I. Clinical and pathological features of the. Expression of the Selected Genes in Publicly. Available PCa Microarray Data

Transcription

1 Supplementary Material I. Clinical and pathological features of the Case/Control set II. III. Comparison of VOG-Δp and pfc approaches Expression of the Selected Genes in Publicly Available PCa Microarray Data

2 Feature Control (N=87) Case (N=86) Total (N=173) p value Age at Surgery Mean (SD) 64.0 (7.18) 64.7 (6.77) 64.3 (6.97) Median Range ( ) ( ) ( ) Preop PSA(ng/ml) Median Q1, Q3 6.8, , , 23.6 Range ( ) ( ) ( ) Clinical Stage, 1997 TNM T1ab 0 (0%) 1 (1.2%) 1 (0.6%) T1c 18 (20.9%) 7 (8.2%) 25 (14.6%) T2a 40 (46.5%) 46 (54.1%) 86 (50.3%) T2b 15 (17.4%) 14 (16.5%) 29 (17%) T34 13 (15.1%) 17 (20%) 30 (17.5%) Gleason Score (51.7%) 49 (57%) 94 (54.3%) (48.3%) 37 (43%) 79 (45.7%) Pathologic Stage, 1997 TNM T2aN0 9 (10.3%) 9 (10.5%) 18 (10.4%) T2bN0 22 (25.3%) 11 (12.8%) 33 (19.1%) T34N0 41 (47.1%) 52 (60.5%) 93 (53.8%) TxN+ 15 (17.2%) 14 (16.3%) 29 (16.8%) Margin Positive 53 (60.9%) 58 (67.4%) 111 (64.2%) Table S1: The clinical and pathologic features of the patients in the case-control study.

3 I. Comparison of VOG-Dp and pfc approaches Results from the current analysis differ from results of analysis by fold change. To determine the overlap between this approach and analysis using only fold-change and p-value (pfc approach; see experimental procedures), results were compared at the end of two steps in the process. First, overlap between VOGs and genes selected by pfc (step 1) was examined. The same set of data was used for both analyses. Comparison of non-neoplastic samples to all tumor samples by each method identified a similar number of candidates (See Supplementary Figure S1a). pfc identified 250 over-expressed probe sets and VOG identified 271 over-expressed probe sets. One hundred and thirty-one probe sets were identified by both methods (Figure S1a). A second comparison evaluated the identification of markers of aggressiveness (prognostic markers) (Figure S1b). pfc was used to compare samples representing non-aggressive (GP3) and aggressive (GP4, GP5, and metastatic cases) tumors (see Methods). This is analogous to the combined VOG- p analysis. In this comparison, pfc identified 120 candidate probe sets while VOG- p identified 126 with p > 10. Overlap was limited to ~18 probesets (Figure S1b). Thus, while the methods identified more than one hundred candidates each, the candidates differed, indicating that candidates selected by the VOG- p approach would not likely have been selected by the more standard pfc method (see Table 1 in the manuscript).

4 pfc VOG pfc VOG-Δp (a) (b) Figure S1 overlap between the proposed approach and standard methods involving p-values and fold change (pfc) (a) overlap between VOGs (271 probesets) and genes selected by the pfc approach for over-expression in PCa (250 probesets), (b) overlap between the probesets selected by the proposed approach (126 probesets, VOG-Δp on the figure) and pfc (120 probesets) for selecting markers of PCa aggressiveness. There is only ~15% overlap between the probesets in the two approaches.

