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Comprehensive pan-cancer analysis indicates UCHL5 as a novel cancer biomarker and promotes cervical cancer progression through the Wnt signaling pathway

Biology Direct volume 19, Article number: 139 (2024) Cite this article

Abstract

Background

UCHL5 was initially recognized as a multifunctional molecule. While recent research has highlighted its involvement in tumor malignant biological behaviors, its specific role in promoting tumor cell apoptosis has drawn particular attention. However, the precise relationship between UCHL5 and various tumor types, as well as its influence within the immune microenvironment, remains unclear.

Methods

The transcriptomic data and clinicopathological parameters across 33 cancer types were obtained from TCGA. Clinical pathological parameters of tumor patients, including gender, age, survival time, and staging, are utilized to evaluate the association between UCHL5 and pan-cancer characteristics. The prognostic significance of UCHL5 was evaluated through Cox analysis and Kaplan-Meier (K-M) methods. Protein expression data for UCHL5 were obtained from The Human Protein Atlas database, and its subcellular localization was further investigated. Additionally, potential correlations between UCHL5 and factors such as tumor-infiltrating immune cells, immunomodulators, microsatellite instability (MSI), and tumor mutation burden (TMB) were explored. The relationship between UCHL5 and immunotherapy efficacy was also assessed in independent cohorts, including IMvigor210, GSE78220, GSE67501, and GSE168204. Finally, the impact of UCHL5 on the malignant biological behavior of cervical cancer cells was investigated through in vitro experiments, along with an exploration of the underlying mechanisms.

Results

We observed that UCHL5 expression levels were elevated in 11 types of cancer tissues compared to their corresponding normal tissues, while levels were lower in five tumor types. Additionally, UCHL5 expression displayed a significant correlation with tumor stage in BRCA, KIRC, LUAD, and TGCT. Cox and K-M analysis indicated that UCHL5 expression was significantly associated with prognosis in KIRC, KICH, CESC, ACC, and UVM. UCHL5 expression was negatively associated with stromal and immune scores in certain cancers. In terms of immune cell infiltration, UCHL5 expression in UCEC, SKCM, and COAD showed a negative correlation with regulatory T cells (Tregs). Furthermore, UCHL5 was widely associated with three types of immunomodulators. It also demonstrated a significant relationship with MSI and TMB in certain cancers and was connected to the immunotherapy efficacy. Finally, in vitro experiments confirmed that UCHL5 knockout enhances apoptosis in cervical cancer cells and disrupts Wnt/β-catenin signaling.

Conclusions

Pan-cancer analysis indicates that UCHL5 is dysregulated in various tumor tissues and is closely associated with survival prognosis, the tumor immune microenvironment, and the efficacy of immunotherapy in certain cancer types. UCHL5 shows promise as a predictive biomarker, and its specific regulatory mechanisms across different cancers warrant further investigation.

Introduction

The ubiquitin-proteasome system (UPS) is essential for protein degradation in eukaryotic cells [1]. It employs ubiquitin (Ub) to tag proteins with polyubiquitin chains for precise recognition and degradation by the proteasome [2]. Ubiquitination is a reversible process, regulated by the addition or removal of these chains through the actions of ubiquitinating and deubiquitinating enzymes (DUBs) [2, 3]. Research has highlighted the UPS’s involvement in different cancer-promoting mechanisms, including cell cycle regulation, programmed cell death, DNA repair, and oncogenic pathways [4,5,6,7]. Consequently, the ubiquitination has emerged as a promising target for anti-cancer therapies, particularly following the approval of proteasome inhibitors such as bortezomib and carfilzomib for multiple myeloma treatment. Nevertheless, the roles of specific components of the ubiquitination process in human cancer are still not fully elucidated [8].

Ubiquitin C-terminal hydrolases (UCHs) are a crucial subset of deubiquitinating enzymes [9]. The UCH family comprises enzymes that primarily recognize and hydrolyze the isopeptide bond at the C-terminal glycine of ubiquitin [10, 11]. By hydrolyzing these bonds in ubiquitin-protein chains, UCHs release ubiquitin, allowing the cell to precisely regulate the stability and function of ubiquitinated proteins [12, 13]. Ubiquitin C-terminal hydrolase L5 (UCHL5) is a significant member of the UCHs family. UCHL5 mainly features two structural domains: the N-terminal UCH catalytic domain and the C-terminal ULD structural domain, which comprises four α-helices [14]. UCHL5 can cleave ubiquitin from the ends of polyubiquitin chains, thereby rescuing poorly ubiquitinated proteins from degradation [15]. Disabling the UCHL5 in mice leads to embryonic death, underscoring its essential role [16]. UCHL5 is not only involved in regulating normal cellular functions but is also connected to the development and progression of different diseases. Increasing evidence confirms its role in various diseases, including cancer, making it a promising research target in these fields [11, 17]. UCHL5 is involved in multiple protein complexes and signaling pathways [18]. Dysregulation of UCHL5 has been observed in some solid tumors and is linked to poorer survival and a higher risk of cancer recurrence [19]. Additionally, study has confirmed that the activation of UCHL5 contributes to tumor immune resistance [20], emphasizing its potential value in regulating the tumor immune microenvironment (TIME). Therefore, understanding UCHL5’s functions and potential mechanisms in human cancer can provide crucial insights for developing new therapeutic strategies.

