RhoJ promotes the progression of clear cell renal cell carcinoma via the TNF-α/NF-κB axis

Introduction

Clear cell renal cell carcinoma (ccRCC), as the most common type of kidney cancer, is characterized by diverse molecular features and poor prognosis (1). Due to the widespread use of abdominal imaging diagnostic techniques, the incidence of ccRCC has been rising in recent decades. Nearly 20% of patients experience relapse in distant sites, despite undergoing radical surgery. Although tyrosine kinase inhibitors (TKIs) have improved ccRCC prognosis, many patients cannot achieve complete remission (2,3). Thus, deep exploration of the molecular pathology may help to elucidate ccRCC biological behaviors and develop effective drugs for ccRCC.

Ras homology (Rho) GTPases function as switches between guanosine triphosphate (GTP) and guanosine diphosphate (GDP), regulating tumor metabolism, senescence, and cell stemness, and therefore impact tumor development and progression (4). Ras homolog family member J (RhoJ), a member of Rho GTPases family, is also known as TC-like 10 (TCL) because over 80% of its amino acids are similar to Ras homolog family member Q (RhoQ, TC10) and cell division cycle 42 (CDC42) (5). RhoJ is crucial for multiple cellular processes, such as vesicular transport, endothelial cell movement, tube formation, actin contractility regulation, lesion adhesion, and adipocyte differentiation (4,6,7). Several bioinformatics studies have shown a positive correlation between elevated RhoJ and poor prognosis in gastric cancer and non-small cell lung cancer (8,9). Moreover, RhoJ could impact diverse aspects of tumor development and progression, including DNA damage repair, epithelial-mesenchymal transition (EMT), and angiogenesis (10-14). Emerging evidence from recent investigations has demonstrated that endothelial RhoJ-positive vesicles serve as carriers for the transportation of α5β1 integrin (10). This transport mechanism plays a pivotal role in modulating fibronectin fibrillogenesis during the process of angiogenesis. Moreover, in lung cancer, vascular endothelial cells exhibit high expression of RhoJ, which promotes tumor-associated angiogenesis (14). This phenomenon is achieved by inhibiting the Ras homologue family member A/Rho-associated coiled-coil containing protein kinase (RhoA/Rock) signaling pathway, thereby regulating the motility, tube formation, and junctional integrity of vascular endothelial cells. ccRCC is characterized by enhanced tumor-associated angiogenesis, which further underscores the significance of RhoJ in ccRCC research. However, the biological functions and underlying molecular mechanisms of RhoJ in ccRCC remain unexplored. In this study, we found that RhoJ is expressed at higher levels in ccRCC tumor cells than in normal renal tubular epithelial cells. These background details make research on RhoJ more meaningful in ccRCC.

Here, we identified RhoJ as the unique Rho GTPase family member associated with poor prognosis in ccRCC. In ccRCC tissues and cells, the expression of RhoJ is significantly elevated. Furthermore, RhoJ promotes ccRCC proliferation, migration, invasion, and EMT while suppressing ccRCC cell apoptosis. Using RNA sequencing, we found that the tumor necrosis factor-alpha/nuclear factor kappa B (TNF-α/NF-κB) pathway may be associated with RhoJ-mediated malignant phenotypes. Importantly, we identified potential RhoJ inhibitors based on a Food and Drug Administration (FDA)-approved drug library. This study revealed a novel mechanism by which RhoJ facilitates ccRCC progression via the TNF-α/NF-κB axis. Ergotamine, irinotecan, ledipasvir, pazopanib, and avodart targeting RhoJ may serve as promising drugs for ccRCC patients. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-132/rc).

Methods

Cell culture

ccRCC cell lines (A498, 786-O) and 293T cells were cultured using Minimum Essential Medium (MEM), Roswell Park Memorial Institute-1640 (RPMI-1640) and Dulbecco’s modified Eagle medium (DMEM), respectively, under conditions of 37 ℃, 5% CO₂, and 10% fetal bovine serum (FBS; Procell, Wuhan, China). Renal cell adenocarcinoma (RENCA) cells were cultured in RPMI-1640 with 10% FBS, 10% pyruvate, non-essential amino acids, and sodium glutamate. All of the cell lines were sourced from the American Type Culture Collection (ATCC, Manassas, VA, USA). Pyrrolidine dithiocarbamate (PDTC; HY-18738) and phorbol 12-myristate 13-acetate (PMA; HY-18739) were obtained from MedChemExpress (MCE) company (Monmouth Junction, NJ, USA).

Generation of stable RhoJ gene knockout or overexpression cell lines

293T cells were used to produce RhoJ gene knockout or overexpression lentiviruses. Transfection was conducted using the jetPRIME reagent kit (Polyplus, Illkirch-Graffenstaden, France). Puromycin (2 µg/mL) (Beyotime, Jiangsu, China) was used to screen stably transfected cell lines after about 2 weeks. The target sequence for knockdown is provided in Table S1.

Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine, and colony formation assay

For the CCK-8 assay, A498 (5,000 cells) with 100 µL complete culture medium were added in 96-well plates, then 10% CCK-8 reagent (Abbkine, Wuhan, China) was added at 0-, 20-, 40-, 60-, and 80-hours. The 5-ethynyl-2'-deoxyuridine (EdU) assay was performed using the EdU Kit (APExBIO, Houston, TX, USA). Briefly, cells (2×10⁵ cells per well) were seeded in 6-well plates for 24 hours, then cultured with EdU for 3 hours. For the colony formation assay, cells were seeded at 500 cells/well in six-well plates and cultured for 7 days.

