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Prashant Kapoor, MD, FACP


Can Plasma Cell–Free RNA Profiling Differentiate Myeloma From Its Premalignant Condition?

By: Vanessa A. Carter, BS
Posted: Tuesday, May 24, 2022

A study conducted by Thuy T.M. Ngo, PhD, of the Knight Cancer Institute, Oregon Health and Science University, Portland, and colleagues aimed to determine the potential of cell-free RNA profiles to distinguish hematologic cancers from their premalignant conditions—specifically multiple myeloma from its precursor monoclonal gammopathy of undetermined significance (MGUS). Altogether, this report demonstrates a proof of principle for the use of messenger RNA transcript in plasma to distinguish among precancerous conditions, noncancerous states, and cancers. The results of this study, which were published in npj Precision Oncology, also focused on liver cirrhosis and the risk for liver cancer.

“A few years ago, not many people believed cell-free messenger RNA could be reliably detected in the blood because it is prone to degradation,” stated Dr. Ngo in a press release. “We found a way to handle it, and we are among the first to apply it in cancer and pre-cancer early detection.”

The investigators sequenced total plasma cell–free RNA from plasma samples of 10 patients with multiple myeloma, 8 with hepatocellular carcinoma, 13 with premalignant conditions, and 20 individuals who did not have cancer. Potential cell-free RNA biomarkers were identified using plasma cell–free RNA sequencing, and the sequencing data were further validated using quantitative reverse transcription polymerase chain reaction.

It was discovered that plasma cell–free RNA biomarkers of multiple myeloma are highly expressed in the bone marrow compared with other tissues and appear to be related to cell cycle processes. Additionally, the cell-free RNA level of these biomarkers was observed to display a gradual transition from noncancerous states through precancerous conditions and cancer.

Of note, although the cell-free RNA results of precancerous conditions require further confirmation, analysis models were able to classify cancer from noncancer controls in a validation cohort. Furthermore, the area under the curve was 0.9 when classifying noncancer donors from those with multiple myeloma.

Disclosure: The study authors reported no conflicts of interest.

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