Non-enzymatic dissociation of FFPE tissue and generation of single cells with intact cell surface markers

Abstract

The present disclosure is directed to a non-enzymatic dissociation method which facilitates the dissociation of one or more formalin-fixed paraffin-embedded tissue samples into dissociated single cells. The present disclosure is also directed to methods of single cell analysis, i.e., methods of analyzing and / or measuring target components (e.g., biomolecules such as, but not limited to, polypeptides, polynucleotides, small molecules, and the like) on or in cells non-enzymatically dissociated from one or more FFPE tissue samples.

Description

NON-ENZYMATIC DISSOCIATION OF FFPE TISSUE AND GENERATION OF SINGLE CELLS WITH INTACT CELL SURFACE MARKERSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] The present disclosure claims the benefit of the filing date of United States Provisional Patent No. 63 / 563,587 filed on March 11, 2024, and United States Provisional Patent Application No. 63 / 636,128 filed on April 19, 2024, the disclosures of which are hereby incorporated by reference herein in their entireties.FIELD OF THE DISCLOSURE

[0002] The present disclosure generally relates to methods of processing a formalin-fixed paraffin embedded biological sample to obtain intact single cells.BACKGROUND OF THE DISCLOSURE

[0003] Cancer is a disease marked by the uncontrolled proliferation of abnormal cells. In normal tissue, cells divide and organize within the tissue in response to signals from surrounding cells, resulting in normal cellular behavior that is carefully orchestrated by the tissue context. Cancer cells do not respond to growth-limiting contextual cues from the surrounding tissue, and they often harbor genetic alterations that drive them to proliferate and form a tumor. As the growth of a tumor progresses, genetic and phenotypic alterations continue to accumulate, allowing populations of cancer cells to overcome additional "checkpoints," such as an anti-tumor immune response, and manifesting as a more aggressive growth phenotype of the cancer cells. If left untreated, metastasis, the spread of cancer cells to distant areas of the body by way of the lymphatic system or bloodstream, may ensue. Metastasis results in the formation of secondary tumors at multiple sites, damaging healthy tissue. Most cancer death is caused by such secondary tumors. Timely diagnosis and treatment of cancer enhances the likelihood of a successful outcome.

[0004] A large repository of biological information is stored in preserved samples, such as formalin-fixed paraffin embedded (FFPE) tissue samples. Such FFPE tissue samples are routinely obtained during surgery, such as surgery to excise a diseased or damaged tissue from a patient. Ploidy and S-phase percentage, derived from the DNA content measurement, are thought to be prognostic biomarkers that can guide cancer treatment. To facilitate the measurement of DNA content in FFPE tissue samples, protocols were developed in the early 1980s to dissociate cellsfrom the FFPE tissue samples. These protocols, which require the use of enzymes to digest the extracellular matrix and liberate cells, produce a dissociation product including nuclei and / or cells missing cell surface markers. As a result, cytoplasmic markers were exclusively used to differentiate cancer from normal nuclei prior to the flow cytometric analysis. Staining dissociated particles from FFPE tissue samples with cell surface markers, such as CD45, CD3, CD8, etc., has not been reported.BRIEF SUMMARY OF THE DISCLOSURE

[0005] The present disclosure is directed to methods of non-enzymatically processing a FFPE tissue sample (e.g., tissue sections / curls, whole FFPE blocks, tissue biopsies, and / or tissue cores) to obtain intact single cells. Applicant has unexpectedly discovered that FFPE tissue samples which have been non-enzymatically dissociated according to the methods described herein provide for a composition including intact single cells, where the cells substantially retain their cell surface biomarkers. Applicant has found that the intact cells non-enzymatically dissociated according to the methods of the present disclosure are capable of being stained for the presence of one or more biomarkers, such as CD3, CD45, CD8, and CD20. Additionally, Applicant has discovered that intact single cells non-enzymatically dissociated from FFPE tissue samples according to the methods described herein facilitate downstream cytometric and / or sequence analysis. Applicant has further discovered that the developed non-enzymatically dissociation methods generate cells with intact cell membranes at a yield comparable or higher than the previously published enzymatic dissociation protocols. These and other concepts are described further herein.

[0006] A first aspect of the present disclosure is a method of generating a single cell composition, including: obtaining one or more FFPE tissue samples; and performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition. In some embodiments, the single cell composition includes no exogeneous enzymes. In some embodiments, no enzymes are added to the obtained one or more FFPE tissue samples during the performance of the one or more non-enzymatic dissociation processes. In some embodiments, the single cell composition includes a suspension. In some embodiments, the single cell composition includes a pellet.

[0007] In some embodiments, one or more histological examinations are performed on the obtained one or more FFPE tissue samples prior to performing the one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples. In some embodiments, a determination is made as to whether to perform the one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples based on results of the one or more histological examinations. In some embodiments, the one or more histological examinations include at least one of an immunocytochemical analysis (e.g., an immunohistochemical analysis, an in-situ hybridization analysis) and a morphological analysis.

[0008] In some embodiments, the one or more FFPE tissue samples are tissue sections. In some embodiments, the one or more FFPE tissue samples are tissue curls. In some embodiments, the one or more FFPE tissue samples are tumor blocks. In some embodiments, the one or more FFPE tissue samples are tissue cores. In some embodiments, the one or more FFPE tissue samples are tissue biopsies.

[0009] In some embodiments, at least 75% of the cells within the generated single cell composition are present as individual cells. In some embodiments, at least 80% of the cells within the generated single cell composition are present as individual cells. In some embodiments, at least 85% of the cells within the generated single cell composition are present as individual cells. In some embodiments, at least 90% of the cells within the generated single cell composition are present as individual cells. In some embodiments, at least 95% of the cells within the generated single cell composition are present as individual cells. In some embodiments, less than about 5% of the cells within the generated single cell composition are clustered or clumped together. In some embodiments, less than about 1% of the cells within the generated single cell composition are clustered or clumped together.

[0010] In some embodiments, the cells within the generated single cell composition retain at least 80% of their cell surface biomarkers. In some embodiments, the cells within the generated single cell composition retain at least 90% of their cell surface biomarkers. In some embodiments, the cells within the generated single cell composition retain at least 95% of their cell surface biomarkers. In some embodiments, the cells within the generated single cell composition retain at least 97% of their cell surface biomarkers. In some embodiments, the cells within the generated single cell composition retain at least 98% of their cell surface biomarkers. In some embodiments,the cells within the generated single cell composition retain at least 99% of their cell surface biomarkers.

[0011] In some embodiments, the one or more non-enzymatic dissociation processes are performed in the presence of one or more buffers and / or non-enzymatic cell conditioning agents. In some embodiments, one or more buffers and / or conditioning agents are added to the obtained one or more FFPE tissue samples prior to performing the one or more non-enzymatic dissociation processes. In some embodiments, one or more additional buffers and / or cell conditioning agents are added after performing each of the one or more non-enzymatic dissociation processes.

[0012] In some embodiments, the one or more non-enzymatic dissociation processes include one or more mechanical dissociation processes. In some embodiments, the one or more non-enzymatic dissociation processes include at least one mechanical dissociation process and at least one filtration process. In some embodiments, the performing of one or more non-enzymatic dissociation processes include (i) performing one or more mechanical dissociation processes on the obtained one or more FFPE tissue samples to provide one or more mechanically dissociated samples; and (ii) performing one or more filtration processes on the one or more mechanically dissociated samples. In some embodiments, no enzymes are added (a) to the one or more FFPE tissue samples during the performance of the one or more mechanical dissociation processes, or (b) to the mechanically dissociated sample during the performance of the one or more filtration processes. In some embodiments, the method further includes agitating and / or sonicating the one or more mechanically dissociated samples prior to and / or after performing the one or more filtration processes.

[0013] In some embodiments, the method further includes analyzing and / or measuring one or more biomolecules of the cells within the single cell composition. In some embodiments, one or more biomolecules are one or more polypeptides. In some embodiments, the polypeptides are enzymes, antigens, or antibodies. In some embodiments, the one or more biomolecules are one or more polynucleotides. In some embodiments, the one or more polynucleotides are single-stranded polynucleotides or double-stranded polynucleotides. In some embodiments, the one or more biomolecules are RNA, mRNA, cDNA, DNA, genomic DNA, microRNA, long noncoding RNA, ribosomal RNA, transfer RNA, mitochondrial DNA, and / or circular DNA.

[0014] In some embodiments, the analyzing and / or measuring of the one or more biomolecules of the cells within the single cell composition includes performing one of animmunoenzymatic analysis, cytometric analysis, a mass analysis, a chromatographic analysis, or a sequence analysis. In some embodiments, the sequence analysis includes single cell sequencing. In some embodiments, the single cell sequencing includes single cell genome sequencing. In some embodiments, the single cell sequencing includes single cell transcriptome sequencing. In some embodiments, the single cell sequencing includes single cell DNA methylome sequencing. In some embodiments, the sequence analysis comprises next-generation sequencing. In some embodiments, the sequence analysis comprises performing next-generation sequencing on one or more sorted populations of cells derived from the generated single cell composition.

[0015] In some embodiments, the method further includes identifying one or more therapeutic targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition. In some embodiments, the method further includes identifying one or more combination therapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition. In some embodiments, the method further includes identifying one or more immunotherapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition. In some embodiments, the method further includes identifying one or more neoantigens based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition. In some embodiments, the method further comprises determining at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, or therapeutic treatment strategy for at least one subj ect based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

[0016] In some embodiments, the method further includes staining the cells within the generated single cell composition for the presence of one or more biomarkers. In some embodiments, the one or more biomarkers are immune cell markers. In some embodiments, the one or more biomarkers are tumor cell markers. In some embodiments, the one or more biomarkers are normal cell markers. In some embodiments, the one or more biomarkers are tumor are cell surface markers. In some embodiments, the one or more biomarkers are immune checkpoint markers. In some embodiments, the one or more biomarkers are growth factor receptor markers. In some embodiments, the one or more biomarkers are hormone receptor markers. In some embodiments, the one or more biomarkers are tumor transcription factor markers. In someembodiments, the one or more biomarkers are intracellular signaling molecule markers. In some embodiments, the one or more biomarkers are fibroblast cell markers.

[0017] In some embodiments, the cells in the generated single cell composition are stained with a fluorescent moiety. In some embodiments, the cells in the generated single cell composition are stained with a chromogenic moiety. In some embodiments, the cells in the generated single cell composition are stained with 4',6-diamidino-2-phenylindole ("DAPI").

[0018] In some embodiments, the method further includes quantifying cells within the single cell composition staining positive for the one or more biomarkers. In some embodiments, the method further includes quantifying normal cells within the single cell composition. In some embodiments, the method further includes quantifying tumor cells within the single cell composition. In some embodiments, the method further includes quantifying immune cells within the single cell composition. In some embodiments, the method further includes identifying cancer cells by quantifying aneuploidy cells within the single cell composition.

[0019] In some embodiments, the method further includes sorting the cells within the single cell composition into one or more populations of cells (e.g., into a tumor cell population and a normal / immune cell population).

[0020] In some embodiments, the sorting is based on cell size. In some embodiments, the sorting is based on the expression of one or more biomarkers.

[0021] In some embodiments, the method further includes extracting one or more nucleic acid molecules from the cells of a tumor cell population. In some embodiments, the method further includes preparing a sequencing library based on the nucleic acid molecules extracted from the cells of the tumor cell population. In some embodiments, the method further includes extracting one or more nucleic acid molecules from the cells of a normal / immune cell population. In some embodiments, the method further includes preparing a sequencing library based on the nucleic acid molecules extracted from the cells of the normal / immune cell population.

[0022] In some embodiments, the method further includes sequencing one or more nucleic acid molecules of the cells of a tumor cell population. In some embodiments, the method further includes sequencing one or more nucleic acid molecules of the cells of a normal / immune cell population. In some embodiments, the sequencing includes single cell sequencing. In some embodiments, the single cell sequencing includes single cell genome sequencing. In some embodiments, the single cell sequencing includes single cell transcriptome sequencing. In someembodiments, the single cell sequencing includes single cell DNA methylome sequencing. In some embodiments, the sequencing includes next-generation sequencing. In some embodiments, the sequencing includes T-cell receptor sequencing (TCRseq). In some embodiments, the nextgeneration sequencing includes pyrosequencing, nanopore sequencing, sequencing-by-synthesis, sequencing-by-ligation, and single molecule real-time sequencing.

[0023] In some embodiments, the method further includes detecting, characterizing, or identifying one or more low prevalence genetic events. In some embodiments, the one or more low prevalence genetic events are selected from a point mutation, a deletion, an addition, a translocation, a genetic fusion, or an amplification of a gene. In some embodiments, the method further includes identifying one or more subclones. In some embodiments, the identified one or more subclones are one or more low prevalence subclones.

[0024] In some embodiments, the method further includes performing a polymerase chain reaction (PCR) on extracted nucleic acid molecules from one or more populations of cells within the generated single cell composition.

[0025] A second aspect of the present disclosure is a method of sequencing one or more nucleic acid molecules within a single cell composition, comprising: obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition; and sequencing one or more nucleic acid molecules of the cells within the generated single cell composition. In some embodiments, the sequencing includes single cell sequencing. In some embodiments, the single cell sequencing includes single cell genome sequencing. In some embodiments, the single cell sequencing includes single cell transcriptome sequencing. In some embodiments, the single cell sequencing includes single cell DNA methylome sequencing. In some embodiments, the sequencing includes next-generation sequencing. In some embodiments, the sequencing of the one or more nucleic acid molecules of the cells within the generated single cell composition generates one or more sequence data sets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more therapeutic targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more combination therapy targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more immunotherapy therapy targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more neoantigens. In some embodiments,the generated one or more sequence data sets are utilized to determine at least one clinical decision, wherein the at least one clinical decision includes determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, or therapeutic treatment strategy for at least one subject.

[0026] A third aspect of the present disclosure is a method of performing a cytometric analysis of cells within a single cell composition, comprising: obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition; and performing a cytometric analysis on the cells within the generated single cell composition. In some embodiments, the cytometric analysis includes flow cytometry. In some embodiments, the cytometric analysis includes fluorescence-activated cell sorting. In some embodiments, the cytometric analysis generates one or more cytometry data sets. In some embodiments, the data within the generated one or more cytometry data sets is gated, such as manually or automatically. In some embodiments, the generated one or more cytometry data sets are utilized to identify one or more therapeutic targets. In some embodiments, the generated one or more cytometry data sets are utilized to identify one or more combination therapy targets. In some embodiments, the generated one or more cytometry data sets are utilized to identify one or more immunotherapy therapy targets. In some embodiments, the generated one or more cytometry data sets are utilized to identify one or more neoantigens. In some embodiments, at least one clinical decision is determined based on the generated one or more cytometry data sets, wherein the at least one clinical decision includes determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

[0027] A fourth aspect of the present disclosure is a method of labeling cells within a single cell composition, comprising: obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition; and labeling one or more biomolecules within or on the surface of the cells in the generated single cell composition. In some embodiments, the one or more biomolecules are labeled using an immunocytochemical technique. In some embodiments, the one or more biomolecules are labeled with one or more detectable moieties. In some embodiments, the one or more detectable moieties are fluorescent moieties. In some embodiments, the one ormore detectable moieties are chromogenic moieties. In some embodiments, the one or more detectable moieties are mass tags. In some embodiments, the one or more biomolecules are labeled in a simplex assay. In some embodiments, the one or more biomolecules are labeled in a multiplex assay. In some embodiments, the cells within the generated single cell composition are sorted into one or more cell populations based on the labeling of the one or more biomolecules. In some embodiments, the cells within the generated single cell composition are quantified based on the labeling of the one or more biomolecules. In some embodiments, the labeled one or more biomolecules are quantified based on expression of the one or more biomolecules. In some embodiments, the labeled one or more biomolecules are scored, either manually or automatically.

