First generation prognostic gene signatures for breast cancer predict both survival and chemotherapy sensitivity and identify overlapping patient populations.

The aims of this study were to compare the performance of six different genomic prognostic markers to predict long-term survival and chemotherapy response on the same patient cohort and assess if clinicopathological variables carry independent prognostic and predictive values. We examined seven clinical variables and six previously described prognostic signatures on 228 tumors from patients who received homogeneous preoperative chemotherapy and had long-term follow-up information for survival. We used the area under the receiver operator characteristic curve (AUC) to compare predictors and also performed univariate and multivariate analyses including the genomic and clinical variables and plotted Kaplan-Meir survival curves. All genomic prognostic markers had statistically similar AUCs and sensitivity to predict 5-year progression-free survival (PFS, sensitivities ranged from 0.591 to 0.773, and AUCs: 0.599-0.673), overall survival (OS, sensitivities: 0.590-0.769, AUCs: 0.596-0.684) and pathologic complete response (pCR, sensitivities: 0.596-0.851, AUCs: 0.614-0.805). In multivariate analysis, the genomic markers were not independent from one another; however, estrogen receptor (Odds Ratio [OR] 7.63, P < 0.001) and HER2 status (OR: 0.37, P = 0.021) showed significant independent predictive values for pCR. Nodal status remained an independent prognostic, but not predictive, variable (OR for PFS: 2.77, P = 0.021, OR for OS: 3.62, P = 0.01). There was moderate to good agreement between different prediction results in pair-wise comparisons. First-generation prognostic-gene signatures predict both chemotherapy response and long-term survival. When multiple predictors are applied to the same case discordant risk prediction frequently occurs.

A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer.

CONTEXT: Prediction of high probability of survival from standard cancer treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE: To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN, SETTING, AND PATIENTS: Prospective multicenter study conducted from June 2000 to March 2010 at the M. D. Anderson Cancer Center to develop and test genomic predictors for neoadjuvant chemotherapy. Patients were those with newly diagnosed ERBB2 (HER2 or HER2/neu)-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens (then endocrine therapy if estrogen receptor [ER]-positive). Different predictive signatures for resistance and response to preoperative (neoadjuvant) chemotherapy (stratified according to ER status) were developed from gene expression microarrays of newly diagnosed breast cancer (310 patients). Breast cancer treatment sensitivity was then predicted using the combination of signatures for (1) sensitivity to endocrine therapy, (2) chemoresistance, and (3) chemosensitivity, with independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. MAIN OUTCOME MEASURES: Distant relapse-free survival (DRFS) if predicted treatment sensitive and absolute risk reduction ([ARR], difference in DRFS between 2 predicted groups) at median follow-up (3 years). RESULTS: Patients in the independent validation cohort (99% clinical stage II-III) who were predicted to be treatment sensitive (28%) had 56% (95% CI, 31%-78%) probability of excellent pathologic response and DRFS of 92% (95% CI, 85%-100%), with an ARR of 18% (95% CI, 6%-28%). Survival was predicted in ER-positive (30% predicted sensitive; DRFS, 97% [95% CI, 91%-100%]; ARR, 11% [95% CI, 0.1%-21%]) and ER-negative (26% predicted sensitive; DRFS, 83% [95% CI, 68%-100%]; ARR, 26% [95% CI, 4%-48%]) subsets and was significant in multivariate analysis. Other genomic predictors showed paradoxically worse survival for patients predicted to be responsive to chemotherapy. CONCLUSION: A genomic predictor combining ER status, predicted chemoresistance, predicted chemosensitivity, and predicted endocrine sensitivity identified patients with high probability of survival following taxane and anthracycline chemotherapy.

PIK3CA-activating mutations and chemotherapy sensitivity in stage II-III breast cancer.

INTRODUCTION: In vitro evidence suggests that PIK3CA (phosphatidylinositol 3-kinase, catalytic, alpha polypeptide) activation may be associated with altered chemotherapy sensitivity in cancer. METHODS: Tumor DNA from 140 patients with stage II-III breast cancer undergoing neoadjuvant chemotherapy was sequenced for PIK3CA mutations on exons 1, 9, and 20. Mutation status was correlated with clinical/pathological parameters and chemotherapy response as (a) pathological complete response (pCR) versus residual cancer or (b) quantitative residual cancer burden (RCB) scores, including stratification for estrogen receptor (ER) expression status, type of chemotherapy, and by exons. RESULTS: Twenty-three patients (16.4%) harbored a PIK3CA mutation, with 12, 11, and 0 mutations located in exons 9, 20, and 1, respectively. PIK3CA exon 9 mutations were more frequent among node-negative (52% versus 25%; P = 0.012) than node-positive tumors, particularly among ER-positive tumors. pCR rates and RCB scores were similar among patients with the wild-type and mutant PIK3CA genes, even after stratification by ER status, chemotherapy regimen (anthracycline versus anthracycline plus paclitaxel), or exon. CONCLUSION: PIK3CA mutations are not associated with altered sensitivity to preoperative anthracycline-based or taxane-based chemotherapies in ER-positive and ER-negative breast tumors. In this study, PIK3CA mutation was associated with a decreased rate of node-positive disease, particularly among ER-positive tumors.

