AbdulFattah Salah Fararjeh1, Ali Al-Khader2,3, Malak Al-Saleem1, Rinad Abu Qauod1. 1. Department of Medical Laboratory Analysis, Faculty of Science, Al-Balqa Applied University, Al-Salt, Jordan. 2. Department of Pathology and Forensic Medicine, Faculty of Medicine, Al-Balqa Applied University, Al-Salt, Jordan. 3. Department of Pathology, Al-Hussein Salt Hospital, Al-Salt, Jordan.
Abstract
Proteasome a highly sophisticated systems that alter protein structure and function. Proteasome 26S Subunit, Non-ATPase (PSMD) genes have been implicated in several types of malignancies. This is the first study to look at how proteasomal subunits are expressed in patients with bladder urothelial carcinoma (BLCA). BLCA was used to evaluate the predictive value of PSMD genes (PSMD1 to PSMD12) in relation to clinicopathological characteristics. PSMD genes' expression patterns at the mRNA level were analyzed using a variety of bioinformatics methods, including gene expression profile integrative analysis (GEPIA), Oncomine, TCGA, and Gene expression Omnibus (GEO) databases. The GEPIA and TCGA dataset survival plot functions were used to assess the prognostic significance of PSMD genes. PSMD2, PSMD3, PSMD4, PSMD8, and PSMD11 genes were significantly overexpressed in BLCA compared with normal bladder tissues. PSMD2 and PSMD8 were significantly overexpressed in BLCA more than other types of cancer. High level of PSMD2 and PSMD8 predicted shorter overall (OS) and progression free survival (PFS) in BLCA patients. High level of PSMD2 was significantly associated with elder age (P < .001), female gender (P = .014), tumor grade (P < .001), and metastasis (P = .003). PSMD2 has been shown to be an independent predictor for OS in BLCA patients based on univariate and multivariate analysis (P < .001). Overall, according to this study, PSMD2 and PSMD8 could be served as a prognostic biomarker for BLCA patients.
Proteasome a highly sophisticated systems that alter protein structure and function. Proteasome 26S Subunit, Non-ATPase (PSMD) genes have been implicated in several types of malignancies. This is the first study to look at how proteasomal subunits are expressed in patients with bladder urothelial carcinoma (BLCA). BLCA was used to evaluate the predictive value of PSMD genes (PSMD1 to PSMD12) in relation to clinicopathological characteristics. PSMD genes' expression patterns at the mRNA level were analyzed using a variety of bioinformatics methods, including gene expression profile integrative analysis (GEPIA), Oncomine, TCGA, and Gene expression Omnibus (GEO) databases. The GEPIA and TCGA dataset survival plot functions were used to assess the prognostic significance of PSMD genes. PSMD2, PSMD3, PSMD4, PSMD8, and PSMD11 genes were significantly overexpressed in BLCA compared with normal bladder tissues. PSMD2 and PSMD8 were significantly overexpressed in BLCA more than other types of cancer. High level of PSMD2 and PSMD8 predicted shorter overall (OS) and progression free survival (PFS) in BLCA patients. High level of PSMD2 was significantly associated with elder age (P < .001), female gender (P = .014), tumor grade (P < .001), and metastasis (P = .003). PSMD2 has been shown to be an independent predictor for OS in BLCA patients based on univariate and multivariate analysis (P < .001). Overall, according to this study, PSMD2 and PSMD8 could be served as a prognostic biomarker for BLCA patients.
Bladder cancer (BLCA) is the ninth most common genitourinary tract malignancy in the
general population, and the fourth among males, with an expected 573 378 new cases
and 200 000 deaths in 2020.
Because men are the primary consumers of cigarettes, smoking ranks as the top
major cause of bladder cancer.
Further studies aimed to explain the association between BLCA and several
other risk factors such as age, sex, genetics, race, alcohol, occupational
carcinogenic exposure, and dietary factors.[3,4]BLCA is classified as non-muscle invasive bladder cancer (NMIBC) or muscle invasive
bladder cancer (MIBC).
