and immune cell infiltration in cancer, highlighting their potential as therapeutic targets. Furthermore, multiple ethnic population studies have confirmed that an eRNAQTL rs3094296-T variant decreases the risk of CRC in populations from China (OR = 0.91, 95%CI 0.88-0.95, P = 2.92 × 10-7) and Europe (OR = 0.92, 95%CI 0.88-0.95, P = 4.61 × 10-6). Mechanistically, rs3094296 had an allele-specific effect on the transcription of the eRNA ENSR00000155786, which functioned as a transcriptional activator promoting the expression of its target gene SENP7. These two genes synergistically suppressed tumor cell proliferation. Our curated list of variants, genes, and drugs has been made available in CancereRNAQTL ( http://canernaqtl.whu.edu.cn/#/ ) to serve as an informative resource for advancing this field.

CONCLUSION

Our findings underscore the significance of eRNAQTLs in transcriptional regulation and disease heritability, pinpointing the potential of eRNA-based therapeutic strategies in cancers.

The identification of hub genes associated with pure ground glass nodules using weighted gene co-expression network analysis

BACKGROUND

Whether there are invasive components in pure ground glass nodules(pGGNs) in the lungs is still a huge challenge to forecast. The objective of our study is to investigate and identify the potential biomarker genes for pure ground glass nodule(pGGN) based on the method of bioinformatics analysis.

METHODS

To investigate differentially expressed genes (DEGs), firstly the data obtained from the gene expression omnibus (GEO) database was used.Next Weighted gene co-expression network analysis (WGCNA) investigate the co-expression network of DEGs. The black key module was chosen as the key one in correlation with pGGN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were done. Then STRING was uesd to create a protein-protein interaction (PPI) network, and the chosen module genes were analyzed by Cytoscape software.In addition the polymerase chain reaction (PCR) was used to evaluate the value of these hub genes in pGGN patients' tumor tissues compared to controls.

RESULTS

A total of 4475 DEGs were screened out from GSE193725, then 225 DEGs were identified in black key module, which were found to be enriched for various functions and pathways, such as extracellular exosome, vesicle, ribosome and so on. Among these DEGs, 6 overlapped hub genes with high degrees of stress method were selected. These hub genes include RPL4, RPL8, RPLP0, RPS16, RPS2 and CCT3.At last relative expression levels of CCT3 and RPL8 mRNA were both regulated in pGGN patients' tumor tissues compared to controls.

CONCLUSIONS

To summarize, the determined DEGs, pathways, modules, and overlapped hub genes can throw light on the potential molecular mechanisms of pGGN.

A novel single-cell model reveals ferroptosis-associated biomarkers for individualized therapy and prognostic prediction in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a prevalent malignancy with a pressing need for improved therapeutic response and prognosis prediction. This study delves into a novel predictive model related to ferroptosis, a regulated cell death mechanism disrupting metabolic processes.

RESULTS

Single-cell sequencing data analysis identified subpopulations of HCC cells exhibiting activated ferroptosis and distinct gene expression patterns compared to normal tissues. Utilizing the LASSO-Cox algorithm, we constructed a model with 10 single-cell biomarkers associated with ferroptosis, namely STMN1, S100A10, FABP5, CAPG, RGCC, ENO1, ANXA5, UTRN, CXCR3, and ITM2A. Comprehensive analyses using these biomarkers revealed variations in immune infiltration, tumor mutation burden, drug sensitivity, and biological functional profiles between risk groups. Specific associations were established between particular immune cell subtypes and certain gene expression patterns. Treatment response analyses indicated potential benefits from anti-tumor immune therapy for the low-risk group and chemotherapy advantages for the high-risk group.

CONCLUSIONS

The integration of this single-cell level model with clinicopathological features enabled accurate overall survival prediction and effective risk stratification in HCC patients. Our findings illuminate the potential of ferroptosis-related genes in tailoring therapy and prognosis prediction for HCC, offering novel insights into the intricate interplay among ferroptosis, immune response, and HCC progression.

Identification of subclusters and prognostic genes based on GLS-associated molecular signature in ulcerative colitis

