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Biomedical subjects

Ying Mao

Publications and source records attributed to Ying Mao.

3 recordsLinked to original sources

Targeting cancer-specific mutations with RNA-triggered chromatin shredding.

Genetic mutations that drive cancer often occur in tumour-suppressor proteins such as the p53 transcription factor, which is altered in 40-50% of cases1,2. However, current therapies often fail to target these mutations because the mutant proteins typically lack defined drug-binding pockets and restoring their endogenous function has proven challenging. Here we program Cas12a2, an RNA-guided CRISPR nuclease with trans-nucleolytic cleavage activity3,4, to kill cancer cells selectively by targeting cancer-specific transcripts. This approach limited cell growth by inducing trans shredding of chromatin and triggering DNA-damage responses and cell death. In contrast to existing methods, RNA-guided Cas12a2 senses cellular RNA signatures, enabling precise targeting of undruggable mutations. Transcript-activated chromatin shredding provides an innovative approach to precision disease treatments for undruggable targets.

Animals

Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy.

Tumor organoids are important tools for cancer research, but current models have drawbacks that limit their applications for predicting response to therapy. Here, we developed a fast, efficient, and complex culture system (IPTO, individualized patient tumor organoid) that accurately recapitulates the cellular and molecular pathology of human brain tumors. Patient-derived tumor explants were cultured in induced pluripotent stem cell (iPSC)-derived cerebral organoids, thus enabling culture of a wide range of human tumors in the central nervous system (CNS), including adult, pediatric, and metastatic brain cancers. Histopathological, genomic, epigenomic, and single-cell RNA sequencing (scRNA-seq) analyses demonstrated that the IPTO model recapitulates cellular heterogeneity and molecular features of original tumors. Crucially, we showed that the IPTO model predicts patient-specific drug responses, including resistance mechanisms, in a prospective patient cohort. Collectively, the IPTO model represents a major breakthrough in preclinical modeling of human cancers, which provides a path toward personalized cancer therapy.

Humans