WO2020181752A1 - 肝细胞癌早筛试剂盒及其制备方法和用途 - Google Patents

肝细胞癌早筛试剂盒及其制备方法和用途 Download PDF

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WO2020181752A1
WO2020181752A1 PCT/CN2019/106064 CN2019106064W WO2020181752A1 WO 2020181752 A1 WO2020181752 A1 WO 2020181752A1 CN 2019106064 W CN2019106064 W CN 2019106064W WO 2020181752 A1 WO2020181752 A1 WO 2020181752A1
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liver cancer
gene
kit
screening
cfdna
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PCT/CN2019/106064
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English (en)
French (fr)
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焦宇辰
曲春枫
王宇婷
王沛
陈坤
宋欠欠
刘慧�
王思振
阎海
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中国医学科学院肿瘤医院
北京泛生子基因科技有限公司
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Priority to EP19918650.3A priority Critical patent/EP3940086A4/en
Priority to KR1020217028609A priority patent/KR20210133232A/ko
Priority to JP2021547820A priority patent/JP7558181B2/ja
Priority to US17/438,050 priority patent/US20220145399A1/en
Publication of WO2020181752A1 publication Critical patent/WO2020181752A1/zh

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    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
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    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/60—Complex ways of combining multiple protein biomarkers for diagnosis

Definitions

  • the present invention belongs to the medical field, and relates to a kit for early screening of hepatocellular carcinoma, and more specifically to a kit for early screening of hepatocellular carcinoma of AFP-negative subjects, and a preparation method and application thereof.
  • HCC hepatocellular carcinoma
  • iCCA intrahepatic cholangiocarcinoma
  • HCC screening has been carried out in multiple cohorts. It is recommended that individuals with liver cirrhosis and individuals with hepatitis B virus surface antigen (HBsAg) positive should be monitored for HCC every 6 months, including ultrasound. (US) and serum alpha-fetoprotein (AFP) test (Omata M, et al. (2017), ibid.).
  • US serum alpha-fetoprotein
  • AFP serum alpha-fetoprotein
  • liver cirrhosis may also have driver mutations that are common in HCC. Analysis of hepatitis, cirrhosis, and non-cancerous liver nodules may be necessary to draw a baseline to accurately identify HCC through imaging or histological clinical verification.
  • liver damage include infection (such as hepatitis B virus infection), obesity, alcoholism, aflatoxin exposure, dyslipidemia, etc., and patients with liver disease are at higher risk of liver cancer.
  • Alpha-fetoprotein (AFP), prothrombin (DCP) and squamous cell carcinoma antigen (SCCA) are protein markers of liver cancer. Studies have shown that the combined measurement of AFP and DCP can improve the sensitivity of predicting liver cancer and effectively distinguish early liver cancer from decompensated liver cirrhosis. However, in many early liver cancers, AFP, DCP and SCCA test results are negative.
  • cfDNA Cellfree DNA
  • HCC Screening Hepatocellular Carcinoma Screening
  • Validation results show that this method can distinguish HCC individuals from non-HCC individuals robustly, with a sensitivity of 85% and a specificity of 93%.
  • the inventor further conducted a prospective study and applied this assay to 331 individuals with normal liver ultrasound examination and serum AFP levels. 24 positive cases were identified, and 4 cases were confirmed to develop HCC after 6-8 months of clinical follow-up. During the follow-up in the same time frame, 307 test-negative individuals were not diagnosed with HCC cases. The assay showed 100% sensitivity, 94% specificity and 17% positive predictive value in the validation set.
  • the kit of the present invention containing specific gene markers and protein markers has been proved to be effective for early HCC screening in non-specific populations, so it can be used for HCC early screening of non-specific populations, more preferably for HCC of AFP-negative subjects Early screening.
  • kits of the present invention are used for prospective early prediction of HCC.
  • Each of the 4 cases of HCC is early ( ⁇ 3cm) at the time of diagnosis, which provides a good basis for subsequent treatment.
  • the inventor’s research evidence shows that the combined detection of cfDNA changes and protein markers is a feasible method to identify early HCC from asymptomatic community groups with unknown HCC status.
  • the present invention provides a kit for early screening of hepatocellular carcinoma, which includes a gene marker detection agent and a protein marker detection agent.
  • the kit may further include a data processing system for converting the information of gene markers and/or protein markers into the hepatocellular carcinoma screening score of the test subject, according to the test subject
  • the screening score of the patient’s hepatocellular carcinoma predicts whether the candidate is a liver cancer patient.
  • the present invention provides a method for early screening of hepatocellular carcinoma, which comprises:
  • the hepatocellular carcinoma screening score and threshold are obtained through a liver cancer prediction model;
  • the method for constructing the liver cancer prediction model includes:
  • the training set is composed of a number of liver cancer patients and a number of high-risk liver cancer patients;
  • the sensitivity and specificity ROC curve of the penalty logistic regression model is obtained. According to the ROC curve, the cut-off value is determined, and this cut-off value is used as the threshold to distinguish liver cancer patients from those at high risk of liver cancer.
  • the present invention provides the use of a gene marker detection agent and a protein marker detection agent for early screening of hepatocellular carcinoma.
  • the present invention provides the use of a gene marker detection agent and a protein marker detection agent in preparing a kit for early screening of hepatocellular carcinoma.
  • the purpose of the present invention is to perform early screening for liver cancer.
  • the present invention first protects an early screening kit for liver cancer, which may include detection reagents for liver cancer mutation genes, DCP detection reagents and AFP detection reagents.
  • the "reagent for detecting liver cancer mutation genes” can be used to detect the mutation type and/or mutation reads and/or gene copy number variation of liver cancer mutation genes in cfDNA.
  • the "mutant gene of liver cancer” may be TP53 gene and/or TERT gene and/or AXIN1 gene and/or CTNNB1 gene.
  • the DCP detection reagent can be used to detect the content of DCP in plasma.
  • the AFP detection reagent can be used to detect the AFP content in plasma.
  • the kit may also include detection reagents and/or cfDNA detection reagents for whether HBV is integrated with genes.
  • the "reagent for detecting whether HBV is integrated with genes” can be used to detect whether there is an integration site between HBV sequence and human genome in cfDNA.
  • the "cfDNA detection reagent" can be used to detect the cfDNA concentration and/or the percentage of the cfDNA content of different insert lengths in the cfDNA.
  • kits may also include a data processing system; the data processing system is used to compare the subject’s liver cancer gene mutation information (ie, information on 11 gene mutation characteristics), DCP content (DCP content in plasma) , AFP content (AFP content in plasma), whether HBV is integrated with genes, cfDNA information and clinical information are converted into the test subject’s hepatocellular carcinoma screening score (ie HCCscreen score), according to the test subject’s The hepatocellular carcinoma screening score predicts whether the test subject is a liver cancer patient.
  • liver cancer gene mutation information ie, information on 11 gene mutation characteristics
  • DCP content DCP content in plasma
  • AFP content AFP content in plasma
  • HBV hepatocellular carcinoma screening score
  • HCCscreen score hepatocellular carcinoma screening score
  • the present invention also protects the application of detection reagents, DCP detection reagents, AFP detection reagents, whether HBV is integrated with genes, and cfDNA detection reagents for any one of the aforementioned liver cancer mutation genes, which can be at least one of A1)-A4) Species:
  • A1) Predict whether the test subject is a liver cancer patient
  • A2) Prepare a kit for predicting whether the test subject is a liver cancer patient
  • the present invention also protects the application of detection reagents, DCP detection reagents, AFP detection reagents, whether HBV is integrated with genes, cfDNA detection reagents, and data processing systems for any of the aforementioned liver cancer mutant genes, which can be A1)-A4) At least one of:
  • A1) Predict whether the test subject is a liver cancer patient
  • A2) Prepare a kit for predicting whether the test subject is a liver cancer patient
  • the present invention also protects the age of the test subject, the sex of the test subject, the DCP content in the plasma of the test subject, the AFP content in the plasma of the test subject, and the "mutation type, mutation reads, and gene copy of the liver cancer mutation gene in the cfDNA of the test subject"
  • the number variation, whether HBV is integrated with the gene, cfDNA concentration, the percentage of cfDNA content of different insert lengths", as the application of markers, can be at least one of A1)-A4):
  • A1) Predict whether the test subject is a liver cancer patient
  • A2) Prepare a kit for predicting whether the test subject is a liver cancer patient
  • the present invention also protects the method for predicting liver cancer, which may include the following steps: detecting the DCP content and AFP content in the plasma of the test subject; detecting the mutation type, mutation reads, gene copy number variation, and whether HBV is compatible with the liver cancer mutation gene in the cfDNA of the test subject The percentage of gene integration, cfDNA concentration and cfDNA content of different insert lengths; record the age and gender of the test subject; convert the information of the test subject into hepatocellular carcinoma screening score (ie HCCscreen score), according to liver The cell cancer screening score predicts whether the test subject is a liver cancer patient.
  • hepatocellular carcinoma screening score ie HCCscreen score
  • the "predicting whether the test subject is a liver cancer patient based on the hepatocellular carcinoma screening score” includes determining the diagnostic threshold through the operating characteristic curve (ROC curve), and comparing the hepatocellular carcinoma screening score of the test subject with the size of the diagnostic threshold , Complete the liver cancer prediction of the test subject.
  • ROC curve operating characteristic curve
  • the HCCscreen score value of the test subject can be calculated by the liver cancer prediction model.
  • the liver cancer prediction model is a penalty logistic regression model developed based on the characteristic scores and grouping information of each patient in the training set.
  • the training set consists of several patients with liver cancer (to form the liver cancer group) and several people at high risk of liver cancer (to form the liver cancer high-risk group). In an embodiment of the present invention, the training set is composed of 65 liver cancer patients and 70 liver cancer high-risk patients.
  • HBV Whether any of the above-mentioned HBV is integrated with genes can be: the degree of integration of HBV with genes, whether HBV is integrated with TERT genes and/or whether HBV is integrated with non-TERT genes (such as APOBEC4, FBX010, FUT8, WDR7, SLC7A10, GUSBP4) .
  • non-TERT genes such as APOBEC4, FBX010, FUT8, WDR7, SLC7A10, GUSBP4
  • the information of any one of the aforementioned liver cancer mutant genes includes the mutation type and/or the mutation reads and/or the information of the gene copy number variation of the liver cancer mutant gene.
  • any of the aforementioned cfDNA information may include the cfDNA concentration and/or the percentage of the cfDNA content of different insert lengths in the cfDNA.
  • the percentage of the cfDNA content of different insert fragment lengths in the cfDNA may specifically be the percentage of free DNA fragment lengths less than 90 bp, the percentage of free DNA fragments 90-140 bp, the percentage of free DNA fragments 141-200 bp, and the free DNA fragments greater than 200 bp. percentage.
  • Interval percentage refers to the percentage of all cfDNA content.
  • Any of the aforementioned clinical information may include age and/or gender.
  • the detection reagents for any of the aforementioned liver cancer mutant genes include reagents for extracting cfDNA (such as MagMAX TM Cell-Free DNA Isolation Kit), reagents for constructing cfDNA library (such as KAPA Hyper Prep Kit) and reagents for hybridizing and capturing target regions (such as sureselect XT target capture kit).
  • reagents for extracting cfDNA such as MagMAX TM Cell-Free DNA Isolation Kit
  • reagents for constructing cfDNA library such as KAPA Hyper Prep Kit
  • reagents for hybridizing and capturing target regions Such as sureselect XT target capture kit.
  • the DCP detection reagent may be a reagent for detecting the content of DCP in plasma. Specifically: the plasma is separated, and the content of DCP is detected by the Abbott ARCHITECT i2000SR chemiluminescence immunoassay analyzer.
  • the AFP detection reagent may be a reagent for detecting the content of AFP in plasma. Specifically, the plasma was separated, and the content of AFP was detected by the American Abbott IMx analyzer.
  • Any one of the aforementioned reagents for detecting whether HBV is integrated with genes can include reagents for extracting cfDNA (such as MagMAX TM Cell-Free DNA Isolation Kit).
  • the cfDNA detection reagents include reagents for extracting cfDNA (such as MagMAX TM Cell-Free DNA Isolation Kit).
  • the characteristics of the detection can be specifically the 20 characteristics in the embodiment, which are specifically as follows:
  • the "reagents for detecting mutations in liver cancer” can be used to detect the 11 features in the examples, which are TP53 gene non-R249S mutation, TERT gene mutation, AXIN1 gene mutation, CTNNB1 gene mutation, TP53R249S hot spot Mutation, CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, CNV dimensionality reduction feature 6 (ie 11 gene mutation features). Specific steps are as follows:
  • the CNV test results are processed as follows: the CNV signal at the level of each chromosome arm (sex chromosomes are deleted to exclude the influence of gender on the CNV signal) is subjected to principal component analysis (PCA) dimensionality reduction processing, and cumulative proportion (cumulative proportion) ⁇ 95% is the threshold, select the first 6 principal components (ie CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, CNV dimensionality reduction feature 6) As CNV-related features, CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, CNV dimensionality reduction feature 6) are used as CNV features for subsequent calculations.
  • the principal component score corresponding to each CNV feature is the feature score of the feature.
  • the low-depth whole-genome sequencing data can be used to analyze the 4 characteristics in the example, which are the percentage of free DNA fragments that are less than 90 bp in length, the percentage of free DNA fragments that are 90-140 bp, the percentage of free DNA fragments that are 141-200 bp, and the free DNA fragments are greater Percentage of 200bp interval.
  • the detection feature of the "cfDNA detection reagent" may specifically be cfDNA concentration.
  • the cfDNA concentration value takes the value after log2 conversion as the characteristic score.
  • the feature used for detection of the "DCP detection reagent" can be specifically one feature in the embodiment, that is, the content of DCP in plasma.
  • the feature used for the detection of the "AFP detection reagent" can specifically be one feature in the embodiment, that is, the content of AFP in plasma.
  • the "detection reagent for whether HBV is integrated with genes” can be specifically used for the detection of the two features in the embodiment, which are the integration of HBV and the integration of HBV and TERT (that is, two gene mutations). feature).
  • mutation site integration and scoring For each gene mutation, an annotation score is given according to the frequency of mutation reads support; then the mutation site score value is added to different ROI (Region Of Interest) intervals (that is, the feature score is obtained) ).
  • ROI Region Of Interest
  • This interval includes 4 genes (TP53, CTNNB1, TERT and AXIN1) and a TP53R249S hotspot mutation location region. Calculated as follows:
  • n is the number of mutations that overlap with the ROI
  • adj_score is the frequency of reads supported by the mutation.
  • TERT integration occurs, the feature score of TERT integration variation is 1 (no need to consider reads support credibility rating); TERT integration does not occur, TERT integration variation The characteristic score is 0.
  • the steps of extracting features related to free DNA length are as follows: Calculate the percentage of cfDNA fragment length in the four intervals ( ⁇ 90bp, 90-140bp, 141-200bp and >200bp), and use these features as predictors, cfDNA fragment length The percentage in the four intervals is the characteristic score.
  • the clinical features include the patient’s age and gender, and are also related to the phenotype of the case.
  • the characteristic score of age is the actual age value of the sample; the characteristic score of male sex is 1, and the characteristic score of female sex is 0.
  • Additional features can include the following 22 features: 13 gene mutation features, 2 protein markers, 5 cfDNA physical features, and 2 basic information components of blood samples.
  • the 13 gene mutation characteristics are TP53 gene non-R249S mutation, TERT gene mutation, AXIN1 gene mutation, CTNNB1 gene mutation, TP53R249S hot spot mutation, CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature Feature 4.
  • CNV dimensionality reduction feature 6 HBV integration variation, whether HBV and TERT integration variation.
  • the two protein markers are AFP and DCP.
  • the five physical characteristics of cfDNA are the percentage of free DNA fragments less than 90bp, the percentage of free DNA fragments of 90-140bp, the percentage of free DNA fragments of 141-200bp, the percentage of free DNA fragments greater than 200bp, and the cfDNA concentration.
  • the basic information of the two blood samples are gender and age.
  • the present invention contains a limited number of candidate biomarkers that are clearly related to HCC.
  • candidate biomarkers In order to avoid overfitting effects when a large number of candidate biomarkers are studied in a limited number of tumors/normal cases, we have included a small number of candidates that are clearly related to HCC.
  • Candidate biomarkers By using research tools for retrospective and/or prospective studies to verify the specific combination of gene markers and protein markers selected in the present invention, it was found that the specific combination achieved excellent effects in both retrospective and prospective verification .
  • the present invention provides a kit for early screening of hepatocellular carcinoma in AFP-negative subjects, which includes a gene marker detection agent and a DCP detection agent.
  • the kit may further include a data processing system for converting the information of gene markers and/or protein markers into the hepatocellular carcinoma screening score of the test subject, according to the test subject
  • the screening score of the patient’s hepatocellular carcinoma predicts whether the candidate is a liver cancer patient.
