Pan-Cancer Analysis of VIM Expression in Human Cancer Tissues

In 2020, more than 19 million cancer cases were diagnosed. One of the best paths to more effective treatment with a chance of being cured for patients is early detection. Vimentin (VIM), as an intermediate lament protein, is broadly expressed in mesenchymal cells. VIM is responsible for several biological processes such as cellular component organization and biogenesis, metabolic processes, and biological regulation. A growing body of literature indicates that expression of the VIM gene (VIM) is disrupted in carcinomas during epithelial–mesenchymal transition. Herein, we broadly analyzed the gene expression and promoter methylation prole of VIM in 19 cancer types across The Cancer Genome Atlas (TCGA). Furthermore, the protein–protein interactions (GeneMANIA and Search Tool for the Retrieval of Interacting Genes (STRING) database) and the alteration frequency of mutations (cBioPortal database) in VIM were analyzed. We proved that VIM is overexpressed in seven of the 19 studied cancer types. For two of them, we observed an association of VIM expression with gene promoter methylation. It must be emphasized that VIM overexpression can be a potential diagnostic biomarker in selected types of cancers. presented as transcripts per (TPM), which is a normalization method for RNA sequencing (RNA-seq). The signicant differences in gene expression between primary clinical stages) and normal tissue were analyzed using online statistical analysis, whereby Student’s t-test was used to calculate the level of statistical signicance (p-value). The statistical signicance of observed patterns is presented as p-values (p ≤ 0.05). The data are presented using gures showing the interquartile range (IQR), the median, minimum, and maximum values, and the 25th (lower Q) and 75th (upper Q) percentiles. GBM—glioblastoma multiforme; HNSC—head-and-neck squamous cell carcinoma; KIRC—kidney renal clear cell carcinoma; KIRP—kidney renal papillary cell carcinoma; LIHC—liver hepatocellular carcinoma; LUAD—lung adenocarcinoma; LUSC—lung squamous cell carcinoma; PAAD—pancreatic adenocarcinoma; PCPG— pheochromocytoma and paraganglioma; READ—rectum adenocarcinoma; SARC—sarcoma; STAD—stomach adenocarcinoma; THCA—thyroid carcinoma; THYM—thymoma. correlation VIM expression gene promoter methylation difference ( ∆ β-value = 0.10) for BRCA between normal and cancer tissue at a level of VIM promoter methylation and gene of gene in signicantly (p ≤ 0.05) in cancer tissues in the cases of KIRC and KIRP, with ∆ β-values of 0.14 and 0.07, respectively. These results revealed that lower VIM gene expression may be associated with gene promoter whereas due to a loss of gene promoter methylation in KIRC and KIRP. carcinoma; out of 33 available records, only 19 types of cancer contained complete information about VIM expression, gender, and promoter methylation in TCGA. Overexpression of VIM was detected for seven cancers, namely, CHOL, GBM, HNSC, KIRC, KIRP, LIHC, and PCPG. Moreover, the increased VIM expression has been proved in every stage of the disease for CHOL, HNSC, KIRC, KIRP, and LIHC. Decreased expression of VIM was reported for six types of cancers, namely, BLCA, BRCA, COAD, LUAD, LUSC, and READ. For the others, six cases of nonstatistical signicances were observed where VIM expression was distinct (ESCA, PAAD, SARC, STAD, THYM, and THCA). Studies also showed that the overexpression of VIM was mostly higher among females. The analysis of correlation between VIM expression and gene promoter methylation showed that, among all dened cancers with a signicant difference in gene expression level, the expression of VIM may be regulated by promoter methylation in the cases of KIRC, KIRP, and BRCA. The analysis of protein–protein interactions using GeneMANIA and STRING leads us to suspect that these protein partners predicted to interact with VIM might be involved in the regulation of VIM-mediated cancer progression and prognosis.


Introduction
The vimentin gene (VIM) is a single-copy gene, located on the short arm of chromosome 10 (10p12) (Rittling and Baserga 1987).
