GSE227919
GSE227919 [Background] This dataset is published under the title "Total RNA sequencing reveals gene expression and microbial alterations shared by oral pre-malignant lesions and cancer.". First published on Mar 22 202. [Content] Head and neck cancers are a complex malignancy comprising multiple anatomical sites, with cancer of the oral cavity ranking among the deadliest and most disfiguring cancers globally. Oral cancer (OC) constitutes a subset of head and neck cancer cases, presenting primarily as tobacco- and alcohol-associated oral squamous cell carcinoma (OSCC), with a 5-year survival rate of ~65%, partly due to the lack of early detection and effective treatments. OSCC arises from premalignant lesions (PMLs) in the oral cavity through a multi-step series of clinical and histopathological stages, including varying degrees of epithelial dysplasia. To gain insights into the molecular mechanisms associated with the progression of PMLs to OSCC, we profiled the whole transcriptome of 66 human PMLs comprising leukoplakia with dysplasia and hyperkeratosis non-reactive (HkNR) pathologies, alongside healthy controls and OSCC. Our data revealed that PMLs were enriched in gene signatures associated with cellular plasticity, such as partial EMT (p-EMT) phenotypes, and with immune response. Integrated analyses of the host transcriptome and microbiome further highlighted a significant association between differential microbial abundance and PML pathway activity, suggesting a contribution of the oral microbiome towards PML evolution to OSCC. Collectively, this study reveals molecular processes associated with PML progression that may help early diagnosis and disease interception at an early stage. [Structure and specifications] 1 file(s). [Topics] Tags: Expression profiling by high throughput sequencing, GPL18573, 9606. [Intended use] Structured tabular data is directly usable for statistical modelling, feature engineering and cohort analysis. [Access and licence] Source page: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227919
Basic Info
About
GSE227919
[Background]
This dataset is published under the title "Total RNA sequencing reveals gene expression and microbial alterations shared by oral pre-malignant lesions and cancer.". First published on Mar 22 202.
[Content]
Head and neck cancers are a complex malignancy comprising multiple anatomical sites, with cancer of the oral cavity ranking among the deadliest and most disfiguring cancers globally. Oral cancer (OC) constitutes a subset of head and neck cancer cases, presenting primarily as tobacco- and alcohol-associated oral squamous cell carcinoma (OSCC), with a 5-year survival rate of ~65%, partly due to the lack of early detection and effective treatments. OSCC arises from premalignant lesions (PMLs) in the oral cavity through a multi-step series of clinical and histopathological stages, including varying degrees of epithelial dysplasia. To gain insights into the molecular mechanisms associated with the progression of PMLs to OSCC, we profiled the whole transcriptome of 66 human PMLs comprising leukoplakia with dysplasia and hyperkeratosis non-reactive (HkNR) pathologies, alongside healthy controls and OSCC. Our data revealed that PMLs were enriched in gene signatures associated with cellular plasticity, such as partial EMT (p-EMT) phenotypes, and with immune response. Integrated analyses of the host transcriptome and microbiome further highlighted a significant association between differential microbial abundance and PML pathway activity, suggesting a contribution of the oral microbiome towards PML evolution to OSCC. Collectively, this study reveals molecular processes associated with PML progression that may help early diagnosis and disease interception at an early stage.
[Structure and specifications]
1 file(s).
[Topics]
Tags: Expression profiling by high throughput sequencing, GPL18573, 9606.
[Intended use]
Structured tabular data is directly usable for statistical modelling, feature engineering and cohort analysis.
[Access and licence]
Source page: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227919
Official Service
Dual Bases in Shaanxi & Sichuan × Direct Access to 10+ Grade-A Tertiary Hospitals
From compliant authorization and collection governance to professional annotation and dataset delivery, we provide a closed-loop, end-to-end service that makes high-quality clinical data ready to use.
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Download
注册下载
Requires a Kaggle account and sign-in to download — suited for users who need to track download history or use the API.
Unavailable公开下载
No registration needed — directly access public samples or documents, ideal for quickly previewing and evaluating dataset quality.
免登录有偿下载
Entrusted download and technical delivery service for public datasets.
提供高速下载与技术交付服务（收技术服务费，非数据销售）
UnavailableThis dataset is primarily hosted publicly on Kaggle. For the complete image package, use the source link or the Kaggle API.
Usage
数据集获取
源站：https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227919
标准获取流程：
- 访问源站链接，注册/登录账号；
- 进入数据集详情页，按页面指引申请权限或直接下载；
- 部分平台提供 SDK，例如：
- OpenDataLab:
pip install openxlab后openxlab.dataset.get(...) - ModelScope:
pip install modelscope后modelscope download - 天池: 登录后页面提供直链下载
以源站「数据下载/使用文档」页面为准。
- OpenDataLab:
数据说明
包含口腔癌、癌前病变和健康对照RNA测序数据，用于早期诊断和分子机制研究。
数据加载示例（表格/文本类）
import pandas as pd, glob, os
files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))
Data Gaps?
Backed by our bases in Shaanxi and Sichuan, we partner directly with over ten Grade-A tertiary hospitals, covering the full pipeline of compliant authorization, data collection and governance, professional annotation, and delivery — providing AI medical teams with ready-to-use, high-quality clinical data.
⚡️ Need data support or annotation services? Contact us now for a professional solution.
