model that mice with persistent *Grm1* expression in melanocytes, harbored significant tumor burden compared to those with suppressed transgene expression indicating that *Grm1* is not only necessary for the initiation of melanoma but also for their continued progression. This is also in agreement with results that show that *Grm1* is capable of transforming immortalized mouse melanocytes *in-vitro* and forming robust tumors *in-vivo* (Shin, Namkoong et al. 2008a). Further studies provide compelling evidence that *Grm1* expression can co-operate with other transformation mediators to support tumorigenicity. Akt2 has been shown to be not only a downstream target of Grm1 activation but is also involved in promoting the invasiveness exhibited by the *Grm1* transformed mouse melanocytes (Shin, Wall et al. 2010). In addition, progeny from an inducible *Grm1-*expressing transgenic mouse model crossed with a stem cell factor (*SCF*) transgenic line exhibited increased populations of melanocytes in the epidermis and shorter latency in melanoma development than in the

Involvement of human metabotropic glutamate receptor 1 (*GRM1*) in melanoma has also been demonstrated in melanoma biopsies and cell lines. Analyses of these samples showed that 80% of the cell lines and over 60% of the biopsy samples exhibited GRM1 expression at the level of both RNA and protein which was not detected in benign nevi (Pollock, Cohen-Solal et al. 2003; Funusaka, Harada et al. 2006; Namkoong, Shin et al. 2007). This would make GRM1 a potential therapeutic target in human melanoma. Previous reports indicated that glutamate receptor antagonists inhibit cell proliferation (Rzeski, Turski et al. 2001; Stepulak, Sifringer et al. 2005). The competitive GRM1 antagonist LY367385 or the noncompetitive GRM1 antagonist Bay 36-7620 were investigated and found to suppress the growth of the GRM1 positive melanoma cells but not of GRM1 negative control cells (Namkoong, Shin et al. 2007). *GRM1* expressing human melanoma cells and *Grm1* transformed mouse melanocytes were observed to release high amounts of glutamate extracellularly which through an autocrine loop is thought to enhance cell proliferation (Namkoong, Shin et al. 2007; Shin, Namkoong et al. 2008a). Riluzole, an FDA approved drug for the treatment of ALS is an inhibitor of glutamate release (Bensimon, Lacomblez et al. 1994; Bryson, Fulton et al. 1996; Lacomblez, Bensimon et al. 2002). We demonstrated that disruption of the autocrine loop by Riluzole through the suppression of the release of glutamate inhibits GRM1 positive melanoma cell proliferation *in-vitro,* tumorigenicity *invivo* and induces apoptosis (Namkoong, Shin et al. 2007). In addition, Riluzole was also shown to inhibit the migration and invasion of GRM1 positive melanoma cells (Le, Chan et al. 2010). A phase 0 clinical trial of Riluzole in stage III and IV patients with resectable melanoma showed a 34% response after only 2 weeks of treatment with significant tumor shrinkage in some patients accompanied by suppression of the MAPK and PI3K/AKT pathways (Yip, Le et al. 2009). A recently completed phase II trial showed modest antitumor activity with 42% of the patients exhibiting stable disease (Mehnert, Wen et al. 2010). These results suggest that Riluzole might display higher efficacy in combination with other

The future of melanoma treatment lies in the identification of drugable targets. Genetic analyses has generated copious amounts of information that illustrate the importance of "personalized medicine" matching each patient's unique genetic predisposition with the available and developing regimens. Novel finding such as the involvement of GRM1 in

*Grm1-*only transgenic mouse model (Abdel-Daim, Funasaka et al. 2010).

anti-melanoma therapies.

**7. Conclusion**

*CDKN2A* mutation carriers is also associated with the development of multiple primary melanomas (van der Velden, Sandkuijl et al. 2001; Goldstein, Landi et al. 2005).

#### **6.2 Metabotropic glutamate receptor 1 (GRM1/mGlu1/mGluR1)**

Excessive glutamate signaling has been shown to underlie many neurological diseases including epilepsy, spasticity, stroke, traumatic brain injury and Amyotrophic Lateral Sclerosis (ALS) (Lee, Zipfel et al. 1999; McNamara 1999). Aberrant glutamate signaling also plays roles in patho-physiological diseases such as chronic pain, depression and anxiety (Swanson, Bures et al. 2005). Recently, glutamate signaling has been shown to be involved in various neoplasms including gliomas, colon cancer, breast carcinomas and melanoma (Albasanz, Ros et al. 1997; Pollock, Cohen-Solal et al. 2003; Chang, Yoo et al. 2005). Metabotropic glutamate receptors transduce glutamate induced signaling through the activation of heterotrimeric G-proteins. These receptors are primarily localized in the central nervous system where they are involved in synaptic transmission and less prominently in somatic tissues where they regulate proliferation, migration and differentiation (Skerry and Genever 2001; Hinoi, Takarada et al. 2004; Hinoi, Takarada et al. 2004; Shin, Martino et al. 2008b). Of the 8 metabotropic glutamate receptors identified (Houamed, Kuijper et al. 1991; Masu, Tanabe et al. 1991; Conn and Pin 1997; Goudet, Magnaghi et al. 2009), metabotropic glutamate receptor 1 is the only one involved in melanoma development (Pollock, Cohen-Solal et al. 2003; Marin, Namkoong et al. 2005; Marin, Namkoong et al. 2006). This discovery was prompted by results of a transgenic mouse study utilizing a 2 KB fragment of genomic DNA (Clone B) (Chen, Tiecher et al. 1989; Colon-Teicher, Wise et al. 1993), that had been shown to commit fibroblasts to undergo adipocyte differentiation upon introduction. Of the 5 transgenic founders with the Clone B transgene and in which an expected obese phenotype was never observed, one of the founder mice (TG3) developed raised lesions on the eyes, snout, tail and peri-anal region at 8 months (Zhu, Reuhl et al. 1998). Subsequent progeny of TG3 developed similar lesions with 100% penetrance. These melanocytic lesions increased in size and number and were also invasive as illustrated by their detection in the lymph nodes, brain, muscles, lungs, choroid plexus and inner ears. These lesions were verified conclusively by histopathology as melanoma with a high degree of similarity to human melanoma. The transgene was found to be localized on a region of mouse chromosome 10 orthologous to human chromosomal band 6q23-24 (Pollock, Cohen-Solal et al. 2003). Seven to eight transgene insertions were integrated in intron 3 of the gene that encodes metabotropic glutamate receptor 1, *Grm1,* with concomitant deletion of 70 Kb of host intronic sequences. The expression of *Grm1* was confirmed in the tumors derived from the raised melanocytic lesions in the pinnae, tails and skin of TG3 mice relative to normal controls. This ectopic expression of *Grm1* in melanocytes was theorized to be the cause of the observed phenotype. Elucidation of the etiological role of aberrant *Grm1* expression in melanocytes was deduced from the targeted expression of *Grm1* in melanocytes under the regulation of melanocyte specific promoter dopachrome tautomerase (*Dct*) (Pollock, Cohen-Solal et al. 2003). Transgenic mice generated with the *Dct-Grm1* transgene, TG (*Grm1*) EPv, developed pigmented lesions on the pinnae and tail at 5-7 months which were histologically similar to those from TG3 mice and were transmitted with 100% penetrance to their offspring. This was conclusive evidence that the ectopic expression of *Grm1* in mouse melanocytes was sufficient to induce spontaneous melanoma *in-vivo*. Recently, another group generated a *Grm1* inducible model of melanoma that exhibits a similar phenotype upon expression of *Grm1* in adult mice (Ohtani, Harada et al. 2008). They showed in their

*CDKN2A* mutation carriers is also associated with the development of multiple primary

