CN111048152A - Experimental method for evaluating treatment effect of cfDNA detection on glioma - Google Patents
Experimental method for evaluating treatment effect of cfDNA detection on glioma Download PDFInfo
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Abstract
An experimental method for evaluating the curative effect of cfDNA detection on glioma treatment comprises the steps of carrying out cfDNA quantitative detection by collecting peripheral blood before and after a healthy model control group, a first glioma model experimental group and a second glioma model experimental group through a grouping experiment, then grouping each model after the operation into a slow group, a stable group and a progressive group by combining with imaging diagnosis, and then respectively carrying out transverse and longitudinal comparative analysis on cfDNA indexes of each group by using a statistical analysis method, thereby determining the relationship between the cfDNA indexes and glioma through multiple verification: and determining whether the cfDNA concentration can be used as a serological index for diagnosing the glioma, determining whether the cfDNA concentration has the prediction capability on the treatment effect of the glioma, and judging whether the cfDNA concentration index has certain evaluation capability on the treatment effect of the glioma. The experimental method for evaluating the treatment effect of cfDNA detection on glioma can provide important basis for the subsequent clinical experiment and evaluation of the treatment effect of glioma.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to medical experiments, in particular to an experimental method for evaluating the treatment effect of cfDNA detection on glioma.
[ background of the invention ]
Glioma refers to a tumor originated from glial cells, is the most common primary intracranial tumor, and is classified into WHOI-IV stage glioma, I, II stage glioma of low grade, and III and IV stage glioma according to WHO central nervous system tumor classification. In recent 30 years, the incidence rate of primary malignant brain tumor is increased year by year, the annual growth rate is 1% -2%, and the method is particularly obvious for the elderly. According to statistics, glioma accounts for about 27% of all central nervous system tumors and about 80% of malignant tumors; among primary malignant central nervous system tumors, Glioblastoma (glioblastomas, GBM, WHO grade IV) has the highest incidence, accounting for 46.1%, followed by diffuse astrocytoma.
Glioma treatment mainly adopts surgical excision and combines radiotherapy, chemotherapy and other comprehensive treatment methods. The diagnosis of glioma and the evaluation of clinical therapeutic effect mainly depend on imaging diagnosis such as CT and MRI examination. Glioma is easy to relapse after operation, and how to find out as early as possible to give patients timely treatment, so that the survival time of the patients is improved. Extensive phase III clinical trials by the european cancer research treatment organization (EORTC) and National Cancer Institute of Canada (NCIC) demonstrated that umirolimine (TMZ) in combination with synchrotron radiation therapy followed by 6 cycles of TMZ-assisted chemotherapy could extend patient survival with a 2-year survival rate increase from 10.4% to 26.5%. After surgery, TMZ-synchronized radiotherapy combined with adjuvant chemotherapy has become the standard treatment for new GBM diagnosis. However, how to predict glioma responsiveness to chemotherapeutic drugs and reduce chemotherapeutic resistance is also the focus of current discussion on chemotherapy.
Due to the presence of the blood-brain barrier, diagnosis of glioma has been lacking effective serological diagnostic indicators to guide clinical diagnosis and assessment of therapeutic efficacy, but recent research results have found that circulating free dna (cfdna) derived from glioma is able to cross the blood-brain barrier and be detected in the peripheral blood. If the detection technology is developed to be mature and is applied to the diagnosis and treatment effect evaluation of glioma patients, great help is brought to clinic, and the blank that the glioma is lack of serological diagnosis indexes for a long time is filled.
[ summary of the invention ]
The invention aims to solve the problems and provides an experimental method for evaluating the treatment effect of cfDNA detection on glioma, which is used for verifying whether the plasma cfDNA level of a glioma model is higher than that of a healthy model and verifying whether the plasma cfDNA of the glioma model changes correspondingly with the change of the disease condition, thereby providing an important basis for the subsequent clinical experiment and the evaluation of the treatment effect of glioma.
In order to achieve the above object, the present invention provides an experimental method for evaluating the therapeutic effect of cfDNA detection on glioma, characterized in that it comprises the following steps:
s1, determining a health model control group, a first glioma model experimental group and a second glioma model experimental group by using a glioma grading method;
s2, quantitatively detecting the cfDNA concentration of each model in the health model control group, the first glioma model experimental group and the second glioma model experimental group respectively, wherein the result is marked as cfDNA 1;
s3, carrying out glioma excision operation on each model in the first glioma model experimental group and the second glioma model experimental group, and then respectively and quantitatively detecting the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group, wherein the result is marked as cfDNA 2;
s4, after radiotherapy operation is carried out on the second glioma model experimental group, the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group is respectively and quantitatively detected, and the result is marked as cfDNA 3;
s5, regrouping each model in the first glioma model experimental group after resection operation and the second glioma model experimental group after resection operation and radiotherapy operation into a slow group, a stable group and a progressive group according to the image diagnosis;
s6, calculating the values of cfDNA1-cfDNA2 and cfDNA1-cfDNA3 of each model in the slow group, the stable group and the progressive group, analyzing the difference of cfDNA indexes in the slow group, the stable group and the progressive group by adopting a statistical analysis method, and if the cfDNA1-cfDNA2 and/or the cfDNA1-cfDNA3 of the slow group are/is significantly higher than the corresponding indexes of the stable group and the progressive group, determining that the cfDNA concentration has the prediction capability on the treatment effect of glioma.
