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Review

Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction

1
Department of Orthopaedic Surgery, The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu 322000, China
2
Department of Orthopaedic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Pers. Med. 2023, 13(5), 705; https://doi.org/10.3390/jpm13050705
Submission received: 4 March 2023 / Revised: 6 April 2023 / Accepted: 17 April 2023 / Published: 22 April 2023

Abstract

:
Prostate cancer (PCa) causes deaths worldwide, ranking second after lung cancer. Bone metastasis (BM) frequently results from advanced PCa, affecting approximately 90% of patients, and it also often results in severe skeletal-related events. Traditional diagnostic methods for bone metastases, such as tissue biopsies and imaging, have substantial drawbacks. This article summarizes the significance of biomarkers in PCa accompanied with BM, including (1) bone formation markers like osteopontin (OPN), pro-collagen type I C-terminal pro-peptide (PICP), osteoprotegerin (OPG), pro-collagen type I N-terminal pro-peptide (PINP), alkaline phosphatase (ALP), and osteocalcin (OC); (2) bone resorption markers, including C-telopeptide of type I collagen (CTx), N-telopeptide of type I collagen (NTx), bone sialoprotein (BSP), tartrate-resistant acid phosphatase (TRACP), deoxypyridinoline (D-PYD), pyridoxine (PYD), and C-terminal pyridinoline cross-linked telopeptide of type I collagen (ICTP); (3) prostate-specific antigen (PSA); (4) neuroendocrine markers, such as chromogranin A (CgA), neuron-specific enolase (NSE), and pro-gastrin releasing peptide (ProGRP); (5) liquid biopsy markers, such as circulating tumor cells (CTCs), microRNA (miRNA), circulating tumor DNA (ctDNA), and cell-free DNA (cfDNA) and exosomes. In summary, some of these markers are already in widespread clinical use, while others still require further laboratory or clinical studies to validate their value for clinical application.

1. Introduction

Prostate cancer (PCa), a prevalent cancer in male patients, is also the second-leading cause of death among all malignancies [1,2]. Only 25% of metastatic PCa patients hit the five-year milestone, compared to 99% in localized PCa patients [3,4], which is usually considered to be incurable [1]. Bone metastases (BM) will eventually occur in 80–90% of individuals with advanced PCa [5,6,7]. Advanced PCa is often treated with pharmacological or surgical castration [8,9]. Unfortunately, the majority of individuals who receive castration therapy eventually acquire untreatable castration-resistant prostate cancer (CRPC), which also causes BM [10,11]. Individuals with BM are susceptible to skeletal-related events (SREs), including intolerable bone pain, which greatly lower patients’ quality of life and raises the chance of death [12,13]. The axial skeleton is where PCa metastasizes most frequently, notably in the pelvis or spine [14,15]. The efficient therapy of BM is frequently hampered by the early detection of the condition.
However, it is challenging to detect BM before the emergence of distal clinical symptoms. Traditional techniques, notably MRI, 99mTc-MDP bone scans, CT, or Choline-PET/CT, play critical roles in detecting PCa BM [16]. What’s more, bone tissue biopsy is the most accurate method of detecting BM thus far. However, due to the invasive operation, low specificity, expensive costs, and radiation exposure risk [17], the clinical application of these methods is constrained. Thus, diagnostic and prognostic biomarkers for PCa BM are unavoidably required.
To predict BM in PCa patients, several investigations on possible blood, urine, and tumor tissue-related indicators were conducted. Any of these indicators that might quickly and correctly forecast the onset of BM before being observed by imaging techniques would be helpful to let high-risk individuals get care as soon as possible.
In this paper, we reviewed the current research status of BM markers for PCa, including bone formation markers, bone resorption markers, prostate-specific antigens, neuroendocrine markers, and liquid biopsy markers (Table 1). We provide recommendations on the clinical use of these indicators by critically and objectively assessing their utility in the diagnosis and prognosis of PCa-induced BM.

2. Bone Formation Markers

BM is produced as a result of PCa cells interacting with bone cells in both ways. Multiple mechanisms can be used by metastatic PCa cells engrafted in the bone to activate osteoblasts and promote the formation of new bone. When cancer cells emit inflammatory cytokines, including IL-1, IL-6, or PGE2, osteoprogenitor cells and osteoclast precursors are attracted and activated [18]. In the second stage, the osteoclast-resorbed bone matrix is released, unleashing trophic growth factors that draw PCa cells as well as factors involved in matrix remodeling, such as PDGF, IGF-I, and MMPs [19]. Furthermore, PSA- and BMP-release by cancer cells has a direct or indirect effect on bone formation [20]. These elements may encourage the growth of metastatic cancers as well as the production of new bones. By releasing these substances in the metastatic niche, RANKL/OPG ratio adjustments can also be made by PCa cells [21,22]. In general, there is a pathological feedback loop in which healthy bone tissue is gradually replaced by disordered bone deposition, thus more osteoclasts are recruited, and more growth factors are released. This cycle is commonly known as the “vicious cycle” of BM [23].
Unlike breast or lung cancers, PCa BM predominantly features osteoblastic lesions, which involve uncontrollable bone formation [20]. This observation indicates that bone formation markers are crucial in the diagnosis of PCa BM. Studies on bone formation markers are listed in Table 2.

2.1. Alkaline Phosphatase (ALP)

The glycoprotein known as ALP is not only present in bones but also in the kidney, gut, placenta as well as the liver. As a low-cost and easily accessible marker, serum ALP has been utilized for decades as a criterion for evaluating PCa BM. It is anticipated it will aid in formulating regular cancer therapy and follow-up plans [38]. The degree of BM is indicated by changes in bone turnover and osteoblastic activity, which are reflected in changes in ALP levels [38,39,40]. Increased levels of ALP were seen in PCa patients with BM, and decreases in ALP levels were also observed in PCa patients with BM after radium-233 radionuclide therapy [41,42]. However, due to its correlation with several non-neoplastic illnesses, including liver cancer and cholecystitis [43], serum total ALP (TALP) shows low sensitivity in the diagnosis of PCa BM, and the cut-off (C/O) value of TALP varies widely in different researches [44]. TALP is better suited for predicting overall survival (OS) than for detecting BM. Clinical trials examining the use of life-extending drugs in metastatic CRPC (mCRPC) have shown that the initial alkaline phosphatase (ALP) level can predict overall survival regardless of the treatment administered [45]. In a meta-analysis, individuals with hormone-sensitive prostate cancer (HSPC) who had high blood ALP levels had an elevated risk of death and disease aggravation [38]. Nevertheless, it has not been demonstrated that TALP can predict survival in PCa patients receiving treatment for hormone-resistant malignancy [46].
Bone-specific alkaline phosphatase (BALP) has shown more potential in various investigations; it is produced by osteoblasts and may also express directly in PCa cells [45] due to its higher specificity [47]. The mineralization of the bone matrix depends on the extracellular enzyme BALP [48]. BALP values are less variable since it is less dependent on food and renal function. Elevated serum BALP is primarily caused by enhanced osteoblastic activity and secondary bone resorption events. These features make BALP a more accurate metric for identifying BM. Zaninotto et al. [24] contrasted 33 healthy individuals with 65 patients who had metastatic PCa, concluding that BALP was more specific (90% vs. 57%) than TALP in diagnosing BM, although both had comparable sensitivity (around 65%).
Patients with BM demonstrated increased TALP and BALP levels compared to those without [25,26,27,49]. In PCa patients, with 18.4 ng/mL as the C/O value, BALP levels exhibited a specificity of 92% and a sensitivity of 92% in BM diagnosis [28]. Furthermore, Karim et al. [29] found from univariate and multivariate analyses that lower BALP levels are a highly important predictor of greater OS in CRPC BM patients. In a meta-analysis of phase III trials of zoledronic acid [50], a higher baseline BAP level in PCa patients predicted more SRE (OR = 1.5; p < 0.03) and PCa progression (OR = 2.6; p < 0.001). These investigations showed that BALP is a more reliable biomarker in PCa BM diagnosis and prognosis compared to TALP.

2.2. Osteocalcin (OC)

OC is the most common non-collagenous protein present in bones. It is synthesized by osteoblasts during osteoid production and is later released into the bloodstream to promote bone growth [51]. Studies have shown that PCa BM patients exhibit higher OC levels [30,47,52], since osteoblasts’ synthesis of OC is very closely tied to the progression of PCa metastasis [52,53]. Thus, elevated serum OC levels are regarded as signs of metastatic disease for PCa. However, Jung et al. [26] reported that OC is rather ineffective as a diagnostic or prognosis indicator of bone metastatic spread. Furthermore, in a comparative study, Maeda et al. [31] found that all markers they mentioned in the text, except for OC, were considerably lower in PCa patients without BM than those with. High lipid amounts that bind OC may also confuse detection [54]. What’s more, previous research has found that circulating OC is highest in early adulthood, lowest in midlife, and has mixed results in older adults [55]. The γ-carboxylated (cOC) and uncarboxylated (ucOC) serve distinct functions in the human body [55,56]. Therefore, OC might not be the best option for predicting BM considering its uncertainty and poor specificity.

2.3. Pro-Collagen Type I N-Terminal Pro-Peptide (PINP) and Pro-Collagen Type I C-Terminal Pro-Peptide (PICP)

PINP and PICP are well-established markers of bone formation. Procollagen peptidases contribute to the production of mature type I collagen. This process involves the breakdown of these peptides from opposite ends of the procollagen molecule [57]. Numerous studies have shown that BM can bring up serum PINP and PICP levels in PCa patients [26,32,58,59]. Koopmans et al. [32] demonstrated that a rise in PINP is a sign that PCa BM is progressing. PINP has a specificity of 78% and sensitivity of 68% in BM defemination when the C/O value is set at 58 mcg/L. Significantly, elevated levels of PINP can be observed eight months before the initial detection of metastases through bone scintigraphy [32]. Jung et al. [26] used logistic regression analysis to predict BM, and the overall correct classification for PINP was 84%. According to a single-variable cox regression analysis, PCa BM patients, who present with elevated serum levels of PINP, had shorter survival in contrast to those with normal levels [33]. Piedra et al. [60] considered PINP an adequate predictor of SREs and mortality risk. PINP was similarly thought to be a reliable predictor of OS in PCa BM patients who were receiving zoledronic acid by Jung et al. [61]. The clinical judgment process is therefore aided by the P1NP level, highlighting the crucial roles of PINP and PICP as PCa BM prognostic and predictive markers.

2.4. Osteopontin (OPN)

OPN is mainly synthesized by osteoblasts [62]. Some studies have shown that PCa proliferation and metastasis are inextricably correlated to OPN [34,63,64]. Using genetically engineered mice, Khodavirdi et al. revealed that OPN expression is found at various phases of the development of prostate neoplasms, especially in metastatic sites [34]. The enhanced capacity of cancer cells to migrate and metastasize is caused by the upregulation of CD44 and MMP-9 expression, which is triggered by αvβ3 binding OPN [63]. Bisphosphonates could inhibit PCa cells’ migration because OPN binds to the v3 receptor and interacts with CD44 and MMP-9 on the cell membrane [65]. A recent meta-analysis demonstrated that BM and lymph node metastasis were favorably correlated with elevated OPN levels [64]. According to Thoms et al. [35], with regard to the response rate in mCRPC patients following chemotherapy, OPN has the same prognostic relevance as PSA. However, they also found that OPN has limited ability to differentiate metastatic PCa from localized PCa. In breast cancer, OPN-R3, as an OPN RNA aptamer, can minimize local progression and distant metastasis by activating PI3K-Akt-like signaling [66]. In conclusion, OPN still needs more experiments to validate its role in diagnosis, prognosis, and therapeutics of advanced PCa.

2.5. Osteoprotegerin (OPG)

OPG can bind to RANKL, impeding its interaction with RANK, thus limiting osteoclast activation and increasing bone mass [67]. The BM of PCa is correlated with the overexpression of OPG. Ye et al. [68] discovered that osteoblasts receive miR-141-3p from PCa cells, which was followed by an increase in OPG expression through p38 MAPK signaling. Osteoblast activity is then stimulated by this progress, which helps create a microenvironment of BM. Al Nakouzi et al. [69] transplanted the IGR-CaP1 cell line into male athymic nude mice that were six weeks old. The researchers discovered that IGR-CaP1-implanted mice exhibited elevated expression of OPG in the bone microenvironment of their tibias. In contrast, control animals that received PBS injections did not exhibit such changes in OPG expression in their tibias. In 2001, Jung et al. [36] had already identified OPG as a biomarker of PCa BM. In this research, the diagnostic sensitivity and specificity of OPG in discriminating PCa patients experiencing BM was 88% and 93%, respectively. Later, Jung et al. [26] compared 10 serum markers in diagnosing PCa BM, and discovered that among all serum markers, OPG, at 3.44 pmol/L, had a specificity of 94% and sensitivity of 93%. Furthermore, in univariate analysis, OPG showed the greatest relative risk, suggesting that it indicates cancer burden rather than being just a predictor of the development of bone density [26]. However, a variety of other organs also produce OPG. Thus, when diagnosing BM, altered serum OPG concentrations brought on by other illness, such as vascular disease [70], must be considered.
Interestingly, several investigations have found that OPG may be involved in the treatment of PCa BM. In a study, PCa cells were injected into severe combined immunodeficient mice both intratibially and subcutaneously, followed by OPG administration [37]. The researchers found that untreated mice had boosted osteoclast counts at the interface of tumor and bone, while OPG-treated mice had regular osteoclast counts. Following OPG treatment, the formation of mixed lytic and sclerotic tibial tumors was thus completely prevented. In another study, OPG inhibited tumor cell growth by decreasing serum PSA levels in a mouse model [71]. In summary, OPG is not only an indicator of bone turnover in PCa patients but also a viable treatment approach for preventing BM of PCa.

