Chao Cheng

Gene-Specific Analysis of Clonal Hematopoiesis Identifies ASXL1 as a Risk Factor for Lung Cancer

The paper identifies ASXL1 mutations in clonal hematopoiesis as a risk factor for lung cancer, particularly in smokers, using large population-based cohorts.

Gene signatures characterizing driver mutations in lung squamous carcinoma are predictive of the progression of pre-cancer lesions

This study develops gene expression signatures from LUSC tumors to predict progression risk of precancerous lesions, finding they outperform genomic aberrations in prognosis and correlate with immune features.

GASPS: A Multi-Omics Framework for Defining Genomic Aberration-Driven Signatures and Predicting Patient Outcomes in Lung Cancer

GASPS develops a statistical framework to define genomic aberration-driven signatures and predict patient outcomes in lung cancer using transcriptomic data.

Heterogeneity and plasticity of the naive CD4+ T cell compartment

This study identifies transcriptionally distinct naive CD4+ T cell subsets in mice and humans using scRNA-seq, showing their functional diversity and environmental responsiveness.

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy

The paper develops TimiGP-Response to analyze the tumor immune microenvironment's association with immunotherapy response across multiple cancer types and identifies key immune cell interactions linked to treatment outcomes.

TimiGP: inferring inter-cell functional interactions and clinical values in the tumor immune microenvironment through gene pairs

TimiGP infers functional interactions between immune cells in the tumor microenvironment and identifies their prognostic value using bulk gene expression and survival data.

Genetic variants associated mRNA stability in lung

This study identifies genetic variants associated with mRNA stability (stQTLs) in lung tissue using RNA-seq data, finding they are enriched in CDS and 3UTR regions and overlap more with RNA-binding protein and microRNA binding sites compared to eQTLs.

Tumor cell intrinsic and extrinsic features predicts prognosis in estrogen receptor positive breast cancer

This study identifies genomic and immunological features that predict prognosis in ER+ breast cancer, showing improved performance over Oncotype DX.

Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data

This study compares the performance and efficiency of four machine learning algorithms on a large rectangular biomedical dataset, finding similar accuracy but varying efficiency with dimension reduction.

An integrative ENCODE resource for cancer genomics

The paper develops a custom ENCODE annotation for cancer genomics, highlighting TF-RBP interactions and network rewiring during oncogenesis, and validates findings using experimental assays.

Co-expression enrichment analysis at the single-cell level reveals convergent defects in neural progenitor cells and their cell-type transitions in neurodevelopmental disorders

The paper identifies a convergent defect in neural progenitor cell transitions during fetal development associated with autism and epilepsy using single-cell RNA sequencing and gene co-expression analysis.