  • any one of the aforementioned gene marker detection agents may include one or more selected from the following, preferably three or four: TP53 detection agent, CTNNB1 detection agent, AXIN1 detection agent, TERT detection agent.
  • any of the above-mentioned gene marker detection reagents can also include a detection reagent for whether HBV is integrated with the gene.
  • Any one of the aforementioned protein marker detection agents may include one or more selected from the group consisting of AFP detection agents and DCP detection agents.
  • the kit of the present invention can be used for HCC early screening of non-specific populations, and can also be used for HCC early screening of specific populations such as AFP-negative subjects. Since AFP is a common test indicator in daily physical examinations such as blood tests, it is likely that the AFP status (negative or positive) of the subject is known. Therefore, in some embodiments, the kit of the present invention is used for early screening of HCC in a specific population such as AFP negative subjects, wherein the kit does not include an AFP detection agent. Similarly, in some embodiments, the kit of the present invention is used for early screening of HCC in a specific population such as DCP negative subjects, wherein the kit does not include a DCP detection agent.
  • the kit of the present invention is used for early HCC screening of a specific population such as AFP and DCP negative subjects, wherein the kit does not include AFP detection agent and DCP detection agent. Therefore, in some embodiments, the present invention provides a kit for early screening of hepatocellular carcinoma in AFP-negative subjects, which includes a gene marker detection agent and a protein marker detection agent, preferably wherein the protein marker detection Agents include DCP detection agents. In some embodiments, the present invention provides a kit for early screening of hepatocellular carcinoma in DCP-negative subjects, which includes a gene marker detection agent and a protein marker detection agent, preferably wherein the protein marker detection agent Includes AFP detection agent.
  • the present invention provides a kit for early screening of hepatocellular carcinoma in AFP and DCP negative subjects, which includes a gene marker detection agent.
  • the gene marker detection agent according to the present invention can detect the presence and/or type of gene markers, including mutation types and mutation reads.
  • the gene marker detection agent according to the present invention further includes a CNV detection agent in some embodiments.
  • CNV detection agents are usually used to detect CNV at the whole genome level, but in some embodiments, they can also be used to detect CNV at local levels, such as genes.
  • the kit of the present invention includes a CNV detection agent for detecting global CNV levels.
  • the kit of the present invention contains a CNV detection agent for detecting local CNV levels.
  • the kit of the present invention includes a CNV detection agent for detecting the CNV level of the TERT gene. The use of CNV detection agents can further improve the sensitivity and specificity of HCC screening.
  • the CNV detection result can be converted into CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, and/or CNV dimensionality reduction feature 6 .
  • the term "gene marker detection agent” is a detection agent used to detect genetic markers, including those well known to those skilled in the art and those described herein.
  • the terms "TP53 detection agent”, “CTNNB1 detection agent”, “AXIN1 detection agent” and “TERT detection agent” are detection agents for detecting the respective designated gene markers, including those well known to those skilled in the art and Described in this article.
  • TP53, CTNNB1, AXIN1, and TERT are well-known to those skilled in the art as common gene markers in the art, such as TERT promoter mutations.
  • the full length of TP53 is detected.
  • one or more exons of TP53 are detected.
  • the present invention is characterized in some aspects by detecting the full length of TP53, rather than only detecting one or more exons of TP53.
  • the gene referred to in the present invention when used as a gene marker, uses at least one or more nucleotide differences between all or part of its sequence obtained by sequencing and its corresponding wild-type sequence. It is not necessarily limited to a specific site.
  • TP53, CTNNB1, AXIN1 and TERT genes are used as gene markers, there can be at least one or more nucleotide differences between their corresponding wild-type sequences in full length.
  • the TP53 gene is used as a gene marker, there can also be at least one or more nucleotide differences between its specific hot spot (for example, R249S) and its corresponding wild-type sequence.
  • TERT gene When a TERT gene is used as a gene marker, there can also be at least one or more nucleotide differences between its specific hotspot (for example, chr5:1295228C>T or chr5:1295250C>T) and its corresponding wild-type sequence.
  • specific hotspot for example, chr5:1295228C>T or chr5:1295250C>T
  • the gene marker detection agent according to the present invention further includes an HBV integration detection agent in some embodiments.
  • HBV integration detection agent is a reagent for detecting whether HBV is integrated in the genome.
  • integration of HBV in the genome may include integration of HBV into the genome near the TERT, for example, within 1.5 kb upstream of the TERT, and integration of HBV into other places in the genome.
  • the subject's genetic markers are detected from the subject's cfDNA.
  • the use process or detection process includes cfDNA extraction and detection, thereby obtaining information related to cfDNA, including, for example, cfDNA concentration and/or cfDNA content. Different insert length as a percentage of cfDNA content and/or cfDNA length detection agent. Therefore, in some embodiments, the "gene marker detection agent" and its subordinate concepts described herein can also function as cfDNA detection agents, and thus can be used interchangeably with "cfDNA detection agents". In other embodiments, the kit of the present invention further includes a cfDNA detection agent.
  • protein marker detection agent is a detection agent used to detect protein markers, including those well known to those skilled in the art and described herein.
  • AFP detection agent and “DCP detection agent” are detection agents used to detect the respective designated protein markers, including those well known to those skilled in the art and described herein.
  • AFP and DCP as common protein markers in the field are well known to those skilled in the art.
  • the subject's protein marker is detected from the subject's blood or its components such as serum or plasma.
  • the kit further includes a blood drawing device.
  • the kit of the present invention may also include a data processing system or be used together with a data processing system.
  • the data processing system may be included in a computer.
  • the data processing system is used to process the detection results of the gene marker detection agent and/or protein marker detection agent according to the present invention.
  • the data processing system uses the detection results of the gene markers and protein markers to calculate the hepatocellular carcinoma screening score.
  • the data processing system compares the hepatocellular carcinoma screening score to a threshold value.
  • the data processing system is used to estimate and/or verify and/or predict HCC, preferably by comparing the hepatocellular carcinoma screening score to a threshold.
  • the present invention has discovered that it is possible to identify individuals with early HCC and distinguish them from non-HCC individuals with chronic liver diseases including cirrhosis.
  • This assay showed a sensitivity of 85% and a specificity of 93% in the diagnosis of HCC in individuals with elevated liver nodules and/or serum AFP by ultrasound. More importantly, the performance is also maintained in the AFP/US negative verification set, with sensitivity and specificity of 100% and 94%, respectively.
  • the current sensitivity is based on a limited number of HCC cases. If additional HCC cases are identified, this may change with long-term follow-up or dynamic CT/MRI detection of all individuals. In this case, the determination of sensitivity and specificity based on follow-up time requires prospective and large-scale clinical trials.
  • the present invention provides a method for early screening of hepatocellular carcinoma, which comprises:
  • PPV can be further improved. High PPV is very helpful for routine clinical application because it will reduce unnecessary anxiety and follow-up examinations for non-HCC individuals.
  • the present invention provides a method for early screening of hepatocellular carcinoma, which comprises:
  • the subject's genetic marker is detected from the subject's cfDNA. That is, the method includes extracting cfDNA of the subject.
  • the subject's protein marker is detected from the subject's blood. That is, the method includes drawing blood from the subject, preferably serum or plasma.
  • a period of time can be 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, one week, two weeks, three weeks, one month, two months, three months, four Month, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, and not limited to these.
  • the threshold for comparison with the calculated hepatocellular carcinoma screening score is 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or 1.0. In a preferred embodiment, the threshold is 0.4. In a preferred embodiment, the threshold is 0.5.
  • the present invention provides the use of a gene marker detection agent and a protein marker detection agent for early screening of hepatocellular carcinoma.
  • the present invention provides the use of a gene marker detection agent and a protein marker detection agent in preparing a kit for early screening of hepatocellular carcinoma.
  • Tumor size is an important clinical parameter in diagnosis, which affects the survival of HCC patients. Unlike protein or RNA-based biomarkers, tumor cells usually contain only one copy of mutant DNA in most cases. A basic question in cfDNA-based early detection screening is whether early tumors release enough copies of mutant DNA to be detected in circulation. Of all the identified HCCs that passed HCC screening in this study, 85% and 68% of cases were ⁇ 5cm and ⁇ 3cm, respectively. HCC tumors ⁇ 5cm are early stage and suitable for curative surgery. Patients with tumors ⁇ 3cm can even have better results, which emphasizes the value of HCC screening in reducing HCC morbidity and mortality. In the verification set, the present invention identifies 4 cases of HCC from the AFP/US negative population, which are 2-3 cm in size. These results clearly show that the sensitivity of HCC screening has good prospects for early HCC detection.
  • the ideal tumor screening method should have high sensitivity and specificity, and it should be easy to implement in clinical practice.
  • This HCC screening assay detects mutations in the coding region and translocations/HBV integration with unknown breakpoints, and the cost is less than $150.
  • the liquid biopsy method can be centralized and standardized, and requires the minimum professional knowledge and equipment in the local hospital/clinic. In general, this method is very suitable as a routine test for HCC screening in high-risk groups.
  • the kit of the invention may also contain additional therapeutic agents.
  • the methods of the invention may also include the administration of additional therapeutic agents.
  • the additional therapeutic agent is a cancer (such as hepatocellular carcinoma) therapeutic agent known in the art.
  • any recited value can be the upper or lower limit of the numerical range. It should also be understood that the present invention encompasses all such numerical ranges, that is, a range having a combination of an upper numerical limit and a lower numerical limit, wherein the respective numerical values of the upper limit and the lower limit can be any numerical values listed in the present invention.
  • the range provided by the present invention should be understood to include all values within the range. For example, 1-10 should be understood to include all of the values 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10, and include fractional values as appropriate.
  • a range expressed as "up to” a certain value should be understood as all values (including the upper limit of the range), such as 0, 1, 2, 3, 4, and 5, and include points as appropriate. Numerical value. At most one week or within a week should be understood to include 0.5, 1, 2, 3, 4, 5, 6 or 7 days. Similarly, the range defined by "at least” should be understood to include the lower values provided and all higher values.
  • the early liver cancer screening markers are mostly protein or gene methylation information.
  • the present invention reports a new type of hepatocellular carcinoma screening (HCC screening) method, which is based on the detection of both serum protein markers and cfDNA changes, and confirms its application in multi-centers with chronic HBV infection
  • HCC screening hepatocellular carcinoma screening
  • the inventors of the present invention confirmed for the first time that the gene mutation information of cfDNA in plasma can be used for early HCC prediction through a large number of experiments.
  • the inventors used the liver cancer prediction model to score the test subject, and predicted whether the test subject was a liver cancer patient through the score value, thereby verifying that the combination of the gene marker and the protein marker of the present invention can effectively perform early HCC screening. It can be seen that early screening, disease tracking, curative effect evaluation, and prognosis prediction for liver cancer through cfDNA detection have important clinical significance.
  • Figure 1 shows the research design plan. Including population recruitment, HCC screening model training, and verification in sampled AFP/US negative individuals.
  • Figure 2 shows the detailed research design plan.
  • Figure 3 shows the design of cfDNA gene profile analysis in HCC screening assay.
  • Figure 4 shows the performance of HCC screening in the training set and validation set.
  • A is the HCC screening score and the contribution of cfDNA and protein biomarkers in the diagnostic model in the training set
  • B is the binary result of the diagnostic model in the training set
  • C is the ROC of the diagnostic model of the HCC screening in the training set Curve
  • D is the HCC screening performance of the verification centralized diagnosis model
  • E is the follow-up and diagnosis of positive cases in the verification centralized HCC screening
  • F is the binary result of the verification centralized diagnosis model
  • G is the AFP/US negative individuals, HCC Screen dynamic CT imaging of 4 HCC cases detected.
  • Figure 5 shows the performance of different training sets.
  • A is the ROC curve of the HCC screening diagnostic model in the training set with healthy individuals without HBV infection as the control
  • B is the training with HCC and non-HCC individuals (left) and the training with HCC and healthy individuals (right Figure).
  • Figure 6 shows the ROC curve of the liver cancer prediction model.
  • Figure 7 is a comparison diagram of model scores in different groups.
  • test materials used in the following examples are all purchased from conventional biochemical reagent stores.
  • each liver cancer patient, each liver cancer high-risk person, and healthy volunteers all give informed consent to the content of this study.
  • MagMAX TM Cell-Free DNA Isolation Kit is a product of Thermo Fisher.
  • KAPA Hyper Prep kit is a product of KAPA company.
  • the sureselect XT target capture kit is a product of Agilent.
  • HCCscreen02 male 56 Liver cancer 8cm HCCscreen03 male 75 Liver cancer 3cm ⁇ 2cm ⁇ 2cm HCCscreen04 male 58 Liver cancer 5.0cm ⁇ 3.0cm HCCscreen05
  • Female 53 Liver cancer - HCCscreen06 male 63 Liver cancer 4.1cm ⁇ 3.2cm HCCscreen07 male 39 Liver cancer 2.3cm ⁇ 2cm ⁇ 1.8cm HCCscreen08 male 42 Liver cancer 3.8cm ⁇ 3.5cm HCCscreen09 male 56 Liver cancer 2.3cm ⁇ 2.6cm HCCscreen10
  • Female 68 Liver cancer 4.7cm ⁇ 4.2cm HCCscreen11 male 53 Liver cancer 2.1cm ⁇ 1.2cm HCCscreen12 male 69 Liver cancer 1.2cm ⁇ 1.4cm HCCscreen13 male 69 Liver cancer - HCCscreen14 male 60 Liver cancer 3.2cm ⁇ 2.6cm HCCscreen15 male 54 Liver cancer 3.0cm ⁇ 2.5cm HCCscreen16 male 62 Liver cancer 3.6cm ⁇ 3.8
  • HCCscreen48 Female 63 High risk of liver cancer - HCCscreen49 Female 55 High risk of liver cancer - HCCscreen50 male 34 High risk of liver cancer - HCCscreen51 male 32 Healthy volunteers - HCCscreen52 male 32 Healthy volunteers - HCCscreen53 male 34 Healthy volunteers - HCCscreen54 male 36 Healthy volunteers - HCCscreen55 male 28 Healthy volunteers - HCCscreen56
  • Female twenty four Healthy volunteers - HCCscreen57 male 32 Healthy volunteers - HCCscreen58 Female 29 Healthy volunteers - HCCscreen59 Female 32 Healthy volunteers - HCCscreen60 male 39 Healthy volunteers - HCCscreen61 male 30 Healthy volunteers - HCCscreen62
  • Female Healthy volunteers - HCCscreen65 Female 33 Healthy volunteers - HCCscreen66 male 28 Healthy volunteers - HCCscreen67
  • tumor size is tumor volume, tumor maximum diameter or tumor maximum cross-sectional area.
  • CCOP-LC cohort Chinese Clinical Register, ChiCTR-EOC-17012835
  • NCC201709011 The research protocol was approved by the Institutional Review Board of the National Cancer Center/National Cancer Research Center/Tumor Hospital of the Chinese Academy of Medical Sciences.
  • HBsAg-positive "healthy" individuals are invited to participate in early HCC screening. All participants underwent serum AFP concentration determination and ultrasound examination (US; Aloka ProSound SSD-4000; Shanghai, China), as well as other standard biochemical tests (Table 2). Based on serum AFP levels and liver nodule testing, individuals are designated as AFP/US positive, suspected, or negative. Individuals with “AFP/US positive” have any of the following: 1) Nodules detected by ultrasound, serum AFP level>400ng/mL; 2) Nodules detected by ultrasound, ⁇ 2cm, regardless of serum AFP concentration; 3) The nodules detected by ultrasound are ⁇ 1cm, and the serum AFP is ⁇ 200ng/ml.
  • AFP/US Individuals with "suspected AFP/US” have any of the following: 1) The liver nodules detected by ultrasound are not considered, and the serum AFP level is ⁇ 20ng/ml; 2) the nodules detected by ultrasound are ⁇ 1cm. Individuals with "AFP/US negative” were defined as serum AFP levels ⁇ 20ng/mL and no liver nodules detected by ultrasound. Individuals with AFP/US positive are referred to a high-level hospital (a tertiary hospital in China) for diagnosis. For example, if a liver cancer patient is determined by dynamic CT or dynamic MRI, they will receive relevant treatment based on clinical practice guidelines (Figure 1) (Omata M, et al.
  • AFP/US positive/suspected cases were further analyzed in the HCC screening assay. According to the diagnosis results in the follow-up examination, participants with reliable diagnosis were selected as the training set in this study.
  • the present invention samples 331 participants from AFP/US negative individuals whose ages are similar to those of AFP/US positive/suspected persons in the HCC screening assay. From May 20 to July 17, 2018 (6-8 months after the baseline blood draw), 331 individuals were followed up by dynamic CT/MRI, AFP/ultrasound or telephone interviews. The CT/MRI images were independently evaluated by two radiologists from the National Cancer Center of the Chinese Academy of Medical Sciences in Beijing.
