A novel prognostic biomarker LCP2 correlates with metastatic melanoma-infiltrating CD8+ T cells

Discovering therapeutic possibilities for polycystic ovary syndrome by targeting XIST and its associated ceRNA network through the analysis of transcriptome data

Long non-coding RNA (lncRNA) regulates many physiological processes by acting as competitive endogenous RNA (ceRNA). The dysregulation of lncRNA X-inactive specific transcript (XIST) has been shown in various human disorders. However, its role in the pathogenesis of polycystic ovary syndrome (PCOS) is yet to be explored. This study aimed to explore the underlying mechanism of XIST in the pathogenesis of PCOS, specifically through dataset functional analysis. GEO PCOS datasets including RNA-seq, microarray, and miRNA-seq in granulosa cells (GCs) and blood, were examined and comprehensively analyzed. Enrichment analysis, ROC curve constructions, lncRNA-miRNA-mRNA interaction network analyses, and qRT-PCR validation were performed followed by a series of drug signature screenings. Our results revealed significant dysregulation in the expression of 1131 mRNAs, 30 miRNAs, and XIST in GCs of PCOS patients compared to healthy individuals. Of the120 XIST-correlated upregulated genes, 25 were enriched in inflammation-related pathways. Additionally, 5 miRNAs were identified as negative regulators of XIST-correlated genes. Accordingly, a ceRNA network containing XIST-miRNAs-mRNAs interactions was constructed. Furthermore, 6 genes, including AQP9, ETS2, PLAU, PLEK, SOCS3, and TNFRSF1B served as both GCs and blood-based biomarkers. By analyzing the number of interactions among XIST, miRNAs, and mRNAs, we pinpointed ETS2 as the pivotal gene within the ceRNA network. Our findings reveal a novel XIST- hsa-miR-146a-5p, hsa-miR-144-3p, and hsa-miR-1271-5p-ETS2 axis that comprehensively elucidates the XIST-associated mechanism underlying PCOS onset. qRT-PCR analysis further confirmed the, overexpression of both XIST and ETS2 . Furthermore, our results demonstrated that XIST and ETS2 were correlated with some assisted reproductive technologies outcomes. Finally, we identified two novel compounds including, methotrexate/folate and threonine using drug-gene interaction databases for PCOS management. These findings provide novel insights into the molecular etiology, diagnosis, and potential therapeutic interventions for PCOS.

Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update

INTRODUCTION

Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma.

AREAS COVERED

The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma.

EXPERT OPINION

While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.

Elucidation of common molecular diagnostic biomarkers between chronic periodontitis and Parkinson's disease via bioinformatics analyses

BACKGROUND AND OBJECTIVES

Parkinson's disease (PD) and chronic periodontitis (CP) are both inflammatory diseases; a correlation between the two diseases has been reported, but the underlying mechanisms of this association have not been investigated. We investigated the common molecular mechanisms between PD and CP and the role of immune cells in the pathogenesis of them using bioinformatics analyses to elucidate the association between the two diseases.

METHODS

We obtained gene expression data from the Gene Expression Omnibus (GEO) database: GSE10334, GSE16134, and GSE23586 for CP gingival samples and GSE20146 for PD brain samples. Subsequently, we conducted an enrichment analysis of the differentially expressed genes (DEGs) using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Moreover, all DEGs were analysed for protein-transcription factor interactions and protein-immune cell co-expression. We constructed protein-transcription factor, protein-protein interaction (PPI), and protein-immune cell co-expression networks using the Cytoscape software. Moreover, we identified the hub genes and investigated them for potential diagnostic value.

RESULTS AND CONCLUSION

We identified 99 DEGs in the three CP datasets, 520 DEGs in the PD dataset and found five common DEGs in the CP and PD datasets, namely CXCR4, CXCL8, CD19, RPTN, and SLC16A9. These common DEGs identified in our study may have a potential impact on disease pathogenesis through the involvement of CXCR4-CXCL8-CD19 protein-complexes in dendritic cells. Therefore, CD19, LCP2, CXCR4, and LYN could be used as target molecules for the clinical diagnosis of both diseases.

