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Precision treatment exploration of breast cancer based on heterogeneity analysis of lncRNAs at the single-cell level

机译:基于单细胞水平LNCRNA异质性分析的乳腺癌精确治疗探讨

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Breast cancer (BC) is a complex disease with high heterogeneity, which often leads to great differences in treatment results. Current common molecular typing method is PAM50, which shows positive results for precision medicine; however, room for improvement still remains because of the different prognoses of subtypes. Therefore, in this article, we used lncRNAs, which are more tissue-specific and developmental stage-specific than other RNAs, as typing markers and combined single-cell expression profiles to retype BC, to provide a new method for BC classification and explore new precise therapeutic strategies based on this method. Based on lncRNA expression profiles of 317 single cells from 11?BC patients, SC3 was used to retype BC, and differential expression analysis and enrichment analysis were performed to identify biological characteristics of new subtypes. The results were validated for survival analysis using data from TCGA. Then, the downstream regulatory genes of lncRNA markers of each subtype were searched by expression correlation analysis, and these genes were used as targets to screen therapeutic drugs, thus proposing new precision treatment strategies according to the different subtype compositions of patients. Seven lncRNA subtypes and their specific biological characteristics are obtained. Then, 57 targets and 210 drugs of 7 subtypes were acquired. New precision medicine strategies were proposed according to the different compositions of patient subtypes. For patients with different subtype compositions, we propose a strategy to select different drugs for different patients, which means using drugs targeting multi subtype or combinations of drugs targeting a single subtype to simultaneously kill different cancer cells by personalized treatment, thus reducing the possibility of drug resistance and even recurrence.
机译:乳腺癌(BC)是一种具有高异质性的复杂疾病,其往往导致治疗结果的差异很大。目前的常见分子键入方法是PAM50,其显示精确药物的阳性结果;然而,由于亚型的不同预测,改善房间仍然存在。因此,在本文中,我们使用了LNCRNA,其比其他RNA更多的组织特异性和发育阶段特异性,作为键入标记和组合的单细胞表达谱来替换BC,为BC分类提供了一种新方法基于此方法的精确治疗策略。基于来自11μlBC患者的317个单细胞的LNCRNA表达谱,SC3用于替换BC,进行差异表达分析和富集分析以鉴定新亚型的生物学特性。使用来自TCGA的数据验证的结果用于存活分析。然后,通过表达相关性分析搜索每种亚型的LNCRNA标记的下游调节基因,并且这些基因被用作筛选治疗药物的靶标,从而根据患者的不同亚型组成提出新的精密处理策略。获得七种LNCRNA亚型及其特定的生物学特性。然后,获得了57个靶标和210种亚型药物。根据患者亚型的不同组成提出了新的精密药物策略。对于不同亚型组合物的患者,我们提出了一种为不同患者选择不同药物的策略,这意味着使用靶向多亚型的药物或靶向单个亚型的药物组合,通过个性化治疗同时杀死不同的癌细胞,从而减少药物的可能性抗性甚至复发。

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