Ulcerative colitis (UC) is a chronic and recurrent inflammatory disease that affects the colon and rectum. The response to treatment varies among individuals with UC. Therefore, the aim of this study was to identify and explore potential biomarkers for different subtypes of UC and examine their association with immune cell infiltration. We obtained UC RNA sequencing data from the GEO database, which included the training set GSE92415 and the validation set GSE87473 and GSE72514. UC patients were classified based on GLS and its associated genes using consensus clustering analysis. We identified differentially expressed genes (DEGs) in different UC subtypes through a differential expression analysis of the training cohort. Machine learning algorithms, including Weighted Gene Co-Expression Network Analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine Recursive Feature Elimination (SVM-RFE), were utilized to identify marker genes for UC. The CIBERSORT algorithm was used to determine the abundance of various immune cells in UC and their correlation with UC signature genes. Finally, we validated the expression of GLS through in vivo and ex vivo experiments. The expression of GLS was found to be elevated in patients with UC compared to normal patients. GLS and its related genes were able to classify UC patients into two subtypes, C1 and C2. The C1 subtype, as compared to the C2 subtype, showed a higher Mayo score and poorer treatment response. A total of 18 DEGs were identified in both subtypes, including 7 up-regulated and 11 down-regulated genes. Four UC signature genes (CWH43, HEPACAM2, IL24, and PCK1) were identified and their diagnostic value was validated in a separate cohort (AUC > 0.85). Furthermore, we found that UC signature biomarkers were linked to the immune cell infiltration. CWH43, HEPACAM2, IL24, and PCK1 may serve as potential biomarkers for diagnosing different subtypes of UC, which could contribute to the development of targeted molecular therapy and immunotherapy for UC.

Reproductive chemical database: a curated database of chemicals that modulate protein targets regulating important reproductive biological processes

Recent studies have shifted the spotlight from adult disease to gametogenesis and embryo developmental events, and these are greatly affected by various environmental chemicals, such as drugs, metabolites, pollutants, and others. Growing research has highlighted the critical importance of identifying and understanding the roles of chemicals in reproductive biology. However, the functions and mechanisms of chemicals in reproductive processes remain incomplete. We developed a comprehensive database called the Reproductive Chemical Database (RCDB) ( https://yu.life.sjtu.edu.cn/ChenLab/RCDB ) to facilitate research on chemicals in reproductive biology. This resource is founded on rigorous manual literature extraction and precise protein target prediction methodologies. This database focuses on the delineation of chemicals associated with phenotypes, diseases, or endpoints intricately associated with four important reproductive processes: female and male gamete generation, fertilization, and embryo development in human and mouse. The RCDB encompasses 93 sub-GO processes, and it revealed 1447 intricate chemical-biological process interactions. To date, the RCDB has meticulously cataloged and annotated 830 distinct chemicals, while also predicting 614 target proteins from a selection of 3800 potential candidates. Additionally, the RCDB offers an online predictive tool that empowers researchers to ascertain whether specific chemicals play discernible functional roles in these reproductive processes. The RCDB is an exhaustive, cross-platform, manually curated database, which provides a user-friendly interface to search, browse, and use reproductive processes modulators and their comprehensive related information. The RCDB will help researchers to understand the whole reproductive process and related diseases and it has the potential to promote reproduction research in the pharmacological and pathophysiological areas.

Deficiency of SDHC promotes metastasis by reprogramming fatty acid metabolism in colorectal cancer

BACKGROUND

Several studies have demonstrated a strong correlation between impaired Succinate dehydrogenase (SDH) function and the advancement of tumors. As a subunit of SDH, succinate dehydrogenase complex subunit C (SDHC) has been revealed to play tumor suppressive roles in several cancers, while its specific role in colorectal cancer (CRC) still needs further investigation.

METHODS

Online database were utilized to investigate the expression of SDHC in colorectal cancer and to assess its correlation with patient prognosis. Cell metastasis was assessed using transwell and wound healing assays, while tumor metastasis was studied in a nude mice model in vivo. Drug screening and RNA sequencing were carried out to reveal the tumor suppressor mechanism of SDHC. Triglycerides, neutral lipids and fatty acid oxidation were measured using the Triglyceride Assay Kit, BODIPY 493/503 and Colorimetric Fatty Acid Oxidation Rate Assay Kit, respectively. The expression levels of enzymes involved in fatty acid metabolism and the PI3K/AKT signaling pathway were determined by quantitative real-time PCR and western blot.

RESULTS

Downregulation of SDHC was found to be closely associated with a poor prognosis in CRC. SDHC knockdown promoted CRC metastasis both in vitro and in vivo. Through drug screening and Gene set enrichment analysis, it was discovered that SDHC downregulation was positively associated with the fatty acid metabolism pathways significantly. The effects of SDHC silencing on metastasis were reversed when fatty acid synthesis was blocked. Subsequent experiments revealed that SDHC silencing activated the PI3K/AKT signaling axis, leading to lipid accumulation by upregulating the expression of aldehyde dehydrogenase 3 family member A2 (ALDH3A2) and reduction of fatty acid oxidation rate by suppressing the expression of acyl-coenzyme A oxidase 1 (ACOX1) and carnitine palmitoyltransferase 1A (CPT1A).

CONCLUSIONS

SDHC deficiency could potentially enhance CRC metastasis by modulating the PI3K/AKT pathways and reprogramming lipid metabolism.

