Spatially resolved transcriptomics and its applications in cancer
Introduction
Recent technological advances provide the ability to interrogate tissues and even whole organisms at ‘omics’ scale and with cellular resolution. Single cell RNA sequencing (scRNAseq) studies of hematologic malignancies have yielded an unprecedented view of cellular dynamics driving these diseases and their responses to therapy [1, 2, 3]. However, application of scRNAseq methods to solid tumors requires tissue dissociation and therefore loss of spatial context [4, 5, 6]. As reviewed, spatial heterogeneity in tumors is driven not only by genotypic diversity that arises during clonal expansion but also by interactions between cancer cells and the immune and stromal cells that comprise the local tumor microenvironment, leading to distinct phenotypes in different regions of a tumor [7]. Understanding the spatial heterogeneity of tumors is clinically consequential, especially in instances where limited physical sampling of tumors is used to guide treatment [8].
SRT encompasses a diverse set of technologies that encode gene expression measurements with information about where in the sample each observation occurred. How this spatial encoding is achieved dictates the capabilities of each technology, including spatial resolution, depth of data per measurement, throughput, cost, and complexity. SRT technologies can require preselection of a panel of transcripts to be profiled, or sample the entire polyadenylated transcriptome. Some SRT methods require costly bespoke equipment and substantial technical support, while others are available as commercial kits requiring almost no specialized equipment. Careful consideration of these properties is required for selection of SRT technologies.
Although this domain of technologies is diverse and rapidly growing, major themes have emerged. Here, we survey currently available SRT technologies for studies of tumor samples, dividing them into 3 major categories-based upon how each technology encodes spatial information: 1) In microdissection, light microscopy is used to select the location and shape of each tissue region collected for subsequent ex situ processing; 2) in situ barcoding-based methods attach specific DNA barcode sequences to known regions of intact tissue samples and use codetection of those barcodes with tissue derived RNAs during subsequent ex situ sequencing to computationally assign spatial information to expression data; 3) Imaging-based methods simultaneously acquire spatial and gene expression information through iterative cycles of fluorescent nucleic acid imaging in intact tissue samples. The resulting images are assembled into a spatially aligned dataset that spans all cycles, and expression data is decoded based on the presence or absence of signal in each pixel for each cycle. Here we describe SRT technologies from each category, summarize their application to cancer research to date, and anticipate future developments (Figure 1, Table 1).
Section snippets
Microdissection-based methods
Microdissection and capture of tissue regions or cells of interest is a well-established and robust method for preservation of spatial information during sample acquisition. In laser capture microdissection (LCM), tissue is sectioned onto specially prepared glass slides, stained and imaged for morphology, and regions of interest as small as single cells are dissected using a microscope-guided laser [9]. LCM is compatible with cryopreserved as well as formalin fixed paraffin embedded (FFPE)
In situ barcoding-based methods
Several methods for spatial RNA quantification using DNA barcoding have been developed. These can be subcategorized broadly based on how barcoding is performed. In one group of technologies, referred to here as solid phase-based capture (SPBC) methods, tissue is delivered to a substrate bearing a pre-arranged set of DNA barcodes. In the second group of technologies, termed selective barcoding (SB) methods, DNA barcodes are either delivered to or collected from selected tissue locations. In situ
Imaging-based methods
Imaging-based SRT methods enable acquisition of data with submicron resolution and are thus particularly well suited for studies of processes occurring at subcellular scales. This resolution comes at the expense of complexity, time, and equipment cost. The sensitivity of imaging-based methods is limited by the ability of optical microscopy to resolve densely packed RNAs in situ. Methodological advancements to overcome this challenge result in decreased throughput [24, 25, 26]. In general,
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
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These authors contributed equally to this work.