Multi-organ single-cell transcriptomics of immune cells uncovered organ-specific gene expression and functions.

Despite the wealth of publicly available single-cell datasets, our understanding of distinct resident immune cells and their unique features in diverse human organs remains limited. To address this, we compiled a meta-analysis dataset of 114,275 CD45+ immune cells sourced from 14 organs in healthy donors. While the transcriptome of immune cells remains relatively consistent across organs, our analysis has unveiled organ-specific gene expression differences (GTPX3 in kidney, DNTT and ACVR2B in thymus).

Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome.

Singleton or low-frequency driver mutations are challenging to identify. We present a domain driver mutation estimator (DOME) to identify rare candidate driver mutations. DOME analyzes positions analogous to known statistical hotspots and resistant mutations in combination with their functional and biochemical residue context as determined by protein structures and somatic mutation propensity within conserved PFAM domains, integrating the CADD scoring scheme.

Novel covalent CDK7 inhibitor potently induces apoptosis in acute myeloid leukemia and synergizes with Venetoclax.

Introduction: The emergence of resistance to the highly successful BCL2-directed therapy is a major unmet need in acute myeloid leukemia (AML), an aggressive malignancy with poor survival rates. Towards identifying therapeutic options for AML patients who progress on BCL2-directed therapy, we studied a clinical-stage CDK7 inhibitor XL102, which is being evaluated in solid tumors (NCT04726332).

Materials And Methods: To determine the anti-proliferative effects of XL102, we performed experiments including time-resolved fluorescence resonance energy transfer, target occupancy, cell cycle and apoptosis-based assays.

An integrated approach to determine the abundance, mutation rate and phylogeny of the SARS-CoV-2 genome.

The analysis of the SARS-CoV-2 genome datasets has significantly advanced our understanding of the biology and genomic adaptability of the virus. However, the plurality of advanced sequencing datasets-such as short and long reads-presents a formidable computational challenge to uniformly perform quantitative, variant or phylogenetic analysis, thus limiting its application in public health laboratories engaged in studying epidemic outbreaks. We present a computational tool, Infectious Pathogen Detector (IPD), to perform integrated analysis of diverse genomic datasets, with a customized analytical module for the SARS-CoV-2 virus.