DARS2 Promotes Bladder Cancer Progression by Enhancing PINK1-Mediated Mitophagy

doi:10.21203/rs.3.rs-5247474/v1

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DARS2 Promotes Bladder Cancer Progression by Enhancing PINK1-Mediated Mitophagy

https://doi.org/10.21203/rs.3.rs-5247474/v1

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Background: Bladder cancer is the tenth most common cancer worldwide. Mitochondria, as central hubs of cellular metabolism, play a crucial role in various diseases and cancers. However, the role and underlying mechanisms of mitophagy, the key process governing mitochondrial quantity and quality control, remain unclear in bladder cancer.

Methods: 824 mitophagy-related genes were collected from the Genecards database. Construction and validation of the mitophagy-related genes prognostic model were completed by univariate Cox analysis, Lasso and SuperPC algorithms, Kaplan-Meier survival, univariate and multifactorial Cox regression. The screening and intervention of DARS2 were done by univariate Cox regression, Monocle3 pseudotime and DepMap analysis as wel as siRNA and shRNA. Mitophagy was detected by flow cytometry analysis, super-resolution microscopy, confocal microscopy and transmission electron microscopy.

Results: We screened 16 mitophagy-related genes to construct a prognostic model, which demonstrated strong predictive performance for overall survival, immune response, and chemotherapy outcomes in bladder cancer patients. Among these genes, DARS2 was identified as having a particularly significant impact on bladder cancer prognosis. Further investigation revealed that DARS2 promotes G1-to-S phase transition by upregulating CDK4 expression, thereby inhibiting cellular senescence and promoting cell proliferation. Additionally, DARS2 enhanced PINK1 expression in bladder cancer cells, leading to increased PINK1-mediated mitophagy. Importantly, both in vitro and in vivo experiments confirmed that DARS2 inhibits cellular senescence and promotes tumor progression by enhancing PINK1-mediated mitophagy.

Conclusions: DARS2 promotes PINK1-mediated mitophagy and facilitates G1-to-S phase transition, thereby delaying cellular senescence and promoting bladder cancer progression. Targeting DARS2 and mitophagy could be a promising therapeutic strategy to improve the prognosis of bladder cancer patients.

Bladder cancer

DARS2

PINK1

Mitophagy

Cellular senescence

Bladder cancer (BCa) is one of the most common malignancies of the urinary system and ranks as the fourth most prevalent cancer in men[1]. According to global statistics, bladder cancer accounts for approximately 573,000 new cases and 213,000 deaths annually, contributing to around 6% of new cancer diagnoses and 4% of cancer-related fatalities, making it a serious public health concern worldwide[1]. At the time of diagnosis, 70-75% of cases are classified as non-muscle-invasive bladder cancer (NMIBC), while 20-25% are categorized as muscle-invasive bladder cancer (MIBC)[2, 3]. Despite aggressive treatment regimens, the five-year survival rate for MIBC remains at only 20%. NMIBC, on the other hand, tends to recur or progress, with recurrence rates ranging from 31% to 78% and progression rates between 1% and 45% over five years[3]. Currently, NMIBC is typically treated with transurethral resection combined with intravesical therapy, whereas MIBC is treated more aggressively with neoadjuvant or adjuvant chemotherapy in combination with radical cystectomy or trimodal therapy (including TURBT, radiotherapy, and chemotherapy)[4]. Cisplatin-based combination chemotherapy is the first-line treatment recommended by authoritative guidelines for metastatic bladder cancer[5]. However, the emergence of chemoresistance severely limits its efficacy[6].

Mitochondria, found in eukaryotic cells, are considered the central hubs of cellular metabolism. They are the primary sites for fatty acid synthesis, oxidative phosphorylation (OXPHOS), ATP production and reactive oxygen species (ROS) generation[7]. However, ROS generated as a byproduct of mitochondrial oxidative phosphorylation can damage mitochondrial proteins, lipids, and DNA. In addition, mitochondria are exposed to various extracellular stressors, further increasing the likelihood of mitochondrial damage[8]. The control of mitochondrial quantity and quality is primarily regulated by mitophagy, a process involving multiple signaling pathways and molecular interaction networks, with the PINK1/Parkin pathway being the most extensively studied[9]. PINK1, known as a serine/threonine kinase that accumulates on damaged mitochondria, activates Parkin, which is subsequently recruited to damaged mitochondria to facilitate autophagosome formation via ubiquitination mechanisms[10]. Mitophagy effectively clears dysfunctional or excess mitochondria, reducing ROS and mitochondrial DNA mutations, thus contributing to normal mitochondrial function and cellular homeostasis[9, 11]. According to report, mitophagy plays a critical role in cancer development, progression, and chemoresistance[12, 13]. In bladder cancer, rapamycin enhances mitophagy via AMPK activation, inhibiting bladder cancer cell proliferation and migration[12]. Additionally, MCM7 upregulates mitophagy levels, suppressing p53 accumulation and maintaining bladder cancer cell stemness[13]. Nitrofurantoin activates the initiation of mitophagy but causes lysosomal impairment at later stages, ultimately inhibiting bladder cancer cell proliferation and promoting apoptosis[14].

