Clear cell renal cell carcinoma (KIRC) is the most common and aggressive malignancy subtype of renal neoplasm that arises from proximal convoluted tubules. It is characterized by poor clinical outcomes and high mortality of patients due to the lack of specific biomarkers for varying stages of the disease and no effective treatment. Proteases are associated with the development of several malignant tumors in humans by their ability to degrade extracellular matrices, facilitating metastasis. Herein, differentially expressed genes in KIRC cases compared to healthy kidneys were screened out from the Gene Expression Profiling Interactive Analysis (GEPIA) database. This data was applied to determine the most elevated protease in KIRC and as a result, A Disintegrin and Metalloproteinase Domain-Like Protein Decysin-1 (ADAMDEC1) was selected. This expression pattern was exclusive for KIRC and not observed for papillary and chromophobe renal cell carcinomas, in which ADAMDEC1 was at the same level in tumors and non-cancer specimens. Furthermore, the ADAMDEC1 significant increase was detected in the fourteen other human malignancies compared to healthy samples, which suggested its strong involvement in cancer development. Next, GEPIA and Pathology Atlas correlated ADAMDEC1 high expression with more advanced tumor grade and shorter survival of KIRC patients. Xena Functional Genomics Explorer presented that ADAMDEC1 could be hypermethylated in some tumor cases and one somatic mutation in the gene sequence was detected. Finally, a Search Tool for the Retrieval of Interacting Genes/Proteins; STRING base was utilized to predict the interactions of ADAMDEC1 with other molecules and construct the signaling network. In summary, ADAMDEC1 showed the tremendous potential to be the predictive marker for the KIRC and its development. Therefore, this review with data analysis can be a good base for further
Proteases, enzymes that break the protein peptide bonds, are located in the cytoplasm, mitochondria, lysosome, and extracellular matrix (
They are responsible for non-specific degradative functions but also can catalyze specific proteolytic processing. Thus proteases are relevant in the control of multiple biological processes in living organisms. Hence, proteases contribute to (i) the fate, localization, and activity of many proteins, (ii) protein-protein interactions, (iii) generation of new bioactive molecules, (iv) cellular information processing (v) molecular signal pathways (
A Disintegrin and Metalloprotease-Like Decysin 1 (ADAMDEC1) is a unique, highly conserved secreted metalloprotease with a very rare zinc-binding motif (HEXXHXXGXXD) within the metalloprotease domain (
Renal cell carcinoma (RCC) accounts for about 3% of adult malignancies, with an accelerating trend (increasing 2%–3% per decade) (
Here, all up-regulated proteases were screened in 623 cases of KIRC based on the Gene Expression Profiling Interactive Analysis (GEPIA) database. Analysis elucidated ADAMDEC1 as the strongest accelerated protease in KIRC compared to healthy kidney tissues. This expression pattern was exclusive for KIRC subtype and distinguished it of chromophobe (KICH) and papillary renal (KIRP) cell carcinomas, which presented a similar ADAMDEC1 level in normal and tumor specimens. Furthermore, according to Pathology Atlas and GEPIA, the ADAMDEC1 expression level increased gradually as the tumor stage and correlated with the shorter survival of KIRC patients. Interestingly, ADAMDEC1 was elevated in other 14 types of tumors, including glioblastoma, breast, cervical, lung and others.
Additionally, Xena Functional Genomics Explorer showed that ADAMDEC1 expression could be modified by hypermethylation and one somatic mutation was detected in the gene sequence. Finally, a Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) base was used to predict the interactions of ADAMDEC1 with other proteins and visualize the signaling network.
This work points out the perspective role of ADAMDEC1 in KIRC and its particular implementation of patient outcomes. In addition, ADAMDEC1 showed the potential for experimental analysis to confirm its diagnostic value and molecular target for KIRC.