  • the present invention provides additional AFP/US tests for individuals who are AFP/US negative at baseline and have not undergone HCC screening tests. Some of them did not choose an additional AFP/US test, and their liver cancer results (ICD-10 code C22) before June 30, 2018 were obtained from the screening center's group-based cancer registry ( Figure 1). Among the 3617 AFP/US negative individuals, 1612 (44.6%) participants were able to follow-up from May 20 to July 17, 2018, that is, 6-8 months after baseline screening. Among them, 87 participants received dynamic CT/MRI, 1120 received AFP/US, and 68 were interviewed by telephone. The liver cancer results of 337 participants were obtained from the local group-based cancer registry ( Figure 2). The HCC status of the other 2005 participants was not available before June 30, 2018 ( Figure 2).
  • the serum DCP level was measured in the Abbott ARCHITECT i2000SR Chemiluminescence Immunoassay Analyzer (CLIA) using a commercial kit.
  • the inventors designed experiments to sequence cfDNA for profile analysis: 1) TP53, CTNNB1, AXIN1 coding region and TERT promoter region (Table 3); 2) HBV integration.
  • the cfDNA fragment was first ligated to an adaptor with a random DNA barcode ( Figure 3).
  • the ligated constructs were amplified through 10 reaction cycles to produce a whole genome library, containing hundreds of redundant constructs with unique DNA barcodes that recognized each original cfDNA fragment.
  • the amplified library is sufficient for 5-10 independent sequencing analyses.
  • the target region is using target-specific primers (TS primer 1) and primers matching the adaptor sequence (Perera BP & Kim J (2016) Next-generation sequencing-based 5'rapid amplification of cDNA ends for alternative promoters.Analytical biochemistry 494: 82-84; Zheng Z, et al. (2014) Anchored multiplex PCR for targeted next-generation sequencing. Nature medicine 20(12): 1479-1484.) ( Figure 3) The 9 cycles of PCR together with the DNA barcode Amplification. A pair of nested primers (TS primer 2) matching the adapter and the target region were used to perform the second round of 15-cycle PCR to further enrich the target region and add the Illumina sequencing adapter ( Figure 3).
  • the present invention can cover the target area >100,000 times with 3Gb sequencing data, making 20 ⁇ redundant sequencing of 5,000 copies of original cfDNA possible.
  • redundant reads from the original cfDNA molecule can be tracked to minimize the calling error inherent in PCR amplification and parallel mutation sequencing (Kinde I, Wu J, Papadopoulos N, Kinzler KW, & Vogelstein B (2011) Detection and quantification of rare mutations with massively parallel sequencing.
  • the present invention uses digital PCR to check the 11 mutations detected in this assay, and verifies all these mutations with a mutation score of 0.03-0.16%.
  • Sequencing reads are processed to extract tags and remove sequence adapters. Then use Trimmomatic (v0.36) to remove residual joints and low-quality areas. Use'bwa(v0.7.10)mem'(Li H & Durbin R(2010) Fast and accurate long-read alignment with Burrows-Wheeler transform.Bioinformatics 26(5):589-595.) with default parameters will be clean The reads are mapped to hg19 and HBV genomes. Use samtools mpileup (Li H, et al. (2009) The Sequence Alignment/Map format and SAMtools.Bioinformatics 25(16): 2078-2079.) to identify candidate mutations consisting of SNP and INDEL in the target region of interest .
  • UID family Unique Identifier family
  • EUID family Effective Unique Identifier family
  • the frequency of each mutation is calculated by dividing the number of alternative EUID families by the sum of the alternative and reference. Further check for mutations manually in IGV.
  • VEP Use Ensembl Variant Effect Predictor (VEP) to annotate candidate variants (Wang J, et al. (2011) CREST maps somatic structural variation in cancer genes with base-pair resolution. Nat Methods 8(8): 652-654).
  • VEP Effective Unique Identifier
  • the mutation frequency (the fraction of reads that support candidate mutations) is highly proportional to the total amount of circulating tumor DNA in the blood and tumor size. Therefore, the present invention uses its reads to support frequency annotation of all input mutations.
  • n is the number of mutations that overlap with the ROI
  • adj_score is the frequency of reads supported by the mutation.
  • DCP and AFP Two protein markers, DCP and AFP, are used in the model of the present invention, because they have been shown as very strong indicators for HCC diagnosis in previous studies (Chen H, et al. (2016) Direct comparison of five serum biomarkers in early diagnosis of hepatocellular carcinoma. Cancer management and research 10:1947-1958.). These values are sorted into multiple numerical categories.
  • the cfDNA concentration is also included in the model feature list of the present invention.
  • the age and gender of the patient also form part of the predictor of the present invention, because it has been shown that the possibility of HCC diagnosis is to some extent related to the age and gender of the individual.
  • RandomForest is used to filter useful variables from candidate features; the inventors apply backward variable subtraction by minimizing unbiased out-of-bag error estimation, eliminating one per run feature. Then the protein, gene markers and clinical information are optimized to build the final features of the binary classifier. In HCC training compared to healthy individuals, only ctDNA SNP/indel mutations and protein markers are used. It does not include HBV-TERT fusion or other HBV integration, because the healthy group did not have HBV infection.
  • the penalty logistic regression model is constructed by a training set containing 65 HCC and 70 non-HCC 135 samples. Through area under the curve (AUC) statistics, model performance is evaluated on both training and validation data sets. The sensitivity and specificity of the model were also determined using an optimized cutoff value of 0.4. Use Youden index for optimization of this cutoff value. In order to perform cluster analysis on gene, protein and CNV levels respectively, the cross-validation coefficient of each feature using penalty logistic regression is also given. The model is started in the R package ‘glmnet’ (R version 3.5.1), and the penalty parameter ⁇ is optimized through 10-fold cross-validation in the training data set, and the optimized value is 0.
  • R package ‘glmnet’ R version 3.5.1
  • the present invention uses a penalty logistic regression model with ctDNA mutations, protein biomarker levels and clinical characteristics as variables.
  • the inventors defined HCC cases and non-HCC cases with dynamic CT/MRI and/or histology in AFP/US positive and AFP/US suspected individuals ( Figure 1).
  • LOOCV Leave-One-Out Cross Validation
  • Example 1 follow-up of clinical parameters and hepatocellular carcinoma (HCC) results of participants at baseline in four screening centers
  • HBsAg blood hepatitis B virus surface antigen
  • the present invention performs HCC liquid biopsy test (HCC screening) on blood samples collected from the verification set during baseline AFP/US screening, and performs follow-up of HCC status 6-8 months after baseline screening.
  • HCC screening HCC liquid biopsy test
  • the present invention uses two types of biomarkers to develop HCC screening assays: 1) genetic changes that are very common in HCC and can be detected in cfDNA; and 2) serum protein markers-alpha-fetoprotein (AFP) and des- ⁇ -carboxyprothrombin (DCP).
  • AFP serum protein markers-alpha-fetoprotein
  • DCP des- ⁇ -carboxyprothrombin
  • most HBV-related HCCs carry at least one mutation in the following genes/locations: TP53, CTNNB1, AXIN1, or TERT promoter (Totoki Y, et al. (2014) Trans-ancestry mutational landscape of hepatocellular carcinoma genomes.Nature genetics46(12):1267-1273; Zhang W, et al.
  • the present invention also considers HBV integration breakpoint as a potential biomarker for HCC. Since the HBV integration site should be unique in each individual cell, the detection of multiple copies (>2) of the specific integration site from plasma (2-3ml) can indicate the clonal expansion of a single cell carrying HBV integration. Only in this case will the resulting tumor release multiple copies of the same genomic DNA into the blood.
  • the present invention designs an assay method that can profile gene changes in parallel.
  • the extracted cfDNA is connected to a custom adapter with a DNA barcode, and then amplified to generate a whole genome library.
  • the inventors used a method similar to rapid amplification of cDNA ends (RACE), using multiple primers covering the coding regions of TP53, CTNNB1 and AXIN1, the promoter region of TERT and the HBV sequence to enrich targets with point mutations and HBV integration (Figure 3) (Chaudhuri AA, et al. (2017) Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling. Cancer discovery 7(12):1394-1403; Waltari E, et al. (2016) 5'Rapid Amplification of cDNA Ends and Illumina MiSeq Reveals B Cell Receptor Features in Healthy Adults, Adults With Chronic HIV-1 Infection, Cord Blood, and Humanized Mice.
  • RACE rapid amplification of cDNA ends
  • the present invention combines these two serum protein markers with changes in cfDNA to study whether this liquid biopsy-based assay (including AFP, DCP and cfDNA) can effectively screen early HCC.
  • the present invention performed HCC screening in individuals who are known to be diagnosed with HCC or have been excluded (non-HCC). 65 cases of HCC and 70 cases of non-HCC were obtained from AFP/US positive/suspected individuals. The HCC positive or HCC negative status is based on dynamic CT/MRI imaging and histological confirmation. Use these 135 cases as a training set and compare the HCC screening results with the clinical diagnosis.
  • the present invention first collapses the different types of cfDNA mutations into regions of interest (ROI) scores for each gene or locus.
  • the ROI score is the weighted sum of the destructive effect and frequency of each point mutation in the ROI.
  • the present invention also adds two structural variant features (HBV integration and other HBV integration in the TERT promoter region), an experimental feature (cfDNA concentration), and two protein Markers (AFP and DCP) and two clinical features (age and gender) were used as the final features for constructing a diagnostic classifier to predict HCC status (Table 2).
  • HCC screening model can distinguish HCC cases from non-HCC cases ( Figure 4, A).
  • T stands for true mutation
  • S stands for suspected mutation
  • HCC screening tested whether HCC screening can detect HCC from HBsAg-positive individuals who are negative for AFP/US and have no clinical symptoms.
  • HCC screening tested 331 AFP/US negative individuals, and 24 positive cases (called HCC screening positive) were identified based on the algorithm obtained from the training set ( Figure 4, D).
  • HCC screening-positive individuals were followed up for 6-8 months to obtain HCC clinical results.
  • 17 were examined by dynamic CT, 4 by AFP/US, and 3 were followed up by telephone interview.
  • 4 were eventually diagnosed as HCC, and the positive predictive value of HCC testing was 17% (E in Figure 4).
  • the present invention also tracked 172 HCC screening negative participants through AFP/US 6-8 months after the baseline AFP/US screening, and no HCC cases were diagnosed.
  • no HCC patients were found ( Figure 2).
  • HCC screening assay produced 17% positive predictive value, 100% (4/4) sensitivity, and 94% specificity (307/327) in AFP/US-negative individuals ( Figure 4F ).
  • diagnosis by dynamic CT all four HCC patients were identified with tumor sizes less than 3 cm (G in Figure 4), and based on the US results at baseline, these four patients had no cirrhosis.
  • the present invention provides AFP/US examination to 944 participants who were AFP/US-negative at the baseline examination and who did not undergo the HCC screening test within 6-8 months after the baseline examination.
  • Four HCC cases (0.4%, 4/944) were detected and further confirmed.
  • Cancer registry records show that no liver cancer results (ICD-10 code C22) were identified in these 337 participants before June 30, 2018, and these participants were negative for AFP/US in the baseline screening and were not screened for HCC Or any further AFP/US screening (Figure 2).
  • Example 5 Use healthy individuals to train liquid biometrics
  • the HCC screening assay has shown a strong ability to identify HCC in high-risk groups. Previous studies predicted that in such high-risk groups, the sensitivity and specificity would be lower than comparisons between cancer patients and healthy individuals without HBV infection or other risk factors. To test this hypothesis, the present invention performed HCC screening on 70 healthy individuals (HBsAg negative) without HBV infection, and used these data to replace 70 HBsAg positive non-HCC cases in the training set. Through the analysis of cfDNA and protein markers, the HCC screening assay can effectively identify HCC cases from healthy individuals with a sensitivity of 98% and a specificity of 100% (Figure 5, A). However, the algorithm derived from this training set (HCC and healthy individuals) performed poorly in HBsAg-positive non-HCC cases.
  • liver cancer patients Blood samples of liver cancer patients were provided by 65 liver cancer patients who had been clinically identified as liver cancer.
  • liver cancer The blood samples of people at high risk of liver cancer are collected from the literature (Omata, M., et al., Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma:a 2017 update.Hepatol Int, 2017.11(4): p.317-370.)
  • the method provided in is identified for 70 high-risk liver cancer patients.
  • the blood samples to be tested are 65 blood samples from liver cancer patients, 70 blood samples from people at high risk of liver cancer, and 100 blood samples from healthy people.
  • step 1 use liquid phase hybridization capture technology to detect the liver cancer mutation gene information in the cfDNA of the blood sample to be tested, such as TP53 gene, AXIN1 gene, CTNNB1 gene, TERT gene promoter, type B HBV and type C HBV Mutation information.
  • the specific steps are:
  • step (1) After completing step (1), take the cfDNA library of the blood sample to be tested, use the sureselect XT target capture kit to hybridize and capture the target area, and then perform sequencing on the Illumina platform with a sequencing depth of 20000 ⁇ .
  • the version, chromosome, starting position, ending position and coverage area of the detected gene or virus are shown in Table 6.
  • liver cancer mutation genes in cfDNA of some blood samples to be tested are shown in columns 2 and 4 in Table 7.
  • step 3 Take the cfDNA library of the blood sample to be tested prepared in step 2 (1), perform low-depth whole-genome sequencing, and then perform CNV detection on the sequencing data (about 3G).
  • the blood samples to be tested are 65 blood samples from liver cancer patients, 70 blood samples from people at high risk of liver cancer, and 100 blood samples from healthy people.
  • step 2 After completing step 1, take the plasma and use the Abbott IMx analyzer to detect the content of AFP.
  • test results of the AFP content in the plasma of some blood samples to be tested are shown in the second column of Table 8.
  • the blood samples to be tested are 65 blood samples from liver cancer patients, 70 blood samples from people at high risk of liver cancer, and 100 blood samples from healthy people.
  • step 2 After completing step 1, take the plasma and use the Abbott ARCHITECT i2000SR chemiluminescence immunoassay analyzer to detect the content of DCP.
  • This interval includes 4 genes (TP53, CTNNB1, TERT and AXIN1) and a TP53R249S hotspot mutation location region. Calculated as follows:
  • n is the number of mutations that overlap with the ROI
  • adj_score is the frequency of reads supported by the mutation.
  • TERT integration occurs, the characteristic score of TERT integration variation is 1; if TERT integration does not occur, the characteristic score of TERT integration variation is 0.
  • the CNV detection result in step two is processed as follows:
  • the scores of 44 CNV signals (sex chromosomes are deleted to exclude the influence of gender on CNV signals) at each arm level are processed by PCA dimensionality reduction, and before selection by R2 value 6 principal components (ie, CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, CNV dimensionality reduction feature 6) as CNV-related features, CNV reduction
  • the R2 value of dimensional feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4, CNV dimensionality reduction feature 5, and CNV dimensionality reduction feature 6 is the feature score.
  • the inventors of the present invention calculated the percentage of cfDNA fragment length in four intervals ( ⁇ 90bp, 90-140bp, 141-200bp and >200bp), and used these characteristics as predictive variables.
  • the cfDNA fragment length accounted for the four intervals The percentage is the characteristic score.
  • the clinical characteristics including the patient's age, gender, and cfDNA concentration were also correlated with the phenotype of the case and were included in the model.
  • the cfDNA concentration value takes the value after log2 conversion as the characteristic score; the characteristic score of age is the actual age value of the sample; the characteristic score of gender is 1 and the characteristic score of gender is 0.
  • the 22 features consist of 13 gene mutation features, 2 protein markers, 5 cfDNA physical features, and 2 basic information about blood samples.
  • the 13 gene mutation characteristics are TP53 gene mutation, TERT gene mutation, AXIN1 gene mutation, CTNNB1 gene mutation, TP53R249S hot spot area, CNV dimensionality reduction feature 1, CNV dimensionality reduction feature 2, CNV dimensionality reduction feature 3, CNV dimensionality reduction feature 4.
  • the two protein markers are AFP and DCP.
  • the five physical characteristics of cfDNA are the percentage of free DNA fragments less than 90bp, the percentage of free DNA fragments of 90-140bp, the percentage of free DNA fragments of 141-200bp, the percentage of free DNA fragments greater than 200bp, and the cfDNA concentration.
  • the basic information of the two blood samples are gender and age.
  • the penalty logistic regression algorithm is used to model the training set data composed of 65 HCCs and 70 high-risk liver cancer patients, and calculate the HCCscreen score value.
  • the cross-validation coefficient of each feature using penalty logistic regression is also given.
  • the model is started in the R package ‘glmnet’ (R version 3.5.1), and the penalty parameter ⁇ is optimized through 10-fold cross-validation in the training data set, and the optimized value is 0.
  • draw the ROC curve (receiver operating characteristic curve) based on the HCCScreen score value and the sample grouping (cancer or non-cancer) information.
  • the HCCScreen score value corresponding to the maximum Youden’s index is taken as the threshold. In this model, 0.4 is selected as the best cut-off value of the model.
  • the liver cancer group (composed of 65 liver cancer patients), the liver cancer high-risk group (composed of 70 liver cancer high-risk patients), and the healthy group (composed of 100 healthy volunteers) as samples are effective for the prognosis method of the liver cancer prediction model in step 7 Verification.
  • the results are shown in Figure 7.
  • the results show that the liver cancer prediction model can predict whether the test subject is a liver cancer patient.
  • the inventors of the present invention confirmed for the first time that the gene mutation information of cfDNA in plasma can be used for early HCC prediction through a large number of experiments.
  • the inventors used the liver cancer prediction model to score the test subject, and predicted whether the test subject is a liver cancer patient through the score value, thereby verifying the effective HCC early screening effect of the combination of the gene marker and the protein marker of the present invention. It can be seen that early screening, disease tracking, curative effect evaluation, and prognosis prediction for liver cancer through cfDNA detection have important clinical significance.

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Abstract

用于肝细胞癌早筛的试剂盒及其制备方法和用途，该试剂盒包括基因标志物检测剂和蛋白标志物检测剂。包含特定基因标志物与蛋白标志物的试剂盒已证实在社区群体中有效实现肝细胞癌早筛，并在前瞻性研究中得到了验证。

Description

肝细胞癌早筛试剂盒及其制备方法和用途 技术领域
本发明属于医学领域，涉及肝细胞癌早筛试剂盒，更具体涉及用于AFP阴性受试者的肝细胞癌早筛的试剂盒，及其制备方法和用途。
背景技术
肝癌包括两种主要病理组织学类型，肝细胞癌(HCC)和肝内胆管细胞癌(iCCA)，其中HCC占比约85-90％，目前晚期HCC没有有效的治疗方法，因此推荐HCC高风险的肝硬化患者进行筛查(Omata M,et al.(2017)Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma:a 2017update.Hepatol Int 11(4):317-370；Marrero JA,et al.(2018)Diagnosis,Staging and Management of Hepatocellular Carcinoma:2018 Practice Guidance by the American Association for the Study of Liver Diseases.Hepatology.)。在中国，依据亚太肝病研究学会的指南，已经在多个队列中开展HCC早期筛查，推荐肝硬化个体和乙肝病毒表面抗原(HBsAg)阳性个体，每6个月进行一次HCC监测，包括超声检查(US)和血清甲胎蛋白(AFP)检测(Omata M,et al.(2017)，同上)。在以前的研究中，采用此种模式早期发现和早期接受治疗显著提高了肝癌的总体生存率(Singal AG,Pillai A,& Tiro J(2014)Early detection,curative treatment,and survival rates for hepatocellular carcinoma surveillance in patients with cirrhosis:a meta-analysis.PLoS medicine 11(4):e1001624.)，但HCC的精确检测需要有经验的专家，进而限制了其在全部HBsAg阳性个体中的广泛应用。此外，一年两次的筛查也与随访预约和产生焦虑相关。目前，中国的大多数HCC案例是基于临床症状而不是通过HCC筛查发现的，而且在医院诊断时已处于晚期。
在最近的研究中，基于细胞游离DNA(cfDNA)的基因改变的液体活检已经在癌症早期检测中表现出良好的效果(Bettegowda C,et al.(2014)Detection of circulating tumor DNA in early-and late-stage human malignancies.Science translational medicine 6(224):224ra224；Chaudhuri AA,et al.(2017)Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling.Cancer discovery 7(12):1394-1403.)。将基因与蛋白质标志物组合，可进一步提高检测的灵敏度和特异性，并且可能在一个测试中筛查多种肿瘤类型(Springer S,et al.(2015)A Combination of Molecular Markers and Clinical Features Improve the Classification of Pancreatic Cysts.Gastroenterology；Cohen JD,et al.(2018)Detection and localization of surgically resectable cancers with a multi-analyte blood test.Science 359(6378):926-930；Cohen JD,et al.(2017)Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers.Proceedings of the National Academy of Sciences of the United States of America 114(38):10202-10207.)。然而，这些研究主要针对HCC住院患者和没有HBV感 染的健康人(Cohen JD,et al.(2018)，同上)。在慢性HBV感染的高危人群中，液体活检检测的性能可能会受到影响，因为一些癌前损伤，如肝硬化，可能也具有HCC中普遍存在的驱动突变。分析肝炎、肝硬化和非癌肝结节可能是绘制基线以通过成像或组织学临床验证来精确鉴定HCC所必要的。
引起肝功能损害的常见原因有感染(如乙型肝炎病毒感染)、肥胖、酗酒、黄曲霉素暴露、血脂异常等等，且肝病患者患肝癌的风险更高。甲胎蛋白(AFP)、异凝血酶原(DCP)和鳞状上皮细胞癌抗原(SCCA)均为肝癌的蛋白标志物。研究表明，AFP和DCP的联合测量可提高预测肝癌的灵敏度，有效区分早期肝癌和失代偿性肝硬化。然而，很多早期肝癌中，AFP、DCP和SCCA检测结果均为阴性。
肿瘤或其它细胞会释放DNA分子进入血液，经过降解，形成游离的DNA片段(Cellfree DNA，cfDNA)。cfDNA的检测在指导肿瘤靶向用药、疗效监测以及癌症的早期筛查等方面表现出极大潜力。我国肝癌患者中约90％有乙型肝炎病毒感染背景，且乙型肝炎病毒相关性肝癌几乎没有KRAS、BRAF等热点突变。
如前所述，过往使用单独的蛋白标志物如AFP作为HCC早筛指标。Chun等，2015(Chun S,Rhie SY,Ki CS,Kim JE,& Park HD(2015)Evaluation of alpha-fetoprotein as a screening marker for hepatocellular carcinoma in hepatitis prevalent areas.Annals of hepatology 14(6):882-888.)报告了使用单独的甲胎蛋白作为筛查标志物，但效果欠佳，阳性预测值约为1-2％。
近期也有尝试用基因变化结合蛋白标志物的方式进行HCC早筛。Joshua D.Cohen等，2018(Cohen J D，Li L，Wang Y，et al.Detection and localization of surgically resectable cancers with a multi-analyte blood test[J].Science，2018，359(6378)：eaar3247.)报告了采用基因突变结合蛋白标志物的方式进行包括HCC的泛癌种的早筛，但其在涉及HCC时未采用例如TERT及其多种形式和/或HBV融合的基因变化。且这项研究只是针对已诊断为HCC的住院患者与健康人群的回顾性研究，未对无HCC症状人群进行前瞻性研究，从而对HCC发生进行预测并给出阳性预测值。
发明公开
传统上，基因变化或蛋白标志物被各自单独用于癌症早筛。也曾有人尝试过用基因变化与蛋白标志物的组合进行癌症早筛。结合游离细胞DNA(cfDNA)和蛋白质的液体活检已经在多种组织类型的早期癌症检测中显示出潜力。然而，这些研究大多数是回顾性的，将先前诊断为癌症的个体作为案例，而健康个体作为对照。而即使对于极少数前瞻性研究，就肝细胞癌而言，现有技术中采用的标志物的预测效果也很差。在此，本发明开发了名为肝细胞癌筛查(HCC筛查)的液体活检测定法，将特定基因标志物与蛋白标志物组合，并在多中心社区人群中证明了其在慢性HBV感染的早期HCC检测中的应用价值。验证结果显示，该方法稳健地将HCC个体与非HCC个体区分开来，具有85％的灵敏度和93％的特异性。发明人进一步进行了前瞻性的研究，将这种测定法应用至肝脏超声检查和血清AFP水平正常的331位个体。识别了24例阳性案例，6-8个月的临床随访后确认4例发展为HCC。在同一时间范围的随访中，307位测试阴性个体没有诊断出HCC案例。该测定法在验证集中 显示100％灵敏度，94％特异性和17％阳性预测值。其阳性预测值(PPV)17％显著高于以前单独用AFP水平筛查所获得的结果(Chun S,Rhie SY,Ki CS,Kim JE,& Park HD(2015)Evaluation of alpha-fetoprotein as a screening marker for hepatocellular carcinoma in hepatitis prevalent areas.Annals of hepatology 14(6):882-888.)，并且高于分别采用本发明中的特定基因标志物和特定蛋白标志物而单独获得的结果。
本发明包含特定基因标志物与蛋白标志物的试剂盒已证实在非特定人群中可有效实现HCC早筛，因此可用于非特定人群的HCC早筛，更优选用于AFP阴性受试者的HCC早筛。
值得注意的是，本发明的试剂盒是用于前瞻性的早期HCC预测，4例HCC各自在诊断时都是早期(<3cm)，为后续治疗提供了良好的基础。发明人的研究证据表明，cfDNA改变和蛋白质标志物的联合检测是从无症状且HCC状态未知的社区群体识别早期HCC的可行方法。
因此，在一个方面，本发明提供了一种用于肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和蛋白标志物检测剂。
所述试剂盒还可包括数据处理系统，所述数据处理系统用于将基因标志物和/或蛋白标志物的信息转换为所述待测者的肝细胞癌筛查分数，根据所述待测者的肝细胞癌筛查分数预测待测者是否为肝癌患者。
在另一个方面，本发明提供了用于肝细胞癌早筛的方法，其包括：
(1)用基因标志物检测剂和蛋白标志物检测剂检测受试者的基因标志物和蛋白标志物；和(2)采用所述基因标志物和蛋白标志物的检测结果计算肝细胞癌筛查分数并与阈值相比较。
上述方法中，所述肝细胞癌筛查分数和阈值通过肝癌预测模型得到；所述肝癌预测模型的构建方法包括：
构建训练集，所述训练集由若干位肝癌患者和若干位肝癌高危者组成；
以训练集的基因标志物和蛋白标志物作为特征，将检测结果转化为特征分值，使用惩罚逻辑回归算法，构建肝癌预测模型，计算肝细胞癌筛查分数；
根据肝细胞癌筛查分数和样本分组信息，得到惩罚逻辑回归模型的敏感性和特异性的ROC曲线，根据ROC曲线，确定截断值，此截断值作为区分肝癌患者和肝癌高危者的阈值。
在又一个方面，本发明提供了基因标志物检测剂和蛋白标志物检测剂用于肝细胞癌早筛的用途。
在又一个方面，本发明提供了基因标志物检测剂和蛋白标志物检测剂在制备用于肝细胞癌早筛的试剂盒中的用途。
本发明的目的为进行肝癌早期筛查。
本发明首先保护一种肝癌早期筛查试剂盒，可包括肝癌突变基因的检测试剂、DCP检测试剂和AFP检测试剂。
所述“肝癌突变基因的检测试剂”可用于检测cfDNA中肝癌突变基因的突变类型和/或突变reads和/或基因拷贝数变异。
所述“肝癌突变基因”可为TP53基因和/或TERT基因和/或AXIN1基因和/或CTNNB1 基因。
所述DCP检测试剂可用于检测血浆中的DCP含量。
所述AFP检测试剂可用于检测血浆中的AFP含量。
所述试剂盒还可包括HBV是否与基因整合的检测试剂和/或cfDNA检测试剂。
所述“HBV是否与基因整合的检测试剂”可用于检测cfDNA中是否有HBV序列与人类基因组的整合位点。
所述“cfDNA检测试剂”可用于检测cfDNA浓度和/或cfDNA中不同插入片段长度的cfDNA含量所占百分比。
上述任一所述试剂盒还可包括数据处理系统；所述数据处理系统用于将待测者的肝癌基因变异信息(即11个基因突变特征的信息)、DCP含量(血浆中的DCP含量)、AFP含量(血浆中的AFP含量)、HBV是否与基因整合、cfDNA信息和临床信息转换为所述待测者的肝细胞癌筛查分数(即HCCscreen评分值)，根据所述待测者的肝细胞癌筛查分数预测待测者是否为肝癌患者。
本发明还保护上述任一所述肝癌突变基因的检测试剂、DCP检测试剂、AFP检测试剂、HBV是否与基因整合的检测试剂和cfDNA检测试剂的应用，可为A1)-A4)中的至少一种：
A1)预测待测者是否为肝癌患者；
A2)制备用于预测待测者是否为肝癌患者的试剂盒；
A3)预测肝癌；
A4)制备用于预测肝癌的试剂盒。
本发明还保护上述任一所述肝癌突变基因的检测试剂、DCP检测试剂、AFP检测试剂、HBV是否与基因整合的检测试剂、cfDNA检测试剂和数据处理系统的应用，可为A1)-A4)中的至少一种：
A1)预测待测者是否为肝癌患者；
A2)制备用于预测待测者是否为肝癌患者的试剂盒；
A3)预测肝癌；
A4)制备用于预测肝癌的试剂盒。
本发明还保护待测者的年龄，待测者的性别，待测者血浆中DCP含量，待测者血浆中AFP含量和“待测者cfDNA中肝癌突变基因的突变类型、突变reads、基因拷贝数变异、HBV是否与基因整合、cfDNA浓度、不同插入片段长度的cfDNA含量所占百分比”，作为标志物的应用，可为A1)-A4)中的至少一种：
A1)预测待测者是否为肝癌患者；
A2)制备用于预测待测者是否为肝癌患者的试剂盒；
A3)预测肝癌；
A4)制备用于预测肝癌的试剂盒。
本发明还保护预测肝癌的方法，可包括如下步骤：检测待测者血浆中DCP含量和AFP含量；检测待测者cfDNA中肝癌突变基因的突变类型、突变reads、基因拷贝数变异、HBV是否与基因整合、cfDNA浓度和不同插入片段长度的cfDNA含量所占百分比；记录待测者 的年龄和性别；将上述待测者的信息转换为肝细胞癌筛查分数(即HCCscreen评分值)，根据肝细胞癌筛查分数预测待测者是否为肝癌患者。
所述“根据肝细胞癌筛查分数预测待测者是否为肝癌患者”包括通过工作特征曲线(ROC曲线)确定诊断阈值，比较待测者的肝细胞癌筛查分数和所述诊断阈值的大小，完成待测者的肝癌预测。
待测者的HCCscreen评分值可以通过肝癌预测模型计算获得。所述肝癌预测模型为根据训练集中各个患者的特征分值和分组信息开发的惩罚逻辑回归模型。训练集由若干位肝癌患者(组成肝癌组)和若干位肝癌高危者(组成肝癌高危组)组成。在本发明的一个实施例中，训练集由65位肝癌患者和70位肝癌高危者组成。
上述任一所述HBV是否与基因整合可为：HBV与基因整合的程度、HBV是否与TERT基因整合和/或HBV是否与非TERT基因(如APOBEC4、FBX010、FUT8、WDR7、SLC7A10、GUSBP4)整合。
上述任一所述肝癌突变基因的信息包括肝癌突变基因的突变类型和/或突变reads和/或基因拷贝数变异的信息。
上述任一所述cfDNA信息可包括cfDNA浓度和/或cfDNA中不同插入片段长度的cfDNA含量所占百分比。所述cfDNA中不同插入片段长度的cfDNA含量所占百分比具体可为游离DNA片段长度小于90bp区间百分比、游离DNA片段90-140bp区间百分比、游离DNA片段141-200bp区间百分比和游离DNA片段大于200bp区间百分比。区间百分比指占所有cfDNA含量的百分比。
上述任一所述临床信息可包括年龄和/或性别。
上述任一所述肝癌突变基因的检测试剂包括提取cfDNA的试剂(如MagMAX TM Cell-Free DNA Isolation Kit)、构建cfDNA文库的试剂(如KAPA Hyper Prep试剂盒)和进行目标区域杂交捕获的试剂(如sureselect XT靶向捕获试剂盒)。
所述DCP检测试剂可为检测血浆中DCP含量的试剂。具体为：分离血浆，采用美国雅培ARCHITECT i2000SR化学发光免疫分析仪检测DCP的含量。
所述AFP检测试剂可为检测血浆中AFP含量的试剂。具体为：分离血浆，采用美国雅培IMx分析仪检测AFP的含量。
上述任一所述HBV是否与基因整合的检测试剂可包括提取cfDNA的试剂(如MagMAX TM Cell-Free DNA Isolation Kit)。
所述cfDNA检测试剂包括提取cfDNA的试剂(如MagMAX TM Cell-Free DNA Isolation Kit)。
上文中，检测(试剂盒检测)的特征具体可为实施例中的20个特征，具体如下：
一、所述“肝癌突变基因的检测试剂”用于检测的特征具体可为实施例中的11个特征，分别为TP53基因非R249S突变、TERT基因突变、AXIN1基因突变、CTNNB1基因突变、TP53R249S热点突变、CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6(即11个基因突变特征)。具体步骤如下：
1、提取待测血液样本cfDNA。
2、取所述待测血液样本cfDNA，采用KAPA Hyper Prep试剂盒构建文库，得到待测血液样本的cfDNA文库。
3、取所述待测血液样本的cfDNA文库，采用sureselect XT靶向捕获试剂盒进行目标区域杂交捕获，然后在Illumina平台进行测序。获得待测血液样本cfDNA中的肝癌突变基因的检测结果(包括突变基因和突变频率)。
4、基因突变结果注释及打分
对cfDNA中肝癌突变基因的检测结果进行注释：突变reads支持频率的注释分数。
5、取待测血液样本的cfDNA文库，进行低深度全基因组测序，然后将测序数据进行CNV检测和cfDNA片段长度检测。
6、基因拷贝数变异检测结果特征提取
对CNV检测结果进行如下处理：对各个染色体臂水平上的CNV信号(性染色体被删除以排除性别对CNV信号造成的影响)进行主成份分析(PCA)降维处理，以累积比例(cumulative proportion)≥95％为阈值，选择前6个主成份(即CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6)作为CNV相关的特征，CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6)作为CNV特征进行后续计算，每个CNV特征对应的主成份分值即为该特征的特征分值。
7、cfDNA片段长度检测
低深度全基因组测序数据可用于分析实施例中的4个特征，分别为游离DNA片段长度小于90bp区间百分比、游离DNA片段90-140bp区间百分比、游离DNA片段141-200bp区间百分比、游离DNA片段大于200bp区间百分比。
二、所述“cfDNA检测试剂”用于检测的特征具体可为cfDNA浓度。cfDNA浓度值取log2转换之后的数值作为特征分值。
三、所述“DCP检测试剂”用于检测的特征具体可为实施例中的1个特征，即血浆中的DCP含量。
四、所述“AFP检测试剂”用于检测的特征具体可为实施例中的1个特征，即血浆中的AFP含量。
五、所述“HBV是否与基因整合的检测试剂”用于检测的特征具体可为实施例中的2个特征，分别为HBV整合变异的情况和HBV与TERT是否整合变异(即2个基因突变特征)。
上文中，突变位点整合和打分：对于每个基因突变，根据突变reads支持频率给出注释分数；然后突变位点打分值被累加到不同的ROI(Region Of Interest)区间(即获得特征分值)。该区间包括4个基因(TP53，CTNNB1，TERT以及AXIN1)及一个TP53R249S热点突变位置区域。计算公式如下：
Figure PCTCN2019106064-appb-000001
其中n是与ROI重叠的突变的数量，adj_score为突变的reads支持频率。
上文中，结构性变异结果特征提取步骤如下：
(1)检测每个样品HBV整合变异的特征分值：对于检测到的每个整合突变，根据reads 支持可信度分为A、B和C三个等级(整合reads数≥10，A级；10>整合reads数>6,B级；其余的为C级，见表7中第3列)，分别对应的分值为1、0.8和0.3分，然后求和，即获得HBV整合变异的特征分值。
(2)检测每个样品HBV与TERT整合变异特征的分值：发生TERT整合，TERT整合变异的特征分值为1(无需考虑reads支持可信度评级)；不发生TERT整合，TERT整合变异的特征分值为0。
上文中，游离DNA长度相关特征提取步骤如下：计算cfDNA片段长度在四个区间(<90bp，90-140bp、141-200bp和>200bp)所占百分比，并将这些特征作为预测变量，cfDNA片段长度在四个区间所占百分比即为特征分值。
上文中，蛋白标志物相关特征提取的步骤如下：
将AFP的实际测量值按照阈值(13、20、200、400)由低到高划分为5个数值等级：0、5、8、20、30，将DCP的实际测量值按照阈值(40、60)由低到高划分为3个数值等级：0、2、5，作为两个蛋白标志物的特征分值。
此外，还可以根据临床及实验相关特征提取2个特征，临床特征包括病人的年龄、性别，也与病例表型呈一定的相关性。其中年龄的特征分值为样本的实际年龄数值；性别为男的特征分值为1，性别为女的特征分值为0。
特征可以包括如下22个特征：13个基因突变特征、2个蛋白标志物、5个cfDNA物理特征和2个血液样本的基本信息组成。13个基因突变特征分别为TP53基因非R249S突变、TERT基因突变、AXIN1基因突变、CTNNB1基因突变、TP53R249S热点突变、CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6、HBV整合变异、HBV与TERT是否整合变异。2个蛋白标志物分别为AFP和DCP。5个cfDNA物理特征分别为游离DNA片段长度小于90bp区间百分比、游离DNA片段90-140bp区间百分比、游离DNA片段141-200bp区间百分比、游离DNA片段大于200bp区间百分比和cfDNA浓度。2个血液样本的基本信息分别为性别和年龄。
癌症早期检测是降低癌症导致的死亡的最有效方式。在最近的研究中，基于cfDNA和/或蛋白质的液体活检在多种组织类型的癌症早期检测中显示出希望(Cohen JD,et al.(2018)，同上)，但没有证明对HCC有良好的预测结果，也没有证明在鉴别早期肝癌和高危人群时的效果。在本研究中，发明人开发和测试了液体活检测定法。在生物标志物的选择中，聚焦于经常改变、具有明确致癌机制的基因生物标志物，例如TERT启动子突变，以及具有明确诊断价值的蛋白质标志物，例如DCP(Lok AS,et al.(2010)Des-gamma-carboxy prothrombin and alpha-fetoprotein as biomarkers for the early detection of hepatocellular carcinoma.Gastroenterology 138(2):493-502.)。本发明包含有限数量的与HCC明确相关的候选生物标志物，为了避免在有限数量的肿瘤/正常案例中研究大量候选生物标志物时出现过度拟合效应，我们纳入了少量与HCC有明确联系的候选生物标志物。通过采用用于回顾性和/或前瞻性研究的研究工具对本发明选择的基因标志物和蛋白标志物的特定组合进行验证，发现该特定组合在回顾性和前瞻性验证中 都获得了优异的效果。
因此，在一个方面，本发明提供了一种用于AFP阴性受试者的肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和DCP检测剂。
所述试剂盒还可包括数据处理系统，所述数据处理系统用于将基因标志物和/或蛋白标志物的信息转换为所述待测者的肝细胞癌筛查分数，根据所述待测者的肝细胞癌筛查分数预测待测者是否为肝癌患者。
上述任一所述基因标志物检测剂可以包括选自以下中的一种或多种，优选三种或四种：TP53检测剂、CTNNB1检测剂、AXIN1检测剂、TERT检测剂。
上述任一所述基因标志物检测剂还可包括HBV是否与基因整合的检测试剂。
上述任一所述蛋白标志物检测剂可以包括选自以下中的一种或多种：AFP检测剂和DCP检测剂。
本发明的试剂盒可用于非特定人群的HCC早筛，也可用于特定人群如AFP阴性受试者的HCC早筛。由于AFP是日常体检如血液检测中的常见测试指标，很可能受试者的AFP状态(阴性或阳性)是已知的。因此，在一些实施方式中，本发明的试剂盒是用于特定人群如AFP阴性受试者的HCC早筛，其中所述试剂盒不包括AFP检测剂。类似地，在一些实施方式中，本发明的试剂盒是用于特定人群如DCP阴性受试者的HCC早筛，其中所述试剂盒不包括DCP检测剂。类似地，在一些实施方式中，本发明的试剂盒是用于特定人群如AFP和DCP阴性受试者的HCC早筛，其中所述试剂盒不包括AFP检测剂和DCP检测剂。因此在一些实施方式中，本发明提供了用于AFP阴性受试者的肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和蛋白标志物检测剂，优选其中所述蛋白标志物检测剂包括DCP检测剂。在一些实施方式中，本发明提供了用于DCP阴性受试者的肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和蛋白标志物检测剂，优选其中所述蛋白标志物检测剂包括AFP检测剂。在一些实施方式中，本发明提供了用于AFP和DCP阴性受试者的肝细胞癌早筛的试剂盒，其包括基因标志物检测剂。根据本发明的基因标志物检测剂可以检测基因标志物的存在和/或类型，包括突变类型和突变reads。
根据本发明的基因标志物检测剂在一些实施方式中还包括CNV检测剂。CNV检测剂通常是用于检测全基因组水平的CNV，但在一些实施方式中，也可用于检测局部水平例如基因的CNV。在一些实施方式中，本发明的试剂盒包含用于检测全局CNV水平的CNV检测剂。在一些实施方式中，本发明的试剂盒包含用于检测局部CNV水平的CNV检测剂。在一些实施方式中，本发明的试剂盒包含用于检测TERT基因的CNV水平的CNV检测剂。CNV检测剂的使用可以进一步提高HCC筛查的灵敏度和特异性。在一些实施方式中，CNV检测结果可以被转换为CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5和/或CNV降维特征6。
如本文所用，术语“基因标志物检测剂”是用于检测基因标志物的检测剂，包括本领 域技术人员所熟知的和本文所描述的。相应地，术语“TP53检测剂”、“CTNNB1检测剂”、“AXIN1检测剂”和“TERT检测剂”是用于检测各自指明的基因标志物的检测剂，包括本领域技术人员所熟知的和本文所描述的。TP53、CTNNB1、AXIN1和TERT作为本领域常见的基因标志物是本领域技术人员所熟知的，例如TERT启动子突变。在一些实施方式中，TP53的全长被检测。在一些实施方式中，TP53的一个或多个外显子被检测。本发明在一些方面的特征在于检测TP53的全长，而不仅是检测TP53的一个或多个外显子。
本领域技术人员容易认识到，本发明所指的基因在充当基因标志物时是利用其通过测序所得的全部或部分序列与其相应野生型序列之间的至少一个或多个核苷酸的差异，而不一定局限于特定位点。TP53、CTNNB1、AXIN1和TERT基因作为基因标志物时可以在全长上与其相应野生型序列之间存在至少一个或多个核苷酸的差异。TP53基因作为基因标志物时还可以在其特定热点区(例如R249S)与其相应野生型序列之间存在至少一个或多个核苷酸的差异。TERT基因作为基因标志物时还可以在其特定热点区(例如chr5:1295228C>T或chr5:1295250C>T)与其相应野生型序列之间存在至少一个或多个核苷酸的差异。
根据本发明的基因标志物检测剂在一些实施方式中还包括HBV整合检测剂。如本文所用，术语“HBV整合检测剂”是用于检测HBV是否整合在基因组中的试剂。在一些实施方式中，HBV整合在基因组中可以包括HBV整合到基因组中TERT附近，例如整合到TERT上游1.5kb内，和HBV整合到基因组中的其他地方。
在一些实施方式中，受试者的基因标志物是从受试者的cfDNA进行检测的。一般而言，在使用本文所述的基因标志物检测剂检测基因标志物时，使用过程或检测过程包括cfDNA提取和检测，由此获知与cfDNA相关的信息，包括例如cfDNA浓度和/或cfDNA中不同插入片段长度占cfDNA含量的百分比和/或cfDNA长度检测剂。因此，在一些实施方式中，本文所述的“基因标志物检测剂”及其下位概念可以同样起到cfDNA检测剂的作用，因而可与“cfDNA检测剂”互换使用。在另一些实施方式中，本发明的试剂盒还包括cfDNA检测剂。
如本文所用，术语“蛋白标志物检测剂”是用于检测蛋白标志物的检测剂，包括本领域技术人员所熟知的和本文所描述的。相应地，术语“AFP检测剂”和“DCP检测剂”是用于检测各自指明的蛋白标志物的检测剂，包括本领域技术人员所熟知的和本文所描述的。AFP和DCP作为本领域常见的蛋白标志物是本领域技术人员所熟知的。
在一些实施方式中，受试者的蛋白标志物是从受试者的血液或其组分如血清或血浆检测。在一些实施方式中，试剂盒还包括抽血用具。
本发明的试剂盒还可包括数据处理系统，或者与数据处理系统一并使用，例如数据处理系统可以包括在计算机中。所述数据处理系统用于处理根据本发明的基因标志物检测剂和/或蛋白标志物检测剂的检测结果。在一些实施方式中，数据处理系统采用所述基因标志物和蛋白标志物的检测结果计算肝细胞癌筛查分数。在一些实施方式中，数据处理系统将肝细胞癌筛查分数与阈值相比较。在一些实施方式中，数据处理系统用于估计和/或验证和/或预测HCC，优选通过将肝细胞癌筛查分数与阈值相比较。
采用该HCC筛查，本发明发现识别早期HCC个体，并将他们与患有慢性肝病包括肝硬化的非HCC个体区别开来是可能的。该测定法在超声检测肝结节和/或血清AFP升高个体的HCC诊断中显示出85％的灵敏度和93％的特异性。更重要的是，性能也在AFP/US阴性验证集中得以保持，灵敏度和特异性分别为100％和94％。当前灵敏度是基于有限数量的HCC案例。如果额外的HCC案例被识别，这可能随着对所有个体的长期随访或动态CT/MRI检测而变化。在这种情况下，根据随访时间确定灵敏度和特异性需要进行前瞻性且大规模的临床试验。然而，验证集目前的阳性预测值(PPV)17％显著高于以前用单独的AFP水平筛查所获得的(Chun S,Rhie SY,Ki CS,Kim JE,& Park HD(2015)Evaluation of alpha-fetoprotein as a screening marker for hepatocellular carcinoma in hepatitis prevalent areas.Annals of hepatology 14(6):882-888.)。
因此，在另一个方面，本发明提供了用于肝细胞癌早筛的方法，其包括：
(1)检测受试者的基因标志物和蛋白标志物；和
(2)采用所述基因标志物和蛋白标志物的检测结果计算肝细胞癌筛查分数并与阈值相比较。
如果对在第一次测试中为阳性的案例提供第二次HCC筛查，PPV可以进一步改善。高PPV对临床常规应用非常有帮助，因为它会减少非HCC个体的不必要的焦虑和随访检查。
因此，在另一个方面，本发明提供了用于肝细胞癌早筛的方法，其包括：
(1)检测受试者的基因标志物和蛋白标志物；
(2)采用所述基因标志物和蛋白标志物的检测结果计算肝细胞癌筛查分数并与阈值相比较；和
(3)如果肝细胞癌筛查分数高于阈值，则在一段时间后对所述受试者重复步骤(1)和(2)一次或多次。
在一个实施方式中，受试者的基因标志物是从受试者的cfDNA检测。即，方法包括提取受试者的cfDNA。
在一个实施方式中，受试者的蛋白标志物是从受试者的血液检测。即，方法包括抽取受试者的血液，优选血清或血浆。
如本文所用，术语“一段时间”可以是1天、2天、3天、4天、5天、6天、一周、两周、三周、一个月、两个月、三个月、四个月、五个月、六个月、七个月、八个月、九个月、十个月、十一个月、一年，且不限于此。
在一些实施方式中，用于与计算的肝细胞癌筛查分数相比较的阈值为0.1、0.2、0.3、0.4、0.5、0.6、0.7、0.8、0.9或1.0。在一个优选实施方式中，阈值是0.4。在一个优选实施方式中，阈值是0.5。
在又一个方面，本发明提供了基因标志物检测剂和蛋白标志物检测剂用于肝细胞癌早筛的用途。
在又一个方面，本发明提供了基因标志物检测剂和蛋白标志物检测剂在制备用于肝细胞癌早筛的试剂盒中的用途。
本领域技术人员理解，本文描述试剂盒时描述的特征、参数和效果等全部限定均可以 适当地结合本发明涉及方法或用途的任何其他方面。
肿瘤大小在诊断时是重要的临床参数，影响HCC患者的存活。与基于蛋白质或RNA的生物标志物不同，肿瘤细胞在大多数情况下通常仅包含一个拷贝的突变体DNA。基于cfDNA的早期检测筛查的一个基本问题是，早期肿瘤是否释放足够拷贝的突变DNA以在循环中检测。在本研究中通过HCC筛查的所有识别的HCC中，85％和68％的案例分别为<5cm和<3cm。<5cm的HCC肿瘤是早期阶段，适合于有疗效的手术。肿瘤<3cm的患者甚至可以具有更好的结果，从而强调了HCC筛查降低HCC发病率和死亡率的价值。在验证集中，本发明从AFP/US阴性群体识别4例HCC，其为2-3cm大小。这些结果清楚地显示，HCC筛查的灵敏度对于早期HCC检测具有很好的前景。
理想的肿瘤筛查方法应具有高灵敏度和特异性，它也应该易于在临床实践中执行。本HCC筛查测定法检测编码区中的突变和具有未知断点的易位/HBV整合，成本<150美元。此外，该液体活检测定法能够集中和标准化处理，并且对当地医院/诊所中的专业知识和设备要求最低。总的来说，该方法非常适合作为高危人群HCC筛查的常规试验。
本发明研究提供的证据表明，在高危人群中基于cfDNA突变和蛋白质标记物筛查在鉴定HCC患者方面具有效力。它是非侵入性的，可以检测早期以及晚期肿瘤。更重要的是，由于驱动基因中的体细胞突变在大多数癌症的发展中是常见的，因此可以修改该策略以用于从单管血液早期筛查其他肿瘤类型或多种肿瘤类型。
本发明的试剂盒还可以包含另外的治疗剂。本发明的方法还可以包括施用另外的治疗剂。在一个实施方式中，所述另外的治疗剂是本领域已知的癌症(如肝细胞癌)治疗剂。
在本申请中出现一系列列举数值的所有地方，应理解任意所列举的数值可以是数值范围的上限或下限。还应理解本发明涵盖所有这样的数值范围，即具有数值上限和数值下限的组合的一个范围，其中上限和下限各自的数值都可以是本发明中列举的任意数值。本发明提供的范围应理解为包括该范围内的所有值。例如，1-10应理解为包括值1、2、3、4、5、6、7、8、9和10中的全部，并视情况包括分数值。表达为“至多(up to)”某个值(例如至多5)的范围应理解为所有值(包括该范围的上限)，例如0、1、2、3、4和5，并视情况包括分数值。至多一周或在一周内应理解为包括0.5、1、2、3、4、5、6或7天。类似地，由“至少”限定的范围应理解为包括所提供的较低值和所有更高的值。
除非另有指出，所有百分比形式是重量/重量。
如本发明所用，“约”应理解为包括在平均值的三个标准偏差内或特定领域中的标准公差范围内。在某些实施方式中，约应理解为不超过0.5的变异。“约”修饰其后所有列举的值。例如，“约1、2、3”表示“约1”、“约2”、“约3”。
冠词“一(a)”和“一个(an)”在本发明中用以指一个或超过一个(即，至少一个)该冠词的语法客体。举例来说，“一个要素”指一个要素或超过一个要素。
术语“包括”在本发明中用以指短语“包括但不限于”并可与其互换地使用。
除非上下文另有明确指出，术语“或”在本发明中包含性地用以指术语“和/或”并可与其互换地使用。
术语“例如”在本发明中用以指短语“例如但不限于”并可与其互换地使用。
本领域技术人员应理解，上文在各个实施方式中记载的技术特征可以单独或组合地与本发明的各个方面的技术方案组合使用。
本发明的一些实施方式通过下文的非限制性实施例说明。
早期肝癌筛查标志物多为蛋白类或基因甲基化信息。本发明报告了一种新型的肝细胞癌筛查(HCC筛查)方法，该方法是基于血清蛋白标志物和cfDNA改变两者的检测，并且证实了其在应用于具有慢性HBV感染的多中心社区群体的早期HCC检测时的效用。本发明的发明人通过大量实验首次证实血浆中cfDNA的基因突变信息可用于早期HCC预测。发明人采用肝癌预测模型对待测者进行评分，通过评分值预测待测者是否为肝癌患者，从而验证了本发明基因标志物与蛋白标志物的组合的能有效的进行HCC早筛。由此可见，通过cfDNA检测对肝癌进行早期筛查、病情追踪、疗效评估、预后预测等具有重要临床意义。
附图说明
图1为研究设计方案。包括人群招募、HCC筛查模型的训练，以及在抽样的AFP/US阴性个体中的验证。
图2为详细研究设计方案。
图3为HCC筛查测定法中cfDNA的基因谱分析的设计。
图4为HCC筛查在训练集和验证集中的表现。其中，A为在训练集中，在诊断模型中，HCC筛查分数以及cfDNA和蛋白生物标志物的贡献；B为训练集中诊断模型的二元结果；C为训练集中HCC筛查的诊断模型的ROC曲线；D为验证集中诊断模型的HCC筛查表现；E为验证集中HCC筛查阳性案例的随访和诊断；F为验证集中诊断模型的二元结果；G为在AFP/US阴性个体中，HCC筛查检测到的4个HCC案例的动态CT成像。
图5为不同训练集的表现。其中A为在用没有HBV感染的健康个体作为对照的训练集中，HCC筛查诊断模型的ROC曲线；B为以HCC和非HCC个体进行训练(左图)和以HCC和健康个体进行训练(右图)。
图6为肝癌预测模型的ROC曲线。
图7为不同组群模型评分比较图。
实施发明的最佳方式
以下的实施例便于更好地理解本发明，但并不限定本发明。
下述实施例中的实验方法，如无特殊说明，均为常规方法。
下述实施例中所用的试验材料，如无特殊说明，均为自常规生化试剂商店购买得到的。
以下实施例中的定量试验，均设置三次重复实验，结果取平均值。
下述实施例中，各个肝癌患者、各个肝癌高危者和健康志愿者均对本研究的内容知情同意。
MagMAX TM Cell-Free DNA Isolation Kit为Thermo Fisher公司的产品。KAPA Hyper Prep试剂盒为KAPA公司的产品。sureselect XT靶向捕获试剂盒为安捷伦公司的产品。
下述实施例中，部分肝癌患者、肝癌高危者和健康志愿者的基本信息详见表1。
表1
编号 性别 年龄 诊断结果(CT) 肿瘤大小
HCCscreen01 男 48 肝癌 1.9cm×2.7cm
HCCscreen02 男 56 肝癌 8cm
HCCscreen03 男 75 肝癌 3cm×2cm×2cm
HCCscreen04 男 58 肝癌 5.0cm×3.0cm
HCCscreen05 女 53 肝癌 -
HCCscreen06 男 63 肝癌 4.1cm×3.2cm
HCCscreen07 男 39 肝癌 2.3cm×2cm×1.8cm
HCCscreen08 男 42 肝癌 3.8cm×3.5cm
HCCscreen09 男 56 肝癌 2.3cm×2.6cm
HCCscreen10 女 68 肝癌 4.7cm×4.2cm
HCCscreen11 男 53 肝癌 2.1cm×1.2cm
HCCscreen12 男 69 肝癌 1.2cm×1.4cm
HCCscreen13 男 69 肝癌 -
HCCscreen14 男 60 肝癌 3.2cm×2.6cm
HCCscreen15 男 54 肝癌 3.0cm×2.5cm
HCCscreen16 男 62 肝癌 3.6cm×3.8cm及1.4cm×1.8cm
HCCscreen17 男 69 肝癌 3.1cm×2.2cm
HCCscreen18 男 68 肝癌 多发，最大4.5cm×3.0cm
HCCscreen19 男 55 肝癌 -
HCCscreen20 女 70 肝癌 4.9cm×4.4cm
HCCscreen21 男 50 肝癌 多发，最大8.0cm×6.5cm，治疗后复发
HCCscreen22 男 70 肝癌 多发，最大14.7cm×13.0cm
HCCscreen23 男 41 肝癌高危 -
HCCscreen24 男 46 肝癌高危 -
HCCscreen25 女 60 肝癌高危 -
HCCscreen26 男 54 肝癌高危 -
HCCscreen27 女 56 肝癌高危 -
HCCscreen28 男 56 肝癌高危 -
HCCscreen29 男 38 肝癌高危 -
HCCscreen30 男 54 肝癌高危 -
HCCscreen31 女 64 肝癌高危 -
HCCscreen32 女 55 肝癌高危 -
HCCscreen33 女 52 肝癌高危 -
HCCscreen34 女 53 肝癌高危 -
HCCscreen35 女 44 肝癌高危 -
HCCscreen36 女 55 肝癌高危 -
HCCscreen37 女 51 肝癌高危 -
HCCscreen38 女 57 肝癌高危 -
HCCscreen39 女 66 肝癌高危 -
HCCscreen40 男 54 肝癌高危 -
HCCscreen41 男 43 肝癌高危 -
HCCscreen42 男 38 肝癌高危 -
HCCscreen43 男 48 肝癌高危 -
HCCscreen44 男 45 肝癌高危 -
HCCscreen45 男 47 肝癌高危 -
HCCscreen46 男 43 肝癌高危 -
HCCscreen47 女 47 肝癌高危 -
HCCscreen48 女 63 肝癌高危 -
HCCscreen49 女 55 肝癌高危 -
HCCscreen50 男 34 肝癌高危 -
HCCscreen51 男 32 健康志愿者 -
HCCscreen52 男 32 健康志愿者 -
HCCscreen53 男 34 健康志愿者 -
HCCscreen54 男 36 健康志愿者 -
HCCscreen55 男 28 健康志愿者 -
HCCscreen56 女 24 健康志愿者 -
HCCscreen57 男 32 健康志愿者 -
HCCscreen58 女 29 健康志愿者 -
HCCscreen59 女 32 健康志愿者 -
HCCscreen60 男 39 健康志愿者 -
HCCscreen61 男 30 健康志愿者 -
HCCscreen62 女 22 健康志愿者 -
HCCscreen63 男 29 健康志愿者 -
HCCscreen64 女 36 健康志愿者 -
HCCscreen65 女 33 健康志愿者 -
HCCscreen66 男 28 健康志愿者 -
HCCscreen67 女 24 健康志愿者 -
HCCscreen68 男 35 健康志愿者 -
HCCscreen69 女 42 健康志愿者 -
HCCscreen70 男 35 健康志愿者 -
HCCscreen71 女 20 健康志愿者 -
HCCscreen72 女 46 健康志愿者 -
HCCscreen73 男 26 健康志愿者 -
HCCscreen74 男 37 健康志愿者 -
HCCscreen75 男 30 健康志愿者 -
HCCscreen76 男 28 健康志愿者 -
HCCscreen77 女 33 健康志愿者 -
HCCscreen78 女 23 健康志愿者 -
HCCscreen79 女 29 健康志愿者 -
HCCscreen80 女 37 健康志愿者 -
HCCscreen81 女 31 健康志愿者 -
HCCscreen82 女 26 健康志愿者 -
HCCscreen83 男 26 健康志愿者 -
HCCscreen84 男 26 健康志愿者 -
HCCscreen85 女 26 健康志愿者 -
HCCscreen86 男 26 健康志愿者 -
HCCscreen87 女 27 健康志愿者 -
HCCscreen88 女 26 健康志愿者 -
HCCscreen89 男 25 健康志愿者 -
HCCscreen90 女 24 健康志愿者 -
注：“-”表示没有记录或没有检测到肿瘤；肿瘤大小为肿瘤体积、肿瘤最大直径或肿瘤最大横截面积。
伦理声明
基于社区群体进行的早期HCC筛查项目，发明人于2017年对肝癌高风险群体建立了 基于社区的队列研究(CCOP-LC队列；中国临床注册，ChiCTR-EOC-17012835)。该研究方案(NCC201709011)由国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院肿瘤医院的机构审查委员会批准。
社区群体中的早期HCC筛查项目的概况
早期HCC筛查是根据卫生部疾病预防控制中心的中国癌症早期检测和早期治疗专家委员会发布的“癌症早期诊断和早期治疗技术方案”进行(Shia YC,Beever JE，Lewin HA，& Schook LB(1991)Restriction fragment length polymorphisms at the porcine t complex polypeptide 1(TCP1)locus.Anim Genet 22(2):194.)。在所有筛查中心都建立了基于群体的癌症登记处和人口动态统计部门(Chen W,et al.(2018)Cancer incidence and mortality in China,2014.Chinese journal of cancer research＝Chung-kuo yen cheng yen chiu 30(1):1-12.)。简而言之，35-69岁的HBsAg阳性“健康”个体被邀请参加早期HCC筛查。所有参与者都进行血清AFP浓度测定和超声检查(US；Aloka ProSound SSD-4000；中国上海)，以及其他标准生物化学测试(表2)。基于血清AFP水平和肝结节检测，将个体指定为AFP/US阳性、疑似或阴性。“AFP/US阳性”个体具有以下中的任一种：1)不考虑超声检测的结节，血清AFP水平>400ng/mL；2)不考虑血清AFP浓度，超声检测到的结节≥2cm；3)超声检测到的结节≥1cm，且血清AFP≥200ng/ml。“AFP/US疑似”个体具有以下中的任一种：1)不考虑超声检测的肝结节，血清AFP水平≥20ng/ml；2)超声检测到的结节≥1cm。“AFP/US阴性”个体定义为血清AFP水平<20ng/mL，且没有超声检测到的肝脏结节。AFP/US阳性个体被转诊至高级医院(中国三级医院)进行确诊，如通过动态CT或动态MRI确定为肝癌患者的，接受基于临床实践指南的相关治疗(图1)(Omata M，et al.(2017)Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma：a 2017update.Hepatol Int 11(4):317-370.)。无确诊的个体被邀请在2个月内返回进行动态CT/MRI检测。AFP/US疑似个体被推荐在2-3个月内接受第二轮血清AFP定量检查和超声检查。
表2 AFP/US筛查和液体活检分析的参与者的一般信息
Figure PCTCN2019106064-appb-000002
Figure PCTCN2019106064-appb-000003
*总共对3255位参与者评估HBV-DNA浓度。
Figure PCTCN2019106064-appb-000004
对于所有HCC筛查参与者，除了标记
Figure PCTCN2019106064-appb-000005
的P值外，采用Chi-square tests。
Figure PCTCN2019106064-appb-000006
进行Fisher's exact tests，并与所有HCC筛查参与者比较。
参与者和研究设计
当前研究中的参与者是从中国江苏和安徽省的四个筛查中心评估个体的CCOP-LC队列获得(图1)。在AFP/US筛查期间(考虑基线，在2017年10月7日至2018年1月31日之间进行)，发明人收集了外周血(在EDTA涂布的管中，5mL)，其在收集后2小时内以4000g离心10分钟以分离血浆和血细胞。所有样品均储存在-80℃。在大多数情况下，0.5mL血浆用于测定蛋白质标志物，2mL血浆用于cfDNA提取。
在HCC筛查测定法中进一步分析176个AFP/US阳性/疑似案例。根据随访检查中的诊断结果，选择具有可靠诊断的参与者作为本研究中的训练集。为了验证发明人的发现，本发明对来自AFP/US阴性个体的331位参与者进行抽样，这些参与者的年龄与HCC筛查测定法中AFP/US阳性/疑似的人相似。从2018年5月20日到7月17日(基线抽血6-8个月后)，通过动态CT/MRI、AFP/超声检查或电话采访对331位个体进行随访。CT/MRI图像由北京中国医学科学院国家癌症中心的两名放射科医师独立评估。在此期间，本发明为在基线为AFP/US阴性并且没有进行过HCC筛查测试的个体提供额外的AFP/US测试。他们中的一些没有选择额外的AFP/US检查，他们在2018年6月30日之前的肝癌结果(ICD-10代码C22)是从筛查中心的基于群体的癌症登记处获得(图1)。在3617位AFP/US阴性个体中，1612(44.6％)位参与者能够在2018年5月20日至7月17日期间即基线筛查6-8个月后随访。其中，87位参与者接受了动态CT/MRI检查，1120位接受了AFP/US，68位通过电话采访。337位参与者的肝癌结果获自当地基于群体的癌症登记处(图2)。其他2005位参与者的HCC状态在2018年6月30日之前无法获得(图2)。
从进行年度体检并且报告没有任何HBV感染的人群中获得70位健康对照者。当献血时，所有人都被确认为HBsAg阴性。
血清DCP浓度的测定
根据生产商的说明书(Abbott Laboratories；Chicago，IL，USA)，使用商业化试剂盒在Abbott ARCHITECT i2000SR化学发光免疫分析仪(CLIA)中测定血清DCP水平。
cfDNA改变的谱分析
发明人设计了试验来测序cfDNA以谱分析：1)TP53、CTNNB1、AXIN1的编码区和TERT的启动子区(表3)；2)HBV整合。简而言之，首先将cfDNA片段连接至具有随机DNA条形码的接头(adaptor)(图3)。连接的构建体通过10个反应循环扩增以产生全基因组文库，含有数百个冗余构建体，其具有识别每个原始cfDNA片段的独特DNA条形码。扩增的文库足以进行5-10次独立的测序分析。靶区域是在使用靶特异性引物(TS引物1)和匹配接合体序列的引物(Perera BP & Kim J(2016)Next-generation sequencing-based5'rapid amplification of cDNA ends for alternative promoters.Analytical biochemistry 494:82-84；Zheng Z,et al.(2014)Anchored multiplex PCR for targeted next-generation sequencing.Nature medicine 20(12):1479-1484.)(图3)的PCR的9个循环中与DNA条形码一起扩增。使用匹配接头和靶区域的一对巢式引物(TS引物2)进行第二轮15个循环的PCR，以进一步富集靶区域并加上Illumina测序接头(图3)。在该基于PCR的测定法中观察到有效富集，>80％的reads映射到<10Kb的小靶区域。采用该测定法，本发明可以覆盖靶区域>100,000次，3Gb测序数据，使得5,000拷贝的原始cfDNA的20×冗余测序成为可能。在DNA条形码连接到原始cfDNA分子的情况下，可以跟踪来自原始cfDNA分子的冗余reads，以最小化在PCR扩增和平行突变测序中固有的调用错误(calling error)(Kinde I,Wu J,Papadopoulos N,Kinzler KW,& Vogelstein B(2011)Detection and quantification of rare mutations with massively parallel sequencing.Proceedings of the National Academy of Sciences of the United States of America108(23):9530-9535；Chaudhuri AA,et al.(2017)Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling.Cancer discovery 7(12):1394-1403.)。本发明用数字PCR检查了这次测定法检测到的11个突变，并用0.03-0.16％的突变分数验证了所有这些突变。
表3 HCC筛查特征及其系数的特性
Figure PCTCN2019106064-appb-000007
Figure PCTCN2019106064-appb-000008
惩罚逻辑回归：λ＝0.14；α＝0。
数据处理和变异检测
测序reads通过处理提取标签并移除序列接头。随后使用Trimmomatic(v0.36)去除残留接头和低质量区域。使用具有默认参数的‘bwa(v0.7.10)mem’(Li H & Durbin R(2010)Fast and accurate long-read alignment with Burrows-Wheeler transform.Bioinformatics 26(5):589-595.)将清洁的reads映射到hg19和HBV基因组。使用samtools mpileup(Li H,et al.(2009)The Sequence Alignment/Map format and SAMtools.Bioinformatics 25(16):2078-2079.)在感兴趣的靶区域中鉴定由SNP和INDEL组成的候选体突变。为了确保准确性，具有相同标签以及开始和结束坐标的reads被分组至唯一标识符(Unique Identifier)家族(UID家族)。含有至少两个reads且其中至少80％的reads的类型相同的UID家族被定义为有效唯一标识符(Effective Unique Identifier)家族(EUID家族)。通过将替代性EUID家族的数量除以替代性和参比者的总和来计算每个突变频率。在IGV中进一步手动检查突变。用Ensembl Variant Effect Predictor(VEP)注释候选变体(Wang J,et al.(2011)CREST maps somatic structural variation in cancer genomes with base-pair resolution.Nat Methods 8(8):652-654)。使用Crest鉴定HBV整合(McLaren W,et al.(2016)The Ensembl Variant Effect Predictor.Genome biology 17(1):122.)，并且需要至少4个软截断序列支持(soft-clip reads supports)。
模型构建
1、特征映射和数据预处理
1)突变注释和评分：
突变频率(支持候选突变的reads的分数)与血液中循环肿瘤DNA的总量以及肿瘤大小高度地成比例。因此，本发明用其reads支持频率注释所有输入突变。
2)突变的分解
通过将突变分解成基因水平或聚焦区域来提取多种基因特征。对于每个感兴趣的区域(ROI)，ROI得分通过计算得出。
Figure PCTCN2019106064-appb-000009
其中n是与ROI重叠的突变的数量，adj_score为突变的reads支持频率。
3)蛋白质和实验标志物
在本发明的模型中使用两种蛋白质标志物DCP和AFP，因为它们已经在之前的研究中显示为HCC诊断的非常强的指标(Chen H,et al.(2018)Direct comparison of five serum biomarkers in early diagnosis of hepatocellular carcinoma.Cancer management and research 10:1947-1958.)。这些值被分等级到多个数值分类中。cfDNA浓度也包括在本发明的模型特征列表中。
4)作为特征的临床信息
患者的年龄和性别也构成本发明的预测器的一部分，因为已经证明HCC诊断的可能性在某种程度上与个体的年龄和性别有关。
2、特征选择
RandomForest用于从候选特征中筛选有用变量；发明人通过使无偏包外误差估计(unbiased out-of-bag error estimation)最小化来应用后向变量减法(backward variables subtraction)，每次运行消除一个特征。然后将蛋白质、基因标志物以及临床信息优化为构建二元分类器的最终特征。在HCC相比于健康个体的训练中，仅使用ctDNA SNP/indel突变和蛋白质标志物。不包括HBV-TERT融合或其他HBV整合，因为健康组没有HBV感染。
3、模型和参数优化
惩罚逻辑回归模型通过包含65个HCC和70个非HCC的135个样品的训练集构建。通过曲线下面积(AUC)统计，在训练和验证数据集两者上评估模型性能。模型的灵敏度和特异性还使用优化的截断值0.4来确定。使用Youden指数用于该截断值的优化。为了分别对基因、蛋白质和CNV水平进行聚类分析，还给出了使用惩罚逻辑回归的每个特征的交叉验证系数。该模型在R包‘glmnet’(R版本3.5.1)中启动，惩罚参数α在训练数据集内通过10倍交叉验证进行优化，优化的值为0。
统计分析
本发明使用以ctDNA突变、蛋白质生物标志物水平以及临床特征作为变量的惩罚逻辑回归模型。发明人在AFP/US阳性和AFP/US疑似个体中定义了具有动态CT/MRI和/或组织学的HCC案例和非HCC案例(图1)。通过对65例HCC和70例非HCC的训练数据集进行100次迭代的LOOCV(Leave-One-Out Cross Validation，留一交叉验证)，计算了HCC筛查测定法的灵敏度和特异性。
实施例1、四个筛查中心中在基线的参与者的临床参数以及肝细胞癌(HCC)结果的随访
在四个筛查中心通过血液乙肝病毒表面抗原(HBsAg)测试对社区个体(n＝72720)进行筛查，并随后进行问卷调查。邀请HBsAg阳性个体(n＝3793)参加AFP/US筛查。在这些HBsAg阳性个体中，176位具有有关的AFP/US结果(命名为AFP/US阳性/疑似组)，而其余HBsAg阳性患者组成AFP/US阴性组(n＝3617)(图1和表3)。为了确定他们的HCC状态，推荐所有AFP/US阳性/疑似个体在首次筛查的2个月内进行动态CT/MRI检测。将具有HCC状态的可靠诊断的患者纳入本研究的训练集，并且对从这些个体获得的基线AFP/US血液样本进行HCC筛查测试(图1)。
在这3617位AFP/US阴性个体中，约60％曾在这项研究的基线筛查前进行了AFP/US筛查(图2和表3)。为减少随访程序中的焦虑和不依从性，本发明主要选择在过去的1-3年中已经进行过AFP/US筛查的个体作为验证集(n＝331)。基于性别、US检测到的肝硬化的比例和血清白蛋白水平，抽样的AFP/US阴性参与者的分布与所有HBsAg阳性参与者类似(图2和表3)。本发明对在基线AFP/US筛查从验证集收集的血样进行HCC液体活检测试(HCC筛查)，并且在基线筛查6-8个月后对HCC状态进行随访。本发明还对没有HBV感染的70位健康个体进行了HCC筛查。
实施例2、采用HCC筛查的HCC标志物的选择和检测
本发明用两类生物标志物开发HCC筛查测定法：1)在HCC中非常普遍，并且可以在cfDNA中检测的基因改变；和2)血清蛋白标志物-甲胎蛋白(AFP)和脱-γ-羧基凝血酶原(DCP)。在以前的癌症基因组研究中，大多数HBV相关HCC携带至少以下基因/位置的一个突变：TP53，CTNNB1，AXIN1或TERT启动子(Totoki Y,et al.(2014)Trans-ancestry mutational landscape of hepatocellular carcinoma genomes.Nature genetics46(12):1267-1273；Zhang W,et al.(2017)Genetic Features of Aflatoxin-associated Hepatocellular Carcinomas.Gastroenterology.)。本发明还考虑HBV整合断点作为HCC的潜在生物标志物。由于HBV整合位点应该在每个个体细胞中是独一无二的，从血浆(2-3ml)检测到多个拷贝(>2)的特定整合位点可以指示携带HBV整合的单个细胞的克隆扩增。只有在这种情况下，由此产生的肿瘤才会向血液中释放同一基因组DNA的多个拷贝。本发明设计了可以平行谱分析(profile)基因变化的测定法。所提取的cfDNA被连接到具有DNA条形码的定制接头，然后被扩增生成全基因组文库。发明人用与cDNA末端快速扩增(RACE)类似的方法，使用覆盖TP53、CTNNB1和AXIN1的编码区、TERT的启动子区和HBV序列的多个引物，富集具有点突变和HBV整合的靶标(图3)(Chaudhuri AA,et al.(2017)Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling.Cancer discovery 7(12):1394-1403；Waltari E,et al.(2018)5'Rapid Amplification of cDNA Ends and Illumina MiSeq Reveals B Cell Receptor Features in Healthy Adults,Adults With Chronic HIV-1Infection,Cord Blood,and Humanized Mice.Frontiers in immunology 9:628.)。二代测序的reads可以通过DNA条形码追踪到原始cfDNA分子，从而从测序/扩增错误中过滤假阳性单核苷酸变异(SNV)(Kinde I,Wu J,Papadopoulos N,Kinzler KW,&Vogelstein B(2011)Detection and quantification of rare mutations with massively parallel sequencing.Proceedings of the National Academy of Sciences of the United States of America 108(23):9530-9535.)。
基于发明人之前的发现和其他受HCC、肝硬化和慢性肝炎影响的住院患者的报告，AFP和DCP的血清蛋白水平的组合在区别早期HCC和失代偿性肝硬化方面表现出显著的灵敏性和特异性(Chen H,et al.(2018)Direct comparison of five serum biomarkers in early diagnosis of hepatocellular carcinoma.Cancer management and research10:1947-1958.)。因此，本发明将这两种血清蛋白标志物与cfDNA的改变进行组合，以研究这种基于液体活检的测定法(包括AFP、DCP和cfDNA)能否有效筛查早期HCC。
实施例3、用HCC筛查测定法进行的临床诊断的一致性
为了确定其在HCC检测中的效用，本发明对已知诊断为HCC或已经排除(非HCC)的个体中进行了HCC筛查。从AFP/US阳性/疑似个体中获得了65例HCC和70例非HCC。该HCC阳性或HCC阴性状态是基于动态CT/MRI成像和组织学确认。将这135例案例用作训练集，并将HCC筛查结果与临床诊断进行比较。为了在测定法中建立整合不同类型的生物标志物的分类器，本发明首先针对每个基因或基因座将不同类型的cfDNA突变分解(collapse)成感兴趣区域(region of interest，ROI)分数。ROI分数是ROI内每个点突变的破坏效 应和频率的加权和。除了基因中SNV/indel突变的ROI分数外，本发明还增加了两个结构变体特征(在TERT启动子区域中的HBV整合和其他HBV整合)、一个实验特征(cfDNA浓度)、两个蛋白标志物(AFP和DCP)以及两个临床特征(年龄和性别)作为构建诊断分类器以预测HCC状态的最终特征(表2)。用这些标志物使用惩罚逻辑回归算法，HCC筛查模型较好地区分HCC案例和非HCC案例(图4中A)。通过对65例HCC和70例非HCC的训练数据集进行了100次重复的留一交叉验证(leave-one-out cross validation)，发现该测定法在HCC诊断具有85％的灵敏度和93％的特异性(曲线下面积＝0.928)(图4中B和4中C)。HCC筛查分数截断值对于最高Youden指数得分为0.4(图5中B和表4)。cfDNA和蛋白标志物两者对HCC识别均有显著贡献(图4中C和表5)。
表4 特征和HCC筛查分数
Figure PCTCN2019106064-appb-000010
Figure PCTCN2019106064-appb-000011
Figure PCTCN2019106064-appb-000012
Figure PCTCN2019106064-appb-000013
Figure PCTCN2019106064-appb-000014
Figure PCTCN2019106064-appb-000015
Figure PCTCN2019106064-appb-000016
Figure PCTCN2019106064-appb-000017
Figure PCTCN2019106064-appb-000018
Figure PCTCN2019106064-appb-000019
Figure PCTCN2019106064-appb-000020
Figure PCTCN2019106064-appb-000021
表5 突变信息
Figure PCTCN2019106064-appb-000022
Figure PCTCN2019106064-appb-000023
Figure PCTCN2019106064-appb-000024
Figure PCTCN2019106064-appb-000025
Figure PCTCN2019106064-appb-000026
Figure PCTCN2019106064-appb-000027
Figure PCTCN2019106064-appb-000028
Figure PCTCN2019106064-appb-000029
Figure PCTCN2019106064-appb-000030
Figure PCTCN2019106064-appb-000031
Figure PCTCN2019106064-appb-000032
Figure PCTCN2019106064-appb-000033
*：T代表真实突变；S代表疑似突变。
实施例4、HCC筛查测定法对AFP/US阴性个体早期HCC的预测值
本发明进一步测试了HCC筛查是否可以从AFP/US阴性并且无临床症状表现的HBsAg阳性个体检测HCC。用HCC筛查测试了331位AFP/US阴性个体，并基于从训练集得到的算法识别24例阳性案例(称为HCC筛查阳性)(图4中D)。
对24位HCC筛查阳性个体进行了6-8个月随访以获得HCC临床结果。在这些个体中，对17位进行动态CT检查，对4位进行AFP/US检查，对3位通过电话采访进行随访。24位HCC筛查阳性个体中有4位最终被诊断为HCC，HCC检测的阳性预测值为17％(图4中E)。另外，一组HCC筛查阴性参与者(n＝70)同意在6-8个月进行动态CT检查，没有人被诊断为HCC。本发明还在基线AFP/US筛查6-8个月后通过AFP/US追踪了172位HCC筛查阴性参与者，没有诊断到HCC案例。在通过电话采访进行随访的65位参与者中，没有发现HCC患者(图2)。总的来说，在这些HCC筛查阴性案例中没有发现HCC案例。综合起来，HCC筛查测定法在AFP/US阴性个体中产生了17％的阳性预测值，100％(4/4)的灵敏度，和94％的特异性(307/327)(图4中F)。在通过动态CT诊断时，识别的所有4个HCC患者肿瘤大小均<3cm(图4中G)，并且根据基线时的US结果，这4位患者没有肝硬化。
本发明在基线检测后6-8个月内向在基线检测时为AFP/US-阴性并且没有进行HCC筛查测试的944位参与者提供AFP/US检查。检测到并进一步确认四例HCC案例(0.4％，4/944)。癌症登记记录显示在2018年6月30日之前在这337位参与者中没有识别到肝癌结果(ICD-10代码C22)，这些参与者在基线筛查中为AFP/US阴性并且没有进行HCC筛查或任何进一步的AFP/US筛查(图2)。
在基线第一次抽血6-8个月后，对24位HCC筛查阳性案例中的13位进行第二次抽血以重复进行HCC筛查测定法。其中一个HCC案例继续为阳性，并且平分比6个月前高。另一个HCC案例在第二次抽血之前已经手术切除肿瘤，HCC筛查显示阴性，与该状态一致。11个HCC筛查阳性的非HCC案例中有7个(64％)在第二次HCC筛查测试中为阴性，尽管其中两个筛查结果接近阈值(0.40)。其余4个非HCC案例在第二次HCC筛查中仍为阳性(图4中E)。这些结果表明，阳性预测值可以通过在第二个时间点重复测试而进一步改进。目前对这些案例都进行随访以进一步验证该测定法。
实施例5、用健康个体训练液体活检测定法
HCC筛查测定法在高风险群体中显示出强大的HCC识别能力。以前的研究预测，在这样的高危人群中，灵敏度和特异性会低于癌症患者与无HBV感染或其他风险因素的健康个体的比较。为了测试这个假设，本发明对70位没有HBV感染的健康个体(HBsAg阴性)进行了HCC筛查，并使用这些数据代替训练集中的70个HBsAg阳性非HCC案例。通过对cfDNA和蛋白标志物的分析，HCC筛查测定法从健康个体有效地识别HCC案例，其灵敏度为98％特异性为100％(图5中A)。然而，从这个训练集(HCC和健康个体)得到的算法在HBsAg阳性非HCC案例中表现不佳。根据该算法，大多数非HCC案例被归类为阳性，而HCC和非HCC案例高度重叠(图5中B)。此外，对验证集的表现不佳。虽然在测试中所有四个HCC案例为阳性，但HBsAg(+)个体中的许多被归类为阳性，产生的特异性和阳性预测值分别只有58％和2.8％(图5中B)。另一方面，除了其在HBsAg阳性验证集中的表现以外，从HCC与非HCC的案例得到的算法正确地将所有健康个体(100％)归类为阴性(图5中B)。
实施例6、进一步包括CNV的液体活检测定法
一、血液样本的获得
肝癌患者血液样本由已通过临床鉴定为肝癌的65位肝癌患者提供。
肝癌高危者血液样本由采用文献(Omata,M.,et al.,Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma:a 2017 update.Hepatol Int,2017.11(4):p.317-370.)中提供的方法鉴定为肝癌高危的70位肝癌高危者提供。
健康人血液样本由100位健康志愿者提供。
二、待测血液样本cfDNA中肝癌突变基因的检测和CNV检测
待测血液样本为65个肝癌患者血液样本、70个肝癌高危者血液样本和100个健康人血液样本。
1、采用MagMAX TM Cell-Free DNA Isolation Kit分别提取待测血液样本cfDNA。
2、完成步骤1后，采用液相杂交捕获技术检测待测血液样本cfDNA中的肝癌突变基因信息，例如TP53基因、AXIN1基因、CTNNB1基因、TERT基因的启动子、B型HBV和C型HBV的突变信息。具体步骤为：
(1)取所述待测血液样本cfDNA，采用KAPA Hyper Prep试剂盒构建文库，得到待测血液样本的cfDNA文库。
(2)完成步骤(1)后，取所述待测血液样本的cfDNA文库，采用sureselect XT靶向捕获试剂盒进行目标区域杂交捕获，然后在Illumina平台进行测序，测序深度20000×。检测的基因或病毒的版本、染色体、起始位置、终止位置和覆盖区域详见表6。
表6
基因或病毒 版本 染色体 起始位置 终止位置 覆盖区域
TP53基因 HG19 17 7572927 7579884 TP53基因外显子全长
AXIN1基因 HG19 16 338122 397000 AXIN1基因外显子全长
CTNNB1基因 HG19 3 41265560 41281237 CTNNB1基因外显子全长
TERT基因 HG19 5 1295228 1295250 TERT基因启动子的第228位和第250位
C型HBV AF533983 1 1 3215 C型HBV基因组的全长
B型HBV AB602818 1 1 3215 B型HBV基因组的全长
部分待测血液样本cfDNA中的肝癌突变基因的检测结果见表7中第2列和第4列。
表7
Figure PCTCN2019106064-appb-000034
Figure PCTCN2019106064-appb-000035
Figure PCTCN2019106064-appb-000036
注：“-”表示没有检测到突变，“--”表示没有检测到整合。
3、取步骤2中(1)制备的待测血液样本的cfDNA文库，进行低深度全基因组测序，然后将测序数据(约3G)进行CNV检测。
三、检测血浆中AFP含量
待测血液样本为65个肝癌患者血液样本、70个肝癌高危者血液样本和100个健康人血液样本。
1、取待测血液样本，在采血管中上下颠倒混匀10次，4℃、2000g离心10min，然后将上层血浆转移至离心管(规格为1.5mL)，4℃、16000g离心10min，收集上清(即血浆)。
2、完成步骤1后，取所述血浆，采用美国雅培IMx分析仪检测AFP的含量。
部分待测血液样本血浆中的AFP含量的检测结果见表8中第2列。
表8
编号 AFP(ng/mL) DCP(mAU/mL) 编号 AFP(ng/mL) DCP(mAU/mL)
HCCscreen01 6.5 178 HCCscreen46 107.99 27.52
HCCscreen02 97.09 98 HCCscreen47 28.96 19.74
HCCscreen03 12 265 HCCscreen48 22.6 28.38
HCCscreen04 238.7 38.59 HCCscreen49 95.88 17.92
HCCscreen05 1210 22.71 HCCscreen50 25.2 33.21
HCCscreen06 5.37 19.14 HCCscreen51 2.55 25.95
HCCscreen07 2136.1 18.58 HCCscreen52 1.24 22.73
HCCscreen08 1380.46 50.14 HCCscreen53 2.7 31.31
HCCscreen09 1843.39 23.06 HCCscreen54 4.51 20.76
HCCscreen10 2.3 180.03 HCCscreen55 3.27 34.29
HCCscreen11 2.06 12.87 HCCscreen56 1.67 16.64
HCCscreen12 1.79 11.39 HCCscreen57 2.42 25.03
HCCscreen13 3338.52 >30000 HCCscreen58 3.09 28.6
HCCscreen14 1.92 72.66 HCCscreen59 4.87 19.58
HCCscreen15 1.71 81.47 HCCscreen60 3.12 17.63
HCCscreen16 1811.25 304.45 HCCscreen61 1.04 25.33
HCCscreen17 6.55 20.84 HCCscreen62 0.973 21.49
HCCscreen18 26.22 188.95 HCCscreen63 1.29 22.82
HCCscreen19 7.66 423.93 HCCscreen64 2 15.77
HCCscreen20 130.95 148.62 HCCscreen65 2.05 18.97
HCCscreen21 14.48 2464.26 HCCscreen66 2.5 22.13
HCCscreen22 199.35 342.12 HCCscreen67 1.04 37.64
HCCscreen23 117.1 26.67 HCCscreen68 - -
HCCscreen24 21.27 27.75 HCCscreen69 - -
HCCscreen25 49.62 13.24 HCCscreen70 - 20.63
HCCscreen26 28.34 39.51 HCCscreen71 1.49 26.29
HCCscreen27 31.64 15.49 HCCscreen72 1.54 15.4
HCCscreen28 37.33 21.09 HCCscreen73 2.29 19.8
HCCscreen29 33.02 27.5 HCCscreen74 4.02 14.7
HCCscreen30 108.3 39.45 HCCscreen75 1.45 29.64
HCCscreen31 32.24 33.92 HCCscreen76 2.11 26.1
HCCscreen32 119.9 21.06 HCCscreen77 4.52 15.12
HCCscreen33 1.86 10.37 HCCscreen78 3.69 18.49
HCCscreen34 4.81 9.19 HCCscreen79 2.65 32.78
HCCscreen35 1 18.34 HCCscreen80 5.47 25.68
HCCscreen36 2.7 11.44 HCCscreen81 2.21 17.95
HCCscreen37 309.58 11.02 HCCscreen82 2.33 21.52
HCCscreen38 7.78 17.99 HCCscreen83 2.41 27.08
HCCscreen39 4.33 14.69 HCCscreen84 2.77 23.78
HCCscreen40 24.7 25.07 HCCscreen85 3.6 17.76
HCCscreen41 35.87 21.34 HCCscreen86 6.55 30.78
HCCscreen42 770.97 23.32 HCCscreen87 2.76 24.36
HCCscreen43 21.85 19.83 HCCscreen88 3.12 35.14
HCCscreen44 43.84 17.12 HCCscreen89 2.86 38.26
HCCscreen45 32.66 24.85 HCCscreen90 3.46 22.29
四、检测血浆中DCP含量
待测血液样本为65个肝癌患者血液样本、70个肝癌高危者血液样本和100个健康人血液样本。
1、取待测血液样本，在采血管中上下颠倒混匀10次，4℃、2000g离心10min，然后将上层血浆转移至离心管(规格为1.5mL)，4℃、16000g离心10min，收集上清(即血浆)。
2、完成步骤1后，取所述血浆，采用美国雅培ARCHITECT i2000SR化学发光免疫分析仪检测DCP的含量。
部分待测血液样本血浆中的DCP含量的检测结果见表8中第3列。
五、数据处理和22个特征分值的获得
1、基因突变结果注释及打分
对步骤二cfDNA中肝癌突变基因的检测结果进行注释：突变reads支持频率的注释分数。突变reads支持在很大程度上反映了组织中变异细胞的百分比，因此它是一个很重要的表型相关因素。
2、突变位点整合和打分
对于每个基因突变，根据突变reads支持频率给出注释分数；然后突变位点打分值被累加到不同的ROI(Region Of Interest)区间(即获得特征分值)。该区间包括4个基因(TP53，CTNNB1，TERT以及AXIN1)及一个TP53R249S热点突变位置区域。计算公式如下：
Figure PCTCN2019106064-appb-000037
其中n是与ROI重叠的突变的数量，adj_score为突变的reads支持频率。
3、结构性变异结果特征提取
(1)检测每个样品HBV与TERT整合变异特征的分值：发生TERT整合，TERT整合变异的特征分值为1；不发生TERT整合，TERT整合变异的特征分值为0。
(2)检测每个样品HBV整合变异的特征分值：对于检测到的每个整合突变，根据reads支持可信度分为A、B和C三个等级(整合reads数≥10，A级；10>整合reads数>6，B级；其余的为C级，见表7中第3列)，分别对应的分值为1、0.8和0.3分，然后求和，即获得HBV整合变异的特征分值。
4、基因拷贝数变异检测结果特征提取
对步骤二中CNV检测结果进行如下处理：对各个臂水平上的共44个CNV信号(性染色体被删除以排除性别对CNV信号造成的影响)分数进行了PCA降维处理，通过R2值选择前6个主成份(即CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6)作为CNV相关的特征，CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6的R2值即为特征分值。
5、游离DNA长度相关特征提取
本发明的发明人计算了cfDNA片段长度在四个区间(<90bp、90-140bp、141-200bp和>200bp)所占百分比，并将这些特征作为预测变量，cfDNA片段长度在四个区间所占百分比即为特征分值。
6、蛋白标志物相关特征提取
将AFP的实际测量值按照阈值(13、20、200、400)由低到高划分为5个数值等级：0、5、8、20、30，将DCP的实际测量值按照阈值(40、60)由低到高划分为3个数值等级：0、2、5，作为两个蛋白标志物的特征分值。
7、临床及实验相关特征提取
临床特征包括病人的年龄、性别，以及cfDNA浓度(cfDNA含量/血浆体积)也与病例表型呈一定的相关性，被纳入模型。其中cfDNA浓度值取log2转换之后的数值作为特征分值；年龄的特征分值为样本的实际年龄数值；性别为男的特征分值为1，性别为女的特征分值为0。
综上所述，22个特征由13个基因突变特征、2个蛋白标志物、5个cfDNA物理特征和2个血液样本的基本信息组成。13个基因突变特征分别为TP53基因突变、TERT基因突变、AXIN1基因突变、CTNNB1基因突变、TP53R249S热点位置区域、CNV降维特征1、CNV降维特征2、CNV降维特征3、CNV降维特征4、CNV降维特征5、CNV降维特征6、HBV与TERT整合变异、HBV与非TERT整合变异。2个蛋白标志物分别为AFP和DCP。5个cfDNA物理特征分别为游离DNA片段长度小于90bp区间百分比、游离DNA片段90-140bp区间百分比、游离DNA片段141-200bp区间百分比、游离DNA片段大于200bp区间百分比和cfDNA浓度。2个血液样本的基本信息分别为性别和年龄。
六、肝癌预测
1、按照步骤一至五的方法，获得待测者22个特征的特征分值；
2、以步骤1获得的特征分值为参数，使用惩罚逻辑回归算法对包括65个HCC和70个肝癌高危者的135个样品组成的训练集数据进行模型构建，计算HCCscreen评分值。为了分别对基因、蛋白质和CNV水平进行聚类分析，还给出了使用惩罚逻辑回归的每个特征的交叉验证系数。该模型在R包‘glmnet’(R版本3.5.1)中启动，惩罚参数α在训练数据集内通过10倍交叉验证进行优化，优化的值为0。随后通过HCCScreen评分值及样本分组(癌或非癌)信息绘制ROC曲线(receiver operating characteristic curve)。取约登指数(Youden’s index)最大时对应的HCCScreen评分值作为阈值。该模型中，选择0.4作为模型最佳的cut-off值。
当HCCScreen>0.4时，判读为肝癌，否则判读为非肝癌。
七、肝癌预测模型有效性的验证
分别以肝癌组(由65位肝癌患者组成)、肝癌高危组(由70位肝癌高危者组成)和健康组(由100位健康志愿者组成)为样本，对步骤七中肝癌预测模型预后方法有效性进行验证。
结果见图7。结果表明，肝癌预测模型可以预测待测者是否为肝癌患者。
工业应用
本发明的发明人通过大量实验首次证实血浆中cfDNA的基因突变信息可用于早期HCC预测。发明人通过采用肝癌预测模型对待测者进行评分，通过评分值预测待测者是否为肝癌患者，而验证了本发明的基因标志物与蛋白标志物的组合的有效HCC早筛效果。由此可见，通过cfDNA检测对肝癌进行早期筛查、病情追踪、疗效评估、预后预测等具有重要临床意义。

Claims (19)

  1. 一种用于肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和/或蛋白标志物检测剂。
  2. 一种用于AFP阴性受试者的肝细胞癌早筛的试剂盒，其包括基因标志物检测剂和DCP检测剂。
  3. 权利要求1或2所述的试剂盒，其特征在于，所述试剂盒还包括数据处理系统，所述数据处理系统用于将基因标志物和/或蛋白标志物的信息转换为所述待测者的肝细胞癌筛查分数，根据所述待测者的肝细胞癌筛查分数预测待测者是否为肝癌患者。
  4. 一种用于肝细胞癌早筛的方法，其包括：
    (1)用基因标志物检测剂和蛋白标志物检测剂检测受试者的基因标志物和蛋白标志物；和
    (2)采用所述基因标志物和蛋白标志物的检测结果计算肝细胞癌筛查分数并与阈值相比较。
  5. 根据权利要求4所述的方法，其特征在于，所述肝细胞癌筛查分数和阈值通过肝癌预测模型得到；
    所述肝癌预测模型的构建方法包括：
    构建训练集，所述训练集由若干位肝癌患者和若干位肝癌高危者组成；
    以训练集的基因标志物和蛋白标志物作为特征，将检测结果转化为特征分值，使用惩罚逻辑回归算法，构建肝癌预测模型，计算肝细胞癌筛查分数；
    根据肝细胞癌筛查分数和样本分组信息，得到惩罚逻辑回归模型的敏感性和特异性的ROC曲线，根据ROC曲线，确定截断值，此截断值作为区分肝癌患者和肝癌高危者的阈值。
  6. 基因标志物检测剂和蛋白标志物检测剂用于肝细胞癌早筛的用途。
  7. 基因标志物检测剂和蛋白标志物检测剂在制备用于肝细胞癌早筛的试剂盒中的用途。
  8. 根据权利要求1-7中任一项所述的试剂盒、方法或用途，其中所述基因标志物检测剂可以包括选自以下中的一种或多种，优选三种或四种：TP53检测剂、CTNNB1检测剂、AXIN1检测剂和TERT检测剂。
  9. 根据权利要求1-8中任一项所述的试剂盒、方法或用途，其中所述蛋白标志物检测剂可以包括选自以下中的一种或多种：AFP检测剂和DCP检测剂。
  10. 根据权利要求1-9中任一项所述的试剂盒、方法或用途，其中所述基因标志物检测剂还包括HBV整合检测剂。
  11. 根据权利要求1-10中任一项所述的试剂盒、方法或用途，其中所述基因标志物检测剂还包括CNV检测剂。
  12. 根据权利要求1-11中任一项所述的试剂盒、方法或用途，其中所述基因标志物检测剂还包括HBV是否与基因整合的检测试剂。
  13. 根据权利要求1-12中任一项所述的试剂盒、方法或用途，其中所述基因标志物检测剂还包括cfDNA浓度和/或cfDNA长度检测剂。
  14. 一种肝癌早期筛查试剂盒，包括肝癌突变基因的检测试剂、DCP检测试剂和AFP检测试剂。
  15. 如权利要求14所述的试剂盒，其特征在于：所述试剂盒还包括HBV是否与基因整合的检测试剂和/或cfDNA检测试剂。
  16. 如权利要求1、2、3、8、9、10、11、12、13、14或15所述的试剂盒，其特征在于：所述试剂盒还包括数据处理系统，所述数据处理系统用于将待测者的肝癌基因变异信息、DCP含量、AFP含量、HBV是否与基因整合、cfDNA信息和临床信息转换为所述待测者的肝细胞癌筛查分数，根据所述待测者的肝细胞癌筛查分数预测待测者是否为肝癌患者。
  17. 肝癌突变基因的检测试剂、DCP检测试剂、AFP检测试剂、HBV是否与基因整合的检测试剂和cfDNA检测试剂的应用，为A1)-A4)中的至少一种：
    A1)预测待测者是否为肝癌患者；
    A2)制备用于预测待测者是否为肝癌患者的试剂盒；
    A3)预测肝癌；
    A4)制备用于预测肝癌的试剂盒。
  18. 待测者的年龄，待测者的性别，待测者血浆中DCP含量，待测者血浆中AFP含量和“待测者cfDNA中肝癌突变基因的突变类型、突变reads、基因拷贝数变异、HBV是否与基因整合、cfDNA浓度、不同插入片段长度的cfDNA含量所占百分比”，作为标志物的应用，为A1)-A4)中的至少一种：
    A1)预测待测者是否为肝癌患者；
    A2)制备用于预测待测者是否为肝癌患者的试剂盒；
    A3)预测肝癌；
    A4)制备用于预测肝癌的试剂盒。
  19. 预测肝癌的方法，包括如下步骤：检测待测者血浆中DCP含量和AFP含量；检测待测者cfDNA中肝癌突变基因的突变类型、突变reads、基因拷贝数变异、HBV是否与基因整合、cfDNA浓度和不同插入片段长度的cfDNA含量所占百分比；记录待测者的年龄和性别；将上述待测者的信息转换为肝细胞癌筛查分数，根据肝细胞癌筛查分数预测待测者是否为肝癌患者。
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