The prevalence of melanoma is increasing worldwide among fair-skinned populations (1). Age-standardized world incidence rates are 0.33-35.8 per 100,000 according to the GLOBOCAN 2020 statistics (2). Melanoma is a cancer arising from the malignant transformation of pigment producing melanocytes. Ultraviolet radiation is an important risk factor for development of melanoma (3). However, the road from sun exposure to cutaneous melanoma is complex and diverse (3). Ultraviolet light is absorbed by nucleic acids, proteins or other endogenous chromophores, triggering biological processes in skin cells (3, 4). The degree of ultraviolet radiation induced stress and the protection against this stress are influenced both intracellular and intercellular molecular interactions (3). The interaction of variable environmental exposure and different genetic susceptibility and other host factors lead to the formation of melanomas with different biological behaviour and clinical characteristics (3, 5). In addition, melanoma derived proopiomelanocortin peptides, glucocorticoids, neurotransmitters, hormones, and intermediates of melanogenesis can affect the local and systemic immune responses, leading to tumor progression and therapy resistance (5). The synthesis of melanin is a tightly regulated multistep biochemical process (5). Melanogenesis can affect melanoma behaviour and disease outcome through regulation of cellular metabolism, and protecting melanoma cells against radiotherapy (6).

Melanoma is a tumor with a high risk of metastasis, and although disease relapse occurs most frequently in the first 3 years after resection of primary tumor, metastasis can occur any time and at any site (7). Thus, easily accessed (e.g., blood) cancer biomarkers for the early detection of disease relapse are urgently needed. The biomarkers should also provide prognostic information related to tumor biology and mirror tumor burden when traditional radiological criteria are not applicable to assess clinical benefit from therapy (8–10). Such biomarkers could improve patient outcomes. Furthermore, therapeutic response to immune checkpoint inhibitors or selective tyrosine kinase inhibitors is heterogeneous due to the complex interactions between the host and tumor (11–13). It is of great interest to identify biomarkers predicting clinical benefit from a particular therapy. Valid prognostic biomarkers associated with a specific aspect of tumor progression and metastasis are good candidates for such predictive models (11–14).

Serum lactate dehydrogenase (LDH) was the first prognostic blood biomarker to be included in the American Joint Committee on Cancer (AJCC) staging system for patients with metastatic melanoma3. In two meta-analyses performed by Petrelli et al. in 2015 and 2019, the prognostic effects of elevated serum LDH proved to be significant in melanoma (15, 16). Serum LDH correlates with tumor volume and necrosis and is not specific to tumor type (15). In addition, an elevation in serum LDH levels may correlate with tissue damage independent of malignancy. The tumor marker, S100B, is more specific to melanoma (9, 17, 18). Serum levels of S100B reflect tumor volume in metastatic disease; however, serum S100B levels can also be elevated in many other diseases, such as cardiovascular diseases, liver cirrhosis, migraine, chronic kidney disease, previous stroke, vitiligo, breast cancer, and SARS-CoV-2 infection (19–21). The only meta-analysis focused on serum S100B and melanoma showed that elevated serum S100B levels are associated with significantly worse survival in patients with melanoma (22).

Serum tumor markers usually have both prognostic and diagnostic predictive value to varying degrees (9, 10). From a diagnostic perspective, serum S100B levels are monitored in many cancer centers to detect disease relapse, while serum LDH is monitored less frequently in melanoma patients. A strong statistical correlation between S100B expression in melanoma tumor tissue samples and tumor stage has been found, and S100B protein is a possible target of therapeutic intervention (23–25). However, the estimates of sensitivity and specificity of serum S100B are highly variable (32-94% and 76-97%, respectively (26). Currently, no consensus on the use of blood tests for monitoring disease recurrence in patients with resected melanoma exists (27–30).

Although many serologic protein and non-protein markers that could aid early diagnosis of melanoma relapse as well as indicate patients’ prognosis have been reported, often primary studies are of variable quality and the findings are inconsistent (11, 23). Systematic reviews and meta-analyses are considered the reliable form to summarize the evidence about the prognostic and diagnostic value of particular factors (31). Meta-analysis to demonstrate whether serum S100B is a valid marker for the diagnosis of melanoma recurrence has not yet been published (23).

The objective of this study was to compare the prognostic and diagnostic abilities of serum S100B and serum LDH in patients with melanoma. Studies using Receiver Operating Characteristic (ROC) curves and Cox multivariate proportional-hazards models were included. The advantage of ROC is that the Area Under the ROC (AUROC) can be used to compare the accuracy of different diagnostic tests (32). The Cox regression model allows to detect and adjust for imbalance in prognostic variables; thus, it can be used to estimate more precisely a marker-dependent prognosis (33).

