Cell-Free RNA Sequencing: Introduction, Advantages, and Workflow

Introduction to Cell-Free RNA Sequencing

Tumor-derived cell-free DNA (cfDNA) has proven to be an effective cancer biomarker. The rapid decrease in sequencing costs, combined with more efficient library preparation methods, has allowed for the detection of cancer-related point mutations, copy number variations, and methylation markers at ever-earlier stages of the disease. According to previous research, cancer cells also release cell-free RNA (cfRNA) into the bloodstream. Overexpression of tumor-specific transcripts could result in the amplification of tumor-derived RNA signals in the blood, making cell-free RNA a promising tool for detecting cancer in patients with low tumor shedding rates. Furthermore, cfRNA may be released into the bloodstream via mechanisms other than cell death, like exosome-mediated signaling by living cells. As a result, tumor-derived cfDNA and cfRNA may come from different cell populations within the tumor microenvironment, potentially increasing the number of cancers that can be detected by combining multiple analytes in the blood.

Figure 1. Cell-free DNA and RNA—measurement and applications in clinical diagnostics with focus on metabolic disorders. (Drag, 2021)

cfRNA research has traditionally focused on microRNAs (miRNA) or a small number of known cancer-related messenger RNAs (mRNA). MiRNAs are reliable and bountiful in plasma, and multiple studies have shown cancer-related changes in miRNA expression. However, preanalytical processing circumstances, quantification strategies, and batch effects can affect miRNA levels, resulting in poor reproducibility, interpretability, and specificity for miRNA biomarkers.

Advantages of Cell-Free RNA Sequencing

Circulating cell-free DNA (cfDNA) and RNA (cfRNA) have a lot of promise as a new class of biomarkers for non-invasive liquid biopsies in a variety of diseases and situations.  cfDNA and cfRNA have been extensively studied in latest years as noninvasive prenatal testing, solid organ transplantation, cancer screening, and tumor monitoring tools. Higher cfDNA concentrations in obese people imply accelerated adipocyte cellular turnover during adipose mass expansion and maybe explicitly associated with the development of adipose tissue insulin resistance by inducing inflammation. Additionally, cfDNA and cfRNA have potential diagnostic value in a variety of obesity-related metabolic disorders, such as nonalcoholic fatty liver disease, type 2 diabetes, and diabetic complications.

Cell-Free RNA Sequencing Workflow

The process flow for cell-free RNA sequencing consists of: cell-free RNA isolation, library preparation, sequencing, output, and analysis.

There are five steps involved in cell-free RNA isolation. The first step is to use a double spin protocol to separate plasma from whole blood specimens.  The second step is to purify total nucleic acid. After that, clean up the cfRNA and perform a DNase I digestion of the eluted nucleic acids according to the manufacturer's instructions. The final step is to conduct a quantitative analysis of cfRNA. Since it is highly heterogeneous in size and present in low concentrations, cell-free RNA isolation, particularly in plasma, is difficult. The RNA retrieved cannot be efficiently identified using standard methods such as the NanoDrop spectrophotometer, gel or capillary electrophoresis, or RNA binding dyes because the expected yields are low.

Purified cfRNA must be used to complete ribosomal RNA (rRNA) depletion during library preparation. The library must then be completed using the rRNA that has been depleted. After that, the finished libraries will be quantified, the quality and size of the libraries will be assessed, and the completed libraries will be stored at -20 degrees Celsius until they are used in sequencing reactions.

The samples are sequenced and the results are analyzed in the final step.

References:

1. Drag MH, Kilpeläinen TO. Cell-free DNA and RNA—measurement and applications in clinical diagnostics with focus on metabolic disorders. Physiological Genomics. 2021 Jan 1;53(1).
2. Larson MH, Pan W, Kim HJ, et al. A comprehensive characterization of the cell-free transcriptome reveals tissue-and subtype-specific biomarkers for cancer detection. Nature communications. 2021 Apr 21;12(1).
3. Dengu F. Next-generation sequencing methods to detect donor-derived cell-free DNA after transplantation. Transplantation Reviews. 2020 Jul 1;34(3).