CN110229894B - Gene combination and application thereof in preparation of reagent for predicting prognosis of patient receiving immune checkpoint inhibitor treatment - Google Patents
Gene combination and application thereof in preparation of reagent for predicting prognosis of patient receiving immune checkpoint inhibitor treatment Download PDFInfo
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Abstract
The invention provides a gene combination and application thereof in preparing a reagent for predicting prognosis of a patient receiving immune checkpoint inhibitor treatment. The invention discloses a TMS55 method for scoring tumor mutation based on 55 gene combinations, wherein TMS is defined as the number of genes containing nonsynonymous mutation in a specific gene combination. TMS55 was divided into three groups of TMS55=0, 1= < TMS55< =5, TMS55>5, and the 1= < TMS55< =5 and TMS55>5 groups had better prognosis and longer overall survival compared to the TMS55=0 group. TMS55 based on the 55 gene combination has higher prediction efficiency than TMB in predicting overall survival after immunotherapy and can have a uniform cutoff value. Therefore, TMS55 can be used for predicting prognosis of patients receiving immune checkpoint inhibition treatment, and is easier to popularize and apply in clinical practice.
Description
Technical Field
The invention belongs to the technical field of biological medicines, and relates to a gene combination and application thereof in preparing a reagent for predicting prognosis of a patient receiving an immune checkpoint inhibitor for treatment.
Background
Immunotherapy is the current research hotspot, and the application of immune checkpoint inhibitors opens up a new era of tumor therapy, but the lack of efficient biomarkers greatly affects the curative effect and application thereof. Tumor Mutation Burden (TMB) refers to the total number of somatic non-synonymous gene mutations detected per million bases, including coding errors, base substitutions, gene insertion or deletion errors, and the like. Somatic mutations are finally expressed at the protein level through transcription and translation, and the mutations generate new antigens such as new protein segments or polypeptide segments, which are recognized as non-self antigens by the autoimmune system to activate T cells and cause immune response. Thus, it is theorized that the higher the TMB, the more tumor associated neoantigen that is produced, the more likely it is to stimulate an immune response, and the better the therapeutic effect will be with immune checkpoint inhibitors.
Currently, more and more studies indicate that TMB is significantly correlated with the efficacy of immune checkpoint inhibitors. High TMB content in malignant melanoma and lung cancer[1]And carcinoma of large intestine[2]Tumor of constant size[3]Is positively correlated with the clinical efficacy of immune checkpoint inhibitors. Recent studies have shown that TMB is effective in predicting overall survival of patients receiving immune checkpoint inhibitors in a variety of solid tumors[4,5]However, its predictive efficacy is limited, only to top 20% of patientsThey are predicted to have a good prognosis (compared to bottom 80%), and the cutoff values for TMB elevation are not uniform among different tumors[4]. These drawbacks greatly affect the widespread use of TMB as a biomarker in immunotherapy.
As the study goes in, researchers found that not all mutations were associated with high TMB and good immunotherapy outcomes. In NSCLC, patients with driver mutations, such as EML4-ALK fusion, EGFR mutations, ROS1 rearrangements, BRAF fusions, etc., often have low TMB expression[2,6-9]. More importantly, partial gene mutations are associated with drug resistance of immune checkpoint inhibitors, e.g., STK11 mutation is significantly associated with drug resistance of PD-L1/PD1 inhibitors in KRAS mutated lung adenocarcinoma patients[10]. Therefore, TMB incorporates all non-synonymous mutations into the calculation at the time of calculation, greatly affecting the predictive potency of TMB as a marker. TMB detection gold Standard is Whole Exon Sequencing (WES)[4]. In view of the high price of whole exon sequencing, targeted gene sequencing is mainly adopted at present, and although research shows that the TMB measured and calculated by the targeted gene sequencing based on large gene combinations is obviously related to the TMB measured and calculated based on WES, the TMB accuracy can be influenced by the sequencing combinations with different sizes. At present, the gene sequencing combination for detecting the TMB contains more and more genes and is higher and higher in cost, and meanwhile, the calculated TMB has differences, so that the uniform cutoff value is more difficult to realize for guiding clinical practice.
In summary, since the calculation of TMB includes negative mutations, the potency of TMB as an immunotherapy-related marker is greatly affected and a uniform cutoff value is lacking.
Disclosure of Invention
In order to overcome the defects and shortcomings of the prior art, the invention aims to provide a combination based on 55 genes, and a Tumor Mutation Scoring (TMS) method is developed through the combination of the genes, wherein the TMS is defined as the number of genes containing nonsynonymous mutations in a specific gene combination. TMS55 based on the 55 gene combination has higher prediction efficiency than TMB in predicting overall survival after immunotherapy and can have a uniform cutoff value. Therefore, TMS55 can be used for predicting prognosis of patients receiving immune checkpoint inhibition treatment, and is easier to popularize and apply in clinical practice.
