A gene marker related to auxiliary diagnosis of lung cancer and application thereof
By screening eight low-expression gene markers in saliva, a detection kit was developed for the early diagnosis of lung cancer. This overcomes the limitations of existing screening methods, achieving efficient, non-invasive, and reliable lung cancer screening, and improving the accuracy and convenience of early diagnosis.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- THE FIRST AFFILIATED HOSPITAL OF GUANGXI MEDICAL UNIVERSITY
- Filing Date
- 2026-03-24
- Publication Date
- 2026-05-29
AI Technical Summary
Existing lung cancer screening methods, such as imaging examinations, have limitations such as high false positive rates and radiation exposure. The sensitivity and specificity of serum tumor marker detection are insufficient to meet the requirements for early screening, and there is a lack of non-invasive and reliable large-scale population screening methods.
Eight low-expression and statistically significant gene markers in saliva (CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C, and UBE3) were screened out, and corresponding detection kits were developed to detect saliva DNA, thereby improving the accuracy and reliability of early diagnosis of lung cancer.
Detection of genes with low expression in saliva significantly improves the accuracy and convenience of early diagnosis of lung cancer, reduces screening costs, is suitable for large-scale population screening and long-term monitoring, and provides a basis for early detection and precision treatment.
Smart Images
Figure CN122104910A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of gene detection technology, and in particular to a gene biomarker related to the auxiliary diagnosis of lung cancer and its application. Background Technology
[0002] Lung cancer is the leading cause of cancer-related morbidity and mortality worldwide. Its early clinical symptoms are often insidious, making diagnosis difficult and easily leading to missed opportunities for optimal treatment. The development and progression of lung cancer involve a complex regulatory network of multiple genes and pathways. In recent years, with the rapid development of molecular diagnostic technologies, early lung cancer screening through body fluid testing has become a research hotspot. Saliva, as a completely non-invasive test sample, contains abundant nucleic acid molecular information and can reflect the body's pathophysiological state. Although the abundance of low-expressed genes in saliva is relatively low, characteristic changes may appear in the early stages of tumor development. These changes often precede the appearance of clinical symptoms, providing a new research direction for the early diagnosis of lung cancer.
[0003] Precise detection of gene expression levels is a key technology for identifying these low-expression biomarkers. Advances in next-generation sequencing technologies and high-sensitivity detection platforms have made it possible to quantitatively analyze low-abundance transcripts in saliva samples. In particular, the application of technologies such as digital PCR and nanopore sequencing has significantly improved the detection sensitivity of low-expression genes, laying the methodological foundation for establishing early lung cancer diagnostic models based on multi-gene combinations. These technologies can not only accurately capture trace changes in gene expression but also enable the simultaneous detection of multiple biomarkers, greatly improving the specificity and reliability of diagnosis.
[0004] Currently, the preferred treatment for early-stage lung cancer is surgical resection of the lesion, with early detection and treatment being crucial. However, current clinical lung cancer screening methods primarily rely on imaging examinations, which, while capable of detecting lung nodules, suffer from limitations such as high false-positive rates and radiation exposure. Although serum tumor marker testing is simple to perform, its sensitivity and specificity are insufficient for early screening. In contrast, detection methods based on low-expression genes in saliva offer significant advantages, including being completely non-invasive, highly reproducible, and cost-effective, making them particularly suitable for large-scale population screening and long-term monitoring. Therefore, optimizing the combination of lung cancer markers in saliva holds promise as an important supplement to the existing lung cancer screening system, providing new technological means for the early detection and precise intervention of lung cancer. Summary of the Invention
[0005] This invention discloses a gene biomarker related to the auxiliary diagnosis of lung cancer and its application. It screens out gene biomarkers related to lung cancer in saliva samples, which can provide a basis for the early diagnosis and precision treatment of lung cancer.
[0006] To achieve the above objectives, the technical solution of the present invention is as follows:
[0007] The first aspect of the present invention provides a gene biomarker related to the auxiliary diagnosis of lung cancer, said biomarker being at least one of CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C, and UBE3.
[0008] Preferably, the genetic markers consist of CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C, and UBE3.
[0009] The second aspect of this invention provides the application of the above-described gene markers in the preparation of auxiliary diagnostic kits for lung cancer.
[0010] A third aspect of the present invention provides a lung cancer auxiliary diagnostic kit for detecting CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C and UBE3 in saliva sample DNA.