Pan-cancer research is a comprehensive analytical approach that spans multiple cancer types, aiming to reveal both the commonalities and specificities among different cancers [21, 22]. By integrating genomic, transcriptomic, epigenomic, and proteomic data across various cancers, Pan-cancer research allows for a deeper understanding of the fundamental mechanisms driving cancer initiation and progression. This study explored UCHL5 expression in pan-cancer and its potential effect on clinical outcomes and the TIME. The research focused on the correlation of UCHL5 with stromal and immune cells, as well as immune modulators. It also examined the relationship between UCHL5 and key predictors of immune checkpoint inhibitors (ICIs) efficacy, such as tumor mutation burden (TMB) and microsatellite instability (MSI). Additionally, we explored the potential value of UCHL5 in predicting the efficacy of ICIs in different immunotherapy cohorts. Finally, the effect of UCHL5 on the biological behavior of cervical cancer cells was investigated through in vitro experiments, along with an exploration of the underlying pathways.

Materials and methods

Data collection

The transcriptomic data and clinicopathological parameters for 33 cancers in this study were obtained from the UCSC Xena (https://xenabrowser.net/). Table 1 lists all the cancer types included in the study. Only samples with complete transcriptome data and corresponding patient survival information were included. Somatic mutation data were sourced from the TCGA (https://portal.gdc.cancer.gov/repository). Perl (v. 5.32.1.1) was utilized to process the transcriptomic data and generate the UCHL5 expression matrix across the 33 tumors. Additionally, UCHL5 subcellular localization and protein expression data were retrieved from The Human Protein Atlas (HPA) (https://www.proteinatlas.org) [23]. The subcellular localization of UCHL5 was also analyzed using the UniProt database (https://www.uniprot.org/) [24]. Transcriptomic and clinical data for the immunotherapy cohorts GSE78220, GSE67501, and GSE168204 were downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). Data for the additional immunotherapy cohort IMvigor210 were obtained from prior research [25].

Table 1 Cancer Types and Abbreviations Included in the Study
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Correlation of UCHL5 with clinical variables and survival prognosis

The R package “limma” was utilized for differential expression analysis to assess the variation of UCHL5 expression between cancer tissues and adjacent normal tissues. Following this, the association between UCHL5 expression and clinical variables (such as tumor stage, gender, and age) was analyzed further, with visualization provided by the R package “ggpubr”. Univariate Cox regression was conducted using the “survminer” and “survival” packages to evaluate the effect of UCHL5 expression on patient survival. The “forestplot” package was employed for visualizing the Cox analysis results. Finally, survival curves were created with the Kaplan-Meier method to assess the effect of UCHL5 expression on overall survival (OS) of patients.

Correlation between UCHL5 expression and tumor microenvironment components

R packages “limma” and “ESTIMATE” were utilized to estimate the quantities of stromal and immune cells in tumor tissues from each patient, providing corresponding stromal and immune scores [26]. The relationship between UCHL5 expression and these immune and stromal scores across various cancers was then analyzed in greater detail, with the R packages “ggplot2,” “ggpubr,” and “ggExtra” employed for result visualization. Additionally, the CIBERSORT method was used to assess the infiltration levels of different immune cell subpopulations [27], and the association between UCHL5 expression and the infiltration levels of these immune cell subpopulations was further examined. Besides, the TISIDB platform (http://cis.hku.hk/TISIDB/index.php) was utilized to assess the relationship between the expression of UCHL5 and immune inhibitors, immune stimulators, and MHC molecules [28].

Correlation of UCHL5 expression with TMB and MSI

TMB refers to the total number of genetic mutations present in a tumor’s DNA per megabase of genome analyzed. It serves as an indicator of the overall mutation load within a tumor, reflecting the extent of genetic alterations that have occurred [29]. High TMB is often associated with increased likelihood of immune checkpoint inhibitor (ICI) responses, as tumors with more mutations are more likely to produce neoantigens that the immune system can recognize and attack. Thus, TMB is used to predict how well a patient might respond to immunotherapy treatments [30, 31]. Meanwhile, MSI refers to the phenomenon where repeated sequences in microsatellite regions of the genome become altered in tumor cells. The presence of MSI can result in the accumulation of numerous mutations in the tumor, generating neoantigens that may serve as potential targets for immunotherapy [32]. To explore the link of UCHL5 expression to TMB or MSI, a correlation radar map was generated using the R package “fmsb”. Additionally, the link between UCHL5 and immunotherapy efficacy was confirmed in four separate cohorts. Based on the method of Mo et al. [33], patients with partial or complete responses were classified as responders, while those with stable or progressive disease were categorized as non-responders. UCHL5 expression levels between the non-responder and responder subgroups were compared, with the results visualized using “ggplot2” and “ggpubr”.

