Study Design
In training set and identification set, we prospectively enrolled TB and LC patients and non-cancer patients as participants for the serum-based non-targeted metabolomics analysis to detect specific markers of both diseases and the identified markers were screened through a binary logistic regression model. In test set, targeted metabolomics technology was used to analyze differences among TB, LC, and pneumonia patients and in non-cancer controls. The SVM model evaluated the predicting rate of potential biomarkers in LC and TB, and provide data for clinical research.
Participants
The study participants were patients who were treated at three centers: LC patients (n=262) from the Second Hospital of Tianjin Medical University; TB patients from Tianjin Haihe Hospital (n=182); and pneumonia patients from the First Affiliated Hospital of the Tianjin University of Chinese Medicine (n=30). The non-cancer control group (n=218) comprised patients with noncancerous diseases who were treated at the Second Hospital of Tianjin Medical University during the same period and were confirmed to have no malignant disease based on a review of the hospital's medical records from the hospital’s medical database. The prespecified blood sampling and sample preparation were undertaken by well-trained researchers. The subject has passed the review of the ethics committee of the Second Hospital of Tianjin Medical University. The age and clinical manifestations of each participant were ascertained, and the basic information of the matched participants is presented in Table 1. This study is registered in the China Clinical Trial Registration Center (registration number ChiCTR2000040666, Registered 07 December 2020, http://www.chictr.org.cn/index.aspx), and the registration unit is the Second Hospital of Tianjin Medical University.
Table 1 Basic information of the participants
|
Training set
|
Identification set
|
|
TB
|
LC
|
NC
|
TB
|
LC
|
NC
|
Total
|
30
|
55
|
35
|
63
|
88
|
63
|
Female
|
15
|
24
|
18
|
41
|
59
|
43
|
Male
|
15
|
31
|
17
|
22
|
29
|
20
|
Age
|
59.27±8.33
|
58.58±5.61
|
59.83±5.62
|
62.21±9.29
|
63.28±7.60
|
62.68±9.31
|
TCT(+/-/NA)
|
15/14/1
|
/
|
/
|
27/29/7
|
/
|
/
|
AFB(+/-/NA)
|
15/15/0
|
/
|
/
|
20/37/6
|
/
|
/
|
Stage
|
|
|
|
/
|
/
|
/
|
I
|
/
|
0
|
/
|
/
|
2
|
/
|
II
|
/
|
8
|
/
|
/
|
28
|
/
|
III
|
/
|
13
|
/
|
/
|
30
|
/
|
IV
|
/
|
8
|
/
|
/
|
28
|
/
|
Abbreviations: NC, non-cancer control; TB, tuberculosis; LC, lung cancer; TCT, tuberculin culture test; AFB, AFB sputum smear.
Inclusion criteria: Patients who were diagnosed based on diagnostic criteria for TB and LC, with pathological confirmation of LC in biopsy specimens or a clinician-confirmed LC based on radiological and clinical findings. According to the 7th edition of the TNM classification, all LC participants had primary lung cancer. The TB patients were diagnosed based on positive results on sputum examination (sputum smear or culture) and evidence of pulmonary TB on chest X-ray or computed tomography scanning. Patients in the age range of 18 to 80 years, regardless of sex; unimpaired consciousness level.
Exclusion criteria: 1) other metabolic diseases, hematological diseases, and cancer; 2) severe infection; and 3) severe cardiovascular, cerebrovascular, liver, or kidney dysfunction.
This study was conducted in accordance with the Declaration of Helsinki and the ethical rules of good clinical practice, and has been approved (approval number KY2020K089) by the ethics committee of the Second Hospital of Tianjin Medical University. The overall sample was randomly subdivided into training, identification, and test sets. Non-targeted metabonomics was used in training and identification set, targeted metabonomics was used in test set(Figure 1).
Non-targeted metabonomic
Sample Preparation
The samples that were frozen and stored at −80℃ were completely thawed in the refrigerator at 4℃, and 80 μL serum was mixed with acetonitrile (chromatography-grade acetonitrile, Oceanpak, Sweden) at a 1:3 volume ratio. After swirling (LP Vortex Mixer, Thermo Fisher Scientific (China) Co., Ltd.) for 1 min, the samples were ultrasonicated (JP-060S ultrasonic cleaner, Jiemeng Cleaning Equipment Co., Ltd.) in an ice-water bath for 10 min and centrifuged (3-18K high-speed centrifuge, Germany Sigma) at 4℃ for 15 min at 13000 rpm; then, 200 μL supernatant was obtained for metabonomic analysis. The supernatants from the training and identification set were tested in ultra-high-performance liquid chromatography-Quadrupole Time-Of-Flight Mass Spectrometry (UPLC/Q-TOF-MS) analysis in positive mode. Each serum sample was pipetted into a centrifuge tube, and then mixed and vortexed for 1 min to prepare a quality control (QC) sample. The QC sample contained the biological information of all samples and can reflect the overall sample status [23] and was used for methodological investigation with the same pre-processing method as that used for the sample.