Preexisting Immunity Drives the Response to Neoadjuvant Chemotherapy in Esophageal Adenocarcinoma

Current treatment for patients with locally advanced esophageal adenocarcinoma (EAC) is neoadjuvant chemotherapy (nCT), alone or combined with radiotherapy, before surgery. However, fewer than 30% of treated patients show a pathologic complete response to nCT, which correlates with increased 5-year survival compared with nonresponders. Understanding the mechanisms of response to nCT is pivotal to better stratify patients and inform more efficacious therapies. Here, we investigated the immune mechanisms involved in nCT response by multidimensional profiling of pretreatment tumor biopsies and blood from 68 patients with EAC (34 prospectively and 34 retrospectively collected), comparing complete responders versus nonresponders to nCT. At the tumor level, complete response to nCT was associated with molecular signatures of immune response and proliferation, increased putative antitumor tissue-resident memory CD39+ CD103+ CD8+ T cells, and reduced immunosuppressive T regulatory cells (Treg) and M2-like macrophages. Systemically, complete responders showed higher frequencies of immunostimulatory CD14+ CD11c+ HLA-DRhigh cells, and reduced programmed cell death ligand 1-positive (PD-L1+) monocytic myeloid-derived suppressor cells, along with high plasma GM-CSF (proinflammatory) and low IL4, CXCL10, C3a, and C5a (suppressive). Plasma proinflammatory and suppressive cytokines correlated directly and inversely, respectively, with the frequency of tumor-infiltrating CD39+ CD103+ CD8+ T cells. These results suggest that preexisting immunity in baseline tumor drives the clinical activity of nCT in locally advanced EAC. Furthermore, it may be possible to stratify patients based on predictive immune signatures, enabling tailored neoadjuvant and/or adjuvant regimens.

SIGNIFICANCE

Multidimensional profiling of pretreatment esophageal adenocarcinoma shows patient response to nCT is correlated with active preexisting immunity and indicates molecular pathways of resistance that may be targeted to improve clinical outcomes.

Identification of molecular signatures in acute myocardial infarction based on integrative analysis of proteomics and transcriptomics

BACKGROUND

Myocardial infarction (MI) is one of the most serious cardiovascular diseases, characterized by a rapid and irreversible decline in myocardial function. Early detection of patients with MI and prolonging the optimal therapeutic window of acute myocardial infarction (AMI) are particularly important. This study aimed to identify the diagnostic biomarkers and novel therapeutic targets for acute myocardial infarction.

METHOD

We generated the AMI mouse models by ligating the proximal left anterior descending coronary artery. Six time points-Sham, AMI 10-min, 1-h, 6-h, 24-h, and 72-h-were chosen to examine the molecular changes that occur during the AMI process. RNA-seq and DIA-MS were performed on the infarcted left ventricular tissues of AMI mice at each time point. Co-expression pattern genes were screened from myocardial infarction samples at different time points by time-series analysis. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to examine these genes. Using the Interactive Gene/Protein Retrieval Tool (STRING) database, the protein-protein interaction network (PPI) was constructed and the hub genes were identified. In order to evaluate the diagnostic value of hub genes, a receiver operating characteristic (ROC) curve was constructed. An independent data set, GSE163772, confirmed the diagnostic value of hub genes further.

RESULT

We obtained the expression profiles at different time points after the occurrence of heart failure through high-throughput sequencing, and found 167 genes with similar expression patterns through time series analysis. The immune response and immune-related pathways had the greatest enrichment of these genes. Among them, Itgb2 Syk, Tlr4, Tlr2, Itgax, and Lcp2 may play key roles as hub genes. Combined with the results of proteomic analysis, it was found that the expression of Coro1a in both omics increased with time. The results of external validation showed that TLR2, ITGAX, and LCP2 had good predictive ability for AMI diagnosis.

CONCLUSION

Itgb2, Syk, Tlr4, Tlr2, Itgax, Lcp2 and Coro1a are considered to be the seven key genes significantly associated with AMI. Our results may provide potential targets for the prevention of adverse ventricular remodeling and the treatment of AMI.

Single-cell transcriptomic analysis reveals differential cell subpopulations and distinct phenotype transition in normal and dissected ascending aorta

BACKGROUND

Acute thoracic aortic dissection (ATAD) is a fatal condition characterized by tear of intima, formation of false lumen and rupture of aorta. However, the subpopulations of normal and dissected aorta remain less studied.

METHODS

Single-cell RNA sequencing was performed including 5 patients with ATAD and 4 healthy controls. Immunohistochemistry and immunofluorescence were used to verify the findings.

