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Integrative landscape analysis of prognostic model biomarkers and immunogenomics of disulfidptosis-related genes in breast cancer based on LASSO and WGCNA analyses.
Liu, Shuyan; Zheng, Yiwen; Li, Shujin; Du, Yaoqiang; Liu, Xiaozhen; Tang, Hongchao; Meng, Xuli; Zheng, Qinghui.
Afiliación
  • Liu S; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
  • Zheng Y; Department of Breast Surgery, General Surgery, Cancer Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310053, Zhejiang, China.
  • Li S; Key Laboratory for Diagnosis and Treatment of Upper Limb Edema and Stasis of Breast Cancer, Hangzhou, 310053, Zhejiang, China.
  • Du Y; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
  • Liu X; Department of Breast Surgery, General Surgery, Cancer Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310053, Zhejiang, China.
  • Tang H; Key Laboratory for Diagnosis and Treatment of Upper Limb Edema and Stasis of Breast Cancer, Hangzhou, 310053, Zhejiang, China.
  • Meng X; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
  • Zheng Q; Department of Breast Surgery, General Surgery, Cancer Center, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310053, Zhejiang, China.
J Cancer Res Clin Oncol ; 149(18): 16851-16867, 2023 Dec.
Article en En | MEDLINE | ID: mdl-37736788
BACKGROUND: Disulfidptosis is a novel type of programmed cell death. However, the value of disulfidptosis-related genes (DRGs) in the prediction of breast cancer prognosis is unclear. METHODS: RNA-seq data of 1231 patients, together with information on patient clinical characteristics and prognosis, were downloaded from TCGA. DRGs were identified between cancerous and non-cancerous tissues. The LASSO algorithm was used to assign half of the samples to the training set. Risk scores were used for construction of a prognostic model for risk stratification and prognosis prediction, and the clinical applicability was examined using a line diagram. The relationships between risk scores, immune cell infiltration, molecular subtypes, and responses to immunotherapy and chemotherapy were examined. RESULTS: We identified and obtained four DRG-related prognostic lncRNAs (AC009097.2, AC133552.5, YTHDF3-AS1, and AC084824.5), which were used for establishing the risk model. Longer survival was associated with low risk. The DRG-associated lncRNAs were found to independently predict patient prognosis. The AUCs under the ROCs for one-, three-, and 5-year survival in the training cohort were 0.720, 0.687, and 0.692, respectively. The model showed that the high-risk patients had reduced overall survival as well as high tumor mutation burdens. Furthermore, high-risk patients showed increased sensitivity to therapeutic drugs, including docetaxel, paclitaxel, and oxaliplatin. CONCLUSION: The risk score model was effective for predicting both prognosis and sensitivity to therapeutic drugs, suggesting its possible usefulness for the management of patients with breast cancer.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / ARN Largo no Codificante Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Revista: J Cancer Res Clin Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / ARN Largo no Codificante Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Revista: J Cancer Res Clin Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Alemania