Excessive glutamate signaling has been shown to underlie many neurological diseases including epilepsy, spasticity, stroke, traumatic brain injury and Amyotrophic Lateral Sclerosis (ALS) (Lee, Zipfel et al. 1999; McNamara 1999). Aberrant glutamate signaling also plays roles in patho-physiological diseases such as chronic pain, depression and anxiety (Swanson, Bures et al. 2005). Recently, glutamate signaling has been shown to be involved in various neoplasms including gliomas, colon cancer, breast carcinomas and melanoma (Albasanz, Ros et al. 1997; Pollock, Cohen-Solal et al. 2003; Chang, Yoo et al. 2005). Metabotropic glutamate receptors transduce glutamate induced signaling through the activation of heterotrimeric G-proteins. These receptors are primarily localized in the central nervous system where they are involved in synaptic transmission and less prominently in somatic tissues where they regulate proliferation, migration and differentiation (Skerry and Genever 2001; Hinoi, Takarada et al. 2004; Hinoi, Takarada et al. 2004; Shin, Martino et al. 2008b). Of the 8 metabotropic glutamate receptors identified (Houamed, Kuijper et al. 1991; Masu, Tanabe et al. 1991; Conn and Pin 1997; Goudet, Magnaghi et al. 2009), metabotropic glutamate receptor 1 is the only one involved in melanoma development (Pollock, Cohen-Solal et al. 2003; Marin, Namkoong et al. 2005; Marin, Namkoong et al. 2006). This discovery was prompted by results of a transgenic mouse study utilizing a 2 KB fragment of genomic DNA (Clone B) (Chen, Tiecher et al. 1989; Colon-Teicher, Wise et al. 1993), that had been shown to commit fibroblasts to undergo adipocyte differentiation upon introduction. Of the 5 transgenic founders with the Clone B transgene and in which an expected obese phenotype was never observed, one of the founder mice (TG3) developed raised lesions on the eyes, snout, tail and peri-anal region at 8 months (Zhu, Reuhl et al. 1998). Subsequent progeny of TG3 developed similar lesions with 100% penetrance. These melanocytic lesions increased in size and number and were also invasive as illustrated by their detection in the lymph nodes, brain, muscles, lungs, choroid plexus and inner ears. These lesions were verified conclusively by histopathology as melanoma with a high degree of similarity to human melanoma. The transgene was found to be localized on a region of mouse chromosome 10 orthologous to human chromosomal band 6q23-24 (Pollock, Cohen-Solal et al. 2003). Seven to eight transgene insertions were integrated in intron 3 of the gene that encodes metabotropic glutamate receptor 1, *Grm1,* with concomitant deletion of 70 Kb of host intronic sequences. The expression of *Grm1* was confirmed in the tumors derived from the raised melanocytic lesions in the pinnae, tails and skin of TG3 mice relative to normal controls. This ectopic expression of *Grm1* in melanocytes was theorized to be the cause of the observed phenotype. Elucidation of the etiological role of aberrant *Grm1* expression in melanocytes was deduced from the targeted expression of *Grm1* in melanocytes under the regulation of melanocyte specific promoter dopachrome tautomerase (*Dct*) (Pollock, Cohen-Solal et al. 2003). Transgenic mice generated with the *Dct-Grm1* transgene, TG (*Grm1*) EPv, developed pigmented lesions on the pinnae and tail at 5-7 months which were histologically similar to those from TG3 mice and were transmitted with 100% penetrance to their offspring. This was conclusive evidence that the ectopic expression of *Grm1* in mouse melanocytes was sufficient to induce spontaneous melanoma *in-vivo*. Recently, another group generated a *Grm1* inducible model of melanoma that exhibits a similar phenotype upon expression of *Grm1* in adult mice (Ohtani, Harada et al. 2008). They showed in their

melanomas (van der Velden, Sandkuijl et al. 2001; Goldstein, Landi et al. 2005).

**6.2 Metabotropic glutamate receptor 1 (GRM1/mGlu1/mGluR1)**

model that mice with persistent *Grm1* expression in melanocytes, harbored significant tumor burden compared to those with suppressed transgene expression indicating that *Grm1* is not only necessary for the initiation of melanoma but also for their continued progression. This is also in agreement with results that show that *Grm1* is capable of transforming immortalized mouse melanocytes *in-vitro* and forming robust tumors *in-vivo* (Shin, Namkoong et al. 2008a). Further studies provide compelling evidence that *Grm1* expression can co-operate with other transformation mediators to support tumorigenicity. Akt2 has been shown to be not only a downstream target of Grm1 activation but is also involved in promoting the invasiveness exhibited by the *Grm1* transformed mouse melanocytes (Shin, Wall et al. 2010). In addition, progeny from an inducible *Grm1-*expressing transgenic mouse model crossed with a stem cell factor (*SCF*) transgenic line exhibited increased populations of melanocytes in the epidermis and shorter latency in melanoma development than in the *Grm1-*only transgenic mouse model (Abdel-Daim, Funasaka et al. 2010).

Involvement of human metabotropic glutamate receptor 1 (*GRM1*) in melanoma has also been demonstrated in melanoma biopsies and cell lines. Analyses of these samples showed that 80% of the cell lines and over 60% of the biopsy samples exhibited GRM1 expression at the level of both RNA and protein which was not detected in benign nevi (Pollock, Cohen-Solal et al. 2003; Funusaka, Harada et al. 2006; Namkoong, Shin et al. 2007). This would make GRM1 a potential therapeutic target in human melanoma. Previous reports indicated that glutamate receptor antagonists inhibit cell proliferation (Rzeski, Turski et al. 2001; Stepulak, Sifringer et al. 2005). The competitive GRM1 antagonist LY367385 or the noncompetitive GRM1 antagonist Bay 36-7620 were investigated and found to suppress the growth of the GRM1 positive melanoma cells but not of GRM1 negative control cells (Namkoong, Shin et al. 2007). *GRM1* expressing human melanoma cells and *Grm1* transformed mouse melanocytes were observed to release high amounts of glutamate extracellularly which through an autocrine loop is thought to enhance cell proliferation (Namkoong, Shin et al. 2007; Shin, Namkoong et al. 2008a). Riluzole, an FDA approved drug for the treatment of ALS is an inhibitor of glutamate release (Bensimon, Lacomblez et al. 1994; Bryson, Fulton et al. 1996; Lacomblez, Bensimon et al. 2002). We demonstrated that disruption of the autocrine loop by Riluzole through the suppression of the release of glutamate inhibits GRM1 positive melanoma cell proliferation *in-vitro,* tumorigenicity *invivo* and induces apoptosis (Namkoong, Shin et al. 2007). In addition, Riluzole was also shown to inhibit the migration and invasion of GRM1 positive melanoma cells (Le, Chan et al. 2010). A phase 0 clinical trial of Riluzole in stage III and IV patients with resectable melanoma showed a 34% response after only 2 weeks of treatment with significant tumor shrinkage in some patients accompanied by suppression of the MAPK and PI3K/AKT pathways (Yip, Le et al. 2009). A recently completed phase II trial showed modest antitumor activity with 42% of the patients exhibiting stable disease (Mehnert, Wen et al. 2010). These results suggest that Riluzole might display higher efficacy in combination with other anti-melanoma therapies.

#### **7. Conclusion**

The future of melanoma treatment lies in the identification of drugable targets. Genetic analyses has generated copious amounts of information that illustrate the importance of "personalized medicine" matching each patient's unique genetic predisposition with the available and developing regimens. Novel finding such as the involvement of GRM1 in

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**18**

*Japan*

**Biomarkers for Melanoma Diagnosis and**

**the Technologies Used to Identify Them**

Melanoma is a malignant tumor originating from melanocytes (pigment-producing cells).  Melanoma can be classified as belonging to one of four subtypes: superficial spreading, nodular, lentigo maligna, and acral lentiginous melanoma. These subtypes are characterized based on prognosis, incidence of metastasis and the frequency of gene mutations (e.g., *BRAF* and *NRAS*) (Saldanha et al., 2006; Jaeger et al., 2007; Markovic et al., 2007; Jönsson et al., 2010). Superficial spreading melanoma is the most common form of melanoma found in Caucasian populations, while the acral lentiginous melanoma is frequently detected in Asian and African populations (Cress and

Several important risk factors that have been linked to the development of melanoma have been identified. Of these risk factors, most can be considered to be either environmental factors, such as exposure to ultraviolet (UV) radiation, especially in childhood, or other host factors such as family history and melanocytic nevi (Markovic et al., 2007; Schulman and Fisher, 2009), but other cancer risk factors such as smoking (Osterlind et al., 1988), diet (Osterlind et al., 1988; Veierod et al., 1997) or hormone therapy (Naldi et al., 2005) have not been found to be associated with an increased risk of melanoma. The risk of developing melanoma is higher in Caucasian than in Asian or African populations. This is closely related to skin pigmentation as melanin has been shown to have a protective function for UV-induced melanoma and Caucasian populations show low levels of melanogenesis (Lens and Dawes, 2004; Hu et al., 2008; Jemal et al., 2010). In general, the melanocortin-1 receptor (MC1R), which is a G-protein-coupled receptor (GPCR), stimulates melanogenesis through the activation of adenylate cyclase and protein kinase A (PKA) (Jordan and Jackson, 1998; Rouzaud et al., 2003). Its genetic variants are associated with melanoma

**1. Introduction**

Holly, 1997; Weyers et al., 1999).

Takeshi Mori1 and Jeong-Hun Kang2

*2Department of Biomedical Engineering,*

*5-7-1 Fujishiro-dai, Suita, Osaka 565-8565,*

*1Department of Applied Chemistry, Faculty of Engineering, Kyushu University, 744 Motooka, Nishi-Ku, Fukuoka 819-0395,*

*National Cerebral and Cardiovascular Center Research Institute,*

## **Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them**

Takeshi Mori1 and Jeong-Hun Kang2

*1Department of Applied Chemistry, Faculty of Engineering, Kyushu University, 744 Motooka, Nishi-Ku, Fukuoka 819-0395, 2Department of Biomedical Engineering, National Cerebral and Cardiovascular Center Research Institute, 5-7-1 Fujishiro-dai, Suita, Osaka 565-8565, Japan*

#### **1. Introduction**

Melanoma is a malignant tumor originating from melanocytes (pigment-producing cells).  Melanoma can be classified as belonging to one of four subtypes: superficial spreading, nodular, lentigo maligna, and acral lentiginous melanoma. These subtypes are characterized based on prognosis, incidence of metastasis and the frequency of gene mutations (e.g., *BRAF* and *NRAS*) (Saldanha et al., 2006; Jaeger et al., 2007; Markovic et al., 2007; Jönsson et al., 2010). Superficial spreading melanoma is the most common form of melanoma found in Caucasian populations, while the acral lentiginous melanoma is frequently detected in Asian and African populations (Cress and Holly, 1997; Weyers et al., 1999).