Further, the health model control group comprises a plurality of health models, the first glioma model test group comprises a plurality of animal models rated as grade I-II gliomas, and the second glioma model test group comprises a plurality of animal models rated as grade III-IV gliomas.
Further, the model in the healthy model control group is a female Balb/cluo nude mouse with the weight of 15-20 g and the age of 5-6 weeks, and the models in the first glioma model experimental group and the second glioma model experimental group are tumor-affected mice established by inoculating the Balb/cluo nude mouse with glioma tumor tissue blocks.
Further, the statistical analysis method is adopted to perform significance difference analysis on the result cfDNA1, and if the concentration of cfDNA of the model in the second glioma model experimental group is significantly higher than that of the model in the first glioma model experimental group, and the concentration of cfDNA of the model in the first glioma model experimental group is significantly higher than that of the model in the healthy model control group, the cfDNA is considered to be a serological index for glioma diagnosis.
Further, when analyzing the difference of the cfDNA index in the slow, stable and progressive groups using a statistical analysis method, it includes the step S61:
taking the values of the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2, the cfDNA1-cfDNA3, the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2, the cfDNA1-cfDNA3, the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2 and the cfDNA1-cfDNA3 as a set of samples respectively;
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA1 of the slow group, the cfDNA1 of the stable group, and the cfDNA1 of the progressive group;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDN2 of the progressive group, is different;
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA3 of the slow group, the cfDNA3 of the stable group, and the cfDNA3 of the progressive group;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the advanced group, is different;
using Kruskal-Wallis test to test whether the overall distribution of samples in the buffering group of cfDNA1-cfDNA3, the stabilizing group of cfDNA1-cfDNA3 and the progressing group of cfDNA1-cfDNA33 is different;
further, step S6 includes step S62:
if the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group are different, the Wilcoxon rank-sum test is used for carrying out difference detection on each two groups of samples of the three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group;
if the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group are different, the Wilcoxon rank-sum test is used for carrying out difference detection on each two groups of samples of the three groups of samples, namely the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group;
further, step S6 includes step S63:
using cfDNA1, cfDNA2 and cfDNA3 of each model in the buffer group as a group of samples, and using Friedman' test to test the difference of the cfDNA in each time of the buffer group;
using cfDNA1, cfDNA2 and cfDNA3 of each model in the stable group as a group of samples, and using Friedman' stest to test the difference of each cfDNA in the stable group;
cfDNA1, cfDNA2, cfDNA3 of each model in the progression group were used as a set of samples and Friedman' stest was used to test for differences in cfDNA of each time in the progression group.
Further, step S6 includes step S64:
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the slow group as a group of samples, and performing difference detection on each group of samples by using post-hoc Wilcoxon signed-rank test;
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the stable group as a group of samples, and performing difference detection on each group of samples by using a post-hoc Wilcoxon signed-rank test;
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the development group as a group of samples, and performing difference detection between every two groups of samples by using post-hoc Wilcoxon signed-rank test;
further, when there is a significant difference in the test results of step S61, step S62, step S63 and step S64, and the cfDNA1-cfDNA2 or cfDNA1-cfDNA3 of the remission group is significantly higher than the corresponding index of the stable group and the progression group, the cfDNA concentration is considered to have a predictive ability for the therapeutic effect of glioma.
Further, when the cfDNA concentration of each model in the healthy model control group, the first glioma model experiment group and the second glioma model experiment group is quantitatively detected, the peripheral blood cfDNA of each model is extracted, and a qPCR detection method is adopted for quantitative detection.
The present invention advantageously contributes to effectively solving the above-mentioned problems. According to the method, by means of a grouping experiment, peripheral blood before and after a health model control group, a first glioma model experiment group and a second glioma model experiment group is collected to carry out cfDNA quantitative detection, then, the models after the operation are grouped into a slow group, a stable group and a progressive group by combining with imaging diagnosis, and then, a statistical analysis method is utilized to carry out transverse and longitudinal comparative analysis on cfDNA indexes of the groups respectively, so that the relation between the cfDNA indexes and the glioma is determined through multiple verification: and determining whether the cfDNA concentration can be used as a serological index for diagnosing the glioma, determining whether the cfDNA concentration has the prediction capability on the treatment effect of the glioma, and judging whether the cfDNA concentration index has certain evaluation capability on the treatment effect of the glioma.
[ description of the drawings ]
Fig. 1 is a statistical reference table of indexes corresponding to respective models grouped according to a health model control group, a first glioma model experiment group, and a second glioma model experiment group.
Fig. 2 is a statistical reference table of indexes corresponding to the models grouped by the relief group, the stability group, and the progression group after the operation.
