CN114720542A - HPPI-TOFMS-based early lung cancer diagnosis exhaled breath marker screening and application thereof - Google Patents

HPPI-TOFMS-based early lung cancer diagnosis exhaled breath marker screening and application thereof Download PDF

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CN114720542A
CN114720542A CN202210323589.3A CN202210323589A CN114720542A CN 114720542 A CN114720542 A CN 114720542A CN 202210323589 A CN202210323589 A CN 202210323589A CN 114720542 A CN114720542 A CN 114720542A
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lung cancer
volatile organic
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邱满堂
王培宇
孟漱石
王少东
李庆运
王东鉴
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Peking University Peoples Hospital
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Abstract

The invention discloses HPPI-TOFMS early lung cancer diagnosis exhaled breath marker screening and application thereof. The invention provides application of 16 volatile organic compounds as lung cancer expiration biomarkers in development of products for diagnosing or assisting in diagnosing lung cancer. The 16 volatile organic compounds are: acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal and 2, 2-dimethyldecane. The inventors of the present invention determined 16 expiratory biomarkers of lung cancer by perioperative expiratory omics testing using HPPI-TOFMS, the combination of which can distinguish lung cancer patients from healthy people, and which can be used in clinical practice to optimize lung cancer screening protocols.

Description

HPPI-TOFMS-based early lung cancer diagnosis exhaled breath marker screening and application thereof
Technical Field
The invention belongs to the field of medical diagnosis, relates to HPPI-TOFMS-based early lung cancer diagnosis exhaled breath marker screening and application thereof, and particularly provides development of 16 Volatile Organic Compounds (VOCs) as lung cancer exhaled breath biomarkers and application of the lung cancer exhaled breath biomarkers in lung cancer diagnosis.
Background
Lung cancer is a leading cause of cancer-related death worldwide. Early diagnosis and treatment are critical to improving lung cancer survival. However, early detection and diagnosis of lung cancer remains challenging due to the lack of early clinical manifestations and specific biomarkers. Annual Low-dose breast computed tomography (LDCT) screening can significantly reduce lung cancer-specific mortality. However, the application of LDCT screening is challenging in several respects. The high cost, radiation exposure and high false positive rate have hindered the use of LDCT in large-scale screening. Currently, there is an urgent need for a highly accurate, non-invasive method for lung cancer screening.
Expiratory omics is considered to be a promising method for lung cancer screening. Alterations in the genome and transcriptome during carcinogenesis and cancer progression will lead to deregulation of metabolic pathways and accumulation of abnormal metabolites. Among many metabolites, cancer-derived Volatile Organic Compounds (VOCs) can diffuse into the alveoli and can be detected in exhaled breath. The concentration of VOCs in exhaled breath has a good correlation with its blood concentration. Gas chromatography-mass spectrometry (GC-MS) is currently considered the "gold standard" for breath biomarker identification and quantification.
Although GC-MS technology is mature, the cumbersome pre-processing steps and time consuming detection procedures limit its application. Other direct mass spectrometric detection methods, such as secondary electrospray ionization, selective ion flow tubes and proton transfer reactions, have also been used for rapid detection of exhaled breath; however, the large amount of water vapor in exhaled breath makes the ionization process more complex and increases the complexity of data analysis. In contrast, High-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) has the advantages of High sensitivity, no need of pretreatment, good moisture resistance, and the like, and is of great interest in breath detection. In previous studies, HIPPI-TOFMS has been used to monitor the concentration of propofol in breath during surgery, to detect volatile metabolites in urine, and to differentiate mixed flavor compounds.
Disclosure of Invention
The technical problem to be solved by the invention is lung cancer diagnosis. The invention provides HPPI-TOFMS early lung cancer diagnosis exhaled breath marker screening and application thereof, and particularly provides development of 16 Volatile Organic Compounds (VOCs) as lung cancer exhaled biomarkers and application of the lung cancer exhaled breath markers in lung cancer diagnosis.
The invention provides application of 16 volatile organic compounds as lung cancer expiration biomarkers in development of products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of the 16 volatile organic compounds is used as a lung cancer expiration biomarker.
The abundance of the 16 volatile organic compounds refers to the abundance of the 16 volatile organic compounds in the breath sample of the subject.
In the application, the method for diagnosing or assisting in diagnosing the lung cancer comprises the following steps: and substituting the abundances of the 16 volatile organic compounds into a model formula to obtain a P value, and then diagnosing or assisting in diagnosing according to a diagnostic standard.
