Currently, many biomarkers are used to predict the response to immunotherapy in melanoma, such as PD-L1 expression, TMB, and MSI-H. However, they also have limitations such as consistency, heterogeneity and cut-off selection [7–9]. Therefore, the construction of predictive models for immunotherapy has significant clinical implications. Construction predictive models for immunotherapy not only enhances the accuracy of predicting individual patient responses, thereby facilitating more tailored treatment plans and improving treatment outcomes, but it also deepens our understanding of the biological characteristics of tumors and their interactions with the immune system [22–25]. This contributes significantly to the development of innovative therapeutic strategies for cancer and steers the direction of future scientific research. Previous studies have shown that the ICD gene signature can be used in identification and construction of immunotherapy and prognosis prediction models for malignant tumors such as head and neck squamous cell carcinoma, stomach adenocarcinoma, and hepatocellular carcinoma [26–28]. However, there is currently no research on whether the ICD gene signature can predict the response and outcome of on-treatment metastatic melanoma patients to ICB therapy. In this study, we utilized 18 ICD gene signatures and employed an elastic net algorithm combined with four distinct datasets to establish a predictive model. This model aims to predict the response of metastatic melanoma patients to immunotherapy.
In this study, based on the elastic net algorithm, we ultimately identified 9 hub ICD signatures as the most effective predictors of the response to ICB therapy. These include Alkaliptosis, Apoptosis, Cuproptosis, Entosis, ICD, LDCD, Necroptosis, Oxeiptosis, and Paraptosis. Alkaliptosis is a form of cell death characterized by a lethal increase in intracellular pH, which has recently become a significant focus in cancer immunotherapy research, especially in pancreatic cancer [29, 30]. This type of cell death is driven by various molecular pathways, primarily involving the activation of the NF-κB pathway. The pathway promotes cell death through intracellular alkalization, which inhibits carbonic anhydrase 9 (CA9) [29, 30]. Apoptosis, also known as programmed cell death, plays a critical role in the regulation of various cancer therapies, including melanoma. It can be induced through intrinsic and extrinsic pathways, which converge on the activation of caspases that facilitate the degradation of key cellular components [31, 32]. In the context of melanoma and other cancers, understanding the pathways that lead to apoptosis is crucial for developing effective immunotherapies [31, 32]. The process of entosis involves a living cell entering into another living cell, forming cell-in-cell structures, ultimately leading to the death of the internal cell through autophagy and lysosomal fusion [33]. Due to entosis leading to aneuploidy in the internal cell and potential autophagy with lysosomal fusion, this process may alter the immunogenicity of tumor cells, thereby affecting the effectiveness of immunotherapy. However, more research is needed to clarify its specific impact on melanoma and its interaction with immunotherapy. ICD is triggered by cells' inability to adapt to specific stresses. Its core features include the release of DAMPs, which can activate the host's immune system [12–13]. This is particularly significant for immunotherapy of cancers, especially melanoma. LDCD is a mode of cell death characterized by lysosomal membrane permeabilization (LMP) and the release of lysosomal enzymes [34]. In the research of immunotherapy for melanoma, lysosomes are considered crucial anticancer targets. By targeting transformation-dependent alterations within lysosomes to disrupt the structure and function of cancer cells, the efficacy of cancer treatment can be enhanced. Particularly in strategies that activate the immune system to attack cancer cells, LDCD may improve the immune response of the treatment by releasing immunogenic signals [34]. Necroptosis is a form of programmed cell death that operates by producing secondary messengers in the tumor microenvironment, which act on immune cells to send danger signals. This necrotic type of cell death optimizes the activation and antigen presentation of immune cells, thereby enhancing the immune system's recognition and elimination of tumors [35]. Oxeiptosis is a recently discovered cell death pathway that is reactive oxygen species (ROS) sensitive, caspase-independent, and non-inflammatory regulatory. Oxeiptosis offers a new perspective for melanoma research, especially in understanding how cells respond to oxidative stress through non-traditional death pathways [36]. Paraptosis is a non-classical form of programmed cell death characterized by swelling of the endoplasmic reticulum and/or mitochondria and cytoplasmic vacuolization [37–38]. This process can lead to the release of damage-associated molecular patterns, thereby promoting ICD [37–38]. This mode of cell death can induce anti-tumor effects in cancer cells and thus holds potential application value in the immunotherapy of melanoma. In conclusion, these studies provide evidence that these 9 hub ICD signatures play an important role in the ICB treatment of patients with metastatic melanoma.
Based on 9 ICD signatures, we analyzed on-treatment samples of metastatic melanoma across four independent cohorts. We successfully constructed and validated a clinical prediction model to predict the ICB response in patients with metastatic melanoma. Our data indicate that metastatic melanoma patients with higher ICDS are more likely to benefit from ICB therapy. Through ROC analysis, we found that both the training cohort and the validation cohort showed an AUC of around 0.8, demonstrating the effective predictive performance of this model. Additionally, our research indicates that patients with higher ICDS have better prognoses, and ICDS is an independent predictor for patients with metastatic melanoma. Our data suggest that clinicians should assess the ICD characteristics of patients before initiating ICB treatment. ICD plays a significant role in cancer immunotherapy. ICD can induce the production of immunostimulatory factors, such as ATP, IL-1β, type I interferons, CXCL10, and HMGB1 [39]. These molecules can regulate the composition and function of innate and adaptive immune cells within the tumor microenvironment. In vitro studies have shown that various types of antitumor treatments can upregulate stress-induced molecules in tumor cells, making them more susceptible to NK cell-mediated killing [39]. Recent studies have shown that stimulating ICD through nanotechnology and intelligent responsive systems can significantly enhance cancer immunotherapy [40]. For example, Academician Tang Benzhong's team from the Chinese University of Hong Kong has developed a light-triggered self-accelerating nano-platform for multifunctional image-guided combination cancer immunotherapy, bringing great hope for cancer treatment [41]. Additionally, in recent years, many researchers have developed risk scoring models based on ICD signatures [26–28], which means that the expression levels of these genes can be used to predict tumor prognosis. In summary, the study of ICD in the immunotherapy of metastatic melanoma has shown great potential. Not only does it play a crucial role in stimulating anti-tumor immune responses, but it can also predict ICB treatment responses and prognosis more accurately through the expression of ICD signatures, thereby providing a basis for personalized treatment.
Although our research provides valuable insights into the treatment of metastatic melanoma, there are certain limitations. The current study included a relatively small sample size and was retrospective in nature. Future research should involve larger, multi-center, prospective studies to further validate these findings.