CN112522409A

CN112522409A - Application of gene marker combination in lung cancer screening and prognosis judgment

Info

Publication number: CN112522409A
Application number: CN202011589177.1A
Authority: CN
Inventors: 杨承刚; 宋宏涛
Original assignee: Beijing Medintell Bioinformatic Technology Co Ltd
Current assignee: Beijing Medintell Bioinformatic Technology Co Ltd
Priority date: 2020-12-29
Filing date: 2020-12-29
Publication date: 2021-03-19

Abstract

The invention discloses application of a gene marker combination in lung cancer screening and prognosis judgment. The gene marker can effectively diagnose the lung cancer, reduce the omission ratio of the lung cancer, is very favorable for early diagnosis and early treatment of the lung cancer, is greatly helpful for improving the prognosis of the lung cancer and reducing the death rate of the lung cancer, and has good clinical use and popularization values.

Description

Application of gene marker combination in lung cancer screening and prognosis judgment

Technical Field

The invention relates to the field of disease diagnosis, in particular to application of a gene marker combination in lung cancer screening and prognosis judgment.

Background

Lung cancer is the most common malignant tumor in china and globally, and is also the leading cause of cancer death in men. The incidence of lung cancer in the female population is second only to breast cancer. Global Burden of Disease (GBD) data shows that over 280 ten thousand people have trachea, bronchi or lung cancer worldwide in 2016, with up to 100 thousand people in china. The number of deaths with the above cancers worldwide in 2016 is 170 ten thousand, accounting for 3.12% of the total deaths. The number of deaths in 2016 in China is 59 ten thousand, accounting for 6.11% of the total deaths. Statistics show that the prevalence and mortality of trachea, bronchi and lung cancer are continuously increased globally from 1990 to 2016, the prevalence and mortality of China are also continuously increased, and the increasing trend is relatively consistent with the global increasing trend.

Yunnan China is one of high cancer incidence areas, and particularly, the incidence rate of female lung cancer is one of the highest areas in the world. The average incidence rate of lung cancer in Yunnan province is 44/10 ten thousand, which is twice of the average incidence rate in China. Wherein, the incidence rate of lung cancer in Xuanwei area of Yunnan province is the first in China. The pathogenesis of Xuanwei lung cancer is unclear. In recent years, the incidence of diseases in areas with concentrated mining industries, such as Xuanwei and Fuyuan, is high, so that the relationship between environmental pollution and lung cancer is not clinically excluded. At present, no effective treatment means is available for lung cancer. Early lung cancer patients can achieve better prognosis through surgical treatment, so early detection of lung cancer can prevent early treatment, prevent disease progression and avoid clinical decompensation complications, which is the basic principle of lung cancer treatment. Early lung cancer often does not show obvious clinical symptoms due to strong compensatory ability of the lung, and the lung cancer is in an advanced stage when the symptoms are obvious. Therefore, the discovery of the diagnostic marker of the lung cancer has good clinical significance and application value.

Clinically, the means for diagnosing lung cancer mainly relies on ultrasound imaging and lung puncture for diagnosis. The sensitivity of ultrasonic diagnosis is low, and lung puncture damages the lung of a patient, so that the risk exists, the popularization is not easy, and many patients cannot be diagnosed until the lung cancer is in the decompensation stage. Recently, it has been found that gene molecules can be used as markers for lung cancer diagnosis, but the sensitivity and specificity of single gene diagnosis need to be improved.

Disclosure of Invention

The invention provides a system for diagnosing lung cancer or predicting the prognosis of lung cancer, which comprises an input device for inputting the expression quantity of a molecular marker, an output device for outputting the diagnosis result of lung cancer or the prognosis result of lung cancer; wherein the molecular marker is EGLN3, MAL, MFAP5, TMPRSS 11E.

Further, the system also includes a computing device comprising a memory and a processor; the memory having stored therein a computer program, the processor being configured to execute the computer program stored in the memory; and the computing device is used for analyzing the possibility of the lung cancer risk result or predicting the prognosis condition of the lung cancer patient according to the expression quantity of the marker.

For example, the computer program runs the following formula: riskScore ═ mRNA expression level (0.089433 × EGLN3 gene) + (0.031948 × MFAP5 gene mRNA expression level) + (0.17524 × MAL gene mRNA expression level) + (0.035276 × TMPRSS11E gene mRNA expression level). The computing device takes the median of the riskScore as a threshold value, and judges that the prognosis of the lung cancer patient is poor when the threshold value is higher than the threshold value; if the value is lower than the threshold value, the prognosis of the lung cancer patient is judged to be good.

Further, the system also comprises a device for detecting the expression level of the molecular marker; preferably, the detection device comprises a real-time quantitative PCR instrument, a real-time quantitative PCR primer, a high-throughput sequencing platform, a detection chip and a chip signal reader.