NMIBC represents the most shape, almost 75% and usually is treated through
transurethral resection. NMIBC indicates a high relapse rate, and patients need
strict examination through cystoscopy and urine cytology, which imparts great
pressure to the affected person and prices for the health care gadget.[6,7] MIBC is a heterogeneous,
aggressive illness which is associated with a 5-years survival rate, almost 60% for
patients with localized illness and less than 10% for patients with remote
metastases. It is characterized by means of genomic instability with high mutation rate.
Each subtype has its novel pathological and molecular features, which can be
used to predict the response to treatment[9-11]A single successful treatment strategy for all MIBC patients has been challenging to
achieve. Thus, individualized therapy is recommended. However, radical cystectomy
alongside pelvic lymph node dissection is deemed the gold standard treatment for
MIBC. A 2009 meta-analysis has supported that neo-adjuvant chemotherapy preceding
the treatment is the optimal curative strategy for MIBC.Kamat et al
investigated the synergetic inhibitory effect of proteasomal inhibitors of
Bortezomib and Gemcitabine as a therapeutic option for bladder cancer through strong
suppression of tumor cell proliferation, which facilitates tumor growth
inhibition.The proteasome (26S proteasome) is a 2.5 MDa hollow cylinder-shaped multi-protein
structure that consists of a core particle (20S proteasome) and a regulatory
particle (RP or 19S proteasome) on 1 or both sides. Six ATPases and 3 additional
peptides without ATPase activity make up the 19S base sub-complex. To carry out the
proteasome function, various subunits of RP have specialized activities. For
example, PSMD4, Rpn13, and PSMD10, the 3 subunits of the base sub complex, having
ubiquitin recognition domains that allow them to identify poly-ubiquitin
chains.[14,15]The ubiquitin-proteasome system (UPS) is a protein turnover pathway that operates in
various cellular processes to degrade or modify about 85% of cellular proteins in
order to sustain adequate cell processes in eukaryotic cells.[16-18] UPS consists of ubiquitin
(Ub) a small β-grasp fold tag protein that functions in post-translational
modification of protein, ubiquitin-activating enzyme (E1), ubiquitin-conjugating
enzyme (E2), ubiquitin-ligase enzymes (E3), 26S proteasome, Deubiquitinase enzymes
(DUBs), and target proteins which act in ubiquitination and in other important
signaling pathways that take part in different physiological processes including
apoptosis, angiogenesis as well as antigen presentation and DNA damage control.
Malfunction or altered expression of UPS may lead to accumulation of proteins,
and is correlated with various human diseases including
malignancies.[20-22]The Proteasome 26S Subunit, Non-ATPase (PSMD) gene family, which includes the PSMD1
to PSMD14, regulate ubiqutinated protein breakdown in circulation as well as
tumorigenesis. Overexpression of PSMD4 has been linked to poor survival in
individuals with breast cancer,[23,24] while it may inhibit
neoplastic invasiveness in colorectal cancer.
PSMD4 expression is related with a considerable increase in
well-differentiated tumors in hepatocellular carcinoma (HCC).
A 2019 study revealed a novel clinical prognostic association of Proteasome
26S Subunit, non-ATPase 3 (PSMD3) expression pattern in breast cancer cell lines
that identified PSMD3 as a stabilizing protein of human epidermal growth factor
receptor 2 (HER2).
A more recent study observed high expression of PSMD6, PSMD9, PSMD11, and
PSMD14 in pancreatic cancer
which have paved the way for further studies to investigate PSMDs as a strong
diagnostic and prognostic biomarker in BLCA. The aim of this study is to perform a
web-based analysis of PSMD genes’ expression levels in BLCA in regard to different
clinicopathological parameters.
Material and Methods
Expression profile of PSMD genes in BLCA using GEPIA
In GEPIA, (http://gepia.cancer-pku.cn/index.html), there are more than
10 000 tumor samples and around 9000 normal samples in an interactive web-based
program that gives RNA sequencing data based on TCGA and GTEx. Differential
expression analysis (DIY), profiling graphing, analysis the correlation between
genes, overall survival analysis, similar gene detection, and principle
component analysis are just a some of the interactive and customizable features
available in GEPIA. For survival analysis, GEPIA use the Log-rank test, often
known as the Mantel–Cox test. The prognostic significance of PSMD genes were
evaluated using the GEPIA survival plot function; patients’ PSMD genes mRNA
levels were divided into 2 groups, high and low, based on median PSMD mRNA
expression levels, with no follow-up restrictions.