3. Bone Resorption Markers

3.1. Bone Sialoprotein (BSP)

BSP is produced by several cell types, including osteoclasts and hypertrophic chondrocytes [72]. BSP is considered a useful bone resorption diagnostic marker that reflects osteoclast activity [73]. Cancer cells may use BSP to get better migration across matrix barriers as they spread to different tissues, especially bone [74,75]. Bellahcène et al. [76] discovered that among patients with breast cancer, higher BSP expression was linked to BM (p = 0.008). Just 8% of patients who tested negative for BSP went on to develop BM, compared to 22% of patients who tested positive for BSP developed BM, according to a retrospective analysis of BSP values in pathological tissue of breast cancer from 454 individuals [77]. High BSP expression may predict BM in PCa, as it did in breast cancer. Waltregny et al. [78] also found high serum BSP levels in individuals with PCa BM. Wei et al. [79] compared BSP’s accuracy with PSA-like indicators in diagnosing PCa BM, demonstrating the higher sensitivity of BSP than other indices. Wang et al. [80] demonstrated that higher BSP levels promote the development of BM. However, Wolfgang et al. [81] found that serum BSP appears to have lower diagnostic potency than all other discovered bone conversion indicators in patients with cancer BM, according to z-score and ROC curve analysis. In addition, according to Jung et al., PCa patients without BM or with lymph node metastases had high serum BSP concentrations as well, much as PCa patients with BM [26]. They hypothesized that excessive BSP expression in PCa tissues would increase serum BSP levels before the occurrence of BM. Jain et al. [82] found that only in the final stage of the illness do serum BSP levels rise in PCa, raising doubts about BSP’s early diagnostic utility in this disease (Table 3). Therefore, unlike in breast cancer, BSP levels should not be regarded as a particular BM marker in PCa diagnosis. Further research should focus on the effectiveness of serum BSP in predicting BM in PCa patients.

3.2. C-Telopeptide of Type I Collagen (CTx) and N-Telopeptide of Type I Collagen (NTx)

Approximately 90% of the organic chemical compounds found in bones are made up of type I collagen. As bones are absorbed, CTx and NTx breakdown products of collagen are released and then collected in urine through renal excretion. In CRPC BM patients, lower urine NTx levels often have some connections with more favorable OS in univariate analyses and multivariate analyses [29,83]. Furthermore, solid tumor patients who had elevated or medium NTx levels exhibited a twofold higher risk of SREs and tumor progression [50]. The same outcomes were seen by Jung et al. in BM patients receiving zoledronic acid treatment. As compared to people who had low NTx levels, they found that those who had elevated NTx levels exhibited a 2.21-fold increased chance of bone lesion development, and patients with intermediate NTx levels announced a 1.57-fold greater risk (both p < 0.001) [61]. The increases in NTx were observed six months before the occurrence of SREs [61]. Thus, elevated NTx levels may aid in the improvement of the follow-up treatment plan. However, it appears that NTx and CTx have a low sensitivity for diagnosing PCa BM. With a C/O value of 26.9 nmol/L BCE, the sensitivity of NTx is 61%. The sensitivity of CTx is even lower, which drops to 30% with a C/O value of 0.627 μg/L [26]. Intriguingly, Piedra et al. [28] discovered that NTx and CTx both had a 100% sensitivity in the detection of BM in PCa without and with BM or some untreated individuals with benign prostate hyperplasia (BPH). Given the scarcity of relevant studies, the application of CTx or NTx alone in diagnosing BM warrants further investigation.

3.3. Tartrate-Resistant Acid Phosphatase (TRACP)

In contrast to CTX and NTX, the level of serum TRACP-5b is unaffected by changes in the time of day, food intake, or renal dysfunction [90]. The specific osteoclast activity marker TRACP-5b is predominantly generated by osteoclasts [91]. TRACP-5b levels have been shown to have significant correlations with BM [26,47]. Jung et al. [26] demonstrated that, at a C/O value of 4.62 U/L, TRACP-5b’s accuracy in diagnosing PCa BM was 77% in sensitivity and 85% in specificity. Yamamichi et al. [84] found that at 335 mIU/dl, TRACP-5b was highly associated with the severity of PCa DM. A combined application of TRACP-5b and PSA can accurately detect PCa BM (AUC = 0.95). According to Ozu et al. [85], patients with BM exhibited significantly greater TRACP-5b levels than those without. Additionally, there was a strong interrelationship between serum TRACP-5b levels and the condition on bone scintigraphy. Salminen et al. [86] demonstrated that at a C/O value of 4.98 U/L, TRACP-5b levels had the highest diagnostic accuracy in distinguishing between individuals with BM and those without. Furthermore, using Kaplan-Meier analysis, they discovered that only 46% of PCa patients with higher TRACP-5b levels (>4.98 U/L) survived for 5 years, whereas for those with lower TRACP-5b levels (<4.98 U/L), 88% of them survived for 5 years (p = 0.002). High osteoclast specificity and resistance to hepatic and renal dysfunction are two characteristics of TRACP-5b. Diet and physiological changes also have no impact on it [84]. In conclusion, TRACP-5b is a reliable biomarker for PCa BM diagnosis.

3.4. C-Terminal Pyridinoline Cross-Linked Telopeptide of Type I Collagen (ICTP)

ICTP is a byproduct generated during the breakdown of type I collagen [92]. According to the reports of Koga et al. [93] and Koopmans et al. [32], PCa patients with BM had serum ICTP levels that were considerably higher than PCa patients without BM. Wei et al. [79] demonstrated that ICTP showed a sensitivity of 69.05% and specificity of 76.8% for the identification of skeletal metastases at a positive critical value of 4.3 U/L. Another study reveals that ICTP’s sensitivity and specificity in diagnosing BCa BM are 78.6% and 88.0%, respectively, at a C/O value of 5.0 ng/mL [87]. Further, they found that ICTP is more effective at differentiating between PCa patients with and without BM when used in conjunction with PSA and ALP. In research involving 83 samples from 70 PCa individuals (32 with and 38 without BM), the ICTP level showed a stronger correlation with the severity of the condition compared with PSA-like bone markers [31]. Furthermore, Kamiya et al. [88] demonstrated that serum ICTP level was an independent predictor of BM and cause-specific survival. Jung et al. [61] showed that in PCa BM treated with zoledronic acid, ICTP was found to be an appropriate predictor of OS. The ICTP level would be beneficial for both patients, who want complete information about their condition, as well as for clinicians when making decisions about additional treatment protocols. In summary, ICTP is an appropriate biomarker for the treatment of PCa BM, especially when combined with other reliable markers.

3.5. Pyridoxine (PYD) and Deoxypyridinoline (D-PYD)

PYD is a cross-link found both within and between collagen molecules that help keep collagen fibers stable and can be deoxidized to form D-PYD cross-linked collagen [94]. With the breakdown of bone tissue, PYD and D-PYD are discharged into the bloodstream [95]. Considerable PYD and DPYD levels were noticed in individuals with PCa BM when compared to those without BM [94,96,97,98]. Furthermore, higher PYD levels were associated with worse OS in a study including 778 PCa patients [89]. Individuals with values above and below the median had different median survival times (15 months vs. 22 months), with a risk ratio of 1.52 (95% CI = 1.28, 1.81). Additionally, because PYD and D-PYD are bone-specific and unaffected by diet, they more accurately depict the degree of BM compared to other bone markers [94].

4. Prostate-Specific Antigen (PSA)

PSA is the cornerstone of PCa screening [99]. PSA testing not only performed well in PCa screening, but it also did well in identifying BM in individuals with PCa. Oesterling first hypothesized that PSA provides valuable insights into the prognosis of BM in 1993. They revealed that it does not seem necessary for newly diagnosed PCa patients (without skeletal symptoms) with serum PSA levels equal to or below 10.0 mg/L to have a staging radionuclide bone scan [100]. Salminen et al. [86] constructed ROC curves in 84 PCa patients to compare the efficacy of various markers in detecting BM. They found that PSA had an area under the curve of 0.87, indicating a good degree of diagnostic precision for BM. Kataoka et al. [87] started research involving 155 men with Pca, which reveals that the sensitivity and specificity of PSA in identifying BM are 100% and 79.8%, respectively, at a threshold value of 40.0 ng/mL. Additionally, they discovered that combining PSA, ICTP, and ALP is more effective in identifying individuals with PCa BM from those without. Ozu et al. [85]’s study including 215 untreated PCa patients revealed that PSA, TRACP, and ALP were important independent predictors of BM, with PSA expressing the highest OR through multivariate logistic regression analysis. The predicted likelihood of BM was strongly associated with the actual incidence of BM as calculated by combining PSA, ALP, and TRACP results.
Additionally, a relationship between PSA levels and tumor heterogeneity, tumor size, and disease severity has been documented [101]. However, PSA is only prostate but not PCa specific. Thus, PSA levels can signal innocuous conditions like prostatitis or BPH [99]. In conclusion, PSA is an effective marker for identifying PCa BM. Yet, combining PSA with other markers will improve the accuracy of PCa BM diagnosis.

5. Neuroendocrine Markers

An invasive subtype of CRPC [102], the primary diagnostic criteria for NEPC include morphological features and the detection of neuroendocrine markers secreted from neuroendocrine tumor cells, including neuron-specific enolase (NSE) and chromogranin A (CgA) [103,104]. Patients diagnosed with mCRPC displayed 2–3 times higher levels of CgA and NSE compared to those with localized PCa, according to an examination of 1095 serum samples from 395 men, including 157 with localized PCa and 238 with mCRPC [105]. Niedworok et al. [106] proved that CgA levels were considerably higher in advanced PCa patients in comparison to clinically localized cases after examining 110 plasma and 127 serum samples. Before the start of abiraterone acetate, Heck et al. [107] evaluated the NSE and CgA levels at baseline in mCRPC patients. If CgA or NSE levels exceeded the baseline values (85 ng/mL and 16 ng/mL, respectively), OS was considerably reduced. According to Kamiya et al. [108], the mean NSE blood levels were considerably higher in PCa BM patients than in patients without such metastatic conditions (p < 0.05), and serum NSE seems to be a standalone death indicator. Furthermore, in some studies, levels of CgA and NSE are also utilized to assess specific effects of chemotherapy and hormonal therapies in CRPC patients [109,110]. However, high CgA levels are also seen in those who have sepsis, cardiac failure, renal failure, hypertension, and several inflammatory diseases [111]. Instead of an absolute value, CgA level may be more informative concerning the earlier stage of PCa.
Another neuroendocrine marker, pro-gastrin releasing peptide (ProGRP), is a reliable indicator for small cell lung cancer [112]. Yu et al. [113] discovered that ProGRP is also useful in diagnosing PCa BM. They observed that the mean ProGRP level in PCa BM patients was 36.81 pg/mL, compared to 22 pg/mL in those without BM. In ROC analysis, the AUC is up to 0.941 when ProGRP was used in combination with total PSA (Table 4).

6. Liquid Biopsy Markers

As the gold standard, liquid biopsy for solid tumor diagnosis is less intrusive, more affordable, and provides real-time tumor status information compared to tissue biopsy. Liquid biopsy markers for cancer are classified into three types: cell-free nucleic acids, extracellular vesicles (EVs), and CTCs (Table 5). These methods might help with PCa BM evaluation and prognosis.

