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Modulation of Molecular Biomarker Expression in Response to Chemotherapy in Invasive Ductal Carcinoma
Breast cancer (BC) has varied morphological and biological features and is classified based on molecular and morphological examinations. Molecular classification of BC is based on biological gene-expression profiling. In this study, biomarker modulation was assessed during BC treatment in 30 previou...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5830017/ https://www.ncbi.nlm.nih.gov/pubmed/29619374 http://dx.doi.org/10.1155/2018/7154708 |
Sumario: | Breast cancer (BC) has varied morphological and biological features and is classified based on molecular and morphological examinations. Molecular classification of BC is based on biological gene-expression profiling. In this study, biomarker modulation was assessed during BC treatment in 30 previously untreated patients. Heterogeneity among patients was pathologically diagnosed and classified into luminal and basal-like immunohistochemical profiles based on estrogen, progesterone, and human epidermal growth factor receptor (ER/PR/HER2) status. Marker heterogeneity was compared with mRNA biomarker expression in patients with BC before and after therapy. Reverse transcription-polymerase chain reaction was performed for molecular characterization. Expression and modulation of biological markers, CK19, hMAM, CEA, MUC, Myc, Ki-67, HER2/neu, ErbB2, and ER, were assessed after treatment, where the expression of the biomarkers CK19, Ki-67, Myc, and CEA was noted to be significantly decreased. Marker expression modulation was determined according to different stages and pathological characteristics of patients; coexpression of three markers (CK19, Ki-67, and Myc) was specifically modulated after therapy. In the histopathologically classified basal-like group, two markers (CK19 and Ki-67) were downregulated and could be considered as diagnostic biomarkers. In conclusion, pathological characteristics and marker variation levels can be evaluated to decide a personalized treatment for patients. |
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