CN113444804B

CN113444804B - Cervical cancer prognosis related gene and application thereof in preparation of cervical cancer prognosis prediction and diagnosis product

Info

Publication number: CN113444804B
Application number: CN202110796866.8A
Authority: CN
Inventors: 杨慧; 邱惠; 谢丛华; 张金方; 周云峰
Original assignee: Zhongnan Hospital of Wuhan University
Current assignee: Zhongnan Hospital of Wuhan University
Priority date: 2021-07-14
Filing date: 2021-07-14
Publication date: 2022-03-15
Anticipated expiration: 2041-07-14
Also published as: CN113444804A

Abstract

The invention discloses a cervical cancer prognosis related gene and application thereof in preparing a cervical cancer prognosis prediction diagnosis product, wherein the cervical cancer prognosis related gene comprises 9 special differential expression genes FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A 7. The invention develops the 9 genes and establishes a prognosis scoring system based on the expression level of the group of genes; the predictive scores of this system can accurately distinguish different clinical prognoses for cervical cancer patients. Multivariate Cox regression analysis shows that the discrimination capability of the multivariate Cox regression analysis on the overall survival rate is remarkably superior to that of gene scoring systems reported in other researches at present. The invention can be used for assisting in predicting the response of a cervical cancer patient to treatment intervention, judging whether the patient benefits from chemotherapy, radiotherapy, targeting, immunization or other treatments, guiding the selection of a treatment scheme and achieving the purpose of individualized medical treatment.

Description

Cervical cancer prognosis related gene and application thereof in preparation of cervical cancer prognosis prediction and diagnosis product

Technical Field

The embodiment of the invention relates to the technical field of biology, in particular to a gene related to cervical cancer prognosis and application thereof in preparing a product for predicting and diagnosing cervical cancer prognosis.

Background

The incidence and mortality of cervical cancer are in the fourth place of female malignant tumors, and the 2020 data of the world health organization shows that about 60.4 ten thousand new cervical cancer cases and 34.2 ten thousand death cases are found each year worldwide. The main etiology of cervical cancer is continuous infection of high-risk HPV virus, and 90% of cervical cancer is pathologically classified into squamous carcinoma.

At present, for early cervical cancer with tumors limited to cervix, the guidelines at home and abroad consistently recommend surgical treatment as the main part, and whether to perform auxiliary radiotherapy and chemotherapy is determined according to the condition of risk factors after surgery; for middle and advanced cervical cancer, radical synchronous radiotherapy and chemotherapy is the main treatment mode. However, although cervical cancer has an average 5-year survival rate of about 45% following standard treatment; but the 5-year survival rate of recurrent metastatic cervical cancer after failure of first-line therapy is only 15%. In order to improve the survival rate of cervical cancer, a plurality of treatment modes such as new adjuvant chemotherapy, consolidation chemotherapy, targeted therapy, immunotherapy and the like are explored endlessly in the cervical cancer for years.

However, due to the heterogeneity of patients' own tumors, even if the pathotype, staging or even treatment received is the same for different cervical cancer patients, their survival and response rate to drugs may vary. This heterogeneity of tumors exists between patients and between individual tumor cells in the same type of tumor. The different genetic backgrounds, intrinsic factors and environmental factors together contribute to the inter-patient tumor heterogeneity. With the wide popularization and application of high-throughput technology and single cell sequencing technology, tumor heterogeneity is a research hotspot in the tumor field at present.

The goal of tumor precision medicine is to accurately stratify tumor patients through a unique genetic background, thereby providing the most effective treatment regimen. Although the cervical cancer is the only tumor with definite disease cause at present, and the early treatment prognosis is good; however, the prognosis is very poor if tumor recurrence and metastasis occur due to the high heterogeneity of the patient's own tumor. Thus, despite the use of multi-modal prognostic assessment and treatment options based on FIGO staging, pathotyping, etc., there is still a lack of effective assessment and prediction systems in terms of patient outcome and multi-modal treatment options, and management and treatment of cervical cancer remains extremely challenging. In recent years, based on the development of high-throughput omics technology, there are a number of biomarkers for the prediction of prognosis and treatment responsiveness of tumor patients.

