WO2018174862A1 - Méthodes et compositions de détection du cancer de la vessie à un stade précoce par profilage d'expression par arn-seq - Google Patents

Méthodes et compositions de détection du cancer de la vessie à un stade précoce par profilage d'expression par arn-seq Download PDF

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WO2018174862A1
WO2018174862A1 PCT/US2017/023476 US2017023476W WO2018174862A1 WO 2018174862 A1 WO2018174862 A1 WO 2018174862A1 US 2017023476 W US2017023476 W US 2017023476W WO 2018174862 A1 WO2018174862 A1 WO 2018174862A1
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bladder cancer
reagents
sample
target analytes
biomarker
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PCT/US2017/023476
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Bruce Xuefeng Ling
Limin Chen
Shiying Hao
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Mprobe Inc.
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    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING 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
    • C12Q1/00Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • CCHEMISTRY; METALLURGY
    • C07ORGANIC CHEMISTRY
    • C07HSUGARS; DERIVATIVES THEREOF; NUCLEOSIDES; NUCLEOTIDES; NUCLEIC ACIDS
    • C07H21/00Compounds containing two or more mononucleotide units having separate phosphate or polyphosphate groups linked by saccharide radicals of nucleoside groups, e.g. nucleic acids
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING 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
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/112Disease subtyping, staging or classification
    • CCHEMISTRY; METALLURGY
    • C12BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12QMEASURING 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
    • C12Q2600/00Oligonucleotides characterized by their use
    • C12Q2600/158Expression markers

Definitions

  • the present invention relates to expression profiling to differentiate early stage bladder cancer patients from normal subjects.
  • Bladder cancer is the most common malignancy of urinary tract. It is one of the most widespread cancers of the world and ranks nine among frequent malignancies existing in world. Accurate and sensitive detection of bladder cancer is critical to diagnose this deadly disease at an early stage, estimate prognosis, predict response to treatment, and monitor recurrence. Due to the lack of disease-specific symptoms, diagnosis and follow-up of bladder cancer has remained a challenge to the urologic community. Cystoscopy, commonly accepted as a gold standard for the detection of bladder cancer, is invasive and relatively expensive, while urine cytology is of limited value specifically in low-grade disease.
  • RNA-seq technology provides a revolutionary tool for transcriptome analysis. Compared with microarray platform, RNA-seq has less background noise due to image analysis and is more sensitive in detection of transcripts with low-abundance or higher fold change in expression. In this invention, we use RNA-seq to find biomarkers for bladder cancer early detection.
  • methods are provided for detecting the level of at least one, at least two, at least three, at least four, or all of the target molecules selected from Table 3, or any sub-combinations thereof, in a sample from a subject.
  • methods are provided for detecting the level of at least one, at least two, at least three, at least four, or all early stage bladder cancer biomarkers identified in experiment conducted during development of embodiments of the present invention.
  • biomarkers are selected from Table 3., or any sub-combinations thereof.
  • a method comprises detecting the level of one or more biomarkers in a sample from a subject.
  • a method of monitoring bladder cancer (e.g., response to treatment, likelihood of mortality, etc.) in a subject comprises forming a biomarker panel having 50 biomarker proteins from bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., comprising P116, OGN, PGM5-AS1 , HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9- AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2C, CDCA8, CDT1, SKA1, ASF1B, SKA3, CDC25C, SAPCD2, C16orf59, GTSE1, CDK1, UHRF1, HJURP, T
  • N is 1 to 50. In some embodiments, N is 2 to 50. In some embodiments, methods comprise panels of any combination of the bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16, OGN, PGM5-AS1 , HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2C, CDCA8, CDT1, SKA1, ASF1B, SKA3, CDC25C, SAPCD2, C16orf59, GTSE1, CDK1, UHRF1 , HJURP, TTK, TOP2A, NEK2, IQG
  • methods comprise comparing biomarker(s) level to a reference value/range or a threshold. In some embodiments, deviation of the biomarker(s) level from the reference value/range, or exceeding or failing to meet the threshold, is indicative of a diagnosis, prognosis, etc. for the subject.
  • each biomarker may be a protein biomarker.
