Fusion Transcript Detection by Long-read Sequencing and a Genomics Study on the Recurrence Prediction of HCC Transplantation Patients

Presenter: Silvia Liu, PhD

Dr. Liuchang’s lab is working on the bioinformatics analysis of genomic data. Specifically, they are focusing on the bioinformatics analysis of sequencing data and biostatistical analysis of the downstream interpretation. IDr. Liu will present two recent studies. One study is on the fusion transcript detection via long-read sequencing technology. Eight colon cancer samples from three patients were collected for long-read RNA-sequencing. The lab performed isoform-level differential expression analysis, mutation calling and fusion transcript discovery. The second study is a genomic study on hepatocellular carcinoma (HCC) patients who received liver transplantation. THe lab applied transcriptome features (by RNA-seq), somatic mutation pathway features (by WES) and Milan score to predict the cancer recurrence status after transplantation.

Background Reading:

• Liu, S., Wu, I., Yu, Y. P., Balamotis, M., Ren, B., Yehezkel, T. B., Luo, J.H.* (2021) Targeted Transcriptome Analysis using Synthetic Long Read Sequencing Uncovers Isoform Reprograming in the Progression of Colon Cancer. Communications Biology, 4, 506.
• Liu, S., Nalesnik, M., Singhi, A., Wood-Trageser, M., Randhawa, P., Ren, B., Humar, A., Liu, P., Yu, Y.P., Tseng, G., Michalopoulos, G.*, Luo, J.H.*. (2021) Transcriptome and exome analyses of hepatocellular carcinoma reveal patterns to predict cancer recurrence in liver transplant patients. Hepatology Communications.