The prognosis markers which are successfully applied to clinic at present and commercialized are two breast cancer tumor gene marker products, can be classified according to different expression conditions of related molecules (ER, HER2 and the like) and pertinently perform operation and auxiliary treatment on different types of breast cancer patients, and can also be used for detecting the prognosis conditions of relapse, metastasis and the like of lymph node negative breast cancer by polygene expression through methods of an Oncotype DX 21-gene (American Genomic Health company) and a MammaPrint 70-gene (Norway Agendia company) and evaluating and guiding treatment. Both tests are now approved by the U.S. FDA, wherein the Oncotyte DX 21-gene has formally become the breast cancer gene detection scheme recommended by the U.S. national comprehensive cancer network in 2015. Genomatic Health also developed an Oncotype DX 7-gene colon cancer polygene test that predicts the risk of recurrence in stage II and stage III a/B colon cancer patients, and physicians and patients can make more informed decisions as to whether chemotherapy is needed post-operatively (stage II) or whether oxaliplatin should be added to the treatment regimen post-operatively (stage III).

However, cervical cancer has apparently lagged relatively in this regard. Currently, no gene detection and scoring system applied to clinical and commercialized cervical cancer prognosis exists worldwide to guide the selection of cervical cancer treatment schemes. In recent years, a plurality of studies analyze cervical Cancer RNA expression profile data sets in international general GEO databases and tcga (the Cancer genoatlas) databases, wherein most of the studies search for key genes from aspects of immunity, post-transcriptional modification or radiotherapy curative effect and the like in cervical Cancer patient tissues, and a group of genes having a predictive effect on cervical Cancer prognosis is not systematically explored, so that a group of gene detection and scoring systems capable of evaluating cervical Cancer prognosis and possibly guiding the selection of treatment schemes thereof is urgently needed to be developed.

Disclosure of Invention

The embodiment of the invention aims to provide a gene related to cervical cancer prognosis and application thereof in preparing a product for predicting and diagnosing cervical cancer prognosis, which can be used for evaluating the cervical cancer prognosis and possibly guiding the selection of a treatment scheme.

In order to achieve the purpose, the invention adopts the following technical scheme:

in a first aspect of the embodiments of the present invention, a set of genes related to prognosis of cervical cancer is provided, wherein the genes related to prognosis of cervical cancer include 9 specific differentially expressed genes FAM20C, SLC25a28, RFC5, RNASEH2A, SLC39a14, APOBEC3B, ERG, TFRC, and MS4a 7.

In a second aspect of the embodiments of the present invention, there is provided a product for detecting a gene associated with prognosis of cervical cancer, comprising a product for detecting mRNA expression levels of the 9 specific differentially expressed genes of claim 1 in a cervical cancer tissue.

Further, the detection product comprises: probes and primers for cervical cancer prognosis-related genes;

the probes can be respectively combined with the 9 special differentially expressed genes through molecular hybridization to generate hybridization signals, and the primers can be used for amplifying the 9 special differentially expressed genes through a PCR-based technology.

A detection kit for the gene related to the cervical cancer prognosis can be further designed, the kit comprises the probe and the primer, and further comprises:

a positive control;

a negative control;

specific primers and probes of the internal standard gene; the internal standard gene comprises one of GAPDH, ACTB and GUBTFRC.

The kit of the present invention may further comprise a means and/or a reagent known in the art for PCR reaction, RNA isolation of a sample, and cDNA synthesis, in addition to the primer or gene probe for the 9-gene marker. The kit of the present invention may further contain, as necessary, a tube or a microplate for mixing the components, instructions describing the method of use, and the like.

In the third aspect of the embodiments of the present invention, an application of the cervical cancer prognosis related gene and the detection product of the cervical cancer prognosis related gene in establishing a prediction system for predicting the risk of cervical cancer prognosis is provided.

In a fourth aspect of the embodiments of the present invention, there is provided a prediction system for predicting cervical cancer prognosis risk, wherein the calculation formula of the prediction system is as follows:

wherein the content of the first and second substances,

the genes i comprise genes FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A 7;

the expression level of the gene i is the mRNA expression level of a gene related to the prognosis of cervical cancer;

the coefficient of the gene i is obtained by carrying out COX multifactor regression analysis on the mRNA expression level of the gene related to cervical cancer prognosis.

The measured coefficients of gene i will vary depending on the sample, the level of mRNA expression obtained by the different detection means.

As a specific embodiment, the coefficients of the gene FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A7 in the coefficients of the gene i in the examples of the present invention are 0.71488, -0.48233, -0.34997, -0.66077, -0.51144, -0.39908, 0.48586 and 0.30260, respectively.

Further, the method for measuring the mRNA expression level of the gene relevant to the cervical cancer prognosis comprises any one or the combination of at least two of PCR, gene chip, second-generation high-throughput sequencing, Panomics or Nanostring metagenomic sequencing.