The invention also provides application of the substance for detecting the 16 volatile organic compounds in preparing a product for diagnosing or assisting in diagnosing lung cancer.
The substance for detecting 16 volatile organic compounds may specifically be a substance for detecting the abundance of 16 volatile organic compounds.
The substance for detecting 16 volatile organic compounds may specifically be a substance for detecting the abundance of 16 volatile organic compounds in an exhaled breath sample of a subject.
In the application, the method for diagnosing or assisting in diagnosing the lung cancer comprises the following steps: and substituting the abundances of the 16 volatile organic compounds into a model formula to obtain a P value, and then diagnosing or assisting in diagnosing according to a diagnostic standard.
The invention also provides a product for diagnosing or assisting in diagnosing lung cancer, which comprises substances for detecting 16 volatile organic compounds.
The substance for detecting 16 volatile organic compounds may specifically be a substance for detecting the abundance of 16 volatile organic compounds.
The substance for detecting 16 volatile organic compounds may specifically be a substance for detecting the abundance of 16 volatile organic compounds in an exhaled breath sample of a subject.
The product also comprises a carrier which is recorded with a model formula and a diagnosis standard.
The model formula is as follows: p is 1/(1+ e)-(-0.01x1+0.001x2+0.001x3+0.01x4-0.001x5+0.001x6-0.027x7-0.004x8+0.022x9+0.005x10-0.007x11+0.001x12-0.005x13+0.034x14+0.073x15+0.007x16-5.181))。
In the model formula, x1 to x16 correspond to the peak values of acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptaldehyde, acetophenone, propylcyclohexane, octaldehyde, nonanal, decanal and 2, 2-dimethyldecane in sequence.
Diagnostic criteria: p ═ 0.267 is a threshold value, and lung cancer was diagnosed at or above the threshold value and non-lung cancer was diagnosed at or below the threshold value.
Any one of the 16 volatile organic compounds is: acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal, and 2, 2-dimethyldecane.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of a volatile organic compound identified based on the m/z value and the ionization model of HPPI-TOFMS.
The substance for detecting the 16 volatile organic compounds may be a device or a combination of reagents.
The substance for detecting 16 volatile organic compounds may be an HPPI-TOFMS instrument.
The substances used for the detection of the 16 volatile organic compounds may be Tedlar bags and HPPI-TOFMS instruments.
The substance for detecting 16 volatile organic compounds may be a reagent required for HPPI-TOFMS.
The materials used for the detection of the 16 volatile organic compounds may be Tedlar bags and reagents required for HPPI-TOFMS.
The invention provides application of 8 volatile organic compounds as lung cancer expiration biomarkers in development of products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of the 8 volatile organic compounds is used as a lung cancer expiration biomarker.
The abundance of the 8 volatile organic compounds refers to the abundance of the 8 volatile organic compounds in the breath sample of the subject.
In the application, the method for diagnosing or assisting in diagnosing the lung cancer comprises the following steps: and substituting the abundances of the 8 volatile organic compounds into a model formula to obtain a P value, and then diagnosing or assisting in diagnosing according to a diagnostic standard.
The invention also provides application of the substance for detecting 8 volatile organic compounds in preparing products for diagnosing or assisting in diagnosing lung cancer.
The substance for detecting 8 volatile organic compounds may specifically be a substance for detecting the abundance of 8 volatile organic compounds.
The substance for detecting 8 volatile organic compounds may specifically be a substance for detecting the abundance of 8 volatile organic compounds in the breath sample of the subject.
In the application, the method for diagnosing or assisting in diagnosing the lung cancer comprises the following steps: and substituting the abundances of the 8 volatile organic compounds into a model formula to obtain a P value, and then diagnosing or assisting in diagnosing according to a diagnostic standard.
The invention also provides a product for diagnosing or assisting in diagnosing lung cancer, which comprises substances for detecting 8 volatile organic compounds.
The substance for detecting 8 volatile organic compounds may specifically be a substance for detecting the abundance of 8 volatile organic compounds.
The substance for detecting 8 volatile organic compounds may specifically be a substance for detecting the abundance of 8 volatile organic compounds in the breath sample of the subject.
The product also comprises a carrier which is recorded with a model formula and a diagnosis standard.
