A team of researchers led by scientists at the Genome Institute of Singapore, and the Jackson Laboratory for Genomic Medicine (JAX) has just published data defining the cell-type composition of cancerous cells from 11 colorectal tumors, as well as adjacent noncancerous cells, a key to more targeted diagnosis and treatment. The findings from this study were published recently in Nature Genetics through an article entitled “Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors.”

Recent advances in tumor genomic sequencing have improved classification of tumor subtypes, guiding more precise cancer treatments and improving patient survival. However, tumors typically contain a variety of cancerous and noncancerous cells that all contribute to the biology of the tumor.

“Using single-cell signatures, colorectal cancers can be further divided into subgroups based on the cell-type composition of tumors,” explained co-lead study investigator Elise Courtois, Ph.D., a research scientist at JAX. “Because each of these subgroups has a different survival probability, our approach can provide oncologists with better information about prognosis and treatment options.”

Currently, gene expression in most tumors has been profiled using bulk transcriptome methods, providing a single transcriptome measure for what represents many cell types. By employing single-cell transcriptomic technology, it is now possible to deconstruct a tumor into its component cell-type parts and therefore gain a better understanding of the underlying biology.

The research team in this study led an effort that screened 626 randomly selected individual cells from the colorectal tumors and adjacent normal cell samples, using single-cell RNA sequencing. Computationally examining each cell's transcriptome (the readout of all the messenger RNA molecules in that cell) using their new algorithm, the researchers identified two distinct subtypes of cancer-associated fibroblasts (CAFs).

“We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA–seq from 11 primary colorectal tumors and matched normal mucosa,” the authors wrote. “To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct CAFs.”

These CAFs significantly contributed to the mesenchymal gene expression found in bulk tumor transcriptome data, a signature more often associated with a cancer cell process known as epithelial-mesenchymal transition. Their data make the case that CAFs contribute to a worse prognosis in colorectal cancer patients.

The findings show promise for even more refined classification of colorectal and other tumors in the future. “And as the cost of single-cell transcriptomic analysis continues to drop, oncologists can access better tumor profiling to guide the treatment of cancer patients,” concluded Paul Robson, Ph.D., director of single-cell biology at JAX and co-senior study investigator.

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