Expression profile of PSMD in BLCA using Oncomine and TCGA dataset
Oncomine, a cancer microarray dataset-providing server that grants access to
about 800 datasets from numerous study cohorts(http://www.oncomine.org),
used to analyzed the mRNA levels of PSMD genes in tumor versus normal bladder
tissues in several studies. TCGA-BC cohort by UCSC (University of California at
Santa Cruz, CA, USA) Cancer Genomics Browser (https://xenabrowser.net/)
assisted the collection of BLCA patients data.
Gene expression Omnibus (GEO) dataset
We used GEO datasets website (https://www.ncbi.nlm.nih.gov/gds) looking for studies on
non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer
(MIBC). A 3 validated GEO microarray datasets, (GSE163899) includes 32 patients
with NMIBC and (GSE145137) dataset from patients with NMIBC progressed to MIBC
and (GSE149582) which analyzed the gene expression signature between de novo
MIBC and progressive MIBC, were downloaded from GEO database (https://www.ncbi.nlm.nih.gov/geo/).
Statistical analysis
SPSS software was used to analyze the BLCA data (SPSS, Inc., Chicago, IL, USA).
One-way ANOVA, Student t-tests and chi-squared tests were used
to analyze the expression level of PSMD gene in tumor versus normal BLCA tissues
in addition to association of the PSMD genes with BLCA clinicopathological
features. The clinical prognostic importance in BC was investigated using
Cox-regression analysis in both univariate and multivariate studies. The
log-rank test was used to compare survival curves plotted using Kaplan–Meier
analysis. *P < .05,
**P < .001 were used to indicate
statistical significance.
Results
Expression level of PSMD genes in bladder urothelial carcinoma
We investigated the expression level of PSMDs in normal versus tumor tissues in
bladder urethral carcinoma (BLCA) using gene expression profile integrative
analysis (GEPIA) based on Box blot analysis. We found that all the analyzed PSMD
genes were upregulated in tumor tissues more than normal tissues except PSMD5.
Exclusively, PSMD2, PSMD3, PSMD4, PSMD8, and PSMD11 genes were significantly
overexpressed at mRNA level in tumor tissues compared with normal bladder
tissues (Figure 1).
When compared to other proteasomal subunits with less than 7.0 Transcription Per
Million (TPM) PSMD2, PSMD4, and PSMD8 showed the greatest expression in tumor
cells (7.6 TPM), (7.9 TPM), and (7.4 TPM), respectively.
Figure 1.
Expression of PSMD genes family in BLCA tumor and normal tissues. Box
plots show PSMD1, PSMD2, PSMD3, PSMD4, PSMD5, PSMD6, PSMD7, PSMD8,
PSMD9, PSMD10, PSMD11, PSMD12 levels in transcription per million (TPM)
in Y axis.
Abbreviation: PSMD, proteasome 26S subunit, non-ATPase, N; Normal, T;
Tumor. The method for differential analysis was one-way ANOVA, with
disease condition (tumor or normal) as the variable for differential
expression calculation; P < .05 was
considered to be significant.
Expression of PSMD genes family in BLCA tumor and normal tissues. Box
plots show PSMD1, PSMD2, PSMD3, PSMD4, PSMD5, PSMD6, PSMD7, PSMD8,
PSMD9, PSMD10, PSMD11, PSMD12 levels in transcription per million (TPM)
in Y axis.Abbreviation: PSMD, proteasome 26S subunit, non-ATPase, N; Normal, T;
Tumor. The method for differential analysis was one-way ANOVA, with
disease condition (tumor or normal) as the variable for differential
expression calculation; P < .05 was
considered to be significant.
