CN114908163A - Marker for predicting curative effect of lung cancer immune checkpoint inhibitor and application thereof - Google Patents

Marker for predicting curative effect of lung cancer immune checkpoint inhibitor and application thereof Download PDF

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CN114908163A
CN114908163A CN202111459016.5A CN202111459016A CN114908163A CN 114908163 A CN114908163 A CN 114908163A CN 202111459016 A CN202111459016 A CN 202111459016A CN 114908163 A CN114908163 A CN 114908163A
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gene
copy number
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gene set
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高树庚
李宁
张恒辉
王书航
毛蓓蓓
任丹丹
应建明
吴立佳
赫捷
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Wuxi Zhenhe Biotechnology Co ltd
Cancer Hospital and Institute of CAMS and PUMC
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Abstract

The invention provides a marker for predicting treatment efficacy of an immune checkpoint inhibitor for a lung cancer subject and application thereof, wherein the marker combination comprises at least one of genes shown in table 1. According to the marker disclosed by the embodiment of the invention, the treatment curative effect of the lung cancer immune checkpoint inhibitor of the subject can be accurately predicted, such as the PD-1/PD-L1 inhibitor, so that the subject which shows a clinical significant benefit after being treated by the immune checkpoint inhibitor can be distinguished, and the response rate of the lung cancer immune checkpoint inhibitor treatment can be significantly improved.

Description

Marker for predicting curative effect of lung cancer immune checkpoint inhibitor and application thereof
Technical Field
The invention relates to the field of biomedicine, in particular to a marker for predicting the curative effect of a lung cancer immune checkpoint inhibitor and application thereof, and more particularly relates to application of a prediction gene set as a prediction for the curative effect of a target lung cancer immune checkpoint inhibitor, a computer-readable storage medium, electronic equipment for predicting the curative effect of the target lung cancer immune checkpoint inhibitor, a method for predicting the curative effect of the target lung cancer immune checkpoint inhibitor, a system for predicting the curative effect of the target lung cancer immune checkpoint inhibitor and a kit for predicting the curative effect of the target lung cancer immune checkpoint inhibitor.
Background
Clinical trials and studies have shown that inhibitors of programmed death receptor 1 (PD-1)/programmed death ligand 1(PD-L1) significantly improve survival in patients with advanced non-small cell lung cancer (NSCLC). Recently, clinical trials for treatment with neoadjuvant Immune Checkpoint Inhibitors (ICI) have been established, providing more insight into the use of this approach in resectable lung cancer. The main pathological remission rate (MPR) of Nivolumab (Nivolumab), atelizumab (Atezolizumab) or sillimab (Sintilimab) can reach 18-83 percent when being treated by single medicine or being combined with other medicines.
Although the results of clinical trials with neoadjuvant immunotherapy are encouraging, not all patients respond well, such as MPR or complete remission of pathology (pCR). An effective predictive biomarker would significantly improve clinical outcome and increase the response rate of immune checkpoint inhibitors. Although immunotherapeutic biomarkers for metastatic disease have been identified, the relationship between Tumor Mutational Burden (TMB) or PD-L1 expression and neoadjuvant immunotherapy response is still controversial. Therefore, the selection of new adjuvant immunotherapy patients is further clarified by using new potential biomarkers, and further research is needed to screen the benefited population.
Disclosure of Invention
The present application is based on the discovery and recognition by the inventors of the following problems:
in the present application, through a large number of experimental searches, the inventors found that the copy number amplification load of a predetermined gene can be used to predict the therapeutic efficacy of a subject tumor immune checkpoint inhibitor, and when the copy number amplification load of the gene reaches a specific threshold, it can be considered that a better immune checkpoint inhibitor treatment can be obtained for the subject, and further, the response rate of the lung cancer immune checkpoint inhibitor treatment can be significantly improved.
Accordingly, in a first aspect of the invention, the invention proposes the use of a gene set comprising at least one of the genes set forth in table 1 as a marker for predicting the efficacy of a lung cancer immune checkpoint inhibitor therapy in a subject. The marker combination according to the embodiments of the present invention can effectively predict the therapeutic efficacy of the subject tumor immune checkpoint inhibitor, thereby increasing the response rate of the lung cancer immune checkpoint inhibitor therapy.
Table 1:
ABL1 AKT1 AKT2 AKT3 ALK ALOX12B APC ARID1A ARID1B ARID2
ASXL1 ATM ATR AURKA AURKB AXIN1 AXL BAP1 BARD1 BCL2L1
BLM BRAF BRCA1 BRCA2 BRD4 BRIP1 CALR CARD11 CASP8 CBFB
CBL CCND1 CCND2 CCND3 CCNE1 CD274 CD79A CD79B CDC73 CDH1
CDK12 CDK4 CDK6 CDK8 CDKN2A CHEK1 CHEK2 CIC CREBBP CSF1R
CSF3R CTCF CTNNB1 CUL3 CYLD DAXX DDR2 DICER1 DIS3 DNMT3A
DOT1L EGFR EP300 EPHA3 EPHA5 EPHA7 EPHB1 ERBB2 ERBB3 ERBB4
ERCC4 ERG ESR1 ETV1 ETV6 EZH2 FANCA FANCC FANCG FAS
FAT1 FBXW7 FGFR1 FGFR2 FGFR3 FGFR4 FH FLCN FLT1 FLT3
FLT4 FOXP1 FUBP1 GATA2 GATA3 GLI1 GNA11 GNA13 GNAQ GNAS
GRIN2A GSK3B HGF HNF1A HRAS IDH1 IDH2 IGF1R IGF2 IKBKE
IL7R IL8 INPP4B IRF4 IRS2 JAK1 JAK2 JAK3 KDM5A KDR
KEAP1 KIT KMT2A KMT2C KMT2D KRAS LMO1 LYN MAP2K1 MAP2K2
MAP2K4 MAP3K1 MDM2 MDM4 MEF2B MEN1 MET MITF MLH1 MPL
MRE11A MSH2 MSH3 MSH6 MTOR MUTYH MYD88 NBN NF1 NF2
NFE2L2 NFKBIA NKX2-1 NOTCH1 NOTCH2 NOTCH3 NPM1 NSD1 NT5C2 NTRK1
NTRK2 NTRK3 NUP93 PALB2 PARK2 PARP1 PAX5 PBRM1 PDCD1 PDCD1LG2
PDGFRA PDGFRB PIGF PIK3C2G PIK3CA PIK3CB PIK3CG PIK3R1 PIK3R2 PLCG2
PMS2 POLD1 POLE PPARG PPP2R1A PRDM1 PREX2 PRKAR1A PRKCI PTCH1
PTEN PTPN11 RAC1 RAD21 RAD50 RAD51 RAD51B RAD51C RAD51D RAD52
RAD54L RAF1 RARA RB1 RET RICTOR RNF43 ROS1 RPTOR RUNX1
SDHA SDHB SDHC SDHD SETD2 SF3B1 SMAD2 SMAD3 SMAD4 SMARCA4
SMARCB1 SMO SPEN SPOP SRC STAT3 STK11 SUFU SYK TBX3
TERT TET2 TGFBR2 TMPRSS2 TNFAIP3 TNFRSF14 top1 TP53 TSC1 TSC2
TSHR U2AF1 VEGFA WHSC1 WHSC1L1 WT1 XPO1
according to an embodiment of the present invention, the above-mentioned use may further include at least one of the following additional technical features:
according to an embodiment of the invention, the lung cancer is non-small cell lung cancer. The gene set is used for predicting the treatment effect of the immune checkpoint inhibitor on patients with non-small cell lung cancer, and the accuracy is high.