6.1. MicroRNA (miRNA)

MiRNAs that originate from within the cell interact with mRNA targets to regulate vital cellular processes [129]. MiRNAs have considerable advantages as biomarkers since they are extremely stable and selective for detection in a variety of physiological fluids [130,131]. Numerous pieces of research have shown that miRNAs were involved in the occurrence and progress of PCa BM [132,133,134]. According to Colden et al. [114], upregulation of miR-466 could significantly attenuate the proliferation and BM of PCa cells by regulating the RUNX2 signaling pathway. Compared with normal tissues, miR-466 was significantly downregulated in PCa tissues (p < 0.0001), and patients with high miR-466 expression had lower recurrence rates and better prognostic outcomes, making it a great potential for diagnostic and prognostic applications in PCa. Ren et al. [135] discovered that tissues of patients with PCa who display signs of BM showed enhanced miR-210-3p levels than those without BM. Following intracardial injection, miR-210p silencing decreased tumor burden and reduce bone metastatic sites.
In blood circulation, miR-141 level was observed a trend of increasing as the disease develops from organ-confined disease to metastatic PCa [115,121]. Further, the prevalence of BM is inversely correlated with miRNA-141 expression [136]. Thus, miR-141-3p could be monitored to determine risk for PCa-related metastatic disease [137]. Peng et al. [116] discovered that serum miR-218-5p levels were considerably lower in PCa BM than in PCa patients without BM. Their ROC curve analysis in PCa patients, with and without BM, showed an AUC of 0.86 (95% CI: 0.80–0.92, p < 0.001). These findings hint that miR-218-5p could be a promising signature molecule for detecting BM in PCa patients. Furthermore, patients with CRPC, which eventually leads to BM, had considerably higher levels of serum miRNA-375, miRNA-378, miRNA-141 [117], and miR-194 [138] than localized PCa. By examining serum samples in PCa BM population, Brase and colleagues [115] also revealed miR-141/375 as the most distinguishing marker for cancer progression.

6.2. Cell-Free DNA (cfDNA) and Circulating Tumor DNA (ctDNA)

Cell-Free DNA (cfDNA) are DNA fragments produced mainly by hematopoietic cells undergoing apoptosis [139] entering circulation. In cancer patients, about 1% of total cfDNA is made up of ctDNA [140], which is discharged into circulation when necrosis or apoptosis occurs in malignant cells. Tumor fraction (TFx), or the proportion of ctDNA in plasma cfDNA, together with cfDNA have been suggested as prognostic biomarkers in malignancies, even though it is not a very high percentage [141]. Jung et al. [118] exemplified that cfDNA levels were much higher in patients with metastatic PCa and showed predictive value for OS of metastatic PCa. In order to profile advanced PCa, Morrison et al. [119] paired cfDNA with radiomic analysis of CT bone scans. They discovered a strong correlation between cfDNA and the CT bone scan results. In addition, Kohli et al. [120] found that mCRPC and mHSPC patients with a large amount of ctDNA were observed to have a poor prognosis. For ctDNA, Choudhury et al. [142] proclaimed that TFx level has predictive performance for early response to therapy, which is associated with the extent of visceral and bone metastases in PCa development.

6.3. Exosomes

While the aforementioned miRNA and cfDNA demonstrate promising value in PCa BM treatment, the presence of exosomes makes them even more potent biomarkers. Exosomes are EVs with a diameter of 50–150 nm. Various cell types release exosomes that carry cell-derived molecules, such as proteins and nucleic acids [143]. Many miRNA molecules that are biostable in body fluids and blood circulation, and function as cancer biomarkers, have been found in exosomes; some refer to them as exosomal shuttle RNA [144]. However, when RNA is extracted directly from plasma, an excessive volume of platelet-derived RNA may provide a significant background of megakaryocyte RNA, obstructing analysis [145]. Biofluids can be a source for enriching exosomes utilizing tumor-specific surface marker proteins, improving the specificity of the analysis [146]. Furthermore, combining exosomal RNA and ctDNA increases the chance of finding mutated copies in blood samples by up to 10-fold when compared to ctDNA alone [147].
The previously mentioned circulating miR-141 and miR-375 are also part of the exosomal miRNAs that play a diagnostic and prognostic role in PCa BM [125,148]. Ye et al., found both miR-141-3p and miR-375 regulate the BM microenvironment by promoting osteoblast activity, thus inducing BM of PCa [68,149]. Circulating miR-141 levels were significantly higher in metastatic PCa compared to localized PCa [115,121]. Further, the combination of circulating exosomal miR-375 and miR-1290 is an effective predictor of prognosis for CRPC patients [150]. In addition, Laura et al. [122] found that urine exosomal miR-141 and miR-375 levels of patients with high-risk PCa were also significantly higher compared to those of patients with low-risk PCa or normal subjects. Similar to the action of miR-141, exosomal hsa-miR-940 targets and promotes the differentiation of MSCs to osteoblasts and can, by implantation, induce a change from an osteolytic to an osteoblastic phenotype in cancer cells [151]. In contrast to the effect of miR-141, Furesi et al. [152] found that miR-27a-3p, miR-26a-5p, and miR-30e-5p are transferred by PCa-derived EV to suppress osteoblast genesis and prevent bone mineralization, thus possibly aiding in the formation of PCa bone tumors. Exosomal miR-21 has been identified as a promising biomarker for the diagnosis of PCa, but higher plasma exosomal miR-21 has also been observed in metastatic PCa compared to localized PCa [121,153].
Exosomal miR-1246 was described by Bhagirath et al. [123] as having the potential to differentiate between benign, aggressive, and normal types of PCa. They demonstrated that miR-1246 level of aggressive PCa increased 31- and 23-fold in contrast to normal prostatic hyperplasia and BPH, respectively. In addition, high expression of urinary exosomal miR-2909 is also considered an important marker for determining the aggressiveness of PCa [124].
Exosomes of another origin, semen exosomes, are promising non-invasive biomarkers like urine exosomes that can help with the diagnosis and prognosis of PCa BM as well. Semen-derived miR-342-3p and miR-374b-5p are useful in differentiating high-risk PCa [154]. Ruiz et al. [125] also observed that the semen-derived exosomes miR-221-3p, miR-222-3p have high accuracy in determining the prognosis of PCa (AUC = 0.857, p = 0.001).
Compared with patients with BPH and non-metastatic PCa, exosomal proteins ITGA3 and ITGB1 were found in higher amounts in the urine of individuals with metastatic PCa according to Bijnsdorp et al. [126]. These proteins may be used as biomarkers in diagnosing PCa metastasis. Other proteins, such as plasma exocrine PSA, have been used to differentiate between BPH and PCa [155]. In another study, PCa-derived exosomes encourage osteoblast proliferation and activity by secreting phospholipase D2, therefore encouraging the development of PCa BM [156]. In conclusion, although some mechanisms need to be further investigated, the various components of the exosome and the combined liquid biopsy are crucial in the diagnosis of PCa BM.

6.4. Circulating Tumor Cells (CTCs)

As cancer cells, CTCs could potentially spread to distant sites. Danila et al. [127] found in 120 subjects with progressing CRPC that individuals with BM alone, or with involvement of both bone and soft tissues, had median CTC counts of 10.5 or 13.5 cells, against 2.5 cells in patients without BM, and that baseline CTC was predictive of survival [127]. In addition to CTC count, CTC phenotyping has also been found to be helpful in PCa BM diagnosis and personalized PCa treatment. A strong correlation was observed in the gene expression patterns of nine genes between plasma CTCs and metastatic tissue samples from PCa BM patients in the spine [157]. Another gene, Ezrin, was found to be more expressed in both CTCs and PCa cells with BM characteristics than in those without [128]. Therefore, CTC phenotyping may provide reliable diagnostic and therapeutic targets. However, due to its rarity and tendency to appear in the late stages of cancer, its early diagnostic utility is still debatable.

7. Conclusions

Due to delayed diagnosis, patients with PCa BM infrequently obtain successful targeted treatment at an early stage. Thus, it is necessary to investigate more precise diagnostic techniques. The use of BM biomarkers can help predict and detect BM early, thus helping to take effective treatment measures. Numerous studies have discussed the roles of biomarkers in assessing the potency of chemotherapy or immunotherapy in PCa BM patients. Furthermore, since the test sample is typically blood or urine, the markers mentioned in the text are simple to obtain and less invasive to the body. This analysis offers an objective and critical overview of five different classes of promising biomarkers: bone formation/resorption markers, PSA, neuroendocrine, and liquid biopsy markers. Some of these bone formation/resorption markers are well established for the diagnosis of BM from PCa, while others require more clinical studies to determine their ultimate utility in diagnosing PCa BM, although their diagnostic and prognostic value has been described in studies on BM from lung cancer or breast cancer. PSA, a traditional PCa diagnostic marker, also contributes to the diagnosis and prognosis of BM from PCa. Although PSA lacks specificity, serial PSA monitoring is usually beneficial in individuals with advanced PCa. Neuroendocrine and liquid markers have been prominently investigated as emerging biomarkers in recent years, but neither are now utilized frequently in PCa clinical practice. For their clinical validation, more prospective studies are required. PCa BM is a complicated condition. PCa cells evade the primary tumor site, colonize and alter the bone microenvironment, and interact with osteoblasts, osteoclasts, and other bone cells in a vicious loop. Each individual has different biomarkers that are beneficial at different phases of BM’s development. In patients with BM, it is doubtful that a single biomarker would be useful for diagnosis or prognosis. Hence, combining numerous biomarkers and imaging modalities is expected to help the assessment of metastatic PCa.

