Program Official

Principal Investigator

Marc Elliott
Lenburg
Awardee Organization

Boston University Medical Campus
United States

Fiscal Year
2021
Activity Code
R01
Early Stage Investigator Grants (ESI)
Not Applicable
Project End Date

Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules

There is an urgent, unmet clinical need to develop non-invasive approaches for distinguishing benign vs. malignant indeterminate pulmonary nodules (IPN) identified on CT chest. We propose to develop and validate integrated clinical, molecular and imaging-based diagnostic models of lung cancer in smokers with nodules 625 mm who are at elevated risk of lung cancer as a result of meeting eligibility criteria for screening, and whose nodules may have been screen-detected or incidentally-detected in routine clinical practice. This nodule size range represents an intermediate risk for disease for which there is the greatest clinical uncertainty in terms of diagnostic management. The investigators at BU have developed and validated a gene expression biomarker, recently launched commercially as a CLIA assay (PerceptaTM) measured in cytologically-normal mainstem bronchus epithelium with high sensitivity and high negative predictive value (NPV) for detecting lung cancer among smokers undergoing bronchoscopy for suspect lung cancer. They have recently extended these cancer-specific molecular alterations within the “field of injury” to develop and validate a similar biomarker in less invasively collected nasal epithelium. Additionally, investigators at UCLA have identified both qualitative and quantitative imaging features that inform diagnostic risk in both screen- and incidentally-detected nodules in older smokers. In Aim 1 of this proposal, we will refine qualitative and quantitative imaging biomarkers, confirm their reproducibility, and determine their contribution to diagnostic models in individuals with nodules 625 mm from the CT arm of the National Lung Screening Trial (NLST). Aim 2 will determine whether bronchial gene expression biomarkers originally validated in high risk cohorts perform equally well in the specific context of patients with IPNs 6-25 mm undergoing bronchoscopy as part of the Detection of Early Lung Cancer Among Military Personnel (DECAMP) consortium, as well as integrate this biomarker with imaging-based markers from Aim 1. Given that not all IPN patients undergo bronchoscopy, Aim 2 will also validate a recently developed nasal gene-expression biomarker in this same cohort and construct models that integrate clinical, imaging, and molecular biomarkers. In Aim 3, the integrated clinical, nasal gene-expression and imaging-based biomarker will then be validated prospectively in multiple cohorts with screen- and incidentally-detected IPNs who are undergoing CT surveillance or biopsy. Our working hypothesis is that diagnostic models that integrate orthogonal feature sets of molecular biomarkers, clinical variables, and imaging features will provide the highest discrimination between benign and malignant IPNs in the 6-25 mm size range in which diagnostic uncertainty is greatest. Given the increasingly widespread implementation of lung cancer screening and dramatically increased numbers of IPNs, we anticipate that sensitive biomarkers with a high NPV would enable physicians to avoid unnecessary procedures in patients with benign disease of the lung, avoiding their associated medical risks and economic costs.

