Malignant melanoma is a highly aggressive malignant tumor, commonly found in the skin, digestive tract, genitals, nasal cavity and eyes (1). Early melanoma can be cured by surgical treatment, but the prognosis of advanced melanoma is poor. Before 2011, chemotherapy was the mainstay of treatment for advanced melanoma with a 5-year survival rate of less than 5% (2, 3). With the development of immune checkpoint inhibitors, the clinical outcomes of patients with advanced melanoma have been significantly improved and some patients can achieve long-term survival. The 5-year survival rate of patients with advanced melanoma treated with programmed cell death protein 1 (PD-1) inhibitors is about 40% (4–6). Nevertheless, the objective response rate of malignant melanoma treated with PD-1 inhibitors is low and more than half of patients cannot benefit from PD-1 inhibitors (4, 7, 8). In addition, PD-1 inhibitors are costly and some patients may experience serious immune-related adverse events. Therefore, it is crucial to identify appropriate prognostic markers and those patients who are most likely to respond to PD-1 inhibitors.

Although the drug development and clinical application of PD-1 inhibitors are progressing rapidly, only a few prognostic markers have been used in clinical practice such as programmed death ligand-1(PD-L1) expression, microsatellite instability (MSI) and tumor mutation burden (TMB) (9–13). These markers play an important role in predicting the efficacy of PD-1 inhibitors, but there are still some limitations due to the need for invasive biopsies to obtain tissue, intratumor heterogeneity in PD-L1 expression and high cost and so on (14). Peripheral blood-based markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and circulating tumor cells are easy to obtain and can be continuously evaluated, which has gained more and more attention.

Cancer-associated inflammation, recognized as one of the hallmarks of cancer, plays an important role in occurrence and development of tumors (15). NLR as a marker of inflammation in peripheral blood is cheap, readily available and easy-to-use. More and more evidence has shown that higher baseline NLR (BLNLR) is associated with poor prognosis of advanced melanoma patients receiving immunotherapy (16–19). In addition, BLNLR before immunotherapy and the relative change of NLR after immunotherapy (ΔNLR%) are also related to the prognosis of advanced patients in European and American populations mainly with cutaneous melanoma (20–22). However, the response of different melanoma subtypes to immunotherapy is highly heterogeneous. In the Chinese population, acral and mucosal melanoma are the main subtypes with a lower TMB, a higher proportion of chromosomal structural variation and a worse prognosis compared with cutaneous melanoma mainly occurs in European and American patients (23). Although current studies have found that BLNLR can predict the response to immunotherapy in the Chinese population (24), there is no report on the prognostic value of ΔNLR% in Chinese patients with advanced melanoma. The aim of this study is to investigate the prognostic value of BLNLR combined with ΔNLR% in patients with metastatic melanoma treated with PD-1 inhibitors in the Chinese population, to stratify the prognosis of patients and to attempt to provide reference for clinical decision making of metastatic melanoma patients in China.

Immunotherapy has become the main treatment for advanced melanoma, bringing significant survival benefits to patients. However, the therapeutic efficacy of immunotherapy in advanced melanoma is highly heterogeneous among different races and different individuals of the same race (25). A high BLNLR is associated with poor prognosis, but not all patients with low BLNLR respond well to immunotherapy. To address this clinical issue, we evaluated the prognostic value of BLNLR and ΔNLR% before third cycle of treatment and combined the two to stratify the prognosis of patients with metastatic malignant melanoma treated with PD-1 inhibitors.

Capone M et al. found that high BLNLR was an independent prognostic risk factor for OS and PFS in a retrospective study involving 97 patients with advanced melanoma who received immunotherapy (26). Qi et al. also confirmed that elevated BLNLR was associated with low immune response rate in the Chinese population (24). In a multicenter retrospective study of 224 patients with advanced melanoma receiving first-line immunotherapy, BLNLR was closely related to ECOG PS, number of metastatic sites and prognosis, and it was also found that ΔNLR% ≥30% during the first two cycles of treatment suggested an increased risk of death (20). Cassidy MR et al. dynamically examined NLR levels in melanoma patients receiving immunotherapy and similarly found that a 30% increase in NLR was an independent risk factor for prognosis (22). Consistent with the above studies, we found that patients with BLNLR≥3 and ΔNLR%≥30% had a significantly increased risk of death and disease progression. In addition, it was found that high-BLNLR was association with male and multiple organ metastases and high-NLR% was association with cutaneous, ocular unknown primary melanoma. These associations indirectly support that BLNLR and ΔNLR% reflect a comples and individualized interaction between both hosts and tumor factors.

