TFAC30 signature is constructed based on the publication described below. Authors of the Hess et.al. paper identified 30 probes on the affy U133 microarray platform whose gene expression profile is predictive with 89% accuracy to complete pathologic response to chemotherapy treatment in the breast study described in same publication. We used the 30 genes targeted by those probes to form the base of the gene set for the signature and assigned +1 or -1 coefficient to genes that are up- or down-activated within the complete responders. The TFAC30 score is the sign-weighted sum of the gene expression value from the 30 genes.
E2F3 + MELK + RRM2 + BTG3 - CTNND2 - GAMT - METRN - ERBB4 - ZNF552 - CA12 - KDM4B - NKAIN1 - SCUBE2 - KIAA1467 - MAPT - FLJ10916 - BECN1 - RAMP1 - GFRA1 - IGFBP4 - FGFR1OP - MDM2 - KIF3A - AMFR - MED13L - BBS4
Title: Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer.
Authors: Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, Booser D, Theriault RL, Buzdar AU, Dempsey PJ, Rouzier R, Sneige N, Ross JS, Vidaurre T, Gomez HL, Hortobagyi GN, Pusztai L.
Citation: J Clin Oncol. 2006 Sep 10;24(26):4236-44. Epub 2006 Aug 8.
21-gene signature is constructed based on the publication described below. Authors of the Paik et.al publication tested RT-PCR assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancer-related genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high)for each patient. We used the 21 genes to form the base of the gene set for the signature and assigned +1 or -1 coefficient to 16 genes that we hypothesized to be up- or down-activated based on the publication, and assign coefficient zero to the 5 reference genes. The 21-gene signature score is the sign-weighted sum of the gene expression value from the 21 genes.
# 21-gene signature
MKI67 + AURKA + BIRC5 + CCNB1 + MYBL2
+ GRB7 + ERBB2
+ CTSL2 + MMP11
# other positive
- ESR1 - PGR - BCL2 - SCUBE2
# other negatives
- GSTM1 - BAG1
Title: A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer
Authors: Soonmyung Paik, M.D., Steven Shak, M.D., Gong Tang, Ph.D., Chungyeul Kim, M.D., Joffre Baker, Ph.D., Maureen Cronin, Ph.D., Frederick L. Baehner, M.D., Michael G. Walker, Ph.D., Drew Watson, Ph.D., Taesung Park, Ph.D., William Hiller, H.T., Edwin R. Fisher, M.D., D. Lawrence Wickerham, M.D., John Bryant, Ph.D., and Norman Wolmark, M.D.
Citation: N Engl J Med. 2004 Dec 30;351(27):2817-26. Epub 2004 Dec 10.
Yau HRneg/Tneg is constructed based on the publication described below. Authors of the Yau et. al. publication identified a novel set of 14 prognostic gene candidates as outcome predictors: CXCL13, CLIC5, RGS4, RPS28, RFX7, EXOC7, HAPLN1, ZNF3, SSX3, HRBL, PRRG3, ABO, PRTN3, MATN1. The authors show a composite HRneg/Tneg gene signature index proved to be more accurate than any individual candidate gene or other reported multigene predictors at the time of publication in identifying cases likely to remain free of metastatic relapse. We used the 14 genes and the univariate Cox analysis coefficient from Table 1 in the publication to form the basis of the signature. The gene signature score is the coefficient-weighted sum of the gene expression value from the 14 genes.
#Yau HRneg/Tneg outcome
-0.3 * RPS28
-0.3 * ANKRD47
-0.58 * EXOC7
-0.5 * MATN1
-0.48 * HRBL
-0.48 * CLIC5
-0.47 * RFX7
-0.47 * PRRG3
-0.44 * ABO
-0.41 * PRTN3
-0.34 * ZNF3
-0.33 * SSX3
-0.19 * CXCL13
+0.17 * HAPLN1
+0.24 * RGS4
Title: A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer
Authors: Christina Yau, Laura Esserman, Dan H Moore, Fred Waldman, John Sninsky and Christopher C Benz
Citation: Breast Cancer Res. 2010 Oct 14;12(5):R85