Author Contributions

Conceptualization, M.Y. and H.W.; data curation, M.Y., L.S., G.B. and Z.Z.; writing—original draft preparation, M.Y. and J.M.; writing—review and editing, M.Y., J.M. and Z.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Siegel, R.L.; Miller, K.D.; Fuchs, H.E.; Jemal, A. Cancer statistics, 2022. CA Cancer J. Clin. 2022, 72, 7–33. [Google Scholar] [CrossRef] [PubMed]
  2. Xia, C.; Dong, X.; Li, H.; Cao, M.; Sun, D.; He, S.; Yang, F.; Yan, X.; Zhang, S.; Li, N.; et al. Cancer statistics in China and United States, 2022: Profiles, trends, and determinants. Chin. Med. J. 2022, 135, 584–590. [Google Scholar] [CrossRef]
  3. Simmons, J.K.; Hildreth, B.E., 3rd; Supsavhad, W.; Elshafae, S.M.; Hassan, B.B.; Dirksen, W.P.; Toribio, R.E.; Rosol, T.J. Animal Models of Bone Metastasis. Vet. Pathol. 2015, 52, 827–841. [Google Scholar] [CrossRef] [PubMed]
  4. Huang, S.H.; Kao, Y.H.; Muller, C.J.F.; Joubert, E.; Chuu, C.P. Aspalathin-rich green Aspalathus linearis extract suppresses migration and invasion of human castration-resistant prostate cancer cells via inhibition of YAP signaling. Phytomedicine 2020, 69, 153210. [Google Scholar] [CrossRef] [PubMed]
  5. Yu, Z.; Zou, H.; Wang, H.; Li, Q.; Yu, D. Identification of Key Gene Signatures Associated with Bone Metastasis in Castration-Resistant Prostate Cancer Using Co-Expression Analysis. Front. Oncol. 2020, 10, 571524. [Google Scholar] [CrossRef] [PubMed]
  6. Qu, L.; Li, S.; Zhuo, Y.; Chen, J.; Qin, X.; Guo, G. Anticancer effect of triterpenes from Ganoderma lucidum in human prostate cancer cells. Oncol. Lett. 2017, 14, 7467–7472. [Google Scholar] [CrossRef]
  7. Lee, S.; Mendoza, T.R.; Burner, D.N.; Muldong, M.T.; Wu, C.C.N.; Arreola-Villanueva, C.; Zuniga, A.; Greenburg, O.; Zhu, W.Y.; Murtadha, J.; et al. Novel Dormancy Mechanism of Castration Resistance in Bone Metastatic Prostate Cancer Organoids. Int. J. Mol. Sci. 2022, 23, 3203. [Google Scholar] [CrossRef]
  8. Morale, M.G.; Tamura, R.E.; Rubio, I.G.S. Metformin and Cancer Hallmarks: Molecular Mechanisms in Thyroid, Prostate and Head and Neck Cancer Models. Biomolecules 2022, 12, 157. [Google Scholar] [CrossRef]
  9. Chi, J.T.; Lin, P.H.; Tolstikov, V.; Oyekunle, T.; Chen, E.Y.; Bussberg, V.; Greenwood, B.; Sarangarajan, R.; Narain, N.R.; Kiebish, M.A.; et al. Metabolomic effects of androgen deprivation therapy treatment for prostate cancer. Cancer Med. 2020, 9, 3691–3702. [Google Scholar] [CrossRef]
  10. Salji, M.; Hendry, J.; Patel, A.; Ahmad, I.; Nixon, C.; Leung, H.Y. Peri-prostatic Fat Volume Measurement as a Predictive Tool for Castration Resistance in Advanced Prostate Cancer. Eur. Urol. Focus. 2018, 4, 858–866. [Google Scholar] [CrossRef]
  11. Yang, L.; Jin, M.; Park, S.J.; Seo, S.Y.; Jeong, K.W. SETD1A Promotes Proliferation of Castration-Resistant Prostate Cancer Cells via FOXM1 Transcription. Cancers 2020, 12, 1736. [Google Scholar] [CrossRef] [PubMed]
  12. Talreja, D.B. Importance of antiresorptive therapies for patients with bone metastases from solid tumors. Cancer Manag. Res. 2012, 4, 287–297. [Google Scholar] [CrossRef] [PubMed]
  13. Coleman, R.E. Clinical features of metastatic bone disease and risk of skeletal morbidity. Clin. Cancer Res. 2006, 12, 6243s–6249s. [Google Scholar] [CrossRef] [PubMed]
  14. Clézardin, P.; Coleman, R.; Puppo, M.; Ottewell, P.; Bonnelye, E.; Paycha, F.; Confavreux, C.B.; Holen, I. Bone metastasis: Mechanisms, therapies, and biomarkers. Physiol. Rev. 2021, 101, 797–855. [Google Scholar] [CrossRef]
  15. Clarke, N.W.; Hart, C.A.; Brown, M.D. Molecular mechanisms of metastasis in prostate cancer. Asian J. Androl. 2009, 11, 57–67. [Google Scholar] [CrossRef] [PubMed]
  16. Wu, H.; Xu, T.; Wang, X.; Yu, Y.B.; Fan, Z.Y.; Li, D.X.; Luo, L.; Yang, X.C.; Jiao, W.; Niu, H.T. Diagnostic Performance of (68) Gallium Labelled Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography and Magnetic Resonance Imaging for Staging the Prostate Cancer with Intermediate or High Risk Prior to Radical Prostatectomy: A Systematic Review and Meta-analysis. World J. Mens. Health 2020, 38, 208–219. [Google Scholar] [CrossRef]
  17. Luna, A.; Vilanova, J.C.; Alcalá Mata, L. Total body MRI in early detection of bone metastasis and its indication in comparison to bone scan and other imaging techniques. Arch. Esp. Urol. 2015, 68, 371–390. [Google Scholar]
  18. Kang, J.; La Manna, F.; Bonollo, F.; Sampson, N.; Alberts, I.L.; Mingels, C.; Afshar-Oromieh, A.; Thalmann, G.N.; Karkampouna, S. Tumor microenvironment mechanisms and bone metastatic disease progression of prostate cancer. Cancer Lett. 2022, 530, 156–169. [Google Scholar] [CrossRef]
  19. Bock, N.; Kryza, T.; Shokoohmand, A.; Röhl, J.; Ravichandran, A.; Wille, M.L.; Nelson, C.C.; Hutmacher, D.W.; Clements, J.A. In vitro engineering of a bone metastases model allows for study of the effects of antiandrogen therapies in advanced prostate cancer. Sci. Adv. 2021, 7, eabg2564. [Google Scholar] [CrossRef]
  20. Hagberg Thulin, M.; Jennbacken, K.; Damber, J.E.; Welén, K. Osteoblasts stimulate the osteogenic and metastatic progression of castration-resistant prostate cancer in a novel model for in vitro and in vivo studies. Clin. Exp. Metastasis 2014, 31, 269–283. [Google Scholar] [CrossRef]
  21. Kim, H.; Lee, J.H.; Lee, S.K.; Song, N.Y.; Son, S.H.; Kim, K.R.; Chung, W.Y. Chemerin Treatment Inhibits the Growth and Bone Invasion of Breast Cancer Cells. Int. J. Mol. Sci. 2020, 21, 2871. [Google Scholar] [CrossRef] [PubMed]
  22. Helo, S.; Manger, J.P.; Krupski, T.L. Role of denosumab in prostate cancer. Prostate Cancer Prostatic Dis. 2012, 15, 231–236. [Google Scholar] [CrossRef] [PubMed]
  23. Yue, Z.; Niu, X.; Yuan, Z.; Qin, Q.; Jiang, W.; He, L.; Gao, J.; Ding, Y.; Liu, Y.; Xu, Z.; et al. RSPO2 and RANKL signal through LGR4 to regulate osteoclastic premetastatic niche formation and bone metastasis. J. Clin. Investig. 2022, 132. [Google Scholar] [CrossRef] [PubMed]
  24. Zaninotto, M.; Secchiero, S.; Rubin, D.; Sciacovelli, L.; Trovò, M.; Bortolus, R.; Plebani, M. Serum bone alkaline phosphatase in the follow-up of skeletal metastases. Anticancer Res. 1995, 15, 2223–2228. [Google Scholar]
  25. Zhao, H.; Han, K.L.; Wang, Z.Y.; Chen, Y.; Li, H.T.; Zeng, J.L.; Shen, Z.; Yao, Y. Value of C-telopeptide-cross-linked Type I collagen, osteocalcin, bone-specific alkaline phosphatase and procollagen Type I N-terminal propeptide in the diagnosis and prognosis of bone metastasis in patients with malignant tumors. Med. Sci. Monit. 2011, 17, Cr626–Cr633. [Google Scholar] [CrossRef]
  26. Jung, K.; Lein, M.; Stephan, C.; Von Hösslin, K.; Semjonow, A.; Sinha, P.; Loening, S.A.; Schnorr, D. Comparison of 10 serum bone turnover markers in prostate carcinoma patients with bone metastatic spread: Diagnostic and prognostic implications. Int. J. Cancer 2004, 111, 783–791. [Google Scholar] [CrossRef]
  27. Rasch-Isla Muñoz, A.; Cataño Cataño, J.G. Usefulness of bone-specific alkaline phosphatase for bone metastases detection in prostate cancer. Arch. Esp. Urol. 2004, 57, 693–698. [Google Scholar]
  28. De la Piedra, C.; Castro-Errecaborde, N.A.; Traba, M.L.; Méndez-Dávila, C.; García-Moreno, C.; Rodriguez de Acuña, L.; Rodriguez-Molina, J. Bone remodeling markers in the detection of bone metastases in prostate cancer. Clin. Chim. Acta 2003, 331, 45–53. [Google Scholar] [CrossRef]
  29. Fizazi, K.; Massard, C.; Smith, M.; Rader, M.; Brown, J.; Milecki, P.; Shore, N.; Oudard, S.; Karsh, L.; Carducci, M.; et al. Bone-related Parameters are the Main Prognostic Factors for Overall Survival in Men with Bone Metastases from Castration-resistant Prostate Cancer. Eur. Urol. 2015, 68, 42–50. [Google Scholar] [CrossRef]
  30. Arai, Y.; Takeuchi, H.; Oishi, K.; Yoshida, O. Osteocalcin: Is it a useful marker of bone metastasis and response to treatment in advanced prostate cancer? Prostate 1992, 20, 169–177. [Google Scholar] [CrossRef]
  31. Maeda, H.; Koizumi, M.; Yoshimura, K.; Yamauchi, T.; Kawai, T.; Ogata, E. Correlation between bone metabolic markers and bone scan in prostatic cancer. J. Urol. 1997, 157, 539–543. [Google Scholar] [CrossRef] [PubMed]
  32. Koopmans, N.; de Jong, I.J.; Breeuwsma, A.J.; van der Veer, E. Serum bone turnover markers (PINP and ICTP) for the early detection of bone metastases in patients with prostate cancer: A longitudinal approach. J. Urol. 2007, 178, 849–853; discussion 853; quiz 1129. [Google Scholar] [CrossRef] [PubMed]
  33. Brasso, K.; Christensen, I.J.; Johansen, J.S.; Teisner, B.; Garnero, P.; Price, P.A.; Iversen, P. Prognostic value of PINP, bone alkaline phosphatase, CTX-I, and YKL-40 in patients with metastatic prostate carcinoma. Prostate 2006, 66, 503–513. [Google Scholar] [CrossRef] [PubMed]
  34. Khodavirdi, A.C.; Song, Z.; Yang, S.; Zhong, C.; Wang, S.; Wu, H.; Pritchard, C.; Nelson, P.S.; Roy-Burman, P. Increased expression of osteopontin contributes to the progression of prostate cancer. Cancer Res. 2006, 66, 883–888. [Google Scholar] [CrossRef] [PubMed]
  35. Thoms, J.W.; Dal Pra, A.; Anborgh, P.H.; Christensen, E.; Fleshner, N.; Menard, C.; Chadwick, K.; Milosevic, M.; Catton, C.; Pintilie, M.; et al. Plasma osteopontin as a biomarker of prostate cancer aggression: Relationship to risk category and treatment response. Br. J. Cancer 2012, 107, 840–846. [Google Scholar] [CrossRef]
  36. Jung, K.; Lein, M.; von Hösslin, K.; Brux, B.; Schnorr, D.; Loening, S.A.; Sinha, P. Osteoprotegerin in serum as a novel marker of bone metastatic spread in prostate cancer. Clin. Chem. 2001, 47, 2061–2063. [Google Scholar] [CrossRef]
  37. Zhang, J.; Dai, J.; Qi, Y.; Lin, D.L.; Smith, P.; Strayhorn, C.; Mizokami, A.; Fu, Z.; Westman, J.; Keller, E.T. Osteoprotegerin inhibits prostate cancer-induced osteoclastogenesis and prevents prostate tumor growth in the bone. J. Clin. Investig. 2001, 107, 1235–1244. [Google Scholar] [CrossRef]
  38. Mori, K.; Janisch, F.; Parizi, M.K.; Mostafaei, H.; Lysenko, I.; Enikeev, D.V.; Kimura, S.; Egawa, S.; Shariat, S.F. Prognostic value of alkaline phosphatase in hormone-sensitive prostate cancer: A systematic review and meta-analysis. Int. J. Clin. Oncol. 2020, 25, 247–257. [Google Scholar] [CrossRef]
  39. Tong, T.; Lei, H.; Guan, Y.; Yang, X.; Liao, G.; Li, Y.; Jiang, D.; Pang, J. Revealing Prognostic Value of Skeletal-Related Parameters in Metastatic Castration-Resistant Prostate Cancer on Overall Survival: A Systematic Review and Meta-Analysis of Randomized Controlled Trial. Front. Oncol. 2020, 10, 586192. [Google Scholar] [CrossRef]
  40. D’Oronzo, S.; Brown, J.; Coleman, R. The value of biomarkers in bone metastasis. Eur. J. Cancer Care 2017, 26, e12725. [Google Scholar] [CrossRef]
