CN114410791A - Method for detecting lung cancer gene fusion based on NanoString platform - Google Patents
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Abstract
The invention discloses a detection method for detecting lung cancer gene fusion based on a NanoString platform, which comprises the following steps: 1. collecting gene fusion information and determining housekeeping genes; 2. designing a probe; 3. establishing a positive threshold calculation model and judging a positive result; most fusion types related to the current lung cancer targeted therapy are collected, the upstream and downstream sequences of each gene fusion breakpoint are determined, and probes are designed based on an element method. The fusion is more comprehensive with other lung cancer related fusion based on NanoString platform detection, especially in the fusion of four genes of MET and NTRK 1/2/3; whether fusion occurs or not is always detected in a mode of detecting whether the 5 'end and the 3' end of the ROS1 gene are unbalanced or not, the detection sensitivity is low, the threshold value is difficult to judge, the algorithm is optimized again, and a new positive judgment standard is determined.
Description
Technical Field
The invention relates to the field of lung cancer detection, in particular to a NanoString platform-based method for detecting lung cancer gene fusion, which is used for detecting lung cancer-related gene fusion so as to guide targeted therapy.
Background
The targeted therapy of lung cancer is an important form of current lung cancer therapy. Targeted therapy is a therapeutic approach directed to the well-established oncogene drivers. The types of variation of oncogenic driver genes are mainly mutations, fusions and amplifications. Fusion-driven variation rates in lung cancer reach 6% -10%, and relevant targeted drugs have been approved for marketing, and lung cancer patients can therefore benefit from this.
At present, a plurality of molecular detection technologies are applied to lung cancer gene fusion detection, mainly including Immunohistochemistry (IHC), Fluorescence In Situ Hybridization (FISH), Polymerase Chain Reaction (PCR) and Next Generation Sequencing (NGS), but each method has certain limitations in application. IHC and FISH can only detect the fusion type of one gene at one time, and the fusion state of different genes needs to be detected for many times, so that the detection requirement of a small sample of a common clinical puncture biopsy cannot be met. In addition, some IHC results are susceptible to interference from different pathological subtypes or the results of the test cannot be used as the final decision. At present, most of FISH can only detect the gene breakage, and can not distinguish the chaperone gene. In addition, the FISH manual judgment is more subjective, and an atypical signal is often generated and is difficult to judge. The fusion type detected by PCR is limited by the primer, and the variety is less. In addition, PCR is prone to false positives due to cross-contamination of PCR. The NGS detection usually has high requirements on sample quality, and has long detection period and complex interpretation result.
The NanoString platform can also be used for detecting lung cancer related gene fusion, and has the advantages of low requirement on sample quality, short detection period, large detection flux and the like. However, no corresponding detection kit exists at home and abroad at present, and the detectable lung cancer fusion probe type reported in the literature only contains a few genes of ALK, RET and ROS 1. Genes such as MET and NTRK, which have been approved for targeted administration, have not been included in the detection range. NanoString can judge fusion occurrence by detecting whether the expression of 5 'end and 3' end of the gene is unbalanced so as to detect unknown fusion types, but the currently disclosed data show that the background expression value of ROS1 gene is very high, the difference between the expression after fusion occurrence and the background expression is very small, which results in lower sensitivity of the method in detecting ROS1 unknown fusion.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a detection method for detecting lung cancer gene fusion based on a NanoString platform.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a detection method for detecting lung cancer gene fusion based on a NanoString platform comprises the following specific steps:
1. gene fusion information collection and housekeeping gene determination
Determining and collecting fusion information of ALK, RET, MET, ROS1 and NTRK1/2/3 by taking the fusion recommended and detected by NCCN non-small cell lung cancer diagnosis and treatment guidelines (2020.v2) as basic guidance; searching the fusion of the seven genes in the lung cancer in a COSMIC database, collecting specific breakpoint information of the seven genes at the 5 'end and the 3' end, finally determining an upstream sequence and a downstream sequence at the fusion breakpoint of the genes according to transcript information of each gene, determining common breakpoints of ALK, RET and ROS1, and acquiring the upstream sequence and the downstream sequence; four housekeeping genes GAPDH, OAZ1, POLR2A, GUSB with different expression levels in lung cancer were selected for quality control and normalization.
