Exploring novel targets of basal-like breast carcinoma by comparative gene profiling and mechanism analysis.
The heterogeneity of breast cancer makes its diagnosis and treatment far from being optimal. Analysis of traditional pathological and prognostic markers based on immunohistochemistry (IHC) is inadequate in elucidating the inherent heterogeneity of breast cancer, especially basal-like breast carcinoma (BLBC) which displays complex and unique epidemiological, phenotypic, and molecular features with distinctive relapse patterns and poor clinical outcomes. Gene expression profiling opened an avenue in research as independent predictors by classifying breast cancers into discrete groups with prognostic references, but it is not cost-effective in clinical application. It is necessary to develop an effective predictive gene list from gene profiling to optimize the treatment with traditional markers. In this report, we analyzed the correlation between IHC and gene profiling of breast cancer with an emphasis on the BLBC, highlighting the potential discovery of diagnostic markers and cellular mechanisms that may guide the development of BLBC-targeted therapy. Random forest-based classification and PAM50 gene-sets were used in the comparison analysis of traditional prognostic markers including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and microarray profiles. An intrinsic 40-gene set was developed to classify breast cancer subtypes, and genes expression differentiations were used to explore the different mechanisms between the BLBC and non-BLBC subtypes based on the comparison of clinicopathological markers and microarray profiling. Pathways and DNA repairs were analyzed to evaluate the biological mechanisms in BLBC and other breast cancer subtypes. It is reasonable to define BLBC as those tumors that are negative for ER, PR, and HER2 by IHC for their accordance with gene expression profiles. Focal adhesion kinase, ERBB, and their signaling pathways may play crucial role in BLBC. The intrinsic 40-gene set can be used to classify breast cancer and help to optimize therapeutic management of BLBC.
Department of Fourth General Surgery, Changhai Hospital, Shanghai 200433, China.
Yan-Mei
YM
Wu
Wei
W
Hu
Yang
Y
Wang
Ning
N
Wang
Li
L
Gao
Zhong-Zhong
ZZ
Chen
Wei-Qiang
WQ
Zheng
D014408:Biomarkers, Tumor / Q000032:analysis; D002277:Carcinoma / Q000737:chemistry / Q000145:classification / Q000235:genetics* / Q000473:pathology; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D004260:DNA Repair; D004273:DNA, Neoplasm / Q000235:genetics / Q000378:metabolism; D004967:Estrogens; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D052138:Genes, Neoplasm; D016158:Genes, p53; D018740:Genetic Heterogeneity; D006801:Humans; D007150:Immunohistochemistry; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D009363:Neoplasm Proteins / Q000235:genetics; D009376:Neoplasms, Hormone-Dependent / Q000737:chemistry / Q000235:genetics; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000032:analysis; D011960:Receptors, Estrogen / Q000032:analysis; D011980:Receptors, Progesterone / Q000032:analysis; D015398:Signal Transduction; D046888:Tissue Array Analysis; D064726:Triple Negative Breast Neoplasms / Q000737:chemistry / Q000145:classification / Q000235:genetics* / Q000473:pathology
D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm; D004967:Estrogens; D009363:Neoplasm Proteins; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; C508053:ERBB2 protein, human