WO2023097244A1 - Methods of determining chromatin alterations - Google Patents

Methods of determining chromatin alterations Download PDF

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Publication number
WO2023097244A1
WO2023097244A1 PCT/US2022/080381 US2022080381W WO2023097244A1 WO 2023097244 A1 WO2023097244 A1 WO 2023097244A1 US 2022080381 W US2022080381 W US 2022080381W WO 2023097244 A1 WO2023097244 A1 WO 2023097244A1
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cell
chromatin
chromosome
probes
cancer
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PCT/US2022/080381
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French (fr)
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Siyuan WANG
Miao Liu
Mandar MUZUMDAR
Sherry AGABITI
Shengyan JIN
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Yale University
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6813—Hybridisation assays
    • C12Q1/6841—In situ hybridisation
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/156—Polymorphic or mutational markers

Definitions

  • the present embodiments relate to methods for determining chromatin alterations in a cell, to methods of identifying cancer subjects, and to methods of identifying cancer biomarkers by determining chromatin alterations in cancer cells.
  • the three-dimensional architecture of the genome affects genomic functions. Multiple genome architectures at different length scales, including chromatin loops, domains, compartments, and lamina- and nucleolus-associated regions, have been discovered. However, how these structures are arranged in the same cell and how they are mutually correlated in different cell types in mammalian tissue are largely unknown. This is especially true in cancer, where defective three-dimensional chromatin organization can alter cellular behavior and be a hallmark of the disease. What is needed are methods of determining altered three-dimensional chromatin organization and structure in cells that could be cancerous. Embodiments provided for herein fulfill these needs as well as others.
  • the present application provides an in situ method for determining the presence of a chromatin alteration in a cell, wherein the chromatin alteration is associated with a cancer, the method comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of the cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome associated with the chromatin alteration, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cell with the plurality of primary probes under conditions that allow binding of the plurality
  • the method further comprises the step of: g) determining that the cell is cancerous when the chromatin alteration is present in the cell.
  • step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample (e.g., a non- cancerous cell) or a reference value.
  • a control sample e.g., a non- cancerous cell
  • the chromosome segment(s) comprises at least about a 1 -kilobase (kb) DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a 7-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a 10-kb DNA region.
  • the plurality of primary probes bind to a plurality of segments of the chromosome associated with the chromatin alteration.
  • the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome.
  • TAD topologically associating domain
  • the plurality of segments can be located in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50 or more TADs of the chromosome.
  • each of the plurality of segments is located within a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 1-kb -1000- kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about an internal 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140-kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 1-kb - 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140- kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 100-kb DNA region of a unique TAD.
  • the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome. In some embodiments, each of the plurality of segments is located within a unique gene and/or gene regulatory element.
  • the plurality of segments are scattered throughout the entire length of the chromosome associated with the chromatin alteration.
  • At least some of the plurality of primary probes comprise the same readout sequence. In some embodiments, the primary probes binding to the same segment comprise the same readout sequence.
  • the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes.
  • the method may further comprise after step e) and before step f) the steps of: h) removing signals generated by the labels of the secondary probes bound to the primary probes; i) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; j) detecting the labels from the different secondary probes; and k) repeating steps h) through j) for one or more times using different pluralities of secondary probes.
  • the plurality of secondary probes comprise the same set of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise two to five different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise two different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise three different sets of secondary probes. In some embodiments, in step b) and/or step (i) the plurality of secondary probes comprise four different sets of secondary probes.
  • the plurality of secondary probes comprise five different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise more than 5 different sets of secondary probes.
  • each set of secondary probes are labeled with the same dye.
  • the plurality of secondary probes may be labeled with a plurality of dyes.
  • the dye(s) are fluorescent dye(s), such as any of those described herein.
  • step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes. In some embodiments, step f) also comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome. In some embodiments, the method further comprises analyzing 3D chromatin architecture using a machine learning method.
  • the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
  • the labeling is performed using fluorescence in situ hybridization (FISH). In some embodiments, the labeling is performed using RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH).
  • FISH fluorescence in situ hybridization
  • MEFISH RNA multiplexed error-robust fluorescence in situ hybridization
  • the cell is fixed. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the mitochondria of the cell.
  • the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof.
  • the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii). chromatin A and B compartment scheme is altered compared to a non-cancerous cell; iii). the nuclear lamina association profile of chromatin is disrupted in the cell; or iv). the chromosome surface localization profile of chromatin is disrupted in the cell.
  • the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). at least one condensed or decondensed chromosome in the cell; ii). more or less intermixed chromosomal folding of at least one chromosome; iii). at least one chromosome with more or less heterogeneous folding conformations; iv). at least one chromosome with more or less polarized A and B compartment organization; v). altered A and B compartment profile of at least one chromosome; vi). altered Rabi configuration or chromosome orientation in the cell nucleus; or vii). altered radial positioning of at least one chromosome in the cell nucleus.
  • a method for identifying a cancer subject comprising determining the presence of a cancer-associated chromatin alteration in a cell of the subject according to the in situ method of any one of embodiments described herein.
  • a method for identifying a cancer biomarker comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the
  • a method for identifying a cancer biomarker comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the
  • step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample (e.g., a non- cancerous cell, or a cell in a different cancer cell state) or reference value.
  • a control sample e.g., a non- cancerous cell, or a cell in a different cancer cell state
  • step h) the gene(s) that are differentially expressed are identified by comparing expression of said gene(s) to a control sample (e.g., a non- cancerous cell, or a cell in a different cancer cell state) or reference value.
  • a control sample e.g., a non- cancerous cell, or a cell in a different cancer cell state
  • the chromosome segment(s) comprises at least about a 1 -kilobase (kb) DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a 5-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a
  • the chromosome segment(s) comprises at least about a 10-kb DNA region.
  • the plurality of primary probes bind to a plurality of segments of the chromosome associated with the chromatin alteration.
  • the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome.
  • TAD topologically associating domain
  • the plurality of segments can be located in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50 or more TADs of the chromosome.
  • each of the plurality of segments is located within a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 1-kb -1000- kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about an internal 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140- kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 1-kb - 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140-kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
  • each of the plurality of segments comprises about a central 100-kb DNA region of a unique TAD.
  • the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome. In some embodiments, each of the plurality of segments is located within a unique gene and/or gene regulatory element.
  • the plurality of segments are scattered throughout the entire length of the chromosome associated with the chromatin alteration.
  • At least some of the plurality of primary probes comprise the same readout sequence. In some embodiments, the primary probes binding to the same segment comprise the same readout sequence.
  • the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes.
  • the method may further comprise after step e) and before step f) the steps of: i) removing signals generated by the labels of the secondary probes bound to the primary probes; j) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; k) detecting the labels from the different secondary probes; and l) repeating steps i) through k) for one or more times using different pluralities of secondary probes.
  • the plurality of secondary probes comprise the same set of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise two to five different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise two different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise three different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise four different sets of secondary probes.
  • the plurality of secondary probes comprise five different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise more than 5 different sets of secondary probes.
  • each set of secondary probes are labeled with the same dye.
  • the plurality of secondary probes may be labeled with a plurality of dyes.
  • the dye(s) are fluorescent dye(s), such as any of those described herein.
  • step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes. In some embodiments, step f) also comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome.
  • the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
  • the labeling is performed using fluorescence in situ hybridization (FISH). In some embodiments, the labeling is performed using RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH).
  • FISH fluorescence in situ hybridization
  • MEFISH RNA multiplexed error-robust fluorescence in situ hybridization
  • the cell is fixed. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the mitochondria of the cell.
  • the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof.
  • the cancer biomarker is selected from one or more of the following chromatin alterations: i) chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii) chromatin A and B compartment schemes are altered compared to a non-cancerous cell; iii) the nuclear lamina association profile of chromatin is disrupted in the cell; or iv) the chromosome surface localization profile of chromatin is disrupted in the cell.
  • the cancer biomarker is selected from one or more of: i) at least one condensed or decondensed chromosome in the cell; ii) more or less intermixed chromosomal folding of at least one chromosome; iii) at least one chromosome with more or less heterogeneous folding conformations, iv) at least one chromosome with more or less polarized A and B compartment organization; v) altered A and B compartment profile of at least one chromosome; vi) altered Rabi configuration or chromosome orientation in the cell nucleus; or vii) altered radial positioning of at least one chromosome in the cell nucleus.
  • a method for identifying a cancer cell comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in the cell according to the in situ method of any one of embodiments described herein.
  • the cell is determined as cancerous when at least one of the following is detected: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv). alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi). altered cis or intra-chromosomal interactions for human Chrl2; vii).
  • a method for identifying a cancer subject comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in a cell of the subject according to the in situ method of any one of embodiments.
  • the subject is determined to have cancer when at least one of the following is detected in the cell: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv). alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi).
  • the cancer that presents a chromatin alteration in human Chrl2 is a lung cancer or pancreatic cancer.
  • the cancer is an advanced lung cancer or pancreatic cancer.
  • the cancer is a preinvasive or invasive lung cancer or pancreatic cancer.
  • a method of treating a cancer in a subject in need thereof comprising inhibition of expression of at least one gene selected from Baspl, Birc5, Cdca8, Cenph, Cenpk, Cenpw, Cited2, Creb312, Elf3, HlfO, Histlh2bc, Hmgb2, Loxl2, Mcm2, Meg3, Nabpl, Nasp, Rad51, Rfc4, Rfc5, Hatl, Histlhlc, Rpll8, Smc4, and Tead2.
  • the cancer being treated is a lung cancer or pancreatic cancer.
  • the treatment method further comprises determining that a cell of the cancer comprises a chromatin alteration using the in situ method of any one of the embodiments described herein.
  • FIG. 1 depicts an illustration of the multiplexed imaging of nucleome architectures (MINA) and chromatin tracing procedure in cancer tissue.
  • Part A top depicts a schematic of K- MADM-p53 mouse models. Efficient Cre-mediated intra-chromosomal recombination can induce oncogenic Kras activation via removing the translational/transcriptional STOP cassette. Inefficient Cre-mediated inter-chromosomal recombination following DNA replication can reconstitute GFP and tdTomato on different chromosomes and link p53 genotypes to fluorescent labeling.
  • Part B depicts a schematic of MINA in K-MADM-p53 models. Adjacent sections are collected from K-MADM-p53 blocks.
  • Fluorescent imaging is performed on one section, and MINA is performed on an adjacent section.
  • Primary probes are hybridized to the genomic DNA.
  • Dye-labeled secondary probes are sequentially hybridized to the primary probes to visualize the 3D positions of individual target genomic regions, separated by photobleaching.
  • Individual chromatin traces are reconstructed after the sequential secondary probe hybridizations. Further analyses of A and B compartmentalization, associations between chromatin and lamina, and chromosome territory surface associations of different topologically associating domains (TADs) can be performed.
  • TADs topologically associating domains
  • FIG. 2 depicts the discovery of the decompaction of Chr6 in advanced GFP + p53' /_ lung adenocarcinoma (LU AD) tumors. Radii of gyration of individual chromosomes are calculated in green (GFP + p53' /_ ) precancerous, green (GFP + p53' /_ ) advanced LU AD tumor, yellow (GFP + RFP + p53 +/ ”) precancerous and colorless morphologically normal control cells. Two-sample t-test is performed to compare the radii of gyration of chromosomes in different cell groups. The p values smaller than 0.001 are indicated with ***.
  • FIG. 3 depicts the discovery of the altered A and B compartments of Chr6 in advanced GFP + p53' /_ LUAD tumors.
  • Part A depicts A and B compartment scores of Chr6 in colorless morphologically normal control cells, yellow (GFP+ RFP+ p53+/-) precancerous, red (RFP+ p53+/+) precancerous, green (GFP+ p53-/-) precancerous, and green (GFP+ p53-/-) advanced LUAD tumor.
  • Part B depicts principal component analysis of A/B compartment scores calculated in colorless morphologically normal control cells, yellow (GFP+ RFP+ p53+/-) precancerous, red (RFP+ p53+/+) precancerous, green (GFP+ p53-/-) precancerous, and green (GFP+ p53-/-) advanced LUAD tumor.
  • Each dot represents principal components of Chr6 A/B compartment scores from cells in a biological replicate.
  • FIG. 4 depicts the discovery of the altered A and B compartments of Chr6 in advanced GFP + p53' /_ PDAC tumors.
  • FIG. 5 depicts the lamina association ratios for all imaged TADs in different cell states. Error bars represent 95% confidence intervals (C. I.).
  • FIG. 6 depicts the discovery of unconventional relationship between lamina association ratios and A-B compartment scores in advanced GFP + p53' /_ LUAD tumors.
  • blue lines represent compartment B genomic regions and red lines represent compartment A genomic regions.
  • the cartoon on the left represents conventional nucleome architectures and the cartoon on the right represents altered nucleome architectures in advanced green LUAD tumors.
  • FIG. 7 depicts chromosome surface ratios for all imaged TADs in different cell states. Error bars represent 95% confidence intervals (C. I.).
  • FIG. 8 depicts the discovery of unconventional relationship between surface association ratios and A-B compartment scores in advanced GFP + p53' /_ LUAD tumors. Correlations between surface association ratios and A/B compartment scores in colorless morphologically normal control cells, yellow (GFP + RFP + p53 +/ ") precancerous, red (RFP + p53 +/+ ) precancerous, green (GFP + p53' /_ ) precancerous, and green (GFP + p53' /_ ) advanced LU AD tumor.
  • FIGs. 9 A and 9B depict the discovery of altered compaction for 19 autosomes in precancerous and LU AD cells.
  • FIG. 9A depicts graphs of the changes of chromosome compaction levels in cancer cells of different states versus wild-type cells in the 19 chromosomes. The y axis shows the log2 of average fold changes of mean inter-loci distances within chromosomes from wild type (WT) cells to green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
  • FIG. 9B depicts the distributions of mean inter-loci distances of the 19 chromosomes in each cell state.
  • FIG. 10 depicts the discovery of altered demixing levels of 19 autosomes in precancerous and LU AD cells.
  • the graphs show the chromatin intermixing levels in each of the 19 chromosomes.
  • the y axis shows standard deviation of all the normalized mean inter-loci distances within chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
  • FIGs. 11 A and 1 IB depict the discovery of altered levels of conformational heterogeneity for the 19 autosomes in precancerous and LU AD cells.
  • FIG. 11 A depicts graphs of the changes of chromosome conformation heterogeneity levels calculated as the coefficient of variation of inter-loci distances in each of the 19 chromosomes. The y axis shows the log2 of the average fold changes of coefficient of variation from WT cells to green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
  • FIG. 11B depicts coefficient of variation of inter-loci distances between each pair of imaged TADs in each of the 19 chromosomes.
  • FIG. 12 depicts an A-B compartmentalization scheme of different cell groups in E14.5 mouse placenta.
  • Part A depicts the A and B compartments of mouse chromosome 19 in different cell groups.
  • cell group 1 has significantly altered, LU AD tumor-like, unconventional A-B compartmentalization schemes compared with other cell groups. Red bars represent A compartments and blue bars represent B compartments.
  • Part B depicts a t-distributed stochastic neighbor embedding (t-SNE) plot of single-cell RNA expression profiles in E14.5 mouse placenta for cell type identification.
  • FIG. 13 depicts the correlations between surface association ratios and A-B compartment scores in different cell groups in E14.5 mouse placenta. Note that cell group 1 has significantly altered, LU AD tumor-like, unconventional correlations between surface association ratios and compartment scores. Red represents A compartments and blue represents B compartments.
  • FIG. 14 depicts the correlations between lamina association ratios and A-B compartment scores in different cell groups in E14.5 mouse placenta. Note that cell group 1 has significantly altered, LU AD tumor-like, unconventional correlations between lamina association ratios and compartment scores.
  • FIG. 15 depicts the distribution of polarization indices of A-B compartments of all targeted chromosomes in the five cell states (wild type, adenoma red, adenoma yellow, adenoma green, and LU AD green).
  • the y-axis is the polarization index.
  • FIG. 16 depicts the distribution of Rabi configuration scores of single cells in the five cell states (wild type, adenoma red, adenoma yellow, adenoma green, and LU AD green).
  • the y-axis is the Rabi configuration score.
  • FIG. 17 depicts the fold changes of radial scores of chromosomes in each cancer state with respect to those in the WT state. A higher value indicates localization near the nuclear periphery, whereas a lower value indicates localization near the nuclear center.
  • FIG. 18 depicts a Potential of Heat-diffusion for Affinity -based Transition Embedding (PHATE) plot of single-cell clustering of 3D genome folding conformations for wild type, adenoma red, adenoma yellow, adenoma green, and LUAD green cell states.
  • PHATE Heat-diffusion for Affinity -based Transition Embedding
  • FIG. 19 depicts a confusion matrix of the machine learning model.
  • the number in each matrix element represents cell counts.
  • Gray scale indicates the range of cell numbers along each column.
  • FIG. 20 depicts a receiver operating characteristic (ROC) curves showing the true vs false positive rates of machine learning model prediction for each cell state (wild type, LUAD, and adenoma).
  • ROC receiver operating characteristic
  • FIG. 21 depicts a t-distributed stochastic neighbor embedding (t-SNE) plot of single-cell clustering of 3D genome folding conformations of the adenoma cells and LUAD cells.
  • the solid black line best separates preinvasive red and yellow adenoma cells (AdenomaR&Y) and invasive LUAD cells.
  • the preinvasive green adenoma cells (AdenomaG) are dispersed on both sides of the line.
  • FIG. 22 depicts a bar plot of the percentages of cells on the left (preinvasive-like, or Prelike) or right (LUAD-like) side of the black line in FIG. 21 in each of the adenoma red and yellow (AdenomaRY), adenoma green (AdenomaG) and LU AD cell states.
  • FIG. 23 depicts a PHATE plot of single-cell clustering of 3D genome folding conformations in AT2 cells (including WT, adenoma, and LU AD cells) and immune cells.
  • FIG. 24 depicts bar graphs showing changes of chromosome compaction in AT2 cells near immune cells versus those far from immune cells in different cell states.
  • the y-axis shows the log2 of average fold changes of mean inter-loci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenoamR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
  • FIG. 25 depicts bar graphs showing changes of chromosome conformational heterogeneity in AT2 cells near immune cells versus those far from immune cells in different cell states.
  • the y-axis shows the log2 of average fold change of the coefficient of variation of interloci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LUAD) cells.
  • FIG. 26 depicts changes of chromatin intermixing levels in AT2 cells near immune cells versus those far from immune cells in different cell states.
  • the y-axis shows the standard deviation of normalized mean inter-loci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LUAD tumor (LUAD) cells.
  • FIGs. 27A and 27B depict the distribution of polarization indices of chromosome A-B compartments in AT2 cells near and far from immune cells in each cell state (FIG. 27A) and the distribution of rabl scores for AT2 cells near and far from immune cells in each cell state (FIG. 27B.
  • FIG. 28 depicts t-SNE plot of single-cell clustering of 3D genome conformations in AT2 cells near and far from immune cells.
  • FIG. 29 depicts a change of gene expression from adenoma green cells to LUAD cells in genomic regions with unchanged, decreased or increased single-cell A/B compartment (scA/B) scores.
  • the y-axis is the log2 fold change of gene expression.
  • FIG. 30 depicts representative gene ontology terms of genes within marker genomic regions with increased scA/B scores from adenoma red and yellow cells to LU AD cells (top panel) and genes within marker regions with decreased scA/B scores from adenoma red and yellow cells to LUAD cells (bottom panel).
  • FIG. 31 depicts CellTiter-Glo results of arrayed RNAi screen targeting candidate cancer progression driver (CPD) genes.
  • the CPD genes are genes with elevated expression levels in marker genomic regions with increased scA/B scores from adenoma green to LUAD cells.
  • the y-axis is the cell count percentage.
  • compositions, methods, and devices are described in terms of “comprising” various components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of’ or “consist of’ the various components and steps.
  • polynucleotide or “nucleic acid molecule” means a molecule comprising a chain of nucleotides covalently linked by a sugar-phosphate backbone or other equivalent covalent chemistry. Double and single-stranded DNAs and RNAs are typical examples of polynucleotides.
  • oligonucleotide or “oligo” means a short, single-stranded polynucleotide of either DNA or RNA.
  • polypeptide or “protein” means a molecule that comprises at least two amino acid resides linked by a peptide bond to form a polypeptide. In some embodiments, the term “peptide” can also be used.
  • in situ methods for determining a chromatin alteration in a cell are also provided herein.
  • methods for identifying a caner biomarker in a cell using in situ visualization of a cancer-associated chromatin alteration in the cell comprise advanced in situ imaging techniques to accurately label the three-dimensional structure of chromatin in a cell.
  • One such imaging technique described herein is Multiplexed Imaging of Nucleome Architectures (MINA) that combines chromatin tracing, DNA or RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH), and/or sequential protein imaging techniques to measure the multi-scale folding of chromatin, gene expressions, and their associations with nuclear landmarks such as nuclear lamina and nucleoli.
