Abstract

Simple Summary

   This study explored the protein expression levels of UCHL1, SNRNP200,
   and PAK4 in clear cell renal cell carcinoma (CCRCC) using advanced
   proteomic techniques. We found that UCHL1 and SNRNP200 are
   significantly upregulated, and PAK4 is downregulated in high-grade
   CCRCC, and all are involved in critical cellular pathways linked to
   cancer progression and poor clinical outcomes. Specifically, UCHL1 is
   implicated in the Akt signaling pathway, SNRNP200 plays a role in RNA
   splicing and cell cycle regulation, and PAK4 is associated with cell
   proliferation and invasion. The enhanced expression of UCHL1 and
   SNRNP200, and decreased expression of PAK4 correlate with shorter
   progression-free survival in CCRCC patients, suggesting their potential
   as prognostic markers and targets for therapeutic intervention. This
   research contributes to the understanding of CCRCC’s molecular dynamics
   and opens new avenues for targeted treatments.

Abstract

   Recent advancements in proteomics have enhanced our understanding of
   clear cell renal cell carcinoma (CCRCC). Utilizing a combination of
   liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by
   immunohistochemical validation, we investigated the expression levels
   of UCHL1, PAK4, and SNRNP200 in high-grade CCRCC samples. Our analysis
   also integrated Reactome pathway enrichment to elucidate the roles of
   these proteins in cancer-related pathways. Our results revealed
   significant upregulation of UCHL1 and SNRNP200 and downregulation of
   PAK4 in high-grade CCRCC tissues compared to non-cancerous tissues.
   UCHL1, a member of the ubiquitin carboxy-terminal hydrolase family,
   showed variable expression across different tissues and was notably
   involved in the Akt signaling pathway, which plays a critical role in
   cellular survival in various cancers. SNRNP200, a key component of the
   RNA splicing machinery, was found to be essential for proper cell cycle
   progression and possibly linked to autosomal dominant retinitis
   pigmentosa. PAK4’s role was noted as critical in RCC cell proliferation
   and invasion and its expression correlated significantly with poor
   progression-free survival in CCRCC. Additionally, the expression
   patterns of these proteins suggested potential as prognostic markers
   for aggressive disease phenotypes. This study confirms the upregulation
   of UCHL1, SNRNP200, and PAK4 as significant factors in the progression
   of high-grade CCRCC, linking their enhanced expression to poor clinical
   outcomes. These findings propose these proteins as potential prognostic
   markers and therapeutic targets in CCRCC, offering novel insights into
   the molecular landscape of this malignancy and highlighting the
   importance of targeted therapeutic interventions.

   Keywords: clear cell, renal, carcinoma, gene expression, spectrometry,
   immunohistochemistry

1. Introduction

   Clear cell renal cell carcinoma (CCRCC) accounts for approximately 3%
   of all cancer cases and is most frequently diagnosed in Western
   countries [[32]1,[33]2,[34]3]. In the industrialized world, CCRCC is
   often diagnosed incidentally during imaging tests such as computed
   tomography scans, ultrasounds, or magnetic resonance imaging [[35]4].
   The classic symptoms—hematuria, flank pain, and palpable masses—are
   observed in only 10% of patients. CCRCCs are tumors of renal stem cell
   origin that typically arise in the tubular epithelium and proximal
   nephron. They account for 75% of RCC cases and are more likely to
   develop hematogenous metastases to the liver, lungs, and bones [[36]4].
   Genetic factors play a significant role, with up to 45% of CCRCC cases
   involving somatic mutations or deletions in the VHL gene.

   Additionally, about 5% of CCRCC cases are due to hereditary VHL
   mutations linked to Von Hippel–Lindau disease and individuals with
   tuberous sclerosis gene mutations are more likely to develop bilateral
   RCC before age 46 [[37]5]. Modifiable risk factors for RCC include food
   and alcohol consumption, obesity, poorly controlled hypertension,
   smoking, and occupational exposures [[38]6]. Enhanced imaging protocols
   are essential to diagnose RCC at an earlier stage, alongside prevention
   programs that aim to improve survival rates and reduce disparities
   [[39]7].

   Patients with large primary tumors or those presenting with metastatic
   disease have observed the highest cancer-specific mortality rates
   [[40]8]. However, the effectiveness of treatments for advanced or
   metastatic CCRCC remains limited, prompting extensive molecular
   research to develop targeted therapies [[41]9]. Understanding the
   molecular complexities in advanced/metastatic CCRCC lays the groundwork
   for developing targeted therapies and refining treatment strategies.
   Recently, significant efforts were directed toward the proteomic
   profiling of CCRCC to identify protein biomarkers [[42]10,[43]11].
   These studies typically involve comparing protein profiles using The
   Cancer Genome Atlas (TCGA) data or contrasting tumor tissue with normal
   tissue [[44]12]. Modern proteomic techniques, such as tandem mass
   spectrometry, and innovative proteogenomic approaches that combine
   reference and sample-specific genomes are enhancing our understanding
   of cancer at the molecular level [[45]13,[46]14,[47]15].