RESULTS

We got 8 cell types from human ascending aorta and identified 50 subpopulations including vascular smooth muscle cells (VSMCs), endothelial cells, fibroblasts, neutrophils, monocytes and macrophages. Six transmembrane epithelial antigen of prostate 4 metalloreductase (STEAP4) was identified as a new marker of synthetic VSMCs. CytoTRACE identified subpopulations with higher differentiation potential in specified cell types including synthetic VSMCs, enolase 1⁺ fibroblasts and myeloid-derived neutrophils. Synthetic VSMCs-derived C-X-C motif chemokine ligand 12 (CXCL12) might interact with neutrophils and fibroblasts via C-X-C motif chemokine receptor 4 (CXCR4) and atypical chemokine receptor 3 (ACKR3), respectively, which might recruit neutrophils and induce transdifferentitation of fibroblasts into synthetic VSMCs.

CONCLUSION

We characterized signatures of different cell types in normal and dissected human ascending aorta and identified a new marker for isolation of synthetic VSMCs. Moreover, we proposed a potential mechanism that synthetic VSMCs might interact with neutrophils and fibroblasts via CXCL12-CXCR4/ACKR3 axis whereby deteriorating the progression of ATAD, which might provide new insights to better understand the development and progression of ATAD.

Construction of Prognostic Risk Model for Small Cell Lung Cancer Based on Immune-Related Genes

Small cell lung cancer (SCLC) is a highly invasive and fatal malignancy. Research at the present stage implied that the expression of immune-related genes is associated with the prognosis in SCLC. Accordingly, it is essential to explore effective immune-related molecular markers to judge prognosis and treat SCLC. Our research obtained SCLC dataset from Gene Expression Omnibus (GEO) and subjected mRNAs in it to differential expression analysis. Differentially expressed mRNAs (DEmRNAs) were intersected with immune-related genes to yield immune-related differentially expressed genes (DEGs). The functions of these DEGs were revealed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Thereafter, we categorized 3 subtypes of immune-related DEGs via K-means clustering. Kaplan-Meier curves analyzed the effects of 3 subtypes on SCLC patients' survival. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE validated that the activation of different immune gene subtypes differed significantly. Finally, an immune-related-7-gene assessment model was constructed by univariate-Lasso-multiple Cox regression analyses. Riskscores, Kaplan-Meier curves, receiver operating characteristic (ROC) curves, and independent prognostic analyses validated the prognostic value of the immune-related-7-gene assessment model. As suggested by GSEA, there was a prominent difference in cytokine-related pathways between high- and low-risk groups. As the analysis went further, we discovered a statistically significant difference in the expression of human leukocyte antigen (HLA) proteins and costimulatory molecules expressed on the surface of CD274, CD152, and T lymphocytes in different groups. In a word, we started with immune-related genes to construct the prognostic model for SCLC, which could effectively evaluate the clinical outcomes and offer guidance for the treatment and prognosis of SCLC patients.

Apprising Diagnostic and Prognostic Biomarkers in Cutaneous Melanoma—Persistent Updating

The incidence of melanoma, a very aggressive skin cancer, has increased over the past few decades. Although there are well-established clinical, dermoscopic and histopathological criteria, the diagnosis is often performed late, which has important implications on the patient’s clinical outcome. Unfortunately, melanoma is one of the most challenging tumors to diagnose because it is a heterogeneous neoplasm at the clinical, histopathological, and molecular level. The use of reliable biomarkers for the diagnosis and monitoring of disease progression is becoming a standard of care in modern medicine. In this review, we discuss the latest studies, which highlight findings from the genomics, epitranscriptomics, proteomics and metabolomics areas, pointing out different genes, molecules and cells as potential diagnostic and prognostic biomarkers in cutaneous melanoma.

Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish

The zebrafish has proven to be a valuable model organism for studying hematopoiesis, but relatively little is known about zebrafish immune cell development and functional diversity. Elucidating key aspects of zebrafish lymphocyte development and exploring the breadth of effector functions would provide valuable insight into the evolution of adaptive immunity. We performed single-cell RNA sequencing on ∼70,000 cells from the zebrafish marrow and thymus to establish a gene expression map of zebrafish immune cell development. We uncovered rich cellular diversity in the juvenile and adult zebrafish thymus, elucidated B- and T-cell developmental trajectories, and transcriptionally characterized subsets of hematopoietic stem and progenitor cells and early thymic progenitors. Our analysis permitted the identification of two dendritic-like cell populations and provided evidence in support of the existence of a pre-B cell state. Our results provide critical insights into the landscape of zebrafish immunology and offer a foundation for cellular and genetic studies.

Identification of Tumor Antigens and Immune Subtypes of Esophageal Squamous Cell Carcinoma for mRNA Vaccine Development

Purpose: The applicability of mRNA vaccines against esophageal squamous cell carcinoma (ESCC) remains unclear. Here, we identified potential antigens for developing mRNA vaccines against ESCC and characterized immune subtypes to select appropriate patients for vaccination.