Prognostic significance of PSMD genes in bladder urothelial carcinoma
Because PSMD2 and PSMD8 showed the highest expression level in BLCA tumor tissues
and high level of both genes predicts bad overall survival in BLCA, differential
expression of PSMD2 and PSMD8 was subsequently evaluated in several types of
cancer. Interestingly, both genes; PSMD2 and PSMD8, were significantly
overexpressed in all type of tumor tissues as shown in Bladder urothelial
carcinoma (BLCA) tumor, Colon adenocarcinoma (COAD), Liver hepatocellular
carcinoma (LIHC), and Pancreatic adenocarcinoma (PAAD) (Figure 2). Particularly, BLCA was shown
to has the highest level of PSMD2 7.9 Transcription Per Million (TPM) and PSMD8
7.7 TPM in comparison to other type of cancers.
Figure 2.
Comparison between mRNA expression of (A) PSMD2 and (B) PSMD8 in Tumor
(T) versus Normal (N) tissues in several type of cancers; BLCA; bladder
carcinoma, BRCA; breast carcinoma, COAD; colon adenocarcinoma, LIHC;
Liver hepatocellular carcinoma, PAAD, pancreatic adenocarcinoma. The
method for differential analysis was one-way ANOVA, with disease
condition (tumor or normal) as the variable for differential expression
calculation; P < .05 was considered
to be significant.
Comparison between mRNA expression of (A) PSMD2 and (B) PSMD8 in Tumor
(T) versus Normal (N) tissues in several type of cancers; BLCA; bladder
carcinoma, BRCA; breast carcinoma, COAD; colon adenocarcinoma, LIHC;
Liver hepatocellular carcinoma, PAAD, pancreatic adenocarcinoma. The
method for differential analysis was one-way ANOVA, with disease
condition (tumor or normal) as the variable for differential expression
calculation; P < .05 was considered
to be significant.The prognostic significance of PSMD genes were evaluated using GEPIA survival
analysis plotter. The overall survival curves showed that high mRNA level of
PSMD2 (P = .03), PSMD8 (P = .052), and PSMD9
(p = .032) was associated with worse overall survival in
BLCA (Figure 3).
However, no significant results have been found in low versus high level of
PSMD1, PSMD3, PSMD4, PSMD6, PSMD7, PSMD10, and PSMD11.
Figure 3.
Overall survival curves of BLCA patients. The Kaplan-Meir curves show the
comparison in overall survival between PSMD genes expression at mRNA
level based on each gene’s mean expression, expression above the mean is
considered high, and expression below the mean is considered low. PSMD1,
PSMD2, PSMD3, PSMD4, PSMD5, PSMD6, PSMD7, PSMD8, PSMD9, PSMD10, PSMD11,
PSMD12. PSMD, proteasome 26S subunit, non-ATPase. The statistical method
for survival analysis was log rank test.
P < .05 was considered to be
significant.
Overall survival curves of BLCA patients. The Kaplan-Meir curves show the
comparison in overall survival between PSMD genes expression at mRNA
level based on each gene’s mean expression, expression above the mean is
considered high, and expression below the mean is considered low. PSMD1,
PSMD2, PSMD3, PSMD4, PSMD5, PSMD6, PSMD7, PSMD8, PSMD9, PSMD10, PSMD11,
PSMD12. PSMD, proteasome 26S subunit, non-ATPase. The statistical method
for survival analysis was log rank test.
P < .05 was considered to be
significant.To confirm these results, we downloaded RNA seq data from 3 different microarray
datasets based on transcriptome analysis to identify the prognostic role of
these genes in NMIBC and MIBC. The first study (GSE163899) was performed on 32
patients who were divided into 3 groups; as shown in the heat map (Figure 4A), the
expression level of PSMD1, PSMD5, PSMD6, PSMD7, PSMD9, PSMD10, PSMD11, and
PSMD12 were low in the 3 groups; no relapse n = 15 (G1), recurrence n = 9 (G2),
and during the progression n = 8 (G3) of the disease. However, PSMD2, PSMD3,
PSMD4, PSMD8 have had higher level in the NMIBC progression phase (Figure 4A).
Figure 4.
