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Proteomic Analysis Uncovers Triple-Negative Breast Cancer Subtypes, Potential Treatment Targets

NEW YORK — A proteomic analysis has uncovered subtypes of triple-negative breast cancer and highlighted potential drug targets for those different groups.

Triple-negative breast cancer exhibits high tumor heterogeneity, metastatic rate, and poor overall survival. While previous studies of this type of cancer have focused on genomic and transcriptomic variations, researchers from Fudan University and elsewhere have now analyzed the proteomes of tumor and noncancerous adjacent tissue from 90 women to examine the tumor protein landscape.

As they reported in Cell Reports on Tuesday, the researchers identified four tumor subgroups with enrichment of different pathways or molecular processes and differing prognoses. They likewise conducted networking analyses and discovered potential therapeutic targets, such as NAE1 and FASN/AKT1.

"Our proteomic work extends and deepens previous genomic and transcriptomic work … by showing what are the proteins really in action in TNBC [and] how they interact with each other in the context of molecular pathways and networks," senior author Weimin Zhu from the Beijing Institute of Lifeomics wrote in an email. "In addition, because proteins play the role of executors of biological functions, our multi-dimensional proteome-based data can be more readily used as a protein pool for the exploration of biomarkers/drug targets of TNBC."

Zhu and his colleagues analyzed tumor and noncancerous adjacent tissue samples previously collected from 90 individuals for the Fudan University Shanghai Cancer Center Triple-Negative Breast Cancer (FUSCCTNBC) cohort. The samples underwent whole-proteome analysis, phosphoproteome profiling, and DNA-binding analysis.

Integrative clustering of the proteome and phosphoproteome data revealed four subtypes, iP-1 through iP-4, with differences in prognosis. In particular, iP-2 was associated with shortest survival, highest lymph node grades, and oldest patient age.

The clusters also had distinct enriched pathways, as iP-1 was highly enriched for cell cycle, DNA replication and elongation, and mRNA splicing pathways, while iP-2 was enriched for androgen receptor signaling and lipid metabolism pathways. Meanwhile, iP-3 and iP-4 were enriched for immune-related pathways and extracellular matrix-related pathways, respectively.

The subtypes overlapped in part with previously defined triple-negative breast cancer subtypes. Most samples falling in iP-1 or iP-2, for instance, were also in the FUSCC BIS and LAR subtypes and the metabolic MPS2 and MPS1 subtypes. Tumors in iP-4, though, mapped to diverse transcriptomic and metabolic subtypes, suggesting some divergence between the transcriptome and proteome.

The researchers also conducted scaffold and co-expression network analyses of the three proteomic datasets in conjunction with the previously collected genomic and transcriptomic data from the cohort. Within subtype iP-2, they found high potential for AKT1 as a therapeutic target, as it could phosphorylate a number of transcription factors and kinases, including FOXO1, MTOR, and PRKCD. AKT1 inhibitors like capivasertib and ipatasertib, they noted, have been reported in some clinical trials to be effective for triple-negative breast cancer.

At the same time, an analysis of transcription factor master regulators found NEA1 to be a signature protein within iP-1, suggesting it may have therapeutic promise. The researchers subsequently treated human triple-negative breast cancer cell lines with the NAE inhibitor MLN4924 to find that cell viability declined among cell lines that otherwise had high NAE1 protein expression.

These findings could help fuel further research into the molecular mechanisms involved in triple-negative breast cancer as well as into possible drug targets. Zhu added that he and his team are looking for a partner or collaborator to help continue with work into the potential drug targets they identified.