  • the method may comprise contacting biomarkers of the sample from the subject with a set of biomarker capture reagents, wherein each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a biomarker being detected.
  • each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a different biomarker being detected.
  • each biomarker capture reagent may be an antibody or an aptamer.
  • a biomarker is an RNA transcript.
  • the method may comprise contacting biomarkers of the sample from the subject with a set of biomarker capture reagents, wherein each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a biomarker being detected.
  • each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a different biomarker being detected.
  • each biomarker capture reagent may be a nucleic acid probe.
  • the sample may be a biological sample (e.g., tissue, fluid (e.g., blood, urine, saliva, etc.), etc.).
  • the sample is filtered, concentrated (e.g., 2-fold, 5-fold, 10 fold, 20-fold, 50-fold, 100-fold, or more), diluted, or un-manipulated.
  • a methods further comprise treating the subject for bladder cancer.
  • treating the subject for bladder cancer comprises a treatment regimen of administering one or more chemotherapeutic, radiation, surgery, etc.
  • biomarkers described herein are monitored before, during, and/or after treatment.
  • methods comprise providing palliative treatment (e.g., symptom relief) to a subject suffering from bladder cancer, but not providing interventional treatment of the bladder cancer.
  • palliative treatment e.g., symptom relief
  • methods comprise providing palliative treatment (e.g., symptom relief) to a subject suffering from bladder cancer, but not providing interventional treatment of the bladder cancer.
  • palliative care is pursued in place of bladder treatment.
  • palliative care is provided in addition to treatment for bladder cancer.
  • a method comprises detecting the level of one or more bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16, OGN, PGM5-AS1, HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2C, CDCA8, CDT1, SKA1, ASF1B, SKA3, CDC25C, SAPCD2, C16orf59, GTSE1, CDK1, UHRF1, HJURP, TTK, TOP2A,
  • one or more bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16,
  • the method further comprises measuring the level one or more of the biomarkers at a second time point.
  • bladder cancer severity is improving (e.g., declining) if the level of said biomarkers improved at the second time point than at the first time point.
  • biomarkers or panels thereof provide a prognosis regarding the future course a bladder cancer in a subject (e.g., likelihood of survival, likelihood of mortality, likelihood of response to therapy, etc.).
  • treatment decisions e.g., whether to treat, surgery, radiation, chemotherapy, etc.
  • are made based on the detection and/or quantification of one or more (e.g., 1, 2, 3, 4, 5) of the biomarkers identified in experiments conducted during development of embodiments of the present invention e.g., comprising PI16, OGN, PGM5-AS1, HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3,
  • kits are provided.
  • a kit comprises at least one, at least two, at least three, at least four, of at least five capture/detection reagents (e.g., antibody, probe, etc.), wherein each capture/detection reagents specifically binds to a different biomarker (e.g., protein or nucleic acid) selected from the bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16, OGN, PGM5-AS1, HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2
  • a kit comprises N capture/detection reagents.
  • N is 1 to 50.
  • N is 2 to 50.
  • N is 3 to 50.
  • N is 4 to 50.
  • N is 5 to 50.
  • At least one of the 51 biomarker proteins is selected from the bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16, OGN, PGM5-AS1, HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1, HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2C, CDCA8, CDT1, SKA1, ASF1B, SKA3, CDC25C, SAPCD2, C16orf59, GTSE1, CDK1, UHRF1, HJURP, TTK, TOP2A, NEK2, IQGAP3, AURKB, KIF20A, TROAP, KIF18B,
  • compositions comprising proteins of a sample from a subject and at least one, at least two, at least three, at least four, at least five capture/detection reagents that each specifically bind to a different biomarker selected from the bladder cancer biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., PI16, OGN, PGM5-AS1, HSPB6, SCARA5, ATP1A2, C2orf40, SCN7A, VIT, PLP1, RBFOX3, ADAMTS9-AS1, XPNPEP2, C16orf89, NRXN1 , HLF, SORCS1, GLP2R, TNXB, TMEM132C, FGF10, AFF3, RP11-867G23.10, CLEC3B, ADRB3, CDCA3, POLQ, KIF2C, CDCA8, CDT1, SKA1, ASF1B, SKA3, CDC25C, SAPCD2, C16orf59, GT
  • FIG. 1 The analysis procedure of RNA sequencing data. Each step and packages used in alignment, quantification, and DE analysis are described in this figure.