Several important risk factors that have been linked to the development of melanoma have been identified. Of these risk factors, most can be considered to be either environmental factors, such as exposure to ultraviolet (UV) radiation, especially in childhood, or other host factors such as family history and melanocytic nevi (Markovic et al., 2007; Schulman and Fisher, 2009), but other cancer risk factors such as smoking (Osterlind et al., 1988), diet (Osterlind et al., 1988; Veierod et al., 1997) or hormone therapy (Naldi et al., 2005) have not been found to be associated with an increased risk of melanoma. The risk of developing melanoma is higher in Caucasian than in Asian or African populations. This is closely related to skin pigmentation as melanin has been shown to have a protective function for UV-induced melanoma and Caucasian populations show low levels of melanogenesis (Lens and Dawes, 2004; Hu et al., 2008; Jemal et al., 2010). In general, the melanocortin-1 receptor (MC1R), which is a G-protein-coupled receptor (GPCR), stimulates melanogenesis through the activation of adenylate cyclase and protein kinase A (PKA) (Jordan and Jackson, 1998; Rouzaud et al., 2003). Its genetic variants are associated with melanoma

Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them 391

Phosphorylation of RAF kinase by RAS activates downstream targets the MAPK extracellular signal-regulated kinase-1 and -2 (MEK1 and MEK2), which causes the phosphorylation of extracellular signal-regulated kinase-1 and -2 (ERK1 and ERK2). Activated ERK1 and 2 has been found to modulate the gene expression necessary for survival and proliferation of melanoma cells, and has been linked to the increase resistance of melanoma cells to apoptosis by inhibiting the activation of caspase 8 (Becker et al., 2006; Sekulic et al., 2008). The *BRAF* mutation is necessary for ERK-mediated survival and proliferation and participates in the reduction of proapoptotic proteins (e.g., Bcl-2 family), while *RAF* genes consist of *ARAF*, *BRAF*, and *CRAF* (also known as *Raf-1*) (Becker et al., 2006; Cartlidge et al., 2008; Sekulic et al., 2008). The *BRAF* mutation, predominantly V600E (substitution of glutamate to valine; previously known to V599E), frequently occurs in melanoma and is strongly related to exposure to UV radiation (Tsao et al., 2004; Wan et al.,

2004; Gray-Schopfer et al., 2005; Becker et al., 2006; Sekulic et al., 2008).

Fig. 1. Intracellular signal transduction of melanoma. RAS/RAF/MEK/ERK,

an increase in the expression of survival or proliferation-associated signals and

apoptosis-associated signals

PI3K/AKT/mTOR, PLC/DAG/PKC, and Wnt/β-catenin pathways are associated with survival, proliferation angiogenesis, and apoptosis of melanoma cells. Melanoma cells show

angiogenesis-associated signals, but a decrease in the expression of tumor suppressor or

incidence and sun sensitivity (Box et al., 2001; Markovic et al., 2007). Moreover, the risk of developing melanoma is greater in males than in females over the age of 40, although the opposite effect is observed in patients under 40 years old (Lens and Dawes, 2004; Jemal et al., 2010).

The global incidence of melanoma has increased over the past decades (Markovic et al., 2007; Jemal et al., 2010, Rigel et al., 2010). The 5-year survival rate for melanoma is higher than for other prominent cancers such as tumors of the prostate, ovary, liver and bile duct, lung and bronchus, colon and rectum, and stomach. Yet, the early diagnosis and treatment of melanoma is crucial to increasing the survival rate (Jemal et al., 2010, Rigel et al., 2010).

An important early diagnostic methodology for melanoma is the ABCDE criteria, which is defined by describing changes to the appearance of the suspected lesion based on the following features: Asymmetry, Border (irregularity), Color (variegation), Diameter and Evolution (over time). Other diagnostic strategies also typically utilized include histological and/or molecular analysis (e.g., genes or proteins profiling) of biopsied material, dermoscopy (also known as dermatoscopy or epiluminescent microscopy) using a lightbased magnification or digital (computer)-assisted device, ultrasound imaging and magnetic resonance imaging (Abbasi et al., 2004; Rigel et al., 2005; Markovic et al., 2007; Psaty and Halpern, 2009; Rigel et al., 2010).

Recently there has also been a move toward establishing biomarkers for malignant melanoma. These types of biological markers are not only beneficial for the diagnosis of melanoma, but also allow physicians to monitor the recurrence of melanoma after surgical resection, or to monitor the effect of radiation or anticancer drug therapies. To identify putative melanoma biomarkers in tissue samples or body fluids, a number of methodologies can be utilized, including two-dimensional gel electrophoresis (2-DE) and high throughput microarray technology.

### **2. Melanoma biomarkers**

#### **2.1 Cellular signals and tissue biomarkers (immunohistochemical biomarkers)**

Signal transduction pathways are the mechanism through which cells respond to the extracellular signals (ligands) required to regulate or modulate downstream gene expression. These extracellular signals activate signal transduction pathways by either penetrating the cellular membrane or binding to specific receptors. The activated receptors are then able to change the quantity or intracellular distribution of the second messengers through the use of effector molecules. Second messengers also activate protein targets, which control downstream gene expression. In these cellular signal transduction pathways, phosphorylation of the target proteins (by protein kinases), or dephosphorylation or proteolytic cleavage (by proteases) play a key role in cell division and motility, apoptosis and carcinogenesis.

In melanoma cells, major signal transduction pathways are RAS/RAF/MEK/ERK and the PI3K/AKT (as known as protein kinase B)/mTOR pathway; however, other pathways such as PLC/DAG/PKC or Wnt/β-catenin pathway have also been identified (Figure 1). The interaction of a number of different ligands [e.g., fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF), or epidermal growth factor (EGF)] with their respective receptors [e.g., growth factor receptors (GFRs) (tyrosine kinase receptors)] leads to the stimulation of the RAS target protein, which has three members (HRAS, KRAS, and NRAS).

incidence and sun sensitivity (Box et al., 2001; Markovic et al., 2007). Moreover, the risk of developing melanoma is greater in males than in females over the age of 40, although the opposite effect is observed in patients under 40 years old (Lens and Dawes, 2004; Jemal et

The global incidence of melanoma has increased over the past decades (Markovic et al., 2007; Jemal et al., 2010, Rigel et al., 2010). The 5-year survival rate for melanoma is higher than for other prominent cancers such as tumors of the prostate, ovary, liver and bile duct, lung and bronchus, colon and rectum, and stomach. Yet, the early diagnosis and treatment of melanoma is crucial to increasing the survival rate (Jemal et al., 2010, Rigel et al., 2010). An important early diagnostic methodology for melanoma is the ABCDE criteria, which is defined by describing changes to the appearance of the suspected lesion based on the following features: Asymmetry, Border (irregularity), Color (variegation), Diameter and Evolution (over time). Other diagnostic strategies also typically utilized include histological and/or molecular analysis (e.g., genes or proteins profiling) of biopsied material, dermoscopy (also known as dermatoscopy or epiluminescent microscopy) using a lightbased magnification or digital (computer)-assisted device, ultrasound imaging and magnetic resonance imaging (Abbasi et al., 2004; Rigel et al., 2005; Markovic et al., 2007; Psaty and

Recently there has also been a move toward establishing biomarkers for malignant melanoma. These types of biological markers are not only beneficial for the diagnosis of melanoma, but also allow physicians to monitor the recurrence of melanoma after surgical resection, or to monitor the effect of radiation or anticancer drug therapies. To identify putative melanoma biomarkers in tissue samples or body fluids, a number of methodologies can be utilized, including two-dimensional gel electrophoresis (2-DE) and high throughput

**2.1 Cellular signals and tissue biomarkers (immunohistochemical biomarkers)**

Signal transduction pathways are the mechanism through which cells respond to the extracellular signals (ligands) required to regulate or modulate downstream gene expression. These extracellular signals activate signal transduction pathways by either penetrating the cellular membrane or binding to specific receptors. The activated receptors are then able to change the quantity or intracellular distribution of the second messengers through the use of effector molecules. Second messengers also activate protein targets, which control downstream gene expression. In these cellular signal transduction pathways, phosphorylation of the target proteins (by protein kinases), or dephosphorylation or proteolytic cleavage (by proteases) play a key role in cell division and motility, apoptosis

In melanoma cells, major signal transduction pathways are RAS/RAF/MEK/ERK and the PI3K/AKT (as known as protein kinase B)/mTOR pathway; however, other pathways such as PLC/DAG/PKC or Wnt/β-catenin pathway have also been identified (Figure 1). The interaction of a number of different ligands [e.g., fibroblast growth factor (FGF), vascular endothelial growth factor (VEGF), or epidermal growth factor (EGF)] with their respective receptors [e.g., growth factor receptors (GFRs) (tyrosine kinase receptors)] leads to the stimulation of the RAS target protein, which has three members (HRAS, KRAS, and NRAS).

al., 2010).