In a fifth aspect of the embodiments of the present invention, there is provided an application of the prediction system in preparing a product for predicting cervical cancer risk, wherein the input variable of the system is the mRNA expression level of the gene associated with cervical cancer prognosis, i.e. a prediction score of cervical cancer risk is obtained.

In a sixth aspect of the embodiments of the present invention, there is provided a cervical cancer prognosis risk prediction system, including:

a processor and a memory coupled to the processor, the memory storing instructions that when executed by the processor use the steps of:

and inputting the mRNA expression level of the gene related to the cervical cancer prognosis into the prediction system to obtain a predictive score of the cervical cancer prognosis risk.

In a seventh aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, uses the steps of:

inputting the input mRNA expression level of the cervical cancer prognosis related gene into the prediction system, and obtaining a cervical cancer prognosis risk prediction score through calculation.

In an eighth aspect of the embodiments of the present invention, there is provided a cervical cancer prognosis prediction diagnosis product, including:

mRNA expression level measurement products of genes related to prognosis of cervical cancer;

and said prediction system or said cervical cancer prognosis risk prediction system or said computer readable storage medium.

One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:

the cervical cancer prognosis related gene and the application thereof in preparing cervical cancer prognosis prediction and diagnosis products provided by the embodiment of the invention have the advantages that the discrimination capability of the 9-gene prognosis scoring system developed by the invention on the total survival rate (OS) is obviously superior to that of other gene scoring systems reported in research through multivariate Cox regression analysis. The system can be used for assisting in predicting the response of a cervical cancer patient to treatment intervention, judging whether the patient benefits from chemotherapy, radiotherapy, targeting, immunization or other treatments, selecting a treatment scheme, avoiding over-treatment and achieving the purpose of individualized treatment.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a GEO data set used in the present invention to screen out genes differentially expressed in normal cervical epithelial and tumor tissues;

FIG. 2A screening of differentially expressed genes for genes associated with OS; FIGS. 2B-E examples of Kaplan-Meier survival curves for representative genes in the cervical cancer gene signature; the p-value is obtained by comparing the differential assays (log-rank test) between the two groups;

FIG. 3A is a screening process of a cervical cancer 9 gene scoring system; FIG. 3B shows genes that appear more frequently than 31 times in the screen; FIG. 3C is a risk assessment of the screened 9 genes in cervical cancer; FIG. 3D is a Kaplan-Meier survival curve for the 9-gene combination; FIG. 3E is a time-dependent ROC curve for the 9-gene combination; FIG. 3F is a prognostic prediction calibration curve for the 9-gene combination;

FIG. 4 is a COX multifactorial regression of the 9-gene combination in the TCGA dataset;

FIG. 5 is a comparison of the efficacy of the 9-gene combination of the present invention in assessing the prognosis of a patient with cervical cancer in combination with other 5 sets of gene combinations published in other studies;

FIG. 6 is AKaplan-Meier survival curve of the 9-gene combination scoring system of the present invention in the validation dataset GSE 44001; b COX multifactor analysis; c, collinear chart; d, correcting the curve;

FIG. 7 is a graph showing the relationship between the 9-gene combination score of the present invention and the expression of PD-L1; a9-difference of PD-L1 expression level in three groups of 'good', 'middle' and 'poor' of gene prognosis scoring system; correlation of B9-Gene prognostic score with expression level of PD-L1.

Detailed Description

The embodiments of the present invention will be described in detail below with reference to specific embodiments and examples, and the advantages and various effects of the embodiments of the present invention will be more clearly apparent therefrom. It will be understood by those skilled in the art that the present embodiments and examples are illustrative of the present invention and are not to be construed as limiting the present invention.

Throughout the specification, unless otherwise specifically noted, terms used herein should be understood as having meanings as commonly used in the art. Accordingly, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which embodiments of the invention belong. If there is a conflict, the present specification will control.

The technical scheme of the invention has the following general idea:

the method screens 2 microarray expression data sets based on a GPL570 platform by searching a GEO database of the national center for Biotechnology information (GIS) of the United states, and then adopts a multi-step bioinformatics method for analysis.

First, 1179 genes whose expression is significantly different between normal cervical tissue and cervical cancer tissue were confirmed.

By using clinical information of a cervical Cancer patient in a TCGA (the Cancer genome atlas) database and expression conditions of related genes, through Survival analysis, 308 genes screened out have significant correlation with the Overall Survival (OS);

a group of 9 gene markers related to the cervical cancer prognosis is determined by adopting a typical discriminant analysis method, and a prognosis scoring system is established on the basis and the evaluation value and accuracy of the prognosis scoring system are verified.

