International Journal of Genomics

Background. Post-renal transplant patients have a high likelihood of developing renal cancer. However, the underlying biological mechanisms behind the development of renal cancer in post-kidney transplant patients remain to be elucidated. Therefore, this study aimed to investigate the underlying biological mechanism behind the development of renal cell carcinoma in post-renal transplant patients. Methods. Next-generation sequencing data and corresponding clinical information of patients with clear cell renal cell carcinoma (ccRCC) were obtained from The Cancer Genome Atlas Program (TCGA) database. The microarray data of kidney transplant patients with or without rejection response was obtained from the Gene Expression Omnibus (GEO) database. In addition, statistical analysis was conducted in R software. Results. We identified 55 upregulated genes in the transplant patients with rejection from the GEO datasets (GSE48581, GSE36059, and GSE98320). Furthermore, we conducted bioinformatics analyses, which showed that all of these genes were upregulated in ccRCC tissue. Moreover, a prognosis model was constructed based on four rejection-related genes, including PLAC8, CSTA, AIM2, and LYZ. The prognosis model showed excellent performance in prognosis prediction in a ccRCC cohort. In addition, the machine learning algorithms identified 19 rejection-related genes, including PLAC8, involved in ccRCC occurrence. Finally, the PLAC8 was selected for further research, including its clinical and biological role. Conclusion. In all, our study provides novel insight into the transition from the rejection of renal transplant to renal cancer. Meanwhile, PLAC8 could be a potential biomarker for ccRCC diagnosis and prognosis in post-kidney transplant patients.

Tomato chlorosis virus (ToCV), transmitted by the whitefly, Bemisia tabaci (Gennadius; Hemiptera: Aleyrodidae) has been continuously emerging on tomato plants and causing a significant economic loss throughout China. In the current study, RNA-Seq analysis was used to explore the gene expression profiles of B. tabaci Mediterranean (MED) that fed on both ToCV-infected and -uninfected tomato plants for 6, 12, 24, and 48 hours, respectively. The results revealed that dynamic changes occurred in the gene expressions of whiteflies at different time intervals after they acquired the virus. A total of 1709, 461, 4548, and 1748 differentially expressed genes (DEGs) were identified after a 6, 12, 24, and 48 hours feeding interval for the viral acquisition, respectively. The least number of expressed genes appeared in whiteflies with the 12 hours feeding treatment, and the largest numbers of those found in those with 24 hours feeding treatment. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that B. tabaci MED responded to ToCV acquisition through altering its nerve system development, fertility, detoxification, glucose metabolism, and immune function before it lost its ability to transmit the virus. The number of DEGs, degree of differential gene expressions, expression level of the same gene, involved biological processes, and metabolic functions in whiteflies post the 12 hours feeding, and viral acquisition were different from those from other three feeding treatments, which could be a significant finding suggesting an effective control of B. tabaci MED should be done less than 12 hours after whiteflies started feeding on ToCV-infected tomatoes. Our results further provided a clarified understanding in how B. tabaci was protected from viral acquisitions through comparison of the differential profile of gene expressions in whiteflies feeding on plants that were infected by semipersistent viruses.

Aim. We sought to profile gut microbiota’s role in combination of Bu Fei Hua Yu (BFHY) with cisplatin treatment. Methods. Non-small cell lung cancer (NSCLC) mice model were constructed followed by treatment with cisplatin alone or combined with BFHY. Mice weight and tumor volume were measured during the experiment. And mice cecum were detected by hematoxylin and eosin, cecum contents were collected for Enzyme Linked ImmuneSorbent Assay, and stool were profiled for metagenomic sequencing. Results. Combination of BFHY with cisplatin treatment decreased the tumor growth and relieved the damage of cecum. Expressions of interleukin-6 (IL-6), interleukin-1β (IL-1β), monocyte chemotactic protein 1 (MCP), and interferon-γ (IFN-γ) were decreased compared with cisplatin treatment alone. Linear discriminant analysis effect size analysis showed that g_Parabacteroides was downregulated and g_Escherichia and g_Blautia were upregulated after cisplatin treatment. After combination with BFHY, g_Bacteroides and g_Helicobacter were decreased. g_Klebsiella, g_Unclssified_Proteobacteria, and g_Unclssified_Clostridiates were increased. Moreover, heatmap results showed that Bacteroides abundance was increased significantly after cisplatin treatment; BFHY combination treatment reversed this state. Function analysis revealed that multiple functions were slightly decreased in cisplatin treatment alone and increased significantly after combination with BFHY. Conclusion. Our study provided evidence of an efficacy of combination of BFHY with cisplatin on treatment of NSCLC and revealed that gut microbiota plays a role in it. The above results provide new ideas on NSCLC treatment.

