JSJian Shi

Jian Shi

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Jian Shi has a total of 11 co-authors. Here are the top co-authors by number of shared publications:

  • Gaoming Liao

    Guangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University

    1 shared publication
  • Jinwei Li

    Guangzhou Medical University, Guangzhou, People’s Republic of China

    1 shared publication
  • Li Liu

    Interdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, Fujian, China

    1 shared publication
  • Min Zhang

    Key Laboratory of Infection and Immunity, Health Commission of Jiangxi Province and School of Basic Medicine, Nanchang Medical College, Nanchang, People’s Republic of China

    1 shared publication
  • Qi Liu

    State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, The First Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China

    1 shared publication
  • Qin

    Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, Harbin, People’s Republic of China

    1 shared publication

Latest Publications

  • Open Access

    Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma

    by Shangyi Luo, Li Liu, Yang Sun, Jian Shi, Yajing Zhang

    Introduction: Intra-tumoral heterogeneity is a prominent characteristic of hepatocellular carcinoma (HCC). However, it remains unexplored whether intra-tumoral transcriptomic differences can capture crucial information regarding HCC evolution and be utilized to derive a predictive signature for patient’s clinical trajectories.Methods: We quantified transcriptomic heterogeneity using four multiregional HCC cohorts comprising 172 samples from 37 patients, and validated transcriptomic heterogeneity and spatial dynamics using multiregional single-cell transcriptomic profiling of 110,817 cells from 34 liver specimens. The HCC evolutionary signature (HCCEvoSig) was developed and assessed across six cross-platform HCC cohorts.Results: Genes exhibiting high intra- and inter-tumor expression variation were significantly enriched in a gene set associated with HCC prognosis, from which we developed and validated a reproducible and robust transcriptomic signature, HCCEvoSig. Multiregional single-cell data confirmed the high intra- and inter-tumoral heterogeneity of HCCEvoSig genes across different cell types, and importantly, demonstrated that the dysregulation of HCCEvoSig genes exhibited a geospatially gradual transition from the non-tumor region to the tumor border and tumor core, as well as from non-malignant to malignant epithelial cells. HCCEvoSig showed significant positive associations with adverse features of HCC, and a high HCCEvoSig risk score predicted increased risks of disease progression and mortality, independent of established clinicopathological indices. Furthermore, HCCEvoSig outperformed 15 published signatures in discriminative ability and prognostic accuracy, particularly regarding 1-year survival rates. Notably, HCCEvoSig demonstrated predictive utility for responses to immunotherapy and trans-arterial chemoembolization. Additionally, we established a well-calibrated predictive nomogram that integrates HCCEvoSig and TNM stage to generate an individualized numerical probability of mortality.Conclusion: Our study reveals that regional transcriptional heterogeneity within tumors is substantial enough to capture survival signals, and the constructed and validated HCCEvoSig provides reliable prognostic information for HCC patients.