Western Blot (WB)

Proteins were extracted using RIPA lysis buffer, quantified by the BCA assay, and separated via SDS-PAGE. Following transfer to PVDF membranes, proteins were blocked with 5% non-fat milk and incubated overnight at 4 °C with primary antibodies against UCHL5 (1:2000 dilution, Proteintech, China), Cleaved Caspase-3 (1:1000 dilution, Abcam, UK), BCL-2 (1:1000 dilution, Abcam, UK), BAX (1:2000 dilution, Proteintech, China), β-catenin (1:1000 dilution, Abcam, UK), c-Myc (1:1000 dilution, Abcam, UK), Poly-ubiquitin (1:500 dilution, Santa Cruz Biotechnology, USA) and β-actin (1:200000 dilution, Abclonal, China). Membranes were then incubated with HRP-conjugated secondary antibodies and visualized using enhanced chemiluminescence.

Cell culture and transfection

Siha and Hela cells were cultured in DMEM medium (Gibco, Thermo Fisher Scientific, USA), supplemented with 10% FBS, at 37 °C in a 5% CO2 atmosphere. The Siha and Hela cell lines were obtained from ATCC (American Type Culture Collection, USA). Cells were transfected with either non-targeting control siRNA (siNC) or UCHL5-targeting siRNA (siUCHL5-1 and siUCHL5-2, GenePharma, China) using jetPRIME® transfection reagent (Polyplus-transfection, France), following the manufacturer’s protocol. The efficiency of the transfections was verified by WB.

Cell proliferation assay

Cell proliferation was assessed with the Cell Counting Kit-8 (CCK-8, Dojindo, Kumamoto, Japan). Cells were plated in 96-well plates at a density of 1,000 cells per well. Cell viability was determined by adding CCK-8 solution to each well, followed by a 4-h incubation at 37 °C, and measuring absorbance.

Cell migration assay

Cell migration was evaluated through wound-healing and transwell assays. In the transwell assay, 10,000 cells were seeded into the upper chambers of transwell inserts (Labselect, China) containing 200 µL of serum-free medium, with the lower chambers containing 800 µL of medium with 10% FBS. After 24 h, migrated cells were fixed with 4% paraformaldehyde and stained with crystal violet. The number of migrated cells was then imaged and quantified. For the wound-healing assay, transfected cells were cultured in six-well plates until 80% confluence. A 200 µL pipette tip was employed to make a straight wound, and after PBS washing, fresh medium was added to allow cells to migrate into the wound area. The migration distance was measured at multiple points over 12 h.

Statistical analysis

Statistical analyses were conducted using R language (v 4.2.2) and GraphPad (v 9.4.1). The Wilcoxon test, with FDR correction applied to the p-values, compared UCHL5 expression between normal and tumor samples. The Kruskal-Wallis test was performed to evaluate the overall differences in UCHL5 expression across different cancer types. K–M method was utilized to plot survival data, and the Cox proportional hazards model assessed the relationship between UCHL5 expression and survival to calculate hazard ratios. Spearman’s method was employed to analyze correlations between UCHL5 expression and MSI or TMB levels. A two-tailed P < 0.05 or FDR < 0.05 was considered significant.

Results

Subcellular localization of UCHL5

UCHL5 is a deubiquitinase involved in various cellular processes, including protein degradation regulation. The UniProt and HPA databases were consulted to determine its intracellular localization, revealing that UCHL5 is distributed across the cytoplasm and nucleus (Fig. 1A, B). Additionally, immunofluorescence data from the HPA database confirmed the presence of UCHL5 in these compartments within both A-431 (Fig. 1C) and U2OS cells (Fig. 1D). This widespread localization highlights UCHL5’s role in multiple cellular functions. Additionally, analyses from the Consensus and HPA databases indicate that UCHL5 is highly expressed in human skeletal muscle, liver, tongue, and pancreas, while it shows lower expression levels in the fallopian tubes, cervix, testis, and choroid plexus (Supplementary Fig. 1).

Fig. 1
figure 1

Subcellular localization of UCHL5. (A, B) Subcellular localization of UCHL5 in the HPA and UniProt databases. (C, D) Immunofluorescence images illustrating the intracellular localization of UCHL5 in A-431 and U2-OS cells

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UCHL5 expression in pan-cancer

The UCHL5 mRNA data from 33 types of tumors, as shown in Fig. 2A, demonstrate differential expression of UCHL5 across various cancers. In the differential expression assessment, UCHL5 exhibits differential expression across cancer tissues and corresponding normal tissues in 16 types of tumors. It is highly expressed in cancer tissues of LIHC, LUAD, LUSC, BLCA, BRCA, ESCA, CESC, CHOL, COAD, STAD, and UCEC, while showing lower expression in GBM, KICH, KIRC, KIRP, and THCA (Fig. 2B). Additionally, UCHL5 expression is significantly associated with patient age in ESCA, LUSC, OV, STAD, and THCA (Fig. 2C). It is also correlated with stage in BRCA, KIRC, LUAD, and TGCT (Fig. 2D). Furthermore, UCHL5 expression varies by gender in LUAD and SARC (Fig. 2E).