This systematic review and meta-analysis were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement (31, 34, 35) ( Supplementary Table 1 : PRISMA-DTA Checklist). The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42019137138).

Intracellular S100 proteins are Ca2+- and Zn2+-sensors involved in several protein interactions regulating a wide variety of cellular processes, including transcription, protein phosphorylation, motility, energy metabolism, which may affect tumor growth (57–59). In addition, extracellular S100B is a damage-associated molecular pattern protein, which may promote tumor progression by contributing to cancer-associated inflammation or by activating signaling pathways in melanoma cells via receptors for advanced glycation end products (57–59). The main source of elevated serum S100B levels in melanoma is the passive release from damaged/necrotic cells; however, the same tumor burden may or may not cause an elevation of S100B serum levels (57). In tumor cells dependent on glycolysis, lactate production increases substantially due to the increased expression and activity of LDH, which converts pyruvate to lactate. Lactate, which is exported by tumor cells, may promote angiogenesis, metastasis, therapy resistance, and immunosuppression (60). In malignant cells at the more oxygenated tumor periphery, lactate is utilized as an energetic source; lactate must be converted to pyruvate via LDH for this purpose (60, 61). Elevated serum LDH in patients with advanced melanoma is primarily due to release from glycolytic tumor cells (LDH3 and 4) (61).

In our meta-analysis, the pooled AUROC for correctly identifying disease relapse proved to be significantly higher for serum S100B than for serum LDH, indicating that serum S100B is a more suitable marker for tumor recurrence during follow-up of patients with cutaneous melanoma. Of note, S100B is the only serum biomarker supported by sufficient data that is routinely available in most hospitals. The serum S100B concentration was shown to be significantly higher in patients of stage III or IV than in those of stages I and II, and significantly higher in patients of stage IV than stage III (62). Serum S100B, however, seemed incapable of predicting sentinel lymph node status (63). Importantly, Abraha et al. found that diagnostic accuracy for detecting advanced disease may be higher by combining an elevated serum S100B and a Breslow tumor thickness of >4mm (62). Elevated levels of serum S100B occur in a number of conditions (19); thus, these findings support that monitoring S100B is recommended primarily in cases of melanoma with a high risk of relapse. Nevertheless, when a pre-specified cutoff (the upper limit of normal or ROC optimized) was used, serum S100B and LDH proved to be similarly and highly specific and moderately sensitive; however, the sensitivity of serum S100B was significantly higher compared to serum LDH. This result suggests that monitoring serum S100B might indicate the need for an imaging examination to detect disease relapse earlier than serum LDH. Further studies, both in clinical trials and in real-world populations, are needed to clarify how the measurement method, cut point, reference test, and patient population affect the accuracy of serum S100B for the detection of disease recurrence. These studies could also explore the sources of the considerable heterogeneity observed in our meta-analysis (31). Nevertheless, melanoma is heterogeneous in terms of biological behavior, due to the heterogeneity of the genome and proteome; the identification of a single biomarker that can be used widely is difficult (3). Further studies are needed to identify additional biomarkers that could be used in combination with serum S100B to increase the chances of early detection of disease relapse (45).

A number of circulating biomarkers are being investigated that may help us in follow-up. Compared to tissue tumor biopsy, peripheral blood sample (liquid biopsy) is more readily available and less heterogeneous (13). Many serologic markers such as enzymes [e.g., matrix metalloproteinase-9 (MMP-9)], secreted proteins (e.g., melanoma inhibiting activity), metabolites of the melanin synthesis pathway (e.g., 5-S-cysteinyl-dopa), circulating nucleic acids (e.g., tyrosinase mRNA, circulating-free DNA BRAFV600E mutation), and peripheral blood immune markers (e.g., soluble PD-L1) have been shown to correlate with tumor progression, survival or response to treatment in patients with melanoma (9–14, 23, 30, 64, 65). Properly designed, conducted, analyzed and reported prediction model studies will determine how to use these markers with the greatest clinical benefit (11, 31, 66, 67).