Publications

  • Billatos E, Vick JL, Lenburg ME, Spira AE. The Airway Transcriptome as a Biomarker for Early Lung Cancer Detection. Clinical cancer research : an official journal of the American Association for Cancer Research. 2018 Jul 1;24(13):2984-2992. Epub 2018 Feb 20. PMID: 29463557
  • Menon AA, Lee M, Ke X, Putman RK, Hino T, Rose JA, Duan F, Ash SY, Cho MH, O'Connor GT, Dupuis J, Hatabu H, Lenburg ME, Billatos ES, Hunninghake GM, DECAMP Investigators, Spira A, Moses E, Beane J, Campbell J, Cunningham J, Liu G, Liu H, Zhang S, Zhang J, Shi X, Merenstein C, Zhao Y, Aberle D, Schnall M, Apgar C, Mahon I, Dymond L, Bauza J, Gevo S, Gastonis C, Marquez H, Elashoff D, Wistuba I, Kadara H, Fujimoto J, Dalgard C, Wilkerson M, Aberle D, Washko G, Kinsey CM, Fine D, Goldstein R, LaCerda K, Battaile J, Kroll M, Keith B, Jackson M, Dubinett S, Lee G, Aryanfar B, Corona R, Vachani A, Soloman S, Atwood C, Owens G, Edvardsson H, Massion P, Helton T, Reid M, Kuzniewski C, Carmichael J, LaPerriere H, ScottParrish J, White L, Kaur A, Browning R Jr, Nelissery M, Akanni F, Rojas L. Bronchial epithelial gene expression and interstitial lung abnormalities. Respiratory research. 2023 Oct 10;24(1):245. PMID: 37817229
  • Hsu W, Sohn JH. Using Radiomics for Risk Stratification: Where We Need to Go. Radiology. 2022 Feb;302(2):435-437. Epub 2021 Nov 2. PMID: 34726541
  • Shen S, Han SX, Aberle DR, Bui AA, Hsu W. An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification. Expert systems with applications. 2019 Aug 15;128:84-95. Epub 2019 Jan 18. PMID: 31296975
  • Lin Y, Fu M, Ding R, Inoue K, Jeon CY, Hsu W, Aberle DR, Prosper AE. Patient Adherence to Lung CT Screening Reporting & Data System-Recommended Screening Intervals in the United States: A Systematic Review and Meta-Analysis. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer. 2022 Jan;17(1):38-55. Epub 2021 Oct 6. PMID: 34624528
  • Winter A, Aberle DR, Hsu W. External validation and recalibration of the Brock model to predict probability of cancer in pulmonary nodules using NLST data. Thorax. 2019 Jun;74(6):551-563. Epub 2019 Mar 21. PMID: 30898897
  • Lin Y, Wei L, Han SX, Aberle DR, Hsu W. EDICNet: An end-to-end detection and interpretable malignancy classification network for pulmonary nodules in computed tomography. Proceedings of SPIE--the International Society for Optical Engineering. 2020 Feb;11314. Epub 2020 Mar 16. PMID: 32606487
  • Smedley NF, Aberle DR, Hsu W. Using deep neural networks and interpretability methods to identify gene expression patterns that predict radiomic features and histology in non-small cell lung cancer. Journal of medical imaging (Bellingham, Wash.). 2021 May;8(3):031906. Epub 2021 May 8. PMID: 33977113
  • Billatos E, Faiz A, Gesthalter Y, LeClerc A, Alekseyev YO, Xiao X, Liu G, Ten Hacken NHT, Heijink IH, Timens W, Brandsma CA, Postma DS, van den Berge M, Spira A, Lenburg ME. Impact of acute exposure to cigarette smoke on airway gene expression. Physiological genomics. 2018 Sep 1;50(9):705-713. Epub 2018 Jun 22. PMID: 29932825
  • Beane J, Campbell JD, Lel J, Vick J, Spira A. Genomic approaches to accelerate cancer interception. The Lancet. Oncology. 2017 Aug;18(8):e494-e502. Epub 2017 Jul 26. PMID: 28759388
  • Lin Y, Fu M, Inoue K, Jeon CY, Hsu W. Response to Letter to the Editor. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer. 2022 Mar;17(3):e27-e28. PMID: 35216733
  • Billatos E, Ash SY, Duan F, Xu K, Romanoff J, Marques H, Moses E, Han MK, Regan EA, Bowler RP, Mason SE, Doyle TJ, San José Estépar R, Rosas IO, Ross JC, Xiao X, Liu H, Liu G, Sukumar G, Wilkerson M, Dalgard C, Stevenson C, Whitney D, Aberle D, Spira A, San José Estépar R, Lenburg ME, Washko GR, DECAMP and COPDGene Investigators. Distinguishing Smoking-Related Lung Disease Phenotypes Via Imaging and Molecular Features. Chest. 2021 Feb;159(2):549-563. Epub 2020 Sep 16. PMID: 32946850
  • Lin Y, Fu M, Inoue K, Jeon CY, Prosper AE. Response to Letter to the Editor. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer. 2022 Apr;17(4):e47-e48. PMID: 35307109
  • Ostrin EJ, Sidransky D, Spira A, Hanash SM. Biomarkers for Lung Cancer Screening and Detection. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2020 Dec;29(12):2411-2415. Epub 2020 Oct 22. PMID: 33093160
  • Paez R, Kammer MN, Tanner NT, Shojaee S, Heideman BE, Peikert T, Balbach ML, Iams WT, Ning B, Lenburg ME, Mallow C, Yarmus L, Fong KM, Deppen S, Grogan EL, Maldonado F. Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules. Chest. 2023 Oct;164(4):1028-1041. Epub 2023 May 25. PMID: 37244587
  • Stackpole ML, Zeng W, Li S, Liu CC, Zhou Y, He S, Yeh A, Wang Z, Sun F, Li Q, Yuan Z, Yildirim A, Chen PJ, Winograd P, Tran B, Lee YT, Li PS, Noor Z, Yokomizo M, Ahuja P, Zhu Y, Tseng HR, Tomlinson JS, Garon E, French S, Magyar CE, Dry S, Lajonchere C, Geschwind D, Choi G, Saab S, Alber F, Wong WH, Dubinett SM, Aberle DR, Agopian V, Han SB, Ni X, Li W, Zhou XJ. Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancer. Nature communications. 2022 Sep 29;13(1):5566. PMID: 36175411
  • Petousis P, Winter A, Speier W, Aberle DR, Hsu W, Bui AAT. Using Sequential Decision Making to Improve Lung Cancer Screening Performance. IEEE access : practical innovations, open solutions. 2019;7:119403-119419. Epub 2019 Aug 16. PMID: 32754420
  • Xu K, Diaz AA, Duan F, Lee M, Xiao X, Liu H, Liu G, Cho MH, Gower AC, Alekseyev YO, Spira A, Aberle DR, Washko GR, Billatos E, Lenburg ME, DECAMP investigators. Bronchial gene expression alterations associated with radiological bronchiectasis. The European respiratory journal. 2023 Jan 27;61. (1). Print 2023 Jan. PMID: 36229050
  • Vachani A, Sequist LV, Spira A. AJRCCM: 100-Year Anniversary. The Shifting Landscape for Lung Cancer: Past, Present, and Future. American journal of respiratory and critical care medicine. 2017 May 1;195(9):1150-1160. PMID: 28459327