Discovery and Validation of Cancer Therapeutic Targets Through the Single-Cell Long-Read RNA-seq Analysis. 

The innovation of single-cell long-read RNA-seq technology has advanced our capacity to characterize the transcriptome at the isoform and single-cell levels, surmounting substantial challenges in detecting and analyzing molecular alteration in cancer cells. Our goal is to devise computational methodologies to expedite the individual single-cell-level identification of concealed oncogenic modifications such as alternative splicing variants, novel isoforms, and mutation profiles based on this state-of-the-art technique. By annotating known and novel isoforms, quantifying isoform expressions, and profiling mutation isoforms with single-cell precision, and subsequently validating the functional implications of discovered candidates, we aim to facilitate the discovery of novel targets for cancer therapy and innovative diagnostic approaches. Furthermore, the resultant bioinformatics tools and our findings will be disseminated to the medical scientific community, potentially contributing to the development of effective diagnostic and therapeutic regimens in the clinic.