Speaker:  Cong Ma, PhD
Affiliation: University of Michigan Medical School
Position:  Assistant Professor of Computational Medicine and Bioinformatics
Host: Youn Kim, PhD, Gibson Lab

Date: Monday May 19th, 2025
Time: 4:00-5:00PM ET
Zoom: https://partners.zoom.us/j/82163676866
Meeting ID: 821 6367 6866

Abstract: A tumor is a heterogeneous mixture of cancerous cells and multiple types of normal cells. Decoding this heterogeneity and identifying the genomic events that drive cancer development are key to studying tumor evolution and progression. Spatially resolved transcriptomics (SRT) technologies sequence expressed RNAs across thousands of locations in a tumor slice; the resulting gene expression signatures reveal the localization of cancer and adjacent normal cell types forming the tumor microenvironment. However, gene expression signatures alone are insufficient to identify cancer clones – subpopulations of cancerous cells that share the same genetic lineage – or to reconstruct the evolution of these clones. In this talk, I will introduce our recently published method, CalicoST, and our on-going improvements. CalicoST simultaneously infers allele-specific copy number aberrations (CNAs) and the spatial distribution of cancer clones using SRT data from one or more tumor slices. CalicoST identifies important types of CNAs – including copy-neutral loss of heterozygosity (LOH) and mirrored subclonal copy number aberrations – that are invisible to existing approaches. From these CNAs, CalicoST infers a phylogeny describing the ancestral relationships between the clones and revealing the spatial evolution of the tumor. Although CalicoST achieves state-of-the-art accuracy in inferring allele-specific CNAs and cancer clones, the optimization problem it tackles is challenging and prone to falling into local optima. To address this, we evaluated the challenges in clone inference using idealized simulations and developed a method to infer potential missing cancer clones for each CalicoST inference result.

Research Links: https://www.nature.com/articles/s41592-024-02438-9

 Dr. Cong Ma is an assistant professor at the University of Michigan, having started this position last September. She earned her Ph.D. in computational biology from Carnegie Mellon University under the supervision of Dr. Carl Kingsford, and subsequently completed a postdoctoral fellowship at Princeton University in Dr. Ben Raphael’s group before joining the University of Michigan. Dr. Ma was awarded the prestigious Damon Runyon Quantitative Biology Fellowship, underscoring the significance of her work in developing computational methods to study spatial tumor evolution.

Click here to be added to our mail list.