We further examined the UCHL5 protein expression in various tumor tissues and corresponding normal tissues using HPA data. Figure 3A illustrates the proportion of UCHL5 protein expression levels (high, medium, and low) across 20 cancer types, illustrating the distinct distribution of these expression levels within each cancer type. The categorization into “high,” “medium,” and “low” expression is based on the staining intensity information provided by the antibody-specific data in the HPA database. IHC staining in the HPA database additionally display the expression of UCHL5 in normal tissues and tumor tissues from various locations (Fig. 3B).

Fig. 2
figure 2

UCHL5 Expression in Pan-cancer. (A) The UCHL5 mRNA data from 33 types of tumors in TCGA. (B) UCHL5 expression across tumor tissues and corresponding normal tissues. (C-E) Relationships between UCHL5 expression and patient age, stage and gender. *FDR < 0.05, **FDR < 0.01, ***FDR < 0.001

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Fig. 3
figure 3

Expression of UCHL5 protein in Pan-cancer. (A) Proportion of UCHL5 protein expression levels (high, medium, and low) across 20 different cancer types, as determined by staining intensity in the HPA database. (B) Representative IHC of UCHL5 in different tumor tissues and corresponding normal tissues using HPA data

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Prognostic significance of UCHL5 across 33 cancers

Cox analysis reveals a significant relationship between UCHL5 expression and disease risk in multiple cancers, including ACC, BLCA, CESC, KIRP, KICH, KIRC, LUAD, OV, PAAD, SKCM, and THCA. Specifically, elevated UCHL5 expression serves as a risk variable in ACC, BLCA, CESC, KICH, KIRP, LUAD, PAAD, and THCA, while it acts as a protective variable in KIRC, OV, and SKCM (Fig. 4A). Furthermore, Kaplan-Meier curve analysis indicates that low UCHL5 expression correlates with longer OS in individuals with KICH, CESC, ACC, and UVM, but is associated with shorter OS in KIRC (Fig. 4B-F). These findings suggest that UCHL5 could serve as a valuable prognostic biomarker, offering insights into the diverse roles of UCHL5 across different cancer types.

Fig. 4
figure 4

Prognostic significance of UCHL5 in Pan-cancer. (A) Cox analysis of UCHL5 in Pan-cancer. (B-F) K-M analysis of UCHL5 in Pan-cancer

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Exploring the association between UCHL5 and TIME in pan-cancer

ESTIMATE algorithm analysis reveals that UCHL5 expression is negatively correlated with immune scores in GBM, STAD, LGG, LUAD, KIRP, and TGCT, and negatively correlated with stromal scores in GBM, STAD, LGG, PCPG, SARC, HNSC, and THYM (Fig. 5A, B). Additionally, immune cell infiltration analysis using the CIBERSORT algorithm (Fig. 6) shows that UCHL5 expression is positively correlated with M2 macrophages and activated natural killer cells in TCGT, but negatively correlated with naive B cells and infiltration. In THYM, UCHL5 expression is negatively correlated with resting mast cells, M2 macrophages, and activated natural killer cells. In UCEC, SKCM, and COAD, UCHL5 expression is negatively correlated with Tregs.

Analysis of immune modulators reveals that UCHL5 expression is positively correlated with TGFBR1 in UVM, negatively correlated with PVRL2 in UVM and KICH, and positively correlated with CD274 in PCGC (Fig. 7A). Among 45 immune stimulators analyzed, UCHL5 expression is positively correlated with ULBP1 and negatively correlated with TNFRSF25 in TCGT. In LIHC, UCHL5 expression is positively correlated with IL6R, while in KIRP, it is negatively correlated with TNFRSF25 (Fig. 7B). Furthermore, MHC molecule correlation analysis reveals that UCHL5 expression is positively correlated with TAPBP in UVM and LGG, negatively correlated with TAP2 in PCGC, and positively correlated with B2M in KIRC (Fig. 7C).

Fig. 5
figure 5

ESTIMATE algorithm analysis of UCHL5 in pan-cancer. (A) Correlation between UCHL5 mRNA expression and immune score. (B) Correlation between UCHL5 mRNA expression and stromal score

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Fig. 6
figure 6

CIBERSORT algorithm analysis of UCHL5 in pan-cancer

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Fig. 7
figure 7

Immune modulators analysis of UCHL5 in pan-cancer. (A-C) Correlation between UCHL5 mRNA expression and immune inhibitors (A), stimulators (B), and MHC molecules (C)

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UCHL5 expression and immunotherapy response

