Table_3：一种新型m6A相关基因签名可影响肺腺癌免疫状态并预测预后和药物敏感性

数据集获取（Figshare）

• 源站标题：Table_3_A Novel M6A-Related Genes Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma.xls
• DOI：10.3389/fimmu.2022.923533.s004
• 发布日期：2022-07-04
• 文件数：1 个
• 文件总体积：7.43 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_3_A_Novel_M6A-Related_Genes_Signature_Can_Impact_the_Immune_Status_and_Predict_the_Prognosis_and_Drug_Sensitivity_of_Lung_Adenocarcinoma_xls/20220828

命令行下载

curl -L -o "Table_3_A Novel M6A-Related Genes Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma.xls" "https://ndownloader.figshare.com/files/36141789"

文件清单

• Table_3_A Novel M6A-Related Genes Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma.xls（7.43 KB）

文件总体积 7.43 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Lung adenocarcinoma (LUAD) is a primary cause of cancer-related death around the world and has a poor outcome and high incidence. Treatment options are, however, restricted. One of the most critical factors in cancer and metastasis is the N6-methyladenine (m6A) alteration on RNA. This modification could alter gene expression and even function at numerous levels, such as the stability, translocation and translation of RNA splicing. This study aimed to construct an m6A-related genes signature to accurately predict the prognosis of LUAD patients. From TCGA datasets, the LUAD patient data and m6A-related genes were retrieved. LUAD patients’ mutational features and differentially expressed genes (DEGs) were investigated. An univariate and LASSO model with m6A-related genes were constructed for the prediction of outcomes in LUAD. It was possible to develop a prognostic nomogram that could quantitatively predict LUAD patients’ overall survival chances at 1, 3, and 5 years. Research into biological processes and cell pathways was carried out using GSEA. This study found six m6A-related DEGs in LUAD patients, and three of these DEGs(HNRNPC, IGFBP3 and IGF2BP1) were linked to the clinical outcomes of LUAD patients. We found that the overall survival rate for all LUAD patients with high-risk subgroup was considerably lower. According to ROC curves, the prognostic signature demonstrated a high degree of accuracy in predicting future outcomes. In addition, we created a novel nomogram achieved great accuracy with this one as well. The researchers also found that the novel signature might favorably modulate the immune response, and high-risk scores samples were more susceptible to numerous chemotherapeutic medicines. Overall, we developed a m6A-related gene prognostic signature that effectively predicted outcomes of LUAD patients and gave an immunological perspective for creating customized therapeutics.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2022.923533.s004（source: https://frontiersin.figshare.com/articles/dataset/Table_3_A_Novel_M6A-Related_Genes_Signature_Can_Impact_the_Immune_Status_and_Predict_the_Prognosis_and_Drug_Sensitivity_of_Lung_Adenocarcinoma_xls/20220828）。