  • Figure 2 Scatterplot of calculated probabilities of bladder cancer with selected 50-gene panel.
  • the model was trained with Random Forest algorithm, 120/36 case/control (134/41 in total) were selected out randomly to train the model.
  • bladder cancer biomarkers are provided.
  • biomarker or “marker” it is meant a molecular entity whose representation in a sample is associated with a disease phenotype.
  • blade cancer it is meant any cancerous growth arising from the bladder, for example, transitional cell carcinoma , squamous cell carcinomas , small cell carcinoma, carcinosarcoma, primary lymphoma, sarcoma, and the like, as known in the art or as described herein.
  • a bladder cancer “biomarker” or “bladder cancer marker” it is meant a molecular entity whose representation in a sample is associated with a bladder cancer phenotype, e.g., the presence of bladder cancer, the stage of bladder cancer, a prognosis associated with the bladder cancer, the predictability of the bladder cancer being responsive to a therapy, etc.
  • the marker may be said to be differentially represented in a sample having a bladder cancer phenotype.
  • Bladder cancer biomarkers include proteins that are differentially represented in a bladder cancer phenotype and their corresponding genetic sequences, i.e., mRNA, DNA, etc.
  • a “gene” or “recombinant gene” it is meant a nucleic acid comprising an open reading frame that encodes for the protein. The boundaries of a coding sequence are determined by a start codon at the 5' (amino) terminus and a translation stop codon at the 3' (carboxy) terminus. A transcription termination sequence may be located 3' to the coding sequence.
  • a gene may optionally include its natural promoter (i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell , i.e., a naturally occurring cell), and associated regulatory sequences, and may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation signals, translational start and stop sequences, ribosome binding sites, and the like.
  • its natural promoter i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell , i.e., a naturally occurring cell
  • associated regulatory sequences may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyaden
  • gene product or "expression product” are used herein to refer to the RNA transcription products (transcripts) of the gene, including mRNA; and the polypeptide translation products of such RNA transcripts, i.e. the amino acid product encoded by a gene.
  • a gene product can be, for example, an RNA transcript of the gene, e.g. an unspliced RNA, an mRNA, a splice variant mRNA, a microRNA, a fragmented RNA, etc.; or an amino acid product encoded by the gene, including, for example, full length polypeptide, splice variants of the full length polypeptide, post-translationally modified polypeptide, and fragments of the gene product, e.g. peptides, etc.
  • an elevated level of marker or marker activity may be associated with the bladder cancer phenotype.
  • a reduced level of marker or marker activity may be associated with the bladder cancer phenotype.
  • T is used to categorize the pathology of the tumor (TX: The primary tumor cannot be evaluated.TO: There is no evidence of a primary tumor in the bladder.Ta: This refers to noninvasive papillary carcinoma. This type of growth often is found on a small section of tissue that easily can be removed with TURBT. However, it tends to come back after treatment.Tis: This stage is carcinoma (cancer) in situ or a "flat tumor.” This means that the cancer is only found on or near the surface of the bladder. The doctor may also call it non- muscle-invasive/superficial bladder cancer or noninvasive flat carcinoma.
  • This type of bladder cancer often comes back after treatment, usually as another noninvasive cancer in the bladder.
  • TI The tumor has spread to the subepithelial connective tissue but does not involve the bladder wall muscle (lamina intestinal, the tissue below the inside lining of the bladder).
  • T2 The tumor has spread to the muscle of the bladder wall.
  • T2a The tumor has spread to the inner half of the muscle of the bladder wall, which may be called the superficial muscle.
  • T2b The tumor has spread to the deep muscle of the bladder (the outer half of the
  • T3 The tumor has grown into the perivesical tissue (the fatty tissue that surrounds the bladder).
  • T3a The tumor has grown into the perivesical tissue, as seen through a
  • the tumor has grown into the perivesical tissue macroscopically, meaning that the tumor(s) is large enough to be seen during imaging tests or to be seen or felt by the doctor.
