Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

Validation of an Automated Quantitative Digital Pathology Approach for Scoring TMEM, a Prognostic Biomarker for Metastasis.

David Entenberg | Maja H Oktay | Timothy D'Alfonso | Paula S Ginter | Brian D Robinson | Xiaonan Xue | Thomas E Rohan | Joseph A Sparano | Joan G Jones | John S Condeelis
Cancers | 2020

Metastasis causes ~90% of breast cancer mortality. However, standard prognostic tests based mostly on proliferation genes do not measure metastatic potential. Tumor MicroEnvironment of Metastasis (TMEM), an immunohistochemical biomarker for doorways on blood vessels that support tumor cell dissemination is prognostic for metastatic outcome in breast cancer patients. Studies quantifying TMEM doorways have involved manual scoring by pathologists utilizing static digital microscopy: a labor-intensive process unsuitable for use in clinical practice. We report here a validation study evaluating a new quantitative digital pathology (QDP) tool (TMEM-DP) for identification and quantification of TMEM doorways that closely mimics pathologists' workflow and reduces pathologists' variability to levels suitable for use in a clinical setting. Blinded to outcome, QDP was applied to a nested case-control study consisting of 259 matched case-control pairs. Sixty subjects of these were manually scored by five pathologists, digitally recorded using whole slide imaging (WSI), and then used for algorithm development and optimization. Validation was performed on the remainder of the cohort. TMEM-DP shows excellent reproducibility and concordance and reduces pathologist time from ~60 min to ~5 min per case. Concordance between manual scoring and TMEM-DP was found to be >0.79. These results show that TMEM-DP is capable of accurately identifying and scoring TMEM doorways (also known as MetaSite score) equivalent to pathologists.

Pubmed ID: 32244564

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

  • Agency: NCI NIH HHS, United States
    Id: P30 CA008748
  • Agency: NCI NIH HHS, United States
    Id: R01 CA216248
  • Agency: NIH HHS, United States
    Id: CA216248
  • Agency: NIH HHS, United States
    Id: S10 OD019961
  • Agency: NIH HHS, United States
    Id: CA100324
  • Agency: NCI NIH HHS, United States
    Id: P01 CA100324

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


BD Biosciences (tool)

RRID:SCR_013311

An Antibody supplier

View all literature mentions

Dako (tool)

RRID:SCR_013530

An Antibody supplier; Dako was purchased by Agilent in 2012 and several years later the websites began to reflect the Dako products as part of the Agilent catalog.

View all literature mentions

Adobe Photoshop (tool)

RRID:SCR_014199

Software for image processing, analysis, and editing. The software includes features such as touch capabilities, a customizable toolbar, 2D and 3D image merging, and Cloud access and options.

View all literature mentions