Exosome-Mediated Communication in Thyroid Cancer: Implications for Prognosis and Therapeutic Targets

Thyroid cancer (THCA) is one of the most common malignancies of the endocrine system. Exosomes have significant value in performing molecular treatments, evaluating the diagnosis and determining tumor prognosis. Thus, the identification of exosome-related genes could be valuable for the diagnosis and potential treatment of THCA. In this study, we examined a set of exosome-related differentially expressed genes (DEGs) (BIRC5, POSTN, TGFBR1, DUSP1, BID, and FGFR2) by taking the intersection between the DEGs of the TCGA-THCA and GeneCards datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the exosome-related DEGs indicated that these genes were involved in certain biological functions and pathways. Protein‒protein interaction (PPI), mRNA‒miRNA, and mRNA-TF interaction networks were constructed using the 6 exosome-related DEGs as hub genes. Furthermore, we analyzed the correlation between the 6 exosome-related DEGs and immune infiltration. The Genomics of Drug Sensitivity in Cancer (GDSC), the Cancer Cell Line Encyclopedia (CCLE), and the CellMiner database were used to elucidate the relationship between the exosome-related DEGs and drug sensitivity. In addition, we verified that both POSTN and BID were upregulated in papillary thyroid cancer (PTC) patients and that their expression was correlated with cancer progression. The POSTN and BID protein expression levels were further examined in THCA cell lines. These findings provide insights into exosome-related clinical trials and drug development.

Transcriptional Comparison Reveals Differential Resistance Mechanisms between CMV-Resistant PBC688 and CMV-Susceptible G29

The Cucumber mosaic virus (CMV) presents a significant threat to pepper cultivation worldwide, leading to substantial yield losses. We conducted a transcriptional comparative study between CMV-resistant (PBC688) and -susceptible (G29) pepper accessions to understand the mechanisms of CMV resistance. PBC688 effectively suppressed CMV proliferation and spread, while G29 exhibited higher viral accumulation. A transcriptome analysis revealed substantial differences in gene expressions between the two genotypes, particularly in pathways related to plant-pathogen interactions, MAP kinase, ribosomes, and photosynthesis. In G29, the resistance to CMV involved key genes associated with calcium-binding proteins, pathogenesis-related proteins, and disease resistance. However, in PBC688, the crucial genes contributing to CMV resistance were ribosomal and chlorophyll a-b binding proteins. Hormone signal transduction pathways, such as ethylene (ET) and abscisic acid (ABA), displayed distinct expression patterns, suggesting that CMV resistance in peppers is associated with ET and ABA. These findings deepen our understanding of CMV resistance in peppers, facilitating future research and variety improvement.

Gene signatures of endoplasmic reticulum stress and mitophagy for prognostic risk prediction in lung adenocarcinoma

Genes associated with endoplasmic reticulum stress (ERS) and mitophagy can be conducive to predicting solid tumour prognosis. The authors aimed to develop a prognosis prediction model for these genes in lung adenocarcinoma (LUAD). Relevant gene expression and clinical information were collected from public databases including Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). A total of 265 differentially expressed genes was finally selected (71 up-regulated and 194 downregulated) in the LUAD dataset. Among these, 15 candidate ERS and mitophagy genes (ATG12, CSNK2A1, MAP1LC3A, MAP1LC3B, MFN2, PGAM5, PINK1, RPS27A, SQSTM1, SRC, UBA52, UBB, UBC, ULK1, and VDAC1) might be critical to LUAD based on the expression analysis after crossing with the ERS and mitochondrial autophagy genes. The prediction model demonstrated the ability to effectively predict the 5-, 3-, and 1-year prognoses of LUAD patients in both GEO and TCGA databases. Moreover, high VDAC1 expression was associated with poor overall survival in LUAD (p < 0.001), suggesting it might be a critical gene for LUAD prognosis prediction. Overall, the prognosis model based on ERS and mitophagy genes in LUAD can be useful for evaluating the prognosis of patients with LUAD, and VDAC1 may serve as a promising biomarker for LUAD prognosis.

EGFR overexpression and macrophage infiltration correlate with poorer prognosis in HPV-negative oropharyngeal cancer via STAT6 signaling

BACKGROUND

The prevalence of HPV-negative oropharyngeal cancer (OPC) is higher in Asian countries. Patients with HPV-negative OPC suffer poor outcomes. Multi-omics analysis could provide researchers and clinicians with more treatment targets for this high-risk group. We aimed to explore the prognostic significance of EGFR overexpression and macrophage infiltration in OPC, especially HPV-negative OPC in this study.