  • T4 The tumor has spread to any of the following: the abdominal wall, the pelvic wall, a man's prostate or seminal vesicle (the tube(s) that carry semen), or a woman's uterus or vagina.T4a: The tumor has spread to the prostate, uterus, or vagina.T4b: The tumor has spread to the pelvic wall or the abdominal wall.); N describes the pathology of local lymph nodes (NX: The regional lymph nodes cannot be evaluated.NO: The cancer has not spread to the regional lymph nodes.N1 : The cancer has spread to a single regional lymph node in the pelvis.N2: The cancer has spread to more than one regional lymph node in the pelvis.N3: The cancer has spread to the common iliac lymph nodes, which are located behind the major arteries in the pelvis,
  • Table.1 The TNM classification for staging of bladder cancer.
  • a biomarker level is detected using a capture reagent.
  • the capture reagent contains a feature that is reactive with a secondary feature on a solid support. In these embodiments, the capture reagent is exposed to the biomarker in solution, and then the feature on the capture reagent is used in conjunction with the secondary feature on the solid support to immobilize the biomarker on the solid support.
  • Capture reagent is selected based on the type of analysis to be conducted.
  • Capture reagents include but are not limited to aptamers, antibodies, other antibody mimetics and other protein scaffolds, autoantibodies, chimeras, small molecules, F(ab')2 fragments, single chain antibody fragments, FV fragments, single chain FV fragments, nucleic acids, lectins, ligand-binding receptors, affybodies, nanobodies, imprinted polymers, avimers, peptidomimetics, hormone receptors, cytokine receptors, and synthetic receptors, and modifications and fragments of these.
  • biomarker presence or level is detected using a
  • biomarker/capture reagent complex the biomarker presence or level is derived from the biomarker/capture reagent complex and is detected indirectly, such as, for example, as a result of a reaction that is subsequent to the biomarker/capture reagent interaction, but is dependent on the formation of the biomarker/capture reagent complex.
  • biomarker presence or level is detected directly from the biomarker in a biological sample.
  • biomarkers are detected using a multiplexed format that allows for the simultaneous detection of two or more biomarkers in a biological sample.
  • capture reagents are immobilized, directly or indirectly, covalently or non-covalently, in discrete locations on a solid support.
  • a multiplexed format uses discrete solid supports where each solid support has a unique capture reagent associated with that solid support, such as, for example quantum dots.
  • an individual device is used for the detection of each one of multiple biomarkers to be detected in a biological sample. Individual devices are configured to permit each biomarker in the biological sample to be processed simultaneously. For example, a microtiter plate can be used such that each well in the plate is used to analyze one or more of multiple biomarkers to be detected in a biological sample.
  • the fluorescent label is a fluorescent dye molecule.
  • the fluorescent dye molecule includes at least one substituted indolium ring system in which the substituent on the 3-carbon of the indolium ring contains a chemically reactive group or a conjugated substance.
  • the dye molecule includes an AlexFluor molecule, such as, for example, AlexaFluor 488, AlexaFluor 532, AlexaFluor 647, AlexaFluor680, or AlexaFluor 700.
  • the dye molecule includes a first type and a second type of dye molecule, such as, e.g., two different AlexaFluor molecules.
  • the dye molecule includes a first type and a second type of dye molecule, and the two dye molecules have different emission spectra.
  • Fluorescence can be measured with a variety of instrumentation compatible with a wide range of assay formats.
  • instrumentation for example, spectrofluorimeters have been designed to analyze microtiter plates, microscope slides, printed arrays, cuvettes, etc. See Principles of
  • a chemiluminescence tag is optionally used to label a component of the biomarker/capture complex to enable the detection of a biomarker level.
  • Suitable chemiluminescent materials include any of oxalylchloride, Rodamin 6G, Ru(bipy)32+, TMAE (tetrakis(dimethylamino)ethylene), Pyrogallol (1 ,2,3-trihydroxibenzene), Lucigenin, peroxyoxalates, Aryl oxalates, Acridinium esters, dioxetanes, and others.
  • the detection method includes an enzyme/substrate combination that generates a detectable signal that corresponds to the biomarker level (e.g., using the techniques of ELISA, Western blotting, isoelectric focusing).
  • the enzyme catalyzes a chemical alteration of the chromogenic substrate which can be measured using various techniques, including spectrophotometry, fluorescence, and chemiluminescence.