  • the three- dimensional structure of chromatin in a cell can be determined. See, for example, Liu et al., Multiplexed imaging of nucleome architectures in single cells of mammalian tissue, Nature Communications (2020); and Liu et al., Chromatin tracing and multiplexed imaging of nucleome architectures (MINA) and RNAs in single mammalian cells and tissue, Nature Protocols, Vol. 16 ( May 2011), which are both incorporated by reference in their entirety. As provided herein, these methods can be used to determine the three-dimensional structure of chromatin in cancer cells to determine when and how the chromatin structure is altered compared to normal non-cancerous cells.
  • chromatin in a cell can be used to determine whether individual cells are cancerous or precancerous.
  • Such three-dimensional chromatin structures can also be used as cancer biomarkers in a subject. Further, specific genes that may regulate cancer chromatin organization have been identified.
  • chromatin tracing and MINA use a microarray-based DNA oligo pool design and synthesis strategy. Briefly, a template oligo pool is designed to bind to a range of chromatin target areas. Primary probes are then synthesized from the oligo pool via limited cycle PCR, in vitro transcription, reverse transcription, alkaline hydrolysis and oligo purification. To allow multiplexed imaging, each primary probe contains a primary targeting region that targets a genomic locus and one or more overhang regions that allow binding of dye-labeled secondary DNA oligo probes. Primary probes targeting the same target share the same secondary readout sequences.
  • chromatin tracing at the topologically associating domain (TAD)-to-chromosome length scale involved the design of thousands of template oligos unique to the central 100 kb of each TAD. For finer-scale chromatin tracing, 150 template oligos targeting each 5-kb region are typically designed. After probe design and synthesis, all primary probes are hybridized to the genomic targets. Dye-labeled secondary probes are then sequentially introduced and hybridized to the primary probes, producing a distinctively bright signal that indicates the target location. 3D epifluorescence images are then acquired via z-stepping, the fluorescence is extinguished via photobleaching and then new secondary probes are introduced to image the next targets. After image acquisition, 3D positions of targets are mapped and linked to their respective chromatin traces.
  • TAD topologically associating domain
  • the cell boundary is labeled, for example, with oligo-conjugated wheat germ agglutinin (WGA) to distinguish individual cells in tissue sections.
  • WGA oligo-conjugated wheat germ agglutinin
  • any cell boundary label can be used to distinguish individual cell boundaries.
  • immunofluorescence staining is then performed to visualize the nucleoli, for example, with anti-fibrillarin primary antibody and Alexa Fluor 647-conjugated secondary antibody.
  • any nucleoli label or method can be used to visualize the nucleoli.
  • the primary probes after post-fixation of the antibodies, the primary probes are hybridized to their respective chromatin regions. A process of secondary probe hybridization, image acquisition, and photobleaching is repeated until all primary probes have been profiled.
  • nuclei is labeled with a DAPI stain to determine the nuclear lamina positions.
  • any nuclei label may be used to determine the nuclear lamina positions.
  • nuclear lamina may be labeled by co-immunofluorescence targeting nuclear lamin protein(s), such as Lamin A, Lamin Bl, Lamin B2, Lamin C, or their combinations.
  • an in situ method for determining the presence of a chromatin alteration in a cell comprising the steps of a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of the cell, and wherein the plurality of primary probes bind to at least a segment of a chromosome associated with the chromatin alteration, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chro
  • the method may further comprise the step of: determining that the cell is cancerous when a cancer-associated chromatin alteration is present in the cell.
  • the step of detecting the chromatin alteration based of signals of the labels of the secondary probes is detected by comparing the signals to a control sample or a reference value.
  • the control sample is a normal, i.e., non-cancerous cell (preferably of the same cell type), or a cell in a different cancer cell state.
  • the control sample is a non-cancerous cell, or a cell in a different cancer cell state from the same tissue sample.
  • the control sample is a non-cancerous cell, or a cell in a different cancer cell state from the same patient.
  • the reference value is from a table of reference values.
  • the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes.
  • the method further comprises the steps of: h) removing signals generated by the labels of the secondary probes bound to the primary probes; i) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; j) detecting the labels from the different secondary probes; and k) repeating steps h) through j) for one or more times using different pluralities of secondary probes. In some embodiments, between each round or repetition of secondary probe, the prior-bound secondary probes have their label signal extinguished.
  • the prior-bound secondary probes have their label signal extinguished by photobleaching. In this way, already detected label does not interfere with each new round of secondary probe application and label detection.
  • the plurality of secondary probes are labeled with a plurality of dyes. In some embodiments, the plurality of secondary probes are labeled with the same dye. In some embodiments, the dye(s) used are fluorescent dye(s). Labels, including fluorescent dyes, are known in the art.
  • probe labels can comprise, but are not limited to, cyanine dyes (e.g., Cy2, Cy3, Cy3B, Cy5, Cy5.5, Cy7, etc.), Alexa Fluor dyes, Atto dyes, photoswitchable dyes, photoactivatable dyes, fluorescent dyes, metal nanoparticles, semiconductor nanoparticles or “quantum dots”, fluorescent proteins such as GFP (Green Fluorescent Protein), or photoactivabale fluorescent proteins, such as PAGFP, PSCFP, PSCFP2, Dendra, Dendra2, EosFP, tdEos, mEos2, mEos3, PAmCherry, PAtagRFP, mMaple, mMaple2, and mMaple3.
  • cyanine dyes e.g., Cy2, Cy3, Cy3B, Cy5, Cy5.5, Cy7, etc.
  • Alexa Fluor dyes e.g., Alexa Fluor dyes
  • Atto dyes e.g., Alexa Fluor dyes
  • the dyes may be attached to an oligonucleotide sequence via a bond that can be cleaved to release the dyes.
  • a fluorophore may be conjugated to an oligonucleotide via a cleavable bond, such as a photocleavable bond.
  • photocleavable bonds include, but are not limited to, l-(2-nitrophenyl)ethyl,
  • the fluorophore may be conjugated to an oligonucleotide via a disulfide bond.
  • the disulfide bond may be cleaved by a variety of reducing agents such as, but not limited to, dithiothreitol, dithioerythritol, beta-mercaptoethanol, sodium borohydride, thioredoxin, glutaredoxin, trypsinogen, hydrazine, diisobutylaluminum hydride, oxalic acid, formic acid, ascorbic acid, phosphorous acid, tin chloride, glutathione, thioglycolate, 2,3- dimercaptopropanol, 2-mercaptoethylamine, 2-aminoethanol, tris(2-carboxyethyl)phosphine, bis(2-mercaptoethyl) sulfone, N,N'-dimethyl-N,N'-bis(mercapto
  • the fluorophore may be conjugated to an oligonucleotide via one or more phosphorothioate modified nucleotides in which the sulfur modification replaces the bridging and/or non-bridging oxygen.
  • the fluorophore may be cleaved from the oligonucleotide, in certain embodiments, via addition of compounds such as but not limited to iodoethanol, iodine mixed in ethanol, silver nitrate, or mercury chloride.
  • the dyes may be chemically inactivated through reduction or oxidation.
  • a chromophore such as Cy5 or Cy7 may be reduced using sodium borohydride to a stable, non-fluorescence state.
  • a fluorophore may be conjugated to an oligonucleotide via an azo bond, and the azo bond may be cleaved with 2-[(2-N-arylamino)phenylazo]pyridine.
  • a fluorophore may be conjugated to an oligonucleotide via a suitable nucleic acid segment that can be cleaved upon suitable exposure to DNAse, e.g., an exodeoxyribonuclease or an endodeoxyribonuclease. Examples include, but are not limited to, deoxyribonuclease I or deoxyribonuclease II.
  • the cleavage may occur via a restriction endonuclease.
  • Non-limiting examples of potentially suitable restriction endonucleases include BamHI, BsrI, Notl, Xmal, PspAI, Dpnl, Mbol, Mnll, Eco57I, Ksp632I, Dralll, Ahall, Smal, Mlul, Hpal, Apal, Bell, BstEII, TaqI, EcoRI, SacI, Hindll, Haell, Drall, Tsp509I, Sau3AI, Pad, etc. Over 3000 restriction enzymes have been studied in detail, and more than 600 of these are available commercially.
  • a fluorophore may be conjugated to biotin, and the oligonucleotide conjugated to avidin or streptavidin.
  • the probes may be removed using corresponding “toe-hold-probes,” which comprise the same sequence as the probe, as well as an extra number of bases of homology to the encoding probes (e.g., 1-20 extra bases, for example, 5 extra bases). These probes may remove the labeled readout probe through a strand-displacement interaction.
  • the term “light” generally refers to electromagnetic radiation, having any suitable wavelength (or equivalently, frequency).
  • the light may include wavelengths in the optical or visual range (for example, having a wavelength of between about 400 nm and about 700 nm, i.e., “visible light”), infrared wavelengths (for example, having a wavelength of between about 780 nm and 1 mm or 300 micrometers and 700 nm), ultraviolet wavelengths (for example, having a wavelength of between about 400 nm and about 10 nm), or the like.
  • more than one entity may be used, i.e., entities that are chemically different or distinct, for example, structurally. However, in other cases, the entities may be chemically identical or at least substantially chemically identical.
  • the dye is “switchable,” i.e., the signaling can be switched between two or more states, at least one of which emits light having a desired wavelength.
  • the entity may emit no light, or emit light at a different wavelength.
  • an entity may be “activated” to a first state able to produce light having a desired wavelength, and “deactivated” to a second state not able to emit light of the same wavelength.
  • An entity is “photoactivatable” if it can be activated by incident light of a suitable wavelength.
  • Cy5 can be switched between a fluorescent and a dark state in a controlled and reversible manner by light of different wavelengths, i.e., 633 nm (or 642 nm, 647 nm, 656 nm) red light can switch or deactivate Cy5 to a stable dark state, while 405 nm green light can switch or activate the Cy5 back to the fluorescent state.
  • red light can switch or deactivate Cy5 to a stable dark state
  • 405 nm green light can switch or activate the Cy5 back to the fluorescent state.
  • the entity can be reversibly switched between the two or more states, e.g., upon exposure to the proper stimuli.
  • a first stimuli e.g., a first wavelength of light
  • a second stimuli e.g., a second wavelength of light
  • Any suitable method may be used to activate the entity.
  • incident light of a suitable wavelength may be used to activate the entity to emit light, i.e., the entity is “photoswitchable.”
  • the photoswitchable entity can be switched between different light-emitting or nonemitting states by incident light, e.g., of different wavelengths.
  • the light may be monochromatic (e.g., produced using a laser) or polychromatic.
  • the entity may be activated upon stimulation by electric field and/or magnetic field.
  • the entity may be activated upon exposure to a suitable chemical environment, e.g., by adjusting the pH, or inducing a reversible chemical reaction involving the entity, etc.
  • any suitable method may be used to deactivate the entity, and the methods of activating and deactivating the entity need not be the same.
  • the entity may be deactivated upon exposure to incident light of a suitable wavelength, or the entity may be deactivated by waiting a sufficient time.
  • a “switchable” entity can be identified by one of ordinary skill in the art by determining conditions under which an entity in a first state can emit light when exposed to an excitation wavelength, switching the entity from the first state to the second state, e.g., upon exposure to light of a switching wavelength, then showing that the entity, while in the second state can no longer emit light (or emits light at a much reduced intensity) when exposed to the excitation wavelength.
  • a switchable entity may be switched upon exposure to light.
  • the light used to activate the switchable entity may come from an external source, e.g., a light source such as a laser light source, another light-emitting entity proximate the switchable entity, etc.
  • the second, light emitting entity in some cases, may be a fluorescent entity, and in certain embodiments, the second, light-emitting entity may itself also be a switchable entity.
  • the switchable entity includes a first, light-emitting portion (e.g., a fluorophore), and a second portion that activates or “switches” the first portion. For example, upon exposure to light, the second portion of the switchable entity may activate the first portion, causing the first portion to emit light.
  • activator portions include, but are not limited to, Alexa Fluor 405 (Invitrogen), Alexa Fluor 488 (Invitrogen), Cy2 (GE Healthcare), Cy3 (GE Healthcare), Cy3B (GE Healthcare), Cy3.5 (GE Healthcare), or other suitable dyes.
  • Examples of light-emitting portions include, but are not limited to, Cy5, Cy5.5 (GE Healthcare), Cy7 (GE Healthcare), Alexa Fluor 647 (Invitrogen), Alexa Fluor 680 (Invitrogen), Alexa Fluor 700 (Invitrogen), Alexa Fluor 750 (Invitrogen), Alexa Fluor 790 (Invitrogen), DiD, DiR, YOYO-3 (Invitrogen), YO-PRO-3 (Invitrogen), TOT-3 (Invitrogen), TO-PRO-3 (Invitrogen) or other suitable dyes.
  • portions may be linked via a covalent bond, or by a linker, such as those described in detail below.
  • Other light-emitting or activator portions may include portions having two quatemized nitrogen atoms joined by a polymethine chain, where each nitrogen is independently part of a heteroaromatic moiety, such as pyrrole, imidazole, thiazole, pyridine, quinoine, indole, benzothiazole, etc., or part of a nonaromatic amine. In some cases, there may be 5, 6, 7, 8, 9, or more carbon atoms between the two nitrogen atoms.
  • the light-emitting portion and the activator portions when isolated from each other, may each be fluorophores, i.e., entities that can emit light of a certain, emission wavelength when exposed to a stimulus, for example, an excitation wavelength.
  • a switchable entity is formed that comprises the first fluorophore and the second fluorophore
  • the first fluorophore forms a first, light-emitting portion
  • the second fluorophore forms an activator portion that switches that activates or “switches” the first portion in response to a stimulus.
  • the switchable entity may comprise a first fluorophore directly bonded to the second fluorophore, or the first and second entity may be connected via a linker or a common entity.
  • Whether a pair of light-emitting portion and activator portion produces a suitable switchable entity can be tested by methods known to those of ordinary skills in the art. For example, light of various wavelength can be used to stimulate the pair and emission light from the light-emitting portion can be measured to determine whether the pair makes a suitable switch.
  • Cy3 and Cy5 may be linked together to form such an entity.
  • Cy3 is an activator portion that is able to activate Cy5, the light-emission portion.
  • light at or near the absorption maximum (e.g., near 532 nm light for Cy3) of the activation or second portion of the entity may cause that portion to activate the first, lightemitting portion, thereby causing the first portion to emit light (e.g., near 647 nm for Cy5).
  • the first, light-emitting portion can subsequently be deactivated by any suitable technique (e.g., by directing 647 nm red light to the Cy5 portion of the molecule).
  • activator portions include 1,5 IAEDANS, 1,8-ANS, 4-Methylumbelliferone, 5-carboxy-2,7-dichlorofluorescein, 5- Carboxyfluorescein (5-FAM), 5-Carboxynapthofluorescein, 5-Carboxytetramethylrhodamine (5- TAMRA), 5-FAM (5-Carboxyfluorescein), 5-HAT (Hydroxy Tryptamine), 5-Hydroxy Tryptamine (HAT), 5-ROX (carboxy-X-rhodamine), 5-TAMRA (5- Carboxytetramethyirhodamine), 6-Carboxyrhodamine 6G, 6-CR 6G, 6-JOE, 7-Amino-4- methylcoumarin, 7- Aminoactinomycin D (7-AAD), 7-Hydroxy-4-methylcoumarin, 9-Amino-6- chloro-2-methoxyacridine,
  • the methods described herein further comprise the step of using one or more different labeling techniques to selectively label one or more of the cell membrane, the nuclear lamina, epigenetic DNA modifications, histone modifications, or RNA molecule of the cell.
  • nuclear lamina labeling can be performed to confirm that the genomic locus of interest labeled with any of the methods disclosed herein is properly located within the nucleus, and to determine any chromatin alterations as they relate to nuclear positioning.
  • the one or more different labeling techniques comprise fluorescence in situ hybridization (FISH).
  • FISH technique is MERFISH.
  • RNA MERFISH can be used simultaneous or sequentially with chromatin tracing.
  • RNA MERFISH uses primary probes containing a primary targeting region that targets RNA species, and one or more overhang regions that allow binding of dye- labeled secondary DNA oligo probes.
  • Primary probes targeting the same RNA target share the same secondary readout sequences.
  • Nucleic acid probes are assigned within a code space such that the assignments are separated by a Hamming distance, which measures the number of incorrect “reads” in a given pattern that cause the nucleic acid probe to be misinterpreted as a different valid nucleic acid probe.
  • the Hamming distance may be at least 2, at least 3, at least 4, at least 5, at least 6, or the like.
  • the assignments may be formed as a Hamming code, for instance, a Hamming(7, 4) code, a Hamming(15, 11) code, a Hamming(31, 26) code, a Hamming(63, 57) code, a Hamming(127, 120) code, etc.
  • the assignments may form a SECDED code, e.g., a SECDED(8,4) code, a SECDED(16,4) code, a SECDED(16, 11) code, a SECDED(22, 16) code, a SECDED(39, 32) code, a SECDED(72, 64) code, etc.
  • the assignments may form an extended binary Golay code, a perfect binary Golay code, or a ternary Golay code.
  • a modified Hamming distance 4 code is used for MERFISH probe design.
  • Primary probes for each RNA species contain a unique combination of 4 out of 16 readout sequences, forming a unique combinatorial 16-bit binary barcode for each RNA species, with 4 bits being ‘ l’s and 12 bits being ‘0’s.
  • For MERFISH around 48 template oligos for each RNA species are designed. After probe design and synthesis, all primary probes are hybridized to the RNA targets.
  • Dye-labeled secondary probes are then sequentially introduced and hybridized to the secondary readout regions on the primary probes, producing a distinctively bright signal that indicates the target location. Fluorescence images are then acquired, the fluorescence is extinguished via photobleaching or other methods and then new secondary probes are introduced to image the next targets. After image acquisition, positions of targets are mapped and decoded as different RNA species.
  • the genomic locus of interest of any method disclosed herein is located within the nucleus of a cell.
  • the genomic locus of interest is at least one topologically associating domain (TAD).
  • TADs are consecutive chromatin regions that can self-interact, and are sub-structures of a chromosome.
  • at least some of the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within the same TAD.
  • the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TADs.
  • the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TAD on the same chromosome. In some embodiments, the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TAD on multiple chromosomes. For example, see Wang et al., Spatial organization of chromatin domains and compartments in single chromosomes, Science, Vol. 353 (Aug. 2016), which is incorporated by reference in its entirety.
  • the methods comprise using the location of the secondary probes to analyze chromatin architecture.
  • a cell is determined to be cancerous when comprises at least one abnormal three-dimensional chromatin architecture.
  • a cell is determined to be cancerous when one or more chromatin alterations are present in the cell.
  • chromatin alteration is an alteration of chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleolus, nuclear speckles or other nuclear bodies, or any combination thereof.
  • the one or more chromatin alterations are chromatin in the cell is/are condensed or decondensed compared to non-cancerous cells; chromatin A and B compartment scheme is altered compared to non-cancerous cells; the nuclear lamina association profile of chromatin is disrupted in the cell; the chromosome surface localization profile of chromatin is disrupted in the cell; or some combination thereof.
  • the one more chromatin alterations is/are condensed or decondensed chromosome(s) in the cell; more or less intermixed chromosomal folding of at least one chromosome as compared to non-cancerous cells; chromosome(s) with more or less heterogeneous folding conformations as compared to non-cancerous cells; chromosome(s) with more or less polarized A and B compartment organization; altered A and B compartment profile of at least one chromosome; altered Rabi configuration or chromosome orientation in the cell nucleus; altered radial positioning of at least one chromosome in the cell nucleus, or any combination thereof.
  • the one or more chromatin alterations are: chromatin in the cell is condensed or decondensed compared to non-cancerous cells; chromatin A and B compartment scheme is altered compared to non-cancerous cells; the nuclear lamina association profile of chromatin is disrupted in the cell; the chromosome surface localization profile of chromatin is disrupted in the cell; condensed/decondensed chromosomes in the cell; the cell has more or less intermixed chromosomal folding as compared to non-cancerous cells; chromosomes with more or less heterogeneous folding conformations as compared to non-cancerous cells; chromosome(s) with more or less polarized A and B compartment organization; altered A and B compartment profile of at least one chromosome; altered Rabi configuration or chromosome orientation in the cell nucleus; altered radial positioning of at least one chromosome in the cell nucleus, or any combination thereof.
  • a method for identifying a cancer biomarker in a cell issuing in situ visualization of a cancer-associated chromatin alteration in the cell is provided.
  • the method comprises any of the method steps disclosed herein.
  • the method for identifying a cancer biomarker detects one or more abnormal three-dimensional chromatin architecture in a cancer cell.
  • the method for identifying a cancer biomarker detects one or more chromatin alterations in a cancer cell.
  • the chromatin alterations or abnormal three-dimensional chromatin architecture is or is part of the cancer biomarker.
  • the one or more chromatin alterations are any of the chromatin alterations disclosed herein.
  • a method for detecting cancer in a subject using in situ visualization of a chromatin alteration of human Chromosome 12 is provided.
  • the method comprises any of the method steps disclosed herein.
  • the method detects cancer in a subject when at least one abnormal three- dimensional chromatin architecture or chromatin alterations of Chrl2 are detected.
  • the cancer is detected when one or more of the following is detected: altered human Chrl2 compaction level; altered human Chrl2 intermixing/demixing level; altered human Chrl2 heterogeneity level; alternations of A and B compartments for human Chrl2; altered polarization level of A and B compartments for human Chrl2; altered cis or intra-chromosomal interactions for human Chrl2; alternations in nuclear lamina association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and lamina association ratios; alternations in chromosome surface association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; alternations in nuclear speckle association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios; or any combination thereof.