Wound healing assay and transwell assay

Cells (5×10⁵ cells per well) were seeded in 6-well plates at and cultured in medium containing 2% FBS. Mitomycin (1 µg/mL) was added to allow cells to adhere for 24 hours. Subsequently, a vertical line was drawn with a 200 µL pipette tip and the scratch was observed at 0- and 24-hours. For Transwell assays, 2×10⁴ cells were seeded with 200 µL of serum-free medium in the upper chamber, with 600 µL of medium containing 10% FBS added to lower chamber. After 24 hours, cells were fixed with 4% paraformaldehyde for 15 minutes and stained with 0.1% crystal violet for 15 minutes.

Cell apoptosis analysis

According to the product manual, supernatants and cells were collected and the apoptosis of cells was detected using the Annexin V-PE Apoptosis Detection Kit [Becton, Dickinson, and Co. (BD), Franklin Lakes, NJ, USA]. All cell suspensions were analyzed using flow cytometer within 1 hour.

Western blot and antibodies

Cells were lysed with radio immunoprecipitation assay (RIPA) containing phenylmethylsulfonyl fluoride (PMSF) and phosphatase inhibitors (Solarbio, Beijing, China). The primary antibodies used in this study included RhoJ (H00057381-M01, Abnova, Taipei, Taiwan); p-p65 (Ser536) [#3033, Cell Signaling Technology (CST), Danvers, MA, USA]; and p65 (#8242T, CST). Vimentin (VIM; #10366), E-cadherin (#20874), N-cadherin (#22018), Snail (#21350), Bax (#50599), Bcl-2 (#12789), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH; #10494) were obtained from Proteintech (Rosemont, IL, USA).

Immunohistochemistry (IHC) staining

After surgical resection, the fresh samples were immediately fixed in formalin. Normal renal tissue was defined as renal cortex more than 1 cm away from the base of the tumor tissue. All tissue samples were carefully reviewed by an experienced pathologist to ensure accurate sampling of both tumor and normal kidney tissue. The diagnosis of ccRCC was confirmed based on a combination of histopathological examination, IHC, and molecular profiling, following the current World Health Organization (WHO) classification criteria for renal cell carcinoma. The nuclear grading of these tumor tissues was evaluated according to the 2016 WHO/International Society of Urological Pathology (ISUP) criteria, with the nuclear grade being 2/3. The Chinese PLA General Hospital approved the study protocol, and all participants provided written informed consent. The samples were incubated with primary antibodies against RhoJ (1:100), CD31 (GB11063-2-100, Servicebio, Wuhan, China, 1:400), CD4 (GB15064-100, Servicebio, 1:400), and CD8α (GB15068-100, Servicebio, 1:400). The proportion of the positive area was calculated using ImageJ (National Institutes of Health, Bethesda, MD, USA). For each sample, three fields of view were randomly captured and the average value was calculated.

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of PLA general hospital (No. S2024-279-01) and informed consent was taken from all the patients.

Enzyme linked immunosorbent assay

A human TNF-α detection kit (Czkewei, Beijing, China) was used for the enzyme-linked immunosorbent assay (ELISA). Supernatants from 786-O cells were collected and stored at −80 ℃ beforehand. The detection procedure was based on the operating instructions and the absorbance was measured at 450 nm.

Quantitative polymerase chain reaction (qPCR) analysis

qPCR analysis was performed using a fluorescence-based qPCR detection system (Bio-Rad, Hercules, CA, USA). The relative quantification of messenger RNA (mRNA) was normalized to human (GAPDH) and calculated using the 2^−ΔΔCT method. Table S2 shows the primer sequences used in this study.

Animal experiments

Animal experiments were performed under a project license (No. S2013-115-01) granted by the ethics board of PLA general hospital, in compliance with the institutional guidelines for the care and use of animals. In this experiment, 8-week-old male Balb/c mice (GemPharmatech, La Jolla, CA, USA) were utilized, and they were kept under 25 ℃ and 12-h/12-h light-dark cycle conditions with free access to water and food. After counting, they were randomly divided into two groups, with five mice in each group. Subsequent experiments were conducted under double-blind conditions. 5×10⁶ RENCA cells were suspended in Matrigel and then injected into the left kidney. Tumors were extracted from the left kidney of each mouse after 4 weeks.

RNA-seq and data analysis

Cellular RNA was prepared and sent to Gene Denovo (Guangzhou, China) for sequencing, and the RNA-seq software from this company was used to detect the whole gene expression profile. Gene expression levels were calculated using transcripts per million (TPM).

Virtual screening analysis and molecular docking

All FDA-approved drugs used for virtual screening were obtained from the DrugBank database. The structure of the RhoJ was generated from Protein Data Bank. Autodock 4.0 software (https://autodock.scripps.edu/) was utilized in docking experiments. The results of docking experiments were visualized via PyMol (https://www.pymol.org/).

Statistical analysis

For the comparison of two groups, statistical analyses were performed using two-tailed unpaired t-tests or the non-parametric Mann-Whitney U test. For multiple group comparisons, analysis of variance (ANOVA) was utilized to assess significant differences among groups. In cellular experiments, each group had three replicates, while in the in vivo animal experiments, each group contained five specimens. Survival analyses were conducted through Kaplan-Meier survival estimation, and the significance of survival differences between groups was evaluated using the log-rank (Mantel-Cox) test. The correlation between the expression levels of the two molecules was calculated using Pearson’s correlation. All statistical computations were executed using GraphPad Prism version 10.0 software (GraphPad Software, San Diego, CA, USA). A P value threshold of less than 0.05 was set as the criterion for statistical significance.