  • Suitable enzymes include, for example, luciferases, luciferin, malate dehydrogenase, urease, horseradish peroxidase (HRPO), alkaline phosphatase, beta-galactosidase, glucoamylase, lysozyme, glucose oxidase, galactose oxidase, and glucose-6-phosphate dehydrogenase, unease, xanthine oxidase, lactoperoxidase, microperoxidase, and the like.
  • HRPO horseradish peroxidase
  • alkaline phosphatase beta-galactosidase
  • glucoamylase lysozyme
  • glucose oxidase galactose oxidase
  • glucose-6-phosphate dehydrogenase unease, xanthine oxidase, lactoperoxidase, microperoxidase, and the like.
  • the detection method is a combination of fluorescence, chemiluminescence, radionuclide or enzyme/substrate combinations that generate a
  • multimodal signaling has unique and advantageous characteristics in biomarker assay formats.
  • the biomarker levels for the biomarkers described herein is detected using any analytical methods including, singleplex aptamer assays, multiplexed aptamer assays, singleplex or multiplexed immunoassays, mRNA expression profiling histological/cytological methods, etc. as discussed below.
  • Measuring mRNA in a biological sample may, in some embodiments, be used as a surrogate for detection of the level of a corresponding protein in the biological sample.
  • a biomarker or biomarker panel described herein can be detected by detecting the appropriate RNA.
  • mRNA expression levels are measured by reverse transcription quantitative polymerase chain reaction (RT-PCR followed with qPCR).
  • RT-PCR reverse transcription quantitative polymerase chain reaction
  • qPCR reverse transcription quantitative polymerase chain reaction
  • qPCR fluorescence as the DNA amplification process progresses.
  • qPCR can produce an absolute measurement such as number of copies of mRNA per cell.
  • Northern blots, microarrays, RNAseq, Invader assays, and RT-PCR combined with capillary electrophoresis have all been used to measure expression levels of mRNA in a sample. See Gene Expression Profiling; Methods and Protocols, Richard A. Shimkets, editor, Humana Press, 2004; herein incorporated by reference in its entirety.
  • Immunoassay methods are based on the reaction of an antibody to its corresponding target or analyte and can detect the analyte in a sample depending on the specific assay format.
  • monoclonal antibodies and fragments are often used because of their specific epitope recognition.
  • Polyclonal antibodies have also been successfully used in various immunoassays because of their increased affinity for the target as compared to monoclonal antibodies.
  • Immunoassays have been designed for use with a wide range of biological sample matrices. Immunoassay formats have been designed to provide qualitative, semi-quantitative, and quantitative results.
  • Quantitative results are generated through the use of a standard curve created with known concentrations of the specific analyte to be detected.
  • the response or signal from an unknown sample is plotted onto the standard curve, and a quantity or level corresponding to the target in the unknown sample is established.
  • ELISA or EIA can be quantitative for the detection of an analyte. This method relies on attachment of a label to either the analyte or the antibody and the label component includes, either directly or indirectly, an enzyme. ELISA tests may be formatted for direct, indirect, competitive, or sandwich detection of the analyte. Other methods rely on labels such as, for example, radioisotopes (I 125 ) or fluorescence.
  • Additional techniques include, for example, agglutination, nephelometry, turbidimetry, Western blot, immunoprecipitation, immunocytochemistry, immunohistochemistry, flow cytometry, Luminex assay, and others (see ImmunoAssay: A Practical Guide, edited by Brian Law, published by Taylor & Francis, Ltd., 2005 edition; herein incorporated by reference in its entirety).
  • Exemplary assay formats include enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, fluorescent, chemiluminescence, and fluorescence resonance energy transfer (FRET) or time resolved-FRET (TR-FRET) immunoassays.
  • ELISA enzyme-linked immunosorbent assay
  • FRET fluorescence resonance energy transfer
  • TR-FRET time resolved-FRET
  • biomarkers include biomarker immunoprecipitation followed by quantitative methods that allow size and peptide level discrimination, such as gel electrophoresis, capillary electrophoresis, planar electrochromatography, and the like.
  • Methods of detecting and/or for quantifying a detectable label or signal generating material depend on the nature of the label.