According to an embodiment of the invention, the immune checkpoint inhibitor is a PD-1/PD-L1 inhibitor. According to a specific embodiment of the present invention, when the immune checkpoint inhibitor is a PD-1/PD-L1 inhibitor, the marker may accurately predict the therapeutic efficacy of the immune checkpoint inhibitor for lung cancer in the subject.
According to embodiments of the invention, the determination of whether the subject immune checkpoint inhibitor treatment is effective is based on the gene copy number amplification load of the gene set.
According to embodiments of the invention, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
According to an embodiment of the present invention, the gene copy number amplification burden is the total number of genes with a gene copy number > 3.
In a second aspect of the invention, a computer-readable storage medium is presented having stored thereon a computer program for predicting lung cancer immune checkpoint inhibitor efficacy in a subject. According to an embodiment of the invention, the program, when executed by the processor, obtains a gene copy number mutation load for the gene set. The computer-readable storage medium according to embodiments of the invention can accurately obtain the gene copy number mutation load of the gene set that can effectively predict whether the subject is suitable for lung cancer immune checkpoint inhibitor therapy.
According to an embodiment of the invention, the set of genes comprises at least one of the genes as shown in table 1.
In a third aspect of the invention, an electronic device for predicting the efficacy of a lung cancer immune checkpoint inhibitor in a subject is presented. According to an embodiment of the invention, comprising: the computer-readable storage medium of the second aspect; and one or more processors for executing the program in the computer-readable storage medium. An electronic device according to an embodiment of the present invention is capable of executing a program in the computer-readable storage medium using the processor to accurately obtain a gene copy number mutation load of the aforementioned gene set that is effective to predict whether the subject is suitable for gastrointestinal tumor immune checkpoint inhibitor therapy. Thus, the electronic device can accurately predict lung cancer immune checkpoint inhibitor efficacy in the subject.
In a fourth aspect of the invention, the invention proposes the use of a gene copy number amplification load of a gene set comprising at least one of the genes listed in table 1 for predicting the efficacy of a treatment with an immune checkpoint inhibitor for lung cancer in a subject. According to the gene copy number amplification load of the gene set disclosed by the embodiment of the invention, the treatment curative effect of the lung cancer immune checkpoint inhibitor of a subject can be accurately predicted, and the response rate of the lung cancer immune checkpoint inhibitor can be remarkably improved.
According to an embodiment of the present invention, the above-mentioned use may further include at least one of the following additional technical features:
according to embodiments of the invention, the subject is judged whether immune checkpoint inhibitor therapy is effective based on the gene copy number amplification load of the gene set.
According to embodiments of the invention, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
According to an embodiment of the present invention, the gene copy number amplification burden is the total number of genes with a gene copy number > 3.
According to an embodiment of the present invention, the gene copy number amplification load of the gene set is obtained by: 1) obtaining a baseline of coverage depth for a gene capture region of a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes; 2) obtaining a depth of coverage of a gene capture region of a gene set derived from the tumor tissue based on sequencing data of the gene set in the tumor tissue; 3) obtaining copy numbers of gene capture regions of the gene set based on log2 values of ratios of baseline depths of coverage of the gene capture regions from the tumor tissue gene set and the gene capture regions from the leukocyte gene set; 4) obtaining the copy number of the gene set based on the copy number of the gene capturing area of the gene set and the weight occupied by the copy number; 5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set. According to an embodiment of the present invention, the weight is not particularly limited, and those skilled in the art can adjust the weight occupied by the copy number of each capture region of the gene set according to the purpose of the experiment and the experimental method.
According to an embodiment of the present invention, the sequencing data of the gene set in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
according to an embodiment of the present invention, the DNA library 1 of the subject is constructed based on the nucleic acid sample 1 of the subject.
According to an embodiment of the present invention, the nucleic acid sample 1 is derived from leukocytes of the subject.
According to an embodiment of the invention, the sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject.
According to an embodiment of the present invention, the DNA library 2 of the subject is constructed based on the nucleic acid sample 2 of the subject.
According to an embodiment of the invention, said nucleic acid sample 2 is derived from tumor tissue of said subject.
In a fifth aspect of the invention, a method of predicting the efficacy of a treatment with an immune checkpoint inhibitor for lung cancer in a subject is presented. According to an embodiment of the invention, comprising: determining whether the subject immune checkpoint inhibitor treatment is effective based on the gene copy number amplification load of the subject gene set to be tested. According to the method provided by the embodiment of the invention, whether the treatment of the immune checkpoint inhibitor of the object is effective or not can be accurately predicted according to the gene copy number amplification load of the gene set of the object to be detected, so that the response rate of the treatment of the immune checkpoint inhibitor of lung cancer is improved.
According to an embodiment of the present invention, the method may further include at least one of the following additional technical features:
according to an embodiment of the invention, the lung cancer is non-small cell lung cancer.
According to embodiments of the invention, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
According to an embodiment of the invention, the set of genes comprises at least one of the genes as shown in table 1.
According to an embodiment of the present invention, the gene copy number amplification burden is the total number of genes with a gene copy number > 3.
According to an embodiment of the present invention, the gene copy number amplification load of the gene set is obtained by: 1) obtaining a baseline of coverage depth for a gene capture region of a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes; 2) obtaining a depth of coverage of a gene capture region of a gene set derived from the tumor tissue based on sequencing data of the gene set in the tumor tissue; 3) obtaining copy numbers of gene capture regions of the gene set based on log2 values of ratios of coverage depths of the gene capture regions derived from the tumor tissue gene set to baseline coverage depths of gene capture regions of the leukocyte gene set; 4) obtaining the gene copy number of the gene set based on the copy number of the gene capture region of the gene set and the weight occupied by the copy number; 5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set. According to an embodiment of the present invention, the setting of the weight is not particularly limited, and those skilled in the art can adjust the weight occupied by the copy number of each capture region of the gene set according to the purpose of the experiment and the experimental method.
