Wei Lü

UniST: A Unified Computational Framework for 3D Spatial Transcriptomics Reconstruction

UniST reconstructs dense 3D spatial transcriptomics data from sparse serial sections, restoring structural continuity and biologically meaningful expression patterns in multiple tissue contexts.

An Interpretable Multi-instance Learner Decodes Cellular Recruitment from Spatially Resolved Transcriptomics

This study introduces a deep learning model called spacer to analyze spatially resolved transcriptomics data, revealing novel insights into cellular recruitment mechanisms in tumors and heart tissue during myocarditis.

Tissue Factor Expression in Penile Squamous Cell Carcinoma: A Marker of HPV-Independent Disease

This study evaluates tissue factor (TF) and TROP2 expression in penile squamous cell carcinoma (PSCC) and links TF to HPV-independent, p53-aberrant disease while TROP2 correlates with HPV-associated PSCC.

Comparison of imaging-based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed, paraffin-embedded tumor samples

This study compares imaging-based spatial transcriptomics platforms using FFPE tumor samples, finding differences in performance and highlighting factors affecting data quality.

Coordinated translational control of multiple immune checkpoints by the integrated stress response pathway in lung cancer

The paper shows that the integrated stress response (ISR) coordinates the translation of PD-L1 and CD155, two immune checkpoint proteins, in lung cancer, and suggests combining ISR inhibition with PD-1 blockade as a therapeutic strategy.

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

DeMixT improves transcriptomic deconvolution by estimating component proportions and expression profiles in heterogeneous samples, showing high accuracy in validation and TCGA data.