2. Probe design
A probe A, a probe B and a protection probe are respectively designed according to the upstream and downstream sequences at the breakpoint of each fusion subtype, four segments of probes (5p-1, 5p-2, 5p-3, 5p-4, 3p-1, 3p-2, 3p-3 and 3p-4) are respectively designed at the upstream and downstream of the common breakpoint of ALK, RET and ROS1, the probes comprise the probe A and the probe B, and the probes comprise the probe A and the probe B are designed at the conserved regions of four housekeeping genes GAPDH, OAZ1, POLR2A and GUSB.
3. Establishing a positive threshold calculation model and judging a positive result
1) Lung adenocarcinoma patient samples that were confirmed to be ALK, RET, ROS, MET, NTRK1/2/3 fusion positive and negative by RNA-based NGS were collected for NanoSring experiments. The specific operation steps are as follows:
a) total RNA was extracted using Qiagen RNA extraction kit, and sample concentration was determined using Nanodrop 2000 and DV200 was determined using Agilent 2100 bioanalyzer;
b) the total input amount of the sample is limited to 30-150ng, DV200 is more than or equal to 30%, the sample, probes (a capture probe, a report probe and a protection probe), hybridization buffer solution and TagSet are mixed uniformly and hybridized, and the hybridization mixture is placed on a PCR instrument at 67 ℃ for hybridization for 16-24 h; after hybridization, the hybridization was diluted to 30-35 ul with RNase-free H2O, the diluted hybrid was transferred to a NanoString-dedicated cartridge by a pipette, and the cartridge was placed in nCounter SPRINT according to the instruction of the apparatus;
c) adding sample information to nCounter SPRINTTMThe Profiler Control Center system can Start running by clicking Start;
d) after the system operation is finished, exporting the generated RCC file;
2) the RCC file is introduced into nSolver (v4.0) software, and whether the quality control is qualified or not is judged by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB) and counts of six positive quality control products; then, normalizing the counts by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB), and exporting the normalized information into an excel table;
3) establishing a positive threshold calculation model
a) Quality control standard: the counts number of the original data of GAPDH gene in the sample is more than 600.
b) Calculation of 5 'and 3' end imbalance positive thresholds for ALK and RET: using the normalized data to calculate the geometric mean of the four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3 'end of ALK and RET genes of each sample to be defined as E3, and then calculating the median of the four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of each sample to be defined as A5; the background values of the ALK and RET genes are defined as B5 (see J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); taking the minimum value of E3/A5(B5) in each sample, dividing the sample into a positive group and a negative group by taking an RNA-based NGS result as a standard, and calculating a positive threshold value by using an ROC curve.
c) Imbalance calculation of 5 'and 3' ends of ROS1 gene: by utilizing the normalized data, the geometric mean of four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3' end of the ROS1 gene of each sample is firstly calculated and is defined as E3, if E3 is more than 700, the method can be used as a primary screening condition for ROS positivity, and if E3 is less than 700, a positive result can be excluded; calculating the median of four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of the ROS1 gene in the sample E3 & gt 700, and defining the median as A5; the background value of the ROS1 gene is defined as B5 (see the literature J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); the maximum value of E3/A5(B5) in each sample was taken, and the RNA-based NGS results were used as a standard to classify the samples into a positive group and a negative group, and the ROC curve was used to calculate the positive threshold.
d) Quality control of MET wild-type probe: and (3) obtaining mean + -2 SD of the counts of the negative quality control substances in one batch by utilizing the standardized data, if the counts of the MET wild-type probe (MET-MET _ E13: E14 and MET-MET _ E14: E15) are more than mean + -2 SD, the quality control is qualified, and the MET-MET _ E13 can be normally judged: E15.
e) and (3) calculating a fusion probe positive threshold: the normalized counts were divided by the median of the counts of the respective fusion probes in each batch (12 samples) and the resulting value was used to assess whether the fusion probes were positive. The maximum value of the values in each sample was evaluated as the value of the ROC curve, the RNA-based NGS results were used as the standard to classify the samples into a positive group and a negative group, and the ROC curve was used to calculate the positive threshold.
f) And (3) judging a positive result: if the ALK, RET and ROS1 genes detect imbalance of 5 'end and 3' end, the fusion type can be judged to be positive, wherein if the fusion probes of the ALK, RET and ROS1 are detected to be positive, a certain fusion can be judged to be positive, and if the fusion probes of the ALK, RET and ROS1 are not detected to be positive, an unknown fusion type of a certain gene can be judged to be positive. A certain fusion positive of ROS1 can also be determined if only a positive ROS1 fusion probe is detected, but no imbalance between the 5 'and 3' ends of the ROS1 gene is detected. If the ALK and RET genes do not detect imbalance of 5 'end and 3' end, but the fusion probes of the ALK and RET are detected to be positive, the fusion possibly detected is considered to be false positive, and the result is judged to be negative. If the MET and NTRK1/2/3 detect that the fusion probe is positive, the determination can be positive.