DARS2 (aspartyl-tRNA synthetase 2) is a key mitochondrial aminoacyl-tRNA synthetase whose dysfunction can impair mitochondrial protein synthesis, leading to mitochondrial dysfunction[15]. Previous research on DARS2 has primarily focused on leukoencephalopathy, with reports indicating that DARS2 deficiency in forebrain hippocampal neurons or myelinating cells mediates mitochondrial dysfunction and cell death[15]. Emerging evidence suggests that DARS2 plays a significant regulatory role in the progression and apoptosis of hepatocellular carcinoma and lung adenocarcinoma, although the precise mechanisms remain unclear[16, 17].

Cellular senescence refers to an irreversible state of cell cycle arrest and is now recognized as a hallmark of cancer[18, 19]. It is characterized by changes in cellular structure and morphology, DNA damage response activation, resistance to apoptosis, cyclin-dependent kinase inhibition, endoplasmic reticulum stress, and the secretion of pro-inflammatory and tissue remodeling factors[20, 21]. Abnormal gene regulation is a major factor in inducing cellular senescence in tumors[22]. Research indicates that cellular senescence plays a dual role in cancer[23]. On the one hand, oncogene activation or tumor suppressor gene loss induces senescence, halting the cell cycle and preventing tumor formation[24]. For instance, BRAF mutations in melanocytes can induce long-lasting senescence, preventing progression to melanoma[24]. On the other hand, senescent cells secrete senescence-associated secretory phenotypes (SASPs) that can promote angiogenesis and tumor progression[25]. For example, HINFP knockout leads to DNA damage-induced senescence, characterized by increased MMP1/3 levels, which enhance invasion and metastasis of non-senescent bladder cancer cells[25]. Investigating the role of cellular senescence in bladder cancer may provide novel insights into improving patient outcomes.

In this study, we uncovered a novel mechanism by which DARS2 regulates cellular senescence in bladder cancer cells. We screened 16 mitophagy-related genes to construct a prognostic model, demonstrating its strong predictive value for overall survival, immune response, and chemotherapy outcomes in bladder cancer patients. We further identified DARS2 for subsequent study and found that DARS2 was significantly upregulated in bladder cancer tissues. Silencing DARS2 increased cellular senescence and inhibited the proliferation of bladder cancer cells. Additionally, silencing DARS2 reduced CDK4 levels, causing cell cycle arrest in the G1 phase, with fewer cells entering the S and G2 phases. Interestingly, we found that DARS2 upregulated PINK1-mediated mitophagy in bladder cancer cells by promoting PINK1 mitochondrial expression, thereby reducing the occurrence of cellular senescence. These experimental results highlight the intrinsic link between DARS2, mitophagy, and bladder cancer cell senescence and proliferation.

2.1. Construction of the prognostic MRGs model

A prognostic model was constructed through the utilization of machine learning-integrated algorithms. Ultimately, a combination of the Lasso and SuperPC algorithms was chosen as the final model.

The Calculation of the risk score for each patient was as follows: Risk score = ANXA2 expression * 0.148207972739551 + CDK5RAP3 expression * (-0.0216587905197319) + CSNK2A2 expression * 0.00595383260568351 + DARS2 expression * 0.0231697095929072 + DCXR expression * 0.209058645007052 + FASN expression * 0.165701072850379 + GFPT2 expression * 0.125204197049992 + MAP1A expression * 0.109561386716842 + PRDX6 expression * 0.127684552011834 + SAR1A expression * 0.0211344182319381 + SCD expression * 0.00674879338858188 + SCO2 expression * (-0.423184153287598) + SPTBN2 expression * 0.106972468192409 + TFRC expression * 0.0712419818434375 + TRIM27 expression * (-0.239048049127721) + UBC expression * 0.1174018352924.

2.2. Sample Source

Bladder cancer (BCa) samples for this study were from patients under treatment at the Department of Urology, Nanfang Hospital, Southern Medical University, between March 1, 2023, and May 31, 2023. A total of six BCa cases were selected, with all associated clinical records and samples approved by the Ethics Committee. Prior to approval, all patients provided informed consent.

2.3. Cell Culture and Reagents

T24 and SW780 bladder cancer cells were utilized in this study. Cells were maintained at 37°C in a humidified atmosphere containing 5% CO₂, cultured on DMEM basic medium (Gibco, C11995500BT) with 10-15% fetal bovine serum (164210, China). The autophagy inducer CCCP (HY-100941) were obtained in MedChemExpress.

2.4. RNA Interference and Lentiviral Transfection

DARS2-targeting siRNA/shRNA was synthesized by GenePharma (Guangzhou, China). The overexpression plasmids for PINK1 were purchased from Miaoling Biotech (Wuhan, China). Transfection of siRNA was performed using Lipofectamine 3000 (Servicebio, USA) for 48 hours according to the manufacturer’s protocol. For DARS2 silencing, lentiviral infection of T24 or SW780 cells was carried out using lentivirus from Genechem (China), followed by selection with DMEM containing 4 μg/mL puromycin (Sigma) for 48-72 hours. The siRNA/shRNA sequence for PINK1 and DARS2 is provided in the supplementary table 7.

