WO2015128490A1 - Multiplexed imaging of tissue samples by mass cytometry with subcellular resolution - Google Patents

Abstract

The inventors have adapted Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) so that it is suitable for single-cell imaging in tissue samples with subcellular resolution. The laser spot size may be 4 μm or less. A time-of-flight mass analyser may be used. The tissue sample may be labelled with four or more rare earth metals.

Description

MULTIPLEXED IMAGING OF TISSUE SAMPLES BY MASS CYTOMETRY

WITH SUBCELLULAR RESOLUTION

FIELD OF THE INVENTION

The present invention relates to the imaging of tissue samples using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) or mass cytometry.

BACKGROUND ART

Single-cell measurements and multiplexed quantitative detection of molecular targets can provide insights on the state and behaviour of individual cells. Techniques which have been used for single-cell analysis include microscopy in combination with specific labelling techniques (e.g. using immunocytochemistry), single-cell imaging mass spectrometry, surface-enhanced Raman scattering spectroscopy, and LA-ICP-MS.

Some of these techniques can readily be extended to in situ imaging of tissues (e.g. using immunohistochemistry), but others cannot. For instance, approaches such as immunofluorescence microscopy (IFM) are useful for imaging down to nanometer resolutions, but are limited in practice to measuring seven or fewer targets simultaneously. In contrast, LA- ICP-MS offers highly multiplexed quantitative analysis of antigen expression in single cells, but it currently lacks the resolution necessary for the imaging of single cells within tissue samples.

It is an object of the invention to provide further and improved techniques for imaging of tissue samples, and in particular to adapt LA-ICP-MS for use as a single-cell imaging technique.

DETAILED DESCRIPTION

ICP-MS has been used for single-cell analysis, but only for cells in suspension [1 ]. The inventors have now adapted laser ablation (LA) to ICP-MS so that this technique is suitable for single-cell imaging in tissue samples. Although tissue imaging via LA-ICP-MS has previously been reported, the disclosed procedures have not achieved high spatial resolution. For instance, LA-ICP-MS has been used to obtain images of brain sections [2] and of cancer tissue [3,4] but single-cell or subcellular resolution was not achieved. In all cases the resolution was limited by the spot size of the ablating laser and/or by overlap/mixing between the analysis of material released in consecutive ablations. For instance, a spot size of 40μηι [2] cannot ablate material with a resolution which is high enough for single-cell imaging in a tissue sample. Similarly, ablation at a frequency of 10 Hz will lead to overlapping signals if the ablated material cannot be transported to the ICP-MS in less than 100 ms; for example the ablation cell used in reference 3 with this ablation frequency had a washout time well in excess of 1 s (which the authors did not note).

The inventors have now provided a LA-ICP-MS system which overcomes these drawbacks and is able to achieve sub-cellular resolution, thereby making available for the first time a LA- ICP-MS technique suitable for single-cell imaging of tissues. The invention therefore provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation with a subcellular resolution at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample. One general advantage of the invention is that it is compatible with techniques and protocols which are already used in immunohistochemistry (IHC), but the use of labels which are detected by LA-ICP-MS now permits more targets to be localised in a sample.

The invention also provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry using a time-of-flight mass analyser, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

The invention also provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling at least four different target molecules in the tissue sample with different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

The invention also provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample;

(ii) demarcating individual cells in the sample; (iii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and

(iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

The invention also provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling one or more a target molecules in the tissue sample with labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations using a laser spot size of 4 μηη or less, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

The invention also provides a method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) providing a labelled tissue sample in which a plurality of different target molecules have been labelled with a plurality of different labelling atoms; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation with a subcellular resolution at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

The invention also provides a method of labelling a tissue sample with four or more (e.g. 5, 6, 7, 8, 9, 10, 12, 13, 14, 15 or more) different transition metal atoms. These atoms associate with specific cellular targets, thereby permitting downstream detection by LA-ICP-MS. Data from the LA-ICP-MS can then be used to create an image of the sample.

The invention also provides a method of imaging a tissue sample, wherein multiple cells of the tissue sample are subjected to mass cytometry at a subcellular resolution.

The invention also provides a method of LA-ICP-MS wherein substantially all of the contents of a single labelled cell are ablated with a single laser shot and then subjected to ICP-MS. Thus substantially all of the contents of a whole cell can be analysed by mass cytometry. Ablation provides a plume containing substantially all of the cell's contents, and this plume can then be introduced into an ICP and subjected to MS, thereby detecting the labelled material and permitting multiplex analysis of the whole cell in a single analysis.

LA-ICP-MS and mass cytometry

The invention uses laser ablation coupled to inductively coupled plasma mass spectrometry (LA-ICP-MS) in a method of imaging a tissue sample. Different target molecules in the sample are labelled with different labelling atoms and LA-ICP-MS is then used across multiple cells of the labelled tissue sample. By linking detected signals to the known positions of the laser ablations which gave rise to those signals the method permits localisation of the labelled target molecule to specific locations on the sample, and thus construction of an image of the sample.

LA-ICP-MS involves subjecting the tissue sample to laser pulses which generate plumes of ablated material from the sample, and these plumes are transferred as aerosols to an ICP-MS instrument for analysis. The labelling atoms in the sample can be distinguished by MS and so their detection reveals the presence or absence of multiple targets in a plume.

The spatial resolution of signals generated in this way depends on two main factors: (i) the spot size of the laser, as signal is integrated over the total area which is ablated; and (ii) the speed at which a plume can be analysed, relative to the speed at which plumes are being generated, to avoid overlap of signal from consecutive plumes as mentioned above.

Thus, in order to analyse individual cells the invention uses a laser spot size which is no larger than these cells, and more specifically uses a laser spot size which can ablate material with a subcellular resolution. This size will depend on the particular cells in a sample, but in general the laser spot will have a diameter of less than 4 μηη e.g. within the range 0.2-4 μηη, 0.25-3μη"ΐ, or 0.4-2 μηη. Thus a laser spot can have a diameter of about 3 μηη, 2 μηη, 1 μηη, or 0.5 μηη. In a preferred embodiment the laser spot diameter is within the range of 0.5-1.5 μηη, or about 1 μηη. Small spot sizes can be achieved using demagnification of wider laser beams and near-field optics. A laser spot diameter of 1 μηη corresponds to a laser focus point of 1 μηη, but the laser focus point can vary by +20% due to numerical aperture of the objective that transfers the laser beam onto the sample surface.

For rapid analysis of a tissue sample a high frequency of ablation is needed, for example 10 Hz or more (i.e. 10 ablations per second, giving 10 plumes per second). In a preferred embodiment the frequency of ablation is within the range 10-200 Hz, within the range 15-100 Hz, or within the range 20-50 Hz. An ablation frequency of at least 20 Hz allows imaging of typical tissue samples to be achieved in a reasonable time. As noted above, at these frequencies the instrumentation must be able to analyse the ablated material rapidly enough to avoid substantial signal overlap between consecutive ablations. It is preferred that the overlap between signals originating from consecutive plumes is <10% in intensity, more preferably <5%, and ideally <1 %.The time required for analysis of a plume will depend on the washout time of the ablation cell, the transit time of the plume aerosol to and through the ICP, and the time taken to analyse the ionised material.

Thus an ablation cell with a short washout time (e.g. 100 ms or less) is advantageous for use with the invention. A cell with a long washout time will either limit the speed at which an image can be generated or will lead to overlap between signals originating from consecutive sample spots (e.g. reference 5, which had signal duration of over 10 seconds). Therefore aerosol washout time is a key limiting factor for achieving high resolution without increasing total scan time. Ablation cells with washout times of≤100 ms are known in the art. For example, reference 6 discloses an ablation cell with a washout time below 100 ms. A particularly suitable ablation cell was disclosed in reference 7 (see also reference 8) which has a washout time of 30 ms or less, thereby permitting a high ablation frequency (e.g. between 20-40 Hz) and thus rapid analysis. The examples herein demonstrate that the signals of plumes generated by 20 Hz laser ablation shots can be fully separated by this ablation cell, thereby enabling imaging of a large area in short time. Using methods of the invention, it is therefore possible to achieve a time per spatially resolved pixel in a final image of less than 100 ms.

