Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival

Abstract

Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal links between wound healing and cancer progression in a variety of common epithelial tumors. Here, in a consecutive series of 295 early breast cancer patients, we show that both overall survival and distant metastasis-free survival are markedly diminished in patients whose tumors expressed this wound-response signature compared to tumors that did not express this signature. A gene expression centroid of the wound-response signature provides a basis for prospectively assigning a prognostic score that can be scaled to suit different clinical purposes. The wound-response signature improves risk stratification independently of known clinico-pathologic risk factors and previously established prognostic signatures based on unsupervised hierarchical clustering ("molecular subtypes") or supervised predictors of metastasis ("70-gene prognosis signature").

Figures

Fig. 1.

Performance of a “wound response” gene expression signature in predicting breast cancer progression. (A) Unsupervised hierarchical clustering of 295 breast cancer samples using 442 available CSR genes. Each row represents a gene; each column represents a sample. The level of expression of each gene, in each sample, relative to the mean level of expression of that gene across all of the samples, is represented by using a red–green color scale as shown in the key; gray indicates missing data. The transcriptional response of each gene in the fibroblast serum response is shown on the right bar (red indicates increased expression, and green indicates reduced expression in response to serum). The dendrogram at the top indicates the similarities among the samples in their expression of the CSR genes. Two main groups of tumors were observed: one group with a gene expression pattern similar to that of serum-activated fibroblasts, termed “activated,” and a second group with a reciprocal expression pattern of CSR genes, termed “quiescent.” Two small subsets of the quiescent group with more heterogeneous expression patterns are indicated by yellow bars. (B and C) Kaplan–Meier survival curves for the two classes of tumors. Patients with tumor expression the activated wound-response signature had worse overall survival (OS) and DMFP compared to those with a quiescent wound-response signature. A total of 126 tumors were classified as activated, and 169 tumors were classified as quiescent. For activated vs. quiescent groups, 10-year OS are 50% vs. 84% (P = 5.6 × 10-10) and 10-year DMFP are 51% vs. 75% (P = 8.6 × 10-6), respectively.

Fig. 2.

A scalable wound-response signature as a guide for chemotherapy. (A) Wound-response signature adds prognostic information within the group of high-risk patients identified by NIH consensus criteria. According to the NIH criteria, 284 patients are high risk and advised to undergo adjuvant chemotherapy; 72 patients had tumor-positive lymph nodes. Patients were classified by using the serum activated fibroblast centroid (threshold = -0.15). The 10-years DMFP for the activated (n = 221) vs. quiescent (n = 61) is 58% vs. 83%, respectively (P = 0.0002). (B) Wound-response signature stratifies St. Gallen criteria high-risk patients. According to St. Gallen criteria, 271 patients are high risk and advised to undergo adjuvant treatment; 72 patients had tumor-positive lymph nodes. When the supervised wound signature was used, the 10-years DMFP for the activated (n = 217) vs. quiescent (n = 56) group is 59% vs. 83%, respectively (P = 0.0005). (C) Graphical representation of number of patients advised to undergo adjuvant systemic treatment and their eventual outcomes based on the supervised wound-response signature or the NIH or St. Gallen criteria in the 185 patients in this data set that did not receive adjuvant chemotherapy. Forty patients had tumor-positive lymph nodes. Yellow indicates chemotherapy, blue indicates no chemotherapy. The bar at left shows which patients have developed distant metastasis as first event: black indicates distant metastasis; white indicated no metastasis. Thus, blue in the lower bar indicates the potentially undertreated patients, yellow in the upper bar shows the potentially overtreated patients.

Fig. 3.

Integration of diverse gene expression signatures for risk prediction. (A) Compendium of gene expression signatures in 295 breast tumors. Shown are correlation values to canonical centroids of classes defined by intrinsic genes (basal, luminal A, luminal B, ErbB2, vs. normal-like), by the 70 genes (poor prognosis vs. good), and by the wound signature (activated vs. quiescent). Orange indicates positive correlation; blue indicates anticorrelation. Each row is a class; each column is a sample. (Lower) Corresponding clinical outcomes; black vertical bar indicated death or metastasis as the first recurrence event. (B) Summary of decision tree analysis. At each node, the dominant risk factor in multivariate analysis is used to segregate patients, and the process is repeated in each subgroup until patients or risk factors became exhausted. We found that the 70-gene signature was able to identify a group of patients with very good prognosis (group 0), and then the wound signature could divide the patients called “poor” by the 70-gene signature into those with moderate and significantly worse outcomes (groups 1 and 2). (C) Distribution of 144 lymph node-positive patients among the three groups defined in B. Because the 70-gene signature was identified by using a select subset of 60 patients with lymph node-negative disease, the decision tree incorporating the 70-gene signature was performed on the independent lymph node-positive subset to have an unbiased evaluation of risk prediction. Hazard ratios of metastasis risk after adjusting for all other factors listed in Table 1 are shown for the three subgroups stratified by the decision tree. (D) Distant metastasis free probabilities of patients stratified by the decision tree analysis. A total of 55, 32, and 57 patients are in group 0, 1, and 2, respectively, and 10 years DMFP for the three groups were 89%, 78%, and 47%, respectively (P = 6.94 × 10-6).