Page 104 - EJMO-9-3

Eurasian Journal of
Medicine and Oncology Novel senescence-based melanoma risk model

the model, an additional SKCM dataset (GSE19234) immune surveillance of melanoma cells. The TCGA
36
was obtained from the GEO database, consisting of database, which includes high-throughput omics data and
35
44 samples. Risk scores were calculated across these samples a wealth of clinical information for cancers such as SKCM,
using the same methodology, and survival outcomes were has been widely used for identifying cancer prognostic
compared between groups with different risk scores. The factors. 19,37
low-risk group demonstrated a significantly better survival A comprehensive analysis of senescence-related
rate compared to the high-risk group, further validating genes revealed that these genes could effectively stratify
the robustness of the risk model (Figure 4E). Moreover, SKCM patients into two distinct subtypes with markedly
increased levels of activated NK cells, anti-tumor M1 varied survival outcomes. Notably, these subtypes were
macrophages, and CD8 T cells were detected in the low- characterized by their unique immune microenvironment
+
risk group, though activated NK cells showed no significant profiles. The immunoactivated subtype, which exhibited
difference between the two groups. These findings further higher expression of cytokines and elevated levels of
support the association between an immune-activated activated immune cells such as NK cells, CD4 memory
+
microenvironment and improved survival in SKCM T cells, and CD8 T cells, demonstrated significantly
+
patients (Figure 4F). In summary, validation of the risk prolonged survival compared to the immune-suppressive
model using both the internal validation set and external subtype. Several studies have shown that activation status
datasets (GSE65904 and GSE19234) demonstrates its of CD8 T cells, including recruitment, proliferation, and
+
robustness and clinical relevance. The association between effector functions, is essential for enhancing the efficacy of
the low-risk group and a favorable immune profile, current therapies for melanoma. In addition, chimeric
4,38
characterized by higher levels of stimulated NK cells, antigen receptors (CAR)-NK cell immunotherapies
CD8 T cells, and M1 macrophages, reinforces the role of are increasingly regarded as a promising alternative,
+
an immunoactivated TME in promoting favorable clinical offering a more favorable safety profile compared to
outcomes. These results offer strong support for the utility CAR-T cell immunotherapies. Furthermore, genes
9
of the risk model in stratifying SKCM patients based on related to key immune pathways, including the IFNs
prognosis and suggest that immune activation plays a key response, inflammatory response, and IL6/JAK/STAT3
role in improving survival. signaling, were significantly upregulated in Cluster2.

4. Discussion These findings emphasize the essential role of the immune
microenvironment in determining patient prognosis and
Here, the prognostic potential of senescence-related genes in suggest that immune activation may play a crucial role in
SKCM was explored, and a robust risk model was developed controlling melanoma progression.
based on these genes. Melanoma, one of the most lethal
types of skin cancer, is marked by significant heterogeneity A previous study conducted a risk model based
in patient survival outcomes. Therefore, identifying on senescence-related genes in SKCM and found that
molecular markers that can predict prognosis is essential the low-risk group exhibited an immune-suppressive
for improving individualized treatment approaches. phenotype, which was significantly associated with poor
39
Senescence-related genes, which are engaged in diverse survival outcomes. However, another study indicated
+
biological processes, including cellular senescence, DNA that NK cells, CD8 T cells, and DCs were more likely to
repair, and immune modulation, have gained attention accumulate in the low senescence-risk group, implying an
40
for their potential role in cancer progression and patient immunoactivated microenvironment. In this study, key
prognosis. Cellular senescence is closely linked to cancer genes were selected from a curated set of 780 senescence-
25-27
progression. While senescence is commonly regarded related genes derived from three studies to construct
as a hallmark of cancer, recent studies have revealed that the risk model, further explaining the association between
the relationship between cellular senescence and cancer cellular senescence and patient survival.
is far more complex. For instance, senescent cancer cells Lasso regression was used to refine twenty-five genes,
secrete IFNs, which upregulate the expression of major followed by multivariate Cox regression to develop the
histocompatibility complex (MHC) Class I molecules on risk model. This model was used to calculate a risk score
the surface of tumor cells. This increased expression of for each patient, which was then validated both internally
MHC I improves the capacity of dendritic cells (DCs) to and externally. The risk model demonstrated strong
deliver tumor antigens to CD8 T cells, which are essential performance in stratifying patients into high-risk and low-
+
for the capacity of the immune system to distinguish and risk groups, with patients in the low-risk group exhibiting
eliminate malignant cells. Furthermore, IFNs gamma significantly improved survival outcomes. In addition,
24
and TNF-induced senescent cancer cells help maintain the Cluster 2 subtype, which exhibited better survival

Volume 9 Issue 3 (2025) 96 doi: 10.36922/ejmo.8574