ADAMDEC1 mRNA sequence was discovered in dendritic cells of human tonsils and categorized into the ADAM family (
Physiologically, the highest expression of ADAMDEC1 was found in the gastrointestinal, expressed predominantly in the macrophages in the lamina propria. The lower intensity of ADAMDEC1 was detected in seen, lymph nodes, tonsils, spleen, urinary bladder and placenta (
The whole-genome transcriptomic analysis associated ADAMDEC1 expression deviations with Crohn’s disease (
ADAMDEC1 downregulation in the inflamed ileal biopsy samples collected from patients with Crohn’s disease compared to healthy controls was detected. This correlation was independent of the degree of mucosal inflammation, thus underlying ADADEC1 role in the pathogenesis of this disease (
About 24 times enhanced ADAMDEC1 level was detected in fibroblast-like synovial cells isolated from joint tissue taken from patients with rheumatoid arthritis (
Next, the enhanced presence of ADAMDEC1 in the circulating monocytes was found to have the third significant positive association with the occurrence of atherosclerotic plaques in the common carotid artery. Thus, it can suggest the potential function of ADAMDEC1 in atherosclerosis and plaque instability development (
In the context of cancerogenesis, the drastic reduction of ADADEC1 in the colorectal adenoma compared to the normal colorectal tissues was associated with poor prognosis of patients. However, it was not connected with the loss of macrophages in tissues, verified by CD68 expression (
Analysis of patients with craniopharyngioma revealed accelerated ADAMDEC1 expression in collected specimens compared to normal brain tissues. The primary craniopharyngioma-derived cells treated with an anti-estrogen drug, tamoxifen, reduced tumor cell proliferation and also the expression of ADAMDEC1 mRNA/protein levels (
A potential mechanistic role for ADAMDEC1 in developing oral squamous cell carcinoma (OSCC) has been shown in experiments based on EGF-receptor (EGFR) activation. An ectopic expression of EGFR is detected in approximately 90% of OSCC, and it is a factor that can drive an aggressive phenotype and contribute to decreased response to radiotherapy. The thrombin-stimulated platelets were shown to secrete ADAMDEC1, resulting in the cleavage of the platelet membrane-bound pro-EGF. The soluble EGF then resulted in a migratory and invasive phenotypic shift in the OSCC via EGFR signaling (
Finally,
RCC is originated from the renal epithelium and accounts for >90% of all kidney malignancies. The disease encompasses >10 histological and molecular subtypes, of which KIRC is most common (70%–80%; accounts for most cancer-related deaths), next, papillary (10%–15%), chromophobe (5%–10%) and collecting duct (1%) RCC (
Approximately 2%–3% of all RCC are hereditary and several autosomal dominant syndromes (e.g., Hippel–Lindau disease) are described. Well-validated targets, including VHL, VEGFR and mTOR and pathways such as HGF/c-MET and Wnt/β-catenin, are strongly related to RCC pathogenesis (
RCC is a disease with complex etiologies, which the combined effect of multiple genes may cause. In this context, VHL (von Hippel-Lindau), p53, p16, p21 and p27 were shown as the primary tumor suppressor genes in RCC, in which VHL and p53 were certified to result in the development of RCC (
Recently the genetic profiling of human RCC has increasingly been used to identify the potential of epigenetic regulatory mechanisms. It was shown that single-stranded molecules (lncRNA, miRNA) (
DNA methylation involves the covalent transfer of a methyl group to the C-5 position of the cytosine DNA ring by DNA methyltransferases and causes gene silencing. The genome-wide DNA methylation study in RCC identified increased global methylation in more aggressive cancer types and a potential risk factor associated with malignant transformation. The variations in sequence hypermethylation were dependents on medical aspects, such as aggressive cancer, tumor size, etc.
The potential therapeutic targets, such as small-molecule multikinase inhibitors that target VEGF receptors (sunitinib and sorafenib), the anti-VEGF antibody bevacizumab, and a mammalian target of rapamycin inhibitor temsirolimus, still are not efficient enough in the KIRC currency and chemioresistance is often observed (
The online database Gene Expression Profiling Interactive Analysis (GEPIA;
ADAMDEC1 expression level was analyzed in 16 other human tumors at the same way.