  • the products of reactions catalyzed by appropriate enzymes can be, without limitation, fluorescent, luminescent, or radioactive or they may absorb visible or ultraviolet light.
  • detectors suitable for detecting such detectable labels include, without limitation, x-ray film, radioactivity counters, scintillation counters, spectrophotometers, colorimeters, fluorometers, luminometers, and densitometers.
  • Any of the methods for detection can be performed in any format that allows for any suitable preparation, processing, and analysis of the reactions. This can be, for example, in multi-well assay plates (e.g., 96 wells or 384 wells) or using any suitable array or microarray. Stock solutions for various agents can be made manually or robotically, and all subsequent pipetting, diluting, mixing, distribution, washing, incubating, sample readout, data collection and analysis can be done robotically using commercially available analysis software, robotics, and detection instrumentation capable of detecting a detectable label.
  • the biomarkers described herein may be detected in a variety of tissue samples using histological or cytological methods.
  • one or more capture reagent s specific to the corresponding biomarkers are used in a cytological evaluation of a sample and may include one or more of the following: collecting a cell sample, fixing the cell sample, dehydrating, clearing, immobilizing the cell sample on a microscope slide,
  • the cell sample is produced from a cell block.
  • one or more capture reagent/s specific to the corresponding biomarkers are used in a histological evaluation of a tissue sample and may include one or more of the following: collecting a tissue specimen, fixing the tissue sample, dehydrating, clearing, immobilizing the tissue sample on a microscope slide, permeabilizing the tissue sample, treating for analyte retrieval, staining, destaining, washing, blocking, rehydrating, and reacting with capture reagent/s in a buffered solution.
  • fixing and dehydrating are replaced with freezing.
  • results are analyzed and/or reported (e.g., to a patient, clinician, researcher, investigator, etc.).
  • Results, analyses, and/or data e.g., signature, disease score, diagnosis, recommended course, etc. are identified and/or reported as an
  • a result may be produced by receiving or generating data
  • results determined by methods described herein can be independently verified by further or repeat testing.
  • analysis results are reported (e.g., to a health care professional (e.g., laboratory technician or manager, physician, nurse, or assistant, etc.), patient, researcher, investigator, etc.).
  • a result is provided on a peripheral, device, or component of an apparatus.
  • an outcome is provided by a printer or display.
  • an outcome is reported in the form of a report.
  • an outcome can be displayed in a suitable format that facilitates downstream use of the reported information.
  • Generating and reporting results from the methods described herein comprises transformation of biological data (e.g., presence or level of biomarkers) into a representation of the characteristics of a subject (e.g., likelihood of mortality, likelihood corresponding to treatment, etc.). Such a representation reflects information not determinable in the absence of the method steps described herein. Converting biologic data into understandable characteristics of a subject allows actions to be taken in response such information.
  • a downstream individual upon receiving or reviewing a report comprising one or more results determined from the analyses provided herein, will take specific steps or actions in response. For example, a decision about whether or not to treat the subject, and/or how to treat the subject is made.
  • receiving a report refers to obtaining, by a communication means, a written and/or graphical representation comprising results or outcomes of analysis.
  • the report may be generated by a computer or by human data entry, and can be communicated using electronic means (e.g., over the internet, via computer, via fax, from one network location to another location at the same or different physical sites), or by another method of sending or receiving data (e.g., mail service, courier service and the like).
  • the outcome is transmitted in a suitable medium, including, without limitation, in verbal, document, or file form.
  • the file may be, for example, but not limited to, an auditory file, a computer readable file, a paper file, a laboratory file or a medical record file.
  • a report may be encrypted to prevent unauthorized viewing.
  • systems and method described herein transform data from one form into another form (e.g., from biomarker levels to diagnoistic/prognostic determination, etc.).
  • the terms “transformed'', "transformation”, and grammatical derivations or equivalents thereof refer to an alteration of data from a physical starting material (e.g., biological sample, etc.) into a digital representation of the physical starting material (e.g., biomarker levels), a condensation/representation of that starting material (e.g., risk level), or a recommended action (e.g., treatment, no treatment, etc.).
  • any combination of the biomarkers described herein can be detected using a suitable kit, such as for use in performing the methods disclosed herein.