The model formula is as follows:
P＝1/(1+e-(0.001x1+0.002x2+0.004x3-0.001x4+0.019x5+0.021x6-0.004x7-0.011x8-6.454))。
in the model formula, x1 to x8 correspond to the peak values of isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal in sequence.
Diagnostic criteria: when P is 0.236, lung cancer is diagnosed as being equal to or greater than the threshold value, and non-lung cancer is diagnosed as being less than the threshold value.
Any one of the above 8 volatile organic compounds is: isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of a volatile organic compound identified based on the m/z value and the ionization model of HPPI-TOFMS.
The substance for detecting 8 volatile organic compounds may be a device or a combination of reagents.
The substance for detecting 8 volatile organic compounds may be an HPPI-TOFMS instrument.
The substances used for detecting 8 volatile organic compounds may be Tedlar bags and HPPI-TOFMS instruments.
The substance for detecting 8 volatile organic compounds may be a reagent required for HPPI-TOFMS.
The materials for detecting 8 volatile organic compounds may be Tedlar bags and reagents required for HPPI-TOFMS.
The invention also protects the application of isoprene as a lung cancer expiration biomarker in developing products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of isoprene is used as a lung cancer expiration biomarker.
The abundance of isoprene refers to the abundance of isoprene in an expiratory sample of the subject.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of isoprene identified based on the m/z value and the ionization model of HPPI-TOFMS.
The invention also discloses application of the substance for detecting isoprene in preparation of products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of isoprene is used as a lung cancer expiration biomarker.
The abundance of isoprene refers to the abundance of isoprene in an expiratory sample of the subject.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of isoprene identified based on the m/z value and the ionization model of HPPI-TOFMS.
The substance for detecting isoprene may be a device or a combination of reagents.
The substance for detecting isoprene may be an HPPI-TOFMS instrument.
Substances used for the detection of isoprene may be Tedlar bags and HPPI-TOFMS instruments.
The substance for detecting isoprene may be a reagent required for HPPI-TOFMS.
The substance for detecting isoprene may be Tedlar bag and reagent required for HPPI-TOFMS.
The invention also protects the application of hexanal as a lung cancer expiration biomarker in developing products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of hexanal is used as a lung cancer expiration biomarker.
The abundance of hexanal refers to the abundance of hexanal in an expiratory sample of the subject.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of hexanal identified based on the m/z value and the ionization model of HPPI-TOFMS.
The invention also protects the application of the substance for detecting hexanal in preparing products for diagnosing or assisting in diagnosing lung cancer.
In the application, the abundance of hexanal is used as a lung cancer expiration biomarker.
The abundance of hexanal refers to the abundance of hexanal in an expiratory sample of the subject.
The abundance may specifically be a spectral peak.
The abundance may specifically be a spectral peak of hexanal identified based on the m/z values and ionization model of HPPI-TOFMS.
The substance for detecting hexanal may be a device or a combination of reagents.
The substance for detecting hexanal may be an HPPI-TOFMS instrument.
The substances for detecting hexanal may be Tedlar bags and HPPI-TOFMS instruments.
The substance for detecting hexanal may be a reagent required for HPPI-TOFMS.
The substance for detecting hexanal may be Tedlar bag and reagents required for HPPI-TOFMS.
The inventors of the present invention determined 16 expiratory biomarkers of lung cancer by perioperative expiratory omics testing using HPPI-TOFMS, the combination of which can distinguish lung cancer patients from healthy people, and which can be used in clinical practice to optimize lung cancer screening protocols.
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FIG. 1 is a schematic flow chart of a discovery study.
FIG. 2 is an example of a mass spectrum in example 1. A: mass spectra of patients before (left) and 4 weeks after (right). B: preoperative mass spectrometry identified 16 VOCs. The characteristics of the patients are as follows: female, age 52, stage IA 3.
FIG. 3 is a graph of perioperative dynamics of 16 VOCs in exhaled breath from a patient with lung cancer. P values represent the peak intensity difference between pre-and post-operative 4 weeks from Wilcoxon paired sign rank-sum test. PO: after the operation.
Fig. 4 is a schematic flow chart of a confirmatory study.
FIG. 5 is a comparison of intensities of peaks in spectra of VOCs in lung cancer patients and healthy humans. P values are from the Mann-Whitney U test. HI: a healthy person; LC: lung cancer.
