Biomarker for predicting EGFR-TKI drug resistance and application thereof

Abstract

The invention discloses a biomarker for predicting EGFR-TKI drug resistance and application thereof, and the biomarker can be used for predicting the EGFR-TKI treatment drug resistance of a LUAD patient so as to optimize a personalized treatment scheme of the LUAD patient. The biomarker for predicting the drug resistance of the EGFR-TKI is VANGL1. The invention also provides an application of the biomarker for predicting EGFR-TKI drug resistance, the biomarker is used for preparing a drug for recovering EGFR-TKI sensitivity, and the drug knockout VANGL1. Or the medicine is used for down-regulating the expression of VANGL1 in PC9 cells and PC-9del19-T790M-C797S cells, and inhibiting the spherical clone forming ability of lung adenocarcinoma cells. Or is used for preparing a medicine for recovering EGFR-TKI sensitivity, and the medicine knocks down VANGL1.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedicine, and in particular to a biomarker for predicting EGFR-TKI resistance, and application of the biomarker for predicting EGFR-TKI resistance in restoring EGFR-TKI sensitivity. Background Art

[0002] Lung cancer is one of the most common malignant tumors in the world. Its morbidity and mortality have remained high for a long time, posing a serious threat to human health. According to statistics from the World Health Organization (WHO), lung cancer ranks first in cancer-related deaths worldwide, and its incidence has shown a significant upward trend in the past few decades. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer, accounting for about 40% of all lung cancer cases. The high morbidity and mortality of LUAD are closely related to its unclear early symptoms, rapid disease progression, and resistance to treatment.

[0003] Although a lot of research has been done on the pathogenesis of LUAD in recent years, individual differences between patients and heterogeneity of treatment sensitivity remain major challenges in clinical practice. There are significant differences in the response of different patients to treatment, which makes the formulation of personalized treatment plans extremely complicated. Epidermal growth factor receptor (EGFR) is one of the most common driver genes in LUAD, and its mutation accounts for a high proportion of LUAD patients. Small molecule EGFR tyrosine kinase inhibitors (EGFR-TKIs), as targeted therapeutic drugs for EGFR mutations, have been widely approved for the first-line treatment of LUAD and have achieved significant efficacy in clinical practice. However, although EGFR-TKIs show good efficacy in initial treatment, most patients will develop acquired or secondary resistance within 1-2 years after treatment. The emergence of this resistance greatly limits the long-term efficacy of TKIs and hinders the further development of precision therapy. Therefore, finding biomarkers that can accurately predict EGFR-TKI resistance is of great significance for optimizing treatment strategies and improving patient survival.

[0004] Cancer stemness refers to a subpopulation of tumor cells with stem cell characteristics. These cells have the ability to self-renew, differentiate and form tumors. Cancer stemness is closely related to tumor recurrence, metastasis and drug resistance. Studies have shown that cancer stemness plays an important role in EGFR-TKI resistance. Cancer stem cells (CSCs) can escape the inhibitory effects of TKIs through a variety of mechanisms, leading to drug resistance.

[0005] VANGL1 (planar cell polarity protein 1) is a core molecule in the Wnt planar cell polarity (Wnt-PCP) signaling pathway, acting as a transmembrane scaffold to transmit signals. During normal lung development, VANGL1 forms a complex with VANGL2 to promote thinning of the lung mesenchyme and expansion of the epithelium, processes that are indispensable in embryonic development. In recent years, the abnormal expression of VANGL1 in various tumors and its biological functions have gradually attracted attention. Studies have shown that VANGL1 is highly expressed in a variety of tumors and is closely related to cell proliferation, migration and invasion. VANGL1 can promote the self-renewal and differentiation ability of tumor cells, thereby maintaining tumor stemness. In LUAD, previous studies have focused on how VANGL1 can mitigate the adverse effects of radiotherapy. However, to date, no studies have reported the role of VANGL1 as a marker of EGFR-TKI resistance in LUAD. Summary of the invention

[0006] In order to overcome the defects of the prior art, the technical problem to be solved by the present invention is to provide a biomarker for predicting EGFR-TKI resistance, which can predict the resistance of LUAD patients to EGFR-TKI treatment, thereby optimizing the personalized treatment plan for LUAD patients.

