Evidence map›Paper›PMID 24748380›Full record

ArticlePloS one2014

Quantitative proteomic analysis of oral brush biopsies identifies secretory leukocyte protease inhibitor as a promising, mechanism-based oral cancer biomarker.

Ya Yang, Nelson L Rhodus, Frank G Ondrey, Beverly R K Wuertz, Xiaobing Chen, Yaqin Zhu, Timothy J Griffin

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Saliva proteomics updates in biomedicine.Journal of biological research (Thessalonike, Greece) · 2019
    Review
  10. Article
  11. Review
  12. Article
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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

7 authors.

Ya YangDepartment of General Dentistry, Ninth People's Hospital, School of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai, China.
Nelson L RhodusOral Medicine, Diagnosis and Radiology, School of Dentistry, University of Minnesota, Minneapolis, Minnesota, United States of America.
Frank G OndreyDepartment of Otolaryngology, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America.
Beverly R K WuertzDepartment of Otolaryngology, Medical School, University of Minnesota, Minneapolis, Minnesota, United States of America.
Xiaobing ChenDepartment of Oral Medicine, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
Yaqin ZhuDepartment of General Dentistry, Ninth People's Hospital, School of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai, China.
Timothy J GriffinDepartment of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, Minnesota, United States of America.

Funding

Characterizing Oral Cancer Progression via Saliva ProteomicsR01DE017734 · NIDCR · UNIVERSITY OF MINNESOTA · PI GRIFFIN, TIMOTHY J. · 2007 to 2010
$1.4M
NIDCR NIH HHS 1R01DE017734NIDCR NIH HHS R01 DE017734
6 · The paper itself

Abstract

A decrease in the almost fifty percent mortality rate from oral cancer is needed urgently. Improvements in early diagnosis and more effective preventive treatments could affect such a decrease. Towards this end, we undertook for the first time an in-depth mass spectrometry-based quantitative shotgun proteomics study of non-invasively collected oral brush biopsies. Proteins isolated from brush biopsies from healthy normal tissue, oral premalignant lesion tissue (OPMLs), oral squamous cell carcinoma (OSCC) and matched control tissue were compared. In replicated proteomic datasets, the secretory leukocyte protease inhibitor (SLPI) protein stood out based on its decrease in abundance in both OPML and OSCC lesion tissues compared to healthy normal tissue. Western blotting in additional brushed biopsy samples confirmed a trend of gradual decreasing SLPI abundance between healthy normal and OPML tissue, with a larger decrease in OSCC lesion tissue. A similar SLPI decrease was observed in-vitro comparing model OPML and OSCC cell lines. In addition, exfoliated oral cells in patients' whole saliva showed a loss of SLPI correlated with oral cancer progression. These results, combined with proteomics data indicating a decrease in SLPI in matched healthy control tissue from OSCC patients compared to tissue from healthy normal tissue, suggested a systemic decrease of SLPI in oral cells correlated with oral cancer development. Finally, in-vitro experiments showed that treatment with SLPI significantly decreased NF-kB activity in an OPML cell line. The findings indicate anti-inflammatory activity in OPML, supporting a mechanistic role of SLPI in OSCC progression and suggesting its potential for preventative treatment of at-risk oral lesions. Collectively, our results show for the first time the potential for SLPI as a mechanism-based, non-invasive biomarker of oral cancer progression with potential in preventive treatment.

Indexed as

BiopsyProteomicsBiomarkers, TumorGenes, ReporterHumansMouth NeoplasmsSecretory Leukocyte Peptidase InhibitorTandem Mass SpectrometryBiomarkers, TumorSecretory Leukocyte Peptidase Inhibitor

Identifiers

PMID24748380
PMCPMC3991667

What OpenQuestion holds

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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.