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Path to Clonal Theranostics in Luminal Breast Cancers
Nawale Hajjaji1,2, Soulaimane Aboulouard1, Tristan Cardon1
1Univ. Lille, Inserm, CHU Lille, U1192, Laboratoire Protéomique, Réponse Inflammatoire et Spectrométrie de Masse (PRISM), Lille, France.
Abstract:
Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.
Insights
This study used spatially resolved proteomics to identify novel protein targets in breast cancer clones, revealing potential for new drug discovery and repurposing. The approach identified unique drug interactions, offering new therapeutic strategies for heterogeneous tumors.
Area of Science:
- Proteomics and Cancer Biology
- Mass Spectrometry Imaging
- Drug Discovery
Background:
- Tumor heterogeneity presents a significant challenge in breast cancer treatment, leading to drug resistance.
- Identifying functionally distinct tumor subpopulations is crucial for developing targeted therapies and achieving clonal theranostics.
- Current approaches often overlook the complexity of intra-tumor heterogeneity.
Purpose of the Study:
- To perform an unsupervised, spatially resolved proteomic analysis of early luminal breast cancer clones.
- To identify novel protein targets and pathways associated with tumor heterogeneity for drug discovery.
- To compare clonal proteomic data with existing databases (TCGA, BC360, CDx) to highlight unique molecular insights.
Main Methods:
- Unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI).
- Analysis of 124 selected tumor clonal areas from early luminal breast cancers, stroma, and metastases.
- Comparative analysis with TCGA, BC360, and CDx datasets to identify unique pathways and drug targets.
Main Results:
- Identified 2868 proteins, with distinct protein classes compared to TCGA transcriptomic data.
- Discovered 139 pathways in the clonal proteome, with only 50-68% overlap with other datasets.
- Found 35 unique anticancer drug matches and a higher number of non-anticancer drug interactions, suggesting drug repurposing potential.
Conclusions:
- Spatially resolved clonal proteomics provides non-redundant molecular knowledge compared to bulk analysis or transcriptomics.
- The identified protein targets and pathways offer promising candidates for breast cancer drug discovery and repurposing.
- This clone-tailored approach enhances the understanding of tumor heterogeneity for developing more effective theranostic strategies.
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