   Essential proteins such as Ubiquitin C-terminal hydrolase 1 (UCHL1),
   which recycles ubiquitin from degraded proteins and facilitates protein
   degradation, are highly expressed in the nervous system and various
   carcinomas [[48]16,[49]17]. The role of the spliceosome, particularly
   the U5 snRNP’s 200 kDa helicase encoded by the SNRNP200 gene, is also
   crucial, given its association with tumor aggressiveness in prostate
   cancer [[50]18,[51]19]. Furthermore, the role of p21-activated kinases
   (PAKs), serine/threonine protein kinases, and downstream effectors of
   the Rho GTPases underscores their significance in cell proliferation,
   angiogenesis, tumorigenesis, and metastasis [[52]20,[53]21].

   Therefore, this study aimed to determine the expression levels of
   UCHL1, SNRNP200, and PAK4 proteins using immunohistochemistry (IHC)
   assay to elucidate the impact of molecular alterations driving
   phenotypic changes and to delineate the mechanisms of CCRCC
   pathobiology and progression for prospective exploration of
   personalized precision-based clinical care.

2. Materials and Methods

2.1. Patients and Cohorts

   This study leverages a CCRCC discovery cohort provided by the Clinical
   Proteomic Tumor Analysis Consortium (CPTAC), consisting of 110
   treatment-naive CCRCC cases alongside 84 paired-matched normal adjacent
   tissue (NAT) samples, as detailed in Clark et al. [[54]15]. Utilizing
   publicly available LC-MS/MS protein expression data and a thorough
   literature review, we identified and selected critical protein markers
   for further investigation and immunohistochemical (IHC) analysis
   ([55]Figure 1). The proteomic data, sourced from the publicly available
   CPTAC dataset, enabled an in-depth examination of protein markers
   contributing to CCRCC development and metastasis. Due to their
   biological significance, we selected proteins with increased expression
   (SNRNP200) and decreased expression (PAK4 and UCHL1) in tumors relative
   to normal adjacent tissues. The expression of the validated markers was
   then correlated with clinical data through IHC analysis, integrating
   proteomic data acquisition, marker validation, and clinical correlation
   into a methodological framework that enhances our understanding of
   CCRCC pathobiology and progression and informs potential clinical
   applications.

Figure 1.

   [56]Figure 1
   [57]Open in a new tab

   Study design: key steps of the study. Acquisition of protein data from
   the CPTAC discovery CCRCC cohort dataset and subsequent analysis of
   protein expression of tumor (T) and normal adjacent tissue (N) to
   select candidate protein markers. The selected protein markers were
   next subjected to immunohistochemical analysis. Assessment of the
   clinical value of the selected proteins for prognosis, diagnosis, and
   targeted therapy for CCRCC patients.

   The validation cohort included 52 ccRCC samples from patients aged 31
   to 84, with 23 participants also enrolled in the CPTAC discovery study.
   Comprehensive demographic and tumor characteristic data—age, gender,
   race, grade, and stage—were systematically documented and are
   summarized in [58]Supplementary Table S1. Of these patients, 26
   developed metastasis while another 26 did not during the five-year
   follow-up period. This investigation focused on adult CCRCC tumors
   confirmed histopathologically. Ethical approval was secured following
   CPTAC guidelines and the study excluded patients who had undergone
   systemic treatment or had additional cancers in the past 12 months.

2.2. Immunohistochemistry and Pathology Evaluation

   IHC analysis was conducted using the Dako Autostainer Link 48,
   following preprogrammed staining protocols and by employing the
   EnVision visualizing kit (Cat No. K800221-2, Dako, Agilent Technologies
   Inc., Carpinteria, CA, USA). Tissue samples were collected
   retrospectively, fixed in 10% neutral buffered formalin for 24 h, and
   then embedded in paraffin. Sections, 4 microns in thickness, were cut
   from formalin-fixed paraffin-embedded (FFPE) blocks and placed on
   positively charged slides. Antigen retrieval was performed using Dako
   Target Retrieval Solution, High pH (Cat No. S2367), in a PT Link
   Pre-Treatment Module (Dako, Agilent Technologies Inc.) at 97 °C for 20
   min. Following antigen retrieval, the sections were incubated with
   primary antibodies for 30 min at room temperature. For the clinical
   validation cohort, three primary antibodies were utilized, as detailed
   in [59]Table 1 The IHC-stained slides were manually evaluated by three
   independent pathologists using the H-score methodology to assess the
   results. The H-score is a semi-quantitative measure that combines both
   the intensity and the percentage of positive staining cells, resulting
   in a score ranging from 0 to 300. It is calculated as follows:
   H-score = (% of cells stained at intensity 1 × 1) + (% of cells stained
   at intensity 2 × 2)
   + (% of cells stained at intensity 3 × 3)

Table 1.

