Breast cancer molecular signatures as determined by SAGE: correlation with lymph node status.

ABBA MC; SUN H; HAWKINS KA; DRAKE JA; HU Y; NUNEZ MI; GADDIS S; SHI T; HORVATH S; SAHIN A; ALDAZ CM

MOLECULAR CANCER RESEARCH

AACR

Lugar: Philadelphia - USA; Año: 2007 vol. 5 p. 881 - 890

1541-7786

Global gene expression measured by DNA microarray platforms have been extensively used to classify breast carcinomas correlating with clinical characteristics, including outcome. We generated a breast cancer Serial Analysis of Gene Expression (SAGE) high-resolution database of ~ 2.7 million tags to perform unsupervised statistical analyses to obtain the molecular classification of breast-invasive ductal carcinomas in correlation with clinicopathologic features. Unsupervised statistical analysis by means of a random forest approach identified two main clusters of breast carcinomas, which differed in their lymph node status (P = 0.01); this suggested that lymph node status leads to globally distinct expression profiles. A total of 245 (55 up-modulated and 190 down-modulated) transcripts were differentially expressed between lymph node (+) and lymph node (-) primary breast tumors (fold change, >2; P < 0.05). Various lymph node (+) up-modulated transcripts were validated in independent sets of human breast tumors by means of real-time reverse transcription-PCR (RT-PCR). We validated significantoverexpression of transcripts for HOXC10 (P = 0.001), TPD52L1 (P = 0.007), ZFP36L1 (P = 0.011), PLINP1 (P = 0.013), DCTN3 (P = 0.025), DEK (P = 0.031), and CSNK1D (P = 0.04) in lymph node (+) breast carcinomas. Moreover, the DCTN3 (P = 0.022) and RHBDD2 (P = 0.002) transcripts were confirmed to be overexpressed in tumors that recurred within 6 years.