Visual analysis of bone malignancies immunotherapy: A bibliometric analysis from 2010 to 2023.

BACKGROUND: Bone malignancies (BM), including osteosarcoma, Ewing's sarcoma, chondrosarcoma, and chordoma, are characterized by high rates of recurrence and mortality, despite the availability of diverse treatment approaches. Immunotherapy has gained increasing importance in cancer treatment. However, there is a lack of comprehensive studies that utilize bibliometric analysis to explore immunotherapy for BM. METHODS: A literature search of English studies on BM and immunotherapy from 2010 to 2023 was conducted in the Web of Science Core Collection database. Bibliometric analysis tools such as VOSviewer, CiteSpace, and R Studio were utilized to examine global trends and research hotspots in this field. RESULTS: A total of 719 eligible articles, including 528 original research articles and 191 reviews, were analyzed. The number of publications has shown an increasing trend over the past 14 years, particularly in the last 5 years. The majority of the published articles on this topic originated from China (284 articles), followed by the United States and Japan. The institution with the highest number of publications and citations was the University of Texas MD Anderson Cancer Center (30 articles; 1638 citations). Dean A. Lee (12 articles) and Richard Gorlick (576 citations) were the authors with the highest contribution in terms of article count and citation count, respectively. Among these journals, Frontiers in Oncology had the highest number of articles (39 articles), while the Journal of Clinical Oncology had the highest number of citations (1878 citations). Additionally, there has been a shift in the keywords from "antitumor activity" and "NK cells" to popular topics such as "PD-L1," "open label," and "single arm." CONCLUSION: A better understanding of the current status and prospects of immunotherapy for BM is crucial for the rationale selection of appropriate BM patients for immunotherapy. This study is expected to help clinical physicians and researchers gain comprehensive insights into the developmental trends of BM immunotherapy, providing practical guidance for the application of immunotherapy in BM patients.

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio.

Purpose: Lymphocyte to C-reactive protein ratio (LCR) is a recognized systemic inflammatory marker and novel prognostic indicator for several cancers. This study investigated the relationship between preoperative LCR and new-onset atrial fibrillation (NOAF) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). Patients and Methods: Patients with AMI (n=662) with no history of atrial fibrillation (AF) were enrolled and classified into NOAF and non-NOAF groups based on the occurrence of postoperative NOAF during hospitalization. Logistic regression models were used to analyze NOAF risk factors and to assess the association between preoperative LCR and NOAF incidence. We constructed a new nomogram from the selected NOAF risk factors, and tested its predictive performance, degree of calibration, and clinical utility using receiver operating characteristic and calibration curves, decision curve analysis, and clinical impact curves. Results: Overall, 84 (12.7%) patients developed NOAF during hospitalization. The LCR was significantly lower in the NOAF group. Preoperative LCR accurately predicted NOAF after AMI and was correlated with increased NOAF risk. Age, body mass index, diabetes, serum albumin levels, uric acid levels, left atrium (LA) diameter, left ventricular ejection fraction, left circumflex artery stenosis > 50%, and Killip class II status were independent predictors of NOAF after AMI. In addition, a new nomogram combined with LCR was constructed to stratify the risk of NOAF in patients with AMI. The performance of the new nomogram was satisfactory, as shown by the receiver operating characteristic curve, calibration curve, decision curve analysis and clinical impact curve. Conclusion: Preoperative LCR was an independent predictor of NOAF in patients with AMI after PCI. The novel nomogram combined with LCR could rapidly and individually identify and treat patients at a high risk of NOAF.

KYNU as a Biomarker of Tumor-Associated Macrophages and Correlates with Immunosuppressive Microenvironment and Poor Prognosis in Gastric Cancer.