   Primary antibodies used for immunohistochemical analysis.
   Antibody Source Identifier Clone Dilution
   Rabbit polyclonal anti-UCHL1 Atlas Antibodies, Stockholm, Sweden Cat#
   HPA005993, RRID:AB_1858560 Polyclonal 1:3000
   Rabbit polyclonal anti-SNRNP200 Atlas Antibodies, Stockholm, Sweden
   Cat# HPA029321, RRID:AB_10604096 Polyclonal 1:225
   Mouse monoclonal anti-PAK4 ThermoFisher Scientific, Waltham, MA, USA
   Cat# MA5-26859, RRID:AB_2723443 OTI1C7 1:150
   [60]Open in a new tab

   In this formula:

   Intensity 1 indicates weak staining.

   Intensity 2 indicates moderate staining.

   Intensity 3 indicates strong staining.

   The percentages represent the proportion of cells exhibiting each
   staining intensity. By summing the products of the intensity scores and
   their respective percentages, the H-score provides a comprehensive
   assessment of the extent and intensity of IHC staining within a given
   specimen [[61]22].

   The cohort used to assess PAK4, SNRNP200, and UCHL1 expression via IHC
   analysis included 52 CCRCC formalin-fixed paraffin-embedded (FFPE)
   samples. IHC specimens were categorized into groups for downstream
   analyses based on H-score ranges. Patients with IHC scores above the
   calculated cutoff were placed in the High IHC score group, while those
   with scores below the cutoff were assigned to the Low IHC score group
   ([62]Table 2). For each protein, the average of all H-scores from the
   52 IHC slides was calculated to determine the cutoff value for
   categorizing patients into High IHC score and Low IHC score groups.
   Notably, one UCHL1 sample was excluded from this analysis.

Table 2.

   Classification of IHC specimens into groups for downstream analyses
   based on H-score ranges.
   Protein H-Score Range—High IHC Score Group H-Score Range—Low IHC Score
   Group Reaction
   PAK4 50–210 0–40 Cytoplasmic, membranous
   SNRNP200 50–150 0–40 Nuclear
   UCHL1 65–300 0–60 Cytoplasmic, membranous, nuclear
   [63]Open in a new tab

2.3. Digital Image Acquisition and Storage

   All IHC slides were digitally scanned with the automated ScanScope AT
   Turbo whole slide scanner (Aperio/Leica Microsystems, Vista, CA, USA)
   using 20× magnification. Digital images of the IHC slides were saved in
   .svs format and reviewed using ImageScope software (12.3.3 version,
   Aperio, Vista, CA, USA) to facilitate a high-quality examination by
   expert pathologists. The digital images were accessed through a
   password-protected Synology Rack Station server (RS18017xs+).

2.4. Statistical Analysis

   Protein abundance differences between normal and tumor tissues in CCRCC
   were computed using a non-parametric Wilcoxon rank-sum test. For
   comparison of IHC scores obtained for the High IHC score group and the
   Low IHC score group of the validation cohort, the Wilcoxon rank-sum
   test was performed. Differences in protein abundance between groups
   were also assessed using the Mann–Whitney U test. Overall survival (OS)
   and progression-free survival (PFS) analyses for the validation cohort
   were performed by dividing the validation cohort into two groups, the
   High IHC score group and the Low IHC score group (separately for each
   protein target), which were then compared using the Kaplan–Meier method
   and log-rank (Mantel–Cox) test. Hazard ratios (HR) and their 95%
   confidence intervals (CI) were calculated to assess the impact on
   survival outcomes. All data were analyzed using GraphPad Prism 10
   software. A p-value <0.05 was used to determine statistical
   significance in all analyses.

2.5. Reactome Pathway Enrichment Analysis

   To gain deeper insights into the cellular processes and tumor
   mechanisms associated with PAK4, SNRNP200, and UCHL1, we conducted a
   Reactome pathway enrichment analysis. This analysis aimed to identify
   the most significant Reactome pathways enriched for each protein,
   thereby elucidating their functional implications in CCRCC.

