Box 2: Multi-omic analysis methods

Tissue spatial transcriptomics

Tissue spatial transcriptomics allows the characterization of gene expression profiles keeping the tissue’s spatial architecture intact. Multiple techniques have been developed for spatial transcriptomics, mainly based on in situ hybridization, in situ capturing, in situ sequencing or microdissection (78).
Fluorescent in situ hybridization (FISH)-based methods exploit the hybridization of fluorescent-labeled RNA-targeting probes with pre-defined transcripts of interest, followed by imaging, visualization, and quantification, which however is limited to the simultaneous detection of a small number of transcripts. Higher efficiency in mRNA detection has been reached with the usage of array-based in situ capturing methods. These arrays have attached barcoded oligonucleotides that capture, through complementarity, the mRNAs present in the sample. Capture is followed by reverse transcription to cDNA and NGS, allowing the detection of more than 10,000 targets (79, 80). The widely used Visium technology is an example of this approach (Visium spatial gene expression, 10X Genomics) (81).
Recent technologies allow to explore the transcriptome of specific regions of interest in FFPE samples through microdissection. The GeoMx Digital Spatial Profiler by Nanostring allows in situ capture of mRNAs using fluorescent-tagged RNA probes, which are linked to UV-photocleavable DNA oligonucleotides of known sequence. The fluorescent-tagged RNA probes are also known as imaging reagents since they will generate a fluorescent image that allows tissue visualization of regions where a specific mRNA is expressed. Once the investigator selects their regions of interest, these areas are exposed to UV light that cleaves the DNA tags in a region-specific manner. This releases indexing oligos that are collected via microcapillary aspiration and dispensed into a microplate and subject to Nanostring mediated counting, or NGS (82). The RNA from FFPE fixed samples very commonly suffers degradation. However, Visium and GeoMx technologies can retrieve good amounts of information from these tissue samples.

Tissue spatial proteomics

The most popular methods of tissue spatial proteomics have the advantage that FFPE samples can be used and, therefore, precious pathological archives can be studied. Strategies for exploring spatial proteomics are based on (i) immunofluorescence, (ii) imaging mass cytometry by time of flight and (iii) sequencing (79). Tissue cyclic immunofluorescence (tCycIF) is an immunofluorescence-based strategy. tCycIF uses FFPE tumor and tissue specimens mounted on glass slides that undergo staining cycles. In every cycle, the specimens are stained with fluorochrome-conjugated antibodies and imaged, followed by chemical inactivation of fluorochromes after each round of immunofluorescence (83). Conventional wide-field, confocal or super-resolution microscopes can be used for image acquisition. After multiple rounds of imaging, a final high-dimensional representation of all the images is assembled into a unique image using computational strategies. The final high-dimension image can be segmented into all individual cells composing the tissue to give single-cell resolution. Neighborhood analysis can also be performed to quantify cell-cell interactions. Of note, tCycIF does not require proprietary reagents, is robust and is a more economical option compared to other spatial proteomics strategies.
CyTOF is a mass spectrometry-based method. In this technology, cellular proteins are detected using antibodies that are conjugated to isotopes from the lanthanide series of rare metals. The sample is imaged using the Hyperion Imaging SystemTM, where these metal-tagged antibodies are laser ablated from regions of interest in the tissue and each ionized metal tag is detected based on differences in their mass instead of the wavelength emitted by a fluorochrome. This technology eliminates the autofluorescence inherent to biological specimens, since the rare metal tags with which the antibodies are conjugated are not present in cells. Also, compensation or background elimination is not needed, since there is no overlap among the signal produced by the ionized metals. In this technology, FFPE samples can be stained with an entire panel of multiple antibodies in a single scanning round without the need for multiple staining and washing cycles. The image is analyzed using a proprietary software package (84).
Finally, GeoMx Digital Spatial Profiler by Nanostring can be adapted for detection of proteins instead of transcripts (described above). In this setting, the FFPE tissues are immunostained with UV-photocleavable oligonucleotide-labeled antibodies. The spatial location of proteins is again achieved by exposure of the region of interest to UV light that photocleaves the oligos, followed by retrieval of the oligos and sequencing. This provides an average count of oligonucleotides in every region of interest (82, 85).

Tissue spatial genomics

Technologies for spatial resolution of the genome that can preserve tissue architecture are less well developed. Nonetheless, using spatially resolved DNA sequencing will finally deliver information on the process of clonal evolution of solid tumors and provide a timeframe for when a specific mutation appeared. FFPE samples are especially problematic since DNA is very commonly degraded in these specimens (86).
Slide-DNA-seq is one new technology that works with cryosectioned intact tissues. Slide-DNA-seq uses cover slip arrays coated with 10 μm DNA-barcoded polystyrene beads, each containing a unique DNA barcode corresponding to its spatial location in the cover slip. This is meant to provide spatial indexing. Then, a 10-μm-thick fresh-frozen tissue section is placed onto the barcoded bead array, treated with HCl for histones removal and treated with the transposase Tn5 to generate DNA fragments that will be flanked with sequencing Illumina adapters. The barcodes are photocleaved from the beads and the resulting DNA sequencing library is amplified by PCR (86, 87).