2.5. Cell Senescence Staining

Cellular senescence was tested using the SA-β-gal kit (KeyGEN BioTECH, KGA5101-100) as instructions. BCa cells were fixed at 26°C for 16 minutes and were overnight cultured with SA-β-gal solution in a CO₂-free incubator at 37°C. BCa cells were then observed under a conventional optical microscope. Image data were analyzed quantitatively using ImageJ software.

2.6. Cell Viability Assay

The BCa cells viability was assessed by CCK8 assay. We spread 3 × 10^3 cells per well in 96-well plates. After attachment, cells received the indicated treatments before we added CCK8 reagent. And then cells were cultured for about 2 hours in humidified incubators at 37°C with 5% CO₂. Then measuring the Optical density at 450 nm (OD450) using an ELISA reader, and data were visualized using GraphPad Prism 8 software.

2.7. Flow Cytometry

Using the cell cycle detection kit (KeyGEN BioTECH, KGA9101-100), we performed cell cycle analysis in accordance with the manufacturer’s protocol. Cells were fixed in 70% cold ethanol (500 μL) overnight, stained with PI/RNase A staining solution (500 μL). Afterwards, cells were incubated for 30-60 minutes in the dark. ROS levels were measured using a ROS detection kit (S0033M, Beyotime) after 30 minutes of incubation. Mitochondrial mass and membrane potential were evaluated using Mitotracker-green (C1048, Beyotime) and TMRE (C2001S, Beyotime), respectively, at a concentration of 10 nM. BD Accuri C6 flow cytometer together with FlowJo X software were used to collect and analyze the data .

2.8. Immunofluorescence

Bladder cancer cells were incubated with 15 nM Mitotracker-green (C1048, Beyotime) and 15 nM Lysotracker-red (C1046, Beyotime) for 25 minutes, with nuclei stained using Hoechst 33342 (C1025, Beyotime). Live-cell fluorescence images were captured using either a laser confocal microscope (FV3000) or a super-resolution microscope (N-SIM+N-STORM, Nikon). Additionally, after transfection of cells with mt-Keima plasmids for 3 days and nuclei stained using Hoechst 33342, live-cell figures were taken through a laser confocal microscope. Image analysis was performed using Imaris software (Oxford Instruments, UK).

2.9. Animal Experiments

Bladder cancer cells were evenly injected into BALB/c nude mice (4-week-old, female) subcutaneously. Tumor volume and mice body weight were recorded daily starting on day 14 post-injection. The nude mice were euthanized on day 28. And their tumor tissues were isolated, photographed, weighed, and subjected to immunohistochemical staining and histopathological evaluation. This project was approved by the Ethics Committee of Nanfang Hospital, Southern Medical University.

2.10. Immunohistochemistry (IHC) Staining

Tissue samples from bladder cancer patients and nude mice accepted standard IHC procedures (fixed in formalin, embedded in paraffin, and sectioned). Slides were incubated overnight at 4°C with primary antibodies (Anti-DARS2 1:200, Anti-PINK1 1:200, Anti-CDK4 1:200), followed by incubation with secondary antibodies (1:250) for 40 minutes at 25°C. The slides were developed using DAB and counterstained with hematoxylin. Images were captured using a slide scanner (DX300, HISTECH, China).

2.11. Statistical Analysis

All statistical analyses and data visualizations were performed using GraphPad Prism 8 software. Statistical significance was determined by one-way ANOVA or Student’s t-test, with results presented as the mean ± SEM from at least three independent experiments (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, ns: not significant).

3.1. Construction and Validation of the MRGs Prognostic Model

To comprehensively explore the role of mitophagy in BCa, we initially collected 824 mitophagy-related genes (MRGs) (with relevance scores >1) from the Genecards database (Supplementary Table 1). Subsequently, to identify MRGs related to prognosis in BCa, Kaplan-Meier survival analysis was performed in TCGA and GSE13507 cohorts, resulting in 2,165 genes associated with prognosis. We selected the intersection of 824 MRGs and 2,165 prognosis-related genes, ultimately choosing 115 MRGs (Fig. 1A). Further univariate Cox regression analysis identified 26 candidate MRGs with prognostic significance (Fig. 1B). Multiple machine learning algorithms were employed to identify model genes.

In the end, a combination of Lasso and SuperPC algorithms was selected for the final model, which exhibited the most stable performance with the smallest 5-year AUC variation across all three cohorts (Fig. 1C-E). Correlation analysis revealed the relationship between BCa prognosis and 16 model genes (Supplementary Table 2), along with their co-expression patterns (Fig. 1F). Apart from CDK5RAP3, TRIM27, and SCO2, all other MRGs were identified as risk factors for BCa prognosis (p<0.05). This analysis provided insights into the interactions among these genes.

Afterwards, heatmaps showed that low-risk group had higher expression of protective genes, while the high-risk group had higher levels of risk genes (Fig. 2A). In the TCGA cohort, the model effectively predicted patient survival, with mean AUC values for 1-year, 3-year, and 5-year survival exceeding 0.7 (0.69, 0.73, and 0.74, respectively) (Fig. 2B, C). Similarly, KM analysis and AUC supported the reliability of the model in the GSE13507 cohort, indicating its sensitivity and specificity in predicting prognosis (Fig. 2D, E). To further validate the independence of our model, univariate as well as multivariate Cox analyses were performed in the TCGA cohort (Fig. 2F, G). These two Cox regression analyses confirmed that stage and age, along with risk score were significant prognostic factors for OS in BCa patients.