The VIM promoter is composed of three different elements which regulate the gene expression. VIM codes for a 57 kDa polypeptide, vimentin, which is one of the most widely expressed and highly conserved proteins of the type III intermediate lament (IF) protein family. The primary biological function of vimentin is to maintain cellular integrity and provide resistance to cellular stress. Moreover, vimentin may form a complex with cell signaling molecules and other adaptor proteins (Eriksson 2009). The cellular localization of vimentin is directly related to its function. The protein forms networks around the cell nucleus and extends from there to the entire cytoplasm, creating a scaffold for cell organelles (Franke 1978;Lowery 2015). The VIM product is a multifunctional protein that can also interact with several other proteins, making it a potential regulator of several physiological processes. In recent years, there has been growing evidence that, during pathological condition such as tissue injury, in ammation, or cancers, vimentin could also be localized outside the cell (Yu 2018). These ndings demonstrate that VIM may be a potential diagnostic biomarker not only in cancer, but also in autoimmune disorders (e.g., Crohn's disease), viral infections (e.g., human immunode ciency virus (HIV)), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Fernandez-Ortega 2016; Yu 2016; Li and Kuemmerle 2020;Li 2020;Zhang 2020;Suprewicz 2021). As an IF protein, vimentin is expressed in many different cells and tissues with a diverse expression abundance. The data from the Human Protein Atlas (https://www.proteinatlas.org/) show that human tissues, such as the ovaries, breasts, lungs, and bone marrow, are characterized by increased VIM expression (Uhlen 2015), while limited expression of VIM is observed in the stomach, rectum, and liver tissue (Uhlen 2015). Within human immune cells, an increased level of VIM was shown in activated macrophages, in contrast to a limited level of expression in T and B lymphocytes, and a lack of expression in Burkitt's lymphoma cell lines (Cain 1983;Perreau 1988;Sommers 1989). Moreover, it has been observed that VIM is expressed in many hormone-independent mammary carcinoma cell lines (Perreau 1988;Sommers 1989).
Current epidemiological data from reports of the World Health Organization (WHO), the International Agency for Research on Cancer (IARC), and the Union for International Cancer Control (UICC) indicate that, over the next two decades, cancer will be the leading cause of death. Cancer diseases are related to unrestrained cell growth which can spread to other parts of the body. Cancer cell invasiveness is, in fact, a key feature of metastatic tumors enabling them to (i) break away from the tumor (separation), (ii) invade through local tissue (invasion), (iii) in ltrate blood (and lymph) vessels (intravasation), (iv) circulate in the blood stream (survival), (v) exit from circulation (extravasation), and (vi) take up residence in vital organs (arrest). Aggressive tumors often metastasize locally or distantly to other organs, causing signi cant morbidity and mortality (Loberg 2005;Siegel 2021). Accordingly,19,292,789 cases of all cancers were reported in 2020 (Siegel 2021). The ve most common types of cancer according to the World Health Organization are breast, lung, colorectal, prostate, and stomach cancer (Fig. 1). As a function of gender, the most often diagnosed are breast, lung, and colorectal cancer in women, and lung, prostate, and colorectal cancer in men (according to the Globocan data source, International Agency for Research on Cancer, World Health Organization, https://gco.iarc.fr/today/home).
A growing body of literature indicates that vimentin controls cell proliferation (Cheng 2016). Extensive research in vimentin-de cient animal models (for example, vim −/− mice) showed that loss of vimentin caused a reduction in brosis and the mesenchymal phenotype of cells (for example, in cholangiocytes), which could be reversed upon vim re-expression (Eckes 1998;Zhou 2019). In contrast, some oncogenes could increase cell proliferation, as a result of a higher vimentin messenger RNA (mRNA) and protein levels (Rathje 2014). Furthermore, VIM expression could be stimulated by lipopolysaccharides (LPS) in the Jurkat cell line and promote apoptosis (Lee 2014). These ndings lead us to suspect that overexpression of VIM could be a key therapeutic target in particular cancers.
Evaluation of VIM expression patterns in normal and cancer tissues can be of considerable value in tumor diagnosis and progression. In the present study, we comprehensively analyzed VIM expression, promoter methylation, and their association with cancer patients using The Cancer Genome Atlas (TCGA) UALCAN database. As previous studies reported a correlation between VIM expression and gene promoter methylation level in different cancer types, such as breast cancer (Ulirsch 2013), colorectal cancer (Li 2018), and gastric cancer (Cong 2016), here in we analyzed whether overexpression of VIM in the cancer types de ned in our study is associated with gene promoter methylation. Additionally, to reveal the potential mechanism of VIM in cancers, we investigated the functional network of the VIM product using GeneMANIA and the protein-protein interaction using the Search Tool for the Retrieval of Interacting Genes (STRING) interactive online tool. These ndings provide useful information about the correlation between VIM expression and cancer diseases.  (Chandrashekar 2017). This user-friendly web platform performs analysis according to the level of gene expression of selected genes and compares them with clinical data from 33 cancer types.
