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The Christiani Lab studies the interplay between environmental exposures, genetics, and disease in human populations, in the research area known as molecular epidemiology. 

Phone 617-432-1641
Location

651 Huntington Avenue
FXB 109–113
Boston, MA 02115

The Boston Lung Cancer Study (BLCS)

The Boston Lung Cancer Study (BLCS) is a cancer epidemiology cohort (CEC) of over 12,000 lung cancer cases enrolled at Massachusetts General Hospital (MGH) and Dana-Farber Cancer Institute (DFCI) since 1992. It has been supported by the National Cancer Institute (NCI). We have collected detailed demographic, smoking, occupational, and dietary information, in addition to pathology, imaging, treatments, oncogenic (somatic driver) mutation status, and biosamples. The BLCS biorepository includes serum, white blood cells, DNA, and ~2,000 tumor and surrounding tissues. This cohort is a member of the NCI-supported International Lung Cancer Consortium (ILCCO) and the Transdisciplinary Research in Cancer of the Lung on Lung Cancer (TRICL), and is one of the few lung CECs contributing data on survival status, with oncogenic mutation data and tissue available. The accumulative follow-up rate for the BLCS cohort has been high, approximately 95%, with nearly complete ascertainment of deaths using the National Death Index and other resources. MGH and DFCI are leaders in systematically genotyping patients for oncogenic mutations. 

The BLCS is supported by NCI Award # 5U01CA209414 

About the BLCS

  • Retrieve pulmonary function and imaging for existing lung cases and prospectively identify new cases for COPD phenotyping. 
  • Conduct a pilot study of radiomics for lung cancer that will focus on building a bioinformatics pipeline to facilitate radiomic analysis in relation to outcomes and genetic data. 
  • Create a genome-wide/targeted methylation database for developing prognostic/predictive biomarkers of lunch cancer 
  • Apply Artificial Intelligence to images for clinical prediction 
  • Apply Natural Language Processing to electronic medical records/data retrieval 
  • Develop and apply novel methods of survival analysis 
  • Recruit new patients and continue follow-up of the BLCS cohort to update data on smoking, diet, physical activity, medication use, weight, other exposures, overall mortality, and other outcomes 
  • Continue to collect and update oncogenic (somatic driver) mutations for the BLCS cohort using existing clinical screening programs supported by existing DF/HCC mechanisms 
  • Maintain data management and quality control systems to maximize the value of the BLCS data for scientific analyses conducted by internal and external investigators 
  • Continue the identification, tracking, and ongoing utilization of FFPE tissue blocks for characterization. 
  • Expand a prospective dimension of the existing cohort. Prospective data and biosamples will be collected at regular follow-up of lung cancer patients, which will be valuable for studies in relation to treatment efficacy, toxicity, and survival, as well as ongoing characterization of relevant biomarkers. 

Requests for data sharing are submitted to the Cancer Epidemiology Cohorts (CEC) PI Dr. David Christiani. Information required for data requests including specific goals, planned analyses, data access, and a statement acknowledging that the data shall be used only for non-proprietary research purposes.

Resource including human tissue sharing request will be reviewed by the Steering Committee. The object of these reviews is to speed exchange of material and information. Requests from CEC investigators will be given high priority, followed by other investigators at Harvard or the DF/HCC and the cancer research community at large.

Please fill out this form to request data, or email David Christiani for more information.

BLCS Team

Co-Investigators

Hugo Aerts

Hugo Aerts, PhD, is Assistant Professor of Radiation Oncology at HMS and DFCI/BWH and Director, Computational Imaging and Bioinformatics Laboratory, DFCI. He is a pioneer in the area of Radiomics, combining computational biology techniques with image analysis to improve precision in the use on radiation in lung cancer.

David Barbie

David A. Barbie, MD, is an Associate Professor of Medicine at Harvard Medical School and the Lowe Center for Thoracic Oncology, and Associate Director of the Robert and Renée Belfer Center for Applied Cancer Science at the Dana-Farber Cancer Institute. He obtained an AB from Harvard College in 1997 and MD from Harvard Medical School in 2002. He is  a key opinion leader in the emerging field of innate antitumor immunity. He promotes a collaborative and open research environment with a diverse group of clinicians and scientists including biologists, biochemists, immunologists, engineers, pathologists and oncologists from around the world. 

