mubashir1837/Breast-Cancer-Gen-Expression-Dataset
𧬠RNA-seq Gene Expression Data for Predicting Neoadjuvant Chemotherapy Response 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⦠See the full description on the dataset page: https://huggingface.co/datasets/mubashir1837/Breast-Cancer-Gen-Expression-Dataset.
𧬠RNA-seq Gene Expression Data for Predicting Neoadjuvant Chemotherapy Response
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.
Dataset Summary
π Files
- `cleaned_expression.csv`
- Shape:
(58, 28,279) - Rows: Samples (patients)
- Columns: Gene expression values
- Last column:
Response 1β Pathological Complete Response (pCR)0β No Response
- `labels.csv`
- Sample IDs and corresponding NAC response labels
- `notebooks/exploration.ipynb`
- Exploratory Data Analysis (EDA)
- PCA and basic visualizations
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.
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)
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
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}
}