Pancreatic Cancer Research

ResearcherTongji UniversityActive in the last 2 years

Zhongqiu Wang

ORCID-verified (high confidence, 0.95), identity_conf@1As of 6 November 2026

Matched on ORCID iD 0000-0001-6681-7345; OpenAlex author ID A5030677018. Sources: OpenAlex.

Their work

Papers
33 (first author 2, last author 24)
Trials
0
Grants
0
Labs led
2
Collaborators
33
Papers, trials and grants by year

2013: 2 papers · 2014: none · 2015: none · 2016: none · 2017: 1 paper · 2018: 4 papers · 2019: 4 papers · 2020: 3 papers · 2021: 5 papers · 2022: 2 papers · 2023: 5 papers · 2024: 4 papers · 2025: 2 papers · 2026: 1 paper

Papers 33

  1. Tumor Microenvironment-Responsive Nanoparticles for Pancreatic Cancer Imaging and Treatment. Last author DOI 10.2147/ijn.s624679↗
  2. Developing and validating a computed tomography radiomics strategy to predict lymph node metastasis in pancreatic cancer. Last author DOI 10.4329/wjr.v17.i8.109373↗
  3. Diagnostic Value of Serum D-dimer, CA19-9, and CT Imaging Features in Pancreatic Ductal Adenocarcinoma and Benign Pancreatic Lesions. Last author DOI 10.7150/jca.111548↗
  4. Multimodal Imaging-Guided Photoimmunotherapy of Pancreatic Cancer by Organosilica Nanomedicine. Last author DOI 10.1002/adhm.202302195↗
  5. CT radiomics for Predicting Survival in Patients with Unresectable Pancreatic Ductal Adenocarcinoma after Chemotherapy Last author DOI 10.21203/rs.3.rs-4284696/v1↗
  6. Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma. Last author DOI 10.4251/wjgo.v16.i4.1256↗
  7. Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography. Co-author DOI 10.4329/wjr.v16.i6.211↗
  8. Biomarkers for pancreatic cancer based on tissue and serum metabolomics analysis in a multicenter study. Last author DOI 10.1002/cam4.5296↗
  9. Untargeted metabolomics characterization of the resectable pancreatic ductal adenocarcinoma. Last author DOI 10.1177/20552076231179007↗
  10. Exploring the key genetic association between chronic pancreatitis and pancreatic ductal adenocarcinoma through integrated bioinformatics. Last author DOI 10.3389/fgene.2023.1115660↗
  11. Editorial: Novel circulating biomarkers and radiomics in pancreatic cancer. Last author DOI 10.3389/fonc.2023.1259070↗
  12. A Gold Nanocage Probe Targeting Survivin for the Diagnosis of Pancreatic Cancer. Last author DOI 10.3390/pharmaceutics15051547↗
  13. Application of Unenhanced Computed Tomography Texture Analysis to Differentiate Pancreatic Adenosquamous Carcinoma from Pancreatic Ductal Adenocarcinoma. Last author DOI 10.1007/s11596-022-2535-2↗
  14. Erratum: Emodin-Conjugated PEGylation of Fe3O4 Nanoparticles for FI/MRI Dual-Modal Imaging and Therapy in Pancreatic Cancer [Corrigendum]. Last author DOI 10.2147/ijn.s361728↗
  15. Letter regarding "Complementary role of computed tomography texture analysis for differentiation of pancreatic ductal adenocarcinoma from pancreatic neuroendoc… First author DOI 10.1007/s00261-020-02793-z↗
  16. Emodin-Conjugated PEGylation of Fe3O4 Nanoparticles for FI/MRI Dual-Modal Imaging and Therapy in Pancreatic Cancer. Last author DOI 10.2147/ijn.s335588↗
  17. Serum Exosomal miRNA-1226 as Potential Biomarker of Pancreatic Ductal Adenocarcinoma. Last author DOI 10.2147/ott.s296816↗
  18. Exogenous HMGB1 Promotes the Proliferation and Metastasis of Pancreatic Cancer Cells. Last author DOI 10.3389/fmed.2021.756988↗
  19. Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma. Last author DOI 10.3389/fonc.2021.744667↗
  20. Diagnostic accuracy of unenhanced CT texture analysis to differentiate mass-forming pancreatitis from pancreatic ductal adenocarcinoma. Co-author DOI 10.1007/s00261-020-02506-6↗
  21. Letter regarding "Nonhypervascular pancreatic neuroendocrine tumors: Spectrum of MDCT imaging findings and differentiation from pancreatic ductal adenocarcinom… First author DOI 10.1016/j.ejrad.2020.109282↗
  22. Computed Tomography-Based Radiomics Signature for the Preoperative Differentiation of Pancreatic Adenosquamous Carcinoma From Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.3389/fonc.2020.01618↗
  23. Differentiation of chronic mass-forming pancreatitis from pancreatic ductal adenocarcinoma using contrast-enhanced computed tomography. Last author DOI 10.2147/cmar.s217033↗
  24. Pancreatic Ductal Adenocarcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade. Co-author DOI 10.2147/cmar.s218414↗
  25. A GPC1-targeted and gemcitabine-loaded biocompatible nanoplatform for pancreatic cancer multimodal imaging and therapy. Last author DOI 10.2217/nnm-2019-0063↗
  26. Evaluation of Texture Analysis for the Differential Diagnosis of Mass-Forming Pancreatitis From Pancreatic Ductal Adenocarcinoma on Contrast-Enhanced CT Images. Last author DOI 10.3389/fonc.2019.01171↗
  27. Plectin-1 Targeted Dual-modality Nanoparticles for Pancreatic Cancer Imaging. Last author DOI 10.1016/j.ebiom.2018.03.008↗
  28. The Levels of Tumor Markers in Pancreatic Neuroendocrine Carcinoma and Their Values in Differentiation Between Pancreatic Neuroendocrine Carcinoma and Pancreat… Co-author DOI 10.1097/mpa.0000000000001181↗
  29. The differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma: the values of CT imaging features and texture analysis. Co-author DOI 10.1186/s40644-018-0170-8↗
  30. Oridonin-loaded and GPC1-targeted gold nanoparticles for multimodal imaging and therapy in pancreatic cancer. Last author DOI 10.2147/ijn.s177993↗
  31. Differentiation of pancreatic neuroendocrine carcinoma from pancreatic ductal adenocarcinoma using magnetic resonance imaging: The value of contrast-enhanced a… Co-author DOI 10.18632/oncotarget.17309↗
  32. In vitro study of SPIO-labeled human pancreatic cancer cell line BxPC-3. Last author DOI 10.1002/cmmi.1499↗
  33. VEGF-C ShRNA inhibits pancreatic cancer growth and lymphangiogenesis in an orthotopic fluorescent nude mouse model. Last author PMID 23393331↗