Based on the prognostic model established previously, we then developed a nomogram to provide a quantitative method for predicting BCa prognosis (Fig. 2H). Calibration plots demonstrated a strong consistency between predicted and actual 1-, 3-, and 5-year OS rates (Fig. 2I). This model offers clinical utility for personalized treatment planning and decision-making.

3.2. Mutation Analysis of Prognostic Model Genes

Notably, the 16 model genes exhibited relatively frequent mutations, with a mutation rate of 16.91% in BCa patients (Fig. 3A). In terms of copy number variations (CNVs), SCD, MAP1A, CSNK2A2, ANXA2, GFPT2, and SAR1A showed more copy number gains than losses, while the remaining genes exhibited more losses than gains (Fig. 3B). The chromosomal locations of CNVs for all 16 MRGs were mapped (Fig. 3C). We then analyzed the differential expression of these 16 genes between BCa and normal tissues in the TCGA database. The results revealed significant differential expression for all genes except ANXA2, CSNK2A2, PRDX6, and MAP1A (Fig. 3D). Abnormal gene mutations, CNVs, and mRNA dysregulation suggest the disruption of mitophagy in BCa. Moreover, considering the important role of epigenetics modifications in gene expression regulation, we assessed the levels of DNA methylation in MRG promoter sequences (Fig. 3E). Compared to non-tumor tissues, the DNA methylation levels surrounding the promoters of all model genes were lower in tumor tissues, suggesting that epigenetic activation might contribute to the abnormal expression of MRGs.

Gene set enrichment analysis (GSEA) was then used to explore the potential biological functions between the groups with high or low risk. Pathways such as myogenesis, epithelial-mesenchymal transition (EMT), hypoxia, angiogenesis, and Hedgehog signaling were significantly enriched in the groups with high risk (Supplementary Fig. 1A). Conversely, pathways including interferon-α and interferon-γ responses were enriched in the groups with low risk significantly (Supplementary Fig. 1B). These findings indicate activation of stromal pathways in the groups with high risk, while the lower risk groups exhibited heightened immune activity, explaining the differences between two groups in survival value. Additionally, differential mutation analysis revealed a higher mutation rate of the key cell cycle regulator TP53 in the groups with high risk compared to the low (53% vs. 43%) (Supplementary Fig. 1C, D). Most TP53 mutations in the group with high risk were missense mutations, which impair its ability to inhibit the cell cycle and promote oncogenic functions. This likely contributes to the increased cell cycle activity observed in the high-risk group.

3.3. Correlation Analysis of Prognostic Model with Immune Landscape and Chemotherapy Response

To evaluate immune infiltration in TCGA-BLCA patients, we employed the CIBERSORT algorithm (Fig. 4A). Notably, the low-risk group showed higher infiltration of immune cells such as memory activated dendritic cells, CD8+ T cells, B cells and follicular helper T cells , while the high one exhibited increased levels of M0 and M2 macrophages (Fig. 4B). These differences highlight distinct immune microenvironments between the two groups.

New metrics like the immune phenotype score (IPS), stromal score, and ESTIMATE score were also assessed to predict patients' responsiveness to immunotherapy. We found elevated IPS scores and lower stromal and ESTIMATE scores in the group with low risk compared to the high (Fig. 4C-E), suggesting a better immunotherapy effect of the patients in the group with low risk. To further explore whether the risk model can predict BCa patient response to immunotherapy, we applied it to the IMvigor210 cohort, which received anti-PD-L1 therapy. Consistent with the TCGA and GSE13507 cohorts, the prognostic model effectively differentiated survival outcomes in these patients (Fig. 4F). Interestingly, patients with lower risk scores exhibited an "inflamed" phenotype characterized by increased immune cell infiltration and improved responses to immunotherapy. In contrast, high-risk patients predominantly showed "desert" or "excluded" phenotypes, indicative of poor immunotherapy responses (Fig. 4G). The low-risk group also had a higher objective response rate (complete or partial response) to anti-PD-L1 therapy compared to the high-risk group (Fig. 4H), underscoring the strong association between risk score and responsiveness to anti-PD-L1 therapy in BCa patients.

Utilizing data from the Genomics of Drug Sensitivity in Cancer (GDSC) database, we predicted the chemotherapy responses between the high-risk and low-risk groups in the TCGA-BLCA cohort. The high-risk group had significantly higher IC50 values for cisplatin, gemcitabine, and doxorubicin, all of which are commonly used chemotherapeutic agents in BCa (Fig. 4I-K). This suggests that patients in the low-risk group may experience better outcomes when treated with these drugs, further supporting the role of mitophagy in BCa chemoresistance.