  • the cancer is a lung or pancreatic cancer. In some embodiments, the cancer is a preinvasive cancer. In some embodiments, the cancer is a preinvasive lung or pancreatic cancer. In some embodiments, the cancer is an advanced cancer. In some embodiments, the cancer is an advanced lung or pancreatic cancer.
  • Example 1 Three-dimensional chromatin architectures as diagnostic and therapeutic biomarkers for cancers.
  • DNA is spatially organized and compacted at multiple levels in the cell nucleus.
  • DNA wraps around core histone octamers to form nucleosomes - the structural unit of chromatin fibers 1-3 .
  • Chromatin fibers are further organized into chromatin loops such as promoter-enhancer loops 4 .
  • consecutive chromatin regions can self-interact and form topologically associating domains(TADs) 5,6 .
  • TADs are further assorted into A and B compartments in each chromosome, which largely correspond to active and inactive chromatin 6-8 .
  • each chromosome occupies a spatially distinct nuclear region called a chromosome territory 9 10 .
  • Particular regions of the genome are also known to be spatially associated with other nuclear components such as the nuclear lamina 11 .
  • Correct three-dimensional (3D) chromatin organization maintains essential cellular processes in the human body 12-18 .
  • Defective 3D chromatin organization can alter cellular behavior and can be a hallmark of cancer.
  • Several lines of evidence suggest altered chromatin organization in cancers: 1) architectural elements of the genome such as insulator sequences (e.g.
  • CTCF-binding sites which often mark TAD boundaries
  • regulatory regions promoters and enhancers
  • the epigenome including DNA and histone modifications which is intimately associated with multiple chromatin architectures above, is significantly disrupted in cancer 23-25
  • cancer-related processes such as oncogene- induced cellular senescence and epithelial-to-mesenchymal transition show chromatin organization changes 26,27 .
  • imaging-based 3D genomic and multi-omic technique “multiplexed imaging of nucleome architectures” (MINA) is applied to profile 3D chromatin architectures of lung and pancreatic cancers 18,29-31 , two leading causes of cancer deaths in the United States 32 .
  • This technique enables spatial tracing of numerous genomic regions along individual chromosomes with nanoscale precision, allowing visualization of 3D chromatin architectures within single cells and analysis of variations across cells.
  • K-MADM-p53 mouse LU AD and PDAC models were leveraged, where preinvasive cancer cells and advanced tumors were labeled with different fluorescent colors 33 .
  • MINA was applied in K-MADM-p53 mouse LU AD and PDAC models.
  • chromatin is overall decondensed in Chr6 of LUAD tumor cells in comparison to normal cells; 2) A and B compartment schemes are distinctively altered in LUAD tumors; 3) nuclear lamina association profile of chromatin and the conventional relationship between A-B compartmentalization and nuclear lamina association are disrupted in the tumor cells; 4) chromosome surface localization profile of chromatin and the conventional tendencies for regions with strong A and B compartment strengths to localize to the surface of the chromosome territory are disrupted in the tumor cells. Similar aberrations in the second aspect (A and B compartment schemes) were also recapitulated in PDAC tumors.
  • Genome-wide 3D chromatin organization was also profiled.
  • Several genome-wide 3D chromatin architectural features are distinctively altered in precancerous and LUAD tumor cells: 1) most chromosomes become more condensed in precancerous cells and become similarly decondensed/more decondensed in LUAD tumors than in normal cells; 2) most chromosomes show less intermixed / more demixed folding in precancerous and LUAD tumor cells than in normal cells; 3) most chromosomes become less heterogeneous regarding their folding conformations in precancerous cells and become similarly heterogeneous/more heterogeneous in LUAD tumors.
  • the MADM system was further leveraged to develop K-MADM-p53 mouse models to study subclonal expansions of GFP + /?53' ' cells and RFP + /?53 +/+ cells in preinvasive Ara -induced lung and pancreatic cancer 33 .
  • Lung (LU AD) and pancreatic (PDAC) tumors were generated by inducing Cre recombinase expression to the lung (via intra-tracheal lentiviral inhalation 35 ) or pancreas (via Pt&7-Cre transgene 36 ). Tumors were dissected at timepoints when all states of cancer progression were observed (20-24 weeks post-lentiviral infection in lung and 6-10 weeks in pancreas).
  • the K-MADM-p53 model provides an ideal system to study 3D chromatin organization during cancer progression, as they enable lineage tracing of marked heterogeneous cancer cell populations encompassing all stages of tumor progression within the same mouse, ranging from RFP + preinvasive cells incapable of progression to morphologically similar GFP + preinvasive cells at various states of progression and morphologically distinct GFP + advanced tumors.
  • MINA MINA to K-MADM-p53 mouse cancer models
  • K-MADM- p53 mouse LU AD and PDAC cancer models were applied to K-MADM- p53 mouse LU AD and PDAC cancer models.
  • GFP and RFP fluorescent imaging was performed first to distinguish RFP + preinvasive cells incapable of progression, GFP + preinvasive cells encompassing all states of progression, and GFP + advanced tumors.
  • MINA was them implemented to reconstruct 3D chromatin conformations in single cells and grouped conformations in each cell population.
  • chromatin tracing multiplexed sequential DNA fluorescence in situ hybridization
  • 1000 primary probes were designed to label a 100-kb region using previously validated computational design criteria 29 ’ 30,42 .
  • Each primary probe contained a unique genomic targeting region that hybridized to the genomic region of interest and a nongenomic readout region with sequences shared by all primary probes targeting the same TAD.
  • Dye-labeled readout probes were sequentially hybridized to the primary probes to image the 3D positions of each TAD with nanoscale precision, followed by photobleaching after each round of imaging.
  • the chromatin tracing procedure is illustrated in FIG. 1. After the sequential readout probe hybridization and imaging, individual 3D chromatin traces within single cells were reconstructed and compared to their differences across cells.
  • an oligonucleotide probe library was designed to target 473 regions across the genome.
  • a previously published probe design strategy called DNA MERFISH was used and each target region was assigned a 100-choose-2 combinatorial binary code 47 .
  • the identities of all target genomic regions can be decoded after sequential readout probe hybridization, imaging, and computational decoding.
  • Digestion buffer 5. Sequential hybridization and imaging
  • Imaging buffer 2xSSC + 50 mM Tris + 10% glucose + 2mM Trolox + 0.5 mg/mL glucose oxidase + 40 pg/mL catalase + 50 units/mL(0.1%) murine RNase inhibitor.
  • the compactness of individual chromatin traces were measured in each cell group by calculating the radii of gyration of the chromatin traces 43 .
  • the sum squared Euclidean distance was calculated between each target TAD to the center-of-mass (mean x, y, z position of all target TADs) of the chromosome territory, and the sum was normalized to the number of target TADs.
  • the square-root of the normalized value was then defined as the radius of gyration of the chromatin trace.
  • A-B compartments are largely associated with active (A) or inactive (B) transcriptional states 45 .
  • A-B compartment identities whether each TAD is sorted into compartment A or B
  • This computational pipeline yields the compartment score of each TAD.
  • TADs in compartment A have positive compartment scores and TADs in compartment B have negative compartment scores.
  • chromatin traces in green LU AD cells had significantly altered A-B compartment profiles compared with traces in other cell groups (FIG. 3).
  • TADs 23-28 changed from compartment A TADs in non-tumor cells to compartment B TADs in LUAD tumors.
  • TADs 48-50 changed from compartment B TADs in non-tumor cells to compartment A TADs in LUAD cells.
  • Similar alterations in A and B compartmentalization were also observed in our mouse PDAC cancer models (FIG. 4).
  • chromatin regions tend to be spatially adjacent to the nuclear lamina. These regions are known as lamina-associated domains 11 , and tend to be heterochromatic and transcriptionally inactive 46 . It has been shown that, conventionally, B compartment regions tend to be proximal to the nuclear lamina and A compartment regions tend to localize to the nuclear interior 30 .
  • nuclear lamina positions were approximated by extracting the nucleus periphery positions from DAPI imaging. For each observed TAD, its spatial distance to the nuclear lamina was measured. TADs within 200 nm from the lamina are considered as being associated with the lamina.
  • the lamina association ratios 30 were measured for each of the 50 targeted TADs along Chr6 by calculating the percentage/probability of each of the TADs to be associated with the nuclear lamina.
  • the lamina association ratio profiles are significantly different among the cell groups (FIG. 5). In non-tumor cells, lamina association ratios were negatively correlated with compartment scores, consistent with the conventional chromatin organization where B compartment TADs tend to be adjacent to the nuclear lamina 30 . However, in green LU AD tumor cells, the preferential association between compartment B regions with the nuclear lamina was disrupted (FIG. 6). The lamina association of chromatin regions and the relationship between lamina association and A-B compartmentalization may serve as diagnostic biomarkers for cancer.
  • a computational metric was used 30 .
  • a 3D convex hull of the chromosome territory was built using all imaged TADs. If a TAD is localized to the surface of the 3D convex hull, the TAD was regarded as being located at the chromosome surface.
  • Surface association ratio is defined as the probability of each TAD being localized to the surface of the chromosome territory. The surface association ratio profiles are significantly different among the cell groups (FIG. 7).
  • A-B compartment scores were analyzed to determine how they were correlated with surface association ratios.
  • Previous work in mouse E14.5 fetal liver has revealed a general principle that genomic regions with strong A and B compartment strengths tend to localize to the surface of the chromosome territory 30 .
  • This conventional organization feature was still preserved in non-tumor cell groups in the lung, where surface association ratios were negatively correlated with B compartment scores and positively associated with A compartment scores.
  • green LU AD cells however, this feature was significantly disrupted, where surface association ratios had no correlation with B compartment scores and a weak negative association with A compartment scores (FIG. 8).
  • the tumor-specific chromosome surface localization profile and its relationship with A-B compartmentalization profile may serve as diagnostic and predictive biomarkers for cancer.
  • Genome-wide MINA was applied to WT and MADM mouse lungs (FIGs. 9A, 9B, 10, 11 A, and 1 IB). Chromatin traces were then separately grouped in WT, red (RFP + p53 +/+ ) precancerous, yellow (GFP + RFP + p53 +/ ") precancerous, green (GFP + p53' /_ ) precancerous, and green (GFP + p53' /_ ) advanced LU AD tumor cells, which covered the full spectrum of LU AD progression. Within each cell group, multiple aspects of chromatin organizations were analyzed, including chromatin compaction, chromatin intermixing/demixing, chromatin conformation heterogeneity. Both precancerous and LU AD tumor cells have significantly disrupted chromatin organizations in all aspects mentioned above.
  • Chromatin compaction was compared for all 19 autosomes in the mouse genome during LUAD cancer progression.
  • mean pairwise distances between each pair of target genomic loci were measured, and the distances in WT, green precancerous, red precancerous, yellow precancerous and LUAD states were compared (FIG. 9B).
  • the average of all fold changes of individual mean pairwise distances between each cancer state and the WT state were also quantified. Paired t-test of the mean pairwise distances between each cancer state and the WT state was performed to identify chromosomes with significant changes in compaction (FIG. 9 A).
  • mean pairwise distances between each pair of target genomic loci on a chromosome was measured. Each mean pairwise distance value was then normalized to the average of all mean pairwise distances. The fold change of the standard deviation of normalized mean pairwise distances was then quantified between each cancer state and WT state to compare the differences. A higher standard deviation or variance indicated a higher level of demixing. F-test of the normalized mean pairwise distances between each cancer state and the WT state was performed to identify chromosomes with significant changes in the level of intermixing or demixing (FIG. 10).
  • chromosomes became more demixed in precancerous and LUAD states, which may serve as a diagnostic biomarker for early-stage lung cancers.
  • Chromatin conformation heterogeneity To compare the levels of chromatin conformation heterogeneity among different LUAD progression states and WT, the coefficient of variation (COV, defined as standard deviation/mean) of the pairwise distances between each pair of target genomic loci on a chromosome was measured. The CO Vs between each cancer state was then compared to the WT state (FIGs. 11 A and 1 IB). A higher COV value indicated a higher level of heterogeneity.
  • COV coefficient of variation
  • scRNA-seq single-cell RNA sequencing dataset containing single-cell RNA expression profiles encompassing all stages of LUAD progression was used, denoted as cancer scRNA-seq dataset throughout this manuscript for simplicity 44 .
  • MINA was applied in E14.5 mouse placenta and it was found that placental trophoblast giant cells and a few other cell types have similar unconventional chromatin organization features as those in green LUAD tumor cells (FIGs. 12, 13, and 14).
  • Example 2 Validation and discovery of additional 3D chromatin organization features as biomarkers for cancer using human samples.
  • a chromosome copy refers to a single copy of a chromosome.
  • a chromosome refers to a chromosome species among 22 autosomes, Chromosome X and Chromosome Y.
  • a and B compartmentalization are identified by using a computational pipeline as discussed above or similar pipelines.
  • association between genomic loci with nuclear lamina As described above, the associations between targeted genomic regions and the nuclear lamina can be identified by approximating nuclear lamina positions by extracting the nucleus periphery positions from whole-nuclear stains such as DAPI stain. Alternatively nuclear lamina labeling with e.g. coimmunofluorescence can be performed.
  • nucleolar positions are approximated from nucleolar marker staining such as co-immunofluorescence targeting fibrillarin. For each observed genomic region, its spatial distance to the nucleolus is measured. Genomic regions within a distance threshold from the nucleolus will be considered as being associated with the nucleolus.
  • Genome-wide MINA data allow for quantifying interactions among genomic loci from different chromosomes.
  • Cis-chromosomal interactions may serve as additional cancer biomarkers.
  • Example 3 Functional validations of candidate genes in regulating 3D chromatin architectures.
  • candidate genes listed in Table 1
  • knock-out or knock-down of these genes in mouse LUAD and PDAC cell lines is performed.
  • the 3D chromatin architectures of these cell lines are profiled both before and after the gene perturbations.
  • the chromatin architectures in the cancer cell lines become more conventional.
  • the analyzed features included chromatin compaction, chromatin conformation heterogeneity, chromatin intermixing, A-B compartmentalization, rabl configuration, and radial positioning of chromosomes in the cell nucleus. While chromatin compaction, chromatin conformation heterogeneity and chromatin intermixing changes were reported in Example 1 above, here other analyses were used, including A-B compartmentalization, rabl configuration and radial positioning of chromosomes in the cell nucleus. Preinvasive adenoma cells adopted more polarized A-B compartment configurations than those of WT and LUAD cells (FIG.
  • the analyses above used the ground-truth cell states from MADM lineage tracing to perform cell-state-specific 3D genome analysis. However, can the 3D genome itself encode cancer cell states at the single cell level? To answer this question, different cancer cell states were clustered based on their 3D genome conformations through an unsupervised machine learning method. To implement single-cell clustering of 3D chromatin organizations, a previously developed scA/B score metric for Dip-C data analysis 1 was adapted to image-based 3D genome data. The scA/B score for each genomic locus was calculated as the average A-B compartment scores of all its spatially adjacent genomic loci.
  • Cancer 3D genome organization is independent of spatial proximity to immune cells.
  • Immune cells as major components of the tumor microenvironment, can regulate LU AD progression.
  • Single-cell clustering of 3D genome organizations showed that AT2 cells (cells of origin of LUAD) at different progression stages and immune cells had different 3D genome conformations (FIG. 23).
  • AT2 cells adjacent to and far from immune cells at each progression stage were computationally categorized and compared their 3D genome organization features including chromatin compaction, chromatin conformation heterogeneity, chromatin intermixing, A-B compartmentalization, and rabl configuration.
  • RNA-seq data was obtained of the adenoma green cells and LUAD cells, the two cell states during the key malignancy progression.
  • progression marker regions defined as targeted genomic regions with significantly altered scA/B scores from adenoma green cells to LUAD cells
  • Gene ontology (GO) terms of genes was analyzed within marker genomic regions with significantly increased and decreased scA/B scores from preinvasive adenoma red and yellow cells to invasive LU AD cells.
  • Genes within marker regions with increased scA/B scores were enriched with GO terms including endothelial cell proliferation, positive regulation of intracellular signal transduction, regulation of cellular biosynthetic process, regulation of metabolic processes, regulation of epithelial cell migration and regulation of angiogenesis and vasculature development.
  • genes within marker regions with decreased scA/B scores were enriched with GO terms including intermediate filament organization, innate immune response, cell differentiation, signal transduction by p53, apoptotic signaling pathway and lung development (FIG. 30).

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Abstract

The present application provides methods for determining chromatin alterations in a cell, to methods of identifying cancer subjects, and to methods of identifying cancer biomarkers by determining chromatin alterations in cancer cells.

Description

METHODS OF DETERMINING CHROMATIN ALTERATIONS
CROSS-REFERENCE TO RELATED APPLICATIONS
This patent application claims priority to U.S. Provisional Application No. 63/264,520, filed November 24, 2021, the disclosure of which is herein incorporated by reference in its entirety.
GOVERNMENT FUNDING
This invention was made with government support under CA193200, CA248136 and CA251037 awarded by National Institutes of Health. The government has certain rights in the invention.
FIELD
The present embodiments relate to methods for determining chromatin alterations in a cell, to methods of identifying cancer subjects, and to methods of identifying cancer biomarkers by determining chromatin alterations in cancer cells.
BACKGROUND
The three-dimensional architecture of the genome affects genomic functions. Multiple genome architectures at different length scales, including chromatin loops, domains, compartments, and lamina- and nucleolus-associated regions, have been discovered. However, how these structures are arranged in the same cell and how they are mutually correlated in different cell types in mammalian tissue are largely unknown. This is especially true in cancer, where defective three-dimensional chromatin organization can alter cellular behavior and be a hallmark of the disease. What is needed are methods of determining altered three-dimensional chromatin organization and structure in cells that could be cancerous. Embodiments provided for herein fulfill these needs as well as others.
SUMMARY
In one aspect, the present application provides an in situ method for determining the presence of a chromatin alteration in a cell, wherein the chromatin alteration is associated with a cancer, the method comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of the cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome associated with the chromatin alteration, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome associated with the chromatin alteration, d) contacting the cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, and f) determining the presence of the chromatin alteration based on the detected signals of the labels of the secondary probes.
In some embodiments, the method further comprises the step of: g) determining that the cell is cancerous when the chromatin alteration is present in the cell.
In some embodiments, in step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample (e.g., a non- cancerous cell) or a reference value.
In some embodiments, the chromosome segment(s) comprises at least about a 1 -kilobase (kb) DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
2-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
3-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
4-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
5-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
6-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a 7-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
8-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a 10-kb DNA region.
In some embodiments, wherein the plurality of primary probes bind to a plurality of segments of the chromosome associated with the chromatin alteration.
In some embodiments, the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome. Depending on the chromosome of interest, the plurality of segments can be located in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50 or more TADs of the chromosome.
In some embodiments, each of the plurality of segments is located within a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 1-kb -1000- kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140-kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
In some embodiments, each of the plurality of segments comprises about a central 1-kb - 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140- kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 100-kb DNA region of a unique TAD.
In some embodiments, the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome. In some embodiments, each of the plurality of segments is located within a unique gene and/or gene regulatory element.
In some embodiments, the plurality of segments are scattered throughout the entire length of the chromosome associated with the chromatin alteration.
In some embodiments, at least some of the plurality of primary probes comprise the same readout sequence. In some embodiments, the primary probes binding to the same segment comprise the same readout sequence.
In some embodiments, in step b) the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes. In such embodiments, the method may further comprise after step e) and before step f) the steps of: h) removing signals generated by the labels of the secondary probes bound to the primary probes; i) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; j) detecting the labels from the different secondary probes; and k) repeating steps h) through j) for one or more times using different pluralities of secondary probes.
In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise the same set of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise two to five different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise two different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise three different sets of secondary probes. In some embodiments, in step b) and/or step (i) the plurality of secondary probes comprise four different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise five different sets of secondary probes. In some embodiments, in step b) and/or step i) the plurality of secondary probes comprise more than 5 different sets of secondary probes.
In some embodiments, each set of secondary probes are labeled with the same dye. In some embodiments, the plurality of secondary probes may be labeled with a plurality of dyes. In some embodiments, the dye(s) are fluorescent dye(s), such as any of those described herein.
In some embodiments, step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes. In some embodiments, step f) also comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome. In some embodiments, the method further comprises analyzing 3D chromatin architecture using a machine learning method.
In some embodiments, the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
In some embodiments, the labeling is performed using fluorescence in situ hybridization (FISH). In some embodiments, the labeling is performed using RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH).
In some embodiments, the cell is fixed. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the mitochondria of the cell.
In some embodiments, the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof.
In some embodiments, the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii). chromatin A and B compartment scheme is altered compared to a non-cancerous cell; iii). the nuclear lamina association profile of chromatin is disrupted in the cell; or iv). the chromosome surface localization profile of chromatin is disrupted in the cell.
