Literature DB >> 21946018

Tumor and inflammation markers in melanoma using tissue microarrays: a validation study.

Trine Ollegaard Jensen1, Rikke Riber-Hansen, Henrik Schmidt, Stephen Jacques Hamilton-Dutoit, Torben Steiniche.   

Abstract

The importance of tumor immune response is ever more evident in melanoma carcinogenesis. One approach to explore the pathological mechanisms involved in such immune responses, and to analyze other tumor prognostic markers in melanoma, is to use tissue microarrays (TMAs). However, TMA technology remains to be adequately validated in this setting. Protein expression patterns in whole slides and TMA sections from 34 melanoma patients were compared for a number of inflammation and tumor cell markers using immunohistochemical stains against CD8 (lymphocytes), CD163 (macrophages), micropthalmia transcription factor, N-cadherin, melanoma cell-adhesion molecule, and c-kit protein (CD117). Using simplified versions of previously published grading systems, the agreement between TMA and whole slide sections ranged between 83 and 96%, and between 81 and 97% for inflammation and tumor cell markers, respectively. We conclude that TMA technology combined with simplified grading systems are appropriate for analyzing both inflammation and tumor cell markers in melanoma.

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Year:  2011        PMID: 21946018     DOI: 10.1097/CMR.0b013e32834a3899

Source DB:  PubMed          Journal:  Melanoma Res        ISSN: 0960-8931            Impact factor:   3.599


  3 in total

1.  Tissue microarray.

Authors:  Kathleen Barrette; Joost J van den Oord; Marjan Garmyn
Journal:  J Invest Dermatol       Date:  2014-09       Impact factor: 8.551

2.  ZEB1 Regulates Multiple Oncogenic Components Involved in Uveal Melanoma Progression.

Authors:  Yao Chen; Xiaoqin Lu; Diego E Montoya-Durango; Yu-Hua Liu; Kevin C Dean; Douglas S Darling; Henry J Kaplan; Douglas C Dean; Ling Gao; Yongqing Liu
Journal:  Sci Rep       Date:  2017-03-03       Impact factor: 4.379

3.  Machine Learning-Assisted Ensemble Analysis for the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer.

Authors:  Yibao Huang; Qingqing Zhu; Liru Xue; Xiaoran Zhu; Yingying Chen; Mingfu Wu
Journal:  Front Oncol       Date:  2022-03-29       Impact factor: 6.244

  3 in total

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