The UALCAN web portal allows correlating the relative expression of selected genes across tumor and normal samples. Moreover, it provides data of patients' gender, age, body weight, race, and many other clinicopathological features such as patient survival or individual cancer stages. TCGA level 3 RNASeq V2 data corresponding to normal tissue and primary tumor samples are presented as a box-and-whisker plot generated by the website. For this work, all values of gene expression level are presented as transcripts per million (TPM), which is a normalization method for RNA sequencing (RNA-seq). The signi cant differences in gene expression between primary tumor (in clinical stages) and normal tissue were analyzed using online statistical analysis, whereby Student's ttest was used to calculate the level of statistical signi cance (p-value). The statistical signi cance of observed patterns is presented as p-values (p ≤ 0.05). The data are presented using gures showing the interquartile range (IQR), the median, minimum, and maximum values, and the 25th (lower Q) and 75th (upper Q) percentiles.

Analysis of VIM Promoter Methylation Using UALCAN Web Portal
The UALCAN web portal was used to analyze differences in VIM promoter methylation level in normal tissue and primary tumor samples. The methylation level, ranging from 0 (unmethylated) to 1 (fully methylated) was estimated using the beta-value, which is the ratio of the methylated probe intensity to the sum of methylated and unmethylated probe intensity. The boxplot available on the UALCAN web portal represented the mean of beta-values from eight CpGs located up to 1500 bp upstream of the VIM transcription start site (TSS). The signi cant differences in promoter methylation level between normal tissue and primary tumor samples were analyzed using Student's t-test. The statistical signi cance of observed patterns is presented as p-values (p ≤ 0.05).

Analysis of VIM Networks Using GeneMANIA and STRING Web Portal
The protein-protein networks of VIM were predicted using GeneMANIA analysis (http://www.genemania.org) (Warde-Farley 2010; Zuberi 2013). This online tool allows visualizing gene networks through bioinformatics methods, such as physical interaction, gene co-expression, gene co-localization, gene enrichment analysis, and website prediction. Functional protein partners for VIM were identi es using the Search Tool for the Retrieval of Interacting Genes (STRING) (version 11.0) analysis web portal (https://stringdb.org/) (Szklarczyk 2019). The score of minimum required interaction was medium con dence (0.4).

Analysis of VIM Mutation Using cBioPortal
Analysis of VIM nonsynonymous mutations in cancer genomes was performed using the cBioPortal for Cancer Genomics (https://www.cbioportal.org/) online platform (Gao 2013). cBioPortal allows performing complex bioinformatics analyses and generating graphical summaries of selected genes. The graphical presentation of mutation analysis constitutes colored plots indicating mutations, fusions, ampli cations, deep deletions, and multiple alterations.

VIM Expression Levels in Distinct Types of Human Cancers
According to TCGA UALCAN web-portal, a higher expression of VIM was found in seven from 19 cancers (Fig. 2). From TCGA database, we retrieved a dataset containing complete information on the VIM expression, gender, and promoter methylation of patients from 19 different types of cancers (Table 1)  It has to be noted that the analysis for BRCA (n = 1097) was performed on the highest number of primary tumor samples, in contrast to CHOL (n = 36), where the number of samples was the lowest. The highest median of the VIM transcript was found for GBM (3474.583), and the poorest was found for LIHC (142.187) ( Table 1).
