UCLA researchers from the Department of Integrative Biology and Physiology have developed a novel method to profile RNA editing in single cells from lung cancer biopsies as a method to predict patient survival.
BACKGROUND: RNA editing occurs naturally in the human transcriptome and has been shown to influence cancer cell behavior and the anti-tumor immune response. Given its prevalence across various cancer types, gaining a deeper understanding of tumor-specific RNA editing and its underlying mechanisms is crucial. Prior research has detected many global RNA editing alterations in patient lung cancer samples. However, since tumors are highly heterogeneous, there is a demand for novel methods that analyze RNA editing at a single-cell level to enable correlation with tumor mutation burden and cancer immunity.
INNOVATION: Researchers at UCLA led by Dr. Xinshu Xiao have developed a novel technology to identify double-stranded RNAs (dsRNAs) in patient tumor biopsy samples, which can be used as biomarkers to predict patient response to immunotherapy in lung cancer and melanoma. UCLA researchers (i) identified tumor-specific RNA editing sites in dsRNAs of lung adenocarcinoma (LUAD) using bulk RNA-sequencing data, (ii) designed multiplexed PCR primers to amplify these dsRNAs, and (iii) created a library from the PCR products for high-throughput sequencing. Single-cell RNA-sequencing (scRNA-seq) analysis revealed that cancer cells exhibited significantly higher RNA editing levels than non-malignant cells, with an enrichment of genes in cancer-associated pathways. Researchers then analyzed RNA editing in LUAD patient samples at different treatment stages: 1) treatment naïve (TN) – before systemic targeted therapy, 2) residual disease (RD) – tumor regressing or stable, and 3) progressive disease (PD) – tumor with acquired drug resistance. UCLA researchers found that there were significant changes in the RNA editing levels of cancer cells across treatments, with PD samples showing the highest levels, followed by the TN and RD groups. Given prior research linking RNA editing to innate immune suppression, researchers tested the correlation between RNA editing and interferon-stimulated gene (ISG) expression in cancer cells. RNA editing levels were negatively associated with ISG RNA abundance, with the strongest negative correlation in PD samples, supporting the hypothesis that RNA editing suppresses of interferon signaling in cancer cells. Further analysis revealed that RNA editing load was a stronger predictor of patient survival than tumor mutation burden (TMB). Higher RNA editing levels were associated with significantly worse patient survival outcomes. In addition, researchers discovered specific dsRNAs whose editing and expression levels together predict patient survival and responsiveness to immunotherapy. Altogether, UCLA researchers have conducted the first single-cell analysis of RNA editing in dsRNAs of lung cancer, demonstrating its potential as a biomarker for patient prognosis and highlighting its implications for cancer therapy.
POTENTIAL APPLICATIONS:
- Disease prognosis in cancer patients treated with immunotherapy
ADVANTAGES:
- This method can be used to identify RNA editing in single cells of tumor biopsies, which has not been done before
- The profiling of multiple RNA editing sites per tumor is cost-effective
- This method can be used to predict patient survival much more effectively than tumor mutation burden (TMB) does
DEVELOPMENT-TO-DATE: UCLA researchers have developed a novel in vitro and bioinformatic method to identify edited RNA from ex vivo patient tumor biopsy samples, which can be used to predict patient survival.
Keywords: RNA editing, TMB, dsRNAs, bulk RNA-seq, multiplex PCR, high-throughput sequencing, scRNA-seq, LUAD, ISGs, bioinformatics, diagnostics