In the US, incidence of PCa has increased annually
by 2–3% between 2015 and 2019 (1).
Additionally, US projections for 2024 show that prostate, lung and
colorectal cancers account for almost half of all new diagnoses in
men, with PCa alone accounting for up to 29% of these cases
(1). Currently, available
diagnostic techniques include PCa biopsy, digital rectal
examination and prostate-specific antigen (PSA) testing (2). Although PSA is the most commonly used
biomarker for PCa diagnosis (3),
its low specificity and sensitivity often result in misdiagnosis
(4), such as in cases of elevated
PSA in prostatitis and benign prostatic hyperplasia (BPH) (5). In addition, PSA-based screening may
lead to overdiagnosis and increase the risk of overtreatment
through the detection of indolent PCa (6,7).
Therefore, there is a great demand to find biomarkers that can
precisely and dynamically characterize the development and
progression of PCa.
In men with an abnormal PSA level, transrectal
ultrasound-guided biopsy has remained the standard procedure for
PCa diagnosis (8,9). However, there is a higher rate of
complications after prostate biopsy in men who are anxious about
these complications (10,11). Liquid biopsy is a minimally invasive
method that offers the advantage of real-time monitoring with
minimal harm to patients with cancer (12,13).
The development of a non-invasive ‘liquid biopsy’ represents a
notable innovation in the field of precision medicine (14). These non-invasive detection
biomarkers include DNA, circulating tumor cells, RNAs (microRNA,
long non-coding RNAs and mRNAs), proteins, sugar structures,
metabolites and peptides (14,15).
In addition, research involving large-scale mass spectrometry-based
proteomics of PCa has previously been published (16,17).
An increasing number of serum protein biomarkers, such as
thrombospondin-1 and cathepsin D, that are increased in PCa are
being investigated (9).
The present review provides a systematic summary of
the emerging peripheral blood protein biomarkers for PCa. Notably,
the clinical value of these protein biomarkers in PCa prediction,
diagnosis, prognosis and drug resistance monitoring is further
summarized and discussed, and holds great potential and promise for
improving PCa stratification management.
Early prediction of dynamic PCa progression is
important for disease management (18). A clinically useful biomarker should
have high sensitivity and specificity, as well as high positive and
negative predictive values (19).
In the current section, peripheral blood protein biomarkers that
predict the oncogenesis, aggressiveness and metastasis of PCa are
summarized.
Chronic inflammation has been reported to cause up
to 20% of human cancers and has been implicated in prostate
carcinogenesis through several mechanisms (20). Pentraxin-3 (PTX3) represents a
pivotal element of the innate immune system involved in cancer
angiogenesis and proliferation (21,22).
Previously, further reports revealed that PTX3 serum levels were
higher in patients with PCa compared with in those with
inflammation or BPH (23). By
contrast, these two groups did not differ in terms of serum PSA or
C-reactive protein (CRP) levels, and there was no association
between PTX3 and CRP serum levels, ruling out the possibility that
elevated PTX3 levels were caused by systemic inflammation (23). These findings suggest that elevated
PTX3 levels in PCa may originate from the tumor's local immune
microenvironment, such as the infiltration of
CD4+CD25+ regulatory T cells (Tregs)
(24), rather than from systemic
inflammation. This does not contradict the theory in previous
studies that inflammation acts as a carcinogenic driver (20,25).
In addition, receiver operating characteristic (ROC) curve analysis
further confirmed the reliability of PTX3 serum levels in
predicting PCa development, with a cut-off value of 3.25 ng/ml and
a sensitivity and specificity of 89.3 and 88.5%, respectively
(23).
