Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort

Antibrush Border Antibody Disease: A Case Series

Antibrush border antibody (ABBA) disease is a rare cause of kidney disease characterized by progressive renal tubular injury associated with immune complex deposition along the basement membranes of the proximal tubule and circulating autoantibodies to brush border antigens. Several antigens have been identified as targets of autoantibodies in this disease, including low-density lipoprotein receptor related protein 2 (LRP2), cubilin, and amnionless proteins. We present 9 patients from 2 academic medical centers and describe the clinicopathologic characteristics and outcome data. All patients presented with acute kidney injury and proteinuria. Pathology confirmed immune complex deposition along proximal tubular basement membranes in all patients, but the majority (6/8) also showed segmental glomerular subepithelial immune complexes. Two of 3 patients treated with rituximab demonstrated stabilization of kidney function; 1 of these patients had mantle cell lymphoma. One patient with lung cancer showed stabilization of disease after treatment of the malignancy. The remaining patients progressed to end-stage kidney disease with either conservative therapy (3 patients) or immunosuppression with glucocorticoids (2 patients). This series highlights the poor prognosis of ABBA disease, but a potential benefit of anti-B cell therapy or treatment of an underlying malignancy in some cases.

A multi-variable predictive warning model for cervical cancer using clinical and SNPs data

Introduction

Cervical cancer is the fourth most common cancer among female worldwide. Early detection and intervention are essential. This study aims to construct an early predictive warning model for cervical cancer and precancerous lesions utilizing clinical data and simple nucleotide polymorphisms (SNPs).

Methods

Clinical data and germline SNPs were collected from 472 participants. Univariate logistic regression, least absolute shrinkage selection operator (LASSO), and stepwise regression were performed to screen variables. Logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), extreme gradient boosting(XGBoost) and neural network(NN) were applied to establish models. The receiver operating characteristic (ROC) curve was used to compare the models' efficiencies. The performance of models was validated using decision curve analysis (DCA).

Results

The LR model, which included 6 SNPs and 2 clinical variables as independent risk factors for cervical carcinogenesis, was ultimately chosen as the most optimal model. The DCA showed that the LR model had a good clinical application.

Discussion

The predictive model effectively foresees cervical cancer risk using clinical and SNP data, aiding in planning timely interventions. It provides a transparent tool for refining clinical decisions in cervical cancer management.

Exploring scavenger receptor class F member 2 and the importance of scavenger receptor family in prediagnostic diseases

Scavenger Receptor Class F Member 2 (SCARF2), also known as the Type F Scavenger Receptor Family gene, encodes for Scavenger Receptor Expressed by Endothelial Cells 2 (SREC-II). This protein is a crucial component of the scavenger receptor family and is vital in protecting mammals from infectious diseases. Although research on SCARF2 is limited, mutations in this protein have been shown to cause skeletal abnormalities in both SCARF2-deficient mice and individuals with Van den Ende-Gupta syndrome (VDEGS), which is also associated with SCARF2 mutations. In contrast, other scavenger receptors have demonstrated versatile responses and have been found to aid in pathogen elimination, lipid transportation, intracellular cargo transportation, and work in tandem with various coreceptors. This review will concentrate on recent progress in comprehending SCARF2 and the functions played by members of the Scavenger Receptor Family in pre-diagnostic diseases.

Integrative analyses of genes related to liver ischemia reperfusion injury

Background

Liver ischemia reperfusion injury (LIRI) is not only a common injury during liver transplantation and major hepatic surgery, but also one of the primary factors that affect the outcome of postoperative diseases. However, there are still no reliable ways to tackle the problem. Our study aimed to find some characteristic genes associated with immune infiltration that affect LIRI, which can provide some insights for future research in the future. Therefore, it is essential for the treatment of LIRI, the elucidation of the mechanisms of LIRI, and exploring the potential biomarkers. Efficient microarray and bioinformatics analyses can promote the understanding of the molecular mechanisms of disease occurrence and development.

Method

Data from GSE151648 were downloaded from GEO data sets, and we performed a comprehensive analysis of the differential expression, biological functions and interactions of LIRI-associated genes. Then we performed Gene ontology (GO) analysis and Kyotoencydlopedia of genes and genomes (KEGG) enrichment analysis of DEGs. At last, we performed a protein-protein interaction network to screen out hub genes.

Results

A total of 161 differentially expressed genes (DEGs) were identified. GO analysis results revealed that the changes in the modules were mostly enriched in the neutrophil degranulation, neutrophil activation involved in immune response, and neutrophil mediated immunity. KEGG enrichment analysis of DEGs demonstrated that LIRI mainly involved the cytokine-cytokine receptor interaction. Our data indicated that macrophages and neutrophils are closely related to LIRI. 9 hub genes were screened out in the protein-protein interaction network.

Conclusions

In summary, our data indicated that neutrophil degranulation, neutrophil activation involved in immune response, neutrophil mediated immunity and cytokine-cytokine receptor interaction may play a key role in LIRI, HRH1, LRP2, P2RY6, PKD1L1, SLC8A3 and TNFRSF8, which were identified as potential biomarkers in the occurrence and development of LIRI. However, further studies are needed to validate these findings and explore the molecular mechanism of these biomarkers in LIRI.