Page 17 - EJMO-9-1

Eurasian Journal of Medicine and
Oncology
Single-cell RNA-seq in malignant skin tumors

to the early cellular response to therapy. Co-activating and complex, posing challenges in bioinformatics for
P2RX7 expression may enhance treatment efficacy and efficiently and accurately extracting key information while
delay resistance development. Another study using single- eliminating interference. In addition, cells are dynamic
cell technology discovered that only a small fraction of entities; however, most current single-cell sequencing
melanoma cells exhibit effective activation of receptor technologies capture only a snapshot of the cell state at
tyrosine kinase and extracellular signal-regulated kinase, a specific moment. Therefore, there is a need to develop
contributing to persistence. This insight provides a non- and explore technologies and algorithms that can capture
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heritable mechanism for understanding the development the dynamic changes of cells over time and across spatial
of resistance to BRAF inhibitors combined with MEK contexts.
inhibitors treatment. The emergence of resistance is The rapid development of single-cell sequencing
multifactorial and complex. By leveraging single-cell technology offers vast potential in cancer research.
technology, researchers can gain a more comprehensive Integrating single-cell sequencing with other omics
understanding of the mechanisms underlying CM technologies, such as single-cell proteomics, epigenomics,
treatment resistance, providing robust support for and spatial transcriptomics, enables researchers to gain
personalized treatment approaches and the development a more comprehensive understanding of tumor biology.
of new therapeutic strategies (Table 3). Spatial transcriptomics (ST) is a technology that studies

6. Challenges and future prospects the expression and spatial relationships of specific genes
within tissues or cells, helping to comprehend the spatial
Single-cell sequencing has significantly advanced the heterogeneity of cell subtypes and gene expression
study of skin tumors, unveiling various aspects such as across different regions of tissues. Despite its relatively
TME characteristics, mechanisms of disease progression, short existence, ST plays a significant role in single-cell
identification of new therapeutic targets, and changes research. 85,86 Wang et al. found that most methods achieve
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in the TME related to treatment efficacy. 83,84 However, cell type decomposition by combining the expression of
challenges persist due to technological limitations and data cell type-specific genes, with the accuracy of these genes
complexity. First, the efficiency of single-cell isolation and relying on the consistency between scRNA-seq and ST
capture is crucial for accurate research outcomes. Changes data. An instance-based transfer learning framework
in cell adaptability and integrity during the isolation that can reduce discrepancies between scRNA-seq and
process, as well as cell omissions during capture, can lead to ST data was developed, allowing for accurate matching
misleading results. In addition, biases in selecting specific of cell type-specific gene expression. In addition, Yang
cell types, experimental errors introduced during sample et al. integrated single-cell transcriptomics and spatial
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processing, and inherent interferences in the technology transcriptomics to construct a high-resolution single-
may affect subsequent analyses. On the other hand, the cell atlas of renal cell carcinoma, dissecting its metabolic
data generated by single-cell sequencing are often massive heterogeneity across spatial locations. The Python package

Table 3. Key studies associated with the use of single‑cell RNA sequencing in cutaneous melanoma
Cancer Cell origin Properties Authors Key findings
type
CM Melanocytes High invasiveness and Deng et al. 67 The exhaustion-associated subgroup 2 represented the terminal state of CD8
metastatic potential T-cell differentiation, leading to poor prognosis, marker genes PMEL, TYRP1, and
EDNRB suggest potential novel therapeutic targets.
Lian et al. 69 CEMIP and NKD1 fibroblast clusters in CM are closely associated with immune
+
+
therapy resistance.
Kim et al. 73 Single-cell sequencing analysis shows that CD244 significantly influences
phagocytosis, antigen presentation, and autophagy, suggesting CD244 deficient
macrophages could be an effective immunotherapy approach.
Shi et al. 75 Patients with the ‘Immune-Hot/Active’ phenotype, characterized by more
non-regulated B cells, cytotoxic CD8 T-cells, and lower mixed states CD8 T-cells,
tend to respond better to anti-PD1 treatment.
Capparelli et al. 79 Revealed a cross-resistance relationship between the SOX10-deficient cell subgroup
and targeted checkpoint inhibitors and immune checkpoint inhibitors, emphasizing
the significance of treating this subgroup.
Abbreviation: CM: Cutaneous melanoma.

Volume 9 Issue 1 (2025) 9 doi: 10.36922/ejmo.5809