WO2024076307A1 - Compositions et procédés d'évaluation d'acides nucléiques dans un échantillon biologique - Google Patents

Compositions et procédés d'évaluation d'acides nucléiques dans un échantillon biologique Download PDF

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WO2024076307A1
WO2024076307A1 PCT/SG2023/050671 SG2023050671W WO2024076307A1 WO 2024076307 A1 WO2024076307 A1 WO 2024076307A1 SG 2023050671 W SG2023050671 W SG 2023050671W WO 2024076307 A1 WO2024076307 A1 WO 2024076307A1
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mir
hsa
sample
level
biomarker
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PCT/SG2023/050671
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Suit-Fong CHAN
He Cheng
Karen Kai Rui GOH
Ruiyang ZOU
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MiRXES Lab Pte. Ltd.
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Publication of WO2024076307A1 publication Critical patent/WO2024076307A1/fr

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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
    • C12Q1/6806—Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay
    • 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
    • C12Q2600/158—Expression markers
    • 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
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention relates generally to the field of molecular biology.
  • the present invention relates to biomarkers, reagents and methods for use in the pre-analytical workflow for the assessment of nucleic acids in biological samples.
  • Improper blood processing may result in cellular contamination or haemolysis of plasma or serum which renders variation in nucleic acid profile unrelated to pathological conditions. Residual platelet contamination is another significant confounding source of circulating nucleic acids. Additionally, assessing the condition of the nucleic acids in a sample is useful for ensuring that the samples with degraded nucleic acids can be identified to reduce potential errors.
  • the application of nucleic acid detection and quantification in the clinical or research labs requires highly reliable and reproducible system to minimise the effect of such confounders. Therefore, proper quality control as well as reliable blood sampling and processing steps become critical preanalytical steps.
  • a method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from the group consisting of hsa-miR-28-5p, hsa-miR- 1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the quality of the sample is determined by a) the level of platelet activation and/or aggregation in the sample, b) the level of haemolysis in the sample, and/or c) the level of stability of nucleic acid in the sample.
  • a) is determined by measuring/detecting/determining the level of one or more biomarker selected from the group consisting of hsa-miR-28-5p and hsa-miR-1973.
  • the method comprises determining the level of one of the following: hsa-miR-28-5p; or hsa-miR-1973; or hsa-miR-1973 and hsa-miR-28-5p.
  • b) is determined by measuring/detecting/determining the level of one or more biomarker selected from the group consisting of hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451a.
  • the method comprises determining the level of one of the following: hsa-miR- 20b-5p; hsa-miR-363-3p; hsa-miR-451 a; hsa-miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363-3p and hsa-miR-451a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa- miR-451a.
  • c) is determined by measuring/detecting/determining the level of one or more biomarker is selected from hsa-miR-143-3p and hsa-miR-618. In some embodiments, the method comprises determining the level of: hsa-miR-143-3p; hsa-miR-618; or hsa-miR-143-3p and hsa-miR- 618.
  • a method of determining the level of platelet activation and/or aggregation in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-28-5p and hsa-miR-1973.
  • the method comprises determining the level of one of the following: hsa-miR- 28-5p; hsa-miR-1973; or hsa-miR-1973 and hsa-miR-28-5p.
  • a method of determining the level of haemolysis in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a.
  • the method comprises determining the level of one of the following: hsa-miR- 20b-5p; hsa-miR-363-3p; hsa-miR-451 a; hsa-miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363-3p and hsa-miR-451a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa- miR-451a.
  • a method of determining the level of stability of nucleic acid in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of: hsa-miR-143-3p; hsa-miR- 618; or hsa-miR-143-3p and hsa-miR-618. In some embodiments, the method further comprises determining the level of one or more biomarker selected from hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • the method further comprises comparing the level of hsa-miR-1973 and/or hsa-miR-28-5p with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of platelet activation and/or aggregation in the sample.
  • the method further comprises comparing the level of one or more of hsa-miR- 20b-5p, hsa-miR-363-3p and hsa-miR-451 a with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of haemolysis in the sample.
  • the method further comprises comparing the level of hsa-miR-143-3p and hsa- miR-618 with that of hsa-miR-1290 and/or hsa-miR-720 to determine the level of stability of nucleic acid in the sample.
  • the method comprises determining the level of at least one biomarker in each of the following group: (a) hsa-miR-28-5p and hsa-miR-1973; (b) hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a; and (c) hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of hsa-miR-28-5p, hsa-miR-1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of biomarkers hsa-miR-28-5p, hsa-miR-1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa- miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • the method comprises comparing the level of two or more biomarkers to determine a score, wherein the score is compared to that of a control for determining the quality of the sample.
  • the sample is a blood sample or a non-cellular bodily fluid sample obtained from a subject, optionally the sample is a plasma and/or serum.
  • kits for use in the method as disclosed herein comprises an isolated set of probes and/or reagents capable of determining the expression level of the one or more biomarker selected from the group consisting of hsa-miR-1973, hsa-miR-28-5p, hsa- miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the kit further comprises an isolated set of probes and/or reagents capable of determining the expression level of one or more biomarker selected from the group consisting of hsa- miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • isolated sets of probes capable of detecting at least one biomarker associated with platelet activation and/or aggregation, haemolysis or nucleic acid degradation in a sample.
  • isolated sets of probes capable of detecting and/or determining the level of at least one biomarker selected from hsa-miR-1973 and hsa-miR-28-5p for use in determining the level of platelet activation and/or aggregation in a sample.
  • the isolated set of probes may further comprise at least one probe for detecting and/or determining the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p.
  • the isolated set of probes comprises probes for detecting and/or determining the level of hsa-miR-1973, hsa-miR-28-5p, hsa-miR-1290 and hsa-miR-10b-5p.
  • isolated sets of probes capable of detecting and/or determining the level of at least one biomarker selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a for use in determining the level of haemolysis in a sample.
  • the isolated set of probes further comprises at least one probe for detecting and/or determining the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p.
  • the isolated set of probes comprises probes for detecting and/or determining the level of hsa-miR-20b-5p, hsa-miR-363-3p, hsa- miR-451a, hsa-miR-1290 and hsa-miR-10b-5p.
  • isolated set of probes capable of detecting and/or determining the level of at least one biomarker selected from hsa-miR-143-3p and hsa-miR-618 for use in determining the level of stability of nucleic acid in a sample, optionally wherein the sample is a stored sample.
  • the isolated set of probes may further include at least one probe for detecting and/or determining the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-720, optionally wherein the sample is a stored sample.
  • the isolated set of probes comprises probes for detecting and/or determining the level of hsa-miR-143-3p, hsa-miR-618, hsa- miR-1290 and hsa-miR-720, optionally wherein the sample is a stored sample.
  • isolated set of probes capable of detecting and/or determining the level of at least one biomarker selected from hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa- miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • the isolated set of probes comprises probes for detecting and/or determining the level of hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • kits for determining the level of platelet activation and/or aggregation in a sample comprising reagents for detecting and/or determining the expression level of at least one biomarker selected from hsa-miR-28-5p and hsa-miR-1973.
  • reagents may include, but is not limited to, probes, primers, aptamers, antibodies, buffers, and enzymes.
  • the kit further comprises reagents for detecting and/or measuring the level of hsa- miR-1290 and hsa-miR-10b-5p. In some examples, the kit comprises reagents for detecting and/or determining the level of hsa-miR-1973, hsa-miR-28-5p, hsa-miR-1290 and hsa-miR-10b-5p. In some examples, such reagents may include, but is not limited to, probes, primers, aptamers, antibodies, buffers, enzymes, and the like.
  • kits for determining the level of haemolysis in a sample comprising an isolated set of probes and/or reagents for detecting and/or determining the expression level of at least one biomarker selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a.
  • the kit comprises reagents for detecting and/or determining the level of hsa-miR-1290 and hsa-miR-10b-5p.
  • the kit comprises reagents for detecting and/or determining the level of hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-1290 and hsa-miR-10b-5p.
  • reagents may include probes, primers, aptamers, antibodies, buffers and enzymes.
  • kits for determining the level of stability of nucleic acid in a sample comprising reagents for detecting and/or determining the expression level of at least one biomarker selected from hsa-miR-143-3p and hsa-miR-618, optionally wherein the sample is a stored sample.
  • the kit further comprises reagents for detecting and/or determining the level of hsa- miR-1290 and hsa-miR-720.
  • the kit comprises reagents for detecting and/or determining the level of hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290 and hsa-miR-720.
  • reagents may include probes, primers, aptamers, antibodies, buffers and enzymes.
  • the method comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-1973 and hsa-miR-28-5p. In some embodiments, the method comprises determining the level of one or two biomarker in the sample, wherein the biomarker is hsa-miR-1973; hsa-miR-28-5p; or hsa-miR-1973 and hsa-miR-28-5p.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p, such as hsa-miR-1290; hsa- miR-10b-5p; or hsa-miR-1290 and hsa-miR-10b-5p.
  • the method further comprises comparing the level of hsa-miR-1973 and/or hsa-miR-28-5p with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of platelet activation and/or aggregation in the sample.
  • Also provided herein is a method of determining the level of haemolysis in a sample the method comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a. In some embodiments, the method comprises determining the level of one, two or three biomarkers.
  • the method comprises determining the level of hsa-miR-20b-5p; hsa-miR-363-3p; hsa- miR-451a; hsa-miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363- 3p and hsa-miR-451 a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a in the sample.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p, such as hsa-miR-1290; hsa- miR-10b-5p; or hsa-miR-1290 and hsa-miR-10b-5p.
  • the method further comprises comparing the level of one or more of hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of haemolysis in the sample.
  • the method comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-1 3-3p and hsa-miR-618. In some embodiments, the method comprises determining the level of hsa-miR-143-3p; hsa-miR-618; or hsa-miR-143-3p and hsa-miR-618 in the sample.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR- 720, such as hsa-miR-1290; hsa-miR-720; or hsa-miR-1290 and hsa-miR-720. In some embodiments, the method further comprises comparing the level of hsa-miR-143-3p and/or hsa-miR- 618 with that of hsa-miR-1290 and/or hsa-miR-720 to determine the level of stability of nucleic acid in the sample.
