Evidence map›Paper›PMID 38787413›Full record

ArticleArchives of dermatological research2024

Development of a biomarker signature associated with anoikis to predict prognosis and immunotherapy response in melanoma.

Zhixuan Wu, Rongrong Zhang, Jingxia Bao, Mengqi Yin, Xiaowu Wang

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Article in Archives of dermatological research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhixuan Wu *The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325015, People's Republic of China.
Rongrong Zhang *The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325015, People's Republic of China.
Jingxia Bao *The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325015, People's Republic of China.
Mengqi YinThe Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, 214200, People's Republic of China. yinmengqi0507@163.com.
Xiaowu WangThe Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325015, People's Republic of China. wangxiaowu_email@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific pattern of programmed cell death associated with tumor regeneration, migration, and metastasis. Nevertheless, limited research has been conducted to investigate the function of anoikis in SKCM. Anoikis-related genes (ARGs) were extracted from Genecards to identify SKCM subtypes and to explore the immune microenvironment between the different subtypes. Prognostic models of SKCM were developed by LASSO COX regression analysis. Subsequently, the predictive value of risk scores in SKCM and the association with immunotherapy were further explored. Finally, the expression of 6 ARGs involved in the model construction was detected by immunohistochemistry and PCR. This study identified 20 ARGs significantly associated with SKCM prognosis and performed disease subtype analysis of samples based on these genes, different subtypes exhibited significantly different clinical features and tumor immune microenvironment (TIME) landscapes. The risk score prognostic model was generated by further screening and identification of the six ARGs. The model exhibited a high degree of sensitivity and specificity to predict the prognosis of individuals with SKCM. These high- and low-risk populations showed different immune statuses and drug sensitivity. Further immunohistochemical and PCR experiments identified significant differential expression of the six ARGs in tumor and normal samples. Anoikis-based features may serve as novel prognostic biomarkers for SKCM and may provide important new insights for survival prediction and individualized treatment development.

Indexed as

AnoikisBiomarkers, TumorImmunotherapyMelanomaSkin NeoplasmsTumor MicroenvironmentCutaneous Malignant MelanomaFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, TumorAnoikisImmune infiltrationImmunotherapy responseMelanomaPrognosis

Identifiers

PMID38787413

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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.