The transit time of a plume aerosol to and through the ICP is easily controlled simply by positioning the ablation cell near to the ICP and by ensuring a sufficient gas flow to transport the aerosol at an appropriate speed directly to the ICP. Transport using argon and helium as described in reference 7 provides good results.

The time taken to analyse the ionised material will depend on the type of mass analyser which is used for detection of ions. For example, instruments which use Faraday cups are generally too slow for analysing rapid signals. Overall, the desired imaging speed (and thus ablation frequency), resolution (and thus laser spot size and ablation cell) and degree of multiplexing will dictate the type(s) of mass analyser which should be used (or, conversely, the choice of mass analyser will determine the speed, resolution and multiplexing which can be achieved).

Mass spectrometry instruments that detect ions at only one mass-to-charge ratio (m/Q, commonly referred to as m/z in MS) at a time, for example using a point ion detector, will give poor results in single cell imaging using multiple labels. Firstly, the time taken to switch between mass-to-charge ratios limits the speed at which multiple signals can be determined, and secondly, if ions are at low abundance then signals can be missed when the instrument is focused on other mass-to-charge ratios. Thus, although the instrument used in references 2 and 3 (Agilent 4500) is sensitive, its quadrupole-based detector is not well suited to imaging with multiple labels because, by design, ions of different mass-to-charge ratios pass through sequentially and so data acquisition for multiple labels is slow. Similarly, the instruments used in references 4 and 7 (Thermo Fisher ElementXR and Element2) analyse only one m/Q at a time and have a large settling time for magnet jumps when measuring multiple m/Q values over a range exceeding the range of an electrostatic field jump. Thus it is preferred to use a technique which offers substantially simultaneous detection of ions having different m/Q values. For instance, instead of using a point ion detector, it is possible to use an array detector (e.g. see Chapter 29 of ref. 9). Multi-collector sector field ICP-MS instruments can be used (e.g. the Thermo Scientific Neptune Plus, Nu Plasma II, and Nu Plasma 1700 systems), and in particular those having a Mattauch-Herzog geometry (e.g. the SPECTRO MS, which can simultaneously record all elements from lithium to uranium in a single measurement using a semiconductor direct charge detector). These instruments can measure multiple m/Q signals substantially simultaneously. Their sensitivity can be increased by including electron multipliers in the detectors. Array sector instruments are not ideal, however, because, although they are useful for detecting increasing signals, they are less useful when signal levels are decreasing, and so they are not well suited in situations where labels are present at highly variable concentrations.

The most preferred MS method for use with the invention is based on time-of-flight (TOF) detection, which can quasi-simultaneously register multiple masses in a single sample. In theory TOF techniques are not ideally suited to ICP ion sources because of their space charge characteristics, but the inventors have shown that TOF instruments can analyse an ICP ion aerosol rapidly enough and sensitively enough to permit feasible single-cell imaging. Whereas TOF mass analyzers are normally unpopular for atomic analysis because of the compromises required to deal with the effects of space charge in the TOF accelerator and flight tube, tissue imaging methods of the invention can be effective by detecting only the labelling atoms, and so other atoms (e.g. those having an atomic mass below 100) can be removed. This results in a less dense ion beam, enriched in the masses in (for example) the 100-250 dalton region, which can be manipulated and focused more efficiently, thereby facilitating TOF detection and taking advantage of the high spectral scan rate of TOF. Thus rapid imaging can be achieved by combining TOF detection with choosing labelling atoms that are uncommon in the sample and ideally having masses above the masses seen in an unlabelled sample e.g. by using the higher mass transition elements. Using a narrower window of label masses thus means that TOF detection to be used for efficient imaging.

Suitable TOF instruments are available from Tofwerk, GBC Scientific Equipment (e.g. the Optimass 9500 ICP-TOFMS), and Fluidigm Canada (e.g. the CyTOF™ and CyTOF™2 instruments). These CyTOF™ instruments have greater sensitivity than the Tofwerk and GBC instruments and are known for use in mass cytometry because they can rapidly and sensitively detect ions in the mass range of rare earth metals (particularly in the m/Q range of 100-200) [10]. Thus these are preferred instruments for use with the invention, and they can be used for imaging with the instrument settings already known in the art e.g. references 1 1 & 12. Their mass analysers can detect a large number of markers quasi-simultaneously at a high mass- spectrum acquisition frequency on the timescale of high-frequency laser ablation [4]. They can measure the abundance of labelling atoms with a detection limit of about 100 per cell, permitting sensitive construction of an image of the tissue sample. Because of these features, mass cytometry can now be used to meet the sensitivity and multiplexing needs for tissue imaging at subcellular resolution. Previously, mass cytometry has been used only to analyze cells in suspension, and information on cell-cell interactions within tissue or tumor microenvironments has therefore been lost. By combining the mass cytometry instrument with a high-resolution laser ablation system and a rapid-transit low-dispersion ablation chamber it has been possible to permit construction of an image of the tissue sample with high multiplexing on a practical timescale. Further details on mass cytometry can be found in references 1 and 13.

The choice of wavelength and power of the laser used for ablation of the sample can follow normal usage in cellular analysis by ICP-MS. The laser must have sufficient fluence to cause ablation to a desired depth, without substantially ablating the supporting sample holder. A laser fluence of between 2-5 J/cm² at 20 Hz is typically suitable e.g. from 3-4 J/cm² or about 3.5 J/cm². Ideally a single laser pulse will be sufficient to ablate cellular material for analysis, such that the laser pulse frequency matches the frequency with which ablation plumes are generated. Lasers will usually be excimer or exciplex lasers. Suitable results can be obtained using an argon fluoride laser (λ = 193 nm). Using an aperture of 25 μηη this laser can be imaged by 25-fold demagnification onto the tissue samples to give a spot size with a 1 μηη diameter. Pulse durations of 10-15 ns with these lasers can achieve adequate ablation. Femtosecond lasers (i.e. with pulse durations <1 ps) can also be used, and would be beneficial due to reduced heat transfer into the sample, but they are very expensive and good imaging results can be achieved without them.

Overall, the laser pulse frequency and strength are selected in combination with the response characteristics of the MS detector to permit distinction of individual laser ablation plumes. In combination with using a small laser spot and an ablation cell having a short washout time, rapid and high resolution imaging is now feasible.

Constructing an image

LA-ICP-MS can provide signals for multiple labelling atoms in plumes. Detection of a label in a plume reveals the presence of its cognate target at the position of oblation. By generating a series of plumes at known spatial locations on the sample's surface the MS signals reveal the location of the labels on the sample, and so the signals can be used to construct an image of the sample. By labelling multiple targets with distinguishable labels it is possible to associate the location of labelling atoms with the location of cognate targets, so the invention can build complex images, reaching levels of multiplexing which far exceed those achievable using existing techniques. The inventors have shown that images generated by the methods of the invention can reproduce the staining patterns and the proportion of cells expressing a given marker as determined by IFM, thereby confirming the invention's suitability for imaging.

Ideally the image will be constructed by performing raster scanning of the laser over the tissue sample. The spacing of consecutive ablations in the raster scan (step size), and between adjacent lines in the raster scan, is ideally the same as the laser spot size which is used (e.g. 1 μηη spacing for a 1 μηη laser spot) in order to achieve complete coverage of a region of interest. In some embodiments, however, methods can use a step size which is smaller than the laser spot size (e.g. at least 2x, 4x, or 5x smaller) as this can lead to smaller ablation areas and thus improve imaging resolution. For achieving the scanning it is possible to move the laser, but it is usually more convenient to move the ablation cell (or the contents of the cell). The movement speed will depend on the ablation frequency and the raster spacing e.g. with 1 μηη raster spacing and 20 Hz ablation the ablation cell will have a translation speed of 20 μηι/β. Support stages which can achieve step sizes of 1 μηι of less are available e.g. with 500 nm or 200 nm step sizes (or even less).

