Evaluating trophinin associated protein as a biomarker of prognosis and therapy response in renal cell carcinoma

Abstract

Background

Trophinin Associated Protein (TROAP) has been implicated in some tumors, yet its role in renal cell carcinoma (RCC) remains underexplored. This study aims to elucidate the prognostic and therapeutic implications of TROAP in RCC, encompassing different subtypes.

Methods

Firstly, we identified the expression patterns of TROAP across various tumors within the TCGA pan-cancer cohort. Subsequently, the prognostic significance of TROAP was validated in three TCGA RCC cohorts and a local cohort. Finally, we conducted functional enrichment analysis, somatic mutations and copy number variations, assessed therapeutic response cohorts, and performed in vitro experiments to explore the biological characteristics of TROAP.

Results

TROAP serves as an unfavorable factor in both the TCGA RCC datasets and our local cohort. Functional enrichment analysis and in vitro experiments have demonstrated its oncogene effect in promoting tumor progression. Additionally, the relationship between TROAP expression and gene mutations in RCC appears to be limited. Furthermore, elevated TROAP expression is associated with reduced efficacy of RCC therapies, including nivolumab and everolimus.

Conclusions

Our findings illustrate TROAP as a pivotal biomarker for prognosis and therapeutic response in RCC. Elevated TROAP expression is indicative of aggressive tumor behavior and resistance to conventional therapies, making it a valuable target for personalized treatment strategies in RCC management.

Introduction

Renal cell carcinoma (RCC) is identified as the third most common urologic malignancy and ranks eighth in overall global cancer prevalence [1]. Annually, it is responsible for initiating over 400,000 new cases and contributes to approximately 175,000 fatalities worldwide [2, 3]. Histological and genetic examinations reveal various RCC subtypes. This investigation primarily addresses three widespread subtypes: renal clear cell carcinoma, chromophobe renal cell carcinoma and papillary renal cell carcinoma [4]. Notably, renal clear cell carcinoma emerges as the predominant subtype, comprising about 70% of all RCC cases [5, 6].

Over the last decade, advancements in the management of RCC have been substantial, leading to the incidental detection of many small renal tumors during routine screenings. Despite these improvements, approximately 17% of patients present with distant metastases at the time of diagnosis [7, 8]. Currently, surgical intervention remains the principal therapeutic approach for renal clear cell carcinoma [4]. In cases of advanced kidney cancer where surgery is not viable, molecularly targeted therapies have been employed to prolong life; however, these treatments are effective in only 30% of cases [9, 10]. Consequently, there is a pressing necessity to delve into the pathogenesis of RCC to unearth potential biomarkers that could aid in prognosis and therapeutic response monitoring.

Trophinin-associated protein (TROAP), also referred to as tastin, plays a crucial role in maintaining centrosome integrity and orchestrating spindle assembly during mitosis [11]. Composed of 778 amino acids, TROAP is a cytoplasmic protein enriched in proline and features three homologous domains [12]. It is encoded by the human TROAP gene located on chromosome 12q13.12 [13]. Initially, researchers identified TROAP’s association with bystin and trophinin, proteins implicated in the early adhesion processes between blastocysts and uterine epithelial cells, potentially forming complexes critical for embryo implantation [14]. In the context of KIRC, TROAP is suspected to enhance tumor proliferation, migration, and metastasis through interaction with STAT3 [15]. Nevertheless, a comprehensive understanding of TROAP’s prognostic significance and its role in pan-RCC remains elusive.

Materials and methods

Public data sources

TCGA-KIRC (renal clear cell carcinoma), TCGA-KIRP (papillary renal cell carcinoma) and TCGA-KICH (chromophobe renal cell carcinoma) Level 3 high-throughput RNA sequencing data, mutation data, and clinical information were acquired from the UCSC XENA platform (https://xenabrowser.net/datapages/). The advanced RCC cohorts were derived from previously published studies [16].

Pan-cancer evaluation

We utilized the R package “TCGAplot” (version 4.0.0) [17], which integrates expression profiles and follow-up information from the TCGA Pan-Cancer cohort. This package enabled us to perform differential expression analysis of TROAP in both non-matched and matched samples within the Pan-Cancer dataset, using the Wilcoxon test for statistical validation. Additionally, we conducted Cox regression analysis to evaluate the prognostic significance of TROAP.

Prognostic analysis

To evaluate the prognostic significance of TROAP, we utilized the R packages “timeROC” (0.4), “survival” (3.5-5) (https://CRAN.R-project.org/package=survival) and “survminer” (0.4.9). These tools were used to calculate the area under the receiver operating characteristic (ROC) curve (AUC), and to perform Cox regression and Kaplan-Meier (KM) analyses. For the KM survival analysis, TROAP expression levels were categorized as high or low based on the optimal cut-off value.