Global gene expression changes induced by prolonged cold ischemic stress and preservation method of breast cancer tissue.

BACKGROUND: Tissue handling can alter global gene expression potentially affecting the analytical performance of genomic signatures, but such effects have not been systematically evaluated. METHODS: Tissue samples from 11 previously untreated breast tumors were minced and aliquots were either snap frozen or placed in RNAlater immediately or after 20, 40, 60, 120 or 180 min at room temperature. RNA was profiled on Affymetrix HG-U133A arrays. We used probe-set-wise hierarchical models to evaluate the effect of preservation method on transcript expression and linear mixed effects models to assess the effect of cold ischemic delay on the expression of individual probe sets. Gene set enrichment analysis identified pathways overrepresented in the affected transcripts. We combined the levels of 41 most sensitive transcripts to develop an index of ischemic stress. RESULTS: Concordance in global gene expression between the baseline and 40 min delay was higher for samples preserved in RNAlater (average concordance correlation coefficient CCC = 0.92 compared to 0.88 for snap frozen). Overall, 481 transcripts (3%) were significantly affected by the preservation method, most of them involved in processes important in cancer. Prolonged cold ischemic delay of up to 3 h induced marginal global gene expression changes (average CCC = 0.90 between baseline and 3 h delay). However 41 transcripts were significantly affected by cold ischemic delay. Among the induced transcripts were stress response genes, apoptotic response genes; among the downregulated were genes involved in metabolism, protein processing and cell cycle regulation. An index combining the expression levels of these genes was proportional to the cold ischemic delay. CONCLUSIONS: Prolonged cold ischemia induces significant transcriptional changes in a small subset of transcripts in the tissue. Furthermore, the expression level of about 3% of the transcripts is affected by the preservation method. These sensitive transcripts should not be included in genomic signatures for more reliable analytical performance.

Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers.

BACKGROUND: Reliable stability and yield of RNA from breast cancer tissues are important for biobanking, clinical trials, and diagnostic testing. METHODS: Aliquots of fresh primary tumor tissue from 17 surgically resected invasive breast cancers were placed into RNAlater at room temperature after tumor removal (baseline) and up to 3 hours thereafter or were snap frozen at baseline and 40 minutes thereafter. Samples were stored at -80°C until gene expression profiling with Affymetrix Human Gene U133A microarrays. We evaluated the effects of cold ischemic time (the time from tumor specimen removal to sample preservation) and sample preservation method on RNA yield, Bioanalyzer-based RNA integrity number, microarray-based 3'/5' expression ratios for assessing transcript integrity, and microarray-based measurement of single-gene and multigene expression signatures. The statistical significance of the effects was assessed using linear mixed effects regression models. All statistical tests were two-sided. RESULTS: Sample preservation in RNAlater statistically significantly improved RNA integrity compared with snap freezing as assessed by the RNA integrity number, which increased from 7.31 to 8.13 units (difference = 0.82 units, 95% confidence interval [CI] = 0.53 to 1.11 units, P < .001), and RNA yield, which increased threefold from 8.9 to 28.6 µg (difference = 19.7 µg, 95% CI = 14.1 to 25.3 µg, P < .001). Prolonged cold ischemic delay at room temperature before sample stabilization decreased the RNA integrity number by 0.12 units/h (95% CI = 0.02 to 0.23 units/h) compared with a projected average RNA integrity number of 7.39 if no delays were present (P = .008) and decreased the RNA yield by 1.5 µg/h (95% CI = 0 to 4 µg/h) from a baseline mean RNA yield of 33.5 µg if no delays were present (P = .019). Prolonged cold ischemia statistically significantly increased the 3'/5' ratio of control gene transcripts, particularly of STAT1 (P < .001). Snap freezing statistically significantly increased the 3'/5' ratio of three control transcripts (ACTB, GAPDH, and 18S rRNA). Expression levels of single genes and multigene signatures for breast cancer were largely unaffected by sample preservation method or cold ischemia. CONCLUSIONS: Sample preservation in RNAlater improves RNA yield and quality, whereas cold ischemia increases RNA fragmentation as measured by the 3'/5' expression ratio of control genes. However, expression levels of single genes and multigene signatures that are of diagnostic relevance in breast cancer were mostly unaffected by sample preservation method or prolonged cold ischemic duration.