[0028] In some embodiments, an analysis of the labeling of the one or more biomolecules is utilized to identify one or more therapeutic targets. In some embodiments, an analysis of the labeling of the one or more biomolecules is utilized to identify one or more combination therapy targets. In some embodiments, an analysis of the labeling of the one or more biomolecules is utilized to identify one or more immunotherapy therapy targets. In some embodiments, an analysis of the labeling of the one or more biomolecules is utilized to identify one or more neoantigens. In some embodiments, an analysis of the labeling of the one or more biomolecules is utilized to determine at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.BRIEF DESCRIPTION OF THE FIGURES

[0029] For a general understanding of the features of the disclosure, reference is made to the drawings. In the drawings, like reference numerals have been used throughout to identify identical elements.

[0030] FIG. 1A provides an overview of a non-enzymatic dissociation process and the potential outcome from various downstream analysis operations in accordance with one embodiment of the present disclosure.

[0031] FIG. IB provides a protocol overview for the non-enzymatic dissociation of FFPE tissue including deparaffinization and rehydration steps for (1) FFPE tissue curls; and (2) FFPE blocks in accordance with one embodiment of the present disclosure.

[0032] FIG. 1C provides an overview of a non-enzymatic dissociation process including the step of using the results of one or more histological examinations / evaluations to determine whether a single cell composition should be generated.

[0033] FIG. 2 provides an overview of tissue processing methods in accordance with one embodiment of the present disclosure, such as immunohistochemical methods and FFPE single cell analysis, which may be used, alone or in combination, to better understand pathology and improve clinical decision making.

[0034] FIG. 3 provides an overview of a non-enzymatic mechanical dissociation workflow in accordance with one embodiment of the present disclosure. In some embodiments, and depending on the FFPE tissue section / block, a second non-enzymatic dissociation may be utilized to obtain a homogenous single cell suspension.

[0035] FIG. 4 provides an overview of filtration steps which may be used to remove unwanted cellular material that would potentially interfere with downstream analysis.

[0036] FIG. 5 provides an example of downstream processing methods which may be applied to a generated single cell composition, including staining the cells within the single cell composition, sorting of the cells within the single cell composition, and / or sequencing genomic material obtained from the cells in the single cell composition.

[0037] FIG. 6 illustrates that the profiling of single cells via sequencing provides insight to genomic variants.

[0038] FIG. 7 provides a gating strategy which may be performed during flow cytometric analysis to select for intact single cells, (a) Dot plot for doublet discrimination; (b) DAPI histogram used to visualize DNA content / Ploidy.

[0039] FIGS. 8A - 8C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3.

[0040] FIGS. 9A - 9C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with Proteinase K for 30 seconds.

[0041] FIGS. 10A - 10C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with Proteinase K for 1 minute.

[0042] FIGS. 11A - 11C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with Proteinase K for 5 minutes.

[0043] FIGS. 12A - 12C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with Proteinase K for 10 minutes.

[0044] FIGS. 13A - 13C illustrate the percentage of positive cells (FIG. 13A), cell concentration (FIG. 13B), and cell size (FIG. 13C) over time after incubation with proteinase K.

[0045] FIGS. 14A - 14C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3.

[0046] FIGS. 15A - 15C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with liberase for 1 hour.

[0047] FIGS. 16A - 16C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with liberase for 3 hours.

[0048] FIGS. 17A - 17C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with liberase for 7 hours.

[0049] FIGS. 18A - 18C provide flow cytometry data of control samples including cells stained for the presence of CD45, CD20, or CD3, where the cells were incubated with liberase overnight.

[0050] FIGS. 19A - 19B illustrate and cell size (FIG. 13 A) and the percentage of positive cells (FIG. 13B) over time after incubation with liberase.

[0051] FIGS. 20A - 20C illustrate flow cytometry data of cells stained for the presence of CD45, CD3, or CD20 after non-enzymatic dissociation according to the methods of the present disclosure.

[0052] FIG. 21 provides examples of breast tumor samples, which have ranging scores of HERZ / HC? / expression, stained and analyzed with flow cytometry. The top row shows the negative control, which has no primary, and how the gate to detect the positive population has been drawn.The second row shows Cytokeratin 8&18 staining. The third row shows HER2 / MCM staining. The fourth row shows Ki67 staining.

[0053] FIG. 22 provides a graph comparing the normalized HER2+ percentage to the HER2 IHC scores. N=11, P values determined using two-way ANOVA; *p<0.05, **p<0.01.

[0054] FIG. 23 sets forth a plot showing individual Ki67 percentages from breast cancer FFPE curls compared to their respective IHC scores on slide. P value and R2value determined by linear regression analysis.

[0055] FIG. 24 provides a graph comparing Ki67 percentage from IHC slides and their respective flow analysis. P value determined by Mann-Whitney test.

[0056] FIGS. 25A and 25B illustrate plots of side scatter versus intensity.

[0057] FIGS. 26A - 26C illustrate that DNA content may be assessed via DAPI, allowing for doublet discrimination and ploidy analysis, while retaining surface marker expression.DETAILED DESCRIPTION

[0058] It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

[0059] As used herein, the singular terms "a," "an," and "the" include plural referents unless context clearly indicates otherwise. Similarly, the word "or" is intended to include "and" unless the context clearly indicates otherwise. The term "includes" is defined inclusively, such that "includes A or B" means including A, B, or A and B.

[0060] As used herein in the specification and in the claims, "or" should be understood to have the same meaning as "and / or" as defined above. For example, when separating items in a list, "or" or "and / or" shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as "only one of or "exactly one of," or, when used in the claims, "consisting of," will refer to the inclusion of exactly one element of a number or list of elements. In general, the term "or" as used herein shall only be interpreted as indicating exclusive alternatives (i.e., "one or the other but not both") when preceded by terms of exclusivity, such as "either," "one of," "only one of' or "exactly one of." "Consisting essentially of," when used in the claims, shall have its ordinary meaning as used in the field of patent law.

[0061] The terms "comprising," "including," "having," and the like are used interchangeably and have the same meaning. Similarly, "comprises," "includes," "has," and the like are used interchangeably and have the same meaning. Specifically, each of the terms is defined consistent with the common United States patent law definition of "comprising" and is therefore interpreted to be an open term meaning "at least the following," and is also interpreted not to exclude additional features, limitations, aspects, etc. Thus, for example, "a device having components a, b, and c" means that the device includes at least components a, b, and c. Similarly, the phrase: "a method involving steps a, b, and c" means that the method includes at least steps a, b, and c. Moreover, while the steps and processes may be outlined herein in a particular order, the skilled artisan will recognize that the ordering steps and processes may vary.

[0062] As used herein in the specification and in the claims, the phrase "at least one," in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, "at least one of A and B" (or, equivalently, "at least one of A or B," or, equivalently "at least one of A and / or B") can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

[0063] As used herein, the term "biological sample," "tissue sample," "specimen" or the like refers to any sample including a biomolecule (such as a protein, a peptide, a nucleic acid, a lipid, a carbohydrate, or a combination thereof) that is obtained from any organism including viruses. Other examples of organisms include mammals (such as humans; veterinary animals like cats, dogs, horses, cattle, and swine; and laboratory animals like mice, rats, and primates), insects, annelids, arachnids, marsupials, reptiles, amphibians, bacteria, and fungi. Biological samples include tissue samples (such as tissue sections and needle biopsies of tissue), cell samples (suchas cytological smears such as Pap smears or blood smears or samples of cells obtained by microdissection), or cell fractions, fragments, or organelles (such as obtained by lysing cells and separating their components by centrifugation or otherwise). Other examples of biological samples include blood, serum, urine, semen, fecal matter, cerebrospinal fluid, interstitial fluid, mucous, tears, sweat, pus, biopsied tissue (for example, obtained by a surgical biopsy or a needle biopsy), nipple aspirates, cerumen, milk, vaginal fluid, saliva, swabs (such as buccal swabs), or any material containing biomolecules that is derived from a first biological sample. In certain embodiments, the term "biological sample" as used herein refers to a sample (such as a homogenized or liquefied sample) prepared from a tumor or a portion thereof obtained from a subject.

[0064] As used herein, the term "biomarker" refers to any molecule or group of molecules found in a biological sample that can be used to characterize the biological sample or a subject from which the biological sample is obtained. For example, a biomarker may be a molecule or group of molecules whose presence, absence, or relative abundance is characteristic of a particular cell or tissue type or state; or characteristic of a particular pathological condition or state; or indicative of the severity of a pathological condition, the likelihood of progression or regression of the pathological condition, and / or the likelihood that the pathological condition will respond to a particular treatment. As another example, the biomarker may be a cell type or a microorganism (such as a bacterium, mycobacterium, fungus, virus, and the like), or a substituent molecule or group of molecules thereof.

[0065] As used herein, "clinical decision" refers to gathering information and integrating this information to draw diagnostic conclusions and / or determine one or more treatments to administer to a subject, such as a mammalian subject, such as a human patient. Such diagnostic conclusions may include the disease from which a subject suffers and what testing should be performed on the subject. In some embodiments, a clinical decision may also include determining disease prognosis, predicting recurrence of disease, predicting targets of therapy of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or a determination of a therapeutic treatment strategy for at least one subject.

[0066] As used herein, the term "clonal mutation" refers to a mutation present in the majority of cells.

[0067] As used herein, the terms "detectable moiety," "reporter moiety," "label" and / or "stain" mean a reagent that is capable of binding to an analyte, being internalized or otherwise absorbed, and being detected, e.g., through shape, morphology, color, fluorescence, luminescence, phosphorescence, absorbance, magnetic properties, or radioactive emission. Likewise, the terms "labeling," "staining," or the like as used herein generally refers to any treatment of a biological specimen that detects and / or differentiates the presence, location, and / or amount (such as concentration) of a particular molecule (such as a lipid, protein, or nucleic acid) or particular structure (such as a normal or malignant cell, cytosol, nucleus, Golgi apparatus, or cytoskeleton) in the biological specimen. For example, staining can provide contrast between a particular molecule or a particular cellular structure and surrounding portions of a biological specimen, and the intensity of the staining can provide a measure of the amount of a particular molecule in the specimen. Staining can be used to aid in the viewing of molecules, cellular structures, and organisms not only with bright-field microscopes, but also with other viewing tools, such as phase contrast microscopes, electron microscopes, and fluorescence microscopes. Some staining performed by the system can be used to visualize an outline of a cell. Other staining performed by the system may rely on certain cell components (such as molecules or structures) being stained without or with relatively little staining other cell components. Examples of types of staining methods performed by the system include, without limitation, histochemical methods, immunohistochemical methods, and other methods based on reactions between molecules (including non-covalent binding interactions), such as hybridization reactions between nucleic acid molecules. Staining methods include, but are not limited to, primary staining methods (e.g., H&E staining, Pap staining, etc.), enzyme-linked immunohistochemical methods, and in situ RNA and DNA hybridization methods, such as fluorescence in situ hybridization (FISH).

[0068] As used herein, "immunohistochemistry" or "IHC" refers to a method of determining the presence or distribution of an antigen in a sample by detecting interaction of the antigen with a specific binding agent, such as an antibody. A sample including an antigen is incubated with an antibody under conditions permitting antibody-antigen binding. Antibodyantigen binding can be detected by means of a detectable moiety conjugated to the antibody (direct detection) or by means of a detectable moiety conjugated to a secondary antibody, which is raised against the primary antibody (e.g., indirect detection). In some examples, IHC is utilized to detect the presence of or determine the amount of one or more proteins in a sample. IHC is furtherdescribes in International Publication No. WO2013019945, the disclosure of which is hereby incorporated by reference in its entirety.

[0069] As used herein, "in situ hybridization" or "ISH" references to a process of contacting a sample containing a target nucleic acid or a genomic target nucleic acid with a labeled probe specifically hybridizable or specific for the target nucleic acid. In some embodiments, the labeled probe (formulated in a suitable hybridization) and the sample are combined, under conditions and for sufficient time to permit hybridization to occur (typically to reach equilibrium). The chromosome preparation is washed to remove excess probe, and detection of specific labeling of the target is performed using standard techniques. IHC is further describes in International Publication No. WO2015124702, the disclosure of which is hereby incorporated by reference in its entirety.

[0070] As used herein, the term "neoantigen" is an antigen that is formed by peptides that are normally absent from the proteome of a cell. The term "antigen" is used herein as it is in art and means a molecule or portion thereof that induces the production of antibodies in an organism capable of antibody production. In some embodiments, the term "neoantigen" refers to a class of tumor antigens which arise from tumor-specific mutations in an expressed protein. In some embodiments, the neoantigen can be derived from any cancer, tumor, or cell thereof. In some embodiments, the term encompasses both a neoantigenic peptide and a polynucleotide encoding a neoantigenic peptide. Not all antigens can elicit an immune response, thus the term "antigenic" is not synonymous with "immunogenic." Likewise, the term "antigen" is not synonymous with "immunogen." As used herein, the neoantigens that are discovered using the methods of the present disclosure may or may not be immunogenic. In some embodiments, the neoantigens discovered using the methods of the present disclosure are immunogenic. In some embodiments, the neoantigens discovered using the methods of the present disclosure are not immunogenic to one host, e.g., a human host, but can be used to generate antibodies in other hosts to target them therapeutically. In some embodiments, the neoantigens of the present disclosure can be specific for each individual population of cells. For example, a population of cells obtained from one subject may contain neoantigens that are different from neoantigens contained in a population of cells obtained from a different subject. Thus, while the cells' DNA may be identical or nearly identical between two cell populations taken from different subjects, the neoantigens contained inthe cell populations could be different. Accordingly, the present disclosure can be applied to methods of personalized medicine.

[0071] As used herein, the term "next generation sequencing" refers to sequencing technologies having high-throughput sequencing as compared to traditional Sanger- and capillary electrophoresis-based approaches, wherein the sequencing process is performed in parallel, for example producing thousands or millions of relatively small sequence reads at a time. Some examples of next generation sequencing techniques include, but are not limited to, sequencing by synthesis, sequencing by ligation, and sequencing by hybridization. These technologies produce shorter reads (anywhere from about 25 - about 500 bp) but many hundreds of thousands or millions of reads in a relatively short time. Examples of such sequencing devices available from Illumina (San Diego, CA) include, but are not limited to iSEQ, MiniSEQ, MiSEQ, NextSEQ, NoveSEQ.

[0072] It is believed that the Illumina next-generation sequencing technology uses clonal amplification and sequencing by synthesis (SBS) chemistry to enable rapid sequencing. The process simultaneously identifies DNA bases while incorporating them into a nucleic acid chain. Each base emits a unique fluorescent signal as it is added to the growing strand, which is used to determine the order of the DNA sequence. A non-limiting example of a sequencing device available from ThermoFisher Scientific (Waltham, MA) includes the Ion Personal Genome Machine™ (PGM™) System.

[0073] It is believed that Ion Torrent sequencing measures the direct release of H+ (protons) from the incorporation of individual bases by DNA polymerase. A non -limiting example of a sequencing device available from Pacific Biosciences (Menlo Park, CA) includes the PacBio Sequel Systems. A non-limiting example of a sequencing device available from Roche (Pleasanton, CA) is the Roche 454. Next-generation sequencing methods may also include nanopore sequencing methods. In general, three nanopore sequencing approaches have been pursued: strand sequencing in which the bases of DNA are identified as they pass sequentially through a nanopore, exonuclease-based nanopore sequencing in which nucleotides are enzymatically cleaved one-by-one from a DNA molecule and monitored as they are captured by and pass through the nanopore, and a nanopore sequencing by synthesis (SBS) approach in which identifiable polymer tags are attached to nucleotides and registered in nanopores during enzyme- catalyzed DNA synthesis. Common to all these methods is the need for precise control of the reaction rates so that each base is determined in order.