According to an embodiment of the present invention, the sequencing data of the gene set in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
according to an embodiment of the present invention, the DNA library 1 of the subject is constructed based on the nucleic acid sample 1 of the subject.
According to an embodiment of the invention, said nucleic acid sample 1 is derived from leukocytes of said subject.
According to an embodiment of the invention, the sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject.
According to an embodiment of the present invention, the DNA library 2 of the subject is constructed based on the nucleic acid sample 2 of the subject.
According to an embodiment of the invention, said nucleic acid sample 2 is derived from tumor tissue of said subject.
In a sixth aspect of the invention, a method of partitioning a population is presented. According to an embodiment of the invention, comprising: partitioning individuals in the population that are suitable or unsuitable for treatment with a lung cancer immune checkpoint inhibitor based on the gene copy number amplification burden of the gene sets of the individuals in the population. According to the method provided by the embodiment of the invention, whether the treatment of the object immune checkpoint inhibitor is effective or not can be accurately predicted according to the size of the gene copy number amplification load of the gene set of the individual to be detected, and the population can be divided into the population suitable for the treatment of the lung cancer immune checkpoint inhibitor and the population not suitable for the treatment of the lung cancer immune checkpoint inhibitor according to the prediction result.
According to an embodiment of the present invention, the method may further include at least one of the following additional technical features:
according to an embodiment of the invention, the set of genes comprises at least one of the genes as shown in table 1.
According to an embodiment of the invention, the lung cancer is non-small cell lung cancer.
According to embodiments of the invention, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
According to an embodiment of the invention, the set of genes comprises at least one of the genes shown in table 1.
According to an embodiment of the present invention, the gene copy number amplification burden is the total number of genes whose gene copy numbers > 3.
According to an embodiment of the present invention, the gene copy number amplification load of the gene set is obtained by: 1) obtaining a baseline of coverage depth for a gene capture region of a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes; 2) obtaining a depth of coverage of a gene capture region of a gene set derived from the tumor tissue based on sequencing data of the gene set in the tumor tissue; 3) obtaining the copy number of a gene capture region of the gene set based on a log2 value of the ratio of the coverage depth of the gene capture region derived from the tumor tissue gene set to a baseline coverage depth of a gene capture region derived from a leukocyte gene set; 4) obtaining the copy number of the gene set based on the copy number of the gene capturing area of the gene set and the weight occupied by the copy number; 5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set. According to an embodiment of the present invention, the setting of the weight is not particularly limited, and those skilled in the art can adjust the weight occupied by the copy number of each capture region of the gene set according to the purpose of the experiment and the experimental method.
According to an embodiment of the present invention, the sequencing data of the gene set in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
according to an embodiment of the present invention, the DNA library 1 of the subject is constructed based on the nucleic acid sample 1 of the subject.
According to an embodiment of the invention, said nucleic acid sample 1 is derived from leukocytes of said subject.
According to an embodiment of the invention, the sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject.
According to an embodiment of the present invention, the DNA library 2 of the subject is constructed based on the nucleic acid sample 2 of the subject.
According to an embodiment of the invention, said nucleic acid sample 2 is derived from tumor tissue of said subject.
In a seventh aspect of the invention, a system for predicting the efficacy of a lung cancer immune checkpoint inhibitor in a subject is provided. According to an embodiment of the invention, comprising: a means for determining the efficacy of treatment with a lung cancer immune checkpoint inhibitor for determining whether treatment with the subject immune checkpoint inhibitor is effective based on the gene copy number amplification load of the subject gene set to be tested. The system provided by the embodiment of the invention can effectively obtain the size of the gene copy number amplification load of the gene set of the object to be detected, so as to judge whether the object immune checkpoint inhibitor treatment is effective, and the response rate of the lung cancer immune checkpoint inhibitor treatment can be improved by applying the system to the object with the effective immune checkpoint inhibitor treatment.
According to an embodiment of the present invention, the system may further include at least one of the following additional technical features:
according to embodiments of the invention, a gene copy number amplification load of less than 8.5 in the subject is indicative of efficacy of treatment with the immune checkpoint inhibitor in the subject.
According to an embodiment of the invention, the set of genes comprises at least one of the genes as shown in table 1.
According to an embodiment of the invention, the system further comprises: a leukocyte gene set coverage depth baseline obtaining device for obtaining a coverage depth baseline of a gene capture region derived from a leukocyte gene set based on sequencing data of the gene set in leukocytes; a device for obtaining the coverage depth of a tumor tissue gene set, which is used for obtaining the coverage depth of a gene capture area derived from the tumor tissue gene set based on the sequencing data of the gene set in the tumor tissue; a gene set gene capture region copy number obtaining device, connected with the leukocyte gene set coverage depth baseline obtaining device and the tumor tissue gene set coverage depth obtaining device, for obtaining the copy number of the gene capture region of the gene set based on the log2 value of the ratio of the coverage depth of the gene capture region derived from the tumor tissue gene set and the coverage depth baseline of the gene capture region derived from the leukocyte gene set; the device for obtaining the gene copy number of the gene set is connected with the device for obtaining the copy number of the gene capture area of the gene set and is used for obtaining the gene copy number of the gene set based on the copy number of each capture area of the gene set and the weight occupied by the copy number; the device for obtaining the gene copy number amplification load of the gene set is connected with the device for obtaining the gene copy number of the gene set and the device for determining the curative effect of the lung cancer immune checkpoint inhibitor and is used for obtaining the gene copy number amplification load of the gene set based on the gene copy number of the gene set.
According to an embodiment of the invention, the system further comprises: a DNA library constructing apparatus 1 for constructing a DNA library 1 of the subject based on a nucleic acid sample 1 of the subject; a DNA library constructing apparatus 2 for constructing a DNA library 2 of the subject based on the nucleic acid sample 2 of the subject; a sequencing data obtaining apparatus 1, said sequencing data obtaining apparatus 1 being connected to said DNA library constructing apparatus 1 and said leukocyte gene set coverage depth baseline obtaining apparatus, and being configured to perform high-throughput sequencing using a DNA library 1 of said subject so as to obtain sequencing data of said gene set in said leukocytes; a sequencing data acquisition device 2, wherein the sequencing data acquisition device 2 is connected with the DNA library construction device 2 and the coverage depth acquisition device of the tumor tissue gene set and is used for carrying out high-throughput sequencing by using the DNA library 2 of the object so as to obtain the sequencing data of the gene set in the white blood cells.