Results

RhoJ is highly expressed in ccRCC and associated with poor prognosis

First, we evaluated the clinical value of the Rho GTPases family in ccRCC patients using the kidney cancer database performed by Huber et al. (15). The results indicated that RhoJ is the only gene that significantly correlated with poor prognosis (P<0.05, Figure 1A,1B). Therefore, we selected RhoJ for further investigation. RhoJ is significantly overexpressed in The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) clinical samples (Figure 1C). Based on clinical samples from our center, we verified that RhoJ is highly expressed in ccRCC (Figure 1D-1F). Also, we detected the expression level of RhoJ in ccRCC cell lines, which indicates that RhoJ is highly expressed in most ccRCC cells (Figure 1G,1H). Collectively, these results suggest a potential oncogenic role of RhoJ in ccRCC, which prompted us to further explore its function in the development and progression of ccRCC.

Figure 1 RhoJ is associated with poor prognosis and overexpressed in ccRCC. (A) The Rho family were subjected to multi-factor Cox regression analysis (left) and forest plot (right). (B) K-M curve of RhoJ in ccRCC patients. (C) Analysis of RhoJ expression in the TCGA-KIRC database. (D) IHC staining of RhoJ in tumor and adjacent tissues (scale bar: 20 µm). (E,F) Western blot analyses of RhoJ in RCC tissues. (G,H) qPCR (G) and western blot (H) analyses RhoJ expression levels in normal and tumor cells. *, P<0.05; ****, P<0.0001. ccRCC, clear cell renal cell carcinoma; CI, confidence interval; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; HR, hazard ratio; IHC, immunohistochemistry; K-M, Kaplan-Meier; Rac, Ras-related C3 botulinum toxin substrate; Rho, Ras-homologous gene family; Rnd, Rho-related novel protein; qPCR, quantitative polymerase chain reaction; TCGA-KIRC, The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma.

RhoJ regulates ccRCC proliferation and tumor growth

We further investigated whether RhoJ affects the development and progression of ccRCC both in vitro and in vivo. Using CCK-8, EdU, and colony formation assays, we found that RhoJ knockdown inhibited ccRCC cell proliferation (Figure 2A-2C). Furthermore, the same experiments were performed using RhoJ-overexpressed ccRCC cells. Consistent with our expectations, RhoJ overexpression apparently promoted the proliferation of ccRCC cells (Figure S1A-S1C). In vivo assay also showed that RhoJ knockdown inhibits orthotopic tumor growth (Figure 2D).

Figure 2 RhoJ knockdown inhibits the proliferation of ccRCC cells in vivo and in vitro. (A) CCK-8 assay assessing the viability of ccRCC cells. (B) Colony formation assay assessing the colony-forming ability of ccRCC cells (crystal violet staining). (C) EdU proliferation assay assessing the proliferation levels of ccRCC cells. (D) Tumor size of orthotopic xenograft models. (E,F) Cell cycle analysis of A498 (E) and 786-O (F) cells. (G) Apoptosis analysis of A498 and 786-O cells. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001; ns, not significant, P≥0.05. ccRCC, clear cell renal cell carcinoma; CCK-8, Cell Counting Kit-8; EdU, 5-ethynyl-2'-deoxyuridine; NC, negative control; RhoJ, Ras-homologous gene family member J.

Rapid cell cycle progression accounts for cancer proliferation (16). Thus, we examined the effect of RhoJ knockdown and overexpression on the cell cycle. The proportion of S-phase ccRCC cells was apparently decreased after knockdown of RhoJ, whereas the proportion of S-phase was significantly increased in RhoJ-overexpressed cells (Figure 2E,2F, Figure S1D). Escaping apoptosis is another characteristic of tumor to obtain limitless growth (17). We also analyzed the apoptosis of ccRCC cells in RhoJ overexpression and knockdown cells, which indicated that the apoptosis ratio was significantly decreased in RhoJ overexpression ccRCC cells (Figure 2G). However, the apoptosis ratio was increased after knockdown of the expression of RhoJ (Figure S1E). Our findings indicate that RhoJ is required for RCC proliferation in vitro and in vivo.

RhoJ promotes ccRCC migration, invasion, and EMT

Next, we tested the influence of RhoJ on ccRCC migration and invasion. The wound healing assays indicated that RhoJ knockdown inhibited the capability of ccRCC cell migration (Figure 3A,3B). Similarly, we conducted Transwell assays and found that RhoJ knockdown decreased the capability of ccRCC cell migration and invasion (Figure 3C,3D). Conversely, after overexpressing the expression of RhoJ, the capability of tumor migration and invasion was significantly increased (Figure S2A,S2B).

Figure 3 RhoJ knockdown inhibits migration, invasion, and EMT in ccRCC cells. (A,B) Effect of RhoJ knockdown on ccRCC cell migration was assessed via wound healing assay. (A) The results were observed under an optical microscope and calculated within ImageJ. (B) Quantification of migration rate. (C,D) Effect of RhoJ knockdown on ccRCC cell migration and invasion was assessed via Transwell assay with crystal violet staining (scale bar, 20 µm; C), quantification of migration rate (D). (E) Correlation analysis between RhoJ and Bcl-2, SNAI1, VIM, and ZEB1 based on TCGA-KIRC database. (F) Western blot analyses of EMT and apoptosis-related markers in RhoJ knockdown and overexpression ccRCC cells. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001. ccRCC, clear cell renal cell carcinoma; EMT, epithelial-mesenchymal transition; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; NC, negative control; RhoJ, Ras-homologous gene family member J; SNAI1, snail family transcriptional repressor 1; TCGA-KIRC, The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma; TPM, transcript per million; VIM, Vimentin; ZEB1, zinc finger E-box binding homeobox 1.