[0074] Strand sequencing requires a method for slowing down the passage of the DNA through the nanopore and decoding a plurality of bases within the channel; ratcheting approaches, taking advantage of molecular motors, have been developed for this purpose. Exonuclease-based sequencing requires the release of each nucleotide close enough to the pore to guarantee its capture and its transit through the pore at a rate slow enough to obtain a valid ionic current signal. In addition, both methods rely on distinctions among the four natural bases, two relatively similar purines and two similar pyrimidines.

[0075] The nanopore SBS approach utilizes synthetic polymer tags attached to the nucleotides that are designed specifically to produce unique and readily distinguishable ionic current blockade signatures for sequence determination. In some embodiments, sequencing of nucleic acid molecules includes via nanopore sequencing includes preparing nanopore sequencing complexes and determining polynucleotide sequences. Methods of preparing nanopores and nanopore sequencing are described in U.S. Patent Application Publication No. 2017 / 0268052, and PCT Publication Nos. WO2014 / 074727, W02006 / 028508, WO2012 / 083249, and WO / 2014 / 074727, the disclosures of which are hereby incorporated by reference herein in their entireties. In some embodiments, tagged nucleotides may be used in the determination of the polynucleotide sequences (see, e.g., PCT Publication No. WO / 2020 / 131759, WO / 2013 / 191793, and WO / 2015 / 148402, the disclosures of which are hereby incorporated by reference herein in their entireties).

[0076] Analysis of the data generated by sequencing is performed using software and / or statistical algorithms that perform various data conversions, e.g., conversion of signal emissions into base calls, conversion of base calls into consensus sequences for a nucleic acid template, etc. Such software, statistical algorithms, and the use of such are described in detail, in U.S. Patent Application Publication Nos. 2009 / 0024331 2017 / 0044606 and in PCT Publication No. WO / 2018 / 034745, the disclosures of which are hereby incorporated by reference herein in their entireties.

[0077] As used herein, the term "polypeptides" includes proteins and fragments thereof. Polypeptides are disclosed herein as amino acid residue sequences. Those sequences are written left to right in the direction from the amino to the carboxy terminus. The amino acid residue sequences include, but are not limited to, Alanine (Ala, A), Arginine (Arg, R), Asparagine (Asn, N), Aspartic Acid (Asp, D), Cysteine (Cys, C), Glutamine (Gin, Q), Glutamic Acid (Glu, E),Glycine (Gly, G), Histidine (H is, H), Isoleucine (He, I), Leucine (Leu, L), Lysine (Lys, K), Methionine (Met, M), Phenylalanine (Phe, F), Proline (Pro, P), Serine (Ser, S), Threonine (Thr, T), Tryptophan (Trp, W), Tyrosine (Tyr, Y), and Valine (Vai, V). In addition, the polypeptide can include non-standard and / or non-naturally occurring amino acids, as well as other amino acids that may be found in phosphorylated and / or glycosylated proteins in organisms such as, but not limited to, animals, plants, insects, protists, fungi, bacteria, algae, single-cell organisms, and the like. The non-standard amino acids include, but are not limited to, selenocysteine, pyrrolysine, gamma- aminobutyric acid, carnitine, ornithine, citrulline, homocysteine, hydroxyproline, hydroxylysine, sarcosine, and the like. The non-naturally occurring amino acids include, but are not limited to, trans-3 -methylproline, 2,4-methanoproline, cis-4-hydroxyproline, trans-4-hydroxyproline, N- methyl-glycine, allo-threonine, methylthreonine, hydroxy-ethylcysteine, hydroxyethylhomocysteine, nitro-glutamine, homoglutamine, pipecolic acid, thiazolidine carboxylic acid, dehydroproline, 3- and 4-m ethylproline, 3, 3 -dimethylproline, tert-leucine, norvaline, 2-azaphenylalanine, 3 -azaphenylalanine, 4-azaphenylalanine, and 4- fluoropheny 1 al anine .

[0078] As used herein, the term "polynucleotide" generally refers to any polyribonucleotide or polydeoxyribonucleotide, which may be unmodified RNA or DNA or modified RNA or DNA. Thus, for instance, polynucleotides as used herein refers to, among others, single- and double-stranded DNA, DNA that is a mixture of single- and double-stranded regions, single- and double-stranded RNA, and RNA that is mixture of single- and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or a mixture of single- and double-stranded regions. The terms "nucleic acid," "nucleic acid sequence," or "oligonucleotide" also encompasses a polynucleotide as defined above. As used herein, the term polynucleotide includes DNAs or RNAs as described above that contain one or more modified bases. Thus, DNAs or RNAs with backbones modified for stability or for other reasons are "polynucleotides" as that term is intended herein. Moreover, DNAs or RNAs comprising unusual bases, such as inosine, or modified bases, such as tritylated bases, to name just two examples, are polynucleotides as the term is used herein.

[0079] As used herein, the terms "primary antibody" and "secondary antibody" refer to different antibodies, where a primary antibody is a polyclonal or monoclonal antibody from one species (rabbit, mouse, goat, donkey, etc.) that specifically recognizes an antigen (e.g., abiomarker) in a sample (e.g., a human biological sample) under study, and a secondary antibody is an antibody (usually polyclonal) from a different species that specifically recognizes the primary antibody, e.g., in its Fc region.

[0080] As used herein, the term "sequencing" refers to the determination of the order and position of bases in a nucleic acid molecule. More particularly, the term "sequencing" refers to biochemical methods for determining the order of the nucleotide bases, adenine, guanine, cytosine, and thymine, in a DNA oligonucleotide. Sequencing, as the term is used herein, can include without limitation parallel sequencing or any other sequencing method known of those skilled in the art, for example, chain-termination methods, rapid DNA sequencing methods, wandering-spot analysis, Maxam-Gilbert sequencing, dye- terminator sequencing, or using any other modern automated DNA sequencing instruments.

[0081] As used herein, the term "subclonal mutation" refers to a mutation present in less than 100% of cancer cells, typically less than 50%. A subclonal mutation can be present in the majority of a tumor (i.e., less than 100%, but greater than 50%) or in the minority of the tumor (i.e., less than 50%).

[0082] As used herein, the term "substantially" means a high degree of identity in quality or quantity, e.g., at least about 70%, or alternatively about 80%, or alternatively about 85%, or alternatively about 90%, or alternatively about 95%, or alternatively about 98%.

[0083] As used herein, the term "tumor" refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. In some embodiments, the tumor is a malignant cancerous tumor (i.e., cancer). In some embodiments, the tumor is a solid tumor or a non-solid or soft tissue tumor. Examples of soft tissue tumors include leukemia (e.g., chronic myelogenous leukemia, acute myelogenous leukemia, adult acute lymphoblastic leukemia, acute myelogenous leukemia, mature B-cell acute lymphoblastic leukemia, chronic lymphocytic leukemia, prolymphocytic leukemia, or hairy cell leukemia) or lymphoma (e.g., non-Hodgkin's lymphoma, cutaneous T-cell lymphoma, or Hodgkin's disease). A solid tumor includes any cancer of body tissues other than blood, bone marrow, or the lymphatic system. Solid tumors can be further divided into those of epithelial cell origin and those of non-epithelial cell origin. Examples of epithelial cell solid tumors include tumors of the gastrointestinal tract, colon, colorectal (e.g., basaloid colorectal carcinoma), breast,prostate, lung, kidney, liver, pancreas, ovary (e.g., endometrioid ovarian carcinoma), head and neck, oral cavity, stomach, duodenum, small intestine, large intestine, anus, gall bladder, labium, nasopharynx, skin, uterus, male genital organ, urinary organs (e.g., urothelium carcinoma, dysplastic urothelium carcinoma, transitional cell carcinoma), bladder, and skin. Solid tumors of non-epithelial origin include sarcomas, brain tumors, and bone tumors.

[0084] As used herein, the terms "tumor sample" or "tumor tissue" encompass samples prepared from a tumor or from a sample potentially including or suspected of comprising cancer cells, or to be tested for the potential presence of cancer cells, such as a lymph node. As used herein, the term "tumor" refers to a mass or a neoplasm, which itself is defined as an abnormal new growth of cells that usually grow more rapidly than normal cells and will continue to grow if not treated sometimes resulting in damage to adjacent structures. Tumor sizes can vary widely. A tumor may be solid, or fluid filled. A tumor can refer to benign (not malignant, generally harmless), or malignant (capable of metastasis) growths. Some tumors can contain neoplastic cells that are benign (such as carcinoma in situ) and, simultaneously, contain malignant cancer cells (such as adenocarcinoma). This should be understood to include neoplasms located in multiple locations throughout the body. Therefore, for purposes of the disclosure, tumors include primary tumors, lymph nodes, lymphatic tissue, and metastatic tumors.

[0085] OVERVIEW

[0086] The present disclosure is directed to a non-enzymatic dissociation method which facilitates the dissociation of one or more FFPE tissue samples into dissociated single cells (hereinafter referred to as "dissociated cells" or "single cells"). For instance, and with reference to FIG. 1A, the present disclosure provides a method of preparing a single cell composition, or a composition substantially comprising intact single cells, where the method comprises (i) obtaining one or more FFPE tissue samples (step 101); and (ii) non-enzymatically dissociating the obtained one or more FFPE tissue samples into single cells (step 102).

[0087] The present disclosure is also directed to methods of single cell analysis, i.e., methods of analyzing and / or measuring target components (e.g., biomolecules such as, but not limited to, polypeptides, polynucleotides, small molecules, and the like) on or in cells non- enzymatically dissociated from one or more FFPE tissue samples. The methods of analyzing and / or measuring target components comprises one or more of immunoenzymatic analysis (e.g., immunohistochemistry, in situ hybridization), cytometric analysis (e.g., flow cytometry,fluorescence-activated cell sorting), polymerase chain reaction (PCR) (including quantitative PCR, real-time quantitative-PCR, multiplex quantitative-PCR, digital droplet PCR, etc.), chromatographic analysis, mass spectroscopy, sequence analysis (e.g., next-generation sequencing, single cell sequencing (including single cell genome sequencing, single cell transcriptome sequencing, and single cell DNA methylome sequencing), etc. (see FIG. 2).

[0088] As such, and again with reference to FIG. 1A, in some embodiments, the method further includes the step of performing one or more downstream analysis operations of the cells in the single cell composition, or the composition substantially comprising the single cells (step 103; see also FIG. 2). The one or more performed downstream analysis operations may then be used to guide or determine one or more clinical decisions (e.g., at least one clinical decision includes determining disease prognosis, predicting recurrence of disease, escalating therapy, deescalating therapy, inclusion of subjects in clinical trials, or therapeutic treatment strategy) (step 104).

[0089] FFPE Tissue Samples

[0090] The single cell suspensions of the present disclosure are derived from one or more FFPE tissue samples. The one or more FFPE tissue samples include fixed tissue samples embedded in wax. In some embodiments, the FFPE tissue samples are biopsy samples. In some embodiments, the one or more FFPE tissue samples are FFPE tissue curls, i.e., a section from an FFPE tissue block. In some embodiments, the tissue curls or sections are about 10 microns in thickness. In other embodiments, the tissue curls or sections are between about 10 and about 30 microns in thickness. In other embodiments, the one or more FFPE tissue samples are entire FFPE tissue blocks. In some embodiments, the FFPE blocks can range from needle biopsies, which are a few micrograms, to blocks that are 3 cm x 2.5 cm x 0.4 cm. In other embodiments, the one or more FFPE tissue samples are tissue cores. In other embodiments, the one or more FFPE tissue samples are tissue biopsies.

[0091] The one or more FFPE tissue samples may, in some embodiments, be derived from tumor tissue (cancerous or non-cancerous tumor tissue), a metastatic lesion, normal tissue, a lymph node, or any combination, therefore. In some embodiments, the FFPE tissue samples are derived from a healthy subject. In other embodiments, the FFPE tissue samples are derived from a subject previously diagnosed with cancer. In yet other embodiments, the FFPE tissue samples are derived from a subject at risk of developing cancer, such as the result of a genetic mutation or prior cancer. In even further embodiments, the FFPE tissue samples are derived from normal tissue adjacent totumor tissue. In yet even further embodiments, the FFPE tissue samples are derived from a patient with an autoimmune disease. In yet even further embodiments, the FFPE tissue samples are derived from a diseased tissue. In yet even further embodiments, the FFPE tissue samples are derived from a diseased liver.

[0092] In some embodiments, multiple FFPE tissue samples, each derived from a different tumor section of a tumor of the same subject, are combined and collectively non-enzymatically dissociated according to the methods described herein. For example, in some embodiments, and to address spatial heterogeneity across multiple blocks taken from the same patient, one or more FFPE tissue samples are combined from multiple FFPE blocks containing tissue removed from the subject.

[0093] The obtained one or more FFPE tissue samples are deparaffmized prior to performing any dissociation processes. As used herein, the term "deparaffmization" refers to removing a part or whole part of any type of an embedded medium from a tissue sample. For example, although not limited, a paraffin-embedded tissue sample may be deparaffmized by treatment with an organic solvent, e.g., toluene, xylene, limonene, or other appropriate solvents.

[0094] Pre-screening of the Obtained FFPE Tissue Sample

[0095] In some embodiments, the obtained one or more FFPE tissue samples may be first "pre-screened" to determine whether the obtained one or more FFPE tissue samples should be processed into single cell compositions or compositions substantially including single cells. For instance, one or more obtained FFPE tissue samples may be "pre-screened" to determine whether they include one or more pre-determined characteristics (e.g., histology features, morphological features, positive biomarker status, negative biomarker status, etc.); and only if the one or more obtained FFPE tissue samples include the one or more pre-determined characteristics are the one or more obtained FFPE tissue samples further processed into a single cell composition or a composition substantially comprising single cells. In some embodiments, the obtained FFPE tissue sample is characterized using a primary stain (such as hematoxylin and eosin staining) or characterized via immunoenzymatic staining (e.g., immunohistochemically stained), including multiplexed immunoenzymatic staining (e.g., multiplex immunohistochemical staining). In other embodiments, the obtained FFPE sample is characterized via polymerase chain reaction, sequencing (e.g., next-generations sequencing), etc.

[0096] In some embodiments, and with reference to FIG. 1C, the methods of the present disclosure further comprise the step of performing one or more histological examinations on at least a portion of the one or more obtained FFPE tissue samples (step 101a); and using the results of the one or more histological examinations to determine whether to generate a single cell composition (step 101b). In some embodiments, the one or more histological examinations includes one or more of a morphological analysis or an immunocytochemical analysis. In some embodiments, the immunocytochemical analysis includes an immunohistochemical analysis of one or more biomarkers. In some embodiments, the immunocytochemical analysis includes in situ hybridization. In some embodiments, the immunocytochemical analysis includes fluorescent situ hybridization. In some embodiments, the histological analysis is performed by a pathologist or histologist. In other embodiments, the histological analysis is automated. In some embodiments, the FFPE tissue samples are virtually stained (morphologically and / or for one or more biomarkers), and the virtually stained images are utilized for histological examination.