[0007] The technical solution of the present invention is: the biomarker for predicting EGFR-TKI resistance is VANGL1, the protein sequence of which is

[0008] MDTESTYSGYSYYSSHSKKSHRQGERTRERHKSPRNKDGRGSEKSVTIQP

[0009] PTGEPLLGNDSTRTEEVQDDNWGETTTAITGTSEHSISQEDIARISKDMED

[0010] SVGLDCKRYLGLTVASFLGLLVFLTPIAFILLPPILWRDELEPCGTICEGLFI

[0011] SMAFKLLILLIGTWALFFRKRRADMPRVFVFRALLLVLIFLFVVSYWLFYG

[0012] VRILDSRDRNYQGIVQYAVSLVDALLFIHYLAIVLLELRQLQPMFTLQVVR

[0013] STDGESRFYSLGHLSIQRAALVVLENYYKDFTIYNPNLLTASKFRAAKHM

[0014] AGLKVYNVDGPSNNATGQSRAMIAAAARRRDSSHNELYYEEAEHERRV

[0015] KKRKARLVVAVEEAFIHIQRLQAEEQQKAPGEVMDPREAAQAIFPSMAR

[0016] ALQKYLRITRQQNYHSMESILQHLAFCITNGMTPKAFLERYLSAGPTLQY

[0017] DKDRWLSTQWRLVSDEAVTNGLRDGIFVLKCLDFSLVVNVKKIPFIILSEEFIDPKSHKFVLRLQSETSV.

[0018] The biomarker for predicting EGFR-TKI resistance of the present invention can predict the resistance of LUAD patients to EGFR-TKI treatment, thereby optimizing the personalized treatment plan for LUAD patients.

[0019] Also provided is an application of a biomarker for predicting EGFR-TKI resistance, which is used for preparing a drug for restoring EGFR-TKI sensitivity, wherein the drug knocks out VANGL1.

[0020] Also provided is a drug for preparing a drug for restoring EGFR-TKI sensitivity, which downregulates PC9 cells and PC-9 del19-T790M-C797S The expression of VANGL1 in cells inhibits the spheroid formation ability of lung adenocarcinoma cells.

[0021] Also provided is a method for preparing a drug for restoring EGFR-TKI sensitivity, wherein the drug knocks down VANGL1. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The following are functional analysis diagrams of VANGL1. 1A shows the expression of VANGL1 in pan-cancer, and the picture shows that VANGL1 is abnormally highly expressed in most cancers; 1B shows the abnormally high expression of VANGL1 in lung adenocarcinoma in the TCGA database; 1C shows the analysis results of the lung adenocarcinoma dataset GSE31547 in the GEO database, which shows that VANGL1 is abnormally highly expressed in lung adenocarcinoma; 1D shows the KM survival analysis curve, and high expression of VANGL1 affects patient survival; 1E shows the diagnostic efficacy curve, and VANGL1 can distinguish between tumor groups and normal groups; 1F shows the COX analysis forest diagram, and high expression of VANGL1 is significantly correlated with poor survival prognosis.

[0023] Figure 2The following are sample transcriptome analysis diagrams. 2A is a differential gene volcano diagram; 2B is a GO enrichment analysis bubble diagram; 2C is a KEGG enrichment analysis bubble diagram.

[0024] Figure 3 This is a mouse single-cell transcription sequencing analysis. 3A is a tSNE diagram of the overall clustering of single-cell sequencing; 3B is a bubble diagram of marker-specific expression; 3C is an inferCNV analysis of tumor cells; 3D is a tSNE diagram of tumor cell re-clustering; 3E is a bubble diagram of marker-specific expression of tumor clustering; 3F is a diagram of the evolution of tumor cell subpopulations analyzed by Monocle; 3G is a diagram of the proportion of cell subpopulations in different samples; 3H is a volcano diagram of differential genes; 3I is a bubble diagram of KEGG enrichment analysis of differential genes.

[0025] Figure 4 4A is a PC9 cell stem sphere formation experiment, 4B is a PC9 cell stem sphere formation experiment with VANGL1 knockdown, and 4C is an osimertinib-resistant PC-9 del19-T790M-C797 S cell stemness sphere test, 4D is PC-9 del19-T790M-C797S Knockdown of VANGL1 resulted in cell stemness sphere formation experiment. It was found that when VANGL1 was knocked down, the sphere formation in tumor cells was significantly inhibited.