The second object of the invention is to provide the application of the reagent for detecting TMS55 of the gene combination in preparing the reagent for predicting the prognosis of a patient receiving immune checkpoint inhibitor treatment.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, there is provided a gene set consisting of 55 genes: EPHA, EPHA, EPHA, MGA, NTRK, PTPRD, ZFLX, ATM, CDKN2, CDKN2Ap16INK4, CREBP, KDR, LATS, NCOR, BRCA, CIC, CTCF, DNMT, EPHB, FANCA, IRS, NCOA, NOTCH, PTCH, RAD54, RNF, SMO, SPEN, TET, NF, CARD, IGF1, MLL, PTPRT, TERT, VHL, PIK3CG, ALK, ARID1, ARID, BRAF, BRCA, ERBB, FAT, GRIN2, MLL, MLL, NOTCH, NOTCH, NRAS, PAK, PIK3C2, POLE, SETD, SETP.
In a second aspect, there is provided the use of a reagent for detecting the tumor mutation score TMS55 of the above gene combination for the manufacture of a reagent for predicting the prognosis of a patient receiving treatment with an immune checkpoint inhibitor, wherein the tumor mutation score TMS55 is the number of genes in the gene combination that contain non-synonymous mutations.
Preferably, in the application, the reagent for detecting the tumor mutation score of the gene combination is a reagent for sequencing.
Preferably, in the use, the tumor mutation score TMS55 has a minimum value of 0, a maximum value of 55, and is an integer, and TMS55 is divided into three groups of TMS55 ═ 0, 1 ═ TMS55 ═ 5, and TMS55>5, and the 1 ═ TMS55 ═ 5 and TMS55>5 patients have better prognosis and longer overall survival time compared to the TMS55 ═ 0 group.
In the present invention, TMS is defined as the number of genes containing non-synonymous mutations in a specific gene combination. TMS55 represents TMS calculated from 55 gene combinations.
The invention calculates the tumor mutation score, namely TMS55, based on 55 gene combinations, and comprises the following steps:
1. providing a tumor sample and a matched peripheral blood sample;
2. respectively extracting DNA and carrying out quality control inspection;
3. respectively carrying out targeted gene sequencing on the DNA samples, wherein the sequencing gene combination at least comprises the following 55 genes: EPHA, EPHA, EPHA, MGA, NTRK, PTPRD, ZFLX, ATM, CDKN2, CDKN2Ap16INK4, CREBP, KDR, LATS, NCOR, BRCA, CIC, CTCF, DNMT, EPHB, FANCA, IRS, NCOA, NOTCH, PTCH, RAD54, RNF, SMO, SPEN, TET, NF, CARD, IGF1, MLL, PTPRT, TERT, VHL, PIK3CG, ALK, ARID1, ARID, BRAF, BRCA, ERBB, FAT, GRIN2, MLL, MLL, NOTCH, NOTCH, NRAS, PAK, PIK3C2, POLE, SETD, SETP.
4. After the quality control of the original sequencing sequence is qualified, the original sequencing sequence is compared with a reference genome (version: hg19 or b37) to carry out mutation analysis, annotation and other biological information analysis of a matched sample, and the existence of non-synonymous mutation in each gene is determined.
5. TMS55, the number of genes containing non-synonymous mutations among the 55 genes, was calculated. Thus, TMS55 is 0 at a minimum value, 55 at a maximum value, and is an integer.
6. TMS55 is divided into three groups, TMS55 ═ 0, 1 ═ TMS55 ═ 5, TMS55>5, depending on the size of TMS 55.
7. The results of the study showed that the 1 ═ TMS55 ═ 5 and TMS55>5 groups of patients had better prognosis and a longer overall survival time compared to the TMS55 ═ 0 group.
Compared with the prior art, the invention has the beneficial effects that:
compared with the existing TMB, the TMS55 has higher efficiency for predicting the patient prognosis, can screen more possible beneficiary patients, and more importantly, TMS55 has a uniform cutoff value and is easy to popularize clinically. In addition, only 55 genes are required for the TMS55 determination, which is obviously less than the existing three-four hundred genes for TMB detection, so that the economic burden of patients is greatly reduced.
Drawings
FIG. 1A shows the correlation results between TMS and TMB.
Fig. 1B shows the correlation results of TMS55 with TMB.
Figure 2A is a graph of the correlation results of TMS55 with overall survival of patients treated with immune checkpoint inhibitors.
Figure 2B is the correlation result of TMB with overall survival of immune checkpoint inhibitor treated patients.
Fig. 2C is a graph of the results of the Hazard Ratio (HR) and P value for TMS55 and TMB in a specific tumor type subgroup survival analysis.
