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Su, M.-J.

Publications and source records attributed to Su, M.-J..

2 recordsLinked to original sources

Transcriptional mediators of treatment resistance in lethal prostate cancer

Metastatic castration resistant prostate cancer (mCRPC) is primarily treated with therapies that prevent transcriptional activity of the androgen receptor (AR), cause DNA damage, or prevent cell division. Clinical resistance to these therapies, including second-generation androgen-targeting compounds such as enzalutamide and abiraterone, is nearly universal. Other treatment modalities, including immune checkpoint inhibitors, have provided minimal benefit except in rare subsets of patients1,2. Both tumour intrinsic and extrinsic cellular programs contributing to therapeutic resistance remain areas of active investigation. Here we use full-length single-cell RNA-sequencing (scRNA-seq) to identify the transcriptional states of cancer and immune cells in the mCRPC microenvironment. Within cancer cells, we identified transcriptional patterns that mediate a significant proportion of inherited risk for prostate cancer, extensive heterogeneity in AR splicing within and between tumours, and vastly divergent regulatory programs between adenocarcinoma and small cell carcinoma. Moreover, upregulation of TGF-{beta} signalling and epithelial-mesenchymal transition (EMT) were both associated with resistance to enzalutamide. We found that some lymph node metastases, but no bone metastases, were heavily infiltrated by dysfunctional CD8+ T cells, including cells undergoing dramatic clonal expansion during enzalutamide treatment. Our findings suggest avenues for rational therapeutic approaches targeting both tumour-intrinsic and immunological pathways to combat resistance to current treatment options.

genomics↗

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors

Single cell genomics is essential to chart the complex tumor ecosystem. While single cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumor tissues, single nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each strategy requires modifications to fit the unique characteristics of different tissue and tumor types, posing a barrier to adoption. Here, we developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We tested eight tumor types of varying tissue and sample characteristics (resection, biopsy, ascites, and orthotopic patient-derived xenograft): lung cancer, metastatic breast cancer, ovarian cancer, melanoma, neuroblastoma, pediatric sarcoma, glioblastoma, pediatric high-grade glioma, and chronic lymphocytic leukemia. Analyzing 212,498 cells and nuclei from 39 clinical samples, we evaluated protocols by cell quality, recovery rate, and cellular composition. We optimized protocols for fresh tissue dissociation for different tumor types using a decision tree to account for the technical and biological variation between clinical samples. We established methods for nucleus isolation from OCT embedded and fresh-frozen tissues, with an optimization matrix varying mechanical force, buffer, and detergent. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types and intrinsic expression profiles, but at different proportions. Our work provides direct guidance across a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

genomics↗