Conference Coverage

Genetic profiles affect smokers’ lung cancer risk


 

FROM ASCO 2023

Smokers with extreme phenotypes of high and low risk of developing tobacco-associated lung cancer have different genetic profiles, according to a multidisciplinary study conducted by specialists from the Cancer Center at the University of Navarra Clinic (CUN). The results were presented at the annual meeting of the American Society for Clinical Oncology.

Ana Patiño García, PhD, director of the genomic medicine unit at the CUN and a coordinator of the research, explained in an interview the main reason why this study was conducted. “This study came straight out of the oncology clinic, where we are constantly encountering patients with lung cancer who have never smoked or who have smoked very little, while we also all know people who have smoked a lot throughout their lifetime and have never developed cancer. This observation has led us to ask whether there are genetic factors that increase or decrease the risk of cancer and protect people against this disease.”

José Luis Pérez Gracia, MD, PhD, oncologist, coordinator of the oncology trials department at the CUN and another of the individuals responsible for this research, said: “This is the first study to validate genetic factors associated with people who appear to be resistant to developing tobacco-related lung cancer or who, on the other hand, are at high risk of developing this disease.”

Pioneering approach

Earlier evidence showed that some smokers develop cancer, and others don’t. “This is a very well-known fact, since everyone knows about some elderly person who has been a heavy smoker and has never developed lung cancer,” said Dr. Pérez. “Unfortunately, we oncologists encounter young smokers who have been diagnosed with this disease. However, despite the importance of understanding the causes behind these phenotypes, it is a question that has never been studied from a genetic standpoint.”

The study was conducted using DNA from 133 heavy smokers who had not developed lung cancer at a mean age of 80 years, and from another 116 heavy smokers who had developed this type of cancer at a mean age of 50 years. This DNA was sequenced using next-generation techniques, and the results were analyzed using bioinformatics and artificial intelligence systems in collaboration with the University of Navarra Applied Medical Research Center and the University of Navarra School of Engineering.

When asked how this methodology could be applied to support other research conducted along these lines, Dr. Patiño said, “The most novel thing about this research is actually its approach. It’s based on groups at the extremes, defined by the patient’s age at the time of developing lung cancer and how much they had smoked. This type of comparative design is called extreme phenotypes, and its main distinguishing characteristic – which is also its most limiting characteristic – is choosing cases and controls well. Obviously, with today’s next-generation sequencing technologies, we achieve a quantity and quality of data that would have been unattainable in years gone by.”

Speaking to the role played by bioinformatics and artificial intelligence in this research, Dr. Patiño explained that they are fairly new techniques. “In fact, these technologies could be thought of as spearheading a lot of the biomedical research being done today. They’ve also somewhat set the stage for the paradigm shift where the investigator asks the data a question, and in the case of artificial intelligence, it’s the data that answer.”

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