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Clinical And Liquid biopsy, Informatics, Breathomics, and Radiomics for Early detection of Cancer (CALIBRE)

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Current lung cancer screening strategies, using low-dose computed tomography, can be refined to improve test characteristics through the use of clinical and laboratory biomarkers. Further, new strategies can be developed that would expand the role of screening to moderate-to-low risk individuals.

The Projects and Cores


Four critical research areas have been identified, along with a fifth project to analyze all combined data, to drive this five-year vision:


Project 1: Clinical and Implementation Research

Developing more efficient ways to perform low dose CT screening scans.


Project 2: Radiomica

Using computer software analytic techniques (also known as artificial intelligence

methods, or AI) to improve interpretation of CT scans.


Project 3: Liquid Biopsy Testing
using simple and non-invasive blood-based tests, instead of surgical tumour biopsies, to enhance screening and diagnostics.

Project 4: Breathomics

Exploring the use of a new innovative device, called an electronic nose, to detect “tumour odours” in exhaled breath, with analyses using artificial intelligence techniques


Project 5: Integrative Analysis

Combining all the data from Projects 1-4 to determine which combined strategy is most effective in the early detection of lung cancer.


The Cores

Cores are cross-project expertise required and include an Administrative core for program coordination, a biostatistics core, a bioinformatics/data science core, and a biospecimen core.  



Over the span of over a decade and through generous philanthropic donations and funding from the Terry Fox Research Institute, biospecimens from the Lusi Wong Early Detection of Lung Cancer Research Program (PIs: Heidi Schmidt, Ming Tsao, Geoffrey Liu) and the Terry Fox Research Institute Pan-Canada Lung Screening trial (PIs: Stephen Lam (BCCA) and Ming Tsao) have generated data and samples stored in the Liu laboratory. These data/samples have have been collected in over 8000 individuals between the two studies, and serve as excellent material from which to test the hypotheses in the five projects.


The scientific goals are:

(1) To optimize clinical prediction models for early detection of lung cancer

(2) To utilize liquid biopsy techniques (including molecular profiling of cell-free DNA and circular RNA technology, and blood-based biomarkers for early cancer detection

(3) To utilize radiomic techniques to better distinguish between cancer versus non-cancerous lesions seen on imaging

(4) To investigate other emerging techniques such as breathomics that can be used for early detection

(5) To integrate data from novel technologies with optimized clinical prediction models for translation into the clinical setting.

(6) Eventual expansion to include other disease sites, in particular head and neck cancer and esophageal cancer.



PMID: 30771523 (J Thor Oncol)

PMID: 29989522 (Radiology)

PMID: 30429608 (Nature)


Funding Sources: National Cancer Institute (USA); Princess Margaret Cancer Foundation; Lusi Wong Family Fund; Canadian Cancer Society Research Institute.

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