The immune nature of kidney cancer stands out when compared to other cancers: More immune cells infiltrate kidney cancers than most other solid tumors, and kidney cancer is one of the most responsive malignancies to today's immunotherapy regimens.

But despite treatment, many patients with clear cell renal carcinoma--the most common type of kidney cancer--eventually relapse and develop incurable metastatic disease.

A new study shows that the presence of a rare and previously unknown type of immune cell in kidney tumors can predict which patients are likely to have cancer recur after surgery. These cells could even be driving aggressive disease.

"Our findings suggest that the presence of these cells could be used to identify patients at high risk of disease recurrence after surgery who may be candidates for more aggressive therapy," says co-senior author. The study was published in the journal Cell.

Though kidney tumors are densely infiltrated by immune cells, cell subtypes and their association with post-surgical outcomes have remained largely unknown.

It's like looking down at Manhattan and seeing that large numbers of people from all over travel into the city every morning, says the study's co-first author. "To understand how these diverse commuters are interacting with Manhattan residents, we need finer details: Who are they; what are they like, where do they go, and what are they doing?"

To uncover the fine details of the immune cells that infiltrate kidney cancers, the researchers combined two of the newest techniques in cancer research.

The first, called single-cell RNA sequencing, captures a snapshot of gene activity in individual cells within a tumor. This high-throughput technique allows researchers to obtain such snapshots inside of tens of thousands of cells from one tumor in a single experiment, providing insights into the identity and behavior of the various cell types.

This powerful technique can identify new types of cells, but there is a drawback. Because single-cell sequencing works by detecting a small number of mRNA molecules inside each cell, it often fails to detect the mRNAs of genes with low expression levels, including key signaling genes and drug targets such as immunotherapy checkpoints.

"In many experiments, single-cell RNA sequencing misses up to 90% of gene activity, a phenomenon known as gene dropout," the author says.

The researchers addressed gene dropout by developing a prediction algorithm that can infer which genes are active by looking at the expression of other related genes. "Even when a lot of the data are missing due to dropout, we still have enough clues to infer the activity of the upstream regulator gene," the author says. "It's like playing 'Wheel of Fortune': I can usually guess what's on the board even when most of the letters are missing."

The algorithm, called meta-VIPER, builds on the VIPER algorithm. With the addition of metaVIPER, the researchers estimate they can accurately detect the activity of 70% to 80% of all regulatory genes in each cell, eliminating dropout across cells.

This combined approach was used to analyze more than 200,000 tumor cells and normal cells in adjacent tissue taken from 11 patients with clear cell renal carcinoma who underwent surgery.

The analysis revealed a unique sub-population of immune cells called macrophages found only in tumors and associated with eventual relapse of disease after initial treatment. The VIPER analysis also revealed the top genes (or master regulators) that control the activity of these macrophages. This "signature" was validated in a second set of patient data obtained through a collaboration with researchers from Vanderbilt University; here the signature strongly predicted relapse in a second set of over 150 patients.

Furthermore, these macrophages were found to interact directly with tumor cells through receptor-ligand gene pairs. "These data raise the intriguing possibility that these macrophages are not just markers of more risky disease but may actually cause the disease to recur and progress," the author says, "and that targeting these cells could improve clinical outcomes."

Thus VIPER-based technologies, such as Oncotreat test, could be used to identify drugs targeting these rare but critical subpopulations, thus preventing the poor outcomes associated with their presence, the author says.

The combination single-cell sequencing with the VIPER algorithm has potential to dissect other types of cancer too, the researchers say.

"Our study demonstrates that the two techniques, when combined, are highly effective at characterizing the cells within a tumor and in surrounding tissues and should have broad applicability, even beyond the study of cancer," the co-senior author says.

https://www.cell.com/cell/fulltext/S0092-8674(21)00573-0