Further, the chip comprises a probe for detecting the expression level of the marker; preferably, the chip also comprises an internal reference probe, wherein the internal reference probe is a probe for detecting the expression level of GAPDH or beta-Actin.

Further, the real-time quantitative PCR primer comprises a real-time quantitative PCR primer for detecting the expression quantity of the molecular marker; preferably, the real-time quantitative PCR primer further comprises an internal reference primer, and the internal reference primer is a real-time quantitative PCR primer for detecting GAPDH or beta-Actin.

The invention also provides application of a reagent for detecting the molecular markers in preparing a product for diagnosing lung cancer or predicting the prognosis of lung cancer, wherein the molecular markers are EGLN3, MAL, MFAP5 and TMPRSS 11E.

Further, the reagent comprises a nucleic acid capable of binding to the molecular marker; the nucleic acid is capable of detecting the expression level of the molecular marker.

Still further, the nucleic acid comprises primers for specific amplification of the molecular marker used in real-time quantitative PCR.

Further, the nucleic acid includes a probe for the molecular marker used in a gene chip.

Further, detecting the molecular marker is performed by:

1) obtaining a subject sample;

2) determining the expression level of the molecular marker in the sample.

The invention also provides a product for diagnosing lung cancer or predicting the prognosis of lung cancer, which comprises a reagent for detecting the expression level of molecular markers, wherein the molecular markers are EGLN3, MAL, MFAP5 and TMPRSS 11E.

Further, the product comprises a chip, a kit, test paper or a high-throughput sequencing platform.

Further, the definition of the reagent is the same as that described above.

The chip comprises a solid phase carrier and an oligonucleotide probe fixed on the solid phase carrier.

The kit comprises reagents for detecting the transcription level of the molecular marker.

The high throughput sequencing platform comprises reagents for detecting the transcript level of the molecular marker.

The test paper comprises a test paper carrier and oligonucleotides fixed on the test paper carrier, wherein the oligonucleotides can detect the transcription level of the molecular marker.

The invention also provides a molecular marker combination for diagnosing lung cancer or predicting the prognosis of lung cancer, wherein the molecular marker combination comprises EGLN3, MAL, MFAP5 and TMPRSS 11E.

The invention also provides a reagent for detecting the expression quantity of the molecular marker combination.

Further, the nucleic acid includes a primer for specifically amplifying the molecular marker used in real-time quantitative PCR, a probe for the molecular marker used in a gene chip.

The primer of the present invention can be prepared by chemical synthesis, appropriately designed by referring to known information using a method known to those skilled in the art, and prepared by chemical synthesis.

The probe of the present invention may be prepared by chemical synthesis, by appropriately designing with reference to known information using a method known to those skilled in the art, and by chemical synthesis, or may be prepared by preparing a gene containing a desired nucleic acid sequence from a biological material and amplifying it using a primer designed to amplify the desired nucleic acid sequence.

The probe that hybridizes to the nucleic acid sequence of a gene may be DNA, RNA, a DNA-RNA chimera, PNA, or other derivatives. The length of the probe is not limited, and any length may be used as long as specific hybridization and specific binding to the target nucleotide sequence are achieved. The length of the probe may be as short as 25, 20, 15, 13 or 10 bases in length. Also, the length of the probe can be as long as 60, 80, 100, 150, 300 base pairs or more, even for the entire gene. Since different probe lengths have different effects on hybridization efficiency and signal specificity, the length of the probe is usually at least 14 base pairs, and at most, usually not more than 30 base pairs, and the length complementary to the nucleotide sequence of interest is optimally 15 to 25 base pairs. The probe self-complementary sequence is preferably less than 4 base pairs so as not to affect hybridization efficiency.

According to the present application, EGLN3 is referenced 112399 in the NCBI database; MFAP5 is referenced as 8076 in the NCBI database; MAL is referenced 4118 in NCBI database; TMPRSS11E is referenced 28983 in the NCBI database.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention without limiting the scope of the invention. In the drawings:

FIG. 1 is a boxplot showing differential mRNA expression of the EGLN3 gene, where A: TCGA; b: GEO;

fig. 2 shows a boxplot of the differential mRNA expression of the MFAP5 gene, where a: TCGA; b: GEO;

fig. 3 shows a boxplot of MAL gene mRNA differential expression, where a: TCGA; b: GEO;

fig. 4 shows a box plot of the differential mRNA expression of TMPRSS11E gene, where a: TCGA; b: GEO;

fig. 5 shows ROC plot of diagnosis of lung adenocarcinoma by EGLN3 gene, wherein a: TCGA; b: GEO;

fig. 6 shows ROC plots of MFAP5 gene diagnosis of lung adenocarcinoma, where a: TCGA; b: GEO;

fig. 7 shows ROC graph of diagnosis of lung adenocarcinoma by MAL gene, wherein a: TCGA; b: GEO;

fig. 8 shows ROC plots of TMPRSS11E gene diagnosis of lung adenocarcinoma, where a: TCGA; b: GEO;

