Although cell-free DNA (cfDNA) has emerged as the favored nucleic acid to analyze in liquid biopsy samples, there are situations when this marker fails to provided necessary information. In such cases, cell-free RNA (cfRNA) might help fill the void.
“Evaluating RNA in liquid biopsies is important because it can be useful for diagnostic, treatment-prediction, or even prognostic purposes,” according to Luis Raez, MD, of the Memorial Cancer Institute and Florida International University. Moreover, “cfRNA can be used to monitor clinical outcomes in lung cancer patients as a complement or maybe an alternative to cfDNA.”

As a case in point, Dr. Raez described a study in which lung adenocarcinomas that were previously found to lack any oncogenic drivers using the MSK-IMPACT DNA sequencing assay were reanalyzed with MSK-Fusion, a sequencing panel specifically focused on select RNAs.1 Of 254 samples that lacked driver mutations by DNA testing, 14% were subsequently found to harbor a fusion alteration by RNA testing, the great majority of which could be matched to targeted therapy.
“Because most of the liquid biopsies we do nowadays are based on cfDNA, that is why we need room for RNA, either to compliment or to enhance what we’re capturing with the cfDNA,” Dr. Raez said. He explained that this is particularly pertinent for NTRK fusions or translocations. DNA-based next-generation sequencing fails to capture NTRK fusions with breakpoints that involve long intron sequences, since these extended DNA stretches cannot be covered by hybridization-capture probes. However, this issue is obviated when analyzing fusion events using RNA.
Dr. Raez underscored the utility of exosomes for providing diagnostic information in patients with cancer. Because exosomes facilitate intracellular communication and are replete with DNA and RNA, large amounts of these extracellular vesicles can be captured, offering up more raw material compared with cfDNA or cfRNA sampling.
Dr. Raez and his colleagues recently developed a quantitative PCR-based test designed to detect EGFR mutations in exosomal RNA and DNA as a complement to PCR analysis of cfDNA. When evaluating their assay in 110 patients with NSCLC, they observed sensitivities of 90%, 83%, and 73% for detecting EGFR L858R, T790M, and exon 19 insertions or deletions, respectively, at specifi cities of 95% or greater.2 Th e addition of exosomal RNA/DNA analysis excelled when it came to detecting EGFR mutations in the 30% of patients with intrathoracic disease (M0/M1a), where cfDNA analysis is typically challenging due to limited circulating tumor DNA released into circulation. Beyond diagnosis, the aspect of cfRNA analysis that Dr. Raez finds most exciting entails serial measurement of RNA markers to evaluate treatment outcomes. Whereas the standard of care in NSCLC is to perform CT scans every 2 to 3 months to assess the response to treatment, researchers are attempting to measure dynamic changes in gene expression as a surrogate of response to do away with the need for repeated imaging assessments.
Dr. Raez’s group is specifically looking to leverage this approach by measuring PD-L1 RNA expression as a marker of response to immune checkpoint inhibitor therapy. “PD-L1 is a very exciting biomarker, but it’s also very frustrating for us. After several years of researching PD-L1 in tissue, we have not found a way to properly use PD-L1,” Dr. Raez explained.
Dr. Raez and his colleagues have found that pretreatment levels of PD-L1 measured from cfRNA in patients with NSCLC are significantly associated with the response to immunotherapy, but not to chemotherapy or targeted therapy. In addition, the changes in PD-L1 RNA over time correlate with the response to therapy (Figure) and can signal the onset of progressive disease before this can be documented radiographically by CT scan.3
Based on this work, Dr. Raez believes that changing cfRNA levels can indicate the response to immune checkpoint inhibitor therapy, and he and his colleagues are continuing their research in this area to demonstrate the utility of PD-L1 gene expression done by RT-PCR for monitoring and predicting treatment outcomes.
References:
1. Benayed R, Offi n M, Mullaney K, et al. High yield of RNA sequencing for targetable kinase fusions in lung adenocarcinomas with no mitogenic driver alteration detected by DNA sequencing and low tumor mutation burden. Clin Cancer Res. 2019(15):4712-4722.
2. Castellanos-Rizaldos E, Zhang X, Tadigotla VR, et al. Exosome-based detection of activating and resistance EGFR mutations from plasma of non-small cell lung cancer patients. Oncotarget. 2019(30):2911-2920.
3. Raez LE, Usher JL, Danenberg K, et al. RNA-based biomarker signatures in plasma as an independent predictor of outcome to chemotherapy in lung, colon, and breast cancers: Correlation of relative PD-L1 expression with immunotherapy outcomes. J Clin Oncol. 2019 (suppl):abstr e14567.