EMT is a vital mechanism associated with cell migration and invasion (18,19). Therefore, we performed the correlation analysis between RhoJ and EMT markers, including VIM and snail family transcriptional repressor 1 (SNAI1) based on TCGA KIRC clinical samples. The expression of RhoJ was shown to be positively correlated with EMT markers (Figure 3E). To verify these results, we examined the expression of EMT-related markers and found that RhoJ overexpression increased the protein levels of Snail, VIM, and N-cadherin and decreased the expression of E-cadherin. However, the expression of Snail, VIM, and N-cadherin were inhibited and that of E-cadherin was increased in RhoJ knockdown ccRCC cells (Figure 3F). Additionally, we also detected markers related to apoptosis, including B-cell lymphoma-2 (Bcl-2) and BCL2-associated X protein (Bax), which showed that RhoJ knockdown promoted Bax expression, but inhibited Bcl-2 expression. In summary, RhoJ could regulate ccRCC EMT and promote ccRCC cell invasion and migration.

RhoJ promotes ccRCC progression by regulating the TNF-α/NF-κB axis

To further explore the regulatory mechanism of RhoJ in ccRCC, we conducted RNA sequencing assay to compare the transcriptome of control and RhoJ knockdown ccRCC cells. Through Venn analysis, we intersected 794 differentially expressed genes (DEGs) from two groups (Figure 4A). Based on these DEGs, we performed the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, which indicated that the TNF signaling pathway was enriched (Figure 4B). The TNF signaling pathway plays a critical role in regulating tumors, which is known to promote tumor growth, migration, and invasion (20). Therefore, we first used ELISA assay to detect TNF-α level in the supernatant of ccRCC cell culture, which indicated that TNF-α was decreased in the RhoJ knockdown ccRCC cells, whereas its level increased in RhoJ overexpression ccRCC cells (Figure 4C). Subsequently, we used qPCR to examine genes among TNF pathway [including tumor necrosis factor (TNF), TNF receptor superfamily member 1A (TNFRSF1A), TNF receptor-associated factor 2 (TRAF2), and mitogen-activated protein kinase kinase kinase 4 (MAP3K4)], which showed that these genes were significantly downregulated in RhoJ knockdown ccRCC cells (Figure 4D).

Figure 4 RhoJ regulates ccRCC progression through the TNF-α signaling pathway. (A) 794 intersected differentially expressed genes identified via Venn analysis. (B) KEGG enrichment analysis for the differentially expressed genes. (C) ELISA analyses of TNF-α in the supernatant of RhoJ knockdown and overexpression ccRCC cells. (D) qPCR analyses of TNF, TNFRSF1A, TRAF2, and MAP3K4 expression levels in RhoJ knockdown ccRCC cells. (E) Western blot analyses of phosphorylated p65 and total p65 in RhoJ knockdown and overexpression ccRCC cells. ***, P<0.001; ****, P<0.0001. ccRCC, clear cell renal cell carcinoma; ELISA, enzyme-linked immunosorbent assay; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; KEGG, Kyoto Encyclopedia of Genes and Genomes; OE, over expression; qPCR, quantitative polymerase chain reaction; RhoJ, Ras-homologous gene family member J; siNC, small interfering RNA negative control; TNF-α, tumor necrosis factor-α.

As a classic downstream molecule of TNF-α, NF-κB plays an important regulatory role in tumor progression (21). Thus, we examined the role of NF-κB in RhoJ-mediated malignant phenotypes. We first detected the expression levels of total nuclear factor NF-kappa-B P65 subunit (p65) and phosphorylation of p65 (p-p65, Ser536) in RhoJ knockdown and overexpression ccRCC cells. The total levels of p65 were unchanged, but the p-p65 level decreased in RhoJ knockdown ccRCC cells. Conversely, the p-p65 level increased in RhoJ overexpression ccRCC cells (Figure 4E).

To further confirm whether the TNF-α/NF-κB axis is required for RhoJ-mediated ccRCC progression, we used PDTC, the specific inhibitor of NF-κB, and NF-κB agonist PMA to perform the rescue experiments. We found that PDTC could significantly inhibit p-p65 level caused by RhoJ overexpression. Meanwhile, the addition of PDTC could increase the expression of E-cadherin and inhibit the expression of VIM caused by RhoJ overexpression (Figure 5A,5B). Subsequently, using ELISA assay, we found that PDTC could significantly inhibit the increased TNF-α caused by RhoJ overexpression (Figure 5C). Phenotypically, we noticed that PDTC could partially rescue cell proliferation and migration induced by RhoJ overexpression in ccRCC cells (Figure 5D,5E).

