Pancreatic Cancer Research

ResearcherJohns Hopkins UniversityActive in the last 2 years

Denis Wirtz

Matched on ORCID iD 0000-0001-6147-3045; OpenAlex author ID A5003835601; NIH RePORTER profile ID 3127500. Sources: OpenAlex.

Their work

Papers
7 (first author 0, last author 2)
Trials
0
Grants
6
Labs led
1
Collaborators
24
Papers, trials and grants by year

2012: 1 grant · 2013: none · 2014: 1 grant · 2015: none · 2016: 1 grant · 2017: 1 paper · 2018: none · 2019: none · 2020: none · 2021: none · 2022: 1 paper · 2023: 2 papers · 2024: 1 paper · 2025: none · 2026: 2 papers, 3 grants

Papers 7

  1. Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. Last author DOI 10.1016/j.cpblue.2026.100008↗
  2. Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer Co-author DOI 10.64898/2026.03.03.709150↗
  3. Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings. Co-author DOI 10.1126/sciadv.ado5103↗
  4. Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer. Co-author DOI 10.1016/j.medj.2022.11.009↗
  5. Intraparenchymal metastases as a cause for local recurrence of pancreatic cancer. Last author DOI 10.1111/his.14839↗
  6. CODA: quantitative 3D reconstruction of large tissues at cellular resolution Co-author DOI 10.1038/s41592-022-01650-9↗
  7. Computational discovery of tissue morphology biomarkers in very long-term survivors with pancreatic ductal adenocarcinoma Co-author DOI 10.1101/207969↗

Grants 6

  1. Engineering self-propelled tumor-infiltrating CAR T cells using synthetic velocity receptors R01CA300052↗
  2. T32: Predoctoral and Postdoctoral Training Program in Nanotechnology for Cancer Research T32CA153952↗
  3. RTB 1 U54CA268083↗
  4. Single-cell phenotyping for therapeutic stratification in pancreatic cancer R01CA174388↗
  5. The Johns Hopkins Cancer Nanotechnology Training Center R25CA153952↗
  6. T-32 NIH Postdoctoral Training Program in Nanotechnology for Cancer Medicine NTCM T32CA130840↗

Closest collaborators

The 24 strongest of 24 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

  1. Laura DeLong Wood · 7 shared papers, 1 shared grant, 2017–2026 · strength 2.21
  2. Pei-Hsun wu · 3 shared papers, 1 shared grant, 2023–2026 · strength 1.56
  3. Ashley L. Kiemen · 6 shared papers, 2022–2026 · strength 1.14
  4. Ralph H. Hruban · 6 shared papers, 2017–2026 · strength 0.99
  5. Pei-Hsun Wu · 4 shared papers, 2017–2026 · strength 0.65
  6. Toby C. Cornish · 3 shared papers, 2022–2026 · strength 0.58
  7. André Forjaz · 2 shared papers, 2026 · strength 0.46
  8. Won Jin Ho · 2 shared papers, 2026 · strength 0.46
  9. David Zwicker · 1 shared paper, 2024 · strength 0.23
  10. Dimitrios N. Sidiropoulos · 1 shared paper, 2026 · strength 0.22
  11. Elana Judith Fertig · 1 shared paper, 2026 · strength 0.22
  12. Paola A. Guerrero · 1 shared paper, 2026 · strength 0.22
  13. Luciane Tsukamoto Kagohara · 1 shared paper, 2026 · strength 0.22
  14. Vincent Bernard Pagan · 1 shared paper, 2026 · strength 0.22
  15. Anirban Maitra · 1 shared paper, 1 shared grant, 2014–2017 · strength 0.22
  16. Jin Peng He · 1 shared paper, 2023 · strength 0.17
  17. Alexander Ioannis Damanakis · 1 shared paper, 2023 · strength 0.17
  18. Nicholas Jason Roberts · 1 shared paper, 2023 · strength 0.17
  19. Elliot K. Fishman · 1 shared paper, 2023 · strength 0.17
  20. Daniel A. Laheru · 1 shared paper, 2023 · strength 0.17
  21. Hai-Quan Mao · 1 shared grant, 2014 · strength 0.14
  22. Seung‐Mo Hong · 1 shared paper, 2022 · strength 0.12
  23. Jacob S. Sarnecki · 1 shared paper, 2017 · strength 0.08
  24. Christopher Lee Wolfgang · 1 shared paper, 2017 · strength 0.08

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.