   Protein expression data for PAK4, SNRNP200, and UCHL1 were obtained
   from the publicly available CPTAC CCRCC dataset. The Reactome pathway
   enrichment analysis was performed using the Reactome database, which
   provides a comprehensive collection of biological pathways. The
   analysis was conducted with the Reactome Pathway Analysis tool, where
   the protein expression data were input to identify pathways
   significantly associated with PAK4, SNRNP200, and UCHL1. A statistical
   significance threshold of p < 0.05 was applied to determine the
   enriched pathways, ensuring that the identified pathways were highly
   likely to be biologically relevant.

3. Results

3.1. Protein Expression Values in CPTAC CCRCC

   Among the analyzed proteins, PAK4, SNRNP200, and UCHL1, SNRNP200
   exhibited significantly increased abundance in CCRCC tissues compared
   to NATs ([64]Figure 2). Conversely, PAK4 and UCHL1 showed elevated
   levels in NATs compared to tumor samples. These findings were
   statistically significant (p < 0.0001), as determined by the
   Mann–Whitney U test.

Figure 2.

   [65]Figure 2
   [66]Open in a new tab

   Protein abundance value distribution between normal adjacent tissue and
   tumor samples for PAK4, SNRNP200, and UCHL1 as measured by LC-MS/MS.
   Boxes outlined in green represent normal adjacent tissue samples and
   boxes outlined in red represent tumor samples (p < 0.0001).

3.2. Immunohistochemical Analysis of UCHL1, SNRNP200, and PAK4 Reveals
Protein Candidates for Further Correlation with Patients’ Clinical Outcomes

   The immunohistochemical analysis revealed distinct expression patterns
   for PAK4, SNRNP200, and UCHL1 in CCRCC cells ([67]Figure 3). PAK4 was
   expressed in both the cytoplasm and the nucleus of CCRCC cells.
   SNRNP200, on the other hand, was predominantly expressed in the nucleus
   of CCRCC cells. UCHL1 was found to be expressed in multiple cellular
   compartments, including the cytoplasm, membrane, and nucleus of CCRCC
   cells. After completing the IHC staining, the resulting scores for each
   protein were analyzed through a pathology evaluation as outlined in the
   [68]Section 2. Subsequently, the IHC scores were correlated with
   survival data of CCRCC patients, aiming to elucidate the potential
   prognostic significance of PAK4, SNRNP200, and UCHL1 expression levels
   in the context of patient outcomes, especially metastasis.

Figure 3.

   [69]Figure 3
   [70]Open in a new tab

   Immunohistochemical analysis showing immunostaining patterns in
   representative tumor sections for PAK4, SNRNP200, and UCHL1 high and
   low expression in the CCRCC validation cohort. Brown color indicates
   positive immunoreaction and blue indicates negative immunoreaction.

3.3. PAK4, SNRNP200, and UCHL1 Protein Expression as Measured by IHC

   Following the IHC analysis, we analyzed the scores for PAK4, SNRNP200,
   and UCHL1. As illustrated in [71]Figure 4, distinct distribution
   patterns were observed in the CCRCC validation cohort. For all
   proteins, the pronounced disparities between the two groups are
   statistically significant, indicating a pronounced dichotomy in their
   expression levels. However, while PAK4 and SNRNP200 had no significant
   outliers, highlighting the uniformity of expression across each
   subgroup, in the High IHC score group of the UCHL1 protein, notable
   outliers exist, indicating variability in its expression among certain
   patients.

Figure 4.

   [72]Figure 4
   [73]Open in a new tab

   Distribution of IHC scores obtained for PAK4, SNRNP200, and UCHL1. The
   scatter plots demonstrate the variation in scores between “high score”
   and “low score” groups across the different proteins. All plots show
   statistically significant differences (p < 0.0001), indicating
   pronounced disparities in IHC scores between the two groups. Notably,
   for UCHL1, the high score group exhibits a wider range of scores,
   indicating varying expression levels among individuals, unlike PAK4 and
   SNRNP200, where the high score groups are more tightly clustered
   without significant outliers.