Methods of the invention are generally used to create two-dimensional (2D) images of a sample, based on the contents of an ablated surface layer. 3D images of a tissue can be prepared by assembling stacks of 2D images (in a x,y plane) from sections of a single sample which are adjacent in the z-axis. As an alternative to assembling 2D images in this way, however, methods of the invention can also be used for direct 3D imaging. This can be achieved in various ways. For instance, if the ablation causes vaporisation with a substantially constant depth then repeated ablation at a single x,y point reveals progressively deeper information in the z-axis. If ablation does not have a substantially constant depth then the volume of ablated material can be measured (e.g. relative to a standard of known volume), and this volume can be easily converted to a z-axis depth. Where 3D imaging is performed it is possible to perform multiple z-axis ablations while x,y location is maintained ('drilling'), or to ablate a sample layer by layer (i.e. perform ablations of a x,y area before moving to a deeper z- axis layer). Layer-by-layer ablation is preferred. Accuracy of 3D imaging is limited by factors such as re-deposition of ablated material, the ability to maintain a constant ablation depth, and the ability of labels to penetrate into the sample, but useful results can still be achieved within the boundaries of these limitations.

Assembly of signals into an image will use a computer and can be achieved using known techniques and software packages. For instance, reference 3 used the GRAPHIS package from Kylebank Software, but other packages such as TERAPLOT can also be used. Imaging using MS data from techniques such as MALDI-MSI is known in the art e.g. reference 14 discloses the 'MSiReader' interface to view and analyze MS imaging files on a Matlab platform, and reference 15 discloses two software instruments for rapid data exploration and visualization of both 2D and 3D MSI data sets in full spatial and spectral resolution e.g. the 'Datacube Explorer' program.

Images obtained using methods of the invention can be further analysed e.g. in the same way that IHC results are analysed. For instance, the images can be used for delineating cell sub- populations within a sample, and can provide information useful for clinical diagnosis. Similarly, SPADE analysis can be used to extract a cellular hierarchy from the high-dimensional cytometry data which methods of the invention provide [16].

Labelling of the tissue sample

The invention provides images of samples which have been labelled with a plurality of different labelling atoms, wherein the labelling atoms are detected in laser-ablated plumes by ICP-MS. The reference to a plurality of different atoms means that more than one atomic species is used to label the sample. These atomic species can be distinguished using ICP-MS (e.g. they have different m/Q ratios), such that the presence of two different labelling atoms within a plume gives rise to two different MS signals.

The invention is suitable for the simultaneous detection of many more than two different labelling atoms, permitting multiplex label detection e.g. at least 3, 4, 5, 10, 20, 30, 32, 40, 50 or even 100 different labelling atoms. Labelling atoms can also be used in a combinatorial manner to even further increase the number of distinguishable labels. The examples demonstrate the use of 32 different labelling atoms in an imaging method, but LA-ICP-MS is intrinsically suitable for parallel detection of higher numbers of different atoms e.g. even over 100 different atomic species [10]. By labelling different targets with different labelling atoms it is possible to determine the cellular location of multiple targets in a single image.

Labelling atoms that can be used with the invention include any species that are detectable by LA-ICP-MS and that are substantially absent from the unlabelled tissue sample. Thus, for instance, ¹²C atoms would be unsuitable as labelling atoms because they are naturally abundant, whereas ¹¹C could in theory be used because it is an artificial isotope which does not occur naturally. In preferred embodiments, however, the labelling atoms are transition metals, such as the rare earth metals (the 15 lanthanides, plus scandium and yttrium). These 17 elements provide many different isotopes which can be easily distinguished by ICP-MS. A wide variety of these elements are available in the form of enriched isotopes e.g. samarium has 6 stable isotopes, and neodymium has 7 stable isotopes, all of which are available in enriched form. The 15 lanthanide elements provide at least 37 isotopes that have non-redundantly unique masses. Examples of elements that are suitable for use as labelling atoms include Lanthanum (La), Cerium (Ce), Praseodymium (Pr), Neodymium (Nd), Promethium (Pm), Samarium (Sm), Europium (Eu), Gadolinium, (Gd), Terbium (Tb), Dysprosium (Dy), Holmium (Ho), Erbium (Er), Thulium (Tm), Ytterbium (Yb), Lutetium (Lu), Scandium (Sc), and Yttrium (Y). For example, the invention can use any of the isotopes of the lanthanides as listed in Tables 1 to 5. In addition to rare earth metals, other metal atoms are suitable for detection by ICP-MS e.g. gold (Au), platinum (Pt), iridium (Ir), rhodium (Rh), bismuth (Bi), etc. The use of radioactive isotopes is not preferred as they are less convenient to handle and are unstable e.g. Pm is not a preferred labelling atom among the lanthanides.

In order to facilitate TOF analysis (see above) it is helpful to use labelling atoms with an atomic mass within the range 80-250 e.g. within the range 80-210, or within the range 100-200. This range includes all of the lanthanides, but excludes Sc and Y. The range of 100-200 permits a theoretical 101 -plex analysis by using different labelling atoms, while permitting the invention to take advantage of the high spectral scan rate of TOF MS. As mentioned above, by choosing labelling atoms whose masses lie in a window above those seen in an unlabelled sample (e.g. within the range of 100-200), TOF detection can be used to provide rapid imaging at biologically significant levels.

Labelling the tissue sample generally requires that the labelling atoms are attached to one member of a specific binding pair (sbp). This labelled sbp is contacted with a tissue sample such that it can interact with the other member of the sbp (the target sbp member) if it is present, thereby localising the labelling atom to a specific location in the sample. The method of the invention then detects the presence of the labelling atom at this specific location and translates this information into an image in which the target sbp member is present at that location. Rare earth metals and other labelling atoms can be conjugated to sbp members by known techniques e.g. reference 17 describes the attachment of lanthanide atoms to oligonucleotide probes for ICP-MS detection, reference 18 describes the use of ruthenium to label oligonucleotides, and Fluidigm Canada sells the MaxPar™ metal labelling kits which can be used to conjugate over 30 different labelling atoms to proteins (including antibodies).

Various numbers of labelling atoms can be attached to a single sbp member, and greater sensitivity can be achieved when more labelling atoms are attached to any sbp member. For example greater than 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100 labelling atoms can be attached to a sbp member. For example, monodisperse polymers containing multiple monomer units may be used, each containing a chelator such as DTPA. DTPA, for example, binds 3+ lanthanide ions with a dissociation constant of around 10^-6 M [1 ]. These polymers can terminate in a thiol- reactive group (e.g. maleimide) which can be used for attaching to a sbp member. For example the thiol-reactive group may bind to the Fc region of an antibody. Other functional groups can also be used for conjugation of these polymers e.g. amine-reactive groups such as N-hydroxy succinimide esters, or groups reactive against carboxyls or against an antibody's glycosylation. Any number of polymers may bind to each sbp member. Specific examples of polymers that may be used include straight-chain ("X8") polymers or third-generation dendritic ("DN3") polymers, both available as MaxPar™ reagents. Use of metal nanoparticles can also be used to increase the number of atoms in a label.

As mentioned above, labelling atoms are attached to a sbp member, and this labelled sbp member is contacted with the tissue sample where it can find the target sbp member (if present), thereby forming a labelled sbp. The labelled sbp member can comprise any chemical structure that is suitable for attaching to a labelling atom and then for imaging according to the invention.

In general terms, methods of the invention can be based on any sbp which is already known for use in determining the location of target molecules in tissue samples (e.g. as used in IHC or fluorescence in situ hybridisation, FISH), but the sbp member which is contacted with the sample will carry a labelling atom which is detectable by ICP-MS. Thus the invention can readily be implemented by using available IHC and FISH reagents, merely by modifying the labels which have previously been used e.g. to modify a FISH probe to carry a label which can be detected by ICP-MS.

The sbp may comprise any of the following: a nucleic acid duplex; an antibody/antigen complex; a receptor/ligand pair; or an aptamer/target pair. Thus a labelling atom can be attached to a nucleic acid probe which is then contacted with a tissue sample so that the probe can hybridise to complementary nucleic acid(s) therein e.g. to form a DNA DNA duplex, a DNA RNA duplex, or a RNA RNA duplex. Similarly, a labelling atom can be attached to an antibody which is then contacted with a tissue sample so that it can bind to its antigen. A labelling atom can be attached to a ligand which is then contacted with a tissue sample so that it can bind to its receptor. A labelling atom can be attached to an aptamer ligand which is then contacted with a tissue sample so that it can bind to its target. Thus labelled sbp members can be used to detect a variety of targets in a sample, including DNA sequences, RNA sequences, proteins, sugars, lipids, or metabolites.