In a subgroup of patients with metastatic melanoma, the levels of serum S100B were not elevated and many studies and reviews have been published on the prognostic effect of serum S100B (17, 18, 29, 68–70). Because of the strong discriminative ability of serum S100B in identifying metastatic disease, the inclusion of studies on patients with all stages of melanoma was considered to be inappropriate for prognostic effect analysis; thus, only studies in which metastatic patients were included were selected. Surprisingly, very few eligible studies were identified because of the scarcity of multivariate analyses, patient selection bias, and significant reporting bias on outcomes in prognostic studies in the field. The Cox regression models that were included in the analysis used established prognostic markers as adjustment factors, e.g., site of metastases, the presence of brain metastasis, treatment. According to our results, the summary adjusted hazard ratio for S100B was similar to that for LDH, i.e. serum S100B has a similar prognostic value as serum LDH in patients with metastatic melanoma. Importantly, in accordance with the different biology coupled with elevated levels of serum LDH and S100B, the studies included in the meta-analysis indicated that the prognostic ability of the two markers was independent. Reviewing the literature, we found only one meta-analysis that examined the association between serum S100B levels and melanoma prognosis. In this meta-analysis, elevated serum S100B levels were associated with significantly poorer survival in melanoma patients (22). MMP-9 plays an important role in melanoma invasiveness. In one study, elevated serum MMP-9 levels and the circulating-free DNA BRAFV600E mutation were found to be associated with poor progression-free survival and overall survival. MMP-9 may be a promising indicator of the response to BRAF inhibitors in combination with the detection of the BRAFV600E mutation (12). The programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) axis plays an important role in circumventing immune surveillance. There is a need for a biomarker that would predict the efficacy of PD-1/PD-L1 inhibitors in patients with metastatic melanoma. Yue C et al. found that a decrease in circulating PD-L1 + tumor cell count was associated with a strong antitumor response. Also, patients with high levels of PD-L1 + circulating tumor cells at baseline are generally susceptible to anti-PD-L1 therapy (71). Since serum S100B and LDH monitoring also appear to be prognostically useful in melanoma patients during BRAF-inhibitor or immune checkpoint inhibitor treatment (69, 70, 72, 73), the combination of these markers could be further evaluated in predictive models identifying subgroups with differential treatment effects. The novelty of this meta-analysis was the comparative approach, the analysis of multiple outcomes, and the inclusion of logistic regression models. Furthermore, the results were derived from the analysis of data from patient populations with more than 1,000 participants for each of the studied outcomes.

A high risk of bias regarding statistical analysis and reporting domain was detected in many predictive studies screened for analysis, but the bias was lower in the selected studies due to the applied inclusion criteria. This, in turn, led to only a few articles being eligible for data extraction, which is a limitation of this meta-analysis. In addition, there was considerable heterogeneity across the included studies. The immunoassays used for measuring serum S100B and the cutoff for determining normal versus elevated S100B levels were not completely uniform across studies. The adjustment factors in the prognostic studies were also not uniform. A limitation of this review is that a majority of eligible prognostic studies came from Germany (German Central Malignant Melanoma Registry), although the data were collected from different periods and/or from an intentionally chosen different setting. Our attempt to contact the first author to obtain information on the extent of potential overlap between populations of prognostic factor studies performed by the same research group was unsuccessful.

The applicability of serum S100B and serum LDH for predicting the progression of melanoma was studied in this review from both diagnostic and prognostic viewpoints. We found that the discriminative ability of serum S100B at identifying disease relapse was greater than that of serum LDH. Since a relapse of melanoma is associated with elevated serum S100B levels in only a subset of patients, serum S100B should be considered in combination with additional serum biomarkers in a multivariable diagnostic prediction model. Furthermore, serum S100B had a similar and independent prognostic strength in metastatic melanoma compared with serum LDH, suggesting that the implementation of both markers in a multivariable prognostic prediction model development would be advantageous. To increase the degree of confidence in the prognostic and diagnostic abilities of various biomarkers, primary predictor studies conducted and reported in accordance with the corresponding quality assessment tools are important.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.

Concept and design: EJ, PH, ZS, and GE. Review questions were formulated by EJ and GE, guided by PH and DP. The applicability of the selected studies to the review question was determined by two authors (EJ and GE), independently, then a consensus was reached through discussion. Search, study selection, and data extraction: EJ and GE. Risk of bias assessment: EJ and GE. Statistical analysis: ZS and AS. Drafting of the manuscript: EJ, TV, and GE. Critical revision of the manuscript: all authors. All authors contributed to the article and approved the submitted version.

This work was supported by the ÚNKP-20-4 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund. Furthermore, the project was supported by the European Union and the European Regional Development Fund GINOP-2.3.2-15-2016-00005 and Hungarian Scientific Research Fund NKFIH K120206.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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