Construction of a novel prognostic model based on lncRNAs-related to DNA damage repair for predicting the prognosis of clear cell renal cell carcinoma DOI Creative Commons
Peng Chen, Jian Li, Renli Tian

и другие.

Annals of Medicine, Год журнала: 2025, Номер 57(1)

Опубликована: Апрель 2, 2025

CcRCC has the characteristics of high aggression, metastasis, mortality, wide tumour heterogeneity and variable clinical course. The purpose this study was to explore potential value lncRNAs-related DNA damage repair (DDR) in predicting prognosis ccRCC by construction verification a novel prognostic model. RNA-seq data were downloaded from public databases. Subsequently, Pearson correlation analysis differential expression performed identify DElncRNAs-related DDR. Then, through univariate Cox LASSO analysis, DDR associated with screened for risk score In addition, functional annotation, mutation burden, immune drug sensitivity analyses based on assess patients different groups. Based four best selected. model these DElncRNAs constructed LASSO. Multivariate showed that age independent factors (p < 0.05). Functional enrichment DDR-related biological processes mainly enriched group. highly mutated genes low groups same (VHL, PBRM1 TTN), but they also had their own unique genes. significantly 0.05) positively correlated infiltration degree CD8 T cells evaluated six algorithms. it found sensitivities drugs Etoposide, Imatinib, Sorafenib, Bosutinib Sunitinib. A satisfactory accuracy survival patients.

Язык: Английский

Construction of a novel prognostic model based on lncRNAs-related to DNA damage repair for predicting the prognosis of clear cell renal cell carcinoma DOI Creative Commons
Peng Chen, Jian Li, Renli Tian

и другие.

Annals of Medicine, Год журнала: 2025, Номер 57(1)

Опубликована: Апрель 2, 2025

CcRCC has the characteristics of high aggression, metastasis, mortality, wide tumour heterogeneity and variable clinical course. The purpose this study was to explore potential value lncRNAs-related DNA damage repair (DDR) in predicting prognosis ccRCC by construction verification a novel prognostic model. RNA-seq data were downloaded from public databases. Subsequently, Pearson correlation analysis differential expression performed identify DElncRNAs-related DDR. Then, through univariate Cox LASSO analysis, DDR associated with screened for risk score In addition, functional annotation, mutation burden, immune drug sensitivity analyses based on assess patients different groups. Based four best selected. model these DElncRNAs constructed LASSO. Multivariate showed that age independent factors (p < 0.05). Functional enrichment DDR-related biological processes mainly enriched group. highly mutated genes low groups same (VHL, PBRM1 TTN), but they also had their own unique genes. significantly 0.05) positively correlated infiltration degree CD8 T cells evaluated six algorithms. it found sensitivities drugs Etoposide, Imatinib, Sorafenib, Bosutinib Sunitinib. A satisfactory accuracy survival patients.

Язык: Английский

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