3.4. PAK4, SNRNP200, and UCHL1 Protein Expression Correlated with Patients’
Clinical Outcomes

   The relationship between the expression levels of target proteins, as
   determined by IHC, and their clinical relevance was evaluated using
   survival analyses. This assessment involved comparing patient outcomes
   based on the highest and lowest IHC scores, as shown in [74]Figure 5.
   Both OS and PFS were monitored over a five-year follow-up period.
   Moreover, the impact of protein expression measured by IHC on patients’
   PFS and OS in the validation cohort is presented in [75]Table 3. Our
   findings indicate that higher expression levels of SNRNP200 and UCHL1
   are associated with poorer PFS (p = 0.002 and p = 0.02, respectively)
   and increased risk of progression (HR = 3.35 and 2.39, respectively),
   while lower expression of PAK4 correlates with poorer PFS (p = 0.03)
   and increased risk of disease progression (HR = 2.57). It should be
   noted that in our study, an HR > 1.0 for PAK4 reflects an unfavorable
   role, where lower expression levels correlate with a higher risk of
   disease progression. The expression levels of PAK4, SNRNP200, and UCHL1
   did not significantly affect OS (p > 0.05). Furthermore, PAK4 shows an
   HR of 1.96, SNRNP200 an HR of 1.41, and UCHL1 an HR of 1.69, all
   indicating potential increases in mortality risk, though none are
   statistically definitive due to CIs that span or approach 1. This
   suggests that while these proteins may influence survival, their
   effects are not conclusively significant.

Figure 5.

   [76]Figure 5
   [77]Open in a new tab

   IHC scores for PAK4 (A), SNRNP200 (B), and UCHL1 (C) were analyzed to
   determine their correlation with patients’ clinical outcomes,
   specifically PFS and OS. Patient outcomes were compared by categorizing
   them according to the highest and lowest IHC scores, providing a clear
   comparison between these two groups. Both OS and PFS were meticulously
   tracked over a five-year follow-up period.

Table 3.

   Impact of protein expression measured by IHC on patients’ survival in
   CCRCC validation cohort. HR and 95% CIs for PAK4, SNRNP200, and UCHL1,
   evaluating their impact on PFS and OS.
   Progression-Free Survival (PFS) Overall Survival (OS)
   Hazard Ratio (HR) 95% CI of HR Hazard Ratio (HR) 95% CI of HR
   PAK4 2.57 1.181–5.569 1.96 0.7027–5.476
   SNRNP200 3.35 1.427–7.842 1.41 0.498–3.995
   UCHL1 2.39 1.092–5.240 1.69 0.602–4.738
   [78]Open in a new tab

3.5. Identification of the Top Significantly Enriched Reactome Pathways
Associated with PAK4, SNRNP200, and UCHL1

   To gain deeper insights into the cellular processes and tumor
   mechanisms associated with PAK4, SNRNP200, and UCHL1, we conducted a
   detailed analysis of the most significant Reactome enrichment pathways,
   as illustrated in [79]Figure 6. The Reactome enrichment analysis was
   specifically designed to reveal the functional implications associated
   with each of the three proteins. The analysis identified statistically
   significant enriched terms for each protein, using a significance
   threshold of p < 0.05, thereby underscoring the distinct biological
   pathways influenced by each protein.

Figure 6.

   [80]Figure 6
   [81]Open in a new tab

   Significant Reactome Enrichment Pathways for PAK4, SNRNP200, and UCHL1.
   Visual representation of statistically significant (p-value < 0.05)
   enriched terms associated with each protein.

   The Reactome enrichment analysis for UCHL1 identified two significantly
   enriched pathways, “Deubiquitination” and “UCH Proteinases”, indicating
   UCHL1’s critical roles in protein ubiquitination processes. For
   SNRNP200, the analysis highlighted its significant involvement in mRNA
   splicing, as evidenced by the enriched pathways associated with this
   fundamental cellular mechanism. For PAK4, the Reactome enrichment
   analysis demonstrated significant enrichment in pathways associated
   with GTPase activity, specifically highlighting RHO GTPase and RAC
   GTPase pathways. Additionally, the analysis revealed significant
   involvement of PAK4 in pathways related to the nervous system.

4. Discussion

   Our investigation of CCRCC patients employed LC-MS/MS analysis from a
   publicly available CPTAC dataset, encompassing a cohort of 110 tumor
   samples. This analysis revealed a noteworthy upregulation in the
   expression levels of SNRNP200 and downregulation of UCHL1 and PAK4
   proteins in the CPTAC tumor samples compared to normal samples. We
   further validated these findings using immunohistochemistry (IHC) in an
   independent cohort of CCRCC patients’ FFPE samples, including
   high-grade CCRCC samples. Interestingly, in high-grade CCRCC, the
   protein expression levels of UCHL1 and SNRNP200 were found to be
   elevated, while PAK4 expression was decreased. Importantly, we
   identified a significant correlation between the particular expression
   profiles of these proteins and shortened PFS in patients with
   high-grade CCRCC. This suggests that UCHL1, SNRNP200, and PAK4 could
   serve as valuable prognostic markers, offering new insights into the
   progression and prognosis of this aggressive cancer subtype. In the
   context of the existing literature, the observed upregulation of UCHL1
   and SNRNP200 and the downregulation of PAK4 provide a novel dimension
   to the molecular landscape of high-grade CCRCC, offering insights that
   complement and extend the current understanding of this aggressive
   cancer subtype.

