Jing Wang

This study shows that in vitro-derived cDC1s resemble tumor-infiltrating DCs and that MHC-I and MHC-II antigen presentation by these cells is essential for effective cancer immunotherapy.

This study identifies YAP1-positive cells in relapsed SCLC that exhibit drug tolerance and transition from SCLC to LCNEC-like features, losing some targets but gaining others.

This study clarifies that NOTCH1 acts as a tumor suppressor in head and neck cancer, reducing cancer stem cells and improving prognosis, despite conflicting prior reports.

This study identifies PDK1 and YAP1/TEAD signaling as drivers of acquired resistance to KRAS inhibitors in NSCLC and suggests their co-targeting as a potential therapeutic strategy.

This study uses CyTOF to profile circulating tumor cells in SCLC patients, identifying subtype-specific markers and treatment response correlations.

This study shows that BRAFV600E-driven lung cancer requires ERBB receptor signaling via ligand-mediated activation, and combined inhibition of BRAFV600E and ERBB improves therapeutic outcomes.

This study identifies three distinct DDR phenotypes in SCLC associated with chemotherapy response and tumor evolution.

This study identifies PI3K-mTOR pathway inhibition as a strategy to overcome acquired resistance to KRASG12C inhibitors in NSCLC by targeting 4E-BP1.

This study shows that SMARCA4 mutations in lung cancer disrupt enhancer landscapes and innate immune gene expression, leading to immunotherapy resistance.

This study shows NPRL2 gene therapy reduces lung metastases in KRAS/STK11 mutant NSCLC in humanized mice by enhancing immune cell infiltration and reducing T cell inhibitory signals.

CombPDX evaluates drug synergism in PDX models using tumor growth curves and provides statistical metrics and inference procedures for combination effects.

This study examines genomic and TCR repertoire heterogeneity in SCLC, finding that lower TCR heterogeneity and mutational burden correlate with better survival.

The paper introduces OBIF, a systems model that identifies molecular drivers of synergy by integrating statistical and biological interactions from omics data.