Stopping Cancer Early – The Best Possible Investment

Lung

The lung cancer team is working toward improving lung cancer screening for all people, regardless of smoking status, to save lives by detecting otherwise lethal cancer early.

Lung cancer is the world’s top cancer killer, claiming more than 1.3 million lives per year. Global statistics show that 25 percent of all cases are not attributable to an individual’s own tobacco use, making lung cancer in non-smokers the seventh leading cause of cancer death worldwide. In addition, there are more than 94 million current and former smokers in the U.S., many of which are at high risk of lung cancer.

The Canary Lung Cancer Team was launched in 2008 to address the pressing need to find potentially lethal lung cancer early and to better understand lung cancer among never smokers, which is a poorly understood and seldom-studied disease. The team is developing markers for risk assessment and early detection applicable to smokers and never smokers that complement imaging strategies.

Team

The Canary Lung Cancer Team includes scientists who are experts at making lab discoveries and seeing patients in the clinic, offering the unique perspectives and expertise needed to deliver a successful screening approach to patients.

The team includes pulmonary specialists and clinicians, cancer biologists, researchers who develop tests to recognize changes in the body due to cancer, and scientists who examine ways to optimize implementation of screening strategies.

Members past and present include:

  • Peter Bach, MD, Memorial Sloan Kettering
  • Ziding Feng, PhD, MD Anderson Cancer Center
  • Sam Gambhir, MD, PhD, Stanford University
  • Adi Gazdar, MD, University of Texas Southwestern
  • Gary Goodman, MD, Swedish Hospital
  • Sam Hanash, MD, PhD, MD Anderson Cancer Center
  • Ite Laird-Offringa, PhD, University of Southern California
  • Wan Lam, PhD, British Columbia Cancer Agency
  • Stephen Lam, MD, British Columbia Cancer Agency
  • Sylvia Plevritis, PhD, Stanford University
  • Katerina Politi, PhD, Yale University
  • Muneesh Tewari, MD,PhD, University of Michigan
  • Mark Thornquist, PhD, Fred Hutchinson Cancer Research Center
  • Harold Varmus, MD, National Cancer Institute
  • Jun Zhu, PhD, Mount Sinai Hospital

Progress and Results

Just two years after the Canary lung team had begun working together, they had already discovered candidate lung cancer biomarkers and had revealed insights about never-smoker lung cancer.

At the same time, the team received the exciting news that the large randomized National Lung Screening Trial (NLST) in the U.S. had been stopped due to significant positive results. The NLST showed that screening heavy smokers with low-dose computed tomography (CT) significantly reduced deaths from lung cancer, compared with screening with chest x-rays.

The NLST findings, combined with the Canary Lung team’s research, afforded an incredible opportunity to save lives by improved screening for lung cancer.

While CT screening reduces lung cancer mortality, the technique has a high false- positive rate, leading to too many unnecessary follow-up tests for findings that are not cancer. In addition, the NLST results may apply only to the population tested in the study – heavy current and former smokers 55 to 74 years of age.

Collaborative 5-Year Study

To build upon our previous research and to improve upon the success of the NLST, partner stakeholders and collaborating institutions, including Canary Foundation and MD Anderson Cancer Center in Houston, Texas, are launching a collaborative five-year study.

In addition to saving lives through low-dose CT, the goal of this study is to test the contribution of biomarkers to CT screening.

Biomarkers have the potential to aid the interpretation of CT scans to reduce the false- positive rate. Biomarkers may also identify individuals at risk for lung cancer who could benefit from screening. The results of this study may become the standard of care for lung cancer screening in the future.

Clinical Studies

Lung Cancer Biomarkers—Launching Trial With 10,000
Partner stakeholders and collaborating institutions, including Canary Foundation and MD Anderson Cancer Center in Houston, Texas, are launching a clinical trial in which blood biomarker data will be incorporated into the CT screening process for lung cancer. The trial will enroll at least 10,000 individuals to be followed for three to five years at a minimum of 10 participating sites in the U.S.

At each visit, participants receive a CT scan, a questionnaire that includes detailed smoking history, and a blood draw. All participating sites will incorporate the same sets of Standard Operating Procedures for protocol design, specimen collection, processing, storage, and shipping.

Biomarkers will be tested for their ability to detect lung cancer and to discriminate cancer versus benign conditions in suspicious CT findings. Biomarkers will also be tested for their ability to predict a risk profile for lung cancer. Top biomarkers include those discovered and validated through the Canary Lung Team’s previous research on blood and tissues from lung cancers that developed in individuals who never smoked. The team is also evaluating all biomarkers that show promise from studies worldwide so that the most promising biomarkers can qualify for validation using samples from this prospective screening trial.

Where Canary Science is Happening

  • Canary Center at Stanford, Palo Alto, California
  • MD Anderson Cancer Center in Houston, Texas

Canary Funded Lung Cancer Papers

Wikoff, W.R., et al. Diacetylspermine Is a Novel Prediagnostic Serum Biomarker for Non-Small-Cell Lung Cancer and Has Additive Performance With Pro-Surfactant Protein B. Journal of Clinical Oncology (2015)

Yoo, S., et al. Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD. PLoS Genetics (2015)

Carlsson, A. et al. Circulating tumor microemboli diagnostics for patients with non-small-cell lung cancer. J Thorac Oncol. (2014)

Sin, D.D., et al. Pro–Surfactant Protein B As a Biomarker for Lung Cancer Prediction. Journal of Clinical Oncology. (2013)

Wu, C., et al. Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma. BMC Bioinformatics (2013)

Taguchi, A., et al. Circulating Pro-Surfactant Protein B as a Risk Biomarker for Lung Cancer. Cancer Epidemiol Biomarkers Prev. (2013)

Lin, R.S. and Plevritis, S.K. Comparing the Benefits of Screening for Breast Cancer and Lung Cancer Using a Novel Natural History Model. Cancer Causes Control. (2012)

Selamat, S.A., et al.  Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression.  Genome Res. (2012)

Thu, K.L., et al.  Lung adenocarcinoma of never smokers and smokers harbor differential regions of genetic alteration and exhibit different levels of genomic instability. PLoS One. (2012)

Taguchi, A., et al. Lung cancer signatures in plasma based on proteome profiling of mouse tumor models. Cancer Cell. (2011)

Zhang, Y.A., et al. Frequent detection of infectious xenotropic murine leukemia virus (XMLV) in human cultures established from mouse xenografts. Cancer Biol Ther. (2011)

Dasgupta, S., et al. Mitochondrial DNA mutations in respiratory complex-I in never-smoker lung cancer patients contribute to lung cancer progression and associated with EGFR gene mutation. J Cell Physiol. (2011)

Nielson, C.H., et al. PET imaging of tumor neovascularization in a transgenic mouse model with a novel 64Cu-DOTA-knottin peptide. Cancer Res. (2010)

Gazdar, A.F., et al. Lung cancer cell lines: Useless artifacts or invaluable tools for medical science? Lung Cancer. (2010)

Chari, R., et al. Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer. Cancer Metastasis Rev. (2010)

Qui, J., et al. Occurrence of autoantibodies to Annexin I, 14-3-3 Theta and LAMR1 in prediagnostic lung lancer sera. J. Clin. Oncology. (2008)

Bach, P.B. Is our natural-history model of lung cancer wrong? Lancet Oncol. (2008)