For cancer researchers, understanding the intricacies of a cell is essential to treating patients and developing new therapies. Often this understanding is found through painstaking examination of a cell’s surface markers, but a study published yesterday by the Fred Hutchinson Cancer Research Center indicates there may be a more effective and time-efficient way to profile patient cells.
The study examined the technology of 10x Genomics, a Bay area biotechnology company, whose platform was used to extract genetic data from blood samples from patients with acute myeloid leukemia.
The platform allows scientists to examine gene expression data from cells on an individual level, and gather data from a huge collection of cells to examine trends and patterns across the entire blood sample.
A single cell from a patient sample is suspended in an oil droplet along with a gel bead in emulsion. A biological reaction between the bead and the cell transforms the cell’s genetic information into a new form that can be read by sequencing machines, allowing researchers to gather data on cells’ gene expressions more quickly and efficiently than current processes allow.
The data Fred Hutch researchers gathered allowed them to identify which patients had a particular AML cell known as an erythroid, which is an important indicator of whether they will need a stem cell transplant.
“We were able to discover cells’ identities without looking at them under a microscope or knowing anything about the patterns of proteins on their surfaces,” said Dr. Jason Bielas, the paper’s senior author and a researcher in Fred Hutch’s Human Biology and Public Health Sciences divisions, in a press release on the study. “That can be particularly helpful in finding leukemic cells from a particular lineage for which there are few surface markers.”
The process can also be helpful in examining cancer cells because it allows cancer cells and healthy cells to be profiled in the same sample, unlike other methods.
Fred Hutch researcher Dr. Jerald Radich, who specializes in leukemia research and co-authored the paper, said in the release that he plans to use the technology in his lab to learn more about the cellular interactions that drive cancer development and relapse after treatment.
“This is one of the ways you can understand more about what’s really going on [in the cancer ecosystem] by deconstructing the bulk population, seeing what cells are really there, how do they change over time, how does their function change, and does that make any difference?” he said in the release. “Once you start understanding what the ecosystem does, and what it takes to keep the cancer at bay, then you can start manipulating that, potentially therapeutically.”