In some embodiments, the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). at least one condensed or decondensed chromosome in the cell; ii). more or less intermixed chromosomal folding of at least one chromosome; iii). at least one chromosome with more or less heterogeneous folding conformations; iv). at least one chromosome with more or less polarized A and B compartment organization; v). altered A and B compartment profile of at least one chromosome; vi). altered Rabi configuration or chromosome orientation in the cell nucleus; or vii). altered radial positioning of at least one chromosome in the cell nucleus.
In another aspect, provided herein is a method for identifying a cancer subject comprising determining the presence of a cancer-associated chromatin alteration in a cell of the subject according to the in situ method of any one of embodiments described herein.
In another aspect, provided herein is a method for identifying a cancer biomarker, comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, f) determining the presence of a chromatin alteration based on the detected signals of the labels of the secondary probes, and g) identifying the chromatin alteration as a cancer biomarker when the chromatin alteration is present in the cancerous cell.
In another aspect, provided herein is a method for identifying a cancer biomarker, comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, f) determining the presence of a chromatin alteration based on the detected signals of the labels of the secondary probes, g) measuring expression of one or more genes associated with the chromatin alteration when the chromatin alteration is present as determined in step f), and h) identifying gene(s) that are differentially expressed in the cancerous cell as a cancer biomarker.
In some embodiments, in step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample (e.g., a non- cancerous cell, or a cell in a different cancer cell state) or reference value.
In some embodiments, in step h) the gene(s) that are differentially expressed are identified by comparing expression of said gene(s) to a control sample (e.g., a non- cancerous cell, or a cell in a different cancer cell state) or reference value.
In some embodiments, the chromosome segment(s) comprises at least about a 1 -kilobase (kb) DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
2-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
3-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
4-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a 5-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
6-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
7-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a
8-kb DNA region. In some embodiments, the chromosome segment(s) comprises at least about a 10-kb DNA region.
In some embodiments, wherein the plurality of primary probes bind to a plurality of segments of the chromosome associated with the chromatin alteration.
In some embodiments, the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome. Depending on the chromosome of interest, the plurality of segments can be located in 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50 or more TADs of the chromosome.
In some embodiments, each of the plurality of segments is located within a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 1-kb -1000- kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about an internal 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140- kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD.
In some embodiments, each of the plurality of segments comprises about a central 1-kb - 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb - 800-kb, 4-kb - 600-kb, 5-kb - 500-kb, 8-kb - 400-kb, 10-kb - 300-kb, 20-kb - 200-kb, 30-kb -150-kb, 35-kb -100-kb, 50-kb -140-kb, or 80-kb -120-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 2-kb, 5-kb, 10-kb, 20-kb, 30-kb, 40-kb, 50-kb, 60-kb, 70-kb, 80-kb, 90-kb, 100- kb, 110-kb, 120-kb, 130-kb, 140-kb, 150-kb, 160-kb, 170-kb, 180-kb, 190-kb, 200-kb, 250-kb, 300-kb, 350-kb, 400-kb, 450-kb, 500-kb, 550-kb, 600-kb, 650-kb, 700-kb, 750-kb, 800-kb, 850- kb, 900-kb, 950-kb, or 1000-kb DNA region of a unique TAD. In some embodiments, each of the plurality of segments comprises about a central 100-kb DNA region of a unique TAD.
In some embodiments, the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome. In some embodiments, each of the plurality of segments is located within a unique gene and/or gene regulatory element.
In some embodiments, the plurality of segments are scattered throughout the entire length of the chromosome associated with the chromatin alteration.
In some embodiments, at least some of the plurality of primary probes comprise the same readout sequence. In some embodiments, the primary probes binding to the same segment comprise the same readout sequence.
In some embodiments, in step b) the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes. In such embodiments, the method may further comprise after step e) and before step f) the steps of: i) removing signals generated by the labels of the secondary probes bound to the primary probes; j) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; k) detecting the labels from the different secondary probes; and l) repeating steps i) through k) for one or more times using different pluralities of secondary probes.
In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise the same set of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise two to five different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise two different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise three different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise four different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise five different sets of secondary probes. In some embodiments, in step b) and/or step j) the plurality of secondary probes comprise more than 5 different sets of secondary probes.
In some embodiments, each set of secondary probes are labeled with the same dye. In some embodiments, the plurality of secondary probes may be labeled with a plurality of dyes. In some embodiments, the dye(s) are fluorescent dye(s), such as any of those described herein.
In some embodiments, step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes. In some embodiments, step f) also comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome.
In some embodiments, the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
In some embodiments, the labeling is performed using fluorescence in situ hybridization (FISH). In some embodiments, the labeling is performed using RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH).
In some embodiments, the cell is fixed. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell. In some embodiments, the segment(s) of the chromosome associated with the chromatin alteration is located within the mitochondria of the cell.
In some embodiments, the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof.
In some embodiments, the cancer biomarker is selected from one or more of the following chromatin alterations: i) chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii) chromatin A and B compartment schemes are altered compared to a non-cancerous cell; iii) the nuclear lamina association profile of chromatin is disrupted in the cell; or iv) the chromosome surface localization profile of chromatin is disrupted in the cell.
In some embodiments, the cancer biomarker is selected from one or more of: i) at least one condensed or decondensed chromosome in the cell; ii) more or less intermixed chromosomal folding of at least one chromosome; iii) at least one chromosome with more or less heterogeneous folding conformations, iv) at least one chromosome with more or less polarized A and B compartment organization; v) altered A and B compartment profile of at least one chromosome; vi) altered Rabi configuration or chromosome orientation in the cell nucleus; or vii) altered radial positioning of at least one chromosome in the cell nucleus.
In another aspect, provided herein is a method for identifying a cancer cell comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in the cell according to the in situ method of any one of embodiments described herein. In some embodiments, the cell is determined as cancerous when at least one of the following is detected: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv). alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi). altered cis or intra-chromosomal interactions for human Chrl2; vii). alternations in nuclear lamina association profile of human Chrl2; viii). altered relationship between human Chrl2 compartment scores and lamina association ratios; ix). alternations in chromosome surface association profile of human Chrl2; x). altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; xi). alternations in nuclear speckle association profile of human Chrl2; or xii). altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios.
In another aspect, provided herein is a method for identifying a cancer subject comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in a cell of the subject according to the in situ method of any one of embodiments. In some embodiments, the subject is determined to have cancer when at least one of the following is detected in the cell: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv). alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi). altered cis or intra-chromosomal interactions for human Chrl2; vii). alternations in nuclear lamina association profile of human Chrl2; viii). altered relationship between human Chrl2 compartment scores and lamina association ratios; ix). alternations in chromosome surface association profile of human Chrl2; x). altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; xi). alternations in nuclear speckle association profile of human Chrl2; or xii). altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios. In some embodiments, the cancer that presents a chromatin alteration in human Chrl2 is a lung cancer or pancreatic cancer. In some embodiments, the cancer is an advanced lung cancer or pancreatic cancer. In some embodiments, the cancer is a preinvasive or invasive lung cancer or pancreatic cancer.
In another aspect, provided herein is a method of treating a cancer in a subject in need thereof comprising inhibition of expression of at least one gene selected from Baspl, Birc5, Cdca8, Cenph, Cenpk, Cenpw, Cited2, Creb312, Elf3, HlfO, Histlh2bc, Hmgb2, Loxl2, Mcm2, Meg3, Nabpl, Nasp, Rad51, Rfc4, Rfc5, Hatl, Histlhlc, Rpll8, Smc4, and Tead2. In some embodiments, the cancer being treated is a lung cancer or pancreatic cancer.
In some embodiments, the treatment method further comprises determining that a cell of the cancer comprises a chromatin alteration using the in situ method of any one of the embodiments described herein.
BRIEF DESCRIPTION OF THE FIGURES
Some of the illustrative panels in the figures were adapted from the previous publications: Liu, M., Lu, Y., Yang, B. et al. Multiplexed imaging of nucleome architectures in single cells of mammalian tissue. Nat Commun 11, 2907 (2020); and Muzumdar, M., Dorans, K., Chung, K. et al. Clonal dynamics following p53 loss of heterozygosity in Kras-driven cancers. Nat Commun 7, 12685 (2016).
FIG. 1 depicts an illustration of the multiplexed imaging of nucleome architectures (MINA) and chromatin tracing procedure in cancer tissue. Part A (top) depicts a schematic of K- MADM-p53 mouse models. Efficient Cre-mediated intra-chromosomal recombination can induce oncogenic Kras activation via removing the translational/transcriptional STOP cassette. Inefficient Cre-mediated inter-chromosomal recombination following DNA replication can reconstitute GFP and tdTomato on different chromosomes and link p53 genotypes to fluorescent labeling. Part B depicts a schematic of MINA in K-MADM-p53 models. Adjacent sections are collected from K-MADM-p53 blocks. Fluorescent imaging is performed on one section, and MINA is performed on an adjacent section. Primary probes are hybridized to the genomic DNA. Dye-labeled secondary probes are sequentially hybridized to the primary probes to visualize the 3D positions of individual target genomic regions, separated by photobleaching. Individual chromatin traces are reconstructed after the sequential secondary probe hybridizations. Further analyses of A and B compartmentalization, associations between chromatin and lamina, and chromosome territory surface associations of different topologically associating domains (TADs) can be performed.
FIG. 2 depicts the discovery of the decompaction of Chr6 in advanced GFP+ p53'/_ lung adenocarcinoma (LU AD) tumors. Radii of gyration of individual chromosomes are calculated in green (GFP+ p53'/_) precancerous, green (GFP+p53'/_) advanced LU AD tumor, yellow (GFP+ RFP+ p53+/") precancerous and colorless morphologically normal control cells. Two-sample t-test is performed to compare the radii of gyration of chromosomes in different cell groups. The p values smaller than 0.001 are indicated with ***.
FIG. 3 depicts the discovery of the altered A and B compartments of Chr6 in advanced GFP+ p53'/_ LUAD tumors. Part A depicts A and B compartment scores of Chr6 in colorless morphologically normal control cells, yellow (GFP+ RFP+ p53+/-) precancerous, red (RFP+ p53+/+) precancerous, green (GFP+ p53-/-) precancerous, and green (GFP+ p53-/-) advanced LUAD tumor. Part B depicts principal component analysis of A/B compartment scores calculated in colorless morphologically normal control cells, yellow (GFP+ RFP+ p53+/-) precancerous, red (RFP+ p53+/+) precancerous, green (GFP+ p53-/-) precancerous, and green (GFP+ p53-/-) advanced LUAD tumor. Each dot represents principal components of Chr6 A/B compartment scores from cells in a biological replicate.
FIG. 4 depicts the discovery of the altered A and B compartments of Chr6 in advanced GFP+ p53'/_ PDAC tumors.
FIG. 5 depicts the lamina association ratios for all imaged TADs in different cell states. Error bars represent 95% confidence intervals (C. I.).
FIG. 6 depicts the discovery of unconventional relationship between lamina association ratios and A-B compartment scores in advanced GFP+ p53'/_ LUAD tumors. In the two cartoons, blue lines represent compartment B genomic regions and red lines represent compartment A genomic regions. The cartoon on the left represents conventional nucleome architectures and the cartoon on the right represents altered nucleome architectures in advanced green LUAD tumors.
FIG. 7 depicts chromosome surface ratios for all imaged TADs in different cell states. Error bars represent 95% confidence intervals (C. I.).
FIG. 8 depicts the discovery of unconventional relationship between surface association ratios and A-B compartment scores in advanced GFP+ p53'/_ LUAD tumors. Correlations between surface association ratios and A/B compartment scores in colorless morphologically normal control cells, yellow (GFP+ RFP+p53+/") precancerous, red (RFP+ p53+/+) precancerous, green (GFP+ p53'/_) precancerous, and green (GFP+ p53'/_) advanced LU AD tumor.
FIGs. 9 A and 9B depict the discovery of altered compaction for 19 autosomes in precancerous and LU AD cells. FIG. 9A depicts graphs of the changes of chromosome compaction levels in cancer cells of different states versus wild-type cells in the 19 chromosomes. The y axis shows the log2 of average fold changes of mean inter-loci distances within chromosomes from wild type (WT) cells to green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells. FIG. 9B depicts the distributions of mean inter-loci distances of the 19 chromosomes in each cell state.
FIG. 10 depicts the discovery of altered demixing levels of 19 autosomes in precancerous and LU AD cells. The graphs show the chromatin intermixing levels in each of the 19 chromosomes. The y axis shows standard deviation of all the normalized mean inter-loci distances within chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
FIGs. 11 A and 1 IB depict the discovery of altered levels of conformational heterogeneity for the 19 autosomes in precancerous and LU AD cells. FIG. 11 A depicts graphs of the changes of chromosome conformation heterogeneity levels calculated as the coefficient of variation of inter-loci distances in each of the 19 chromosomes. The y axis shows the log2 of the average fold changes of coefficient of variation from WT cells to green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells. FIG. 11B depicts coefficient of variation of inter-loci distances between each pair of imaged TADs in each of the 19 chromosomes.
FIG. 12 depicts an A-B compartmentalization scheme of different cell groups in E14.5 mouse placenta. Part A depicts the A and B compartments of mouse chromosome 19 in different cell groups. Note that cell group 1 has significantly altered, LU AD tumor-like, unconventional A-B compartmentalization schemes compared with other cell groups. Red bars represent A compartments and blue bars represent B compartments. Part B depicts a t-distributed stochastic neighbor embedding (t-SNE) plot of single-cell RNA expression profiles in E14.5 mouse placenta for cell type identification. FIG. 13 depicts the correlations between surface association ratios and A-B compartment scores in different cell groups in E14.5 mouse placenta. Note that cell group 1 has significantly altered, LU AD tumor-like, unconventional correlations between surface association ratios and compartment scores. Red represents A compartments and blue represents B compartments.
FIG. 14 depicts the correlations between lamina association ratios and A-B compartment scores in different cell groups in E14.5 mouse placenta. Note that cell group 1 has significantly altered, LU AD tumor-like, unconventional correlations between lamina association ratios and compartment scores.
FIG. 15 depicts the distribution of polarization indices of A-B compartments of all targeted chromosomes in the five cell states (wild type, adenoma red, adenoma yellow, adenoma green, and LU AD green). The y-axis is the polarization index.
FIG. 16 depicts the distribution of Rabi configuration scores of single cells in the five cell states (wild type, adenoma red, adenoma yellow, adenoma green, and LU AD green). The y-axis is the Rabi configuration score.
FIG. 17 depicts the fold changes of radial scores of chromosomes in each cancer state with respect to those in the WT state. A higher value indicates localization near the nuclear periphery, whereas a lower value indicates localization near the nuclear center.
FIG. 18 depicts a Potential of Heat-diffusion for Affinity -based Transition Embedding (PHATE) plot of single-cell clustering of 3D genome folding conformations for wild type, adenoma red, adenoma yellow, adenoma green, and LUAD green cell states.
FIG. 19 depicts a confusion matrix of the machine learning model. The number in each matrix element represents cell counts. Gray scale indicates the range of cell numbers along each column.
FIG. 20 depicts a receiver operating characteristic (ROC) curves showing the true vs false positive rates of machine learning model prediction for each cell state (wild type, LUAD, and adenoma).
FIG. 21 depicts a t-distributed stochastic neighbor embedding (t-SNE) plot of single-cell clustering of 3D genome folding conformations of the adenoma cells and LUAD cells. The solid black line best separates preinvasive red and yellow adenoma cells (AdenomaR&Y) and invasive LUAD cells. The preinvasive green adenoma cells (AdenomaG) are dispersed on both sides of the line. FIG. 22 depicts a bar plot of the percentages of cells on the left (preinvasive-like, or Prelike) or right (LUAD-like) side of the black line in FIG. 21 in each of the adenoma red and yellow (AdenomaRY), adenoma green (AdenomaG) and LU AD cell states.
FIG. 23 depicts a PHATE plot of single-cell clustering of 3D genome folding conformations in AT2 cells (including WT, adenoma, and LU AD cells) and immune cells.
FIG. 24 depicts bar graphs showing changes of chromosome compaction in AT2 cells near immune cells versus those far from immune cells in different cell states. The y-axis shows the log2 of average fold changes of mean inter-loci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenoamR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LU AD) cells.
FIG. 25 depicts bar graphs showing changes of chromosome conformational heterogeneity in AT2 cells near immune cells versus those far from immune cells in different cell states. The y-axis shows the log2 of average fold change of the coefficient of variation of interloci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LU AD tumor (LUAD) cells.
FIG. 26 depicts changes of chromatin intermixing levels in AT2 cells near immune cells versus those far from immune cells in different cell states. The y-axis shows the standard deviation of normalized mean inter-loci distances for each of the 19 chromosomes in WT, green precancerous (AdenomaG), red precancerous (AdenomaR), yellow precancerous (AdenomaY), and advanced LUAD tumor (LUAD) cells.
FIGs. 27A and 27B depict the distribution of polarization indices of chromosome A-B compartments in AT2 cells near and far from immune cells in each cell state (FIG. 27A) and the distribution of rabl scores for AT2 cells near and far from immune cells in each cell state (FIG. 27B.
FIG. 28 depicts t-SNE plot of single-cell clustering of 3D genome conformations in AT2 cells near and far from immune cells.
FIG. 29 depicts a change of gene expression from adenoma green cells to LUAD cells in genomic regions with unchanged, decreased or increased single-cell A/B compartment (scA/B) scores. The y-axis is the log2 fold change of gene expression. FIG. 30 depicts representative gene ontology terms of genes within marker genomic regions with increased scA/B scores from adenoma red and yellow cells to LU AD cells (top panel) and genes within marker regions with decreased scA/B scores from adenoma red and yellow cells to LUAD cells (bottom panel).
FIG. 31 depicts CellTiter-Glo results of arrayed RNAi screen targeting candidate cancer progression driver (CPD) genes. The CPD genes are genes with elevated expression levels in marker genomic regions with increased scA/B scores from adenoma green to LUAD cells. The y-axis is the cell count percentage.
DETAILED DESCRIPTION
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing, suitable methods and materials are described herein. In the case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting. Other features and advantages of the embodiments provided for herein will be apparent from the present detailed description and claims. All cited references, papers, and patent publications or patents mentioned herein are included by reference in their entirety.
The term “about” or “approximately” means plus or minus 10% of the numerical value of the number with which it is being used. Therefore, about 50% means in the range of 45% 55%. The singular forms “a”, “an”, and “the” include plural reference unless the context clearly dictates otherwise.
The terms “comprise,” “have,” and “include” and their conjugates, as used herein, mean “including but not limited to.” While various compositions, methods, and devices are described in terms of “comprising” various components or steps (interpreted as meaning “including, but not limited to”), the compositions, methods, and devices can also “consist essentially of’ or “consist of’ the various components and steps.
The terms “polynucleotide” or “nucleic acid molecule” means a molecule comprising a chain of nucleotides covalently linked by a sugar-phosphate backbone or other equivalent covalent chemistry. Double and single-stranded DNAs and RNAs are typical examples of polynucleotides. The terms “oligonucleotide” or “oligo” means a short, single-stranded polynucleotide of either DNA or RNA.
The term “polypeptide” or “protein” means a molecule that comprises at least two amino acid resides linked by a peptide bond to form a polypeptide. In some embodiments, the term “peptide” can also be used.
Provide herein are in situ methods for determining a chromatin alteration in a cell. Also provided herein are methods for identifying a caner biomarker in a cell using in situ visualization of a cancer-associated chromatin alteration in the cell. Generally, the methods comprise advanced in situ imaging techniques to accurately label the three-dimensional structure of chromatin in a cell. One such imaging technique described herein is Multiplexed Imaging of Nucleome Architectures (MINA) that combines chromatin tracing, DNA or RNA multiplexed error-robust fluorescence in situ hybridization (MERFISH), and/or sequential protein imaging techniques to measure the multi-scale folding of chromatin, gene expressions, and their associations with nuclear landmarks such as nuclear lamina and nucleoli. In this way, the three- dimensional structure of chromatin in a cell can be determined. See, for example, Liu et al., Multiplexed imaging of nucleome architectures in single cells of mammalian tissue, Nature Communications (2020); and Liu et al., Chromatin tracing and multiplexed imaging of nucleome architectures (MINA) and RNAs in single mammalian cells and tissue, Nature Protocols, Vol. 16 (May 2011), which are both incorporated by reference in their entirety. As provided herein, these methods can be used to determine the three-dimensional structure of chromatin in cancer cells to determine when and how the chromatin structure is altered compared to normal non-cancerous cells. Thus, specific aspects of the three-dimensional structure of chromatin in a cell can be used to determine whether individual cells are cancerous or precancerous. Such three-dimensional chromatin structures can also be used as cancer biomarkers in a subject. Further, specific genes that may regulate cancer chromatin organization have been identified.