METHODS

EGFR alternation was evaluated with TCGA, PanCancer Atlas through cBioProtal. EGFR mRNA expression in HPV-negative head and neck squamous cell carcinoma was analyzed using the Tumor Immune Estimation Resource (TIMER 2.0). We also examined EGFR/STAT6/MRC1 expression in paraffin-embedded tissues from a p16-negative OPC cohort. The correlation between EGFR expression and macrophage activation was explored using Person's correlation coefficient. The impact of biomarkers or macrophage infiltration on 5-year overall survival and recurrence-free survival were analyzed using Kaplan-Meier survival curves.

RESULTS

EGFR alteration rate was 15%, 13%, and 0% for HPV-negative HNSCC (excluding OPC), HPV-negative OPC, and HPV-positive OPC. High EGFR expression was associated with increased tumor infiltration of immune cells, such as macrophages. We observed positive correlations between EGFR, STAT6, and MRC1 expression in p16-negative OPC. Higher MRC1 expression was associated with poorer survival rates.

CONCLUSIONS

There is strong correlation between EGFR overexpression and M2 polarization in patients with p16-negative OPC. Immunotherapy with or without EGFR inhibitor could be considered in these high-risk patients.

Yigansan ameliorates maternal immune activation-induced autism-like behaviours by regulating the IL-17A/TRAF6/MMP9 pathway: Network analysis and experimental validation

BACKGROUND

Maternal immune activation (MIA) is a significant factor inducing to autism spectrum disorder (ASD) in offspring. The fundamental principle underlying MIA is that inflammation during pregnancy impedes fetal brain development and triggers behavioural alterations in offspring. The intricate pathogenesis of ASD renders drug treatment effects unsatisfactory. Traditional Chinese medicine has strong potential due to its multiple therapeutic targets. Yigansan, composed of seven herbs, is one of the few that has been proven to be effective in treating neuro-psychiatric disorders among numerous traditional Chinese medicine compounds, but its therapeutic effect on ASD remains unknown.

HYPOTHESIS

Yigansan improves MIA-induced ASD-like behaviours in offspring by regulating the IL-17 signalling pathway.

METHODS

Pregnant C57BL/6J mice were intraperitoneally injected with poly(I:C) to construct MIA models and offspring ASD models. Network analysis identified that the IL-17A/TRAF6/MMP9 pathway is a crucial pathway, and molecular docking confirmed the binding affinity between the monomer of Yigansan and target proteins. qRT-PCR and Western blot were used to detect the expression levels of inflammatory factors and pathway proteins, immunofluorescence was used to detect the distribution of IL-17A, and behavioural tests were used to evaluate the ASD-like behaviours of offspring.

RESULTS

We demonstrated that Yigansan can effectively alleviate MIA-induced neuroinflammation of adult offspring by regulating the IL-17A/TRAF6/MMP9 pathway, and the expression of IL-17A was reduced in the prefrontal cortex. Importantly, ASD-like behaviours have been significantly improved. Moreover, we identified that quercetin is the effective monomer for Yigansan to exert therapeutic effects.

CONCLUSION

Overall, this study was firstly to corroborate the positive therapeutic effect of Yigansan in the treatment of ASD. We elucidated the relevant molecular mechanism and regulatory pathway involved, determined the optimal therapeutic dose and effective monomer, providing new solutions for the challenges of drug therapy for ASD.

Next-generation neonicotinoid: The impact of cycloxaprid on the crustacean decapod Penaeus vannamei

Cycloxaprid, a new neonicotinoid pesticide, poses ecological risks, particularly in aquatic environments, due to its unique action and environmental dispersal. This study investigated the ecotoxicological effects of various concentrations of cycloxaprid on Penaeus vannamei over 28 days. High cycloxaprid levels significantly altered shrimp physiology, as shown by changes in the hepatosomatic index and fattening. Indicators of oxidative stress, such as increased serum hemocyanin, respiratory burst, and nitric oxide, as well as decreased phenol oxidase activity, were observed. Additionally, elevated activities of lactate dehydrogenase, succinate dehydrogenase, and isocitrate dehydrogenase indicated disrupted energy metabolism in the hepatopancreas. Notably, analyses of the nervous system revealed marked disturbances in neural signaling, as evidenced by elevated acetylcholine, octopamine, and acetylcholinesterase levels. Transcriptomic analysis highlighted significant effects on gene expression and metabolic processes in the hepatopancreas and nervous system. This study demonstrated that cycloxaprid disrupts neural signaling and oxidative balance in P. vannamei, potentially affecting its growth, and provides key insights into its biochemical and transcriptomic toxicity in aquatic systems.

Anoikis and SPP1 in idiopathic pulmonary fibrosis: integrating bioinformatics, cell, and animal studies to explore prognostic biomarkers and PI3K/AKT signaling regulation

OBJECTIVE

This study aims to explore the relevance of anoikis in idiopathic pulmonary fibrosis (IPF) and identify associated biomarkers and signaling pathways.