Prognostic role of PSMD genes in NMIBC and MIBC. (A) Heatmap analysis of
PSMD genes in non- muscle invasive bladder cancer (NMIBC); no relapse
group 1 (n = 15), recurrence group 2 (n = 9), and progression group 3
(n = 8). The data were downloaded from GEO dataset (GSE163899). (B)
Differential expression of PSMD genes in a patient at different time
interval; T1 patient at diagnosis with NMIBC, T2 patient after
developing MIBC and at recurrence and metastasis during chemotherapy
(gemcitabine/paclitaxel and sequential paclitaxel) the data was
downloaded from GEO (GSE145137) dataset. (C) PSMD gene expression
signature between de novo MIBC and progressive MIBC n = 12 de novo and
n = 14 progressive MIBC. The data was downloaded from GEO dataset was
(GSE149582). Student t test has been used for
statistical analysis. P < .05 was
considered to be significant.
Prognostic role of PSMD genes in NMIBC and MIBC. (A) Heatmap analysis of
PSMD genes in non- muscle invasive bladder cancer (NMIBC); no relapse
group 1 (n = 15), recurrence group 2 (n = 9), and progression group 3
(n = 8). The data were downloaded from GEO dataset (GSE163899). (B)
Differential expression of PSMD genes in a patient at different time
interval; T1 patient at diagnosis with NMIBC, T2 patient after
developing MIBC and at recurrence and metastasis during chemotherapy
(gemcitabine/paclitaxel and sequential paclitaxel) the data was
downloaded from GEO (GSE145137) dataset. (C) PSMD gene expression
signature between de novo MIBC and progressive MIBC n = 12 de novo and
n = 14 progressive MIBC. The data was downloaded from GEO dataset was
(GSE149582). Student t test has been used for
statistical analysis. P < .05 was
considered to be significant.Moreover, the second microarray dataset GSE145137 using mRNA sequencing data from
patients with non-muscle invasive bladder cancer. The RNA seq data analysis was
performed at 3 different intervals: at time of diagnosis T1-NMIBC, after
progressing to MIBC after second transurethral resection T2 and the third time
as recurrent and chemotherapy-resistant. As shown in (Figure 4B), high levels of PSMD2, PMSD8,
and PSMD4 were shown in the T2 and in the third group which may be associated
with the development of MIBC.Finally, we downloaded gene expression profile from GSE149582 dataset, 26 samples
from the discovery phase were included, the patients were grouped into de novo
MIBC and progression MIBC. Based on the microarray results, we found that PSMD2
was high in de novo MIBC compared with non-muscle invasive bladder cancer who
progressed to MIBC (Figure
4C), no significant results were found in PSMD8, PSMD4 or PSMD11
between the 2 groups.
Oncomine database for PSMD2 and PSMD8
analysis
Using several bladder cancer datasets in Oncomine database, we analyzed the
expression level of PSMD2 and PSMD8 in several bladder carcinoma subtypes such
as; infiltrating bladder urothelial carcinoma and superficial bladder cancer. As
shown in (Figure 5A),
PSMD2 and PSMD8 mRNA expression were high in most of the study cohorts in both
subtypes; infiltrating bladder urothelial carcinoma and superficial bladder
cancer. These results indicated that PSMD2 and PSMD could be associated with
muscle invasive bladder carcinoma.
Figure 5.
(A) PSMD2 and PSMD8 expression in different study cohort in non-invasive
and invasive bladder urothelial carcinoma using Oncomine database. (B)
Survival curves overall survival (OS) and progression free survival
(PFS) for PSMD2 and PSMD8 in bladder carcinoma using TCGA database. The
statistical method for survival analysis was log rank test.
P < .05 was considered to be
significant.
(A) PSMD2 and PSMD8 expression in different study cohort in non-invasive
and invasive bladder urothelial carcinoma using Oncomine database. (B)
Survival curves overall survival (OS) and progression free survival
(PFS) for PSMD2 and PSMD8 in bladder carcinoma using TCGA database. The
statistical method for survival analysis was log rank test.
P < .05 was considered to be
significant.