Background: Kynureninase (KYNU) is a potential prognostic marker for various tumor types. However, no reports on the biological effects and prognostic value of KYNU in gastric cancer (GC) exist. Methods: GC-associated single-cell RNA sequencing and bulk RNA sequencing (bulk-seq) data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. The differential expression of KYNU between GC and normal gastric tissues was first analyzed based on the bulk-seq data, followed by an exploration of the relationship between KYNU and various clinicopathological features. The Kaplan-Meier survival and Cox regression analyses were performed to determine the prognostic value of KYNU. The relationship between KYNU expression and immune cell infiltration and immune checkpoints was also explored. The biological function of KYNU was further examined at the single-cell level, and in vitro experiments were performed to examine the effect of KYNU on GC cell proliferation and invasion. Results: KYNU expression was significantly elevated in GC samples. Clinical features and survival analysis indicated that high KYNU expression was associated with poor clinical phenotypes and prognosis, whereas Cox analysis showed that KYNU was an independent risk factor for patients with GC. Notably, high expression of KYNU induced a poor immune microenvironment and contributed to the upregulation of immune checkpoints. KYNU-overexpressing macrophages drove GC progression through unique ligand-receptor pairs and transcription factors and were associated with adverse clinical phenotypes in GC. KYNU was overexpressed in GC cells in vitro, and KYNU knockout significantly inhibited GC cell proliferation and invasion. Conclusion: High KYNU expression promotes an adverse immune microenvironment and low survival rates in GC. KYNU and KYNU-related macrophages may serve as novel molecular targets in the treatment of GC.

Integrated analysis of single-cell and bulk RNA-sequencing reveals the poor prognostic value of ABCA1 in gastric adenocarcinoma.

PURPOSE: ATP-binding cassette A1 (ABCA1) is a potential prognostic marker for various tumor types. However, the biological effects and prognostic value of ABCA1 in gastric adenocarcinoma (GAC) remain unknown. METHODS: GAC-associated single-cell RNA and bulk RNA-sequencing (bulk-seq) data were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively. The differential expression of ABCA1 between GAC and normal gastric tissues was analyzed based on the bulk-seq data. Additionally, the relationship between ABCA1 expression and various clinicopathological features was explored. Furthermore, Kaplan-Meier survival and Cox regression analyses were performed to establish the prognostic value of ABCA1. The relationships between ABCA1 expression and anti-tumor drug sensitivity and immune checkpoints were also explored. Finally, the biological functions of ABCA1 were evaluated at the single-cell level, and in vitro studies were performed to assess the effects of ABCA1 on GAC cell proliferation and invasion. RESULTS: ABCA1 expression is significantly elevated in GAC samples compared with that in normal gastric tissues. Clinical features and survival analysis revealed that high ABCA1 expression is associated with poor clinical phenotypes and prognosis, whereas Cox analysis identified ABCA1 as an independent risk factor for patients with GAC. Furthermore, high ABCA1 expression suppresses sensitivity to various chemotherapeutic drugs, including cisplatin and mitomycin, while upregulating immune checkpoints. ABCA1-overexpressing macrophages are associated with adverse clinical phenotypes in GAC and express unique ligand-receptor pairs that drive GAC progression. In vitro, ABCA1-knockdown GAC cells exhibit significantly inhibited proliferative and invasive properties. CONCLUSION: High ABCA1 expression promotes an adverse immune microenvironment and low survival rates in patients with GAC. Furthermore, ABCA1 and ABCA1-producing macrophages may serve as novel molecular targets in GAC treatment.

Integrated analysis of single-cell and bulk RNA-sequencing data reveals the prognostic value and molecular function of THSD7A in gastric cancer.