To further investigate, we performed an analysis of VIM expression according to the clinicopathological features of selected cancers in the UALCAN database . Analysis of VIM expression in cancer tissue as a function of gender only showed signi cant differences between male and female in BRCA, GBM, KIRC, LUAD, LUSC, PAAD, and THCA (p-values: 4.6 × 10 − 3 , 4.0 × 10 − 2 , 3.8 × 10 − 2 , 4.3 × 10 − 2 , 3.9 × 10 − 2 , 4.7 × 10 − 2 , and 3.6 × 10 − 2 , respectively; data not shown). The TPM level of VIM expression was higher for females in BRCA, GBM, LUAD, LUSC, and PAAD. In KIRC and THCA, expression of VIM was signi cantly elevated in the male subgroup (data not shown). We also investigate the correlation between VIM expression and individual cancer stages in groups where VIM expression has been elevated (data not shown). Our analysis con rms that in CHOL, HNSC, KIRC, KIRP, and LIHC the VIM expression has been statistically increased at every cancer stage (Stage from 1 to 4) in comparison to normal tissues (with one exception in stage 3 of CHOL, where was the only one sample). For GBM and PCPG, there was no available information in the database about VIM expression at individual cancer stages. An analysis of the correlation of VIM expression with gene promoter methylation showed that, among all cancers for which the expression of VIM gene was signi cantly lower in cancer tissue than in normal tissue samples, the gene promoter methylation level was signi cantly higher (p ≤ 0.05) in cancer tissue than in normal tissue in the cases of BLCA, BRCA, COAD, and LUSC (Table 2).
However, we only observed a methylation difference (∆β-value = 0.10) for BRCA between normal and cancer tissue at a level that may indicate a biologically signi cant correlation of VIM promoter methylation and gene expression. Furthermore, among all cancers for which we observed overexpression of VIM gene in cancer tissues, the promoter methylation level was signi cantly lower (p ≤ 0.05) in cancer tissues in the cases of KIRC and KIRP, with ∆β-values of 0.14 and 0.07, respectively. These results revealed that lower VIM gene expression may be associated with a gain of gene promoter methylation in BRCA, whereas overexpression of VIM may be due to a loss of gene promoter methylation in KIRC and KIRP.

Gene, Protein Interaction Network and Mutation Analysis of VIM
The protein-protein interaction network showed an association between genes for VIM. The GeneMANIA analysis revealed information about predicted gene functions using web analysis tool (Fig. 6A). The central node representing VIM was surrounded by 20 nodes representing genes that greatly correlated with VIM in terms of physical interaction, co-expression, predictions, colocalization, and genetic interactions. The genes displaying the strongest correlations with VIM included DES, TCAP, TTN, NEB, TMOD1 and SERPINH1. Further analysis, by the STRING database identi ed known interactions for 10 discovered proteins (Fig. 6B). VIM as the center node was associated with apoptotic proteins (caspase-3, -6, -7, and − 8), a transcription factor (signal transducer and activator of transcription 3 (STAT3)), and the muscle-speci c IF desmin (DES). Thus, these protein partners predicted to interact with VIM might be involved in regulating cancer progression and prognosis. Analysis of the frequency of VIM mutations in different cancer types was performed using the cBioPortal database (Fig. 6C). Alterations were found in BLCA (4.87%) and endometrial carcinoma (4.44%), whereas renal carcinoma exhibited the lowest frequency (0.57%). Endometrial carcinoma presented the most mutations (3.24%), in contrast to diffuse glioma, which had the lowest number of mutations (0.19%). Ovarian epithelial tumor showed the highest ampli cation (2.91%), whereas the lowest value was discovered for non-small-cell lung cancer and HNSC (0.19% for both). In nonseminomatous germ cell tumor, alterations appeared only in the form of a deep deletion (1.16%). Interestingly, in adrenocortical carcinoma, we observed an equal frequency of mutations and deep deletions (1.1% for both).

Discussion
One of the main molecular mechanisms involved in oncogenesis and the promotion of cancer progression is epithelial-tomesenchymal transition (EMT) (Meng 2011). During the EMT process, cells lose their epithelial characteristics, especially polarity, and obtain a migratory behavior (Xu 2009). This leads to them altering their shape and exhibiting increased motility (Xu 2009). Besides, persistent in ammation and hypoxia lead to creating a speci c micro-environment in which the interaction between normal and neoplastic cells (like direct contact, secretion of active substances) contributes to a change in the tumor phenotype during EMT (Huber 2005;Hugo 2007;Qureshi 2015). The EMT process is widely described in the literature and plays an essential role in the stages of cancer development. First, cells acquire the ability to migrate, which means that they can separate themselves from the rest of the population. Second, the transition process allows cells to access regional lymph nodes as well as blood vessels; thirdly, it enables the continuous leaving of the original site and the creation of micro-metastases (Huber 2005;Hugo 2007;Qureshi 2015). The acquired mesenchymal phenotype is connected with the expression of mesenchymal cytoskeletal proteins, such as vimentin, which induces the formation of focal adhesion complexes, thereby facilitating cell migration (Imamichi and Menke 2007;Zhao 2009).