[0097] By way of example, breast cancer patients are routinely screened for the expression of Her2 / neu via immunohistochemistry. Patients with intermediate staining (1+ or 2+) would then be analyzed via flow cytometry to quantify the total percentage of the tumor that is expressing Her2 / neu. Alternatively, the cells of the patients that have high levels of staining (3+) may then be sorted for Her2 staining so that the cells could be collected and then analyzed via nextgeneration sequencing. Similarly, immunohistochemistry may be used to screen for patients with significant immune invasion into the tumor, then flow cytometry would be used to quantify the immune cell component, followed by sorting of the cells for further analysis by RNAseq. In some embodiments, H&E can be used to differentiate between histological features in the same tissue, for instance squamous versus adeno-squamous histology in lung cancer. Using these features, FFPE blocks could be selected that contain multiple histologies, and single cells could be generated for downstream analysis and / or processing, such as via flow cytometry, sorting, or sorting then RNAseq.

[0098] Dissociation of Single Cells from the Obtained FFPE Tissue Sample

[0099] In some embodiments, single cells are non-enzymatically dissociated from an obtained FFPE tissue sample to provide a single cell composition or a composition substantially including intact single cells (see FIGS. 1A and IB). As used herein, a "single cell composition" may refer to a composition wherein at least 70% of the cells, following non-enzymatic dissociationaccording to the methods described herein, are present as single cells, such as wherein at least 75% of the cells are present as single cells, such as wherein at least 80% of the cells are present as single cells, such as wherein at least 85% of the cells are present as single cells, such as wherein at least 90% of the cells are present as single cells, such as wherein at least 91% of the cells are present as single cells, such as wherein at least 92% of the cells are present as single cells, such as wherein at least 93% of the cells are present as single cells, such as wherein at least 94% of the cells are present as single cells, such as wherein at least 95% of the cells are present as single cells, such as wherein at least 96% of the cells are present as single cells, such as wherein at least 97% of the cells are present as single cells, such as wherein at least 98% of the cells are present as single cells, such as wherein at least 99% of the cells are present as single cells, or such as wherein 100% of the cells are present as single cells.

[0100] Alternatively, a "single cell composition" may refer to composition wherein less than about 20% of the cells, following non-enzymatic dissociation according to the methods described herein, are clumped or clustered together, such as less than about 15% of the cells are clumped or clustered together, such as less than about 10% of the cells are clumped or clustered together, such as less than about 5% of the cells are clumped or clustered together, such as less than about 4% of the cells are clumped or clustered together, such as less than about 3% of the cells are clumped or clustered together, such as less than about 2% of the cells are clumped or clustered together, or such as less than about 1% of the cells are clumped or clustered together.

[0101] Notably, the dissociation processes of the present disclosure are performed without the addition of enzymes. In some embodiments, the processes of the present disclosure are performed without the addition of proteolytic enzymes that would separate cells via degradation of the proteins attaching themselves to each other and the surrounding matrix. For example, the dissociation of the single cells from FFPE tissue samples of the present disclosure is performed in the absence of the addition of enzymes such as collagenase (e.g., Collagenase 3, Collagenase 4), trypsin, elastase, hyaluronidase, papain, DNase I, neutral protease, trypsin inhibitors, Gelatinase- A, Stromelysin 1, Matrilysin, Neutrophil collagenase, Gelatinase-B, Stromelysin 2, Stromelysin 3, Macrophage metalloelastase, MT1-MMP, MT2-MMP, MT3-MMP, MT4-MMP, Enamelysin, X- MMP, CA-MMP, MT5-MMP, MT6-MMP, Matrily sin-2, MMP-22, endoproteinase, chymotrypsin, endoproteinase Asp-N, endoproteinase Arg-C, endoproteinase Glu-C (V8 protease), endoproteinase Lys-C, pepsin, thermolysin, elastase, papain, proteinase K, subtilisin,clostripain, exopeptidase, carboxypeptidase A, carboxypeptidase B, carboxypeptidase P, carboxypeptidase Y, cathepsin C, acylamino-acid-releasing enzyme, and pyroglutamate aminopeptidase. The skilled artisan will appreciate, however, the one or more enzymes may be added to a single cell composition after the single cell composition is generated so as to facilitate further downstream processing (e.g., DNA Ligase, DNA Polymerase).

[0102] Non-enzymatic dissociation of an obtained FFPE tissue sample according to the methods described herein provides for a single cell composition, wherein the cells retain at least 80% of their biomarkers, such as at least 90% of their biomarkers, such as at least 95% of their biomarkers, such as at least 96% of their biomarkers, such as at least 97% of their biomarkers, such as at least 98% of their biomarkers, such as at least 99% of their biomarkers, or 100% of their biomarkers. In comparison, samples comprising cells prepared by enzymatic, chemical, and / or biochemical dissociation methods, retain less than 50% of their biomarkers, such as less than 40% of their biomarkers, such as less than 30% of their biomarkers, such as less than 20% of their biomarkers, such as less than 10% of their biomarkers, such as less than 5% of their biomarkers. Specifically, Applicant has shown that enzymatic dissociation methods result in the complete, or inconsistent loss of cell surface markers in formalin fixed tissues (see, e.g., FIGS. 13A and 19B); while non-enzymatic dissociation of FFPE tissue samples according to the methods of the present disclosure permit the preservation of substantially all cell surface markers (see FIGS. 20A - 20C; see also Example 2, herein).

[0103] In some embodiments, single cells are non-enzymatically dissociated from an FFPE sample using one or more mechanical dissociation processes. As used herein, "dissociation" is a process whereby an overall size, weight, and / or complexity of an obtained FFPE tissue sample is reduced. "Mechanical dissociation" refers to a dissociation of an obtained FFPE tissue sample using one or more mechanical sources and / or with one or more sources that each apply physical forces to the obtained FFPE tissue sample. In some embodiments, the one or more mechanical dissociation techniques include applying physical forces onto the obtained FFPE tissue sample such as shearing, slicing, cutting, vibration, pressure, crushing to pull apart or tear or otherwise separate the tissue sample into smaller pieces. In other embodiments, the one or more mechanical dissociation techniques include homogenizing, shearing, cutting, mincing, scraping, or scratching the obtained FFPE tissue sample. In some embodiments, the at least one mechanical dissociation process comprises the use of a mortar and pestle, a dounce homogenizer, a tissue grinder, a Waringblender, a mortar, and pestle, triuration with a glass Pasteur pipette, vortexing, a hand-held electronic rotary blade tissue homogenizer, or a bead beating homogenizer.

[0104] In some embodiments, mechanical dissociation may take place in several steps, where during each step the size, weight, and / or complexity of the mechanically dissociated sample is further reduced. For instance, in some embodiments, and depending on the type of mechanical dissociation technique applied, an initial mechanical dissociation process may result in a mechanically dissociated sample which includes a mixture of cell clusters, clumps of cells, and / or individual cells. In these embodiments, the mechanically dissociated sample comprising the clusters, clumps, and / or individual cells may then be further mechanically dissociated using one or more mechanical dissociation processes to provide a further dissociated solution, i.e., one where the size, weight, and / or complexity of any clusters and / or clumps of cells is reduced.

[0105] By way of example, and with reference to FIG. 3, a first mechanical dissociation process may be performed with a first apparatus or by applying a first type of physical force to the obtained FFPE tissue sample to provide a first mechanically dissociated sample (step 105). This first mechanically dissociated sample may include a mixture of cell clusters, clumps of cells, and individual cells. The first mechanically dissociated sample may then be subjected to a second mechanical dissociation process, such as with a second apparatus or by applying a second type of physical force to the first mechanically dissociated sample (step 106). As shown in FIG. 3, this processes may be repeated one or more times (step 107, dashed lined) as necessary.

[0106] In some embodiments, each mechanical dissociation process may be performed for a period of time ranging from between about 5 seconds to about 5 minutes, such as from about 5 seconds to about 4 minutes, from about 10 seconds to about 3 minutes, from about 10 seconds to about 2 minutes, etc.

[0107] In some embodiments, mechanical dissociation of an obtained FFPE tissue sample is performed in the presence of one or more fluids, such as one or more buffers and / or one or more non-enzymatic cell conditioning agents. Suitable buffers include borate buffers, phosphate buffers, citrate buffers, tris buffers, phosphate-buffered saline (PBS), Tris-buffered saline (TBS), and combinations thereof. In some embodiments, the mechanical dissociation of one or more obtained FFPE tissue samples is performed in the presence of distilled water. In some embodiments, any resulting single cell composition includes the cells and a fluid, such as water, a buffer, and / or a cell conditioning agent. In some embodiments, any resulting single cellcomposition includes the cells and a fluid, such as water, a buffer, and / or a cell conditioning agent; but is free from any exogeneous enzymes.

[0108] Exemplary cell conditioning reagents include solutions comprising ethylenediaminetetraacetic acid (EDTA) or a boric acid buffer. A partial list of possible reagents for inclusion within a cell conditioning solution is disclosed in Analytical Morphology, Gu, ed., Eaton Publishing Co. (1997) at pp. 1-40, the disclosure of which is hereby incorporated by reference in its entirety. Sodium dodecyl sulfate (SDS) and / or ethylene glycol may be included in the conditioning solution. Furthermore, metal ions or other materials may be added to these reagents to increase effectiveness of the cell conditioning. Exemplary cell conditioning solutions are available from Ventana Medical Systems, Inc., Tucson, AZ (Cell Conditioning 1 (CC1) catalog # 950-124; Cell Conditioning 2 (CC2) catalog #: 950-123; SSC (10X) catalog # 950-110; ULTRA Cell Conditioning (ULTRA CC1) catalog # 950-224; ULTRA Cell Conditioning (ULTRA CC2) catalog # 950-223, Protease 1 catalog # 760-2018; Protease 2 catalog # 760- 2019; Protease 3 catalog #: 760-2020).

[0109] In some embodiments, one or more fluids, such as one or more buffers and / or conditioning agents, are added to the obtained FFPE tissue sample prior to performing the one or more mechanical dissociation processes (but after the FFPE tissue sample is deparaffinized). In other embodiments, one or more fluids, such as one or more buffers and / or conditioning agents, are added to the obtained FFPE tissue sample during mechanical dissociation and / or between each of the one or more mechanical dissociation steps. In some embodiments, between about 50 pL to about 1000 pL of one or more fluids, such as one or more buffers and / or conditioning agents, are added before, during, and / or after each of the one or more mechanical dissociation steps, such as between about 100 pL to about 1000 pL, such as between about 100 pL to about 900 pL, such as between about 100 pL to about 800 pL, such as between about 100 pL to about 500 pL, or about such as between about 100 pL to about 250 pL.

[0110] In some embodiments, the one or more fluids, such as one or more buffers and / or one or more cell conditioning agents, are introduced to the FFPE tissue sample or any intermediate mechanically dissociated sample at a temperature ranging from between about 20°C to about 90°C, such as between about 25°C to about 90°C, such as between about 30°C to about 90°C, such as between about 35°C to about 90°C, such as between about 40°C to about 90°C, such as between about 45°C to about 90°C, such as between about 50°C to about 90°C, such as between about 60°Cto about 90°C, such as between about 70°C to about 90°C, or such as between about 80°C to about 90°C. In some embodiments, the one or more fluids, such as one or more buffers and / or one or more cell conditioning agents, are introduced to the FFPE tissue sample or any intermediate mechanically dissociated sample at a temperature of about 80°C, such as about 81 °C, such as about 82°C, such as about 83°C, such as about 84°C, such as about 85°C, such as about 86°C, such as about 87°C, such as about 88°C, such as about 89°C, or such as about 90°C.[0U1] In some embodiments, a mechanically dissociated sample may be further processed. In some embodiments, the further processing may include performing one or more filtration processes, agitation processes, sonication processes, separation processes, centrifugation processes, and / or lateral flow processes. In some embodiments, the one or more dissociation processes include at least one mechanical dissociation process, at least one filtration process, and at least one agitation or sonication process. Such further processing steps may be conducted without introducing any exogeneous enzymes to the mechanically dissociated sample. For instance, and with reference to FIG. 4, in some embodiments, one or more mechanical dissociation processes are performed (step 112) on an obtained FFPE tissue sample (step 111) to generate a mechanically dissociated sample. In some embodiments, the mechanically dissociated sample is then further processed, such as filtered or otherwise separated from other components, to provide a single cell composition (step 113). Steps 112 and 113 may be repeated one or more times (step 114) using the same or different mechanical dissociation and / or further processing techniques, e.g., further filtration processes. One or more downstream analytical operations may then be performed on this single cell composition (step 115; see also FIG. 2). Example 1 sets forth one particular method of preparing a single cell composition using one or more non-enzymatic dissociation processes, including one or more filtration processes.

[0112] In some embodiments, the mechanically dissociated sample may be further processed by passing the mechanically dissociated sample through one or more meshes or one or more filters, such as a series of one or more meshes or a series of one or more filters. In some embodiments, the one or more meshes or one or more filters may have a pore size ranging from about 1 micron to about 150 microns. In some embodiments, the one or more meshes or one or more filters may have a pore size ranging from about 1 micron to about 100 microns. In some embodiments, the one or more meshes or one or more filters may have a pore size ranging from about 1 micron to about 50 microns. In some embodiments, the one or more meshes or one ormore filters may have a pore size ranging from about 10 microns to about 30 microns. In some embodiments, the one or more meshes or one or more filters may have a pore size ranging from about 15 microns to about 25 microns. In some embodiments, the one or more meshes or one or more filters may have a pore size ranging or about 20 microns.

[0113] In other embodiments, the one or more meshes or one or more filters may have a pore size less than 100 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 80 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 70 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 60 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 50 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 40 microns. In other embodiments, the one or more meshes or one or more filters may have pore size less than 30 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 20 microns. In other embodiments, the one or more meshes or one or more filters may have a pore size less than 10 microns. In some embodiments, a series of meshes or filters ranging in size from about 1 micron to about 150 microns is used to separate cells within the homogenate.

[0114] In some embodiments, additional fluid, e.g., a buffer and / or a cell conditioning agent, is added prior to passing the mechanically dissociated sample through the one or more meshes or one or more filters. In some embodiments, the mechanically dissociated sample is incubated with the additional fluid, e.g., buffer and / or cell conditioning agent, for a time period ranging from between about 30 seconds to about 20 minutes, such as between about 5 minutes to about 20 minutes, etc. prior to passing the mechanically dissociated sample through the one or more meshes or one or more filters. In some embodiments, the mechanically dissociated sample is incubated with the additional fluid, e.g., buffer and / or cell conditioning agent, for about 5 minutes, for about 10 minutes, or for about 15 minutes prior to passing the mechanically dissociated sample through the one or more meshes or one or more filters. In some embodiments, the single cells that pass through the one or more meshes or one or more filters are washed with one or more fluids, such as one or more buffers and / or one or more cell conditioning agents.

[0115] In some embodiments, the method further includes agitating and / or sonicating the mechanically dissociated sample prior to and / or after the performance of the one or more filtrationprocesses. As used herein, the term "sonication" refers to the application of sound waves (acoustic energy) transmitted through a liquid medium. In some embodiments, sound waves may cause particles (e.g., cell clumps, cell clusters, or individual cells) to oscillate about their mean position. In some embodiments, sonication leads to the dissociation of cell clusters to single cells. In some embodiments, additional buffers and / or non-enzymatic cell conditioning agents are added to the composition during agitation and / or sonication (see Example 1, herein).

[0116] In some embodiments, the single cells collected after being passed through the one or more meshes or one or more fdters are centrifuged, the supernatant removed, and the cell pellet collected (see Example 1, herein). The cell pellet may be resuspended prior to performing any downstream processing operations, e.g., resuspended in ImL of a buffer.

[0117] The disclosed non-enzymatic dissociation methods may be automated, in whole or in part. For instance, steps set forth in FIGS. 3 and 4 may be automated.