The invention has the beneficial effects that: 1. most fusion types related to the current lung cancer targeted therapy are collected, the upstream and downstream sequences at the fusion break point of each gene are determined, and a probe is designed on the basis of an element method. The fusion is more comprehensive with other lung cancer related fusion based on NanoString platform detection, especially in the fusion of four genes of MET and NTRK 1/2/3.
2. Whether fusion occurs or not is always detected in a mode of detecting whether the 5 'end and the 3' end of the ROS1 gene are unbalanced or not, the detection sensitivity is low, the threshold value is difficult to judge, the algorithm is optimized again, and a new positive judgment standard is determined.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention relates to a probe detection method for detecting lung cancer gene fusion based on a NanoString platform, which comprises the following specific steps:
1. gene fusion information collection and housekeeping gene determination
Determining and collecting fusion information of ALK, RET, MET, ROS1 and NTRK1/2/3 by taking the fusion recommended and detected by NCCN non-small cell lung cancer diagnosis and treatment guidelines (2020.v2) as basic guidance; searching the fusion of the seven genes in a COSMIC database, collecting specific breakpoint information of the seven genes at the 5 'end and the 3' end, finally determining an upstream sequence and a downstream sequence at the gene fusion breakpoint according to transcript information of each gene, determining common breakpoints of ALK, RET and ROS1, and acquiring the upstream sequence and the downstream sequence; four housekeeping genes GAPDH, OAZ1, POLR2A, GUSB were selected for normalization. The genes and fusion lists are shown in attached Table 1;
2. probe design
Respectively designing a probe A, a probe B and a protection probe according to an upstream and downstream sequence at a breakpoint of each fusion subtype, respectively designing four segments of probes (5p-1, 5p-2, 5p-3, 5p-4, 3p-1, 3p-2, 3p-3, 3p-4) at the upstream and downstream of a common breakpoint of ALK, RET and ROS1, including the probe A and the probe B, designing the probes in a conserved region of a housekeeping gene, including the probe A and the probe B, wherein the probe information is shown in attached table 1;
3. establishing a positive threshold calculation model and judging a positive result
1) Lung adenocarcinoma patient samples that were confirmed to be ALK, RET, ROS, MET, NTRK1/2/3 fusion positive and negative by RNA-based NGS were collected for NanoSring experiments. The specific operation steps are as follows:
a) total RNA was extracted using Qiagen RNA extraction kit, and sample concentration was determined using Nanodrop 2000 and DV200 was determined using Agilent 2100 bioanalyzer;
b) the total input amount of the sample is limited to 30-150ng, DV200 is more than or equal to 30%, the sample, probes (a capture probe, a report probe and a protection probe), hybridization buffer solution and TagSet are mixed uniformly and hybridized, and the hybridization mixture is placed on a PCR instrument at 67 ℃ for hybridization for 16-24 h; after hybridization, the hybridization was diluted to 30-35 ul with RNase-free H2O, the diluted hybrid was transferred to a NanoString-dedicated cartridge by a pipette, and the cartridge was placed in nCounter SPRINT according to the instruction of the apparatus;
c) adding sample information to nCounter SPRINTTMThe Profiler Control Center system can Start running by clicking Start;
d) after the system operation is finished, exporting the generated RCC file;
2) the RCC file is introduced into nSolver (v4.0) software, and whether the quality control is qualified or not is judged by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB) and counts of six positive quality control products; then, normalizing the counts by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB), and exporting the normalized information into an excel table;
3) establishing a positive threshold calculation model
a) Quality control standard: the counts number of the original data of GAPDH gene in the sample is more than 600.
b) Calculation of 5 'and 3' end imbalance positive thresholds for ALK and RET: using the normalized data to calculate the geometric mean of the four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3 'end of ALK and RET genes of each sample to be defined as E3, and then calculating the median of the four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of each sample to be defined as A5; the background values of the ALK and RET genes are defined as B5 (see J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); taking the minimum value of E3/A5(B5) in each sample, dividing the sample into a positive group and a negative group by taking an RNA-based NGS result as a standard, and calculating a positive threshold value by using an ROC curve as follows: ALK ═ 3, at which threshold the sensitivity of detection of ALK fusions reached 94.1% and specificity reached 100%. RET ═ 5, at which threshold the sensitivity of ALK fusion detection reached 92.8% and specificity reached 100%.