5 III. Expression of the Selected Genes in Publicly Available PCa Microarray Data We examined the expression of the selected genes in publicly available expression data including Gene Expression Omnibus (1-3). For the most part, we observed variable over-expression of the validated genes (Table 1 of manuscript) in prostate tumor cases, especially in aggressive or metastatic prostate tumors and, therefore, generally consistent with the results in the main body of our study. Excerpts of our analysis shown below indicate that candidate genes are markers of aggressive tumors. 1- Varambally, Chinnaiyan et al. Cancer Cell Nov;8(5): : Study included 6 non-neoplastic prostate tissues (including 2 pooled non-neoplastic cases), 7 clinically localized primary prostate cancer (including 2 pooled PCa primeries), and 6 metastatic PCa (including 2 pooled metastatic cases). Figures below depict the expression of the selected genes presented in Table 1 according to the data by Varambally et al _s_at, TOP2A N1 N2 N3 N4 NX1 NX2 P1 P2 P3 P4 P5 PX1 PX2 W1 W2 W3 W4 WX 1 WX 2

6 Non-Neoplastic Prostate Pooled Non-Neoplastic Prostate Prostate Cancer Pooled Prostate Cancer Metastatic Prostate Cancer Pooled Metastatic Prostate Cancer _s_at, RRM N1 N2 N3 N4 NX1 NX2 P1 P2 P3 P4 P5 PX1 PX2 W1 W2 W3 W4 WX1 WX _s_at, KHRDSB N1 N2 N3 N4 NX1 NX2 P1 P2 P3 P4 P5 PX1 PX2 W1 W2 W3 W4 WX1 WX2

7 _at, SSTR N1 N2 N3 N4 NX1 NX2 P1 P2 P3 P4 P5 PX1 PX2 W1 W2 W3 W4 WX1 WX2

8 2- Best and Chuaqui et al. Clin Cancer Res Oct 1;11(19 Pt 1): Study included expression profiling of LCM-selected cells from 10 androgenindependent primary prostate tumor biopsies and 10 primary, untreated androgen-dependent tumors. Even though our analysis did not consider hormonal dependence in gene selection, it is interesting to observe that 3 of 5 of the selected genes tend to have higher expression in hormone independent tumors, which is the very advanced type of PCa. NRP-1 TOP2A

9 RRM2 KHDRBS3 SSTR1

10 3- Dhanasekaran, Chinnaiyan et al. Nature Aug 23;412(6849): Study included more than 50 normal and neoplastic prostate specimens and three prostate-cancer cell lines. Profiling was done on a 10K human cdna micorarray that covers about 5,520 known genes. Of the selected genes in our study, TOP2A was the only annotated gene that was profiled. A variable overexpression of TOP2A was observed in metastatic PCa cases. 6 TOP2A BPH-205 BPH-202 BPH-203 BPH-201 NAT-102 NAT-105 NAT-106 Prostatitis BPH-204 PCA-402 PCA-403 PCA-404 PCA-410 PCA-408 PCA-401 PCA-409 PCA-405 PCA-406 PCA-405 MET-301 MET-302 MET-307 MET-303 MET-304 MET-305 MET-306 Du145 LnCap PC3 Various benign conditions Localized Prostate Cancer Metastatic Prostate Cancer Prostate Cancer Cell Lines

11 References 1. Best, C. J., Gillespie, J. W., Yi, Y., Chandramouli, G. V., Perlmutter, M. A., Gathright, Y., Erickson, H. S., Georgevich, L., Tangrea, M. A., Duray, P. H., Gonzalez, S., Velasco, A., Linehan, W. M., Matusik, R. J., Price, D. K., Figg, W. D., Emmert-Buck, M. R., and Chuaqui, R. F. Molecular alterations in primary prostate cancer after androgen ablation therapy. Clin Cancer Res, 11: , Varambally, S., Yu, J., Laxman, B., Rhodes, D. R., Mehra, R., Tomlins, S. A., Shah, R. B., Chandran, U., Monzon, F. A., Becich, M. J., Wei, J. T., Pienta, K. J., Ghosh, D., Rubin, M. A., and Chinnaiyan, A. M. Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression. Cancer Cell, 8: , Dhanasekaran, S. M., Barrette, T. R., Ghosh, D., Shah, R., Varambally, S., Kurachi, K., Pienta, K. J., Rubin, M. A., and Chinnaiyan, A. M. Delineation of prognostic biomarkers in prostate cancer. Nature, 412: , 2001.