From this TCGARNA-seq data, we also further validated the prognostic significance of 9 genes; meanwhile, in another GEO data set, the significance of the 9-gene prognosis scoring system is also verified. In addition, researches show that the prediction effect of the 9-gene is obviously superior to that of gene scoring systems reported in other researches at present.

The terms "gene probe" and "primer" as used herein refer to an oligonucleotide, preferably a single-stranded deoxyribonucleotide, including natural (naturally occuring) dNMP (dAMP, dGMP, dCMP and dTMP), an anamorphic nucleotide or a non-natural nucleotide, and may further comprise a ribonucleotide.

The gene probes and primers utilized in the present invention comprise hybridizing nucleotide sequences complementary to the target location of the target nucleic acid. The term "complementary" means that the primer or probe is sufficiently complementary to selectively hybridize to a target nucleic acid sequence under hybridization conditions, and has the meaning of including both substantial complementarity (substentiality complementarity) and perfect complementarity (perfect complementarity), preferably being perfect complementarity. The term "substantially complementary sequence" as used herein includes not only completely identical sequences but also sequences that are partially different from the target sequence to be compared and that can function as primers for the specific target sequence. The sequences of the gene probe and the primer do not need to have a sequence completely complementary to a part of the sequence of the template, and may have sufficient complementarity within a range that can hybridize with the template and exert their inherent effects. Therefore, the gene probe and the primer of the present invention do not need to have a sequence completely complementary to the nucleotide sequence as a template, and may have sufficient complementarity within a range that can hybridize to the template and exert their inherent effects. The design of PRIMERs and gene probes is well within the skill of those in the art, and can be accomplished, for example, using PRIMER design programs (e.g., PRIMER3 program).

The determination of the mRNA expression level in the present invention can be performed using methods well known in the art, including but not limited to quantitative PCR, gene chip, next generation high throughput sequencing, Panomics or Nanostring techniques.

In the present invention, the sample is tumor tissue of a cervical cancer patient, including but not limited to fresh biopsy tissue, post-operative tissue, fixed tissue and paraffin-embedded tissue. The cervical cancer prognosis prediction diagnosis label can be detected by different detection technology platforms, including but not limited to quantitative PCR, gene chip, second-generation high-throughput sequencing, Panomics and Nanostring technologies, and corresponding gene primers (quantitative PCR) and probes (gene chip, second-generation high-throughput sequencing, Panomics and Nanostring technologies) are designed aiming at different technology platforms. Preferably, the expression level of the target gene is detected, and more preferably, the expression level of the target gene is quantitatively detected. In order to detect the expression level, RNA must be isolated from a sample tissue, and a method for isolating RNA in a sample known in the art can be used. The calculation method of the prediction score is defined as above, but the absolute value of the prediction score and the score demarcation can be different according to different technical platforms and need to be determined respectively.

Unless otherwise specifically stated, various raw materials, reagents, instruments, equipment and the like used in the examples of the present invention are commercially available or can be prepared by an existing method.

The cervical cancer prognosis related gene and the application thereof in preparing a cervical cancer prognosis prediction diagnosis product will be described in detail below by combining examples, comparative examples and experimental data.

Example 1 Gene involved in prognosis of cervical cancer and screening method thereof

Screening of genes related to cervical cancer prognosis comprises the following specific steps:

step 1, screening genes with different expression levels in a sample:

2 data sets (GSE6791, GSE63514) comprising normal cervical epithelial tissue and cervical cancer tissue specimens were selected from the GEO database, totaling 32 normal cervical tissues and 48 cervical cancer samples. Comparing the gene expression between normal cervical tissue and cervical cancer tissue, determining 2 genes with significant differential expression in data set, obtaining 998 differential genes with up-regulated expression in tumor tissue and 181 differential genes with down-regulated expression in tumor tissue (| log2Fold Change (FC) | >1, and the corrected p value is less than 0.01);

the GEO data set applied in the invention screens out the genes which are differentially expressed in normal epithelium and tumor tissues of the cervix, and the result is shown in figure 1.

And 2, further evaluating the influence of the differential expression of the 1179 genes on the cervical cancer prognosis by utilizing the 248 clinical information of the cervical cancer squamous carcinoma patients in the TCGA database and the expression conditions of the related genes and adopting R language survival and surviver packages:

first, the optimal cut-off values of the 1179 gene expressions are respectively searched, the gene expressions are divided into two groups of high expression and low expression according to the optimal cut-off values of the gene expressions, and the influence of the high expression level or the low expression level of the genes on the overall survival period (OS) is evaluated by using Cox regression analysis, a Kaplan-Meier survival curve and a logarithmic rank test.