Fig. 3 is sample data when cfDNA1, cfDNA2, cfDNA3 of each model in the group were buffered as a group of samples.
Fig. 4 is sample data when cfDNA1, cfDNA2, cfDNA3 of each model in the stable group were used as one set of samples.
Fig. 5 is sample data when cfDNA1, cfDNA2, cfDNA3 of each model within the progression group was used as a set of samples.
Fig. 6 shows 6 sample data sets when cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3, and cfDNA2-cfDNA3 of each model in the buffered group were used as one sample set.
Fig. 7 shows 6 sample data sets of a set of samples, which are cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3, and cfDNA2-cfDNA3 of each model in the stable group.
Fig. 8 is 6 sample data sets of cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3, and cfDNA2-cfDNA3 of each model in the progression group as one sample set.
[ detailed description ] embodiments
The following examples are further illustrative and supplementary to the present invention and do not limit the present invention in any way.
The experimental method for evaluating the treatment effect of cfDNA detection on glioma comprises the following steps:
and S1, determining a health model control group, a first glioma model experiment group and a second glioma model experiment group by using a glioma grading method.
The health model control group comprises a plurality of health animal models, the first glioma model experiment group comprises a plurality of animal models rated as glioma of I-II, and the second glioma model experiment group comprises a plurality of animal models rated as glioma of III-IV. In this embodiment, 10 models are selected for each group, that is, the health model control group includes 10 health models, the first glioma model experimental group includes 10 models rated as grade I to II glioma, and the second glioma model experimental group includes 10 models rated as grade III to IV glioma. In order to facilitate control, the number of models selected from the healthy model control group, the first glioma model experimental group and the second glioma model experimental group is preferably consistent. For convenience of description, in the present embodiment, as shown in fig. 1, models are respectively identified as model 1, model 2, model 3, model 4, model 5, model 6, model 7, model 8, model 9, model 10, model 11, model 12, model 13, model 14, model 15, model 16, model 17, model 18, model 19, model 20, model 21, model 22, model 23, model 24, model 25, model 26, model 27, model 28, model 29, and model 30. Wherein, the model 1, the model 2, the model 3, the model 4, the model 5, the model 6, the model 7, the model 8, the model 9 and the model 10 are healthy model comparison groups; model 11, model 12, model 13, model 14, model 15, model 16, model 17, model 18, model 19 and model 20 are a first glioma model experimental group; model 21, model 22, model 23, model 24, model 25, model 26, model 27, model 28, model 29, model 30 are the second glioma model experimental group.
In the embodiment, the model in the healthy model control group is Balb/cluo nude mice, the female parent and the age of the mice are 5-6 weeks, and the weight of the mice is 15-20 g; the models in the first glioma model experimental group and the second glioma model experimental group are tumor-bearing mice established by inoculating glioma tumor tissue blocks. In order to improve the reference of the experimental results, the basic parameters of the animal models in the healthy model control group, the first glioma model experimental group and the second glioma model experimental group are approximately the same, for example, the animal models are female, and the mice are 5-6 weeks old and have the body weight of 20-25 g. The model nude mice in the healthy model control group can be directly purchased, the models in the first glioma model experiment group and the second glioma model experiment group can be directly purchased from Balb/cluo nude mice, then modeling culture is carried out by adopting a known glioma tumor tissue block inoculation method, the growth of glioma is monitored, the mice with glioma growing to be evaluated as grade I-II glioma are used as the model mice of the first glioma model experiment group, and the mice with glioma growing to be evaluated as grade III-IV glioma are used as the model mice of the second glioma model experiment group. The classification of glioma can be carried out according to classification and classification of glioma of WHO central nervous system tumor 4 (2007) [36], and the glioma is pathologically classified.
The method for inoculating glioma tumor on mouse can refer to the known technology, and the modeling step is not specifically described in this embodiment. To ensure experimental consistency, each mouse in the first and second glioma model test groups should be modeled using the same tumor inoculation method.
After a health model control group, a first glioma model experiment group and a second glioma model experiment group are determined, the next step is carried out:
s2, quantitatively detecting the cfDNA concentration of each model in the health model control group, the first glioma model experimental group and the second glioma model experimental group respectively, and marking the result as cfDNA 1.