In an eighth aspect of the invention, a kit for predicting the efficacy of a treatment with an immune checkpoint inhibitor of lung cancer in a subject is presented. According to an embodiment of the invention, a reagent for detecting any gene in the gene set is included. The kit provided by the embodiment of the invention can effectively detect a sample separated from the body of the object, and based on a reagent for detecting any gene in the gene set, the detected sample is the copy number of any gene in the gene set, so that the curative effect of the lung cancer immune checkpoint inhibitor treatment of the object can be accurately predicted, and the reagent is applied to the object with the effective immune checkpoint inhibitor treatment, so that the response rate of the lung cancer immune checkpoint inhibitor treatment is improved.
According to an embodiment of the present invention, the kit may further comprise at least one of the following additional technical features:
according to an embodiment of the invention, the set of genes comprises at least one of the genes as shown in table 1.
According to an embodiment of the invention, the lung cancer is non-small cell lung cancer.
According to an embodiment of the invention, at least one of the following is included: DNA extraction reagents, banking reagents or high throughput sequencing reagents.
According to an embodiment of the invention, the kit further comprises: a reference data set used as a reference for a gene set.
According to an embodiment of the present invention, the kit further comprises a first computer program product for performing the method of predicting lung cancer immune checkpoint inhibitor efficacy in a subject according to the fifth aspect.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a diagram of a system apparatus according to an embodiment of the present invention, the system comprising means for determining the efficacy of a lung cancer immune checkpoint inhibitor;
FIG. 2 is a diagram of a system apparatus according to an embodiment of the present invention, the system includes a lung cancer immune checkpoint inhibitor efficacy determining apparatus, a leukocyte gene set coverage depth baseline obtaining apparatus, a tumor tissue gene set coverage depth obtaining apparatus, a gene set gene capture region copy number obtaining apparatus, a gene set gene copy number amplification load obtaining apparatus;
fig. 3 is a diagram of an apparatus of a system according to an embodiment of the present invention, the system including a lung cancer immune checkpoint inhibitor therapeutic apparatus, a white blood cell gene set coverage depth baseline acquisition apparatus, a tumor tissue gene set coverage depth acquisition apparatus, a gene set gene capture region copy number acquisition apparatus, a gene set gene copy number amplification load acquisition apparatus, a DNA library construction apparatus 1, a DNA library construction apparatus 2, a sequencing data acquisition apparatus 1, and a sequencing data acquisition apparatus 2;
FIG. 4 is an experimental flow diagram according to an embodiment of the invention;
FIG. 5 is a graph of analysis of the copy number expansion load results calculated for 22 non-small cell lung cancer patients receiving neoadjuvant treatment with a PD-1 inhibitor, in accordance with an embodiment of the present invention; wherein,
FIG. a is a graph showing the results of analysis of the correlation between copy number expansion load and the pathological remission rate after neoadjuvant immunotherapy,
panel b is a graph of the results of comparing the copy number expansion load of patients with major pathological remission (MPR, defined as residual surviving tumor ≦ 10% during surgery) and non-small cell lung cancer patients without major pathological remission (non-MPR),
panels c and d are graphs of the distribution of MPR and non-MPR patients in the high copy number amplification burden or low copy number amplification burden groups; and
FIG. 6 is a graph showing the results of calculating Tumor Mutation Burden (TMB), PD-L1 (expression level detected using 22C3 antibody, tumor diagnosis score (TPS. gtoreq. 50% is regarded as high expression) and Area Under ROC Curve (AUC) of 3 indexes of copy number amplification burden (tumor Under ROC Curve) of 22 non-small cell lung cancer patients receiving new adjuvant therapy with PD-1 inhibitor using Receiver Operating Characteristic Curve (ROC) to evaluate the copy number amplification burden, TMB and PD-L1 indexes each ability to predict the efficacy of new adjuvant immunotherapy with PD-1 inhibitor, according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs; as used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Herein, the term "about" is used to provide the flexibility and inaccuracy associated with a given term, measure or value. The degree of flexibility for a particular variable can be readily determined by one skilled in the art.
Concentrations, amounts, and other numerical data may be presented herein in a range format. It is to be understood that such a range format is used merely for convenience and brevity and should be interpreted flexibly to include not only the numerical values explicitly recited as the limits of the range, but also to include all the individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly recited. Moreover, such an interpretation should apply regardless of the breadth of the range or feature being described.
Any steps recited in any method or process claims may be executed in any order and are not limited to the order presented in the claims.
As used herein, the terms "tissue sample" and "tumor tissue sample" are used interchangeably and refer to a baseline tumor tissue sample prior to neoadjuvant immunotherapy of a patient.
As used herein, the terms "tumor tissue DNA", "tissue DNA" and "FFPE-DNA" are used interchangeably and refer to the DNA of a baseline tumor tissue sample from a patient prior to neoadjuvant therapy.
Herein, Copy Number Variation (CNV) of DNA fragments is caused by rearrangement of genome, including amplification and deletion of DNA fragments greater than 1kb in length. CNVs are important components of genomic structural variation and are one of the important causative factors of human diseases. Abnormal DNA copy number changes are a clinical indicator of the prognosis for the development of a tumor and are considered to have the potential to guide the administration of drugs to patients with tumors. The high-throughput sequencing CNV can detect large CNV fragments on the whole genome level or CNV of target gene interval detection DNA fragments.
Herein, copy number amplification (CN gain) refers to gene copy number >3 and copy number deletion (CN loss) refers to gene copy number < 1.5.
Herein, the term "novel adjuvant therapy with immune checkpoint inhibitors" refers to a treatment regimen performed before surgery to control and eliminate tumors by restoring a collective anti-tumor immune response through inhibition of immune checkpoint function.
Herein, the term "single-ended mode sequencing" refers to sequencing only one single strand of a library DNA molecule; the term "paired-end mode sequencing" refers to the separate sequencing of two complementary single strands of the same library DNA molecule.
Herein, the term "depth of coverage" is calculated by dividing the number of all short-read bases that match the genome by the length of the genome. It is usually expressed as 1X, 2X, 3X,. (1, 2 or 3 fold coverage), often referred to as sequencing depth or coverage depth (depth of coverage).
Herein, the term "Median", also called Median, a term used in statistics, is a number in the middle of a set of data arranged in sequence, and represents a value in a sample, population or probability distribution, which can divide a value set into two equal parts. For a finite number set, the median can be found by sorting all the observed values high and low. If there are even numbers of observations, the mean of the two most intermediate values is taken as the median.