In a typical embodiment of the invention the labelled sbp member is an antibody. Labelling of the antibody can be achieved through conjugation of one or more labelling atom binding molecules to the antibody, for example using the MaxPar™ conjugation kit as described above. Antibodies which recognise cellular proteins that are useful for imaging are already widely available for IHC usage, and by using labelling atoms instead of current labelling techniques (e.g. fluorescence) these known antibodies can be readily adapted for use in methods of the invention, but with the benefit of increasing multiplexing capability. Antibodies used with the invention can recognise targets on the cell surface or targets within a cell. Antibodies can recognise a variety of targets e.g. they can specifically recognise individual proteins, or can recognise multiple related proteins which share common epitopes, or can recognise specific post-translational modifications on proteins (e.g. to distinguish between tyrosine and phospho- tyrosine on a protein of interest, to distinguish between lysine and acetyl-lysine, to detect ubiquitination, etc). After binding to its target, labelling atom(s) conjugated to an antibody can be detected to reveal the location of that target in a sample.

The labelled sbp member will usually interact directly with a target sbp member in the sample. In some embodiments, however, it is possible for the labelled sbp member to interact with a target sbp member indirectly e.g. a primary antibody may bind to the target sbp member, and a labelled secondary antibody can then bind to the primary antibody, in the manner of a sandwich assay. Usually, however, the invention relies on direct interactions, as this can be achieved more easily and permits higher multiplexing. In both cases, however, a sample is contacted with a sbp member which can bind to a target sbp member in the sample, and at a later stage label attached to the target sbp member is detected.

One feature of the invention is its ability to detect multiple (e.g. 10 or more, and even up to 100 or more) different target sbp members in a sample e.g. to detect multiple different proteins and/or multiple different nucleic acid sequences. To permit differential detection of these target sbp members their respective sbp members should carry different labelling atoms such that their signals can be distinguished by ICP-MS. For instance, where ten different proteins are being detected, ten different antibodies (each specific for a different target protein) can be used, each of which carries a unique label, such that signals from the different antibodies can be distinguished. In some embodiments, it is desirable to use multiple different antibodies against a single target e.g. which recognise different epitopes on the same protein. Thus a method may use more antibodies than targets due to redundancy of this type. In general, however, the invention will use a plurality of different labelling atoms to detect a plurality of different targets.

If more than one labelled antibody is used with the invention, it is preferable that the antibodies should have similar affinities for their respective antigens, as this helps to ensure that the relationship between the quantity of labelling atoms detected by LA-ICP-MS and the abundance of the target antigen in the tissue sample will be more consistent across different sbp's (particularly at high scanning frequencies).

If a target sbp member is located intracellularly it will typically be necessary to permeabilize cell membranes before or during contacting of the sample with the labels. For example when the target is a DNA sequence but the labelled sbp member cannot penetrate the membranes of live cells, the cells of the tissue sample can be fixed and permeabilised. The labelled sbp member can then enter the cell and form a sbp with the target sbp member. In this respect, known protocols for use with IHC and FISH can be utilised. Usually, a method of the invention will detect at least one intracellular target and at least one cell surface target. In some embodiments, however, the invention can be used to detect a plurality of cell surface targets while ignoring intracellular targets. Overall, the choice of targets will be determined by the information which is desired from the method, as the invention will provide an image of the locations of the chosen targets in the sample.

Tissue samples

The invention provides a method of imaging a tissue sample. The tissue sample comprises a plurality of interacting cells, and the method subjects a plurality of these cells to laser ablation in order to provide an image of these cells in the tissue sample. In general, the invention can be used to analyse tissue samples which are now studied by IHC techniques, but with the use of labels which are suitable for detection by LA-ICP-MS.

Any suitable tissue sample can be used in the methods described herein. For example, the tissue can be epithelium tissue, muscle tissue, nerve tissue, etc., and combinations thereof. For diagnostic or prognostic purposes the tissue can be from a tumor. In some embodiments a sample may be from a known tissue, but it might be unknown whether the sample contains tumor cells. Imaging can reveal the presence of targets which indicate the presence of a tumor, thus facilitating diagnosis. The tissue sample may comprise breast cancer tissue, for example human breast cancer tissue or human mammary epithelial cells (HMLE). The tissue sample may comprise formalin-fixed, paraffin-embedded (FFPE) tissue. The tissues can be obtained from any living multicellular organism, but will usually be human.

The tissue sample will usually be a section e.g. having a thickness within the range of 2-10 μηη, such as between 4-6 μm . Techniques for preparing such sections are well known from the field of IHC e.g. using microtomes, including dehydration steps, including embedding, etc. Thus a tissue may be chemically fixed and then sections can be prepared in the desired plane. Cryosectioning or laser capture microdissection can also be used for preparing tissue samples. Samples may be permeabilised e.g. to permit of reagents for labelling of intracellular targets (see above).

The size of a tissue sample to be analysed will be similar to current IHC methods, although the maximum size will be dictated by the laser ablation apparatus, and in particular by the size of sample which can fit into its ablation cell. A size of up to 5 mm x 5 mm is typical, but smaller samples (e.g. 1 mm x 1 mm) are also useful (these dimensions refer to the size of the section, not its thickness).

In addition to being useful for imaging tissue samples, the invention can instead be used for imaging of cellular samples such as monolayers of adherent cells or of cells which are immobilised on a solid surface (as in conventional immunocytochemistry). These embodiments are particularly useful for the analysis of adherent cells that cannot be easily solubilized for cell- suspension mass cytometry. Thus, as well as being useful for enhancing current immunohistochemical analysis, the invention can be used to enhance immunocytochemistry.

After being prepared, the sample will be placed into a laser ablation cell and then subjected to analysis according to the invention. Single cell analysis

Methods of the invention include laser ablation of multiple cells in a sample, and thus plumes from multiple cells are analysed and their contents are mapped to specific locations in the sample to provide an image. In most cases a user of the method will need to localise the signals to specific cells within the sample, rather than to the sample as a whole. To achieve this, the boundaries of cells (e.g. the plasma membrane, or in some cases the cell wall) in the sample can be demarcated.

Demarcation of cellular boundaries can be achieved in various ways. For instance, a sample can be studied using conventional techniques which can demarcate cellular boundaries, such as microscopy. An image of this sample can then be prepared using a method of the invention, and this image can be superimposed on the earlier results, thereby permitting the LCP-MS signals to be localised to specific cells.

To avoid the need to use multiple techniques, however, it is possible to demarcate cellular boundaries as part of the imaging method of the invention. Such boundary demarcation strategies are familiar from IHC and immunocytochemistry, and these approaches can be adapted by using labels which can be detected by ICP-MS. For instance, the method can involve labelling of target molecule(s) which are known to be located at cellular boundaries, and signal from these labels can then be used for boundary demarcation. Suitable target molecules include abundant or universal markers of cell boundaries, such as members of adhesion complexes (e.g. β-catenin or E-cadherin). Some embodiments can label more than one membrane protein in order to enhance demarcation.

In addition to demarcating cell boundaries by including suitable labels, it is also possible to demarcate specific organelles in this way. For instance, antigens such as histones (e.g. H3) can be used to identify the nucleus, and it is also possible to label mitochondrial-specific antigens, cytoskeleton-specific antigens, Golgi-specific antigens, ribosome-specific antigens, eic, thereby permitting cellular ultrastructure to be analysed by methods of the invention.

Signals which demarcate the boundary of a cell (or an organelle) can be assessed by eye, or can be analysed by computer using image processing. Such techniques are known in the art for other imaging techniques e.g. reference 19 describes a segmentation scheme that uses spatial filtering to determine cell boundaries from fluorescence images, reference 20 discloses an algorithm which determines boundaries from brightfield microscopy images, reference 21 discloses the CellSeT method to extract cell geometry from confocal microscope images, and reference 22 discloses the CellSegm MATLAB toolbox for fluorescence microscope images. A method which is useful with the invention uses watershed transformation and Gaussian blurring. These image processing techniques can be used on their own, or they can be used and then checked by eye.

Once cellular boundaries have been demarcated it is possible to allocate signal from specific target molecules to individual cells. It can also be possible to quantify the amount of a target analyte(s) in an individual cell e.g. by calibrating the methods against quantitative standards. Methods of the invention are highly quantitative. In comparison with known methods they do not suffer from sample autofluorescence, there are minimal or no matrix effects as compared to those common in MALDI and SIMS imaging, there is no need for an amplification step such as is often applied in IHC, the tissue can be completely sampled, and the methods has a wide dynamic range of ~10⁵.

