Evidence map›Paper›PMID 34984415›Full record

ArticleComputational and systems oncology2021

A validated mathematical model of FGFR3-mediated tumor growth reveals pathways to harness the benefits of combination targeted therapy and immunotherapy in bladder cancer.

Kamaldeen Okuneye, Daniel Bergman, Jeffrey C Bloodworth, Alexander T Pearson, Randy F Sweis, Trachette L Jackson

Open access · goldAbstract read
In one paragraph

Article in Computational and systems oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Mathematical Modeling ofBioengineering (Basel, Switzerland) · 2025
    Article
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  9. Mathematical Modeling Support for Lung Cancer Therapy-A Short Review.International journal of molecular sciences · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Kamaldeen OkuneyeApplied BioMath, LLC, Concord, Massachusetts, USA.
Daniel BergmanDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, USA.
Jeffrey C BloodworthSection of Hematology/Oncology, Department of Medicine, The University of Chicago, Chicago, Illinois, USA.
Alexander T PearsonSection of Hematology/Oncology, Department of Medicine, The University of Chicago, Chicago, Illinois, USA.
Randy F SweisSection of Hematology/Oncology, Department of Medicine, The University of Chicago, Chicago, Illinois, USA.
Trachette L JacksonDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0000-0003-2803-3341
University of Chicago · USUniversity of Michigan · USApplied BioMath (United States) · US

Funding

Multiscale Computational Models Guided By Emerging Cellular Dynamics Quantification For Predicting Optimum Immune Checkpoint And Targeted Therapy SchedulesU01CA243075 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI JACKSON, TRACHETTE · 2020 to 2024
$2.6M
Elucidating immunotherapy resistance mechanisms in non-T cell-inflamed bladder cancerK08CA234392 · NCI · UNIVERSITY OF CHICAGO · PI SWEIS, RANDY F. · 2018 to 2021
$851k
NCI NIH HHS K08 CA234392NCI NIH HHS U01 CA243075
6 · The paper itself

Abstract

Bladder cancer is a common malignancy with over 80,000 estimated new cases and nearly 18,000 deaths per year in the United States alone. Therapeutic options for metastatic bladder cancer had not evolved much for nearly four decades, until recently, when five immune checkpoint inhibitors were approved by the U.S. Food and Drug Administration (FDA). Despite the activity of these drugs in some patients, the objective response rate for each is less than 25%. At the same time, fibroblast growth factor receptors (FGFRs) have been attractive drug targets for a variety of cancers, and in 2019 the FDA approved the first therapy targeted against FGFR3 for bladder cancer. Given the excitement around these new receptor tyrosine kinase and immune checkpoint targeted strategies, and the challenges they each may face on their own, emerging data suggest that combining these treatment options could lead to improved therapeutic outcomes. In this paper, we develop a mathematical model for FGFR3-mediated tumor growth and use it to investigate the impact of the combined administration of a small molecule inhibitor of FGFR3 and a monoclonal antibody against the PD-1/PD-L1 immune checkpoint. The model is carefully calibrated and validated with experimental data before survival benefits, and dosing schedules are explored. Predictions of the model suggest that FGFR3 mutation reduces the effectiveness of anti-PD-L1 therapy, that there are regions of parameter space where each monotherapy can outperform the other, and that pretreatment with anti-PD-L1 therapy always results in greater tumor reduction even when anti-FGFR3 therapy is the more effective monotherapy.

Indexed as

bladder cancerFGFR3-targeted therapyimmune checkpoint inhibitorsmathematical model

Identifiers

PMID34984415
PMCPMC8722426
OpenAlexW3165651406

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.