TMB and MSI have been validated as predictive biomarkers for the efficacy of immunotherapy. Correlation radar plots (Fig. 8A) and lollipop charts (Fig. 8B) illustrate that UCHL5 expression is positively correlated with both MSI and TMB in several cancer types, including UCEC, STAD, and READ. Moreover, UCHL5 expression shows a significant association with TMB in ACC, UVM, THYM, SKCM, PRAD, PAAD, LIHC, LUAD, LUSC, LAML, HNSC, GBM, BRCA, and BLCA (Supplementary Table e1). Additionally, UCHL5 expression is significantly correlated with MSI in TGCT, LGG, GBM, and DLBC (Supplementary Table e2). Subsequently, we investigated the relationship between UCHL5 expression and the effectiveness of immunotherapy across four distinct cancer immunotherapy cohorts. Our analysis revealed that in the PD1 blockade treatment cohort for metastatic melanoma (GSE168204), responders exhibited significantly lower levels of UCHL5 expression compared to non-responders (Fig. 8C). While this trend was also noted in another melanoma cohort (GSE78220) and a renal cell carcinoma cohort (GSE67501), the differences did not reach statistical significance (Fig. 8D, E). However, in the advanced urothelial carcinoma cohort (IMvigor210), a notable finding emerged: responders to atezolizumab treatment had significantly higher UCHL5 expression compared to non-responders (Fig. 8F). This suggests that UCHL5 expression may play a distinct role in influencing the response to different types of immunotherapy, warranting further investigation into its potential as a biomarker for predicting treatment outcomes.

Fig. 8
figure 8

UCHL5 expression and immunotherapy response. (A) Overlayed correlation plots showing the relationship between UCHL5 mRNA expression and both TMB and MSI across different cancer types. (B) Lollipop charts displaying the ranking and statistical significance of the correlation analysis for TMB and MSI with UCHL5 expression. (C-F) UCHL5 expression in non-response and response subgroups across the GSE168204, GSE67501, GSE78220 and IMvigor210 cohorts

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UCHL5 knockdown enhances apoptosis and impairs Wnt/β-catenin pathway in cervical cancer

To explore the role of UCHL5 in apoptosis and Wnt/β-catenin signaling, we conducted a series of experiments using Hela and Siha cells transfected with either non-targeting control siRNA (siNC) or UCHL5-targeting siRNA (siUCHL5-1 and siUCHL5-2). The effects of UCHL5 knockdown on cell viability was assessed using CCK-8 assays. As shown in Fig. 9A, transfection with UCHL5-siRNA significantly inhibited cell viability compared to control cells. Moreover, Transwell migration and wound healing assays revealed that UCHL5 knockdown substantially impaired cell migration (Fig. 9B-E). Western blot analysis confirmed that UCHL5 knockdown effectively decreased UCHL5 protein levels in both cell lines (Fig. 9F). This reduction was associated with a significant increase in Cleaved Caspase-3 and the pro-apoptotic protein BAX, coupled with a corresponding decrease in the anti-apoptotic protein BCL-2, indicating that UCHL5 knockdown promotes apoptosis in these cells (Fig. 9F). Additionally, UCHL5 knockdown caused a significant reduction in β-catenin and c-Myc levels, key components of the Wnt/β-catenin signaling pathway, suggesting that UCHL5 may stabilize β-catenin and facilitate Wnt/β-catenin signaling (Fig. 9G). To further explore whether the cellular phenotypes regulated by UCHL5 were mediated through the Wnt/β-catenin pathway, we introduced Wnt3a, an activator of the Wnt/β-catenin pathway. The results demonstrated that, compared to UCHL5 knockdown alone, Wnt3a alleviated the reduction in β-catenin and c-Myc levels induced by UCHL5 knockdown (Fig. 9H). This mitigation was also associated with a notable decrease in Cleaved Caspase-3 and BAX, along with a corresponding increase in BCL-2 expression (Fig. 9I).

UCHL5, part of the ubiquitin C-terminal hydrolase family, facilitates the deubiquitination of substrates, which stabilizes target proteins. Our findings indicate that UCHL5 knockdown increased polyubiquitination levels in both Hela and Siha cells, suggesting that UCHL5 plays a critical role in regulating protein ubiquitination (Fig. 9J). Taken together, these findings suggest that UCHL5 is a crucial regulator of the Wnt/β-catenin signaling pathway and apoptosis. Knockdown of UCHL5 leads to diminished Wnt/β-catenin signaling, increased polyubiquitination, and enhanced apoptosis. Therefore, UCHL5 may regulate the cell apoptosis through the Wnt/β-catenin pathway in cervical cancer cells.

