Identification of Diagnostic Markers for Breast Cancer Based on Differential Gene Expression and Pathway Network

Background: Breast cancer is the second largest cancer in the world, the incidence of breast cancer continues to rise worldwide, and women’s health is seriously threatened. Therefore, it is very important to explore the characteristic changes of breast cancer from the gene level, including the screening of differentially expressed genes and the identification of diagnostic markers.Methods: The gene expression profiles of breast cancer were obtained from the TCGA database. The edgeR R software package was used to screen the differentially expressed genes between breast cancer patients and normal samples. The function and pathway enrichment analysis of these genes revealed significant enrichment of functions and pathways. Next, download these pathways from KEGG website, extract the gene interaction relations, construct the KEGG pathway gene interaction network. The potential diagnostic markers of breast cancer were obtained by combining the differentially expressed genes with the key genes in the network. Finally, these markers were used to construct the diagnostic prediction model of breast cancer, and the predictive ability of the model and the diagnostic ability of the markers were verified by internal and external data.Results: 1060 differentially expressed genes were identified between breast cancer patients and normal controls. Enrichment analysis revealed 28 significantly enriched pathways (p < 0.05). They were downloaded from KEGG website, and the gene interaction relations were extracted to construct the gene interaction network of KEGG pathway, which contained 1277 nodes and 7345 edges. The key nodes with a degree greater than 30 were extracted from the network, containing 154 genes. These 154 key genes shared 23 genes with differentially expressed genes, which serve as potential diagnostic markers for breast cancer. The 23 genes were used as features to construct the SVM classification model, and the model had good predictive ability in both the training dataset and the validation dataset (AUC = 0.960 and 0.907, respectively).Conclusion: This study showed that the difference of gene expression level is important for the diagnosis of breast cancer, and identified 23 breast cancer diagnostic markers, which provides valuable information for clinical diagnosis and basic treatment experiments.

Diagnostic markers of human papillomavirus persistence and progression of cervical intraepithelial neoplasia

Cervical intraepithelial neoplasia is widespread among patients of the reproductive period, the peak of the incidence occurs at a young age, often when the reproductive function has not yet been performed. The oncological alertness of the medical community is justified: the incidence of cervical cancer has increased by 24.6% over the past ten years, and in the structure of cancer mortality in the age group of 30–39 years cervical cancer occupies the 1st place accounting for 23%. Тhe same time aggressive management of the disease in patients who have not yet performed their reproductive function is associated with the loss of significant volume of cervical tissues and an increase in the frequency of premature birth. The most acute issue is the tactics of managing cervical neoplasia of the second degree of severity, when there is still hope for the regression of the disease, but at the same time there is a high risk of transition to dysplasia of the third degree of severity and subsequently to invasive cancer. The search for diagnostic markers that allow predicting the probability of regression and, conversely, the unfavorable course of the disease is the most important task solution of which will allow optimizing tactics in controversial clinical cases and avoiding unnecessary surgical aggression, improving the perinatal outcomes of patients undergoing surgical treatment. The search for new economically feasible and diagnostically valuable markers allowing us to predict the course of the disease and determine the amount of necessary surgical treatment continues, but the most significant at this moment is still the determination of the coexpression of p16 and Ki-67 in immunocytochemical studies and p16INK4a in immunohistochemical studies. The diagnostic sensitivity of determining the co-expression of p16INK4a/Ki67 is 98.5%, and the expression of p16INK4a in CIN II indicates that in 81% of cases there is a tendency to a progressive course of the disease.