When the cfDNA concentration of each model is quantitatively detected, plasma cfDNA can be extracted by collecting peripheral blood of each model, and then the cfDNA can be quantitatively detected by a known quantitative detection method. In this embodiment, the specific method is as follows:
1. plasma cfDNA extraction: collecting peripheral blood of a mouse by using an EDTA (ethylene diamine tetraacetic acid) anticoagulation tube, and centrifuging at the speed of 1600rpm/min for 10 minutes to separate plasma; the separated plasma was extracted with the DNeasy Blood & Tissue Kit from Qiagen as per the instructions, after which the extracted cfDNA was diluted out to several, e.g. 7, different concentrations of cfDNA standards with the semer fly Standard (Human DNA Standard, 438746, 100 ng/ul);
2. preparation of a qPCR reaction system: mu.l of reaction system was supplemented with enucleated enzyme water using 2. mu.l of lcfDNA standard, 2X SYBR GREEN MASTER MIX, 1mM dATP, 1mM dCTP, 1mM dGTP and 1mM dTTP, and 0.2. mu.M primer; wherein the primer parameters are as follows:
primer 1 (Total concentration, human LINE-1family, 97bp)
Front direction 5'-tggcacatatacaccatggaa-3'
Reverse 5' -tgagaatgatggtttccaatttc-3
Primer 2 (Long fragment concentration, human LINE-1family, 300bp)
Front direction 5'-ACACCTATTCCAAAATTGACCAC-3'
And (3) reversing: 5'-TTCCCTCTACACACTGCTTTGA-3'
3. qPCR reaction: pre-denaturation, 95 ℃,1 minute, 1 cycle; denaturation, 95 ℃ for 8 seconds; annealing/extension at 60 ℃ for 15 seconds; denaturation, annealing/extension for 35 cycles;
4. cfDNA quantitative calculation: and setting a linear standard curve according to the CT value and the Log value of the copy number of the standard substance, and quantitatively calculating the concentration of the detected mouse peripheral blood sample.
Since the health model control group, the first glioma model experiment group, and the second glioma model experiment group have a plurality of models in common, the cfDNA1 is a set including a plurality of cfDNA concentration values, each model quantitatively detects one cfDNA concentration value, and for convenience of description, the cfDNA concentration values of the models are collectively called cfDNA 1. In the present example, 30 models were provided in total, and therefore, 30 cfDNA concentration values were included in total in the cfDNA1, which are denoted by X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, X12, X13, X14, X15, X16, X17, X18, X19, X20, X21, X22, X23, X24, X25, X26, X27, X28, X29, X30, respectively, as shown in fig. 1. Wherein, X1, X2, X3, X4, X5, X6, X7, X8, X9 and X10 are cfDNA concentration values of each model in a healthy model control group; x11, X12, X13, X14, X15, X16, X17, X18, X19, X20 are cfDNA concentration values of each model in the first glioma model test group, and X21, X22, X23, X24, X25, X26, X27, X28, X29, X30 are cfDNA concentration values of each model in the second glioma model test group.
cfDNA1 is an indicator of cfDNA when each model was not treated with surgery, and was used as a benchmark for comparative analysis with the indicator of cfDNA after the model was treated.
After quantitatively measuring the pre-operative cfDNA concentration cfDNA1 of each model, the next step was performed:
s3, carrying out glioma excision operation on each model in the first glioma model experimental group and the second glioma model experimental group, and then respectively and quantitatively detecting the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group, wherein the result is marked as cfDNA 2;
in this step, the model is subjected to a glioma-removing operation, which may be performed by a known technique. The cfDNA concentration of each model was quantitatively determined, in synchronization with the quantitative determination step in step S2.
The cfDNA2 should be tested as long as possible within the same day, e.g., quantitatively at 2 weeks after glioma excision in each model. In order to ensure consistency and eliminate interference of external factors, the steps of the excision operation of each model and the feeding conditions after the excision operation should be kept as consistent as possible.
Similarly, cfDNA2 is a collection containing several cfDNA concentration values, one for each model, quantitatively detected. In this step, the cfDNA concentration value of each model is collectively referred to as cfDNA 2. In this example, the first and second glioma model test groups had 20 models in total, and thus, the cfDNA2 included 20 cfDNA concentration values in total, which are denoted as M11, M12, M13, M14, M15, M16, M17, M18, M19, M20, M21, M22, M23, M24, M25, M26, M27, M28, M29, and X30, respectively, as shown in fig. 1. Wherein, M11, M12, M13, M14, M15, M16, M17, M18, M19 and M20 are cfDNA concentrations of each model in the first glioma model experimental group after the last resection operation, and M21, M22, M23, M24, M25, M26, M27, M28, M29 and M30 are cfDNA concentrations of each model in the second glioma model experimental group after the first resection operation.
When the cfDNA2 was counted by the quantitative assay, the next step was performed:
s4, after radiotherapy operation is carried out on the second glioma model experimental group, the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group is respectively and quantitatively detected, and the result is marked as cfDNA 3.
Wherein, the cfDNA concentration of each model in the second glioma model experimental group is quantitatively detected within about 1-2 weeks after the radiotherapy operation. In the step, the cfDNA concentration of each model in the first glioma model experimental group is quantitatively detected according to actual conditions, for example, the cfDNA concentration can be detected in the same day with each model in the second glioma model experimental group, or each model in the first glioma model experimental group can be detected at certain intervals. In this embodiment, for more convenient and clear description of the method of the present invention, it is preferable that each model in the second glioma model test group is quantitatively tested within the same day of week 2 after the radiotherapy operation, and the test result is labeled as cfDNA 3. Similarly, 20 cfDNA concentration values in total are included in the cfDNA3, which are denoted as N11, N12, N13, N14, N15, N16, N17, N18, N19, N20, N21, N22, N23, N24, N25, N26, N27, N28, N29, and X30, respectively, as shown in fig. 1. Wherein, N11, N12, N13, N14, N15, N16, N17, N18, N19 and N20 are cfDNA concentrations quantitatively detected by each model in the first glioma model experimental group, and N21, N22, N23, N24, N25, N26, N27, N28, N29 and N30 are cfDNA concentrations quantitatively detected by each model in the second glioma model experimental group after radiotherapy operation.