In recent years, there has been growing interest in the biological function of vimentin (Menko 2014;Cheng 2016;Ghosh 2018;Patteson 2019;Li and Kuemmerle 2020;Li 2020;Zhang 2020;Suprewicz 2021). As a multifunctional protein, vimentin is differentially expressed in diverse cell types, whereby it may also play a tissue-speci c function. Study on knockout mice (vim −/− ) showed that a lack of vimentin or destabilization of the vimentin network enhances lamellipodia formation in all directions without net cell displacement (Helfand 2011). Cancer is one of the most common causes of death worldwide (Siegel 2021). It is estimated that, in the last year, this problem increased worldwide, mainly due to the limited access to diagnostics and appropriate therapies resulting from the ongoing pandemic. In this work, we analyzed the expression of VIM as a potential biomarker and a therapeutic target in diverse cancers.
The result of our study showed that, out of 33 available records, only 19 types of cancer contained complete information about VIM expression, gender, and promoter methylation in TCGA. Overexpression of VIM was detected for seven cancers, namely, CHOL, GBM, HNSC, KIRC, KIRP, LIHC, and PCPG. Moreover, the increased VIM expression has been proved in every stage of the disease for CHOL, HNSC, KIRC, KIRP, and LIHC. Decreased expression of VIM was reported for six types of cancers, namely, BLCA, BRCA, COAD, LUAD, LUSC, and READ. For the others, six cases of nonstatistical signi cances were observed where VIM expression was distinct (ESCA, PAAD, SARC, STAD, THYM, and THCA). Studies also showed that the overexpression of VIM was mostly higher among females. The analysis of correlation between VIM expression and gene promoter methylation showed that, among all de ned cancers with a signi cant difference in gene expression level, the expression of VIM may be regulated by promoter methylation in the cases of KIRC, KIRP, and BRCA. The analysis of protein-protein interactions using GeneMANIA and STRING leads us to suspect that these protein partners predicted to interact with VIM might be involved in the regulation of VIM-mediated cancer progression and prognosis.
We are aware that our research may have some limitation. The rst is the inconsiderable number of patients, especially in normal tissue samples in CHOL, ESCA, GBM, PAAD, PCPG, and THYM. Given that in some cases our ndings are based on a limited number of data, the result from such analyses should therefore be treated with caution. This nding needs to be con rmed on a larger group of patients. The second limitation is the lack of own analyses that could con rm or contradict conclusions drawn only from bioinformatic analyses. The third is that extracellular VIM expression was not determined in this study. These limitations highlight the di culties that must be considered while conducting the bioinformatic analysis. Further data collection is required to determinate precisely the role of VIM as a potential diagnostic biomarker. In addition, it should be emphasized that the human body is a combination of different types of cells. Even within one organ, we often observe many different types of cells with different biological functions. For example, the liver tissue is a combination of hepatocytes, cholangiocytes, sinusoidal endothelial cells, Kupffer cells and hepatic stellate cells (Puche 2013). Thus, the precise determination of VIM expression in each cell group may provide the basis for a better understanding of its biological function.
The overexpression of VIM seen in numerous cancer studies indicates that gene expression may be directly related to a speci c cancer's aggressiveness (e.g., hepatocellular carcinoma and stomach adenocarcinoma). However, in both of these cancer types, different mechanisms underlying vimentin's contribution were observed (Takemura 1994;Fuyuhiro 2010). In stomach cancer, VIM overexpression is correlated with a signi cantly higher incidence of lymph-node metastasis (Jin 2010). In contrast to previous data, overexpression of VIM in LIHC cells suppresses their proliferative and invasive capabilities (Li 2008). Moreover, the enhanced expression of VIM in colorectal cancer is positively correlated with expanded migration and invasive potential (McInroy and Maatta 2007). Despite the more effective diagnosis of gastric cancers, their mortality rate remains high, with a < 30% survival rate (Zhu 2017). Furthermore, elevated VIM expression has been reported in lung cancer (Helfand 2011), and it is also a prognostic factor of poor survival in non-small-cell lung cancer (Richardson 2012). Moreover, VIM overexpression in breast cancers is correlated with increased invasion and promotes epithelial cell migration (Gilles 1999;Kokkinos 2007). Silencing of VIM in cisplatin-resistant ovarian cancer cell lines A2780-DR and HO-8910 increased the expression levels of exocytotic proteins, which have been proposed as a new therapeutic target for treating drug-resistant ovarian cancer (Huo 2016).