Moreover, in another immune-related study, high
levels of serum B- and T-lymphocyte attenuator (sBTLA) and serum
T-cell immunoglobulin and mucin domain-3 (sTIM3) were associated
with the risk of aggressive PCa. Specifically, the q-value
(Benjamini-Hochberg correction method) of sBTLA was <0.15 using
multiple comparison methods [odds ratio (OR)=2.7; 95% confidence
interval (CI) 1.3-5.6; P=0.01; q=0.14] (26). Researchers have also reported that
the binding of herpesvirus entry mediator (HVEM)-BTLA inhibits
T-cell activation and proliferation, leading to impeded antitumor
immunity (26). In both studies,
immune-related proteins were found to have the potential to be
predictive biomarkers for PCa, whereas sBTLA and sTIM3 predicted
aggressiveness. Furthermore, a previous study revealed that soluble
E-cadherin is a more effective predictor of the aggressiveness of
PCa compared with PSA (27). It
regulates human nanos C2HC-type zinc finger 1, which interacts with
p120 catenin and induces tumor cell migration and invasion
(28).
Metastatic PCa (mPCa) is most often incurable and is
the main cause of mortality (29).
A previous study first used genomic analysis to confirm that
myeloid differentiation factor-2 (MD2) showed excellent performance
in predicting the risk of tumor metastasis (30). Moreover, measurements of serum MD2
protein levels revealed that their levels were associated with the
metastasis of PCa (30). Recently,
a group of nine proteins was shown to be elevated in mPCa compared
with localized PCa by immunohistochemistry (31). In particular, pleiotrophin (PTN)
levels were increased in the serum of men in the Cambridge
Prognostic Groups 5 (CPG5) group compared with those in the benign
and CPG1 groups (31). In addition,
researchers have discovered that PTN is a secreted growth factor
with multiple functions associated with tumor growth and metastasis
(32). These studies suggest that
PTN and MD2 may represent novel biomarkers for the prediction of
localized PCa with metastatic potential, and they are expected to
support clinical decision-making and optimal health care delivery.
However, PCa is a highly heterogeneous tumor whose expression
patterns of molecular markers notably differ across stages. The
utility of these biomarkers requires further studies to confirm
their validity and generalizability.
A growing number of studies have suggested that the
widespread use of PSA for PCa screening and early diagnosis
improves patient outcomes and reduces mortality (33–36).
Ribonuclease 4 (RNASE4), a protein biomarker that enhances the
diagnostic accuracy of PSA in PCa, also promotes tumor progression
by stimulating cancer cell proliferation and inducing angiogenesis
(37). Using an enzyme-linked
immunosorbent assay, Vanli et al (37) measured RNASE4 levels in plasma
samples from healthy controls (n=120) and patients with PCa
(n=120). The results revealed that the ROC curve of RNASE4 plus PSA
provides the most accurate PCa diagnosis, with an area under the
ROC curve (AUC) of 0.99 (0.98-1.00) (37), suggesting that the plasma RNASE4
level in combination with the PSA level improves diagnostic
accuracy and reduces misdiagnosis.
In addition, spondin 2 (SPON2) is considered to be a
promising diagnostic biomarker for PCa when the PSA concentration
is <4 ng/ml (38). As members of
the F-spondin family can modulate the Wnt/β-catenin signaling
pathway during tumor development, SPON2, which belongs to this
family, may promote cancer growth (39). Research regarding PCa suggests that
characterizing SPON2 may help predict diagnosis (40). In patients with a total PSA <4
ng/ml, the diagnostic efficacy of SPON2 (AUC=0.921; 95% CI:
0.827-0.973) was significantly superior to that of total PSA
(AUC=0.537; 95% CI: 0.409-0.660; P<0.001) (38). However, SPON2 has only been
validated in a small study involving 286 patients with PCa
(38). The lack of a multicenter
cohort limits its practical applicability.
Filamin A (FLNA) is influenced by the effects of
androgens on cell migration and FLNA cleavage (41). It has been identified as a potential
serum biomarker for PCa diagnosis (42). Recently, the clinical value of FLNA
in the diagnosis of PCa has also been researched. In men with a PSA
concentration between 4 and 10 ng/ml (the gray zone) and a negative
digital rectal examination, FLNA serum levels were shown to
reliably distinguish patients with PCa from those with BPH
(43,44). It is also worth mentioning that
Golgi membrane protein 1 (GOLM1), a Golgi protein upregulated in
localized PCa (45), was shown by
Dong et al (46) to have
excellent diagnostic efficacy in the PSA gray zone. The ROC curve
analysis indicated that GOLM1 had a sensitivity of 0.774 and a
specificity of 0.713 when the PSA concentration was within the 4–10
ng/ml range, demonstrating superior sensitivity and specificity
compared with PSA (46). The
research identified GOLM1 and FLNA as potential biomarkers for
diagnosing PCa in the gray zone. These biomarkers may reduce the
likelihood of prostate biopsy in patients. However, the diagnostic
utility of these protein biomarkers still needs to be determined in
larger populations before their broad clinical application.