In other embodiments, to obtain more experimental data for more accurate verification, after the second glioma model test group is subjected to radiotherapy, multiple quantitative detections may be performed on each of the models in the first glioma model test group and the second glioma model test group, for example, one quantitative detection is performed at 2 weeks after radiotherapy, and another quantitative detection is performed at 2 weeks later, at this time, the detection result cfDNA3 includes multiple sets of cfDNA concentration values, and in the statistical analysis process of the significance difference, the statistical analysis method is similar to that in this embodiment, except that the number of samples to be analyzed is greater than that in this embodiment.
When the cfDNA3 was counted by the quantitative assay, the next step was performed:
s5, diagnosing each model in the first glioma model experimental group after resection and the second glioma model experimental group after resection and radiotherapy according to imaging, and dividing each model into a slow group, a stable group and a progressive group according to RANO standard. Wherein, the remission group is the remission of the disease; the stable group basically controls the state of the illness, and the state of the illness is more stable; the development group shows good treatment effect.
The classification of the slow, stable and progressive groups may be performed according to known imaging diagnosis, wherein the number of models in the slow, stable and progressive groups may be consistent or inconsistent depending on the diagnosis group. In the present embodiment, as shown in fig. 2, the models 11, 14, 18, 22, 26, 27, and 30 are divided into a relief group; the model 12, the model 13, the model 15, the model 17, the model 19, the model 20, the model 24, the model 28, and the model 29 are classified into a stable group, and the model 16, the model 21, the model 23, and the model 25 are classified into a progress group.
After the models were classified into a remission group, a stabilization group and a progression group according to the imaging diagnosis, the next step was performed:
s6, calculating the values of cfDNA1-cfDNA2 and cfDNA1-cfDNA3 based on cfDNA1 detected before the operation, analyzing the difference of cfDNA indexes in a slow group, a stable group and a progress group by adopting a statistical analysis method, and if the cfDNA1-cfDNA2 and/or cfDNA1-cfDNA3 of the slow group is/are significantly higher than the corresponding indexes of the stable group and the progress group, determining that the cfDNA concentration has the prediction capability on the treatment effect of glioma.
Specifically, the method comprises the following detailed steps:
s61, taking the values of cfDNA1 of a buffering group, cfDNA2 of the buffering group, cfDNA3 of the buffering group, cfDNA1-cfDNA2 of the buffering group, cfDNA1-cfDNA3 of the buffering group, cfDNA1 of a stable group, cfDNA2 of a stable group, cfDNA3 of the stable group, cfDNA1-cfDNA2 of the stable group, cfDNA1-cfDNA3 of the stable group, cfDNA1 of a progress group, cfDNA2 of the progress group, cfDNA3 of the progress group, cfDNA1-cfDNA2 of the progress group and cfDNA1-cfDNA3 of the progress group as a group of samples respectively; for example, for the present example, as shown in fig. 2, the samples of cfDNA1 of the remission group include a set of values of X14, X18, X22, X26, X27, X30; the cfDNA1-cfDNA3 samples of the progression group included the set of values X16-N16, X21-N21, X23-N23, X25-N25. The contents of each set of samples may be analogized with reference to fig. 2.