Mass Spectrometric Analysis
Using electrospray ionization (ESI source), mass spectrometric analysis was performed in positive ionization mode with the following conditions: capillary voltage 2.0 kV, ionization source temperature 100°C, dry gas flow rate 10 mL/min, esolvation flow rate 600 L/D, desolvation temperature 450℃, cone air flow rate 50 L/D, and quadrupole scanning range m/z 50–1000.
Chromatographic Analysis
In this experiment, Waters ACQUITY UPLC (Waters Corporation, USA) was used for metabolomics research under the following conditions: chromatographic column: UPLC BEH C18 (2.1×100 mm, 1.7 μm, Waters Corporation, Milford, USA), column temperature: 45°C; flow rate: 0.3 mL/min; injection volume: 5 μL; and mobile phase composition: A: 0.1% formic acid (chromatography-grade formic acid (ROE, USA)) in water and B: 0.1% formic acid in acetonitrile. The elution gradient was 0.0–0.5 min, 1% B; 0.5–2.0 min, 1%–50% B; 2–9 min, 50%–99% B; 9–10 min, 99% B; 10.0–10.5 min, 99%–1% B; and 10.5–12.0 min, 1% B.
Procedures of Methodological Investigation
Instrument precision test: We took the same QC sample and made 6 consecutive injections. The data were exported as the peak area, after the missing value was filled, and the relative standard deviation (RSD) value of each ion feature was calculated; the features with <30% accounted for >70%.
Method precision test: Six QC samples were prepared in parallel and continuously injected for analysis. The data were exported as peak area, after the missing value was filled, the RSD value of each ion feature was calculated, and the features with RSD <30% accounted for >70%.
Sample stability test: We took the same QC sample and injected samples at six time points during the whole injection process. The data were exported as peak area, after the missing value was filled, the RSD value of each ion feature was calculated. and the features with RSD <30% accounted for >70%.
Statistical Analysis
UPLC-Q-TOF/MS technology was used to analyze the metabolomic profile of clinical serum samples in the NC, TB, and LC groups. Data collected by the instrument were passed through the Masslynx (version 4.1) data processing system (software parameters: mass error 0.01 da; retention time error 0.5 min), the intensity of each ion was normalized to the total number of ions, and the data formed included retention time, m/z value, and peak area. These data were imported into the SIMCA-P version 14.1 (Umetrics, Sweden) for multivariate statistical analysis. Unsupervised principal component analysis (PCA) and supervised partial least squares discriminant analysis (PLS-DA) models were established to identify potential discriminant variables[24]. The PCA model was used to eliminate outlier samples. According to a variable importance in the projection (VIP) parameter >1 of the metabolic ion in the PLS-DA model, the T-test was used to screen out substances with p<0.05 to indicate the least-different molecular metabolites. We used the m/z value to search through HMDB (http://www.hmdb.ca/), and preliminarily screened out different small molecular metabolites based on fragment information.
Targeted Metabolomic Analysis
Sample preparation: Samples frozen and stored at −80℃ were thawed completely in the refrigerator at 4℃; then, 5 μL samples were taken into an EP tube, 995 μL methanol was added, vortexed for 1 min, allowed to stand for 5 min, centrifuged at 13,000 rpm for 10 min, and the supernatant was obtained for injection analysis. An appropriate amount of methanol was added into the weighed mixture to dilute 250, 100, 50, 25, 10, 5, 2.5, 1, and 0.5 ng/mL series solution for use as the standard solution.
Conditions of mass spectrometry analysis: The source voltage was ES+3.00 KV, source temperature was 400℃, gas-flow rate was 700 L/h, and cone was 50 L/h. The ion pair information of phenylalanylphenylalanine is 313.1/119.9, the cone is 30V, the collision is 18V.
Conditions of chromatographic analysis: In this experiment, UPLC (I-class)-MS (xexo TQD) was used for quantitative analysis. The chromatographic column was Waters ACQUITY UPLC BEH C18; column and sample-chamber temperatures: 35℃ and 4℃, respectively. The mobile phase comprised A: 0.1% formic acid in water; B: 1% formic acid water in acetonitrile; the flow rate was 0. 3 mL/min, and the injection volume was 1 μL. The specific elution gradient was 0–1 min, 5% B; 1.0–2.3 min, 5%–15% B; 2.3–3.0 min, 15%–100% B; 3.0–4.5 min, 100% B; 4.5–5.0 min, 100%–5% B; and 5–7 min, 5% B.
Methodology investigation: The standard curve was detected every day to determine the linearity and the minimum limit of quantitation.