Functional enrichment

We assessed the correlation between TROAP expression and other mRNA expressions using correlation analysis. The “clusterProfiler” R package (version 4.8.1) [18] was employed for Gene Set Enrichment Analysis (GSEA) to perform functional enrichment.

Immunohistochemistry

In this study, RCC tissue samples were obtained from Shanghai Zhuoli Biotech Company. The tissue microarray (HKid-CRCC150CS-01) consisted of a total of 148 valid samples derived from patients diagnosed with KIRC. This tissue microarray includes 74 cases of KIRC and 74 matched normal tissue adjacent to the tumor (NAT). The collection of tissue samples was ethically approved by the Ethics Committee of Shanghai Zhuoli Biotech Company (SHLLS-BA-22101102). Prior to embedding in paraffin, samples were fixed in 4% formaldehyde. Each tissue block was sectioned into 4 μm thick slices, treated with a 1% H2O2 solution, and blocked with non-immunogenic goat serum. The sections were incubated overnight at 4 °C with primary antibodies, followed by a 30-minute room temperature incubation with biotinylated secondary antibodies to bind to the primary antibodies. The specific immunohistochemistry (IHC) staining procedure was consistent with our previous studies [19]. Scoring for immunoreactive cells was based on the percentage of positive staining cells and the intensity of staining, calculated by adding the percentage score and the intensity score. The scoring for the percentage of immunoreactive cells was defined as follows: 0 (0%), 1 (1–10%), 2 (11–50%), and 3 (> 50%). Staining intensity was visually scored and categorized as follows: 0 (negative), 1 (weak), 2 (moderate), and 3 (strong). The antibody used was an anti-TROAP antibody (Novus Biologicals, NBP1-92532).

Immune cell infiltration

The immune cell infiltration in TCGA-KIRC, TCGA-KIRP, and TCGA-KICH datasets was analyzed using the “IOBR” R package (version 0.99.9) [20]. Specifically, we employed the xCELL algorithm within the “IOBR” package to compute Type 2 T helper (Th2) cell scores for each sample. Spearman correlation analysis was then performed to evaluate the relationship between TROAP expression and Th2 cell infiltration.

Western blotting

Cell lysates were generated by harvesting cells and lysing them in RIPA buffer supplemented with protease inhibitors. Proteins from these lysates were separated using SDS-PAGE and then transferred onto PVDF membranes. These membranes were initially blocked using 5% non-fat milk before being incubated with a primary anti-TROAP antibody (Novus Biologicals, NBP1-92532) a, followed by incubation with an anti-β-ACTIN-Rb secondary antibody (Novus Biologicals). Subsequent to antibody binding, the membranes were washed three times in PBST, each wash lasting 10 min, in preparation for detection. β-ACTIN, utilized as a normalization control, was also added at a 1:5000 dilution (Novus Biologicals). The intensities of the protein bands were quantified using Image J software.

Cell culture and transfection

The Caki-1 and 786-O cell lines were acquired from Beina Chuanglian Biotechnology Institute (Beijing, China). Prior to use, all cell lines underwent mycoplasma testing and were authenticated via short tandem repeat (STR) profiling. The cells were maintained at 37 °C in an atmosphere containing 5% CO₂. Transfections were executed with GP-transfect-Mate (GenePharma, Suzhou, China), adhering to the supplied protocol [21]. Both a negative control (NC) and TROAP-specific siRNA (Table S1, Ribobio, Guangzhou, China) were introduced to the RCC cells as per the experimental design.

Cell counting Kit-8 assay

A 96-well plate was set up with roughly 4,000 cells that had been transiently transfected. This setup was replicated across five wells for each condition. The cells were incubated for time intervals of 2, 24, 48, and 72 h, after which 100 µL of a 1:9 dilution of CCK-8 solution in culture medium was administered to each well. Following an additional incubation period of 2 h, the optical density (OD) was measured at 450 nm using a spectrophotometer to assess cell viability.

Cell migration assay

To evaluate cell migration, we seeded about 40,000 transiently transfected cells in the upper chamber of a transwell apparatus using serum-free medium, while the lower chamber was filled with complete medium. The cells were incubated at 37 °C in an environment containing 5% CO₂ for a duration of 48 h. Post-incubation, cells were washed with saline, fixed with paraformaldehyde, and stained with 0.1% crystal violet. The stained cells were then visualized and quantified using microscopy.

