Supplementary Online Content Hatzis C, Pusztai L, Valero V, et al. Genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer. JAMA. 2011;305(18):1873- 1881. eMethods eTable 1. Chemotherapy and Pretreatment Biopsy Details for the Study Cohorts eFigure 1. Flowchart of Biospecimen Accrual and Testing in the Discovery Cohort (A) and Validation Cohort (B) eFigure 2. Outline of the Process and Cohorts Used for Developing the Predictive Signatures for Early Relapse (A), Excellent Pathologic Response (B), and Extensive Residual Disease (C) Detailed Methods eResults eTable 2. Comparison of Genomic Signatures Performance for Predicting 3-Year DRFS eFigure 3. Kaplan-Meier Estimates of Distant Relapse–Free Survival in the Discovery Cohort (A-D) and the Independent Validation Cohort (E-H) of Patients Treated With Sequential Taxane-Anthracycline Chemotherapy, Then Endocrine Therapy if Hormone Receptor–Positive, Stratified by Other Signatures Reported to be Predictive of Response to Neoadjuvant Taxane- Anthracycline Chemotherapy eFigure 4. Kaplan-Meier Estimates of Distant Relapse–Free Survival in the ER-Positive Subsets of the Discovery Cohort (A-D) and the Independent Validation Cohort (E-H) of Patients Treated With Sequential Taxane-Anthracycline Chemotherapy, Then Endocrine Therapy if Hormone Receptor–Positive, Stratified by Other Signatures Reported to be Predictive of Response to Neoadjuvant Taxane-Anthracycline Chemotherapy eFigure 5. Kaplan-Meier Estimates of Distant Relapse–Free Survival in the ER-Negative Subsets of the Discovery Cohort (A-D) and the Independent Validation Cohort (E-H) of Patients Treated With Sequential Taxane-Anthracycline Chemotherapy, Then Endocrine Therapy if Hormone Receptor–Positive, Stratified by Other Signatures Reported to be Predictive of Response To Neoadjuvant Taxane-Anthracycline Chemotherapy eTable 3. Multivariate Cox Regression Analysis of Association With DRFS eFigure 6. Kaplan-Meier Estimates of Distant Relapse–Free Survival According to Genomic Predictions as Sensitive to Adjuvant Endocrine Therapy and/or Chemotherapy (Rx Sensitive) or Insensitive to Either Treatments (Rx Insensitive) in Clinically Node-Negative Patients Who Did Not Receive Any Chemotherapy (A) and Patients With ER-Positive Cancer That Were Predicted to Have Low Sensitivity to Endocrine Therapy and Who Received Tamoxifen as Their Adjuvant Therapy (B) eFigure 7. Kaplan-Meier Estimates of Distant Relapse–Free Survival in the ER-Positive Subset of the Independent Validation Cohort With Predicted Insensitivity to Endocrine Therapy (Low SET). Patients were treated with sequential taxane-anthracycline chemotherapy followed by endocrine therapy. This analysis excludes the subset of ER-positive breast cancers with predicted sensitivity to endocrine therapy (SET high or intermediate) eReferences Predictor Gene Lists Genes for Early Relapse in ER-Positive Breast Cancer Genes for Early Relapse in ER-Negative Breast Cancer Genes for Excellent Pathologic Response in ER-Positive Breast Cancer Genes for Excellent Pathologic Response in ER-Negative Breast Cancer Genes for Extensive Residual Disease in ER-Positive Breast Cancer Genes for Extensive Residual Disease in ER-Negative Breast Cancer This supplementary material has been provided by the authors to give readers additional information about their work. © 2011 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/02/2021 eMethods eTable 1. Chemotherapy and Pretreatment Biopsy Details for the Study Cohorts Discovery Cohort Validation Cohort (N=310) (N=198) Needle Biopsy for Genomic Testing FNA 227 157 CBX 83 41 Chemotherapy Regimen Entirely Neoadjuvant T x 12 → FAC x 4 → Sx1 227 73 AC x 4 → T/Tx x 4 → Sx2 83 - TxX x 4 → FEC x 4 → Sx3 - 92 Partial Neoadjuvant FAC/FEC x 6 → Sx → T x 124 - 18 Entirely Adjuvant Sx → T x 12 → FAC/FEC x 45 - 12 Sx → TxX x 4 → FEC x 46 - 2 Sx → Tx x 4 → FEC x 47 - 1 FNA: fine needle aspiration CBX: core needle biopsy Sx: surgery (1) 12 weekly doses of paclitaxel (T) followed by four cycles of fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) and then surgery. (2) Four cycles of doxorubicin (A) and cyclophosphamide (C) followed by four cycles of paclitaxel (T) (N=60) or docetaxel (Tx) (N=18) or taxane not specified (N=5) and then surgery. (3) Four cycles of docetaxel (Tx) with capecitabine (X) followed by four cycles of fluorouracil (F), epirubicin (E) and cyclophosphamide (C) and then surgery. (4) Six cycles of fluorouracil (F), doxorubicin (A) or epirubicin (E), and cyclophosphamide (C) followed by surgery and then by 12 weekly doses of paclitaxel (T). (5) Surgery followed by 12 weekly doses of paclitaxel (T) and then by four