Figure 5 RhoJ mediates the progression of ccRCC cells through TNF-α/NF-κB axis. (A) qPCR analyses of RhoJ and RELA proto-oncogene (RELA) expression levels in RhoJ overexpression ccRCC cells treated with PDTC or not. (B) WB analyses of RhoJ, p-p65, T-p65, Vimentin and E-cadherin in RhoJ overexpression ccRCC cells treated with PDTC or not. (C) ELISA analyses of TNF-α in the supernatant of RhoJ overexpression ccRCC cells treated with PDTC or not. (D) CCK-8 assay detecting the activity of RhoJ overexpression ccRCC cells treated with PDTC or not. (E) Transwell migration assay with crystal violet staining detecting the migration ability of RhoJ overexpression ccRCC cells treated with PDTC or not (scale bar, 20 µm). (F) qPCR analyses of RhoJ and RELA expression levels in RhoJ knockdown ccRCC cells treated with PMA or not. (G) WB analyses of RhoJ, p-p65, T-p65, Vimentin, and E-cadherin in RhoJ knockdown ccRCC cells treated with PMA or not. (H) ELISA analyses of TNF-α in the supernatant of RhoJ overexpression ccRCC cells treated with PMA or not. (I) CCK-8 assay detecting the activity of RhoJ knockdown ccRCC cells treated with PMA or not. (J) Transwell migration assay with crystal violet staining detecting the migration ability of RhoJ knockdown ccRCC cells treated with PMA or not. Scale bar, 20 µm. *, P<0.05; **, P<0.01; ***, P<0.001; ****, P<0.0001; ns, not significant, P≥0.05. CCK-8, Cell Counting Kit-8; ccRCC, clear cell renal cell carcinoma; DMSO, dimethyl sulfoxide; ELISA, enzyme-linked immunosorbent assay; NC, negative control; PDTC, pyrrolidine dithiocarbamate; PMA, phorbol 12-myristate 13-acetate; qPCR, quantitative polymerase chain reaction; TNF-α, tumor necrosis factor-α; WB, western blot.

In RhoJ knockdown ccRCC cells, PMA could increase p-p65 level caused by RhoJ knockdown. Also, the addition of PMA could increase the expression of VIM and inhibit the expression of E-cadherin caused by RhoJ knockdown as well (Figure 5F,5G). Meanwhile, PMA could rescue TNF-α level caused by RhoJ knockdown (Figure 5H). Similarly, PMA could partially rescue cell proliferation and migration induced by RhoJ knockdown (Figure 5I,5J). Our results indicated that RhoJ might regulate ccRCC progression through the TNF-α/NF-κB axis.

Available drugs targeting RhoJ are selected through virtual screening

Currently, there are no commercially available RhoJ inhibitors for clinical application. Therefore, we sought to identify potential RhoJ inhibitors by performing molecular docking-based virtual screening from 1,597 FDA-approved drugs (Figure 6A). First, we found that the Lys 165, Lys 198, Lys 200, Val 161, and Ala 164 are common amino acids binding to the drugs. Then, using Autodock Vina and the docking score, 271 FDA-approved drugs were identified (table available at https://cdn.amegroups.cn/static/public/tau-2025-132-1.xlsx). Among these drugs, ergotamine, irinotecan, dihydroergotamine, and ledipasvir were the top 4 potent drugs that could bind to the active pocket of RhoJ (Figure 6B-6E). Noticeably, pazopanib, a targeted drug that used in patients with advanced or metastatic kidney cancer (24), was also identified in this study (Figure 6F). Avodart capsule, also known as dutasteride, is an oral formulation with good solubility and bioavailability (25). Here, we found that avodart could target RhoJ as well (Figure 6G). These results offer a preclinical proof of concept that targeting RhoJ might be a new method to ccRCC therapy.

Figure 6 Available drugs targeting RhoJ are selected through FDA-approved drugs. (A) Flow diagram of the screening and selection process. (B-G) Docking pattern of FDA-approved drugs with RhoJ. Visualization was performed using PyMOL and Discovery Studio 2023 (22,23). FDA, Food and Drug Administration.

Discussion

ccRCC is the most common subtype of kidney cancer. Despite advancements in surgical techniques, targeted therapies, and immunotherapies, the prognosis for advanced ccRCC patients remains poor (26,27). Therefore, there is an urgent need to identify novel treatment modalities and drugs to enhance the efficacy of ccRCC treatment.

Rho GTPases are small G proteins, which could regulate chemoresistance, angiogenesis, and metabolic reprograming. The most commonly studied members of Rho GTPases consist of more than 20 protein members. It has been reported that members of the Rho GTPases family could regulate diverse malignant processes. In lung adenocarcinoma, RhoQ could mediate tumor EMT through transforming growth factor beta 1 (TGF-β1) (28). In gastric cancer, mutated RhoA induces actin/cytoskeletal rearrangements and promotes the activity of focal adhesion formation (29). However, few studies on the Rho family in ccRCC have been reported.

In this study, we found that RhoJ is the only member of Rho GTPases family that is significantly correlated with poor prognosis in ccRCC patients. Moreover, RhoJ is highly expressed in ccRCC tissues and cell lines. RhoJ, a member of the CDC42 subfamilies, has recently emerged as a critical regulator of cytoskeleton and actomyosin contractility (30). Previous studies have found that RhoJ is also overexpressed in various malignancies and negatively associated with a poor prognosis in glioblastoma, breast cancer, lung cancer, gastric cancer, and melanoma (8,9,12,31). We also explored the biological functions of RhoJ in ccRCC. In vitro and in vivo experiments all demonstrated that RhoJ enhances ccRCC proliferation, migration, invasion, and tumor growth. Further, upregulated RhoJ could accelerate cell cycle progression, inhibit apoptosis, and enhance ccRCC EMT. These results suggest that RhoJ is an oncogene that promotes ccRCC progression.

We then investigated the mechanism of RhoJ in promoting ccRCC progression. Using RNA sequencing, we found that RhoJ may regulate TNF signaling pathway. The TNF signaling pathway plays a complex role in cancer biology, affecting tumor development, progression, and treatment outcomes (32). Among TNF signaling pathways, TNF-α is the most crucial molecular, which plays an essential role in cancer progression (33). Here, we found that RhoJ promotes the expression and release of TNF-α in ccRCC, which suggests that TNF-α expression could be modulated by RhoJ.

Current studies have found that TNF-α exerts its biological effects primarily through the activation of NF-κB, a key transcription factor. Upon TNF-α stimulation, the NF-κB signaling pathway is activated, resulting in the expression of genes associated with cell proliferation, angiogenesis, and anti-apoptotic responses (34). Here, we found that RhoJ could promote the phosphorylation of NF-κB and EMT-related markers, including E-cadherin and VIM. To further confirm if the TNF-α/NF-κB axis is required for RhoJ-mediated ccRCC progression, we used PDTC and PMA, the respective inhibitor and agonist of NF-κB, to explore whether the effect of RhoJ was regulated by the TNF-α/NF-κB axis. We found that both PDTC and PMA could significantly rescue the phosphorylation level of P65 caused by RhoJ overexpression or knockdown. Meanwhile, the addition of PDTC and PMA could rescue the expression of TNF-α, E-cadherin, and VIM caused by RhoJ overexpression or knockdown. Importantly, we noticed that PDTC and PMA could also rescue cell proliferation and migration induced by RhoJ in ccRCC cells. In glioma and colon cancer, activation of TNF-α/NF-κB signaling promotes tumor progression by enhancing cell proliferation, migration, and EMT (35,36), which is consistent with our findings in ccRCC. Therefore, our data indicated that RhoJ might regulate ccRCC progression through the TNF-α/NF-κB axis. Research has shown that RhoA, another member of the Rho GTPase family, stimulates the transcription of inflammatory cytokines such as TNF-α and interleukin-6 (IL-6) via the Rock1/Rock2 signaling axis during neuroinflammation. This regulatory effect hinges on the promotion of NF-κB nuclear translocation (37). These insights into RhoA’s function offer valuable clues regarding the mechanism underlying RhoJ-mediated TNF-α release. Nevertheless, comprehensive elucidation of the precise molecular mechanisms necessitates additional experimental investigation.

The relationship between RhoJ and tumor-associated angiogenesis has been widely demonstrated (10,14). In ccRCC, which is characterized by enhanced angiogenesis, we also conducted preliminary explorations. As shown in Figure S3, through IHC, we observed that the expression of platelet and endothelial cell adhesion molecule 1 (CD31) decreased in the RhoJ knockdown group. These results indicate that RhoJ may be associated with angiogenesis in ccRCC, but its mechanism still needs further investigation. Furthermore, considering that molecules among the Rho GTPase family, such as RhoA and Cdc42, have been shown to be involved in the process of immune regulation to varying degrees (38,39), we also carried out IHC (Figure S3) to explore its role in immune regulation. However, compared with the control group, there was no significant change in the proportion of T-cell surface glycoprotein CD4 (CD4)⁺ and T-cell surface glycoprotein CD8 alpha chain (CD8α)⁺ cells in the RhoJ knockdown group. In this study, we found that TNF-α levels increased when RhoJ is present, indicating a potential role in modulating the tumor microenvironment (TME) (40). However, as previous research has shown, the interplay between these molecules is intricate and multifaceted. Although our current findings did not yield conclusive evidence of RhoJ’s immunomodulatory function, it is crucial to recognize that this does not rule out its involvement in immune regulation entirely. On the contrary, these results highlight the necessity for additional experimental studies to comprehensively understand the complex immunomodulatory mechanisms of RhoJ.

Targeted inhibition of RhoJ emerges as a promising therapeutic strategy for tumor suppression (10). However, currently, there are still no specific inhibitors or drugs targeting RhoJ available for safety evaluations. Here, utilizing virtual screening and molecular docking analysis, 271 FDA-approved drugs targeting the oncogene RhoJ were screened. Among these drugs, ergotamine was identified as the top potent drug that could bind to the active pocket of RhoJ. Ergotamine is an effective agent for migraine (41); however, whether this drug could be used in ccRCC treatment was not reported. In advanced and metastatic RCC, pazopanib has been shown to improve tumor response and progression-free survival (PFS) (24). In this study, we noticed that pazopanib, an oral angiogenesis inhibitor, has the potential to target RhoJ. Additionally, avodart, a drug commonly used for treating prostatic hyperplasia and androgenetic alopecia (42,43), may also be associated with RhoJ-targeting properties. RhoJ is recognized as a downstream molecule of vascular endothelial growth factor receptor (VEGFR), playing a role in promoting tumor angiogenesis. This suggests that pazopanib, an angiogenesis inhibitor (24), may interact with components of the RhoJ signaling pathway. Although some research has shown that dutasteride can inhibit RhoA expression in benign prostatic hyperplasia tissues, no studies have specifically investigated its effects on RhoJ expression or other molecules within the RhoJ signaling cascade (42). In essence, both pazopanib and dutasteride may interact with RhoJ and its associated pathways, albeit to different extents. However, conclusive evidence regarding these potential off-target effects remains elusive, necessitating further experimental investigation to fully elucidate their mechanisms of action.