  41. Scalzi, P.; Baiocco, C.; Genovese, S.; Trevisan, A.; Sirotova, Z.; Poti, C. Evaluation of bone metastases by 18F-choline PET/CT in a patient with castration-resistant prostate cancer treated with radium-223. Urologia 2017, 84, 61–64. [Google Scholar] [CrossRef] [PubMed]
  42. Miyazaki, K.S.; Kuang, Y.; Kwee, S.A. Changes in Skeletal Tumor Activity on (18)F-choline PET/CT in Patients Receiving (223)Radium Radionuclide Therapy for Metastatic Prostate Cancer. Nucl. Med. Mol. Imaging 2015, 49, 160–164. [Google Scholar] [CrossRef] [PubMed]
  43. Chung, J.H.; Park, M.S.; Kim, Y.S.; Chang, J.; Kim, J.H.; Kim, S.K.; Kim, S.K. Usefulness of bone metabolic markers in the diagnosis of bone metastasis from lung cancer. Yonsei Med. J. 2005, 46, 388–393. [Google Scholar] [CrossRef] [PubMed]
  44. Yamamichi, G.; Kato, T.; Uemura, M.; Nonomura, N. Diagnosing and Prognosing Bone Metastasis in Prostate Cancer: Clinical Utility of Blood Biomarkers. Anticancer. Res. 2023, 43, 283–290. [Google Scholar] [CrossRef]
  45. Heinrich, D.; Bruland, Ø.; Guise, T.A.; Suzuki, H.; Sartor, O. Alkaline phosphatase in metastatic castration-resistant prostate cancer: Reassessment of an older biomarker. Future Oncol. 2018, 14, 2543–2556. [Google Scholar] [CrossRef]
  46. Petrioli, R.; Rossi, S.; Caniggia, M.; Pozzessere, D.; Messinese, S.; Sabatino, M.; Marsili, S.; Correale, P.; Salvestrini, F.; Manganelli, A.; et al. Analysis of biochemical bone markers as prognostic factors for survival in patients with hormone-resistant prostate cancer and bone metastases. Urology 2004, 63, 321–326. [Google Scholar] [CrossRef]
  47. Hegele, A.; Wahl, H.G.; Varga, Z.; Sevinc, S.; Koliva, L.; Schrader, A.J.; Hofmann, R.; Olbert, P. Biochemical markers of bone turnover in patients with localized and metastasized prostate cancer. BJU Int. 2007, 99, 330–334. [Google Scholar] [CrossRef]
  48. Xue, Y.; Li, R.; Zhao, Y.; Li, L.; Zhou, Y. Effects of sleeve gastrectomy on bone mass, microstructure of femurs and bone metabolism associated serum factors in obese rats. BMC Endocr. Disord. 2021, 21, 173. [Google Scholar] [CrossRef]
  49. Ebert, W.; Muley, T.; Herb, K.P.; Schmidt-Gayk, H. Comparison of bone scintigraphy with bone markers in the diagnosis of bone metastasis in lung carcinoma patients. Anticancer Res. 2004, 24, 3193–3201. [Google Scholar]
  50. Coleman, R.E.; Major, P.; Lipton, A.; Brown, J.E.; Lee, K.A.; Smith, M.; Saad, F.; Zheng, M.; Hei, Y.J.; Seaman, J.; et al. Predictive value of bone resorption and formation markers in cancer patients with bone metastases receiving the bisphosphonate zoledronic acid. J. Clin. Oncol. 2005, 23, 4925–4935. [Google Scholar] [CrossRef]
  51. Lopes, L.S.; Schwartz, R.P.; Ferraz-de-Souza, B.; da Silva, M.E.; Corrêa, P.H.; Nery, M. The role of enteric hormone GLP-2 in the response of bone markers to a mixed meal in postmenopausal women with type 2 diabetes mellitus. Diabetol. Metab. Syndr. 2015, 7, 13. [Google Scholar] [CrossRef] [PubMed]
  52. Gardner, T.A.; Lee, S.J.; Lee, S.D.; Li, X.; Shirakawa, T.; Kwon, D.D.; Park, R.Y.; Ahn, K.Y.; Jung, C. Differential expression of osteocalcin during the metastatic progression of prostate cancer. Oncol. Rep. 2009, 21, 903–908. [Google Scholar] [CrossRef]
  53. Nimptsch, K.; Rohrmann, S.; Nieters, A.; Linseisen, J. Serum undercarboxylated osteocalcin as biomarker of vitamin K intake and risk of prostate cancer: A nested case-control study in the Heidelberg cohort of the European prospective investigation into cancer and nutrition. Cancer Epidemiol. Biomarkers Prev. 2009, 18, 49–56. [Google Scholar] [CrossRef] [PubMed]
  54. Lee, A.J.; Hodges, S.; Eastell, R. Measurement of osteocalcin. Ann. Clin. Biochem. 2000, 37 Pt 4, 432–446. [Google Scholar] [CrossRef] [PubMed]
  55. Smith, C.; Voisin, S.; Al Saedi, A.; Phu, S.; Brennan-Speranza, T.; Parker, L.; Eynon, N.; Hiam, D.; Yan, X.; Scott, D.; et al. Osteocalcin and its forms across the lifespan in adult men. Bone 2020, 130, 115085. [Google Scholar] [CrossRef] [PubMed]
  56. Hayashi, Y.; Kawakubo-Yasukochi, T.; Mizokami, A.; Takeuchi, H.; Nakamura, S.; Hirata, M. Differential Roles of Carboxylated and Uncarboxylated Osteocalcin in Prostate Cancer Growth. J. Cancer 2016, 7, 1605–1609. [Google Scholar] [CrossRef]
  57. Krege, J.H.; Lane, N.E.; Harris, J.M.; Miller, P.D. PINP as a biological response marker during teriparatide treatment for osteoporosis. Osteoporos. Int. 2014, 25, 2159–2171. [Google Scholar] [CrossRef]
  58. Akimoto, S.; Furuya, Y.; Akakura, K.; Ito, H. Comparison of markers of bone formation and resorption in prostate cancer patients to predict bone metastasis. Endocr. J. 1998, 45, 97–104. [Google Scholar] [CrossRef]
  59. Koizumi, M.; Yonese, J.; Fukui, I.; Ogata, E. The serum level of the amino-terminal propeptide of type I procollagen is a sensitive marker for prostate cancer metastasis to bone. BJU Int. 2001, 87, 348–351. [Google Scholar] [CrossRef]
  60. De la Piedra, C.; Alcaraz, A.; Bellmunt, J.; Meseguer, C.; Gómez-Caamano, A.; Ribal, M.J.; Vázquez, F.; Anido, U.; Samper, P.; Esteban, E.; et al. Usefulness of bone turnover markers as predictors of mortality risk, disease progression and skeletal-related events appearance in patients with prostate cancer with bone metastases following treatment with zoledronic acid: TUGAMO study. Br. J. Cancer 2013, 108, 2565–2572. [Google Scholar] [CrossRef]
  61. Jung, K.; Miller, K.; Wirth, M.; Albrecht, M.; Lein, M. Bone turnover markers as predictors of mortality risk in prostate cancer patients with bone metastases following treatment with zoledronic acid. Eur. Urol. 2011, 59, 604–612. [Google Scholar] [CrossRef] [PubMed]
  62. Wang, K.X.; Denhardt, D.T. Osteopontin: Role in immune regulation and stress responses. Cytokine Growth Factor Rev. 2008, 19, 333–345. [Google Scholar] [CrossRef] [PubMed]
  63. Zhao, H.; Chen, Q.; Alam, A.; Cui, J.; Suen, K.C.; Soo, A.P.; Eguchi, S.; Gu, J.; Ma, D. The role of osteopontin in the progression of solid organ tumour. Cell. Death Dis. 2018, 9, 356. [Google Scholar] [CrossRef]
  64. Yu, A.; Guo, K.; Qin, Q.; Xing, C.; Zu, X. Clinicopathological and prognostic significance of osteopontin expression in patients with prostate cancer: A systematic review and meta-analysis. Biosci. Rep. 2021, 41, BSR20203531. [Google Scholar] [CrossRef]
  65. Desai, B.; Rogers, M.J.; Chellaiah, M.A. Mechanisms of osteopontin and CD44 as metastatic principles in prostate cancer cells. Mol. Cancer 2007, 6, 18. [Google Scholar] [CrossRef]
  66. Mi, Z.; Guo, H.; Russell, M.B.; Liu, Y.; Sullenger, B.A.; Kuo, P.C. RNA aptamer blockade of osteopontin inhibits growth and metastasis of MDA-MB231 breast cancer cells. Mol. Ther. 2009, 17, 153–161. [Google Scholar] [CrossRef] [PubMed]
  67. Zinonos, I.; Luo, K.W.; Labrinidis, A.; Liapis, V.; Hay, S.; Panagopoulos, V.; Denichilo, M.; Ko, C.H.; Yue, G.G.; Lau, C.B.; et al. Pharmacologic inhibition of bone resorption prevents cancer-induced osteolysis but enhances soft tissue metastasis in a mouse model of osteolytic breast cancer. Int. J. Oncol. 2014, 45, 532–540. [Google Scholar] [CrossRef]
  68. Ye, Y.; Li, S.L.; Ma, Y.Y.; Diao, Y.J.; Yang, L.; Su, M.Q.; Li, Z.; Ji, Y.; Wang, J.; Lei, L.; et al. Exosomal miR-141-3p regulates osteoblast activity to promote the osteoblastic metastasis of prostate cancer. Oncotarget 2017, 8, 94834–94849. [Google Scholar] [CrossRef]
  69. Al Nakouzi, N.; Bawa, O.; Le Pape, A.; Lerondel, S.; Gaudin, C.; Opolon, P.; Gonin, P.; Fizazi, K.; Chauchereau, A. The IGR-CaP1 xenograft model recapitulates mixed osteolytic/blastic bone lesions observed in metastatic prostate cancer. Neoplasia 2012, 14, 376–387. [Google Scholar] [CrossRef]
  70. Ndip, A.; Williams, A.; Jude, E.B.; Serracino-Inglott, F.; Richardson, S.; Smyth, J.V.; Boulton, A.J.; Alexander, M.Y. The RANKL/RANK/OPG signaling pathway mediates medial arterial calcification in diabetic Charcot neuroarthropathy. Diabetes 2011, 60, 2187–2196. [Google Scholar] [CrossRef]
  71. Kiefer, J.A.; Vessella, R.L.; Quinn, J.E.; Odman, A.M.; Zhang, J.; Keller, E.T.; Kostenuik, P.J.; Dunstan, C.R.; Corey, E. The effect of osteoprotegerin administration on the intra-tibial growth of the osteoblastic LuCaP 23.1 prostate cancer xenograft. Clin. Exp. Metastasis 2004, 21, 381–387. [Google Scholar] [CrossRef] [PubMed]
  72. Kruger, T.E.; Miller, A.H.; Godwin, A.K.; Wang, J. Bone sialoprotein and osteopontin in bone metastasis of osteotropic cancers. Crit. Rev. Oncol. Hematol. 2014, 89, 330–341. [Google Scholar] [CrossRef] [PubMed]
  73. Chawalitpong, S.; Chokchaisiri, R.; Suksamrarn, A.; Katayama, S.; Mitani, T.; Nakamura, S.; Athamneh, A.A.; Ritprajak, P.; Leelahavanichkul, A.; Aeimlapa, R.; et al. Cyperenoic acid suppresses osteoclast differentiation and delays bone loss in a senile osteoporosis mouse model by inhibiting non-canonical NF-κB pathway. Sci. Rep. 2018, 8, 5625. [Google Scholar] [CrossRef] [PubMed]
  74. Chen, J.; Rodriguez, J.A.; Barnett, B.; Hashimoto, N.; Tang, J.; Yoneda, T. Bone sialoprotein promotes tumor cell migration in both in vitro and in vivo models. Connect. Tissue Res. 2003, 44 (Suppl. S1), 279–284. [Google Scholar] [CrossRef] [PubMed]
  75. Karadag, A.; Ogbureke, K.U.; Fedarko, N.S.; Fisher, L.W. Bone sialoprotein, matrix metalloproteinase 2, and alpha(v)beta3 integrin in osteotropic cancer cell invasion. J. Natl. Cancer Inst. 2004, 96, 956–965. [Google Scholar] [CrossRef] [PubMed]
  76. Bellahcene, A.; Kroll, M.; Liebens, F.; Castronovo, V. Bone sialoprotein expression in primary human breast cancer is associated with bone metastases development. J. Bone Miner. Res. 1996, 11, 665–670. [Google Scholar] [CrossRef]
  77. Bellahcène, A.; Menard, S.; Bufalino, R.; Moreau, L.; Castronovo, V. Expression of bone sialoprotein in primary human breast cancer is associated with poor survival. Int. J. Cancer 1996, 69, 350–353. [Google Scholar] [CrossRef]
  78. Waltregny, D.; Bellahcène, A.; Van Riet, I.; Fisher, L.W.; Young, M.; Fernandez, P.; Dewé, W.; de Leval, J.; Castronovo, V. Prognostic value of bone sialoprotein expression in clinically localized human prostate cancer. J. Natl. Cancer Inst. 1998, 90, 1000–1008. [Google Scholar] [CrossRef]
  79. Wei, R.J.; Li, T.Y.; Yang, X.C.; Jia, N.; Yang, X.L.; Song, H.B. Serum levels of PSA, ALP, ICTP, and BSP in prostate cancer patients and the significance of ROC curve in the diagnosis of prostate cancer bone metastases. Genet. Mol. Res. 2016, 15, 15. [Google Scholar] [CrossRef]
  80. Wang, Y.; Zhang, X.F.; Dai, J.; Zheng, Y.C.; Zhang, M.G.; He, J.J. Predictive value of serum bone sialoprotein and prostate-specific antigen doubling time in patients with bone metastasis of prostate cancer. J. Huazhong Univ. Sci. Technolog Med. Sci. 2013, 33, 559–562. [Google Scholar] [CrossRef]
