Spatial transcriptomics uncovers new treatment paths for triple-negative breast cancer

Researchers reveal the intricate molecular landscape of triple-negative breast cancer (TNBC), uncovering actionable spatial archetypes and gene signatures that pave the way for personalized therapies and better outcomes.

Study: Spatial transcriptomics reveals substantial heterogeneity in triple-negative breast cancer with potential clinical implications. Image Credit: Shutterstock AI / Shutterstock.com

In a recent study published in the journal Nature Communications, researchers analyze tumor architecture, cell composition, and microenvironment in patients with triple-negative breast cancer (TNBC) using spatial transcriptomics and histomorphological analysis. A total of nine TNBC spatial archetypes were identified and associated with disease outcomes and actionable features, as well as a tertiary lymphoid structure gene signature predictive of immunotherapy response.

Characterizing TNBC

About 15-20% of all breast cancer (BC) patients have TNBC, a malignancy associated with poor prognosis due to its heterogeneity and lack of effective treatment options. Multiomics analyses of bulk tumors have identified five molecular subtypes in TNBC, including basal-like (BL), immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal (M), and mesenchymal stem-like (MSL).

TNBC subtypes differ in their genomic, transcriptomic, and tumor microenvironment profiles, with distinct prognoses and therapeutic implications. For example, due to its high immune gene expression, the IM subtype is associated with better outcomes and potential responsiveness to immunotherapy. Comparatively, the LAR subtype, which is characterized by androgen receptor expression and frequent phosphatidyli-nositol 3-kinase (PIK3CA) mutations, is associated with poorer outcomes.

The tumor microenvironment, including tumor-infiltrating lymphocytes (TILs) and lymphoid aggregates, is increasingly recognized as a key factor in prognosis and treatment response. However, traditional ribonucleic acid (RNA) sequencing of bulk tumors fails to capture intratumoral heterogeneity, clonal interactions, and spatial organization of the tumor microenvironment.

Spatial transcriptomics (ST) has emerged as a powerful tool for spatially resolving transcriptomic data within tumor tissues and providing unprecedented insights into tumor heterogeneity and microenvironment interactions. Although still in its early stages for BC research, ST is a promising tool that can improve our understanding of the complexity of TNBC and guide the development of targeted therapies.

About the study

In the present study, researchers use ST on TNBC tumors to analyze intratumoral heterogeneity, tumor-stroma interactions, and immune features with the aim of identifying clinically relevant spatial archetypes and a predictive tertiary lymphoid structure (TLS) gene signature.

A total of 94 early-stage TNBC patients treated between 2000 and 2016 were included in the current study, from whom 96 frozen tumor samples were obtained for ST analysis. Tumor sections were histologically annotated and classified by tumor immune microenvironment (TIME) immunophenotypes.

Tumor samples were also analyzed for tumor-stroma composition, tertiary lymphoid structures, and morphological features. Bulk RNA sequencing was performed for transcriptomic validation.

External validation datasets from METABRIC, SCAN-B, I-SPY2, and non-BC immunotherapy cohorts were used for cross-cohort analyses. Morphological and transcriptomic data were integrated to identify critical immune and tumor-stroma interactions, spatial patterns, and clinically relevant biomarkers. Essential TNBC-related genes were selected for detailed investigation based on their biological and therapeutic relevance.

Study findings

High-quality sequencing data were obtained for 281 subarrays from 92 patients, totaling 270,310 spatial transcriptomic spots. Molecular subtypes were associated with distinct patterns.

More specifically, IM, BL, and M subtypes were enriched in tumor content, whereas LAR and MSL subtypes had more stroma. Lymphocytes were prominent in IM subtypes, whereas LAR and MSL were more frequently observed in fat tissue and vessels. Tumor patches varied by size and number across subtypes, with larger patches in BL and IM and smaller patches present in LAR, M, and MSL subtypes.

Deconvolution analysis indicated that both tumor and stroma compartments drive TNBC subtypes. Whereas IM and MSL subtypes were stroma-dominant, LAR, M, and BL were tumor-dominated.

Tumors exhibited subtype-specific biological features, such as epithelial-mesenchymal transition (EMT) signaling in M, proliferation and deoxyribonucleic acid (DNA) repair in BL, and metabolic other pathways in LAR. Stroma compartments varied, with MSL stroma exhibiting angiogenesis and cancer-associated fibroblast activity, whereas IM stroma was enriched in immune signals.

Clinical outcome analysis revealed that M subtype tumors with MSL stroma had better distant relapse-free survival. Larger tumor patches were associated with proliferation and immune signaling, although smaller patches correlated with metabolism and hormone pathways.

TLSs were enriched in immune cells and associated with better patient prognoses. A 30-gene TLS signature accurately predicted TLS regions and correlated with favorable outcomes, including higher pathological complete response rates in TNBC treated with immunotherapy.

Unsupervised clustering revealed 418 molecular clusters grouped into 14 mega clusters (MCs), which varied by immune activation, angiogenesis, and immune evasion. Some MCs, like MC 9, were linked to better outcomes, whereas others, like MC 14, suggested immune suppression.

Nine distinct spatial architectures (SAs) were identified, with some, such as SA 4, associated with immune activation and favorable outcomes. The analysis of the SAs provided insights into therapeutic vulnerabilities, suggesting potential targets like poly (adenosine diphosphate) [ADP]-ribose) polymerase (PARP) inhibitors, anti-cell differentiation antigen 37 (CD73) therapies, and antibody-drug conjugates for human epidermal growth factor receptor 3 (HER3) and trophoblast cell surface antigen 2 (TROP2).

Conclusions

TNBC is characterized by complex molecular and cellular heterogeneity. The current study demonstrates how ST can reveal clinically relevant tumor features, immune responses, and therapeutic targets that may not be evident in traditional classifications.