Halpern, 2009; Rigel et al., 2010).

microarray technology.

and carcinogenesis.

**2. Melanoma biomarkers**

Phosphorylation of RAF kinase by RAS activates downstream targets the MAPK extracellular signal-regulated kinase-1 and -2 (MEK1 and MEK2), which causes the phosphorylation of extracellular signal-regulated kinase-1 and -2 (ERK1 and ERK2). Activated ERK1 and 2 has been found to modulate the gene expression necessary for survival and proliferation of melanoma cells, and has been linked to the increase resistance of melanoma cells to apoptosis by inhibiting the activation of caspase 8 (Becker et al., 2006; Sekulic et al., 2008). The *BRAF* mutation is necessary for ERK-mediated survival and proliferation and participates in the reduction of proapoptotic proteins (e.g., Bcl-2 family), while *RAF* genes consist of *ARAF*, *BRAF*, and *CRAF* (also known as *Raf-1*) (Becker et al., 2006; Cartlidge et al., 2008; Sekulic et al., 2008). The *BRAF* mutation, predominantly V600E (substitution of glutamate to valine; previously known to V599E), frequently occurs in melanoma and is strongly related to exposure to UV radiation (Tsao et al., 2004; Wan et al., 2004; Gray-Schopfer et al., 2005; Becker et al., 2006; Sekulic et al., 2008).

Fig. 1. Intracellular signal transduction of melanoma. RAS/RAF/MEK/ERK, PI3K/AKT/mTOR, PLC/DAG/PKC, and Wnt/β-catenin pathways are associated with survival, proliferation angiogenesis, and apoptosis of melanoma cells. Melanoma cells show an increase in the expression of survival or proliferation-associated signals and angiogenesis-associated signals, but a decrease in the expression of tumor suppressor or apoptosis-associated signals

1) These receptors also stimulate melanoma angiogenesis. 2) The β-catenin functions as a cell adhesionassociated molecule. 3) Other studies suggested a decrease in the expression of antiapoptotic Bcl-2 in metastatic melanoma (Fecker et al., 2006; Zhuang et al., 2007). 4) The angiogenesis-associated molecules take part in melanoma metastasis. 5) The chemokine receptors also play an important role in melanoma growth.

 7) The antigens are found

Table 1. (continues) Tissue biomarkers (immunohistochemical biomarkers) for the diagnosis

Rad et al., 2004

Molina-Ortiz et al., 2009

Integrin

mainly in metastatic melanoma.

Antigens 7)

of melanoma and changes in their expression levels

Melanocyte lineage/differentiation antigens

6) The E-cadherin also functions as a tumor suppressor-associated molecule. 7) The antigens are found mainly in metastatic melanoma.

Table 1. (continues) Tissue biomarkers (immunohistochemical biomarkers) for the diagnosis of melanoma and changes in their expression levels

392 Breakthroughs in Melanoma Research

**Biomarkers Changes of expression References** Survival or proliferation-associated molecules GFRs (e.g., EGFR, VEGFR, FGFR, and PIGFR) 1) Increased Lacal et al., 2000; Ribatti et al., 2003; Odorisio et al., 2006; Diaz et al., 2007 GPCRs (e.g., Wnt/fizzled receptor and chemokine receptors) 1) Increased Lee et al., 2008 c-kit, one of GPCRs Increased, but decreased in metastatic melanoma Janku et al., 2005 Activated PI3K Increased Becker et al., 2006; Sekulic et al., 2008 Activated AKT Increased Stahl et al., 2004 Activated ERK1/2 Increased Cohen et al., 2002 Activated protein kinase C (PKC)

α β-catenin 2) Increased Sanders et al., 1999; Widlund et al., 2002

Cytokines (e.g., IL-1, IL-6, IL-8, and IL-10) Increased Ciotti et al., 1995

Heat shock proteins (HSPs) (e.g., HSP 27 or 90) Increased McCarthy et al., 2008; Coupland et al., 2010

in metastatic melanoma

Antiapoptotic Bcl-2 family (Bcl-2, Bcl-XL, and Mcl-1) Increased 3) Leiter et al., 2000; Boisvert-Adamo et al., 2009

Decreased Fecker et al., 2006; Tchernev and Orfanos, 2007

Decreased Eisenmann et al., 2003; Karst et al., 2005;

Ley et al., 2005; Qin et al., 2005; Zhang et al., 2006

Garraway et al., 2005;

Fecker et al., 2006; Hoek et al., 2008

Microphthalmia transcription factor (MITF) Increased, but decreased

the diagnosis of melanoma and changes in their expression levels

Apoptosis-associated molecules

Proapoptotic Bcl-2 family (multidomain proteins;

Bax and Bak)

1) These receptors also stimulate melanoma angiogenesis. 2) The β-catenin functions as a cell adhesionassociated molecule. 3) Other studies suggested a decrease in the expression of antiapoptotic Bcl-2 in metastatic melanoma (Fecker et al., 2006; Zhuang et al., 2007). 4) The angiogenesis-associated molecules take part in melanoma metastasis. 5) The chemokine receptors also play an important role in melanoma growth. Table 1. (continues on next page) Tissue biomarkers (immunohistochemical biomarkers) for

Proapoptotic Bcl-2 family

(BH3-only proteins; Bad, Bid, Bim, PUMA, and NOXA)

Tumor suppressor-associated molecules

TRAIL-R1 (DR4) and TRAIL-R2 (DR5) Decreased Zhang et al., 1999; Zhuang et al., 2006

Activated NF-κB Increased Ueda and Richmond, 2006

p4ARF Decreased Krimpenfort et al., 2001; Rizos et al., 2001

p16INK4A Decreased Krimpenfort et al., 2001

PTEN Decreased Stahl et al., 2003; Wu et al., 2003

Inhibitor of growth family member 3 (ING3) Decreased Wang et al., 2007

Matrix metalloproteinases (MMPs) Increased Hofmann et al., 2000

Urokinase plasminogen activator receptor (uPAR) Increased de Vries et al., 1994; Ferrier et al., 2000

Chemokine receptors (CXCR4, CCR7, and CCR10) 5) Increased Payne and Cornelius, 2002;

Cytoskeleton/structure proteins (e.g., vimentin) Increased Coupland et al., 2010; Li et al., 2010

Scala et al., 2005; Richmond et al., 2009

Increased Scala et al., 2005; Varney et al., 2006;

Richmond et al., 2009

Angiogenesis-associated molecules 4)

Chemokine receptors (CXCR1 and CXCR2);

one family of GPCRs

Metastasis-associated proteins

Cell adhesion-associated molecules

Increased Lahn and Sundell, 2004; Kang et al., 2008

Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them 395

In the absence of vascularization, the growth of melanoma is limited to 0.2 – 0.3 cm due to the limited diffusion of oxygen and nutrients into the tumor. For additional growth, angiogenesis is essential for providing adequate blood supply to the growing lesion. Angiogenesis is regulated by proangiogenic factors, such as VEGF, FGF, tumor necrosis factor (TNF), and interleukin-8 (IL-8) and by antiangiogenic factors, such as interferons (IFNs) and angiostatin. An increase in vascular density provides a greater supply of oxygen and nutrients to cells, leading to melanoma growth (Folkman, 2007; Mahabeleshwar and Byzova, 2007). High levels of proangiogenic factors in the serum of melanoma patients can

Multiple cytokines (e.g., IL-1, 4, 6, 8, 10 and 14), which are correlated with melanoma growth, angiogenesis and metastasis, have been observed in the serum of melanoma patient at both the protein and/or mRNA level. Serum levels of these cytokines are increased in metastatic melanoma patients, suggesting that they can be used as an indicator of melanoma progression (Porter et al., 2001; Varney et al., 2006; Yurkovetsky et al., 2007). Moreover, the serum concentration of the soluble IL-2 receptor is elevated in patients with metastatic melanoma and elevated serum IL-2 receptor levels are associated with lowered survival rates (Boyano et al., 1997; Ottaiano et al., 2006). Interestingly, IFNs are soluble cytokines, but possess antiangiogenic and antitumor activities. An increase in the melanoma progressionassociated cytokines leads to a reduction in IFNs levels, but there is a decrease in the serum levels of melanoma progression-associated cytokines in melanoma patients following immunomodulatory therapy with IFNs (mainly IFN-α2b)(Singh and Varner, 1998; Jonasch and Haluska, 2001; Yurkovetsky et al., 2007; Dummer and Mangana, 2009; Hofmann et al., 2011). Thus, the analysis of a number of different serum cytokines may be a useful means of