  • the method further comprises comparing the level of two or more biomarker to determine a score for determining the level of platelet activation and/or aggregation, stability of nucleic acid or level of haemolysis in a sample.
  • the method comprises comparing the level of two or more biomarkers, wherein one of the biomarkers is a reference or normaliser biomarker.
  • the score is compared to that of a control for determining the level of platelet activation and/or aggregation, stability of nucleic acid or level of haemolysis in a sample.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis comprises detecting the presence of at least one of the following conditions in the sample: (a) level of platelet activation and/or aggregation; (b) level of haemolysis; and/or (c) level of stability of nucleic acid, wherein should one or more of the above conditions is identified in the sample, a person with the relevant skill in the art would be able to make the judgement to: (a) not to proceed with nucleic acid analysis for the sample; (b) to make adjustments in the data analysis for the affected sample to adjust for the biasness of the nucleic acid profile in said sample; and/or (c) to undertake other corrective measures necessary to derive useful information on the nucleic acid content of the sample.
  • the method comprises determining in the sample the level of one or more biomarkers selected from hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa- miR-363-3p, hsa-miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa-miR-10b-5p and hsa- miR-720.ln some embodiments, the method comprises determining the level of at least one biomarker in each of the following group: (a) hsa-miR-1973 and hsa-miR-28-5p; (b) hsa-miR-20b-5p, hsa-miR- 363-3p and
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290, hsa-miR-10b-5p and hsa-miR- 720.
  • the method further comprises determining the level of one, two or three biomarkers, such as hsa-miR-1290; hsa-miR-10b-5p; hsa-miR-720; hsa-miR-1290 and hsa-miR-10b- 5p; hsa-miR-1290 and hsa-miR-720; hsa-miR-10b-5p and hsa-miR-720; or hsa-miR-1290, hsa-miR- 10b-5p and hsa-miR-720.
  • biomarkers such as hsa-miR-1290; hsa-miR-10b-5p; hsa-miR-720; hsa-miR-1290 and hsa-miR-10b-5p and hsa-miR-720.
  • the method comprises determining the level of hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa- miR-10b-5p and hsa-miR-720.
  • the method further comprises comparing the level of two or more biomarkers to determine a score for determining the quality of a sample. In some embodiments, the score is compared to that of a control for determining the quality of the sample.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis comprises detecting in the sample the level of platelet activation and/or aggregation in the sample by detecting the level of at least one biomarker selected from hsa-miR-1973 and hsa-miR-28-5p compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa- miR-1290 and hsa-miR-10b-5p.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis comprises detecting in the sample the level of haemolysis in the sample by detecting the level of at least one biomarker selected from hsa-miR-20b- 5p, hsa-miR-363-3p and hsa-miR-451a compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis comprises detecting in the sample the level of stability of nucleic acid in the sample by detecting the level of at least one biomarker selected from hsa-miR-143-3p and hsa-miR-618 compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-720.
  • the present disclosure refers to a kit for use in performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis, comprising reagents for detecting the expression of at least one biomarker selected from the group consisting of hsa-miR- 1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p and hsa- miR-618.
  • the kit further comprises reagents for detecting the expression of at least one biomarker selected from the group consisting of hsa-miR-1290, hsa-miR-10b-5p and hsa- miR-720.
  • reagents may include probes, primers, aptamers, antibodies, buffers and enzymes.
  • kits for use in any of the methods comprises an isolated set of probes and/or reagents capable of determining the level of the one or more biomarkers of the preceding claims.
  • kits as disclosed herein may further comprise instructions for the reagents to be used for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis. Therefore, the kits may further comprise instructions for using the reagents to assess the presence of at least one of the following conditions in the sample: (a) level of platelet activation and/or aggregation; (b) level of haemolysis; and/or (c) level of stability of nucleic acid.
  • a biological sample e.g., blood
  • methods for collecting a biological sample comprises: (a) collecting an initial first volume of the biological sample; and subsequently, (b) collecting a second volume of the biological sample in a separate container, for use in nucleic acid analysis.
  • the initial first volume and second volume of biological samples are not to be combined for nucleic acid analysis and preferentially, be collected in discrete containers.
  • the containers may be, but not limited to, tubes, flasks, bags and compartments within containers.
  • the initial first volume of the biological sample may be discarded and the volume to be discarded may be at least 1 millilitre (mL). In another aspect, the initial first volume of the biological sample to be discarded may be approximately 1 -2mL.
  • the first centrifugation may be carried out at a speed of from 1 ,000g to 5,000g, such as from 1 ,000g to 4,000g, such as from 1 ,000g to 2,000g, such as 1 ,500g.
  • the second centrifugation would be carried out at a speed of from 1 ,500g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 2,500g.
  • the centrifugation time for the first and second centrifugation may be independently selected from 1 min to 30 min, such as from 5 min to 20 min, such as 15 min.
  • the methods of processing a biological sample for nucleic acid analysis may include cryopreservation of the first supernatant after the first centrifugation, with the second centrifugation being carried out following the thawing of the cryopreserved first supernatant (i.e., after freeze/thaw).
  • a method of collecting and processing a biological sample for nucleic acid analysis comprising: (a) collecting an initial first volume of biological sample; (b) collecting a second volume of biological sample in a separate container; (c) subjecting the second volume of the biological sample to a first centrifugation to provide a first supernatant; and (d) subjecting the first supernatant to a second centrifugation to provide a second supernatant.
  • the first centrifugation may be carried out at a speed of from 1 ,000g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 1 ,500g.
  • the second centrifugation may be carried out at a speed of 1 ,500g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 2,500g.
  • the centrifugation time for the first and second centrifugation may be independently selected from 1 min to 30 min, such as from 5 min to 20 min, such as 15 min.
  • the first supernatant may be cryopreserved after the first centrifugation, with the second centrifugation performed following the thawing of the cryopreserved first supernatant.
  • the method may further comprise determining in the second supernatant, the level of at least one biomarker selected from hsa-miR-1973, hsa-miR-28-5p, hsa- miR-20b-5p, hsa-miR-363-3p, hsa-miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa- miR-10b-5p and hsa-miR-720.
  • the sample is selected from a tissue sample (e g. biopsy tissue sample), a blood sample, or a non-cellular bodily fluid sample obtained from a subject, optionally the sample is a plasma and/or serum.
  • the biomarker is microRNA (miRNA).
  • the one or more biomarkers are detected/determined by methods known in the art such as, but is not limited to, sequencing, nucleic acid hybridisation, microarray and nucleic acid amplification.
  • nucleic acid amplification may include, but is not limited to, a reverse transcription-quantitative polymerase chain reaction (RT-qPCR), reverse transcription-polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), a locked nucleic acid PCR, a clustered regularly interspaced short palindromic repeat (CRISPR)-based assay, isothermal amplification assay, and the like.
  • RT-qPCR reverse transcription-quantitative polymerase chain reaction
  • RT-PCR reverse transcription-polymerase chain reaction
  • qPCR quantitative polymerase chain reaction
  • locked nucleic acid PCR a locked nucleic acid PCR
  • CRISPR clustered regularly interspaced short palindromic repeat
  • RNA can refer to a gene, protein, or nucleic acid whose level of expression or concentration in a sample is altered compared to that of a control.
  • a nucleic acid can refer to a deoxyribonucleic acid (DNA) or a ribonucleic acid (RNA).
  • RNA may further refer to a messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA) or small RNAs such as microRNAs (miRNAs), PlWI-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), small interfering RNAs (siRNAs), Y RNA and small nuclear RNAs (snRNAs).
  • mRNA messenger RNA
  • rRNA ribosomal RNA
  • tRNA transfer RNA
  • small RNAs such as microRNAs (miRNAs), PlWI-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), small
  • circulating biomarkers shall refer to cell-free biomarkers found in blood and may include nucleic acids, extracellular vesicles, proteins and metabolites.
  • the term circulating nucleic acids may refer to circulating tumour DNA, mRNA, miRNA or other small RNAs found in blood.
  • nucleic acid analysis can refer to the detection or measurement of nucleic acids (e.g., miRNA, circulating DNA, mRNA or other small RNA) using sequencing (e.g. Sanger sequencing, bisulfite sequencing or next generation sequencing), nucleic acid hybridization (e.g., northern blot), microarray and nucleic acid amplification (e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR), reverse transcription polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), a locked nucleic acid (LNA) real-time PCR, a CRISPR-based assay, or isothermal amplification assay.
  • sequencing e.g. Sanger sequencing, bisulfite sequencing or next generation sequencing
  • nucleic acid hybridization e.g., northern blot
  • microarray and nucleic acid amplification e.g., quantitative reverse transcription polymerase chain reaction (qRT-PCR), reverse transcription polymerase chain reaction (RT-PCR), quantitative polyme
  • An isothermal amplification assay can, for example, include, but is not limited to, a nicking endonuclease amplification reaction (NEAR) assay, a transcription mediated amplification (TMA) assay, a loop-mediated isothermal amplification (LAMP) assay, a helicase-dependent amplification (HDA) assay, a clustered regularly interspaced short palindromic repeat (CRISPR) assay, or a strand displacement amplification (SDA) assay.
  • NEAR nicking endonuclease amplification reaction
  • TMA transcription mediated amplification
  • LAMP loop-mediated isothermal amplification
  • HDA helicase-dependent amplification
  • CRISPR clustered regularly interspaced short palindromic repeat
  • SDA strand displacement amplification
  • nucleic acid analysis may refer to the detection or measurement of circulating nucleic acids (e.g., miRNA).
  • a control refers to a level of expression or concentration of a biomarker that is indicative or correlated with a different outcome compared to the outcome of interest.
  • a biomarker can be a nucleic acid whose level of expression or concentration is altered (e.g, increased or decreased) due to a phenomenon (e.g., degradation, storage, haemolysis, platelet activation, centrifugation, etc) compared to that of a control which had not undergone the alteration. It is understood by anyone with the relevant skill in the art that comparing the level of expression in the control does not necessarily entail obtaining a control sample and testing said sample at the same time as the test subject.