  • the biomarkers described herein may be combined in any suitable combination, or may be combined with other markers not described herein.
  • any kit can contain one or more detectable labels as described herein, such as a fluorescent moiety, etc.
  • a kit includes (a) one or more capture reagents for detecting one or more biomarkers in a biological sample, and optionally (b) one or more software or computer program products for providing a diagnosis prognosis for the individual from whom the biological sample was obtained.
  • one or more instructions for manually performing the above steps by a human can be provided.
  • a kit comprises a solid support, a capture reagent, and a signal generating material.
  • the kit can also include instructions for using the devices and reagents, handling the sample, and analyzing the data. Further the kit may be used with a computer system or software to analyze and report the result of the analysis of the biological sample.
  • kits can also contain one or more reagents (e.g., solubilization buffers, detergents, washes, or buffers) for processing a biological sample.
  • reagents e.g., solubilization buffers, detergents, washes, or buffers
  • Any of the kits described herein can also include, e.g., buffers, blocking agents, mass spectrometry matrix materials, serum/plasma separators, antibody capture agents, positive control samples, negative control samples, software and information such as protocols, guidance and reference data.
  • kits are provided for the analysis of glioma, wherein the kits comprise PCR primers for one or more biomarkers described herein.
  • a kit may further include instructions for use and correlation of the biomarkers.
  • kits may include a DNA array containing the complement of one or more of the biomarkers described herein, reagents, and/or enzymes for amplifying or isolating sample DNA.
  • the kits may include reagents for real-time PCR, for example, TaqMan probes and/or primers, and enzymes.
  • a kit can comprise (a) reagents comprising at least one capture reagent for determining the level of one or more biomarkers in a test sample, and optionally (b) one or more algorithms or computer programs for performing the steps of comparing the amount of each biomarker quantified in the test sample to one or more predetermined cutoffs.
  • an algorithm or computer program assigns a score for each biomarker quantified based on said comparison and, in some embodiments, combines the assigned scores for each biomarker quantified to obtain a total score.
  • an algorithm or computer program compares the total score with a predetermined score, and uses the comparison to determine a diagnosis prognosis.
  • one or more instructions for manually performing the above steps by a human can be provided.
  • the subject following a determination that a subject has suffers from bladder cancer, the subject is appropriately treated.
  • therapy is administered to treat bladder cancer.
  • therapy is administered to treat complications of bladder cancer (e.g., surgery, radiation, chemotherapy).
  • treatment comprises palliative care.
  • methods of monitoring treatment of glioma are provided.
  • the present methods of detecting biomarkers are carried out at a time 0.
  • the method is carried out again at a time 1, and optionally, a time 2, and optionally, a time 3, etc., in order to monitor the progression of bladder cancer or to monitor the effectiveness of one or more treatments of bladder cancer.
  • Time points for detection may be separated by, for example at least 4 hours, at least 8 hours, at least 12 hours, at least 1 day, at least 2 days, at least 4 days, at least 1 week, at least 2 weeks, at least 1 month, at least 2 months, at least 3 months, at least 4 months, at least 6 months, or by 1 year or more.
  • a treatment regimen is altered based upon the results of monitoring (e.g., upon determining that a first treatment is ineffective).
  • the level of intervention may be altered.
  • Reagents, cloning vectors, and kits for genetic manipulation referred to in this disclosure are available from commercial vendors such as BioRad, Stratagene, Invitrogen, Sigma-Aldrich, and ClonTech.
  • the raw count RNA sequencing data for bladder cancer patients were downloaded from GDC data portal.
  • the patient clinical data, including specific tumor stage and grade, are downloaded from GDC data port.
  • the SRA RNA sequencing data for normal tissue were downloaded from GTEx data portal through dbGaP (Table 2).
  • the two data sets were then manually curated based on the available stage and grade information from patient clinical data.
  • the entire RNAseq pipeline was divided into two parts for GTEx data: alignment and quantification ( Figure 1).
  • the alignment step consists of: SRAto bam conversion using SRA Toolkits (SRA Toolkit development team), bam to fastq conversion using Biobambam (Tischler G et al.,2014), and fastq to aligned bam conversion using STAR (Alex D et al,.2016).
