Novel lipometabolism biomarker for chemotherapy and immunotherapy response in breast cancer.
Novel lipometabolism biomarker for chemotherapy and immunotherapy response in breast cancer.
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DOI：
10.1186/s12885-022-10110-8
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发表时间：
2022-10-01
期刊：
影响因子：
3.8
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中科院分区：
文献类型：
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新的证据表明，异常的脂质代谢会影响癌细胞的侵袭、转移、干性和肿瘤微环境。然而，乳腺癌中与脂肪代谢相关的分子标志物尚未进一步建立。此外，已经进行了大量研究，仅通过 RNA 测序图谱来筛选乳腺癌的预后特征。目前，还没有对多组学数据进行综合分析来提取更好的生物标志物。因此，我们从TCGA数据库下载了乳腺癌的转录组、单核苷酸突变和拷贝数变异数据集，并通过LASSO回归分析构建了12个基因的风险评分。根据中位风险评分将乳腺癌患者分为高风险组和低风险组。高风险组的预后比低风险组差。接下来，我们观察了12个脂质代谢相关基因LMRG的突变频率和拷贝数变异频率，并分析了拷贝数变异和riskScore与OS的关系。同时，ESTIMATE和CIBERSORT算法评估了肿瘤免疫分数和免疫细胞浸润程度。在免疫治疗中，通过TCIA分析和TIDE算法发现高风险患者的疗效更好。此外，还评估了六种常见化疗药物的有效性。最后，估计高危患者对六种化疗药物和六种小分子候选药物敏感。总之，LMRG 可用作从头肿瘤生物标志物，以更好地预测乳腺癌患者的预后以及免疫疗法和化疗的治疗效果。在线版本包含可在 10.1186/s12885-022-10110-8 获取的补充材料。
Emerging proof shows that abnormal lipometabolism affects invasion, metastasis, stemness and tumor microenvironment in carcinoma cells. However, molecular markers related to lipometabolism have not been further established in breast cancer. In addition, numerous studies have been conducted to screen for prognostic features of breast cancer only with RNA sequencing profiles. Currently, there is no comprehensive analysis of multiomics data to extract better biomarkers. Therefore, we have downloaded the transcriptome, single nucleotide mutation and copy number variation dataset for breast cancer from the TCGA database, and constructed a riskScore of twelve genes by LASSO regression analysis. Patients with breast cancer were categorized into high and low risk groups based on the median riskScore. The high-risk group had a worse prognosis than the low-risk group. Next, we have observed the mutated frequencies and the copy number variation frequencies of twelve lipid metabolism related genes LMRGs and analyzed the association of copy number variation and riskScore with OS. Meanwhile, the ESTIMATE and CIBERSORT algorithms assessed tumor immune fraction and degree of immune cell infiltration. In immunotherapy, it is found that high-risk patients have better efficacy in TCIA analysis and the TIDE algorithm. Furthermore, the effectiveness of six common chemotherapy drugs was estimated. At last, high-risk patients were estimated to be sensitive to six chemotherapeutic agents and six small molecule drug candidates. Together, LMRGs could be utilized as a de novo tumor biomarker to anticipate better the prognosis of breast cancer patients and the therapeutic efficacy of immunotherapy and chemotherapy. The online version contains supplementary material available at 10.1186/s12885-022-10110-8.
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影响因子：
7.3
作者：
JENSEN, V;LADEKARL, M;SOERENSEN, FB
通讯作者：
SOERENSEN, FB
影响因子：
14.9
作者：
Kanehisa M;Furumichi M;Sato Y;Ishiguro-Watanabe M;Tanabe M
通讯作者：
Tanabe M
影响因子：
16.1
作者：
Butler LM;Perone Y;Dehairs J;Lupien LE;de Laat V;Talebi A;Loda M;Kinlaw WB;Swinnen JV
通讯作者：
Swinnen JV
影响因子：
--
作者：
Ogiya R;Niikura N;Kumaki N;Yasojima H;Iwasa T;Kanbayashi C;Oshitanai R;Tsuneizumi M;Watanabe KI;Matsui A;Fujisawa T;Saji S;Masuda N;Tokuda Y;Iwata H
通讯作者：
Iwata H
影响因子：
5.8
作者：
Eftekhari, Rahil;Esmaeili, Rezvan;Majidzadeh-A, Keivan
通讯作者：
Majidzadeh-A, Keivan