In some embodiments, chromatin tracing and MINA use a microarray-based DNA oligo pool design and synthesis strategy. Briefly, a template oligo pool is designed to bind to a range of chromatin target areas. Primary probes are then synthesized from the oligo pool via limited cycle PCR, in vitro transcription, reverse transcription, alkaline hydrolysis and oligo purification. To allow multiplexed imaging, each primary probe contains a primary targeting region that targets a genomic locus and one or more overhang regions that allow binding of dye-labeled secondary DNA oligo probes. Primary probes targeting the same target share the same secondary readout sequences. In some embodiments, chromatin tracing at the topologically associating domain (TAD)-to-chromosome length scale involved the design of thousands of template oligos unique to the central 100 kb of each TAD. For finer-scale chromatin tracing, 150 template oligos targeting each 5-kb region are typically designed. After probe design and synthesis, all primary probes are hybridized to the genomic targets. Dye-labeled secondary probes are then sequentially introduced and hybridized to the primary probes, producing a distinctively bright signal that indicates the target location. 3D epifluorescence images are then acquired via z-stepping, the fluorescence is extinguished via photobleaching and then new secondary probes are introduced to image the next targets. After image acquisition, 3D positions of targets are mapped and linked to their respective chromatin traces.
In some embodiments, the cell boundary is labeled, for example, with oligo-conjugated wheat germ agglutinin (WGA) to distinguish individual cells in tissue sections. In some embodiments, any cell boundary label can be used to distinguish individual cell boundaries. In some embodiments, immunofluorescence staining is then performed to visualize the nucleoli, for example, with anti-fibrillarin primary antibody and Alexa Fluor 647-conjugated secondary antibody. In some embodiments, any nucleoli label or method can be used to visualize the nucleoli. In some embodiments, after post-fixation of the antibodies, the primary probes are hybridized to their respective chromatin regions. A process of secondary probe hybridization, image acquisition, and photobleaching is repeated until all primary probes have been profiled. Finally, the nuclei is labeled with a DAPI stain to determine the nuclear lamina positions. In some embodiments, any nuclei label may be used to determine the nuclear lamina positions. In some embodiments, nuclear lamina may be labeled by co-immunofluorescence targeting nuclear lamin protein(s), such as Lamin A, Lamin Bl, Lamin B2, Lamin C, or their combinations. Once all of the labeling and imaging is complete, chromatin traces, nuclear lamina and nucleolar positions are reconstructed within single cells.
In some embodiments, an in situ method for determining the presence of a chromatin alteration in a cell is provided. In some embodiments the method comprising the steps of a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of the cell, and wherein the plurality of primary probes bind to at least a segment of a chromosome associated with the chromatin alteration, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome associated with the chromatin alteration, d) contacting the cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, and f) determining the presence of the chromatin alteration based on the detected signals of the labels of the secondary probes.
In some embodiments, the method may further comprise the step of: determining that the cell is cancerous when a cancer-associated chromatin alteration is present in the cell.
In some embodiments, the step of detecting the chromatin alteration based of signals of the labels of the secondary probes is detected by comparing the signals to a control sample or a reference value. In some embodiments, the control sample is a normal, i.e., non-cancerous cell (preferably of the same cell type), or a cell in a different cancer cell state. In some embodiments, the control sample is a non-cancerous cell, or a cell in a different cancer cell state from the same tissue sample. In some embodiments, the control sample is a non-cancerous cell, or a cell in a different cancer cell state from the same patient. In some embodiments, the reference value is from a table of reference values.
In some embodiments, the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes. In such embodiments, the method further comprises the steps of: h) removing signals generated by the labels of the secondary probes bound to the primary probes; i) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; j) detecting the labels from the different secondary probes; and k) repeating steps h) through j) for one or more times using different pluralities of secondary probes. In some embodiments, between each round or repetition of secondary probe, the prior-bound secondary probes have their label signal extinguished. In some embodiments, the prior-bound secondary probes have their label signal extinguished by photobleaching. In this way, already detected label does not interfere with each new round of secondary probe application and label detection. In some embodiments, the plurality of secondary probes are labeled with a plurality of dyes. In some embodiments, the plurality of secondary probes are labeled with the same dye. In some embodiments, the dye(s) used are fluorescent dye(s). Labels, including fluorescent dyes, are known in the art. For example, probe labels can comprise, but are not limited to, cyanine dyes (e.g., Cy2, Cy3, Cy3B, Cy5, Cy5.5, Cy7, etc.), Alexa Fluor dyes, Atto dyes, photoswitchable dyes, photoactivatable dyes, fluorescent dyes, metal nanoparticles, semiconductor nanoparticles or “quantum dots”, fluorescent proteins such as GFP (Green Fluorescent Protein), or photoactivabale fluorescent proteins, such as PAGFP, PSCFP, PSCFP2, Dendra, Dendra2, EosFP, tdEos, mEos2, mEos3, PAmCherry, PAtagRFP, mMaple, mMaple2, and mMaple3. Other suitable signaling entities are known to those of ordinary skill in the art. See, e.g., U.S. Pat. No. 7,838,302 or U.S. Pat. Apl. Ser. No. 61/979,436, each incorporated herein by reference in its entirety.
In one set of embodiments, the dyes may be attached to an oligonucleotide sequence via a bond that can be cleaved to release the dyes. In one set of embodiments, a fluorophore may be conjugated to an oligonucleotide via a cleavable bond, such as a photocleavable bond. Nonlimiting examples of photocleavable bonds include, but are not limited to, l-(2-nitrophenyl)ethyl,
2-nitrobenzyl, biotin phosphoramidite, acrylic phosphoramidite, diethylaminocoumarin, 1 -(4,5- dimethoxy-2-nitrophenyl)ethyl, cyclo-dodecyl (dimethoxy-2-nitrophenyl)ethyl, 4-aminomethyl-
3 -nitrobenzyl, (4-nitro-3-(l-chlorocarbonyloxyethyl)phenyl)methyl-S-acetylthioic acid ester, (4- nitro-3-(l-thlorocarbonyloxyethyl)phenyl)methyl-3-(2-pyridyldithiopropionic acid) ester, 3-
(4, 4'-dimethoxytrityl)-l-(2-nitrophenyl)-propane-l,3-diol-[2-cy anoethyl -(N,N-diisopropyl)]- phosphoramidite, l-[2-nitro-5-(6-trifluoroacetylcaproamidomethyl)phenyl]-ethyl-[2-cyano-ethyl- (N,N-diisopropyl)]-phosphoramidite, l-[2-nitro-5-(6-(4,4'- dimethoxytrityloxy)butyramidomethyl)phenyl]-ethyl-[2-cyanoethyl-(N,N-diisopropyl)]- phosphoramidite, l-[2-nitro-5-(6-(N-(4,4'-dimethoxytrityl))-biotinamidocaproamido- methyl)phenyl]-ethyl-[2-cyanoethyl-(N,N-diisopropyl)]-phosphoramidite, or similar linkers. In another set of embodiments, the fluorophore may be conjugated to an oligonucleotide via a disulfide bond. The disulfide bond may be cleaved by a variety of reducing agents such as, but not limited to, dithiothreitol, dithioerythritol, beta-mercaptoethanol, sodium borohydride, thioredoxin, glutaredoxin, trypsinogen, hydrazine, diisobutylaluminum hydride, oxalic acid, formic acid, ascorbic acid, phosphorous acid, tin chloride, glutathione, thioglycolate, 2,3- dimercaptopropanol, 2-mercaptoethylamine, 2-aminoethanol, tris(2-carboxyethyl)phosphine, bis(2-mercaptoethyl) sulfone, N,N'-dimethyl-N,N'-bis(mercaptoacetyl)hydrazine, 3- mercaptoproptionate, dimethylformamide, thiopropyl-agarose, tri-n-butylphosphine, cysteine, iron sulfate, sodium sulfite, phosphite, hypophosphite, phosphorothioate, or the like, and/or combinations of any of these. In another embodiment, the fluorophore may be conjugated to an oligonucleotide via one or more phosphorothioate modified nucleotides in which the sulfur modification replaces the bridging and/or non-bridging oxygen. The fluorophore may be cleaved from the oligonucleotide, in certain embodiments, via addition of compounds such as but not limited to iodoethanol, iodine mixed in ethanol, silver nitrate, or mercury chloride. In yet another set of embodiments, the dyes may be chemically inactivated through reduction or oxidation. For example, in one embodiment, a chromophore such as Cy5 or Cy7 may be reduced using sodium borohydride to a stable, non-fluorescence state. In still another set of embodiments, a fluorophore may be conjugated to an oligonucleotide via an azo bond, and the azo bond may be cleaved with 2-[(2-N-arylamino)phenylazo]pyridine. In yet another set of embodiments, a fluorophore may be conjugated to an oligonucleotide via a suitable nucleic acid segment that can be cleaved upon suitable exposure to DNAse, e.g., an exodeoxyribonuclease or an endodeoxyribonuclease. Examples include, but are not limited to, deoxyribonuclease I or deoxyribonuclease II. In one set of embodiments, the cleavage may occur via a restriction endonuclease. Non-limiting examples of potentially suitable restriction endonucleases include BamHI, BsrI, Notl, Xmal, PspAI, Dpnl, Mbol, Mnll, Eco57I, Ksp632I, Dralll, Ahall, Smal, Mlul, Hpal, Apal, Bell, BstEII, TaqI, EcoRI, SacI, Hindll, Haell, Drall, Tsp509I, Sau3AI, Pad, etc. Over 3000 restriction enzymes have been studied in detail, and more than 600 of these are available commercially. In yet another set of embodiments, a fluorophore may be conjugated to biotin, and the oligonucleotide conjugated to avidin or streptavidin. An interaction between biotin and avidin or streptavidin allows the fluorophore to be conjugated to the oligonucleotide, while sufficient exposure to an excess of addition, free biotin could “outcompete” the linkage and thereby cause cleavage to occur. In addition, in another set of embodiments, the probes may be removed using corresponding “toe-hold-probes,” which comprise the same sequence as the probe, as well as an extra number of bases of homology to the encoding probes (e.g., 1-20 extra bases, for example, 5 extra bases). These probes may remove the labeled readout probe through a strand-displacement interaction. As used herein, the term “light” generally refers to electromagnetic radiation, having any suitable wavelength (or equivalently, frequency). For instance, in some embodiments, the light may include wavelengths in the optical or visual range (for example, having a wavelength of between about 400 nm and about 700 nm, i.e., “visible light”), infrared wavelengths (for example, having a wavelength of between about 780 nm and 1 mm or 300 micrometers and 700 nm), ultraviolet wavelengths (for example, having a wavelength of between about 400 nm and about 10 nm), or the like. In certain cases, as discussed in detail below, more than one entity may be used, i.e., entities that are chemically different or distinct, for example, structurally. However, in other cases, the entities may be chemically identical or at least substantially chemically identical.
In one set of embodiments, the dye is “switchable,” i.e., the signaling can be switched between two or more states, at least one of which emits light having a desired wavelength. In the other state(s), the entity may emit no light, or emit light at a different wavelength. For instance, an entity may be “activated” to a first state able to produce light having a desired wavelength, and “deactivated” to a second state not able to emit light of the same wavelength. An entity is “photoactivatable” if it can be activated by incident light of a suitable wavelength. As a nonlimiting example, Cy5, can be switched between a fluorescent and a dark state in a controlled and reversible manner by light of different wavelengths, i.e., 633 nm (or 642 nm, 647 nm, 656 nm) red light can switch or deactivate Cy5 to a stable dark state, while 405 nm green light can switch or activate the Cy5 back to the fluorescent state. In some cases, the entity can be reversibly switched between the two or more states, e.g., upon exposure to the proper stimuli. For example, a first stimuli (e.g., a first wavelength of light) may be used to activate the switchable entity, while a second stimuli (e.g., a second wavelength of light) may be used to deactivate the switchable entity, for instance, to a non-emitting state. Any suitable method may be used to activate the entity. For example, in one embodiment, incident light of a suitable wavelength may be used to activate the entity to emit light, i.e., the entity is “photoswitchable.” Thus, the photoswitchable entity can be switched between different light-emitting or nonemitting states by incident light, e.g., of different wavelengths. The light may be monochromatic (e.g., produced using a laser) or polychromatic. In another embodiment, the entity may be activated upon stimulation by electric field and/or magnetic field. In other embodiments, the entity may be activated upon exposure to a suitable chemical environment, e.g., by adjusting the pH, or inducing a reversible chemical reaction involving the entity, etc. Similarly, any suitable method may be used to deactivate the entity, and the methods of activating and deactivating the entity need not be the same. For instance, the entity may be deactivated upon exposure to incident light of a suitable wavelength, or the entity may be deactivated by waiting a sufficient time.
Typically, a “switchable” entity can be identified by one of ordinary skill in the art by determining conditions under which an entity in a first state can emit light when exposed to an excitation wavelength, switching the entity from the first state to the second state, e.g., upon exposure to light of a switching wavelength, then showing that the entity, while in the second state can no longer emit light (or emits light at a much reduced intensity) when exposed to the excitation wavelength.
In one set of embodiments, as discussed, a switchable entity may be switched upon exposure to light. In some cases, the light used to activate the switchable entity may come from an external source, e.g., a light source such as a laser light source, another light-emitting entity proximate the switchable entity, etc. The second, light emitting entity, in some cases, may be a fluorescent entity, and in certain embodiments, the second, light-emitting entity may itself also be a switchable entity.
In some embodiments, the switchable entity includes a first, light-emitting portion (e.g., a fluorophore), and a second portion that activates or “switches” the first portion. For example, upon exposure to light, the second portion of the switchable entity may activate the first portion, causing the first portion to emit light. Examples of activator portions include, but are not limited to, Alexa Fluor 405 (Invitrogen), Alexa Fluor 488 (Invitrogen), Cy2 (GE Healthcare), Cy3 (GE Healthcare), Cy3B (GE Healthcare), Cy3.5 (GE Healthcare), or other suitable dyes. Examples of light-emitting portions include, but are not limited to, Cy5, Cy5.5 (GE Healthcare), Cy7 (GE Healthcare), Alexa Fluor 647 (Invitrogen), Alexa Fluor 680 (Invitrogen), Alexa Fluor 700 (Invitrogen), Alexa Fluor 750 (Invitrogen), Alexa Fluor 790 (Invitrogen), DiD, DiR, YOYO-3 (Invitrogen), YO-PRO-3 (Invitrogen), TOT-3 (Invitrogen), TO-PRO-3 (Invitrogen) or other suitable dyes. These may linked together, e.g., covalently, for example, directly, or through a linker, e.g., forming compounds such as, but not limited to, Cy5-Alexa Fluor 405, Cy5-Alexa Fluor 488, Cy5-Cy2, Cy5-Cy3, Cy5-Cy3.5, Cy5.5-Alexa Fluor 405, Cy5.5-Alexa Fluor 488, Cy5.5-Cy2, Cy5.5-Cy3, Cy5.5-Cy3.5, Cy7-Alexa Fluor 405, Cy7-Alexa Fluor 488, Cy7-Cy2, Cy7-Cy3, Cy7-Cy3.5, Alexa Fluor 647-Alexa Fluor 405, Alexa Fluor 647-Alexa Fluor 488, Alexa Fluor 647-Cy2, Alexa Fluor 647-Cy3, Alexa Fluor 647-Cy3.5, Alexa Fluor 750-Alexa Fluor 405, Alexa Fluor 750-Alexa Fluor 488, Alexa Fluor 750-Cy2, Alexa Fluor 750-Cy3, or Alexa Fluor 750-Cy3.5. Those of ordinary skill in the art will be aware of the structures of these and other compounds, many of which are available commercially. The portions may be linked via a covalent bond, or by a linker, such as those described in detail below. Other light-emitting or activator portions may include portions having two quatemized nitrogen atoms joined by a polymethine chain, where each nitrogen is independently part of a heteroaromatic moiety, such as pyrrole, imidazole, thiazole, pyridine, quinoine, indole, benzothiazole, etc., or part of a nonaromatic amine. In some cases, there may be 5, 6, 7, 8, 9, or more carbon atoms between the two nitrogen atoms.
In certain cases, the light-emitting portion and the activator portions, when isolated from each other, may each be fluorophores, i.e., entities that can emit light of a certain, emission wavelength when exposed to a stimulus, for example, an excitation wavelength. However, when a switchable entity is formed that comprises the first fluorophore and the second fluorophore, the first fluorophore forms a first, light-emitting portion and the second fluorophore forms an activator portion that switches that activates or “switches” the first portion in response to a stimulus. For example, the switchable entity may comprise a first fluorophore directly bonded to the second fluorophore, or the first and second entity may be connected via a linker or a common entity. Whether a pair of light-emitting portion and activator portion produces a suitable switchable entity can be tested by methods known to those of ordinary skills in the art. For example, light of various wavelength can be used to stimulate the pair and emission light from the light-emitting portion can be measured to determine whether the pair makes a suitable switch.
As a non-limiting example, Cy3 and Cy5 may be linked together to form such an entity. In this example, Cy3 is an activator portion that is able to activate Cy5, the light-emission portion. Thus, light at or near the absorption maximum (e.g., near 532 nm light for Cy3) of the activation or second portion of the entity may cause that portion to activate the first, lightemitting portion, thereby causing the first portion to emit light (e.g., near 647 nm for Cy5). See, e.g., U.S. Pat. No. 7,838,302, incorporated herein by reference in its entirety. In some cases, the first, light-emitting portion can subsequently be deactivated by any suitable technique (e.g., by directing 647 nm red light to the Cy5 portion of the molecule).
