Evidence map›Paper›PMID 35820346›Full record

ReviewOral oncology2022

The mouse oral carcinoma (MOC) model: A 10-year retrospective on model development and head and neck cancer investigations.

Michihisa Kono, Shin Saito, Ann Marie Egloff, Clint T Allen, Ravindra Uppaluri

Open access · greenAbstract readReview
In one paragraph

Review in Oral oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.6field-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

30 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
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  7. Sex influences on tumor innervation.Biology of sex differences · 2026
    Article
  8. Article
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  11. Review
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  16. Nerve Types and Classification of Neurons Innervating Oral Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  17. Review
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  19. Roles of ZEB1 and ZEB2 in E-cadherin expression and cell aggressiveness in head and neck cancer.Genes to cells : devoted to molecular & cellular mechanisms · 2024
    Article
  20. 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

5 authors at 4 institutions in 2 countries.

Michihisa KonoDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States; Department of Otolaryngology - Head and Neck Surgery, Asahikawa Medical University, Asahikawa, Japan. Electronic address: Michihisa_Kono@DFCI.HARVARD.EDU.
Shin SaitoDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States; Department of Otolaryngology - Head and Neck Surgery, Keio University School of Medicine, Tokyo, Japan. Electronic address: SHIN_SAITO@DFCI.HARVARD.EDU.
Ann Marie EgloffDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States; Department of Surgery/Otolaryngology, Brigham and Women's Hospital, United States. Electronic address: aegloff@bwh.harvard.edu.
Clint T AllenSection on Translational Tumor Immunology, National Institutes on Deafness and Communication Disorders, NIH, Bethesda, MD, United States. Electronic address: clint.allen@nih.gov.
Ravindra UppaluriDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States; Department of Surgery/Otolaryngology, Brigham and Women's Hospital, United States. Electronic address: RAVINDRA_UPPALURI@DFCI.HARVARD.EDU.
Brigham and Women's Hospital · USAsahikawa Medical University · JPKeio University · JPNational Institute on Deafness and Other Communication Disorders · US

Funding

Characterization and Enhancement of Anti-Tumor Immune Responses in Head and Neck CancerZIADC000087 · NIDCD · NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS · PI ALLEN, CLINT · 2015 to 2022
$13.5M
Defining mechanisms of immunotherapy resistance in head and neck squamous cell carcinomasU01DE029188 · NIDCR · DANA-FARBER CANCER INST · PI BARBIE, DAVID A, HADDAD, ROBERT I. · 2019 to 2019
$4.3M
Immunotherapeutic responses to neoantigens in head and neck cancerR01DE027736 · NIDCR · DANA-FARBER CANCER INST · PI UPPALURI, RAVINDRA · 2018 to 2022
$2.9M
NIDCR NIH HHS R01 DE027736NIDCR NIH HHS U01 DE029188
6 · The paper itself

Abstract

Preclinical models of cancer have long been paramount to understanding tumor development and advancing the treatment of cancer. Creating preclinical models that mimic the complexity and heterogeneity of human tumors is a key challenge in the advancement of cancer therapy. About ten years ago, we created the mouse oral carcinoma (MOC) cell line models that were derived from 7, 12-dimethylbenz(a) anthracene (DMBA)-induced mouse oral squamous cell cancers. This model has been used in numerous investigations, including studies on tumor biology and therapeutics. We have seen remarkable progress in cancer immunology in recent years, and these cell lines, which are syngeneic to C57BL/6 background, have also been used to study the anti-tumor immune response. Herein, we aim to review the MOC model from its development and characterization to its use in non-immunological and immunological preclinical head and neck squamous cell carcinoma (HNSCC) studies. Integrating and refining these MOC model studies and extending findings to other systems will provide crucial insights for translational approaches aimed at improving head and neck cancer treatment.

Indexed as

Carcinoma, Squamous CellHead and Neck NeoplasmsMouth NeoplasmsAnimalsCell Line, TumorDisease Models, AnimalHumansMiceMice, Inbred C57BLRetrospective StudiesSquamous Cell Carcinoma of Head and NeckCarcinogen-induced cancerImmunocompetent mouse modelsOral squamous cell carcinoma

Identifiers

PMID35820346
PMCPMC9364442
OpenAlexW4284959821

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.