Orhun Davarci, M.Sc.

Background: Breast cancer (BC) is the most commonly diagnosed cancer in women and the leading cause of death due to cancer among females¹. In 2017, more than a quarter million new cases of breast cancer were diagnosed in the US alone, and 13% of all women in the US will be diagnosed with a type of breast cancer over their lifetimes². Human epidermal growth factor receptor-positive breast cancer (HER2+BC) is one of the primary subtypes of breast cancer, comprising nearly 15-30% of all cases in the US^3–5. Although the 5-year survival rate of HER2+BC is higher than 94% percent with recommended therapy, HER2+BC heterogeneity remains one of the major factors that result in the development of treatment resistance^5,6. Emphasizing spatial variability in genomics, transcriptomics, and proteomics can lead to a better understanding of tissue biology through spatially resolving multi-omics data⁷. Thus, with a high degree of heterogeneity in its composition and response to therapy, HER2+ BC provides an effective model to investigate spatial multi-omics methods to generate pertinent information for clinical decision-making.

Research Objectives: In this narrative review, we explored the potential of incorporating spatial variability into multi-omics approaches to generate pertinent insights on the treatment of HER2+BC.

Methods: An online search in the PubMed database was conducted from 2017 to 2024 using the following keywords: “HER2+ Breast Cancer”, “Spatial proteomics”, “Spatial transcriptomics”, and “Spatial genomics”.

Results: Employing spatial multi-omics on HER2+BC tissue samples can generate relevant information about the underlying disease process. Spatially orienting genomics contributed to the identification of increased diversity in the in-situ stage of HER2+BC⁸. Employing spatial transcriptomics (ST) is shown to reveal high-resolution cell-state colocalization patterns. The ST data-derived colocalization signals between B and T cells can be used to identify immune structures that are indicative of positive prognosis³. Additionally, ST can reveal type I interferon-associated macrophage T-cell interaction, a potential mechanism for immune response, which may hint at an occurrence of antitumor within HER2+BC. Although its ability to predict complete responders to HER2+ therapy is behind immunohistochemistry, Spatial proteomics-derived signals can make accurate predictions while generating an immense amount of molecular-level spatially resolved information.

Conclusion: HER2+BC possesses a great degree of inter and intra-tumor heterogeneity, contributing to its resistance to anti-HER2 therapy. Spatial multi-omics approaches, provide an avenue to reveal this heterogeneity to guide diagnoses and treatments of HER2+BC. Developing spatial multi-omics tools for HER2+BC can enhance disease management from diagnosis to treatment.

Works Cited:

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2. National Institutes of Health. National Cancer Institute. Surveillance, Epidemiology, and End Results Program. Cancer stat facts: female breast cancer. Accessed April 28, 2024. https://seer.cancer.gov/statfacts/html/ breast.html
3. Andersson A, Larsson L, Stenbeck L, et al. Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions. Nat Commun. 2021;12(1):6012. doi:10.1038/s41467-021-26271-2
4. McNamara KL, Caswell-Jin JL, Joshi R, et al. Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response. Nat Cancer. 2021;2(4):400-413. doi:10.1038/s43018-021-00190-z
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7. Schulz D, Zanotelli VRT, Fischer JR, et al. Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry. Cell Syst. 2018;6(1):25-36.e5. doi:10.1016/j.cels.2017.12.001
8. Lu P, Foley J, Zhu C, et al. Transcriptome and genome evolution during HER2-amplified breast neoplasia. Breast Cancer Res. 2021;23(1):73. doi:10.1186/s13058-021-01451-6