Fig. 6 is an illustration of combinations for expiratory VOCs and lung cancer. A: volcano plots show the variation and difference in peak expiratory VOC intensities for lung cancer patients and healthy people. B-C: correlation analysis of 16 VOCs in healthy and lung cancer patients. D: the expression of 16 VOCs in lung cancer diagnosis. E: the performance of a combination of 16 VOCs in the diagnosis of lung cancer. F: the performance of the combination of VOCs in lung cancer diagnosis in 8.
Detailed Description
The present invention is described in further detail below with reference to specific embodiments, which are given for the purpose of illustration only and are not intended to limit the scope of the invention. The examples provided below serve as a guide for further modifications by a person skilled in the art and do not constitute a limitation of the invention in any way.
The experimental procedures in the following examples, unless otherwise indicated, are conventional and are carried out according to the techniques or conditions described in the literature in the field or according to the instructions of the products. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.
Unless otherwise stated, the quantitative tests in the following examples were performed in triplicate, and the results were averaged.
In an embodiment, the classified data is expressed in frequency (percentage) and the continuous data is expressed in mean ± standard deviation or median (interquartile range). Changes in perioperative VOCs peak intensity were assessed using the Wilcoxon paired signed rank sum test. Methods for assessing differences between groups include ANOVA, Pearson's Chi-Square test, Mann-Whitney U test, and Kruskal-Wallis test. And (3) researching the relation between the peak intensity of the lung cancer and the peak intensity of the VOCs by adopting a multivariate logistic regression model and a conditional backward method. A clinical predictive model based on multifactorial logistic regression was developed to evaluate the performance of VOCs for lung cancer diagnosis. In a confirmatory study, sensitivity, specificity, accuracy, positive predictive value and negative predictive value were calculated to assess the diagnostic performance of exhaled VOCs on lung cancer. Subject work curves were plotted and the Area under the curve (AUC) was calculated. A two-tailed P value <0.05 in the differential test was considered statistically significant. All analyses were performed using the IBM SPSS statistical software Windows version (version 24.0, IBM corp., Armonk, NY, USA) and the R tool (version 4.1.2).
Example 1 biomarker screening (discoverability study)
A schematic flow diagram of the discovery study is shown in figure 1.
Screening of subjects and subject information
The discovery study was conducted in the Beijing university Hospital from 9 to 12 months of 2020. Breath samples were taken at three time points, i.e., the day of surgery (preoperative), 3 days post-surgery, and 4 weeks post-surgery morning. The study was approved by the ethical committee of the people hospital, Beijing university (2019PHB 095-01). All patients were informed of the study protocol and gave written consent prior to study entry. The study was conducted according to the diagnostic accuracy reporting criteria (STARD) reporting guidelines (Bossuyt PM, Reitssma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L, et al. STARD 2015: an updated list of assessment items for reporting diagnostic access records BMJ. 2015; 351: h5527.DOI:10.1136/bmj. h5527.).
Subject inclusion criteria in the discovery study were: patients suspected of having lung lesions are aged 18 years or more and are scheduled to undergo surgical resection. Preoperative exclusion criteria were as follows: (1) the cancer history exists within 5 years before the operation; (2) preoperative antitumor therapy; (3) active infection; (4) liver or kidney dysfunction; (5) there was a lack of written informed consent for participation. Postoperative exclusion criteria were as follows: (1) pathologically confirmed benign lung disease; (2) lack of planned breath sampling; (3) serious perioperative complications that may affect the detection of the expiratory omics. During the course of the investigative study, a total of 112 patients underwent pulmonary surgery. 18 patients were excluded according to pre-operative exclusion criteria. The post-operative pathology of 6 patients was diagnosed as benign disease and was therefore excluded. Another 4 patients were excluded due to lack of breath sampling for 4 weeks post-surgery. No serious complications or deaths were seen during the study. Finally, 84 lung cancer patients (including 27 males and 57 females) were included in the data analysis (see table 1 for patient characteristics). The mean age was 55.0. + -. 10.2 years. Most patients are diagnosed with early stage adenocarcinoma. Wedge resection is most common, followed by lobectomy and segmental resection.
