The presence of circulating genetically abnormal cells in blood predicts risk of lung cancer in individuals with indeterminate pulmonary nodules.
Shahram Tahvilian, Joshua D Kuban, David F Yankelevitz, Daniel Leventon, Claudia I Henschke, Jeffrey Zhu, Lara Baden, Rowena Yip, Fred R Hirsch, Rebecca Reed, Ashley Brown, Allison Muldoon, Michael Trejo, Benjamin A Katchman, Michael J Donovan, Paul C Pagano
Author Information
Shahram Tahvilian: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Joshua D Kuban: Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
David F Yankelevitz: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Daniel Leventon: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Claudia I Henschke: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jeffrey Zhu: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lara Baden: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Rowena Yip: Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Fred R Hirsch: Icahn School of Medicine, Center for Thoracic Oncology, Tisch Cancer Institute at Mount Sinai, New York, NY, USA.
Rebecca Reed: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Ashley Brown: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Allison Muldoon: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Michael Trejo: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Benjamin A Katchman: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Michael J Donovan: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA.
Paul C Pagano: LungLife AI, Inc, 2545 W. Hillcrest Drive, Suite 140, Thousand Oaks, CA, USA. ppagano@lunglifeai.com.
PURPOSE: Computed tomography is the standard method by which pulmonary nodules are detected. Greater than 40% of pulmonary biopsies are not lung cancer and therefore not necessary, suggesting that improved diagnostic tools are needed. The LungLB™ blood test was developed to aid the clinical assessment of indeterminate nodules suspicious for lung cancer. LungLB™ identifies circulating genetically abnormal cells (CGACs) that are present early in lung cancer pathogenesis. METHODS: LungLB™ is a 4-color fluorescence in-situ hybridization assay for detecting CGACs from peripheral blood. A prospective correlational study was performed on 151 participants scheduled for a pulmonary nodule biopsy. Mann-Whitney, Fisher's Exact and Chi-Square tests were used to assess participant demographics and correlation of LungLB™ with biopsy results, and sensitivity and specificity were also evaluated. RESULTS: Participants from Mount Sinai Hospital (n = 83) and MD Anderson (n = 68), scheduled for a pulmonary biopsy were enrolled to have a LungLB™ test. Additional clinical variables including smoking history, previous cancer, lesion size, and nodule appearance were also collected. LungLB™ achieved 77% sensitivity and 72% specificity with an AUC of 0.78 for predicting lung cancer in the associated needle biopsy. Multivariate analysis found that clinical and radiological factors commonly used in malignancy prediction models did not impact the test performance. High test performance was observed across all participant characteristics, including clinical categories where other tests perform poorly (Mayo Clinic Model, AUC = 0.52). CONCLUSION: Early clinical performance of the LungLB™ test supports a role in the discrimination of benign from malignant pulmonary nodules. Extended studies are underway.