The inability of current diagnostic tests to
distinguish between indolent and aggressive PCa is a major clinical
challenge (47). Soluble urokinase
plasminogen activator receptor (suPAR) may indirectly induce tumor
cell proliferation, migration and invasion (48). Recently, research on suPAR as a
diagnostic biomarker for aggressive PCa has shown promising
progress. A study by Wach et al (49) revealed that serum suPAR levels were
higher in patients with a Gleason score (GS) >7 compared with in
those with a GS 5–7 or <5 (P<0.011), supporting the clinical
value of suPAR in identifying aggressive PCa. On the basis of this
evidence, suPAR can be proposed as a stratified biomarker for high
GS (>7) PCa.
As PCa is remarkably heterogeneous, it can be
classified into several intermediate clinical states, and the
management of the therapeutic course of the different states and
the timely prevention of metastatic disease may benefit from
clinically useful prognostic biomarkers (54). In the current section, circulating
protein biomarkers that hold prognostic value for classifying PCa,
predicting disease prognosis, overall survival (OS) and biochemical
recurrence (BCR) are briefly summarized.
Strong evidence from histology and genetic studies
suggests that persistent systemic inflammation may serve a role in
the early stages of PCa development (55–57).
Kälin et al (58) identified
important prognostic biomarkers for PCa, including CRP, in a PTEN
conditional knockout mouse model. In addition, another study
revealed that serum CRP levels were associated with increased odds
of high-risk PCa, mPCa and high PSA levels (≥20 mg/), with ORs of
1.29 (95% CI, 1.06-1.56), 1.32 (95% CI, 1.05-1.65) and 1.51 (95%
CI, 1.26-1.81), respectively (59).
Similarly, higher haptoglobin levels were associated with the
likelihood of mPCa, high PSA levels and high-grade PCa (59). These studies suggest that CRP and
haptoglobin levels predict poor prognosis in PCa.
BCR and metastatic progression in PCa were
independently predicted by high tissue PTN (31). Moreover, Minas et al
(63) examined the association
between immune-related proteins, including PTN, and the risk of
developing PCa in 3,094 serum samples. The study revealed that 33%
of patients with elevated levels of tumor necrosis factor receptor
superfamily member 9 (TNFRSF9) and PTN succumbed to PCa within a
10-year period, whereas only 5% of patients with low levels of
either protein died of PCa, supporting the ability of PTN and
TNFRSF9 to predict poor prognosis and OS. Tregs expressing TNFRSF9
can suppress antitumor immune responses (64). This biological role is consistent
with research findings that serum TNFRSF9 is associated with lethal
PCa (63). In addition, treatment
efficacy may be affected by soluble T-cell regulatory proteins
[mostly immune checkpoint-related (ICK)-related proteins] released
from immune and tumor cells (65).
Wang et al (26) reported
that serum levels of several ICK-related proteins were associated
with PCa progression and BCR. Specifically, sCD28, sCD80, soluble
cytotoxic T-lymphocyte antigen 4, soluble glucocorticoid-induced
tumor necrosis factor receptor, soluble HVEM and soluble
indoleamine 2,3-dioxygenase were associated with both BCR and
progression risk (all P<0.05) (26). Moreover, among the ICK factors,
sBTLA was the most important serum biomarker associated with
progression (P=3.3×10−3; q=0.028; HR=6.5; 95% CI,
1.9-22.8) (26). Management of PCa
requires refinement and standardization, and these emerging serum
biomarkers can improve PCa risk stratification and prediction of
BCR. However, further studies are needed to confirm the association
of the tumor immune suppression signature with PCa.
