Biomarker-spectrum-based lung cancer risk prediction kit for high-risk groups in rural China
A technology of biomarkers and kits, applied in the field of medical biology, can solve problems such as unreported, loss of radical surgery, difficult to achieve, etc., and achieve the effect of simple expression level
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Embodiment 1
[0031] The composition of the kit of the invention:
[0032] Consists of biomarkers and enzyme-labeled antibodies, carbonate buffer with pH 9.6, phosphate buffer with pH 7.4, serum protein diluent, stop solution, tetramethylbenzidine substrate solution, normal Composition of serum and positive control serum.
[0033] The biomarkers include gastrin release propeptide, carcinoembryonic antigen, fragments of cytokeratin 19 and squamous cell carcinoma antigen; the carbonate buffer with a pH of 9.6 is composed of 1.59 grams of sodium carbonate and 2.93 grams of sodium bicarbonate is added to 1L of distilled water; the phosphate buffer with a pH of 7.4 is 0.2 grams of potassium dihydrogen phosphate, 2.9 grams of disodium hydrogen phosphate dodecahydrate, 8.0 grams of sodium chloride, 0.2 Grams of potassium chloride, 0.5mL Tween-20 added to 1L of distilled water; the serum protein diluent is 0.1 grams of bovine serum, goat serum or rabbit serum protein added to 100mL of phosphate buffer ...
Embodiment 2
[0048] The present invention collects 715 patients from the rural population who have been clinically determined to have high risk factors for lung cancer, and finally diagnoses 434 lung cancer patients by pathology. The serum of 154 lung cancer patients is sampled by randomization method; at the same time, in the serum bank of 281 non-lung cancer patients, 235 normal human sera were sampled by randomization method. Chemiluminescence microparticle immunoassay was used to detect four biomarkers in serum, and clinical information such as patient age, smoking history, gender and so on was collected. The obtained model sensitivity and specificity are shown in Table 1. The ROC curve of a lung cancer risk prediction model based on biomarker profiles for high-risk groups in rural China is as follows figure 1 Shown.
[0049] Table 1 Effectiveness of lung cancer risk prediction model based on biomarker profile for high-risk groups in rural China
[0050]
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