  • said control could be a control sample incorporated in the kit or a threshold set to represent the range of expression of the biomarker where expression levels falling into this range would identify a test sample as having undergone a phenomenon (e.g., degradation, storage, haemolysis, platelet activation, centrifugation, etc) that led to the alteration of the measured biomarker.
  • a phenomenon e.g., degradation, storage, haemolysis, platelet activation, centrifugation, etc
  • level or “expression level” of a biomarker refers to the concentrations of the biomarkers in the sample and may be expressed in any suitable forms of concentration known to the person skilled in the art, such as ng/ pL, copy number, log(concentration), Iog2 copies/mL, threshold cycle (Ct) or quantification cycle (Cq) from qPCR and Ct or Cq power of 2.
  • sample biological sample or biological material
  • biological sample is intended to include any sampling of cells, tissues, or bodily fluids in which expression of a biomarker can be detected.
  • samples and biological samples include, but are not limited to, biopsies, smears, blood, lymph, urine, saliva, or any other bodily secretion or derivative thereof.
  • Blood can, for example, include whole blood, plasma, serum, or any derivative of blood.
  • the sample or biological sample is whole blood, and/or a non-cellular bodily fluid.
  • the non-cellular bodily fluid may comprise serum or plasma. Samples can be obtained from a subject by a variety of techniques, which are known to those skilled in the art.
  • the term “differential expression” refers to the measurement of a component (such as a cellular component) in comparison to a control or another sample, and thereby determining the difference in, for example concentration, presence or intensity of said component (such as said cellular component).
  • the result of such a comparison can be given in the absolute, that is a component is present in the samples and not in the control, or in the relative, that is the expression or concentration of component is increased or decreased compared to the control.
  • the terms “increased” and “decreased” in this case can be interchanged with the terms “upregulated” and “downregulated” which are also used in the present disclosure.
  • determining the stability of the nucleic acid in a sample refers to the assessment of a sample to determine whether the nucleic acid content in said sample has been altered (chemically and/or structurally) due to prolonged storage or incorrect storage condition leading to degradation or alteration of at least some of the nucleic acid within the sample.
  • determining the level of haemolysis in a sample refers to assessing the extent of breakdown of erythrocytes, commonly referred to as red blood cells, resulting in the release of haemoglobin into the surrounding fluid in the sample.
  • the determination of level of haemolysis may be performed using any common methods known in the art. Common methods to determine haemolysis may include, but is not limited to, visual inspection, quantification of cell-free haemoglobin level (e.g. using a human haemoglobin enzyme-linked immunosorbent assay (ELISA)), and the like.
  • ELISA human haemoglobin enzyme-linked immunosorbent assay
  • determining the level of platelet activation and/or aggregation in a sample refers to measuring the level of platelet-to-platelet (thrombocytes) adhesion to aggregation in the sample, or the extent of clot formation.
  • the level of platelet activation can be assessed by methods known in the art, such as, but is not limited to, flow cytometry (to detect the activated platelets directly), ELISA (to detect markers related to platelet activation (e.g. thromboxane A2 and B2 (TXA2 and TXB2)), and the like.
  • performing quality control on a sample and/or assessing the quality of a sample intended for nucleic acid analysis may refer to determining if a sample has undergone degradation due to prolonged storage, incorrect storage condition or improper sample handling procedures leading to degradation of at least some of the nucleic acid within the sample, hence altering the detectable level of at least some of the nucleic acids contained within the sample.
  • performing quality control on a sample and/or assessing the quality of a sample for use in nucleic analysis may refer to determining whether a sample has undergone alterations to its nucleic acid level due to improper sample handling, prolonged storage or incorrect storage condition to create variations that are unrelated to the original condition of the sample.
  • alterations could be the release of cellular nucleic acids due to cellular contamination, activation of cellular response (e.g., platelet activation or aggregation) or haemolysis leading to contamination of the plasma or serum. It is understood by someone with knowledge in the art that, in some cases, such alterations may result in unacceptably low signal-to-noise ratio, which may render such samples unsuitable for analysis as the nucleic acid expression data could be uninformative or biased, leading to possible misinterpretation or misidentification of relevant biomarkers of interest.
  • the person with the relevant skill in the art would be able to make the judgement to: (a) not to proceed with nucleic acid analysis for the sample; (b) to make adjustments in the data analysis for the affected sample to adjust for the biasness of the nucleic acid profile in said sample; and/or (c) to undertake other corrective measures necessary to derive useful information on the nucleic acid content of the sample.
  • probe refers to any molecule or agent that is capable of selectively detecting an intended target biomolecule, for example, by binding directly or indirectly to the target biomolecule.
  • the target molecule can be a biomarker, for example, a nucleotide transcript or a protein encoded by or corresponding to a biomarker.
  • Probes can be synthesized by one of skill in the art, or derived from appropriate biological preparations, in view of the present disclosure. Probes can be specifically designed to be labelled. Examples of molecules that can be utilized as probes include, but are not limited to, RNA, DNA (e.g, primers), proteins, peptides, antibodies, aptamers, affibodies, and organic molecules.
  • a probe designed for the detection of a nucleic acid biomarker such a probe may be directed to the target region, the complementary nucleic acid sequence on the reverse strand or copies of the same generated via an amplification process.
  • (statistical) classification refers to the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.
  • An example is assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.).
  • classification is considered an instance of supervised learning, i.e., learning where a training set of correctly identified observations is available.
  • the corresponding unsupervised procedure is known as clustering and involves grouping data into categories based on some measure of inherent similarity or distance.
  • the individual observations are analysed into a set of quantifiable properties, known variously as explanatory variables or features. These properties may variously be categorical (e.g., "A”, “B”, “AB” or “O”, for blood type), ordinal (e.g., “large”, “medium” or “small”), integer-valued (e.g., the number of occurrences of a part word in an email) or real-valued (e.g., a measurement of blood pressure). Other classifiers work by comparing observations to previous observations by means of a similarity or distance function. An algorithm that implements classification, especially in a concrete implementation, is known as a classifier. The term “classifier” sometimes also refers to the mathematical function, implemented by a classification algorithm, which maps input data to a category.
  • the term “pre-trained” or “supervised (machine) learning” refers to a machine learning task of inferring a function from labelled training data.
  • the training data can consist of a set of training examples.
  • each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal).
  • a supervised learning algorithm that is the algorithm to be trained, analyses the training data and produces an inferred function, which can be used for mapping new examples.
  • An optimal scenario will allow for the algorithm to correctly determine the class labels for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way.
  • the term “score” refers to an integer or number, that can be determined mathematically, for example by using computational models known in the art, which can include but are not limited to, SMV, as an example, and that is calculated using any one of a multitude of mathematical equations and/or algorithms known in the art for the purpose of statistical classification. Such a score is used to enumerate one outcome on a spectrum of possible outcomes. The relevance and statistical significance of such a score depends on the size and the quality of the underlying data set used to establish the results spectrum. For example, a blind sample may be input into an algorithm, which in turn calculates a score based on the information provided by the analysis of the blind sample. This results in the generation of a score for said blind sample.
  • a decision can be made, for example, how likely the patient, from which the blind sample was obtained, has cancer or not.
  • the ends of the spectrum may be defined logically based on the data provided, or arbitrarily according to the requirement of the experimenter. In both cases the spectrum needs to be defined before a blind sample is tested.
  • the score generated by such a blind sample for example the number “45” may indicate that the corresponding patient has cancer, based on a spectrum defined as a scale from 1 to 50, with “1" being defined as being cancer-free and “50” being defined as having cancer.
  • FIG. 1 shows the hemoglobin level, platelet activation, and miRNA expression levels in blood samples under different processing methods: serum with a clotting duration of 30 min (serum 30); serum with a clotting duration of 60 min (serum 60); serum with clotting duration of 90 min (serum 90); normal plasma samples (plasma); platelet-poor-plasma (PPP).
  • serum with a clotting duration of 30 min serum with a clotting duration of 30 min (serum 60); serum with clotting duration of 90 min (serum 90); normal plasma samples (plasma); platelet-poor-plasma (PPP).
  • A Haemolysis level measured by human hemoglobin enzyme-linked immunosorbent assay (ELISA). The hemoglobin concentration was similar among all serum samples but higher in both plasma and PPP samples.
  • ELISA human hemoglobin enzyme-linked immunosorbent assay
  • TXB2 concentration in both plasma and PPP was minimal as platelet activation did not take place.
  • C The miRNA expression examined by miRNA profiling. The average expression level of all measured miRNAs was used to indicate the expression level for a sample. miRNA level increased when clotting duration increased in serum. miRNA expression was highest in plasma while PPP had comparable expression level to serum.
  • FIG. 2 shows the principal component analysis (PCA) scatter plot from 356 miRNA profiling after global normalization.
  • PCA principal component analysis
  • (a) hsa-miR-1973 and (b) hsa-miR-28-5p showed higher expression in plasma than PPP.
  • the expression in serum also correlated well with TXB2 level (platelet activation),
  • TXB2 depicts the expression of miRNA markers and thromboxane B2 (TBX2) in different sample types.
  • A-D Platelet-related markers are hsa-miR-1973 (A) and hsa-miR-28-5p (B), and reference markers are hsa-miR-1290 (C) and hsa-miR-10b-5p (D).
  • E: TBX2 level is shown. miRNA expression level in Iog2 copy numbers per milliliter of samples (Log2 copies/mL) was determined by miRNA profiling. TBX2 was measured by enzyme-linked immunosorbent assay. Refer to Table 3 for the P value from one-way analysis of variance, n 10.
  • FIG. 5 depicts the expression of platelet-related biomarkers in different sample types. Blood was collected from 12 healthy volunteers and processed into serum (60 minutes of clotting), plasma, and platelet-poor plasma (PPP).
  • A-D The expression of platelet-related biomarkers hsa-miR-1973 (A) and hsa-miR-28-5p (B) and reference markers hsa-miR-1290 (C) and hsa-miR-10b-5p (D) in serum (60 minutes of clotting), plasma and PPP.
  • the results indicate that PPP had the lowest expression of platelet-related biomarkers, A and A, among the different samples.
