Congratulations to Assistant Professor of Biostatistics Jeff Miller, who has received a Prevention and Early Detection for Emerging Researchers (PEER) Award from the Zhu Family Center for Global Cancer Prevention. The goal of this award is to provide funding for investigators who are interested in developing a career in early diagnosis and precision prevention that will increase equity of cancer outcomes across populations burdened by cancer disparity.
Dr. Miller’s research is on Transformational Methods for Early Cancer Detection Using Cell-Free DNA. Abstract below.
If detected early, many cancers can be successfully treated, leading to a high rate of survival. Unfortunately, cancer is often detected at late stages since current screening technologies have insufficient sensitivity and specificity at low tumor fractions. Cell-free DNA (cfDNA) sequencing presents an exciting possibility for highly accurate, non-invasive cancer screening. When cells die, they often release small fragments of their DNA into the bloodstream. Thus, when cancer is present, plasma from routine blood draws contains DNA from cancer cells. By performing genome sequencing on this plasma cfDNA, it is possible to non-invasively detect and analyze cancers. However, advanced statistical methods are needed to extract the signal from the noise. The fraction of tumor-derived cfDNA fragments is very small, on the order of 1/1000 or less for early stage cancers. The objective of this project is to develop a flexible suite of statistical methods for cancer detection and analysis using cfDNA sequencing data at low tumor fractions. (Aim1) Develop robust nonparametric Poisson regression framework, applied to mutational signatures. (Aim 2) Develop grammar-based methods for complex models of sequential data, applied to copy number alterations. (Aim 3) Develop integrated Bayesian framework for robust cancer detection from cfDNA sequencing.