[0026] Figure 5 To inhibit VANGL1 and reduce EGFR-TKI resistance. Among them, 5A is the experimental grouping of mice; 5B is a picture of mouse transplanted tumors; 5C is a graph of mouse tumor growth curve; 5D is a graph of mouse tumor weight; 5E is a flow cytometry graph of the mouse control group and the knockdown of VANGL1. The results show that knockdown of VANGL1 inhibits the expression of stemness marker CD133; 5F is an organoid staining graph of patient samples with high and low expression of VANGL1; 5G is the EGFR-TKI drug sensitivity curve in the VANGL1 high and low expression groups. The results show that the lower the expression of VANGL1, the more sensitive it is to EGFR-TKI drugs. DETAILED DESCRIPTION

[0027] This biomarker for predicting EGFR-TKI resistance is VANGL1, and its protein sequence is: See sequence table SEQ-1.

[0028] The biomarker for predicting EGFR-TKI resistance of the present invention can predict the resistance of LUAD patients to EGFR-TKI treatment, thereby optimizing the personalized treatment plan for LUAD patients.

[0029] Preferably, VANGL1 is abnormally highly expressed in lung adenocarcinoma.

[0030] Preferably, VANGL1 expression is positively correlated with tumor stemness.

[0031] Preferably, VANGL1 overexpression promotes tumor growth and osimertinib resistance.

[0032] Also provided is an application of a biomarker for predicting EGFR-TKI resistance, which is used for preparing a drug for restoring EGFR-TKI sensitivity, wherein the drug knocks out VANGL1.

[0033] Preferably, the drug reduces tumor stemness and sensitizes EGFR-TKI resistance.

[0034] Also provided is a drug for preparing a drug for restoring EGFR-TKI sensitivity, which downregulates PC9 cells and PC-9 del19-T790M-C797S The expression of VANGL1 in cells inhibits the spheroid formation ability of lung adenocarcinoma cells.

[0035] Also provided is a method for preparing a drug for restoring EGFR-TKI sensitivity, wherein the drug knocks down VANGL1.

[0036] Preferably, the drug sensitizes the inhibitory effect of osimertinib on drug-resistant tumor cells.

[0037] The beneficial technical effects of the present invention are as follows:

[0038] 1. Bioinformatics analysis showed that VANGL1 was highly expressed in lung adenocarcinoma and was a risk factor for poor prognosis of lung adenocarcinoma.

[0039] (1) In the TCGA database, the expression of VANGL1 in lung adenocarcinoma tumor tissues was higher than that in normal tissues (P<0.001). In the GEO lung adenocarcinoma dataset (GSE40791 and GSE31547), it was also found that VANGL1 was abnormally highly expressed in tumors (P=0.022; P=0.003).

[0040] (2) KM survival curve was used to analyze the relationship between VANGL1 expression and patient survival. The results showed that high expression of VANGL1 affected the patient's survival time (P<0.01); ROC curve was used to evaluate the diagnostic efficacy of VANGL1 expression in distinguishing tumor group from normal group. The analysis results showed that VANGL1 expression could accurately predict lung adenocarcinoma (LUAD), with an area under the curve (AUC) of 0.790 and a 95% confidence interval of 0.741-0.834.

[0041] (3) According to univariate and multivariate survival analysis, VANGL1 was a risk factor for overall survival (OS) in LUAD patients (hazard ratio [HR] = 1.56) and was an independent risk factor of traditional clinical factors (HR = 2.62).

[0042] 2. Lung adenocarcinoma samples were collected to construct lung adenocarcinoma tumor organoids. Transcriptome sequencing found that the differential expression of VANGL1 affected tumor stemness, thereby affecting the growth rate of tumor organoids and affecting the EGFR-TKI resistance pathway.

[0043] 3. After VANGL1 knockout, tumor stemness can be reduced and EGFR-TKI resistance can be affected.

[0044] (1) Single-cell sequencing analysis was performed after mice developed tumors. InferCNV was used to analyze epithelial cells in lung adenocarcinoma, and chromosome copy number variation was found, which was defined as tumor cells. Monocle was used to analyze the evolution of tumor cell subpopulations, and it was found that VANGL1 gene knockout significantly reduced the number of tumor stem cells, confirming its correlation with tumor stem cell characteristics. Differential gene expression analysis showed significant enrichment of the EGFR-TKI resistance pathway, supporting the role of VANGL1 in tumor resistance.