VIM expression can be modulated at the transcriptional level by noncoding RNA, especially microRNA (miRNA). These small molecules, the expression levels of which are disrupted in cancer, could impact target genes. Additionally, VIM is directly or indirectly targeted by miRNA, making it a potential target in therapies. It has been proven that, in breast cancer cells, miR-138 modulates metastasis and EMT (Zhang 2016). Another molecule, miR-122, may affect tissue-remodeling genes, such as VIM or hypoxiainducible factor-1 (HIF-1α), potentially inducing endothelial-mesenchymal transition (Csak 2015). Furthermore, miR-141 and miR-200c regulate vimentin by suppressing its expression in renal tubular epithelial cells (Shi 2014;Huang 2015;Tanaka 2015). Moreover, in gastric cancers, overexpression of miR-1275 could indirectly repress the metastasis and invasion of cancer cells via VIM (Mei 2019). Furthermore, overexpression of miR-1246 inhibited the activities of vimentin and N-cadherin through inhibiting EMT in prostate cancer (Bhagirath 2018). Nevertheless, according to miRTarBase (http://mirtarbase.mbc.nctu.edu.tw/php/index.php), which is the starting point for many researchers, VIM is only a target gene for human miRNAs miR-9, -138, -30a, -26b, -17, -16, -1301, -615, -3605, -378a, and − 506. The discovery of miRNAs has offered great hope for the diagnosis, prognosis, and potential prediction of many diseases, including cancers.
Recent studies also showed that vimentin could play a crucial role in cancer development and subsequent reaction of the immune system. Researchers suggest that vimentin is involved in the apoptosis of neutrophils and lymphocytes (Morishima 1999;Byun 2001;Lavastre 2002;Moisan and Girard 2006;Hsu 2014). Interestingly, Su et al. (Su 2019) also reported a positive role of vimentin in lymphocyte apoptosis, which may serve as a potential serum biomarker for sepsis prognosis. Moreover, vimentin has also been proposed as a possible cellular target for the treatment of coronavirus disease 19 (COVID-19) (Li 2020;Zhang 2020). Because vimentin is suggested as a co-receptor for the entry of SARS-CoV-2 into cells, drugs that decrease the expression of vimentin can be used to treat patients with COVID-19 (Yu 2016).
On one hand, VIM could represent a good biomarker with diagnostic implications when it is overexpressed in speci c cancer types.
On the other hand, we assume that the decreased expression of VIM could potentially be key for therapeutic approaches. This study only used bioinformatics analyses available on online databases. Furthermore, investigations of vimentin during carcinogenesis are necessary to optimize experimental and clinical therapeutic approaches for cancer patients. Evaluation of the expression patterns of distinct genes in normal and cancer tissues may be of superior value in tumor diagnosis and prognosis. Since the spread of cancer cells is considered to be one of the most important causes of disease progression, treatment failure, and consequently patient death, identifying markers which allow rapid detection of this process can be a breakthrough in cancer treatment. A comprehensive approach which takes into consideration the interactions between molecular pro les and the metastasis of cancer cells might also allow for the development of personalized therapy. Lastly, using the databases highlighted in this study, researchers could explore additional signaling networks in cancer or other diseases, including viral infections.

Conclusions
In the current study, we used several online bioinformatics platforms and web tools (TCGA UALCAN, GeneMANIA, STRING, and cBioPortal) to conduct a systematic analysis of VIM expression in selected types of cancer. We proved that VIM is overexpressed in CHOL, GBM, HNSC, and KIRC, especially among women. The analysis of correlation between VIM expression and gene promoter methylation demonstrated that VIM expression may be regulated by promoter methylation in three types of cancer (KIRC, KIRP, and BRCA). Our analysis suggests that VIM overexpression may be a potentially novel diagnostic biomarker in selected cancers. Moreover, VIM could be a potential therapeutic target for a further analysis.  Global cancer incidence cases in 2020, worldwide, for both sexes and all ages, according to the Globocan data source by the World Health Organization.