   In our study, IHC analysis identified distinct expression patterns for
   PAK4, SNRNP200, and UCHL1 in CCRCC cells. UCHL1 was localized in the
   cytoplasm, membrane, and nucleus, highlighting its multifunctional
   roles in cellular regulation [[82]17]. The results we obtained from the
   Reactome enrichment analysis for UCHL1 identified ‘Deubiquitination’
   and ‘UCH Proteinases’ as significantly enriched pathways, illuminating
   the involvement in crucial ubiquitin-mediated processes and protein
   degradation pathways. These pathways are vital for maintaining cellular
   homeostasis and play significant roles in cancer development and
   progression. The link between UCHL1 and deubiquitination underscores
   its significance in cellular functioning but also positions it as a
   potential therapeutic target [[83]23]. This finding calls for further
   research into the specific mechanisms through which UCHL1 influences
   tumorigenesis.

   The IHC scores obtained for UCHL1 showed a bimodal distribution, with
   significant outliers in the High IHC score group, indicating variation
   in expression among some patients. This variability suggests
   heterogeneity within the CCRCC patient population, potentially
   reflecting distinct molecular subtypes or clinical phenotypes. UCHL1 is
   differently expressed across tissues and tumors. While it is among the
   most abundant proteins in the brain, it has been identified as either
   an oncogene or a tumor suppressor in different carcinomas, such as
   nasopharyngeal, gastric, colorectal, and ovarian
   [[84]24,[85]25,[86]26]. In the kidney, UCHL1 is highly expressed in
   distal tubules and minimally in collecting ducts [[87]27].
   Interestingly, it was hypothesized that UCHL1 expression may be
   actively repressed during the initial stages of tumorigenesis, with its
   re-expression in later stages potentially serving as a reliable
   indicator of metastatic disease [[88]28]. This observation aligns with
   recent research showing higher frequencies of UCHL1 methylation in
   primary CCRCC compared to normal kidney epithelium, suggesting a
   complex role of UCHL1 in the progression of renal cancer [[89]29].

   UCHL1 overexpression in CCRCC was associated with a more aggressive
   potential and metastatic cancer phenotype and, in some cases, a poor
   prognosis for the patient [[90]29,[91]30,[92]31]. Our study confirmed
   these findings, as high expression of UCHL1 was associated with worse
   PFS. Seliger B et al. showed that the methylation of the UCHL1 DNA
   promoter leads to UCHL1 silencing in both ccRCC cell lines and primary
   lesions, mainly of clear cell subtype. This is corroborated by the
   observation that both the transcriptional and translational expression
   patterns exhibit a link with the methylation status of the CpG islands
   in the UCHL1 DNA promoter [[93]30]. UCHL1 promotes cell survival and
   growth in B-cell malignancies, significantly influencing the Akt
   signaling pathway, crucial for cell proliferation and survival in
   cancers like lymphoma [[94]32,[95]33,[96]34]. As a critical component
   of the proteasome targeting the ubiquitin-dependent protein degradation
   pathway, UCHL1 is involved in key cellular functions such as
   proliferation, cell cycling, apoptosis, and intracellular signaling
   [[97]35], all of which are often disrupted in cancer [[98]36]. Ummnanni
   R et al. described UCHL1 downregulation in prostate cancer and its
   tumor suppressor function in LNCaP prostate cancer [[99]37]. Their
   analysis showed significantly lower levels of UCHL1 in cancerous
   prostate tissue compared to nearby non-cancerous tissue [[100]37].

   Current therapeutic approaches targeting UCHL1 in CCRCC include
   investigating its role in tumor growth and resistance to treatments
   like bevacizumab. UCHL1 mediates the deubiquitination of KDM4B,
   stabilizing KDM4B protein levels, which then promotes VEGFA expression
   and angiogenesis. UCHL1’s interaction with KDM4B is crucial for CCRCC
   malignancy and targeting UCHL1 has been shown to suppress tumor growth
   and enhance sensitivity to bevacizumab [[101]38].

