Gut Microbiome Biomarkers for Early Lung Adenocarcinoma from a Multi-Center Study

A multi-center study characterizing the gut microbiome in lung adenocarcinoma (LUAD) patients. The dataset likely contains microbial composition data used to develop and validate a diagnostic model. It was authored by Weidong Zhang and last updated on 2026-05-14.

Use Cases

• Training machine learning models for cancer diagnosis based on gut microbiome features.
• Identifying microbial biomarkers associated with early-stage lung adenocarcinoma.
• Comparing the performance of different ML models (e.g., Random Forest) for diagnostic tasks.
• Validating diagnostic models across geographically distinct patient cohorts.

Strengths

• Model validation across multiple independent cohorts, including Jiangsu and Hainan.
• The developed Random Forest model achieved a high AUC of 0.998 in the training cohort.
• Includes data from 175 early-stage LUAD patients and 107 healthy controls in the training set.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (2.1 KB), suggesting it contains summary or model results rather than raw sequence data.

Provenance

Source

figshare

Collection Method

Prospective, randomized, multi-center study characterizing the gut microbiome.

Freshness

Last updated 2026-05-14 05:47:12; freshness should be verified.

Geography

Data includes cohorts from at least Jiangsu and Hainan provinces in China.