Elevated serum levels of human epididymis protein 4 in adult patients with proliferative lupus nephritis.

Background: This study aimed to access whether serum human epididymis protein 4 (HE4) level could identify lupus nephritis (LN) pathological classes in adults and children. Methods: The serum HE4 levels of 190 healthy subjects and 182 patients with systemic lupus erythematosus (SLE) (61 adult-onset LN [aLN], 39 childhood-onset LN [cLN], and 82 SLE without LN) were determined using Architect HE4 kits and an Abbott ARCHITECT i2000SR Immunoassay Analyzer. Results: Serum HE4 level was significantly higher in the aLN patients (median, 85.5 pmol/L) than in the patients with cLN (44 pmol/L, P < 0.001) or SLE without LN (37 pmol/L, P < 0.001), or the healthy controls (30 pmol/L, P < 0.001). Multivariate analysis showed that serum HE4 level was independently associated with aLN. Stratified by LN class, serum HE4 level was significantly higher in the patients with proliferative LN (PLN) than in those with non-PLN, and this difference was found only in aLN (median, 98.3 versus 49.3 pmol/L, P = 0.021) but not in cLN. Stratified by activity (A) and chronicity (C) indices, the aLN patients with class IV (A/C) possessed significantly higher serum HE4 levels than those with class IV (A) (median, 195.5 versus 60.8 pmol/L, P = 0.006), and this difference was not seen in the class III aLN or cLN patients. Conclusion: Serum HE4 level is elevated in patients with class IV (A/C) aLN. The role of HE4 in the pathogenesis of chronic lesions of class IV aLN needs further investigation.

Single-Cell RNA Sequencing Revealed a 3-Gene Panel Predicted the Diagnosis and Prognosis of Thyroid Papillary Carcinoma and Associated With Tumor Immune Microenvironment.

Objective: The objective of this research was to screen prognostic related genes of thyroid papillary carcinoma (PTC) by single-cell RNA sequencing (scRNA-seq), to construct the diagnostic and prognostic models based on The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) data, and to evaluate the association between tumor immune microenvironment and the prognostic model. Method: The differentially expressed genes (DEGs) and tumor evolution were analyzed by scRNA-seq based on public databases. The potential regulatory networks of DEGs related to prognosis were analyzed by multi-omics data in the THCA. Logistic regression and Cox proportional hazards regression were utilized to construct the diagnosis and prognostic model of PTC. The performance of the diagnostic model was verified by bulk RNA sequencing (RNA-seq) of our cohort. The tumor immune microenvironment associated with the prognostic model was evaluated using multi-omics data. In addition, qRT-PCR was performed on tumor tissues and adjacent normal tissues of 20 patients to verify the expression levels of DEGs. Results: The DEGs screened by scRNA-seq can distinguish between tumor and healthy samples. DEGs play different roles in the evolution from normal epithelial cells to malignant cells. Three DEGs ((FN1, CLU, and ANXA1)) related to prognosis were filtered, which may be regulated by DNA methylation, RNA methylation (m6A) and upstream transcription factors. The area under curve (AUC) of the diagnostic model based on 3-gene in the validation of our RNA-seq was 1. In the prognostic model based on 3-gene, the overall survival (OS) of high-risk patients was shorter. Combined with the clinical information of patients, a nomogram was constructed by using tumor size (pT) and risk score to quantify the prognostic risk. The age and tumor size of high-risk patients in the prognostic model were greater. In addition, the increase of tumor mutation burden (TMB) and diversity of T cell receptor (TCR), and the decrease of CD8+ T cells in high-risk group suggest the existence of immunosuppressive microenvironment. Conclusion: We applied the scRNA-seq pipeline to focus on epithelial cells in PTC, simulated the process of tumor evolution, and revealed a prognostic prediction model based on 3 genes, which is related to tumor immune microenvironment.