[0045] (2) The spheroidization assay was used to evaluate its effect on the stemness characteristics of lung adenocarcinoma cells and down-regulate PC9 cells and PC-9 del19-T790M-C797S The expression of VANGL1 in cells significantly inhibited the spheroid colony-forming ability of lung adenocarcinoma cells, which further verified the regulatory effect of VANGL1 on the characteristics of tumor stem cells.

[0046] 4. By observing the inhibitory effect of VANGL1 knockdown on lung adenocarcinoma transplanted tumors; and the inhibitory effect of combined osimertinib on osimertinib-resistant cell line immunodeficient mouse transplanted tumors. The results showed that VANGL1 knockdown can significantly inhibit the growth of mouse transplanted tumors; and can sensitize osimertinib to the inhibitory effect of resistant cell nude mouse transplanted tumors. In addition, through the verification of organoids derived from patient samples, it was found that when VANGL1 is lowly expressed, it is more sensitive to osimertinib.

[0047] The embodiments of the present invention are described in detail below.

[0048] Experimental Example 1

[0049] The expression of VANGL1 in tumors was analyzed by bioinformatics, and the effect of VANGL1 on the prognosis of lung adenocarcinoma was analyzed.

[0050] (1) The scale function was used to convert the gene expression levels in the TCGA database and the GEO database, and the difference analysis of VANGL1 expression between the tumor group and the normal group was performed. The paired difference analysis was analyzed using Wilcoxon Signed Rank Tests. The expression distribution of VANGL1 gene in normal and tumor tissues in the TCGA database and GEO data, the Wilcoxon rank sum test result P value was less than 0.05, the results are as follows Figure 1 (AC) display.

[0051] (2) The Kaplan-Meier analysis of the significance of the difference in survival time between patients with high and low expression of VANGL1 in the TCGA database showed that high expression of VANGL1 affected the survival time of patients. Figure 1D). The ROC analysis was performed using the pROC package in R language to calculate the area under the curve (AUC) and its 95% confidence interval (95% CI) to evaluate the diagnostic performance of VANGL1 in distinguishing tumor groups from normal groups. The results showed that the higher the diagnostic efficacy of VANGL1, the higher the AUC value was greater than 0.7 ( Figure 1 E).

[0052] (3) The survival package of R language was used to perform univariate and multivariate Cox survival analysis on VANGL1 gene expression and traditional clinical variables to evaluate their effects on patient survival time. Univariate analysis showed that high expression of VANGL1 gene was significantly associated with poor survival prognosis. Even after controlling for the effects of other clinical variables, VANGL1 gene still showed statistical significance, thus proving that it is an independent prognostic factor ( Figure 1 F).

[0053] Experimental Example 2

[0054] Lung adenocarcinoma samples were collected to construct lung adenocarcinoma tumor organoids, and the results showed that the growth rates of organoids were different. Transcriptome sequencing of samples: Total RNA was extracted from a variety of samples (including tissues and cells). RNA sequencing was performed using the Illumina platform, and gene expression was quantified by removing low-quality data. The DESeq2 software package was used to perform differential expression analysis on the original read matrix. Functional enrichment analysis was performed on differentially expressed genes to further study the pathways and molecular functions affected by these genes. Gene identifiers were converted using the org.Hs.eg.db database, and GO and KEGG enrichment analysis was performed using the clusterProfiler software package. Finally, ggplot2 was used to visualize the enrichment results. The results showed that transcriptome sequencing found that compared with the growth rate, the fast-growing group had 1,675 highly differentially expressed genes and 1,491 lowly differentially expressed genes compared with the slow-growing group, among which VANGL1 was significantly highly expressed. The differential expression of VANGL1 affects tumor stemness, thereby affecting the growth rate of tumor organoids, and affects the EGFR-TKI resistance pathway ( Figure 2 ).

[0055] Experimental Example 3

[0056] (1) VANGL1 was further knocked out in mouse lung cancer cells LLC1, and single-cell sequencing was performed after the mice were inoculated with tumors. Single-cell analysis of epithelial cells in lung adenocarcinoma using inferCNV revealed the presence of chromosomal copy number variations and defined them as tumor cells. Further cell clustering analysis identified six cell subtypes. Using Monocle to analyze the evolution of tumor cell subpopulations, it was found that the C3 and C6 cell clusters were rich in stem cell characteristics and were identified as tumor stem cells. VANGL1 gene knockout significantly reduced the number of tumor stem cells, confirming its correlation with tumor stem cell characteristics. In addition, differential gene expression analysis showed significant enrichment of the EGFR-TKI resistance pathway, supporting the role of VANGL1 in tumor resistance ( Figure 3 ).

