Cancer cell evolution and drug discovery
CAMBRIDGE, Mass.—The heterogeneity of cancer genetics has been a growing area of concern in oncology. The mounting research in this area of cancer research has led to greater understanding of why not all drugs work for all people, even when they have what seems to be the same kind of cancer. It has informed the growing field of precision medicine and prompted work on companion diagnostics to help get the right drugs to the right cancer victims based on genetic markers.
This variation in genetics in cancers of all kinds also has led to some new insights and findings at the Broad Institute of MIT and Harvard, which notes, via an article on their website by Tom Ulrich, “Long thought to be genetically stable and identical, cancer cell lines harbor significant levels of genetic variation, which may help explain why it can be hard to reproduce findings in cell line-based research.”
As the Broad Institute points out, cell lines form the backbone of cancer research, from basic research into genetics to drug discovery. The cells collected from patients’ tumor samples are cultured to grow indefinitely in the laboratory, and researchers have relied on those lines remaining stable over time.
As the Broad article stresses, however, “[While] scientists have thought that individual cell lines remain genetically uniform even as they continue to grow and divide, they can in fact evolve in ways that dramatically change their responses to drugs ... This continuing evolution of cells within cell lines—potentially driven by the laboratory conditions in which they are grown—may help explain why different studies that use the same cell lines often have conflicting results.” The Broad researchers published these and related finding in a recent Nature article entitled “Genetic and transcriptional evolution alters cancer cell line drug response.”
As the abstract of the Nature paper relates: “Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others.”
As the Broad researchers advise, this means that scientists need to employ an extra level of care to help ensure that cell line-based models of cancer accurately reflect the tumor they are studying. As part of the means to this end, the research team released not just their research findings, but also an online tool called Cell STRAINER that is intended to help researchers benchmark their models.
“The main message here is not that cell lines and culture-based models are bad. Rather, you should know your model, and understand its properties and limitations,” said Broad core institute member and Cancer Program director Todd Golub, who was the study’s co-senior author, along with Broad associate member and Dana-Farber Cancer Institute (DFCI) adult neuro-oncologist Rameen Beroukhim. “Knowing requires a level of genetic and genomic characterization beyond what we usually think about. Skipping this sort of careful characterization is not an option.”
The lack of any systematic effort thus far to measure how the cells in cancer cell lines change genetically over time and the extent to which it occurs—and whether those changes affect drug responses—is a problem that needs to be addressed, the researchers say.
“You can find many examples in the literature pointing out inconsistencies in drug sensitivity data from cell line experiments,” noted Uri Ben-David, the study’s first author and a postdoctoral fellow in the Golub lab. “We wanted to look for signs of evolution and connect the dots between changes within lines and those inconsistencies.”
The researcher’s first began to suspect that these cell lines evolve when they reanalyzed sequencing data from 106 lines housed in two large collections: the Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) and the Sanger Institute’s Genomics of Drug Sensitivity in Cancer. These lines should be genetically identical in both collections, but the team found high levels of variability. For instance, 19 percent of the genetic mutations the team found were present in only one collection or the other. And thus began their work to run deep molecular analyses on 27 strains of the estrogen receptor-positive breast cancer line MCF-7, as noted in the Nature abstract quote above, as well as 23 strains of the lung cancer line A549.
Per the Broad article by Ulrich online, “The analysis included whole-genome DNA sequencing, targeted DNA sequencing of nearly 450 genes commonly mutated in cancer and bulk and single-cell RNA-sequencing. Each of the strains represented a batch of cells from the line with a distinct history (e.g., different kinds of lab manipulation, different length of time in culture, different original source).
“Their data revealed striking genomic differences between strains, ranging from single base pair mutations to large-scale changes in genome structure (e.g., losses of entire chromosome arms) to major changes in gene expression—all indicating that the cells lines were neither as stable nor as identical as researchers thought. These genetic and expression differences also affected the strains’ growth rates, cell size and shape, and other traits.”
By conducting experiments under varying laboratory conditions, the team found that something as simple as altering the nutrient media might give certain cells in a line a growth advantage over others, driving evolution in a genetic distinct population within the cells that are being cultivated. Also, according to the Broad article, “the team also found that the progeny of isolated single cells could spontaneously acquire new mutations, showing that new, genetically diverse populations of cells could arise within a cell line strain from individually isolated ones.”
The findings complement some other research led by Ben-David, Beroukhim and Golub and published in 2017 in Nature Genetics that examined patient-derived xenograft (PDX) models. That work revealed that over time, human cancer cells in PDX models lose characteristic genetic features seen in patients and gain new features not encountered in humans—this shift also correlated with changes in the models’ drug sensitivities.
“Technology has given us new perspectives on how cancer cells evolve in patients, and we need to apply that same perspective to the models we use to study cancer in the laboratory,” commented Broad institute scientist and Cancer Program associate director Jesse Boehm, who leads efforts to generate cell models from patient tumors and was not involved in the study. “We’ve learned that tumors aren’t static in patients. Now, we’ve learned that the laboratory models we use to study cancer are also subject to evolutionary pressures. These findings tell us as a field that we need to adopt more nuanced view about cell models and adjust the practices we use to generate, propagate and employ such models accordingly.”
To sum it up in the authors’ words, the Nature paper concludes: “We found that changes in clonal composition underlie much of the observed variability in cell line behavior. Such clonal composition changes follow selection by particular conditions (for example, growth medium) or by genetic manipulations associated with a population bottleneck. The genetic distance between cell line strains was strongly correlated with their gene expression distance and with their drug-response distance. Cell line diversification can therefore be estimated using inexpensive profiling methods ... To facilitate routine assessment of cell line diversification, we have created the Cell STRAINER (strain instability profiler) portal (https://cellstrainer.broadinstitute.org), where users can upload cell line genomic data and measure their strain’s genetic distance from a reference.
“Variation within cancer cell lines can also be useful in at least two ways. First, deeper characterization (for example, by single-cell sequencing) of the heterogeneity within cultures of common cell lines could enable the study of cooperative and competitive interactions between cancer cell populations and mechanisms of pre-existing drug resistance. Second, owing to their matched genetic background, naturally occurring ‘isogenic-like’ strains could help to uncover the association between molecular features and phenotypes such as drug response.
“We conclude that cancer cell lines remain a powerful tool for cancer research, but their genomic evolution leads to a high degree of variation across cell line strains, which must be considered in experimental design and data interpretation.”