  • Statistical analyses were performed with one-way analysis of variance. **P ⁇ 0.01 , ***P ⁇ 0.001 , and ****P ⁇ 0.0001.
  • FIG. 6 depicts the expression profile of miRNA in red blood cells (RBCs), platelet-poor plasma (PPP) spiked with different concentration of RBC lysate (hemo 1 , hemo 2, and hemo 3) and non-spiked PPP (no hemo).
  • RBCs red blood cells
  • PPP platelet-poor plasma
  • the expression of the RBC-related markers hsa-miR-20b-5p, hsa-miR-363-3p, and hsa- miR-451a increased when the RBC concentration increased.
  • FIG. 7 depicts the expression profile of miRNA in red blood cells (RBCs), platelet-poor plasma (PPP) spiked with different concentration of RBC lysate (hemo 1 , hemo 2, and hemo 3) and non-spiked PPP (no hemo).
  • A The difference in miRNA expression (A) in RBC and spiked PPP against non-spiked PPP. Each bar represents an individual miRNA.
  • A Hemoglobin levels (measured by ELISA) were significantly higher in discard tubes when compared to 6-mL tube and 10-mL tube (* p ⁇ 0.05).
  • B Haemolysis scores: mean raw threshold cycle (Cq) of red blood cell- related miRNAs minus mean Cq of reference miRNAs. No significant difference was seen in haemolysis score for tubes with different sizes.
  • C Platelet scores: mean Cq of platelet-related miRNAs minus mean Cq of reference miRNAs. No significant difference was seen in Platelet score for tubes with different sizes.
  • Statistical analyses were performed with one-way analysis of variance (A) and paired t-test (B and C).
  • FIG. 10 shows the comparison of sample quality from post freeze-thaw spin.
  • A Haemolysis scores: mean raw threshold cycle (Cq) of red blood cell-related miRNAs minus mean Cq of reference miRNAs. The haemolysis scores remained unchanged at all conditions.
  • B Platelet scores: mean Cq of platelet-related miRNAs minus mean Cq of reference miRNAs. The platelet score showed that the best condition was Con2. For FT (Freeze-thaw) samples, the second spin upon thawing (Con4) can partially remove platelets, hence increasing the platelet score.
  • A Hemoglobin level by Hb ELISA. The assay showed an elevated hemoglobin level in on ice samples.
  • B Haemolysis scores: mean raw threshold cycle (Cq) of red blood cell-related miRNAs minus mean Cq of reference miRNAs. The haemolysis score was consistent with Hb ELISA and showed significant difference in on ice samples.
  • C Platelet scores: mean Cq of platelet-related miRNAs minus mean Cq of reference miRNAs. The platelet score slightly decreased in on ice samples indicating lysis of platelets.
  • FIG. 14 shows the regression coefficient of miRNA against expression in Log2 copies/mL for (A) serum and (B) PPP at 4 °C.
  • Each marker represents one individual miRNA.
  • hsa-miR-143-3p and hsa- miR-618 were highlighted because they were chosen to be stability markers, whereas hsa-miR-1290 and hsa-miR-720 were highlighted as reference markers.
  • Stability markers were identified as miRNAs negatively correlated to storage time, decent expression in samples and poses minimal correlation with both haemolysis and platelet.
  • Regression coefficient was obtained from linear regression performed between miRNA expression level in serum or PPP samples and storage duration (days) at 4°C. There is a negative correlation trend between degradation and miRNA expression level in (A) serum and (B) PPP.
  • Regression coefficient (y axis) was obtained from linear regression performed between miRNA expression level in serum or PPP samples and storage duration (days) at 4°C.
  • FIG. 16 depicts a schematic workflow of recommended blood collection, processing, and storage conditions.
  • PPP platelet-poor plasma
  • RBCs red blood cells.
  • Circulating nucleic acids such as miRNAs were identified in human plasma and serum as well as in other body fluids such as urine or tears. Such nucleic acids are involved in post-transcriptional gene regulation of cellular processes such as cell differentiation, proliferation, and apoptosis. It was also discovered that circulating nucleic acid expression levels were altered in multiple pathological conditions, forming ‘signatures’ in various diseases including diabetes, heart diseases, drug-induced liver injury and cancers. Routine biopsies from tissues are too invasive and not practical for the diagnosis and prognosis of diseases. The research direction was then focused on circulating nucleic acid biomarkers.
  • miRNAs are non-coding RNAs of 21 ⁇ 22 nucleotides long which are synthesized in the cell nucleus. miRNAs have been shown to be relatively stable in storage and therefore the degradation of miRNAs in the sample could be a potentially useful indication to reflect the degradation rate of the nucleic acids present in the sample.
  • stability-related miRNA biomarkers a panel of biomarkers can be established to provide a measurement of the stability of the nucleic acids in samples to be used for nucleic acid analysis.
  • the present invention relates to isolated sets of probes suitable for use as a quality control panel in measuring key parameters that are relevant for determining the condition of sample.
  • the isolated sets of probes may comprise the following:
  • the establishment of the above sample quality control panel using haemolysis-related, platelet- related and stability-related miRNAs allow the screening of ideal samples to be used in downstream nucleic acid analysis for diagnostics, research, and measurement.
  • the use of the panel can also be further expanded to study the biasness of different cohorts, which may improve sampling procedures and research quality.
  • the present disclosure relates to isolated sets of probes capable of detecting at least one biomarker selected from hsa-miR-1973 and hsa-miR-28-5p for use in determining the level of platelet activation and/or aggregation in a sample.
  • the isolated set of probes for use in determining the level of platelet activation and/or aggregation in a sample may further include at least one probe for detecting at least one biomarker selected from the group of hsa-miR-1290 and hsa-miR-10b-5p for use as a reference gene or a normaliser.
  • the isolated set of probes for use in determining the level of platelet activation and/or aggregation in a sample may comprise a set of probes for detecting hsa-miR-1973, hsa-miR-28-5p, hsa-miR-1290 and hsa-miR- 10b-5p.
  • the present disclosure may also relate to isolated sets of probes capable of detecting at least one biomarker selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a for use in determining the level of haemolysis in a sample.
  • the isolated set of probes for use in determining the level of haemolysis in a sample may further comprise at least one probe for detecting at least one biomarker selected from the group of hsa-miR-1290 and hsa-miR-10b-5p for use as a reference gene or a normaliser.
  • the isolated set of probes for use in determining the level of haemolysis in a sample may comprise a set of probes for detecting hsa-miR- 20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-1290 and hsa-miR-10b-5p.
  • the present disclosure may also relate to isolated sets of probes capable of detecting at least one biomarker selected from hsa-miR-143-3p and hsa-miR-618 for use in determining the level of stability of nucleic acid in a sample, optionally wherein the sample is a stored sample.
  • the isolated set of probes for use in determining the stability of nucleic acid in a sample may further comprise at least one probe for detecting at least one biomarker selected from the group of hsa-miR-1290 and hsa-miR-720 for use as a reference gene or a normaliser, optionally wherein the sample is a stored sample.
  • the isolated set of probes for use in determining the stability of nucleic acid in a sample may comprise a set of probes for detecting hsa-miR-143-3p, hsa- miR-618, hsa-miR-1290 and hsa-miR-720.
  • kits for determining the occurrence of platelet activation and/or aggregation in a sample comprising reagents (for example probes, primers, aptamers, antibodies, buffers and enzymes) for detecting the expression of at least one biomarker selected from hsa-miR-1973 and hsa-miR-28-5p.
  • reagents for example probes, primers, aptamers, antibodies, buffers and enzymes
  • Such a kit for determining the level of platelet activation and/or aggregation in a sample may further comprise reagents for detecting hsa-miR-1290 and hsa-miR- 10b-5p.
  • the kit for use in determining the level of platelet activation and/or aggregation in a sample comprises reagents for detecting hsa-miR-1973, hsa-miR-28-5p, hsa-miR- 1290 and hsa-miR-10b-5p.
  • kits for determining the level of haemolysis in a sample comprising reagents (for example probes, primers, aptamers, antibodies, buffers and enzymes) for detecting the expression of at least one biomarker selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a.
  • reagents for example probes, primers, aptamers, antibodies, buffers and enzymes
  • Such a kit for determining the level of haemolysis in a sample may further comprise reagents for detecting hsa-miR-1290 and hsa-miR-10b-5p.
  • the kit for use in determining the level of haemolysis in a sample comprises reagents for detecting hsa-miR-20b- 5p, hsa-miR-363-3p, hsa-miR-451a, hsa-miR-1290 and hsa-miR-10b-5p.
  • kits for determining the level of stability of nucleic acid in a sample comprising reagents (for example probes, primers, aptamers, antibodies, buffers and enzymes) for detecting the expression of at least one biomarker selected from the group consisting of hsa-miR-143-3p and hsa-miR-618.
  • reagents for example probes, primers, aptamers, antibodies, buffers and enzymes
  • Such a kit for determining the stability of nucleic acid in a sample may further comprise reagents for detecting hsa-miR-1290 and hsa-miR-720.
  • the kit for use in determining the stability of nucleic acid in a sample comprises reagents for detecting hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290 and hsa-miR-720.
  • the sample described herein may be a stored sample.
  • the kits as disclosed herein may further comprise instructions on how to use the reagents comprised within the kits.
  • the kits may further comprise instructions to use the reagents in methods as described herein.
  • the kits may comprise instructions to use the reagents in methods of performing quality control on a sample and/or assessing quality of a sample for nucleic acid analysis.
  • kits may further comprise instructions to use the reagents in methods of determining the level of platelet activation and/or aggregation in a sample, or in methods of determining the level of haemolysis in a sample, or in methods of determining the level of stability of nucleic acid in a sample.
  • a method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from the group consisting of hsa-miR-28-5p, hsa-miR- 1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method may comprise determining the level of two or more, three or more, four or more, five or more, six or more, or all seven biomarkers selected from the group consisting of hsa-miR-28-5p, hsa-miR-1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis involve the analysis of various aspects of a sample as described herein.
  • the quality of the sample is determined by: a) the level of platelet activation and/or aggregation in the sample, b) the level of haemolysis in the sample, and/or c) the level of stability of nucleic acid in the sample.
