Poverty link to cancer survival


Study's findings appear to suggest that part of the reason why women with breast cancer from deprived areas have worse overall survival may be related to mutations in the p53 gene

“There is a genetic explanation for why women from poor backgrounds are less likely to beat breast cancer,” BBC News reported. It said researchers have found an association between a woman’s postcode and a particular mutation of a gene linked with a poorer prognosis for breast cancer.

The researchers found that women who lived in deprived areas were more likely to have p53 mutations, and were less likely to have survived cancer-free. The p53 gene normally acts to suppress the development of tumours, but if it is mutated it increases the risk that a cell may become cancerous.

These findings suggest that part of the reason why women from deprived areas have worse overall and disease-free survival from breast cancer may be related to mutations in the p53 gene. Exactly how socio-economic status interacts with the p53 gene to have this effect will require further investigation. 

Although the suggestion is made in the news reports that poor lifestyle factors, such as smoking or drinking may be responsible, the current study did not investigate the reason for the higher level of p53 mutations in the more deprived group, so it is not possible to say whether this is the case.

Where did the story come from?

The research was carried out by Dr Lee Baker and colleagues from Dundee University, Ninewells Hospital and Medical School in Dundee, and Roche (the manufacturers of the genetic test used). The study was funded by Breast Cancer Research, Scotland. The paper was published in the peer-reviewed British Journal of Cancer .

This study was reported on by the BBC News and The Guardian , which both covered it accurately. BBC News suggested that “poor lifestyle may trigger” the mutations, and The Guardian mentions a survey that found that factors associated with deprivation such as smoking, drinking and an unhealthy diet could make the p53 mutation more likely. However, the survey mentioned was not part of the current research study, which did not assess the causes of the p53 mutations.

What kind of research was this?

This cohort study investigated whether there is a relationship between socio-economic status, certain genetic mutations in breast cancer, and survival or recurrence of the cancer. Women from deprived areas have poorer survival rates from breast cancer than women from more affluent areas. However, it is not clear what causes this difference. Previous studies have suggested that certain mutations in the p53 gene are associated with more aggressive breast cancers, and can predict how successful treatment will be. The researchers wanted to know whether the effect that socio-economic status has on prognosis is related to differences in this gene.

The study used donated tissue from a tissue bank that had already been collected. Some clinical and pathological information about the women was also collected prospectively which increases the likelihood that it is accurate. One limitation is that the researchers had to rely solely on the information that had been previously collected, and this may not have included all of the factors that could have affected the results, and that they would have liked to take into account.

The data on gene mutation and socio-economic status was examined cross-sectionally, as the tissue samples were collected at the time of surgery. The women were then followed up over time to determine their outcomes. As the tissue was collected at the time of surgery, looking at the DNA from this tissue gives a snapshot of what mutations were present in the cancer cells at the time of treatment, and that could have affected the women’s outcomes after surgery.

What did the research involve?

The researchers used primary breast cancer tissue that had been donated to a tissue bank for research purposes. They extracted DNA from these samples, and used a genetic test to look for mutations in the p53 gene. They looked at where the women who had given these samples lived, and how deprived the area was. This data was then analysed to see whether the level of deprivation in the area where a woman lived was related to whether she had p53 mutations. The researchers also looked at whether a woman’s p53 status was related to the characteristics of her tumour, how long she survived overall, and how long she survived without a recurrence of her cancer.

The samples were obtained from 246 Caucasian women with primary breast cancer who had surgery to remove it between 1997 and 2001, and who had not previously received treatment. The women were all diagnosed and treated at the same centre. The removed tissue was stored in a tissue bank and the women followed up for at least five years to see what their outcomes were. Information on the women’s tumours and their outcomes were collected prospectively.