METHOD

Unsupervised consensus cluster analysis was employed to categorize IPF patients into subtypes. We utilized Weighted Gene Co-Expression Network Analysis (WGCNA) and Protein-Protein Interaction network construction to identify anoikis-related modules and key genes. A prognostic signature was developed using Lasso and multivariate Cox regression analysis. Single-cell sequencing assessed hub gene expression in various cell types, and both cell and animal experiments confirmed IPF-related pathways.

RESULTS

We identified two distinct anoikis-associated subtypes with differing prognoses. WGCNA revealed essential hub genes, with SPP1 being prominent in the anoikis-related signature. The anoikis-related signature is effective in determining the prognosis of patients with IPF. Single-cell sequencing highlighted significant differences in SPP1 expression, notably elevated in fibroblasts derived from IPF patients. In vivo and in vitro experiments demonstrated that SPP1 enhances fibrosis in mouse lung fibroblasts by regulating p27 through the PI3K/Akt pathway.

CONCLUSION

Our research demonstrates a robust prognostic signature associated with anoikis and highlights SPP1 as a pivotal regulator of the PI3K/AKT signaling pathway in pulmonary fibrosis.

Bioinformatic analysis of the role of immune checkpoint genes and immune infiltration in the pathogenesis and development of premature ovarian insufficiency

PURPOSE

With advances in immunology, increasing evidence suggests that immunity is involved in premature ovarian insufficiency (POI) pathogenesis. This study investigated the roles of immune checkpoint genes and immune cell infiltration in POI pathogenesis and development.

METHODS

The GSE39501 dataset and immune checkpoint genes were obtained from the Gene Expression Omnibus database and related literature. The two datasets were intersected to obtain immune checkpoint-related differentially expressed genes (ICRDEGs), which were analyzed using Gene Ontology and Kyoto Encyclopedia of Gene and Genomes enrichment analysis, weighted correlation network analysis, protein-protein interaction and related microRNAs, transcription factors, and RNA binding proteins. The immune cell infiltration of ICRDEGs was explored, and receiver operating characteristic curves were used to validate the diagnostic value of ICRDEGs in POI.

RESULTS

We performed ICRDEG functional enrichment analysis and found that these genes were closely related to immune processes, such as T cell activation. Specifically, they are enriched in various biological processes and pathways, such as cell adhesion molecule and T cell receptor signaling pathways. Weighted correlation network analysis identified seven hub genes: Cd200, Cd274, Cd28, neurociliary protein-1, Cd276, Cd40lg, and Cd47. Furthermore, we identified 112 microRNAs, 17 RNA-binding proteins, and 101 transcription factors. Finally, immune infiltration analysis showed a clear positive correlation between hub genes and multiple immune cell types.

CONCLUSION

Bioinformatic analysis identified seven potential ICRDEGs associated with POI, among which the immune checkpoint molecules CD200 and neurociliary protein-1 may be involved in the pathogenesis of POI.

Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology

Protein-protein interactions (PPIs) involve the physical or functional contact between two or more proteins. Generally, proteins that can interact with each other always have special relationships. Some previous studies have reported that gene ontology (GO) terms are related to the determination of PPIs, suggesting the special patterns on the GO terms of proteins in PPIs. In this study, we explored the special GO term patterns on human PPIs, trying to uncover the underlying functional mechanism of PPIs. The experimental validated human PPIs were retrieved from STRING database, which were termed as positive samples. Additionally, we randomly paired proteins occurring in positive samples, yielding lots of negative samples. A simple calculation was conducted to count the number of positive samples for each GO term pair, where proteins in samples were annotated by GO terms in the pair individually. The similar number for negative samples was also counted and further adjusted due to the great gap between the numbers of positive and negative samples. The difference of the above two numbers and the relative ratio compared with the number on positive samples were calculated. This ratio provided a precise evaluation of the occurrence of GO term pairs for positive samples and negative samples, indicating the latent GO term patterns for PPIs. Our analysis unveiled several nuclear biological processes, including gene transcription, cell proliferation, and nutrient metabolism, as key biological functions. Interactions between major proliferative or metabolic GO terms consistently correspond with significantly reported PPIs in recent literature.

An ontology of mechanisms of action in behaviour change interventions

Background

Behaviour change interventions influence behaviour through causal processes called "mechanisms of action" (MoAs). Reports of such interventions and their evaluations often use inconsistent or ambiguous terminology, creating problems for searching, evidence synthesis and theory development. This inconsistency includes the reporting of MoAs. An ontology can help address these challenges by serving as a classification system that labels and defines MoAs and their relationships. The aim of this study was to develop an ontology of MoAs of behaviour change interventions.