c) Imbalance calculation of 5 'and 3' ends of ROS1 gene: by utilizing the normalized data, the geometric mean of four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3' end of the ROS1 gene of each sample is firstly calculated and is defined as E3, if E3 is more than 700, the method can be used as a primary screening condition for ROS positivity, and if E3 is less than 700, a positive result can be excluded; calculating the median of four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of the ROS1 gene in the sample E3 & gt 700, and defining the median as A5; the background value of the ROS1 gene is defined as B5 (see the literature J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); the maximum value of E3/A5(B5) in each sample is taken, RNA-based NGS results are taken as a standard to be divided into a positive group and a negative group, the ROC curve is used for calculating the positive threshold value of 1.852, and the sensitivity of detecting ROS1 fusion reaches 81.82% and the specificity reaches 100% under the threshold value.
d) Quality control of MET wild-type probe: and (3) obtaining mean + -2 SD of the counts of the negative quality control substances in one batch by utilizing the standardized data, if the counts of the MET wild-type probe (MET-MET _ E13: E14 and MET-MET _ E14: E15) are more than mean + -2 SD, the quality control is qualified, and the MET-MET _ E13 can be normally judged: E15.
e) and (3) calculating a fusion probe positive threshold: the normalized counts were divided by the median of the counts of the respective fusion probes in each batch (12 samples) and the resulting value was used to assess whether the fusion probes were positive. The maximum value of the values in each sample was determined as the value of the ROC curve, and the results of RNA-based NGS were used as the standard to classify the samples into positive and negative groups, and the positive threshold calculated using the ROC curve was 5.
f) And (3) judging a positive result: if the ALK, RET and ROS1 genes detect imbalance of 5 'end and 3' end, the fusion type can be judged to be positive, wherein if the fusion probes of the ALK, RET and ROS1 are detected to be positive, a certain fusion can be judged to be positive, and if the fusion probes of the ALK, RET and ROS1 are not detected to be positive, an unknown fusion type of a certain gene can be judged to be positive. A certain fusion positive of ROS1 can also be determined if only a positive ROS1 fusion probe is detected, but no imbalance between the 5 'and 3' ends of the ROS1 gene is detected. If the ALK and RET genes do not detect imbalance of 5 'end and 3' end, but the fusion probes of the ALK and RET are detected to be positive, the fusion possibly detected is considered to be false positive, and the result is judged to be negative. If the MET and NTRK1/2/3 detect that the fusion probe is positive, the determination can be positive.
Attached table 1
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments or portions thereof without departing from the spirit and scope of the invention.
Claims (1)
1. The detection method for detecting the lung cancer gene fusion based on the NanoString platform comprises the following specific steps:
(1) gene fusion information collection and housekeeping gene determination
Determining and collecting fusion information of ALK, RET, MET, ROS1 and NTRK1/2/3 by taking the fusion recommended and detected by NCCN non-small cell lung cancer diagnosis and treatment guidelines (2020.v2) as basic guidance; searching the fusion of the seven genes in the lung cancer in a COSMIC database, collecting specific breakpoint information of the seven genes at the 5 'end and the 3' end, finally determining an upstream sequence and a downstream sequence at the fusion breakpoint of the genes according to transcript information of each gene, determining common breakpoints of ALK, RET and ROS1, and acquiring the upstream sequence and the downstream sequence; four housekeeping genes GAPDH, OAZ1, POLR2A, GUSB with different expression levels in lung cancer were selected for quality control and normalization;
(2) probe design
Respectively designing a probe A, a probe B and a protection probe according to an upstream and downstream sequence at a breakpoint of each fusion subtype, respectively designing four segments of probes (5p-1, 5p-2, 5p-3, 5p-4, 3p-1, 3p-2, 3p-3 and 3p-4) at the upstream and downstream of a common breakpoint of ALK, RET and ROS1, wherein the probes comprise the probe A and the probe B, and designing probes at conserved regions of four housekeeping genes GAPDH, OAZ1, POLR2A and GUSB, wherein the probes comprise the probe A and the probe B;
(3) establishing a positive threshold calculation model and judging a positive result, wherein the specific steps are as follows: 1) lung adenocarcinoma patient samples that were confirmed to be ALK, RET, ROS1, MET, NTRK1/2/3 fusion positive and negative by RNA-based NGS were collected for NanoSring experiments. The specific operation steps are as follows:
a) total RNA was extracted using Qiagen RNA extraction kit, and sample concentration was determined using Nanodrop 2000 and DV200 was determined using Agilent 2100 bioanalyzer;
b) the total input amount of the sample is limited to 30-150ng, DV200 is more than or equal to 30%, the sample, probes (a capture probe, a report probe and a protection probe), hybridization buffer solution and TagSet are mixed uniformly and hybridized, and the hybridization mixture is placed on a PCR instrument at 67 ℃ for hybridization for 16-24 h; after hybridization, the hybridization was diluted to 30-35 ul with RNase-free H2O, the diluted hybrid was transferred to a NanoString-dedicated cartridge by a pipette, and the cartridge was placed in nCounter SPRINT according to the instruction of the apparatus;
c) adding sample information to nCounter SPRINTTMThe Profiler Control Center system can Start running by clicking Start;
d) after the system operation is finished, exporting the generated RCC file;
2) the RCC file is introduced into nSolver (v4.0) software, and whether the quality control is qualified or not is judged by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB) and counts of six positive quality control products; then, normalizing the counts by using four housekeeping genes (GAPDH, OAZ1, POLR2A and GUSB), and exporting the normalized information into an excel table;
3) establishing a positive threshold calculation model
a) Quality control standard: the count number of the original data of the GAPDH gene in the sample is more than 600;
b) calculation of 5 'and 3' end imbalance positive thresholds for ALK and RET: using the normalized data to calculate the geometric mean of the four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3 'end of ALK and RET genes of each sample to be defined as E3, and then calculating the median of the four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of each sample to be defined as A5; the background values of the ALK and RET genes are defined as B5 (see J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); taking the minimum value of E3/A5(B5) in each sample, dividing the sample into a positive group and a negative group by taking an RNA-based NGS result as a standard, and calculating a positive threshold value by using an ROC curve;
c) imbalance calculation of 5 'and 3' ends of ROS1 gene: by utilizing the normalized data, the geometric mean of four probes (3p-1, 3p-2, 3p-3 and 3p-4) at the 3' end of the ROS1 gene of each sample is firstly calculated and is defined as E3, if E3 is more than 700, the method can be used as a primary screening condition for ROS positivity, and if E3 is less than 700, a positive result can be excluded; calculating the median of four probes (5p-1, 5p-2, 5p-3 and 5p-4) at the 5' end of the ROS1 gene in the sample E3 & gt 700, and defining the median as A5; the background value of the ROS1 gene is defined as B5 (see the literature J Mol Diagn 2014 Mar; 16 (2): 229-43.A single-tube multiplexed assay for detecting ALK, ROS1, and RET fusions in lung cancer); taking the maximum value of E3/A5(B5) in each sample, dividing the sample into a positive group and a negative group by taking an RNA-based NGS result as a standard, and calculating a positive threshold value by using an ROC curve;
d) quality control of MET wild-type probe: and (3) obtaining mean + -2 SD of the counts of the negative quality control substances in one batch by utilizing the standardized data, if the counts of the MET wild-type probe (MET-MET _ E13: E14 and MET-MET _ E14: E15) are more than mean + -2 SD, the quality control is qualified, and the MET-MET _ E13 can be normally judged: e15;
e) and (3) calculating a fusion probe positive threshold: the normalized counts were divided by the median of the counts of the respective fusion probes in each batch (12 samples) and the resulting value was used to assess whether the fusion probes were positive. Solving the maximum value of the numerical value in each sample as the value of an ROC curve, dividing the value into a positive group and a negative group by taking an RNA-based NGS result as a standard, and calculating a positive threshold value by using the ROC curve;
f) and (3) judging a positive result: if the ALK, RET and ROS1 genes detect that the 5 'end and the 3' end are unbalanced, the fusion type can be judged to be positive, wherein if fusion probes of the ALK, RET and ROS1 are detected to be positive, a certain fusion can be judged to be positive, and if the fusion probes of the ALK, RET and ROS1 are not detected to be positive, an unknown fusion type of a certain gene can be judged to be positive; a certain fusion positive of ROS1 can also be determined if only a positive ROS1 fusion probe is detected, but no imbalance between the 5 'and 3' ends of the ROS1 gene is detected. If the ALK and RET genes do not detect imbalance of 5 'end and 3' end, but the fusion probes of the ALK and RET are detected to be positive, the fusion possibly detected is considered to be false positive, and the result is judged to be negative. If the MET and NTRK1/2/3 detect that the fusion probe is positive, the determination can be positive.
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