Here, we found that these drugs listed in Table 1 might treat ccRCC by targeting RhoJ as well. However, the precise molecular mechanisms still need to be studied.

Conclusions

This study enhanced the understanding of RhoJ in regulating ccRCC progression. Importantly, ergotamine, irinotecan, ledipasvir, pazopanib, and avodart could be potential novel and effective drugs targeting RhoJ in ccRCC treatment.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the ARRIVE and MDAR reporting checklists. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-132/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-132/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-132/prf

Funding: This study was supported by the Special Research Project of Capital Health Development(No. 2024-1-5042), PLA General Hospital Youth Independent Innovation Science Fund Growth Project (No. 22QNCZ029), PLA General Hospital-Third Medical Center Discipline Innovation and Development Special Fund Project (No. 2024BJ-04), and Fostering Fund of Chinese PLA General Hospital for National Excellent Young Scholar Science Fund (No. 2020-YQPY-006).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-132/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of PLA general hospital (No. S2024-279-01) and informed consent was taken from all the patients. Animal experiments were performed under a project license (No. S2013-115-01) granted by the ethics board of PLA general hospital, in compliance with the institutional guidelines for the care and use of animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Young M, Jackson-Spence F, Beltran L, et al. Renal cell carcinoma. Lancet 2024;404:476-91. [Crossref] [PubMed]
2. Powles T, Albiges L, Bex A, et al. Renal cell carcinoma: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol 2024;35:692-706. [Crossref] [PubMed]
3. Rathmell WK, Rumble RB, Van Veldhuizen PJ, et al. Management of Metastatic Clear Cell Renal Cell Carcinoma: ASCO Guideline. J Clin Oncol 2022;40:2957-95. [Crossref] [PubMed]
4. Bagci H, Sriskandarajah N, Robert A, et al. Mapping the proximity interaction network of the Rho-family GTPases reveals signalling pathways and regulatory mechanisms. Nat Cell Biol 2020;22:120-34. [Crossref] [PubMed]
5. Vignal E, De Toledo M, Comunale F, et al. Characterization of TCL, a new GTPase of the rho family related to TC10 andCcdc42. J Biol Chem 2000;275:36457-64. [Crossref] [PubMed]
6. Nishizuka M, Arimoto E, Tsuchiya T, et al. Crucial role of TCL/TC10beta L, a subfamily of Rho GTPase, in adipocyte differentiation. J Biol Chem 2003;278:15279-84. [Crossref] [PubMed]
7. de Toledo M, Senic-Matuglia F, Salamero J, et al. The GTP/GDP cycling of rho GTPase TCL is an essential regulator of the early endocytic pathway. Mol Biol Cell 2003;14:4846-56. [Crossref] [PubMed]
8. Zeng T, Chen C, Yang P, et al. A Protective Role for RHOJ in NonSmall Cell Lung Cancer Based on Integrated Bioinformatics Analysis. J Comput Biol 2020;27:1092-103. [Crossref] [PubMed]
9. Kim C, Yang H, Park I, et al. Rho GTPase RhoJ is Associated with Gastric Cancer Progression and Metastasis. J Cancer 2016;7:1550-6. [Crossref] [PubMed]
10. Sundararaman A, Fukushima Y, Norman JC, et al. RhoJ Regulates α5β1 Integrin Trafficking to Control Fibronectin Remodeling during Angiogenesis. Curr Biol 2020;30:2146-2155.e5. [Crossref] [PubMed]
11. Ho H, Soto Hopkin A, Kapadia R, et al. RhoJ modulates melanoma invasion by altering actin cytoskeletal dynamics. Pigment Cell Melanoma Res 2013;26:218-25. [Crossref] [PubMed]
12. Wang M, Jiang X, Yang Y, et al. Rhoj Is a Novel Target for Progression and Invasion of Glioblastoma by Impairing Cytoskeleton Dynamics. Neurotherapeutics 2020;17:2028-40. [Crossref] [PubMed]
13. Ho H, Aruri J, Kapadia R, et al. RhoJ regulates melanoma chemoresistance by suppressing pathways that sense DNA damage. Cancer Res 2012;72:5516-28. [Crossref] [PubMed]
14. Kim C, Yang H, Fukushima Y, et al. Vascular RhoJ is an effective and selective target for tumor angiogenesis and vascular disruption. Cancer Cell 2014;25:102-17. [Crossref] [PubMed]
15. Huber W, Wagner R, Sueltmann H. Transcription profiling of 74 kidney tumor samples of different histological type, differentiation grade, stage and with data on chromosomal aberrations and follow-up. BioStudies. 2013. Available online: https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-DKFZ-1
16. Zhang DY, Sun QC, Zou XJ, et al. Long noncoding RNA UPK1A-AS1 indicates poor prognosis of hepatocellular carcinoma and promotes cell proliferation through interaction with EZH2. J Exp Clin Cancer Res 2020;39:229. [Crossref] [PubMed]