[0118] Following sufficient mechanical dissociation of the obtained FFPE sample, any subpopulations of cells that were originally spatially segregated within the obtained FFPE sample are substantially uniformly distributed throughout the single cell composition. That is, as a result of mechanically dissociating the obtained FFPE tissue sample, any heterogeneity of cells within the obtained FFPE tissue sample is substantially uniformly distributed within the resulting composition comprising the single cells (or any portion or aliquot removed therefrom), such that the composition comprising the single cells (or any portion or fraction thereof) substantially uniformly expresses the heterogeneity of the obtained FFPE tissue sample (or one or more obtained FFPE tissue sample) from which it was derived.

[0119] Staining of the Single Cells in the Generated Single Cell Composition

[0120] The present disclosure also provides for methods of staining the dissociated cells in the generated single cell composition (or the composition substantially including single cells) following the non-enzymatic dissociation of the one or more FFPE tissue samples (see, e.g., FIG. 5, step 202). In some embodiments, the dissociated cells are stained for the presence of one or more biomolecules, such as one or more biomarkers.

[0121] In some embodiments, the single cells may be stained with a nuclear counterstain, such as DAPI, hematoxylin, Hoescht, or propidium iodite. Yet other nuclear markers that may be stained are set forth in the table below:

[0122] In some embodiments, the dissociated cells in the single cell composition are stained by contacting the single cell composition with one or more detection probes, which may be visualized by contacting the single cell composition with one or more detection reagents including one or more detectable moieties. A "detectable moiety" is a molecule or material that can produce a detectable (such as visually, electronically, or otherwise) signal that indicates the presence (i.e., qualitative analysis) and / or concentration (i.e., quantitative analysis) of the epitopetagged antibody in a sample. A detectable signal can be generated by any known or yet to be discovered mechanism including absorption, emission and / or scattering of a photon (including radio frequency, microwave frequency, infrared frequency, visible frequency, and ultra-violet frequency photons). In some embodiments, the detectable moiety includes chromogenic, fluorescent, phosphorescent and luminescent molecules and materials, catalysts (such as enzymes) that convert one substance into another substance to provide a detectable difference (such as by converting a colorless substance into a colored substance or vice versa, or by producing a precipitate or increasing sample turbidity), haptens that can be detected through antibody-haptenbinding interactions using detectably labeled antibody conjugates, mass tags, paramagnetic and magnetic molecules or materials, etc.

[0123] In some embodiments, the detectable moiety is a fluorophore. Fluorophores belong to several common chemical classes including coumarins, fluoresceins (or fluorescein derivatives and analogs), rhodamines, resorufins, luminophores and cyanines. Additional examples of fluorescent molecules can be found in Molecular Probes Handbook — A Guide to Fluorescent Probes and Labeling Technologies, Molecular Probes, Eugene, OR, TheroFisher Scientific, 11thEdition. In other embodiments, the fluorophore is selected from xanthene derivatives, cyanine derivatives, squaraine derivatives, naphthalene derivatives, coumarin derivatives, oxadiazole derivatives, anthracene derivatives, pyrene derivatives, oxazine derivatives, acridine derivatives, arylmethine derivatives, and tetrapyrrole derivatives. In other embodiments, the fluorescent moiety is selected from a CF dye (available from Biotium), DRAQ and CyTRAK probes (available from BioStatus), BODIPY (available from Invitrogen), Alexa Fluor (available from Invitrogen), DyLight Fluor (e.g. DyLight 649) (available from Thermo Scientific, Pierce), Atto and Tracy (available from Sigma Aldrich), FluoProbes (available from Interchim), Abberior Dyes (available from Abberior), DY and MegaStokes Dyes (available from Dyomics), Sulfo Cy dyes (available from Cyandye), HiLyte Fluor (available from AnaSpec), Seta, SeTau and Square Dyes (available from SETA BioMedicals), Quasar and Cal Fluor dyes (available from Biosearch Technologies), SureLight Dyes (available from APC, RPEPerCP, Phycobilisomes)(Columbia Biosciences), and APC, APCXL, RPE, BPE (available from Phyco-Biotech, Greensea, Prozyme, Flogen).

[0124] In some embodiments, the detectable moiety is a molecule detectable via brightfield microscopy. Non-limiting examples of brightfield dyes compatible with IHC, including multiplex IHC, and methodologies of using the same are disclosed in US 10,041,950, the disclosure of which is hereby incorporated by reference herein in its entirety. Specific examples of brightfield dyes (also referred to as chromogens) include, but are not limited to, diaminobenzidine (DAB), 4- (dimethylamino) azobenzene-4'-sulfonamide (DABSYL), tetramethylrhodamine, N,N'- biscarboxypentyl-5,5'-disulfonato-indo-dicarbocyanine (Cy5), and Rhodamine 110 (Rhodamine), 4-nitrophenylphospate (pNPP), fast red, bromochloroindolyl phosphate (BCIP), nitro blue tetrazolium (NBT), BCIP / NBT, fast red, AP Orange, AP blue, tetramethylbenzidine (TMB), 2,2'- azino-di-[3-ethylbenzothiazoline sulphonate] (ABTS), 4-chloronaphthol (4-CN), nitrophenyl-(3- D-galactopyranoside (ONPG), o-phenylenediamine (OPD), 5-bromo-4-chloro-3-indolyl-P-galactopyranoside (X-Gal), methylumbelliferyl-P-D-galactopyranoside (MU-Gal), p-nitrophenyl- a-D-galactopyranoside (PNP), 5-bromo-4-chloro-3-indolyl-P-D-glucuronide (X-Gluc), 3-amino- 9-ethyl carbazol (AEC), fuchsin, iodonitrotetrazolium (INT), tetrazolium blue, or tetrazolium violet. In some embodiments, the brightfield dye is selected from TAMRA, Dabsyl, Dabcyl, Cy3, CyB, Cy3.5, Cy5, Cy5.5, Cy7, rhodamine 800 and fluorescein. In some embodiments, the brightfield dye is a conjugate including at least two chromogens, such as at least two chromogens selected from TAMRA, Dabsyl, Dabcyl, Cy3, CyB, Cy3.5, Cy5, Cy5.5, Cy7, rhodamine 800 and fluorescein. In some embodiments, the brightfield dye is selected from those disclosed in United States Patent Publication No. 2021 / 0055285, the disclosure of which is hereby incorporated by reference herein in its entirety. Commercial brightfield dyes include DISCOVERY Red, DISCOVERY Yellow, DISCOVERY Blue, DISCOVERY Purple, DISCOVERY Silver, DISCOVERY Teal, and DISCOVERY Green, each of which are available from Roche Diagnostics.

[0125] Other detectable moieties and detection strategies are described in United States Patent Nos. 11,249,085, 11,249,085, and 10,168,336; and in United States Patent Application Publication No. 2012 / 0171668, the disclosures of which are hereby incorporated by reference herein in their entireties.

[0126] Suitable methods of staining samples with detection probes and detection reagents are described in United States Patent Publication Nos. 2023 / 019258, 2019 / 0204330, 2017 / 0089911, and 2019 / 0187130; in United States Patent Nos. 5,583,001, 10,168,336, and 10,041,950; and in PCT Publication No. WO / 2017 / 085307, the disclosures of which are hereby incorporated by reference herein in their entireties. For example, in some embodiments, the detection probes utilized are specific for certain biomarkers present on or in the dissociated cells in the single cell composition. In some embodiments, the detection probes are selected from primary antibodies that are specific for protein biomarkers present on or in the dissociated cells in the single cell composition. In other embodiments, the detection probes are selected from oligonucleotide probes antibodies that are specific for biomolecules (e.g., nucleic acids molecules) present in the dissociated cells in the single cell composition.

[0127] In some embodiments, the dissociated cells in the generated single cell composition are stained in a simplex assay. In a simplex assay, a single detectable moiety is used for all biomarker-specific reagents bound to the sample. Thus, for example, an immunohistochemical orflow cytometry assay for a single biomarker using a single detectable moiety would be considered a simplex IHC or flow cytometry assay.

[0128] In other embodiments, the dissociated cells in the generated single cell composition are stained in a multiplex assay. A multiplex assay involves staining multiple biomarkers in a single aliquot where at least some of the biomarkers are differentially labeled. Thus, for example, an IHC or flow cytometry assays for two distinct biomarkers in the same sample, with a different detectable moiety for each biomarker would be considered a multiplex IHC or flow cytometry assay.

[0129] In some embodiments, the cells in the single cell composition are stained for the presence of one or more surface biomarkers. Examples of biomarkers (surface biomarkers, cytoplasmic biomarkers, or nuclear biomarkers) include, but are not limited to, CD3, CD4, CD8, CD25, CD163, CD45LCA, CD45RA, CD45RO, PD-1, TIM-3, LAG-3, CD28, CD57, FOXP3, EPCAM, CK8 / 18, Her2, Ki67, ER, PR, Vimentin, Cyclin D, p21, CDT1, Cyclin E, pRB, Cyclin A, and Geminin. In other embodiments, the cells in the single cell composition are stained for the presence of one or more of EGFR, FGFR, PDGFR, MET, MT-MMP, the MMP family of proteases, Urokinase, and Cadherins, or other receptor tyrosine kinases. In yet other embodiments, the cells in the single cell composition are stained for the presence of one or more of PD-1, TIM- 3, and LAG-3.

[0130] In other embodiments, the cells in the single cell composition are stained for the presence of one or more immune cell biomarkers. For example, an immune cell marker may be specific for a particular immune cell type such as B cells or T cells. According to embodiments, at least some of the markersfor which marker images are derived are CD-antigens (CD: “cluster of differentiation”). In particular, the markers may comprise or consist of CD antigens allowing the identification of the immune cell type (see table below). Non-limiting examples of immune cell biomarkers include CD3, CD4, CD8, CD19, CD20, CDl lc, CD123, CD56, CD14, CD33, CD45, CD25, CD22, CD61, CD31, CD30, CD38, or CD66b. The immune cell-specific biomarkers are not limited to proteins detectable with IHC; for example, the immune cell-specific biomarker may be a nucleic acid sequence of interest detectable with ISH techniques.

[0131] In other embodiments, the cells in the single cell composition are stained for the presence of one or more immune checkpoint markers. Examples of immune checkpoint markers include, but are not limited to, the following markers: CTLA-4, cytotoxic T lymphocyte associated protein 4; DC, dendritic cells; IDO, indoleamine 2,3-dioxygenase; IL, interleukin; LAG3, lymphocyte activation gene 3; MHC, major histocompatibility complex; PD-1, programmed cell death protein 1; PDL-1, programmed death ligand 1; PDL-2, programmed death ligand 2; TCR, T cell receptor; TGF, tumor necrosis factor; Tim-3, T cell and immunoglobulin mucin domain 3; and Treg, regulatory T cells.

[0132] PD-1 / CD279 is expressed on activated T cells which binds to PD-L1 or PD-L2 on tumor cells, resulting in inactivation and death of T cells. The absence of PD-1 expression on T cells has shown to significantly delay in tumor growth and increase CD8+ T cells within the TME in mouse models. CTLA-4 / CD152 is responsible for suppressing CD8+ T-cell activation. TIM- 3 is a negative regulator immune checkpoint. TIM-3 is expressed on IFN-y producing CD4+ T helper 1 (Thl) and CD8+ T cells (Tel) as well as on natural killer cells, mast cells, dendritic cells, B cells, macrophages. LAG3 is an important immune checkpoint molecule with relevance to several diseases, including cancer. LAG-3 binds to MHC class II in addition to other ligands including galectin-3 and LSECtin. Like PD-1, LAG3 (or CD223) is up-regulated on many cell types including, tumor-infiltrating lymphocytes (CD4, CD8) and regulatory T cells. LAG3 is important for optimal T cell regulation and homeostasis. IDO is an enzyme which degrades tryptophan, an essential amino acid abundant in the lung, colon, and intestine. It catalyzes theoxidative ring cleavage of the pyrrole moiety of not only tryptophan, but also serotonin, melatonin, and other indoleamine derivatives. IDO is expressed by cancer cells but also by endothelial cells, immune cells within the TEM, peripheral blood cells, fibroblasts and in blood. (See Ephraim R, et al., Checkpoint Markers and Tumor Microenvironment: What Do We Know? Cancers (Basel). 2022 Aug 4; 14(15):3788. Doi: 10.3390 / cancersl4153788. PMID: 35954452; PMCID: PMC9367329, the disclosure of which is hereby incorporated by reference herein in its entirety).

[0133] In other embodiments, the cells in the single cell composition are stained for the presence of one or more growth factor receptor markers. By way of example, the human epidermal growth factor receptor-2 (HER2) receptor is a transmembrane glycoprotein with tyrosine kinase activity that belongs to the epidermal growth factor receptor family. By way of another example, the epidermal growth factor (EGF) receptor (EGFR) is one of four homologous transmembrane proteins that mediate the actions of a family of growth factors including EGF, transforming growth factor-a, and the neuregulins.

[0134] In other embodiments, the cell sin the single cell composition are stained for the presence of one or more hormone receptor markers. Non-limiting examples of hormone receptor markers include estrogen receptor (ER) and progesterone receptor (PR).

[0135] In other embodiments, the cell sin the single cell composition are stained for the presence of one or more transcription factor markers. Non-limiting examples of transcription factors include the following: ERG; ETV1 (ER81); FLU; ETS1; ETS2; ELK1; ETV6 (TEL1); ETV7 (TEL2); GABP.alpha.; ELF1; ETV4 (E1AF; PEA3); ETV5 (ERM); ERF; PEA3 / E1AF; PU.l; ESE1 / ESX; SAP1 (ELK4); ETV3 (METS); EWS / FLI1; ESEI; ESE2 (ELF5); ESE3; PDEF; NET (ELK3; SAP2); NERF (ELF2); and FEV.

[0136] In other embodiments, the cells in the single cell composition are stained for the presence of one or more tumor cell biomarkers. Examples of tumor cell-specific biomarkers may include, but are not limited to, cytokeratins detectable with the pan keratin antibody (e.g., basic cytokeratins, many of the acidic cytokeratins), other cytokeratins such as cytokeratin 7 (CK7) and cytokeratin 20 (CK20), chromogranin, synaptophysin, CD56, thyroid transcription factor- 1 (TTF- 1), p53, leukocyte common antigen (LCA), vimentin, smooth muscle actin, or the like (e g., see Capelozzi, V., I Bras Pneumol. 2009; 35(4):375-382, the disclosure of which is hereby incorporated by reference herein in its entirety). The tumor cell-specific biomarkers are notlimited to proteins detectable with IHC; for example, the tumor cell-specific biomarker may be a nucleic acid sequence of interest detectable with ISH techniques.

[0137] In other embodiments, the cells in the single cell composition are stained for the presence of one or more intracellular signaling molecules, e.g., adenosine 44 / 42 mitogen-activated protein kinase (MAPK or ERK1 / 2), cAMP response element-binding protein (CREB), signal transducer and activator of transcription 3 (STAT3), and suppressor of cytokine signaling 3 (S0CS3).

[0138] In some embodiments, the stained one or more biomarkers are scored, either manually or automatically (such as with one or more software algorithms or machine learning algorithms). In some embodiments, an analysis of the staining of the one or more biomarkers is utilized to identify one or more therapeutic targets. In some embodiments, an analysis of the staining of the one or more biomarkers is utilized to identify one or more combination therapy targets. In some embodiments, an analysis of the staining of the one or more biomarkers is utilized to identify one or more immunotherapy therapy targets. In some embodiments, an analysis of the staining of the one or more biomarkers is utilized to identify one or more neoantigens. In some embodiments, an analysis of the staining of the one or more biomarkers is utilized to determine at least one clinical decision, wherein the at least one clinical decision includes determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

[0139] In some embodiments, the cells are virtually stained, such as virtually stained for the presence of one or more biomarkers; or virtually morphologically stained (i.e., where a virtually stained image manifests the appearance of an unstained biological specimen as if it were stained with a morphological stain). In some embodiments, the cells are virtually stained according to the methods described in U.S. Patent No. 11,482,320 and in U.S. Publication No. 2024 / 0046473, the disclosures of which are hereby incorporated by reference herein in their entireties. In other embodiments, the cells are virtually stained according to the methods described in International Application No. PCT / US2025 / 013949, filed on January 31, 2025, the disclosure of which is hereby incorporated by reference herein in its entirety.