Fig. 9
figure 9

UCHL5 knockdown enhances apoptosis and impairs Wnt/β-catenin signaling in cervical cancer. (A) Transfection with UCHL5-siRNA significantly inhibited cell viability compared to control cells. (B-E) Wound healing and transwell migration assays revealed that UCHL5 knockdown substantially impaired cell migration. (F) Western blot analysis confirmed that UCHL5 knockdown effectively reduced UCHL5 protein levels in both cell lines, which was associated with a significant increase in Cleaved Caspase-3 and the pro-apoptotic protein BAX, alongside a corresponding decrease in the anti-apoptotic protein BCL-2. (G) UCHL5 knockdown resulted in a marked reduction in β-catenin and c-Myc levels. (H) Compared to UCHL5 knockdown alone, Wnt3a alleviated the reduction in β-catenin and c-Myc levels induced by UCHL5 knockdown. (I) Wnt3a alleviated the significant increase in Cleaved Caspase-3 and BAX, as well as the corresponding decrease in BCL-2 expression induced by UCHL5 knockdown. (J) UCHL5 knockdown increased polyubiquitination levels in both Hela and Siha cells

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Discussion

Ubiquitination is a critical post-translational modification that plays a significant role in tumor development [34, 35]. Besides abnormal transcription, another mechanism leading to abnormal protein expression in tumors is the disruption of the protein degradation pathway, with the ubiquitination degradation pathway being the most common. The process of deubiquitination, carried out by deubiquitinases, is essential for regulating ubiquitination [36, 37]. UCHL5 has emerged as a key player, attracting increasing interest due to its involvement in inflammatory diseases and tumor progression [38].

In the present research, we conducted an extensive evaluation of UCHL5 across pan-cancer, identifying its potential value as a biomarker for tumor prognosis and immunotherapy prediction. We observed that UCHL5 is highly expressed in cancer tissues of CESC, BRCA, ESCA, CHOL, COAD, BLCA, LIHC, LUSC, STAD, LUAD, and UCEC, while showing lower expression in GBM, KICH, KIRC, KIRP, and THCA, indicating significant heterogeneity in UCHL5 expression across different cancers. Although UCHL5 expression is generally unrelated to age, gender, and tumor stage in most cancers, it is notably associated with tumor stage in BRCA, KIRC, LUAD, and TGCT, suggesting that UCHL5 UCHL5 may play a role in the progression of these cancers. Chow et al. demonstrated that the UCHL5 inhibitor b-AP15 overcomes cisplatin resistance in urothelial carcinoma by suppressing tumor stem cell properties [39]. In another study on bladder cancer, UCHL5 was shown to promote tumor cell proliferation and migration by activating c-Myc through the AKT/mTOR signaling pathway [40]. In a study of estrogen receptor-positive BRCA, UCHL5 inhibitors were found to induce cell cycle arrest and promote apoptosis in tumor cells, and were associated with caspase activation and endoplasmic reticulum stress [41]. Previous studies have found that increased UCHL5 expression in renal cell carcinoma (RCC) cells reduces the antigen processing and presentation by B cells within RCC tumors. Further research revealed that UCHL5 expression in RCC tumors is associated with transport proteins, and its abundance is significantly elevated in the blood of individuals with advanced RCC, suggesting that circulating UCHL5 could be a potential prognostic biomarker for RCC [42]. In a study of LUAD, UCHL5 levels were found to be associated with tumor size, lymph node infiltration, and TNM staging, with high expression indicating a poorer survival for LUAD patients [43]. Further research showed that silencing UCHL5 in LUAD cells significantly inhibited cell proliferation and reduced the expression of key cell cycle proteins [43]. Additionally, the UCHL5 inhibitor b-AP15 induces effective tumor suppression in non-small cell lung cancer [44]. In a study of colorectal cancer (CRC), UCHL5 was shown to be significantly involved in tumor advancement and resistance to 5-fluorouracil, suggesting that targeting UCHL5 could be a promising therapeutic strategy for CRC [45]. In studies of PAAD, overexpression of UCHL5 significantly affects cell growth, stem-like properties, and migration abilities. This effect may be related to UCHL5’s ability to directly deubiquitinate and stabilize the ELK3 protein [46]. Interestingly, a study on gastric cancer found that cytoplasmic UCHL5 tumor positivity might be associated with improved prognosis. The analysis indicated that positive cytoplasmic UCHL5 expression in tumors is associated to increased survival rates in patients with smaller tumors and those at stage I-II [47]. Notably, in this study, low UCHL5 expression was associated with longer OS in KICH individuals but shorter OS in KIRC, indicating that UCHL5 may exhibit a dual function depending on the genetic background or molecular subtype of the tumor. This duality suggests the possibility that UCHL5 can have opposing effects even within tumors of the same anatomical site but different pathological types. Overall, these findings suggest that assessing UCHL5 expression could be valuable for predicting prognosis in certain tumors and that targeting UCHL5 may represent a potential therapeutic strategy for some cancers.

