Exploring vulnerable building blocks in protein-protein interaction networks of breast tumor and adjacent normal tissues.
Tumor-adjacent normal tissues (TANTs) histologically and morphologically look normal and are commonly used as a control in patient-based cancer studies.
APA
Kumar S, Agrawal A, Vindal V (2026). Exploring vulnerable building blocks in protein-protein interaction networks of breast tumor and adjacent normal tissues.. Computational biology and chemistry, 120(Pt 1), 108647. https://doi.org/10.1016/j.compbiolchem.2025.108647
MLA
Kumar S, et al.. "Exploring vulnerable building blocks in protein-protein interaction networks of breast tumor and adjacent normal tissues.." Computational biology and chemistry, vol. 120, no. Pt 1, 2026, pp. 108647.
PMID
40850172
Abstract
Tumor-adjacent normal tissues (TANTs) histologically and morphologically look normal and are commonly used as a control in patient-based cancer studies. Previous studies have revealed that TANTs present a unique transitional state between healthy normal and tumor tissues. However, little or no knowledge exists about the landscape of protein-protein interactions (PPIs) in TANTs and how they differ from the tumor tissues. Herein, we integrated the PPI data mapped onto the differentially expressed genes in TANTs and tumor tissues compared to healthy normal tissues. This led to the reconstruction of six tissue-specific PPI networks, including TANTs and breast tumor tissues (viz., Luminal A, Luminal B, Her2, Basal, and Normal-Like). First, these PPI networks were analyzed using network influence and vulnerability analyses from the NetVA R package. Consequently, it revealed 134 vulnerable proteins (VPs), 21 vulnerable protein pairs (VPPs), and 94 influential proteins (IPs) that were present across all six tissue networks. Further, we identified a set of 34 proteins as common hubs and another set of seven proteins as common bottlenecks across all six tissue networks. Next, all VPs, IPs, hubs, and bottlenecks were investigated for their associations with various diseases, including cancers, and found sharing a significant number of well-known cancer-associated proteins, viz., AR, BRCA1, ERBB2, FN1, FOXA1, JUN, MKI67, and NRAS. Thus, by applying network vulnerability, influence, and gene-disease association-based analyses, we suggest lists of known and candidate proteins along with their associated protein complexes potentially involved in breast cancer tumorigenesis and present across TANTs and different breast cancer subtypes.
MeSH Terms
Breast Neoplasms; Humans; Female; Protein Interaction Maps; Breast
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