Harnessing Single Cell and Spatial Omics to Accelerate Precision Cancer Medicine

Yasser Riazalhosseini
Victor Phillip Dahdaleh Institute of Genomic Medicine, and (2) Department of Human Genetics, McGill University, Montreal, Quebec, Canada

Yasser Riazalhosseini, PhD (Presenter) McGill University

Presenter Bio: Dr. Riazalhosseini is the Head of the Cancer Genomics program at the Institute of Genomic Medicine and an Associate Professor of Human Genetics at McGill University. His multidisciplinary research program uses systems biology approaches that combine genomics data with detailed clinical annotations, and high-throughput functional studies to identify biomarkers and therapeutic targets for precision medicine in cancer and other conditions.

Relevant Financial Disclosures (within past 24 months, reported on May 22, 2025) No relevant financial relationship(s) to disclose.

INTRODUCTION:
The advancements in single-cell and spatial profiling technologies have opened new avenues for high-resolution studies that are critical for unravelling molecular mechanisms that underlie complex disorders, including cancer. Renal cell carcinoma (RCC), the most common form of kidney cancer, is characterized by its heterogeneity at histological and molecular features, and diverse clinical outcomes. Whereas, single-cell RNA sequencing (scRNA-seq) studies have advanced our understanding of cellular heterogeneity in RCC, they have mainly focused on differences in tumor microenvironment. As such, the cancer cell-intrinsic transcriptomic basis of histopathological diversity in RCC remains poorly understood.

METHODS:
We performed an integrated analysis of single cell, spatial and bulk RNA sequencing data to develop a transcriptome atlas for subtypes and clinically-relevant histological features, including sarcomatoid and rhabdoid dediffentiation phenotypes, in RCC. Specifically, we used scRNA-seq from 38 human RCC and normal kidney samples across diverse subtypes, along with spatial transcriptome data from 375 regions within 55 RCC to establish transcriptome signatures for diverse histological features of tissues exhibiting sarcomatoid or rhabdoid dedifferentiation or typical RCC features. We then applied these gene signatures to bulk RNA-sequencing data of 1017 RCC tumors from The Cancer Genome Atlas (TCGA) to investigate their performance for tumor diagnosis and predicting disease outcomes.

RESULTS:
We observed diagnostic discrepancies between histological examinations and molecular transcriptome signatures for about 8% of TCGA cases. Notably, the misdiagnosed tumors predominantly exhibit rare RCC histological subtypes, including clear cell papillary renal cell tumor (ccpRCT), for which no clinically-approved diagnostic markers are available. Our further analysis revealed potentially new diagnostic protein biomarkers, which we have validated through immunoblotting in an independent cohort of 500 RCC cases. Furthermore, our analysis has revealed substantial reprograming of stroma in sarcomatoid and rhabdoid regions compared to classical clear cell and papillary RCC (ccRCC and pRCC) regions.

CONCLUSIONS:
Our research introduces new biomarkers for precise diagnosis of rare subtypes of RCC. Furthermore, results from these studies enhance our understanding of biological underpinnings of disease progression, particularly development of aggressive sarcomatoid and rhabdoid histological features, paving the way for the rational development of therapeutic strategies in RCC. These results will be presented at the conference.