Evidence map›Paper›PMID 30129680›Full record

ArticleMolecular carcinogenesis2018

Dual use of hematopoietic and mesenchymal stem cells enhances engraftment and immune cell trafficking in an allogeneic humanized mouse model of head and neck cancer.

John J Morton, Stephen B Keysar, Loni Perrenoud, Tugs-Saikhan Chimed, Julie Reisinger, Brian Jackson, Phuong N Le, Cera Nieto, Karina Gomez, Bettina Miller and 4 more

Abstract read
In one paragraph

Article in Molecular carcinogenesis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

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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

14 authors.

John J MortonDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.ORCID 0000-0002-4171-8858
Stephen B KeysarDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Loni PerrenoudDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Tugs-Saikhan ChimedDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Julie ReisingerDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Brian JacksonDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Phuong N LeDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Cera NietoDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Karina GomezDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Bettina MillerDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.
Dexiang GaoDepartment of Biostatistics and Informatics, School of Medicine, University of Colorado, Aurora, Colorado.
Hilary SomersetDepartment of Pathology, School of Medicine, University of Colorado, Aurora, Colorado.
Xiao-Jing WangDepartment of Pathology, School of Medicine, University of Colorado, Aurora, Colorado.
Antonio JimenoDivision of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado, Aurora, Colorado.

Funding

University of Colorado Cancer Center Support Grant - Lung Cancer Patient-Derived Xenografts with Autologous Human Immune SystemsP30CA046934 · NCI · UNIVERSITY OF COLORADO DENVER · PI James V Degregori · 1988 to 2026
$117.0M
Targeting PD-L1 interactome signaling to enhance immunotherapy efficacy in head and neck squamous cell cancerR01CA149456 · NCI · UNIVERSITY OF COLORADO DENVER · PI Antonio Jimeno · 2010 to 2026
$5.6M
Training in Translational Research of Lung, Head and Neck CancerT32CA174648 · NCI · UNIVERSITY OF COLORADO DENVER · PI KARAM, SANA D · 2013 to 2022
$4.2M
Institutional Training in Otolaryngology ResearchT32DC012280 · NIDCD · UNIVERSITY OF COLORADO DENVER · PI Yuri Agrawal, Sue C. Kinnamon · 2013 to 2026
$3.4M
Identifying oral cancer stem cell properties affected by the microenvironmentR01DE024371 · NIDCR · UNIVERSITY OF COLORADO DENVER · PI JIMENO, ANTONIO, WANG, XIAO-JING · 2014 to 2017
$2.1M
Development of an autologous humanized model of melanoma exploring human thymic education capacityR01CA213102 · NCI · UNIVERSITY OF COLORADO DENVER · PI JIMENO, ANTONIO · 2017 to 2019
$1.7M
NCI NIH HHS P30 CA046934NCI NIH HHS R01 CA149456NCI NIH HHS R01 CA213102NCI NIH HHS T32 CA174648NIDCD NIH HHS T32 DC012280NIDCR NIH HHS R01 DE024371
6 · The paper itself

Abstract

In this report, we describe in detail the evolving procedures to optimize humanized mouse cohort generation, including optimal conditioning, choice of lineage for engraftment, threshold for successful engraftment, HNSCC tumor implantation, and immune and stroma cell analyses. We developed a dual infusion protocol of human hematopoietic stem and progenitor cells (HSPCs) and mesenchymal stem cells (MSCs), leading to incremental human bone marrow engraftment, and exponential increase in mature peripheral human immune cells, and intratumor homing that includes a more complete lineage reconstitution. Additionally, we have identified practical rules to predict successful HSPC/MSC expansion, and a peripheral human cell threshold associated with bone marrow engraftment, both of which will optimize cohort generation and management. The tremendous advances in immune therapy in cancer have made the need for appropriate and standardized models more acute than ever, and therefore, we anticipate that this manuscript will have an immediate impact in cancer-related research. The need for more representative tools to investigate the human tumor microenvironment (TME) has led to the development of humanized mouse models. However, the difficulty of immune system engraftment and minimal human immune cell infiltration into implanted xenografts are major challenges. We have developed an improved method for generating mismatched humanized mice (mHM), using a dual infusion of human HSPCs and MSCs, isolated from cord blood and expanded in vitro. Engraftment with both HSPCs and MSCs produces mice with almost twice the percentage of human immune cells in their bone marrow, compared to mice engrafted with HSPCs alone, and yields 9- to 38-fold higher levels of mature peripheral human immune cells. We identified a peripheral mHM blood human B cell threshold that predicts an optimal degree of mouse bone marrow humanization. When head and neck squamous cell carcinoma (HNSCC) tumors are implanted on the flanks of HSPC-MSC engrafted mice, human T cells, B cells, and macrophages infiltrate the stroma of these tumors at 2- to 8-fold higher ratios. In dually HSPC-MSC engrafted mice we also more frequently observed additional types of immune cells, including regulatory T cells, cytotoxic T cells, and MDSCs. Higher humanization was associated with in vivo response to immune-directed therapy. The complex immune environment arising in tumors from dually HSPC-MSC engrafted mice better resembles that of the originating patient's tumor, suggesting an enhanced capability to accurately recapitulate a human TME.

Indexed as

Disease Models, AnimalHematopoietic Stem CellsHematopoietic Stem Cell TransplantationMesenchymal Stem CellsMesenchymal Stem Cell TransplantationAnimalsBiomarkersHead and Neck NeoplasmsHumansImmunophenotypingMiceMice, KnockoutTransplantation, HeterologousBiomarkerscancer microenvironmenthead and neck cancerhematopoietic stem cellhumanized mouse modelpatient-derived xenograft

Identifiers

PMID30129680
PMCPMC6452868

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Registered trials

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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.