BCa is one of the most prevalent malignancies of the genitourinary system, which has been identified as the fourth and tenth leading cause of cancer-related deaths in males and females, respectively . The pathogenesis of BCa is complex and involves several factors at multiple steps, including intrinsic genetic factors and extrinsic environmental factors, as with other cancers. Such as smoking, chemical pollution, genetic mutation, and single nucleotide polymorphism, etc [13-15]. Currently, with the rapid development of molecular biology techniques, the mechanism of BCa research and medical treatment have been greatly improved. However, the critical pathogenesis in BCa is incompletely understood, the long-term prognosis of BCa remains poor, patients with BCa usually have no specific symptoms in the early stage, most of them were already at an advanced stage when they are detected . Clinicians are largely faced with advanced and metastatic disease for which few interventions are available. Thus, in order to reduce the risk of death in BCa, highly specific and sensitive biomarkers are urgently needed as they can help in gaining knowledge on the pathogenesis of the disease and determining individualized treatment.
Bioinformatics is a multidisciplinary research area, which is specifically used to identify candidate genes to help understand the genetic basis of diseases and provide new insights for the study of molecular mechanisms. In the present study, we extracted microarray data from the GSE23732 dataset to identify DEGs between cancerous and normal specimens, a total of 396 DEGs comprising 344 upregulated genes and 52 downregulated genes were screened using bioinformatics analysis. KEGG and GO enrichment analyses were used to gain a deeper understanding of potential biological functions and pathways associated with bladder tumorigenesis. GO enrichment results showed that DEGs were mainly enriched in proteinaceous extracellular matrix, extracellular matrix, and extracellular space. These results suggest that most DEGs are enriched in extracellular regions, which are involved in the proliferation and migration. Additionally, for KEGG pathway analysis, the pathways associated with DEG were primarily related to the PI3K-Akt pathway, focal adhesion, and MAPK signaling pathway. The PI3K-Akt signaling pathway plays a crucial role in malignant tumorigenesis and progression. Overactivation of the PI3K/Akt signaling pathway promotes malignant transformation of cells by regulating cell proliferation, apoptosis, migration, immune evasion and drug resistance [17-20]. whereas inhibition of the PI3K/Akt signaling pathway can inhibit the growth cycle of bladder cancer cells . Focal adherence is a membrane related macromolecule assembly that links the actin cytoskeleton and integrin to the extracellular matrix. Previous studies indicated that it plays an important role in the regulation of cell proliferation, migration, and invasion, and is closely associated with the development of various malignant tumors [22-24]. MAPK is an important signaling pathway that mediates extracellular signals to intracellular. Four major MAPK pathways have been identified in mammals: namely p38, c-jun, ERK and ERK5 signaling pathway . The activation of MAPK signaling pathway affects not only tumorigenesis and progression, but also metastasis, invasion and drug resistance [26, 27].
In addition, a PPI network was constructed to investigate the interrelationship of the DEGs using MCC method in cytoHubba, and the ten hub genes were identified, which were MYH11, MYL9, MYLK, TAGLN, CNN1, LMOD1, SMTN, TPM2, ACTG2, and ACTC1. However, only MYLK, CNN1, TAGLN and LMOD1 had relationships with both OS and DFS, so they were subjected to further analysis, where they all had low expression levels in tumor tissues but high expression levels in normal tissues. In addition, their low expression levels were associated with a better prognosis. From these results, we assume that MYLK, CNN1, TAGLN and LMOD1 may function as oncogenes.
MYLK, also referenced as MLCK, is a calmodulin-dependent threonine/serine kinase found on chromosome 3 (3q21.1) which is part of the immunoglobulin gene superfamily and is widely distributed in various eukaryotic and non-muscle cells . MYLK consists of four regions, including the N-terminal actin-binding region, the central kinase region, the calmodulin-binding region and the C-terminal myosin-binding region. The function of MYLK is to enhance the activity of myosin, which in turn promotes the contraction of myosin and the adhesion of stress fibers . MYLK regulates myosin activity through phosphorylation and dephosphorylation of myosin light chains and plays an important role in many biological processes such as proliferation, differentiation and metastasis. Previous studies have shown that overexpression of MYLK is a negative prognostic factor for carcinogenesis and prognosis in different neoplasms, including hepatocellular, gastric, prostate and breast carcinomas [30-32]. Current findings demonstrated that MYLK expressed itself differently in cancerous and normal tissues and was identified as a pivot gene in the PPI network. Patients with high MYLK expression had shorter OS and DFS, these results suggest that MYLK may be a potential oncogene.
CNN1, also known as calmodulin 1, is one of three calmodulin isoforms. The gene encoding this protein is located on human chromosome 19 (19q13.2), and is a marker for differentiation of cardiac and smooth muscle . CNN1 plays an important role in the development of blood vessels through the stabilization of actin and inhibition of cellular motility. For example, it has been pointed out that downregulation of CNN1 may inhibit the development of ovarian cancer . However, our results showed that higher expression of CNN1 correlated with poorer prognosis of BCa. We hypothesized that CNN1 could function as a tumor suppressor gene in the human body, however, with the development and progression of BCa, the hub gene can be captured by tumor cells and transformed into harmful genes, so tumor cell protection becomes a major role of CNN1. From another perspective, it is known that the stromal microenvironment in tumor tissue is different from the stroma of the corresponding normal tissue in many human cancers. Given that studies have focused on CNN1 in BCa, the underlying biological function of CNN1 requires further investigation.
TAGLN, also called SM22, is a part of the calponin family of actin-binding proteins. TAGLN demonstrates great potential to alter motility via its interactions with actin. As an actin-binding protein, aberrant expression of TAGLN has been shown to be associated with other cancers, including, pulmonary adenocarcinoma, and pancreatic cancer [35-37]. Chen Z et al. demonstrated that TAGLN upregulation can promote the migration and invasion of BCa cells via invadopodia formation and the induction of epithelial-mesenchymal transition . This finding is consistent with our research, and we suggest that TAGLN may serve as a potential prognostic biomarker for BCa.
The last hub gene is LMOD1, also known as Leiomodin-1, could be activated by serum response factor (SRF) or myocardin (MYOCD) and functions in smooth muscle cell differentiation . Previous studies reported that aberrant upregulation of LMOD1 as a poor prognostic marker in a variety of tumors, including colorectal cancer, Leiomyosarcoma and prostate cancer [40-42]. The relationship between LMOD1 and the pathogenesis of BCa remain unclear. However, considering the significant role of LMOD1 in tumors and combined with the results of our analysis, we suggest that LODM1 may be a potential biomarker in BCa.
Taken together, the purpose of this study was to detect DEGs involved in tumorigenesis BCa through bioinformatics analysis. A total of 396 DEGs were identified. Subsequently, the key nodes identified in the PPI network constructed with these DEGs and the genes involved in the significant module, including MYLK, CNN1, TAGLN, and LMOD1, may play a major role in the development of BCa, and can function as potential biomarkers for BCa. However, our research contained certain shortcomings. First of all, the data were obtained from public databases, and the quality of the data was not evaluated. Secondly, our research has limited itself to selecting candidate biomarkers associated with pathogenesis and prognosis, which may lead to the neglect of certain information. Last but not least, the results were fully based on the use of publicly available databases, so biological experiments were necessary to validate our findings, such as qPCR, western blot, and subcutaneous tumor model of nude mice, which would be carried out in our future studies.