Imagine discovering that a dear friend of yours is a con artist with a fabricated identity. Suddenly everything you knew about that person, all the experiences you’d shared over the years, the understandings you thought you’d gained – you couldn't trust any of it.
A similar drama plays out all too often in the world of cells, specifically in specialized populations of cells (“cell lines”) that are the workhorses of biological research. Scientists can spend their entire careers working with a single cell line, trusting that their cell lines have been correctly identified. Yet in about one out of every seven cases, that assumption turns out to be false.
The results can be devastating. At best, only a small population of cells and set of experiments must be discarded. At worst, it’s years of research and millions of dollars down the drain, significantly setting back any progress against diseases like cancer.
A Case of Mistaken Identity
One of the most infamous cases of misidentification was MDA-MB-435. A supposed model of metastatic breast cancer, this cell line was later discovered to be genetically identical to skin cancer. By the time this shocking revelation came to light, MDA-MB-435 had already been used in more than a thousand scientific publications. The ramifications of the mix-up stretched back through decades of research.
How does this happen? In most cases, the roots of such problems are simple mistakes. A single contamination occurs at some point in a scientist’s work, introducing a foreign cell into an otherwise pure cell culture. If that foreign cell can thrive in the cell culture environment and multiply faster than native cells, it can quickly replace the original cell line. And when those cells are shared with other labs – a common practice in the scientific community – that simple mistake escalates quickly.
The takeover of a cell line can easily slip under the radar unless specialized tests are used to verify cell identity. Unfortunately, few scientists see a need for testing as they trust their sources and verification takes time away from their primary research.
But we can’t afford to continue making these types of mistakes. We need new solutions. That’s why our research group has created a new framework for verifying the identity of cells.
What’s in a Name
To tackle the fundamental issue of mixed-up cells, we first had to deal with an even more basic concern: Language. Specifically, cell nomenclature, or the way cell lines are named.
Perhaps you’ve experienced similar issues with your own name. Different official records may list your name in slightly different ways: John vs. Jonathan, full middle name vs. middle initial, maiden name vs. married name, etc. A search for the wrong variation could make it seem that you don’t exist in the record at all.
Even minor variations in punctuation and spacing can yield vastly different search results – making it virtually impossible to fully crosscheck the identity of cells against existing databases.
The same is true with cell lines. In the absence of a standardized system, different groups of scientists have adopted their own names and conventions. The result is a lot of overlap (for example, LAN-1 (DSMZ, ACC655) and LA-N-1 (RIKEN, RCB0483)). Even minor variations in punctuation and spacing can yield vastly different search results – making it virtually impossible to fully crosscheck the identity of cells against existing databases.
To address this issue, we devised a system that gives unique and standardized names to each cell line, and we’ve already used it to sort through thousands of cancer cell lines. To encourage the establishment of a unified database, we’ve made this resource available to the entire scientific community.
Dusting for Prints
A critical component of the new vocabulary is genetic “fingerprinting.” Every cell line can be uniquely identified based on its genetic information. Using two important types of genetic fingerprints called short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs), we can confirm cell identity and detect almost any kind of contamination.
An additional important step to protecting the identity of cell lines is implementing a good tracking system. We built just such a system into our centralized cell repository, called gCELL. We track all cells, from racks in cell banks to vials in individual labs, with barcodes. Now if a contamination occurs, we can quickly assess the extent of the problem and stop it from spreading.
With these tools in place, we believe we’ve laid the foundation for a major shift in the culture of cell culture. Our hope is that over time, scientists from around the industry and academia will utilize and improve upon this system, adding more cell lines, creating a unified database to help eliminate cell-line confusion.
Read more about these important findings in our Nature publication, “Improving the culture of cell culture: A resource for cell line authentication, quality control, annotation and data integration.”