Other non-limiting examples of potentially suitable activator portions include 1,5 IAEDANS, 1,8-ANS, 4-Methylumbelliferone, 5-carboxy-2,7-dichlorofluorescein, 5- Carboxyfluorescein (5-FAM), 5-Carboxynapthofluorescein, 5-Carboxytetramethylrhodamine (5- TAMRA), 5-FAM (5-Carboxyfluorescein), 5-HAT (Hydroxy Tryptamine), 5-Hydroxy Tryptamine (HAT), 5-ROX (carboxy-X-rhodamine), 5-TAMRA (5- Carboxytetramethyirhodamine), 6-Carboxyrhodamine 6G, 6-CR 6G, 6-JOE, 7-Amino-4- methylcoumarin, 7- Aminoactinomycin D (7-AAD), 7-Hydroxy-4-methylcoumarin, 9-Amino-6- chloro-2-methoxyacridine, ABQ, Acid Fuchsin, ACMA (9-Amino-6-chloro-2-methoxyacridine), Acridine Orange, Acridine Red, Acridine Yellow, Acriflavin, Acriflavin Feulgen SITSA, Alexa Fluor 350, Alexa Fluor 405, Alexa Fluor 430, Alexa Fluor 488, Alexa Fluor 500, Alexa Fluor 514, Alexa Fluor 532, Alexa Fluor 546, Alexa Fluor 555, Alexa Fluor 568, Alexa Fluor 594, Alexa Fluor 610, Alexa Fluor 633, Alexa Fluor 635, Alizarin Complexon, Alizarin Red, AMC, AMCA-S, AMCA (Aminomethylcoumarin), AMCA-X, Aminoactinomycin D, Aminocoumarin, Aminomethylcoumarin (AMCA), Anilin Blue, Anthrocyl stearate, APTRA-BTC, APTS, Astrazon Brilliant Red 4G, Astrazon Orange R, Astrazon Red 6B, Astrazon Yellow 7 GLL, Atabrine, ATTO 390, ATTO 425, ATTO 465, ATTO 488, ATTO 495, ATTO 520, ATTO 532, ATTO 550, ATTO 565, ATTO 590, ATM 594, ATTO 610, ATTO 61 IX, ATTO 620, ATTO 633, ATTO 635, ATTO 647, ATTO 647N, ATTO 655, ATTO 680, ATTO 700, ATTO 725, ATTO 740, ATTO-TAG CBQCA, ATTO-TAG FQ, Auramine, Aurophosphine G, Aurophosphine, BAO 9 (Bisaminophenyloxadiazole), BCECF (high pH), BCECF (low pH), Berberine Sulphate, Bimane, Bisbenzamide, Bisbenzimide (Hoechst), bis-BTC, Blancophor FFG, Blancophor SV, BOBO-1, BOBO-3, Bodipy 492/515, Bodipy 493/503, Bodipy 500/510, Bodipy 505/515, Bodipy 530/550, Bodipy 542/563, Bodipy 558/568, Bodipy 564/570, Bodipy 576/589, Bodipy 581/591, Bodipy 630/650-X, Bodipy 650/665-X, Bodipy 665/676, Bodipy Fl, Bodipy FL ATP, Bodipy Fl-Ceramide, Bodipy R6G, Bodipy TMR, Bodipy TMR-X conjugate, Bodipy TMR-X, SE, Bodipy TR, Bodipy TR ATP, Bodipy TR-X SE, BO-PRO-1, BO-PRO-3, Brilliant Sulphoflavin FF, BTC, BTC-5N, Calcein, Calcein Blue, Calcium Crimson, Calcium Green, Calcium Green-1 Ca2+ Dye, Calcium Green-2 Ca2+, Calcium Green-5N Ca2+, Calcium Green-C18 Ca2+, Calcium Orange, Calcofluor White, Carboxy-X-rhodamine (5-ROX), Cascade Blue, Cascade Yellow, Catecholamine, CCF2 (GeneBlazer), CFDA, Chromomycin A, Chromomycin A, CL-NERF, CMFDA, Coumarin Phalloidin, CPM Methylcoumarin, CTC, CTC Formazan, Cy2, Cy3.1 8, Cy3.5, Cy3, Cy5.1 8, cyclic AMP Fluorosensor (FiCRhR), Dabcyl, Dansyl, Dansyl Amine, Dansyl Cadaverine, Dansyl Chloride, Dansyl DHPE, Dansyl fluoride, DAPI, Dapoxyl, Dapoxyl 2, Dapoxyl 3' DCFDA, DCFH (Diehl orodihydrofluorescein Diacetate), DDAO, DHR (Dihydorhodamine 123), Di-4-ANEPPS, Di-8-ANEPPS (non-ratio), DiA (4-Di- 16-ASP), Diehl orodihydrofluorescein Diacetate (DCFH), DiD — Lipophilic Tracer, DiD (DiIC18(5)), DIDS, Dihydorhodamine 123 (DHR), Dil (DiIC18(3)), Dinitrophenol, DiO (DiOC18(3)), DiR, DiR (DiIC18(7)), DM-NERF (high pH), DNP, Dopamine, DTAF, DY-630- NHS, DY-635-NHS, DyLight 405, DyLight 488, DyLight 549, DyLight 633, DyLight 649, DyLight 680, DyLight 800, ELF 97, Eosin, Erythrosin, Erythrosin ITC, Ethidium Bromide, Ethidium homodimer-1 (EthD-1), Euchrysin, EukoLight, Europium (III) chloride, Fast Blue, FDA, Feulgen (Pararosaniline), FIF (Formaldehyd Induced Fluorescence), FITC, Flazo Orange, Fluo-3, Fluo-4, Fluorescein (FITC), Fluorescein Diacetate, Fluoro-Emerald, Fluoro-Gold (Hydroxy stilbamidine), Fluor-Ruby, FluorX, FM 1-43, FM 4-46, Fura Red (high pH), Fura Red/Fluo-3, Fura-2, Fura-2/BCECF, Genacryl Brilliant Red B, Genacryl Brilliant Yellow 10GF, Genacryl Pink 3G, Genacryl Yellow SGF, GeneBlazer (CCF2), Gloxalic Acid, Granular blue, Haematoporphyrin, Hoechst 33258, Hoechst 33342, Hoechst 34580, HPTS, Hydroxy coumarin, Hydroxy stilbamidine (FluoroGold), Hydroxytryptamine, Indo-1, high calcium, Indo-1, low calcium, Indodicarbocyanine (DiD), Indotricarbocyanine (DiR), Intrawhite Cf, JC-1, JO-JO-1, JO-PRO-1, LaserPro, Laurodan, LDS 751 (DNA), LDS 751 (RNA), Leucophor PAF, Leucophor SF, Leucophor WS, Lissamine Rhodamine, Lissamine Rhodamine B, Calcein/Ethidium homodimer, LOLO-1, LO-PRO-1, Lucifer Yellow, Lyso Tracker Blue, Lyso Tracker Blue- White, Lyso Tracker Green, Lyso Tracker Red, Lyso Tracker Yellow, LysoSensor Blue, LysoSensor Green, LysoSensor Yellow/Blue, Mag Green, Magdala Red (Phloxin B), Mag-Fura Red, Mag-Fura-2, Mag-Fura-5, Mag-Indo-1, Magnesium Green, Magnesium Orange, Malachite Green, Marina Blue, Maxiion Brilliant Flavin 10 GFF, Maxiion Brilliant Flavin 8 GFF, Merocyanin, Methoxy coumarin, Mitotracker Green FM, Mitotracker Orange, Mitotracker Red, Mitramycin, Monobromobimane, Monobromobimane (mBBr-GSH), Monochlorobimane, MPS (Methyl Green Pyronine Stilbene), NBD, NBD Amine, Nile Red, Nitrob enzoxadi dole, Noradrenaline, Nuclear Fast Red, Nuclear Yellow, Nylosan Brilliant lavin EBG, Oregon Green, Oregon Green 488-X, Oregon Green, Oregon Green 488, Oregon Green 500, Oregon Green 514, Pacific Blue, Pararosaniline (Feulgen), PBFI, Phloxin B (Magdala Red), Phorwite AR, Phorwite BKL, Phorwite Rev, Phorwite RPA, Phosphine 3R, PKH26 (Sigma), PKH67, PMIA, Pontochrome Blue Black, POPO-1, POPO-3, PO-PRO-1, PO-PRO-3, Primuline, Procion Yellow, Propidium lodid (PI), PyMPO, Pyrene, Pyronine, Pyronine B, Pyrozal Brilliant Flavin 7GF, QSY 7, Quinacrine Mustard, Resorufin, RH 414, Rhod-2, Rhodamine, Rhodamine 110, Rhodamine 123, Rhodamine 5 GLD, Rhodamine 6G, Rhodamine B, Rhodamine B 200, Rhodamine B extra, Rhodamine BB, Rhodamine BG, Rhodamine Green, Rhodamine Phallicidine, Rhodamine Phalloidine, Rhodamine Red, Rhodamine WT, Rose Bengal, S65A, S65C, S65L, S65T, SBFI, Serotonin, Sevron Brilliant Red 2B, Sevron Brilliant Red 4G, Sevron Brilliant Red B, Sevron Orange, Sevron Yellow L, SITS, SITS (Primuline), SITS (Stilbene Isothiosulphonic Acid), SNAFL calcein, SNAFL-1, SNAFL-2, SNARF calcein, SNARF1, Sodium Green, SpectrumAqua, SpectrumGreen, SpectrumOrange, Spectrum Red, SPQ (6- methoxy-N-(3-sulfopropyl)quinolinium), Stilbene, Sulphorhodamine B can C, Sulphorhodamine Extra, SYTO 11, SYTO 12, SYTO 13, SYTO 14, SYTO 15, SYTO 16, SYTO 17, SYTO 18, SYTO 20, SYTO 21, SYTO 22, SYTO 23, SYTO 24, SYTO 25, SYTO 40, SYTO 41, SYTO 42, SYTO 43, SYTO 44, SYTO 45, SYTO 59, SYTO 60, SYTO 61, SYTO 62, SYTO 63, SYTO 64, SYTO 80, SYTO 81, SYTO 82, SYTO 83, SYTO 84, SYTO 85, SYTOX Blue, SYTOX Green, SYTOX Orange, Tetracycline, Tetramethylrhodamine (TAMRA), Texas Red, Texas Red-X conjugate, Thiadicarbocyanine (DiSC3), Thiazine Red R, Thiazole Orange, Thioflavin 5, Thioflavin S, Thioflavin TCN, Thiolyte, Thiozole Orange, Tinopol CBS (Calcofluor White), TMR, TO-PRO-1, TO-PRO-3, TO-PRO-5, TOTO-1, TOTO-3, TRITC (tetramethylrodamine isothiocyanate), True Blue, TruRed, Ultralite, Uranine B, Uvitex SFC, WW 781, X-Rhodamine, XRITC, Xylene Orange, Y66F, Y66H, Y66W, YO-PRO-1, YO-PRO- 3, YOYO-1, YOYO-3, SYBR Green, Thiazole orange (interchelating dyes), or combinations thereof.
In some embodiments, the methods described herein further comprise the step of using one or more different labeling techniques to selectively label one or more of the cell membrane, the nuclear lamina, epigenetic DNA modifications, histone modifications, or RNA molecule of the cell. For example, nuclear lamina labeling can be performed to confirm that the genomic locus of interest labeled with any of the methods disclosed herein is properly located within the nucleus, and to determine any chromatin alterations as they relate to nuclear positioning. In some embodiments, the one or more different labeling techniques comprise fluorescence in situ hybridization (FISH). In some embodiments, the FISH technique is MERFISH.
In some embodiments, RNA MERFISH can be used simultaneous or sequentially with chromatin tracing. Briefly, RNA MERFISH uses primary probes containing a primary targeting region that targets RNA species, and one or more overhang regions that allow binding of dye- labeled secondary DNA oligo probes. Primary probes targeting the same RNA target share the same secondary readout sequences. Nucleic acid probes are assigned within a code space such that the assignments are separated by a Hamming distance, which measures the number of incorrect “reads” in a given pattern that cause the nucleic acid probe to be misinterpreted as a different valid nucleic acid probe. In some embodiments, the Hamming distance may be at least 2, at least 3, at least 4, at least 5, at least 6, or the like. In addition, in one set of embodiments, the assignments may be formed as a Hamming code, for instance, a Hamming(7, 4) code, a Hamming(15, 11) code, a Hamming(31, 26) code, a Hamming(63, 57) code, a Hamming(127, 120) code, etc. In another set of embodiments, the assignments may form a SECDED code, e.g., a SECDED(8,4) code, a SECDED(16,4) code, a SECDED(16, 11) code, a SECDED(22, 16) code, a SECDED(39, 32) code, a SECDED(72, 64) code, etc. In yet another set of embodiments, the assignments may form an extended binary Golay code, a perfect binary Golay code, or a ternary Golay code. In some embodiments, for the combinatorial barcoding of MERFISH in MINA implementations, a modified Hamming distance 4 code is used for MERFISH probe design. Primary probes for each RNA species contain a unique combination of 4 out of 16 readout sequences, forming a unique combinatorial 16-bit binary barcode for each RNA species, with 4 bits being ‘ l’s and 12 bits being ‘0’s. For MERFISH, around 48 template oligos for each RNA species are designed. After probe design and synthesis, all primary probes are hybridized to the RNA targets. Dye-labeled secondary probes are then sequentially introduced and hybridized to the secondary readout regions on the primary probes, producing a distinctively bright signal that indicates the target location. Fluorescence images are then acquired, the fluorescence is extinguished via photobleaching or other methods and then new secondary probes are introduced to image the next targets. After image acquisition, positions of targets are mapped and decoded as different RNA species.
In some embodiments, the genomic locus of interest of any method disclosed herein is located within the nucleus of a cell. In some embodiments, the genomic locus of interest is at least one topologically associating domain (TAD). TADs are consecutive chromatin regions that can self-interact, and are sub-structures of a chromosome. In some embodiments, at least some of the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within the same TAD. In some embodiments, the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TADs. In some embodiments, the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TAD on the same chromosome. In some embodiments, the plurality of primary probes comprise first oligonucleotides that bind to genomic loci of interest within several TAD on multiple chromosomes. For example, see Wang et al., Spatial organization of chromatin domains and compartments in single chromosomes, Science, Vol. 353 (Aug. 2016), which is incorporated by reference in its entirety.
In some embodiments, the methods comprise using the location of the secondary probes to analyze chromatin architecture. In some embodiments, after performing any of the methods disclosed herein, a cell is determined to be cancerous when comprises at least one abnormal three-dimensional chromatin architecture. In some embodiments, a cell is determined to be cancerous when one or more chromatin alterations are present in the cell. In some embodiments, chromatin alteration is an alteration of chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to- centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleolus, nuclear speckles or other nuclear bodies, or any combination thereof. In some embodiments, the one or more chromatin alterations are chromatin in the cell is/are condensed or decondensed compared to non-cancerous cells; chromatin A and B compartment scheme is altered compared to non-cancerous cells; the nuclear lamina association profile of chromatin is disrupted in the cell; the chromosome surface localization profile of chromatin is disrupted in the cell; or some combination thereof. In some embodiments, the one more chromatin alterations is/are condensed or decondensed chromosome(s) in the cell; more or less intermixed chromosomal folding of at least one chromosome as compared to non-cancerous cells; chromosome(s) with more or less heterogeneous folding conformations as compared to non-cancerous cells; chromosome(s) with more or less polarized A and B compartment organization; altered A and B compartment profile of at least one chromosome; altered Rabi configuration or chromosome orientation in the cell nucleus; altered radial positioning of at least one chromosome in the cell nucleus, or any combination thereof. In some embodiments, the one or more chromatin alterations are: chromatin in the cell is condensed or decondensed compared to non-cancerous cells; chromatin A and B compartment scheme is altered compared to non-cancerous cells; the nuclear lamina association profile of chromatin is disrupted in the cell; the chromosome surface localization profile of chromatin is disrupted in the cell; condensed/decondensed chromosomes in the cell; the cell has more or less intermixed chromosomal folding as compared to non-cancerous cells; chromosomes with more or less heterogeneous folding conformations as compared to non-cancerous cells; chromosome(s) with more or less polarized A and B compartment organization; altered A and B compartment profile of at least one chromosome; altered Rabi configuration or chromosome orientation in the cell nucleus; altered radial positioning of at least one chromosome in the cell nucleus, or any combination thereof.
In some embodiments, a method for identifying a cancer biomarker in a cell issuing in situ visualization of a cancer-associated chromatin alteration in the cell is provided. In some embodiments, the method comprises any of the method steps disclosed herein. In some embodiments, the method for identifying a cancer biomarker detects one or more abnormal three-dimensional chromatin architecture in a cancer cell. In some embodiments, the method for identifying a cancer biomarker detects one or more chromatin alterations in a cancer cell. In some embodiments, the chromatin alterations or abnormal three-dimensional chromatin architecture is or is part of the cancer biomarker. In some embodiments, the one or more chromatin alterations are any of the chromatin alterations disclosed herein.
In some embodiments, a method for detecting cancer in a subject using in situ visualization of a chromatin alteration of human Chromosome 12 (Chrl2) is provided. In some embodiments, the method comprises any of the method steps disclosed herein. In some embodiments, the method detects cancer in a subject when at least one abnormal three- dimensional chromatin architecture or chromatin alterations of Chrl2 are detected. In some embodiments, the cancer is detected when one or more of the following is detected: altered human Chrl2 compaction level; altered human Chrl2 intermixing/demixing level; altered human Chrl2 heterogeneity level; alternations of A and B compartments for human Chrl2; altered polarization level of A and B compartments for human Chrl2; altered cis or intra-chromosomal interactions for human Chrl2; alternations in nuclear lamina association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and lamina association ratios; alternations in chromosome surface association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; alternations in nuclear speckle association profile of human Chrl2; altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios; or any combination thereof. In some embodiments, the cancer is a lung or pancreatic cancer. In some embodiments, the cancer is a preinvasive cancer. In some embodiments, the cancer is a preinvasive lung or pancreatic cancer. In some embodiments, the cancer is an advanced cancer. In some embodiments, the cancer is an advanced lung or pancreatic cancer.
EXAMPLES
The present invention is also described and demonstrated by way of the following examples. However, the use of these and other examples anywhere in the specification is illustrative only and in no way limits the scope and meaning of the invention or of any exemplified term. Likewise, the invention is not limited to any particular preferred embodiments described here. Many modifications and variations of the invention may be apparent to those skilled in the art upon reading this specification, and such variations can be made without departing from the invention in spirit or in scope. The invention is to be limited only by the appended claims, including the full scope of equivalents to which those claims are entitled.
Example 1: Three-dimensional chromatin architectures as diagnostic and therapeutic biomarkers for cancers.
Introduction
DNA is spatially organized and compacted at multiple levels in the cell nucleus. First, DNA wraps around core histone octamers to form nucleosomes - the structural unit of chromatin fibers1-3. Chromatin fibers are further organized into chromatin loops such as promoter-enhancer loops4. At higher levels, consecutive chromatin regions can self-interact and form topologically associating domains(TADs)5,6. TADs are further assorted into A and B compartments in each chromosome, which largely correspond to active and inactive chromatin6-8. At the end of the spectrum, each chromosome occupies a spatially distinct nuclear region called a chromosome territory9 10. Particular regions of the genome are also known to be spatially associated with other nuclear components such as the nuclear lamina11.
Correct three-dimensional (3D) chromatin organization maintains essential cellular processes in the human body12-18. Defective 3D chromatin organization can alter cellular behavior and can be a hallmark of cancer. Several lines of evidence suggest altered chromatin organization in cancers: 1) architectural elements of the genome such as insulator sequences (e.g. CTCF-binding sites, which often mark TAD boundaries) and regulatory regions (promoters and enhancers) are recurrently mutated in human tumors19-22; 2) the epigenome including DNA and histone modifications, which is intimately associated with multiple chromatin architectures above, is significantly disrupted in cancer23-25; 3) cancer-related processes such as oncogene- induced cellular senescence and epithelial-to-mesenchymal transition show chromatin organization changes26,27.
Despite the knowledge above, our understanding of the cancer 3D chromatin architectures are still limited due to technical challenges. On one hand, conventional sequencingbased techniques such as high-throughput chromosome conformation capture (Hi-C) have been applied to cancers to indirectly infer 3D chromatin conformations27,28. But these methods require cell dissociations from the native tissue environment and often rely on population-averaging to achieve high genomic resolution, which is not ideal to study the heterogeneous cancer genomes. On the other hand, conventional imaging technologies lack the spatial resolution and multiplexing ability necessary to reveal the detailed 3D chromatin organization. Therefore, it still remains largely unexplored how 3D chromatin organization differs between tumor cells and normal cells in the native tissue context during cancer progression, and how 3D chromatin folding may vary among single cells and sub-clones in the complex tumors. Answers to these questions can enrich our understanding of cancer genome organization, and can provide unexploited resources for diagnostic and therapeutic biomarker discovery.
To fill in these gaps in knowledge, previously developed imaging-based 3D genomic and multi-omic technique “multiplexed imaging of nucleome architectures” (MINA) is applied to profile 3D chromatin architectures of lung and pancreatic cancers18,29-31, two leading causes of cancer deaths in the United States32. This technique enables spatial tracing of numerous genomic regions along individual chromosomes with nanoscale precision, allowing visualization of 3D chromatin architectures within single cells and analysis of variations across cells. To mimic the human lung adenocarcinoma (LU AD) and pancreatic ductal adenocarcinoma (PDAC) cancer progression, established K-MADM-p53 mouse LU AD and PDAC models were leveraged, where preinvasive cancer cells and advanced tumors were labeled with different fluorescent colors33. MINA was applied in K-MADM-p53 mouse LU AD and PDAC models. By grouping chromosomes in cells of different cancer progression stages, 3D chromatin architectures were profiled along the cancer growth trajectory and identified tumor-specific features of chromatin organization. Several spatial architectures in mouse chromosome 6 (Chr6) were significantly disrupted in LUAD tumor cells: 1) chromatin is overall decondensed in Chr6 of LUAD tumor cells in comparison to normal cells; 2) A and B compartment schemes are distinctively altered in LUAD tumors; 3) nuclear lamina association profile of chromatin and the conventional relationship between A-B compartmentalization and nuclear lamina association are disrupted in the tumor cells; 4) chromosome surface localization profile of chromatin and the conventional tendencies for regions with strong A and B compartment strengths to localize to the surface of the chromosome territory are disrupted in the tumor cells. Similar aberrations in the second aspect (A and B compartment schemes) were also recapitulated in PDAC tumors. These four aspects of chromatin organization changes are specific to the tumor cells and may serve as novel diagnostic biomarkers. Genome-wide 3D chromatin organization was also profiled. Several genome-wide 3D chromatin architectural features are distinctively altered in precancerous and LUAD tumor cells: 1) most chromosomes become more condensed in precancerous cells and become similarly decondensed/more decondensed in LUAD tumors than in normal cells; 2) most chromosomes show less intermixed / more demixed folding in precancerous and LUAD tumor cells than in normal cells; 3) most chromosomes become less heterogeneous regarding their folding conformations in precancerous cells and become similarly heterogeneous/more heterogeneous in LUAD tumors. These three aspects of chromatin organization changes are captured at the precancerous stage and can serve as predictive and diagnostic biomarkers for the early-stage preinvasive cancers. Furthermore, to uncover the molecular mechanisms underlying the chromatin architectural changes, 25 genes were identified that may regulate the observed changes. These genes may serve as novel therapeutic targets for cancer treatment. Research Designs and Methods
1. K-MADM-p53 mouse cancer models
Cancer arises from a reiterative process of genome variation, clonal selection and clonal expansion34. It has long been difficult to study clonal evolution in physiologically relevant autochthonous cancer models due to technical challenges in inducing sequential mutations in subclonal populations and tracing them unambiguously at single-cell resolution. To meet this challenge, a Mosaic Analysis with Double Markers (MADM) system was previously developed that generated TdTomato-expressing (RFP+) homozygous wild-type and green-fluorescent protein-expressing (GFP+) homozygous mutant cells via a rare Cre/loxP-mediated inter- chromosomal mitotic recombination event, which coupled genotype to fluorescent labeling in single cells33. The MADM system was further leveraged to develop K-MADM-p53 mouse models to study subclonal expansions of GFP+/?53' ' cells and RFP+/?53+/+ cells in preinvasive Ara -induced lung and pancreatic cancer33. Lung (LU AD) and pancreatic (PDAC) tumors were generated by inducing Cre recombinase expression to the lung (via intra-tracheal lentiviral inhalation35) or pancreas (via Pt&7-Cre transgene36). Tumors were dissected at timepoints when all states of cancer progression were observed (20-24 weeks post-lentiviral infection in lung and 6-10 weeks in pancreas). In these models, the p53~ ~ cells, instead of p53+/+ cells, progressed to advanced LUAD and PDAC, indicating that p53 constrained cancer progression to advanced stages33. However, what remains surprising and unexplored is that despite the prevalence of p53 /_ clones in a majority of preinvasive tumors (lung adenomas or pancreatic intraepithelial neoplasia), only a small minority of p53~ ~ clones progresses to advanced adenocarcinoma. Thus, p53 loss is permissive but insufficient to drive tumor expansion. As tumor mutational burden in mouse cancer models is low37,38, additional molecular events such as 3D chromatin aberrations and subsequent transcription disruptions can be involved to drive cancer progression. Therefore, the K-MADM-p53 model provides an ideal system to study 3D chromatin organization during cancer progression, as they enable lineage tracing of marked heterogeneous cancer cell populations encompassing all stages of tumor progression within the same mouse, ranging from RFP+ preinvasive cells incapable of progression to morphologically similar GFP+ preinvasive cells at various states of progression and morphologically distinct GFP+ advanced tumors.
