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Updated: May 31, 2026
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Potential treatment targets in the whole-tissue proteome of triple negative breast cancer
Tram B Doan1, Merridee A Wouters2,3, Jiashu Hu1,4
1Centre for Cancer Research, The Westmead Institute for Medical Research, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
Abstract:
Triple Negative Breast Cancer (TNBC) is recognised as heterogeneous, with distinct subtypes specified by histopathologic and gene expression analysis. However, these do not align closely to treatment response and there is an on-going need for both clinically applicable biomarkers and new effective treatments. Comprehensive profiling of the TNBC tissue proteome has potential to bring new perspective to these challenges. We report global proteomic profiles of 312 TNBC cases derived from Data Independent Acquisition-Mass Spectrometry (DIA-MS) analysis, coupled with gene expression profiling in a subset of cases (n = 97). This showed differential expression of protein cassettes reflecting the key features of 1) cellular growth and proliferation, 2) immune activation, 3) mesenchymal elements and 4) luminal androgen receptor phenotype. In combination, these cassettes distinguished TNBC subtypes that align to potential treatments. We also found an association between immune activation and improved survival that was influenced by the presence of lymph node metastases. In our cohort and in a validation dataset, the combination of a five protein immune activation signature with lymph node status was highly predictive of survival, suggesting that a combination of tissue proteomics with clinical features could be an informative guide to TNBC management. This large proteomic study forms a resource to progress this goal.
Insights
Researchers profiled the proteome of triple-negative breast cancer (TNBC) to identify new subtypes and biomarkers. A five-protein immune signature combined with lymph node status accurately predicts survival in TNBC patients.
Area of Science:
- Oncology
- Proteomics
- Genomics
Background:
- Triple-negative breast cancer (TNBC) is a heterogeneous disease with subtypes that do not consistently predict treatment response.
- There is a critical need for clinically applicable biomarkers and novel therapeutic strategies for TNBC.
- Comprehensive proteomic profiling offers a promising avenue to gain new insights into TNBC heterogeneity and identify potential therapeutic targets.
Purpose of the Study:
- To conduct a large-scale proteomic analysis of TNBC tissue.
- To identify distinct TNBC subtypes based on protein expression profiles.
- To discover novel biomarkers that correlate with treatment response and patient survival.
Main Methods:
- Global proteomic profiling of 312 TNBC cases using Data Independent Acquisition-Mass Spectrometry (DIA-MS).
- Gene expression profiling was performed on a subset of 97 cases.
- Statistical analysis was employed to identify differential protein expression and survival associations.
Main Results:
- Proteomic profiles revealed distinct protein cassettes associated with cellular growth, immune activation, mesenchymal features, and luminal androgen receptor phenotype.
- These protein cassettes differentiated TNBC subtypes that align with potential treatment strategies.
- An association between immune activation and improved survival was observed, influenced by lymph node metastasis.
- A five-protein immune activation signature combined with lymph node status demonstrated high predictive power for survival in both the discovery and validation cohorts.
Conclusions:
- Tissue proteomic profiling can reveal TNBC subtypes that are more clinically relevant than current classifications.
- A combination of a five-protein immune signature and lymph node status serves as a potent predictor of TNBC patient survival.
- This study provides a valuable proteomic resource to advance TNBC management and therapeutic development.