Combinations with other techniques

Methods of the invention can be combined with other imaging techniques, and images obtained from the different techniques can be combined to give a richer composite image. For instance, a sample might first be imaged by a conventional technique such as microscopy using fluorescent and/or visible labels (e.g. IHC analysis). As such techniques are non-destructive, and as their labels generally do not include atoms which give useful LCP-MS signals (typically they are made of the same atoms as the sample itself; if they do contain atoms which would be visible in a MS spectrum then their presence can easily be compensated for in the MS step e.g. by not using these as labelling atoms), the sample can then be imaged by a method of the invention, and the microscopy and mass cytometry results can be used in combination.

If a method of the invention is combined with another destructive imaging technique (e.g. MALDI imaging [23]) then it is preferred that the two techniques are used on adjacent sections of the same tissue.

General

The term "comprising" encompasses "including" as well as "consisting" e.g. a composition "comprising" X may consist exclusively of X or may include something additional e.g. X + Y.

The term "about" in relation to a numerical value x is optional and means, for example, x+10%.

The word "substantially" does not exclude "completely" e.g. a composition which is "substantially free" from Y may be completely free from Y. Where necessary, the word "substantially" may be omitted from the definition of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 a shows IFM on serial breast cancer tissue sections of the luminal HER2+ subtype (case no. 37) using unlabelled (left) and metal-labelled (right) antibodies recognizing five markers (from top to bottom: H3; HER2; CK8/18; E-Cad; Vim). Letters indicate the label color, where c=cyan, r=red, y=yellow

Figure 1 b shows IFM (left) and CyTOF imaging mass cytometry (right) on breast cancer tissue sections of the luminal HER2+ subtype (case nos. 210, 23 and 37) using metal-labelled antibodies recognizing the same five markers as Figure 1 a.

Figure 2a shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 210. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of cytokeratin 8/18 (red), H3 (cyan) and vimentin (yellow).

Figure 2b shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 210. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of cytokeratin 7 (red), H3 (cyan) and CD44 (yellow). Figure 2c shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 210. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of pan-actin (red), progesterone receptor (blue) and CD68 (yellow).

Figure 2d shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 23. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of HER2 (red), H3 (cyan) and vimentin (yellow).

Figure 2e shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 23. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of E-cadherin (red), cytokeratin 7 (yellow) and phosphorylation on S235/S236 on S6 (blue).

Figure 2f shows a mass cytometry image of a luminal HER2+ breast cancer tissue sample, case no. 23. A total of 32 proteins and phosphorylation sites were measured simultaneously at 1 -μηι resolution (tables 1 and 2). Overlay of β-catenin (red), estrogen receptor (blue) and CD68 (yellow). Scale bars, 25 μηι.

Figure 3 shows analysis of adherent cells by imaging mass cytometry (top two rows; C) or IFM (bottom two rows; IFM). The micrographs show human mammary epithelial cells labelled and imaged as indicated with metal-labelled antibodies recognizing a panel of phosphorylated residues (from left to right: PLCv2, pY759; ERK, pT202/pY204; p38, pT180/pY182; S6, pS235/pS236), either with (rows 1 & 3; +) or without (rows 2 & 4; -) a 30-min treatment with the tyrosine phosphatase inhibitor vanadate. Scale bars, 25 μηη. Exposure was kept constant for each control-stimulated comparison but not between different antibodies.

Figure 4a shows a SPADE tree identifying overlapping cell populations with the indicated marker patterns. Light gray areas contain cells with low marker expression in all channels. Vim, vimentin; E-Cad, E-cadherin; CK8/18, cytokeratin 8/18; CK7, cytokeratin 7; β-Cat, β-catenin; ER, estrogen receptor; CAH IX, carbonic anhydrase IX; PR, progesterone receptor; med, medium.

Figure 4b shows a cluster tree showing the CD20 side population for tumor case no. 201 . The colors indicate the expression level of indicated marker, and the size of the node corresponds to the percentage of cells from a given patient that fell within a cell cluster.

Figures 4c to 4i show cluster trees showing the cell subpopulations of a HER2+ sample. Case numbers are (c) 359 (d) 254 (e) 210 (f) 199 (g) 201 (h) 294 (i) 276, which is a luminal sample.

Figure 5 shows signal separation of ablation chamber at 20 Hz. The shown signal is the summed intensity of all isotopes of interest. Counts were summed over all measured channels.

Figure 6 shows a comparison of the specificity of metal-labelled antibodies analyzed by IFM (left) and CyTOF imaging mass cytometry (right) on breast cancer tissue sections of the Luminal HER2+ subtype (PR case no. 210, HER2 and cytokeratin 8/18 case no. 23). Hoechst 33258 and H3 are shown in cyan and the three specific markers in red (top: PR; middle: Her2; bottom: CK8/18). The scale maxima indicating the counts per laser shot were adjusted as follows: H3, 200 (case no. 210) and 400 (case no. 23); PR, 10; HER2, 50; cytokeratin 8/18, 30. The white size bars in the images indicate 25 μm .

Figure 7a shows an image of tissue no. 210 showing overlay of β-catenin (red), H3 (cyan), and pS6 (yellow). For figures 7a-d the scale maxima indicating the counts per laser shot were adjusted as follows: pS6, 15 (tissue no. 210) and 20 (tissue no. 23); H3, 200 (tissue no. 210) and 400 (tissue no. 23); β-catenin, 20; HER2, 30; CAH IX, 15; E-Cadherin, 20; vimentin, 400; Cytokeratin 8/18, 25. The white size bars in the images indicate 25 μm .

Figure 7b shows an image of tissue no. 210 showing overlay of HER2 (red), H3 (cyan), and CAH IX (yellow).

Figure 7c shows and image of tissue no. 210 showing overlay of E-cadherin (red), H3 (cyan), and vimentin (yellow).

Figure 7d shows an image of tissue no. 23 showing overlay of cytokeratin 8/18 (red), H3 (cyan), and phosphorylation on S6 (yellow).

Figures 8 A-E show IFM images of metal-labelled (top-left) and unlabelled antibodies (top-right) on serial sections of case no. 37. The single-cell intensity distributions of the IFM analysis of the metal-labelled antibody (bottom-left) and the unlabelled antibody (bottom-right) are shown, plotting intensity against events. Event numbers were not normalized. The mean signal is represented by the red line. The median signal is represented by the green square.

Figure 9a and 9b show a comparison between single-plex IHC (left two panels) and 32-plex imaging mass cytometry (right-hand panel) measurements. Sections of Luminal HER2+ tumor were used (case no. 210), but sections were not serial. The scale maxima indicating the counts per laser shot were adjusted as follows: HER2, 30; PR, 10; CK8/18, 80; H3, 200. The white size bars in the images indicate 25 μm .

MODES OF CARRYING OUT THE INVENTION

The examples presented below demonstrate an imaging technique that extends the multiplexed analysis capabilities of CyTOF-based mass cytometry to make spatially resolved measurements using LA-ICP-TOFMS. Further details are disclosed in reference 24 and its supplementary information (all incorporated herein by reference), including color copies of Figures 1 -4 and 6-9.

Example 1 - Imaging a tissue sample using mass cytometry

A workflow has been developed which couples mass cytometry, ICC and IHC analyses with a high-resolution laser ablation system to allow analysis of adherent cells and tissue sections with subcellular resolution of 1 μm .

In the first step, the cell sample or tissue section was prepared for antibody labelling using routine ICC and IHC protocols [25]. Antibodies were selected to target 32 proteins and protein modifications relevant to breast cancer. Before staining, antibodies were tagged with a unique rare-earth-metal isotope of defined atomic mass.

After air drying, the sample was positioned in the laser ablation chamber described in reference 7, which minimizes aerosol dispersion for high-resolution, high-throughput and highly sensitive analyses. The tissue was then ablated spot by spot and line by line, and the ablated material was then transported by a mixed argon and helium stream to a CyTOF mass cytometer.

Figure 5 shows that the signals of individual laser shots at 20 Hz, summed over all measured channels, were fully separated. The limit of detection was approximately six ion counts (corresponding to ~ 500 molecules), assuming Poisson statistics.

