Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: A large-scale pan-cancer cohort, machine learning and experimental study: [RETRACTED]
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Background: Lymph node metastasis (LNM) is an independent prognostic factor in numerous types of cancer. Therefore, a LNM-related gene-based nomogram may precisely predict survival and drug sensitivity, and reveal the mechanism underlying LNM. Materials and Methods: Gene sequencing profiles of pan-cancer data (33 cancer types) were acquired from The Cancer Genome Atlas UCSC Xena database. Patients were classified into primary (N = 10,071) and testing (N = 5,036) cohorts. The lymph node score (LNscore) was established via single-cell RNA sequencing, whole-transcriptome sequencing, machine learning, and Cox regression analyses. A novel prognosis model, formulated by incorporating the LNscore and clinical characteristics, was evaluated using the concordance index, calibration curve, and decision curve analysis. Moreover, patients were assigned into high- and low-risk groups according to the median LNscore. We investigated these two groups for survival prognosis, functional enrichment, immune infiltration, and drug sensitivity. In addition, we silenced and overexpressed insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). We also analyzed the behavior of breast cancer (BRCA) cells regarding lymphatic metastasis and lymphangiogenesis in vitro. IGF2BP2 stimulated the proliferation of BRCA cells via 5-Ethynyl-2’-deoxyuridine and Cell Counting Kit-8 experiments. Results: A LNM-related set of 12 genes was identified and utilized to determine the LNscore. The concordance-index of both cohorts in the LNscore-based model was >0.7. The immune landscape revealed that the sensitivity to immunotherapy might be better in the high-risk group versus the low-risk group. In addition, we discovered that IGF2BP2 was overexpressed in BRCA tissues and significantly associated with poor survival. Functional analysis indicated that IGF2BP2 promoted BRCA cell migration and proliferation. Additionally, IGF2BP2 accelerated lymphatic metastasis and lymphangiogenesis in vivo. Conclusions: A novel LNscore-based model was established via comprehensive analysis of LNM-related genes. This model can accurately predict patient survival and drug sensitivity, and reveal the mechanism of LNM in the pan-cancer setting.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: A large-scale pan-cancer cohort, machine learning and experimental study: [RETRACTED]
- Date Crossref
- 19/02/2024
- Éditeur
- Ovid Technologies (Wolters Kluwer Health)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Guangdong Academy of Medical Sciences pays non établi dans la noticeÉtablissement de santé
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Guangdong Provincial People's Hospital pays non établi dans la noticeÉtablissement de santé
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Southern Medical University Department of Breast Cancer pays non établi dans la noticeUniversité ou école supérieure
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South China University of Technology pays non établi dans la noticeUniversité ou école supérieure
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Chinese Academy of Medical Sciences & Peking Union Medical College Plastic Surgery Hospital pays non établi dans la noticeUniversité ou école supérieure
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Peking Union Medical College Hospital pays non établi dans la noticeÉtablissement de santé
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Nanchang University Department of Urology pays non établi dans la noticeUniversité ou école supérieure
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Third Affiliated Hospital of Nanchang University pays non établi dans la noticeÉtablissement de santé
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First Affiliated Hospital of Nanchang University pays non établi dans la noticeÉtablissement de santé
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School of Medicine pays non établi dans la noticeUniversité ou école supérieure
Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital et Department of Breast Cancer — Southern Medical University, avec 7 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.