Methods

To develop the MoA Ontology, we (1) defined the ontology's scope; (2) identified, labelled and defined the ontology's entities; (3) refined the ontology by annotating (i.e., coding) MoAs in intervention reports; (4) refined the ontology via stakeholder review of the ontology's comprehensiveness and clarity; (5) tested whether researchers could reliably apply the ontology to annotate MoAs in intervention evaluation reports; (6) refined the relationships between entities; (7) reviewed the alignment of the MoA Ontology with other relevant ontologies, (8) reviewed the ontology's alignment with the Theories and Techniques Tool; and (9) published a machine-readable version of the ontology.

Results

An MoA was defined as "a process that is causally active in the relationship between a behaviour change intervention scenario and its outcome behaviour". We created an initial MoA Ontology with 261 entities through Steps 2-5. Inter-rater reliability for annotating study reports using these entities was α=0.68 ("acceptable") for researchers familiar with the ontology and α=0.47 for researchers unfamiliar with it. As a result of additional revisions (Steps 6-8), 23 further entities were added to the ontology resulting in 284 entities organised in seven hierarchical levels.

Conclusions

The MoA Ontology extensively captures MoAs of behaviour change interventions. The ontology can serve as a controlled vocabulary for MoAs to consistently describe and synthesise evidence about MoAs across diverse sources.

Genome-Wide Identification and Characterization of miRNAs and Natural Antisense Transcripts Show the Complexity of Gene Regulatory Networks for Secondary Metabolism in Aristolochia contorta

Aristolochia contorta Bunge is an academically and medicinally important plant species. It belongs to the magnoliids, with an uncertain phylogenetic position, and is one of the few plant species lacking a whole-genome duplication (WGD) event after the angiosperm-wide WGD. A. contorta has been an important traditional Chinese medicine material. Since it contains aristolochic acids (AAs), chemical compounds with nephrotoxity and carcinogenicity, the utilization of this plant has attracted widespread attention. Great efforts are being made to increase its bioactive compounds and reduce or completely remove toxic compounds. MicroRNAs (miRNAs) and natural antisense transcripts (NATs) are two classes of regulators potentially involved in metabolism regulation. Here, we report the identification and characterization of 223 miRNAs and 363 miRNA targets. The identified miRNAs include 51 known miRNAs belonging to 20 families and 172 novel miRNAs belonging to 107 families. A negative correlation between the expression of miRNAs and their targets was observed. In addition, we identified 441 A. contorta NATs and 560 NAT-sense transcript (ST) pairs, of which 12 NATs were targets of 13 miRNAs, forming 18 miRNA-NAT-ST modules. Various miRNAs and NATs potentially regulated secondary metabolism through the modes of miRNA-target gene-enzyme genes, NAT-STs, and NAT-miRNA-target gene-enzyme genes, suggesting the complexity of gene regulatory networks in A. contorta. The results lay a solid foundation for further manipulating the production of its bioactive and toxic compounds.

Multi-Omics Analysis Reveals the Toxicity of Polyvinyl Chloride Microplastics toward BEAS-2B Cells

Polyvinyl chloride microplastics (PVC-MPs) are microplastic pollutants widely present in the environment, but their potential risks to human lung health and underlying toxicity mechanisms remain unknown. In this study, we systematically analyzed the effects of PVC-MPs on the transcriptome and metabolome of BEAS-2B cells using high-throughput RNA sequencing and untargeted metabolomics technologies. The results showed that exposure to PVC-MPs significantly reduced the viability of BEAS-2B cells, leading to the differential expression of 530 genes and 3768 metabolites. Further bioinformatics analyses showed that PVC-MP exposure influenced the expression of genes associated with fluid shear stress, the MAPK and TGF-β signaling pathways, and the levels of metabolites associated with amino acid metabolism. In particular, integrated pathway analysis showed that lipid metabolic pathways (including glycerophospholipid metabolism, glycerolipid metabolism, and sphingolipid metabolism) were significantly perturbed in BEAS-2B cells following PVC-MPs exposure. This study provides new insights and targets for a deeper understanding of the toxicity mechanism of PVC-MPs and for the prevention and treatment of PVC-MP-associated lung diseases.

Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma

Background

Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC).

Methods

The cervical squamous cell carcinoma dataset (GSE63514) was downloaded from the Gene Expression Omnibus (GEO). Two psoriasis-related datasets (GSE13355 and GSE14905) were merged into one comprehensive dataset after removing batch effects. Differentially expressed genes were identified using Limma and co-expression network analysis (WGCNA), and machine learning random forest algorithm (RF) was used to screen the hub genes. We analyzed relevant gene enrichment pathways using GO and KEGG, and immune cell infiltration in psoriasis and CESC samples using CIBERSORT. The miRNA-mRNA and TFs-mRNA regulatory networks were then constructed using Cytoscape, and the biomarkers for psoriasis and CESC were determined. Potential drug targets were obtained from the cMAP database, and biomarker expression levels in hela and psoriatic cell models were quantified by RT-qPCR.

