Evidence map›Paper›PMID 26045786›Full record

ArticleInternational journal of clinical and experimental pathology2015

An immunohistochemical analysis of stathmin 1 expression in uterine smooth muscle tumors: differential expression in leiomyosarcomas and leiomyomas.

Mary-Margaret L Allen, Jonathan J Douds, Sharon X Liang, Mohamed M Desouki, Vinita Parkash, Oluwole Fadare

Open access · greenAbstract readComparative Study
In one paragraph

Article in International journal of clinical and experimental pathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

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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

11 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Molecular-Based Immunohistochemical Algorithm for Uterine Leiomyosarcoma Diagnosis.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. STMN1 and MKI67 Are Upregulated in Uterine Leiomyosarcoma and Are Potential Biomarkers for its Diagnosis.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  10. Review
  11. 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

6 authors at 4 institutions in 1 country.

Mary-Margaret L AllenDepartment of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine Nashville, TN, United States.
Jonathan J DoudsDepartment of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine Nashville, TN, United States.
Sharon X LiangDepartment of Pathology and Laboratory Medicine, North Shore-LIJ Health System and Hofstra North Shore-LIJ School of Medicine New Hyde Park, NY, USA.
Mohamed M DesoukiDepartment of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine Nashville, TN, United States.
Vinita ParkashDepartment of Pathology, Yale University School of Medicine New Haven, CT ; Department of Pathology, Bridgeport Hospital Bridgeport, CT, USA.
Oluwole FadareDepartment of Pathology, University of California San Diego San Diego, CA.
Vanderbilt University · USBridgeport Hospital · USNorthwell Health · USUniversity of San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The oncogenic phosphatidylinositol 3-kinase-AKT-mammlian target of rapamycin pathway (PI3K-AKT-mTOR) pathway is known to be activated in uterine smooth muscle tumors, and Stathmin 1 (STMN1) expression has been identified as a marker of PI3K-AKT-mTOR pathway activation. We hypothesized that STMN1 may have some diagnostic utility and explored how well STMN1 expression correlated with histologic classifications of uterine smooth muscle tumors into benign and malignant groupings. 84 smooth muscle tumors were assessed for STMN1 expression by immunohistochemistry. These included spindle cell leiomyosarcoma (n=32), conventional spindle cell leiomyomas (n=30), atypical (symplastic) leiomyoma (n=5), cellular leiomyoma (n=7), smooth muscle tumor of uncertain malignant potential (n=4), mitotically active leiomyomas (n=2), benign metastasizing leiomyoma (n=3), and cotyledonoid dissecting leiomyoma (n=1). All spindle cell leiomyosarcomas were positive (32/32 positive; 100%) as compared with conventional leiomyomata (11/30; 37%) (P<0.0001). The average immunohistochemical score (0-12+, reflective of intensity and extent) for leiomyosarcomas was 8.7 (±1.43) whereas the conventional leiomyomata average score was 1.6 (±1.07) (P<0.0001). This difference in scores was reflected in the patterns of expression: leiomyosarcomas were predominantly strongly and diffusely positive whereas leiomyomata were predominantly weakly, albeit diffusely positive when expression was present. The sensitivity of STMN1 expression for leiomyosarcomas was 100%. However, the specificity was found to be only 55% (CI=43-68%). The negative and positive predictive values for leiomyosarcomas were 100% and 52% respectively. The odds ratio (OR) for any STMN1 expression in predicting a spindle cell leiomyosarcoma diagnosis from this dataset was highly significant (OR=144, P=0.0006). Thirteen non-smooth muscle tumors that involved the uterus all showed at least focal STMN1 immunoreactivity. In summary, STMN1 is a highly sensitive marker for leiomyosarcoma but is suboptimally specific for diagnostic purposes. The 100% negative predictive value for leiomyosarcoma may offer some diagnostic utility in a small sample, since the absence of STMN1 immunoreactivity in a putative leiomyosarcoma is a strong argument against this diagnostic possibility.

Indexed as

ImmunohistochemistryBiomarkers, TumorDiagnosis, DifferentialFemaleHumansLeiomyomaLeiomyosarcomaPredictive Value of TestsPrognosisStathminUterine NeoplasmsBiomarkers, TumorStathminSTMN1 protein, humanimmunohistochemistryleiomyomaLeiomyosarcomastathminSTMN1

Identifiers

PMID26045786
PMCPMC4440095
OpenAlexW572737304

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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.