Tumor heterogeneity is one of the biggest challenges of cancer diagnostics and treatment. Though multi-institutional research efforts, such as The Cancer Genome Atlas (TCGA), have focused on assessing the heterogeneity of tumors among different patients, large-scale studies of precise cellular and clonal tumor composition have only recently become feasible. This is in large part thanks to rapid development of single-cell genomics techniques. When applied to cancer research and diagnostics, single-cell analysis offers a high-resolution view of the cellular and molecular makeup of cancer.
Hallmarks of cancer
A seminal paper by Douglas Hanahan and Robert Weinberg titled “Hallmarks of Cancer” proposed that cancer development can be described as a gradual acquisition of a set of qualities, including limitless replication potential and metastatic ability. These features are dependent on an interplay of multiple cellular populations within the tumor. Some are malignant tumor cells that acquired mutations leading to uncontrolled cell division, and others are genetically normal cells that the tumor has coerced to do its bidding. The latter include endothelial cells forming blood vessels that support tumor growth and metastasis, as well as regulatory immune cells that repress the immune response. This complex interaction of cell types forms a dynamic tumor microenvironment, which is believed to be the basis of differential responses to therapy between cancer patients and drug resistance. Unraveling this complexity requires techniques capable of analyzing molecular profiles of single tumor cells.
Single-cell transcriptomics to dissect tumor heterogeneity
Single-cell RNA sequencing (scRNA-seq) has advanced at an unprecedented rate. It is now a method of choice for studying cellular composition of complex tissues, including tumors. scRNA-seq requires reactions to be performed in nanoliter volumes to label all RNA originating from the same single cell with a unique molecular barcode. The method enables detection of rare and previously uncharacterized cell types. It has evolved from being capable of analyzing tens or hundreds of cells to producing thousands or tens of thousands of single-cell transcriptional profiles in a single experiment, with droplet-based methods offering the largest cellular throughput (Figure). scRNA-seq was among the first single-cell genomics techniques to be applied to cancer research (Figure, panel A) and it uncovered intratumor heterogeneity of primary glioblastoma and cellular composition and drug resistance mechanisms of metastatic melanoma. Thanks to its ability to profile minor cellular populations, scRNA-seq has been instrumental to studies of cancer stem cells (CSCs), which are believed to be crucial to cancer’s resistance to drug mechanisms. scRNA-seq has also helped to characterize the molecular signatures of CSCs in chronic myeloid leukemia, and to decipher developmental programs of human oligodendroglioma.
Beyond gene expression: Single-cell DNA and epigenetic profiling
Current techniques for single-cell analysis are not limited to RNA expression. Single-cell DNA profiling of somatic mutations in tumor cells offers insight into the genetic evolution of cancer (Figure, panel B). For example, a recent study used droplet microfluidics to analyze clonal somatic mutations in myeloid leukemia by performing targeted DNA sequencing in single cells. In addition to variation in the DNA sequence, changes in the epigenetic landscape were shown to constitute a hallmark of cancer. Reversing malignant epigenetic changes has been an efficient therapeutic approach to many types of tumors. Advances in single-cell epigenetic profiling (Figure, panel C), such as single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) and single-cell DNA methylation analysis, allowed for multimodal analysis of DNA, RNA, and epigenetic status of single tumor cells from lung adenocarcinoma and hepatocellular carcinomas.
Single-cell analysis in precision oncology and cancer diagnostics
Precision oncology is a relatively novel biomedical research avenue that strives to leverage genomic information derived from the patient’s tumor to tailor personalized therapy. Single-cell approaches have only recently been included in the arsenal of personalized oncology, but they are already showing promise. For example, single-cell analysis has been applied to cancer immunotherapy, which has recently proven to be a highly efficient therapeutic option in certain types of cancer. In one study, single-cell analysis of T cell receptor repertoire (Figure, panel D) indicated that subtypes of regulatory tumor-infiltrating T cells upregulating protein layilin suppress immune response in liver cancer.
Another single-cell technique that holds promise for cancer diagnostics aims to isolate and sequence RNA of single circulating tumor cells (CTCs). This method proved instrumental in identifying biomarkers of CTCs in melanoma and pancreatic cancer. Two recent methods combining RNA and protein epitope profiling in single cells, if applied to CTCs, can offer even greater sensitivity in cancer diagnostics.
Single-cell technologies have revolutionized the approach to cancer research. As these techniques continue to develop and start integrating into the personalized oncology and cancer diagnostics, we are bound to see major transformations in the way cancer is treated.