The biological role and prognostic value of thrombospondin domain-containing 7A (THSD7A) in gastric cancer remain unclear. Our purpose was to determine the molecular mechanisms underlying the functioning of THSD7A and its prognostic value in gastric cancer. Gastric cancer-associated single cell and bulk RNA sequencing data obtained from two databases, were analyzed. We used bulk RNA sequencing to examine the differential expression of THSD7A in gastric cancer and normal gastric tissues and explored the relationship between THSD7A expression and clinicopathological characteristics. Kaplan-Meier survival and Cox analyses revealed the prognostic value of THSD7A. Gene set enrichment and immune infiltration analyses were used to determine the cancer-promoting mechanisms of THSD7A and its effect on the immune microenvironment. We explored the relationship between THSD7A expression and sensitivity of anti-tumor drugs and immune checkpoint levels. Biological functions of THSD7A were validated at single-cell and in vitro levels. THSD7A expression was significantly increased in gastric cancer samples. High THSD7A expression was associated with poor clinical phenotypes and prognoses. Cox analysis showed that THSD7A was an independent risk factor for patients with gastric cancer. Enrichment analysis suggested that epithelial-mesenchymal transition and inflammatory responses may be potential pro-cancer mechanisms of THSD7A. Upregulation of THSD7A promoted infiltration by M2 macrophages and regulatory T cells. High THSD7A expression suppressed the sensitivity of patients with gastric cancer to drugs, such as 5-fluorouracil, bleomycin, and cisplatin, and upregulated immune checkpoints, such as HAVCR2, PDCD1LG2, TIGIT, and CTLA4. At the single cell level, THSD7A was an endothelial cell-associated gene and endothelial cells overexpressing THSD7A showed unique pro-oncogenic effects. In vitro experiments confirmed that THSD7A was overexpressed in gastric cancer samples and cells, and that knocking out THSD7A significantly inhibited gastric cancer cell proliferation and invasion. THSD7A overexpression may be a unique prognostic marker and therapeutic target in gastric cancer. Therefore, our study provides a new perspective on the precise treatment of gastric cancer.

ELOVL6 is associated with immunosuppression in lung adenocarcinoma through bioinformatics analysis.

The aim of this paper was to reveal the correlation between the expression of ELOVL fatty acid elongase 6 (ELOVL6) gene in lung adenocarcinoma (LUAD) and its clinical significance, immune cell infiltration level and prognosis. Expression profile data of ELOVL6 mRNA were collected from the cancer genome atlas database to analyze the differences in ELOVL6 mRNA expression in LUAD tissues and normal lung tissues, and to analyze the correlation between ELOVL6 and information on clinicopathological features. Based on TIMER database, TISDIB database and GEPIA2 database, the correlation between ELOVL6 expression and tumor immune cell infiltration in LUAD was analyzed. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses of ELOVL6-related co-expressed genes were performed to identify the involved signaling pathways and to construct their co-expressed gene protein interaction networks. Drugs affected by ELOVL6 expression were screened based on the Cell Miner database. These findings suggest that ELOVL6 plays an important role in the course of LUAD, and the expression level of this gene has a close relationship with clinicopathological characteristics and survival prognosis, and has the potential to become a prognostic marker and therapeutic target for LUAD.

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data.

BACKGROUND: The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs). METHODS: scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays. RESULTS: The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines. CONCLUSIONS: We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice.

Integrated single-cell RNA sequencing analysis reveals a mesenchymal stem cell-associated signature for estimating prognosis and drug sensitivity in gastric cancer.

BACKGROUND: Mesenchymal stem cells (MSCs) play an important role in regulating all stages of the immune response, angiogenesis, and transformation of matrix components in the tumor microenvironment. The aim of this study was to identify the prognostic value of MSC-related signatures in patients with gastric cancer (GC). METHODS: MSC marker genes were identified by analyzing single-cell RNA sequencing (scRNA-seq) data for GC from the Gene Expression Omnibus (GEO) database. Using bulk sequencing data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD), as a training cohort, and data from GEO, as a validation cohort, we developed a risk model consisting of MSC prognostic signature genes, and classified GC patients into high- and low-MSC risk subgroups. Multifactorial Cox regression was used to evaluate whether MSC prognostic signature was an independent prognostic factor. An MSC nomogram was constructed combining clinical information and risk grouping. Subsequently, we evaluated the effect of MSC prognostic signature on immune cell infiltration, antitumor drugs and immune checkpoints and verified the expression of MSC prognostic signature by in vitro cellular assays. RESULTS: In this study, 174 MSC marker genes were identified by analyzing scRNA-seq data. We identified seven genes (POSTN, PLOD2, ITGAV, MMP11, SDC2, MARCKS, ANXA5) to construct MSC prognostic signature. MSC prognostic signature was an independent risk factor in the TCGA and GEO cohorts. GC patients in the high-MSC risk group had worse prognoses. In addition, the MSC nomogram has a high clinical application value. Notably, the MSC signature can induce the development of a poor immune microenvironment. GC patients in the high MSC-risk group were more sensitive to anticancer drugs and tended to have higher levels of immune checkpoint markers. In qRT-PCR assays, the MSC signature was more highly expressed in GC cell lines. CONCLUSIONS: The MSC marker gene-based risk signature developed in this study can not only be used to predict the prognosis of GC patients, but also has the potential to reflect the efficacy of antitumor therapies.