TABLE 1 characteristics of Lung cancer patients
Feature(s) Data (N84)
Social and demographic data
Age, year of age 55.0±10.2
Gender (woman) 57(67.9)
Body mass index 24.1(22.9-26.3)
History of smoking 12(14.3)
Complication before operation
Diabetes mellitus 9(10.7)
Cardiovascular diseases 22(26.2)
Cerebrovascular disease 3(3.6)
Respiratory diseases 2(2.4)
Thyroid disease 10(11.9)
Surgical method
Lung lobe resection 35(41.7)
Resection of lung segment 4(4.8)
Wedge resection 45(53.6)
Pathological data
Pathological type of tumor
Adenocarcinoma 80(95.2)
Squamous cell carcinoma 1(1.2)
Small cell carcinoma 3(3.6)
Staging of pathology
IA1/IA2/IA3/II-III 47/18/10/9(56.0/21.4/11.9/10.7)
Lymph node metastasis 9(10.7)
Multiple primary cancers 10(11.9)
Second, preliminary screening of biomarkers
In view of the wide variety of volatile organic compounds in exhaled breath, the inventors reviewed the prior art to select potential expiratory biomarkers for lung cancer, and the lung cancer-associated VOCs reported in no less than two original studies were selected as potential expiratory biomarkers. Through earlier studies, 28 kinds of VOCs are preliminarily selected for further verification. Information on the 28 VOCs, mainly hydrocarbons (aromatic and aliphatic) and oxygenates (aldehydes, alcohols, phenols, carboxylic acids, ethers and furans) is shown in table 2.
TABLE 2
Figure BDA0003572666250000071
Figure BDA0003572666250000081
Method for collecting breath sample and detecting abundance of biomarkers in breath sample
1. Breath collection protocol
All exhaled breath samples were collected by trained investigators using prepared Tedlar airbags. The evening before the breath collection, the Tedlar bags were baked at 60 ℃ for 3 hours to completely release possible interfering substances and were continuously purged with high-purity nitrogen 4 times. Breath samples were collected in a stationary room and the corresponding ambient air was collected. The participants rinsed their mouth first with purified water, then performed a single deep inhalation, and then completely breathed into the Tedlar bag through the mouth. A total of 1000 ml of expired gas was collected. Carbon dioxide sensors were used to ensure alveolar air was collected: exhaled gas collection will not begin until the carbon dioxide sensor detects a carbon dioxide concentration of more than 4%. All participants were asked to fast for at least 8 hours and not to consume spicy food, alcohol or coffee the evening before breath collection.
2. Detecting biomarker abundance in breath samples
Peaks of VOCs spectra (average D, Li E, Zhou Q, Wang X, Li H, Ju B, et al. Online Monitoring of Integrated amplified reactive by acetic acid-Assisted reactive photosynthetic Sound, 8, 90(8), 5280-9.DOI: 10.1021/a. analytical. 8B 00171; Wang Y, Jiang J, Hua L, Hou K, Xie Y, Chen P, 707, et al. high-Pressure Ionic emission TOFMS for TOFMS), peak of Exhaled Breath sample No. 18, found No. 8, found No. 5-9, found No. 3H, found No. 8B 00171; found No. 35. F H, found No. 8, found No. K, Xie Y, Chen P, 707, et al. high-Pressure Ionic emission TOF S, found No. 47, found No. 8, found No. 5. F, found No. 5. F, found No. 8, found No. 5, found No. 8, found No. 3, found in sample No. 5, found No. 3, found No. 5, No. 3, found No. 3, No. 8, No. 3, No. 8, No. 3, No. 8, No. 4, No. 3, No. 8, No. 4, No. 8, No. 3, No. 8, No. 3, No. 8, No. 3, No. 8, No. 3, No. 8.
The HPPI-TOFMS consists of an HPPI ion source based on a vacuum ultraviolet lamp and an orthogonal accelerated time of flight (TOF) mass analyzer. TOF mass analyzers using a 0.4 meter field-free drift tube can achieve a mass resolution of 4000 (half of full width maximum) at a mass to charge ratio (m/z) of 92. The gas phase breath sample is directly led from the gas bag through the stainless steel capillaryThe ionized region is accessed. To eliminate VOCs condensation in the breath and minimize surface adsorption, the stainless steel capillary was heated to 100 ℃ and the HPPI ion source was heated to 60 ℃. The TOF signal was recorded with a 400 picosecond time-to-digital converter at 25kHz and all mass spectra were accumulated for 60 seconds. All mass spectrometers require mass calibration before being put into use. In general, 1, 2-dichloroethylene, tetrachloroethylene and hexachloro-1, 3-butadiene, which are well known m/z materials, are uniformly distributed within the desired mass range. Calibration formula y ═ ax2+ bx + c is used to achieve time-of-flight to m/z conversion. This calibration process is done by the mass spectrometer software. Mass spectrum peaks with m/z less than 500 detected by HPPI-TOFMS were recorded. And preprocessing mass spectrum data, and further completing noise reduction, baseline correction and VOCs characteristic detection. Ambient background air data was subtracted from the exhaled breath sample and the data was used for further analysis.
