Tobacco smoking undermines anti-cancer safeguards by causing harmful DNA mutations

Scientists at the Ontario Institute for Cancer Research (OICR) have uncovered one way tobacco smoking causes cancer and makes it harder to treat by undermining the body's anti-cancer safeguards.

Their new study, published today in Science Advances, links tobacco smoking to harmful changes in DNA called 'stop-gain mutations' that tell the body to stop making certain proteins before they are fully formed.

They found that these stop-gain mutations were especially prevalent in genes known as 'tumor-suppressors', which make proteins that would normally prevent abnormal cells from growing.

"Our study showed that smoking is associated with changes to DNA that disrupt the formation of tumor suppressors," says Nina Adler, a University of Toronto PhD student who led the study during her postgraduate research in Dr. Jüri Reimand's lab at OICR. "Without them, abnormal cells are allowed to keep growing unchecked by the cell's defenses and cancer can develop more easily."

Adler, Reimand and colleagues used powerful computational tools to analyze DNA from more than 12,000 tumour samples across 18 different types of cancer. Their analysis showed a strong link between stop-gain mutations in lung cancer and the telltale 'footprint' that smoking leaves in DNA.

The researchers then looked at whether how much someone smoked had an impact. Sure enough, their analysis showed that more smoking led to more of these harmful mutations, which can ultimately make cancer more complex and harder to treat.

Tobacco does a lot of damage to our DNA, and that can have a major impact on the function of our cells. Our study highlights how tobacco smoking actually deactivates critical proteins, which are the building blocks of our cells, and the impact that can have on our long-term health."

Dr. Jüri Reimand, an OICR Investigator and Associate Professor at the University of Toronto

The study also identified other factors and processes responsible for creating large numbers of stop-gain mutations, which are also called 'nonsense' mutations. Some, like a group of enzymes called APOBEC that is strongly linked to stop-gain mutations in breast cancer and other cancer types, occur naturally in the body. Other factors like unhealthy diet and alcohol consumption are also likely to have similar damaging effects on DNA, but Reimand says more information is needed to fully understand how that works.

As for smoking, Adler says the findings from this study are an important piece of the puzzle behind a leading cause cancer in the world.

"Everyone knows that smoking can cause cancer, but being able to explain one of the ways this works at a molecular level is an important step in understanding how our lifestyle affects our risk of cancer," Adler says.

OICR President and Scientific Director Dr. Laszlo Radvanyi says these new insights should reinforce that tobacco smoking is one of the biggest threats to our health.

"This is further proof of the immense damage smoking has on our bodies, and further evidence that stopping smoking is always the right choice," Radvanyi says.

Source:
Journal reference:

Adler, N., et al. (2023). Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes. Science Advances. doi.org/10.1126/sciadv.adh3083.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Machine learning model predicts CDK4/6 inhibitor effectiveness in metastatic breast cancer