NSCLC肿瘤基因组分析数据集

数据集获取（Figshare）

• 源站标题：Table 3_Genomic profiling of NSCLC tumors with the TruSight oncology 500 assay provides broad coverage of clinically actionable genomic alterations and detection of known and novel associations between genomic alterations, TMB, and PD-L1.xlsx
• DOI：10.3389/fonc.2024.1473327.s004
• 发布日期：2024-11-27
• 文件数：1 个
• 文件总体积：21.00 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_3_Genomic_profiling_of_NSCLC_tumors_with_the_TruSight_oncology_500_assay_provides_broad_coverage_of_clinically_actionable_genomic_alterations_and_detection_of_known_and_novel_associations_between_genomic_alterations_TMB_and_PD-L1_xlsx/27915687

命令行下载

curl -L -o "Table 3_Genomic profiling of NSCLC tumors with the TruSight oncology 500 assay provides broad coverage of clinically actionable genomic alterations an.xlsx" "https://ndownloader.figshare.com/files/50830806"

文件清单

• Table 3_Genomic profiling of NSCLC tumors with the TruSight oncology 500 assay provides broad coverage of clinically actionable genomic alterations an.xlsx（21.00 KB）

文件总体积 21.00 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

IntroductionMatching patients to an effective targeted therapy or immunotherapy is a challenge for advanced and metastatic non-small cell lung cancer (NSCLC), especially when relying on assays that test one marker at a time. Unlike traditional single marker tests, comprehensive genomic profiling (CGP) can simultaneously assess NSCLC tumors for hundreds of genomic biomarkers and markers for immunotherapy response, leading to quicker and more precise matches to therapeutics.
MethodsIn this study, we performed CGP on 7,606 patients with advanced or metastatic NSCLC using the Illumina TruSight Oncology 500 (TSO 500) CGP assay to show its coverage and utility in detecting known and novel features of NSCLC.
ResultsTesting revealed distinct genomic profiles of lung adenocarcinoma and squamous cell carcinomas and detected variants with a current targeted therapy or clinical trial in >72% of patient tumors. Known associations between genomic alterations and immunotherapy markers were observed including significantly lower TMB levels in tumors with therapy-associated alterations and significantly higher PD-L1 levels in tumors with ALK, MET, BRAF, or ROS1 driver mutations. Co-occurrence analysis followed by network analysis with gene module detection revealed known and novel co-occurrences between genomic alterations. Further, certain modules of genes with co-occurring genomic alterations had dose-dependent relationships with histology and increasing or decreasing levels of PD-L1 and TMB, suggesting a complex relationship between PD-L1, TMB, and genomic alterations in these gene modules.
DiscussionThis study is the largest clinical study to date utilizing the TSO 500. It provides an opportunity to further characterize the landscape of NSCLC using this newer technology and show its clinical utility in detecting known and novel facets of NSCLC to inform treatment decision-making.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fonc.2024.1473327.s004（source: https://frontiersin.figshare.com/articles/dataset/Table_3_Genomic_profiling_of_NSCLC_tumors_with_the_TruSight_oncology_500_assay_provides_broad_coverage_of_clinically_actionable_genomic_alterations_and_detection_of_known_and_novel_associations_between_genomic_alterations_TMB_and_PD-L1_xlsx/27915687）。