  81. Withold, W.; Armbruster, F.P.; Karmatschek, M.; Reinauer, H. Bone sialoprotein in serum of patients with malignant bone diseases. Clin. Chem. 1997, 43, 85–91. [Google Scholar] [CrossRef] [PubMed]
  82. Jain, A.; McKnight, D.A.; Fisher, L.W.; Humphreys, E.B.; Mangold, L.A.; Partin, A.W.; Fedarko, N.S. Small integrin-binding proteins as serum markers for prostate cancer detection. Clin. Cancer Res. 2009, 15, 5199–5207. [Google Scholar] [CrossRef] [PubMed]
  83. Rajpar, S.; Massard, C.; Laplanche, A.; Tournay, E.; Gross-Goupil, M.; Loriot, Y.; Di Palma, M.; Bossi, A.; Escudier, B.; Chauchereau, A.; et al. Urinary N-telopeptide (uNTx) is an independent prognostic factor for overall survival in patients with bone metastases from castration-resistant prostate cancer. Ann. Oncol. 2010, 21, 1864–1869. [Google Scholar] [CrossRef] [PubMed]
  84. Yamamichi, G.; Kato, T.; Yumiba, S.; Tomiyama, E.; Koh, Y.; Nakano, K.; Matsushita, M.; Hayashi, Y.; Ishizuya, Y.; Watabe, T.; et al. Diagnostic and prognostic significance of tartrate-resistant acid phosphatase type 5b in newly diagnosed prostate cancer with bone metastasis: A real-world multi-institutional study. Int. J. Urol. 2023, 30, 70–76. [Google Scholar] [CrossRef]
  85. Ozu, C.; Nakashima, J.; Horiguchi, Y.; Oya, M.; Ohigashi, T.; Murai, M. Prediction of bone metastases by combination of tartrate-resistant acid phosphatase, alkaline phosphatase and prostate specific antigen in patients with prostate cancer. Int. J. Urol. 2008, 15, 419–422. [Google Scholar] [CrossRef]
  86. Salminen, E.K.; Kallioinen, M.J.; Ala-Houhala, M.A.; Vihinen, P.P.; Tiitinen, S.L.; Varpula, M.; Vahlberg, T.J. Survival markers related to bone metastases in prostate cancer. Anticancer Res. 2006, 26, 4879–4884. [Google Scholar]
  87. Kataoka, A.; Yuasa, T.; Kageyama, S.; Tsuchiya, N.; Habuchi, T.; Iwaki, H.; Narita, M.; Okada, Y.; Yoshiki, T. Diagnosis of bone metastasis in men with prostate cancer by measurement of serum ICTP in combination with alkali phosphatase and prostate-specific antigen. Clin. Oncol. 2006, 18, 480–484. [Google Scholar] [CrossRef]
  88. Kamiya, N.; Suzuki, H.; Yano, M.; Endo, T.; Takano, M.; Komaru, A.; Kawamura, K.; Sekita, N.; Imamoto, T.; Ichikawa, T. Implications of serum bone turnover markers in prostate cancer patients with bone metastasis. Urology 2010, 75, 1446–1451. [Google Scholar] [CrossRef]
  89. Lara, P.N., Jr.; Ely, B.; Quinn, D.I.; Mack, P.C.; Tangen, C.; Gertz, E.; Twardowski, P.W.; Goldkorn, A.; Hussain, M.; Vogelzang, N.J.; et al. Serum biomarkers of bone metabolism in castration-resistant prostate cancer patients with skeletal metastases: Results from SWOG 0421. J. Natl. Cancer Inst. 2014, 106, dju013. [Google Scholar] [CrossRef]
  90. Kikuchi, W.; Ichihara, K.; Mori, K.; Shimizu, Y. Biological sources of variations of tartrate-resistant acid phosphatase 5b in a healthy Japanese population. Ann. Clin. Biochem. 2021, 58, 358–367. [Google Scholar] [CrossRef]
  91. Guo, H.; Weng, W.; Zhang, S.; Rinderknecht, H.; Braun, B.; Breinbauer, R.; Gupta, P.; Kumar, A.; Ehnert, S.; Histing, T.; et al. Maqui Berry and Ginseng Extracts Reduce Cigarette Smoke-Induced Cell Injury in a 3D Bone Co-Culture Model. Antioxidants 2022, 11, 2460. [Google Scholar] [CrossRef] [PubMed]
  92. Hanson, D.A.; Weis, M.A.; Bollen, A.M.; Maslan, S.L.; Singer, F.R.; Eyre, D.R. A specific immunoassay for monitoring human bone resorption: Quantitation of type I collagen cross-linked N-telopeptides in urine. J. Bone Miner. Res. 1992, 7, 1251–1258. [Google Scholar] [CrossRef] [PubMed]
  93. Koga, H.; Naito, S.; Koto, S.; Sakamoto, N.; Nakashima, M.; Yamasaki, T.; Noma, H.; Kumazawa, J. Use of bone turnover marker, pyridinoline cross-linked carboxyterminal telopeptide of type I collagen (ICTP), in the assessment and monitoring of bone metastasis in prostate cancer. Prostate 1999, 39, 1–7. [Google Scholar] [CrossRef]
  94. Sano, M.; Kushida, K.; Takahashi, M.; Ohishi, T.; Kawana, K.; Okada, M.; Inoue, T. Urinary pyridinoline and deoxypyridinoline in prostate carcinoma patients with bone metastasis. Br. J. Cancer 1994, 70, 701–703. [Google Scholar] [CrossRef]
  95. Coleman, R.E.; Houston, S.; James, I.; Rodger, A.; Rubens, R.D.; Leonard, R.C.; Ford, J. Preliminary results of the use of urinary excretion of pyridinium crosslinks for monitoring metastatic bone disease. Br. J. Cancer 1992, 65, 766–768. [Google Scholar] [CrossRef]
  96. Takeuchi, S.; Arai, K.; Saitoh, H.; Yoshida, K.; Miura, M. Urinary pyridinoline and deoxypyridinoline as potential markers of bone metastasis in patients with prostate cancer. J. Urol. 1996, 156, 1691–1695. [Google Scholar] [CrossRef] [PubMed]
  97. Miyamoto, K.K.; McSherry, S.A.; Robins, S.P.; Besterman, J.M.; Mohler, J.L. Collagen cross-link metabolites in urine as markers of bone metastases in prostatic carcinoma. J. Urol. 1994, 151, 909–913. [Google Scholar] [CrossRef] [PubMed]
  98. Takeuchi, S.; Saitoh, H. The clinical usefulness of urinary pyridinoline and deoxypyridinoline as potential markers of bone metastasis in patients with prostate cancer. Nihon Rinsho 1998, 56, 2077–2081. [Google Scholar]
  99. Sekhoacha, M.; Riet, K.; Motloung, P.; Gumenku, L.; Adegoke, A.; Mashele, S. Prostate Cancer Review: Genetics, Diagnosis, Treatment Options, and Alternative Approaches. Molecules 2022, 27, 5730. [Google Scholar] [CrossRef]
  100. Oesterling, J.E.; Martin, S.K.; Bergstralh, E.J.; Lowe, F.C. The use of prostate-specific antigen in staging patients with newly diagnosed prostate cancer. JAMA 1993, 269, 57–60. [Google Scholar] [CrossRef]
  101. Partin, A.W.; Carter, H.B.; Chan, D.W.; Epstein, J.I.; Oesterling, J.E.; Rock, R.C.; Weber, J.P.; Walsh, P.C. Prostate specific antigen in the staging of localized prostate cancer: Influence of tumor differentiation, tumor volume and benign hyperplasia. J. Urol. 1990, 143, 747–752. [Google Scholar] [CrossRef] [PubMed]
  102. Asrani, K.; Torres, A.F.; Woo, J.; Vidotto, T.; Tsai, H.K.; Luo, J.; Corey, E.; Hanratty, B.; Coleman, I.; Yegnasubramanian, S.; et al. Reciprocal YAP1 loss and INSM1 expression in neuroendocrine prostate cancer. J. Pathol. 2021, 255, 425–437. [Google Scholar] [CrossRef] [PubMed]
  103. Vlachostergios, P.J.; Puca, L.; Beltran, H. Emerging Variants of Castration-Resistant Prostate Cancer. Curr. Oncol. Rep. 2017, 19, 32. [Google Scholar] [CrossRef] [PubMed]
  104. Muoio, B.; Pascale, M.; Roggero, E. The role of serum neuron-specific enolase in patients with prostate cancer: A systematic review of the recent literature. Int. J. Biol. Markers 2018, 33, 10–21. [Google Scholar] [CrossRef] [PubMed]
  105. Szarvas, T.; Csizmarik, A.; Fazekas, T.; Hüttl, A.; Nyirády, P.; Hadaschik, B.; Grünwald, V.; Püllen, L.; Jurányi, Z.; Kocsis, Z.; et al. Comprehensive analysis of serum chromogranin A and neuron-specific enolase levels in localized and castration-resistant prostate cancer. BJU Int. 2021, 127, 44–55. [Google Scholar] [CrossRef] [PubMed]
  106. Niedworok, C.; Tschirdewahn, S.; Reis, H.; Lehmann, N.; Szücs, M.; Nyirády, P.; Romics, I.; Rübben, H.; Szarvas, T. Serum Chromogranin A as a Complementary Marker for the Prediction of Prostate Cancer-Specific Survival. Pathol. Oncol. Res. 2017, 23, 643–650. [Google Scholar] [CrossRef] [PubMed]
  107. Heck, M.M.; Thaler, M.A.; Schmid, S.C.; Seitz, A.K.; Tauber, R.; Kübler, H.; Maurer, T.; Thalgott, M.; Hatzichristodoulou, G.; Höppner, M.; et al. Chromogranin A and neurone-specific enolase serum levels as predictors of treatment outcome in patients with metastatic castration-resistant prostate cancer undergoing abiraterone therapy. BJU Int. 2017, 119, 30–37. [Google Scholar] [CrossRef]
  108. Kamiya, N.; Akakura, K.; Suzuki, H.; Isshiki, S.; Komiya, A.; Ueda, T.; Ito, H. Pretreatment serum level of neuron specific enolase (NSE) as a prognostic factor in metastatic prostate cancer patients treated with endocrine therapy. Eur. Urol. 2003, 44, 309–314; discussion 314. [Google Scholar] [CrossRef]
  109. Yang, K.; Li, T.; Gao, Z.; Zhang, W. Effect of abiraterone combined with prednisone on serum CgA and NSE in metastatic castration-resistant prostate cancer without previous chemotherapy. Trop. J. Pharm. Res. 2019, 18, 631–637. [Google Scholar] [CrossRef]
  110. Fléchon, A.; Pouessel, D.; Ferlay, C.; Perol, D.; Beuzeboc, P.; Gravis, G.; Joly, F.; Oudard, S.; Deplanque, G.; Zanetta, S.; et al. Phase II study of carboplatin and etoposide in patients with anaplastic progressive metastatic castration-resistant prostate cancer (mCRPC) with or without neuroendocrine differentiation: Results of the French Genito-Urinary Tumor Group (GETUG) P01 trial. Ann. Oncol. 2011, 22, 2476–2481. [Google Scholar] [CrossRef]
  111. Ploussard, G.; Rozet, F.; Roubaud, G.; Stanbury, T.; Sargos, P.; Roupret, M. Chromogranin A: A useful biomarker in castration-resistant prostate cancer. World J. Urol. 2022, 41, 361–369. [Google Scholar] [CrossRef] [PubMed]
  112. Dong, A.; Zhang, J.; Chen, X.; Ren, X.; Zhang, X. Diagnostic value of ProGRP for small cell lung cancer in different stages. J. Thorac. Dis. 2019, 11, 1182–1189. [Google Scholar] [CrossRef] [PubMed]
  113. Yu, M.; Yang, C.; Wang, S.; Zeng, Y.; Chen, Z.; Feng, N.; Ning, C.; Wang, L.; Xue, L.; Zhang, Z. Serum ProGRP as a novel biomarker of bone metastasis in prostate cancer. Clin. Chim. Acta 2020, 510, 437–441. [Google Scholar] [CrossRef] [PubMed]
  114. Colden, M.; Dar, A.A.; Saini, S.; Dahiya, P.V.; Shahryari, V.; Yamamura, S.; Tanaka, Y.; Stein, G.; Dahiya, R.; Majid, S. MicroRNA-466 inhibits tumor growth and bone metastasis in prostate cancer by direct regulation of osteogenic transcription factor RUNX2. Cell. Death Dis. 2017, 8, e2572. [Google Scholar] [CrossRef]
  115. Brase, J.C.; Johannes, M.; Schlomm, T.; Fälth, M.; Haese, A.; Steuber, T.; Beissbarth, T.; Kuner, R.; Sültmann, H. Circulating miRNAs are correlated with tumor progression in prostate cancer. Int. J. Cancer 2011, 128, 608–616. [Google Scholar] [CrossRef]
  116. Peng, P.; Chen, T.; Wang, Q.; Zhang, Y.; Zheng, F.; Huang, S.; Tang, Y.; Yang, C.; Ding, W.; Ren, D.; et al. Decreased miR-218-5p Levels as a Serum Biomarker in Bone Metastasis of Prostate Cancer. Oncol. Res. Treat. 2019, 42, 165–185. [Google Scholar] [CrossRef]
  117. Nguyen, H.C.; Xie, W.; Yang, M.; Hsieh, C.L.; Drouin, S.; Lee, G.S.; Kantoff, P.W. Expression differences of circulating microRNAs in metastatic castration resistant prostate cancer and low-risk, localized prostate cancer. Prostate 2013, 73, 346–354. [Google Scholar] [CrossRef]
  118. Jung, K.; Stephan, C.; Lewandowski, M.; Klotzek, S.; Jung, M.; Kristiansen, G.; Lein, M.; Loening, S.A.; Schnorr, D. Increased cell-free DNA in plasma of patients with metastatic spread in prostate cancer. Cancer Lett. 2004, 205, 173–180. [Google Scholar] [CrossRef]