cycles of fluorouracil (F), doxorubicin (A) or epirubicin (E), and cyclophosphamide (C). (6) Surgery followed by four cycles of docetaxel (Tx) with capecitabine (X) and then followed by four cycles of fluorouracil (F), epirubicin (E) and cyclophosphamide (C). (7) Surgery followed by four cycles of docetaxel (Tx) and then by four cycles of fluorouracil (F), epirubicin (E) and cyclophosphamide (C). © 2011 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/02/2021 eMethods (Continued) eFigure 1. Flowchart of Biospecimen Accrual and Testing in the Discovery Cohort (A) and Validation Cohort (B) © 2011 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/02/2021 eMethods (Continued) eFigure 2. Outline of the Process and Cohorts Used for Developing the Predictive Signatures for Early Relapse (A), Excellent Pathologic Response (B), and Extensive Residual Disease (C) A B C SET‐Low All Patients All Patients Lymph node Positive ER Positive ER Negative ER Positive ER Negative ER Positive ER Negative (N=87) (N=90) (N=170) (N=131) (N=170) (N=131) Univariate Cox Welch test Welch test Bootstrap Bootstrap Bootstrap Candidate Candidate Candidate Candidate Candidate Candidate Probe sets Probe sets Probe sets Probe sets Probe sets Probe sets (235) (268) (209) (244) (256) (202) Cox TGDR TGDR Univariate AUC AUC Shrinkage Maximization Maximization Final Final Final Final Final Final Probe sets Probe sets Probe sets Probe sets Probe sets Probe sets (33) (27) (39) (55) (73) (54) © 2011 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/02/2021 eMethods (Continued) Detailed Methods 1. Microarray Data Processing and Normalization Measurement of the expression level of a gene transcript from Affymetrix microarray data is calculated from a weighted median of the intensity signals of a set of oligonucleotide probes that each identifies a different site of the gene transcript sequence. Each specific oligonucleotide probe is paired with a designed mismatch probe so that the measurement of specific binding to target sequence (perfect match probe) is relative to background nonspecific binding (mismatch probe). Therefore, a “probe set” refers to the set of probe pairs (perfect and mismatch) to multiple regions of a single gene transcript sequence. Some gene transcripts are recognized by more than one probe set on the microarray. Raw intensity files (.CEL) from each microarray were processed using MAS5.0 (R/Bioconductor, www.bioconductor.org) 1 to normalize to a mean array intensity of 600 and to generate probe set-level expression values. Expression values were then log2-transformed and subsequently scaled by the expression levels of 1322 breast cancer reference genes to reference values that had been established as the median expression of these genes in an independent reference cohort of invasive breast cancer (N=444). The quality of hybridization and microarray profiling was assessed based on a set of 8 metrics that compare the expression level of the reference genes in each sample to the historical reference values before and after scaling. Metrics include the median deviation, the inter-quartile range (IQR) of deviations, the Kolmogorov-Smirnov statistic for equality of the distributions and the p-value of the K-S statistic. Dimensionality was reduced through a principal component analysis (PCA) model of the 8 metrics which were further summarized in two multivariate statistics, the Hotteling T2 and the sum of squares of the residuals or Q statistic 2. Control limits for Q and T2 for sample acceptance were established from historical in-control samples. Prior to analysis for predictor development, 2,522 probe sets that either had low specificity (extensions _xfri_ in their name), were housekeeping probes (starting with AFFX) or were not adequately expressed (log2-transformed intensity of at least 5 in at least 75% of the arrays) were removed. A total of 16,289 probe sets (73% of all) were retained for further analysis. 2. Identification of Predictive Signature For Early Relapse Distant relapse events or deaths were the endpoint for defining resistance following therapy. Time to event was determined since the time of initial diagnosis. In an effort to isolate the effect of chemotherapy on the survival of higher risk patients, this analysis utilized only predicted endocrine non-sensitive (SET-Low), clinically lymph node positive (LN+) patients (eFigure 2A). Each probe set was evaluated in univariate Cox regression analysis and the significance of its association with the risk of distant relapse was assessed based on the likelihood ratio test relative to the null model. P-values for the significance of each probe set were