[0140] Flow Cytometry

[0141] The present disclosure also provides methods of generating cytometry data for the cells in the generated single cell composition and evaluating the obtained cytometry data. In someembodiments, the obtained cytometric data can provide quantitative and qualitative data about fluorescently stained cells, such as the presence of certain surface biomarkers or intracellular molecules (e.g., DNA). In some embodiments, the generated cytometry data is utilized to identify one or more therapeutic targets. In some embodiments, the generated cytometry data is utilized to identify one or more combination therapy targets. In some embodiments, the generated cytometry data is utilized to identify one or more immunotherapy therapy targets. In some embodiments, the generated cytometry data is utilized to identify one or more neoantigens. In some embodiments, the generated cytometry data is utilized to determine at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

[0142] Various methods of cytometrically assaying stained cells derived from one or more FFPE tissue samples include flow cytometrically assaying using a flow cytometer, cell cytometrically assaying a labeled cell suspension, e.g., by using a cell cytometer, and the like. In some embodiments, additional cellular parameters, assayed cytometrically, may also find use in detecting neoplastic cells of the present disclosure.

[0143] In some embodiments, the methods of the present disclosure further comprise quantifying stained cells within the single cell composition positively expressing one or more biomarkers based on the obtained cytometry data. In some embodiments, the method includes quantifying tumor cells within the single cell composition based on the obtained cytometry data. In other embodiments, the method includes quantifying normal or immune cells within the single cell composition based on the obtained cytometry data.

[0144] Flow cytometry is a method using multi-parameter data for identifying and distinguishing between different particles (e.g., cell) types i.e., particles that vary from one another in terms of label (wavelength, intensity), size, etc., in a fluid medium. In flow cytometrically analyzing a sample, an aliquot of the sample is first introduced into the flow path of the flow cytometer. When in the flow path, the cells in the sample are passed substantially one at a time through one or more sensing regions, where each of the cells is exposed separately and individually to a source of light at a single wavelength (or in some instances two or more distinct sources of light) and measurements of cellular parameters, e.g., light scatter parameters, and / or marker parameters, e.g., fluorescent emissions, as desired, are separately recorded for each cell. The datarecorded for each cell is analyzed in real time or stored in a data storage and analysis means, such as a computer, for later analysis, as desired.

[0145] The flow cytometry data generated can be plotted into scatter plots and / or histograms and divided into regions. Regions are shapes that are drawn or positioned (either manually or automatically) around a population of interest on a one or two parameter scatter plot or histogram. Exemplary region shapes include two dimensional polygons, circles, ellipses, irregular shapes, or the like. When a region is used to limit or isolate cells or events that are drawn or positioned on a scatter plot or histogram, such that those isolated cells or events can be manifested in a subsequent scatter plot or histogram, this process is referred to as gating.

[0146] Gates and regions are placed around populations of cells with common characteristics, usually forward scatter, side scatter and biomarker expression, to investigate and quantify these populations of interest. To select an appropriate gate, the data is plotted to obtain appropriate separation of subpopulations of particles, e.g., by adjusting the configuration of the instrument, including e.g., excitation parameters, collection parameters, compensation parameters, etc. In some instances, this procedure is completed by plotting forward scatter content (FSC) versus side scatter content (SSC) on a two-dimensional dot plot. Alternatively, fluorescence intensity may be plotted versus SSC. The flow cytometry operator then selects the desired population of cells (i.e., those cells within the gate) and excludes cells which are not within the gate. Where desired, the operator may select the gate by drawing one or more lines (e.g., vertical, and / or horizontal lines) around the desired population using a cursor on a computer screen. Only those cells within the gate are then further analyzed by plotting the other parameters for these cells, such as fluorescence. The process of gating does not change the data, i.e., it only depicts it in a way that flow cytometry analysts find themselves familiar with.

[0147] Non-limiting examples of suitable flow cytometer systems include those available from commercial suppliers including but not limited to, e.g., Becton-Dickenson (Franklin Lakes, NJ), Life Technologies (Grand Island, NY), Acea Biosciences (San Diego, CA), Beckman- Coulter, Inc. (Indianapolis, IN), Bio-Rad Laboratories, Inc. (Hercules, CA), Cytonome, Inc. (Boston, MA), Amnis Corporation (Seattle, WA), EMD Millipore (Billerica, MA), Sony Biotechnology, Inc. (San Jose, CA), Stratedigm Corporation (San Jose, CA), Union Biometrica, Inc. (Holliston, MA), Cytek Development (Fremont, CA), Propel Labs, Inc. (Fort Collins, CO), Orflow Technologies (Ketchum, ID), handyem inc. (Quebec, Canada), Sysmex Corporation(Kobe, Japan), Partec Japan, Inc. (Tsuchiura, Japan), Bay bioscience (Kobe, Japan), Furukawa Electric Co. Ltd. (Tokyo, Japan), On-chip Biotechnologies Co., Ltd (Tokyo, Japan), Apogee Flow Systems Ltd. (Hertfordshire, United Kingdom), and the like.

[0148] An example of a cytometric analysis, including a gating of cytometry data, is shown in FIG. 7. For example, gating the cells during flow cytometric analysis creates a narrow and specific population from a broad one. The first two parameters are for threshold and scatter setup. Forward scatter height (FSC-H) versus side scatter height (SSC-H) and forward scatter area (FSC-A) versus side scatter area (SSC-A) are both dot plots used to adjust the voltage of the FSC and SSC to remove debris and ensure that all events are in view. The first gate created is used to exclude events with an FSC-A and SSC-A of less than 50 x 103.

[0149] The second gate created is used for doublet discrimination, which isolates intact single cells from doublets, cell fragments, and debris not excluded in the first gate. This gate is created on a DAPI width versus DAPI area dot plot with a rectangular gate around the singlet population centered at DAPI area around 50 x 103. The length of the singlets gate is drawn to include cells with a DAPI area of 200 x 103to account for cells that may be in different phases of the cell cycle. The width of the singlets gate should be placed between 50-100 x 103to exclude doublets from the analysis. The DAPI histogram is used to visualize DNA content and ploidy for the events within the singlets gate. Adjusting the voltage to center the DAPI histogram around 50 x 103allows visualization of the diploid population, and hence aneuploid populations greater than 100 X 103.

[0150] The third gate is used to select for the positive population of interest and is created on the negative control sample. The secondary antibody used in this analysis was Alexa Fluor 647 (AF647), therefore the dot plot viewing the events within the singlets gate is comparing AF647-A vs SSC-A. The fluorescence voltage is adjusted to move the singlets area to less than or equal to 102and the positive gate is drawn starting from the area at 103encompassing the entirety of the AF647-A and SSC-A beyond that point.

[0151] The parameters set while analyzing the negative control remain the same while analyzing the positive sample. The positive cells will be shown within the gate comparing AF647- A vs SSC-A with an AF647-A greater than or equal to 103.

[0152] In some embodiments, the cytometric analysis comprises mass cytometry. Mass cytometry is a mass spectrometry technique based on inductively coupled plasma massspectrometry and time of flight mass spectrometry used for the determination of the properties of cells (cytometry). In some embodiments, antibodies are conjugated with isotopically pure elements, and these antibodies are used to label cellular proteins. In some embodiments, cells are nebulized and sent through an argon plasma, which ionizes the metal-conjugated antibodies. In some embodiments, the metal signals are then analyzed by a time-of-flight mass spectrometer. It is believed that the mass cytometry approach overcomes limitations of spectral overlap in flow cytometry by utilizing discrete isotopes as a reporter system instead of traditional fluorophores which have broad emission spectra.

[0153] Sorting of Cells

[0154] In some embodiments, the dissociated cells in the generated single cell composition are sorted into one or more populations of single cells. In some embodiments, the dissociated cells are sorted using "fluorescence-activated cell sorting" (FACS). FACS is a flow cytometry technique that allows simultaneous collection of data and sorting of cells based on one or more parameters. Methods of sorting cells using FACS are described in United States Patent Publication Nos. 2020 / 0049599, 2020 / 0011775, and 20040265835, the disclosures of which are hereby incorporated by reference herein in their entireties.

[0155] In other embodiments, the single cells are sorted using magnetic-activated cell sorting. In yet other embodiments, the dissociated cells are sorted or processed using a set of buoyant particles, such as described in United States Patent No. 11,583,893, the disclosure of which is hereby incorporated by reference herein in its entirety.

[0156] In some embodiments, sorting is achieved using a sized-based sorting procedure. In some embodiments, a sized-based sorting step sorts dissociated cells into a first cellular population and a second cellular population, wherein the first cellular population is enriched with tumor cells and wherein the second particle population is enriched with normal cells. In some embodiments, the normal cells have an average diameter of less than 12 pm; and the tumor cells have an average diameter of greater than 12 pm. In some embodiments, the sorting of the cells is carried out with a microfluidic device. Other methods of sized-based sorting are described in PCT Publication No. WO / 2018 / 189040 and in United States Patent No. 11,768,137, the disclosures of which are hereby incorporated by reference herein in their entireties.

[0157] In some embodiments, the single cells are enriched by an antibody -based enrichment method, such as a bead-based antibody enrichment method. In other embodiments,the single cells are enriched using one of the systems or methods described in U.S. Publication Nos. 2024 / 0066520, 2023 / 0166291 or 2023 / 0314428, the disclosures of which are hereby incorporated by reference herein in their entireties.

[0158] Sequencing

[0159] In some embodiments, one or more nucleic acid molecules within the cells of the generated single cell composition, or any aliquot derived therefrom, are sequenced. In some embodiments, the sequencing of the one or more nucleic acid molecules of the cells within the generated single cell composition generates one or more sequence data sets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more therapeutic targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more combination therapy targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more immunotherapy therapy targets. In some embodiments, the generated one or more sequence data sets are utilized to identify one or more neoantigens. In some embodiments, the generated one or more sequence data sets are utilized to determine at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

[0160] In some embodiments, the sequencing of the one or more nucleic acid molecules within the cells of the generated single cell composition includes a next-generation sequencing (NGS) technique. NGS examines the genome of a cell population and provides an "average genome" of the cell population. In some embodiments, the sequencing includes T-cell receptor sequencing (TCRseq). TCR-Seq (T-cell Receptor Sequencing) is a method used to identify and track specific T cells and their clones (see Redmond et al., 2016 Genome Medicine, 8:80, the disclosure of which is hereby incorporated by reference herein in its entirety). TCR-Seq utilizes the unique nature of a T-cell receptor (TCR) as a ready-made molecular barcode.

[0161] In other embodiments, the sequencing of the one or more nucleic acid molecules within the cells of the generated single cell composition includes a single cell sequencing technique. Single-cell sequencing technologies refer to the sequencing of a single-cell genome or transcriptome, so as to obtain genomic, transcriptome or other multi-omics information to reveal cell population differences and cellular evolutionary relationships. As compared with NGS, singlecell sequencing measures the genomes of individual cells in a cell population. Compared with traditional sequencing technology, single-cell technologies have the advantages of detecting heterogeneity among individual cells, distinguishing a small number of cells, and delineating cell maps. Single cell sequencing technologies can measure different types of genetic material -the genome, the transcriptome or the methylome - of a single cell.

[0162] In some embodiments, genomic material is extracted from single cells, such as single cells from the one or more populations of single cells prepared after cell sorting. In some embodiments, genomic material is amplified within isolated individual cells. In some embodiments, the extracted genomic material is amplified, optionally barcoded, and a sequencing library is prepared including the genomic material from an isolated single cell. The sequencing library is then sequenced, such as with a NGS sequencing apparatus.

[0163] In some embodiments, the single cell sequencing includes single cell genome sequencing (scDNA-seq), which facilitates the genomic heterogeneity of a cellular population to be studied. For instance, scDNA-seq of the single cells derived from an FFPE tissue sample may be used to study the intra-tumor genetic heterogeneity or to identify novel carcinogenic mutations.

[0164] In some embodiments, the single cell sequencing includes single cell transcriptome sequencing (scRNA seq). In some embodiments, scRNA-seq is used to measure the RNA molecules within a single cell derived from FFPE tissue samples, thereby providing data pertaining to the transcriptome when the single cells within the FFPE tissue sample were collected.

[0165] In some embodiments, the single cell sequencing includes single cell DNA methylome sequencing (scDNA-Met-seq). Methylation is an epigenetic mechanism that changes the DNA activity without affecting its sequence. In some embodiments, scDNA-Met-seq is utilized to study the epigenetic changes within an otherwise genetically identical cellular population.

[0166] In some embodiments, one or more genetic variants are identified within sequencing data obtained from next-generation sequencing and / or single cell sequencing (see, e.g., FIG. 6). In some embodiments, the methods of the present disclosure further include determining whether the identified one or more genetic variants are clonal or subclonal. In some embodiments, one or more neoantigens are derived from the identified subclonal mutations. In some embodiments, the derivation of neoantigens enables drug discovery, vaccine generation, and / or CAR-T cell engineering. In other embodiments, a ctDNA monitoring panel may be developedbased on the identified genetic variants. In some embodiments, the ctDNA panel may be used to monitor for genetic variants may be result in distant metathesis. In yet other embodiments, a minimal residual disease (MRD) panel may be developed based on the identified genetic variants. In yet other further embodiments, a clonal structure may be computed based on the identified genetic variants. In some embodiments, the computed clonal structure may be used to assess the separation between truncal variants and sub-clonal variants.

[0167] In some embodiments, the method further includes detecting, characterizing, or identifying one or more low prevalence genetic events. In some embodiments, the one or more low prevalence genetic events are selected from a point mutation, a deletion, an addition, a translocation, a genetic fusion, or an amplification of a gene. In some embodiments, the method further includes identifying one or more subclones. In some embodiments, the identified one or more subclones are one or more low prevalence subclones. In some embodiments, the one or more low prevalence subclones have a prevalence of less than 0.0001% within the sequenced genomic material. In some embodiments, the one or more low prevalence subclones have a prevalence of less than 0.00001% within the sequenced genomic material.

[0168] EXAMPLES

[0169] Example 1 - Non-Enzymatic Dissociation Protocol

[0170] Sample type: FFPE tissue curls, FFPE Tissue blocks

[0171] Protocols:

[0172] (1) Dissociation of FFPE sections:

[0173] Curls were directly cut from a block or scraped from a slide.

[0174] 2, 25pm curl sections were obtained in a 1.5mL epi tube

[0175] ImL Xylene was added and incubated for 10 min.

[0176] Xylene was removed without breaking the scrolls.

[0177] ImL fresh Xylene was added and incubated for 10 min.

[0178] xylene was removed without breaking scrolls.

[0179] ImL of 100% Ethanol was added and incubated for 30 sec.

[0180] Ethanol was removed without breaking scrolls.

[0181] ImL fresh 100% Ethanol was added and incubated for 30 sec.

[0182] Ethanol was removed without breaking scrolls.

[0183] ImL 70% Ethanol was added and incubated for 30 sec.

[0184] Ethanol was removed without breaking scrolls.

[0185] ImL of 50% Ethanol was added and incubated for 30 sec.

[0186] Ethanol was removed without breaking scrolls.