Closest collaborators

The 25 strongest of 33 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

  1. Shuai Ren · 23 shared papers, 2019–2025 · strength 4.25
  2. Kai Guo · 11 shared papers, 2019–2024 · strength 1.61
  3. Yingying Cao · 8 shared papers, 2020–2025 · strength 1.52
  4. Lina Song · 8 shared papers, 2018–2024 · strength 1.19
  5. Wenli Qiu · 8 shared papers, 2018–2026 · strength 1.19
  6. Rui Zhao · 7 shared papers, 2019–2023 · strength 0.99
  7. Rong Chen · 6 shared papers, 2019–2023 · strength 0.93
  8. Xiao Chen · 8 shared papers, 2017–2021 · strength 0.80
  9. Zipeng Lu · 3 shared papers, 2021–2023 · strength 0.48
  10. Ying Tian · 2 shared papers, 2024 · strength 0.47
  11. Yuan Li · 2 shared papers, 2023 · strength 0.36
  12. Huifeng Zhang · 2 shared papers, 2019–2024 · strength 0.30
  13. Yuan Li · 1 shared paper, 2025 · strength 0.28
  14. Yong Zhu · 1 shared paper, 2024 · strength 0.28
  15. Xiaoling Zhuge · 3 shared papers, 2017–2018 · strength 0.25
  16. Chuangen Guo · 3 shared papers, 2017–2018 · strength 0.25
  17. Yongkang Liu · 3 shared papers, 2013–2021 · strength 0.24
  18. Jian He · 1 shared paper, 2023 · strength 0.17
  19. Kai Zhang · 1 shared paper, 2023 · strength 0.17
  20. Donghui Li · 1 shared paper, 2023 · strength 0.17
  21. Li Zhu · 1 shared paper, 2021 · strength 0.14
  22. Cheng Wang · 1 shared paper, 2021 · strength 0.13
  23. Xin Chen · 1 shared paper, 2021 · strength 0.13
  24. Jianhua Wang · 1 shared paper, 2021 · strength 0.13
  25. Tao Li · 1 shared paper, 2021 · strength 0.13

How to reach this person

A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.