After data preprocessing, the 32 transient, single isotope signals were plotted using the coordinates of each single laser shot, and a high-dimensional image of the sample was generated by overlaying all analyzed measurement channels. Next, single-cell features were computationally segmented using a watershed algorithm, and the marker expression data were matched to individual cells. The single-cell data were used for all downstream data analyses and to investigate cell subpopulations within a set of 21 tumor and normal samples total from 20 breast cancer patients.

Patients and specimen characteristics

Tissue micro arrays (TMAs) contained FFPE breast cancer tissues of the major subtypes and normal breast tissues, as described previously [26]. All tumors analyzed by imaging mass cytometry were reevaluated by two experienced clinical pathologists by hematoxylin and eosin staining to identify representative areas. Tumor stage and Bloom-Richardson-Elston (BRE) grade were assigned according to the Union for International Cancer Control (UICC) and World Health Organization (WHO) criteria. Classification of breast cancer subtypes was based on IHC expression patterns of ER, PR and HER2. HER2 status was assessed by HER2 IHC and HER2 FISH [27].

Preparation of HMLE cells for imaging mass cytometry

Human mammary epithelial (HMLE) cells [28] were grown to -80% confluency on glass coverslips and were either mock treated or treated with 125 μΜ vanadate for 30 min at 37 °C. Cells were prepared for imaging mass cytometry and IFM using a standard ICC protocol [25].

Antibodies

Antibodies were obtained in carrier/protein-free buffer and then prepared using the MaxPar® antibody conjugation kit according to the manufacturer's instructions [29]. After we determined the percent yield by measurement of absorbance at 280 nm, the metal-labelled antibodies were diluted in a stabilization solution for long-term storage at 4 °C. Antibodies used in this study are listed in Tables 1 to 5.

Preparation of breast cancer tissue sections for IHC, IFM and imaging mass cytometry

All classical IHC stains of the TMA demonstrated in these examples were conducted on a Ventana Benchmark XT using Ventana prediluted antibodies, and standard protocols. Samples were stained for HER2, PR, cytokeratin 8/18 and H3. Exposure times for a given marker were kept constant for the comparative analysis of each antibody. Images were processed by ImageJ software.

Tissue no. 23 and FFPE breast cancer TMAs and corresponding healthy tissue were sectioned at a 5-μηι thickness for imaging mass cytometry. Sections were de-waxed overnight in xylene and rehydrated in a graded series of alcohol (ethanol absolute, ethanohdeionized water 90:10, 80:20, 70:30, 50:50, 0:100; 10 min each [30]). Heat-induced epitope retrieval was conducted in a water bath at 88 °C in Tris-EDTA buffer at pH 9 for 20 min. After immediate cooling, the TMA was blocked with 1 % BSA in PBS/0.1 % Triton X-100 for 30 min. For staining, TMA samples were incubated overnight at 4 °C with an antibody master mix (Tables 1 , 4 and 5). Samples were then washed five times with PBS/0.1 % Triton X-100.

For the TMA core no. 210 shown in Figures 1 b, 2 and 7, the following protocol was used: heat- induced epitope retrieval at 92-94 °C in Tris-EDTA buffer at pH 9 for 20 min. After immediate cooling, the TMA section was blocked with 3% BSA in TBS/0.1 % Triton X-100 for 45 min. TMA samples were incubated overnight at 4 °C with an antibody master mix (Table 2) containing all antibodies except for anti-pSHP2, anti-CD31 , anti-TWIST, anti-CD3, anti-SLUG, and anti-EGFR. After a wash step with 2x TBS/0.1 % Triton X-100 and 2x TBS, those antibodies were added, and samples were incubated 2.5 h at room temperature and then 1 h at 4 °C. After being washed, samples were dried at room temperature before imaging mass cytometry.

High-spatial resolution laser ablation

Tissue sections were analyzed by imaging mass cytometry, as discussed above. A modified ArF excimer GeoLas C laser system (Coherent) delivered a homogenized UV laser beam (λ = 193 nm) to an aperture of 25 μm , which was imaged by 25-fold demagnification on the tissue samples. The resulting laser beam of 1 μm in diameter and 3.5 J/cm² laser fluence was used to ablate the antibody-stained tissue at a frequency of 20 Hz. The resulting laser ablation crater of the tissue was ~1 μm in diameter (as determined by scanning electron microscopy). The translation speed of the laser ablation chamber was 20 μm /s. Individual line scans with 1 - μm distance were rastered in order to fully remove the tissue layer within the region of interest. The laser ablation chamber used to enable high-spatial resolution, high-sensitivity imaging on the laser ablation system is described in detail in ref. 7. The ablated sample aerosol was directly transported to a CyTOF mass cytometer by argon and helium gas flows. The CyTOF instrument settings were described previously [1 1 ,12] with CyTOF software version 5.1 .598.

Single-cell segmentation

Topological single-cell segmentation is necessary before single-cell protein expression analysis. To detect the cell boundaries in the images, the cell membrane proteins β-catenin, HER2 and cytokeratin 8/18 were incorporated into the experimental protocol; staining for the protein H3 was used to identify cell nuclei. Images showed well-aligned morphological cell boundaries and centers. Further cell segmentation was achieved by watershed transformation [31 ,32]. First, the membrane images and the negative nucleus image were overlaid to yield maximum cell- boundary information. Then the images were Gaussian blurred to minimize imaging artifacts and noise. Finally, watersheds were searched along the cell membranes with the Matlab imaging toolbox (Matlab R201 1 b). The best segmentation results were achieved with prior Gaussian blurring (kernel width of 3-4.5 pixels) and standard parameters for watersheds [31 ]. All single-cell boundaries were visually evaluated and corrected if necessary. The contents of the boundary masks were then subjected to single-cell analysis. Finally, single-cell marker expressions were normalized to the median H3 signal obtained from each image. Comparison of single-cell marker intensities

For immunofluorescence images, the single-cell segmentation was performed using a CellProfiler [33] segmentation pipeline. All intensities were rescaled from 0 to 1 , and outliers (<0.1 % sample size) were removed. For imaging mass cytometry data, the cell events extracted from the watershed algorithm were analyzed (see above). Preprocessing and further analysis were performed in Matlab 2013a using the Wilcoxon rank-sum test as an alternative to the Student's t-test, as normal distribution cannot be assumed. The positive and negative single cells were estimated by a globally defined threshold for each method. For each comparison one biological replicate was available.

Calculation of limit of detection

The limit of detection (LOD) was calculated for signals in a time duration identical to the integration time for a single laser shot (50 ms or one image pixel). The averaged background signals of most of the channels was less than one count per laser shot. On the basis of Poisson statistics, the LOD in ion counts was then determined according to the following formula [34]: LOD = 3.29 x S + 2.71 , where S is the s.d. of the background signal integrated in this time duration (S is assumed to be square root of the mean background; hence, conservatively estimated, S = 1 ). Therefore, the LOD of the image (mean background corrected) was estimated to be six counts per image pixel.

Data analysis and image visualisation

All data processing was performed using Matlab routines (Matlab R2012a). The transient signal data were exported from the mass cytometer in text format. The file consists of push numbers (i.e., time) in rows and mass channels in columns, and the measured values are given as ion counts. The recorded signals in each channel were integrated over 768 pushes, equivalent to a 10-ms time window (1 push ≈ 13 s). Subsequently, each laser-generated pulse (50-ms duration) in the transient signals was integrated into a single laser shot signal. Finally, images of each mass channel were reconstructed by plotting the laser shot signals in the same order they were recorded, line scan by line scan. For further data analysis, the mean background determined over a duration of ~1 s of each individual channel obtained before the first line scan started was subtracted from each individual image data set.