FIG. 2A screening of differentially expressed genes for genes associated with OS; FIGS. 2B-E examples of Kaplan-Meier survival curves for representative genes in the cervical cancer gene signature; the p-value is obtained by comparing the differential assays (log-ranktest) between the two groups;

as can be seen from fig. 2, a significant correlation was found between the expression level of 308 of the 1179 genes and the overall survival of cervical cancer patients (corrected p-value < 0.05); among them, high expression of 121 genes was a risk factor for prognosis, and high expression of 187 genes was a protective factor for prognosis (FIG. 2A). FIGS. 2B-E show the effect of four representative gene expression levels on patient prognostic survival. The cervical cancer prognosis related gene marker will be screened from these 308 genes. Finally, these genes were ranked according to p-value and HR generated by the COX regression one-way analysis above (see table 1);

TABLE 1

And 3, screening characteristic genes for cervical cancer prognosis:

by the method of leave ten out, gene expressions of 238 patients are randomly extracted into a data set in 248 patient gene expression data sets at a time, 308 differentially expressed genes are subjected to forward stepwise Cox regression analysis in each data set, a model is automatically incorporated into genes which have significant influence on survival prognosis in 308 genes until 100 gene models which have significant influence on survival prognosis are generated, and finally, the occurrence frequency of the genes in all 100 groups of gene models is counted.

FIG. 3B shows the frequency distribution diagram of 39 genes with frequency of 10 or more in each gene in 100 gene models, the frequencies are arranged from high to low, and it can be seen from FIG. 3B that the frequency of the first 15 genes is 38 or more, the frequency of the 16 th gene is 31, and a truncation occurs, so that 15 genes with frequency of 38 or more are selected, and in the gene expression data set of 248 cervical squamous cell carcinoma patients, the forward stepwise COX regression analysis is performed again, and finally, 9 genes are automatically included in the model as genes having significant influence on survival prognosis, thereby constituting the 9-gene prognosis gene profile of the invention.

And secondly, screening to obtain the genes related to the prognosis of the cervical cancer, wherein the genes related to the prognosis of the cervical cancer comprise 9 special differential expression genes FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A 7.

TABLE 2

Example 2 cervical cancer prognosis risk prediction System of cervical cancer prognosis-related Gene and method for establishing the same

First, based on the results of example 1, the cervical cancer 9-gene prognosis scoring system was developed in example 2 of the present invention. We applied stepwise canonical discriminant analysis (canonical diagnostic analysis) to identify gene markers that could identify the prognosis of patients with 100% accuracy, and finally determined a set of scoring systems consisting of 9 specific cervical cancer prognostic genes, yielding 100% prognostic prediction accuracy.

These genes include: FAM20C, SLC25a28, RFC5, RNASEH2A, SLC39a14, APOBEC3B, ERG, TFRC and MS4a 7. The COX multifactorial regression model of the 9-gene combination in the TCGA dataset is shown in FIG. 4. Each gene is a sequence of each gene known in the art or a sequence of a synonym (synonym) of each gene, preferably a sequence of each human-derived gene, more preferably FAM20C is a sequence described in Genbank accession No. 56975, SLC25a28 is a sequence described in Genbank accession No. 81894, RFC5 is a sequence described in Genbank accession No. 5985, RNASEH2A is a sequence described in Genbank accession No. 10535, SLC39a14 is a sequence described in Genbank accession No. 23516, APOBEC3B is a sequence described in Genbank accession No. 9582, ERG is a sequence described in Genbank accession No. 2078, TFRC is a sequence described in Genbank accession No. 7037, and MS4a7 is a sequence described in Genbank accession No. 58475. Synonyms for each gene and their sequences can be searched by Genbank or Swissprot.

Second, prediction system for prognosis risk of cervical cancer

1. The cervical cancer prognosis scoring system described above uses the prediction score to calculate the probability of survival of the patient. The scoring system is defined as a linear combination of gene expression levels based on the Cox risk function coefficients. The calculation formula of the cervical cancer prognosis score is as follows:

wherein, the coefficient of the gene i in the formula is shown in the table 3, and the expression level of the gene i is the mRNA expression level of the gene related to the cervical cancer prognosis;

TABLE 3 typical discriminant function coefficients

2. The prognostic score for each patient can be used to assess their overall survival and risk of death.

Our defined prediction score calculation method is as follows:

(1) the samples are ranked according to the prognosis scores of the samples, the cut-off values of the best three-part method of the prognosis scores are found out through an X-tile method according to the scores of the samples, and the patients are divided into three groups of (good "," middle "and" poor ") according to the cut-off values.

