Evidence map›Paper›PMID 39832036›Full record

ArticleDiscover oncology2025

Inhibition of programmed cell death by melanoma cell subpopulations reveals mechanisms of melanoma metastasis and potential therapeutic targets.

Yuepeng An, Fu Zhao, Hongling Jia, Siyu Meng, Ziwei Zhang, Shuxiao Li, Jiusi Zhao

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yuepeng An *The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, 150040, China.
Fu Zhao *Shandong University of Traditional Chinese Medicine, Jinan, 250014, China.
Hongling Jia *The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, 250014, Shandong, China.
Siyu MengNortheast International Hospital, Shenyang, 110180, China.
Ziwei Zhang *Department of Plastic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China. andreavaimukas@sjtu.edu.cn.
Shuxiao Li *Department of Burns and Plastic Reconstructive Surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000, Guangxi Province, China. 977817863@qq.com.
Jiusi Zhao *The First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, 150040, China. zjs_0807999@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melanoma is an aggressive type of skin cancer that arises from melanocytes, the cells responsible for producing skin pigment. In contrast to non-melanoma skin cancers like basal cell carcinoma and squamous cell carcinoma, melanoma is more invasive. Melanoma was distinguished by its rapid progression, high metastatic potential, and significant resistance to conventional therapies. Although it accounted for a small proportion of skin cancer cases, melanoma accounts for the majority of deaths caused by skin cancer due to its ability to invade deep tissues, adapt to diverse microenvironments, and evade immune responses. These unique features highlighted the challenges of treating melanoma and underscored the importance of advanced tools, such as single-cell sequencing, to unravel its biology and develop personalized therapeutic strategies. Thus, we conducted a single-cell analysis of the cellular composition within melanoma tumor tissues and further subdivided melanoma cells into subpopulations. Through analyzing metabolic pathways, stemness genes, and transcription factors (TFs) among cells in different phases (G1, G2/M, and S) as well as between primary and metastatic foci cells, we investigated the specific mechanisms underlying melanoma metastasis. We also revisited the cellular stemness and temporal trajectories of melanoma cell subpopulations, identifying the core subpopulation as C0 SOD3 + Melanoma cells. Our findings revealed a close relationship between the pivotal C0 SOD3 + Melanoma cells subpopulation and oxidative pathways in metastatic tumor tissues. Additionally, we analyzed prognostically relevant differentially expressed genes (DEGs) within the C0 SOD3 + Melanoma cells subpopulation and built a predictive model associated with melanoma outcomes. We selected the gene IGF1 with the highest coefficient (coef) value for further analysis, and experimentally validated its essential function in the proliferation and invasive metastasis of melanoma. In immune infiltration analysis, we discovered the critical roles played by M1/M2 macrophages in melanoma progression and immune evasion. Furthermore, the development and progression of malignant melanoma were closely associated with various forms of programmed cell death (PCD), including apoptosis, autophagic cell death, ferroptosis, and pyroptosis. Melanoma cells often resisted cell death mechanisms, maintaining their growth by inhibiting apoptosis and evading autophagic cell death. Meanwhile, the induction of ferroptosis and pyroptosis was thought to trigger immune responses that helped suppress melanoma dissemination. A deeper understanding of the relationship between melanoma and PCD pathways provided a critical foundation for developing novel targeted therapies, with the potential to enhance melanoma treatment efficacy. These findings contributed to the development of novel prognostic models for melanoma and shed light on research directions concerning melanoma metastasis mechanisms and therapeutic targets.

Indexed as

MacrophagesMelanomaOxidative phosphorylationProgrammed cell deathSingle-cell RNA sequencingTumor metastasis

Identifiers

PMID39832036
PMCPMC11747064

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.