   Small nuclear ribonucleoprotein U5 subunit 200 (U5 snRNP200) is a
   conserved and essential component of the RNA splicing machinery,
   primarily localized in the nucleus, as confirmed by our IHC results.
   However, although U5 snRNP200 functions in the nucleus, previous
   research indicates that, in its absence, the U5 snRNP complex can form
   in the cytoplasm, subsequently assembling into the larger U5 snRNP
   complex within the nucleus [[102]39]. In terms of tissue-specific
   expression, SNRNP200 exhibits varied levels across different tissues;
   in the kidney, for example, expression is low in glomerular cells and
   medium in tubular cells [[103]27]. In hepatocellular carcinoma (HCC),
   its expression is significantly elevated and positively correlates with
   tumor size, serum AFP levels, organ invasion, and poor survival
   outcomes [[104]40,[105]41]. Furthermore, SNRNP200 is implicated in the
   aggressiveness of prostate cancer tumors, highlighting its role in
   tumor pathology and suggesting its potential as a target for
   therapeutic intervention [[106]19,[107]42]. Mutations in SNRNP200 have
   been linked to conditions like autosomal dominant retinitis pigmentosa
   and single-cell RNA-seq studies in acute myeloid leukemia (AML) cells
   have demonstrated a strong association between cell surface expression
   of U5 snRNP200 and components of the antiviral innate response pathway
   [[108]43,[109]44].

   The IHC scores for SNRNP200 are sharply divided between high and low,
   revealing a pronounced dichotomy in expression levels that could impact
   the clinical management of cancer. This distinction offers essential
   insights into patient stratification, prognosis, and therapeutic
   approaches. Furthermore, Reactome enrichment analysis has shown that
   SNRNP200 is notably enriched in pathways related to mRNA splicing,
   underscoring its crucial role in regulating splicing events that are
   vital for tumorigenesis. Dysregulation of mRNA splicing is recognized
   as a cancer hallmark, contributing substantially to tumor heterogeneity
   and progression by altering gene expression patterns [[110]45].
   SNRNP200 is a crucial part of the spliceosome and plays an important
   role in mRNA splicing in CCRCC [[111]46]. Targeting splicing issues in
   this cancer could offer potential therapeutic benefits. The
   overexpression of SNRNP200 in prostate cancer has been associated with
   tumor aggressiveness [[112]19]. This study is the first report
   demonstrating that, in humans, SNRNP200 is highly correlated with PFS
   in CCRCC. The identification of specific splicing isoforms associated
   with CCRCC may provide valuable biomarkers for disease diagnosis and
   prognosis.

   Current therapeutic approaches for targeting SNRNP200 in CCRCC are
   still emerging but there is significant potential based on findings
   from studies in other cancers, particularly AML. In AML, targeting
   SNRNP200 with engineered antibodies has demonstrated potential by
   enhancing the immune-mediated clearance of cancer cells and avoiding
   off-target effects [[113]44]. Combining SNRNP200-targeted therapies
   with existing treatments, such as immune checkpoint inhibitors, could
   improve outcomes by disrupting cancer cell processes and boosting
   immune responses. Further research is needed to fully explore its
   therapeutic potential in CCRCC.

   In our study, PAK4 was expressed in both the cytoplasm and the nucleus
   of CCRCC cells, indicating its potential involvement in intracellular
   signaling pathways. PAKs, often overexpressed or amplified in various
   human cancers, play a critical role in cell transformation, making them
   promising targets for therapeutic intervention
   [[114]47,[115]48,[116]49,[117]50]. PAKs are involved in regulating
   various cellular functions such as cell proliferation, angiogenesis,
   tumorigenesis, and metastasis [[118]51]. Specifically, in RCC, PAK1 has
   been shown to regulate cell proliferation, invasion,
   anchorage-independent growth, apoptosis, and resistance to
   5-fluorouracil [[119]52].

   In terms of clinical implications, the elevated expression of PAK4 is
   associated with early recurrence and reduced survival rates in patients
   with nonmetastatic CCRCC, particularly those classified as low-risk
   following nephrectomy [[120]53]. Interestingly, our IHC results showed
   that PAK4 expression was decreased in high-grade CCRCC, showing a
   strong association with metastasis appearance. Evidence suggests that
   PAKs play a crucial role in the biology of RCC, indicating an
   association between total PAK expression and aggressiveness and poor
   survival [[121]54]. Our study assessed the impact of PAK4 expression in
   surgically treated RCC and found a significant association with PFS in
   CCRCC, although PAK4 was not identified as a top-ranked gene in this
   context by Linehan et al. [[122]55]. This aligns with findings from
   Park et al., which indicated that the PAK4-Slug axis might exacerbate
   the prognosis of prostate cancer by promoting the
   epithelial–mesenchymal transition [[123]56]. Additionally, Liu et al.
   reported that high PAK4 expression is linked to early recurrence and
   poor survival in patients with non-metastatic clear cell RCC
   post-surgery [[124]53]. However, high PAK4 expression has been
   identified as a poor prognostic factor in two specific patient
   subgroups: those with early T stage (T1–2) disease and those with low
   Fuhrman grade (grade 1–2), underscoring the complex role of PAK4 in RCC
   and highlighting its potential as a target for personalized medicine
   approaches [[125]53]. Although many studies show high levels of PAK4 in
   RCC, there are also reports of varying expression levels depending on
   the study design and patient groups. Different trends in studies
   highlight the complexity of cancer biology and the need for careful
   interpretation. We think this explains the differences and emphasizes
   the importance of considering context in biomarker studies.

