Biology subjects

Ren, B.-G.

Publications and source records attributed to Ren, B.-G..

3 recordsLinked to original sources

bioRxiv2025

Deep Spatial Sequencing Revealing Differential Immune Responses in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal cancers for humans. HCC is highly heterogeneous. In this study, we performed ultra-depth ([~]1 million reads per spot) spatial sequencing on a case of HCC. Sixteen distinct spatial expression clusters were identified. Each of these clusters was spatially contiguous and had distinct gene expression patterns. In contrast, benign liver tissues showed minimal heterogeneity in terms of gene expression. Numerous immune cell-enriched spots were identified in both HCC and benign liver regions. Cells adjacent to these immune cell-enriched spots showed significant alterations in their gene expression patterns. Interestingly, the responses of HCC cells to the nearby immune cells were significantly more intense and broader, while the responses of benign liver cells to immune cells were somewhat narrow and muted, suggesting an innate difference in immune cell activities towards HCC cells in comparison with benign liver cells. When standard-depth sequencing was performed, significant numbers of genes and pathways that were associated with these changes disappeared. Qualitative differences in some pathways were also found. These results suggest that deep spatial sequencing may help to uncover previously unidentified mechanisms of liver cancer development.

cancer biology↗

bioRxiv2023

Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells

The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate Long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPseq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection (UMAP) analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen (HLA) molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPseq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.

genomics↗

bioRxiv2020

Targeted Transcriptome Analysis using Synthetic Long Read Sequencing Uncovers Isoform Reprograming in the Progression of Colon Cancer

Diversity in human gene expression stems, to a large extent, from splicing exons into multiple mRNA isoforms. Characterization of isoforms requires accurate long-read sequencing. However, read lengths, high error rates, low throughput and large input requirements are some of the challenges that remain to be addressed in sequencing technologies. In this study, we used a barcoding-based synthetic long read (SLR) isoform sequencing approach, LoopSeq, to generate sequencing reads sufficiently long and accurate to identify isoforms using standard short read Illumina sequencers. The method identifies isoforms from control RNA samples with 99.4% accuracy and a 0.01% per-base error rate, exceeding the accuracy reported for other long-read sequencing technologies. Applied to targeted transcriptome sequencing of over 10,000 genes from colon cancers and their metastatic counterparts, LoopSeq revealed large scale isoform redistributions from benign colon mucosa to primary colon cancer and metastatic cancer and identified several novel gene fusion isoforms in the colon cancer samples. Strikingly, our data showed that most single nucleotide variants (SNVs) occurred dominantly in specific isoforms and that some SNVs underwent isoform switching in cancer progression. The ability to use short read sequencers to generate accurate long-read isoform information as the raw unit of transcriptional information holds promise as a new and widely accessible approach in RNA isoform analyses.

genomics↗