Document Type
Article
Publication Date
12-13-2022
Abstract
Background and rationale: Liver derived messenger ribonucleic acid (mRNA) transcripts were reported to be elevated in the circulation of hepatocellular carcinoma (HCC) patients. We now report the detection of high-risk mRNA variants exclusively in the circulation of HCC patients. Numerous genomic alleles such as single nucleotide polymorphisms (SNPs), nucleotide insertions and deletions (called Indels), splicing variants in many genes, have been associated with elevated risk of cancer. Our findings potentially offer a novel non-invasive platform for HCC surveillance and early detection.
Approach: RNAseq analysis was carried out in the plasma of 14 individuals with a diagnosis of HCC, 8 with LC and no HCC, and 6 with no liver disease diagnosis. RNA from 6 matching tumors and 5 circulating extracellular vesicle (EV) samples from 14 of those with HCC was also analyzed. Specimens from two cholangiocarcinoma (CCA) patients were also included in our study. HCC specific SNPs and Indels referred as “variants” were identified using GATK HaplotypeCaller and annotated by SnpEff to filter out high risk variants.
Results: The variant calling on all RNA samples enabled the detection of 5.2 million SNPs, 0.91 million insertions and 0.81 million deletions. RNAseq analyses in tumors, normal liver tissue, plasma, and plasma derived EVs led to the detection of 5480 high-risk tumor specific mRNA variants in the circulation of HCC patients. These variants are concurrently detected in tumors and plasma samples or tumors and EVs from HCC patients, but none of these were detected in normal liver, plasma of LC patients or normal healthy individuals. Our results demonstrate selective detection of concordant high-risk HCC-specific mRNA variants in free plasma, plasma derived EVs and tumors of HCC patients. The variants comprise of splicing, frameshift, fusion and single nucleotide alterations and correspond to cancer and tumor metabolism pathways. Detection of these high-risk variants in matching specimens from same subjects with an enrichment in circulating EVs is remarkable. Validation of these HCC selective ctmRNA variants in larger patient cohorts is likely to identify a predictive set of ctmRNA with high diagnostic performance and thus offer a novel non-invasive serology-based biomarker for HCC.
Recommended Citation
Block, Timothy; Zezulinski, Daniel; Kaplan, David E.; Lu, Jingqiao; Zanine, Samantha; Zhan, Tingting; Doria, Cataldo; and Sayeed, Aejaz, "Circulating Messenger RNA Variants as a Potential Biomarker for Surveillance of Hepatocellular Carcinoma" (2022). Department of Pharmacology and Experimental Therapeutics Faculty Papers. Paper 150.
https://jdc.jefferson.edu/petfp/150
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Table_1_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (464 kB)
Table_2_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (273 kB)
Table_3_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (234 kB)
Table_4_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (117 kB)
Table_5_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (2949 kB)
Table_6_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (2229 kB)
Table_7_Circulating messenger RNA variants as a potential biomarker for surveillance of hepatocellular carcinoma.xlsx (10 kB)
Language
English
Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Medical Biomathematics and Biometrics Commons
Comments
This article is the author's final published version in Frontiers in Oncology, Volume 12, December 2022, Article number 963641.
The published version is available at https://doi.org/10.3389/fonc.2022.963641. Copyright © 2022 Block, Zezulinski, Kaplan, Lu, Zanine, Zhan, Doria and Sayeed.