   Current therapeutic approaches for treating CCRCC are increasingly
   exploring the potential of targeting PAK4. Several small molecule
   inhibitors targeting PAK4, such as ATP-competitive inhibitors like
   PF-3758309 and LCH-7749944, have shown promising effects in different
   cancers in preclinical models by inhibiting PAK4 activity and
   subsequently reducing tumor growth and metastasis
   [[126]57,[127]58,[128]59]. However, the non-specificity and off-target
   effects of these inhibitors have limited their clinical success.
   Recently, the development of proteolysis targeting chimeras (PROTACs)
   targeting PAK4 has emerged as a novel therapeutic strategy. These
   PROTACs selectively degrade PAK4, offering a more targeted approach
   that may overcome the limitations of classical inhibitors. Early
   studies suggest that PAK4-targeting PROTACs not only inhibit tumor
   growth but also enhance immune responses, potentially improving
   outcomes when combined with existing therapies like immune checkpoint
   inhibitors. While these findings are promising, further investigation
   is needed to determine the safety, efficacy, and clinical utility of
   PAK4-targeted therapies in ccRCC.

5. Conclusions

   In conclusion, our comprehensive analysis utilizing LC-MS/MS and
   followed by immunohistochemistry has unveiled a significant elevation
   in UCHL1 and SNRNP200 and a decrease in PAK4 protein expression levels
   in high-grade clear CCRCC. The rigorous validation of these findings
   underscores the robustness of our results. Moreover, the observed
   correlation between increased expression of UCHL1 and SNRP200 and
   decreased expression of PAK4 and shorter PSF in high-grade CCRCC
   patients suggests prognostic relevance. This study not only expands our
   understanding of the molecular factors associated with CCRCC
   progression but also opens avenues for further research into targeted
   therapeutic interventions aimed at mitigating the adverse outcomes
   associated with UCHL1, SNRNP200, and PAK4 expression in this context.

6. Study Limitations

   This study has several limitations that should be acknowledged. First,
   the number of samples used for immunohistochemical (IHC) validation was
   relatively small, consisting of 52 CCRCC cases with formalin-fixed
   paraffin-embedded (FFPE) blocks. The limited sample size may affect the
   generalizability of the findings and the robustness of statistical
   analyses. Future studies with larger cohorts are needed to validate
   these results and strengthen the conclusions drawn from this research.

   Second, the IHC analysis was conducted using research antibodies rather
   than in vitro diagnostic (IVD) antibodies. The use of research
   antibodies was necessitated by the unavailability of suitable IVD
   antibodies for the targeted proteins. While research antibodies can
   provide valuable insights, their performance may vary and their
   specificity and sensitivity might not be as rigorously validated as IVD
   antibodies. This limitation should be considered when interpreting the
   results and the findings should be corroborated with additional studies
   using IVD antibodies when they become available.

Supplementary Materials

   The following supporting information can be downloaded at
   [129]https://www.mdpi.com/article/10.3390/cancers16162844/s1, Table S1.
   Characteristics of patients included in the study.
   [130]cancers-16-02844-s001.zip^ (139KB, zip)

Author Contributions

   Conceptualization, M.K. and I.K.-G.; methodology, G.B.; software, G.B.;
   validation, M.K. and I.K.-G.; formal analysis, M.K. and I.K.-G.;
   investigation, M.K. and I.K.-G..; resources, I.K.-G.; data curation,
   M.K. and I.K.-G.; writing—original draft preparation, M.K.;
   writing—review and editing, M.K. and I.K.-G.; visualization, M.K.;
   supervision, A.A. and M.W.; project administration, M.W.; funding
   acquisition, M.K. All authors have read and agreed to the published
   version of the manuscript.

Institutional Review Board Statement

   The study was conducted in accordance with the Declaration of Helsinki
   and approved by the Institutional Ethics Committee of Poznań University
   of Medical Sciences KB: 302/21.

Informed Consent Statement

   Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

   All data on which the manuscript was based, if not already included in
   its text, are available from the corresponding author on a reasonable
   request.

Conflicts of Interest

   The authors declare no conflicts of interest.

Funding Statement

   This research received no external funding.

Footnotes

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References