Hiroto Hatabu, MD, PhD, is Professor of Radiology, BWH and HMS, Medical Director of Center for Pulmonary functional imaging (CPFI) and Clinical Director of the MRI Program at BWH. Dr. Hatabu is also a practicing chest radiologist and has significant research experience in lung cancer imaging for diagnosis and treatment response. In the course of the development of Center for Pulmonary Functional Imaging and Image-based Phenotyping, Dr. Hatabu has instituted the system infrastructure with PC-based workstations to handle 10,000 to 30,000 CT scans with 20 TB hard disc memory. Collaborating with Drs. Christiani, Johnson, Mak, and Nishino, Dr. Hatabu will contribute expertise toward the continued development of infrastructure to collect and analyze imaging data in the BLCS cohort comprising more than 10,000 cases.

John Iafrate

John Iafrate, MD, PhD, is the director of the Center for Integrated Diagnostics, a clinical laboratory for molecular diagnostics at the MGH. He oversees the Translational Research Laboratory (TRL), a shared effort of the Pathology Department and Mass General Cancer Center. The TRL provides rapid personalized genomic testing to help inform cancer treatment decisions for patients. Dr. Iafrate received his MD and PhD from the State University of New York at Stony Brook in 2000, and was trained in anatomic and molecular genetic pathology at the BWH. He joined the MGH staff in 2005. His post-doctoral work involved the discovery and description of a novel source of human genetic diversity, CNV. He established a cancer diagnostics lab focusing on genetic fingerprints that help guide novel, targeted therapies. His laboratory launched SNaPshot several years ago, an assay that tests over 100 of the most common mutations in tumors. His research is focused on lung and brain tumors, and he has been closely involved in the clinical development of crizotinib and companion diagnostics in ALK-positive and ROS1-positive lung cancers.

Michael Lanuti, MD, is a board certified Thoracic Surgeon with special interest in lung cancer research, new techniques for lung cancer staging, and minimally invasive lung surgery.

Yi Li, PhD, MS, is a Professor of Biostatistics at the University of Michigan. His expertise is in developing new methods for survival analysis. His current research interests are survival analysis, longitudinal and correlated data analysis, measurement error problems, spatial models and clinical trial designs. His group is developing methodologies for analyzing large-scale and high-dimensional datasets, with direct applications in observational studies as well in genetics/genomics.

Xihong Lin

Dr. Xihong Lin is the Henry Pickering Walcott Professor of Biostatistics, Chair, Department of Biostatistics, HSPH. Dr. Lin is a leading expert in statistical genetics and genomics and statistical methods for epidemiological data and massive data. Dr. Lin’s research interests lie in the development and application of statistical and computational methods for 1) analysis of massive genetic and genomic data in population and medical science; and 2) analysis of complex and big data in observational and clinical studies, especially in cancer research. She is widely recognized for her contributions in these areas in both (bio)statistical and genetic epidemiology communities, particularly for her work in longitudinal data analysis, kernel machine methods, and statistical genetics and genomics. She has been closely collaborating with epidemiologists, clinical scientists and biologists in lung, breast, prostate, and NPC cancers, and has made several important discoveries in cancer etiology, biology, and medicine. Dr. Lin has published over 230 papers, many in leading statistics, genetics, and health science journals. She is the senior author on many methods papers and the leading statistician on many substantive papers.

Raymond Mak, MD, is Assistant Professor of Radiation Oncology, BWH/DFCI/HMS. Dr. Mak is a radiation oncologist specializing in the treatment of patients with lung cancer, and will provide expertise in designing clinical outcomes research in early stage (I-III) lung cancer, utilizing nested cohorts within the BLCS cohort, and collected tumor genotype/phenotype data. He will also provide experience in re-purposing genomic, imaging and clinical datasets from within the BLCS cohort to study treatment-related outcomes and toxicity in early-stage lung cancer. He will oversee patient accrual, clinical data collection, and bio-specimen collection from this site. He will collaborate with Drs. Aerts, Hatabu, and Nishino to generate an imaging database and quantitative imaging analysis pipeline.

Lynette Sholl, MD, is an Assistant Professor of Pathology at HMS/DFCI/BWH. Her research focuses on identifying pathologic, immunohistochemical, and genetic markers that will improve the classification of lung cancer, provide predictive information regarding therapy, and provide more precise prognostic information. With the advent of high-throughput next-generation sequencing technologies, she is engaged in translation of novel observations surrounding tumors.

Henning Willers, MD, is an Associate Professor of Radiation Oncology at HMS and MGH. He has researched in radiation biology since 1991 and as a laboratory-based PI since 2005. His basic and translational research activities are directed at furthering our understanding of how NSCLCs respond to radiation and radiosensitizing drugs. Specifically, we seek to identify the signaling pathways that contribute to the radioresistance of KRAS-mutant lung adenocarcinoma which is an emerging clinical problem.

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