How is single-cell sequencing accelerating progress against cancer?

Single-cell sequencing transformed our ability to study cells individually and with much higher resolution, giving us a clearer picture of how each cell type is different and how they function within a tumor sample. But what is it, and how is it helping scientists and clinicians find new ways to treat cancer?

Up until recently, DNA and RNA sequences were determined through bulk sequencing techniques that averaged the amount of genetic material among all the cells in a given sample. While this approach helped identify potential targets for various therapies, it also makes it hard to pinpoint which specific cells contain the target. It’s like studying the entire forest versus the individual trees within.

But that all changed in 2011, when MD Anderson’s Nicholas Navin, Ph.D., chair of Systems Biology, pioneered a new method of isolating an individual tumor cell within a sample and amplifying its genetic sequences. This made it possible to analyze each cell separately. Repeating this process with many individual cells within a tumor can provide invaluable information – creating a snapshot of all the different types of cells and how they interact. This work played a pivotal role in starting the field of single-cell genomics, which has since revolutionized cancer research.   

“Over the last 10 years, single-cell sequencing technologies have gotten quicker and more cost-effective, making it possible to translate into the clinic,” Navin says. “These tools have helped researchers look at cellular differences within tumors and provide insights into their microenvironments. They’re going to be helpful in other areas such as early detection, diagnostics, non-invasive monitoring and clinical decision-making.”

The advantages of single-cell sequencing compared to traditional bulk sequencing

Let’s say you have a bowl of fruit salad as your tumor sample and you want to study strawberries specifically. Single-cell sequencing would allow you to examine and identify the components of each fruit (strawberries, oranges, kiwis, grapes). This gives a very clear picture of the genomes from each cell type and allows you to identify a potential gene, or target, that can only be found in the strawberries so that whatever therapy or drug you use can be specifically tailored to attack exactly what you want.

In contrast, traditional bulk sequencing is like analyzing a blended fruit smoothie. You can still find a potential target that is present in the sample, but you wouldn’t be able to tell exactly which fruit it came from.

This is why single-cell sequencing has been so instrumental in enabling researchers to individually tailor drugs and therapies directly to a specific gene site on specific types of cells. Not only is it more thorough, but researchers also don’t need as much sample material and the sequencing machines have higher sensitivity. This allows researchers to dive deeper into the biology of different systems which was previously unthinkable because now there is a way to find these targets while minimizing potential damage to neighboring cells.

Single-cell sequencing has advanced our understanding of cancer and can help identify new cancer therapies

Using single-cell DNA (scDNA-seq) or RNA (scRNA-seq) sequencing data with other computational tools has helped drive a new generation of information that can paint a clearer picture of cancer development. This allows researchers to identify unique genetic alterations in different subtypes of cancers that might explain why some cancers are more resistant to certain treatments.

A few recent highlights include:

Along with his colleagues, Navin recently developed a new computational approach that combines scRNA-seq with spatial transcriptomics – which measures spatial gene expression in lots of small cell groups – to pinpoint the location of different cell types within a tissue. This tool, called CellTrek, allows researchers to visually show the location of these cells and map out the molecular data on top of the structural data to classify different types of cells and tumors even further and better guide treatment approaches.

Michael Andreeff, M.D., Ph.D., has led other scRNA-seq studies that have led to further understanding and identification of very rare cells that lead to relapse in patients with acute myeloid leukemia. This would be difficult to study without scRNA-seq because they represent only one out of every 10,000 cells.   

Single-cell analysis has also led to advances in the evolution of prostate cancer cells by Amado Zurita-Saavedra, M.D., and Ana Aparicio, M.D., who are able to noninvasively study the progression of circulating tumor cells in the blood of prostate tumors and bone marrow metastases throughout a patient’s treatment even with limited samples.

Recent studies using single-cell sequencing techniques at AACR

Several recent studies using single-cell sequencing also are being presented at the 2023 American Association for Cancer Research (AACR) Annual Meeting, highlighting the many potential uses and deeper insights possible with this technological innovation. These studies include:

• Kangyu Lin, Ph.D., and colleagues used scRNA-seq to identify a single-cell stemness signature for colorectal cancer to better predict the risk of relapse after surgical resection. (Abstract 2454)
  
  
• Elshad Hasanov, Ph.D., used scRNA-seq and spatial transcriptomics to map brain metastases from kidney cancer to identify targets responsible for immunotherapy resistance. (Session 5788)
  
  
• Elaine Stur, Ph.D., and colleagues performed single-cell analyses of over 100,000 cells in high-grade serous ovarian cancer to understand the differences between primary tumors versus tumors found in the omentum. (Abstract 5782)
  
  
• Yun Yan, Ph.D., and colleagues identified cell types that are reprogrammed in malignant triple-negative breast cancer, providing new data to predict patient response to chemotherapy. (Abstract 2147)
  
  
• scRNA-seq allowed Bo Zhu, Ph.D., and his team to establish models of precancerous lung adenocarcinomas to help study early lung carcinogenesis and identify ways to intercept it in the future. (Abstract 6513)
  
  
• Susana Castro Pando and her team used these technologies to study the interactions between tumor cells and immune cells, neurons and fibroblasts in pancreatic tumors. They identified IL-17/IL-17RA signaling as a regulator of B7-H4 which promotes tumorigenesis. (Abstract 1188)
  
  
• Vincent Bernard, M.D., Ph.D., and colleagues used scRNA-seq to understand what happens to cells after they undergo stereotactic body radiation therapy for pancreatic cancer. (Abstract 1096)
  
  
• Kaile Wang, Ph.D., and colleagues developed Arc-well, the first high-throughput method that can perform single-cell DNA sequencing from formalin-fixed paraffin-embedded (FFPE) materials. (Abstract 125)
  
  
• A novel Spatial Nucleus Barcoding (SNuBar) method allowed Zhenna Xiao, Ph.D., and colleagues to investigate the spatial microenvironment in ductal-carcinoma-in-situ breast cancer. (Abstract 76)

Single-cell sequencing and spatial transcriptomics are groundbreaking technologies that have allowed scientists and clinicians to take a closer look at the ins and outs of tumor progression and find specific genes that they can target. These tools have greatly accelerated progress against cancer and are invaluable in the development of therapeutic strategies that can improve patient outcomes and, ultimately, end cancer.

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