  • the quality of the sample is determined by a) the level of platelet activation and/or aggregation in the sample, which in turn is determined by measuring/detecting/determining the level of one or more biomarker selected from the group consisting of hsa-miR-28-5p and hsa-miR- 1973.
  • the method comprises determining the level of one of the following: hsa- miR-28-5p; or hsa-miR-1973; or hsa-miR-1973 and hsa-miR-28-5p.
  • a method of determining the level of platelet activation and/or aggregation in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-28-5p and hsa-miR-1973.
  • the method comprises determining the level of one of the following: hsa-miR- 28-5p; hsa-miR-1973; or hsa-miR-1973 and hsa-miR-28-5p.
  • the method comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-1973 and hsa-miR-28-5p. In some embodiments, the method comprises determining the level of one or two biomarker in the sample, wherein the biomarker is hsa-miR-1973; hsa-miR-28-5p; or hsa-miR-1973 and hsa-miR-28-5p.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p, such as hsa-miR-1290; hsa- miR-10b-5p; or hsa-miR-1290 and hsa-miR-10b-5p.
  • the method further comprises comparing the level of hsa-miR-1973 and/or hsa-miR-28-5p with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of platelet activation and/or aggregation in the sample, such as comparing the level of: hsa-miR-28-5p with that of hsa-miR-1290; hsa-miR-28-5p with that of hsa-miR-10b-5p; hsa-miR-28-5p with that of hsa-miR-1290 and hsa-miR-10b-5p; hsa-miR-1973 with that of hsa-miR-1290; hsa-miR-1973 with that of hsa-miR-10b-5p; hsa-miR-1973 with that of hsa-miR
  • the quality of the sample is determined by b) the level of haemolysis in the sample, which in turn is determined by measure/detecting/determining the level of one or more biomarker selected from the group consisting of hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451a.
  • the method comprises determining the level of one of the following: hsa-miR- 20b-5p; hsa-miR-363-3p; hsa-miR-451 a; hsa-miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363-3p and hsa-miR-451a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa- miR-451a.
  • a method of determining the level of haemolysis in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a.
  • the method comprises determining the level of one of the following: hsa-miR- 20b-5p; hsa-miR-363-3p; hsa-miR-451 a; hsa-miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363-3p and hsa-miR-451a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa- miR-451a.
  • Also provided herein is a method of determining the level of haemolysis in a sample the method comprises determining the level of one or more s in the sample, wherein the one or more biomarker is selected from hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a. In some embodiments, the method comprises determining the level of one, two or three biomarkers.
  • the method comprises determining the level of hsa-miR-20b-5p; hsa-miR-363-3p; hsa-miR-451 a; hsa- miR-20b-5p and hsa-miR-363-3p; hsa-miR-20b-5p and hsa-miR-451 a; hsa-miR-363-3p and hsa-miR- 451 a; or hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a in the sample.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p, such as hsa-miR-1290; hsa-miR-10b-5p; or hsa- miR-1290 and hsa-miR-10b-5p.
  • the method further comprises comparing the level of one or more of hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a with that of hsa-miR- 1290 and/or hsa-miR-10b-5p to determine the level of haemolysis in the sample, such as comparing the level of: hsa-miR-20b-5p with that of hsa-miR-1290; hsa-miR-20b-5p with that of hsa-miR-10b-5p; hsa-miR-20b-5p with that of hsa-miR-1290 and hsa-miR-10b-5p; hsa-miR-363-3p with that of hsa-miR-1290; hsa-miR-363-3p with that of hsa-miR-10b-5p;
  • the quality of the sample is determined by c) the level of stability of nucleic acid in the sample, which in turn is determined by measuring/detecting/determining the level of one or more biomarker is selected from hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of: hsa-miR-143-3p; hsa-miR-618; or hsa-miR-143-3p and hsa-miR-618.
  • a method of determining the level of stability of nucleic acid in a sample comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of: hsa-miR-143-3p; hsa-miR- 618; or hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of one or more biomarker in the sample, wherein the one or more biomarker is selected from hsa-miR-143-3p and hsa-miR-618. In some embodiments, the method comprises determining the level of hsa-miR-143-3p; hsa-miR-618; or hsa-miR-143-3p and hsa-miR-618 in the sample.
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290 and hsa-miR- 720, such as hsa-miR-1290; hsa-miR-720; or hsa-miR-1290 and hsa-miR-720.
  • the method further comprises comparing the level of hsa-miR-143-3p and/or hsa-miR- 618 with that of hsa-miR-1290 and/or hsa-miR-720 to determine the level of stability of nucleic acid in the sample, such as comparing the level of: hsa-miR-143-3p with that of hsa-miR-1290; hsa-miR-143-3p with that of hsa-miR-720; hsa-miR-143-3p with that of hsa-miR-1290 and hsa-miR-720; hsa-miR-618 with that of hsa-miR-1290; hsa-miR-618 with that of hsa-miR-720; hsa-miR-618 with that of hsa-miR-1290 and hsa-miR-12
  • the method further comprises comparing the level of two or more biomarker to determine a score for determining the level of platelet activation and/or aggregation, stability of nucleic acid or level of haemolysis in a sample.
  • the method comprises comparing the level of two or more biomarkers, wherein one of the biomarkers is a reference or normaliser biomarker.
  • the score is compared to that of a control for determining the level of platelet activation and/or aggregation, stability of nucleic acid or level of haemolysis in a sample.
  • such methods for performing quality control and/or assessing quality of a sample on a sample for nucleic acid analysis comprises detecting in the sample the level of platelet activation and/or aggregation in the sample by detecting the level of at least one biomarker selected from hsa-miR-1973 and hsa-miR-28-5p compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-10b-5p as a reference or normaliser.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for nucleic acid analysis comprises detecting in the sample the level of haemolysis in the sample by detecting the level of at least one biomarker selected from hsa-miR-20b-5p, hsa- miR-363-3p and hsa-miR-451 a compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR- 10b-5p as a reference or normaliser.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for nucleic acid analysis comprises detecting in the sample the level of stability of nucleic acid in the sample by detecting the level of at least one biomarker selected from hsa-miR-143- 3p and hsa-miR-618 compared to a control.
  • such a method may further include detecting the level of at least one biomarker selected from hsa-miR-1290 and hsa-miR-720 as a reference or normaliser.
  • the method further comprises determining the level of one or more biomarker selected from hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • the method further comprises comparing the level of hsa-miR-1973 and/or hsa-miR-28-5p with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of platelet activation and/or aggregation in the sample.
  • the method further comprises comparing the level of one or more of hsa-miR- 20b-5p, hsa-miR-363-3p and hsa-miR-451 a with that of hsa-miR-1290 and/or hsa-miR-10b-5p to determine the level of haemolysis in the sample.
  • the method further comprises comparing the level of hsa-miR-143-3p and hsa- miR-618 with that of hsa-miR-1290 and/or hsa-miR-720 to determine the level of stability of nucleic acid in the sample.
  • the method comprises determining the level of at least one biomarker in each of the following group: (a) hsa-miR-28-5p and hsa-miR-1973; (b) hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a; and (c) hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of hsa-miR-28-5p, hsa-miR-1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p and hsa-miR-618.
  • the method comprises determining the level of biomarkers hsa-miR-28-5p, hsa-miR-1973, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa- miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • such methods for performing quality control on a sample and/or assessing quality of a sample for nucleic acid analysis comprise detecting the presence of at least one of the following conditions in the sample: (a) level of platelet activation and/or aggregation; (b) level of haemolysis; and/or (c) level of stability of nucleic acid, wherein should one or more of the above conditions is identified in the sample, the person with the relevant skill in the art would be able to make the judgement to either: (a) not to proceed with nucleic acid analysis for the sample; (b) to make adjustments in the data analysis for the affected sample to adjust for the biasness of the nucleic acid profile in said sample; or (c) to undertake other corrective measures necessary to derive useful information on the nucleic acid content of the sample.
  • the present disclosure relates to methods for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis, wherein the method comprises determining in the sample the level of one or more biomarkers selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, hsa-miR-618, hsa-miR- 1290, hsa-miR-10b-5p and hsa-miR-720.
  • biomarkers selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-m
  • the method comprises determining the level of at least one biomarker in each of the following group: (a) hsa-miR-1973 and hsa-miR-28- 5p; (b) hsa-miR-20b-5p, hsa-miR-363-3p and hsa-miR-451 a; and (c) hsa-miR-143-3p and hsa-miR- 618. In some embodiments, the method comprises determining the level of at least one biomarker in each group, such as least 3, 4, 5, 6 or 7 biomarkers.
  • biomarkers listed for determining each of the conditions such as the level of platelet activation and/or aggregation, level of haemolysis and level of stability of nucleic acid
  • the use of one or any suitable number of biomarker may be sufficient for determining each condition.
  • the use of one or any suitable number of reference or normaliser biomarker for each condition may also be sufficient.
  • the method for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis comprises determining the level of one or more of the following combination of biomarkers: hsa-miR-28-5p, hsa-miR-143-3p, hsa-miR-20b-5p; hsa-miR-28-5p, hsa-miR-143-3p, hsa-miR-363-3p; hsa-miR-28-5p, hsa-miR-143-3p, hsa-miR-451a; hsa-miR-28-5p, hsa-miR-618, hsa-miR-20b-5p; hsa-miR-28-5p, hsa-miR-618, hsa-miR-363-3p; hsa-miR-28-5p,
  • the method further comprises determining the level of one or more reference or normaliser biomarker selected from hsa-miR-1290, hsa-miR-10b-5p and hsa-miR- 720.
  • the method further comprises determining the level of one, two or three biomarkers, such as hsa-miR-1290; hsa-miR-10b-5p; hsa-miR-720; hsa-miR-1290 and hsa-miR-10b- 5p; hsa-miR-1290 and hsa-miR-720; hsa-miR-10b-5p and hsa-miR-720; or hsa-miR-1290, hsa-miR- 10b-5p and hsa-miR-720.