Association of PSMD2 and PSMD8 with BLCA clinicopathological features
Next, the correlation between PSMD2, PSMD8 and bladder cancer clinicopathological
features has been analyzed from BLCA-TCGA records (Table 1). High level of PSMD2 was
significantly associated with older age
(P < .001), female gender
(P = .014), tumor grade (P < .001), and
metastasis (P = .003). No significant association had been
found with clinical stage or lymph node metastasis or Lymphovascular invasion.
On the other hand, high level of PSMD8 was significantly associated with older
age at initial diagnosis (P < .01) and with
tumor extent (P = .025), no clear correlations have been found
with other clinical parameters.
Table 1.
Correlation between PSMD2 and PSMD8 mRNA level and clinicopathological
parameters of bladder urothelial carcinoma.
Parameters
PSMD2 low (n)
PSMD2 high (n)
P-Value
PSMD8 low (n)
PSMD8 high (n)
P-Value
Gender
Female
51
67
.014*
110
8
.443
Male
174
134
280
28
Age
<60
106
0
<.001**
105
1
.01**
>61
119
201
285
35
Tumor extent
T1
2
2
.050*
4
0
.025*
T2
71
53
32
92
T3
94
110
68
136
T4
40
22
18
44
Grade
1
20
203
<.001**
10
11
.101
2
1
199
123
279
Node
N0
123
115
.247
81
166
.454
N1
21
28
11
38
N2
41
39
24
56
N3
28
16
28
Stage
16
I
2
0
.229
2
0
.143
II
78
56
41
93
III
72
74
49
97
IV
72
72
40
102
Metastasis
No
126
80
.003*
74
132
.163
Yes
98
119
59
158
Lymphovascular invasion
No
63
69
.515
121
11
.936
Yes
83
78
148
13
Chi-square test was used to analyze the correlation between PSMD2 or
PSMD8 with BLCA clinicopathological features. High; expression above
the mean, and Low; expression below the mean.
*P < .05,
**P < .001. The bold is
indicated for the significant results.
Correlation between PSMD2 and PSMD8 mRNA level and clinicopathological
parameters of bladder urothelial carcinoma.Chi-square test was used to analyze the correlation between PSMD2 or
PSMD8 with BLCA clinicopathological features. High; expression above
the mean, and Low; expression below the mean.
*P < .05,
**P < .001. The bold is
indicated for the significant results.Univariate survival analysis showed that PSMD2, PSMD8, and tumor grade were
predictors for overall survival; PSMD2 hazard ratio (HR) = 7.689, 95% confident
interval (CI) = (5.143-11.494) (P < .001).
PSMD8 HR = 1.746, 95% CI = (1.147-2.659) (P = .009). Tumor
grade, HR = 7.292, 95% CI = (1.21-52.078) (P = .048). However,
Multivariate analysis showed that only PSMD2 was predictive for OS in BLCA
patients, PSMD2 HR = 8.041, 95% confident interval CI = (4.715-13.713)
(P < .001) (Table 2).
Table 2.
Univariate and multivariate analysis of OS in TCGA-BLCA patients
according to PSMD2 and PSMD8 mRNA level.
Parameters
Univariate analysis
Multivariate analysis
P-Value
HR ratio (95% Cl)
P-Value
HR ratio (95% Cl)
PSMD2 (high vs low)
<.001**
7.689 (5.143-11.494)
<.001**
8.041 (4.715-13.713)
PSMD8 (high vs low)
.009*
1.746 (1.147-2.659)
.681
1.118 (0.657-1.900)
Stage (III and IV vs I and II)
.580
1.093 (0.797-1.500)
.383
1.490 (0.609-3.646)
Tumor extent (I and II vs III and IV)
.920
1.017 (0.734-1.408)
.568
0.788 (0.348-1.784)
Grade (high vs low)
.048*
7.292 (1.21-52.078)
.482
2.042 (0.279-14.930)
Node (Positive vs negative)
.289
1.073 (0.942-1.221)
.992
1.001 (0.841-1.191)
Lymphovascular invasion
.130
0.774 (0.555-1.078)
.109
0.748 (0.524-1.067)
Metastasis (yes vs no)
.896
1.000 (0.999-1.001)
.720
1.000 (0.999-1.001)
CI, confidence interval; Cox regression analysis, hazard ratio (95%
confidence interval). High; expression above the mean, and Low;
expression below the mean. *P < .05,
**P < .001. The bold is
indicated for the significant results.