Urinary biomarkers for melanoma diagnosis have received much greater interest because of the relative ease of sample collection and handling compared with the analysis of blood or tissue samples, but this form of sample may lack the sensitivity required for a diagnostic biomarker. Of the urinary biomarkers of melanoma already identified (Table 3), 5SCD and 6-hydroxy-5-methoxyindole-2-carboxylic acid (6H5MI2C), are intermediate metabolites in melanin pigment formation, and have been the most extensively studied. An increase in urine levels of these markers has been associated with tumor progression and low survival rates (Kärnell et al., 1997; Bánfalvi et al., 2000; Wakamatsu et al., 2002). In healthy patients, the urinary levels of these markers are influenced by age (Meyerhöffer et al., 1998), sex (Morishima and Hanawa, 1981; Kågedal et al., 1992), skin color (Wirestrand et al., 1985) and season (Ito et al., 1987), but not by pregnancy (Carstam et al., 1985). Although both 5SCD and 6H5MI2C have been detected in the urine of melanoma patients, because of the higher levels of 5SCD, this marker is considered a more reliable urinary biomarker for melanoma than the 6H5MI2C (Kärnell et al., 1997, 2000; Wakamatsu et al., 2006). Moreover, the 90-kDa glycoprotein (TA-90)(Rote et al., 1980; Euhus et al., 1989), S100A7 (Brouard et al., 2002) and β-human chorionic gonadotropin (Carter et al., 1995) have also been identified in the urine

Of these urinary biomarkers, 5SCD, 6H5MI2C, and S100A7 can be considered the most melanoma-specific of the urinary biomarkers (Kärnell et al., 1997; Bánfalvi et al., 2000;

be used as an indicator of melanoma at diagnosis.

monitoring the efficacy of immunomodulatory therapy.

**2.3 Urinary biomarkers for melanoma diagnosis**

of patients with melanoma (Table 3).

Brouard et al., 2002; Wakamatsu et al., 2002).

Moreover, phosphorylation of AKT kinase by phosphatidyl inositol 3-kinase (PI3K) stimulates the mammalian target of rapamycin (mTOR), which leads to the survival and proliferation of melanoma cells. The AKT/mTOR pathway suppresses apoptosis by decreasing the levels of pro-apoptotic proteins (e.g., BAD and caspase-9). Among the three AKT members (AKT1, AKT2, and AKT3), it is AKT3 that is often overexpressed in melanoma (Stahl et al., 2004) and is regulated by the phosphatase and tensin homolog (PTEN), which degrades the products of PI3K (Wu et al., 2003; Becker et al., 2006; Sekulic et al., 2008).

In addition, many antigens, which have immunostimulatory or activator roles in tumorigenesis, have been identified in metastatic melanoma.  Melanocyte lineage/differentiation antigens are associated with the production of melanin pigments and have been identified in both normal melanocytes and melanoma (Thomson et al., 1985; Houghton et al., 1988). Cancer/testis antigens are abundant in normal tissues during development, but in mature cells, their expression is restricted to the male germ cells in the testis and to various tumors (Simpson et al., 2005).

As indicated, several gene mutations such as *NRAS* (Q61K/R), *BRAF* (V600E), *PTEN*, and *CDKN2A* mutation play an important role in the occurrence of melanoma (Tsao et al., 2004; Wan et al., 2004; Gray-Schopfer et al., 2005; Becker et al., 2006; Sekulic et al., 2008). These mutations are excellent targets for the diagnosis of melanoma. Moreover, in the context of melanoma prognosis, melanoma cells show an increase in the expression of survival or proliferation-associated molecules, angiogenesis-associated molecules, and in the expression of antigens, but a decrease in the expression of tumor suppressor-associated proteins (e.g., PTEN) or proapoptotic proteins (e.g., Bax and Bak) is observed (Table 1). Thus, these molecules, which show altered expression levels in melanoma relative to normal cells, are useful tissue biomarkers (immunohistochemical biomarkers) for melanoma diagnosis. However, in spite of these discoveries, these markers are not specific to melanoma and there are few melanoma-specific tissue biomarkers, excluding melanocyte lineage/differentiation antigens and melanoma-associated antigens (e.g., TRP1/gp75 and 2, Melan-A/MART-1, and TA-90) that are overexpressed in metastatic melanoma.

#### **2.2 Serologic biomarkers for melanoma diagnosis**

Many researchers have identified putative serologic biomarkers for melanoma diagnosis (Table 2), which play a key role in the growth and survival of melanoma cells. Typically, these markers activate survival and/or proliferation-associated and angiogenesis-associated signal transduction pathways after binding with their receptors. The most important receptors of this kind are GFRs (e.g., VEGFR and FGFR) and GPCRs (e.g., MC1R, Wnt/frizzled receptor, and chemokine receptor) (Halaban, 1996; Lee et al., 2008).

The primary antigens that have been observed in the serum of melanoma patients are melanocyte lineage/differentiation antigens and melanoma-associated antigens. The existence of these antigens in serum is closely associated with melanoma progression and low survival rates. Thus, these types of markers are useful as prognostic biomarkers and have potential to act as therapeutic targets.

Moreover, phosphorylation of AKT kinase by phosphatidyl inositol 3-kinase (PI3K) stimulates the mammalian target of rapamycin (mTOR), which leads to the survival and proliferation of melanoma cells. The AKT/mTOR pathway suppresses apoptosis by decreasing the levels of pro-apoptotic proteins (e.g., BAD and caspase-9). Among the three AKT members (AKT1, AKT2, and AKT3), it is AKT3 that is often overexpressed in melanoma (Stahl et al., 2004) and is regulated by the phosphatase and tensin homolog (PTEN), which degrades the products of PI3K (Wu et al., 2003; Becker et al., 2006; Sekulic et

In addition, many antigens, which have immunostimulatory or activator roles in tumorigenesis, have been identified in metastatic melanoma.  Melanocyte lineage/differentiation antigens are associated with the production of melanin pigments and have been identified in both normal melanocytes and melanoma (Thomson et al., 1985; Houghton et al., 1988). Cancer/testis antigens are abundant in normal tissues during development, but in mature cells, their expression is restricted to the male germ cells in the

As indicated, several gene mutations such as *NRAS* (Q61K/R), *BRAF* (V600E), *PTEN*, and *CDKN2A* mutation play an important role in the occurrence of melanoma (Tsao et al., 2004; Wan et al., 2004; Gray-Schopfer et al., 2005; Becker et al., 2006; Sekulic et al., 2008). These mutations are excellent targets for the diagnosis of melanoma. Moreover, in the context of melanoma prognosis, melanoma cells show an increase in the expression of survival or proliferation-associated molecules, angiogenesis-associated molecules, and in the expression of antigens, but a decrease in the expression of tumor suppressor-associated proteins (e.g., PTEN) or proapoptotic proteins (e.g., Bax and Bak) is observed (Table 1). Thus, these molecules, which show altered expression levels in melanoma relative to normal cells, are useful tissue biomarkers (immunohistochemical biomarkers) for melanoma diagnosis. However, in spite of these discoveries, these markers are not specific to melanoma and there are few melanoma-specific tissue biomarkers, excluding melanocyte lineage/differentiation antigens and melanoma-associated antigens (e.g., TRP1/gp75 and 2, Melan-A/MART-1,

Many researchers have identified putative serologic biomarkers for melanoma diagnosis (Table 2), which play a key role in the growth and survival of melanoma cells. Typically, these markers activate survival and/or proliferation-associated and angiogenesis-associated signal transduction pathways after binding with their receptors. The most important receptors of this kind are GFRs (e.g., VEGFR and FGFR) and GPCRs (e.g., MC1R,

The primary antigens that have been observed in the serum of melanoma patients are melanocyte lineage/differentiation antigens and melanoma-associated antigens. The existence of these antigens in serum is closely associated with melanoma progression and low survival rates. Thus, these types of markers are useful as prognostic biomarkers and

Wnt/frizzled receptor, and chemokine receptor) (Halaban, 1996; Lee et al., 2008).

al., 2008).

testis and to various tumors (Simpson et al., 2005).

and TA-90) that are overexpressed in metastatic melanoma.

**2.2 Serologic biomarkers for melanoma diagnosis**

have potential to act as therapeutic targets.

In the absence of vascularization, the growth of melanoma is limited to 0.2 – 0.3 cm due to the limited diffusion of oxygen and nutrients into the tumor. For additional growth, angiogenesis is essential for providing adequate blood supply to the growing lesion. Angiogenesis is regulated by proangiogenic factors, such as VEGF, FGF, tumor necrosis factor (TNF), and interleukin-8 (IL-8) and by antiangiogenic factors, such as interferons (IFNs) and angiostatin. An increase in vascular density provides a greater supply of oxygen and nutrients to cells, leading to melanoma growth (Folkman, 2007; Mahabeleshwar and Byzova, 2007). High levels of proangiogenic factors in the serum of melanoma patients can be used as an indicator of melanoma at diagnosis.

