Loss of Setd2 Induces the Upregulation of Genes Related to Akt/Mtor Signaling Pathway

Patients with polycystic kidney disease (PKD) have a high risk of developing renal cell carcinoma (RCC). SET domain–containing 2(SETD2) is the only molecule known to regulate lysine trimethylation (H3K3me3) of histone H3 in human tissue, and SETD2 is identified as a tumor suppressor in ccRCC. Although there are some studies revealing some mechanism about PKD developing ccRCC, the underlying mechanism remains largely reported. We collected the Kidney samples from SETD2 conditional knockout mice described before (Rao, 2021) and detected the expression levels of some important genes related to Akt/mTOR signaling pathway. Besides, we found that SETD2 is closely related to Akt/mTOR signaling pathway and can be regulated by Western blot analysis, qRT-PCR and immunofluorescence. For clinical translation, the cross-talks between SETD2 and Akt/mTOR signaling may provide a potential strategy to prevent tumorigenesis in patients with ccRCC therapy

Pan‐Cancer Single‐Nucleus Total RNA Sequencing Using snHH‐Seq

Abstract Tumor heterogeneity and its drivers impair tumor progression and cancer therapy. Single‐cell RNA sequencing is used to investigate the heterogeneity of tumor ecosystems. However, most methods of scRNA‐seq amplify the termini of polyadenylated transcripts, making it challenging to perform total RNA analysis and somatic mutation analysis.Therefore, a high‐throughput and high‐sensitivity method called snHH‐seq is developed, which combines random primers and a preindex strategy in the droplet microfluidic platform. This innovative method allows for the detection of total RNA in single nuclei from clinically frozen samples. A robust pipeline to facilitate the analysis of full‐length RNA‐seq data is also established. snHH‐seq is applied to more than 730 000 single nuclei from 32 patients with various tumor types. The pan‐cancer study enables it to comprehensively profile data on the tumor transcriptome, including expression levels, mutations, splicing patterns, clone dynamics, etc. New malignant cell subclusters and exploring their specific function across cancers are identified. Furthermore, the malignant status of epithelial cells is investigated among different cancer types with respect to mutation and splicing patterns. The ability to detect full‐length RNA at the single‐nucleus level provides a powerful tool for studying complex biological systems and has broad implications for understanding tumor pathology