Can Your Breath Help With Early Diagnosis of Mesothelioma?

Two of the challenges for malignant mesothelioma cancer are early diagnosis and predicting whether patients will respond well to treatment.

Could your breath be a solution to both?

Two separate studies hint at the potential to use human breath to predict whether individuals exposed to asbestos will develop mesothelioma and whether people diagnosed with the cancer will benefit from treatment.

The Journal of Breath Research has a study that tested whether breath analysis can differentiate asbestos-exposed individuals from people with pleural mesothelioma. While asbestos is the only cause of this cancer, most people exposed to asbestos will not develop mesothelioma.

Then, a study highlighted at the International Association for the Study of Lung Cancer (IASLC) 2023 World Conference on Lung Cancer in Singapore looked at whether breath analysis can differentiate between treatment responders and non-responders.

Both studies analyzed what’s called “volatile organic compounds” in exhaled breath. These compounds can include markers for mesothelioma and other cancers.

 

Predicting Mesothelioma Ahead of Time

Being able to predict whether a patient will develop mesothelioma is arguably the most crucial part of these two studies. Mesothelioma has what’s called a “long latency period,” which means it takes longer than most cancers to form.

Asbestos exposure is the only cause of mesothelioma, but individuals who develop the cancer often experience symptoms relative to common illnesses. Mesothelioma tumors are often undetectable for 20-50 years after their asbestos exposure. Therefore, a lot of patients don’t realize they have mesothelioma right away because they don’t connect their past exposure to the possibility of having cancer.

Predicting whether someone will develop this disease can help get an early diagnosis of mesothelioma, which means the patients can begin treatment before the tumors grow or spread much. This is crucial to defeating mesothelioma and a common part of survival stories.

The breath test conducted in one study differentiated 112 asbestos-exposed individuals from six pleural mesothelioma patients with 87% accuracy. Asbestos-exposed individuals were screened once a year. All six pleural mesothelioma patients were correctly classified as having mesothelioma thanks to breath analysis, and out of 112 asbestos-exposed individuals, the test identified 78 as having pleural mesothelioma.

While the test was 100% accurate in identifying mesothelioma in diagnosed pleural mesothelioma patients, there was a high false positivity rate.

 

Predicting Patient Response to Treatment

Mesothelioma is an aggressive cancer with an average survival of 1-2 years. The standard treatment options for mesothelioma are surgery, chemotherapy, immunotherapy and radiation. While surgery is the first choice, not many patients are fit enough or have a localized cancer to benefit from an aggressive surgery.

Chemotherapy and immunotherapy are the most common therapies used to treat mesothelioma. However, not all patients respond the best to them, either due to side effects or not controlling tumors.

Being able to predict which patients will respond best to treatment can save some patients from enduring uncomfortable and life-altering side effects. Mesothelioma Guide previously reported how breath tests could indicate the success of immunotherapy.

In the study presented at the World Conference on Lung Cancer, there were 13 patients with pleural mesothelioma. They received a CT scan before treatment and every three months after treatment. They were classified as either having a stable disease (meaning treatment worked) or progressive disease (meaning treatment did not work).

Breath samples were collected from the patients at the same time as each CT scan, and volatile organic compounds were identified to differentiate between responders and non-responders. There was no difference in the treatment offered to the patients.

The study identified an 89% accuracy in distinguishing between stable disease and progressive disease after treatment ended. It also was 89% accurate in predicting before treatment started whether patients would have stable disease or progressive disease after treatment ended.

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