非小细胞肺癌FHITlow/pHER2high转录组特征预测结局和免疫治疗反应数据表

数据集获取（Figshare）

• 源站标题：DataSheet_1_Transcriptomic FHITlow/pHER2high signature as a predictive factor of outcome and immunotherapy response in non-small cell lung cancer.pdf
• DOI：10.3389/fimmu.2022.1058531.s001
• 发布日期：2022-12-05
• 文件数：1 个
• 文件总体积：1.81 MB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet_1_Transcriptomic_FHITlow_pHER2high_signature_as_a_predictive_factor_of_outcome_and_immunotherapy_response_in_non-small_cell_lung_cancer_pdf/21672056

命令行下载

curl -L -o "DataSheet_1_Transcriptomic FHITlow/pHER2high signature as a predictive factor of outcome and immunotherapy response in non-small cell lung cancer.pdf" "https://ndownloader.figshare.com/files/38420306"

文件清单

• DataSheet_1_Transcriptomic FHITlow/pHER2high signature as a predictive factor of outcome and immunotherapy response in non-small cell lung cancer.pdf（1.81 MB）

文件总体积 1.81 MB（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

IntroductionIn recent decades, the development of immunotherapy and targeted therapies has considerably improved the outcome of non-small cell lung cancer (NSCLC) patients. Despite these impressive clinical benefits, new biomarkers are needed for an accurate stratification of NSCLC patients and a more personalized management. We recently showed that the tumor suppressor fragile histidine triad (FHIT), frequently lost in NSCLC, controls HER2 receptor activity in lung tumor cells and that tumor cells from NSCLC patients harboring a FHITlow/pHER2high phenotype are sensitive to anti-HER2 drugs. Here, we sought to identify the transcriptomic signature of this phenotype and evaluate its clinical significance.
Materials and methodsWe performed RNA sequencing analysis on tumor cells isolated from NSCLC (n=12) according to FHIT/pHER2 status and a functional analysis of differentially regulated genes. We also investigated the FHITlow/pHER2high signature in The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) (n=489) and lung squamous cell carcinoma (LUSC) (n=493) cohorts and used the tumor immune dysfunction and exclusion (TIDE) model to test the ability of this signature to predict response to immune checkpoint inhibitors (ICI).
ResultsWe showed that up-regulated genes in FHITlow/pHER2high tumors were associated with cell proliferation, metabolism and metastasis, whereas down-regulated genes were related to immune response. The FHITlow/pHER2high signature was associated with the higher size of tumors, lymph node involvement, and late TNM stages in LUAD and LUSC cohorts. It was identified as an independent predictor of overall survival (OS) in LUAD cohort. FHITlow/pHER2high tumors were also predictive of poor response to ICI in both LUAD and LUSC cohorts.
ConclusionThese data suggest that ICI might not be a relevant option for NSCLC patients with FHITlow/pHER2high tumors and that anti-HER2 targeted therapy could be a good therapeutic alternative for this molecular subclass with poorer prognosis.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2022.1058531.s001（source: https://frontiersin.figshare.com/articles/dataset/DataSheet_1_Transcriptomic_FHITlow_pHER2high_signature_as_a_predictive_factor_of_outcome_and_immunotherapy_response_in_non-small_cell_lung_cancer_pdf/21672056）。