Methods: RNA-seq, genetic alteration data, and corresponding clinical information of ESCC patients were obtained from the Cancer Genome Atlas (TCGA) database. The RNA-seq data of normal esophageal tissue were obtained from the Genotype-Tissue Expression (GTEx) database. Potential tumor antigens were screened by analyzing differentially expressed and mutated genes and potential antigens with significant differences in prognosis were screened using the Kaplan-Meier method. The proportion of immune cell infiltration in the tumor microenvironment was estimated using CIBERSORT and MCPcounter, and the correlation of potential antigens with antigen-presenting cells and major histocompatibility complex class II was analyzed. Subsequently, immune subtypes were constructed using consensus clustering analysis and characterized by single-sample gene set enrichment analysis and weighted gene co-expression network analysis (WGCNA). The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to analyze the drug sensitivity of different immune subtypes.

Results: Four overexpressed and mutated tumor antigens associated with antigen presentation and poor prognosis were identified in ESCC, including NLRC5, FCRL4, TMEM229B, and LCP2. By consensus clustering, we identified two immune-associated ESCC subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2); the prognosis of the two subtypes was statistically different. In addition, the two immune subtypes had distinctly different cellular, molecular, and clinical characteristics. IS1 patients have a distinct immune “hot” phenotype with strong immune tolerance, whereas patients with IS2 have an immune “cold” phenotype. Differential expression of immune checkpoints and immunogenic cell death modulators was observed between the different immune subtypes. Finally, we found that IS1 and IS2 patients showed different drug sensitivities to common anti-tumor drugs, possibly facilitating the development of individualized treatment regimens for patients.

Conclusion: NLRC5, LCP2, TMEM229B, and FCRL4 are potential antigens for ESCC mRNA vaccines, and such vaccines may be more suitable for IS2 patients. This study provides a theoretical basis for mRNA vaccines against ESCC, by identifying the critical characteristics to predict ESCC prognosis and select suitable patients for vaccination.

Identification of Prognosis Biomarkers for High-Grade Serous Ovarian Cancer Based on Stemness

In this paper, high-grade serous ovarian cancer (HGSOC) is studied, which is the most common histological subtype of ovarian cancer. We use a new analytical procedure to combine the bulk RNA-Seq sample for ovarian cancer, mRNA expression-based stemness index (mRNAsi), and single-cell data for ovarian cancer. Through integrating bulk RNA-Seq sample of cancer samples from TCGA, UCSC Xena and single-cell RNA-Seq (scRNA-Seq) data of HGSOC from GEO, and performing a series of computational analyses on them, we identify stemness markers and survival-related markers, explore stem cell populations in ovarian cancer, and provide potential treatment recommendation. As a result, 171 key genes for capturing stem cell characteristics are screened and one vital cancer stem cell subpopulation is identified. Through further analysis of these key genes and cancer stem cell subpopulation, more critical genes can be obtained as LCP2, FCGR3A, COL1A1, COL1A2, MT-CYB, CCT5, and PAPPA, are closely associated with ovarian cancer. So these genes have the potential to be used as prognostic biomarkers for ovarian cancer.

Lymphocyte cytosolic protein 2 is a novel prognostic marker in lung adenocarcinoma

OBJECTIVE

Lymphocyte cytosolic protein 2 (LCP2) is often ectopically expressed in various human tumors. However, the clinical significance and role of LCP2 in lung adenocarcinoma (LUAD) remain unclear. This study explored the prognostic significance of LCP2 in LUAD patients.

METHODS

LCP2 expression in LUAD tissues was analyzed using data from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Western blotting was employed to detect LCP2 expression in LUAD. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to explore signaling pathways mediated by LCP2 co-regulatory genes. Immunohistochemistry was used to examine levels of LCP2 and programmed death ligand 1 (PD-L1) in 68 LUAD patients. Associations between LCP2 expression and clinicopathological features, prognoses, and PD-L1 levels among the LUAD in-patients were analyzed.

RESULTS

Among the 68 LUAD in-patients, LCP2 expression was correlated with clinical stage and lymph node metastasis. LUAD patients with high LCP2 expression were associated with increased overall survival. LCP2 expression may be associated with an enrichment of several immune functions. Moreover, our immunohistochemistry results demonstrated that LCP2 expression was positively correlated with PD-L1 expression in LUAD tissues.

CONCLUSIONS

In the study, LCP2 was found to be a favorable prognostic biomarker in LUAD patients.