The main purpose of our study was to assess the feasibility of using single base mutations, specifically in the p53 gene, as molecular markers for the detection of minimal residual disease. Rather than exclusively advocating p53 as a potential marker for this purpose, we used p53 simply as a model, and the findings of our study could be applied to other genes in which subtle alterations are present in malignant cells. p53 was chosen in this study for three main reasons, namely:
- It is the single most frequently mutated gene in human cancers—one in five or more sporadic breast cancers have an alteration.11,18–21
- A large subgroup of the patient cohort selected for PBPC collection (patients with metastatic disease) had an adverse prognosis, or demonstrated aggressive or extensive disease, and historically this group has a higher incidence of p53 mutation.
- The heterogeneous location and nature of p53 mutations, with most (79%) being single base mutations located in hot spot regions corresponding to exons 5–8, with both transversions and transitions represented,22,23 posed a major challenge but made this a good system to test the feasibility of such an approach.
The ras oncogene family has been used more often in the context of minimal residual disease detection, but differs from p53 by having mutations occurring largely within a small number of codons (codons 12, 13, and 61),10
hence reducing the complexity of ARMS.
“The main limitation to a more sensitive system is the inability of the amplification refractory mutation system to differentiate effectively between wild-type and mutant DNA”
The PCR primers for initial screening of p53 mutations ensured that approximately 90% of reported mutations in breast cancer were detected by DGGE.24
The incidence of somatic p53 mutations in our patient cohort (approximately a quarter of the cases) was similar to other published series. Of 11 samples successfully sequenced, four were found in recognised hot spot codons (codons 175, 248 (two patients), and 273), consistent with other studies on sporadic breast cancer.24
However, the number of patients amenable to the study of minimal residual disease was greatly reduced by (1) the failure to obtain reliable sequence information (two of 15); (2) the presence of constitutional polymorphisms (two of 15); and (3) a failure to optimise the ARMS stage fully (four of 15). Only a small number of studies describe methods to optimise ARMS, mostly based on models with one or a small number of single base changes.25–28
Our study attempted to optimise a heterogeneous system of mutant markers. Because of the subtle nature of the genetic alterations, only half of the 10 evaluable systems were sufficiently optimised. This experience is at variance with other studies. Whereas our results suggested that the important factors were the use of an additional mismatch in the ARMS primer, Ta, and the concentration of magnesium, others reported that the concentrations of magnesium and the primer were more crucial.29
Ta and the dNTP concentration were reported to have little influence on optimising the reaction.25,30,31
Although pyrimidine–pyrimidine and purine–purine mismatches at the 3′ end of a primer are most refractory to strand extension, this was not an important factor in determining ARMS optimisation.30,31
Applying ARMS to the detection of minimal residual disease requires a high “discrimination sensitivity” between WT and mutant DNA. Reported sensitivities range from 1/10031
when radioisotopes are used, or glycerol added. Our range of sensitivities of 1/100 to 1/1000 falls within this range, and the main limitation to a more sensitive system is the inability of ARMS to differentiate effectively between WT and mutant DNA. Optimisation experiments for each ARMS system ensure that WT DNA is not amplified, but at the same time reduce the efficiency of amplifying the mutant species. DNA extracted from stored, paraffin wax embedded pathological specimens may be of inferior quality compared with that from fresh tumours, but we found no evidence that such DNA is not efficiently amplified by PCR. Moreover, tumour DNA quality would be more likely to influence the initial PCR, DGGE, and sequencing, but not the sensitivity of ARMS to detect minimal residual disease. Each ARMS reaction used 1 μg of genomic DNA, which contained approximately 3 × 105
copies of an autosomal gene.28
p53 alterations occur commonly with loss of heterozygosity, resulting in only 1.5 × 105
copies/1 μg DNA. On the assumption that ARMS can amplify one single molecule of mutated p53 within 1 μg of template DNA, the maximum sensitivity would be in the order of 1/105
, and probably much lower in practice when non-radioisotopic methods are used to visualise the products, as our results suggest.
Take home messages
- The detection of single base genetic changes to assess minimal residual disease in breast cancer is a complex process, which is labour intensive and therefore unlikely to play an important role in clinical practice
- In addition, it is relatively insensitive, lacks sensitivity, and is limited to a small number of patients and to certain mutations
- Reverse transcriptase polymerase chain reaction methods may be more suited to the detection of minimal residual disease
In conclusion, the detection of minimal residual disease using p53 missense mutations is a multistep procedure requiring mutation detection, sequencing, and ARMS optimisation. We found that this approach was labour intensive, lacked specificity, and was relatively insensitive. RT-PCR techniques, which use a much larger number of copies of nucleic acid, may be a more suitable vehicle to study minimal residual disease in these patients.32–34