Univariate and multivariate analysis of OS in TCGA-BLCA patients
according to PSMD2 and PSMD8 mRNA level.CI, confidence interval; Cox regression analysis, hazard ratio (95%
confidence interval). High; expression above the mean, and Low;
expression below the mean. *P < .05,
**P < .001. The bold is
indicated for the significant results.Consistent with survival curves from GEPIA websites, Kaplan Meier survival
analysis from TCGA database showed that high level of PSMD2 and PSMD8 had worse
overall survival (OS) and Progression Free Interval (PFI) (Figure 5B). These results clearly
indicated that PSMD2 and PSMD8 are important predictors for Clinical
consequences in BLCA and might have critical roles for BLCA tumorigenesis.
Discussion
The high BLCA recurrence rate and requirement for invasive diagnostic and tracking
techniques, along with cystoscopy, makes bladder urothelial carcinoma one of the
costliest human cancers from early evaluation to death. While the 2 main techniques;
cystoscopy and urine cytology are considered as the gold standard for preliminary
BLCA diagnosis and monitoring, there is still a need to discover novel, non-invasive
specific biomarkers for the better diagnosis and prediction for tissues after
cystectomy or transurethral resection (TURBT).PSMD genes have been implicated in several types of malignancies. Recently, we
identified PSMD3, a 19S regulatory subunit, as a prognostic and therapeutic marker
for HER2 positive breast cancer.
A new recent study had been recognized several proteasomal subunits as
prognostic biomarkers for pancreatic ductal adenocarcinoma.
To the best of our knowledge, the current study is the first for analyzing
the expression level of proteasomal subunit genes in bladder urothelial
carcinoma.In the current study, we used several bioinformatics websites to investigate the
expression level of PSMD genes in bladder urothelial carcinoma such as GEPIA,
Oncomine, TCGA, and GEO databases. The mRNA expression levels for PSMD genes were
obtained from several cohort studies which were performed based on RNA seq analysis.
Most of PSMD genes were upregulated in BLCA in contrast to regular normal tissues,
notably PSMD2 and PSMD8 were the most expressed genes in tumor tissues.
Interestingly, several studies demonstrated the upregulation of PSMD2 in solid
tumors such as lung adenocarcinoma, breast cancer, gastric cancer and in
hepatocellular carcinoma cell line, HepG2 cell line[21,22,26,27] which indicated the important
role of PSMD2 in tumorigenesis. However, the exact role of PSMD8 in cancer is still
elusive. We found a lower level of PSMD5 in tumor tissues compared to normal bladder
cells, which is consistent with a prior study that found PSMD5 mRNA and protein
levels were downregulated in colorectal tumors. PSMD5 silencing promotes the
formation of 26S proteasomes. PSMD5 interaction with proteasome subunits is, in
other words, transitory.Based on both GEPIA and TCGA databases, high level of PSMD2 and PSMD8 predicted
shorter overall survival and progression free survival, which indicated the
unfavorable prognostic role of PSMD2 and PSMD8 in BLCA. High level of PSMD2 was also
associated with age at diagnosis, gender, grade, and metastasis status. PSMD2 has
been shown to be an independent predictor for OS in BLCA patients based on
univariate and multivariate analysis
(P < .001).When the PSMD2 mRNA level was high, we found that 32% of the patients were male and
only 16% of the patients were female. There was no substantial difference in the
relationship between PSMD8 and gender. It has also long been known that BLCA
incidence is approximately 4 times higher in males than in females in the US.
In accordance with the gender disparity in BLCA risk, the mortality of this
sickness inside the US is likewise greater than 3-fold higher in men than in women.
Furthermore, high level of PSMD2 was associated with patients elder than
60 years’ old which account for around 47% of the patients. Further studies are
recommended to test the usefulness of PSMD2 as a biomarker to diagnosis BLCA in men
and for people exceed 60 years old.Consistently, PSMD2 was previously examined in breast cancer included in 797
ubiquitin proteasomal system (UPS) genes. PSMD2, was identified as oncogene and high
level of PSMD2 had predicted worse overall survival. PSMD2 was also shown to be
associated with age, lymph node metastasis and TNM stage.
