Genetic insights into the shared molecular mechanisms of Crohn’s disease and breast cancer: a Mendelian randomization and deep learning approach

The objective of this study was to explore the potential genetic link between Crohn's disease and breast cancer, with a focus on identifying druggable genes that may have therapeutic relevance. We assessed the causal relationship between these diseases through Mendelian randomization and investigated gene-drug interactions using computational predictions. This study sought to identify common genetic pathways possibly involved in immune responses and cancer progression, providing a foundation for future targeted treatment research. The dataset comprises single nucleotide polymorphisms used as instrumental variables for Crohn's disease, analyzed to explore their possible impact on breast cancer risk. Gene ontology and pathway enrichment analyses were conducted to identify genes shared between the two conditions, supported by protein-protein interaction networks, colocalization analyses, and deep learning-based predictions of gene-drug interactions. The identified hub genes and predicted gene-drug interactions offer preliminary insights into possible therapeutic targets for breast cancer and immune-related conditions. This dataset may be valuable for researchers studying genetic links between autoimmune diseases and cancer and for those interested in the early identification of potential drug targets.

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Publication Details

Journal
Discover Oncology
Published
2025-02-18
DOI
https://doi.org/10.1007/s12672-025-01978-6
Primary Topic
Inflammatory Bowel Disease
Type
article
Field-Weighted Citation Impact
0.00
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article

Genetic insights into the shared molecular mechanisms of Crohn’s disease and breast cancer: a Mendelian randomization and deep learning approach

Zhiwei Wang, Pei Wang, Ju Yang, Zong Yao Zhang
1 links
Discover Oncology
Inflammatory Bowel Disease
article

Genetic insights into the shared molecular mechanisms of Crohn’s disease and breast cancer: a Mendelian randomization and deep learning approach

Zhiwei Wang, Pei Wang, Ju Yang, Zong Yao Zhang
article en

Abstract

The objective of this study was to explore the potential genetic link between Crohn's disease and breast cancer, with a focus on identifying druggable genes that may have therapeutic relevance. We assessed the causal relationship between these diseases through Mendelian randomization and investigated gene-drug interactions using computational predictions. This study sought to identify common genetic pathways possibly involved in immune responses and cancer progression, providing a foundation for future targeted treatment research. The dataset comprises single nucleotide polymorphisms used as instrumental variables for Crohn's disease, analyzed to explore their possible impact on breast cancer risk. Gene ontology and pathway enrichment analyses were conducted to identify genes shared between the two conditions, supported by protein-protein interaction networks, colocalization analyses, and deep learning-based predictions of gene-drug interactions. The identified hub genes and predicted gene-drug interactions offer preliminary insights into possible therapeutic targets for breast cancer and immune-related conditions. This dataset may be valuable for researchers studying genetic links between autoimmune diseases and cancer and for those interested in the early identification of potential drug targets.

Discover OncologyVol. 16(1)
Bengbu Medical College (CN), Huaian First People’s Hospital (CN)
Good health and well-being
Openalex Percentile: Top 96%
Inflammatory Bowel Disease
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Genetic insights into the shared molecular mechanisms of Crohn’s disease and breast cancer: a Mendelian randomization and deep learning approach — Zhiwei Wang, Pei Wang, et al. · Discover Oncology (2025) | TGRS Research Map | TGRS