For visualization only, the images of each individual channel were upsampled to a width of 1 ,500 pixels, with the image ratio maintained using bicubic automatic resampling in Adobe Photoshop v.13. For image artifact correction, noise reduction was implemented in Adobe Photoshop v.13 with these settings: strength 5, preserve details 2%, reduce color noise 0% and sharpen details 40%. For PR (case nos. 23 and 210) and cleaved caspase 3 (case no. 210), "despeckle" and Gaussian blur (kernel width, 0.25 pixels) before upsampling were applied. For all data analysis steps, only raw data were used unless otherwise mentioned. For Figure 1 b the scale maximum indicating the counts per laser shot was adjusted for imaging mass cytometry as follows, from top to bottom: H3, 200; HER2, 30 and H3, 200; CK8/18, 80 and H3, 200; E- cadherin, 40 and H3, 400; vimentin, 80 and H3, 400. For Figure 2 the scale maximum indicating the counts per laser shot were adjusted as follows. Tissue no. 210: H3, 200; CK8/18, 80; vimentin, 400; CK7, 25; CD44, 50; PR, 10; pan-actin, 40; CD68, 20. Tissue no. 23: HER2, 50; H3, 400; vimentin, 100; E-cadherin, 30; cytokeratin 7, 25; pS6, 20; β-catenin, 40; ER, 40; and CD68, 10. For Figure 3 the maximum ion counts shown for each protein phosphorylation site were identical between treatment and control conditions, and the scale maximum indicating the counts per laser shot were adjusted as follows: PLCv2, 600; ERK, 100; p38, 60 and S6, 60.

Example 2 - Effect of labelling atoms on antibody specificity

Experiments were performed using FFPE breast cancer samples to determine if labelling of antibodies would interfere with their target specificity. Unlabelled and labelled antibodies were compared using IFM analysis on serial sections of tissues no. 210 and no. 37, which are from tumors of the same type. Figure 1 a shows that no apparent change in antibody specificity due to the metal labelling was observed.

Figure 1 a shows IFM on serial breast cancer tissue sections of the luminal HER2+ subtype (case no. 37) using unlabelled and metal-labelled antibodies recognizing the indicated markers.

Quantitative analysis showed that the differences of the mean single-cell fluorescence intensity of each marker between unlabelled and metal-labelled antibodies, although significant, were small. These differences were well within the range of the variability typically observed in experimental procedures and among serial tissue sections that are similar but not identical. The similarity between unlabelled and metal-labelled antibodies was further confirmed by the congruency of the single-cell marker fluorescence intensity distributions over the analyzed intensity range for all tested antibody pairs (Figures 8a-e).

Figures 8a-e show IFM images of metal-labelled and unlabelled antibody against H3, HER2, cytokeratin 8/18, E-cadherin, and vimentin, on serial sections of case no. 37. These images were used to quantitatively compare single-cell signal intensities. The single-cell intensity distributions of the IFM analysis of the metal-labelled antibody and the unlabelled antibody are comparable. Event numbers were not normalized.

Example 3 - Validation of the method of imaging by comparison with IFM

Images generated by mass cytometry reproduced the same staining patterns and the percentage of cells expressing a given marker as determined by IFM. IFM and imaging mass cytometry were used on tumor sections (no. 210 and no. 23) from the same luminal HER2+ subtype each; both methods gave antibody staining patterns expected for this subtype (Figure 1 b, Figure 6 and Tables 1 and 2). The marker H3, a nucleosomal DNA packaging protein is typically observed in the nuclei. Progesterone receptor (PR), a transcription factor activated in luminal breast cancer, HER2, an epidermal growth factor receptor family member, as well as cytokeratin 8/18 and the epithelial cell-cell junction component E-cadherin, are typically observed in the plasma membrane. Vimentin indicates the stromal compartment. These patterns are in agreement with antibody validation by others.

The percentages of tumor cells expressing the analyzed markers were similar in IFM and imaging mass cytometry on serial tissue sections. Figure 1 b shows 100% and 100% for H3, respectively; 75% and 79% for HER2; and 63% and 66% for cytokeratin 8/18. Figure 2 and Figure 7 show mass cytometry images of further markers.

Figure 1 b shows IFM and CyTOF imaging mass cytometry on breast cancer tissue sections of the luminal HER2+ subtype (case nos. 210, 23 and 37) using metal-labelled antibodies recognizing the indicated markers. E-cadherin (E-Cad) and vimentin (Vim) were not analyzed on serial sections.

Figure 6 shows comparison of the specificity of metal-labelled antibodies analysed by IFM and by CyTOF imaging mass cytometry on breast cancer tissue sections of the Luminal HER2+ subtype (PR case no. 210, HER2 and cytokeratin 8/18 case no. 23). No apparent changes in specificity were found.

Example 4 - Effect of multiplexing on antibody behaviour

Single-plex IHC, duplex IFM and 32-plex imaging mass cytometry analysis yielded congruent results. Single-plex IHC analysis using identical antibodies (cytokeratin 8/18 and H3) or using different antibody clones but against the same target (HER2 and PR) in the same luminal HER2+ tumor (no. 210), yielded similar staining patterns. For both IHC and imaging mass cytometry >90% of the epithelial cells expressed these markers as shown in Figure 9a and b. Sections of the same Luminal HER2+ tumour were used (case no.210) for mass cytometry and IHC shown in figure 9a and 9b, but the sections were not serial. No apparent difference in staining pattern was found. The scale maxima indicating the counts per laser shot were adjusted as follows: HER2, 30; PR, 10; CK8/18, 80; H3, 200. For Figure 9a, the same antibody clones for the imaging mass cytometry and IHC analysis were used. For Figure 9b, different antibody clones for the imaging mass cytometry and IHC analysis were used (imaging mass cytometry: HER2, BD (3B5); PR, Epitomics (EP2) and IHC: HER2, Ventana (4B5); PR, Ventana (1 E2)).

The antibodies measured in duplex in the IFM analysis showed comparable properties in terms of spatial distribution and the percentages of tumor cells expressing a given analyzed marker to those in the 32-plexed CyTOF analysis (Figure 1 b and Figure 6). Together, these results indicate that multiplexing did not lead to observable changes in antibody behaviour.

The results presented in these examples therefore show that imaging mass cytometry enables simultaneous and highly multiplexed tissue imaging with subcellular resolution. There were no apparent changes in specificity and performance between unlabelled and labelled antibodies, nor between antibodies used in single-plex IHC, duplex IFM and multiplex analyses using imaging mass cytometry.

Example 5 - Evaluation of an adherent cell line in an ICC protocol

Imaging mass cytometry was tested to determine whether it could be used to evaluate an adherent cell line in an ICC protocol. Analysis of 28 markers by imaging mass cytometry of mock-treated and phosphotyrosine phosphatase inhibitor-treated HMLE cells revealed the expected signaling responses. Table 3 shows the details of the markers and antibodies used in this analysis. Increased phosphorylation was observed on Y759 on PLCv2, T202 and Y204 on ERK1 (T184 and Y186 on ERK2) and T180 and Y182 on p38 as shown in Figure 3.

Figure 3 shows analysis of adherent cells by IFM and imaging mass cytometry. The micrographs shown in Figure 3 show human mammary epithelial cells labelled and imaged as indicated with antibodies recognizing a panel of phosphorylated residues, without ('control') and with ('stimulated') a 30-min treatment with the tyrosine phosphatase inhibitor vanadate. Exposure was kept constant for each control-stimulated comparison but not between different antibodies. Note that primary- and secondary-antibody detection were used for imaging mass cytometry and IFM, respectively.

The results attained for mass cytometry are consistent with data from an IFM analysis of similarly treated and prepared HMLE cells (Figure 3). For other non-tyrosine phosphorylation sites, including on S235 and S236 on S6, no induction was observed.

Therefore the methods of the invention are suitable for imaging adherent cell monolayers as well as ex vivo samples.

Example 6 - Analysis of tumour heterogeneity in breast cancer

In breast cancer, the expression of HER2, estrogen receptor (ER) and PR are used to define the main subtypes, including luminal HER2-, luminal HER2+, HER2+ and triple negative [35] and [36]. The methods of the invention were tested with the aims of (i) delineating cell subpopulation phenotypes using our multiplexed measurements and (ii) evaluating whether previously observed breast cancer heterogeneity within and between those subtypes could be detected using imaging mass cytometry [37], [38], and [39]. 32-plex imaging mass cytometry was used to analyse 21 FFPE samples on a tissue microarray (TMA) that had been previously classified by a pathologist into the main breast cancer subtypes or as normal.

