A risk model of gene signatures for predicting platinum response and survival in ovarian cancer.
A risk model of gene signatures for predicting platinum response and survival in ovarian cancer.
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DOI：
10.1186/s13048-022-00969-3
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发表时间：
2022-03-31
影响因子：
4
通讯作者：
Zheng Z
中科院分区：
文献类型：
--
作者：
Chen S;Wu Y;Wang S;Wu J;Wu X;Zheng Z
卵巢癌（OC）是女性生殖道中最致命的肿瘤。对铂类化疗耐药的增加是目前OC治疗的主要障碍。稳健和准确的基因表达模型是区分铂类药物治疗反应和评估OC患者预后的重要工具。本研究对230例来自美国癌症基因组图谱（TCGA）OV数据集的样本进行mRNA表达谱、单核苷酸多态性（SNP）和拷贝数变异（CNV）分析，筛选差异表达基因（DEG）。分别采用随机森林算法和LASSO考克斯回归模型，通过R.应用基因表达综合数据库（GEO）作为验证集。通过基因表达、单核苷酸多态性（SNP）和拷贝数变异（CNV）数据的综合分析，筛选出48个差异表达基因（DEG）。构建了一个10基因分类器，其可以精确区分铂敏感性样品，在训练集中AUC为0.971，在GEO数据集中AUC为0.926（GSE 638855）。此外，进一步选择8个最佳基因来构建预后风险模型，其预测与训练队列中的实际生存结果一致（p = 9.613e-05），并在GSE 638855中验证（p = 0.04862）。PNLDC 1、SLC 5A 1和SYNM被鉴定为与铂类药物应答状态和预后相关的枢纽基因，并在复旦大学上海肿瘤中心（FUSCC）队列中得到进一步验证。这些发现揭示了一个特定的风险模型，可以作为有效的生物标志物，以确定患者的铂反应状态和预测OC患者的生存结局。PNLDC 1、SLC 5A 1和SYNM是中枢基因，可作为OC治疗的潜在生物标志物。在线版本包含补充材料，可通过10.1186/s13048-022-00969-3获得。
Ovarian cancer (OC) is the deadliest tumor in the female reproductive tract. And increased resistance to platinum-based chemotherapy represents the major obstacle in the treatment of OC currently. Robust and accurate gene expression models are crucial tools in distinguishing platinum therapy response and evaluating the prognosis of OC patients. In this study, 230 samples from The Cancer Genome Atlas (TCGA) OV dataset were subjected to mRNA expression profiling, single nucleotide polymorphism (SNP), and copy number variation (CNV) analysis comprehensively to screen out the differentially expressed genes (DEGs). An SVM classifier and a prognostic model were constructed using the Random Forest algorithm and LASSO Cox regression model respectively via R. The Gene Expression Omnibus (GEO) database was applied as the validation set. Forty-eight differentially expressed genes (DEGs) were figured out through integrated analysis of gene expression, single nucleotide polymorphism (SNP), and copy number variation (CNV) data. A 10-gene classifier was constructed which could discriminate platinum-sensitive samples precisely with an AUC of 0.971 in the training set and of 0.926 in the GEO dataset (GSE638855). In addition, 8 optimal genes were further selected to construct the prognostic risk model whose predictions were consistent with the actual survival outcomes in the training cohort (p = 9.613e-05) and validated in GSE638855 (p = 0.04862). PNLDC1, SLC5A1, and SYNM were then identified as hub genes that were associated with both platinum response status and prognosis, which was further validated by the Fudan University Shanghai cancer center (FUSCC) cohort. These findings reveal a specific risk model that could serve as effective biomarkers to identify patients’ platinum response status and predict survival outcomes for OC patients. PNLDC1, SLC5A1, and SYNM are the hub genes that may serve as potential biomarkers in OC treatment. The online version contains supplementary material available at 10.1186/s13048-022-00969-3.
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DOI：
10.1186/1756-9966-29-135
发表时间：
2010-10-15
期刊：
Journal of experimental & clinical cancer research : CR
影响因子：
--
作者：
Ehira N;Oshiumi H;Matsumoto M;Kondo T;Asaka M;Seya T
通讯作者：
Seya T
卵巢癌糖酵解相关预后基因特征的建立及其与肿瘤微环境免疫浸润的关系
影响因子：
7.4
作者：
Bi J;Bi F;Pan X;Yang Q
通讯作者：
Yang Q
一组新颖的生物标志物，可区分小型分化良好的 HCC 与发育不良结节及结果值
影响因子：
3.8
作者：
Jin GZ;Dong H;Yu WL;Li Y;Lu XY;Yu H;Xian ZH;Dong W;Liu YK;Cong WM;Wu MC
通讯作者：
Wu MC
影响因子：
50.5
作者：
Eisenhauer, E. A.
通讯作者：
Eisenhauer, E. A.
影响因子：
8.4
作者：
BOLIS, G;SCARFONE, G;PARAZZINI, F
通讯作者：
PARAZZINI, F