Herein, the term "weight" is a relative concept. The weight of an indicator is the relative importance of the indicator in the overall evaluation and can be expressed as a factor or percentage of the indicator, e.g., the copy number of gene 1 is 4 × 10% +5 × 20% +6 × 70% when the copy number of the A, B, C capture region of gene 1 is 4, 5, 6, respectively, and the copy number of A, B, C capture region is 10%, 20%, 70%.
For the convenience of understanding, the inventors briefly describe the present invention, and in the present invention, the inventors predict the efficacy of neoadjuvant therapy of immune checkpoint inhibitors for patients with non-small cell lung cancer based on copy number amplification loads calculated from gene copy number variations in the DNA of tumor tissues of patients with non-small cell lung cancer. The method comprises the following specific steps: s1, collecting tumor tissues and paired leukocyte samples before new adjuvant therapy of the patient with non-small cell lung cancer, and extracting tumor tissue DNA and leukocyte DNA; s2, constructing a gene library by adopting tumor tissue DNA and leucocyte DNA; s3, utilizing the specific hybridization of the target sequence capture probe and the target area to capture and enrich the target gene from the gene library and obtain the target sequencing data of the tumor tissue DNA and the leucocyte DNA; s4, using the matched leucocyte DNA as a control, calculating the copy number value of the target gene of the tumor tissue DNA sample; s5, calculating the gene copy number amplification load of the tumor tissue; s6, predicting the curative effect of the non-small cell lung cancer patient immune check point inhibitor neoadjuvant therapy according to the copy number expansion load. Wherein, after the copy number variation obtained in step S4, the following steps are performed: A) calculating the copy number amplification load value of the tumor tissue sample of the patient: copy number amplification load-the total number of genes in each sample in which copy number amplification occurred; wherein copy number amplification represents a gene copy number > 3; B) and predicting the new adjuvant therapy effect of the immune checkpoint inhibitor of the patient with the non-small cell lung cancer according to the copy number expansion load. The therapeutic effect comprises the therapeutic effect of the novel adjuvant therapy of the non-small cell lung cancer immune checkpoint inhibitor, and the immune checkpoint is PD-1. And B) selecting a threshold value of X, wherein the tumor patients more than or equal to X are high-risk patients, and the tumor patients less than X are low-risk patients. Among them, in non-small cell lung cancer patients, the resulting copy number expansion burden is classified into low groups of tumor patients according to the threshold X, and is more likely to benefit from neoadjuvant treatment with immune checkpoint inhibitors. More preferably, when the threshold is 8.5, the method can predict the curative effect of the immune checkpoint inhibitor more accurately, wherein the tumor patients with the tumor size of more than or equal to 8.5 are high-risk patients, and the tumor patients with the tumor size of less than 8.5 are low-risk patients, wherein the threshold is not particularly limited, and one skilled in the art can select different thresholds according to different experimental or screening purposes.
In some embodiments of the present invention, a system for predicting the efficacy of a lung cancer immune checkpoint inhibitor in a subject is provided, as shown in figure 1, comprising: a device for determining lung cancer immune checkpoint inhibitor therapeutic efficacy S1000, the device for determining lung cancer immune checkpoint inhibitor therapeutic efficacy S1000 configured to determine whether a subject immune checkpoint inhibitor therapy is effective based on a gene copy number amplification load of a gene set of the subject to be tested. The system provided by the embodiment of the invention can effectively obtain the size of the gene copy number amplification load of the gene set of the object to be detected, so as to judge whether the object is effective in treatment of the immune checkpoint inhibitor, and the response rate of the lung cancer immune checkpoint inhibitor treatment can be improved by applying the system to the object with effective treatment of the immune checkpoint inhibitor.
According to some embodiments of the present invention, the system may further comprise at least one of the following additional features:
according to some embodiments of the invention, a gene copy number amplification load of less than 8.5 in the subject is indicative of efficacy of treatment with the immune checkpoint inhibitor in the subject.
According to some embodiments of the invention, the gene set comprises at least one of the genes shown in table 1.
According to some embodiments of the invention, as shown in fig. 2, the system further comprises: a leukocyte gene set coverage depth baseline obtaining device S300 for obtaining a coverage depth baseline of a gene capture region derived from a leukocyte gene set based on sequencing data of the gene set in leukocytes; a tumor tissue gene set coverage depth obtaining device S600 for obtaining a coverage depth of a gene capture region derived from a tumor tissue gene set based on sequencing data of the gene set in a tumor tissue; a gene set gene capture region copy number obtaining device S700, the gene set gene capture region copy number obtaining device S700 being connected with the leukocyte gene set coverage depth baseline obtaining device S300 and the tumor tissue gene set coverage depth baseline obtaining device S600, and being used for obtaining the domain copy number of the gene capture region of the gene set based on the log2 value of the ratio of the coverage depth of the gene capture region derived from the tumor tissue gene set to the coverage depth baseline of the gene capture region derived from the leukocyte gene set; a gene set gene copy number obtaining device S800, wherein the gene set gene copy number obtaining device S800 is connected with the gene set gene capture region copy number obtaining device S700 and is used for obtaining the gene copy number of the gene set based on the copy number of each capture region of the gene set and the occupied weight of the copy number; a gene copy number amplification load obtaining device S900 of the gene set, wherein the gene copy number amplification load obtaining device S900 of the gene set is connected with the gene copy number obtaining device S800 of the gene set and the device S1000 for determining the curative effect of the lung cancer immune check point inhibitor, and is used for obtaining the gene copy number amplification load of the gene set based on the gene copy number of the gene set.
According to some embodiments of the invention, as shown in fig. 3, the system further comprises: a DNA library constructing apparatus 1S100 for constructing a DNA library 1 of the subject based on a nucleic acid sample 1 of the subject; a DNA library constructing device 2S400 for constructing a DNA library 2 of the subject based on the nucleic acid sample 2 of the subject; a sequencing data obtaining means 1S200, said sequencing data obtaining means 1S200 being connected to said DNA library constructing means 1S100 and said leukocyte gene set coverage depth baseline obtaining means S300, and being adapted to perform high-throughput sequencing with said DNA library 1 of said subject so as to obtain sequencing data derived from said gene set in said leukocytes; a sequencing data obtaining means 2S500, said sequencing data obtaining means 2S500 being connected to said DNA library constructing means 2S400 and said tumor tissue gene set coverage depth obtaining means S600, and being adapted to perform high throughput sequencing using said subject DNA library 2 so as to obtain sequencing data of said gene set in said white blood cells.
The invention will now be described with reference to specific examples, which are intended to be illustrative only and not to be limiting in any way.
