Technology Spotlight
Single-cell Genomics to Decipher the Complexity of Hematologic Malignancies

Single-cell genomics enables characterization of individual cells within a heterogeneous population, uncovering cellular diversity and identifying rare, distinct subpopulations. The process involves isolating single cells and capturing their genomic information. Several approaches have been developed to decipher different levels of information, including single-cell DNA sequencing (scDNA-seq), single-cell RNA sequencing (scRNA-seq), and various single-cell epigenomic methods.

The scDNA- and scRNA-seq approaches are used most frequently. Typically, single-cell sequencing workflows include an initial cellular enrichment step, such as density-gradient centrifugation to isolate mononuclear cells from bone marrow or peripheral blood, cell dissociation from a solid tissue, or red blood cell lysis. Cells of interest are often enriched further, for example, by using immunomagnetic beads. Other isolation methods include fluorescence-activated cell sorting,³  laser-capture microdissection,⁴  or droplet-based microfluidic methods,⁵  which allow for simultaneous characterization of thousands of cells.

For the next steps after isolation of DNA or messenger RNA (mRNA) from single cells, numerous protocols have been established to amplify the small amounts of material that can be obtained from a single cell. In the case of scDNA-seq, whole-genome amplification (WGA) can be done using polymerase chain reaction (PCR), multiple displacement amplification (MDA), or hybrid methods (such as multiple annealing and loop-based amplification cycling [MALBAC] or PicoPLEX).^1,2,6,7  In RNA-seq, mRNA from isolated cells is typically retrotranscribed into complementary DNA (cDNA), followed by PCR-based amplification and sequencing. At present, sequencing of single cell-derived libraries is most commonly performed on the Illumina platform. Other sequencing platforms include those developed by Oxford NanoPore Technologies, Pacific Biosciences, and Ion Torrent. All these methods provide data on genomic and molecular heterogeneity at the single-cell level, but with different strengths and weaknesses. The data they produce are therefore often complementary.

scDNA-seq enables investigation of somatic mutations, copy number variations, and genomic rearrangements at the single-cell level. The approach can be employed to define clonal evolution, quantify mutational heterogeneity within individual cells, and dissect development and progression of hematologic malignancies. Obtaining the complex information on the (sub)clonal composition of the tumor can help to identify treatment-refractory subclones early, before relapsed disease becomes clinically apparent. scDNA-seq of bone marrow aspirates may also represent a tool for assessment of measurable residual disease in hematologic malignancies such as multiple myeloma (MM).

Furthermore, interrogation of circulating tumor cells can provide a minimally invasive alternative to bone marrow aspiration or biopsy that reveals comprehensive information about the existing disease in solid tumors and hematologic malignancies.^8,9  This may help with detection and prediction of treatment response or resistance, as well as disease relapse. Another possible application of single-cell sequencing of circulating tumor cells is cancer screening or early detection, in addition to diagnosis in case the primary tumor is difficult to access through a regular biopsy. With the ability to distinguish newly emerging disease clones, it can be used as a precision medicine tool to identify potentially actionable therapeutic targets.

Apart from its applications in the cancer field, scDNA-seq can be used to study the genetic diversity and function of microbial organisms in blood, skin, gut flora, and the environment.^1,10  Various platforms for scDNA-seq have been developed.^2,11  Some of the commercially available scDNA-seq kits use MDA as the DNA-amplification method.¹¹  Other platforms use PCR or a combination of both techniques for WGA.^1,11 

While scDNA-seq is a potent technique with substantial information capacity, it has some limitations. One of those limitations lies in the fact that the most time-efficient and cost-effective methods with the highest throughput often yield relatively low coverage of the entire genome. Additionally, amplification errors can be introduced during the amplification process of the initial small quantity of scDNA input.^1,10 

scRNA-seq allows for transcriptome profiling of individual cells. Similar to scDNA-seq, it is a valuable tool in cancer research that can be used to infer arm-level copy number variants and translocations and detect mutations. Although scDNA-seq provides better resolution to detect genomic events, scRNA-seq produces several additional layers of data that provide insight into the functional characteristics of cells in addition to genomic events. It enables detection of splice variants and transcriptional signatures,¹²  which can be exploited to infer transcription factor activity and signaling pathway activation,¹³  and for the robust distinction of clonotypes.^13,14 

These layers of information within single cells provide unprecedented power to define heterogeneity among cell populations. Importantly, the ability to define transcriptional heterogeneity with scRNA-seq is not limited to cancer cells. It is also an excellent tool for dissecting the tumor microenvironment and the immune system in general. It allows clinicians to track gene expression changes that underly the initiation of a disease or those that occur over the course of a therapy, which is helpful for understanding the mechanisms of neoplastic transformation, tumor development, and therapy resistance.^13,15,16  An example of the latter is the interrogation of T-cell exhaustion as a resistance mechanism to chimeric antigen receptor (CAR) T-cell therapy. T-cell populations can be distinguished easily from other cell types by scRNA-seq, and the up-regulation of signaling pathways that are associated with exhaustion can be determined in parallel. This information may be used as a predictor of immunotherapeutic efficacy and can help in selecting the optimal therapy for an individual patient or the most efficacious order in which different treatments should be given.