FIG. 9 shows ROC plots for EGLN3+ MAL + MFAP5+ TMPRSS11E combined diagnosis of lung adenocarcinoma, where A: TCGA; b: GEO;

FIG. 10 shows a survival plot of EGLN3+ MAL + MFAP5+ TMPRSS11E in TCGA for predicting prognosis of lung adenocarcinoma;

FIG. 11 shows a survival plot of EGLN3+ MAL + MFAP5+ TMPRSS11E in GEO for predicting prognosis of lung adenocarcinoma.

Detailed Description

The following detailed description of embodiments of the present application will be made with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present application, are given by way of illustration and explanation only, and are not intended to limit the present application.

Example 1 Gene markers associated with diagnosis and prognosis of Lung cancer

1. Data download

Downloading RNA-seq data and clinical information of lung adenocarcinoma from a TCGA database, and removing a sample with missing survival information, wherein the residual sample amount is paracarcinoma: cancer 59: 500. Chip data and clinical information of the GSE31210 dataset were downloaded from GEO, and the sample size was paracarcinoma: cancer 20: 226.

2. Data normalization

RNA-seq data for TCGA was normalized using Voom method, and chip data for GEO was normalized using RMA method.

3. Differential expression analysis

Differential expression analysis was performed using the "limma" package in the R software, with screening criteria for differential genes being adj. pvalue <0.05, | log2FC | > 1. Under this standard, there are 3948 differentially expressed genes, 1504 differentially expressed genes up-regulated, and 2444 differentially expressed genes down-regulated in TCGA. There were 866 differentially expressed genes, 323 up-regulated differentially expressed genes, and 543 down-regulated differentially expressed genes in the GEO. There were 717 genes differentially expressed in agreement in both databases, 241 in agreement with up-regulation and 476 in agreement with down-regulation.

4. One-factor Cox analysis

A one-way Cox analysis was performed on 717 genes with consistent differential expression, and genes with P <0.05 were considered to have an effect on survival in patients with lung adenocarcinoma. Under this standard, there are 246 genes in the TCGA database and 314 genes in the GEO database. After the intersection treatment, 156 genes were obtained.

5. Multi-gene joint prediction ROC curve analysis

Receiver Operating Curves (ROCs) were plotted using the R package "pROC" (version 1.15.0), AUC values, sensitivity and specificity were analyzed, and the diagnostic efficacy of the markers alone or in combination was judged.

When the diagnostic efficacy of the individual index is judged, the expression level of the gene (log2 expression level) is directly used for analysis, and the level corresponding to the point with the highest john index is selected as the cutoff value.

When the diagnosis efficiency of the index combination is judged, firstly, the genes are subjected to logistic regression, wherein independent variables are corresponding indexes, dependent variables are diseased conditions, the probability of whether each individual suffers from cancer can be calculated through a fitted regression curve, and different probability division threshold values are determined to obtain a prediction result. The optimal probability partition threshold is determined by the point at which the john index is maximum. And according to the determined probability partition threshold, the sensitivity and specificity of each joint scheme in the training group and the verification group can be calculated.

6. Lasso cox regression analysis

And carrying out Lasso cox regression analysis to construct a LASSO regression model. TCGA data as training set and GEO data as test set. The Lasso cox regression model coefficient (X1-4) and the linear combination of mRNA expression level are used for constructing the prognostic gene signature.

riskScore＝(X1*expression level of mRNA1)+(X2*expression level of mRNA2)+(X3*expression level of mRNA3)+(X4*expression level of mRNA4)。

According to the median of the riskScore, lung adenocarcinoma patients are analyzed into two groups of high-risk (high-score) and low-risk (low-score) groups, and the difference of the two groups in survival time is compared through KM survival analysis, so that the prediction value of the gene signature in the aspect of prognosis is evaluated. To validate the predictive value of the gene signature, a risk score was calculated in the GEO data using the same formula.

7. Results

1) Differential expression of genes

The differential expression of EGLN3, MAL, MFAP5, TMPRSS11E in TCGA and GEO databases is shown in FIGS. 1-4, and the differences are statistically significant.

2) ROC curve analysis

Diagnostic potency data for EGLN3, MAL, MFAP5, TMPRSS11E and combinations are seen in table 1, table 2 and figures 5-9.