Through the aforementioned pan-cancer analysis, we further highlighted the significant role of UCHL5 in CESC. In the 33 cancer types studied, UCHL5 was expressed at high levels in CESC. Additionally, Cox regression and Kaplan-Meier analyses indicate that UCHL5 expression is significantly associated with CESC prognosis, suggesting its potential as a key biomarker for tumor progression and patient outcome in CESC. However, the functional role of UCHL5 in CESC remains to be explored. The bioinformatics analysis of this study indicates that UCHL5 is significantly upregulated in cervical cancer (CESC) tissues, enhancing its potential as a key participant in CESC. Therefore, we propose that UCHL5 may be involved in the progression of CESC. Subsequent in vitro studies revealed that UCHL5 knockout significantly inhibited cervical cancer cell proliferation and migration. Additionally, UCHL5 knockout led to an increase in apoptosis markers such as Cleaved Caspase-3 and BAX, accompanied by a decrease in the anti-apoptotic protein BCL-2, indicating that UCHL5 promotes tumor cell survival in cervical cancer by regulating apoptosis pathways.

The Wnt/β-catenin signaling pathway plays a vital role in various biological functions, ranging from embryonic development to tumor progression [48]. Previous studies have confirmed that UCHL5 serves as a positive modulator of the Wnt signaling pathway in african clawed frog embryos [49]. In hepatocellular carcinoma, UCHL5 promotes glycolysis through activation of the Wnt/β-catenin pathway and thus promotes hepatocellular carcinoma progression [38]. Additionally, a study on endometrial cancer observed that UCHL5 accelerates tumor growth by activating the Wnt/β-catenin signaling pathway [50]. Interestingly, a study involving cell lines such as SW480, MCF7, and A549 demonstrated that UCHL5 exhibits a negative regulatory effect on the Wnt signaling pathway [51]. The results indicate that UCHL5 regulates the Wnt signaling pathway differently, or even oppositely, depending on the biological context. In our study based on cervical cancer cell lines, UCHL5 knockout led to a decrease in key components of the Wnt/β-catenin signaling pathway, namely β-catenin and c-Myc. To explore this further, we introduced Wnt3a, an activator of the pathway, which partially restored β-catenin and c-Myc levels, mitigating the effects of UCHL5 knockdown. This was accompanied by a decrease in Cleaved Caspase-3 and BAX, and an increase in BCL-2, suggesting that UCHL5’s regulation of apoptosis might be mediated through the Wnt/β-catenin signaling pathway. Additionally, our findings support UCHL5’s role as a deubiquitinase, as its knockout increased polyubiquitination levels, highlighting its critical role in regulating protein ubiquitination. Overall, our study suggests that UCHL5 is a key regulator of the Wnt/β-catenin signaling pathway and apoptosis in cervical cancer cells, with its knockdown leading to weakened Wnt/β-catenin signaling and enhanced apoptosis, underscoring its potential as a therapeutic target for modulating cervical cancer cell cycle, proliferation, and survival.

The tumor immune microenvironment and its associated immune responses are crucial factors influencing tumor prognosis. Previous studies have shown that UCHL5 is positively involved in the innate immune response in Drosophila through its N-terminal Uch domain [52]. Additionally, the activation of UCHL5 has been shown to play a role in promoting tumor immune resistance [20]. To further explore the potential role of UCHL5 in the tumor immune microenvironment, we first analyzed the correlation between UCHL5 expression and immune cell infiltration. The ESTIMATE algorithm reveals that UCHL5 expression is negatively correlated with immune and stromal scores in several cancers, including GBM, STAD, and LGG. CIBERSORT analysis shows UCHL5 positively correlates with M2 macrophages and activated NK cells in TGCT but negatively with these cells in THYM. It also negatively correlates with Tregs in UCEC, SKCM, and COAD. In addition, our analysis of immune modulators revealed several consistent correlations between UCHL5 expression and key immune factors across different cancer types. Notably, UCHL5 was positively correlated with CD274 (PD-L1) in certain cancers, which is a critical immune checkpoint protein involved in immune evasion by inhibiting T-cell activation [53]. This suggests that UCHL5 may contribute to immune escape mechanisms in these tumors. Conversely, the negative correlation between UCHL5 and TNFRSF25, a receptor involved in T-cell responses [54], suggests that UCHL5 may also impact immune suppression in certain cancer types. Similarly, the correlation with TAPBP, a protein involved in antigen presentation [55], in certain cancers further supports the hypothesis that UCHL5 could influence the immune response by modulating antigen processing and presentation. These findings highlight a potential role for UCHL5 in shaping the immune microenvironment of tumors, possibly by modulating immune evasion and influencing immune surveillance pathways. However, while these correlations are intriguing, the precise mechanisms underlying these associations remain to be elucidated. Further functional studies, including in vitro and in vivo experiments, are required to confirm how UCHL5 might interact with these immune modulators and its broader implications for tumor immunity and immune therapy responses. Overall, these analyses underscore the complex role of UCHL5 in modulating immune and stromal components across various cancers, indicating its potential as a biomarker or therapeutic target in cancer immunology.