The absolute value of the prediction score and the score demarcation may be different for different technical platforms and need to be determined separately.

(2) Three groups of 248 patients with cervical squamous cell carcinoma were subjected to Kaplan-Meier analysis and Log-Rank test; COX regression analysis was performed simultaneously, comparing the "medium" and "poor" groups with the "good" group, respectively, calculating Hazard Ratios (HR), determining differences in Overall Survival (OS) of the three groups of patients, and performing the analysis.

Specifically, the method comprises the following steps:

in the embodiment of the invention, 248 patients with cervical squamous cell carcinoma are ranked according to the prognosis scores, the cut-off values of the optimal three-component method of the prognosis scores are found out by the X-tile method according to the scores, and the patients are divided into three groups of (good "," medium "and" poor "prognosis) according to the upper and lower cut-off values.

Three groups of 248 patients with cervical squamous cell carcinoma were subjected to Kaplan-Meier analysis and Log-Rank test; performing COX regression analysis simultaneously, comparing the "middle" and "poor" groups with the "good" group respectively, calculating Hazard Ratios (HR), and determining the difference of Overall Survival (OS) of three groups of patients;

FIG. 3D is a Kaplan-Meier survival curve for the 9-gene in 248 patients.

FIG. 4 forest chart shows that inclusion of tumor T stage, FIGO stage, age and whether radiotherapy was used for COX multifactorial analysis, the risk ratios for the "poor" and "medium" groups of patients of the 9-gene prognosis scoring system of the invention compared to the "good" group of patients were 8.11 (95% CI 3.12-21.81, p <0.001) and 4.29 (95% CI 1.71-10.76, p ═ 0.002), respectively.

In addition, the patients were scored according to the scoring system and then fitted with 2-year, 3-year and 5-year time-dependent ROC curves and calibration curves, as shown in fig. 3E, the areas under the curves of 2-year, 3-year and 5-year were 0.82, 0.72 and 0.71, respectively, indicating that the scoring system had good diagnostic efficacy; the 2-year, 3-year, and 5-year calibration curves all almost coincided with the standard curve as shown in FIG. 3F, indicating that the scoring system is better able to predict prognosis. These results strongly demonstrate the ability of this 9-gene marker and the prognostic scoring system to discriminate between patients with different prognoses, and to discriminate well between patients with good or poor prognosis.

Thirdly, comparing with the cervical cancer gene marker of published research

As mentioned above, there are 5 studies reporting cervical cancer gene markers. We compared the 9-gene scoring system with 5 reported gene scoring systems. In the gene expression data set of TCGA248 cervical carcinoma patients, the multivariate COX regression analysis is respectively carried out on 5 gene scoring systems of the research, the corresponding coefficient of each gene of the research is respectively calculated, and the prognosis scores of 248 cervical carcinoma patients are calculated by using the same formula.

The cutoff values of the best triage for the prognosis scores were found for each study by X-tile, and the patients were classified into (prognosis) "good", "medium", and "poor" groups according to the upper and lower cutoff values. The difference in Overall Survival (OS) was determined for three groups of patients from Kaplan-Meier analysis and Log-Rank test for each study (FIG. 5).

The COX multifactor assay results showed that inclusion of tumor T stage, fix stage, age, whether radiotherapy was administered and other 5 studies were covariates, suggesting that the risk ratios for the "poor" versus "good" patients of the 9-gene prognosis scoring system of the invention were 11.18 (95% CI 3.31-37.9, p <0.001) and 5.47 (95% CI 1.79-16.76, p ═ 0.003), respectively.

In the other 5 studies, the risk ratio between patients in the "poor" and "medium" groups of the 6-gene scoring system was statistically significant compared to patients in the "good" group ("poor" group vs "good", HR 7.44, 95% CI 1.80-30.74, p 0.006; "medium" group vs "good", HR 3.95, 95% CI 1.08-14.40, p 0.038); 4-Gene scoring System the risk ratio of patients in the "poor" versus "good" group was statistically significant ("poor" vs "good" group, HR 6.06, 95% CI 1.92-19.16, p 0.002), and none of the scoring systems of the other 3 studies was statistically significant.