Colony formation assay

Cells were plated at a density of 1,000 cells per well in 6-well plates and incubated at 37 °C with 5% CO₂ for a period of two weeks. Upon completion of the incubation period, the colonies were rinsed twice with cold phosphate-buffered saline (PBS), fixed using 4% paraformaldehyde for 15 min, and subsequently stained with 1% crystal violet for 20 min at ambient temperature. After staining, the colonies that were clearly visible were enumerated.

Mutation analysis

We utilized the R package ‘maftools’ to explore potential differences in gene mutation profiles between high and low TROAP expression groups [22]. This analysis allowed us to quantitatively assess the genomic variations and understand the mutational landscape associated with varying levels of TROAP expression.

Statistical analysis

Spearman’s method was employed for correlation assessments, while continuous variables were compared using the Wilcoxon rank-sum test. Categorical variables were analyzed using either the Chi-squared test or Fisher’s exact test as appropriate.

Results

Expression profile of TROAP across various tumor

As depicted in Fig. 1A, within the TCGA pan-cancer dataset, TROAP exhibits varying expression patterns across different cancer types. Notably, in three subtypes of RCC, TROAP is consistently expressed at higher levels in cancerous tissues. This phenomenon is similarly observed in matched samples from the TCGA pan-cancer dataset (Fig. 1B). Additionally, we observed that TROAP expression is higher in all cancer tissues compared to normal tissues. However, overall, its expression level in RCC is lower than in most other cancer types.

Fig. 1

Expression Pattern of TROAP in The Cancer Genome Atlas. (A) Differential analysis of TROAP in unmatched normal and cancer tissues. (B) Differential analysis of TROAP in matched normal and cancer tissues. Cox regression analysis reveals the prognostic value of TROAP in pan-cancer, (C) Overall Survival, (D) Progression Free Interval. *p < 0.05; **p < 0.01; ***p < 0.001, **** p < 0.0001; NS, No Significance

Moreover, in pan-cancer prognostic analysis using either Overall Survival (OS) or Progression Free Interval (PFI) as endpoints, TROAP is associated with poor prognosis in RCC (Fig. 1C-D). These findings suggest that TROAP holds considerable potential as a biomarker for RCC. Furthermore, TROAP serves as an adverse prognostic factor in most cancer types, except for ovarian cancer (OV) and thymoma (THYM), where it acts as a protective factor (P < 0.05).

TROAP is an adverse prognostic factor for RCC

Initially, to evaluate the prognostic relevance of TROAP in RCC, we conducted Kaplan-Meier survival analysis, AUC assessments, and Cox regression analysis across KIRC, KICH, and KIRP subtypes. As illustrated in Fig. 2A, using KICH as an example, we observed that patients grouped by high expression of TROAP had poorer outcomes in Kaplan-Meier survival analysis with OS and PFI as endpoints. Furthermore, the ROC analysis at three time points consistently showed AUC values exceeding 0.7. Subsequent univariate and multivariate Cox regression analyses confirmed that elevated TROAP expression serves as an independent prognostic risk factor in KICH (Fig. 2A, Table S2). Similar patterns were also noted in KIRC and KIRP, although some ROC AUC values in KIRC were slightly below 0.7 (Fig. 2B-C, Table S2). These findings conclusively establish TROAP as an independent adverse prognostic factor in RCC.

Fig. 2

Prognostic Value of TROAP in RCC. Kaplan-Meier survival analysis, time-dependent ROC, and multivariate Cox regression analysis, (A) chromophobe renal cell carcinoma, (B) renal clear cell carcinoma, (C) papillary renal cell carcinoma

Immunohistochemistry in local cohort

Subsequently, in our local cohort of KIRC, we conducted immunohistochemistry to corroborate findings from public datasets. The prognostic utility of TROAP in KIRC was further investigated using a tissue microarray. As depicted in Fig. 3A and B, TROAP was predominantly located in the cytoplasm. Upon evaluating the local cohort, we observed that TROAP expression was significantly higher in cancer compared to benign tissues (Fig. 3C). Additionally, in higher-stage groups (above Stage II), TROAP expression exceeded that in lower-stage groups (Stage II or below) (Fig. 3D). Survival analysis of cases with follow-up data revealed that higher TROAP expression was associated with shorter OS (Fig. 3E). These findings from the IHC align with our transcriptomic data.