Single-Cell RNA Sequencing Reveals the Role of Epithelial Cell Marker Genes in Predicting the Prognosis of Colorectal Cancer Patients.

Single-cell RNA sequencing (scRNA-seq) is increasingly used in studies on gastrointestinal cancers. This study investigated the prognostic value of epithelial cell-associated biomarkers in colorectal cancer (CRC) using scRNA-seq data. We downloaded and analysed scRNA-seq data from four CRC samples from the Gene Expression Omnibus (GEO), and we identified marker genes of malignant epithelial cells (MECs) using CRC transcriptome and clinical data downloaded from The Cancer Genome Atlas (TCGA) and GEO as training and validation cohorts, respectively. In the TCGA training cohort, weighted gene correlation network analysis, univariate Cox proportional hazard model (Cox) analysis, and least absolute shrinkage and selection operator regression analysis were performed on the marker genes of MEC subsets to identify a signature of nine prognostic MEC-related genes (MECRGs) and calculate a risk score based on the signature. CRC patients were divided into high- and low-risk groups according to the median risk score. We found that the MECRG risk score was significantly correlated with the clinical features and overall survival of CRC patients, and that CRC patients in the high-risk group showed a significantly shorter survival time. The univariate and multivariate Cox regression analyses showed that the MECRG risk score can serve as an independent prognostic factor for CRC patients. Gene set enrichment analysis revealed that the MECRG signature genes are involved in fatty acid metabolism, p53 signalling, and other pathways. To increase the clinical application value, we constructed a MECRG nomogram by combining the MECRG risk score with other independent prognostic factors. The validity of the nomogram is based on receiver operating characteristics and calibration curves. The MECRG signature and nomogram models were well validated in the GEO dataset. In conclusion, we established an epithelial cell marker gene-based risk assessment model based on scRNA-seq analysis of CRC samples for predicting the prognosis of CRC patients.

Maternal Zearalenone exposure impacted ovarian follicle formation and development of suckled offspring.

Zearalenone (ZEN) is a secondary metabolite, which is mainly produced by Fusarium fungi and exists in various feeds and agricultural products. Recently, an increasing amount of data has shown that ZEN, as an estrogen-like hormone, can have harmful effects on the female reproductive system, especially on oogenesis and folliculogenesis. Breast milk is considered to be the ideal form of nutrition for infants; however, there are some records of contaminants in food, such as mycotoxins, which may be transferred from maternal blood to milk. In this study, we investigated the toxic effects of breast milk on folliculogenesis in offspring following maternal ZEN exposure. Our results showed that maternal ZEN exposure significantly inhibited the process of primordial follicle (PF) assembly and reduced the number of PFs in suckled offspring's ovaries. In addition, RNA-seq analysis showed that RIG-I-like receptor (RLRs) signaling pathways were activated after exposed to ZEN, which increased the expression levels of DNA damage (γ-H2AX, RAD51, and PARP1) and apoptosis related protein (BAX/BCL2 and Caspase-3). Finally, ZEN exposure interfered with follicular development, as evidenced by the reduced percentages of oocyte maturation and embryonic development when the offspring grew to adolescence. It is worth noting that maternal ZEN exposure disrupted the tri-methylation levels of H3K4, H3K9, and H3K27 in the offspring's oocytes. Our results indicated that maternal ZEN exposure affected ovarian development in offspring through the breast milk, which may be detrimental to their reproductive capability in adult life.

ArrayOU: a web application for microarray data analysis and visualization.

A web-based microarray data analysis tool, ArrayOU (freely available at www.bioinformatics.plantbio.ohiou.edu.), has been developed at the Ohio University Genomics Facility for the research and education community to analyze Agilent microarray data. Agilent's microarray pipeline has gained in popularity as a result of its ease of use and low cost of customized arrays. The current version of the ArrayOU pipeline allows users to visualize, analyze, and annotate microarray data from commercially available and customized Agilent expression arrays and is extendable for further implementations.