Results

In this study, we identified 27 key genes associated with psoriasis and cervical squamous cell carcinoma. NCAPH, UHRF1, CDCA2, CENPN and MELK were identified as hub genes using the Random Forest machine learning algorithm. Chromosome mitotic region segregation, nucleotide binding and DNA methylation are the major enrichment pathways for common DEGs in the mitotic cell cycle. Then we analyzed immune cell infiltration in psoriasis and cervical squamous cell carcinoma samples using CIBERSORT. Meanwhile, we used the cMAP database to identify ten small molecule compounds that interact with the central gene as drug candidates for treatment. By analyzing miRNA-mRNA and TFs-mRNA regulatory networks, we identified three miRNAs and nine transcription factors closely associated with five key genes and validated their expression in external validation datasets and clinical samples. Finally, we examined the diagnostic effects with ROC curves, and performed experimental validation in hela and psoriatic cell models.

Conclusions

We identified five biomarkers, NCAPH, UHRF1, CDCA2, CENPN, and MELK, which may play important roles in the common pathogenesis of psoriasis and cervical squamous cell carcinoma, furthermore predict potential therapeutic agents. These findings open up new perspectives for the diagnosis and treatment of psoriasis and squamous cell carcinoma of the cervix.

Whole-genome selection signature differences between Chaohu and Ji'an red ducks

Assessing the genetic structure of local varieties and understanding their genetic data are crucial for effective management and preservation. However, the genetic differences among local breeds require further explanation. To enhance our understanding of their population structure and genetic diversity, we conducted a genome-wide comparative study of Chaohu and Ji'an Red ducks using genome sequence and restriction site-associated DNA sequencing technology. Our analysis revealed a distinct genetic distinction between the two breeds, leading to divided groups. The phylogenetic tree for Chaohu duck displayed two branches, potentially indicating minimal impact from artificial selection. Additionally, our ROH (runs of homozygosity) analysis revealed that Chaohu ducks had a lower average inbreeding coefficient than Ji'an Red ducks. We identified several genomic regions with high genetic similarity in these indigenous duck breeds. By conducting a selective sweep analysis, we identified 574 candidate genes associated with muscle growth (BMP2, ITGA8, MYLK, and PTCH1), fat deposits (ELOVL1 and HACD2), and pigmentation (ASIP and LOC101797494). These results offer valuable insights for the further enhancement and conservation of Chinese indigenous duck breeds.

Highly variable biological effects of statins on cancer, non-cancer, and stem cells in vitro

Statins, the drugs used for the treatment of hypercholesterolemia, have come into the spotlight not only as chemoadjuvants, but also as potential stem cell modulators in the context of regenerative therapy. In our study, we compared the in vitro effects of all clinically used statins on the viability of human pancreatic cancer (MiaPaCa-2) cells, non-cancerous human embryonic kidney (HEK 293) cells and adipose-derived mesenchymal stem cells (ADMSC). Additionally, the effect of statins on viability of MiaPaCa-2 and ADMSC cells spheroids was tested. Furthermore, we performed a microarray analysis on ADMSCs treated with individual statins (12 μM) and compared the importance of the effects of statins on gene expression between stem cells and pancreatic cancer cells. Concentrations of statins that significantly affected cancer cells viability (< 40 μM) did not affect stem cells viability after 24 h. Moreover, statins that didn´t affect viability of cancer cells grown in a monolayer, induce the disintegration of cancer cell spheroids. The effect of statins on gene expression was significantly less pronounced in stem cells compared to pancreatic cancer cells. In conclusion, the low efficacy of statins on non-tumor and stem cells at concentrations sufficient for cancer cells growth inhibition, support their applicability in chemoadjuvant tumor therapy.

