Evidence map›Paper›PMID 37289729›Full record

ArticlePLoS computational biology2023

Computational simulations of tumor growth and treatment response: Benefits of high-frequency, low-dose drug regimens and concurrent vascular normalization.

Mohammad R Nikmaneshi, Rakesh K Jain, Lance L Munn

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
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

3 authors at 2 institutions in 2 countries.

Mohammad R NikmaneshiEdwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Rakesh K JainEdwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
Lance L MunnEdwin L. Steele Laboratories, Department of Radiation Oncology, Harvard Medical School and Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.ORCID 0000-0003-0698-7232
Harvard University · USSharif University of Technology · IR

Funding

Targeting physical stress-driven mechanisms to overcome glioblastoma treatment resistanceU01CA261842 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI JAIN, RAKESH K., MUNN, LANCE L. · 2021 to 2025
$3.1M
Improving treatment of HER2+ breast cancer brain metastasis by targeting lipid metabolismR01CA259253 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI JAIN, RAKESH K., VANDER HEIDEN, MATTHEW G. · 2021 to 2025
$2.3M
Reprogramming the tumormicroenvironment to improve immunotherapy of glioblastomaR01CA269672 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Rakesh K. Jain · 2022 to 2026
$1.9M
Multiplexed device for rapid coagulopathy testingR21EB031982 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI HARDIN, CHARLES COREY, MUNN, LANCE L. · 2021 to 2021
$462k
NCI NIH HHS R01 CA259253NCI NIH HHS R01 CA269672NCI NIH HHS U01 CA261842NIBIB NIH HHS R21 EB031982
6 · The paper itself

Abstract

Implementation of effective cancer treatment strategies requires consideration of how the spatiotemporal heterogeneities within the tumor microenvironment (TME) influence tumor progression and treatment response. Here, we developed a multi-scale three-dimensional mathematical model of the TME to simulate tumor growth and angiogenesis and then employed the model to evaluate an array of single and combination therapy approaches. Treatments included maximum tolerated dose or metronomic (i.e., frequent low doses) scheduling of anti-cancer drugs combined with anti-angiogenic therapy. The results show that metronomic therapy normalizes the tumor vasculature to improve drug delivery, modulates cancer metabolism, decreases interstitial fluid pressure and decreases cancer cell invasion. Further, we find that combining an anti-cancer drug with anti-angiogenic treatment enhances tumor killing and reduces drug accumulation in normal tissues. We also show that combined anti-angiogenic and anti-cancer drugs can decrease cancer invasiveness and normalize the cancer metabolic microenvironment leading to reduced hypoxia and hypoglycemia. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity.

Indexed as

Antineoplastic AgentsNeoplasmsAngiogenesis InhibitorsHumansImmunotherapyNeovascularization, PathologicPharmaceutical PreparationsTumor MicroenvironmentAngiogenesis InhibitorsAntineoplastic AgentsPharmaceutical Preparations

Identifiers

PMID37289729
PMCPMC10249820
OpenAlexW4379931480

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.