17. Murata T, Aritake K, Matsumoto S, et al. Prostagladin D2 is a mast cell-derived antiangiogenic factor in lung carcinoma. Proc Natl Acad Sci U S A 2011;108:19802-7. [Crossref] [PubMed]
18. Bakir B, Chiarella AM, Pitarresi JR, et al. EMT, MET, Plasticity, and Tumor Metastasis. Trends Cell Biol 2020;30:764-76. [Crossref] [PubMed]
19. Rinderle CH, Baker CV, Lagarde CB, et al. Screening of a kinase inhibitor library identified novel targetable kinase pathways in triple-negative breast cancer. Anticancer Drugs 2025;36:39-48. [Crossref] [PubMed]
20. Ababneh O, Nishizaki D, Kato S, et al. Tumor necrosis factor superfamily signaling: life and death in cancer. Cancer Metastasis Rev 2024;43:1137-63. [Crossref] [PubMed]
21. Mirzaei S, Saghari S, Bassiri F, et al. NF-κB as a regulator of cancer metastasis and therapy response: A focus on epithelial-mesenchymal transition. J Cell Physiol 2022;237:2770-95. [Crossref] [PubMed]
22. Dassault Systèmes BIOVIA, Discovery Studio Modeling Environment, Release 2023. San Diego: Dassault Systèmes, 2023.
23. The PyMOL Molecular Graphics System, Version 3.0 Schrödinger, LLC.
24. Chellappan DK, Chellian J, Ng ZY, et al. The role of pazopanib on tumour angiogenesis and in the management of cancers: A review. Biomed Pharmacother 2017;96:768-81. [Crossref] [PubMed]
25. Shin HW, Kim JE, Park YJ. Nanoporous Silica Entrapped Lipid-Drug Complexes for the Solubilization and Absorption Enhancement of Poorly Soluble Drugs. Pharmaceutics 2021;13:63. [Crossref] [PubMed]
26. Sánchez-Gastaldo A, Kempf E, González Del Alba A, et al. Systemic treatment of renal cell cancer: A comprehensive review. Cancer Treat Rev 2017;60:77-89. [Crossref] [PubMed]
27. Rose TL, Kim WY. Renal Cell Carcinoma: A Review. JAMA 2024;332:1001-10. [Crossref] [PubMed]
28. Satoh K, Sakai S, Nishizuka M. Knockdown of RhoQ, a member of Rho GTPase, accelerates TGF-β-induced EMT in human lung adenocarcinoma. Biochem Biophys Rep 2022;32:101346. [Crossref] [PubMed]
29. Zhang H, Schaefer A, Wang Y, et al. Gain-of-Function RHOA Mutations Promote Focal Adhesion Kinase Activation and Dependency in Diffuse Gastric Cancer. Cancer Discov 2020;10:288-305. [Crossref] [PubMed]
30. Chong CF, Hasnizan NYU, Ahmad Mokhtar AM. Navigating the landscape of Rho GTPase signalling system in autoimmunity: A bibliometric analysis spanning over three decades (1990 to 2023). Cell Signal 2023;111:110855. [Crossref] [PubMed]
31. Shen J, Su X, Wang S, et al. RhoJ: an emerging biomarker and target in cancer research and treatment. Cancer Gene Ther 2024;31:1454-64. [Crossref] [PubMed]
32. Chu WM. Tumor necrosis factor. Cancer Lett 2013;328:222-5. [Crossref] [PubMed]
33. Idriss HT, Naismith JH. TNF alpha and the TNF receptor superfamily: structure-function relationship(s). Microsc Res Tech 2000;50:184-95. [Crossref] [PubMed]
34. Taniguchi K, Karin M. NF-κB, inflammation, immunity and cancer: coming of age. Nat Rev Immunol 2018;18:309-24. [Crossref] [PubMed]
35. Su X, Liu J, Tu Z, et al. DNMT3A promotes glioma growth and malignancy via TNF-α/NF-κB signaling pathway. Transl Cancer Res 2024;13:1786-806. [Crossref] [PubMed]
36. Liu BX, Xie Y, Zhang J, et al. SERPINB5 promotes colorectal cancer invasion and migration by promoting EMT and angiogenesis via the TNF-α/NF-κB pathway. Int Immunopharmacol 2024;131:111759. [Crossref] [PubMed]
37. Glotfelty EJ, Tovar-Y-Romo LB, Hsueh SC, et al. The RhoA-ROCK1/ROCK2 Pathway Exacerbates Inflammatory Signaling in Immortalized and Primary Microglia. Cells 2023;12:1367. [Crossref] [PubMed]
38. Kumagai S, Togashi Y, Sakai C, et al. An Oncogenic Alteration Creates a Microenvironment that Promotes Tumor Progression by Conferring a Metabolic Advantage to Regulatory T Cells. Immunity 2020;53:187-203.e8. [Crossref] [PubMed]
39. Shi LL, Chen Y, Xie MX, et al. UBE2T/CDC42/CD276 signaling axis mediates brain metastasis of triple-negative breast cancer via lysosomal autophagy. J Immunother Cancer 2025;13:e010782. [Crossref] [PubMed]
40. Laha D, Grant R, Mishra P, et al. The Role of Tumor Necrosis Factor in Manipulating the Immunological Response of Tumor Microenvironment. Front Immunol 2021;12:656908. [Crossref] [PubMed]
41. Tfelt-Hansen P, Saxena PR, Dahlöf C, et al. Ergotamine in the acute treatment of migraine: a review and European consensus. Brain 2000;123:9-18. [Crossref] [PubMed]
42. Tsujimura A, Fukuhara S, Soda T, et al. Histologic evaluation of human benign prostatic hyperplasia treated by dutasteride: a study by xenograft model with improved severe combined immunodeficient mice. Urology 2015;85:274.e1-8. [Crossref] [PubMed]
43. Andrade JFM, Verbinnen A, Bakst A, et al. Topical dutasteride for androgenic alopecia: current state and prospects. Ther Deliv 2025;16:271-83. [Crossref] [PubMed]

(English Language Editor: J. Jones)