  • the quantification step consists of: quality improvement filtering using Fixmate
  • the output from quantification step results in gene raw counts for GTEx data and is combined with GDC gene profile for further downstream analysis.
  • the gene expression profile was then pre-filtered based on the mean expression per gene.
  • the filtered profile is then normalized using quantile metric and is converted into log2 scale.
  • combat package (from edgeR, http://www.r-proiect.orQ) is then used to perform further normalization between GDC case, GDC control, and GTEx control to minimize the difference between normal controls from two databases ( Figure 1 ).
  • the normalized gene profile is then analyzed by linear model using R package 'lirnma' (http://www.r-project.org/).
  • the 50 genes with relatively low p-values and relatively large absolute value of log2 fold change were selected as our panel. Random forest analysis.
  • the selected gene expression profile was firstly normalized to z-score across all the samples.
  • the probability of each sample in each subgroup can be calculated ( Figure 2).
  • Receiver-operator characteristic (ROC) analysis was conducted ( Figure 3) to evaluate the ability of the selected gene expression profile in differentiating the subjects in the testing cohort with early stage bladder cancer patients from those normal samples. This process was repeated 500 times using bootstrapping algorithm to get more accurate evaluation of the model.
  • RNA sequencing data for early stage bladder cancer tissue and normal bladder tissue were downloaded from GDC and GTEx data portal.
  • the patient clinical data, including specific tumor stage and grade, are downloaded from GDC data port.
  • the normal bladder tissue data from GTEx were processed using developed RNA-seq pipeline.
  • the Random Forest based risk model stratified all subjects in training and testing cohorts into two levels of risk for progression as discussed above (normal or early stage). 50 selected genes profiles (normalized) were used as the model input. The risk scores of all samples having bladder cancer were calculated by the model ( Figure 2). We use 0.5 as the cutoff threshold.
  • Unsupervised hierarchical clustering analysis was applied to the selected genes profiles to visually depict the association of the disease status with the abundance patterns of these genes profiles ( Figure 4). This analysis demonstrated two major clusters reflecting normal samples and early stage bladder cancer samples. The error rate of the unsupervised clustering is 1.1%, which reinforced the effectiveness of the selected gene profiles for bladder cancer assessment.

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Abstract

L'invention concerne des marqueurs du cancer de la vessie, des panels de marqueurs du cancer de la vessie, et des méthodes d'obtention d'une représentation du niveau des marqueurs du cancer de la vessie pour un échantillon, sur la base d'un profilage d'expression par ARN-seq. Ces compositions et méthodes sont utilisables dans un certain nombre d'applications dont, par exemple, le diagnostic du cancer de la vessie, le pronostic du cancer de la vessie, la surveillance d'un sujet atteint de cancer de la vessie, et la détermination d'un traitement du cancer de la vessie. L'invention concerne en outre des systèmes, des dispositifs et des trousses associés, utilisables dans la mise en pratique desdites méthodes.
PCT/US2017/023476 2017-03-21 2017-03-21 Méthodes et compositions de détection du cancer de la vessie à un stade précoce par profilage d'expression par arn-seq WO2018174862A1 (fr)

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CN109371118A (zh) * 2018-10-31 2019-02-22 北京致成生物医学科技有限公司 PRSS27和/或C16orf89在制备骨性关节炎诊断制剂中的应用
KR20220122197A (ko) * 2021-02-26 2022-09-02 충북대학교 산학협력단 비근침윤성 방광암의 예후 예측을 위한 바이오마커 및 이의 용도

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Cited By (3)

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Publication number Priority date Publication date Assignee Title
CN109371118A (zh) * 2018-10-31 2019-02-22 北京致成生物医学科技有限公司 PRSS27和/或C16orf89在制备骨性关节炎诊断制剂中的应用
KR20220122197A (ko) * 2021-02-26 2022-09-02 충북대학교 산학협력단 비근침윤성 방광암의 예후 예측을 위한 바이오마커 및 이의 용도
KR102632423B1 (ko) * 2021-02-26 2024-01-31 충북대학교 산학협력단 비근침윤성 방광암의 예후 예측을 위한 바이오마커 및 이의 용도

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