ArticleCancer medicine2021
Predicting the immune landscape of invasive breast carcinoma based on the novel signature of immune-related lncRNA.
Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The Clinical Utility of lncRNAs and Their Application as Molecular Biomarkers in Breast Cancer.International journal of molecular sciences · 2023Review
- The current advances of lncRNAs in breast cancer immunobiology research.Frontiers in immunology · 2023Review
- Establishment and Validation of a Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Lower-Grade Glioma.Frontiers in neurology · 2022Article
- Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer.Frontiers in immunology · 2022Article
- Predicting the immune landscape of invasive breast carcinoma based on the novel signature of immune-related lncRNA.Cancer medicine · 2021Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundThe composition of the population of immune-related long non-coding ribonucleic acid (irlncRNA) generates a signature, irrespective of expression level, with potential value in predicting the survival status of patients with invasive breast carcinoma.
methodsThe current study uses univariate analysis to identify differentially expressed irlncRNA (DEirlncRNA) pairs from RNA-Seq data from The Cancer Genome Atlas (TCGA). 36 pairs of DEirlncRNA pairs were identified. Using various algorithms to construct a model, we have compared the area under the curve and calculated the 5-year curve of Akaike information criterion (AIC) values, which allows determination of the threshold indicating the maximum value for differentiation. Through cut-off point to establish the optimal model for distinguishing high-risk or low-risk groups among breast cancer patients. We assigned individual patients with invasive breast cancer to either high risk or low risk groups depending on the cut-off point, re-evaluated the tumor immune cell infiltration, the effectiveness of chemotherapy, immunosuppressive biomarkers, and immunotherapy.
resultsAfter re-assessing patients according to the threshold, we demonstrated an effective means of distinguish the severity of the disease, and identified patients with different clinicopathological characteristics, specific tumor immune infiltration states, high sensitivity to chemotherapy,wellpredicted response to immunotherapy and thus a more favorable survival outcome.
conclusionsThe current study presents novel findings regarding the use of irlncRNA without the need to predict precise expression levels in the prognosis of breast cancer patients and to indicate their suitability for anti-tumor immunotherapy.
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