# A proteotranscriptomic approach to dissect the molecular landscape of human retinoblastoma

## TL;DR

This study uses proteotranscriptomics to explore the molecular features of retinoblastoma, identifying potential new therapeutic targets.

## Contribution

The study integrates RNA sequencing and proteomics with spatial analysis to reveal novel tumor cell clusters and potential cancer stem cells in retinoblastoma.

## Key findings

- RNA and protein levels showed moderate correlation, highlighting the need for integrated analysis.
- IMC identified 67,000 single cells grouped into 11 clusters, including CD44+/c-Myc+ tumor cells.
- Antigen-presenting cells showed elevated CD68 levels in retinoblastoma samples.

## Abstract

Retinoblastoma is a rare pediatric eye cancer caused by mutations in the RB1 gene, which regulates retinal cell growth. Early detection and treatment are critical for preventing vision loss and improving survival outcomes. This study aimed to perform an integrated proteotranscriptomic characterization of human retinoblastoma to provide a deeper understanding of disease biology and to identify novel therapeutic targets.

Paired tumor and adjacent retinal tissue samples were dissected from seven eyes. RNA sequencing and liquid chromatography-mass spectrometry were performed on the same samples. The spatially resolved cellular landscape was assessed using Imaging Mass Cytometry (IMC).

The correlation between RNA and protein level was moderate with variations across different pathways, underscoring the value of an integrated proteotranscriptomic approach. IMC identified more than 67,000 single cells in 11 distinct clusters, including antigen presenting cells, T cells, stroma cells, vascular cells and two clusters of proliferating and CD44/c-Myc positive tumor cells. Antigen presenting cells expressed higher levels of CD68 in retinoblastoma compared to controls.

CD44+ and high-c-Myc-expressing tumor cells may represent cancer stem cells with possible involvement in metastasis, warranting further validation. Our multilayered approach could pave the way for enhanced molecular assessments and novel targeted therapies for human retinoblastoma.