In the past decade, PCa management has notably
changed. In addition to surgical treatment and chemotherapy, novel
drug treatments, such as cabazitaxel (66), next-generation androgen receptor
(AR) inhibitors, abiraterone (ABI) (67), enzalutamide (ENZA) (68), immunotherapy (sipuleucel-T)
(69) and poly ADP-ribose
polymerase inhibitors (70), have
become available. However, the outcome remains poor for men who
progress to metastatic castration-resistant prostate cancer (mCRPC)
(71). Improved drug resistance
monitoring strategies are still urgently needed.
In addition, trophoblastic cell-surface antigen
(TROP-2) is a transmembrane protein that is expressed in PCa and is
overexpressed in multiple malignancies (76–78).
It is a therapeutic target for antibody-drug conjugates (79) and captures peripheral blood
circulating tumor cells (CTCs) in mCRPC (80). The results indicated that the number
of CTCs captured with anti-TROP-2 antibodies was strongly
associated with the number of CTCs captured with epithelial cell
adhesion molecule antibodies (Pearson r=0.92) (80). By monitoring the number of
TROP-2-positive CTCs, the response of a patient to treatment and
disease progression can be assessed (80). The TROP-2 gene is expressed in mCRPC
from luminal and basal tumors but is expressed at lower levels in
patients with neuroendocrine PCa (80). ALCAM and TROP-2 can be used as
biomarkers for further research, to monitor the effect of treatment
in real time, assess dynamic changes in mCRPC and provide a basis
for personalized treatment. The aforementioned protein markers are
summarized in Table I with their
associated clinical values.
In accordance with the evidence presented in the
current review, several questions remain to be addressed: i) The
capacity to fulfill the identical rigorous enrollment requirements
stipulated in the clinical trial study design; ii) the potential
for these peripheral blood protein biomarkers to be used in
clinical applications; iii) the impact of multiple treatment
methods at the same time on the accuracy of serum protein markers
in clinical applications; and iv) the potential benefits of
combined testing for patients.
As previously discussed, the emerging peripheral
blood protein biomarkers for PCa are discussed in the present
review, and their clinical value and potential applications are
highlighted. However, a biomarker should undergo five major phases
of development before it is utilized in clinical settings to
benefit the population. These phases include: i) Preclinical
exploratory studies; ii) clinical assay development and validation;
iii) retrospective longitudinal studies; iv) prospective screening
studies; and v) randomized control studies (81). Most biomarkers discussed in the
present review have completed the first two phases (preclinical
exploration and assay validation), providing a strong foundation
for further investigation. Regrettably, these protein biomarkers
have not yet undergone a complete cycle of development. For
example, LAMB1 has not been subjected to long-term monitoring or
randomized control studies. In the absence of randomized testing in
the general population, determining whether LAMB1 can reduce the
overall disease burden is not possible. Ferrari et al
(30) validated the importance of
MD2 for predicting metastasis in a murine model but lacked
prospective screening studies and multicenter cohorts. The absence
of these stages makes it impossible to determine the optimal timing
of the test and complicates the screening of the target population,
consequently increasing the risk in clinical trials. Moreover,
these protein biomarkers require higher-level clinical validation,
such as phase III clinical trials. The results of the validation
and evaluation of these peripheral blood protein biomarkers are
submitted to regulatory authorities. None of the biomarkers
discussed in the present review have undergone this step and
therefore cannot be legally used in the clinic, which could have
implications for medical decision-making and patient care or even
more serious consequences.
Furthermore, current protein biomarker research
requires multi-omics studies in combination with proteomics.
Technological advances in mass spectrometry (MS)-based proteomics
have led to high-throughput and highly sensitive analytical
platforms. Sun et al (82)
employed data-independent acquisition MS (DIA-MS) to perform
comprehensive proteomic analysis on 918 tissue samples from 306
Chinese patients with PCa, identifying >10,000 distinct
proteins. Moreover, the authors developed a 16-protein panel that
effectively predicts BCR for patients with PCa (82). With unprecedented depth and
accuracy, sample analysis has opened up new avenues for biological
research and clinical applications (83). However, in vitro diagnostics
(IVDs) require stringent quality control measures (83). Currently, most MS-based experiments
are performed in research laboratories rather than IVD-certified
clinical ones (83). Non-standard
laboratories may lead to inconsistencies in standards.