Then, using Kruskal-Wallis test to perform overall analysis on samples belonging to the same kind of cfDNA indexes, and confirming whether there is a difference in overall distribution:
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA1 of the slow group, the cfDNA1 of the stable group, and the cfDNA1 of the progressive group; namely, whether the remission group, the stabilization group and the progression group have differences on the whole is analyzed by taking cfDNA1 as an index;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDN2 of the progressive group, is different; namely, whether the remission group, the stabilization group and the progression group have differences on the whole is analyzed by taking cfDNA2 as an index;
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA3 of the slow group, the cfDNA3 of the stable group, and the cfDNA3 of the progressive group; namely, whether the remission group, the stabilization group and the progression group have differences on the whole is analyzed by taking cfDNA3 as an index;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the advanced group, is different; namely, whether the slow group, the stable group and the progress group have differences on the whole is analyzed by taking cfDNA1-cfDNA2 as an index;
using Kruskal-Wallis test to test whether the overall distribution of samples in the buffering group of cfDNA1-cfDNA3, the stabilizing group of cfDNA1-cfDNA3 and the progressing group of cfDNA1-cfDNA33 is different; namely, whether the slow group, the stable group and the progress group have differences on the whole is analyzed by taking cfDNA1-cfDNA3 as an index;
whether the samples of the same type of indexes have differences in the whole can be analyzed by using the Kruskal-Wallis test, when the general test shows that the differences exist, particularly the differences among the groups of samples in the same type of indexes cannot be given, at this time, the Wilcoxon rank-sum test is further used for the group of samples with significant differences to test the differences among the samples in the same type of indexes, and the specific step S62 is as follows:
if the three groups of samples, i.e., the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group, have differences on the whole after the step S61, the difference detection is further performed between each two groups of samples, i.e., the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group, by using a Wilcoxon rank-sum test; the method can be used for analyzing three groups of samples, namely a slow group sample, a stable group sample and a progress group sample, and particularly, the cfDNA1 indexes of the samples in which groups have significant differences;
if the three groups of samples, i.e., the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group, have differences on the whole after the step S61, the difference detection is further performed between each two groups of samples, i.e., the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group, by using a Wilcoxon rank-sum test; the method can be used for analyzing three groups of samples, namely a slow group sample, a stable group sample and a progress group sample, and particularly, the cfDNA2 indexes of the samples in which groups have significant differences;
if the three groups of samples, i.e., the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group, have differences on the whole after the step S61, the difference detection is further performed between each two groups of samples, i.e., the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group, by using a Wilcoxon rank-sum test; the method can be used for analyzing three groups of samples, namely a slow group sample, a stable group sample and a progress group sample, and particularly, the cfDNA3 indexes of the samples in which groups have significant differences;
if the samples of the three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group, have differences on the whole after the step S61, the Wilcoxon rank-sum test is further used for carrying out difference detection on the samples of each two groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group; the method can be used for analyzing three groups of samples, namely a slow group sample, a stable group sample and a progressive group sample, and particularly has significant difference in cfDNA1-cfDNA2 indexes among the samples;
if the samples of the three groups of samples, namely the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group, have differences on the whole after the step S61, the Wilcoxon rank-sum test is further used for carrying out difference detection on the samples of each two groups of samples, namely the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group; the method can be used for analyzing three groups of samples, namely a slow group sample, a stable group sample and a progressive group sample, and particularly has significant difference in cfDNA1-cfDNA3 indexes among the samples;
the Wilcoxon rank-sum test can be used for testing which groups of samples have significant differences among the slow group, the stable group and the progressive group under the same indexes, and the Wilcoxon rank-sum test is used for longitudinally analyzing and comparing the differences among different groups, but cannot transversely analyzing and comparing whether each cfDNA in the same group has the difference. For comprehensive analytical comparison, differential analysis of cfDNA within the same group was performed using Friedman' S test, which is performed as follows at step S63:
using cfDNA1, cfDNA2 and cfDNA3 of each model in the buffer group as a group of samples, and using Friedman' test to test the difference of the cfDNA in each time of the buffer group; the data for this set of samples is shown in figure 3.
Using cfDNA1, cfDNA2 and cfDNA3 of each model in the stable group as a group of samples, and using Friedman' stest to test the difference of each cfDNA in the stable group; the data for this set of samples is shown in fig. 4.
cfDNA1, cfDNA2, cfDNA3 of each model in the progression group were used as a set of samples and Friedman' stest was used to test for differences in cfDNA of each time in the progression group. The data for this set of samples is shown in fig. 5.
Using Friedman's test, it can be analyzed whether there is a significant difference in cfDNA1, cfDNA2, cfDNA3 within the same group, which cannot be analyzed which indices have significant differences, e.g., whether there is a large difference between cfDNA1 and cfDNA2, or a large difference between cfDNA2 and cfDNA 3. To further analyze which of the indicators within the same group are more different, a post-hoc Wilcoxon signed-rank test is further used for the test, and the step S64 is as follows:
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the slow group as a group of samples, and performing difference detection on each group of samples by using post-hoc Wilcoxon signed-rank test; the data for the 6 sets of samples are shown in fig. 6.
Using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the stable group as a group of samples, and performing difference detection on each group of samples by using a post-hoc Wilcoxon signed-rank test; the data for the 6 sets of samples are shown in fig. 7.
Using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the development group as a group of samples, and performing difference detection between every two groups of samples by using post-hoc Wilcoxon signed-rank test; the data for the 6 sets of samples is shown in fig. 8.
The post-hoc Wilcoxon signed-rank test can be used for comparing the indexes in the same group in pairs, for example, whether the cfDNA1 and the cfDNA2 are different or not, whether the cfDNA1-cfDNA2 and the cfDNA1 are different or not can be analyzed and compared, and the indexes in the same group are analyzed and compared transversely.
Similarly, a statistical analysis method is adopted to perform significance difference analysis on cfDNA1 of a healthy model control group, a first glioma model experiment group and a second glioma model experiment group, cfDNA1 in the healthy model control group, cfDNA1 in the first glioma model experiment group and cfDNA1 in the second glioma model experiment group are respectively used as a group of samples, the Kruskal-Wall is test is adopted to analyze the population of the samples, and Wilcoxon rank-sum test is adopted to perform difference analysis between each two groups of samples, so that whether the cfDNA1 indexes of the healthy model control group, the first glioma model experiment group and the second glioma model are different or not is analyzed.