  • biomarkers such as hsa-miR-1290; hsa-miR-10b-5p; hsa-miR-720; hsa-miR-1290 and hsa-miR-10b-5p and hsa-miR-720.
  • the method comprises determining the expression level of hsa-miR-1973, hsa- miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451a, hsa-miR-143-3p, hsa-miR-618, hsa- miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • the method further comprises comparing the level of two or more biomarkers to determine a score for determining the quality of a sample. In some embodiments, the method comprises comparing the level of two or more biomarkers, wherein one of the biomarkers is a reference or normaliser biomarker. In some embodiments, the score is compared to that of a control for determining the quality of the sample.
  • the method comprises comparing the level of two or more biomarkers to determine a score, wherein the score is compared to that of a control for determining the quality of the sample.
  • the sample is a blood sample or a non-cellular bodily fluid sample obtained from a subject.
  • the sample is a plasma and/or serum.
  • kits for use in the method as disclosed herein comprises an isolated set of probes and/or reagents capable of determining the expression level of the one or more biomarker selected from the group consisting of hsa-miR-1973, hsa-miR-28-5p, hsa- miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • kits for use in performing quality control on a sample for nucleic acid analysis comprising reagents for detecting the expression of at least one biomarker as described herein.
  • the kit comprises reagents for detecting the expression of one or more biomarker selected from the group consisting of hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363- 3p, hsa-miR-451 a, hsa-miR-143-3p and hsa-miR-618.
  • the kit further comprises reagents for detecting the expression of at least one biomarker selected from the group consisting of hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720.
  • reagents may include probes, primers, aptamers, antibodies, buffers and enzymes.
  • kits for use in any of the methods comprises an isolated set of probes and/or reagents capable of determining the level of the one or more biomarkers of the preceding claims.
  • Compositions for use in the methods disclosed herein include, but are not limited to, probes, antibodies, affibodies, nucleic acids, and/or aptamers. Preferred compositions can detect the level of expression (e.g., miRNA) of a panel of biomarkers from a biological sample.
  • kits can include all components necessary or sufficient for assays, which can include, but is not limited to, detection reagents (e.g., probes), buffers, control reagents (e.g., positive and negative controls), amplification reagents, solid supports, labels, instruction manuals, etc.
  • the kit comprises a set of probes for the panel of biomarkers and a solid support to immobilize the set of probes.
  • the kit comprises a set of probes for the panel of biomarkers, a solid support, and reagents for processing the sample to be tested (e.g., reagents to isolate the protein or nucleic acids from the sample).
  • kits as disclosed herein may further comprise instructions for the reagents to be used for performing quality control on a sample and/or assessing quality of a sample for use in nucleic acid analysis. Therefore, the kits may further comprise instructions for using the reagents to assess the presence of at least one of the following conditions in the sample: (a) level of platelet activation and/or aggregation; (b) level of haemolysis; and/or (c) level of stability of nucleic acid.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-1973 and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-28-5p, hsa- miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-28-5p and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-20b-5p and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR-28-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-363-3p and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-451 a, hsa-miR-143-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-451 a and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-1 3-3p, and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-143-3p and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR-28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a and hsa-miR-618.
  • the method of assessing the quality of a sample for use in a nucleic acid analysis comprises determining the level of hsa-miR-618 and at least one, at least two, at least three, at least four, at least five, at least six biomarkers selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a and hsa-miR-143-3p.
  • a biological sample e.g., blood
  • methods for collecting a biological sample comprises: (a) collecting an initial first volume of biological sample; and subsequently, (b) collecting a second volume of the biological sample in a separate container for use in nucleic acid analysis.
  • the initial first volume and second volume of biological samples are not to be combined for nucleic acid analysis and preferentially, be collected in discrete containers.
  • the containers may be, but not limited to, tubes, flasks, bags and compartments within containers.
  • the initial first volume of the biological sample may be discarded and the volume to be discarded may be at least 1 millilitre (mL).
  • the initial first volume of sample to be discarded may be approximately 1 -2mL.
  • such methods of sample collection may reduce haemolysis and/or contamination (e.g., from skin cell, microorganisms, etc) that may alter the nucleic acid content of the sample.
  • the collection of the initial first volume to be discarded may comprise more than one sample draw, provided that the objective of each sample draw for the initial first volume is performed with the intent of obtaining a higher quality subsequent sample for nucleic acid analysis (i.e. in the second volume).
  • “discarding” the first sample shall refer to the non-use of said initial sample for nucleic acid analysis.
  • such initial samples may be used for purposes other than nucleic acid analysis, particularly forthe analysis of circulating nucleic acids (e.g, miRNAs).
  • Also disclosed herein are methods of collecting a sample for nucleic acid analysis the method may comprise (a) collecting an initial first volume of the sample; and (b) further collecting a second volume of the sample in a separate container for use in nucleic acid analysis.
  • Also disclosed herein are methods of processing a sample for nucleic acid analysis the method comprises: (a) subjecting the sample to a first centrifugation at a speed of from 1 ,000g to 5,000g for a first period of time to provide a first supernatant; and (b) subjecting the supernatant obtained from (a) to a second centrifugation at a speed of from 1 ,500g to 5,000g for a second period of time to provide a second supernatant.
  • the first centrifugation may be carried out at a speed of from 1 ,000g to 5,000g, such as from 1 ,000g to 4,000g, such as from 1 ,000g to 2,000g, such as 1 ,500g.
  • the second centrifugation would be carried out at a speed of from 1 ,500g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 2,500g.
  • the centrifugation time for the first and second centrifugation may be independently selected from 1 min to 30 min, such as from 5 min to 20 min, such as 15 min.
  • the methods of processing a biological sample for nucleic acid analysis may include cryopreservation of the first supernatant after the first centrifugation, with the second centrifugation being carried out following the thawing of the cryopreserved first supernatant (i.e., after freeze/thaw).
  • Also disclosed herein are methods of collecting and processing a biological sample for nucleic acid analysis comprising: (a) collecting an initial first volume of the biological sample; (b) further collecting a second volume of the biological sample in a separate container; (c) subjecting the second volume of the biological sample to a first centrifugation at a speed of from 1 ,000g to 5,000g for a first period of time to provide a first supernatant; and (d) subjecting the first supernatant obtained from (c) to a second centrifugation at a speed of from 1 ,500g to 5,000g for a second period of time to provide a second supernatant.
  • the second centrifugation may be performed after at least one freeze/thaw of the sample after the first centrifugation.
  • the first and second period of time may be independently selected from 1 min to 30 min, such as from 5 min to 20 min, such as 15 min.
  • the method may further comprise: determining in the second supernatant the expression level of one or more miRNAs selected from hsa-miR-1973, hsa-miR-28- 5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, hsa-miR-618, hsa-miR-1290, hsa-miR-10b-5p and hsa-miR-720; and optionally determining in the second supernatant the expression level of one or more miRNAs selected from hsa-miR-1290, hsa-miR-10b-5p and hsa-miR- 720.
  • the method of collecting and processing a biological sample for nucleic acid comprising: (a) collecting an initial first volume of biological sample; (b) collecting a second volume of biological sample in a separate container; (c) subjecting the second volume of the biological sample to a first centrifugation to provide a first supernatant; and (d) subjecting the first supernatant to a second centrifugation to provide a second supernatant.
  • the first centrifugation may be carried out at a speed of from 1 ,000g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 1 ,500g.
  • the second centrifugation may be carried out at a speed of 1 ,500g to 5,000g, such as from 1 ,500g to 4,000g, such as from 1 ,500g to 3,000g, such as 2,500g.
  • the centrifugation time for the first and second centrifugation may be independently selected from 1 min to 30 min, such as from 5 min to 20 min, such as 15 min.
  • the first supernatant may be cryopreserved after the first centrifugation, with the second centrifugation performed following the thawing of the cryopreserved first supernatant.
  • the method may further comprise determining in the second supernatant, the level of at least one biomarker selected from hsa-miR-1973, hsa-miR- 28-5p, hsa-miR-20b-5p, hsa-miR-363-3p, hsa-miR-451 a, hsa-miR-143-3p, hsa-miR-618, hsa-miR- 1290, hsa-miR-10b-5p and hsa-miR-720.
  • the biomarker may be microRNA (miRNA).
  • miRNA microRNA
  • miRNA miRNA
  • miRNA RNA
  • miR RNA analogue
  • MiRNAs are encoded in genes distinct from the mRNAs whose expression they control.
  • miRNA or “microRNA” refers to single-stranded RNA molecules of at least 10 nucleotides and of not more than 35 nucleotides covalently linked together.
  • the polynucleotides are molecules of 10 to 33 nucleotides in length, or of 15 to 30 nucleotides in length, or of 17 to 27 nucleotides in length, or of 18 to 26 nucleotides in length, i.e., 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 28, 29, 30, 31 , 32, 33, 34, or 35 nucleotides in length, not including, optionally, labels and/or elongated sequences (e.g., biotin stretches).
  • the sequences of the miRNAs as described herein are provided in Table 1.
  • miRNA is a type of polynucleotide that has sequences comprising letters such as “AUGC.” It will be understood that the nucleotides are in 5’->3’ order from left to right and that “A” denotes adenosine, “U” denotes uracil, “G” denotes guanosine, and “C” denotes cytosine, unless otherwise noted.
  • the letters A, U, G, and C can be used to refer to the base themselves, to the nucleosides, or to the nucleotides comprising the bases, as is standard in the art.
  • RNA-, and protein-based detection methods that either directly or indirectly detect the biomarkers described herein.
  • the present invention also provides compositions, reagents, and kits for such diagnostic purposes.
  • the diagnostic methods described herein may be qualitative or quantitative. Quantitative diagnostic methods may be used, for example, to compare a detected biomarker level to a cut-off or threshold level. Where applicable, qualitative or quantitative diagnostic methods can also include amplification of target, signal, or intermediary.
  • the one or more biomarkers are detected/determined by methods selected from sequencing, nucleic acid hybridisation, microarray and nucleic acid amplification such as a reverse transcription-quantitative polymerase chain reaction (RT-qPCR), reverse transcription-polymerase chain reaction (RT-PCR), quantitative polymerase chain reaction (qPCR), a locked nucleic acid PCR, a clustered regularly interspaced short palindromic repeat (CRISPR)-based assay, or isothermal amplification assay.
