Pancreatic Cancer Research

ResearcherMemorial Sloan Kettering Cancer CenterNo recent work listed

Brian J. McCarthy

Verified by NIH RePORTER profile ID (good confidence)As of 13 November 2026

Matched on NIH RePORTER profile ID 8335686.

Their work

Counts cover pancreatic cancer work only: a researcher’s other papers, trials and grants are not in these records.

Pancreatic cancer papers
3
Pancreatic cancer trials
0
Pancreatic cancer grants
1
Collaborators
11
Papers, trials and grants by year

2018: 1 paper · 2019: none · 2020: 1 grant · 2021: none · 2022: 2 papers

Papers 3

  1. Circulating tumor and invasive cell expression profiling predicts effective therapy in pancreatic cancer. Co-author DOI 10.1002/cncr.34269↗
  2. ChemoSensitivity Assay Guided Metronomic Chemotherapy Is Safe and Effective for Treating Advanced Pancreatic Cancer. Co-author DOI 10.3390/cancers14122906↗
  3. Circulating Tumor and Invasive Cell Gene Expression Profile Predicts Treatment Response and Survival in Pancreatic Adenocarcinoma. Co-author DOI 10.3390/cancers10120467↗

Grants 1

  1. Pharmacogenomic and circulating tumor cell approach to individualized treatment of pancreatic cancer R01CA202762↗

Closest collaborators

The 11 strongest of 11 ranked by shared papers, trials and grants, with recent and small-team work weighing most.

  1. Kenneth H. Yu · 3 shared papers, 1 shared grant, 2018–2022
  2. Mark Ricigliano · 1 shared paper, 1 shared grant, 2018–2020
  3. William H. Isacoff · 1 shared paper, 2022
  4. Eileen Mary O'Reilly · 2 shared papers, 2018–2022
  5. Marinela Capanu · 2 shared papers, 2018–2022
  6. Anna M. Varghese · 1 shared paper, 2022
  7. Ghassan K. Abou-Alfa · 1 shared paper, 2022
  8. Wungki Park · 1 shared paper, 2022
  9. Andrew S. Epstein · 1 shared paper, 2022
  10. David Paul Kelsen · 1 shared paper, 2022
  11. Maeve Aine Lowery · 1 shared paper, 2018

How to reach this person

A chain of introductions through people who have published, run trials or held grants together (the fewest links first, then the links with the most shared work). Built from public records only; no contact details are kept.