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. 2005 Sep 20;102(38):13550-5.
doi: 10.1073/pnas.0506230102. Epub 2005 Sep 2.

An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival

Lance D Miller  1 , Johanna Smeds, Joshy George, Vinsensius B Vega, Liza Vergara, Alexander Ploner, Yudi Pawitan, Per Hall, Sigrid Klaar, Edison T Liu, Jonas Bergh
Affiliations

An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival

Lance D Miller et al. Proc Natl Acad Sci U S A. .

Erratum in

  • Proc Natl Acad Sci U S A. 2005 Dec 6;102(49):17882

Abstract

Perturbations of the p53 pathway are associated with more aggressive and therapeutically refractory tumors. However, molecular assessment of p53 status, by using sequence analysis and immunohistochemistry, are incomplete assessors of p53 functional effects. We posited that the transcriptional fingerprint is a more definitive downstream indicator of p53 function. Herein, we analyzed transcript profiles of 251 p53-sequenced primary breast tumors and identified a clinically embedded 32-gene expression signature that distinguishes p53-mutant and wild-type tumors of different histologies and outperforms sequence-based assessments of p53 in predicting prognosis and therapeutic response. Moreover, the p53 signature identified a subset of aggressive tumors absent of sequence mutations in p53 yet exhibiting expression characteristics consistent with p53 deficiency because of attenuated p53 transcript levels. Our results show the primary importance of p53 functional status in predicting clinical breast cancer behavior.

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Figures

Fig. 1.
Fig. 1.
The p53 signature is associated with p53 status in independent data sets. Clustergrams are oriented as outlined in Fig. 5. (A) Expression profiles of the Uppsala tumors segregated by the 32-gene signature. Unigene symbols and GenBank IDs are listed to the right. (B) P53 mt and wt breast tumors from Sørlie et al. (18) were clustered by using a nine-gene subset of the p53 signature. (C) P53 mt and wt liver tumors (predicted by immunohistochemistry) from Chen et al. (19) were clustered by using an eight-gene subset of the p53 signature. Green dendrogram branches denote tumors with the wt-like configuration; red branches indicate those with mt-like profiles. Probe IMAGE clone IDs from the original studies are listed. Black bars denote mt p53 status.
Fig. 2.
Fig. 2.
Transcript levels of p53 and its transcriptional targets are consistent with classification results. Expression levels of p53-pathway-relevant genes were examined in different tumor subgroups. The four tumor subgroups are defined as follows: (i) p53 mt tumors classified as mt-like (n = 46), (ii) p53 wt tumors classified as mt-like (n = 26), (iii) p53 wt tumors classified as wt-like (n = 167), and (iv) p53 mt tumors classified as wt-like (n = 12). Differences in transcript levels were determine by t test and are shown in a summary table to the right; P values >0.05 are shown in gray.
Fig. 3.
Fig. 3.
The p53 classifier has greater prognostic significance than p53 mutation status alone. Kaplan-Meier survival plots for disease-specific survival are shown for patients classified according to p53 mutation status (A and E), the p53 classifier (B, C, and F), or both (D). All patients were assessed in A, B, and D. Only the patients with p53 wt tumors were assessed in C. Sixty-seven ER+, hormone-treated (TAM) patients were assessed in E and F.
Fig. 4.
Fig. 4.
The p53 signature predicts survival in independent clinically diverse data sets. (A) Tumor dendrogram from clustering 60 tumors and 22 genes (27 probes) from Ma et al. (20). (B and C) Patient subgroups determined by the primary tumor branches (C1-C4) were analyzed for correlations with DFS. (D) Tumor dendrogram from clustering 76 tumors and 9 genes from Sørlie et al. (18). Patient subgroups defined by the primary tumor branches (C1 and C2) were analyzed for correlations with disease-specific survival (DSS) (E) and DFS (F). (G) Tumor dendrogram from clustering 97 tumors and 21 genes (25 probes) from van't Veer et al. (21). (H and I) Primary tumor clusters (C1-C5) defined patient subgroups for DFS analysis. Red branches denote tumors with the p53 mt-like signature; black branches identify those with the wt-like signature. Black triangles indicate patients who relapsed within 5 years. See Fig. 7 for gene heat maps and probe IDs.
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