NLR is a marker of systemic inflammatory response, but the mechanism of its effect on the prognosis of advanced melanoma immunotherapy is still unclear. Lymphocytes are the main effector cells of anti-tumor response and tumor-infiltrating lymphocytes can predict the efficacy of immunotherapy (27, 28). Several studies have shown that lymphopenia is associated with poor prognosis in a variety of tumors (29–31). Neutrophils reflect the inflammatory state of the host and are a marker of cancer (15). They are involved in the occurrence, proliferation and metastasis of tumors. Neutrophils can be recruited to inflammatory sites by chemokines and contribute to cancer initiation by DNA damage, angiogenesis and immunosuppression (32, 33). Neutrophil elastase (NE) produced by neutrophils can be endocytosed by tumor cells and then degrade insulin receptor substrate 1(IRS1) to free PI3K bound to IRS1, ultimately promoting tumor proliferation through the PI3K-AKT signal pathway (34). Neutrophils can also reduce the arginine in T cells by secreting arginase-1(ARG-1), thereby inhibiting the activation and proliferation of CD3 mediated T cells, ultimately leading to tumor proliferation (35). In addition, matrix metalloprotenase-9 (MMP-9) produced by neutrophils can promote the release of vascular endothelial growth factor (VEGF) to promote angiogenesis and participate in the process of tumor growth and metastasis (36). When it comes to tumor metastasis, neutrophils can do this by promoting cancer cell migration, intravasation and extravasation (33). Tumor-derived cathepsin G can induce cell migration and promote the entry of cancer cells into blood vessels. Neutrophil extracellular traps(NETs), a fibrous network composed of chromatin and proteins released from neutrophils, are able to capture circulating tumor cells and promote their dissemination at distant organs, leading to cancer metastasis (37). In addition, NE and MMP-9 can cleat membrane protein to induce the proliferation of dormant cancer cells in metastatic sites (38). A high NLR level may indicate an enhanced inflammatory response in the tumor microenvironment and a weakened lymphocyte-mediated anti-tumor response, thus reflecting the prognostic characteristics of melanoma patients.

The important problem of immunotherapy is the low response rate. In the Chinese population, the objective response rate of PD-1 inhibitors in patients with advanced melanoma is 15%-18.2% (39–43). Therefore, it is very important to find prognostic markers for immunotherapy in Chinese patients with malignant melanoma. BLNLR can predict the outcome of PD-1 inhibitors treatment in Chinese melanoma patients (24). However, the treatment of cancer is a dynamic process, so the dynamic change of NLR is more likely to better respond to the prognosis of PD-1 inhibitors treatment of melanoma patients. In this study, we found that the combination of BLNLR and ΔNLR% before the third cycle of treatment could enhance the predictive ability and better distinguish the prognosis of patients with melanoma under PD-1 inhibitors treatment. Melanoma patients with BLNLR <3 and ΔNLR% < 30% (34.9%) had a median OS of 20 months, which was significantly longer than the other three groups and were more likely to benefit from PD-1 inhibitors. In contrast, patients with BLNLR≥3 and ΔNLR%≥30% (14.3%) had extremely poor survival, with a median OS of only 5 months and all died within 10 months. In addition, it should be emphasized that the time point before the third cycle of treatment was chosen in this study, which was consistent with the time point when the first imaging examination was performed after treatment to assess the efficacy. If imaging examination before the third cycle treatment indicated stable or slight progression and the patient had low BLNLR and low ΔNLR%, it could be considered safe to continue this treatment. On the contrary, if the imaging examination before the third cycle of treatment indicates that the disease is slightly progressive but does not reach the progressive standard and the patient belongs to the high BLNLR and high ΔNLR% groups, doctors and patients should be cautious about the prognosis of such patients and there is a certain risk of disease progress in continuing PD-1 inhibitors. It has come to our knowledge that this is the first study to demonstrate in Chinese population that the combination of BLNLR and ΔNLR% enables prediction of prognosis in melanoma patients receiving PD-1 inhibitors. These results provide a strong basis for the combined use of BLNLR and ΔNLR% as prognostic markers to optimize patient benefit.

This study is a small sample and single-center retrospective study with potential selection bias and confounding factors. Due to the rarity of melanoma in the Chinese population, the number of patients included in this study was only 63. Subgroup analysis was not performed to further explore the effect of BLNLR and ΔNLR% on prognosis under different treatment methods. Based on the above limitations, further multi-center and large-sample prospective studies are needed to verify the conclusions of this study.

BLNLR combined with ΔNLR% can enhance the prognostic ability of metastatic melanoma patients treated with PD-1 inhibitors. Patients with low BLNLR and low ΔNLR% before the third cycle of treatment are more likely to benefit from PD-1 inhibitors. On the contrary, high BLNLR and high ΔNLR% is association with a very poor prognosis, which combined with other clinically relevant details such as imaging examination may be the reason for the change of treatment in this subgroup of patients. In conclusion, BLNLR combined with ΔNLR% can simply, economically and dynamically reflect the prognosis of metastatic melanoma, assisting clinicians in selecting treatment strategies to a certain extent.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Ethics Committee of The First Affiliated Hospital of Zhengzhou University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

CW, WZ, and YD performed the literature search and designed the study. CW, SL, XL, and KC contributed to the acquisition, analysis, and interpretation of the data. CW and SL wrote the original draft of the manuscript. WZ and YD edited the manuscript. All authors contributed to the article and approved the submitted version.