Detailed Description
The features and advantages of the present invention will be further understood from the following detailed description taken in conjunction with the accompanying drawings. The examples provided are merely illustrative of the method of the present invention and do not limit the remainder of the disclosure in any way.
The following examples were analyzed for target gene sequencing data, survival data and TMB data of Tumor samples from patients receiving an immune test inhibitor treatment, which were disclosed in "Tumor tissue samples obtained from" Tumor tissue samples "(reference 4) published by Samstein RM et al, 2019 at Nat Genet.
[ example 1 ] TMS55 analysis of 1661 cases of target Gene sequencing data of patients receiving Immunocompaction inhibitors
First, treatment of samples in reference 4
1. Providing a tumor sample and a matched peripheral blood sample
The tumor samples collected must be tumor samples taken before treatment with immune checkpoint inhibitors, including primary foci, metastatic lymph nodes and distant metastasis specimens, and tumor cells in malignant effusion can be grouped if sufficient targeted gene detection is available. Providing 5-micron anti-drop slices for the wax stone specimen, wherein the surgical specimen is not less than 5 slices, and the puncture specimen is not less than 10 slices; for formalin-fixed specimens, the surgical specimens are not less than 50mg, and the puncture specimens are not less than 1 needle; malignant pleural effusion/cerebrospinal fluid/pericardial effusion and the like are collected by using a STREK tube, and the volume is not less than 8 ml. The matched peripheral blood sample is collected by an STRRECK tube, and the volume is not less than 2 ml. The blood sample is post-treated within 30min after separation.
2. DNA extraction and quality control inspection
The DNA sample needs to satisfy the conditions that the nucleic acid quality is more than or equal to 300ng, the OD260/280 ratio is between 1.8 and 2.2, the concentration is more than or equal to 10 ng/muL, and the volume is more than or equal to 10 muL. The agarose gel electrophoresis DNA band is clear without degradation and RNA and protein pollution.
3. The DNA samples are subjected to targeted gene sequencing respectively, and all patients receive targeted gene sequencing containing at least 300 genes, wherein the targeted gene sequencing contains the following 55 genes: EPHA, EPHA, EPHA, MGA, NTRK, PTPRD, ZFLX, ATM, CDKN2, CDKN2Ap16INK4, CREBP, KDR, LATS, NCOR, BRCA, CIC, CTCF, DNMT, EPHB, FANCA, IRS, NCOA, NOTCH, PTCH, RAD54, RNF, SMO, SPEN, TET, NF, CARD, IGF1, MLL, PTPRT, TERT, VHL, PIK3CG, ALK, ARID1, ARID, BRAF, BRCA, ERBB, FAT, GRIN2, MLL, MLL, NOTCH, NOTCH, NRAS, PAK, PIK3C2, POLE, SETD, SETP. Double-ended sequencing with a read length of 100bp using the Illumina HiSeq 2500 platform was used as an example.
4. After sequencing, converting the BCL file into a FastQ format file through a BCL2FASTQ, performing quality control through FastQC, performing reference genome (version: hg19 or b37) comparison through BWA software, performing index and format conversion through Samtools software, removing redundant information and noise generated by sequencing through Picard software, searching for differences between sample sequencing data and a reference genome through GATK, listing the differences, and performing functional annotation through Annovar mutation to obtain a mutant gene list of the sample.
Example 2 comparison of the results for 1661 patients receiving inhibitors of the immunodetection TMS55 and TMB
The invention calculates TMS and TMB of 1661 patients receiving the immunodetection inhibitor by using the targeted gene sequencing data of tumor samples of the patients receiving the immunodetection inhibitor disclosed in reference 4, and the result shows that TMS and TMB have obvious correlation (figure 1). Total TMS including all sequencing genes was of very high relevance to TMB (R0.98, P)<2×10-16Fig. 1A). In the identification of positive and negative mutant genes, the invention identifies 55 positive mutant genes, and calculates TMS55, namely the number of nonsynonymous mutant genes in the 55 genes. Thus, TMS55 is 0 at a minimum value, 55 at a maximum value, and is an integer. Its TMS55 also has a high correlation with TMB (R ═ 0.91, P)<2×10-16Fig. 1B). These results indicate that, although TMS55 removed a large number of negative and optional mutant genes, TMS55 still has a significant association with TMB, which is also the basis for the ability of TMS55 to also serve as a predictive marker.