Fig. 3

Immunohistochemistry of TROAP expression in clinical samples. (A) Representative images of tumor tissues. (B) Representative images of benign tissues. (C) Scoring statistics for benign and tumor tissues. (D) Scoring statistics for low grade and high grade tissues. (E) Kaplan-Meier survival analysis

Functional enrichment analysis

Following the elucidation of TROAP’s prognostic importance in RCC, we further explored its potential biological roles. Employing Gene set enrichment analysis based on Hallmarks pathways, we displayed the top five pathways with the highest enrichment scores in three RCC subtypes (Fig. 4). Interestingly, across KIRC, KIRP, and KIRP, the pathways of E2F_TARGETS, G2M_CHECKPOINT and MYC_TARGETS were consistently enriched. These findings suggest that TROAP may exert an oncogenic effect in RCC.

Fig. 4

Functional enrichment analysis of TROAP

Gene mutation regard to TROAP

In our transcriptomic-focused study, we analyzed the role of TROAP in relation to gene mutations. As depicted in Fig. 5A, in KIRC, mutation frequencies exceeding 20% were observed in three genes: VHL at 40%, PBRM1 at 41%, and TTN at 24%. In KICH, TP53 exhibited a notably high mutation frequency of 31%, with other genes showing frequencies below 10% (Fig. 5B). For KIRP, the highest mutation frequency was 19% for TTN, with others remaining below 10% (Fig. 5C). However, after grouping by the median expression levels of TROAP, most gene mutation frequencies showed no significant differences. Notable exceptions included a higher mutation frequency of BAP1 in the high TROAP expression group in KIRC, and a lower mutation frequency of LRP2 in the high TROAP expression group in KIRP. These findings suggest that TROAP’s relationship with gene mutations in RCC may be limited.

Fig. 5

Gene mutation landscape related to TROAP. (A) Renal Clear Cell Carcinoma. (B) Chromophobe. (C) Renal Papillary Cell Carcinoma. *P < 0.05; **P < 0.01; ***P < 0.001

TROAP is associated with poor therapeutic response

Upon establishing TROAP as an adverse prognostic factor in RCC, we endeavored to explore its correlation with the therapeutic response. In the advanced RCC cohort, we observed that patients with high TROAP expression exhibited poorer outcomes under nivolumab treatment, consistent across both OS and PFS metrics (Fig. 6A). Similarly, patients with high TROAP expression also showed worse prognosis in terms of PFS when treated with everolimus (Fig. 6A).

Fig. 6

TROAP is a biomarker for therapy response in RCC. (A) Survival analysis of TROAP in advanced RCC cohorts. (B) Submap analysis forecasting immunotherapy response across pan-RCC. (C) Correlation between TROAP expression and Th2 cell in pan-RCC

To further substantiate the connection between TROAP expression and immunotherapy response, we conducted submap analysis within the RCC cohorts. While results were statistically non-significant in the KICH cohort, a similar trend was noted elsewhere; lower TROAP expression was associated with a higher response rate to anti-PD-1 immunotherapy (Fig. 6B). These findings suggest TROAP’s potential as a predictive marker for RCC immunotherapy and everolimus responses.

Additionally, we initiated a preliminary investigation into the mechanisms linking TROAP to immunotherapy response. Through xCELL immune infiltration analysis, we identified a significant negative correlation between TROAP and Th2 cells in RCC, indicating that TROAP may associated with the aberrant immune microenvironment in RCC (Fig. 7C).

Fig. 7

Oncogene effect of TROAP in vitro. (A) Western blot analysis was employed to evaluate the effectiveness of TROAP silencing in Caki-1 and 786-O cell lines. (B) Clone formation to determine the colony-forming ability of Caki-1 and 786-O cell lines. (C) The CCK-8 assay was conducted to measure the proliferation rates of Caki-1 and 786-O cell lines. (D) Transwell assays were performed to assess the invasive potential of Caki-1 and 786-O cell lines. *P < 0.05; **P < 0.01; ***P < 0.001;****P < 0.0001

Oncogene effect of TROAP in vitro

In our final series of experiments, we investigated the function of TROAP in RCC cell lines. Three si-RNA sequences targeting TROAP were designed and transfected into Caki-1 and 786-O cell lines. As illustrated in Fig. 7A, si-1 and si-2 demonstrated high knockdown efficiency, and were therefore chosen for further analysis. Following TROAP knockdown, a significant decrease in cellular proliferation was observed in the plate cloning assay (Fig. 7B). Likewise, cell viability was notably reduced in the CCK-8 assay after TROAP silencing (Fig. 7C). Moreover, the transwell migration assay showed a substantial reduction in cell migration capabilities upon TROAP depletion (Fig. 7D). These results collectively highlight the oncogene effect of TROAP in RCC cell lines.