In step S6, when analyzing the sample by using the statistical analysis method, for how to use Kruskal-Wallis test, Wilcoxon rank-sum test, Friedman' S test, post-hoc Wilcoxon aligned-rank test to test the sample data, the known techniques can be referred to, and the detailed steps of the analysis will not be specifically described in this embodiment.
When the test method is used for analyzing and comparing the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2 and the cfDNA1-cfDNA3 transversely and longitudinally respectively, analysis can be carried out according to the analysis result to determine whether the cfDNA concentration can be used as a serological index for diagnosing the glioma, determine whether the cfDNA concentration has the capability of predicting the treatment effect of the glioma and determine whether the cfDNA concentration index has certain assessment capability on the treatment effect of the glioma.
When the results of significant difference analysis on cfDNA1 indexes of a healthy model control group, a first glioma model experiment group and a second glioma model experiment group show that the concentration of cfDNA of a model in the second glioma model experiment group is obviously higher than that of cfDNA of a model in the first glioma model experiment group, and the concentration of cfDNA of a model in the first glioma model experiment group is obviously higher than that of cfDNA of a model in the healthy model control group, it can be judged that cfDNA can be used as a serological index for glioma diagnosis.
When the results of the longitudinal and transverse significant difference analysis of the cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3, cfDNA2-cfDNA3 indexes of the slow group, the stable group, and the progressive group show that: when the detection results of the steps S61, S62, S63 and S64 are significantly different, and the cfDNA1-cfDNA2 or cfDNA1-cfDNA3 of the remission group is significantly higher than the corresponding indexes of the stable group and the progression group, the cfDNA concentration is considered to have the prediction capability on the treatment effect of the glioma, and the cfDNA concentration index has a certain evaluation capability on the treatment effect of the glioma.
When the result of the significant difference analysis is different from the above result, the following is specifically analyzed according to specific situations: for example, when the analysis result of step S61 shows that there is no significant difference, it indicates that the cfDNA concentration does not change much after the operation before and after the operation; when the analysis result of step S61 shows that there is a significant difference, the analysis result of step S62 shows that the sample difference between the remission group and the stable group or the progression group is large, and the sample difference between the stable group and the progression group is small, it indicates that the cfDNA concentration after one surgical treatment is large, and the cfDNA concentration after the surgical treatment is large.
The experimental method provided by the invention aims to provide a way to verify whether the cfDNA concentration is suitable for diagnosing glioma and to verify whether the cfDNA changes correspondingly with the progress of disease conditions and after various treatment measures, so as to judge whether cfDNA indexes are suitable for evaluating the treatment effect of glioma. Since the invention provides a verification method, specific experimental data are not given in the method, but those skilled in the art can still perform experimental design according to the method of the invention to verify whether cfDNA indexes are associated with glioma.
While the invention has been described with reference to the above embodiments, the scope of the invention is not limited thereto, and the above components may be replaced with similar or equivalent elements known to those skilled in the art without departing from the spirit of the invention.
Claims (10)
1. An experimental method for evaluating the therapeutic effect of cfDNA detection on glioma is characterized by comprising the following steps:
s1, determining a health model control group, a first glioma model experimental group and a second glioma model experimental group by using a glioma grading method;
s2, quantitatively detecting the cfDNA concentration of each model in the health model control group, the first glioma model experimental group and the second glioma model experimental group respectively, wherein the result is marked as cfDNA 1;
s3, carrying out glioma excision operation on each model in the first glioma model experimental group and the second glioma model experimental group, and then respectively and quantitatively detecting the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group, wherein the result is marked as cfDNA 2;
s4, after radiotherapy operation is carried out on the second glioma model experimental group, the cfDNA concentration of each model in the first glioma model experimental group and the second glioma model experimental group is respectively and quantitatively detected, and the result is marked as cfDNA 3;
s5, regrouping each model in the first glioma model experimental group after resection operation and the second glioma model experimental group after resection operation and radiotherapy operation into a slow group, a stable group and a progressive group according to the image diagnosis;
s6, calculating the values of cfDNA1-cfDNA2 and cfDNA1-cfDNA3 of each model in the slow group, the stable group and the progressive group, analyzing the difference of cfDNA indexes in the slow group, the stable group and the progressive group by adopting a statistical analysis method, and if the cfDNA1-cfDNA2 and/or the cfDNA1-cfDNA3 of the slow group are/is significantly higher than the corresponding indexes of the stable group and the progressive group, determining that the cfDNA concentration has the prediction capability on the treatment effect of glioma.
2. The assay of claim 1 wherein the control group of health models comprises a plurality of health models, the first experimental group of glioma models comprises a plurality of animal models rated as grade I-II gliomas, and the second experimental group of glioma models comprises a plurality of animal models rated as grade III-IV gliomas.