The invention sets a unified cutoff value for TMS55, namely dividing patients into TMS55 as 0, 1 according to the height of TMS55<＝TMS55<5 and TMS55>And 5, three groups. The patients are divided into three groups of Bottom 80%, Top 10-20% and Top 10% according to the height of TMB in different tumor types. In the survival analysis of 1661 patients, both TMS55 and TMB were significantly associated with the overall survival of the patients (fig. 2). In the survival analysis, the x-axis of the survival curve represents survival time and the y-axis represents survival probability. The more open the curves in the different groups represent the higher the predictive potency of their survival markers. In FIG. 2A, 1<＝TMS55<5 and TMS55>The survival curve of the group 5 is obviously higher than that of the group TMS55 ═ 0 (P)<2×10-16). More importantly, the risk ratio (HR) is an important indicator in survival analysis, with HR values greater than 1 indicating a poor prognosis and HR values less than 1 indicating a generationThe table correlates with good prognosis, with smaller values for HR less than 1, the higher the predictive potency. 1 compared to TMS 55-group 0<＝TMS55<5 and TMS55>HR values for group 5 were 0.772 (95% Confidence Interval (CI): 0.659-0.904, P ═ 0.001) and 0.307 (95% CI: 0.238-0.397, P:, respectively<2×10-16) (FIG. 2A) whereas in TMB analysis the HR values for the top 10-20% and top 10% groups were 0.730 (95% CI: 0.580-0.917, P ═ 0.007) and 0.529 (95% CI: 0.403-0.694, P ═ 4.67 × 10) respectively, as compared to the bottom 80% group-6) (FIG. 2B). Thus, TMS55 has advantages over TMB in that TMS55 has lower HR values in the survival assay (TMS 550.307 vs TMB 0.529) and more significant P values (TMS 55P)<2×10-16Comparative TMB P4.67 × 10-6) More importantly, TMS55 is more reasonably grouped for a given cutoff value, enabling the greatest possible screening of patients who may benefit (see 1 of FIG. 2A)<＝TMS55<5 and TMS55>Number of 5 groups of patients).
In the survival analysis, 95% CI of HR values crossed the line with HR ═ 1, representing a P value greater than 0.05, with no statistical significance. In fig. 2C, the diamonds represent HR values, the horizontal lines represent 95% CI of HR values, and HR values for TMS55 and TMB in all subgroups (diamonds) are less than 1, suggesting that both are associated with good prognosis. However, in a specific tumor type subgroup analysis, TMS55 had a smaller HR value than TMB and was significantly associated with overall survival in more tumor types, e.g., TMS55 was significantly associated with overall patient survival in colorectal, melanoma and renal cell carcinoma (with HR values less than 0.5 and 95% CI of HR values not crossing the line HR 1), whereas TMB was not significant (with HR values greater than 0.5 and 95% CI of HR values crossing the line HR 1), with P values represented by diamond-shaped gray values and deeper values representing smaller P values (fig. 2C).
The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited thereto, and any simple modifications or equivalent substitutions of the technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present invention are within the scope of the present invention.
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Claims (2)
1. use of a reagent for detecting the tumor mutation score TMS55 of a gene combination for the manufacture of a reagent for predicting the prognosis of a patient receiving an immune checkpoint inhibitor treatment, wherein said gene combination consists of the following 55 genes: EPHA3, EPHA5, EPHA7, MGA, NTRK3, PTPRD, ZFHX3, ATM, CDKN2A, CDKN2Ap16INK4A, CREBP, KDR, LATS1, NCOR1, BRCA1, CIC, CTCF, DNMT1, EPHB1, FANCA, IRS1, NCOA 1, NOTCH 1, PTCH1, RAD54 1, RNF 1, SMO, SPEN, TET1, NF1, CARD1, IGF 11, MLL 1, PRPTT, TERT, VHL, PIK3CG, ALK, ARID 11, ARID1, BRAF, CA1, ERBB 72, FAT = 1, MLL 1, NOTCH 1, NOTCH3 TMS, NRTMS, NRTP = 1, NRTP 72, NRTP 1, and the number of the three groups 1, the number of the tumor genes are equal to the number of the BRHA 633672, the same as the number of the BRBB 1, the number of the three groups 1, the number of the BRTP 1, the number of the non-synonymous 1, the number of the non-labeled 1, the number of the lung 1, the number of the lung 1, the lung 36, the overall lifetime is longer.
2. The use according to claim 1, wherein the reagent for detecting the tumor mutation score TMS55 of the gene combination according to claim 1 is a sequencing reagent.
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| CN111334575A (en) * | 2020-02-18 | 2020-06-26 | 至本医疗科技（上海）有限公司 | Use of NOTCH family gene variants for predicting sensitivity of solid tumor patients to immune checkpoint inhibitor therapy |
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| CN113061656A (en) * | 2021-03-25 | 2021-07-02 | 南京先声医学检验有限公司 | Use of mutations in the TET1 gene for predicting susceptibility of colon cancer patients to immune checkpoint inhibitor therapy |
| CN113106157B9 (en) * | 2021-05-24 | 2023-08-25 | 温州医科大学附属第二医院（温州医科大学附属育英儿童医院） | Kit for predicting prognosis survival time of tumor immunotherapy and application thereof |
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