The median (mean) HR was about 1.5-fold and 1.84-fold higher for the "poor" versus "good" patients of the 9-gene scoring system of the present invention, respectively (see fig. 5). These results indicate that the ability of the 9-gene markers of the present invention to differentiate cervical cancer patients with different prognosis (overall survival) is significantly better than the results reported in the other 5 studies. We first screened the tumor-associated genes against the differences in gene expression between tumor and normal tissues, while other studies were based only on gene expression in tumor tissues or only on gene expression associated with immune, post-transcriptional modification or radiotherapy treatment.

Example 3 cervical cancer prognosis Risk prediction System

The embodiment of the invention provides a cervical cancer prognosis risk prediction system, which comprises:

the prediction system described in example 2 was inputted with the input mRNA expression level of the gene associated with prognosis of cervical cancer, and a predictive risk score for prognosis of cervical cancer was obtained.

Embodiment 4 computer-readable storage Medium

Embodiments of the present invention provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the embodiment 2 method and/or the embodiment 3 method.

Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the method operations described above, and may also perform related operations in the method provided by any embodiment of the present invention.

From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes instructions for enabling an electronic device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.

It should be noted that, in the foregoing embodiment, each included unit and each included module are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.

Application example 1 prediction of prognostic effect in clinical cervical cancer patients

Tumor tissues of clinically accepted cervical cancer patients, which may include fresh biopsy tissue, post-operative tissue, fixed tissue and paraffin-embedded tissue, are collected and RNA is extracted. Then the kit developed by the invention and a corresponding instrument are used for quantitatively detecting the expression levels of 9 genes of a prognosis scoring system. The expression level of the 9 gene is input into a prognosis score formula established by the invention:

after calculating the patient's predictive score, the physician predicts the patient's prognosis, such as 5-year survival, based on the score. We have now established a model by retrospective studies, successfully validated in the GSE44001 dataset (table of fig. 6). Patients were scored by calculating the prognosis score for all patients in the data set and using X-tile to stratify patients according to their scores. Significant differences between the "good" and "poor" prognosis patient cohorts were analyzed using Kaplan-Meier. We found that patients with high prognostic scores had significantly shorter DFS than low scoring patients (p <0.05) (fig. 4). The 9 gene prognosis scoring system is proved to be capable of repeatedly predicting the prognosis of the cervical cancer patient, and is probably equally effective in the aspects of prediction of total survival rate and DFS prediction. We also planned to conduct prospective studies to further refine the scoring system.

Application example 2, prediction of whether cervical cancer patients with only 1 clinical intermediate risk factor need auxiliary radiotherapy and chemotherapy after operation

And predicting whether the cervical cancer patients with only 1 intermediate risk factor need auxiliary radiotherapy and chemotherapy after the operation. If 1 high-risk factor (lymph node positive, parauterine infiltration and stump positive) or 2 medium-risk factors (vascular cancer embolus, invasion of muscle wall external 1/2 and tumor larger than 4cm) exist in early cervical cancer patients after operation, the guidelines recommend postoperative adjuvant radiotherapy and chemotherapy. However, for patients with 1 intermediate risk factor, the guidelines do not recommend postoperative adjuvant chemotherapy. However, some of these patients are prone to recurrent metastases. Because not all patients with 1 intermediate risk factor after operation can benefit from the postoperative auxiliary radiotherapy and chemotherapy, in order to reduce ineffective or excessive treatment and reduce medical cost and treat partial patients with 1 intermediate risk factor after operation in a targeted manner, the invention predicts whether the cervical cancer patients with only 1 intermediate risk factor need the auxiliary radiotherapy and chemotherapy after operation by implementing the following scheme: tumor tissues, which may include fresh biopsy tissue, post-operative tissue, fixed tissue and paraffin-embedded tissue, are collected and RNA is extracted from clinically accepted cervical cancer patients. Then, the kit developed by the invention and a corresponding instrument are used for quantitatively detecting the expression level of the 9 gene of the prognostic scoring system. The expression level of the 9 gene is input into a prognosis score formula established by the invention:

after calculating the patient's predictive score, the physician considers whether the patient should receive postoperative adjuvant chemotherapy based on the score. Patients with poor prognosis are indicated by the prediction score, and doctors can be recommended to carry out postoperative adjuvant chemotherapy on the patients.

Application example 3 prediction of response of clinical cervical cancer patients to immunotherapy

The immunotherapy of cervical cancer can obviously prolong the life cycle of patients, and the curative effect is improved by combining the traditional chemotherapy drugs or anti-angiogenesis targeted drugs. Most of the target points of the current marketed immunotherapeutic drugs are PD-1 or PD-L1, and the curative effects of the drugs are obviously related to the tumor tissue immune microenvironment score and the expression of PD-L1.