The tissue was tested with a ‘microarray’, a system that can test DNA samples for many different mutations at the same time. The microarray assessed the DNA sequence at 1268 positions within the p53 gene, and could detect single ‘letter’ changes and deletions in the sequence at these points. The analyses compared women in three ways by looking at:

  • all women in the study,
  • all women with p53 mutations, and
  • all women without p53 mutations.

The level of deprivation in the areas where the women lived was calculated based on the commonly used Carstairs index of socio-economic status, which gives deprivation scores for individual postcode areas. Women in the most deprived areas (worst 10% of scores) were compared with women in less deprived areas (the remaining 90%).

The researchers also investigated whether differences in treatment or tumour characteristics could account for differences in outcomes.

What were the basic results?

Of the 246 women followed for five years or more, 205 (83%) were still alive at their last follow up, 184 (75%) were alive without recurrence of their cancer, and 41 (17%) had died. There were 17 women (7%) from the most deprived areas.

Certain tumour characteristics were more common among these women (grade 3 tumours and HER2-positive tumours), while there was no difference in other tumour characteristics (tumour size, lymph node status, and oestrogen or progesterone receptor status) or treatments received. Women from the most deprived areas were more likely to have a relapse or die than women from less deprived areas.

The researchers found that just over a quarter of tumours carried a p53 mutation (64 out of 246 tumours or 26%). Women with p53 mutations were more likely to have a higher tumour grade, tumour spread to armpit (axillary) lymph nodes, HER-2 positive tumours and oestrogen receptor negative cancers.

Women with p53 mutations had lower overall survival and disease-free survival five years after their surgery than those without mutations in the gene. Mutations in the p53 gene were more common in women from the most deprived areas. Almost 60% of these women had p53 mutations in their tumours (10 out of 17 tumours).

Fewer women in the most deprived areas who had p53 mutations were still alive five years after their cancer diagnosis (24%) compared with women from less deprived areas with p53 mutations (72%). Women from the most deprived areas who had p53 mutations were also less likely to have survived five years without recurrence of their disease (20%) than women from less deprived areas with p53 mutations (56%). These differences were statistically significant, even after adjustment for tumour characteristics that could be affecting results.

However, there were no differences in overall or disease-free survival between the deprivation categories in analyses looking only at women without p53 mutations.

How did the researchers interpret the results?

The researchers conclude that, “p53 mutation in breast cancer is associated with socio-economic deprivation and may provide a molecular basis, with therapeutic implications, for the poorer outcome in women from deprived communities”.


These findings appear to suggest that part of the reason why women with breast cancer from deprived areas have worse overall survival and disease-free survival, may be related to mutations in the p53 gene. Exactly how socio-economic status interacts with the p53 gene to have this effect is not clear and will require further investigation. Other points to note about the current study are that:

  • The measure of the women’s level of deprivation was based on the women’s postcode. Though this is an accepted method for measuring deprivation, it may not give as exact a measure as a more thorough assessment of individual women’s socio-economic characteristics (e.g. household income, education and so on).
  • The study was relatively small, with few women in the most deprived category (17 women). Technically, this means that the results are less reliable than they would be with a larger sample, and the authors acknowledge that further studies will be needed to confirm the results.
  • The researchers were able to take into account some factors that could affect potentially have affected the results, but there may be others, such as inflammatory markers, that were not measured. The researchers say it is possible that some of these unmeasured factors could explain some of the effect seen.
  • The study only included Caucasian women, so the results may not apply to other ethnic groups.

The study did not assess why women in the more deprived areas have more p53 mutations. Previous studies have shown that women from more deprived areas have poorer breast cancer prognosis than those from less deprived areas, although the reasons for this are not clear. This study has investigated whether p53 plays a role in this.

Although some news sources have suggested that lifestyle factors such as smoking or alcohol use could be to blame, this study did not assess why p53 mutations were more common in the deprived group. Therefore no conclusions can be drawn about what factors might be responsible. Further research will help to solve this.

Article Metadata Date Published: Tue, 15 Aug 2017
Author: Zana Technologies GmbH
NHS Choices