皮肤黑色素瘤（CM）被广泛认为是一种高度侵袭性的恶性肿瘤，与相当程度的发病率和不良预后相关。尽管有这样的认识，缺氧相关的长非编码 RNA (HRL) 在 CM 发病机制中的确切作用仍然是一个活跃的研究领域。本研究试图通过彻底筛选和提取缺氧相关基因 (HRG) 来阐明 HRL 在 CM 中的作用。特别是，我们进行了单变量和多变量 Cox 回归分析，以评估 HRL 预后特征的独立性。我们的结果表明，可以根据五个预后 HRL 建立一个新的风险模型。值得注意的是，卡普兰-迈耶生存分析证实，与高风险患者相比，低风险评分患者的总体生存率显着更高。此外，我们利用共识聚类分析将 CM 患者分为两种不同的亚型，这揭示了他们的预后和免疫浸润情况的显着差异。我们的列线图结果证实，HRL 预后特征可作为独立的预后指标，为 CM 患者的生存概率提供准确的评估。值得注意的是，我们的 ESTIMATE 和 ssGSEA 分析结果强调了低风险和高风险 CM 患者群体之间免疫浸润情况的显着差异。此外，IPS 和 TIDE 结果表明，不同风险亚型的 CM 患者可能对免疫治疗表现出良好的反应。富集分析和 GSVA 结果表明，免疫相关信号通路可能介导 HRL 在 CM 中的作用。最后，我们的肿瘤突变负荷 (TMB) 结果表明，低风险评分的患者具有较高的 TMB 状态。总之，本研究建立的基于 HRL 的风险模型提供了准确的预后预测，并与 CM 的免疫浸润景观相关，从而为该疾病的未来临床管理提供了新的见解。

Cutaneous melanoma (CM) is widely acknowledged as a highly aggressive form of malignancy that is associated with a considerable degree of morbidity and poor prognosis. Despite this recognition, the precise role of hypoxia-related long noncoding RNAs (HRLs) in the pathogenesis of CM remains an area of active research. This study sought to elucidate the contribution of HRLs in CM by conducting a thorough screening and extraction of hypoxia-related genes (HRGs). In particular, we conducted univariate and multivariate Cox regression analyses to assess the independence of the prognostic signature of HRLs. Our results demonstrated that a novel risk model could be established based on five prognostic HRLs. Remarkably, patients with low-risk scores exhibited significantly higher overall survival rates compared to their high-risk counterparts, as confirmed by Kaplan-Meier survival analysis. Furthermore, we utilized consensus clustering analysis to categorize CM patients into two distinct subtypes, which revealed marked differences in their prognosis and immune infiltration landscapes. Our nomogram results confirmed that the HRLs prognostic signature served as an independent prognostic indicator, offering an accurate evaluation of the survival probability of CM patients. Notably, our findings from ESTIMATE and ssGSEA analyses highlighted significant disparities in the immune infiltration landscape between low- and high-risk groups of CM patients. Additionally, IPS and TIDE results suggested that CM patients in different risk subtypes may exhibit favorable responses to immunotherapy. Enrichment analysis and GSVA results indicated that immune-related signaling pathways may mediate the role of HRLs in CM. Finally, our tumor mutation burden (TMB) results indicated that patients with low-risk scores had a higher TMB status. In summary, the establishment of a risk model based on HRLs in this study provided an accurate prognostic prediction and correlated with the immune infiltration landscape of CM, thereby providing novel insights for the future clinical management of this disease.