  119. Morrison, G.; Buckley, J.; Ostrow, D.; Varghese, B.; Cen, S.Y.; Werbin, J.; Ericson, N.; Cunha, A.; Lu, Y.T.; George, T.; et al. Non-Invasive Profiling of Advanced Prostate Cancer via Multi-Parametric Liquid Biopsy and Radiomic Analysis. Int. J. Mol. Sci. 2022, 23, 2571. [Google Scholar] [CrossRef]
  120. Kohli, M.; Tan, W.; Zheng, T.; Wang, A.; Montesinos, C.; Wong, C.; Du, P.; Jia, S.; Yadav, S.; Horvath, L.G.; et al. Clinical and genomic insights into circulating tumor DNA-based alterations across the spectrum of metastatic hormone-sensitive and castrate-resistant prostate cancer. EBioMedicine 2020, 54, 102728. [Google Scholar] [CrossRef]
  121. Yaman Agaoglu, F.; Kovancilar, M.; Dizdar, Y.; Darendeliler, E.; Holdenrieder, S.; Dalay, N.; Gezer, U. Investigation of miR-21, miR-141, and miR-221 in blood circulation of patients with prostate cancer. Tumour Biol. 2011, 32, 583–588. [Google Scholar] [CrossRef] [PubMed]
  122. Foj, L.; Ferrer, F.; Serra, M.; Arévalo, A.; Gavagnach, M.; Giménez, N.; Filella, X. Exosomal and Non-Exosomal Urinary miRNAs in Prostate Cancer Detection and Prognosis. Prostate 2017, 77, 573–583. [Google Scholar] [CrossRef] [PubMed]
  123. Bhagirath, D.; Yang, T.L.; Bucay, N.; Sekhon, K.; Majid, S.; Shahryari, V.; Dahiya, R.; Tanaka, Y.; Saini, S. microRNA-1246 Is an Exosomal Biomarker for Aggressive Prostate Cancer. Cancer Res. 2018, 78, 1833–1844. [Google Scholar] [CrossRef] [PubMed]
  124. Wani, S.; Kaul, D.; Mavuduru, R.S.; Kakkar, N.; Bhatia, A. Urinary-exosomal miR-2909: A novel pathognomonic trait of prostate cancer severity. J. Biotechnol. 2017, 259, 135–139. [Google Scholar] [CrossRef]
  125. Ruiz-Plazas, X.; Altuna-Coy, A.; Alves-Santiago, M.; Vila-Barja, J.; García-Fontgivell, J.F.; Martínez-González, S.; Segarra-Tomás, J.; Chacón, M.R. Liquid Biopsy-Based Exo-oncomiRNAs Can Predict Prostate Cancer Aggressiveness. Cancers 2021, 13, 250. [Google Scholar] [CrossRef]
  126. Bijnsdorp, I.V.; Geldof, A.A.; Lavaei, M.; Piersma, S.R.; van Moorselaar, R.J.; Jimenez, C.R. Exosomal ITGA3 interferes with non-cancerous prostate cell functions and is increased in urine exosomes of metastatic prostate cancer patients. J. Extracell. Vesicles 2013, 2, 22097. [Google Scholar] [CrossRef]
  127. Danila, D.C.; Heller, G.; Gignac, G.A.; Gonzalez-Espinoza, R.; Anand, A.; Tanaka, E.; Lilja, H.; Schwartz, L.; Larson, S.; Fleisher, M.; et al. Circulating tumor cell number and prognosis in progressive castration-resistant prostate cancer. Clin. Cancer Res. 2007, 13, 7053–7058. [Google Scholar] [CrossRef]
  128. Chen, Z.; Wang, J.; Lu, Y.; Lai, C.; Qu, L.; Zhuo, Y. Ezrin expression in circulating tumor cells is a predictor of prostate cancer metastasis. Bioengineered 2022, 13, 4076–4084. [Google Scholar] [CrossRef]
  129. Fabris, L.; Ceder, Y.; Chinnaiyan, A.M.; Jenster, G.W.; Sorensen, K.D.; Tomlins, S.; Visakorpi, T.; Calin, G.A. The Potential of MicroRNAs as Prostate Cancer Biomarkers. Eur. Urol. 2016, 70, 312–322. [Google Scholar] [CrossRef]
  130. Lu, J.; Getz, G.; Miska, E.A.; Alvarez-Saavedra, E.; Lamb, J.; Peck, D.; Sweet-Cordero, A.; Ebert, B.L.; Mak, R.H.; Ferrando, A.A.; et al. MicroRNA expression profiles classify human cancers. Nature 2005, 435, 834–838. [Google Scholar] [CrossRef]
  131. Chen, X.; Ba, Y.; Ma, L.; Cai, X.; Yin, Y.; Wang, K.; Guo, J.; Zhang, Y.; Chen, J.; Guo, X.; et al. Characterization of microRNAs in serum: A novel class of biomarkers for diagnosis of cancer and other diseases. Cell. Res. 2008, 18, 997–1006. [Google Scholar] [CrossRef] [PubMed]
  132. Kim, K.; Kim, H.H.; Lee, C.H.; Kim, S.; Cheon, G.J.; Kang, K.W.; Chung, J.K.; Youn, H. Therapeutic efficacy of modified anti-miR21 in metastatic prostate cancer. Biochem. Biophys. Res. Commun. 2020, 529, 707–713. [Google Scholar] [CrossRef] [PubMed]
  133. Jones, D.Z.; Schmidt, M.L.; Suman, S.; Hobbing, K.R.; Barve, S.S.; Gobejishvili, L.; Brock, G.; Klinge, C.M.; Rai, S.N.; Park, J.; et al. Micro-RNA-186-5p inhibition attenuates proliferation, anchorage independent growth and invasion in metastatic prostate cancer cells. BMC Cancer 2018, 18, 421. [Google Scholar] [CrossRef] [PubMed]
  134. Oh-Hohenhorst, S.J.; Lange, T. Role of Metastasis-Related microRNAs in Prostate Cancer Progression and Treatment. Cancers 2021, 13, 4492. [Google Scholar] [CrossRef]
  135. Ren, D.; Yang, Q.; Dai, Y.; Guo, W.; Du, H.; Song, L.; Peng, X. Oncogenic miR-210-3p promotes prostate cancer cell EMT and bone metastasis via NF-κB signaling pathway. Mol. Cancer 2017, 16, 117. [Google Scholar] [CrossRef]
  136. Zhang, H.L.; Qin, X.J.; Cao, D.L.; Zhu, Y.; Yao, X.D.; Zhang, S.L.; Dai, B.; Ye, D.W. An elevated serum miR-141 level in patients with bone-metastatic prostate cancer is correlated with more bone lesions. Asian J. Androl. 2013, 15, 231–235. [Google Scholar] [CrossRef]
  137. Kelly, B.D.; Miller, N.; Sweeney, K.J.; Durkan, G.C.; Rogers, E.; Walsh, K.; Kerin, M.J. A Circulating MicroRNA Signature as a Biomarker for Prostate Cancer in a High Risk Group. J. Clin. Med. 2015, 4, 1369–1379. [Google Scholar] [CrossRef]
  138. Das, R.; Gregory, P.A.; Fernandes, R.C.; Denis, I.; Wang, Q.; Townley, S.L.; Zhao, S.G.; Hanson, A.R.; Pickering, M.A.; Armstrong, H.K.; et al. MicroRNA-194 Promotes Prostate Cancer Metastasis by Inhibiting SOCS2. Cancer Res. 2017, 77, 1021–1034. [Google Scholar] [CrossRef]
  139. Stejskal, P.; Goodarzi, H.; Srovnal, J.; Hajdúch, M.; van ‘t Veer, L.J.; Magbanua, M.J.M. Circulating tumor nucleic acids: Biology, release mechanisms, and clinical relevance. Mol. Cancer 2023, 22, 15. [Google Scholar] [CrossRef]
  140. Snow, A.; Chen, D.; Lang, J.E. The current status of the clinical utility of liquid biopsies in cancer. Expert. Rev. Mol. Diagn. 2019, 19, 1031–1041. [Google Scholar] [CrossRef]
  141. Fan, G.; Zhang, K.; Yang, X.; Ding, J.; Wang, Z.; Li, J. Prognostic value of circulating tumor DNA in patients with colon cancer: Systematic review. PLoS ONE 2017, 12, e0171991. [Google Scholar] [CrossRef] [PubMed]
  142. Choudhury, A.D.; Werner, L.; Francini, E.; Wei, X.X.; Ha, G.; Freeman, S.S.; Rhoades, J.; Reed, S.C.; Gydush, G.; Rotem, D.; et al. Tumor fraction in cell-free DNA as a biomarker in prostate cancer. JCI Insight 2018, 3, e122109. [Google Scholar] [CrossRef] [PubMed]
  143. Pegtel, D.M.; Gould, S.J. Exosomes. Annu. Rev. Biochem. 2019, 88, 487–514. [Google Scholar] [CrossRef] [PubMed]
  144. Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Lötvall, J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell. Biol. 2007, 9, 654–659. [Google Scholar] [CrossRef] [PubMed]
  145. Brinkman, K.; Meyer, L.; Bickel, A.; Enderle, D.; Berking, C.; Skog, J.; Noerholm, M. Extracellular vesicles from plasma have higher tumour RNA fraction than platelets. J. Extracell. Vesicles 2020, 9, 1741176. [Google Scholar] [CrossRef] [PubMed]
  146. Yu, W.; Hurley, J.; Roberts, D.; Chakrabortty, S.K.; Enderle, D.; Noerholm, M.; Breakefield, X.O.; Skog, J.K. Exosome-based liquid biopsies in cancer: Opportunities and challenges. Ann. Oncol. 2021, 32, 466–477. [Google Scholar] [CrossRef]
  147. Krug, A.K.; Enderle, D.; Karlovich, C.; Priewasser, T.; Bentink, S.; Spiel, A.; Brinkmann, K.; Emenegger, J.; Grimm, D.G.; Castellanos-Rizaldos, E.; et al. Improved EGFR mutation detection using combined exosomal RNA and circulating tumor DNA in NSCLC patient plasma. Ann. Oncol. 2018, 29, 700–706. [Google Scholar] [CrossRef]
  148. Lorenc, T.; Klimczyk, K.; Michalczewska, I.; Słomka, M.; Kubiak-Tomaszewska, G.; Olejarz, W. Exosomes in Prostate Cancer Diagnosis, Prognosis and Therapy. Int. J. Mol. Sci. 2020, 21, 2118. [Google Scholar] [CrossRef]
  149. Li, S.L.; An, N.; Liu, B.; Wang, S.Y.; Wang, J.J.; Ye, Y. Exosomes from LNCaP cells promote osteoblast activity through miR-375 transfer. Oncol. Lett. 2019, 17, 4463–4473. [Google Scholar] [CrossRef]
  150. Huang, X.; Yuan, T.; Liang, M.; Du, M.; Xia, S.; Dittmar, R.; Wang, D.; See, W.; Costello, B.A.; Quevedo, F.; et al. Exosomal miR-1290 and miR-375 as prognostic markers in castration-resistant prostate cancer. Eur. Urol. 2015, 67, 33–41. [Google Scholar] [CrossRef]
  151. Hashimoto, K.; Ochi, H.; Sunamura, S.; Kosaka, N.; Mabuchi, Y.; Fukuda, T.; Yao, K.; Kanda, H.; Ae, K.; Okawa, A.; et al. Cancer-secreted hsa-miR-940 induces an osteoblastic phenotype in the bone metastatic microenvironment via targeting ARHGAP1 and FAM134A. Proc. Natl. Acad. Sci. USA 2018, 115, 2204–2209. [Google Scholar] [CrossRef] [PubMed]
  152. Furesi, G.; de Jesus Domingues, A.M.; Alexopoulou, D.; Dahl, A.; Hackl, M.; Schmidt, J.R.; Kalkhof, S.; Kurth, T.; Taipaleenmäki, H.; Conrad, S.; et al. Exosomal miRNAs from Prostate Cancer Impair Osteoblast Function in Mice. Int. J. Mol. Sci. 2022, 23, 1285. [Google Scholar] [CrossRef] [PubMed]
  153. Joković, S.M.; Dobrijević, Z.; Kotarac, N.; Filipović, L.; Popović, M.; Korać, A.; Vuković, I.; Savić-Pavićević, D.; Brajušković, G. MiR-375 and miR-21 as Potential Biomarkers of Prostate Cancer: Comparison of Matching Samples of Plasma and Exosomes. Genes 2022, 13, 2320. [Google Scholar] [CrossRef] [PubMed]
  154. Barceló, M.; Castells, M.; Bassas, L.; Vigués, F.; Larriba, S. Semen miRNAs Contained in Exosomes as Non-Invasive Biomarkers for Prostate Cancer Diagnosis. Sci. Rep. 2019, 9, 13772. [Google Scholar] [CrossRef] [PubMed]
  155. Logozzi, M.; Angelini, D.F.; Giuliani, A.; Mizzoni, D.; Di Raimo, R.; Maggi, M.; Gentilucci, A.; Marzio, V.; Salciccia, S.; Borsellino, G.; et al. Increased Plasmatic Levels of PSA-Expressing Exosomes Distinguish Prostate Cancer Patients from Benign Prostatic Hyperplasia: A Prospective Study. Cancers 2019, 11, 1449. [Google Scholar] [CrossRef]
  156. Borel, M.; Lollo, G.; Magne, D.; Buchet, R.; Brizuela, L.; Mebarek, S. Prostate cancer-derived exosomes promote osteoblast differentiation and activity through phospholipase D2. Biochim. Biophys. Acta Mol. Basis Dis. 2020, 1866, 165919. [Google Scholar] [CrossRef] [PubMed]
  157. Josefsson, A.; Larsson, K.; Månsson, M.; Björkman, J.; Rohlova, E.; Åhs, D.; Brisby, H.; Damber, J.E.; Welén, K. Circulating tumor cells mirror bone metastatic phenotype in prostate cancer. Oncotarget 2018, 9, 29403–29413. [Google Scholar] [CrossRef]
Table 1. Diagnostic and prognostic biomarkers in prostate cancer bone metastases.
Table 1. Diagnostic and prognostic biomarkers in prostate cancer bone metastases.
Bone formation markers• Alkaline Phosphatase (ALP)
• Osteocalcin (OC)
• Pro-collagen type I N-terminal pro-peptide(PINP)/Pro-collagen type I C-terminal pro-peptide(PICP)
• Osteopontin (OPN)
• Osteoprotegerin (OPG)
Bone resorption markers• Bone sialoprotein (BSP)
• C-telopeptide of type I collagen (CTx)/N-telopeptide of type I collagen (NTx)