A genome-wide association study inside a highly metastatic lung cancer cell
line identified genes related to UPS including PSMD2 as a metastatic signature gene
that was associated with worse prognosis in lung and breast cancers.PSMD2 has been shown to be involved in cell cycle and to increase cell proliferation,
loss of PSMD2 function leads to the inhibition of cell proliferation in BC and HepG2
cell lines.
However, it is still not clear based on in vitro or in vivo if there is a
role of PSMD2 in metastasis.Most bladder cancers are non-muscle invasive at initial diagnosis. However, they are
characterized by high recurrence rate reaching around 75%
and around 25% in MIBC. MIBC is highly aggressive and the 5-years overall
survival is less than 15% in patients with no treatment history. In Spite of its
favorable survival, NMIBC recurs frequently and may finally develop to
muscle-invasive bladder cancer (MIBC), which requires repeated cystoscopic resection
or may require radial cystectomy.
Therefore, identifying novel prognostic biomarkers can be the initial step
for accurate prognosis prediction and treatment. This study showed that PSMD2 and
PSMD8 are low expressed in NMIBC. However, they seem to be associated with
progressive NMIBC but not recurrence. Moreover, PSMD2 and PSMD8 showed high level of
expression in MIBC and recurrent MIBC in association with lung metastasis and
chemotherapy resistance based on GEO study GSE149582
in comparison with the non-MIBC.These data could provide a novel prognostic differences between NMIBC and MIBC,
further studies are needed to validate the role of PSMD2 or/and PSMD8 in progression
steps from NMIBC to MIBC or in de novo MIBC. This research is of an investigative
character, we used the RNA-Seq versus Microarray datasets to validate the expression
and prognostic values of PSMD2 and PSMD8 in NMIBC and MIBC. In order to translate
these finding to clinical settings, PSMD2 expression level and function in vitro, in
vivo and in large cohort samples from BLCA patients are recommended.
Conclusion
We found that high level of PSMD2 and PSMD8 associated with worse overall survival
and progression free survival, which indicated the unfavorable prognostic role in
patients with BLCA. Furthermore, high level of PSMD2 was correlated with age at
diagnosis, gender, grade, and metastasis status. PSMD2 found to be an independent
predictor for OS in BLCA patients. Interestingly, the mRNA level of PSMD2 and PSMD8
was detected at high level in muscle invasive bladder cancer patients and low level
in non-invasive bladder cancer patients, suggesting that they may play a role in
disease development.
Authors: Marcus George Kwesi Cumberbatch; Ibrahim Jubber; Peter C Black; Francesco Esperto; Jonine D Figueroa; Ashish M Kamat; Lambertus Kiemeney; Yair Lotan; Karl Pang; Debra T Silverman; Ariana Znaor; James W F Catto Journal: Eur Urol Date: 2018-09-26 Impact factor: 20.096
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Authors: Michael B Cook; Sanford M Dawsey; Neal D Freedman; Peter D Inskip; Sara M Wichner; Sabah M Quraishi; Susan S Devesa; Katherine A McGlynn Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-03-17 Impact factor: 4.254
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Authors: Aurélie Kamoun; Aurélien de Reyniès; Yves Allory; Gottfrid Sjödahl; A Gordon Robertson; Roland Seiler; Katherine A Hoadley; Clarice S Groeneveld; Hikmat Al-Ahmadie; Woonyoung Choi; Mauro A A Castro; Jacqueline Fontugne; Pontus Eriksson; Qianxing Mo; Jordan Kardos; Alexandre Zlotta; Arndt Hartmann; Colin P Dinney; Joaquim Bellmunt; Thomas Powles; Núria Malats; Keith S Chan; William Y Kim; David J McConkey; Peter C Black; Lars Dyrskjøt; Mattias Höglund; Seth P Lerner; Francisco X Real; François Radvanyi Journal: Eur Urol Date: 2019-09-26 Impact factor: 20.096