OMICS: A Journal of Integrative Biology

Cigarette smoking is the major cause of chronic inflammatory diseases such as chronic obstructive pulmonary disease (COPD). It is paramount to develop pharmacological interventions and delivery strategies against the cigarette smoke (CS) associated oxidative stress in COPD. This study in Wistar rats examined cysteamine in nanoemulsions to counteract the CS distressed microenvironment. In vivo, 28 days of CS and 15 days of cysteamine nanoemulsions treatment starting on 29th day consisting of oral and inhalation routes were established in Wistar rats. In addition, we conducted inflammatory and epithelial-to-mesenchymal transition (EMT) studies in vitro in human bronchial epithelial cell lines (BEAS2B) using 5% CS extract. Inflammatory and anti-inflammatory markers, such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, IL-1β, IL-8, IL-10, and IL-13, have been quantified in bronchoalveolar lavage fluid (BALF) to evaluate the effects of the cysteamine nanoemulsions in normalizing the diseased condition. Histopathological analysis of the alveoli and the trachea showed the distorted, lung parenchyma and ciliated epithelial barrier, respectively. To obtain mechanistic insights into the CS COPD rat model, “shotgun” proteomics of the lung tissues have been carried out using high-resolution mass spectrometry wherein genes such as ABI1, PPP3CA, PSMA2, FBLN5, ACTG1, CSNK2A1, and ECM1 exhibited significant differences across all the groups. Pathway analysis showed autophagy, signaling by receptor tyrosine kinase, cytokine signaling in immune system, extracellular matrix organization, and hemostasis, as the major contributing pathways across all the studied groups. This work offers new preclinical findings on how cysteamine taken orally or inhaled can combat CS-induced oxidative stress.

For precision in clinical oncology practice, detection of tumor-derived peptides and proteins in urine offers an attractive and noninvasive alternative for diagnostic or screening purposes. In this study, we report comparative quantitative proteomic profiling of urine samples from patients with gastric cancer and healthy controls using tandem mass tags-based multiplexed mass spectrometry approach. We identified 1504 proteins, of which 246 were differentially expressed in gastric cancer cases. Notably, ephrin A1 (EFNA1), pepsinogen A3 (PGA3), sortilin 1 (SORT1), and vitronectin (VTN) were among the upregulated proteins, which are known to play crucial roles in the progression of gastric cancer. We also found other overexpressed proteins, including shisa family member 5 (SHISA5), mucin like 1 (MUCL1), and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. Using a novel approach for targeted proteomics, SureQuant, we validated changes in abundance of a subset of proteins discovered in this study. We confirmed the overexpression of vitronectin and sortilin 1 in an independent set of urine samples. Altogether, this study provides molecular candidates for biomarker development in gastric cancer, and the findings also support the promise of urinary proteomics for noninvasive diagnostics and personalized/precision medicine in the oncology clinic.

Prostate cancer (PCa) represents a huge public health burden among men. Many susceptibility genetic factors for PCa still remain unknown. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for PCa risk by assessing 79,194 cases and 61,112 controls of European ancestry in the PRACTICAL, CRUK, CAPS, BPC3, and PEGASUS consortia. We identified 120 splicing introns of 97 genes showing an association with PCa risk at false discovery rate (FDR)-corrected threshold (FDR <0.05). Of them, 33 genes were enriched in PCa-related diseases and function categories. Fine-mapping analysis suggested that 21 splicing introns of 19 genes were likely causally associated with PCa risk. Thirty-five splicing introns of 34 novel genes were identified to be related to PCa susceptibility for the first time, and 11 of the genes were enriched in a cancer-related network. Our study identified novel loci and splicing introns associated with PCa risk, which can improve our understanding of the etiology of this common malignancy.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic disease of the lung with poor prognosis. Fibrosis results from remodeling of the interstitial tissue. A wide range of gene expression changes are observed, but the role of micro RNAs (miRNAs) and circular RNAs (circRNA) is still unclear. Therefore, this study aimed to establish an messenger RNA (mRNA)–miRNA–circRNA competing endogenous RNA (ceRNA) regulatory network to uncover novel molecular signatures using systems biology tools. Six datasets were used to determine differentially expressed genes (DEGs) and miRNAs (DEmiRNA). Accordingly, protein–protein, mRNA–miRNA, and miRNA–circRNA interactions were constructed. Modules were determined and further analyzed in the Drug Gene Budger platform to identify potential therapeutic compounds. We uncovered common 724 DEGs and 278 DEmiRNAs. In the protein–protein interaction network, TMPRSS4, ESR2, TP73, CLEC4E, and TP63 were identified as hub protein coding genes. The mRNA–miRNA interaction network revealed two modules composed of ADRA1A, ADRA1B, hsa-miR-484 and CDH2, TMPRSS4, and hsa-miR-543. The DEmiRNAs in the modules further analyzed to propose potential circRNA regulators in the ceRNA network. These results help deepen the understanding of the mechanisms of IPF. In addition, the molecular leads reported herein might inform future innovations in diagnostics and therapeutics research and development for IPF.

Kidney renal cell carcinoma (KIRC) is the most common type of renal cancer. Kidney malignancies have been ranked in the top 10 most frequently occurring cancers. KIRC is a prevalent malignancy with a poor prognosis. The disease has risen for the last 40 years, and robust biomarkers for KIRC are needed for precision/personalized medicine. In this bioinformatics study, we utilized genomic data of KIRC patients from The Cancer Genome Atlas for biomarker discovery. A total of 314 samples were used in this study. We identified many differentially expressed genes (DEGs) categorized as upregulated or downregulated. A protein-protein interaction network for the DEGs was then generated and analyzed using the Search Tool for the Retrieval of Interacting Genes plugin of Cytoscape. A set of 10 hub genes was selected based on the Maximum Clique Centrality score defined by the CytoHubba plugin. The elucidated set of genes, that is, CALCA, CRH, TH, CHAT, SLC18A3, FSHB, MYH6, CAV3, KCNA4, and GBX2, were then categorized as potential candidates to be explored as KIRC biomarkers. The survival analysis plots for each gene suggested that alterations in CHAT, CAV3, CRH, MYH6, SLC18A3, and FSHB resulted in decreased survival of KIRC patients. In all, the results suggest that genomic alterations in selected genes can be explored to inform biomarker discovery and for therapeutic predictions in KIRC.