BR regulates wheat root salt tolerance by maintaining ROS homeostasis

MAIN CONCLUSION

Trace amounts of epibrassinolide (EpiBL) could partially rescue wheat root length inhibition in salt-stressed situation by scavenging ROS, and ectopic expression of TaDWF4 or TaBAK1 enhances root salt tolerance in Arabidopsis by balancing ROS level. Salt stress often leads to ion toxicity and oxidative stress, causing cell structure damage and root development inhibition in plants. While prior research indicated the involvement of exogenous brassinosteroid (BR) in plant responses to salt stress, the precise cytological role and the function of BR in wheat root development under salt stress remain elusive. Our study demonstrates that 100 mM NaCl solution inhibits wheat root development, but 5 nM EpiBL partially rescues root length inhibition by decreasing H2O2 content, oxygen free radical (OFR) content, along with increasing the peroxidase (POD) and catalase (CAT) activities in salt-stressed roots. The qRT-PCR experiment also shows that expression of the ROS-scavenging genes (GPX2 and CAT2) increased in roots after applying BR, especially during salt stress situation. Transcriptional analysis reveals decreased expression of BR synthesis and root meristem development genes under salt stress in wheat roots. Differential expression gene (DEG) enrichment analysis highlights the significant impact of salt stress on various biological processes, particularly "hydrogen peroxide catabolic process" and "response to oxidative stress". Additionally, the BR biosynthesis pathway is enriched under salt stress conditions. Therefore, we investigated the involvement of wheat BR synthesis gene TaDWF4 and BR signaling gene TaBAK1 in salt stress responses in roots. Our results demonstrate that ectopic expression of TaDWF4 or TaBAK1 enhances salt tolerance in Arabidopsis by balancing ROS (Reactive oxygen species) levels in roots.

Exploring Alashan Ground Squirrel (Spermophilus alashanicus) Diversity: Metagenomic and Transcriptomic Datasets from the Helan Mountains

This study investigates the adaptive strategies of the Alashan Ground Squirrel (Spermophilus alashanicus) in response to habitat changes, as rodents are sensitive indicators of ecosystem changes. Despite its ecological importance, the genome and microbiome of this species have not been thoroughly studied. This research fills this gap by presenting the first comprehensive metagenomic and transcriptomic datasets of the species. Transcriptomic data was collected from five tissue types, including heart, liver, cecum, muscle, and blood, resulting in the assembly of 72,156 unigenes. Metagenomic sequencing identified predominant bacterial groups such as Firmicutes, Bacteroidetes, Verrucomicrobia, Urovircota, and Proteobacteria. Our workflow involved RNA and DNA extraction, library preparation, assembly, and annotation, yielding valuable insights into gene discovery, microbial composition, and further genome and microbial function studies. In conclusion, our findings have significant implications for understanding the adaptive mechanisms of this species in response to environmental changes.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

Identification Of Endothelial Cell Immune-related Gene Signature for Lung Adenocarcinoma by Integrated Analysis of Single-cell and Bulk RNA Sequencing Data

Background: The role of endothelial cells in tumor progression is considerable, yet the effect of endothelial cell immune-related genes (EIRGs) is still unclear. This research aimed to scrutinize the prognostic value of EIRGs in lung adenocarcinoma (LUAD) and provide further insights into the abovementioned uncertainties. Methods: After single-cell RNA sequencing (scRNA-seq) samples were obtained from the Gene Expression Omnibus (GEO) database, they were integrated with bulk RNA sequencing data from The Cancer Genome Atlas (TCGA). Prognostic markers were determined and a prognostic model was developed. From this model, a nomogram was constructed. We analyzed the biological mechanism of the EIRGs in LUAD, including functional enrichment, tumor mutational burden (TMB), tumor microenvironment (TME) analyses and drug sensitivity. We validated the signature by validating the external cohort GSE31210 and RT-qPCR. Results: After analyzing the model constructed from eight EIRGs, we observed that high-risk group (HG) LUAD patients (a risk score exceeding 4.65) exhibited unfavorable outcomes according to Kaplan‒Meier survival curves. This outcome was confirmed by GSE31210. The nomogram based on the model demonstrated significant predictive value. HG was influenced primarily by steroid hormone biosynthesis and ECM receptor interactions. The TMB in HGs was greater than that in the LG. Analysis of drug sensitivity revealed the direction for individualized treatment for both risk cohorts. Variations in the expression of EIRGs have been confirmed via RT-qPCR in several LUAD cell lines. Conclusions: The prognostic model and nomogram above are valuable for determining the survival rate and treatment options for LUAD patients.

White Isthmus Transcriptome Analysis Reveals the Mechanism of Translucent Eggshell Formation

The presence of translucent eggshells is a type of egg quality issue that impacts egg sales. While many researchers have studied them, the exact mechanisms behind their formation remain unclear. In this study, we conducted a transcriptomic differential expression analysis of the isthmus region of the oviduct in both normal egg- and translucent egg-laying hens. The analysis revealed that differentially expressed gene pathways were predominantly concentrated in the synthesis, modification, and transport of eggshell membrane proteins, particularly collagen proteins, which provide structural support. These findings suggest that variations in the physical structure of the eggshell membrane, resulting from changes in its chemical composition, are the fundamental cause of translucent eggshell formation. This research provides a theoretical reference for reducing the occurrence of translucent eggs.