基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Breast Cancer Plasticity after Chemotherapy Highlights the Need for Re-Evaluation of Subtyping in Residual Cancer and Metastatic Tissues.
Breast Cancer Plasticity after Chemotherapy Highlights the Need for Re-Evaluation of Subtyping in Residual Cancer and Metastatic Tissues.
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本研究提出一种新方法,用于识别可预测适合接受新辅助治疗的三阴性乳腺癌(TNBC)患者预后的生物标志物。研究采用 TNBC 患者队列的生存和 RNA 测序数据,发现 276 个基因的表达与患者生存相关。随后根据有无 Wnt(Wingless/Integrated)通路和间质(Mes)标志物(Wnt/Mes)将患者分为两大类。Wnt/Mes 相关基因表达较低的患者结局良好,随访期间无死亡;Wnt/Mes 基因高表达患者在 19 个月内死亡率较高,达到 50%。已鉴定的基因列表可进一步验证,且可能用于制定适合新辅助治疗 TNBC 患者的治疗方案,为开发更有效的 TNBC 治疗提供有价值的见解。数据还显示,化疗前后基因表达谱显著不同,多数肿瘤转变为更具间质/干细胞样特征的表达谱。为验证这一观察,我们使用基因表达数据,对治疗前和治疗后的乳腺癌肿瘤进行微阵列预测分析 50(PAM50)分子分型的计算机分析。
结果显示,药物干预和转移后,部分肿瘤会转变为其他亚型,导致治疗效果减弱。这凸显了对化疗后复发或转移的患者重新评估、重点进行分子分型的必要性。根据重新细分的亚型制定个体化治疗策略,对于优化患者疗效至关重要。
This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes).
Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC.
Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data.
Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals.
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