Single-cell and bulk transcriptome analysis reveals tumor cell heterogeneity and underlying molecular program in uveal melanoma

Abstract

Abstract Background Uveal melanoma (UM) is a rare and deadly eye cancer with high metastatic potential. Despite the predominance of malignant cells within the tumor microenvironment, the heterogeneity and underlying molecular features remain to be fully characterized. Methods We analyzed single-cell transcriptomic profiling of 37,660 malignant cells from 17 UM tumors. A consensus non-negative factorization algorithm was used to decipher transcriptional programs underlying tumor cell-intrinsic heterogeneity. Tumor-infiltrated immune cells were computationally estimated from bulk transcriptomes and bioinformatics methods. A gene signature was derived for subtyping and prognostic stratification and validated in multicenter cohorts. Results ScRNA-seq analysis revealed the existence of diverse subpopulations and transcriptional variability among malignant cells within and between tumors. Furthermore, we observed that the heterogeneity of malignant cell states and compositions correlated with genomic, immunological, and clinical characteristics. By identifying gene expression programs associated with malignant cell heterogeneity at the single cell level, UM samples were classified into two distinct intra-tumoral subtypes (ITMHlo and ITMHhi) with different prognoses and immune microenvironments. Finally, a machine learning-derived 9-gene signature was developed to translate single-cell information into bulk tissue transcriptomes for patient stratification and was validated in multicenter cohorts. Conclusions Our study provides insight into understanding the intra-tumoral heterogeneity of UM and its potential impact on patient stratification.

Keywords

• Uveal melanoma
• Single-cell RNA sequencing
• Intra-tumoral heterogeneity