[0187] ImL water was added and incubated for 30 sec.

[0188] water was removed without breaking scrolls.

[0189] ImL PBS was added kept on ice.

[0190] — Move forward with cell conditioning —

[0191] (2) Dissociation of whole block:

[0192] A whole block with the cassette was submerged in xylene. Alternatively, the wax block including the tissue can be removed from the cassette by taking a razor blade and cuttingand then submerged in xylene. The block remains in xylene until all wax is dissolved (~2 hours depending on tissue size).

[0193] Shaking as well as replacing xylene can reduce the incubation time.

[0194] When the wax was completely dissolved, xylene was removed and ImL of 100% ethanol was added, incubate for 1 min.

[0195] Ethanol was removed and replaced with fresh ImL of 100% ethanol, and then incubated for 1 min.

[0196] Ethanol was removed and replaced with ImL of 70% ethanol, and then incubated for 1 min.

[0197] Ethanol was removed and replaced with ImL of 50% ethanol, and then incubated for 1 min.

[0198] Ethanol was removed and replaced with ImL of water, and then incubated for 1 min.

[0199] Ethanol was removed and replaced with ImL PBS and then kept on ice.

[0200] — Move forward with cell conditioning —

[0201] (3) Cell Conditioning

[0202] When ready to start the cell conditioning process remove PBS without breaking disturbing the tissue; make sure the tissue is at the bottom of the epi tube to help with pestle dissociation.

[0203] CC1 was heated to 85°C for 10 min prior to starting (note: adding warmed CC1 to tissue aids with mechanical dissociation

[0204] 100 pL of CC1 was added at 85°C to the tissue.

[0205] Mechanical dissociation with an IKA blender or manual dissociation using a pestle was performed. When using a pestle, grasp the pestle between the thumb and fingers and rotate the pestle clockwise and counterclockwise 10 - 20X inside the tube and go up and down with the scrolls trapped between the wall of the tube and the pestle for dissociation or until the scroll is broken into similarly sized smaller pieces. Do not discard the pestle.

[0206] 900 pL of CC1 was added to the tube while rinsing the pestle tip into the tube to collect any additional tissue pieces sticking to the pestle.

[0207] Incubated for 15 min at 85°C.

[0208] After incubation, the mix was pipetted up and down 10 - 20x.

[0209] The mix was passed through a 30 pm filter.

[0210] The tube was washed with ImL PBS and pass through the same filter.

[0211] Centrifuge at 900 rpm for 5 min

[0212] The supernatant was removed being careful to not remove any of the cell pellet.

[0213] Resuspend in ImL PBS or 90103 (if moving forward with flow cytometry)

[0214] Cells were counted using Countess II

[0215] If cell clumps were visible:

[0216] Good yield, but clumps: pass through a new 20 pM filter

[0217] Poor yield, but clumps: sonicate for 2 min and count again.

[0218] Clumps remain after sonication: pass through a new 20pM filter.

[0219] Example 2 - Comparison of Non-Enzymatic and Enzymatic Dissociation of Tissue Samples

[0220] Overview

[0221] Since many protocols use enzymes during the dissociation of cells, it was desirable to assess the effect of enzyme on cells. Specifically, it was desirable to assess the effect of enzymes on cell surface markers. It was hypothesized that enzymes would digest the cell surface affecting the cells' ability to be stained and sorted by FACS. Cells were dissociated from homogenized fixed tonsil (tonsil used a tissue model and no enzymes used in the dissociation process), then cells were treated with Proteinase K (PK) in one experiment and Liberase TH in another. Flow cytometry was then used to evaluate various cell surface markers to determine how they were affected by the enzymes.

[0222] Procedure

[0223] To evaluate the impact of proteolytic enzymes that are currently standard in fresh tissue dissociation on protein cell surface markers, formalin fixed tissue was dissociated either (i) in the absence of added enzymes, or (ii) dissociated with one of proteinase K or liberase.

[0224] Non-Enzymatic Dissociation

[0225] Tissues that was non-enzymatically dissociated were incubated in cell conditioning buffer prior to mechanical dissociation.

[0226] Dissociation in the Presence of Proteinase K

[0227] Tissues that were enzymatically dissociated with proteinase K (PK), were incubated at 37°C for either 30 seconds, 1 minute, 5 minutes, or 10 minutes prior to mechanical dissociation. For example:

[0228] Starting number of cells: 10M in 250 pL PKD (PKD is a proteinase K dissociation buffer from Qiageny:

[0229] Samples were treated with 10 pL PK for:

[0230] -30s

[0231] -1 min

[0232] -5 min

[0233] -10 min

[0234] Cells that were not treated with PK were used as a control (see FIGS. 8A - 8C)

[0235] Dissociation in the Presence of Liber ase

[0236] Tissues that were enzymatically dissociated with liberase were incubated at 37°C for either 1 minute, 3 minutes, 7 minutes, or overnight (and prior to mechanical dissociation). For example:

[0237] Starting number of cells: 10M

[0238] Samples treated with Liberase TH (cells were resuspend in 210 pL Liberase TH(5mg / m) + 840 pL RPMI) for:

[0239] 1 hour

[0240] 3 hours

[0241] 7 hours

[0242] Overnight

[0243] Cells that were not treated with Liberase LH were used as a control (see FIGS. 14A - 14C).

[0244] After dissociation according to these three protocols, and following a wash to remove all enzymes, cells from each dissociation protocol were incubated with primary antibodies against CD45, CD20, or CD3 and detected via flow cytometry using a fluorescent secondary antibody.

[0245] Following only 30 seconds of incubation with proteinase K, both CD45 and CD20 were undetectable via flow cytometry (i.e., no cells are detectable) (see FIGS. 9A - 9C). Thenumber of detectable CD3 cells dropped by 50% at 30 seconds, and 75% at 10 minutes of proteinase K digestion (see FIGS. 9 - 12).

[0246] When treated with liberase, there were no cells positive for CD20 after only 1 minute (see FIGS. 15A - 15C). The number of CD45 positive cells decreased at the 1 -minute incubation and continued to decrease until there were no CD45 positive cells at the overnight incubation time (see FIGS. 15 - 18). More CD3 cells were detectable when treated with liberase, however at the overnight incubation time there was a greater than 10% loss in the number of cells positive for CD3 (see FIGS. 18A - 18C).

[0247] In comparison, cytometric analysis of tissues that were non-enzymatically dissociated as noted above (and in accordance with the methods disclosed herein), retained all cell surface markers (see FIGS. 20A - 20C).

[0248] These results demonstrate that enzymatic dissociation methods result in the complete, or inconsistent loss of cell surface markers in formalin fixed tissues (see FIGS. 13 A - 13C and FIGS. 19A - 19B). Whereas, when only dissociating formalin fixed cells with cell conditioning and mechanical methods preserve all cell surface markers and can be robustly analyzed by flow cytometry (see FIGS. 20A - 20C).

[0249] Example 3 - Optimizing flow cytometry to analyze biomarker expression in FFPE samples and biopsy-like models

[0250] Introduction

[0251] Flow cytometry is a well-established method to analyze cell populations using primary antibodies and fluorescence detection. The ability to use flow cytometry to analyze FFPE tissue has been optimized, which facilitates the screening of a larger proportion of FFPE blocks in addition to a 4-micron section. Applying this method to biopsy-like samples (smaller than about 27 mg) could extend the number of biomarker tests on small tissue samples.

[0252] Method

[0253] Breast cancer FFPE blocks were sectioned for H&E, stained for HER2 and Ki67 on Benchmark Ultra, and scored by a pathologist. Starting material included either two, 25-micron curls from each FFPE block or biopsy-like samples completely removed from the FFPE block to generate single cells, with a minimum of 200,000 cells as input for antibody staining. Cells were stained in suspension with HER2, Ki67, or Cytokeratin 8&18 antibodies, and DNA content was assessed via DAPI staining. All samples were analyzed on a BD FACSMelody flow cytometerand analysis was performed using FCS Express 7 software. HER2+ and Ki67+ cell populations were normalized to the Cytokeratin 8&18+ population to compare across the cohort. The flow percentage of positive cells were then compared to their respective IHC scores.

[0254] Comparing Flow Analysis to IHC Scores

[0255] The population percentage was obtained via gating the cytometric data, such as in accordance with the methods described herein. The positive percentage pulled from the flow analysis represents the positive population expressing the biomarker of interest. Depending on the biomarker of interest, this value may be normalized against the Cytokeratin 8&18 positive population percentage to be able to compare sample to sample. For example, HER2 / we« percentage was divided by the Cytokeratin 8&18 percentage to normalize the HER2 / / / C expression to the present epithelial cells in each respective sample. This normalized value could then be compared to the IHC score generated by the pathologist reading the stained slide stained with the same biomarker. A biomarker like Ki67 does not need to be normalized because all cells in the sample may experience proliferation. The results of this analysis are demonstrated in FIGS. 22 - 24.

[0256] Results

[0257] On average 28,000 single cells were generated per 1 -micron thick section of breast FFPE tissue and 54,000 single cells generated per Img of FFPE sample. Although flow analysis showed no statistical significance between Ki67+ cells and their respective IHC score, there was positive correlation between HER2+ cells per Cytokeratin 8&18+ cells, and their respective HER2 IHC scores with a statistical significance between 0 and 2+ / 3+, and 1+ and 2+ / 3+ scores (see FIGS. 21, 25, and 26).

[0258] Conclusion

[0259] It has been demonstrated that millions of intact single cells can be generated from FFPE curls and entire blocks, using non-enzymatic mechanical dissociation methods. Flow cytometry has the potential to analyze FFPE samples using workflows and technologies that have existed in the hematopathology space for decades. Analysis of single cells from biopsy-like models can be analyzed for aneuploidy using DAPI and may enable additional biomarker analysis from small and limited tissue samples.

[0260] This example demonstrates that (i) mechanical dissociation of FFPE tissue results in intact single cells which retain their surface marker expression; (ii) the application of flowcytometry to visualize surface markers in FFPE tissue is a novel methodology; and (iii) that the application of this methodology could extend the number of biomarker tests on small tissue samples, including aneuploidy analysis.

[0261] Additional Embodiments

[0262] Another aspect of the present disclosure is a method of generating a composition substantially comprised of single cells, wherein the method comprises (i) obtaining an FFPE tissue sample; and (ii) performing one or more dissociation processes on the obtained FFPE tissue sample to generate the composition substantially comprised of the single cells, wherein the composition is free from exogeneous enzymes; and wherein no enzymes are added to the obtained FFPE tissue sample during the performance of the one or more dissociation processes. In some embodiments, the composition substantially including the single cells is a suspension. In some embodiments, the composition substantially including the single cells is a cell pellet.

[0263] Another aspect of the present disclosure is a method of generating a single cell composition, wherein the method comprises (i) obtaining an FFPE sample; (ii) performing one or more mechanical dissociation processes to the obtained FFPE sample to generate a mechanically dissociated sample; (iii) performing one or more filtration processes on the mechanically dissociated sample to provide the single cell composition; wherein the single cell composition is free from exogeneous enzymes; and wherein no enzymes are added (a) to the FFPE sample during the performance of the one or more mechanical dissociation processes, or (b) to the mechanically dissociated sample during the performance of the one or more filtration processes.

[0264] All the U.S. patents, U.S. patent application publications, U.S. patent applications, foreign patents, foreign patent applications and non-patent publications referred to in this specification and / or listed in the Application Data Sheet are incorporated herein by reference, in their entirety. Aspects of the embodiments can be modified, if necessary to employ concepts of the various patents, applications, and publications to provide yet further embodiments.

[0265] Although the present disclosure has been described with reference to a number of illustrative embodiments, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, reasonable variations and modifications are possible in the component parts and / or arrangements of the subject combination arrangement within the scope of the foregoing disclosure, the drawings, and the appended claims withoutdeparting from the spirit of the disclosure. In addition to variations and modifications in the component parts and / or arrangements, alternative uses will also be apparent to those skilled in the art.

Claims

Claims1. A method of generating a single cell composition, comprising: a. obtaining one or more formalin-fixed paraffin-embedded (FFPE) tissue samples; and b. performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition.

2. The method of claim 1, wherein the single cell composition comprises no exogeneous enzymes.

3. The method of any one of claims 1 - 2, wherein no enzymes are added to the obtained one or more FFPE tissue samples during the performance of the one or more non-enzymatic dissociation processes.

4. The method of any one of claims 1 - 3, wherein the one or more FFPE samples are tissue sections / tissue curls.

5. The method of any one of claims 1 - 3, wherein the one or more FFPE samples are tumor blocks, tissue cores, or tissue biopsies.

6. The method of any one of claims 1 - 5, wherein at least 75% of the cells within the single cell composition are present as individual cells.

7. The method of any one of claims 1 - 5, wherein at least 90% of the cells within the single cell composition are present as individual cells.

8. The method of any one of claims 1 - 7, wherein the cells within the single cell composition retain at least 90% of their cell surface biomarkers.

9. The method of any one of claims 1 - 8, wherein the one or more non-enzymatic dissociation processes are performed in the presence of one or more buffers and / or non-enzymatic cell conditioning agents.

10. The method of any one of claims 1 - 8, further comprising contacting the one or more FFPE tissue samples with a buffer and / or a non-enzymatic cell conditioning agent, where the buffer and / or the non-enzymatic cell conditioning agent have a temperature ranging from between about 30°C to about 90°C.

11. The method of claim 10, wherein the temperature is between about 50°C to about 90°C.

12. The method of claim 10, wherein the temperature is between about 60°C to about 90°C.

13. The method of any one of claims 1 - 12, wherein the one or more non-enzymatic dissociation processes comprise one or more mechanical dissociation processes.

14. The method of any one of claims 1 - 12, wherein the performing of one or more non- enzymatic dissociation processes comprises (i) performing one or more mechanical dissociation processes on the obtained one or more FFPE tissue samples to provide one or more mechanically dissociated samples; and (ii) performing one or more filtration processes on the one or more mechanically dissociated samples.

15. The method of claim 14, further comprising agitating and / or sonicating the one or more mechanically dissociated samples prior to and / or after performing the one or more filtration processes.

16. The method of any one of claims 14 - 15, wherein no enzymes are added (a) to the one or more FFPE tissue samples during the performance of the one or more mechanical dissociation processes, or (b) to the mechanically dissociated sample during the performance of the one or more filtration processes.

17. The method of any one of the preceding claims, further comprising analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

18. The method of claim 17, wherein the one or more biomolecules are one or more polypeptides.

19. The method of claim 18, wherein the polypeptides are enzymes, antigens, or antibodies.

20. The method of claim 17, wherein the one or more biomolecules are one or more polynucleotides.

21. The method of claim 20, wherein the one or more polynucleotides are single-stranded polynucleotides or double-stranded polynucleotides.

22. The method of claim 17, wherein the one or more biomolecules are RNA, mRNA, cDNA, DNA, genomic DNA, microRNA, long noncoding RNA, ribosomal RNA, transfer RNA, circular DNA, or mitochondrial DNA.

23. The method of any one of claims 17 - 22, wherein the analyzing and / or measuring of the one or more biomolecules of the cells within the single cell composition comprises performing one of an immunoenzymatic analysis, a cytometric analysis, a chromatographic analysis, a mass analysis, or a sequence analysis.