2. Implementation of MINA to K-MADM-p53 mouse cancer models To study contributions of 3D chromatin organization to cancer progression and identify novel cancer biomarkers based on 3D chromatin organization, MINA was applied to K-MADM- p53 mouse LU AD and PDAC cancer models. In tissue sections from the mouse models, GFP and RFP fluorescent imaging was performed first to distinguish RFP+ preinvasive cells incapable of progression, GFP+ preinvasive cells encompassing all states of progression, and GFP+ advanced tumors. MINA was them implemented to reconstruct 3D chromatin conformations in single cells and grouped conformations in each cell population. To study 3D chromatin conformations at the levels of TADs, compartments and chromosome territories, chromatin tracing (multiplexed sequential DNA fluorescence in situ hybridization) probes were designed to target 50 TADs spanning along Chr6, as the ra gene is localized on Chr6 and mutant Aras can drive LUAD and PDAC progression39^41. For each TAD, 1000 primary probes were designed to label a 100-kb region using previously validated computational design criteria29’30,42. Each primary probe contained a unique genomic targeting region that hybridized to the genomic region of interest and a nongenomic readout region with sequences shared by all primary probes targeting the same TAD. Dye-labeled readout probes were sequentially hybridized to the primary probes to image the 3D positions of each TAD with nanoscale precision, followed by photobleaching after each round of imaging. The chromatin tracing procedure is illustrated in FIG. 1. After the sequential readout probe hybridization and imaging, individual 3D chromatin traces within single cells were reconstructed and compared to their differences across cells.
To profile genome-wide 3D chromatin organization, an oligonucleotide probe library was designed to target 473 regions across the genome. A previously published probe design strategy called DNA MERFISH was used and each target region was assigned a 100-choose-2 combinatorial binary code47. The identities of all target genomic regions can be decoded after sequential readout probe hybridization, imaging, and computational decoding.
Upon acquisition of the chromatin architectures in cells of different cancer progression stages, multiple aspects of chromatin architectures were analyzed, including chromatin compaction, A-B compartmentalization, chromatin associations with nuclear lamina, chromatin localizations relative to the surface of chromosome territory, chromatin intermixing/demixing, and chromatin conformation heterogeneity. By comparing these aspects of chromatin architectures across different cancer cell states and normal cells, tumor-specific chromatin architectures were identified that can serve as diagnostic biomarkers for cancer. 3. Tissue Sectioning and primary probe hybridization
1. Balance the mouse MADM lung tissue block at -20 °C for 1.5h. Frozen blocks are sectioned at a thickness of 10 pm at -20 °C on a cryostat.
2. Prepare consecutive tissue section for H&E staining
3. Dry the tissue sections at RT for 1.5h and use parafilm to seal them and store them at - 20 °C.
4. Balance tissue sections at RT for 10 mins. Hydrate with DPBS.
5. Incubate DAPI in DPBS at a concentration of 1 : 1000 for 5 mins. Wash with DPBS twice, each time 2 mins.
6. Prepare imaging buffer. Assemble the imaging chamber.
7. Take fluorescent images of the samples. Choose FOVs for each sample. Use the dualview set-up. Trace hybO, including 560, 488, and 405 channels.
8. After tracing, use a marker pen to label the tissue area and then de-assemble the chamber, put the coverslip into DPBS.
9. Permeabilize the tissue section with 0.5% triton in DPBS for 30 mins at RT. Wash twice with DPBS afterwards.
10. Treat with 0.5ug/ml proteinase K in 2% SDS in 2*SSC at 37 °C for 10 mins. Wash with DPBS twice.
11. Incubate the samples in 0.1 M HC1 for 5 mins. Use DPBS to wash 3 times.
12. Digest with 0.1 mg/mL RNase A in DPBS for 45 mins at 37 °C.
13. Wash cells with 2*SSC twice. Then incubate for 30 mins at RT in 2xSSC + 50% formamide + 0.1% Tween-20.
14. Prepare hybridization buffer (2xSSC + 50% formamide + 20% dextran sulfate). Add 1 pl 5-8 pM acrydite-labeled probes in 25pl hybridization buffer. Flip the coverslip onto a slide, sandwiching the probes above. Heat denature on 86 °C heat block for 3 mins. Incubate overnight at 37 °C in a humid chamber.
4. Embedding and clearing
1. Wash encoded primary probes at 60 °C two times using 2xSSCT, then once at RT. Bead incubation before embedding. 2. Cover 2x3" two slide with 1 ml gel stick solution for 10 mins in air.
3. De-gas the gel solution for 10 mins.
4. Add 43 pl embedding mixture to the slide and flip the coverslip onto the slide, so that the sample is emerged into the embedding mixture. Wait for 1.5h for the gel to solidify. 5. Digest in digestion buffer (2xSSC+2%SDS+l%Protein K) at 37 °C overnight.
Beads load buffer:
Figure imgf000039_0001
Gel solution: double dense gel 45ul
Figure imgf000039_0002
Embedding mixture:
Figure imgf000039_0003
Digestion buffer:
Figure imgf000039_0004
5. Sequential hybridization and imaging
1. Prepare readout hybridization buffer: 2xSSC + 20% EC + 0.05% murine RNase inhibitor.
2. Dilute secondary probes (aliquoted into luM stock) to 3nM in the readout hybridization buffer.
3. Prepare readout wash buffer: 2xSSC + 20% EC.
4. Prepare imaging buffer: 2xSSC + 50 mM Tris + 10% glucose + 2mM Trolox + 0.5 mg/mL glucose oxidase + 40 pg/mL catalase + 50 units/mL(0.1%) murine RNase inhibitor.
5. Dilute Trolox in ethanol. Add layer of mineral oil to the imaging buffer before imaging.
6. Prepare bleaching buffer: 2xSSC.
7. Set up sequential hybridization experiments and perform multiplexed imaging on the microscope.
Readout hybridization buffer: 50ml
Figure imgf000040_0001
Readout wash buffer: 50ml
Figure imgf000040_0002
Bleaching buffer(2*SSC): 50ml
Figure imgf000040_0003
Image Buffer: 50ml
Figure imgf000041_0001
Results
1. Multiple aspects of 3D chromatin organization of Chr6 are disrupted in LU AD tumors and can serve as diagnostic biomarkers for cancer
After the implementation of MINA in LU AD cancer tissue, Chr6 chromatin traces in WT, red (RFP+p53+/+) precancerous, yellow (GFP+ RFP+p53+/") precancerous, green (GFP+ p53‘ /_) precancerous, and green (GFP+ p53'/_) advanced LU AD tumor cells were grouped, which covered the full spectrum of LU AD progression. Within each cell group, multiple aspects of chromatin organization were analyzed including chromatin compaction, A and B compartmentalization, nuclear-lamina associations of chromatin, and chromosome-territory- surface localizations of chromatin. LU AD tumor cells have significantly disrupted chromatin organization in all aspects mentioned above.
Chromatin compaction
The compactness of individual chromatin traces were measured in each cell group by calculating the radii of gyration of the chromatin traces43. To calculate the radius of gyration, the sum squared Euclidean distance was calculated between each target TAD to the center-of-mass (mean x, y, z position of all target TADs) of the chromosome territory, and the sum was normalized to the number of target TADs. The square-root of the normalized value was then defined as the radius of gyration of the chromatin trace. Radii of gyration of all chromatin traces within each cell group was measured and two-sample /-test was performed to compare radii of gyration between LU AD tumor cells and each group of green precancerous, red precancerous and morphologically normal colorless control cells. Chr6 traces in green LU AD cells were significantly more decondensed than traces in other groups (FIG. 2), which may be correlated with its enhanced gene expression44. This LUAD-specific Chr6 decompaction may serve as a diagnostic and predictive biomarker for cancer.
A and B compartmentalization
A-B compartments are largely associated with active (A) or inactive (B) transcriptional states45. To measure the TADs’ A-B compartment identities (whether each TAD is sorted into compartment A or B), a computational pipeline was introduced in previous works29-31. This computational pipeline yields the compartment score of each TAD. TADs in compartment A have positive compartment scores and TADs in compartment B have negative compartment scores.
In mouse LUAD cancer models, chromatin traces in green LU AD cells had significantly altered A-B compartment profiles compared with traces in other cell groups (FIG. 3). For example, TADs 23-28 changed from compartment A TADs in non-tumor cells to compartment B TADs in LUAD tumors. TADs 48-50 changed from compartment B TADs in non-tumor cells to compartment A TADs in LUAD cells. Similar alterations in A and B compartmentalization were also observed in our mouse PDAC cancer models (FIG. 4). These specific A-B compartment changes may serve as diagnostic and predictive biomarkers for cancer.
Lamina association o f chromatin and its relationship with A-B compartments
In the cell nucleus, particular chromatin regions tend to be spatially adjacent to the nuclear lamina. These regions are known as lamina-associated domains11, and tend to be heterochromatic and transcriptionally inactive46. It has been shown that, conventionally, B compartment regions tend to be proximal to the nuclear lamina and A compartment regions tend to localize to the nuclear interior30. To quantify the associations between each targeted TAD and the nuclear lamina, nuclear lamina positions were approximated by extracting the nucleus periphery positions from DAPI imaging. For each observed TAD, its spatial distance to the nuclear lamina was measured. TADs within 200 nm from the lamina are considered as being associated with the lamina. Then the lamina association ratios30 were measured for each of the 50 targeted TADs along Chr6 by calculating the percentage/probability of each of the TADs to be associated with the nuclear lamina. The lamina association ratio profiles are significantly different among the cell groups (FIG. 5). In non-tumor cells, lamina association ratios were negatively correlated with compartment scores, consistent with the conventional chromatin organization where B compartment TADs tend to be adjacent to the nuclear lamina30. However, in green LU AD tumor cells, the preferential association between compartment B regions with the nuclear lamina was disrupted (FIG. 6). The lamina association of chromatin regions and the relationship between lamina association and A-B compartmentalization may serve as diagnostic biomarkers for cancer.
Chromosome-surface localization of chromatin and its relationship with A-B compartments
To determine whether a TAD is localized to the surface of the chromosome territory, a computational metric was used30. A 3D convex hull of the chromosome territory was built using all imaged TADs. If a TAD is localized to the surface of the 3D convex hull, the TAD was regarded as being located at the chromosome surface. Surface association ratio is defined as the probability of each TAD being localized to the surface of the chromosome territory. The surface association ratio profiles are significantly different among the cell groups (FIG. 7).
Furthermore, A-B compartment scores were analyzed to determine how they were correlated with surface association ratios. Previous work in mouse E14.5 fetal liver has revealed a general principle that genomic regions with strong A and B compartment strengths tend to localize to the surface of the chromosome territory30. This conventional organization feature was still preserved in non-tumor cell groups in the lung, where surface association ratios were negatively correlated with B compartment scores and positively associated with A compartment scores. In green LU AD cells, however, this feature was significantly disrupted, where surface association ratios had no correlation with B compartment scores and a weak negative association with A compartment scores (FIG. 8). The tumor-specific chromosome surface localization profile and its relationship with A-B compartmentalization profile may serve as diagnostic and predictive biomarkers for cancer.
2. Multiple aspects of genome-wide 3D chromatin organization are disrupted in LU AD tumors and can serve as diagnostic biomarkers for cancer
Genome-wide MINA was applied to WT and MADM mouse lungs (FIGs. 9A, 9B, 10, 11 A, and 1 IB). Chromatin traces were then separately grouped in WT, red (RFP+ p53+/+) precancerous, yellow (GFP+ RFP+ p53+/") precancerous, green (GFP+ p53'/_) precancerous, and green (GFP+ p53'/_) advanced LU AD tumor cells, which covered the full spectrum of LU AD progression. Within each cell group, multiple aspects of chromatin organizations were analyzed, including chromatin compaction, chromatin intermixing/demixing, chromatin conformation heterogeneity. Both precancerous and LU AD tumor cells have significantly disrupted chromatin organizations in all aspects mentioned above.
Chromatin compaction
Chromatin compaction was compared for all 19 autosomes in the mouse genome during LUAD cancer progression. For each chromosome, mean pairwise distances between each pair of target genomic loci were measured, and the distances in WT, green precancerous, red precancerous, yellow precancerous and LUAD states were compared (FIG. 9B). The average of all fold changes of individual mean pairwise distances between each cancer state and the WT state were also quantified. Paired t-test of the mean pairwise distances between each cancer state and the WT state was performed to identify chromosomes with significant changes in compaction (FIG. 9 A). Along the LUAD progression trajectory from WT to precancerous to LUAD, most chromosomes became more compacted in the precancerous stage, and then became similarly compacted or more decondensed in the LUAD stage in comparison to the WT state. The increased chromatin compaction in the precancerous stage measured by MINA can serve as a diagnostic and predictive biomarker for early-stage lung cancers. Chromatin intermixing/demixing
To compare chromatin intermixing/demixing features during LUAD progression, mean pairwise distances between each pair of target genomic loci on a chromosome was measured. Each mean pairwise distance value was then normalized to the average of all mean pairwise distances. The fold change of the standard deviation of normalized mean pairwise distances was then quantified between each cancer state and WT state to compare the differences. A higher standard deviation or variance indicated a higher level of demixing. F-test of the normalized mean pairwise distances between each cancer state and the WT state was performed to identify chromosomes with significant changes in the level of intermixing or demixing (FIG. 10). Along the LUAD progression trajectory from WT to precancerous to LUAD, most chromosomes became more demixed in precancerous and LUAD states, which may serve as a diagnostic biomarker for early-stage lung cancers. Chromatin conformation heterogeneity To compare the levels of chromatin conformation heterogeneity among different LUAD progression states and WT, the coefficient of variation (COV, defined as standard deviation/mean) of the pairwise distances between each pair of target genomic loci on a chromosome was measured. The CO Vs between each cancer state was then compared to the WT state (FIGs. 11 A and 1 IB). A higher COV value indicated a higher level of heterogeneity. The average of all fold changes of individual CO Vs between each cancer state and the WT state was quantified, and paired t-test of the COV values was performed to identify chromosomes with significant changes in conformation heterogeneity. Along the LUAD progression trajectory from WT to precancerous to LUAD, most chromosomes became less heterogeneous in precancerous states and then became similarly heterogeneous in LUAD states in comparison to the WT state. This feature may serve as a diagnostic and predictive biomarker for early-stage preinvasive lung cancers.
3. Multiple genes may regulate the cancer 3D chromatin architectures and could serve as drug targets for cancer treatment
To identify genes regulating the unconventional cancer-specific chromatin organization in LUAD tumors, a previously published single-cell RNA sequencing (scRNA-seq) dataset containing single-cell RNA expression profiles encompassing all stages of LUAD progression was used, denoted as cancer scRNA-seq dataset throughout this manuscript for simplicity44. Meanwhile, MINA was applied in E14.5 mouse placenta and it was found that placental trophoblast giant cells and a few other cell types have similar unconventional chromatin organization features as those in green LUAD tumor cells (FIGs. 12, 13, and 14). To discover which genes may regulate the shared unconventional chromatin architectures in LUAD and placental cells, the shared upregulated gene expressions between LUAD cells in the cancer scRNA-seq dataset44 and the relevant placental cell types in E14.5 mouse placenta scRNA-seq dataset were identified50. Gene Ontology analysis was then performed to identify genes involved in DNA/chromatin regulations. A list of 25 candidate genes including Smc4, Hmgb2, Mcm2, and Rad51 were identified that may regulate the unconventional cancer-associated or cancer-like chromatin architectures. The full set of candidate genes is listed in Table 1. By inhibiting the expression of these upregulated genes or their expression products, one may remedy the atypical chromatin architectures in cancer and obtain beneficial outcome in cancer treatment. Table 1. Candidate genes that can regulate chromatin architectures
Figure imgf000046_0001
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Example 2: Validation and discovery of additional 3D chromatin organization features as biomarkers for cancer using human samples.
To comprehensively validate and further discover 3D chromatin organization features as cancer biomarkers, the following features are quantified for all 23 pairs of chromosomes in both pre-invasive and invasive human lung and pancreatic cancer tissues, and in adjacent WT tissues. The phrase ‘a chromosome copy’ refers to a single copy of a chromosome. The phrase ‘a chromosome’ refers to a chromosome species among 22 autosomes, Chromosome X and Chromosome Y.
1) Compaction, quantified by the radii of gyration of chromatin traces or by the fold changes of mean pairwise distances between target genomic loci.
2) Intermixing/demixing, quantified by a standard deviation or variance of the normalized mean pairwise distances. The normalization procedure is to remove the confounding effect from chromatin compaction.
3) Heterogeneity, quantified and compared to levels of chromatin conformation heterogeneity among different cancer progression states and WT tissues by using the coefficient of variation (or similar measures) of pairwise distances between target genomic loci.
4) A and B compartmentalization. A-B compartment schemes among different cancer progression states and WT tissues are identified by using a computational pipeline as discussed above or similar pipelines.
5) Polarization of A and B compartments. To measure whether A and B compartment genomic regions are spatially localized in a polarized, side-by-side manner, quantification metrics29,30 are used to yield a polarization index of A and B compartments for each chromosome copy. A higher polarization index value indicates a more polarized chromosome configuration.
6) Association between genomic loci with nuclear lamina. As described above, the associations between targeted genomic regions and the nuclear lamina can be identified by approximating nuclear lamina positions by extracting the nucleus periphery positions from whole-nuclear stains such as DAPI stain. Alternatively nuclear lamina labeling with e.g. coimmunofluorescence can be performed.
7) Association between genomic loci with the nucleolus. To quantify the associations between each targeted genomic region and the nucleolus, nucleolar positions are approximated from nucleolar marker staining such as co-immunofluorescence targeting fibrillarin. For each observed genomic region, its spatial distance to the nucleolus is measured. Genomic regions within a distance threshold from the nucleolus will be considered as being associated with the nucleolus.
8) Association between genomic loci with the nuclear speckle. To quantify the associations between each targeted genomic region and the nuclear speckle, nuclear speckle positions are approximated using nuclear speckle marker staining such as coimmunofluorescence targeting SC35. For each observed genomic region, its spatial distance to the nuclear speckle is measured. Genomic regions within a distance threshold from the nuclear speckle will be considered as being associated with the nuclear speckle.
9) Localization of genomic loci to the surface of the chromosome territory. As described above, a previously introduced algorithm is used to identify genomic loci located at the surface of their corresponding chromosome territories.
10) Trans-chromosomal interactions. Genome-wide MINA data allow for quantifying interactions among genomic loci from different chromosomes.
11) Cis-chromosomal interactions. Besides the chromatin features above, certain cis- chromosomal interactions may serve as additional cancer biomarkers.
12) Telomere-to-centromere orientation analysis. To analyze the organizations of telomeres and centromeres, a computational pipeline as described previously is used.51 This analysis yields: a) whether centromeres/telomeres tend to localize to the surface of chromosome territories, and b) whether the telomere-to-centromere orientations of multiple chromosomes adopt the polarized Rabi configuration, defined as centromeres and telomeres pointing towards the opposite poles of the nucleus.
Example 3: Functional validations of candidate genes in regulating 3D chromatin architectures. To further validate the functions of candidate genes (listed in Table 1) in regulating the cancer-associated chromatin architectures, knock-out or knock-down of these genes in mouse LUAD and PDAC cell lines is performed. The 3D chromatin architectures of these cell lines are profiled both before and after the gene perturbations. Upon the knock-out or knock-down of one or more of the target candidate genes, the chromatin architectures in the cancer cell lines become more conventional.
Example 4. Additional 3D genome studies.
1. Structural bottleneck of the 3D genome at the adenoma stage prior to LUAD progression.
With the genome-wide chromatin tracing data described above, multiple computational analysis pipelines were developed and applied to extract structural features of 3D genome in the different cell states, including wild-type (WT), red (TdTomato+ p53+/+) preinvasive adenoma, yellow (GFP+/TdTomato+ p53+/-) preinvasive adenoma, green (GFP+ p53-/-) preinvasive adenoma, and green (GFP+ p53-/-) advanced LUAD lung tumor cells. The analyzed features included chromatin compaction, chromatin conformation heterogeneity, chromatin intermixing, A-B compartmentalization, rabl configuration, and radial positioning of chromosomes in the cell nucleus. While chromatin compaction, chromatin conformation heterogeneity and chromatin intermixing changes were reported in Example 1 above, here other analyses were used, including A-B compartmentalization, rabl configuration and radial positioning of chromosomes in the cell nucleus. Preinvasive adenoma cells adopted more polarized A-B compartment configurations than those of WT and LUAD cells (FIG. 15); chromosome orientations (shown by Rabl scores) were less aligned in preinvasive adenoma cells than in WT cells, and chromosome orientations of LUAD cells became more aligned than those of preinvasive adenoma cells (FIG. 16); Chr8, Chrl3 and Chrl6 are placed closer to nuclear periphery in adenoma cells than in WT, and then move back towards nuclear interior in LUAD, while Chr7 and Chrl9 show the opposite movements (FIG. 17). These new results, in combination with the results described in Example 1 above, suggest the existence of an early stringent selection on 3D genome conformation at the adenoma stage, while more heterogeneous and WT-like conformations are tolerated at the later LUAD stage. 2. Machine learning strategies to extract 3D genome encoding of different cancer states.
