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Pan-cancer DNA methylation signature quantification of lifestyle exposures and cancer prognosis
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Abstract
Background: Alcohol consumption, body mass index (BMI) and cigarette smoking are among the most well-studied lifestyle cancer risk exposures which can also change the host’s epigenetic methylation patterns. Some of the changes associated with lifestyle exposure are specific and stable over time, thus, can be used to predict and quantify the exposure. Although the link between these lifestyle exposures and increased odds ratio (OR) of different cancer types is well known, their role in predicting cancer survival remains less clear. We hypothesized that by using predicted lifestyle exposures based on the methylation profiles in tumour DNA we could predict the overall survival probability in cancer patients associated with these exposures. Results: The Cancer Genome Atlas (TCGA) Pan-Cancer dataset was used to test the prognostic value of the predicted DNAmethylation (DNAm) alcohol, BMI and smoking exposures in 24 cancer types (n= 8,238 subjects). Multivariable Cox proportional hazards models with adjustment for age, cancer stage and other exposures were used to calculate the hazards ratio (HR) for overall survival associated with these predicted DNAm exposures. We observed specific cancer types with strong associations between poorer survival and higher alcohol consumption (bladder, brain, esophageal, and head and neck cancers), higher BMI (bladder, pancreatic and post-menopausal breast cancers), and smoking (B-cell lymphoma, stomach, bladder and lung cancers). Interestingly, we also observed associations between better survival from kidney cancer with higher alcohol consumption and smoking exposures. For alcohol consumption we found a positive association between HR and OR across all cancers, indicating that for cancers where alcohol is a significant risk factor, it is also associated with poorer survival (p = 0.022). This was not the case for the BMI (p = 0.548) or smoking exposures (p = 0.193). Conclusions: In conclusion, these DNAm exposure signatures may provide novel information on the relationship between these lifestyle factors and cancer outcomes.
Title: Pan-cancer DNA methylation signature quantification of lifestyle exposures and cancer prognosis
Description:
Abstract
Background: Alcohol consumption, body mass index (BMI) and cigarette smoking are among the most well-studied lifestyle cancer risk exposures which can also change the host’s epigenetic methylation patterns.
Some of the changes associated with lifestyle exposure are specific and stable over time, thus, can be used to predict and quantify the exposure.
Although the link between these lifestyle exposures and increased odds ratio (OR) of different cancer types is well known, their role in predicting cancer survival remains less clear.
We hypothesized that by using predicted lifestyle exposures based on the methylation profiles in tumour DNA we could predict the overall survival probability in cancer patients associated with these exposures.
Results: The Cancer Genome Atlas (TCGA) Pan-Cancer dataset was used to test the prognostic value of the predicted DNAmethylation (DNAm) alcohol, BMI and smoking exposures in 24 cancer types (n= 8,238 subjects).
Multivariable Cox proportional hazards models with adjustment for age, cancer stage and other exposures were used to calculate the hazards ratio (HR) for overall survival associated with these predicted DNAm exposures.
We observed specific cancer types with strong associations between poorer survival and higher alcohol consumption (bladder, brain, esophageal, and head and neck cancers), higher BMI (bladder, pancreatic and post-menopausal breast cancers), and smoking (B-cell lymphoma, stomach, bladder and lung cancers).
Interestingly, we also observed associations between better survival from kidney cancer with higher alcohol consumption and smoking exposures.
For alcohol consumption we found a positive association between HR and OR across all cancers, indicating that for cancers where alcohol is a significant risk factor, it is also associated with poorer survival (p = 0.
022).
This was not the case for the BMI (p = 0.
548) or smoking exposures (p = 0.
193).
Conclusions: In conclusion, these DNAm exposure signatures may provide novel information on the relationship between these lifestyle factors and cancer outcomes.
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