LAUSR

The long reads of Nanopore sequencing permit accurate transcript assembly and ease in discovering novel transcripts with potentially important functions in cancers. The wide adoption of Nanopore sequencing for transcript quantification, however, is largely limited by high costs. To address this issue, we developed a bioinformatics software, NovelQuant, that can specifically quantify long‐read‐assembled novel transcripts with short‐read sequencing data. Nanopore Direct RNA Sequencing was carried out on three hepatocellular carcinoma (HCC) patients’ tumor, matched portal vein tumor thrombus, and peritumor to reconstruct the HCC transcriptome. Then, based on the reconstructed transcriptome, NovelQuant was applied on Illumina RNA sequencing data of 59 HCC patients’ tumor and paired peritumor to quantify novel transcripts. Our further analysis revealed 361 novel transcripts dysregulated in HCC and that 101 of them were significantly associated with prognosis. There were 19 novel prognostic transcripts predicted to be long noncoding RNAs (lncRNAs), and some of them had regulatory targets that were reported to be associated with HCC. Additionally, 42 novel prognostic transcripts were predicted to be protein‐coding mRNAs, and many of them could be involved in xenobiotic metabolism. Moreover, the tumor‐suppressive roles of two representative novel prognostic transcripts, CDO1‐novel (lncRNA) and CYP2A6‐novel (protein‐coding mRNA), were further functionally validated during HCC progression. Overall, the current study shows a possibility of combining long‐ and short‐read sequencing to explore functionally important novel transcripts in HCC with accuracy and cost‐efficiency, which expands the pool of molecular biomarkers that could enhance our understanding of the molecular mechanisms of HCC.