To delve deeper into the cellular localization of the 16 model genes in BCa, single-cell analysis was conducted. Dimensionality reduction, clustering, and cell annotation revealed seven distinct cell types (Supplementary Fig. 2A, B, Supplementary Table 3), with most model genes being predominantly expressed in epithelial cells (Supplementary Fig. 2C). This suggests that aberrant mitophagy likely occurs in tumor epithelial cells. Given this, we assessed whether the expression of these genes could impact epithelial cell function. By utilizing the AUCell algorithm, epithelial cells were divided into high and low expression groups for the 16 MRGs, and differentially expressed genes (DEGs) were identified (Supplementary Table 4). GO enrichment analysis of these DEGs indicated significant alterations in the mitochondrial matrix and protein-containing mitochondrial complexes within BCa epithelial cells (Supplementary Fig. 2D). KEGG enrichment analysis indicated that the 16 model genes altered the levels of mitophagy in epithelial cells. Furthermore, significant changes were observed in drug resistance pathways, the p53 signaling pathway, and immune-related pathways between the high and low 16-MRG groups (Supplementary Fig. 2E, Supplementary Table 5). In summary, our single-cell data analysis indicated that most dysregulated MRGs were predominantly expressed in tumor epithelial cells, suggesting abnormal mitophagy in BCa tumor epithelial cells and further emphasizing the close link between BCa and mitophagy.

3.4. The Potential Role of DARS2 in Bladder Cancer Progression

To identify the most important MRG among the 16 genes for bladder cancer prognosis, we performed univariate Cox regression analysis, identifying 13 genes with HR > 1, indicating that higher expression of these genes is associated with poorer prognosis (Fig. 5A). Next, to further identify core genes closely related to bladder cancer progression, we integrated multiple single-cell datasets of BCa and extracted epithelial cells for Monocle3 pseudotime analysis. The results showed that UBC, MAP1A, DARS2, DCXR, and GFPT2 were progressively upregulated during the malignant transformation from normal epithelial cells to NMIBC-associated epithelial cells and MIBC-associated epithelial cells, suggesting that these five genes are closely related to BCa progression (Fig. 5B-D).

DepMap is a large-scale gene screening project aimed at identifying gene dependencies in cancer cells by integrating data from the Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE)[26, 27]. In the DepMap project, CRISPR-Cas9 technology was used to knock out genes in 1,100 cancer cell lines to assess their impact on cell proliferation and survival[27]. Based on the aforementioned genes UBC, MAP1A, DARS2, DCXR, and GFPT2, we utilized DepMap to further understand their roles in various cancers, including BCa. Notably, only UBC, DARS2, and DCXR showed significant inhibition of tumor cell proliferation and survival upon knockout (Fig. 5E). Specifically, UBC and DARS2 stood out, with 113 of 333 cell lines showing dependency on UBC and 315 of 1,150 cell lines dependent on DARS2. Finally, to confirm the interaction between these core genes and mitophagy, we used Alphafold3 artificial intelligence to predict the protein-protein interaction potential between UBC, DARS2, and PINK1, a key gene in mitophagy, and selected the gene with the highest interaction potential for subsequent experimental studies (Fig. 5F, G). The results revealed that the interaction potential between DARS2 and PINK1 was significantly higher than that between UBC and PINK1. Therefore, DARS2 was chosen for further in-depth investigation.

To investigate DARS2's role in BCa further, we collected surgical pathology specimens from patients who underwent radical cystectomy at Nanfang Hospital's Department of Urology. Both DARS2 mRNA and protein expression were found to be significantly elevated in tumor tissues compared to adjacent normal tissues (Fig. 5H, I). Immunohistochemical (IHC) staining of paraffin-embedded tissue sections confirmed that DARS2 expression was markedly higher in BCa tissues than in adjacent non-cancerous tissues (Fig. 5J). These findings indicate that DARS2 is highly expressed in bladder cancer tumor tissues, likely contributing to the progression of the disease.

3.5. DARS2 Promotes G1-to-S Phase Transition by Upregulating CDK4 Expression and thereby Inhibiting Cellular Senescence

To gain further insight into the biological function of DARS2 in bladder cancer (BCa), we performed GO and KEGG enrichment analyses using the TCGA_BLCA dataset. The analyses revealed that DARS2 is predominantly enriched in pathways linked to cellular senescence, cell cycle regulation, DNA replication, and DNA damage repair (Fig. 6A). Prior studies have demonstrated a strong connection between cellular senescence, cell cycle regulation, and DNA repair processes, all of which are critical in cancer development and progression[28]. Given this, we explored whether DARS2 promotes BCa progression by modulating cellular senescence. We first assessed DARS2 expression across five BCa cell lines and utilized siRNA to knock down DARS2 expression in the T24 and SW780 cell lines, which exhibited the highest DARS2 expression levels (Fig. 6B-E). Knockdown of DARS2 significantly increased the proportion of cells positive for SA-β-gal staining, suggesting that DARS2 inhibition induces cellular senescence in BCa cells (Fig. 6F).

Since cellular senescence is characterized by irreversible cell cycle arrest and is closely associated with reduced proliferation, we further investigated the effects of DARS2 on cell proliferation and cell cycle progression[18]. Our results demonstrated that DARS2 knockdown inhibited the proliferation of BCa cells, leading to a significant arrest of cells in the G1 phase and a reduced number of cells progressing to the S and G2 phases (Fig. 6G-I). This indicates that DARS2 facilitates the transition from G1 to S and G2 phases, thereby limiting cellular senescence and promoting cell proliferation. Furthermore, we observed that DARS2 enhanced the migration and invasion capabilities of BCa cells in vitro (Supplementary Fig. 3A).