  • RT-qPCR reverse transcription-quantitative polymerase chain reaction
  • RT-PCR reverse transcription-polymerase chain reaction
  • qPCR quantitative polymerase chain reaction
  • CRISPR clustered regularly interspaced short palindromic repeat
  • biomarkers can be combined to form a biomarker panel and a predictive score may be generated, for example using a linear model. From such a score, the cut-off threshold to determine if the quality of the sample is acceptable for further analysis may be derived. An example would be to calculate such a risk score using logistic regression, a form of linear model.
  • the prediction score may also be calculated using a classification algorithm selected from the group comprising support vector machine algorithm, logistic regression algorithm, multinomial logistic regression algorithm, Fisher’s linear discriminant algorithm, quadratic classifier algorithm, perceptron algorithm, k-nearest neighbours algorithm, artificial neural network algorithm, random forests algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method combining multiple learning algorithms.
  • a classification algorithm selected from the group comprising support vector machine algorithm, logistic regression algorithm, multinomial logistic regression algorithm, Fisher’s linear discriminant algorithm, quadratic classifier algorithm, perceptron algorithm, k-nearest neighbours algorithm, artificial neural network algorithm, random forests algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method combining multiple learning algorithms.
  • the challenge in the field pertains to identifying relevant biomarkers, such as the relevant stability related biomarkers, that could be reliably applied to identify a sample in which the nucleic acid has degraded and
  • the calculation of a prediction score can be, but are not limited to, support vector machine algorithm, logistic regression algorithm, multinomial logistic regression algorithm, Fisher’s linear discriminant algorithm, quadratic classifier algorithm, perceptron algorithm, k-nearest neighbours algorithm, artificial neural network algorithm, random forests algorithm, decision tree algorithm, naive Bayes algorithm, adaptive Bayes network algorithm, and ensemble learning method combining multiple learning algorithms.
  • the calculation of the prediction score may be calculated using linear models and support vector machine algorithms.
  • range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosed ranges. Accordingly, the description of a range should be considered to have specifically disclosed all the possible sub-ranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed sub-ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1 , 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.
  • Platelet-related miRNA as factor in miRNA in non-l To examine the changes of miRNA expression level in blood samples under different processing methods, serum samples with clotting duration of 30 min, 60 min and 90 min (serum 30, serum 60 and serum 90, respectively), plasma and Plate-let-poor-plasma (PPP) were examined. PPP is plasma samples which went through double-spin to eliminate platelets. Blood from 10 healthy subjects were collected for this study. Human Haemoglobin ELISA was used to measure the level of cell-free haemoglobin in samples as an indicator of haemolysis. The haemoglobin concentration remained low and did not vary in the serum after different clotting duration. Both plasma and PPP showed higher haemoglobin concentration than the serum samples, but the results were similar to each other (FIG.
  • TXB2 Thromboxane B2
  • ELISA was used to measure the level of TXB2 in serum as an indicator of platelet activation and aggregation.
  • the TXB2 level increased when serum clotting duration increased, (e.g. the TXB2 level correlated to serum clotting duration up to 90 mins), indicating that more platelets were activated in longer time.
  • Both plasma and PPP showed low TXB2 concentration as platelet aggregation and activation did not take place (FIG.
  • PCA principal component analysis
  • the miRNA expressions in serum 30, serum 60 and serum 90 were profiled and analysed. Linear regression was performed to find correlation between miRNAs and platelet activation from a short to long clotting duration.
  • the miRNAs that had P value ⁇ 0.05 were identified as biomarkers which are strongly correlated with platelet activation.
  • two miRNAs, hsa-miR-1973 and hsa-miR- 28-5p, were chosen as platelet-related markers due to the strong correlation with platelet activation and reasonable expression in serum. (FIG. 3A, B).
  • PPP platelet-poor plasma
  • TBX2 thromboxane B2.
  • Platelet-related and RBC-related miRNAs can be used to evaluate the quality of processed plasma samples. Expression of the markers was normalized against reference genes during data analysis to generate a haemolysis score and a platelet score. The geometric mean was used to calculate the aggregated value for two platelet-related miRNAs, three RBC-related miRNAs and the two reference genes. To be more specific, the haemolysis score was calculated by normalizing the expression of RBC-related miRNAs against the reference gene (CqRBc - Cq nO rm), whereas the platelet score was calculated by normalizing the expression of platelet-related miRNA against the reference gene (Cq P iateiet- Cq n orm). Higher scores indicated that samples had lesser miRNA contamination from RBCs or platelets.
  • the effects of the stepwise processing of PPP were calculated using the haemoglobin level, haemolysis score and platelet score.
  • Haemolysis score was calculated by normalizing the expression of RBC-related miRNAs against reference gene (CqRBc-Cq n orm). Platelet score was calculated by normalising the expression of platelet-related miRNA against reference genes (Cq P iate-Cqnorm). Higher scores indicate samples with less miRNA contamination from red blood cells or platelets. There was no significant difference in haemolysis score for plasma collected in different tube sizes (FIG. 8B). Similarly, there was no significant difference in platelet score for plasma collected in different tube sizes (FIG. 8C).
  • the haemolysis score indicated a slight decrease in lower first spin (Con5 and Con6), although this was not significant (FIG. 9A). This indicates a higher first spin is slightly more effective in removing red blood cells.
  • the second spin speed did not affect the haemolysis score (Coni to Con4).
  • the platelet score was more affected by the second spin speed (FIG. 9B). A slight upward trend was observed when the second spin speed increased, regardless of first spin speed.
  • Con4 which had the highest second spin speed at 5000 g showed the lowest platelet score, with a statistically significant difference compared with Coni . This trend was deduced to be due to the lysis of platelets under a high spin speed.
  • Con2 or Con3 (first spin at 1500 g, 15 min and second spin at 2000 g to 3000 g, 15 min) could be the ideal blood processing protocol for miRNA assays from the aspect of minimally confounding haemolysis and platelet factors. Therefore, a standardized dual-spin protocol of 1500 g for 15 min as first spin and 2500 g for 15 min as second spin, both at room temperature, was established for the processing of PPP.
  • Coni represents single spin without going a freeze-thaw cycle, which served as the baseline in this study;
  • Con2 represents the dual-spin protocol that was developed in the section “Centrifugation Protocol” above;
  • Con3 represents the single-spin protocol that had undergone one freeze-thaw cycle, whilst Con4 represents the dual-spin protocol with the second spin performed only after one freezethaw cycle.
  • Example 3 Stability biomarkers for sample storage
  • a stability study was conducted to assess the integrity of miRNA in PPP and serum samples after storage at various temperature. This study is important for evaluating the reliability of biomarker discovery in biobank samples. Blood was drawn from four healthy volunteers and processed into PPP and serum. All samples were kept at 25 °C, 4 °C, -20 °C and -80 °C for various duration. RNA was extracted at each timepoint with spike-ins of synthetic RNA functioning as the workflow normalization. The miRNA profiling was performed at the end of the study.
  • hsa-miR-143-3p A similar trend was seen in PPP profile for hsa-miR-143-3p (FIG. 14B).
  • Similar trend for these two miRNAs was seen in the PPP samples.
  • These miRNAs were chosen as stability or reference markers not only because of their abundant expression, but also the low correlation with both haemolysis and platelets. This was to ensure that the use of stability markers and references had a minimal confounding effect as a result of the presence of platelet and haemolysis.
  • the result of the regression analysis implied that the decay of miRNAs can be induced by both storage time and temperature.
  • a correlation analysis was performed using the regression coefficient and expression on miRNAs.
  • the correlation analysis was extended to the percentage of GO and length of miRNA.
  • the result indicates that the degradation of miRNA is also correlated with the percentage of GC of the sequence and the length of miRNA in both serum and plasma (see R and R value in FIG. 15).
  • Initial analysis showed that the regression coefficient has no correlation with the GC content of the sequence and the length of miRNA, but subsequent analysis of the same data suggested otherwise.
  • the application of dual-spin can be practically implemented in a clinical setting to obtain a high-quality PPP sample for miRNA analysis.
  • the schematic workflow of recommended blood processing is shown in FIG. 16.
  • a post freeze-thaw spin of stored plasma could partially remove confounding platelets and other cell debris.
  • whole blood samples can be stored at room temperature for up to 7 hours for the least haemolysis- and platelet-confounding impacts. This finding is consistent with previous studies that reported that on-ice storage of whole blood causes changes in plasma quality and damage to platelet membrane integrity.
  • the miRNA in serum or plasma is stable for up to 1 year if stored at -20 °C or -80 °C based on the real-time stability studies.
  • the results indicate that miRNA decays in two distinct phases.
  • the first phase occurs a few days after the blood draw, and the second phase occurs after a long period of storage. It is possible that previous publications are observing the second phase in stored samples.
  • the result indicates that degradation is correlated with the abundance, percentage of GC, and length of miRNA in both serum and PPP samples.
  • sample quality control panel using RBC-related, platelet-related and stability- related miRNAs will allow the screening of ideal samples to be used in downstream miRNA research and measurement.
  • the impact of haemolysis- and platelet-confounding factors is associated with the biological signal. If the disease of interest generates strong changes of related miRNA into the circulating, it is likely that the signal can tolerate higher noise that comes from the confounding factor. However, if the disease signal is subtle, the sample QC must be stringent to prevent the noise from overwhelming the disease signal. It is possible for the user laboratories to define an acceptable range of this panel based on their application. Users can follow the Clinical and Laboratory Standard Institute guideline EP07-A2 to generate samples of different QC scores using platelet or RBC spikein.
  • the cutoff can then be identified at which point miRNA of interest shows significant changes compared with the control.
  • the absolute score not only the absolute score but also the score difference between groups matters.
  • the imbalance of the QC score will have to be taken into consideration in statistical analysis or machine learning. Therefore, the use of the panel can be further expanded to study the degree of bias of different cohorts, which may improve research quality.
