Receptor for hyaluronan-mediated motility (RHAMM) defines an invasive niche associated with tumor progression and predicts poor outcomes in breast cancer patients.

Breast cancer invasion and metastasis result from a complex interplay between tumor cells and the tumor microenvironment (TME). Key oncogenic changes in the TME include aberrant synthesis, processing, and signaling of hyaluronan (HA). Hyaluronan-mediated motility receptor (RHAMM, CD168; HMMR) is an HA receptor enabling tumor cells to sense and respond to this aberrant TME during breast cancer progression. Previous studies have associated RHAMM expression with breast tumor progression; however, cause and effect mechanisms are incompletely established. Focused gene expression analysis of an internal breast cancer patient cohort confirmed that increased RHAMM expression correlates with aggressive clinicopathological features. To probe mechanisms, we developed a novel 27-gene RHAMM-related signature (RRS) by intersecting differentially expressed genes in lymph node (LN)-positive patient cases with the transcriptome of a RHAMM-dependent model of cell transformation, which we validated in an independent cohort. We demonstrate that the RRS predicts for poor survival and is enriched for cell cycle and TME-interaction pathways. Further analyses using CRISPR/Cas9-generated RHAMM-/- breast cancer cells provided direct evidence that RHAMM promotes invasion in vitro and in vivo. Immunohistochemistry studies highlighted heterogeneous RHAMM protein expression, and spatial transcriptomics associated the RRS with RHAMM-high microanatomic foci. We conclude that RHAMM upregulation leads to the formation of 'invasive niches', which are enriched in RRS-related pathways that drive invasion and could be targeted to limit invasive progression and improve patient outcomes. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Multiomic Analysis of Subtype Evolution and Heterogeneity in High-Grade Serous Ovarian Carcinoma.

Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy-number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes. SIGNIFICANCE: This study infers whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are, therefore, appropriate targets for therapy and demonstrates that this is not the case for HGSOC.