Columbia University’s new Cancer Biostatistics program will serve as a hub for investigators with expertise in biostatistics and bioinformatics, aiming to advance cancer research through development of innovative, comprehensive data analytical methods and tools. Directed by Jianhua Hu, PhD, the group emphasizes cancer-related biostatistics curriculum, practice, and research.
“With a plethora of novel targeted therapies in cancer, biostatistics can help researchers more effectively and adaptively design clinical trials for testing new treatments,” says Dr. Hu, who joined Columbia University’s Herbert Irving Comprehensive Cancer Center (HICCC)
Dr. Hu came to Columbia from MD Anderson Cancer Center at the University of Texas where she was on the faculty in the Department of Biostatistics. At Columbia University Irving Medical Center (CUIMC), Dr. Hu is professor of biostatistics with appointments at the Mailman School of Public Health and in the Department of Medicine
The new Cancer Biostatistics program focuses on providing a rigorous academic and research program that bridges medical and analytical methods with curriculum. Members of the new program are collaborating with HICCC researchers on various cancer-related basic, translational, and clinical projects. The primary goal is to foster scientific rigor and research quality by providing statistical support to various research projects and collaborating on development of innovative analytical methods that can efficiently and properly address new challenges presented by the deluge of data in cancer research.
Biostatistics plays a significant role in cancer research and discovery. Particularly, entering the era of data science, various types of ‘omics” data, including genomics, transcriptomics, proteomics, and electronic health record data, emerge to provide unprecedented opportunities to explore molecular processes behind cancer formation and progression at genomic, transcriptomic, and proteomic levels simultaneously. Deciphering information gleaned from these data-rich sources, explains Hu, provides an opportunity to improve fundamental knowledge of biological mechanisms behind the disease’s development and aid in the discovery of new therapies.
“These unconventional biomedical problems and unique datasets present engaging new problems to the biostatistician, as many classical statistical techniques are not applicable,” says Dr. Hu. “It is critical for cancer biostatisticians to carefully adopt and develop innovative statistical methods for such challenging problems, and thus provide appropriate analytical tools to help achieve scientifically meaningful discoveries in cancer.”
The Cancer Biostatistics program at Columbia also will engage in training and mentoring the next generation of biostatisticians through collaborative research opportunities, and involving them in the development of advanced statistical methodology.
For the program, Dr. Hu has been actively recruiting staff- and faculty-level members, postdoctoral fellows, and graduate students. To date, there are three full-time MS- and PhD- level biostatisticians in addition to several faculty members of biostatistics who have contributed to the program. Her group has been helping HICCC researchers on various research projects, from clinical trial design, protocol development, grant application, data analysis, to manuscript preparation.
Dr. Hu’s research aims to improve disease diagnosis, prognosis, and treatment by developing methods to addresses unconventional data analysis challenges in biomedical studies. She analyzes high-dimensional genomics/proteomics, imaging, and longitudinal data, models disease heterogeneity, and develops adaptive designs to achieve personalized treatments. As the PI, she has recently obtained a R01 from NIH to develop new statistical methods for longitudinal and high-dimensional microbiome data to explore the association between microbiome and chemotherapy infection in AML patients. At Columbia, Dr. Hu is also directing the Biostatistics and Bioinformatics Core for the Pancreas SPORE and Biostatistics Core for the Brain Tumor SPORE, applications of which were submitted in September 2019.