Department of Biostatistics and Computational Biology
Giovanni Parmigiani, PhD, Chair Developing and applying quantitative methods for cancer
research
Today, quantitative ideas are part of the foundations of cancer
research, because of the variation in etiology and response to
therapy and the prominent role of data-intensive technologies in
high throughput biology, imaging, and elsewhere. In parallel,
computational ideas are entering clinical activities: probabilistic
risk assessment algorithms and genomic approaches to guiding
treatment are just two examples. Increasingly, oncologists use
tools and interpret research results that rely heavily on complex
statistical and computational approaches.
To meet these challenges, the Department's faculty conduct basic
research in statistical and computational methods for clinical and
translational research, population-based studies, and cancer
biology. They also develop software for research and clinical
applications, and perform high-throughput genomic experiments
guided by their computational insights. All members collaborate
extensively in interdisciplinary research, providing expert advice
on experimental design, data collection, data storage, data
integration, as well as data analysis of clinical, laboratory, and
population-based studies.
Research team
Currently, the Department is comprised of 32 faculty, 3 research
associates, 33 research fellows, 22 MA biostatisticians and 16
bioinformaticians. In addition, there are at least 31 graduate
students working with faculty members at any time. During 2010,
Department members authored or coauthored more than 150
peer-reviewed publications.
National role in clinical trials and outcomes studies
Reflecting their national prominence in supporting multicenter
clinical trials, members of the Department have supported the
Eastern Cooperative Oncology Group (ECOG), a consortium with more
than 350 hospitals and treatment centers throughout the United
States, for many years. Funded by the National Cancer Institute to
conduct multicenter clinical trials in adult malignancies, ECOG
maintains a database of more than 110,000 cancer cases and is
conducting active follow-up on more than 20,000 patients who have
participated in clinical trials. The Statistical Center of ECOG is
currently led by Robert Gray, PhD.
The International Breast Cancer Study Group (IBCSG) is a network
of institutions in Europe, South America, Australia, New Zealand,
Asia, and South Africa. Since 1977, IBCSG has conducted large,
randomized Phase III clinical trials evaluating the timing and
duration of chemotherapy and the role of endocrine therapy as
adjuvant treatment for breast cancer. IBCSG is considered to be a
leader in the field of tailored treatment approaches for specific
subpopulations of patients with breast cancer. For many years, the
Statistical Center was led by Richard Gelber, PhD; it is now directed by Department member Meredith Regan, ScD.
Members of the Department also work closely with the AIDS
Clinical Trial Group, and are coordinating statistics for studies
of pediatric AIDS as well as immunologic markers of human
immunodeficiency virus (HIV) infection.
The Department is similarly committed to observational studies
of outcomes in cancer. For example, the Cancer Care Outcomes
Research and Surveillance Consortium, or CanCORS, is a prospective
follow-up study of 10,000 patients newly diagnosed with colorectal
or lung cancer. The Statistical Coordinating Center for CanCORS is
led by David Harrington, PhD, former department chair.
In all these areas, faculty pursue an active agenda of
methodological investigations. For example Yi Li, PhD, is using
data from ongoing trials to develop statistical tools for
identifying patients who will respond to specific chemotherapy
treatments. In 2006, the Department recruited Armin Schwartzman, PhD, an expert in multivariate and
high-dimensional data analysis, who is rapidly developing a
cutting-edge research program in signal and image analyses as they
apply to cancer.
Dana-Farber/Harvard Cancer Center
Faculty and staff statisticians play central roles in the
development of all clinical research protocols at
Dana-Farber/Harvard Cancer Center (DF/HCC), the largest
NCI-designated Comprehensive Cancer Center in the country. Faculty
serve as members of DF/HCC's Scientific Review Committee as well as
the Institutional Review Board.
DF/HCC's Biostatistics Core is located at Dana-Farber and is
directed by faculty member Paul Catalano, ScD. The core provides consultation and
assistance to Cancer Center members in all DF/HCC Research
Programs.
Research and collaboration in Computational Biology
In 2008, John Quackenbush, PhD, established the Center for Cancer
Computational Biology (CCCB) at Dana-Farber. This research center
provides broad-based support for the analysis and interpretation of
genomic and other large-scale data. In doing so, CCCB furthers
basic, clinical, and translational research by providing new ways
of understanding human cancer. The Center is focused on developing
new methods for improving the analysis and interpretation of
genomic data through the integration of diverse data types. As
such, the Center provides Dana-Farber investigators with
state-of-the-art assistance in the collection, management,
analysis, and interpretation of large-scale data. It also provides
software, services, and training in order to assist investigators
in advancing their personal research.
The faculty also pursue an active program of independent
research in the computational biology of cancer. For example,
Quackenbush created an integrated clinical and research data portal
that will serve as the basis for the personal genomics initiative
at the Institute, and created a new web-based resource, GeneSigDB,
that brings together more than 500 published genomic signatures. Guo-Cheng Yuan, PhD, developed a computational method, called
N-score, to predict the positions of nucleosomes in the genome. Cheng Li, PhD, continued expanding his own DChip, one of the
most widely used genomic analysis tools. Xiaole (Shirley) Liu, PhD, developed novel tools for exploring
the mechanisms of gene regulation, including the MACS algorithm for
analysis of ChIP-seq data. Lastly, Giovanni Parmigiani, PhD, who
joined the Department in 2009, continues his work on computational
approaches for identifying families at risk of inherited
susceptibility to cancer, which has yielded widely used algorithms
such as BRCAPRO, PancPRO, and MMRpro.
Teaching the next generation of biostatisticians and
computational biologists
The Department has a close partnership with the Department of
Biostatistics at Harvard School of Public Health, where the
majority of the faculty have primary academic appointments.
Department faculty are leaders of training grants and curriculum
development initiatives, direct research, and teach in the doctoral
program there, as well as the undergraduate degree program in
statistics at Harvard College.
Awards of note
Two department faculty members received significant awards in
the last year: Marvin Zelen, PhD, founding chair of the Department, received
the American Cancer Society's Medal of Honor, the highest honor
bestowed by the ACS in recognition of outstanding contributions to
cancer control in three categories; and Richard Gelber, PhD, was a co-recipient of the Brinker Award,
one of the most prestigious awards given for breast cancer research
and supported by Susan G. Komen for the Cure.