In order to reduce ineffective or excessive application of immunotherapy drugs and reduce medical costs, the present invention is implemented to predict the response of clinical cervical cancer patients to the above-mentioned immunotherapy drugs; tumor tissues, which may include fresh biopsy tissue, post-operative tissue, fixed tissue and paraffin-embedded tissue, are collected and RNA is extracted from clinically accepted cervical cancer patients. Then, the kit developed by the invention and a corresponding instrument are used for quantitatively detecting the expression level of the 9 gene of the prognostic scoring system. The expression level of the 9 gene is input into a prognosis score formula established by the invention:

after calculating the patient's predictive score, the physician considers whether the patient should receive the corresponding immunotherapy based on the score. We currently modeled TCGA248 patients with cervical squamous carcinoma by calculating the prognostic scores of all patients in the data set and using X-tile to stratify the patients according to their scores. Analyzing the significant differences in PD-L1 expression levels between the "good", "medium", and "poor" prognosis patient cohorts using the Kruskal-Wallis H test method, we found that patients with the "poor" prognosis group had significantly lower PD-L1 expression levels than patients with the "medium" and "good" prognosis groups (p <0.01) (fig. 7A); meanwhile, we analyzed the correlation of PD-L1 expression level with patient prognosis score using Spearman correlation analysis method and found that PD-L1 expression level was significantly negatively correlated with patient score (p <0.001) (fig. 7B). These results indicate that the 9-gene prognosis scoring system can predict the responsiveness of a cervical cancer patient to PD-1/PD-L1 immunotherapy, so that the immunotherapy is more targeted, unnecessary ineffective and excessive medical treatment is reduced, and prospective clinical tests are planned to be implemented in the future to further perfect the prediction effect of the scoring system on the curative effect of the immunotherapy.

Finally, it should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.

It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the embodiments of the present invention and their equivalents, the embodiments of the present invention are also intended to encompass such modifications and variations.

Claims

1. The cervical cancer prognosis related gene composition is characterized by consisting of 9 special differential expression genes FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A 7.

2. A test product for the gene composition for cervical cancer prognosis, which comprises a product for measuring the mRNA expression level of the gene composition for cervical cancer prognosis according to claim 1 in a cervical cancer tissue.

3. The test product of the genetic composition for cervical cancer prognosis according to claim 2, wherein said test product comprises: and (3) probes and primers for detecting the cervical cancer prognosis related gene composition.

4. The cervical cancer prognosis related gene composition of claim 1, and the application of the detection product of the cervical cancer prognosis related gene composition of claims 2 to 3 in establishing a prediction system for predicting the cervical cancer prognosis risk and preparing a cervical cancer prognosis prediction diagnosis product.

5. A cervical cancer prognosis risk prediction system, the system comprising:

inputting the mRNA expression level of the cervical cancer prognosis-related gene composition according to claim 1 into the following calculation formula to obtain a cervical cancer prognosis risk prediction score; the calculation formula is as follows:

predictive score =

(ii) a Wherein the content of the first and second substances,

the gene i is 9 genes of genes FAM20C, SLC25A28, RFC5, RNASEH2A, SLC39A14, APOBEC3B, ERG, TFRC and MS4A 7;

the expression level of the gene i is the mRNA expression level of the cervical cancer prognosis related genome composition;

the coefficient of the gene i is obtained by carrying out COX multifactor regression analysis on the mRNA expression level of the gene composition related to cervical cancer prognosis; the method for measuring the mRNA expression level of the gene composition related to the cervical cancer prognosis comprises any one or the combination of at least two of PCR, gene chip, second-generation high-throughput sequencing, Panomics or Nanostring metagenomic sequencing.

6. A computer-readable storage medium having a computer program stored thereon, the computer program when executed by a processor using the steps of:

inputting the mRNA expression level of the gene composition for cervical cancer prognosis according to claim 1 into the following calculation formula, and calculating to obtain a predictive score of the risk of cervical cancer prognosis; the calculation formula is as follows:

predictive score =

(ii) a Wherein the content of the first and second substances,

the coefficient of the gene i is obtained by carrying out COX multifactor regression analysis on the mRNA expression level of the gene composition related to cervical cancer prognosis.

7. Use of the prediction system of claim 5 in the preparation of a product for predicting the risk of prognosis of cervical cancer.

8. A prognostic diagnostic product for cervical cancer, comprising:

the product for measuring the expression level of mRNA of the gene composition for cervical cancer prognosis according to claim 1;

and the cervical cancer prognostic risk prediction system according to claim 5 or the computer-readable storage medium according to claim 6.