Discussion

RCC represents the most prevalent malignant tumor of the upper urinary tract within the urinary system, constituting 3% of all adult malignancies [23, 24]. Advances in diagnostic and therapeutic techniques have elevated the 5-year survival rate for RCC to 74%, with advanced metastases occurring in only 12% of cases [25]. Beyond surgical interventions, other treatment approaches often fail to yield satisfactory outcomes. Consequently, identifying sensitive biomarkers and specific therapeutic targets for tailored treatment strategies holds critical clinical importance for enhancing the survival rates of RCC patients.

In this study, through multi-omics data and experimental validation, we have identified the potential of TROAP as a biomarker for RCC. Extensive research has demonstrated TROAP’s elevated expression across various malignancies including prostate cancer [26], breast cancer [27], colorectal cancer [28], hepatocellular carcinoma [29], and gastric cancer [30]. Han Liu and colleagues have elucidated that TROAP modulates the cell division cycle 20 (CDC20) and affects spindle microtubules (ASPM), thereby facilitating malignant tumor progression during the S and G2 phases of the cell cycle [31]. Additionally, TROAP has been shown to influence tumor progression through diverse pathways, such as enhancing disease advancement via the Wnt3/survival protein signaling pathway in prostate cancer [26]. Notably, TROAP expression is positively associated with clinical severity in hepatocellular carcinoma, which correlates with poorer overall and disease-free survival [29]. These findings are consistent with our observations in RCC.

Furthermore, we observed that TROAP expression is relatively lower in RCC compared to most other cancers. We hypothesize two potential reasons for this phenomenon. Firstly, TROAP may exhibit tissue specificity. As shown in Fig. 1A, the top three cancers with the highest TROAP expression are Testicular Germ Cell Tumors (TGCT), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) and Uterine Carcinosarcoma (UCS), all of which are tumors of the reproductive system. Secondly, gene mutations often influence mRNA expression. However, our multi-omics analysis indicates that TROAP’s relationship with gene mutations in RCC may be limited. This could also contribute to the lower expression of TROAP in RCC compared to other cancers. The above perspectives are preliminary hypotheses. We plan to validate these ideas through more comprehensive experiments and analyses in our future work.

In our functional enrichment analysis, the pathways E2F_TARGETS, G2M_CHECKPOINT, and MYC_TARGETS were consistently enriched across KIRC, KIRP and KICH. E2F1, which has been extensively studied in RCC, exhibits dual functions in VHL-defective renal cell carcinoma, largely depending on the balance between HIF1α and HIF2α. It appears that E2F1 may act oncogene effect in advanced tumors predominantly expressing HIF2α, while functioning as a tumor suppressor in others [32]. The G2M checkpoint is crucial for maintaining genomic stability by ensuring DNA integrity and blocking the mitotic progression of cells with compromised DNA. Alterations in the G2M checkpoint or its downstream signaling pathways can influence cancer progression and may provide markers for assessing tumor behavior, response to treatment, or prognosis [33]. Additionally, targeting the G2M checkpoint might offer therapeutic opportunities to enhance the sensitivity of cancer cells to DNA-damaging agents or to selectively trigger apoptosis in ccRCC with defective DNA repair mechanisms [34]. Similarly, other research groups have recognized the clinical significance of MYC pathways in renal cancer [35]. Therefore, our findings are corroborated by other studies, further validating the significant role of in RCC.

Additionally, we validated TROAP’s function within RCC cell lines, despite previous reports by Wang et al. detailing cell assays on TROAP [15]. Our study employed different cell lines and experimental techniques, enhancing our understanding of TROAP in vitro. More significantly, we reported for the first time that TROAP can serve as a biomarker for the response to RCC pharmacotherapy. Nivolumab and everolimus are critical components of the therapeutic regimen for advanced RCC, and our results contribute new evidence supporting the clinical translational potential of TROAP.

Furthermore, we conducted a preliminary analysis of the mechanisms by which high TROAP expression correlates with poor immunotherapy response. Through immune cell infiltration analysis in three RCC contexts, we found a positive correlation between TROAP expression and Th2 cell infiltration. Research indicates that inhibiting Th2 cells during immunotherapy can significantly bolster the host immune response and inhibit tumor growth [36]. Suppression of Th2 cytokines has been shown to enhance the infiltration and proliferation of cytotoxic CD8 + T cells, and to increase their secretion of cytotoxic cytokines, thereby activating antitumor T cell immunity [37].

However, this study recognizes several limitations. Constraints in time restricted a thorough mechanistic investigation of TROAP’s function in RCC. Planned future studies aim to systematically explore and amend these limitations.

In conclusion, our research underscores the critical role of TROAP in RCC, establishing its potential as a biomarker for prognosis and therapeutic response.