Identification of Diagnostic Markers Correlated With HIV+ Immune Non-response Based on Bioinformatics Analysis

Background: HIV-infected immunological non-responders (INRs) are characterized by their inability to reconstitute CD4+ T cell pools after antiretroviral therapy. The risk of non-AIDS-related diseases in INRs is increased, and the outcome and prognosis of INRs are inferior to that of immunological responders (IRs). However, few markers can be used to define INRs precisely. In this study, we aim to identify further potential diagnostic markers associated with INRs through bioinformatic analyses of public datasets.Methods: This study retrieved the microarray data sets of GSE106792 and GSE77939 from the Gene Expression Omnibus (GEO) database. After merging two microarray data and adjusting the batch effect, differentially expressed genes (DEGs) were identified. Gene Ontology (GO) resource and Kyoto Encyclopedia of Genes and Genomes (KEGG) resource were conducted to analyze the biological process and functional enrichment. We performed receiver operating characteristic (ROC) curves to filtrate potential diagnostic markers for INRs. Gene Set Enrichment Analysis (GSEA) was conducted to perform the pathway enrichment analysis of individual genes. Single sample GSEA (ssGSEA) was performed to assess scores of immune cells within INRs and IRs. The correlations between the diagnostic markers and differential immune cells were examined by conducting Spearman’s rank correlation analysis. Subsequently, miRNA-mRNA-TF interaction networks in accordance with the potential diagnostic markers were built with Cytoscape. We finally verified the mRNA expression of the diagnostic markers in clinical samples of INRs and IRs by performing RT-qPCR.Results: We identified 52 DEGs in the samples of peripheral blood mononuclear cells (PBMC) between INRs and IRs. A few inflammatory and immune-related pathways, including chronic inflammatory response, T cell receptor signaling pathway, were enriched. FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1 were considered as potential diagnostic markers. ssGSEA results showed that the IRs had significantly higher enrichment scores of seven immune cells compared with IRs. The miRNA-mRNA-TF network was constructed with 97 miRNAs, 6 diagnostic markers, and 26 TFs, which implied a possible regulatory relationship.Conclusion: The six potential crucial genes, FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1, may be associated with clinical diagnosis in INRs. Our study provided new insights into diagnostic and therapeutic targets.

Diagnostic Value of Immune-Related Genes in Kawasaki Disease

Kawasaki disease (KD) is a systemic vasculitis that predominantly damages medium- and small-sized vessels, and mainly causes coronary artery lesions (CALs). The diagnostic criterion of KD mainly depends on clinical features, so children could be easily misdiagnosed and could suffer from CALs. Through analysis, a total of 14 immune-related DEGs were obtained, of which IL1B, ADM, PDGFC, and TGFA were identified as diagnostic markers of KD. Compared with the non-KD group, KD patients contained a higher proportion of naive B cells, activated memory CD4 T cells, gamma delta T cells, and neutrophils, while the proportions of memory B cells, CD8 T cells, activated memory CD4 T cells, and activated NK cells were relatively lower. In conclusion, immune-related genes can be used as diagnostic markers of KD, and the difference in immune cells between KD and non-KD might provide new insight into understanding the pathogenesis of KD.

Selection of New Diagnostic Markers for Dirofilaria Repens Infections With the Use of Phage Display Technology

Dirofilaria repens is a parasitic nematode causing vector-borne disease (dirofilariasis), considered an emerging problem in veterinary and human medicine. Although main hosts are carnivores, particularly dogs, D. repens shows high zoonotic potential. The disease spreads uncontrollably, affecting new areas. Since there is no vaccine against dirofilariasis, the only way to limit disease transmission is an early diagnosis. Currently, diagnosis depends on the detection of microfilariae in the host bloodstream using modified Knott's test or multiplex PCR. However, the efficacy of tests relying on microfilariae detection is limited by microfilariae periodic occurrence. Therefore, a new reliable diagnostic test is required. Our study aimed to select new diagnostic markers for dirofilariasis with potential application in diagnostics. We focused on single epitopes to ensure high specificity of diagnosis and avoid cross-reactivity with the other parasite infections common in dogs. Using phage display technology and 12-mer peptides library, we selected epitopes highly reactive with IgG from sera of infected dogs. Additionally, our study presents the possibility of detecting D. repens specific cell-free DNA in dogs with no microfilaria but high IgG and IgM antibody levels against parasite somatic antigen.