And the result obtained in the third step is the characteristic spectrum peak value of each Volatile Organic Compound (VOC), namely the spectrum peak value, and is used for representing the abundance of the VOC.
Fourth, result analysis
The spectral peaks of the 28 VOCs at the three time points are shown in table 3. The spectral peaks of most VOCs show fluctuating changes between the three time points. It is contemplated that perioperative drug metabolism and surgical stress may affect the post-operative third day's expiratory study. According to the clinical practice of the inventors, the physiological state of the patient substantially returned to normal at 4 weeks post-surgery. Therefore, the inventors focused on comparing the preoperative and postoperative peri-expiratory results. An example of the different mass spectra at the two time points is shown in fig. 2A (left panel before surgery and right panel 4 weeks after surgery). Based on Wilcoxon paired sign rank sum test, the peak intensity of the spectrum of 15 VOCs decreases significantly during this period, which are: 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal and 2, 2-dimethyldecane. However, the peak intensity of the spectrum of acetaldehyde increased significantly around the post-operative period. An example of the identification of 16 VOCs in a mass spectrum is shown in fig. 2B. The dynamic change in the spectral peak intensity of these volatile organic compounds at three time points is shown in fig. 3. These 16 volatile organic compounds were selected as possible lung cancer exhalation biomarkers for further analysis. The patient information for fig. 2 is: female, 52 years old, IA3 installments.
TABLE 3 Change of volatile organic Compounds in preoperative and postoperative exhalations of Lung cancer patients
Figure BDA0003572666250000091
Figure BDA0003572666250000101
Example 2 biomarker confirmation and evaluation (confirmatory study)
A schematic flow chart of the confirmatory study is shown in figure 4.
Screening of subjects and subject information
Verification of the lung cancer exhalation marker was performed at the first subsidiary hospital of zhengzhou university.
The inclusion criteria for lung cancer patients in the confirmatory study were the same as the inclusion criteria for lung cancer patients in the discoverable study; breath samples were collected on the day of surgery or biopsy (preoperative). Healthy persons in confirmatory studies refer to persons who received physical examinations on LDCT but had no positive results; breath samples were collected on the day of physical examination. All participants were asked to fast for at least 8 hours and not to consume spicy food, alcohol or coffee the evening before breath collection.
Confirmatory studies included 157 lung cancer patients and 368 healthy people. Subject characteristics are shown in table 4. Patients with lung cancer are older than healthy people and have a higher prevalence of cardiovascular disease. In healthy people, the history of smoking and drinking is more common.
TABLE 4 characteristics of the Subjects
Figure BDA0003572666250000111
Method for collecting breath sample and detecting abundance of biomarkers in breath sample
The same procedure as in step three of example 1.
Third, result analysis
The spectral peak intensities of the 16 VOCs in the breath samples of both groups of people are shown in fig. 5.
1. Individual diagnostic performance
The comparison of the peak intensities of the spectra of the above 16 VOCs between the two groups is shown in fig. 5(HI for healthy people and LC for lung cancer). All of these VOCs showed a significant increase in peak intensity in lung cancer patients compared to healthy humans. The volcano plot (fig. 6A) shows the multiplicative changes and differences in 16 VOCs between lung cancer patients and healthy people. Correlation analysis showed that the lung cancer patients and healthy individuals were enriched differently for VOCs (fig. 6B and 6C, respectively), indicating that the association pattern of VOCs was different in the two groups.
After correction of confounders (including age, sex, smoking history, drinking history and complications), lung cancer status (compared to healthy persons) remains an independent correlation factor for the increase in peak intensity of the spectrum of VOCs, see table 6.
TABLE 6 multivariate analysis of the relationship between lung cancer and peak intensity rise of VOC spectra
Figure BDA0003572666250000112
Figure BDA0003572666250000121
Figure 6D shows the individual diagnostic performance of 16 VOCs for lung cancer, and a summary of the data is presented in table 7. The AUC for isoprene and hexanal was highest, with isoprene AUC of 0.859 and hexanal AUC of 0.843.
TABLE 716 Performance of VOCs for differential diagnosis of Lung cancer patients and health examiners
Figure BDA0003572666250000122
2. Diagnostic Performance of 16 VOCs
And establishing a clinical prediction model based on multi-factor logistic regression.