Mesenchymal–epithelial transition (MET) factor is a proto-oncogene encoding tyrosine kinase receptor with hepatocyte growth factor (HGF) or scatter factor (SF). It is found on the human chromosome number 7 and regulates the diverse cellular mechanisms of the human body. The impact of mutations occurring in the MET gene is demonstrated by their detrimental effects on normal cellular functions. These mutations can change the structure and function of MET leading to different diseases such as lung cancer, neck cancer, colorectal cancer, and many other complex syndromes. Hence, the current study focused on finding deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) and their subsequent impact on the protein’s structure and functions, which may contribute to the emergence of cancers. These nsSNPs were first identified utilizing computational tools like SIFT, PROVEAN, PANTHER-PSEP, PolyPhen-2, I-Mutant 2.0, and MUpro. A total of 45359 SNPs of MET gene were accumulated from the database of dbSNP, and among them, 1306 SNPs were identified as non-synonymous or missense variants. Out of all 1306 nsSNPs, 18 were found to be the most deleterious. Moreover, these nsSNPs exhibited substantial effects on structure, binding affinity with ligand, phylogenetic conservation, secondary structure, and post-translational modification sites of MET, which were evaluated using MutPred2, RaptorX, ConSurf, PSIPRED, and MusiteDeep, respectively. Also, these deleterious nsSNPs were accompanied by changes in properties of MET like residue charge, size, and hydrophobicity. These findings along with the docking results are indicating the potency of the identified SNPs to alter the structure and function of the protein, which may lead to the development of cancers. Nonetheless, Genome-wide association study (GWAS) studies and experimental research are required to confirm the analysis of these nsSNPs.

Bovine respiratory disease (BRD) is one of the major health issues in the cattle industry, resulting in significant financial crises globally. There is currently no good treatment, and cattle are made resistant to pneumonia through disease-resistant breeding. The serial blood samples from six Xinjiang brown (XJB) calves were collected for the RNA sequencing (RNA-seq). The obtained six samples were grouped into two groups, in each group as infected with BRD and healthy calves, respectively. In our study, the differential expression mRNAs were detected by using RNA-seq and constructed a protein–protein interaction (PPI) network related to the immunity in cattle. The key genes were identified by protein interaction network analysis, and the results from RNA-seq were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A total of 488 differentially expressed (DE) mRNAs were identified. Importantly, the enrichment analysis of these identified DEGs classified them as mainly enriched in the regulation and immune response processes. The 16 hub genes were found to be related to immune pathways categorized by PPIs analysis. Results revealed that many hub genes were related to the immune response to respiratory disease. These results will provide the basis for a better understanding of the molecular mechanism of bovine resistance to BRD.

Background. The genetic factors and pathogenesis of idiopathic dilated cardiomyopathy-induced heart failure (IDCM-HF) have not been understood thoroughly; there is a lack of specific diagnostic markers and treatment methods for the disease. Hence, we aimed to identify the mechanisms of action at the molecular level and potential molecular markers for this disease. Methods. Gene expression profiles of IDCM-HF and non-heart failure (NF) specimens were acquired from the database of Gene Expression Omnibus (GEO). We then identified the differentially expressed genes (DEGs) and analyzed their functions and related pathways by using “Metascape”. Weighted gene co-expression network analysis (WGCNA) was utilized to search for key module genes. Candidate genes were identified by intersecting the key module genes identified via WGCNA with DEGs and further screened via the support vector machine-recursive feature elimination (SVM-RFE) method and the least absolute shrinkage and selection operator (LASSO) algorithm. At last, the biomarkers were validated and evaluated the diagnostic efficacy by the area under curve (AUC) value and further confirmed the differential expression in the IDCM-HF and NF groups using an external database. Results. We detected 490 genes exhibiting differential expression between IDCM-HF and NF specimens from the GSE57338 dataset, with most of them being concentrated in the extracellular matrix (ECM) of cells related to biological processes and pathways. After screening, 13 candidate genes were identified. Aquaporin 3 (AQP3) and cytochrome P450 2J2 (CYP2J2) showed high diagnostic efficacy in the GSE57338 and GSE6406 datasets, respectively. In comparison to the NF group, AQP3 was significantly down-regulated in the IDCM-HF group, while CYP2J2 was significantly up-regulated. Conclusion. As far as we know, this is the first study that combines WGCNA and machine learning algorithms to screen for potential biomarkers of IDCM-HF. Our findings suggest that AQP3 and CYP2J2 could be used as novel diagnostic markers and treatment targets of IDCM-HF.