[0011] This invention screened eight key genes in saliva that were expressed at low levels and had statistical significance. Based on ROC curve calculations, it identified ten genes with low expression in saliva: CLYBL-AS2 (P=4.33e-05, AUC=0.98), EVI2A (P=0.000325, AUC=0.94), FAM195A (P=0.000725, AUC=0.92), and LOC100288721 (P=0.000487, AUC=0.93). The values of LRMP (P=4.33e-05, AUC=0.98), NME7 (P=2.17e-05, AUC=0.99), OR4D2 (P=0.00013, AUC=0.96), RPS15A (P=4.33e-05, AUC=0.98), TNRC6C (P=0.000725, AUC=0.92), and UBE3B (P=0.0015, AUC=0.9) were significant in differentiating between lung cancer and non-cancerous patients.
[0012] The test kits developed based on the above test results can be used for the auxiliary diagnosis of lung cancer patients at all stages. As an effective supplement to the lung cancer screening system, they help improve the accuracy, timeliness and precision of the tests, while also increasing the convenience of screening and reducing screening costs, thus helping lung cancer patients achieve "early detection and early treatment".
[0013] The genetic markers in this invention are derived from saliva, making the detection safe, non-invasive, highly acceptable, and easy to operate, which is beneficial for large-scale screening. Attached Figure Description
[0014] Figure 1 It is a differential analysis of saliva DNA data and a volcano map.
[0015] Figure 2A This is the ROC curve of the gene marker CLYBL-AS2 that distinguishes between lung cancer and non-lung cancer patients.
[0016] Figure 2B This is the ROC curve of the gene marker EVI2A, which distinguishes between lung cancer and non-lung cancer patients.
[0017] Figure 2C This is the ROC curve of the genetic marker FAM195A, which distinguishes between lung cancer and non-lung cancer patients.
[0018] Figure 2D This is the ROC curve of the gene marker NME7, which distinguishes between lung cancer and non-lung cancer patients.
[0019] Figure 2E This is the ROC curve of the genetic marker OR4D2, which distinguishes between lung cancer and non-lung cancer patients.
[0020] Figure 2F This is the ROC curve of the gene marker RPS15A, which distinguishes between lung cancer and non-lung cancer patients.
[0021] Figure 2G This is the ROC curve of the gene marker TNRC6C, which distinguishes between lung cancer and non-lung cancer patients.
[0022] Figure 2H This is the ROC curve of the gene marker UBE3B, which distinguishes between lung cancer and non-lung cancer patients. Detailed Implementation
[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with the embodiments of this invention. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0024] A thorough search of the Gene Expression Omnibus (GEO) database revealed the GSE32175 dataset. Normalization was performed using the `normalizeBetweenArrays` algorithm in R to remove batch effects. Then, the `limma` package was used to calculate differentially expressed genes, identifying those with logFC absolute value > 0 and p < 0.05. For low-expression differentially expressed genes in the GSE32175 dataset (including FAM195A, OR4D2, CLYBL-AS2, EVI2A, UBE3B, NME7, RPS15A, and TNRC6C), the Wilcoxon rank-sum test (a non-parametric test) was used to assess the significance of their expression differences between lung cancer patients and non-lung cancer controls. Furthermore, Receiver Operating Characteristic (ROC) curves were used to analyze the diagnostic efficacy of each gene, and the area under the curve (AUC) was calculated to evaluate their potential biomarker value in distinguishing between lung cancer and non-lung cancer samples.
[0025] Result: Combination Figure 1 As shown, eight genes with low expression and statistical significance were screened from 22,866 genes, including CLYBL-AS2, EVI2A, FAM195A, NME7, OR4D2, RPS15A, TNRC6C, and UBE3B. Furthermore, combining Figure 2 and Table 1, the ROC curves suggest that these eight low-expressed genes in saliva have differential diagnostic value for lung cancer and non-cancerous patients.
[0026] Table 1 ROC Curve Analysis
[0027] Genetic markers Location P AUC CLYBL-AS2 99690098-99690971 4.33e-05 0.98 EVI2A 31316410-31321622 0.000325 0.94 FAM195A 641828-648474 0.000725 0.92 NME7 169132531-169367797 2.17e-05 0.99 OR4D2 58166982-58171116 0.00013 0.96 RPS15A 18781295-18790334 4.33e-05 0.98 TNRC6C 77957557-78108835 0.000725 0.92 UBE3B 109477634-109547829 0.0015 0.9
[0028] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A gene biomarker associated with the auxiliary diagnosis of lung cancer, characterized in that: The genetic marker is composed of at least one of CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C, and UBE3B.
2. The gene markers related to the auxiliary diagnosis of lung cancer according to claim 1, characterized in that: The genetic markers consist of CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C, and UBE3.
3. The use of the gene marker as described in claim 1 or 2 in the preparation of a lung cancer auxiliary diagnostic kit.
4. A lung cancer auxiliary diagnostic kit, characterized in that: The kit is used to detect CLYBL-AS2, EVI2A, FAM195A, LOC100288721, LRMP, NME7, OR4D2, RPS15A, TNRC6C and UBE3 in saliva sample DNA.