Cell subpopulations and cell transitions were identified using spanning-tree progression analysis of density-normalized events (SPADE) [16]. For SPADE analysis of analyzed tumors, the cell events extracted from the watershed algorithm were analyzed on http://cytobank.org/ and using the software tool SPADE [16]. The following summarizes the SPADE algorithm within the context of this imaging-based single-cell analysis. First, density-dependent downsampling of all extracted cell events to a prespecified target number was performed. The following settings were implemented: Arcsinh Cofactor = 5, target number of clusters = 150, downsample to target number of events = 5. The analysis was run by using the software Cytoscape_v.2.8.3. The downsampled cell events were then clustered according to the expression of 19 markers (ER, PR, CD68, CD20, c-MYC, HER2, pAMPK, H3, pERK, pBad, CD44, β-catenin, vimentin, cytokeratin 7, CAH IX, E-cadherin, pS6, caspase 3 and cytokeratin 8/18) into phenotypically similar agglomerates of cells. Phenotypically similar agglomerates of cells were connected via edges to draw a minimum spanning tree. Next an upsampling step was performed to assign each cell event from the initial data set to the most representative agglomerate. Finally, the minimum spanning tree was projected in two dimensions, and circles of the tree representing cell agglomerates were colored by median intensity level of a given measured parameter allowing visualization of marker expression across the entire cellular hierarchy. For the SPADE trees representing the cell populations, the node size was given as percent total (for example, number of cells from a given image falling into a cell cluster). Attribute values used are: 0/5/7/15/maximum, node size: 60/120/150/200/200. In Figure 4, for HER2, the colour bar was set in the range 4-9 with steps 4/4.5/5/6/7/8.5/9. CD20-positive cell subpopulations are displayed, and the colour bar was set in the range 0-9 in the following steps: 1/3/5/6/7/8/9.

Figure 4 shows imaging mass cytometry analysis of tumor heterogeneity. 21 samples from 20 breast cancer patients were analyzed. The SPADE tree identifies overlapping cell populations with the indicated marker patterns. Light gray areas contain cells with low marker expression in all channels (Figure 4a). Figure 4b shows a cluster tree showing the CD20 side population for tumor case no. 201 . Figures 4c-g show HER2+ cell subpopulations by breast cancer subtype reflect the underlying heterogeneity of these cells: case nos. 359 (c), 254 (d), 210 (e), 199 (f) and 201 (g) are shown. Figures 4h-i show cluster trees showing the cell subpopulations of a HER2+ (case no. 294; h) and luminal HER2+ sample (case no. 276; i). The colors indicate the expression level of indicated marker, and the size of the node corresponds to the percentage of cells from a given patient that fell within a cell cluster.

The SPADE tree reflects stromal cell subpopulations expressing vimentin, epithelial tumor cell subpopulations expressing a wide range of markers, and CD20+ immune cells (Figure 4a and b). Levels of HER2 (Figure 4a,c-i), vimentin, PR, ER, β-catenin, carbonic anhydrase (CAH) IX, E-cadherin, c-MYC and others varied considerably (Figure 4a). Clear differences in expression were visible even within the same tumor, in particular for cytokeratin 8/18, cytokeratin 7, HER2 and E-cadherin staining (Figure 2). The identified cell subpopulations also partly reflected the expected breast cancer subtypes, as branches were driven by markers used for patient classification: for example, HER2+ and luminal HER2+ (Figure 4e,f,h,i).

The SPADE analysis partly reflected the tumor subtypes as can be seen in Figure 4. However, this does not detract from the powerful visualization capabilities of the SPADE tool for high dimensional single-cell data that allows manual assignment of cell subpopulations and therefore the delineation of a map of breast cancer cell subpopulations as shown above.

Seven samples were classified as either HER2+ or luminal HER2+. These samples populated the HER2-positive branches in the SPADE tree, but there were also unique subpopulations differing in cytokeratin 8/18, E-cadherin, β-catenin and c-MYC expression (Figure 4a). For example, luminal HER2+ tumor no. 210 (Figure 4e), which overexpressed c-MYC. These differences within the same breast cancer subtype indicate interpatient tumor heterogeneity (Figure 4e,f,h,i).

These modes of carrying out the invention demonstrate that mass cytometry enables simultaneous imaging of cell-type markers, signalling activity and hallmarks of cancer, such as hypoxia. Taken together, these analyses delineated breast cancer cell subpopulations present in the analyzed FFPE samples, identified their spatial arrangement, and revealed differences within the same patient and among patients with the same tumor classification.

It will be understood that the invention is described above by way of example only and modifications may be made whilst remaining within the scope and spirit of the invention.

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Table 2 - Antibodies used for tumor case no. 210 (Figures 1, 2 and 6)

Table 3 - Antibodies used for adherent cell imaging (Figure 3)

Table 4 - Antibodies used for tissue imaging (TMA 1)

Table 5 - Antibodies used for tissue imaging (TMA 2)

Claims

CLAIMS 1. A method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation with a subcellular resolution at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

2. A method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry using a time-of-flight mass analyser, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

3. A method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling at least four different target molecules in the tissue sample with different labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

4. A method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling a plurality of different target molecules in the tissue sample with a plurality of different labelling atoms, to provide a labelled tissue sample; (ii) demarcating individual cells in the sample; (iii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

5. A method of imaging a tissue sample comprising a plurality of cells, the method comprising steps of: (i) labelling one or more a target molecules in the tissue sample with labelling atoms, to provide a labelled tissue sample; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation at multiple known locations using a laser spot size of 4 μηη or less, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

A method of imaging a tissue sample comprising a plurality of cells, the method comprising

6.

steps of: (i) providing a labelled tissue sample in which a plurality of different target molecules have been labelled with a plurality of different labelling atoms; (ii) subjecting multiple cells of the labelled tissue sample to laser ablation with a subcellular resolution at multiple known locations, to form a plurality of plumes; and (iii) subjecting plumes to inductively coupled plasma mass spectrometry, whereby detection of labelling atoms in the plumes permits construction of an image of the tissue sample.

7. The method of any preceding claim, wherein the image has a resolution of less than 2μη"ΐ.

8. The method of any preceding claim, wherein the image has a subcellular resolution and laser ablation of the sample occurs at a frequency of at least 10 Hz.

9. The method of any preceding claim, wherein the laser ablation uses a laser spot size within the range of 0.2 - 2 μηη.

10. The method of any preceding claim, wherein laser ablation occurs in an ablation cell having a washout time of 100 ms or less.

1 1 . The method of claim 10, wherein laser ablation occurs (i) in an ablation cell having a washout time of 30 ms or less (ii) at a frequency of at least 20 Hz.

12. The method of any preceding claim, wherein the laser has a fluence of 2-5 J/cm².

13. The method of any preceding claim, wherein the laser is an excimer or exciplex laser.

14. The method of any preceding claim, wherein at least 20 (e.g. at least 30, or at least 50) different labelling atoms having different atomic masses are used.

15. The method of any preceding claim, wherein the labelling atoms are substantially absent from the sample prior to labelling.

16. The method of any preceding claim, wherein the labelling atoms are transition metals such as lanthanides.

17. The method of any preceding claim, wherein the labelling atoms have atomic masses within the range 80-250.

18. The method of any preceding claim, wherein the mass spectrometry step uses time-of-flight detection.

19. The method of any preceding claim, wherein target molecules are labelled with metal- conjugated antibodies and/or with metal-conjugated nucleic acid probes.

20. The method of any preceding claim, wherein at least one intracellular target and at least one cell surface target are labelled.

21 . The method of any preceding claim, wherein the tissue sample is from a tumor or contains tumor cells.

22. The method of any preceding claim, wherein the tissue sample is a section.

23. The method of any preceding claim, wherein laser ablation occurs by raster scanning.

24. The method of claim 23, wherein the raster scanning has a step size which is substantially the same as the laser spot size.

25. The method of any preceding claim, wherein individual cells in the sample are demarcated.

26. The method of any preceding claim, wherein target molecules are quantified.

27. The method of any preceding claim, wherein the sample is analysed by microscopy before being subjected to laser ablation.

28. A method of labelling a tissue sample with four or more transition metals (e.g. rare earth metals) having different atomic masses.

29. A method of imaging a tissue sample, wherein multiple cells of the tissue sample are subjected to mass cytometry at a subcellular resolution.

30. A method of imaging a tissue sample, wherein multiple cells of the tissue sample are subjected to LA-ICP-TOFMS at a subcellular resolution.

31 . The method of any preceding claim, for imaging a monolayer of adherent cells or for imaging cells immobilised on a solid surface, instead of imaging a tissue sample.