24. The method of claim 23, wherein the sequence analysis comprises single cell sequencing.

25. The method of claim 24, wherein the single cell sequencing comprises single cell genome sequencing.

26. The method of claim 24, wherein the single cell sequencing comprises single cell transcriptome sequencing.

27. The method of claim 24, wherein the single cell sequencing comprises single cell DNA methylome sequencing.

28. The method of claim 23, wherein the sequence analysis comprises next-generation sequencing.

29. The method of claim 23, wherein the cytometric analysis comprises flow cytometry.

30. The method of claim 23, wherein the cytometric analysis comprises mass cytometry.

31. The method of claim 17, further comprising identifying one or more therapeutic targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

32. The method of claim 17, further comprising identifying one or more combination therapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

33. The method of claim 17, further comprising identifying one or more immunotherapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

34. The method of claim 17, further comprising identifying one or more neoantigens based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

35. The method of claim 17, further comprising determining at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects of clinical trials, therapeutic treatment strategy for at least one subject based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition, escalating therapy, and deescalating therapy.

36. The method of any one of claims 1 - 16, further comprising staining the cells within the single cell composition for the presence of one or more biomarkers.

37. The method of 36, wherein the one or more biomarkers are immune cell markers.

38. The method of claim 36, wherein the one or more biomarkers are tumor cell markers.

39. The method of claim 36, wherein the one or more biomarkers are normal cell markers.

40. The method of claim 36, wherein the one or more biomarkers are selected from the group consisting of cell surface markers, immune checkpoint markers, growth factor receptor markers, hormone receptor markers, and tumor transcription factor markers.

41. The method of any one of claims 36 - 40, wherein the cells are stained with a fluorescent moiety.

42. The method of any one of claims 36 - 40, wherein the cells are stained with a chromogenic moiety.

43. The method of any one of claims 36 - 40, further comprising gating the stained cells into one or more cell populations.

44. The method of any one of claims 36 - 40, further comprising quantifying cells within the single cell composition staining positive for the one or more biomarkers.

45. The method of any one of claims 1 - 16, further comprising quantifying tumor cells within the single cell composition based on the expression one or more tumor cell biomarkers.

46. The method of any one of claims 1 - 16, further comprising quantifying normal cells within the single cell composition based on the expression of one or more normal cell biomarkers.

47. The method of any one of claims 1 - 16, further comprising sorting the cells within the single cell composition into one or more populations of cells based on cell size.

48. The method of any one of claims 36 - 40, further comprising sorting the cells within the single cell composition into one or more populations of cells based on the presence of the one or more stained biomarkers.

49. The method of claim 48, wherein the one or more populations of cells comprises a tumor cell population.

50. The method of claim 49, further comprising extracting one or more nucleic acid molecules from the cells of the tumor cell population.

51. The method of claim 50, further comprising preparing a sequencing library based on the nucleic acid molecules extracted from the cells of the tumor cell population.

52. The method of claim 49, further comprising generating one or more sequencing data sets by sequencing one or more nucleic acid molecules of the cells of the tumor cell population.

53. The method of claim 52, wherein the sequencing comprises single cell sequencing.

54. The method of claim 53, wherein the single cell sequencing comprises single cell genome sequencing.

55. The method of claim 53, wherein the single cell sequencing comprises single cell transcriptome sequencing.

56. The method of claim 53, wherein the single cell sequencing comprises single cell DNA methylome sequencing.

57. The method of claim 52, wherein the sequencing comprises next-generation sequencing.

58. The method of claim 57, wherein the next-generation sequencing comprises pyrosequencing, nanopore sequencing, sequencing-by-synthesis, sequencing-by-ligation, and single molecule real-time sequencing.

59. The method of claim 52, further comprising detecting, characterizing, or identifying one or more low prevalence genetic events in the generated one or more sequencing data sets.

60. The method of claim 59, wherein the one or more low prevalence genetic events are selected from a point mutation, a deletion, an addition, a translocation, a genetic fusion, or an amplification of a gene.

61. The method of claim 52, further comprising identifying one or more subclones in the generated one or more sequencing data sets.

62. The method of claim 61, wherein the identified one or more subclones are one or more low prevalence subclones.

63. The method of claim 62, wherein the one or more low prevalence subclones have a prevalence of less than 0.0001% within the sequenced genomic material.

64. The method of claim 48, wherein the one or more populations of cells comprises a normal cell population; and wherein one or more sequencing data sets are generated by sequencing one or more nucleic acid molecules of the cells of the normal cell population.

65. The method of claim 50, further comprising performing a polymerase chain reaction (PCR) on the extracted one or more nucleic acid molecules.

66. The method of claim 1, further comprising performing one or more histological examinations on the obtained one or more FFPE tissue samples; and determining whether to generate the single cell composition based on the results of the one or more performed histological examinations.

67. A method of generating a single cell composition, comprising:a. obtaining one or more formalin-fixed paraffin-embedded (FFPE) tissue samples; b. performing one or more histological examinations on at least a portion of the obtained one or more FFPE tissue samples; c. determining whether to generate the single cell composition based on the results of the one or more performed histological examinations; and d. performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition.

68. The method of claim 67, wherein the one or more histological examination comprises a morphological analysis.

69. The method of claim 67, wherein the one or more histological examination comprises an immunocytochemical analysis.

70. The method of claim 69, wherein the immunocytochemical analysis comprises an immunohistochemical analysis of one or more biomarkers.

71. The method of claim 69, wherein the immunocytochemical analysis comprises in situ hybridization.

72. The method of claim 67, wherein the generated single cell composition comprises no exogeneous enzymes.

73. The method of claim 67, wherein no enzymes are added to the obtained one or more FFPE tissue samples during the performance of the one or more non-enzymatic dissociation processes.

74. The method of any one of claims 67 - 73, further comprising analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

75. The method of claim 74, wherein the one or more biomolecules are one or more polypeptides.

76. The method of claim 75, wherein the polypeptides are enzymes, antigens, or antibodies.

77. The method of claim 74, wherein the one or more biomolecules are one or more polynucleotides.

78. The method of claim 77, wherein the one or more polynucleotides are single- stranded polynucleotides or double-stranded polynucleotides.

79. The method of claim 75, wherein the one or more biomolecules are RNA, mRNA, cDNA, DNA, genomic DNA, microRNA, long noncoding RNA, ribosomal RNA, transfer RNA, circular DNA, or mitochondrial DNA.

80. The method of any one of claims 74 - 79, wherein the analyzing and / or measuring of the one or more biomolecules of the cells within the single cell composition comprises performing one of an immunoenzymatic analysis, cytometric analysis, a chromatographic analysis, a mass analysis, or a sequence analysis.

81. The method of claim 80, wherein the sequence analysis comprises single cell sequencing.

82. The method of claim 81, wherein the single cell sequencing comprises single cell genome sequencing.

83. The method of claim 81, wherein the single cell sequencing comprises single cell transcriptome sequencing.

84. The method of claim 81, wherein the single cell sequencing comprises single cell DNA methylome sequencing.

85. The method of claim 80, wherein the sequence analysis comprises next-generation sequencing.

86. The method of claim 74, further comprising identifying one or more therapeutic targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

87. The method of claim 74, further comprising identifying one or more combination therapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

88. The method of claim 74, further comprising identifying one or more immunotherapy targets based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

89. The method of claim 74, further comprising identifying one or more neoantigens based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

90. The method of claim 74, further comprising determining at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy,deescalating therapy, or therapeutic treatment strategy for at least one subject based on the analyzing and / or measuring one or more biomolecules of the cells within the single cell composition.

91. A method of sequencing one or more target nucleic acid molecules within a single cell composition, comprising: obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition; and sequencing one or more target nucleic acid molecules of the cells within the generated single cell composition.

92. The method of claim 91, wherein the sequencing comprises single cell sequencing.

93. The method of claim 92, wherein the single cell sequencing comprises single cell genome sequencing.

94. The method of claim 92, wherein the single cell sequencing comprises single cell transcriptome sequencing.

95. The method of claim 92, wherein the single cell sequencing comprises single cell DNA methylome sequencing.

96. The method of claim 91, wherein the sequencing comprises next-generation sequencing.

97. The method of any one of claims 91 - 96, wherein the sequencing of the one or more target nucleic acid molecules of the cells within the generated single cell composition generates one or more sequence data sets.

98. The method of claim 97, wherein the generated one or more sequence data sets are utilized to identify one or more therapeutic targets.

99. The method of claim 97, wherein the generated one or more sequence data sets are utilized to identify one or more combination therapy targets.

100. The method of claim 97, wherein the generated one or more sequence data sets are utilized to identify one or more immunotherapy therapy targets.

101. The method of claim 97, wherein the generated one or more sequence data sets are utilized to identify one or more neoantigens.

102. The method of claim 97, wherein the generated one or more sequence data sets are utilized to determine at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion ofsubjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

103. A method of performing a cytometric analysis of cells within a single cell composition, comprising obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cell composition; and performing a cytometric analysis on the cells within the generated single cell composition.

104. The method of claim 103, wherein the cytometric analysis comprises flow cytometry.

105. The method of claim 103, wherein the cytometric analysis comprises fluorescence- activated cell sorting.

106. The method of any one of claims 103 - 105, wherein cytometric analysis generates one or more cytometry data sets.

107. The method of claim 106, wherein the data within the generated one or more cytometry data sets is gated, such as manually or automatically.

108. The method of claim 106, wherein the generated one or more cytometry data sets are utilized to identify one or more therapeutic targets.

109. The method of claim 106, wherein the generated one or more cytometry data sets are utilized to identify one or more combination therapy targets.

110. The method of claim 106, wherein the generated one or more cytometry data sets are utilized to identify one or more immunotherapy therapy targets.

111. The method of claim 106, wherein the generated one or more cytometry data sets are utilized to identify one or more neoantigens.

112. The method of claim 106, wherein the generated one or more cytometry data sets are utilized to determine at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

113. A method of labeling cells within a single cell composition, comprising obtaining one or more FFPE tissue samples; performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate the single cellcomposition; and labeling one or more biomolecules within or on the surface of the cells in the generated single cell composition.

114. The method of claim 113, wherein one or more therapeutic targets are identified based on the labeling of the one or more biomolecules.

115. The method of claim 113, wherein one or more combination therapy targets are identified based on the labeling of the one or more biomolecules.

116. The method of claim 113, wherein one or more combination immunotherapy targets are identified based on the labeling of the one or more biomolecules.

117. The method of claim 113, wherein one or more neoantigens are identified based on the labeling of the one or more biomolecules.

118. The method of claim 113, wherein at least one clinical decision is determined based on the labeling of the one or more biomolecules, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects in clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject.

119. The method of claim 113, wherein the cells within the generated single cell composition are quantified based on the labeling of the one or more biomolecules.

120. The method of claim 113, wherein the labeled one or more biomolecules are quantified based on expression of the one or more biomolecules.

121. The method of claim 113, wherein the labeled one or more biomolecules are scored, either manually or automatically.

122. The method of any one of claims 113- 121, wherein the one or more biomolecules are labeled using an immunocytochemical technique.

123. A method of comparing a first data set derived from an immunoenzymatic analysis to a second data set derived from a cytological analysis, comprising: a. obtaining one or more formalin-fixed paraffin-embedded (FFPE) tissue samples; b. analyzing and / or measuring at least one biomolecule within the one or more FFPE tissue samples to provide the first data set, wherein the analyzing and / or measuring of the at least one biomolecule in the one or more FFPE tissue samples comprises performing the immunoenzymatic analysis on the one or more FFPE tissue samples;c. performing one or more non-enzymatic dissociation processes on the obtained one or more FFPE tissue samples to generate a single cell composition; d. analyzing and / or measuring the at least one biomolecule in the single cell composition to provide the second data set, wherein the analyzing and / or measuring of the at least one biomolecule in the single cell composition comprises performing a cytometric analysis; and f. comparing the first and second data sets.

124. The method of claim 123, wherein the cytometric analysis comprises flow cytometry.

125. The method of claim 123, wherein the cytometric analysis comprises mass cytometry.

126. The method of any one of claims 123 - 125, wherein the immunoenzymatic analysis comprises an immunohistochemical analysis.

127. The method of claim 123, further comprising identifying one or more therapeutic targets based on the comparison of the first and second data sets.

128. The method of claim 123, further comprising identifying one or more combination therapy targets based on the comparison of the first and second data sets.

129. The method of claim 123, further comprising identifying one or more immunotherapy targets based on the comparison of the first and second data sets.

130. The method of claim 123, further comprising determining at least one clinical decision, wherein the at least one clinical decision comprises determining disease prognosis, predicting recurrence of disease, inclusion of subjects of clinical trials, escalating therapy, deescalating therapy, or therapeutic treatment strategy for at least one subject based on the comparison between the first and second data sets.

131. The method of any one of claims 123 - 130, wherein the single cell composition comprises no exogeneous enzymes.

132. The method of any one of claims 123 - 130, wherein no enzymes are added to the obtained one or more FFPE tissue samples during the performance of the one or more non- enzymatic dissociation processes.

133. The method of any one of claims 123 - 130, wherein the one or more FFPE samples are tissue sections / tissue curls.

134. The method of any one of claims 123 - 130, wherein the one or more FFPE samples are tumor blocks, tissue cores, or tissue biopsies.

135. The method of any one of claims 123 - 130, wherein at least 75% of the cells within the single cell composition are present as individual cells.

136. The method of any one of claims 123 - 130, wherein at least 90% of the cells within the single cell composition are present as individual cells.

137. The method of any one of claims 123 - 130, wherein the cells within the single cell composition retain at least 90% of their cell surface biomarkers.

138. The method of any one of claims 123 - 130, wherein the one or more non-enzymatic dissociation processes are performed in the presence of one or more buffers and / or non- enzymatic cell conditioning agents.

139. The method of any one of claims 123 - 130, further comprising contacting the one or more FFPE tissue samples with a buffer and / or a non-enzymatic cell conditioning agent, where the buffer and / or the non-enzymatic cell conditioning agent have a temperature ranging from between about 30°C to about 90°C.

140. The method of claim 139, wherein the temperature is between about 50°C to about 90°C.

141. The method of claim 139, wherein the temperature is between about 60°C to about 90°C.

142. The method of any one of claims 123 - 141, wherein the one or more non-enzymatic dissociation processes comprise one or more mechanical dissociation processes.

143. The method of any one of claims 123 - 141, wherein the performing of one or more non-enzymatic dissociation processes comprises (i) performing one or more mechanical dissociation processes on the obtained one or more FFPE tissue samples to provide one or more mechanically dissociated samples; and (ii) performing one or more fdtration processes on the one or more mechanically dissociated samples.

144. The method of claim 143, further comprising agitating and / or sonicating the one or more mechanically dissociated samples prior to and / or after performing the one or more filtration processes.

145. The method of any one of claims 143 - 144, wherein no enzymes are added (a) to the one or more FFPE tissue samples during the performance of the one or more mechanicaldissociation processes, or (b) to the mechanically dissociated sample during the performance of the one or more filtration processes.

146. The method of any one of claims 123 - 145, wherein the at least one biomolecule is a polypeptide.

147. The method of claim 146, wherein the polypeptides are enzymes, antigens, or antibodies.

148. The method of any one of claims 123 - 145, wherein the at least one biomarker is a normal cell marker.

149. The method of any one of claims 123 - 145, wherein the at least one biomarker is selected from the group consisting of cell surface markers, immune checkpoint markers, growth factor receptor markers, hormone receptor markers, and tumor transcription factor markers.

150. The method of any one of claims 123 - 149, further comprising preparing a third data set, wherein the third data set is derived from a chromatographic analysis, a mass analysis, or a sequence analysis of the cells within the single cell composition.

151. The method of claim 150, wherein the single cell sequencing comprises single cell genome sequencing.

152. The method of claim 150, wherein the single cell sequencing comprises single cell transcriptome sequencing.

153. The method of claim 150, wherein the single cell sequencing comprises single cell DNA methylome sequencing.

154. The method of claim 150, wherein the sequence analysis comprises next-generation sequencing.

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