Clinical outcomes and correlates of TP53 mutations and cancer

Abstract

The initial observation that p53 accumulation might serve as a surrogate biomarker for TP53 mutation has been the cornerstone for vast translational efforts aimed at validating its clinical use for the diagnosis, prognosis, and treatment of cancer. Early on, it was realized that accurate evaluation of p53 status and function could not be achieved through protein-expression analysis only. As our understanding of the p53 pathway has evolved and more sophisticated methods for assessment of p53 functional integrity have become available, the clinical and molecular epidemiological implications of p53 abnormalities in cancers are being revealed. They include diagnostic testing for germline p53 mutations, and the assessment of selected p53 mutations as biomarkers of carcinogen exposure and cancer risk and prognosis. Here, we describe the strengths and limitations of the most frequently used techniques for determination of p53 status in tumors, as well as the most remarkable latest findings relating to its clinical and epidemiological value.

Figure 1.

The TP53 mutational spectrum in familial and sporadic cancer. (A) Germline TP53 missense mutations result in earlier onset of cancers in LFS (p = .017 for index cases, and p = .004 for carriers). Mutation spectrum of (B) germline and (C) somatic TP53 mutations. Reproduced from the IARC p53 database (http://www-p53.iarc.fr) using the provided bioinformatics tools (Petitjean et al. 2007). (A, Adapted, with permission, from Bougeard et al. 2008 [© BMJ Group].)

Figure 2.

Graphical representation of the number of studies that have shown an association or lack of association of TP53 mutation with poor survival. The cumulative number of patients in all cohorts reported in those studies is indicated as n for each cancer type. Data were extracted from the IARC p53 database R13 release (http://www-p53.iarc.fr) and were updated with 20 new studies appearing in 2006–2009.

Figure 3.

Kaplan-Meier survival curves of patients with breast cancer stratified by the type of TP53 gene mutation found in their tumor. Survival of patients without mutation or with a silent mutation within exons 5 to 8 (blue line), with a missense mutation within exons 5 to 8 but outside the DNA binding domains (red line), with a missense mutation in the DNA binding domains (green line), and with a mutation other than missense within exons 5 to 8 (black line). (Reprinted, with permission, from Olivier et al. 2006 [© AACR].)

Figure 4.

Cancer genome landscapes of typical (A) colorectal or (B) breast tumors. Nonsilent somatic mutations are plotted in two-dimensional space representing chromosomal positions of RefSeq genes. Peaks indicate individual genes mutated at high frequency, with peak height reflecting mutation prevalence. The dots represent genes that were somatically mutated in the individual colorectal (Mx38) or breast (B3C) tumor displayed. The mountain on the right of both landscapes represents TP53 (chromosome 17), and is shared by both breast and colorectal cancers. (Reprinted, with permission, from Wood et al. 2007 [© AAAS].)

Figure 5.

MicroRNAs are integral to the p53 network and their abnormalities may have clinical implications. MicroRNAs mir-34a, b, and c, are transcriptionally transactivated by p53 and are downstream effectors of p53 function. MicroRNA mir-125b negatively regulates p53 expression. In addition to TP53 mutations and deletions, abnormalities in microRNAs, such as methylation of mir-34 (Lujambio et al. 2008) and/or amplification of mir-125b (Bousquet et al. 2008) may affect downstream p53 functions.