Multiple cytokines (e.g., IL-1, 4, 6, 8, 10 and 14), which are correlated with melanoma growth, angiogenesis and metastasis, have been observed in the serum of melanoma patient at both the protein and/or mRNA level. Serum levels of these cytokines are increased in metastatic melanoma patients, suggesting that they can be used as an indicator of melanoma progression (Porter et al., 2001; Varney et al., 2006; Yurkovetsky et al., 2007). Moreover, the serum concentration of the soluble IL-2 receptor is elevated in patients with metastatic melanoma and elevated serum IL-2 receptor levels are associated with lowered survival rates (Boyano et al., 1997; Ottaiano et al., 2006). Interestingly, IFNs are soluble cytokines, but possess antiangiogenic and antitumor activities. An increase in the melanoma progressionassociated cytokines leads to a reduction in IFNs levels, but there is a decrease in the serum levels of melanoma progression-associated cytokines in melanoma patients following immunomodulatory therapy with IFNs (mainly IFN-α2b)(Singh and Varner, 1998; Jonasch and Haluska, 2001; Yurkovetsky et al., 2007; Dummer and Mangana, 2009; Hofmann et al., 2011). Thus, the analysis of a number of different serum cytokines may be a useful means of monitoring the efficacy of immunomodulatory therapy.

#### **2.3 Urinary biomarkers for melanoma diagnosis**

Urinary biomarkers for melanoma diagnosis have received much greater interest because of the relative ease of sample collection and handling compared with the analysis of blood or tissue samples, but this form of sample may lack the sensitivity required for a diagnostic biomarker. Of the urinary biomarkers of melanoma already identified (Table 3), 5SCD and 6-hydroxy-5-methoxyindole-2-carboxylic acid (6H5MI2C), are intermediate metabolites in melanin pigment formation, and have been the most extensively studied. An increase in urine levels of these markers has been associated with tumor progression and low survival rates (Kärnell et al., 1997; Bánfalvi et al., 2000; Wakamatsu et al., 2002). In healthy patients, the urinary levels of these markers are influenced by age (Meyerhöffer et al., 1998), sex (Morishima and Hanawa, 1981; Kågedal et al., 1992), skin color (Wirestrand et al., 1985) and season (Ito et al., 1987), but not by pregnancy (Carstam et al., 1985). Although both 5SCD and 6H5MI2C have been detected in the urine of melanoma patients, because of the higher levels of 5SCD, this marker is considered a more reliable urinary biomarker for melanoma than the 6H5MI2C (Kärnell et al., 1997, 2000; Wakamatsu et al., 2006). Moreover, the 90-kDa glycoprotein (TA-90)(Rote et al., 1980; Euhus et al., 1989), S100A7 (Brouard et al., 2002) and β-human chorionic gonadotropin (Carter et al., 1995) have also been identified in the urine of patients with melanoma (Table 3).

Of these urinary biomarkers, 5SCD, 6H5MI2C, and S100A7 can be considered the most melanoma-specific of the urinary biomarkers (Kärnell et al., 1997; Bánfalvi et al., 2000; Brouard et al., 2002; Wakamatsu et al., 2002).

1) These proangiogenic factors also function as an important stimulator for melanoma growth.2) These proangiogenic factors also take part in melanoma metastasis.

Table 2. (continues on next page) Serologic biomarkers for the diagnosis of melanoma

Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them 397

3) Antigens that are found in melanoma tissues become good immunohistochemical biomarkers. 4) The

Table 2. (continues) Serologic biomarkers for the diagnosis of melanoma

associated inflammatory response Deichmann et al., 2000; Findeisen et al., 2009 Lactate dehydrogenase (LDH) An indicator for liver metastasis; a prognostic indicator in metastatic melanoma Deichmann et al., 2000; Findeisen et al., 2009; Zhuang et al., 2010 Glypican-3 (GPC3) Unknown exactly, but may function as a survival or proliferation-associated factor Nakatsura et al., 2004; Ikuta et al., 2005 PKCα A survival or proliferation-associated protein Kang et al., 2009 5SCD A precursor of melanin; Increased in metastatic prognosis Kärnell et al., 1997, 2000; Bánfalvi et al., 2000; Wakamatsu et al., 2002 6H5MI2C A precursor of melanin; Increased in metastatic prognosis Hara et al., 1994; Kärnell et al., 1997, 2000 Serum amyloid A (SAA) A superfamily of acute-phase proteins and proinflammatory adipokine Findeisen et al., 2009 Cystatin C A potent inhibitor of cysteine proteases; Increased primary and metastatic melanoma Kos et al., 1997; Ervin and Cox, 2005

Biomarkers Functions References Other antigens Galectin-3 A β-galactoside-binding protein; Increased in metastatic prognosis Vereecken et al., 2006, 2009 Synovial sarcoma X breakpoint-2 (SSX-2) A family of highly homologous synovial sarcoma X (SSX) breakpoint proteins and repressive gene regulator Kyyamova et al., 2006 Gangliosides (GM2, GD2, GM3, and GD3) Group of glycosphingolipids; Relate to interactions between melanoma cells Ravindranath et al., 2003 Cytokines and cytokine receptors 4) IL-1 Survival or proliferation-associated factor Porter et al., 2001; Yurkovetsky et al., 2007 IL-4 Survival or proliferation-associated factor Porter et al., 2001 IL-6 Survival or proliferation-associated factor Deichmann et al., 2000; Moretti et al., 2001; Porter et al., 2001; Yurkovetsky et al., 2007 IL-10 Survival or proliferation-associated factor Moretti et al., 2001; Porter et al., 2001 IL-12 Survival or proliferation-associated factor Moretti et al., 2001; Yurkovetsky et al., 2007 Soluble IL-2 receptor Survival or proliferation-associated factor Boyano et al., 1997; Ottaiano et al., 2006 Other serologic biomarkers YKL-40 Unknown exactly, but may function as a survival or proliferation-associated factor Johansen et al., 2006; Schmidt et al., 2006 C reactive protein (CRP) Unknown exactly, but may relate to tumor-

cytokines also take part in melanoma metastasis.

3) Antigens that are found in melanoma tissues become good immunohistochemical biomarkers. 4) The cytokines also take part in melanoma metastasis.

Table 2. (continues) Serologic biomarkers for the diagnosis of melanoma

396 Breakthroughs in Melanoma Research

Biomarkers Functions References Proangiogenic factors VEGF 1) VEGF receptor (VEGFR) ligand Lacal et al., 2000 FGF 1) FGF receptor (FGFR) ligand Ribatti et al., 2003 EGF 1) EGF receptor (EGFR) ligand Hurks et al., 2000 Placental growth factor (PIGF) 1) Neuropilin-1 and -2 receptor ligand Lacal et al., 2000; Odorisio et al., 2006 TNF 1) GPCR ligand Singh and Varner 1998; Lie et al., 2005 IL-8 (CXCL8) 1) GPCR (specially, chemokine receptor CXCR1 and 2) ligand Singh and Varner 1998; Lie et al., 2005; Varney et al., 2006 Laminin-5 2) Laminin receptor (e.g., integrin α6β4 and α7β1) ligand Ziober et al., 1999; Nikolopoulos et al., 2004 Osteopontin 2) Integrin αvβ3 ligand Zhou et al., 2005; Kadkol et al., 2006 uPA 2) uPAR ligand Delbaldo et al., 1994; de Vries et al., 1994; Ferrier et al., 2000 Antigens 3) Melanocyte lineage/Differentiation antigens Tyrosinase Regulator enzyme in melanin synthesis; Increased in metastatic prognosis Sonesson et al., 1995; Stevens et al., 1996 gp100/pmel-17 Melanin synthesis-associated melanosomal matrix glycoprotein; Increased in metastatic prognosis Pardo et al., 2007 S100 proteins (e.g., S100B) Cell division and differentiation-associated acidic calcium-binding protein; Increased in metastatic prognosis Henze et al., 1997; Schlagenhauff et al., 2000; Findeisen et al., 2009 MIA A small soluble protein; Increased in metastatic prognosis Bosserhoff et al., 1999; Schmidt and Bosserhoff, 2009 L-dopa/L-tyrosine ratio An index of tyrosinase functional activity; Increased in metastatic prognosis Letellier et al., 1999; Stoitchkov et al., 2002 Melanoma-associated antigens TA-90 Potential immunostimulator or antineoplastic activator; Increased in metastatic prognosis Rote et al., 1980; Kelley et al., 1998 Survivin (one of apoptosis inhibitors gene family) Apoptosis inhibition; Increased in metastatic prognosis Tas et al., 2004 Cytoplasmic/high-molecular-weight melanoma-associated antigen (CYT-

1) These proangiogenic factors also function as an important stimulator for melanoma growth.2) These

Table 2. (continues on next page) Serologic biomarkers for the diagnosis of melanoma

proangiogenic factors also take part in melanoma metastasis.