In recent years, immune checkpoint inhibitors (ICIs) have emerged as a key strategy in cancer therapy. Identifying biomarkers to predict ICIs treatment response is of great importance. MSI and TMB have been established as effective predictors of ICI efficacy in certain tumors [56, 57]. TMB measures the total number of mutations in a tumor sample and is typically associated with responsiveness to immune checkpoint inhibitors, as tumors with high mutational burden may have a better response to immunotherapy. MSI assesses variations in microsatellite regions of a tumor, which are prone to errors during DNA replication. High MSI usually indicates defects in mismatch repair genes, which are also linked to immune therapy responsiveness. Both MSI and TMB share a similar underlying principle as biomarkers for predicting immune therapy efficacy: mutations generate altered peptides processed by MHC, leading to the formation of new antigens that elicit effective anti-tumor immune responses. Consequently, there may be an overlap between tumors with high TMB and those with high MSI or mismatch repair deficiencies [58]. Our analysis reveals that UCHL5 shows consistent correlations with TMB and MSI in UCEC, STAD, and READ. However, in GBM, UCHL5 expression is inversely related to TMB and positively associated with MSI. This contradictory phenomenon may arise from UCHL5 influencing these two mutational characteristics through different mechanisms, reflecting its complex role in various mutational types or mechanisms, or potentially due to tumor heterogeneity. Understanding this relationship will require further research to elucidate UCHL5’s specific functions and mechanisms within the tumor immune microenvironment.

To further explore UCHL5’s potential as a predictive marker for immune checkpoint inhibitor (ICI) efficacy, we examined the correlation between UCHL5 expression and treatment outcomes across four ICI treatment cohorts. The results indicated that in the anti-PD1 treatment cohort for metastatic melanoma, non-responders had significantly higher UCHL5 expression compared to responders, suggesting a potential negative correlation between UCHL5 and PD1 treatment response. Conversely, in the cohort receiving atezolizumab for advanced urothelial carcinoma, UCHL5 expression was significantly lower in non-responders compared to responders, showing an opposite trend. These findings suggest that UCHL5’s role in ICI treatment may be cancer-specific, highlighting the need for further research to clarify its precise function and mechanisms in predicting ICI efficacy across different tumor types.

Conclusion

This study is the first to reveal the potential value of UCHL5 as a pan-cancer prognostic biomarker. The findings indicate that UCHL5 may act as a prognostic predictor for various cancers. Additionally, UCHL5 is broadly connected to various parameters of the TIME across multiple cancers, indicating its potential role in immune regulation and predicting immune therapy responses. Future research should focus on exploring the specific regulatory mechanisms of UCHL5 within different tumor immune microenvironments to further validate its potential as a predictor of immune therapy efficacy.

Data availability

The data are available from the corresponding author for reasonable requests. The R scripts utilised in this study are publicly available at https://github.com/dyz1989/Scripts.git.

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Acknowledgements

The authors sincerely acknowledge the publicly available TCGA, GEO, HPA, UCSC and TISIDB databases. We also wish to thank Dr. Yuanliang Gu for his valuable assistance with the statistical analysis during the revision of this manuscript.

Funding

The present research was funded by the Postgraduate Research and Practice Innovation Project of Anhui Medical University (NO: YJS20230019).

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  1. Lingling Bao and Yuefei Wu contributed equally to this work.

Authors and Affiliations

  1. Department of Hematology and Oncology, Beilun Branch of the First Affiliated Hospital, College of Medicine, Zhejiang University, Ningbo, China

    Lingling Bao, Kailang Li & Xin Xu

  2. Department of Hematology and Oncology, Beilun People’s Hospital, Ningbo, China

    Lingling Bao, Kailang Li & Xin Xu

  3. Radiotherapy Department, The Second People’s Hospital of Wuhu, Wuhu, China

    Yuefei Wu

  4. Department of Radiation Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China

    Zhengting Ren

  5. Oncology Department of Integrated Traditional Chinese and Western Medicine, First Affiliated Hospital of Anhui Medical University, Hefei, China

    Yi Huang, Yue Jiang, Yingquan Ye & Zhongxuan Gui

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Contributions

L.B, Y.Y, and Z.G conceived and designed the study, Y.W, Y.H, and Y.J collected the data and clinical specimens. L.B, Y.Y, Y.W, and Z.R analyzed the data, searched the literature and evaluated the quality. Z.G, K.L, and X.X conducted the experiments. L.B, Z.G, and Z.G prepared the first draft of the manuscript and corrected it. All authors read and approved the final manuscript. All authors contributed to the study conception and design.

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Correspondence to Xin Xu, Yingquan Ye or Zhongxuan Gui.

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Supplementary Material 1: Fig. 1 Consensus (A) and HPA (B) database analyses reveal high UCHL5 expression in skeletal muscle, liver, tongue, and pancreas, with lower levels in fallopian tubes, cervix, testis, and choroid plexus.

13062_2024_588_MOESM2_ESM.xlsx

Supplementary Material 2: Table 1. Correlation between UCHL5 and TMB in pan-cancer. Table 2. Correlation between UCHL5 and MSI in pan-cancer.

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Bao, L., Wu, Y., Ren, Z. et al. Comprehensive pan-cancer analysis indicates UCHL5 as a novel cancer biomarker and promotes cervical cancer progression through the Wnt signaling pathway. Biol Direct 19, 139 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13062-024-00588-6

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