Anura Anji, Conjeti Sailesh, Das Raunak Kumar, Pal Mousumi, Paul Ranjan Rashmi, Bag Swarnendu, Ray Ajoy Kumar, Chatterjee Jyotirmoy
School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India.
Chair for Computer Aided Medical Procedures and Augmented Reality, Fakulät für Informatik, Technische Universität München, Garching bei München, Germany.
Head Neck. 2016 May;38(5):653-69. doi: 10.1002/hed.23962. Epub 2015 Jun 29.
Evaluation of molecular pathology markers using a computer-aided quantitative assessment framework would help to assess the altered states of cellular proliferation, hypoxia, and neoangiogenesis in oral submucous fibrosis and could improve diagnostic interpretation in gauging its malignant potentiality.
Immunohistochemical (IHC) expression of c-Myc, hypoxia-inducible factor-1-alpha (HIF-1α), vascular endothelial growth factor (VEGF), VEGFRII, and CD105 were evaluated in 58 biopsies of oral submucous fibrosis using computer-aided quantification. After digital stain separation of original chromogenic IHC images, quantification of the diaminobenzidine (DAB) reaction pattern was performed based on intensity and extent of cytoplasmic, nuclear, and stromal expression.
Assessment of molecular expression proposed that c-Myc and HIF-1α may be used as strong screening markers, VEGF for risk-stratification and VEGFRII and CD105 for prognosis of precancer into oral cancer.
Our analysis indicated that the proposed method can help in establishing IHC as an effective quantitative immunoassay for molecular pathology and alleviate diagnostic ambiguities in the clinical decision process.
使用计算机辅助定量评估框架对分子病理学标志物进行评估,将有助于评估口腔黏膜下纤维化中细胞增殖、缺氧和新生血管生成的改变状态,并可改善对其恶性潜能的诊断解读。
采用计算机辅助定量分析,对58例口腔黏膜下纤维化活检组织中c-Myc、缺氧诱导因子-1α(HIF-1α)、血管内皮生长因子(VEGF)、血管内皮生长因子受体II(VEGFRII)和CD105的免疫组化(IHC)表达进行评估。在对原始显色免疫组化图像进行数字染色分离后,基于细胞质、细胞核和基质表达的强度和范围,对二氨基联苯胺(DAB)反应模式进行定量分析。
分子表达评估表明,c-Myc和HIF-1α可用作强有力的筛查标志物,VEGF用于风险分层,VEGFRII和CD105用于癌前病变发展为口腔癌的预后评估。
我们的分析表明,所提出的方法有助于将免疫组化确立为一种有效的分子病理学定量免疫测定方法,并减少临床决策过程中的诊断歧义。