Evidence map›Paper›PMID 35402248›Full record

ArticleFrontiers in oncology2022

Paclitaxel Chemotherapy Elicits Widespread Brain Anisotropy Changes in a Comprehensive Mouse Model of Breast Cancer Survivorship: Evidence From

Lauren D Otto, Kathryn L G Russart, Praveen Kulkarni, Dana M McTigue, Craig F Ferris, Leah M Pyter

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 16% 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, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
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  12. Microglia contribute to mammary tumor-induced neuroinflammation in a female mouse model.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2024
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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 4 institutions in 1 country.

Lauren D OttoInstitute for Behavioral Medicine Research, Ohio State University Wexner Medical Center, Columbus, OH, United States.
Kathryn L G RussartInstitute for Behavioral Medicine Research, Ohio State University Wexner Medical Center, Columbus, OH, United States.
Praveen KulkarniCenter for Translational Neuroimaging, Department of Psychology and Pharmaceutical Sciences, Northeastern University, Boston, MA, United States.
Dana M McTigueDepartment of Neuroscience, Ohio State University, Columbus, OH, United States.
Craig F FerrisCenter for Translational Neuroimaging, Department of Psychology and Pharmaceutical Sciences, Northeastern University, Boston, MA, United States.
Leah M PyterInstitute for Behavioral Medicine Research, Ohio State University Wexner Medical Center, Columbus, OH, United States.
Institute for Behavioral Medicine · USNortheastern University · USThe Ohio State University · USThe Ohio State University Wexner Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is one of the most common diseases in the United States with 1 in 8 women developing the disease in her lifetime. Women who develop breast cancer are often post-menopausal and undergo a complex sequence of treatments including surgery, chemotherapy, and aromatase inhibitor therapy. Both independently and through potential interactions, these factors and treatments are associated with behavioral comorbidities reported in patients (e.g., fatigue), although the underlying neurobiological mechanisms are poorly understood. Currently, brain imaging is the most feasible way to assess neurobiology in patients. Indeed, breast cancer patients display alterations in white matter connections and chemotherapy is associated with decreased white and gray matter in the corpus callosum and cortex as well as decreased hippocampal volume. However, imaging in breast cancer rodent models is lacking, impeding translation of the mechanistic neurobiological findings made possible through modeling. Furthermore, current rodent models of breast cancer often lack the complexity of typical multimodal breast cancer treatments, thereby limiting translational value. The present study aimed to develop a comprehensive model of post-menopausal breast cancer survival using immunocompetent ovariectomized mice, including an orthotopic syngeneic tumor, surgical tumor removal, chemotherapy, and aromatase inhibitor therapy. Using this model, we systematically investigated the cumulative effects of chemotherapy and hormone replacement therapy on neurostructure and behavior using diffusion weighted imaging, open field test, and spontaneous alternation test. Our previous findings, in a simplified chemotherapy-only model, indicate that this regimen of chemotherapy causes circulating and central inflammation concurrent with reduced locomotor activity. The current study, in the more comprehensive model, has recapitulated the peripheral inflammation coincident with reduced locomotor activity as well as demonstrated that chemotherapy also drives widespread changes in brain anisotropy. Validating the clinical relevance of this comprehensive rodent breast cancer model will allow for additional neurobiological investigations of the interactions among various cancer components associated with behavioral comorbidities, as well as the relationship between these mechanisms and neurostructural imaging changes that can be measured in cancer patients.

Indexed as

comorbiditiescytokinesDTI/DWIfatiguemammary tumorsurvivortranslational

Identifiers

PMID35402248
PMCPMC8984118
OpenAlexW4220671095

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.