The examples, where specific techniques or conditions are not indicated, are to be construed according to the techniques or conditions described in the literature in the art or according to the product specifications. The reagents or instruments used are not indicated by the manufacturer, and are all conventional products commercially available.
Example 1 Effect of copy number expansion load value on the therapeutic efficacy of immune checkpoint inhibitors in non-Small cell Lung cancer patients
In this example, the treatment efficacy is predicted by establishing copy number expansion load values based on 22 cases of non-small cell lung cancer patients receiving new adjuvant therapy with PD-1 inhibitor, and predicting the immunotherapy efficacy by evaluating the copy number expansion load of the patients, and the operation flow of this experiment is shown in fig. 4. The specific experimental contents are as follows:
1.1 Experimental procedures
1) Baseline tumor tissues and paired leukocyte samples were collected prior to neoadjuvant therapy for 22 non-small cell lung cancer patients.
2) Extracting tumor tissue and leukocyte DNA:
extracting tumor tissues: extracting 22 cases of non-small cell lung cancer patient tumor tissue DNA (FFPE-DNA) by adopting a magnetic bead method paraffin DNA pre-packaging extraction kit and a 48-bit nucleic acid extractor;
extracting a white blood cell sample: extracting leukocyte DNA by adopting a TGuide S32 magnetic bead method blood genome extraction kit-T5C and a TGuide S32 full-automatic nucleic acid extraction and purification instrument;
DNA concentration was quantified using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer;
the FFPE-DNA and the leukocyte DNA obtained by extraction are fragmented by a Covaris M220 ultrasonicator, and the DNA is broken into 150-200bp fragments.
3) Pool-building hybridization capture enrichment
FFPE-DNA sample library construction: constructing a DNA library by using a KAPA Hyper Prep Kit;
white blood cell DNA sample library construction: fragmentation of gDNA and end-repair addition a was performed with the tiaseq fast DNA fragmentation/end-repair/dA addition module, followed by adaptor ligation with the tiaseq fast ligation module. Purifying the joint connection product by using an Agencour AMPure XP after joint connection, then finishing Library Amplification by using KAPA Library Amplification kit, and purifying the amplified Library by using Agencour AMPure XP magnetic beads;
quality control of the library: quantitating the library concentration using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer;
library hybrid capture: FFPE-DNA and white blood cell DNA library pooling together, using a vacuum concentrator to evaporate and dry, and adding IDT hybridization capture reagent and panel probe to perform target fragment hybridization capture reaction.
Quality control of the capture and enrichment library: the DNA concentration was quantified using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer, and the library fragment distribution was examined using an Agilent 2100 nucleic acid fragment analyzer.
4) Sequencing on machine
High throughput sequencing was performed in paired end mode using a Novaseq 6000 (neminer) sequencer.
1.2 copy number amplification load analysis:
1) the sequenced tumor tissue DNA Panel sequencing data were aligned according to the human genome (hg19) using BWA software (v0.7.17) according to standard analytical protocols, and BAM files were de-duplicated and assembled using Picard toolkit (v2.1.0) and GATK analytical tool (v 3.7).
2) Copy number variation of each gene in tumor samples was analyzed using CNVkit (v0.9.2) with paired leukocyte DNA as control, and gene copy number >3 was considered as copy number amplification.
3) Copy number amplification load was calculated for each sample based on copy number amplification for 22 patients:
copy number amplification load-the total number of genes in each sample in which copy number amplification occurred; wherein the copy number amplification is a gene copy number > 3.
4) Dividing the patients into a group with high copy number amplification load and a group with low copy number amplification load according to a threshold value (the threshold value is the median of 22 patient gene copy number amplification loads), and carrying out correlation analysis on the copy number amplification loads and the curative effect of the patients receiving new adjuvant immunotherapy.
Thirdly, a result part:
a total of 22 non-small cell lung cancer patients were tested for analysis of baseline samples of immune checkpoint inhibitors prior to neoadjuvant therapy. And calculating the copy number amplification load value of the tumor tissue sample of the patient. The correlation analysis curve in panel a of FIG. 5 shows that the copy number expansion burden of the baseline tumor tissue sample before treatment of the patient is significantly negatively correlated with the primary pathological remission rate; figure 5, panel b, shows patients with significantly lower copy number amplification burden for obtaining Major Pathology Relief (MPR) than non-MPR.
The patients were grouped using the threshold (copy number expansion load value ═ 8.5), and the results of the experiment are shown in the graphs c and d in fig. 5, the patients in the low copy number expansion load group are more likely to benefit from the new adjuvant immunotherapy with PD-1 inhibitor, and the patients in the low copy number expansion load group obtain MPR at a higher rate.
Example 2 copy number expansion load value, TMB, PD-L1 methods for predicting treatment efficacy of immune checkpoint inhibitor in lung cancer patients
This example is based on the ability of 22 non-small cell lung cancer patients receiving neoadjuvant treatment with a PD-1 inhibitor to compare copy number expansion burden, TMB and PD-L1 for predicting the efficacy of neoadjuvant immunotherapy. The specific experimental contents are as follows:
2.1 Experimental procedures
1) Baseline tumor tissues and paired leukocyte samples were collected prior to neoadjuvant therapy for 22 non-small cell lung cancer patients.
2) Extracting tumor tissue and leukocyte DNA:
extracting tumor tissues: extracting 22 cases of non-small cell lung cancer patient tumor tissue DNA (FFPE-DNA) by adopting a magnetic bead method paraffin DNA pre-packaging extraction kit and a 48-bit nucleic acid extractor;
white blood cell sample extraction: extracting leukocyte DNA by adopting a TGuide S32 magnetic bead method blood genome extraction kit-T5C and a TGuide S32 full-automatic nucleic acid extraction and purification instrument;
DNA concentration was quantified using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer;
the FFPE-DNA and the leukocyte DNA obtained by extraction are fragmented by a Covaris M220 ultrasonicator, and the DNA is broken into 150-200bp fragments.
3) Pool-building hybridization capture enrichment
FFPE-DNA sample library construction: constructing a DNA library by using a KAPA Hyper Prep Kit;
white blood cell DNA sample library construction: fragmentation of gDNA and end-repair plus a was performed with tiaseq fast DNA fragmentation/end-repair/dA addition module, followed by linker ligation with tiaseq fast ligation module. Purifying the joint connection product by using an Agencour AMPure XP after joint connection, then finishing Library Amplification by using KAPA Library Amplification kit, and purifying the amplified Library by using Agencour AMPure XP magnetic beads;
quality control of the library: quantitating the library concentration using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer;
library hybrid capture: after FFPE-DNA and leukocyte DNA library firing are carried out together, evaporating to dryness by using a vacuum concentrator, and adding an IDT hybridization capture reagent and a panel probe to carry out a target fragment hybridization capture reaction;
quality control of the capture and enrichment library: the DNA concentration was quantified using an Equalbit 1 × dsDNA HS Assay Kit and a Qubit 4.0 fluorometer, and the library fragment distribution was examined using an Agilent 2100 nucleic acid fragment analyzer.