TABLE 1 TCGA diagnostic Performance analysis

Index (I)	AUC	Sensitivity of the composition	Specificity of
				EGLN3	0.868	0.780	0.915
MFAP5	0.645	0.416	0.864
				MAL	0.871	0.826	0.847
TMPRSS11E	0.891	0.742	1.000
				EGLN3+MAL+MFAP5+TMPRSS11E	0.986	0.928	1.000

TABLE 2 GEO diagnostic efficacy analysis

Index (I)	AUC	Sensitivity of the composition	Specificity of
				EGLN3	0.820	0.646	1.000
MFAP5	0.722	0.752	0.700
				MAL	0.890	0.810	0.950
TMPRSS11E	0.858	0.699	0.900
				EGLN3+MAL+MFAP5+TMPRSS11E	0.978	0.907	1.000

3) Prognostic assay

TCGA data is used as a training set, and a Lasso cox regression model coefficient and the linear combination of mRNA expression level are used for constructing a prognostic gene signature.

riskScore ═ mRNA expression level (0.089433 × EGLN3 gene) + (0.031948 × MFAP5 gene mRNA expression level) + (0.17524 × MAL gene mRNA expression level) + (0.035276 × TMPRSS11E gene mRNA expression level).

The lung adenocarcinoma patients are analyzed into two groups of high-risk and low-risk according to the median of the riskScore, and the difference of the survival time of the two groups is compared through KM survival analysis, so that the overall survival rate of the patients in the high-risk group is obviously lower than that of the patients in the low-risk group. The same formula is used to calculate the risk score in the GEO data. Consistent with the results of the TCGA cohort, the overall survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (fig. 10 and 11).

In conclusion, gene signatures based on the four genes of the present invention are able to predict the overall survival rate of lung adenocarcinoma.

The preferred embodiments of the present application have been described in detail with reference to the accompanying drawings, however, the present application is not limited to the details of the above embodiments, and various simple modifications can be made to the technical solution of the present application within the technical idea of the present application, and these simple modifications are all within the protection scope of the present application.

It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described in the present application.

In addition, any combination of the various embodiments of the present application is also possible, and the same should be considered as disclosed in the present application as long as it does not depart from the idea of the present application.

Claims

1. A system for diagnosing lung cancer or predicting the prognosis of lung cancer, comprising an input means for inputting an expression level of a molecular marker, an output means for outputting a result of diagnosis of lung cancer or a result of prognosis of lung cancer; wherein the molecular marker is EGLN3, MAL, MFAP5, TMPRSS 11E;

preferably, the system further comprises a computing device comprising a memory and a processor; the memory having stored therein a computer program, the processor being configured to execute the computer program stored in the memory;

preferably, the system further comprises a means for detecting the expression level of the molecular marker; preferably, the detection device comprises a real-time quantitative PCR instrument, a real-time quantitative PCR primer, a high-throughput sequencing platform, a detection chip and a chip signal reader;

preferably, the chip comprises a probe for detecting the expression level of the marker; preferably, the chip also comprises an internal reference probe, wherein the internal reference probe is a probe for detecting the expression level of GAPDH or beta-Actin;

preferably, the real-time quantitative PCR primer comprises a real-time quantitative PCR primer for detecting the expression amount of the molecular marker; preferably, the real-time quantitative PCR primer further comprises an internal reference primer, and the internal reference primer is a real-time quantitative PCR primer for detecting GAPDH or beta-Actin.

2. Use of a reagent for detecting molecular markers for the preparation of a product for diagnosing lung cancer or predicting the prognosis of lung cancer, wherein the molecular markers are EGLN3, MAL, MFAP5, TMPRSS 11E.

3. The use according to claim 2, wherein the agent comprises a nucleic acid capable of binding to the molecular marker; the nucleic acid is capable of detecting the expression level of the molecular marker.

4. The kit of claim 3, wherein said nucleic acid comprises primers used in real-time quantitative PCR that specifically amplify said molecular markers.

5. The kit of claim 3, wherein said nucleic acid comprises a probe for said molecular marker used in a gene chip.

6. Use according to claim 2, characterized in that the detection of the molecular marker is carried out by:

1) obtaining a subject sample;

2) determining the expression level of the molecular marker in the sample.

7. A product for diagnosing lung cancer or predicting the prognosis of lung cancer, which comprises a reagent for detecting the expression level of molecular markers EGLN3, MAL, MFAP5, TMPRSS 11E.

8. The product of claim 7, wherein the product comprises a chip, a kit, a dipstick, or a high throughput sequencing platform.

9. A molecular marker panel for diagnosing lung cancer or predicting the prognosis of lung cancer, wherein the molecular marker panel comprises EGLN3, MAL, MFAP5, TMPRSS 11E.

10. A reagent for detecting the expression level of the combination of molecular markers according to claim 9; preferably, the agent comprises a nucleic acid capable of binding to the molecular marker; the nucleic acid is capable of detecting the expression level of the molecular marker; preferably, the nucleic acid comprises primers used in real-time quantitative PCR for specifically amplifying the molecular markers, and probes for the molecular markers used in gene chips.