3. The experimental method for evaluating the therapeutic effect of cfDNA detection on glioma according to claim 2, wherein the model in the healthy model control group is female Balb/cluo nude mice with the weight of 15-20 g and the age of 5-6 weeks, and the model in the first and second glioma model test groups is tumor-affected mice established by inoculating Balb/cluo nude mice with glioma tumor tissue blocks.
4. The assay of claim 2 or 3 wherein the cfDNA concentration of the model in the second glioma model assay group is significantly higher than the cfDNA concentration of the model in the first glioma model assay group, and the cfDNA concentration of the model in the first glioma model assay group is significantly higher than the cfDNA concentration of the model in the healthy model control group, the cfDNA is considered as a serological indicator for glioma diagnosis, when the statistical analysis is performed on the resulting cfDNA 1.
5. The experimental method for evaluating the efficacy of cfDNA testing for glioma treatments according to claim 2 or 3, wherein, when analyzing the difference of cfDNA indicators in the remission group, the stable group and the progression group using a statistical analysis method, it comprises the steps of S61:
taking the values of the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2, the cfDNA1-cfDNA3, the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2, the cfDNA1-cfDNA3, the cfDNA1, the cfDNA2, the cfDNA3, the cfDNA1-cfDNA2 and the cfDNA1-cfDNA3 as a set of samples respectively;
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA1 of the slow group, the cfDNA1 of the stable group, and the cfDNA1 of the progressive group;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDN2 of the progressive group, is different;
using Kruskal-Wallis test to test whether there is a difference in the overall distribution of the three groups of samples, namely, the cfDNA3 of the slow group, the cfDNA3 of the stable group, and the cfDNA3 of the progressive group;
using Kruskal-Wallis test to test whether the overall distribution of three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the advanced group, is different;
the Kruskal-Wallis test was used to test whether there was a difference in the overall distribution of samples from the buffered group of cfDNA1-cfDNA3, the stabilized group of cfDNA1-cfDNA3, and the advanced group of cfDNA1-cfDNA 33.
6. The assay method for assessing the efficacy of cfDNA testing on glioma treatment of claim 5 wherein: the step S6 further includes a step S62:
if the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA1 of the slow group, the cfDNA1 of the stable group and the cfDNA1 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA2 of the slow group, the cfDNA2 of the stable group and the cfDNA2 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group are different, difference detection is carried out between each two groups of samples of the three groups of samples, namely the cfDNA3 of the slow group, the cfDNA3 of the stable group and the cfDNA3 of the progress group by using a Wilcoxonrank-sum test;
if the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group are different, the Wilcoxon rank-sum test is used for carrying out difference detection on each two groups of samples of the three groups of samples, namely the cfDNA1-cfDNA2 of the slow group, the cfDNA1-cfDNA2 of the stable group and the cfDNA1-cfDNA2 of the progress group;
if the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group are different, the Wilcoxon rank-sum test is used for carrying out difference detection on each two groups of samples of the three groups of samples, namely the cfDNA1-cfDNA3 of the slow group, the cfDNA1-cfDNA3 of the stable group and the cfDNA1-cfDNA3 of the progress group.
7. The experimental method for testing the efficacy of cfDNA in the treatment of glioma according to claim 6, wherein step S6 further comprises the step S63:
using cfDNA1, cfDNA2 and cfDNA3 of each model in the buffer group as a group of samples, and using Friedman's test to test the difference of the cfDNA in each time of the buffer group;
using cfDNA1, cfDNA2 and cfDNA3 of each model in the stable group as a group of samples, and using Friedman's test to test the difference of each cfDNA in the stable group;
cfDNA1, cfDNA2, cfDNA3 of each model within the progression group were used as a set of samples and Friedman's test was used to test for differences in cfDNA within the progression group.
8. The experimental method for testing the efficacy of cfDNA in the treatment of glioma according to claim 7, wherein step S6 further comprises the step S64:
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the slow group as a group of samples, and performing difference detection on each group of samples by using post-hoc Wilcoxon signed-rank test;
using cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the stable group as a group of samples, and performing difference detection on each group of samples by using a post-hoc Wilcoxon signed-rank test;
the cfDNA1, cfDNA2, cfDNA3, cfDNA1-cfDNA2, cfDNA1-cfDNA3 and cfDNA2-cfDNA3 of each model in the development group are respectively used as a group of samples, and difference detection is carried out between each two groups of samples by using post-hoc Wilcoxon signed-rank test.
9. The experimental method for testing the efficacy of cfDNA in the treatment of glioma according to claim 8, wherein: when the detection results of the steps S61, S62, S63 and S64 are significantly different, and the cfDNA1-cfDNA2 or cfDNA1-cfDNA3 of the remission group is significantly higher than the corresponding indexes of the stable group and the progression group, the cfDNA concentration is considered to have the prediction capability on the treatment efficacy of glioma.
10. The assay method for assessing the efficacy of cfDNA detection on glioma treatment according to claim 1, wherein the cfDNA concentration of each model in the healthy model control group, the first glioma model assay group, and the second glioma model assay group is quantitatively determined by extracting the cfDNA of peripheral blood of each model and using a qPCR detection method.
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