4) Sequencing on machine
High throughput sequencing was performed in paired end mode using a Novaseq 6000 (neminer) sequencer.
5) The PD-L1 positive tumor cell proportion of the tumor tissue is detected by using a 22C3 antibody by using an immunohistochemical method.
2.2 data analysis
1) For the sequenced tumor tissue DNA Panel sequencing data, BAM files were de-duplicated and assembled using Picard toolkit (v2.1.0) and GATK analysis tool (v 3.7) according to standard analytical procedures using BWA software (v0.7.17) for sequence alignment according to the human genome (hg 19).
2) Copy number variation of each gene in tumor samples was analyzed using CNVkit (v0.9.2) with paired leukocyte DNA as control, assuming gene copy number >3 as copy number amplification and gene copy number <1.5 as copy number deletion.
3) Copy number amplification load was calculated for each sample based on copy number amplification for 22 patients:
copy number amplification load-the total number of genes in each sample in which copy number amplification occurred; wherein copy number amplification represents a gene copy number > 3.
4) Tumor tissue sample TMB values were calculated for 22 patients with paired leukocyte DNA as a control.
5) Based on immunohistochemistry results, tumor tissue samples from 22 patients were obtained with PD-L1 positive tumor cell proportion (TPS).
6) The area under the curve (AUC) is calculated by using an ROC curve, and the prediction capability of 3 indexes of copy number amplification load, TMB and PD-L1 on the curative effect of the new adjuvant immunotherapy of the PD-1 inhibitor is evaluated.
2.3 analysis of results
The primary line samples of 22 patients with non-small cell lung cancer tested with immune checkpoint inhibitor before neoadjuvant therapy were analyzed to calculate the copy number expansion load value, TMB value and PD-L1 TPS of the patient tumor tissue samples.
Specific experimental results as shown in fig. 6, the area under the ROC curve (AUC) of copy number expansion load was higher (AUC 0.8143) compared to the major pathological remission rates predicted by TMB and PD-L1 TPS to suppress PD-1 in neoadjuvant non-small cell lung cancer patients. The ability of copy number expansion load to predict the rate of primary pathological remission in non-small cell lung cancer patients treated with the novel adjuvant of PD-1 inhibitors was shown to be superior to TMB and PD-L1 TPS.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims (24)

1. Use of a gene set comprising at least one of the genes set forth in table 1 as a marker for predicting the efficacy of an immune checkpoint inhibitor for lung cancer in a subject.
2. The use according to claim 1, wherein the lung cancer is non-small cell lung cancer.
3. The use according to claim 1, wherein the immune checkpoint inhibitor is a PD-1/PD-L1 inhibitor.
4. The use of claim 1, wherein the determination of whether the subject is effectively treated with an immune checkpoint inhibitor is based on the gene copy number amplification load of the gene set,
optionally, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
5. Use according to claim 4, wherein the gene copy number amplification burden is the total number of genes with a gene copy number > 3.
6. A computer-readable storage medium on which is stored a computer program for predicting lung cancer immune checkpoint inhibitor efficacy in a subject, wherein the program when executed by a processor obtains a gene copy number mutation load for a gene set;
optionally, the gene set comprises at least one of the genes set forth in table 1.
7. An electronic device for predicting lung cancer immune checkpoint inhibitor efficacy in a subject, comprising: the computer-readable storage medium of claim 6; and one or more processors to execute the program in the computer-readable storage medium.
8. Use of a gene copy number amplification load of a gene set comprising at least one of the genes set forth in table 1 in predicting the efficacy of a treatment with an immune checkpoint inhibitor for lung cancer in a subject.
9. The use of claim 8, wherein the determination of whether the subject is effectively treated with an immune checkpoint inhibitor is based on the gene copy number amplification load of the gene set,
optionally, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor.
10. Use according to claim 8 or 9, characterized in that the gene copy number amplification burden is the total number of genes with a gene copy number > 3.
11. Use according to any one of claims 8 to 10, wherein the gene copy number amplification load of the gene set is obtained by:
1) obtaining a baseline of coverage depth for a gene capture region in a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes;
2) obtaining a depth of coverage of a gene capture region in a gene set derived from a tumor tissue based on sequencing data of the gene set in the tumor tissue;
3) obtaining the copy number of each captured region of the gene in the gene set based on the log2 value of the ratio of the coverage depth of the gene captured region in the gene set derived from the tumor tissue to the baseline coverage depth of the gene captured region in the gene set derived from the white blood cells;
4) obtaining the gene copy number of the gene set based on the copy number of each capture region of the gene set and the weight occupied by the copy number;
5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set;
optionally, the sequencing data of the set of genes in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
optionally, the subject's DNA library 1 is constructed based on the subject's nucleic acid sample 1;
optionally, the nucleic acid sample 1 is derived from leukocytes of the subject;
optionally, sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject;
optionally, the subject's DNA library 2 is constructed based on the subject's nucleic acid sample 2;
optionally, the nucleic acid sample 2 is derived from tumor tissue of the subject.
12. A method of predicting the efficacy of a treatment with an immune checkpoint inhibitor for lung cancer in a subject, comprising: determining whether the subject immune checkpoint inhibitor treatment is effective based on the gene copy number amplification load of the subject gene set to be tested;
optionally, the lung cancer is non-small cell lung cancer;
optionally, the gene copy number amplification load of less than 8.5 is indicative of clinical benefit of the subject receiving treatment with an immune checkpoint inhibitor;
optionally, the gene set comprises at least one of the genes set forth in table 1.
13. The method of claim 12, wherein the gene copy number amplification burden is the total number of genes with gene copy numbers > 3.
14. The method of claim 12 or 13, wherein the gene copy number amplification load of the gene set is obtained by:
1) obtaining a baseline of coverage depth for a gene capture region of a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes;
2) obtaining a depth of coverage of a gene capture region of a gene set derived from the tumor tissue based on sequencing data of the gene set in the tumor tissue;
3) obtaining copy numbers of each capture region of genes in the gene set based on log2 values of the ratio of the depth of coverage of the gene capture region from the tumor tissue gene set to the baseline depth of coverage of the gene capture region from the white blood cells;
4) obtaining the gene copy number of the gene set based on the copy number of the gene capture region of the gene set and the weight occupied by the copy number;
5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set;
optionally, the sequencing data of the set of genes in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
optionally, the subject's DNA library 1 is constructed based on the subject's nucleic acid sample 1;
optionally, the nucleic acid sample 1 is derived from leukocytes of the subject;
optionally, sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject;
optionally, the subject's DNA library 2 is constructed based on the subject's nucleic acid sample 2;
optionally, the nucleic acid sample 2 is derived from tumor tissue of the subject.