• Tartrate-resistant acid phosphatase (TRACP)
• C-terminal pyridinoline cross-linked telopeptide of type I collagen (ICTP)
• Pyridinoline (PYD) and deoxypyridinoline (D-PYD)
PSA• Prostate-specific antigen (PSA)
Neuroendocrine markers• Chromogranin A (CgA)
• Neurone-specific enolase (NSE)
• Pro-gastrin-releasing peptide (ProGRP)
Liquid biopsy markers• MicroRNA
• Cell free DNA (cfDNA)/Circulating tumor DNA (ctDNA)
• Exosomes
• Circulating tumor cells (CTCs)
Table 2. Studies on bone formation markers.
Table 2. Studies on bone formation markers.
MarkerReferenceSample LocationSample Size (N)Finding
ALPZaninotto et al. [24]Serum65BALP was more specific (90% vs. 57%) than TALP in diagnosing BM, although both had comparable sensitivity (around 65%).
Zhao et al. [25]Serum792When BALP level is above 15.55 ng/mL, it has the greatest accuracy for diagnosing PCa BM.
Jung et al. [26]Serum187At a C/O value of 15.2 ng/mL, BALP’s sensitivity and specificity for diagnosing PCa BM are 75% and 93% respectively.
Rasch et al. [27]Serum111The sensitivity and specificity of the diagnosis of PCa BM at a mean BALP value of 29.28 ng/mL were 83.8% and 78%, respectively.
Piedra et al. [28]Serum67In PCa patients, with 18.4 ng/mL as the C/O value, BALP levels exhibited a specificity of 92% and a sensitivity of 92% in BM diagnosis.
Fizazi et al. [29]Serum1901Lower BALP level (<146 U/L) is a highly important predictor of greater OS in CRPC BM patients.
OCArai et al. [30]Serum63OC levels were significantly higher in patients with BM than in those without, and OC responded to endocrine therapy in BM patients.
Jung et al. [26]Serum187OC is rather ineffective as a diagnostic or prognosis indicator of bone metastatic spread.
Maeda et al. [31]Serum70Other bone formation/resorption markers, except for OC, were considerably lower in PCa patients without BM than those with.
PINP/PICPKoopmans et al. [32]Serum64PINP has a specificity of 78% and sensitivity of 68% in BM defemination when the C/O value is set at 58 mcg/L. Elevation of PINP can occur earlier than BM.
Jung et al. [26]Serum187Logistic regression analysis shows the overall correct classification for PINP to predict BM was 84%.
Brasso et al. [33]Serum153Those with elevated serum levels of PINP had shorter survival.
OPNKhodavirdi et al. [34]Tissue20PCa OPN expression showed a gradient increase from early local infiltration to stage of distant metastasis in mice.
Thoms et al. [35]Serum245OPN is predictive of prognosis in mCRPC patients after chemotherapy. OPN has limited ability to differentiate metastatic PCa from localized PCa.
OPGJung et al. [36]Serum164At a C/O value given in the text, the diagnostic sensitivity and specificity of OPG in discriminating PCa patients experiencing BM are 88% and 93%, respectively.
Jung et al. [26]Serum187OPG, at 3.44 pmol/L, had a specificity of 94% and sensitivity of 93%, respectively.
Zhang et al. [37]Serum30Prevention of metastatic tibial PCa tumor formation was observed after OPG treatment.
Table 3. Studies on bone resorption markers.
Table 3. Studies on bone resorption markers.
MarkerReferenceSample LocationSample Size (N)Finding
BSPBellahcène et al. [77]Tissue454Among breast cancer patients, those with high BSP expression exhibit higher metastasis rates.
Wei et al. [79]Serum83The sensitivity and specificity of BSP for diagnosing PCa BM were 80.95% and 72.8%, higher than other markers mentioned in the text.
Wang et al. [80]Serum356At a C/O value of 33.26 ng/mL, the sensitivity and specificity for differentiating PCa BM are 78.21% and 79.28%.
Withold et al. [81]Serum/Urine132Serum BSP have lower diagnostic potency than all other discovered bone conversion indicators in patients with cancer BM.
Jung et al. [26]Serum187Both lymph node metastases and BM can cause an increase in BSP, thus reducing the diagnostic accuracy.
Jain et al. [82]Serum302Only in the final stage of the illness do serum BSP levels rise in PCa, raising doubts about BSP’s early diagnostic utility in this disease.
CTx/NTxRajpar et al. [83]Urine94In CRPC BM patients, lower urine NTx levels often had some connections with more favorable OS.
Coleman et al. [50]Urine1824In many cancers, including PCa, high levels of urinary NTx mean a higher incidence of SRE.
Jung et al. [61]Serum52PCa patients who had elevated NTx levels exhibited higer risk of bone lesion. The increases in NTx were observed 6 months before the occurrence of SREs
Jung et al. [26]Serum187With a C/O value of 26.9 nmol/L BCE, the sensitivity of NTx is 61%. The sensitivity of CTx is 30% with a C/O value of 0.627 μg/L.
Piedra et al. [28]Urine67NTx and CTx both had a 100% sensitivity in the detection of BM in PCa without and with BM
TRACPJung et al. [26]Serum187At a C/O value of 4.62 U/L, TRACP-5b’s accuracy in diagnosing PCa BM was 77% in sensitivity and 85% in specificity, respectively.
Yamamichi et al. [84]Serum282Combined application of TRACP 5b and PSA can accurately detect PCa BM (AUC = 0.95).
Ozu et al. [85]Serum215There is a strong interrelationship between serum TRACP-5b levels and the condition on bone scintigraphy
Salminen et al. [86]Serum84At a C/O value of 4.98 U/L, TRACP-5b levels had high diagnostic accuracy in diagnosing PCa BM (AUC = 0.82). TRACP-5b predicts OS.
I-CTPWei et al. [79]Serum83ICTP showed a sensitivity of 69.05% and specificity of 76.8% for the identification of PCa BM at a positive critical value of 4.3 U/L.
Kataoka et al. [87]Serum155ICTP’s sensitivity and specificity in diagnosing BCa BM are 78.6% and 88.0%, respectively, at a C/O value of 5.0 ng/mL.
Kamiya et al. [88]Serum222ICTP has a fairly high accuracy in predicting PCa BM (AUC = 0.85).
Jung et al. [61]Serum52Cox regression model shows that ICTP was an appropriate predictor of OS.
PYD/D-PYDLara et al. [89]Serum778Cox regression analysis reveals that OS was negatively correlated with higher PYD levels.
Table 4. Studies on ALP and neuroendocrine markers.
Table 4. Studies on ALP and neuroendocrine markers.
MarkerReferenceSample LocationSample Size (N)Finding
ALPOesterling et al. [100]Serum2064It is unnecessary for newly diagnosed PCa patients (without skeletal symptoms) with serum PSA levels equal to or below 10.0 mg/L to have a staging radionuclide bone scan.
Salminen et al. [86]Serum84PSA has a good degree of diagnostic precision for BM (AUC = 0.87).
Kataoka et al. [87]Serum155Sensitivity and specificity of PSA in identifying BM are, respectively, 100% and 79.8% at a threshold value of 40.0 ng/mL.
Ozu et al. [85]Serum215PSA, TRACP, and ALP were important independent predictors of BM. PSA expressing the highest OR through multivariate logistic regression analysis
CgA/NSESzarvas et al. [105]Serum395Patients diagnosed with mCRPC displayed 2–3 times higher levels of CgA and NSE compared to those with localized PCa.
Niedworok et al. [106]Serum237CgA levels were higher in advanced PCa patients than clinically localized cases (45 ng vs. 23 ng/mL, p < 0.001;41 vs. 22 ng/mL, p = 0.002)
Heck et al. [107]Serum45OS was considerably reduced when CgA or NSE levels exceeded the baseline values (85 ng/mL and 16 ng/mL, respectively).
Kamiya et al. [108]Serum163NSE blood levels were considerably higher in PCa BM patients than in patients without PCa BM (p < 0.05). Patients with higher NSE levels have poorer survival.
ProGRPYu et al. [113]Serum163Mean ProGRP level in PCa BM patients was 36.81 pg/mL, compared to 22 pg/mL in those without BM. ProGRP along with total PSA have high accuracy in diagnosing PCa BM (AUC = 0.941).
Table 5. Studies on liquid biopsy markers.
Table 5. Studies on liquid biopsy markers.
MarkerReferenceSample LocationSample Size (N)Finding
miRNAColden et al. [114]Tissue96Compared with normal tissues, miR-466 was significantly downregulated in PCa tissues (p < 0.0001), and patients with high miR-466 expression had lower recurrence rates and better prognostic outcomes.
Brase et al. [115]Serum/Tissue674Both miR-141 and miR-375 levels are elevated in serum or tissue samples of PCa BM patients.
Peng et al. [116]Serum/Tissue223Serum miR-218-5p levels were considerably lower in PCa BM than in PCa patients without BM (AUC = 0.86).
Nguyen et al. [117]Serum84Serum MiR-375, miR-378 and miR-141 are significantly elevated in mCRPC patients.
cfDNA/ctDNAJung et al. [118]Serum184CfDNA levels were much higher in patients with metastatic PCa and cfDNA has predictive value for OS.
Morrison et al. [119]Serum22Discovered a strong correlation between cfDNA and the CT bone scan results in metastatic CRPC patients.
Kohli et al. [120]Serum303mCRPC and mHSPC patients with large percentage of ctDNA were observed a poor prognosis.
ExsomesYaman et al. [121]Serum51Levels of miR-141, miR-21, miR-221 were significantly higher in metastatic PCa compared to localized PCa. MiR-141 was the most significant difference (p < 0.001; AUC = 75.5%).
Foj et al. [122]Urine162Urine exosomal miR-141, miR-21 and miR-375 levels of patients with high-risk PCa were significantly higher compared to patients with low-risk PCa or normal subjects.
Bhagirath et al. [123]Serum12MiR-1246 level differ between benign, aggressive, and normal types of PCa. miR-1246 level of aggressive PCa increased 31- and 23-fold in contrast to normal prostatic hyperplasia and BPH.
Wani et al. [124]Urine210Levels of miR-2909 can show changes in the aggressiveness of PCa.
Ruiz et al. [125]Semen97Semen-derived exosomes miR-221-3p, miR-222-3p have high accuracy in determining the prognosis of PCa (AUC = 0.857, p = 0.001).
Bijnsdorp et al. [126]Urine13Exosomal proteins ITGA3 and ITGB1 were found in higher amounts in the urine of individuals with metastatic Pca.
CTCDanila et al. [127]Serum120Individuals with BM had a CTC counts of 10.5 cells, against 2.5 cells in patients without BM, and baseline CTC was predictive of survival.
Chen et al. [128]Serum/Tissue80Ezrin was found to be more expressed in both CTCs and PCa cells with BM characteristics than in those without.
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Ying, M.; Mao, J.; Sheng, L.; Wu, H.; Bai, G.; Zhong, Z.; Pan, Z. Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction. J. Pers. Med. 2023, 13, 705. https://doi.org/10.3390/jpm13050705

AMA Style

Ying M, Mao J, Sheng L, Wu H, Bai G, Zhong Z, Pan Z. Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction. Journal of Personalized Medicine. 2023; 13(5):705. https://doi.org/10.3390/jpm13050705

Chicago/Turabian Style

Ying, Mingshuai, Jianshui Mao, Lingchao Sheng, Hongwei Wu, Guangchao Bai, Zhuolin Zhong, and Zhijun Pan. 2023. "Biomarkers for Prostate Cancer Bone Metastasis Detection and Prediction" Journal of Personalized Medicine 13, no. 5: 705. https://doi.org/10.3390/jpm13050705

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