The ability of eukaryotic cells to transition from the G1 phase to the S and G2 phases is primarily controlled by the G1 phase checkpoint, in which CDK4 and CDK6 interact with cyclin D1 to play a critical role[29]. Additionally, P53, a key protein involved in the DNA damage checkpoint, induces P21 transcription, leading to G1 phase arrest[30]. Therefore, we further assessed the expression levels of CDK4, CDK6, P53, and P21. The results showed that DARS2 knockdown reduced CDK4 expression, while the expression levels of CDK6, P53, and P21 remained unchanged (Fig. 6J-L). Our results demonstrated that DARS2 promotes G1-to-S phase transition by upregulating CDK4 expression, thereby inhibiting cellular senescence in BCa cells.

3.6. DARS2 Promotes PINK1-Mediated Mitophagy in Bladder Cancer Cells

Although we initially identified DARS2 from MRGs, its role in mitophagy remains unknown. Therefore, we conducted further analyses and experimental validations. GSEA enrichment analysis of the GSE13507 dataset revealed that DARS2 is significantly enriched in mitophagy-related pathways (Supplementary Fig. 3B). Additionally, DARS2 showed significant correlations with multiple mitophagy-related genes (Supplementary Fig. 3C), with a particular focus on the interaction between DARS2 and PINK1. Our experiments further revealed that knockdown of DARS2 significantly downregulated PINK1 protein expression, although PINK1 mRNA levels remained unchanged (Supplementary Fig. 3D, E). Previous reports indicate that DARS2 encodes aspartyl-tRNA synthetase, which plays a critical role in mitochondrial amino acid synthesis[15]. Hence, abnormal expression of DARS2 may impair mitochondrial protein synthesis. Based on this biological function, we hypothesized that DARS2 might influence PINK1 mitochondrial synthesis. We established stable DARS2 knockdown BCa cells and isolated mitochondrial proteins (Supplementary Fig. 4A, B). As predicted, DARS2 knockdown significantly reduced mitochondrial PINK1 protein levels (Supplementary Fig. 4C). These results demonstrate that DARS2 promotes mitochondrial synthesis of the mitophagy-related protein PINK1.

To investigate whether changes in PINK1 expression after DARS2 regulation affect mitophagy, we first assessed the overall autophagy levels in the cells. By detecting LC3II/I, we found that autophagy levels decreased following DARS2 knockdown (Fig. 7A, B). Abnormal accumulation of ROS leads to irreversible mitochondrial damage, indirectly triggering mitophagy, an essential pathway for mitochondrial quality control[31]. Conversely, normal levels of mitophagy effectively remove damaged mitochondria and stabilize intracellular ROS levels under physiological conditions[32]. Given the close relationship between ROS and mitophagy, we first measured ROS levels before examining mitophagy. The results showed a significant increase in ROS levels in BCa cells following DARS2 knockdown (Fig. 7C). Further experiments revealed that the total number of mitochondria, as labeled by Mitotracker, significantly increased following DARS2 knockdown, while TMRE staining indicated a reduction in the proportion of mitochondria with normal membrane potential (Fig. 7D). This suggests that DARS2 knockdown may cause impaired clearance of damaged mitochondria, leading to the accumulation of depolarized mitochondria. We then used Mitotracker-green to label mitochondria and Lysotracker-red to label lysosomes. Super-resolution and confocal fluorescence microscopy showed a reduction in the colocalization of mitochondria and lysosomes following DARS2 knockdown, indicating decreased mitophagy levels (Fig. 7E, F). We further transfected BCa cells with the mt-Keima plasmid, which localizes to mitochondria, to assess the interaction between mitochondria and lysosomes. The plasmid exhibits green fluorescence in neutral pH mitochondria and red fluorescence in acidic pH lysosomes. Consistent with previous results, DARS2 knockdown reduced the colocalization of mitochondria with lysosomes, indicating decreased mitophagy (Fig. 7G). Finally, transmission electron microscopy revealed a significant decrease in mitophagy following DARS2 knockdown, with more mitochondria displaying vacuolization and abnormal swelling, likely due to impaired clearance of damaged mitochondria (Fig. 7H). Our results demonstrate that DARS2 promotes PINK1-mediated mitophagy in BCa cells.

3.7. DARS2 Inhibits Cellular Senescence and Promotes Tumor Growth by Enhancing PINK1-Mediated Mitophagy

To further elucidate the link between DARS2-regulated mitophagy and cellular senescence, we overexpressed PINK1 and added CCCP in DARS2 knockdown BCa cells. CCCP (carbonyl cyanide m-chlorophenyl hydrazone) is a protonophore that increases the permeability of the mitochondrial inner membrane to H+, causing loss of membrane potential and inducing rapid mitochondrial depolarization and mitophagy[33]. Interestingly, PINK1 overexpression and CCCP treatment not only significantly increased autophagy levels but also partially restored the decreased CDK4 expression caused by DARS2 knockdown (Fig. 8A, B).