  • Standardization of preanalytical variables represents a critical step in the clinical implementation as well as research studies. Although there are blood collection tubes with preservative for the stabilization of cell-free nucleic acid, they are often costly. In addition, different blood collection systems may also alter the analytical output. Therefore, the development of more preanalytical solutions will benefit the development of miRNA panels as diagnostic and research tools.
  • the supernatants were transferred to new microtubes which were subsequently stored at -80 °C until further analysis.
  • the red blood cell pellets were collected into microtube for further experiments.
  • PPP platelet-poor-plasma
  • the spun plasma was transferred into a 15 mL tube which were centrifuged second time at 2500 g for 15 min to remove platelets.
  • the top 2/3 of the supernatants were aliquoted into microtubes and stored at -80 °C.
  • serum separator tube Becton Dickinson, Madison, UK, catalogue no. 367814
  • the blood tubes were centrifuged at 1500 g for 15 min.
  • the supernatants were transferred into microtubes and stored at -80 °C until further analysis.
  • one of the blood tubes was centrifuged at 1000 g for 15 min and the other two were centrifuged at 1500 g for 15 min.
  • the supernatant was aspirated from each tube and dispensed into 15 mL tubes for the second spin.
  • Various centrifugation conditions (1500 g for 20 min, 2000 g for 15 min, 3000 g for 15 min, and 5000 g for 5 min) were used in the second spin.
  • EDTA tubes were centrifuged at 1500 g for 15 min at room temperature. Afterward, plasma was transferred into 15 mL tube for the second spin at 2500 g for 15 min at room temperature. The top two-third of the supernatant from the second tube were considered to be PPP and transferred into cryotubes for use.
  • K2-EDTA tubes were processed using 1500 g centrifugation speed for 15 min.
  • the supernatant from each tube was dispensed into four different tubes, one of them underwent RNA extraction immediately, one of them was centrifuged again at 2500 g for 15 min before RNA extraction, and two of the tubes were stored at -80 °C and subjected to a freeze-thaw cycle. After thawing, only one of the freeze-thawed tubes went through a second centrifugation at 2500 g for 15 min. Both tubes underwent RNA extraction after a freeze-thaw cycle.
  • blood from four healthy, non-fasting male or female subjects between 25 and 60 years of age was drawn into discard tubes, for up to 1 mL, and subsequently switched to serum tubes and K2-EDTA tubes.
  • the serum processing was performed by allowing 60 minutes for clotting before centrifugation at 1500 g for 15 min.
  • the storage conditions of the serum samples were 25 °C for 3 days; 4 °C for 3, 7 and 30 days; -20 °C for 3, 7, 30, 90, 180 and 360 days; -80 °C for 3, 7, 30, 90, 180 and 360 days.
  • Day 0 represented freshly processed serum.
  • the PPP processing was done using the dual-spin protocol.
  • the storage conditions of the PPP samples were 25 °C for 3 and 7 days; 4 °C for 3, 7, 14 and 30 days; -20 °C for 3, 7, 14, 30, 60, 90, 180, 270 and 360 days; -80 °C for 3, 7, 14, 30, 60, 90, 180, 270 and 360 days.
  • Day 0 represented freshly processed PPP.
  • the tubes and processing conditions were randomized and did not follow collection order.
  • Red blood cell pellets were washed with Phosphate Buffered Saline for two times.
  • the ACK Lysis buffer (Gibco Biosciences, Dublin, Ireland, catalogue no. A1049201) was added to the pellets at an equivalent volume. The mixture was gently resuspended and swirled for 30 seconds. The mixture was then centrifuged for 10 min at 2000 x g, and the supernatant containing the red blood cell lysate was collected. The lysed red blood cells were spiked into PPP to generate contrived samples with abundant haemolysis-related miRNA.
  • Haemolysis was assessed by quantification of cell-free haemoglobin. Levels of cell-free haemoglobin in the plasma or serum were measured by Human Haemoglobin ELISA kit (Abeam, Cambridge, MA) following protocol from the product insert. Platelet activation was assessed by the quantification of Thromboxane B2 (TXB2) by ELISA (R&D Systems, Minneapolis, MN) according to manufacturer’s protocol. The TXB2 ELISA is specific to TXB2 in cell culture supernatant, serum, plasma, and urine, with a sensitivity of 0.31 ng/mL.
  • RNAs were isolated from 200 pL of serum or plasma using Maxwell RSC miRNA Plasma and Serum Kit on Promega Maxwell RSC 48 Instrument (Promega, Wisconsin, USA) according to the manufacturer’s protocol. Three spike-ins of synthetic short RNAs with distinct sequences from endogenous human miRNAs were added to the lysis buffer as controls to normalize workflow variations. The resulting miRNA was eluted using 50 pL of nuclease free water. miRNA profiling
  • the miRNA profiling was performed following an established protocol in MiRXES Lab (Zou R, et al., Cancers (Basel) 2021 , 13:1-12). A total of 356 miRNAs were profiled using the multiplexed RT-qPCR platform developed in MiRXES Lab Pte. Ltd. Isolated miRNAs underwent reverse transcription using an in-house reverse transcription system and modified stem-loop RT primer pools (MiRXES, Singapore) on a Veriti Thermal Cycler (Applied Biosystem, Waltham, MA, USA) according to manufacturer’s instructions.
  • RNA-specific qPCR assay a miRNA-specific qPCR assay and ID3EAL miRNA qPCR Master Mix according to the manufacturer’s instruction (MiRXES, Singapore).
  • the qPCR reaction for each sample was performed with technical duplicates on the Quantstudio 5 Real-Time PCR System (Applied Biosystem, Waltham, MA, USA).
  • Raw threshold cycle (Cq) values were calculated using the QuantStudio Design and Analysis software 1.4.3 with automatic baseline setting and a threshold of 0.4.
  • miRNA profiling absolute expression of each miRNA (number of copies present) was calculated by interpolation of sample Cq values with synthetic miRNA standard curves after correcting for variations in RT-qPCR efficiency with spike-ins. Any miRNA with Cq number greater than that of the no template controls (NTCs) were deemed undetectable and removed from analysis. The data underwent normalization with spike-ins to exclude variation during RNA isolation and RT-qPCR.
  • the miRNAs included in the panel were hsa-miR-1973 and hsa-miR-28-5p as platelet-related biomarkers; hsa-miR-20b-5p, hsa-miR-363-3p, and hsa-miR-451a as RBC-related biomarkers; and hsa-miR-1290 and hsa-miR-10b-5p as reference marker for both RBC-related and platelet-related biomarkers.
  • RNA was reverse transcribed using ID3EAL cDNA synthesis reagents (MiRXES) with a modified stem-loop reverse transcription primer pool assembled for the panel.
  • ID3EAL miRNA reverse transcription buffer ID3EAL reverse transcriptase
  • reverse transcription primer pool assembled for the panel.
  • a total of 5 pL of extracted RNA was mixed with ID3EAL miRNA reverse transcription buffer, ID3EAL reverse transcriptase, and reverse transcription primer pool in a total reaction volume of 15 pL.
  • the reaction mixture was incubated at 42 °C for 30 minutes, followed by 95 °C for 5 minutes to inactivate the reverse transcriptase on a C1000 Touch Thermal Cycler (Bio-Rad).
  • PCR amplification was performed in a total reaction volume of 15 pL containing cDNA, 1 x ID3EAL miRNA qPCR master mix, 1 x ID3EAL miRNA qPCR primers (MiRXES), topped up with nuclease-free water, qPCR amplification and detection were performed on QuantStudio 5 Real-Time PCR System (Thermo Fisher Scientific) with the following cycling conditions: 95 °C for 10 minutes, 40 °C for 5 minutes, followed by 40 cycles of 95 °C for 10 seconds and 60 °C for 30 seconds (optical reading).
  • Raw cycle threshold (Cq) values were calculated using QuantStudio Design and Analysis software version 1.5 and a threshold of 0.4. Cq values was used for the interpretation of the results.
  • miRNA profiling all the expression levels were presented in Iog2 copy numbers per millilitre of samples (Log2 copies/mL). The miRNA profile was obtained by normalizing individual miRNAs with their overall expression in all samples (Mestdagh P, et al., Genome Biol. 2009, 10:R64). The miRNAs underwent Z-score standardization before principal component analysis (PCA) was performed. Statistical analysis was performed using MATLAB software version R2019b (MathWorks Inc., Natick, MA).
  • a linear regression model was used to investigate the correlation among miRNA expression, haemolysis, platelets, stability and storage. To examine if platelet-related miRNA is a major confounding factor, linear regression was performed between expression level of detectable miRNA and TXB2 level in serum samples. To identify platelet-related miRNA, linear regression was performed between serum clotting duration and expression level of all detectable miRNAs.
  • Those miRNAs with p value ⁇ 0.05 in the regression analysis were inferred as having high correlation and identified as potential biomarkers.
  • linear regression was performed between duration (days) at 4 °C and level of expression of all detectable miRNAs. All linear regression was performed using MATLAB R2019b. Correlation analysis was performed using GraphPad Prism software version 9.2.0 (GraphPad Software Inc., San Diego, CA).
  • the RBC score and platelet score were calculated using ACq (average Cq of biomarkers minus average Cq of reference). Higher scores indicate samples with less haemolysis or platelet content.
  • One-way ANOVA was performed to determine if there is significant difference between groups.
  • sample size calculation was performed using MATLAB R2019b with 80% power.
  • One-way analysis of variance or paired t-test was performed using GraphPad Prism 9.2.0 to determine whether there was a significant difference between groups.

Abstract

Des compositions et des procédés d'application de celles-ci sont divulgués pour une utilisation dans le flux de travail préanalytique pour l'évaluation d'acides nucléiques dans des échantillons biologiques ainsi que des biomarqueurs et des réactifs applicables pour le contrôle de qualité du résultat d'un tel flux de travail.
PCT/SG2023/050671 2022-10-04 2023-10-04 Compositions et procédés d'évaluation d'acides nucléiques dans un échantillon biologique WO2024076307A1 (fr)

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WO2016177776A1 (fr) * 2015-05-04 2016-11-10 Academisch Medisch Centrum Biomarqueurs pour la détection de l'insensibilité à l'aspirine

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