The analyses above used the ground-truth cell states from MADM lineage tracing to perform cell-state-specific 3D genome analysis. However, can the 3D genome itself encode cancer cell states at the single cell level? To answer this question, different cancer cell states were clustered based on their 3D genome conformations through an unsupervised machine learning method. To implement single-cell clustering of 3D chromatin organizations, a previously developed scA/B score metric for Dip-C data analysis1 was adapted to image-based 3D genome data. The scA/B score for each genomic locus was calculated as the average A-B compartment scores of all its spatially adjacent genomic loci. In a 2D display of the highdimensional clustering, WT cells and LU AD cells occupied two trajectories while preinvasive adenoma cells were clustered in a tight area at the transitioning region in between WT and LUAD (FIG. 18), consistent with the bottleneck and early stringent selection discussions above. To test if the 3D genome alone can allow robust calling of cell state at the single cell level, supervised machine learning was performed using a quadratic support vector machine model, with a 79.7% accuracy in calling single cell states using the trained model (FIGs. 19 and 20). These results showed that 3D genome organization can encode cell states during oncogenesis at the single cell level, and may be developed into novel diagnostic biomarkers of cancer.
One standing mystery of the K-MADM-p53 mouse LUAD model was that only a subset of the green (GFP+ p53-/-) preinvasive adenoma cells progressed into LUAD, even though the green adenoma and LUAD cells shared the same mutation burden2. Given 3D genome can encode cancer states, it was speculated that the subset of green preinvasive adenoma cells that progressed into LUAD may have specific 3D genome features linked to their transformation potentials. To test this hypothesis, single-cell clustering was performed on the preinvasive adenoma red and yellow cells, preinvasive adenoma green cells and invasive LUAD cells. The preinvasive adenoma red and yellow cells and invasive LUAD cells formed distinct clusters, whereas adenoma green cells were dispersed in both clusters (FIG. 21). A division line was computationally identified that maximized the proportions of preinvasive red and yellow cells and invasive LUAD cells on each side of the line, and quantified the percentage of adenoma green cells distributed to either side. A subset of adenoma green cells adopted the LUAD-like 3D chromatin organization prior to LUAD transition (FIG. 22). This indicated that 3D chromatin organization changes precede malignancy progression, and may serve as a driver of cancer progression potentials of the adenoma cells.
3. Cancer 3D genome organization is independent of spatial proximity to immune cells.
Immune cells, as major components of the tumor microenvironment, can regulate LU AD progression. Single-cell clustering of 3D genome organizations showed that AT2 cells (cells of origin of LUAD) at different progression stages and immune cells had different 3D genome conformations (FIG. 23). To study whether the 3D genome re-organization observed in AT2 cells during LUAD progression were linked to their spatial proximities to immune cells, AT2 cells adjacent to and far from immune cells at each progression stage were computationally categorized and compared their 3D genome organization features including chromatin compaction, chromatin conformation heterogeneity, chromatin intermixing, A-B compartmentalization, and rabl configuration. No systematic strong differences or only mild differences (based on fold change values) in these 3D genome organization features were observed between AT2 cells adjacent to and far from immune cells (FIGs. 24, 25, 26, 27A and 27B). Furthermore, based on the single cell clustering of 3D genome organizations, AT2 cells adjacent to and far from immune cells had similar 3D genome conformations (FIG. 28). These indicated that the 3D genome organization changes in AT2 cells during LUAD progression were cell-autonomous and independent of spatial proximity to immune cells.
4. Using 3D genome to discover candidate cancer progression driver genes.
To explore potential functional consequences of the 3D chromatin re-organization in different cancer cell states, RNA-seq data was obtained of the adenoma green cells and LUAD cells, the two cell states during the key malignancy progression. Gene expression changes within “progression marker regions”, defined as targeted genomic regions with significantly altered scA/B scores from adenoma green cells to LUAD cells, were a focus of this study. In comparison to genes in regions with unchanged scA/B scores, the genes in marker regions with increased scA/B scores showed significantly increased RNA expression, whereas the genes in marker regions with decreased scA/B scores showed significantly decreased RNA expression (FIG. 29). Gene ontology (GO) terms of genes was analyzed within marker genomic regions with significantly increased and decreased scA/B scores from preinvasive adenoma red and yellow cells to invasive LU AD cells. Genes within marker regions with increased scA/B scores were enriched with GO terms including endothelial cell proliferation, positive regulation of intracellular signal transduction, regulation of cellular biosynthetic process, regulation of metabolic processes, regulation of epithelial cell migration and regulation of angiogenesis and vasculature development. On the other hand, genes within marker regions with decreased scA/B scores were enriched with GO terms including intermediate filament organization, innate immune response, cell differentiation, signal transduction by p53, apoptotic signaling pathway and lung development (FIG. 30). These results were consistent with the expected biological pathway changes during LU AD progression, suggesting that 3D genome organization functionally encodes cancer progression. It was speculated that genes with elevated expression levels in marker genomic regions with increased scA/B scores from adenoma green to LU AD cells could serve as candidate cancer progression driver (CPD) genes. To validate the gene functions in LU AD progression, an arrayed lentiviral RNAi screen targeting 25 CPD genes with 75 short hairpin RNAs (shRNAs, 3 shRNAs per gene) was performed in two primary LU AD mouse cell lines isolated from a KP mouse model and the K-MADM-p53 mouse model. Each CPD gene was knocked down and the subsequent influences on cell proliferation was studied using the CellTiter-Glo assay as a readout. It was found that knockdown of 84% of CPD genes caused a defect in cancer cell growth in both cell lines. (FIG. 31). These results demonstrated that the 3D genome profiling technique in cancer can lead to functional insights and the discovery of new candidate cancer progression driver genes.
References
1. Tan, L., Xing, D., Chang, C.-H., Li, H. & Xie, X. S. Three-dimensional genome structures of single diploid human cells. Science 361, 924-928 (2018).
2. Muzumdar, M. D. et al. Clonal dynamics following p53 loss of heterozygosity in Kras-driven cancers. Nat. Commun. 7, 12685 (2016).
* * *
The present invention is not to be limited in scope by the specific embodiments described herein. Indeed, various modifications of the invention in addition to those described herein will become apparent to those skilled in the art from the foregoing description. Such modifications are intended to fall within the scope of the appended claims. All patents, applications, publications, test methods, literature, and other materials cited herein are hereby incorporated by reference in their entirety as if physically present in this specification.

Claims

WHAT IS CLAIMED IS:
1. An in situ method for determining the presence of a chromatin alteration in a cell, wherein the chromatin alteration is associated with a cancer, the method comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of the cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome associated with the chromatin alteration, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome associated with the chromatin alteration, d) contacting the cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, and f) determining the presence of the chromatin alteration based on the detected signals of the labels of the secondary probes.
2. The method of claim 1, said method further comprises the step of: g) determining that the cell is cancerous when the chromatin alteration is present in the cell.
3. The method of claim 1 or 2, wherein in step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample or a reference value.
4. The method of claim 3, wherein the control sample is a non-cancerous cell.
5. The method of any one of claims 1-4, wherein said chromosome segment(s) comprises at least about a 1 -kilobase (kb) DNA region.
6. The method of any one of claims 1-5, wherein the plurality of primary probes bind to a
-56- plurality of segments of the chromosome associated with the chromatin alteration.
7. The method of claim 6, wherein the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome.
8. The method of claim 6 or 7, wherein each of the plurality of segments is located within a unique T D .
9. The method of claim 8, wherein each of the plurality of segments comprises about an internal 1-1000-kilobase (kb) DNA region of a unique TAD.
10. The method of claim 9, wherein each of the plurality of segments comprises about an internal 10-100-kilobase (kb) DNA region of a unique TAD.
11. The method of claim 10, wherein each of the plurality of segments comprises about a central 100-kilobase (kb) DNA region of a unique TAD.
12. The method of claim 6, wherein the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome.
13. The method of claim 12, wherein each of the plurality of segments is located within a unique gene and/or gene regulatory element.
14. The method of any one of claims 6 to 13, wherein the plurality of segments are scattered throughout the entire length of the chromosome associated with the chromatin alteration.
15. The method of any one of claims 1 to 14, wherein at least some of the plurality of primary probes comprise the same readout sequence.
16. The method of any one of claims 6 to 15, wherein the primary probes binding to the same segment comprise the same readout sequence.
17. The method of any one of claims 1-16, wherein in step b) the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes.
18. The method of claim 17, wherein the method further comprises after step e) and before step f) the steps of: h) removing signals generated by the labels of the secondary probes bound to the primary probes; i) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; j) detecting the labels from the different secondary probes; and
-57- k) repeating steps h) through j) for one or more times using different pluralities of secondary probes.
19. The method of claim 18, wherein in step b) and/or step i) the plurality of secondary probes comprise the same set of secondary probes.
20. The method of claim 18, wherein in step b) and/or step i) the plurality of secondary probes comprise two to five different sets of secondary probes.
21. The method of claim 19 or 20, wherein each set of secondary probes are labeled with the same dye.
22. The method of any one of claims 1-18, wherein the plurality of secondary probes are labeled with a plurality of dyes.
23. The method of claim 21 or 22, wherein the dye(s) are fluorescent dye(s).
24. The method of any one of claims 1 to 23, wherein step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes.
25. The method of claim 24, wherein step f) further comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome.
26. The method of claim 25, wherein the method further comprises analyzing 3D chromatin architecture using a machine learning method.
27. The method of any one of claims 1-26, wherein the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
28. The method of claim 27, wherein the labeling is performed using fluorescence in situ hybridization (FISH).
29. The method of claim 28, wherein the labeling is performed using RNA multiplexed error- robust fluorescence in situ hybridization (MERFISH).
30. The method of any one of claims 1 to 29, wherein the cell is fixed.
31. The method of any one of claims 1 to 30, wherein the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell.
32. The method of any one of claims 1 to 31, wherein the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B
-58- compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to-centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof. The method of any one of claims 1 to 32, wherein the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii). chromatin A and B compartment scheme is altered compared to a non-cancerous cell; iii). the nuclear lamina association profile of chromatin is disrupted in the cell; or iv). the chromosome surface localization profile of chromatin is disrupted in the cell. The method of any one of claims 1 to 33, wherein the cell is determined as cancerous when one or more of the following chromatin alterations is present in the cell: i). at least one condensed or decondensed chromosome in the cell; ii). more or less intermixed chromosomal folding of at least one chromosome; iii). at least one chromosome with more or less heterogeneous folding conformations; iv). at least one chromosome with more or less polarized A and B compartment organization; v). altered A and B compartment profile of at least one chromosome; vi). altered Rabi configuration or chromosome orientation in the cell nucleus; or vii). altered radial positioning of at least one chromosome in the cell nucleus. A method for identifying a cancer subject comprising determining the presence of a cancer-associated chromatin alteration in a cell of the subject according to the method of any one of claims 1-34. A method for identifying a cancer biomarker, comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a
-59- cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes, e) detecting the labels of the secondary probes, f) determining the presence of a chromatin alteration based on the detected signals of the labels of the secondary probes, and g) identifying the chromatin alteration as a cancer biomarker when the chromatin alteration is present in the cancerous cell. A method for identifying a cancer biomarker, comprising the steps of: a) providing a plurality of primary probes, each of which comprises a first oligonucleotide, wherein said first oligonucleotide comprises a target sequence and a readout sequence, wherein the target sequence binds to a genomic locus of a cancerous cell, and wherein the plurality of primary probes bind to at least a segment of at least a chromosome, b) providing a plurality of secondary probes, each of which comprises a second oligonucleotide and a label, wherein the second oligonucleotide comprises a sequence that binds to the readout sequence of at least one of the plurality of primary probes, c) contacting the cancerous cell with the plurality of primary probes under conditions that allow binding of the plurality of primary probes to the at least a segment of the chromosome, d) contacting the cancerous cell with the plurality of secondary probes under conditions that allow binding of the secondary probes to the primary probes,
-60- e) detecting the labels of the secondary probes, f) determining the presence of a chromatin alteration based on the detected signals of the labels of the secondary probes, g) measuring expression of one or more genes associated with the chromatin alteration when the chromatin alteration is present as determined in step f), and h) identifying gene(s) that are differentially expressed in the cancerous cell as a cancer biomarker.
38. The method of claim 36 or 37, wherein in step f) the presence of chromatin alteration is determined by comparing detected signals of the labels of the secondary probes to a control sample or a reference value.
39. The method of claim 37, wherein in step h) the gene(s) that are differentially expressed are identified by comparing expression of said gene(s) to a control sample or a reference value.
40. The method of claim 38 or 39, wherein the control sample is a non-cancerous cell, or a cell in a different cancer cell state.
41. The method of any one of claims 36-40, wherein said chromosome segment comprises at least about a 1 -kilobase (kb) DNA region.
42. The method of any one of claims 36-41, wherein the plurality of primary probes bind to a plurality of segments of the chromosome.
43. The method of claim 42, wherein the plurality of segments are located in more than one topologically associating domain (TAD) of the chromosome.
44. The method of claim 42 or 43, wherein each of the plurality of segments is located within a unique topologically associating domain (TAD).
45. The method of claim 44, wherein each of the plurality of segments comprises about an internal 1-1000-kilobase (kb) DNA region of a unique TAD.
46. The method of claim 45, wherein each of the plurality of segments comprises about an internal 10-100-kilobase (kb) DNA region of a unique TAD.
47. The method of claim 46, wherein each of the plurality of segments comprises about a central 100-kilobase (kb) of a unique TAD.
48. The method of claim 42, wherein the plurality of segments are located in more than one gene and/or gene regulatory element in the chromosome.
49. The method of claim 48, wherein each of the plurality of segments is located within a unique gene and/or gene regulatory element.
50. The method of any one of claims 42 to 49, wherein the plurality of segments are scattered throughout the entire length of the chromosome.
51. The method of any one of claims 36 to 50, wherein at least some of the plurality of primary probes comprise the same readout sequence.
52. The method of any one of claims 42 to 51, wherein the primary probes binding to the same segment comprise the same readout sequence.
53. The method of any one of claims 36 to 52, wherein in step b) the plurality of secondary probes comprise secondary probes binding only to a subset of the plurality of primary probes.
54. The method of claim 53, wherein the method further comprises after step e) and before step f) the steps of: i) removing signals generated by the labels of the secondary probes bound to the primary probes; j) contacting the cell with a different plurality of secondary probes that bind a different subset of primary probes; k) detecting the labels from the different secondary probes; and l) repeating steps i) through k) for one or more times using different pluralities of secondary probes.
55. The method of claim 54, wherein in step b) and/or step j) the plurality of secondary probes comprise the same set of secondary probes.
56. The method of claim 54, wherein in step b) and/or step j) the plurality of secondary probes comprise two to five different sets of secondary probes.
57. The method of claim 55 or 56, wherein each set of secondary probes are labeled with the same dye.
58. The method of any one of claims 36-54, wherein the plurality of secondary probes are labeled with a plurality of dyes.
59. The method of claim 57, or 58, wherein the dye(s) are fluorescent dye(s).
60. The method of any one of claims 36 to 59, wherein step f) further comprises determining in three dimensions (3D) location(s) of the segment(s) of the chromosome based on the detected signals of the labels of the secondary probes.
61. The method of claim 60, wherein step f) further comprises analyzing chromatin architecture using the 3D location(s) of the segment(s) of the chromosome.
62. The method of any one of claims 36-61, wherein the method further comprises selectively labeling one or more of the cell membrane, the nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, epigenetic DNA modifications, histone modifications, or RNA molecules of the cell.
63. The method of claim 62, wherein the labeling is performed using fluorescence in situ hybridization (FISH).
64. The method of claim 63, wherein the labeling is performed using RNA multiplexed error- robust fluorescence in situ hybridization (MERFISH).
65. The method of any one of claims 36 to 64, wherein the cell is fixed.
66. The method of any one of claims 36 to 65, wherein the segment(s) of the chromosome associated with the chromatin alteration is located within the nucleus of the cell.
67. The method of any one of claims 36 to 66, wherein the chromatin alteration is an alteration in chromatin compaction, intermixing/demixing, heterogeneity, A and B compartmentalization scheme, polarization of A and B compartments, rabl configuration, radial positioning of chromosomes in cell nucleus, cis or intra-chromosomal interactions, trans or inter-chromosomal interactions, telomere-to-centromere orientations, localization of chromatin regions to chromosome territory surface, or associations between chromatin and nuclear lamina, nucleoli, nuclear speckles, other nuclear bodies, or any combination thereof.
68. The method of any one of claims 36 to 67, wherein the cancer biomarker is selected from one or more of the following chromatin alterations: i) chromatin in the cell is condensed or decondensed compared to a non-cancerous cell; ii) chromatin A and B compartment schemes are altered compared to a non- cancerous cell; iii) the nuclear lamina association profile of chromatin is disrupted in the cell; or iv) the chromosome surface localization profile of chromatin is disrupted in the cell.
69. The method of any one of claims 36 to 68, wherein the cancer biomarker is selected from
-63- one or more of: i) at least one condensed or decondensed chromosome in the cell; ii) more or less intermixed chromosomal folding of at least one chromosome; iii) at least one chromosome with more or less heterogeneous folding conformations; iv) at least one chromosome with more or less polarized A and B compartment organization; v) altered A and B compartment profile of at least one chromosome; vi) altered Rabi configuration or chromosome orientation in the cell nucleus; or vii) altered radial positioning of at least one chromosome in the cell nucleus.
70. A method for identifying a cancer cell comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in the cell according to the method of any one of claims 1 to 34.
71. The method of claim 70, wherein the cell is determined as cancerous when at least one of the following is detected: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv). alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi). altered cis or intra-chromosomal interactions for human Chrl2; vii). alternations in nuclear lamina association profile of human Chrl2; viii). altered relationship between human Chrl2 compartment scores and lamina association ratios; ix). alternations in chromosome surface association profile of human Chrl2; x). altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; xi). alternations in nuclear speckle association profile of human Chrl2; or xii). altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios.
72. A method for identifying a cancer subject comprising determining the presence of a chromatin alteration in human Chromosome 12 (Chrl2) in a cell of the subject according
-64- to the method of any one of claims 1 to 34. The method of claim 72, wherein the subject is determined to have cancer when at least one of the following is detected in the cell: i). altered human Chrl2 compaction level; ii). altered human Chrl2 intermixing/demixing level; iii). altered human Chrl2 heterogeneity level; iv) alternations of A and B compartments for human Chrl2; v). altered polarization level of A and B compartments for human Chrl2; vi). altered cis or intra-chromosomal interactions for human Chrl2; vii). alternations in nuclear lamina association profile of human Chrl2; viii). altered relationship between human Chrl2 compartment scores and lamina association ratios; ix). alternations in chromosome surface association profile of human Chrl2; x). altered relationship between human Chrl2 compartment scores and chromosome surface association ratios; xi). alternations in nuclear speckle association profile of human Chrl2; or xii). altered relationship between human Chrl2 compartment scores and nuclear speckle association ratios. The method of any one of claims 70-73, wherein the cancer is a lung cancer or pancreatic cancer. The method of any one of claims 70-72, wherein the cancer is an advanced lung cancer or pancreatic cancer. The method of any one of claims 70-75, wherein the cancer is a preinvasive or invasive lung cancer or pancreatic cancer. A method of treating a cancer in a subject in need thereof comprising inhibition of expression of at least one gene selected from Baspl, Birc5, Cdca8, Cenph, Cenpk, Cenpw, Cited2, Creb312, Elf3, HlfO, Histlh2bc, Hmgb2, Loxl2, Mcm2, Meg3, Nabpl, Nasp, Rad51, Rfc4, Rfc5, Hatl, Histlhlc, Rpll8, Smc4, and Tead2. The method of claim 77, wherein the method further comprises determining that a cell of the cancer comprises a chromatin alteration using the method of any one of claims 1 to 34.
-65-
79. The method of claim 77 or 78, wherein the cancer is a lung cancer or pancreatic cancer.
-66-
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Citations (3)

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Publication number Priority date Publication date Assignee Title
US20030087248A1 (en) * 2001-02-20 2003-05-08 Morrison Larry E. Methods and probes for the detection of cancer
US20090203896A1 (en) * 2003-06-03 2009-08-13 Balkrishen Bhat Modulation of survivin expression
WO2021138078A1 (en) * 2019-12-30 2021-07-08 President And Fellows Of Harvard College Genome-scale imaging of the 3d organization and transcriptional activity of chromatin

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030087248A1 (en) * 2001-02-20 2003-05-08 Morrison Larry E. Methods and probes for the detection of cancer
US20090203896A1 (en) * 2003-06-03 2009-08-13 Balkrishen Bhat Modulation of survivin expression
WO2021138078A1 (en) * 2019-12-30 2021-07-08 President And Fellows Of Harvard College Genome-scale imaging of the 3d organization and transcriptional activity of chromatin

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