Moreover, PINK1 overexpression and CCCP treatment significantly reduced SA-β-gal positivity and increased cell proliferation compared to the DARS2 knockdown group (Fig. 8C, D). More importantly, this treatment alleviated G1 phase arrest caused by DARS2 knockdown (Fig. 8E). These findings suggest that DARS2 promotes CDK4 expression and G1-to-S phase transition by enhancing PINK1-mediated mitophagy, thereby delaying cellular senescence and promoting BCa cell proliferation.

To assess the effects of DARS2 on tumor growth in vivo, we performed subcutaneous tumor xenograft experiments using nude mice (Fig. 9A-C). The results demonstrated that DARS2 knockdown significantly reduced both tumor size and weight, an effect that was partially reversed by PINK1 overexpression (Fig. 9D, E). Immunohistochemical analysis of the tumor tissues confirmed that PINK1 and CDK4 expression levels were markedly reduced following DARS2 knockdown, with partial restoration upon PINK1 overexpression, consistent with our earlier experimental findings (Fig. 9F). These results indicate that DARS2 knockdown exerts an anti-tumor effect by promoting PINK1-dependent mitophagy.

To further explore the clinical significance of the DARS2-PINK1-CDK4 axis, we utilized the ssGSEA algorithm to calculate the overall expression levels of the DARS2-PINK1-CDK4 axis in each sample across multiple bladder cancer cohorts, generating a Prognostic Score (Fig. 9G). Our results showed that the DARS2-PINK1-CDK4 axis is highly expressed in BCa and is significantly positively correlated with higher tumor grade, stage, and distant metastasis across multiple datasets (Fig. 9H-N). Additionally, this axis was significantly associated with poorer overall survival outcomes and suboptimal responses to various drug treatments in patients (Fig. 9O-Q, Supplementary Table 6). In summary, DARS2 promotes PINK1-mediated mitophagy, upregulates CDK4 expression, and facilitates G1-to-S phase transition, thereby delaying cellular senescence and promoting tumor growth. Targeting the DARS2-PINK1-CDK4 axis holds promise for improving the prognosis of BCa patients.

Bladder cancer is one of the most common malignant tumors affecting the urinary system worldwide, with complex pathological types and mechanisms of progression[3, 34]. Patients with bladder cancer often face challenges such as high recurrence rates, chemotherapy resistance, and poor prognosis[3, 35]. Thus, exploring the molecular mechanisms underlying bladder cancer and identifying new therapeutic targets are of great clinical importance. In recent years, the role of cellular senescence in cancer has garnered significant attention[36, 37]. Cellular senescence is characterized by irreversible cell cycle arrest and acts as a stress response that typically inhibits cell proliferation, thereby preventing the malignant spread of cancer cells[38]. However, senescent cells secrete pro-inflammatory factors and matrix-degrading enzymes, collectively known as senescence-associated secretory phenotypes (SASPs), which can activate the tumor microenvironment and promote tumor progression[25, 39]. This dual nature of cellular senescence underscores its complex role in cancer development. Therefore, understanding the molecular basis of cellular senescence in bladder cancer is crucial for gaining insights into tumorigenesis and developing novel therapeutic strategies.

Mitophagy, which is responsible for clearing damaged mitochondria and maintaining mitochondrial health, plays a vital role in energy metabolism and the reduction of reactive oxygen species (ROS) accumulation within cells[9, 40]. The role of mitophagy in cancer is complex. On the one hand, mitophagy can suppress tumorigenesis by eliminating damaged mitochondria and reducing ROS levels[41]. On the other hand, excessive mitophagy may provide energy for cancer cells and promote tumor progression[41, 42]. This duality has made mitophagy a controversial and challenging area of research in cancer.

In this study, we utilized several machine learning algorithms to develop a prognostic model based on mitophagy-related genes and identified 16 genes closely associated with bladder cancer prognosis, with DARS2 emerging as a key gene. DARS2 encodes mitochondrial aspartyl-tRNA synthetase, which plays a crucial role in mitochondrial protein synthesis[15]. While previous studies have implicated DARS2 in liver and lung cancer progression, its role in bladder cancer has remained largely unexplored[16, 17]. Through in vitro experiments on bladder cancer cell lines, we found that silencing DARS2 significantly inhibited cell proliferation and increased cellular senescence. Specifically, DARS2 knockdown downregulated CDK4, induced cell cycle arrest in the G1 phase, increased SA-β-gal staining, and reduced proliferation. These findings suggest that DARS2 acts as a key regulatory factor in bladder cancer cells.

Next, we investigated whether DARS2 regulates cellular senescence in bladder cancer cells through a mitophagy-dependent pathway. PINK1, a key regulator in the mitophagy pathway, accumulates on the outer mitochondrial membrane in response to mitochondrial damage and recruits Parkin to facilitate autophagic degradation of damaged mitochondria[43]. Our study was the first to reveal the relationship between DARS2 and PINK1. Our experiments showed that DARS2 knockdown significantly downregulated PINK1 protein expression in bladder cancer cells, although PINK1 mRNA levels were not significantly altered. This suggests that DARS2 may regulate PINK1 expression through mitochondrial synthesis, post-translational modification, or protein stability rather than transcription. By isolating mitochondrial proteins, we found that DARS2 knockdown inhibited mitochondrial synthesis of PINK1, supporting our hypothesis. Further immunofluorescence and confocal microscopy observations showed that DARS2 knockdown significantly reduced the colocalization of mitochondria and lysosomes, indicating decreased mitophagy. Transmission electron microscopy also revealed increased vacuolization and swelling of mitochondria in DARS2 knockdown cells, which are typical signs of impaired mitophagy.