The model formula is as follows: p is 1/(1+ e)-(-0.01x1+0.001x2+0.001x3+0.01x4-0.001x5+0.001x6-0.027x7-0.004x8+0.022x9+0.005x10-0.007x11+0.001x12-0.005x13+0.034x14+0.073x15+0.007x16-5.181))。
In the model formula, x1 to x16 correspond to the peak values of acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptaldehyde, acetophenone, propylcyclohexane, octaldehyde, nonanal, decanal and 2, 2-dimethyldecane in sequence.
Diagnostic criteria: p ═ 0.267 is the threshold, and lung cancer was diagnosed at or above the threshold, while healthy (non-lung cancer) was diagnosed at or below the threshold.
And substituting the spectral peak values of the 16 VOCs in the breath samples of all the subjects into the model formula to obtain a diagnosis result. Comparing the diagnosis result of the subject with the actual diseased condition of the subject. The diagnostic AUC was 0.952, sensitivity was 89.2%, specificity was 89.1%, and accuracy was 89.1% (fig. 6E).
3. Diagnostic performance of 8 VOCs
The diagnostic performance of the first eight AUC VOCs combinations in table 7 was evaluated. The first eight AUC VOCs were isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal, and decanal.
And establishing a clinical prediction model based on multi-factor logistic regression.
The model formula is as follows:
P＝1/(1+e-(0.001x1+0.002x2+0.004x3-0.001x4+0.019x5+0.021x6-0.004x7-0.011x8-6.454))。
in the model formula, x1 to x8 correspond to the peak values of isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal in sequence.
Diagnostic criteria: p-0.236 is a threshold, and lung cancer is diagnosed at or above the threshold, while healthy (non-lung cancer) is diagnosed at or below the threshold.
And substituting the spectral peak values of the 8 VOCs in the breath samples of all the subjects into the model formula to obtain a diagnosis result. Comparing the diagnosis result of the subject with the actual diseased condition of the subject. The diagnostic AUC was 0.931, the sensitivity was 86.0%, the specificity was 87.2%, and the accuracy was 86.9% (fig. 6F).
The present invention has been described in detail above. It will be apparent to those skilled in the art that the invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with reference to specific embodiments, it will be appreciated that the invention can be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The use of some of the essential features is possible within the scope of the claims attached below.

Claims (10)

1.16 volatile organic compounds are used as the lung cancer expiration biomarker to develop products for diagnosing or assisting in diagnosing lung cancer; the 16 volatile organic compounds are: acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal, and 2, 2-dimethyldecane.
2. The use of a substance for detecting 16 volatile organic compounds for the manufacture of a product for use in the diagnosis or the aided diagnosis of lung cancer; the 16 volatile organic compounds are: acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal, and 2, 2-dimethyldecane.
3. A product for diagnosing or aiding in the diagnosis of lung cancer, comprising a substance for detecting 16 volatile organic compounds; the 16 volatile organic compounds are: acetaldehyde, 2-hydroxyacetaldehyde, isoprene, valeraldehyde, butyric acid, toluene, 2, 5-dimethylfuran, cyclohexanone, hexanal, heptanal, acetophenone, propylcyclohexane, octanal, nonanal, decanal, and 2, 2-dimethyldecane.
4.8 volatile organic compounds are used as lung cancer expiration biomarkers in developing products for diagnosing or assisting in diagnosing lung cancer; the 8 volatile organic compounds are: isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal.
5. The use of a substance for detecting 8 volatile organic compounds for the manufacture of a product for use in the diagnosis or the aided diagnosis of lung cancer; the 8 volatile organic compounds are: isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal.
6. A product for diagnosing or aiding in the diagnosis of lung cancer, comprising a substance for detecting 8 volatile organic compounds; the 8 volatile organic compounds are: isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2-dimethyldecane, heptanal and decanal.
7. Application of isoprene as a lung cancer expiration biomarker in development of products for diagnosis or auxiliary diagnosis of lung cancer.
8. The application of the substance for detecting isoprene in the preparation of products for diagnosing or assisting in diagnosing lung cancer.
9. Application of hexanal as a lung cancer expiration biomarker in development of products for diagnosis or auxiliary diagnosis of lung cancer.
10. The use of a substance for the detection of hexanal in the manufacture of a product for the diagnosis or for the aided diagnosis of lung cancer.
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