A vast number of scRNA-seq protocols have been described. Generally, some available scRNA-seq methods are able to detect the full-length transcript, while others, the so called tag-based methods, detect 5’ or 3’ end of transcripts.¹  Methods for single-cell sequencing of full-length mRNA typically provide greater information content for splice variants and somatic mutations and allow for detection of a greater number of genes.^6,7,17  Droplet-based sequencing of either the 5’ or 3’ end of mRNA provides data on a larger number of cells at a lower cost per cell.¹  Choosing a particular platform for scRNA-seq usually comes with the trade-off between cost- and time-effectiveness and transcriptome coverage.

Single-cell epigenomics is gaining popularity as another closely related single-cell genomic approach. These technologies provide insight into the nongenetic mechanisms that drive and regulate important aspects of cancer biology. Epigenetic mechanisms play significant roles in cellular differentiation and developmental programs, thus affecting processes such as tumor development, progression, metastases, and resistance to therapy — even in the absence of distinct genetic drivers. Moreover, single-cell epigenomics allows for interrogation of nongenetic dependencies within the tumor microenvironment, reflecting the complex process of “cellular cross-talk” at the single-cell level. Various methods to interrogate different levels of chromatin regulation have been described, such as DNA methylation, changes in chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D interactions.¹⁸ 

The single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is a popular method used to interrogate the chromatin landcape at the single-cell level. It uses insertion of sequencing adapters into accessible genome areas to facilitate Tn5 transposition as a measure of chromatin accessibility. Not only does it represent an excellent tool to investigate the intratumoral heterogeneity as described above, it can also help to interrogate the regulatory networks in the immune microenvironment and stroma.¹⁸ 

Post-translational histone modification is another method of gene-expression regulation, leading to changes in chromatin states, which can be transcriptionally permissive or repressive. Investigation of histone modification at the single-cell level can depict regulatory mechanisms associated with therapeutic resistance and disease relapse that are present even in a small subpopulation of the tumor. Several techniques have been developed to interrogate histone modification with single-cell resolution. Examples of these techniques include single-cell chromatin immunoprecipitation sequencing (scCHIP-seq), which, along with the histones, can map DNA-interacting proteins such as transcription factors, as well as single-cell chromatin immunocleavage sequencing (scChIC-seq), which uses a mononuclease-bound antibody to target a specific histone modification, followed by cleavage and sequencing of the surrounding DNA.¹⁸ 

Some limitations of the currently available single-cell epigenomics methods are, in many cases, their low throughput, limited epigenome coverage, relatively high costs, and experimental challenges such as amplification bias and the risk of DNA damage associated with certain processing techniques.¹⁸ 

In recent years, multiomic approaches, combining different single-cell sequencing tools, have emerged. These technologies allow for a simultaneous interrogation of two or more levels of gene expression and its regulation at the single-cell level, thus helping to decipher the interactions among the genome, transcriptome, epigenome, and proteome.^2,19  Other single-cell multiomic tools enable the analysis of several types of epigenetic regulations in one approach.¹⁸  Single-cell spatial transcriptomics and epigenomics are exciting approaches that have evolved over the last few years. They allow for a three-dimensional representation to determine the spatial distribution of cells, combined with the single-cell transcriptome or epigenome profiling.^18,20  Moreover, platforms that integrate CRISPR-Cas9 technology into scRNA-seq have been developed.² 

In summary, single-cell genomics and various related approaches to interrogate single cells have emerged as transformative tools in hematology, unraveling hematologic disorders at the cellular and molecular level. By uncovering cellular heterogeneity, clonal dynamics, and regulatory networks, these techniques have provided unparalleled insights into molecular mechanisms, the underlying genomics of disease, and therapeutic resistance. Two of the main challenges of single-cell technologies are their complexity, which have made standardization across centers difficult, and their high cost. Despite the unprecedented insight that single-cell technologies provide into cancer, these obstacles, thus far, have hindered their adoption in clinical routine. Future advancements in technology and analytical tools will address these limitations, further enhancing the potential of single-cell genomics in hematology.

Drs. Blocka and Lohr indicated no relevant conflicts of interest.