Moreover, our study found that DARS2 knockdown significantly increased ROS levels in bladder cancer cells. ROS is a major inducer of mitophagy, and under normal conditions, mitophagy effectively removes damaged mitochondria and maintains stable intracellular ROS levels[32]. However, DARS2 knockdown led to mitochondrial damage accumulation, further increasing ROS levels. This may be both a result of decreased mitophagy and a cause of increased cellular senescence. Overexpression of PINK1 or treatment with the autophagy inducer CCCP partially restored the decrease in mitophagy and the increase in cellular senescence caused by DARS2 knockdown, further confirming that DARS2 regulates bladder cancer cell senescence through PINK1-mediated mitophagy.

Previous research on DARS2 has primarily focused on its role in neurological diseases[15]. This study is the first to explore its function in bladder cancer, revealing its critical role in regulating the cell cycle, inhibiting cellular senescence, and promoting cell proliferation. We propose a molecular mechanism where DARS2 suppresses cellular senescence and promotes bladder cancer progression through PINK1-mediated mitophagy. This discovery offers new insights into the roles of DARS2 and mitophagy in bladder cancer. Moreover, our study identified the clinical relevance of the DARS2-PINK1-CDK4 axis in bladder cancer. Bioinformatics analysis showed that elevated expression of this axis is significantly associated with poor prognosis in bladder cancer patients, suggesting that targeting this axis could be a promising therapeutic approach. For patients who respond poorly to conventional chemotherapy or immunotherapy, targeting DARS2 could provide a novel treatment strategy.

Despite revealing the importance of DARS2 in bladder cancer, several questions remain unresolved. First, the precise molecular mechanisms linking DARS2, PINK1, and CDK4 require further investigation. It is unclear whether DARS2 influences mitophagy through other pathways or intersects with additional autophagy-related pathways. Additionally, the role of DARS2 may vary across different subtypes of bladder cancer, and the effects of different tumor microenvironments on DARS2-mediated mitophagy regulation requires further investigation. Future studies should explore the feasibility of targeting DARS2 and develop targeted therapies against DARS2 or PINK1, with the goal of providing more precise treatment options for bladder cancer patients.

In this study, we constructed a prognostic model by screening 16 mitophagy-related genes. Our model showed strong predictive value for overall survival, immune response, and chemotherapy outcomes in patients with BCa. DARS2, identified as a more valuable gene, was upregulated in bladder cancer tissues. Silencing DARS2 increased cellular senescence and inhibited the proliferation of bladder cancer cells by PINK1-mediated mitophagy. Mechanistically, inhibition of mitophagy by silencing DARS2 reduced CDK4 levels, causing cell cycle arrest in the G1 phase, with fewer cells entering the S and G2 phases. In conclusion, DARS2 and mitophagy exhibit important predictive effects in bladder cancer progression, and may be new targets for cancer treatment in the future.

BCa, Bladder cancer; NMIBC, Nonmuscle invasive bladder cancer; MIBC, Muscle invasive bladder cancer; OXPHOS, Oxidative phosphorylation; ROS, Reactive oxygen species; DARS2, Aspartyl-tRNA synthetase 2; SASPs, Senescence-associated secretory phenotypes; MRGs, Mitophagy-related genes; GSEA, Gene set enrichment analysis; DEGs, Differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; TMRE, Tetramethylrhodamine ethyl ester; CCCP, Carbonyl cyanide m-chlorophenyl hydrazone.

Funding

This study was supported by the Natural Science Foundation of Guangdong Province of China (2023A1515010236) (F.L.), the National Natural Science Foundation of China (82073162) (WL.T.) (82372867) (WL.T.).

Data availability statement

The datasets and experimental materials in this study are available from the corresponding author upon reasonable request.

Acknowledgments

We thank the Department of Urology, Nanfang Hospital, Southern Medical University and the Pathology Laboratory, School of Basic Medicine, Southern Medical University for their support of this work.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used ChatGPT 3.5 in order to improve language and readability. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

CRediT authorship contribution statement

Dongqing Li: Writing – original draft, Writing – review & editing, Validation, Methodology, Data curation, Formal analysis, Conceptualization, Project administration. Hang Su: Writing – original draft, Writing – review & editing, Resources, Methodology, Investigation, Formal analysis, Data curation. Yuan Huang: Software, Investigation, Visualization, Methodology. Zihuan Wang: Validation, Software, Data Curation. Jinge Zhang: Software, Methodology, Investigation. Chen Chen: Investigation, Methodology. Lina Hou: Visualization, Software, Formal analysis, Resources. Wanlong Tan: Supervision, Validation, Funding acquisition. Fei Li: Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

Conflict of interests

The authors have declared that no conflict of interest exists.

Ethics approval and consent to participate

This project was approved by the Ethics Committee of Nanfang Hospital, Southern Medical University. Prior to approval, all patients provided informed consent.

Consent for publication

All authors agreed to publish this study.

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DARS2 Promotes Bladder Cancer Progression by Enhancing PINK1-Mediated Mitophagy

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