Standardizing experimental protocols and data formats would enhance
reproducibility and cross-study comparisons, ultimately
accelerating scientific progress (83). Moreover, methods have now been
developed to detect programmed death ligand 1 expression in CTCs,
and its prognostic and predictive value is currently under
investigation (13). We hypothesize
that technological advances will resolve a number of the challenges
associated with applying these peripheral blood protein biomarkers
in clinical practice such as multi-omics integration,
standardization of testing and cost.
Combined tests facilitate early detection of PCa,
decrease over-detection and provide information for risk
stratification (84). Compared with
PSA, FLNA combined with prostate volume and age in men whose PSA
concentration was elevated (between 4 and 10 ng/ml) resulted in
superior detection performance (43). Furthermore, logistic regression was
used to identify two biomarker panels that achieved the best
performance: i) Prostate health index (PHI), fucosylated PSA
(Fuc-PSA), syndecan-1 (SDC1), and growth differentiation factor 15;
and ii) PHI, Fuc-PSA, SDC1, and TEK receptor tyrosine kinase
(85). At a fixed sensitivity of
95%, the panels demonstrated a significant improvement in
specificity in the distinction between aggressive PCa and low-risk
PCa (76.0 vs. 56%; P=0.029) and between low-risk PCa and non-PCa
(78.2 vs. 65.5%; P=0.010) (85).
Multivariate panels of serum biomarkers demonstrated improvement
over the performance of the PHI, which may contribute to the
management of PCa. These panels demonstrate superior performance in
identifying invasive diseases, partly due to their ability to
detect immune evasion. For instance, the biological function of
TNFRSF9-expressing Tregs is mediated by its soluble isoform, which
is generated through alternative splicing and acts as a decoy
receptor to antagonize antitumor immunity and promote tumor
survival (86). Additionally, PTN
promotes cancer progression through increased vascular endothelial
growth factor deposition in the vasculature, leading to vascular
disruption (32). The clinical
relevance of these mechanisms is underscored by findings that serum
levels of both TNFRSF9 and PTN are associated with lethal PCa and
predict poor patient survival (63). However, the underlying relationships
between them have yet to be described. The individual biomarkers
referenced in the present review possess unique mechanisms of
action that serve their specific clinical applications. Future
mechanistic research should elucidate how these biomarkers act
synergistically, thereby strengthening the link between biomarker
mechanisms and specific clinical applications.
In summary, PSA is widely used in PCa testing.
However, controversy exists regarding PSA screening and the risk
associated with PCa overdiagnosis. Therefore, the present review
summarizes the emerging peripheral blood protein biomarkers for the
accurate diagnosis and selection of optimal treatment options.
However, it is not currently appropriate to clinically implement
the biomarkers discussed in the present review. Future efforts must
prioritize higher-level validation, develop multi-omics integration
strategies and forge stronger links between biomarker mechanisms
and specific clinical applications. The rapidly evolving field of
targeted proteomics will be instrumental in building the validation
platforms needed to achieve these goals.
Not applicable.
The present study was supported by grant from National Natural
Science Foundation of China Project (grant no. 81802571 to WL) and
Zhejiang Medical and Health Science and Technology Project (grant
no. 2019RC039 to WL).
Not applicable.
MC wrote and completed the manuscript and abstract.
FW made substantive revisions to the key content of the manuscript.
WW and KF consulted the relevant literature and completed the
English revisions. MC, KX and XG completed the design of the
framework of the manuscript and completed the tables. WL and ZT
provided constructive feedback and guidance, completed critical
revisions and proofread the manuscript. All authors have read and
approved the final version of the manuscript. Data authentication
is not applicable.
Not applicable.
Not applicable.
The authors declare that they have no competing
interests.
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