15. A method of partitioning a population of people, comprising: partitioning individuals in the population that are suitable or unsuitable for treatment with a lung cancer immune checkpoint inhibitor based on the gene copy number amplification burden of the gene sets of the individuals in the population;
optionally, the gene set comprises at least one of the genes set forth in table 1;
optionally, the lung cancer is non-small cell lung cancer.
16. The method of claim 15, wherein the gene copy number amplification load of less than 8.5 is indicative of the individual in the population being eligible for treatment with a lung cancer immune checkpoint inhibitor.
17. The method of claim 15 or 16, wherein the gene copy number amplification load of the gene set is obtained by:
1) obtaining a baseline of coverage depth for a gene capture region of a gene set derived from leukocytes based on sequencing data for the gene set in the leukocytes;
2) obtaining a depth of coverage of a gene capture region of a gene set derived from the tumor tissue based on sequencing data of the gene set in the tumor tissue;
3) obtaining copy numbers of each capture region of genes in the gene set based on log2 values of the ratio of the depth of coverage of the gene capture region from the tumor tissue gene set to the baseline depth of coverage of the gene capture region from the leukocyte gene set;
4) obtaining the gene copy number of the gene set based on the copy number of the gene capture region of the gene set and the weight occupied by the copy number;
5) obtaining a gene copy number amplification load for the gene set based on the gene copy number of the gene set;
optionally, the sequencing data of the set of genes in the leukocytes is obtained by high throughput sequencing using DNA library 1 of the subject;
optionally, the subject's DNA library 1 is constructed based on the subject's nucleic acid sample 1;
optionally, the nucleic acid sample 1 is derived from leukocytes of the subject;
optionally, sequencing data of said gene set in said tumor tissue is obtained by high throughput sequencing using DNA library 2 of said subject;
optionally, the subject's DNA library 2 is constructed based on the subject's nucleic acid sample 2;
optionally, the nucleic acid sample 2 is derived from tumor tissue of the subject.
18. A system for predicting the efficacy of a treatment with an immune checkpoint inhibitor for lung cancer in a subject, comprising:
a means for determining the therapeutic efficacy of a treatment with a lung cancer immune checkpoint inhibitor, the means for determining the therapeutic efficacy of a treatment with a lung cancer immune checkpoint inhibitor being configured to determine whether the treatment with the subject immune checkpoint inhibitor is effective based on the gene copy number amplification load of the gene set of the subject to be tested;
optionally, a gene copy number amplification load of less than 8.5 in said subject is indicative of efficacy of treatment with an immune checkpoint inhibitor in said subject;
optionally, the gene set comprises at least one of the genes set forth in table 1.
19. The system of claim 18, further comprising:
a leukocyte gene set coverage depth baseline obtaining device for obtaining a coverage depth baseline of a gene capture region derived from a leukocyte gene set based on sequencing data of the gene set in leukocytes;
a device for obtaining the coverage depth of a tumor tissue gene set, which is used for obtaining the coverage depth of a gene capture area derived from the tumor tissue gene set based on the sequencing data of the gene set in the tumor tissue;
a gene set gene capture region copy number obtaining device, connected with the leukocyte gene set coverage depth baseline obtaining device and the tumor tissue gene set coverage depth obtaining device, for obtaining the domain copy number of the gene capture region of the gene set based on the log2 value of the ratio of the coverage depth of the gene capture region in the tumor tissue gene set to the coverage depth baseline of the gene capture region in the leukocyte gene set;
the device for obtaining the gene copy number of the gene set is connected with the device for obtaining the copy number of the gene capture area of the gene set and is used for obtaining the gene copy number of the gene set based on the copy number of each capture area of the gene set and the weight occupied by the copy number;
the device for obtaining the gene copy number amplification load of the gene set is connected with the device for obtaining the gene copy number of the gene set and the device for determining the curative effect of the lung cancer immune checkpoint inhibitor and is used for obtaining the gene copy number amplification load of the gene set based on the gene copy number of the gene set.
20. The system of claim 18 or 19, further comprising:
a DNA library constructing apparatus 1 for constructing a DNA library 1 of the subject based on a nucleic acid sample 1 of the subject;
a DNA library constructing apparatus 2 for constructing a DNA library 2 of the subject based on the nucleic acid sample 2 of the subject;
a sequencing data obtaining device 1, said sequencing data obtaining device 1 being connected to said DNA library constructing device 1 and said leukocyte gene set coverage depth baseline obtaining device, and being configured to perform high-throughput sequencing using said DNA library 1 of said subject, so as to obtain sequencing data of said gene set in said leukocytes;
a sequencing data acquisition device 2, wherein the sequencing data acquisition device 2 is connected with the DNA library construction device 2 and the coverage depth acquisition device of the tumor tissue gene set and is used for carrying out high-throughput sequencing by using the DNA library 2 of the object so as to obtain the sequencing data of the gene set in the white blood cells.
21. A kit for predicting the efficacy of a lung cancer immune checkpoint inhibitor therapy in a subject, comprising reagents for detecting any one of a set of genes;
optionally, the gene set comprises at least one of the genes set forth in table 1;
optionally, the lung cancer is non-small cell lung cancer.
22. The kit of claim 21, comprising at least one of:
DNA extraction reagent, library construction reagent or high-throughput sequencing reagent.
23. The kit of claim 21, wherein the kit further comprises:
a reference data set used as a reference for a gene set.
24. The kit of any one of claims 21 to 23, further comprising a first computer program product for performing the method of predicting lung cancer immune checkpoint inhibitor efficacy in a subject of any one of claims 12 to 14.
CN202111459016.5A 2021-12-02 2021-12-02 Marker for predicting curative effect of lung cancer immune checkpoint inhibitor and application thereof Pending CN114908163A (en)

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CN116254347A (en) * 2023-05-15 2023-06-13 南京世和基因生物技术股份有限公司 Application of combined marker in preparation of prediction reagent for immunotherapy curative effect of non-small cell lung cancer patient

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116254347A (en) * 2023-05-15 2023-06-13 南京世和基因生物技术股份有限公司 Application of combined marker in preparation of prediction reagent for immunotherapy curative effect of non-small cell lung cancer patient

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