【佳学基因检测】三阴性乳腺癌坏死性凋亡相关亚型的鉴定及预后模型

肿瘤基因检测需要多长时间香港

根据认识到《Front Immunol》在. 2022 Aug 19;13:964118.发表了一篇题目为《三阴性乳腺癌坏死性凋亡相关亚型的鉴定及预后模型》肿瘤靶向药物治疗基因检测临床研究文章。该研究由Shengyu Pu, Yudong Zhou, Peiling Xie, Xiaoqian Gao, Yang Liu, Yu Ren, Jianjun He, Na Hao 等完成。促进了肿瘤的正确治疗与个性化用药的发展，进一步强调了基因信息检测与分析的重要性。

肿瘤靶向药物及正确治疗临床研究内容关键词：

TCGA,免疫,坏死性凋亡,预后,三阴性乳腺癌

肿瘤靶向治疗基因检测临床应用结果

背景：坏死性凋亡被认为是一种新的程序性坏死细胞死亡形式，与各类肿瘤的转移、进展和预后有关。然而，坏死性凋亡相关基因（NRGs）在三阴性乳腺癌（TNBC）中的潜在作用尚不清楚。方法：我们从癌症基因组图谱（TCGA）数据库和Gene表达式综合 (GEO) 数据库。我们分析了 TNBC 中 67 个 NRGs 的表达、体细胞突变和拷贝数变异 (CNV)，然后观察它们的相互作用、生物学功能和预后价值。通过 Lasso 和 COX 回归分析，构建了预测总生存期（总生存期）的 NRGs 相关风险模型，并验证了其预测能力。贼后，分析了risk_score与免疫细胞浸润、肿瘤微环境（TME）、免疫检查点和肿瘤突变负荷（TMB）、癌症干细胞（CSC）指数、药物敏感性的关系。 结果：共鉴定出67个NRGs在我们的分析中。少数基因（23.81%）检测到体细胞突变，大部分基因出现CNV的高频率，它们之间存在密切的相互作用。这些基因在免疫相关过程中显着富集。生成了一个七基因风险评分，包含 TPSG1、KRT6A、GPR19、EIF4EBP1、TLE1、SLC4A7、ESPN。低危组在 TNBC 中 总生存期 较好，免疫评分较高，TMB 和 CSC 指数较高，常用治疗药物的 IC50 值较低。为了提高临床实用性，我们在 risk_score 中添加了年龄、stage_T 和 stage_N，并构建了一个更全面的列线图来预测 总生存期。经验证，列线图具有良好的预测能力，1年、3年和5年总生存期的AUC值分别为0.847、0.908和0.942。结论：我们的研究确定了NRGs对TNBC免疫和预后的显着影响。这些发现有望为 TNBC 的个性化治疗提供新的策略并提高其临床获益。免疫;坏死性凋亡；预后；三阴性乳腺癌。

肿瘤发生与反复转移国际数据库描述：

Background: Necroptosis is considered to be a new form of programmed necrotic cell death, which is associated with metastasis, progression and prognosis of various types of tumors. However, the potential role of necroptosis-related genes (NRGs) in the triple negative breast cancer (TNBC) is unclear.Methods: We extracted the gene expression and relevant clinicopathological data of TNBC from The Cancer Genome Atlas (TCGA) databases and the Gene Expression Omnibus (GEO) databases. We analyzed the expression, somatic mutation, and copy number variation (CNV) of 67 NRGs in TNBC, and then observed their interaction, biological functions, and prognosis value. By performing Lasso and COX regression analysis, a NRGs-related risk model for predicting overall survival (OS) was constructed and its predictive capabilities were verified. Finally, the relationship between risk_score and immune cell infiltration, tumor microenvironment (TME), immune checkpoint, and tumor mutation burden (TMB), cancer stem cell (CSC) index, and drug sensitivity were analyzed.Results: A total 67 NRGs were identified in our analysis. A small number of genes (23.81%) detected somatic mutation, most genes appeared to have a high frequency of CNV, and there was a close interaction between them. These genes were remarkably enriched in immune-related process. A seven-gene risk_score was generated, containing TPSG1, KRT6A, GPR19, EIF4EBP1, TLE1, SLC4A7, ESPN. The low-risk group has a better OS, higher immune score, TMB and CSC index, and lower IC50 value of common therapeutic agents in TNBC. To improve clinical practicability, we added age, stage_T and stage_N to the risk_score and construct a more comprehensive nomogram for predicting OS. It was verified that nomogram had good predictive capability, the AUC values for 1-, 3-, and 5-year OS were 0.847, 0.908, and 0.942.Conclusion: Our research identified the significant impact of NRGs on immunity and prognosis in TNBC. These findings were expected to provide a new strategy for personalize the treatment of TNBC and improve its clinical benefit.Keywords: TCGA; immune; necroptosis; prognosis; triple negative breast cancer.