New high-throughput method greatly expands view of how mutations affect cells

There are millions of mutations and other genetic variants in cancer

Now, in a report published in Nature Biotechnology, a research team from the Broad Institute of MIT and Harvard has unveiled a large-scale, high-resolution method to simultaneously functionally Assessing a large number of protein-coding mutations can provide rich phenotypic information that can be used to study any genetic mutation in cancer or other diseases

"When you look at the genetic data of patient tumors, most of the cancer-related mutations are actually very rare, which means we know very little about the role of these mutations,

The new approach, called single-cell expression-based variant-impacting phenotyping (sc-eVIP), builds on Perturb-seq

By recording the expression profile of each disturbed cell using single-cell RNA sequencing, the team could both identify the mutation a given cell carries (based on the construct's unique barcode) and examine the broader impact of the mutation on the cell's overall expression state

"In a sense, we're using cells as biosensors," said Oana Ursu, a postdoctoral researcher in Regev's lab who previously worked at Broad University's Karaman Cell Observatory and now works at Genentech University

"So far, most techniques used to interpret coding variants are scalable, but they read relatively simple ones, such as cell viability, or may only look at a single feature

To test the potential of sc-eVIP, the team chose to study the most commonly mutated genes in cancer, TP53, and KRAS, which encodes a key oncogene that causes many cancers to grow abnormally

The atlas also revealed the broader impact of each mutation on the cell's state, based on how the activity of various pathways in individual cells changed

Boehm noted: "The cancer community has long embraced the binary conceptual framework of 'driver mutations' and 'passenger mutations', with driver mutations promoting cancer development and progression, while passenger mutations are completely inert and just happen to arise in the process

While the team focused on cancer-related genes and mutations in this study, they noted that sc-eVIP is genetically indeterminate and highly scalable, using single-cell RNA sequencing as a readout, providing An efficient and generalizable method to generate rich phenotypic data

"If we can map where each cancer-associated variant sits on the continuum of effects across various cancers and cell types, we can better understand how variants affect cell states, which in turn affect cancer development, growth, and development," Boehm said.

Support for this study came from the National Cancer Institute, the National Human Genome Institute, the Mark Foundation for Cancer Research, the Howard Hughes Medical Institute, the Broad next10 and functional variants program, and the Broad Institute's Klarman Cells Observatory, and other sources