抗PD-(L)1免疫治疗非小细胞肺癌生物标志物研究数据表4

数据集获取（Figshare）

• 源站标题：Table 4_Biomarkers of success of anti-PD-(L)1 immunotherapy for non-small cell lung cancer derived from RNA- and whole-exome sequencing: results of a prospective observational study on a cohort of 85 patients.xlsx
• DOI：10.3389/fimmu.2024.1493877.s001
• 发布日期：2024-12-11
• 文件数：1 个
• 文件总体积：6.16 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_4_Biomarkers_of_success_of_anti-PD-_L_1_immunotherapy_for_non-small_cell_lung_cancer_derived_from_RNA-_and_whole-exome_sequencing_results_of_a_prospective_observational_study_on_a_cohort_of_85_patients_xlsx/28011974

命令行下载

curl -L -o "Table 4_Biomarkers of success of anti-PD-(L)1 immunotherapy for non-small cell lung cancer derived from RNA- and whole-exome sequencing: results of a .xlsx" "https://ndownloader.figshare.com/files/51111731"

文件清单

• Table 4_Biomarkers of success of anti-PD-(L)1 immunotherapy for non-small cell lung cancer derived from RNA- and whole-exome sequencing: results of a .xlsx（6.16 KB）

文件总体积 6.16 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

BackgroundImmune checkpoint inhibitors (ICIs) treatment have shown high efficacy for about 15 cancer types. However, this therapy is only effective in 20-30% of cancer patients. Thus, the precise biomarkers of ICI response are an urgent need.
MethodsWe conducted a prospective observational study of the prognostic potential ofseveral existing and putative biomarkers of response to immunotherapy in acohort of 85 patients with lung cancer (LC) receiving PD-1 or PD-L1 targeted ICIs. Tumor biosamples were obtained prior to ICI treatment and profiled by whole exome and RNA sequencing. The entire 403 putative biomarkers were screened, including tumor mutation burden (TMB) and number of cancer neoantigens, 131 specific HLA alleles, homozygous state of 11 HLA alleles and their superfamilies; four gene mutation biomarkers, expression of 45 immune checkpoint genes and closely related genes, and three previously published diagnostic gene signatures; for the first time, activation levels of 188 molecular pathways containing immune checkpoint genes and activation levels of 19 pathways algorithmically generated using a human interactome model centered around immune checkpoint genes. Treatment outcomes and/or progression-free survival (PFS) times were available for 61 of 85 patients with LC, including 24 patients with adenocarcinoma and 27 patients with squamous cell LC, whose samples were further analyzed. For the rest 24 patients, both treatment outcomes and PFS data could not be collected. Of these, 54 patients were treated with PD1-specific and 7 patients with PD-L1-specific ICIs. We evaluated the potential of biomarkers based on PFS and RECIST treatment response data.
ResultsIn our sample, 45 biomarkers were statistically significantly associated with PFS and 44 with response to treatment, of which eight were shared. Five of these (CD3G and NCAM1 gene expression levels, and levels of activation of Adrenergic signaling in cardiomyocytes, Growth hormone signaling, and Endothelin molecular pathways) were used in our signature that showed an AUC of 0.73 and HR of 0.27 (p=0.00034) on the experimental dataset. This signature was also reliable (AUC 0.76, 0.87) for the independent

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2024.1493877.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_4_Biomarkers_of_success_of_anti-PD-_L_1_immunotherapy_for_non-small_cell_lung_cancer_derived_from_RNA-_and_whole-exome_sequencing_results_of_a_prospective_observational_study_on_a_cohort_of_85_patients_xlsx/28011974）。