Shuqiang Li

The paper identifies recipient stem-cell persistence and T-cell dysregulation as predictors of relapse after HSCT in AML/MDS by analyzing single-cell RNA and TCR sequencing data.

This study shows EED inactivation impairs SCLC tumorigenesis and drives LUAD-to-SCLC transformation, highlighting its role in maintaining SCLC neuroendocrine identity.

This study identifies ASXL1 truncating mutations as a driver of leukemic resistance to T cell attack and proposes EZH2 inhibition as a therapeutic strategy to overcome this resistance.

The paper analyzes single-cell data from bone marrow samples to identify immune cell interactions that predict response to adoptive cellular therapy in myeloid leukemia.

This paper introduces IN-DEPTH and SGCC for spatial multi-omics analysis, revealing EBV-related immunomodulatory differences in DLBCL.

DIISCO infers dynamic intercellular interactions from time-series single-cell data using a Bayesian framework, showing its ability to capture time-dependent communication patterns in simulated and CAR-T cell data.

The paper maps T cell state evolution during response and resistance to adoptive cellular therapy using single-cell transcriptomics and machine learning, identifying key exhausted subsets and their origins.

Seven single-cell and single-nucleus protocols run side by side on the same cell lines, PBMCs and mouse cortex, analysed through one pipeline: 10x Chromium led the high-throughput methods.

The paper analyzes MYOD-mediated reprogramming of human fibroblasts using single-cell RNA-Seq to identify molecular determinants of reprogramming success and failure.

The paper identifies eQTLs in glomerular and tubulointerstitial kidney tissues from nephrotic syndrome patients, finds tissue-specific eQTLs, and integrates them with a GWAS to identify associated genes.

This paper describes a method using DSP fixation to preserve single cells for RNA sequencing, showing it maintains RNA complexity and reduces technical variability.

The paper uses pseudotemporal ordering to analyze single-cell data and reveals dynamics and regulators of cell fate decisions.