MAA/HMW-MAA) Unknown exactly, but may relate to melanoma progression Vergilis et al., 2005

Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them 399

tumor tissue is heterogeneous mixture of several cell types, cultured cell lines may be preferable for the screening of biomarkers. To search for biomarkers useful for the diagnosis of metastases, primary and metastatic cell lines were compared and several candidate biomarkers were successfully discovered (Table 4) (Bernard et al., 2003; Zuidervaart et al., 2006; Al-Ghoul et al., 2008). Proteomics analysis of melanoma-associated fibroblast stromal cells revealed the aberrant expression of several proteins not detected in normal fibroblasts (Paulitschke et al., 2009). These proteins may promote tumor progression. However, the passages number of the melanoma cell lines tested was found to produce changes in the proteome, which may underscore the invasive character observed in melanoma cells line

Screening methods Samples Biomarkers Remarks References

MUC18 HMG-1

HSP 27 Galectin-1

Periostin

HSP 27 Vimentin

**3.2 Screening biomarkers obtained from serum and secreted from cultured cell lines**  Because serum samples are far less invasive to obtain than biopsied material, the discovery of serological biomarkers has received a great deal of attention. Well-defined biomarkers enable early detection, allow the appropriate classification of tumor types (which provides the clinician insight into the best choice of therapy), and enable the patient to be more thoroughly monitored for progression and regression. However, there are several difficulties with screening serological biomarkers: (1) the presence of abundant blood proteins, which may inhibit the detection of biomarkers, and (2) the low serum concentration of the biomarker after it is secreted from tumor tissue and diluted in the bloodstream (Simpson et al., 2008). Hence, processes by which the abundant blood proteins are removed from the sample or the target proteins are concentrated are essential to address these problems. As a result of these difficulties inherent in serum proteomics, the secretome

(a 90-kDa glycoprotein) Stanniocalcin-1 (a 56-kDa glycoprotein)

Hepatoma-derived growth factor (HDGF) Nucleophosmin B23

Increased in melanoma

Increased in higher passages

Increased in metastases

metastatic melanoma

Increased; melanomaassociated antigens

Increased in disomy UM

Cyclophilin A Increased in

Bernard et al., 2003

Pardo et al., 2006

Zuidervaart et al., 2006

Al-Ghoul et al., 2008

Paulitschke et al., 2009

Coupland et al., 2010

that have been passaged many times (Pardo et al., 2006).

metastatic melanoma cell lines, and normal melanocyte lines

melanoma (UM) cell lines with varying passages

UM primary and metastatic cell lines

cell lines

fibroblasts and normal fibroblast

and disomy 3

Table 4. Biomarker screening for tumor tissues and cell lines

metastatic melanoma

2-DE/MALDI-TOF-MS Primary and

2-DE/LC-MS/MS Uveal malignant

2-DE/MS/MS Primary and

LC-MS/MS Melanoma-associated

2-DE/MS/MS UM with monosomy 3

has received much attention recently.

2-DE/MALDI-TOF/

TOF-MS

Table 3. Urinal biomarker for the diagnosis of melanoma

#### **2.4 Biomarkers for early melanoma diagnosis**

The early diagnosis of melanoma is closely related to an increase in survival rate. Although many prognostic biomarkers (mainly metastatic prognosis biomarkers) of melanoma have been reported, there are very few capable of allowing an early diagnosis. Glypican-3 (GPC3) is a membrane-bound heparin sulfate proteoglycan which is overexpressed in several tumors. It has been suggested that GPC3 may be a useful early stage biomarker for patients with the early stages of the disease (0 - II) (Nakatsura et al., 2004; Ikuta et al., 2005). Moreover, cyclooxygenase-2 (COX-2) (Chwirot and Kuźbicki, 2007), serum amyloid A (SAA) (Mian et al., 2005; Findeisen et al., 2009) and DNA methylation profiling (Conway et al., 2011) can be used to distinguish between early melanomas and benign nevi.

## **3. Screening techniques of melanoma biomarkers**

Before the development of high throughput proteomics techniques, biomarker candidates were identified based on known melanoma molecular pathways and validated by traditional techniques such as western blotting, ELISA and immunohistochemical analysis. However, the recent development of proteomics has enabled novel biomarkers to be screened from across a much larger section of the proteome. The most widely used technique for this form of screening is one whereby the samples are first separated by 2-DE and then each protein is identified by mass spectrometry (MS).  These techniques employ simple separation procedures such as capillary chromatography and surface chromatography prior MS analysis.

#### **3.1 Screening for tumor tissues and cell lines**

Biomarkers discovered from tissue samples and cultured cell lines also have utility for the development of diagnostic and prognostic assays. Tissue microarray is a high throughput technique in which many tissue samples can be screened simultaneously. This technique is suitable for the validation of candidate biomarkers, which are first obtained by other proteomics techniques. Several biomarkers of melanoma such as HSP 90 (McCarthy et al., 2008), ING3 (Wang et al., 2007), and the epidermal growth factor receptor family member HER3 (Reschke et al., 2008) were validated using this technique.

For comprehensive screening of biomarkers from lysates collected from tumor tissue and cultured cells, 2-DE combining MS is used as a standard method. The representative attempts of biomarker screening of melanoma lysates are summarized in Table 4. Since

Bánfalvi et al., 2000; Wakamatsu et al., 2002

5SCD Yamada et al., 1992; Kärnell et al., 1997;

6H5MI2C Yamada et al., 1992; Kärnell et al., 1997 TA-90 Rote et al., 1980; Euhus et al., 1989

The early diagnosis of melanoma is closely related to an increase in survival rate. Although many prognostic biomarkers (mainly metastatic prognosis biomarkers) of melanoma have been reported, there are very few capable of allowing an early diagnosis. Glypican-3 (GPC3) is a membrane-bound heparin sulfate proteoglycan which is overexpressed in several tumors. It has been suggested that GPC3 may be a useful early stage biomarker for patients with the early stages of the disease (0 - II) (Nakatsura et al., 2004; Ikuta et al., 2005). Moreover, cyclooxygenase-2 (COX-2) (Chwirot and Kuźbicki, 2007), serum amyloid A (SAA) (Mian et al., 2005; Findeisen et al., 2009) and DNA methylation profiling (Conway et

Before the development of high throughput proteomics techniques, biomarker candidates were identified based on known melanoma molecular pathways and validated by traditional techniques such as western blotting, ELISA and immunohistochemical analysis. However, the recent development of proteomics has enabled novel biomarkers to be screened from across a much larger section of the proteome. The most widely used technique for this form of screening is one whereby the samples are first separated by 2-DE and then each protein is identified by mass spectrometry (MS).  These techniques employ simple separation procedures such as

Biomarkers discovered from tissue samples and cultured cell lines also have utility for the development of diagnostic and prognostic assays. Tissue microarray is a high throughput technique in which many tissue samples can be screened simultaneously. This technique is suitable for the validation of candidate biomarkers, which are first obtained by other proteomics techniques. Several biomarkers of melanoma such as HSP 90 (McCarthy et al., 2008), ING3 (Wang et al., 2007), and the epidermal growth factor receptor family member

For comprehensive screening of biomarkers from lysates collected from tumor tissue and cultured cells, 2-DE combining MS is used as a standard method. The representative attempts of biomarker screening of melanoma lysates are summarized in Table 4. Since

al., 2011) can be used to distinguish between early melanomas and benign nevi.

capillary chromatography and surface chromatography prior MS analysis.

HER3 (Reschke et al., 2008) were validated using this technique.

Biomarkers References

Table 3. Urinal biomarker for the diagnosis of melanoma

**3. Screening techniques of melanoma biomarkers**

**3.1 Screening for tumor tissues and cell lines**

**2.4 Biomarkers for early melanoma diagnosis**

S100A7 Brouard et al., 2002 β-human chorionic gonadotropin Carter et al., 1995

tumor tissue is heterogeneous mixture of several cell types, cultured cell lines may be preferable for the screening of biomarkers. To search for biomarkers useful for the diagnosis of metastases, primary and metastatic cell lines were compared and several candidate biomarkers were successfully discovered (Table 4) (Bernard et al., 2003; Zuidervaart et al., 2006; Al-Ghoul et al., 2008). Proteomics analysis of melanoma-associated fibroblast stromal cells revealed the aberrant expression of several proteins not detected in normal fibroblasts (Paulitschke et al., 2009). These proteins may promote tumor progression. However, the passages number of the melanoma cell lines tested was found to produce changes in the proteome, which may underscore the invasive character observed in melanoma cells line that have been passaged many times (Pardo et al., 2006).

