mubashir1837/Breast-Cancer-Gen-Expression-Dataset

🧬 RNA-seq Gene Expression Data for Predicting Neoadjuvant Chemotherapy Response

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Overview

The Breast Cancer Gene Expression Dataset contains RNA-seq gene expression profiles from 58 breast cancer patients treated with neoadjuvant chemotherapy (NAC).
The dataset is processed and cleaned from the publicly available NCBI GEO dataset GSE280902 and is designed for machine learning, bioinformatics, and translational cancer research.

The primary goal of this dataset is to support prediction of pathological complete response (pCR) to NAC using gene expression data.

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Dataset Summary

Attribute	Description
Patients	58
Responders	29
Non-responders	29
Genes	28,278 protein-coding genes
Data Type	RNA-seq (tabular)
Task	Binary classification
Response Variable	NAC response

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📁 Files

• cleaned_expression.csv

  • Shape: (58, 28,279)
  • Rows: Samples (patients)
  • Columns: Gene expression values
  • Last column: Response
    • 1 → Pathological Complete Response (pCR)
    • 0 → No Response

• labels.csv

  • Sample IDs and corresponding NAC response labels

• notebooks/exploration.ipynb

  • Exploratory Data Analysis (EDA)
  • PCA and basic visualizations

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Data Description

• Samples: Pretreatment breast cancer tissue samples
• Genes: Protein-coding genes only
• Response Variable:
  • 1 = Responder (pCR)
  • 0 = Non-responder

No additional biological transformations were applied beyond cleaning, formatting, and labeling.

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Source

• GEO Accession: GSE280902

• Original Study:

  Guevara-Nieto HM et al. (2025).
  Identification of predictive pretreatment biomarkers for neoadjuvant chemotherapy response in Latino invasive breast cancer patients.
  Molecular Medicine

• Original Data Repository: NCBI Gene Expression Omnibus (GEO)

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Use Cases

This dataset is suitable for:

• Machine learning classification (response vs. non-response)
• Feature selection and biomarker discovery
• Dimensionality reduction (PCA, UMAP)
• Deep learning on tabular genomics data
• Educational use in bioinformatics and data science

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Citation

If you use this dataset, please cite:

APA

Mubashir Ali. (2025). Breast Cancer Gene Expression Dataset [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/14273820

BibTeX

@misc{mubashir_ali_2025,
    title={Breast Cancer Gene Expression Dataset},
    url={https://www.kaggle.com/dsv/14273820},
    DOI={10.34740/KAGGLE/DSV/14273820},
    publisher={Kaggle},
    author={Mubashir Ali},
    year={2025}
}