On 12 July Humanitas hosted the Clearly meeting, a multi-center European project of which Humanitas is the coordinator and which is part of the Transcan 2 programme, part of Horizon 2020. At the Humanitas Congress Centre, leading European experts in cancer screening and translational research met to discuss the prevention of lung cancer through the identification of circulating biomarkers and imaging.
The Clearly meeting was also an opportunity to present SMAC (Smokers Health Multiple Action), a free screening project for heavy smokers and ex-smokers that includes a low-dose chest CT scan, combined with intense anti-smoking activity.
What is Clearly and how was it formed? We talk about this topic with Dr. Giulia Veronesi, Head of the Section of Robotic Surgery of Humanitas, at the Operative Unit of Thoracic Surgery directed by Professor Marco Alloisio.
Lung Cancer and Screening
“More lung cancer deaths occur each year than combined colon, breast and prostate cancers. Lung cancer is the most common cancer in the world, with 1.8 million new cases and 1.6 million deaths in 2012. This cancer is often diagnosed in an advanced stage, with a 5-year survival rate of 16%.
Randomized and observational studies have shown that screening with low-dose CT scans reduces the number of deaths from lung cancer. Screening a population of people with a substantially high risk for this neoplasm has more benefits than risks. However, this screening is not a process without potential risks, such as false positives, which can lead to invasive procedures and complications,” explains Dr. Veronesi.
The role of biomarkers
“In principle, biomarkers can help in the identification of individuals who may benefit from low-dose CT scans or may complement the CT scans for the assessment of undetermined nodules. These markers can be found in various biological fluids, particularly blood, urine, saliva or sputum; exhaled breathing has also been explored as a source of biomarkers, in addition to bronchial and nasal brushing. Blood in particular, with its cellular constituents, micro-particles and plasma, represents a rich source of biomarkers. Another line of research involves models of cancer prediction that are based on automatic learning of the computer based on CT images, to assist doctors in the management of indeterminate pulmonary nodules detected randomly or on the screen. Such systems may be able to reduce the variability in nodal classification, improve decision making, and ultimately reduce the number of benign nodules that are unnecessarily followed or processed,” continues the practitioner.
The need for collaboration: the Clearly study
“Although considerable attention has been focused on the approach called liquid biopsy for lung cancer detection, it is likely that no single marker or approach will be useful alone, hence the need to explore combinations of markers and approaches to determine the most viable. This undertaking represents a major effort. There are thousands of publications in literature related to potential biomarkers of lung cancer. Testing candidate biomarkers, individually or in combination with bioinformatics technologies relevant to the intended application, is generally beyond the means of individual laboratories and requires a significant collaborative effort.
For this reason we have set up the Clearly (Validation of multiparametric models and Circulating and imaging biomarkers to improve Lung cancer EARLY detection) study consortium, which involves three clinical centers in Europe, five research laboratories and two advanced bioinformatics centers in five different European countries. Through the work of this international European team of high-profile scientists, we hope to accelerate the uptake of lung cancer screening programmes in Europe. The biomarkers and methods proposed could increase the rate of early cancer detection, facilitate the selection of candidates for screening and help the development of targeted molecular drugs to stop tumor progression,” concluded Dr. Veronesi.
Watch the interviews with European experts at the Clearly meeting: