CN117542529B - Method, system, device and storage medium for predicting non-recurrent death risk of HLA-incompatible allogeneic hematopoietic stem cell transplantation - Google Patents
Method, system, device and storage medium for predicting non-recurrent death risk of HLA-incompatible allogeneic hematopoietic stem cell transplantation Download PDFInfo
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Abstract
The present disclosure provides a method, system, apparatus, storage medium for predicting risk of non-recurrent death in HLA-incompatible allogeneic hematopoietic stem cell transplantation. The prediction method comprises the following steps: s100, preliminary prediction: preliminarily predicting the risk of non-recurrent death of the target object based on the biomarker prediction model; if the target subject is at high risk in non-recurrent death, proceeding to step S200; s200, accurately predicting: calculation of the third exon of HLA-II Gene based on the donor HLA-II GeneA value; comparison ofAnd accurately predicting the risk of non-recurrent death of the target object by the value and a preset HED threshold. The present disclosure is directed to a donor by introducingAnd taking the value as a new risk factor, and accurately predicting the target object which is preliminarily predicted to be at medium and high risk so as to improve the accuracy of prediction and reduce the false positive rate of the crowd which is preliminarily predicted to be at medium and high risk.
Description
Technical Field
The disclosure relates to the technical field of medical care informatics, in particular to a method, a system, equipment and a storage medium for predicting non-recurrent death risk of HLA non-allogeneic hematopoietic stem cell transplantation.
Background
Hematopoietic Stem Cell Transplantation (HSCT) is a therapeutic means for restoring normal hematopoietic function in patients by removing abnormal (tumor, immune) cells in the patients by large-dose radiotherapy and chemotherapy, and then transplanting hematopoietic stem cells to the patients. Among them, hematopoietic stem cell transplantation can be classified into autologous hematopoietic stem cell transplantation and allogeneic (allogeneic) hematopoietic stem cell transplantation according to their donor-recipient relationship.
The risk of non-recurrent death of a subject at a time point after receiving allogeneic hematopoietic stem cell transplantation can be classified into three classes, low, medium, and high, where the risk of non-recurrent death of the subject at a time point after receiving allogeneic hematopoietic stem cell transplantation is predicted based on the concentration of a biomarker (e.g., sST2, REG3, AREG, TNFR1, etc.). The incidence of non-recurrent death in the low risk population, the incidence of non-recurrent death in the medium risk population, and the incidence of non-recurrent death in the high risk population, were predicted to be 6%, 20%, 38% in the non-recurrent death in the non-heterogeneous hematopoietic stem cell transplantation population. Wherein, the incidence rate of non-recurrent death in the population with medium and high risk is predicted to be 26%, and 74% of the population with medium and high risk is predicted to have no non-recurrent death in practice. Thus, there is a need to more accurately predict the risk of non-recurrent death of non-conforming allogeneic hematopoietic stem cell transplantation targets.
Disclosure of Invention
To overcome the problems in the related art, the present disclosure provides an HLA-incompatible allogeneic hematopoietic stemMethods, systems, devices, and storage media for predicting risk of non-recurrent death in cell transplantation. The present disclosure relates to the transplantation of non-conforming allogeneic hematopoietic stem cells from a subject at a third exon of a HLA-class II gene of a selected donorThe value is used as a new risk factor, and the target object which is preliminarily predicted to be at medium and high risk is accurately predicted, so that the accuracy of preliminary prediction of non-recurrent death of allogeneic hematopoietic stem cell transplantation can be improved, and the false positive rate of the crowd which is preliminarily predicted to be at medium and high risk can be reduced.
In a first aspect of the present disclosure, the present disclosure provides a method of predicting risk of non-recurrent death of HLA-mismatched allogeneic hematopoietic stem cell transplantation, the method comprising the steps of:
s100, preliminary prediction:
preliminary predicting the degree of risk of non-recurrent death of the target subject at a time point after receiving non-conforming allogeneic hematopoietic stem cell transplantation based on the concentrations of biomarkers sST2 and TNFR 1; if the target object is at a low risk of non-recurrent death at the current time node, not entering step S200; if the target object is at high risk in non-recurrent death at the current time node, then step S200 is entered;
s200, accurately predicting:
s201, obtaining a nucleotide sequence of a DQB1 locus gene and a nucleotide sequence of a DRB1 locus gene in a donor HLA-II gene;
s202, decoding a nucleotide sequence of a DQB1 locus gene into an amino acid sequence of a corresponding protein; and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein;
s203, calculating and obtaining the third exon of the DQB1 locus gene according to the amino acid sequence decoded by the DQB1 locus geneA value;
calculating the DRB1 locus gene according to the amino acid sequence decoded by the DRB1 locus geneAt the third exonA value;
at the third exon of HLA-II geneThe value is +.>Value sum->And (3) summing;
s204, willThe value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
In some alternative embodiments, theValue and said->The calculation formula of the value is:
wherein alpha, beta and gamma represent inverse mean weight factors;
i and j represent two amino acids of the allele at the same position, respectively;
c represents an amino acid composition;
p represents the polarity of the amino acid;
v represents the molecular volume of the amino acid.
In some alternative embodiments, the formulas for α, β, γ are shown below, respectively:
wherein n represents the number of amino acid species in the encoded amino acid sequence;
representing the difference between the two amino acid compositions after the combination of n amino acids;
representing the difference between the polarities of two amino acids after the combination of n amino acids;
the difference in molecular volume between two amino acids after n amino acids are combined two by two is shown.
In some alternative embodiments, inAccurately predicting that the target object is at low risk of non-recurrent death at the current time point under the condition that the value is less than or equal to the HED threshold;
at the position ofWith values greater than the HED threshold, the target subject is precisely predicted to be at high risk of non-recurrent death at the current time point.
Illustratively, the HED threshold is chosen to be 5.7. In some alternative embodiments, the method of preliminary prediction comprises the steps of:
s101, obtaining sST2 concentration and TNFR1 concentration of a target object at a certain time point after receiving the transplantation of non-compatible allogeneic hematopoietic stem cells;
s102, calculating the non-recurrent death probability of the target object at the current time point based on the biomarker prediction model;
the calculation formula of the biomarker prediction model is as follows:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />Represents TNFR1 concentration; a. b and c represent parameters obtained by training a biomarker predictive model;
s103, comparing the non-recurrent death probability P with a preset probability threshold to preliminarily predict the risk of non-recurrent death of the target object after receiving the transplantation of the non-compatible allogeneic hematopoietic stem cells.
In some embodiments, a is selected from 1.6014.
In some embodiments, b is selected from 3.2513.
In some embodiments, c is selected from-22.121.
In some embodiments, the biomarker predictive model is calculated as:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />TNFR1 concentration was expressed.
In some optional embodiments, the preset probability threshold includes a first probability threshold, and if the probability of non-recurrent death is less than or equal to the first probability threshold, preliminarily predicting that the target subject is at low risk of non-recurrent death at the current time point;
if the non-recurrent death probability P is greater than the first probability threshold, preliminarily predicting that the target subject is at a medium-high risk of non-recurrent death at the current time point.
In some optional embodiments, the preset probability threshold further includes a second probability threshold, and the second probability threshold is greater than the first probability threshold;
if the non-recurrent death probability P is larger than or equal to a second probability threshold, preliminarily predicting that the target object is at high risk of non-recurrent death at the current time point;
if the probability of non-recurrent death P is greater than the first probability threshold and the probability of non-recurrent death P is less than the second probability threshold, preliminarily predicting that the target object is at risk of non-recurrent death at the current time point.
Illustratively, the first probability threshold is selected from 0.0683.
Illustratively, the second probability threshold is selected from 0.1602.
In a second aspect of the present disclosure, the present disclosure provides a prediction system for predicting a risk of non-recurrent death of HLA-non-conforming allogeneic hematopoietic stem cell transplantation based on the prediction method of the first aspect of the present disclosure, the prediction system comprising a preliminary prediction module and an accurate prediction module:
a preliminary prediction module for preliminarily predicting the risk level of non-recurrent death of the target subject at a certain time point after receiving the transplantation of the non-conforming allogeneic hematopoietic stem cells based on the sST2 concentration and the TNFR1 concentration; if the target object is in the condition of low risk of non-recurrent death at the current time node, the accurate prediction module is not entered; if the target object is at a high risk in non-recurrent death at the current time node, entering an accurate prediction module;
the accurate prediction module comprises a gene data acquisition module, a decoding module, a secondary calculation module and a secondary prediction module,
the gene data acquisition module is used for acquiring the nucleotide sequence of the DQB1 locus gene and the nucleotide sequence of the DRB1 locus gene in the HLA-II type gene of the donor;
a decoding module for decoding the nucleotide sequence of the DQB1 locus gene into the amino acid sequence of the corresponding protein and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein;
the second-level calculation module is used for calculating and obtaining the position of the third exon of the DQB1 locus gene according to the amino acid sequence decoded by the DQB1 locus geneCalculating the value of the third exon of the DRB1 locus gene according to the amino acid sequence decoded by the DRB1 locus gene>Value, and according to->Value sum->Value calculation of +.2 at the third exon of HLA-II Gene>A value;
a secondary prediction module for predictingThe value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
In some alternative embodiments, the preliminary prediction module comprises a biomarker acquisition module, a primary calculation module, a primary prediction module,
biomarker acquisition module: for obtaining the concentration of biomarkers sST2 and TNFR1 in a subject at a time point after receiving a non-conforming allogeneic hematopoietic stem cell transplant;
the primary computing module: for calculating a non-recurrent mortality probability P based on sST2 concentration and TNFR1 concentration;
a primary prediction module: for comparing the probability of non-recurrent death P with a predetermined probability threshold to preliminarily predict the risk of non-recurrent death of the target subject after receiving the non-conforming allogeneic hematopoietic stem cell transplantation.
In a third aspect of the present disclosure, the present disclosure provides a prediction apparatus for HLA-incompatible allogeneic hematopoietic stem cell transplantation non-recurrent death risk, characterized in that the prediction apparatus comprises a memory and a processor; wherein the memory is used for storing program instructions; the processor is configured to invoke program instructions, which when executed implement the steps of the prediction method according to the first aspect of the present disclosure.
In a fourth aspect of the present disclosure, the present disclosure provides a computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, performs the steps of the prediction method according to the first aspect of the present disclosure.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flow chart illustrating a method of predicting risk of non-recurrent death of HLA-incompatible allogeneic hematopoietic stem cell transplantation according to an exemplary embodiment.
Fig. 2 is a graph of cumulative incidence of non-recurrent death in a population of non-allogeneic hematopoietic stem cell transplants that were initially predicted to be at high risk in non-recurrent death, with accurate prediction, at a HED threshold of 5.7.
FIG. 3 is a graph of cumulative occurrence of non-recurrent deaths in a population initially predicted to be at high risk and a population accurately predicted to be at high risk, and a graph of cumulative occurrence of non-recurrent deaths in a population initially predicted to be at risk and a population accurately predicted to be at low risk.
Detailed Description
The present disclosure discloses a method, system, apparatus, and storage medium for predicting risk of non-recurrent death in HLA-incompatible allogeneic hematopoietic stem cell transplantation, and those skilled in the art can suitably modify the process parameters to implement the method in light of the present disclosure. It is expressly noted that all such similar substitutions and modifications will be apparent to those skilled in the art, and are deemed to be included in the present disclosure. While the methods and applications of the present disclosure have been described in terms of preferred embodiments, it will be apparent to those skilled in the relevant art that variations and appropriate changes and combinations of the methods and applications described herein can be made to practice and use the disclosed technology without departing from the spirit and scope of the disclosure.
Interpretation of the terms
As used in this disclosure, the term "hematopoietic stem cell transplantation" can be divided into, by donor source: autograft, xenograft, and syngeneic transplants. Wherein "xenograft" is further divided into sibling donor transplants and non-blood donor transplants. "isogenic transplantation" is a transplantation in which the recipient and donor genes are identical, and in humans refers only to transplantation between syngeneic twins.
As used in this disclosure, the term "allogeneic hematopoietic stem cell transplantation" is divided into full-phase and non-phase according to the degree of phase of ten sites of human leukocyte antigen (Human Leukocyfe Antigen, HLA) genes, wherein full-phase refers to the same ten sites in the HLA genes of a recipient and non-phase refers to the different at least one site in the HLA genes of the recipient and donor.
As used in this disclosure, the term "non-recurrent death (NRM) is defined as death that is not associated with disease recurrence/progression.
As used in this disclosure, the term "risk" refers to the likelihood that an event will occur within a particular period of time, such as the onset of non-recurrent death of a non-conforming allogeneic hematopoietic stem cell transplant.
As used in this disclosure, the term "risk prediction" includes a probability, odds ratio, or likelihood risk prediction that a predicted event may occur.
As used in this disclosure, the term "sST2" refers to a soluble growth-stimulated expressed gene 2 protein (soluble growth stimulation expresses gene 2 protein).
As used in this disclosure, the term "TNFR1" refers to tumor necrosis factor receptor 1 (tumor necrosis factor receptor 1).
As used in this disclosure, the terms "sST2 concentration" and "TNFR1 concentration" are derived from a blood sample or other biological fluid. Wherein the term "blood sample" is meant to include whole blood, plasma and serum samples.
As used in this disclosure, the term "threshold" is used to assess the sensitivity of a factor to an effector response produced by an organism. In the prediction of non-recurrent death risk of non-allogeneic hematopoietic stem cell transplantation, reasonable setting of the threshold has important guiding significance for prognosis evaluation of a target subject receiving non-xenogeneic hematopoietic stem cell transplantation and selection of a prognosis treatment scheme of the target subject.
Method for predicting non-recurrent death risk of HLA-incompatible allogeneic hematopoietic stem cell transplantation
In one embodiment, a method of predicting the risk of non-recurrent death of an HLA-incompatible allogeneic hematopoietic stem cell transplant is provided. FIG. 1 is a flow chart illustrating a method of predicting risk of non-recurrent death of HLA-incompatible allogeneic hematopoietic stem cell transplantation, according to one exemplary embodiment, the method comprising the steps of: s100, preliminary prediction; s200, accurate prediction.
The preliminary prediction method comprises the following steps:
in step S101, the concentration of sST2 and the concentration of TNFR1 in the target subject at a certain time point after receiving the transplantation of the non-conforming allogeneic hematopoietic stem cells are obtained.
In step S102, calculating a non-recurrent mortality probability of the target subject at the current time point based on the biomarker prediction model;
the calculation formula of the biomarker prediction model is as follows:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />Represents TNFR1 concentration; a. b and c represent parameters obtained by training a biomarker predictive model.
Specifically, a is selected from 1.6014, b is selected from 3.2513, and c is selected from-22.121. Accordingly, the calculation formula of the biomarker prediction model is as follows:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />TNFR1 concentration was expressed.
It should be noted that the values of a, b and c are a preferred implementation, and there may be a range of fluctuations in the values of a, b and c when actually implemented.
In step S103, the probability of non-recurrent death P is compared with a preset probability threshold to preliminarily predict the risk of non-recurrent death of the target subject after receiving the transplantation of non-conforming allogeneic hematopoietic stem cells. The preset probability threshold comprises a first probability threshold and a second probability threshold, and the second probability threshold is larger than the first probability threshold. If the probability of non-recurrent death is less than or equal to the first probability threshold, preliminarily predicting that the target object is at low risk of non-recurrent death at the current time point, and not entering step S200; if the probability of non-recurrent death P is greater than the first probability threshold and the probability of non-recurrent death P is less than the second probability threshold, initially predicting that the target object is at risk of non-recurrent death at the current time point, then step S200 is entered; if the probability of non-recurrent death P is greater than or equal to the second probability threshold, the method proceeds to step S200 if the preliminary prediction is that the target subject is at high risk of non-recurrent death at the current time point.
Specifically, the first probability threshold is 0.0683 and the second probability threshold is 0.1602.
The method for accurately predicting comprises the following steps:
in step S201, the nucleotide sequence of the DQB1 site gene and the nucleotide sequence of the DRB1 site gene in the donor HLA-II class gene are obtained.
In step S202, the nucleotide sequence of the DQB1 locus gene is decoded into the amino acid sequence of the corresponding protein; and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein.
In step S203, the third exon of the DQB1 locus gene is calculated based on the amino acid sequence decoded by the DQB1 locus geneA value; calculating the +.about.f at the third exon of DRB1 locus gene according to the amino acid sequence decoded by DRB1 locus gene>A value; a third exon of HLA-II gene>The value is +.>Value sum->Sum of values.
In particular, the method comprises the steps of,value sum->The calculation formula of the value is:
wherein i and j represent two amino acids of the allele at the same position, respectively; c represents an amino acid composition; p represents the polarity of the amino acid; v represents the amino acid molecular volume; alpha, beta, gamma denote inverse mean weight factors.
Wherein the amino acid composition uses a GRAR740101 composition expressed in an AAindex database (Amino acid index database); amino acid polarity the AAindex database indicates GRAR740102 polarity; the amino acid molecular volumes used were the molecular volumes expressed in AAindex database for GRAR 740103. WhileValue sum->The three physicochemical characteristics of GRAR740101 composition, GRAR740102 polarity and GRAR740103 molecular volume are calculated based on the physicochemical distance between Grantham amino acids, and the physicochemical differences of the amino acid sequences between HLA typing alleles are quantified.
The calculation formulas of alpha, beta and gamma are respectively as follows:
wherein n represents the number of amino acid species in the encoded amino acid sequence;
represents two kinds of amino acids after n kinds of amino acids are combined in pairsDifferences in composition;
representing the difference between the polarities of two amino acids after the combination of n amino acids;
the difference in molecular volume between two amino acids after n amino acids are combined two by two is shown.
Illustratively, if n=20,is the sum of the differences between the two amino acid compositions after the combination of 20 amino acids (380 groups without considering the combination of the amino acids); />Is the sum of the differences between the polarities of the two amino acids after the combination of 20 amino acids (380 groups without considering the combination of the amino acids); />Is the sum of the differences in molecular volumes of the two amino acids after the 20 amino acids are combined two by two (380 groups without regard to self-combination).
In step S204The value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
Wherein, inAccurately predicting that the target object is at low risk of non-recurrent death at the current time point under the condition that the value is less than or equal to the HED threshold;
at the position ofIn the case where the value is greater than the HED threshold, the target is accurately predictedSubjects are at high risk of non-recurrent death at the current time point.
Illustratively, the HED threshold is chosen to be 5.7. Fig. 2 is a graph of cumulative incidence of non-recurrent death in a population of non-allogeneic hematopoietic stem cell transplants that were initially predicted to be at high risk in non-recurrent death, with accurate prediction, at a HED threshold of 5.7. Wherein the time point when the biomarkers (sST 2 and TNFR 1) reached peak concentrations after the target subject received the non-conforming allogeneic hematopoietic stem cell transplantation was recorded as day 0 (D0).
The calculation formula for predicting the biomarker reaching the peak concentration of the target object after receiving the non-conforming allogeneic hematopoietic stem cell transplantation is as follows:
wherein value represents the distance value between the biomarker indicator factors for each target object at each time point;
n represents the number of biomarker index factors
X i Represents biomarker concentration (in pg/ml).
The biomarker concentration at the time point when the value of each target object reached maximum was taken to be approximately the peak concentration, and this time point was then noted as day 0 (D0). Specifically, in the present disclosure, n is 2 and the two biomarker index factors are sST2 and TNFR1, respectively. By passing throughThe peak biomarker concentration for each target subject is determined.
As can be seen from fig. 2, the accurate prediction is that there is a significant difference in the occurrence rate of non-recurrent death in the low risk group and the high risk group, with a p value of 0.002. The non-recurrent death accumulation occurrence rate curves of the high-risk group and the high-risk group accurately predicted based on the biomarker prediction model are shown in fig. 3, the non-recurrent death occurrence rate of the high-risk group and the high-risk group accurately predicted are not significantly different, and the p value is 0.717. The cumulative occurrence rate curve of non-recurrent death in the risk group and the low risk group predicted accurately based on the biomarker prediction model is shown in fig. 3, the non-recurrent death occurrence rate in the risk group and the low risk group predicted accurately are predicted accurately to have large difference, and the p value is 0.058 and is close to obvious.
It can be seen that the incidence of non-recurrent mortality in high risk populations is accurately predicted to rise to 34.8%. The incidence of non-recurrent mortality in low risk populations was accurately predicted to be reduced to 3.7%. The preliminary prediction shows that the false positive rate of the middle and high risk population is reduced by 12.2% after accurate prediction. Compared with the method which only carries out preliminary prediction, the prediction accuracy of non-recurrent death after preliminary prediction and accurate prediction is improved by 15%, and the prediction accuracy of non-recurrent death risk in non-dissimilar hematopoietic stem cell transplantation population is effectively improved.
Thus, the present disclosure is directed at the donor HLA-class II third Exon (Exon 3) by introductionThe value is used as a new risk factor, and the prediction accuracy of non-recurrent death of the non-heterogeneous allogeneic hematopoietic stem cell transplantation can be remarkably improved.
HLA-incompatible allogeneic hematopoietic stem cell transplantation non-recurrent mortality risk prediction system
In one embodiment, a system for predicting risk of non-recurrent death of HLA-non-conforming allogeneic hematopoietic stem cell transplantation is provided, which is based on the method for predicting risk of non-recurrent death of non-conforming allogeneic hematopoietic stem cell transplantation of embodiments of the present disclosure. The prediction system comprises a preliminary prediction module and an accurate prediction module.
The preliminary prediction module comprises a biomarker acquisition module, a primary calculation module and a primary prediction module.
Biomarker acquisition module: for obtaining the concentration of the biomarkers sST2 and TNFR1 in a target subject at a time point after receiving the transplantation of non-conforming allogeneic hematopoietic stem cells.
The primary computing module: for calculating the probability of non-recurrent death P based on sST2 concentration and TNFR1 concentration.
A primary prediction module: comparing the probability of non-recurrent death P with a preset probability threshold to preliminarily predict the risk of non-recurrent death of the target subject after receiving the transplantation of non-conforming allogeneic hematopoietic stem cells; if the target object is in the condition of low risk of non-recurrent death at the current time node, the accurate prediction module is not entered; if the target object is at high risk in non-recurrent death at the current time node, the accurate prediction module is entered.
The accurate prediction module comprises a gene data acquisition module, a decoding module, a secondary calculation module and a secondary prediction module.
The gene data acquisition module is used for acquiring the nucleotide sequence of the DQB1 locus gene and the nucleotide sequence of the DRB1 locus gene in the HLA-II type gene of the donor.
And the decoding module is used for decoding the nucleotide sequence of the DQB1 locus gene into the amino acid sequence of the corresponding protein and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein.
The second-level calculation module is used for calculating and obtaining the position of the third exon of the DQB1 locus gene according to the amino acid sequence decoded by the DQB1 locus geneCalculating the value of the third exon of the DRB1 locus gene according to the amino acid sequence decoded by the DRB1 locus gene>Value, and according to->Value sum->Value calculation of +.2 at the third exon of HLA-II Gene>Values.
A secondary prediction module for predictingThe value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
HLA-incompatible allogeneic hematopoietic stem cell transplantation non-recurrent death risk prediction device
In one embodiment, a prediction device for a risk of non-recurrent death of HLA-incompatible allogeneic hematopoietic stem cell transplantation is provided, the prediction device comprising a memory and a processor; wherein the memory is used for storing program instructions; the processor is configured to invoke the program instructions, which when executed, implement the steps of a method of predicting risk of non-recurrent death of HLA-non-conforming allogeneic hematopoietic stem cell transplantation according to embodiments of the present disclosure.
Computer readable storage medium
In one embodiment, a computer readable storage medium is provided having stored thereon a computer program which, when executed by a processor, performs the steps of a method of predicting risk of non-recurrent death of HLA-non-allogeneic hematopoietic stem cell transplantation of an embodiment of the present disclosure.
The above describes in detail a method, system, apparatus, and storage medium for predicting risk of non-recurrent death in HLA-incompatible allogeneic hematopoietic stem cell transplantation provided by the present disclosure. Specific examples have been set forth herein to illustrate the principles and embodiments of the present disclosure, and the description of the examples above is only intended to assist in understanding the methods of the present disclosure and the core ideas thereof. It should be noted that it would be obvious to those skilled in the art that various improvements and modifications can be made to the present disclosure without departing from the principles of the present disclosure, and such improvements and modifications fall within the scope of the claims of the present disclosure.
Claims (10)
1. A method for predicting risk of non-recurrent death in HLA-incompatible allogeneic hematopoietic stem cell transplantation, comprising the steps of:
s100, preliminary prediction:
preliminarily predicting the risk degree of non-recurrent death of the target object at a certain time point after receiving the transplantation of the non-compatible allogeneic hematopoietic stem cells based on the biomarker prediction model; if the target object is at a low risk of non-recurrent death at the current time node, not entering step S200; if the target object is at high risk in non-recurrent death at the current time node, then step S200 is entered;
the method of preliminary prediction comprises the steps of:
s101, obtaining sST2 concentration and TNFR1 concentration of a target object at a certain time point after receiving the transplantation of non-compatible allogeneic hematopoietic stem cells;
s102, calculating the non-recurrent death probability of the target object at the current time point based on the biomarker prediction model;
the calculation formula of the biomarker prediction model is as follows:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />Represents TNFR1 concentration; a. b and c represent parameters obtained by training a biomarker predictive model;
s103, comparing the non-recurrent death probability P with a preset probability threshold to preliminarily predict the risk of non-recurrent death of the target object after receiving the transplantation of the non-compatible allogeneic hematopoietic stem cells;
s200, accurately predicting:
s201, obtaining a nucleotide sequence of a DQB1 locus gene and a nucleotide sequence of a DRB1 locus gene in a donor HLA-II gene;
s202, decoding a nucleotide sequence of a DQB1 locus gene into an amino acid sequence of a corresponding protein; and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein;
s203, calculating and obtaining the third exon of the DQB1 locus gene according to the amino acid sequence decoded by the DQB1 locus geneA value;
calculating the third exon of the DRB1 locus gene according to the amino acid sequence decoded by the DRB1 locus geneA value;
at the third exon of HLA-II geneThe value is +.>Value sum->Sum of values;
the saidValue and said->The calculation formula of the value is:
wherein alpha, beta and gamma represent inverse mean weight factors;
i and j represent two amino acids of the allele at the same position, respectively;
c represents an amino acid composition;
p represents the polarity of the amino acid;
v represents the amino acid molecular volume;
s204, willThe value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
2. The prediction method according to claim 1, wherein the calculation formulas of α, β, γ are respectively as follows:
wherein n represents the number of amino acid species in the encoded amino acid sequence;
representing the difference between the two amino acid compositions after the combination of n amino acids;
representing the difference between the polarities of two amino acids after the combination of n amino acids;
the difference in molecular volume between two amino acids after n amino acids are combined two by two is shown.
3. The pre-formulation according to any one of claims 1 to 2The measuring method is characterized in thatAccurately predicting that the target object is at low risk of non-recurrent death at the current time point under the condition that the value is less than or equal to the HED threshold;
at the position ofWith values greater than the HED threshold, the target subject is precisely predicted to be at high risk of non-recurrent death at the current time point.
4. The prediction method according to claim 1, wherein the calculation formula of the biomarker prediction model is:
wherein P represents a non-recurrent mortality probability;represents the concentration of sST 2; />TNFR1 concentration was expressed.
5. The method of claim 1 or 4, wherein the predetermined probability threshold comprises a first probability threshold, and if the probability of non-recurrent death is less than or equal to the first probability threshold, initially predicting that the target subject is at low risk of non-recurrent death at the current time point;
if the non-recurrent death probability P is greater than the first probability threshold, preliminarily predicting that the target subject is at a medium-high risk of non-recurrent death at the current time point.
6. The prediction method according to claim 5, wherein the preset probability threshold further comprises a second probability threshold, and the second probability threshold is greater than the first probability threshold;
if the non-recurrent death probability P is larger than or equal to a second probability threshold, preliminarily predicting that the target object is at high risk of non-recurrent death at the current time point;
if the probability of non-recurrent death P is greater than the first probability threshold and the probability of non-recurrent death P is less than the second probability threshold, preliminarily predicting that the target object is at risk of non-recurrent death at the current time point.
7. A prediction system for predicting the risk of non-recurrent death of HLA-non-conforming allogeneic hematopoietic stem cell transplantation based on the prediction method of any one of claims 1 to 6, comprising a preliminary prediction module and a precise prediction module:
the preliminary prediction module is used for preliminarily predicting the risk degree of non-recurrent death of the target object at a certain time point after the target object receives the transplantation of the non-compatible allogeneic hematopoietic stem cells by the biomarker prediction model; if the target object is in the condition of low risk of non-recurrent death at the current time node, the accurate prediction module is not entered; if the target object is at a high risk in non-recurrent death at the current time node, entering an accurate prediction module;
the accurate prediction module comprises a gene data acquisition module, a decoding module, a secondary calculation module and a secondary prediction module,
the gene data acquisition module is used for acquiring the nucleotide sequence of the DQB1 locus gene and the nucleotide sequence of the DRB1 locus gene in the HLA-II type gene of the donor;
a decoding module for decoding the nucleotide sequence of the DQB1 locus gene into the amino acid sequence of the corresponding protein and decoding the nucleotide sequence of the DRB1 locus gene into the amino acid sequence of the corresponding protein;
the second-level calculation module is used for calculating and obtaining the position of the third exon of the DQB1 locus gene according to the amino acid sequence decoded by the DQB1 locus geneValue according to DRThe amino acid sequence decoded by the B1 locus gene calculates the +.about.f at the third exon of the DRB1 locus gene>Value, and according to->Value sum->Value calculation of +.2 at the third exon of HLA-II Gene>A value;
a secondary prediction module for predictingThe value is compared with a preset HED threshold to accurately predict the risk of non-recurrent death of the target subject following non-conforming allogeneic hematopoietic stem cell transplantation.
8. The prediction system of claim 7, wherein the preliminary prediction module comprises a biomarker acquisition module, a primary calculation module, a primary prediction module,
biomarker acquisition module: for obtaining a biomarker concentration for a subject at a time point after receiving a non-conforming allogeneic hematopoietic stem cell transplant;
the primary computing module: the method comprises the steps of preliminarily calculating non-recurrent death probability P according to a biomarker prediction model;
a primary prediction module: for comparing the probability of non-recurrent death P with a predetermined probability threshold to preliminarily predict the risk of non-recurrent death of the target subject after receiving the non-conforming allogeneic hematopoietic stem cell transplantation.
9. A prediction apparatus for a risk of non-recurrent death in HLA-incompatible allogeneic hematopoietic stem cell transplantation, the prediction apparatus comprising a memory and a processor; wherein the memory is used for storing program instructions; the processor is configured to invoke program instructions which, when executed, implement the steps of the prediction method according to any of claims 1 to 6.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor is adapted to the steps of the prediction method according to any of claims 1 to 6.
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