[0057] (2) The spheroidization assay was used to evaluate its effect on the stemness characteristics of lung adenocarcinoma cells, verifying the regulatory effect of VANGL1 on the characteristics of tumor stem cells.

[0058] The cells were grouped into PC9 cells, PC9 cells with VANGL1 knockdown, and osimertinib-resistant PC-9 del19-T790M-C797S Cells and PC-9 del19-T790M-C797S Knockdown VANGL1 cells. Wash with PBS and digest. After collection, resuspend and count the cells and adjust the concentration to 4000 cells / mL in PBS. After centrifugation, collect the cell pellet and add 1 mL of spheroid culture medium. Inoculate the cells into 96-well plates, 10 wells per group. Cells were grown under standard conditions (37°C, 5% CO 2 ) for two weeks. Observe and photograph the spheroid formation from the 8th, 10th, 12th and 14th days. Count the number of spheroids with a diameter greater than 75 microns. Spheroid formation efficiency (SPE) = number of spheroids with a diameter greater than 75 microns in each well / total number of cells initially seeded in each well. The results showed that when VANGL1 expression was reduced, spheroid formation in tumor cells was significantly inhibited, inhibiting tumor stemness ( Figure 4 ).

[0059] Experimental Example 4

[0060] The inhibitory effect of VANGL1 knockdown on lung adenocarcinoma xenografts was observed; and the inhibitory effect of VANGL1 knockdown on xenografts in immunodeficient mice with osimertinib-resistant cell lines was observed. A total of 24 male NCG mice, all 5-6 weeks old, were used. After a three-day adaptation period, a tumor model was constructed. Mice were subcutaneously injected with PC-9 del19-T790M-C797S Cells and PC-9 del19-T790M-C797S Each mouse received 1.5 × 10 6 The tumor size was measured daily to calculate the tumor volume (volume = length × width 2 × 0.5). When the tumor volume reached 50 mm3 At 3 pm, the mice were randomly divided into a treatment group and a control group. The treatment group received osimertinib orally daily at a dose of 10 mg / kg. The body weight and tumor volume of the mice were monitored every two days. After 28 days of treatment, the mice were killed and the tumor tissues were collected and weighed. In order to detect the specific tumor stemness marker CD133, antibody staining was used for flow cytometry detection and analyzed on a FACSCanto II flow cytometer (BD Biosciences). Data analysis was performed using FlowJo VX software. The results showed that knockdown of VANGL1 can significantly inhibit the growth of mouse transplanted tumors and reduce the expression of tumor stemness marker CD133; and can sensitize the inhibitory effect of osimertinib on drug-resistant cell nude mouse transplanted tumors ( Figure 5 AE). Eight clinical samples of lung adenocarcinoma were collected for organoid culture, and immunohistochemistry was used to quantitatively analyze VANGL1. Drug sensitivity testing showed that low expression of VANGL1 was more sensitive to osimertinib ( Figure 5 FG).

[0061] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. A biomarker for predicting EGFR-TKI resistance, characterized by: It is VANGL1, and the protein sequence is.

2. The biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: VANGL1 is abnormally overexpressed in lung adenocarcinoma.

3. The biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: VANGL1 expression is positively correlated with tumor stemness.

4. The biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: VANGL1 overexpression promotes tumor growth and osimertinib resistance.

5. The use of a biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: It is used to prepare a drug for restoring EGFR-TKI sensitivity, which knocks out VANGL1.

6. The use of a biomarker for predicting EGFR-TKI resistance according to claim 5, characterized in that: The drug reduces tumor stemness and sensitizes EGFR-TKI resistance.

7. The use of a biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: It is used to prepare a drug for restoring EGFR-TKI sensitivity, which downregulates PC9 cells and PC-9 del19-T790M-C797S The expression of VANGL1 in cells inhibits the spheroid formation ability of lung adenocarcinoma cells.

8. The use of a biomarker for predicting EGFR-TKI resistance according to claim 1, characterized in that: It is used to prepare a drug for restoring EGFR-TKI sensitivity by knocking down VANGL1.

9. The use of a biomarker for predicting EGFR-TKI resistance according to claim 8, characterized in that: The drug sensitizes the inhibitory effect of osimertinib on drug-resistant cell tumors.

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