Protease list was downloaded from MEROPS The Peptidase Database (
ADAMDEC1 expression level with tumor grade information was collected from Pathology Atlas (
By GEPIA the ADAMDEC1 ectopic expression was correlated with survival of KIRC patients. The Kaplan-Meier plots log-rank allowed for identification of predictive value of analyzed gene.
By USC Xena Browser (
The potential interactions of ADAMDEC1 with other molecules was visualized by The Search Tool for the Retrieval of Interacting Genes - STRING database (
Using the GEPIA database, all significantly up-regulated genes in 623 KIRC cases compared to the healthy cohort (100 samples) were listed. Next, by MEROPS The Peptidase Database, all changed proteases were selected and a shortlist of twentieth strongest changed proteases is included below (
Symbols | Gene description | Fold change = Tumor expression/ |
---|---|---|
A Disintegrin and Metalloproteinase Domain-Like Protein Decysin-1 | 30.6 | |
Stanniocalcin 2 | 29.07 | |
Granzyme K | 13.2 | |
Granzyme H | 11.47 | |
Proprotein Convertase Subtilisin/Kexin Type 6 | 10.30 | |
Granzyme A | 10.24 | |
Cathepsin W | 10.00 | |
Tryptase Beta 2 | 8.94 | |
Calpain 12 | 8.31 | |
Matrix Metallopeptidase 9 | 7.25 |
The strongest changed
Further,
To investigate the possible relationship between hypermethylation and ADAMDEC1 expression, an analysis of methylation among KIRC cases was performed using USC Xena browser (
Additionally, the somatic mutations were checked and missense variant p.W23R/substitution T to C (hg38 ch8:24,384,571) in one case was detected (
Proteins and protein-protein interactions form the backbone of the cellular complex machinery. Thus, for the full understanding of biological phenomena, the full network needs to be considered. The Search Tool for the Retrieval of Interacting Genes-STRING database collected scored and integrated all publicly available sources of protein-protein interaction information, and to complemented these with computational predictions. The STRING database uses protein-protein co-occurrence as one type of text mining evidence for protein interactions. Text mining (text data mining) transforms unstructured text into a structured format to identify meaningful patterns and new insights. Text mining systems are designed to extract information from the text in a domain-oriented manner (
Here, STRING was used to seek potential interactions between ADAMDEC1 with other molecules (
As the outcome, the co-expression was found for CXCL9 and SLAMF9. Text mining systems showed the interactions with proteins, including DUOXA1, ZNF511, CXCL9, KNDC1, GPR123, DUOX2A, SMPDL3A, SLAMF8, ERIN1, TACSTD2, with a different score value.
Recently, ADAMDEC1 has been connected with the development of varied human diseases, including cancers. Herein, the presented review with database analysis demonstrates the first evidence for positive relations of ADAMDEC1 expression with KIRC cases and its worse outcomes. It can implicate the potential role of ADAMDEC1 in the pathogenesis of KIRC. The presented findings support the further experimental analysis of ADAMDEC1 as a KIRC biomarker and suggest its essential function in diagnosing and promoting KIRC. If validated, this biomarker can significantly facilitate the introduction of new therapies based on protease inhibition that profoundly affects the efficient treatment of KIRC patients. Additionally, this knowledge can be helpful in research based on specific protease inhibitors against KIRC development.
renal cell carcinoma
clear cell renal cell carcinoma
A Disintegrin and Metalloprotease-Like Decysin
Gene Expression Profiling Interactive Analysis database
squamous cell carcinoma
von Hippel-Lindau
vascular endothelial growth factor
breast invasive carcinoma
cervical squamous cell carcinoma and endocervical adenocarcinoma
lymphoid neoplasm diffuse large B-cell lymphoma
esophageal carcinoma
glioblastoma multiforme
head and neck squamous cell carcinoma
lung adenocarcinoma lung squamous cell carcinoma
ovarian serous cystadenocarcinoma
pancreatic adenocarcinoma
skin cutaneous melanoma
stomach adenocarcinoma
testicular germ cell tumors and uterine
kidney chromophobe
kidney renal papillary cell carcinoma
protein-protein interaction