Table 4. Biomarker screening for tumor tissues and cell lines

#### **3.2 Screening biomarkers obtained from serum and secreted from cultured cell lines**

Because serum samples are far less invasive to obtain than biopsied material, the discovery of serological biomarkers has received a great deal of attention. Well-defined biomarkers enable early detection, allow the appropriate classification of tumor types (which provides the clinician insight into the best choice of therapy), and enable the patient to be more thoroughly monitored for progression and regression. However, there are several difficulties with screening serological biomarkers: (1) the presence of abundant blood proteins, which may inhibit the detection of biomarkers, and (2) the low serum concentration of the biomarker after it is secreted from tumor tissue and diluted in the bloodstream (Simpson et al., 2008). Hence, processes by which the abundant blood proteins are removed from the sample or the target proteins are concentrated are essential to address these problems. As a result of these difficulties inherent in serum proteomics, the secretome has received much attention recently.

Biomarkers for Melanoma Diagnosis and the Technologies Used to Identify Them 401

disease is key to increasing the survival rate. Of several melanoma biomarkers identified, GPC3, COX-2, SAA and DNA methylation profiling may hold promise for the diagnosis of

Abbasi NR, Shaw HM, Rigel DS, Friedman RJ, McCarthy WH, Osman I, Kopf AW, Polsky D

Akaraviputh T, Arunakul S, Lohsiriwat V, Iramaneerat C, Trakarnsanga A (2010). Surgery

Al-Ghoul M, Brück TB, Lauer-Fields JL, Asirvatham VS, Zapata C, Kerr RG, Fields GB

Bakalian S, Marshall JC, Logan P, Faingold D, Maloney S, Di Cesare S, Martins C, Fernandes

Bánfalvi T, Gilde K, Boldizsár M, Fejös Z, Horváth B, Liszkay G, Beczássy E, Kremmer T

Barrow C, Browning J, MacGregor D, Davis ID, Sturrock S, Jungbluth AA, Cebon J (2006).

Becker JC, Kirkwood JM, Agarwala SS, Dummer R, Schrama D, Hauschild A (2006)

Bernard K, Litman E, Fitzpatrick JL, Shellman YG, Argast G, Polvinen K, Everett AD,

Boisvert-Adamo K, Longmate W, Abel EV, Aplin AE (2009). Mcl-1 is required for melanoma

Bosserhoff AK, Lederer M, Kaufmann M, Hein R, Stolz W, Apfel R, Bogdahn U, Buettner R

Box NF, Duffy DL, Irving RE, Russell A, Chen W, Griffyths LR, Parsons PG, Green AC,

Boyano MD, García-Vázquez MD, Gardeazabal J, García de Galdeano A, Smith-Zubiaga I,

Brouard MC, Saurat JH, Ghanem G, Siegenthaler G (2002). Urinary excretion of epidermal-

Molecularly targeted therapy for melanoma. *Cancer*, 106, 2317-2327.

of melanoma progression. *Cancer Res*, 63, 6716-6725.

cell resistance to anoikis. *Mol Cancer Res*, 7, 549-556.

squamous cell carcinoma. *J Invest Dermatol*, 116, 224-229.

and IL-6 levels in patients with melanoma. *Oncology*, 54, 400-406.

(2004). Early diagnosis of cutaneous melanoma: revisiting the ABCD criteria.

for gastrointestinal malignant melanoma: experience from surgical training center.

(2008). Comparative proteomic analysis of matched primary and metastatic

BF, Burnier MN Jr (2008). Molecular pathways mediating liver metastasis in

(2000). Serum concentration of 5-S-cysteinyldopa in patients with melanoma. *Eur J*

Tumor antigen expression in melanoma varies according to antigen and stage. *Clin*

Fukasawa K, Norris DA, Ahn NG, Resing KA (2003). Functional proteomic analysis

(1999). MIA, a novel serum marker for progression of malignant melanoma.

Sturm RA (2001). Melanocortin-1 receptor genotype is a risk factor for basal and

Cañavate ML, Raton JA, Bilbao I, Díaz-Pérez JL (1997). Serum-soluble IL-2 receptor

type fatty acid-binding protein and S100A7 protein in patients with cutaneous

early melanoma.

**5. References**

*JAMA*, 292, 2771-2776.

*Clin Invest*, 30, 900-904.

*Cancer Res*, 12, 764-771.

*Anticancer Res*, 19, 2691-2693.

melanoma. *Melanoma Res*, 12, 627-631.

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patients with uveal melanoma. *Clin Cancer Res*, 14, 951-956.

Table 5 summarizes a number of different reports in which comprehensive screening of biomarkers from serum and the secretome occurred. By comparing the secretome between melanoma and normal melanocyte, several potential biomarkers were successfully discovered (Pardo et al., 2007; Paulitschke et al., 2009). The traditional serological biomarkers of melanoma such as LDH, S100B and CRP lack sensitivity as early stage melanoma biomarkers. To search for early stage biomarkers, Findeisen et al. extensively analyzed the serum proteome of about 600 melanoma patients at each stage of the disease (stages I - IV) by SELDI-TOF-MS technique (Mian et al., 2005; Findeisen et al., 2009). This analysis led to the discovery of a new biomarker, SAA, which was found to be highly sensitive for detecting early stage melanoma.

Table 5. Biomarker screening for serum and secretome of cell lines

#### **4. Summary and overall conclusions**

Melanoma biomarkers have the capacity not only to diagnose melanoma, but also to allow patients to be monitored for recurrence after surgical resection and to allow the effect of anticancer drug treatments to be evaluated. Advanced technologies (e.g., high throughput technologies in genomics or proteomics) have contributed much to the hunt for melanoma biomarkers in tissue samples or body fluids and have typically been MS-based or arraybased technologies.

Several immunohistochemical, serologic and urinary biomarkers have been reported to be very useful diagnostic and prognostic biomarkers. However, there is a paucity of data on melanoma-specific biomarkers, with the exception of the melanocyte lineage/differentiation antigens and melanoma-associated antigens, and some urinary biomarkers such as 5SCD, 6H5MI2C and S100A7.

Moreover, several melanoma biomarkers with prognostic capabilities, mainly for the detection of metastatic disease, have been applied to clinical use. However, there is s still a great need to identify melanoma early-stage melanoma biomarkers, as early detection of the disease is key to increasing the survival rate. Of several melanoma biomarkers identified, GPC3, COX-2, SAA and DNA methylation profiling may hold promise for the diagnosis of early melanoma.

#### **5. References**

400 Breakthroughs in Melanoma Research

Table 5 summarizes a number of different reports in which comprehensive screening of biomarkers from serum and the secretome occurred. By comparing the secretome between melanoma and normal melanocyte, several potential biomarkers were successfully discovered (Pardo et al., 2007; Paulitschke et al., 2009). The traditional serological biomarkers of melanoma such as LDH, S100B and CRP lack sensitivity as early stage melanoma biomarkers. To search for early stage biomarkers, Findeisen et al. extensively analyzed the serum proteome of about 600 melanoma patients at each stage of the disease (stages I - IV) by SELDI-TOF-MS technique (Mian et al., 2005; Findeisen et al., 2009). This analysis led to the discovery of a new biomarker, SAA, which was found to be highly

Screening methods Samples Biomarkers Remarks References

gp100/pmel-17 Cathepsin D Mad-9 (syntenin 1)

Cytokines (e.g. IL-1, IL-6, TNF-α)

Glutathione peroxidase

Melanoma biomarkers have the capacity not only to diagnose melanoma, but also to allow patients to be monitored for recurrence after surgical resection and to allow the effect of anticancer drug treatments to be evaluated. Advanced technologies (e.g., high throughput technologies in genomics or proteomics) have contributed much to the hunt for melanoma biomarkers in tissue samples or body fluids and have typically been MS-based or array-

Several immunohistochemical, serologic and urinary biomarkers have been reported to be very useful diagnostic and prognostic biomarkers. However, there is a paucity of data on melanoma-specific biomarkers, with the exception of the melanocyte lineage/differentiation antigens and melanoma-associated antigens, and some urinary biomarkers such as 5SCD,

Moreover, several melanoma biomarkers with prognostic capabilities, mainly for the detection of metastatic disease, have been applied to clinical use. However, there is s still a great need to identify melanoma early-stage melanoma biomarkers, as early detection of the

SAA Increased

Increased in melanoma

Increased in patients with longer relapsefree survival (RFS) values

Increased in malanoma

in early stages

Pardo et al., 2007

Yurkovetsky et al., 2007

Paulitschke et al., 2009

Mian et al., 2005 Findeisen et al., 2009

sensitive for detecting early stage melanoma.

2D-GE/LC-MS/MS UM cell lines and normal

Multiplex

immunobaed assay

based technologies.

6H5MI2C and S100A7.

melanocytes

individuals

LC-MS/MS Malanoma cell lines and

stages

**4. Summary and overall conclusions**

SELDI-TOF-MS Serum of melanoma

Serum of melanoma patients and healthy

normal melanocyte

patients with different

Table 5. Biomarker screening for serum and secretome of cell lines

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