KR102601997B1 - Kit for diagnosing early progression of cervical cancer - Google Patents

Abstract

The present invention relates to a biomarker for diagnosing early progression of cervical cancer and its use. More specifically, as a result of analyzing microRNA contained in exosomes isolated from the blood of cervical cancer patients receiving anticancer radiation treatment before and after treatment, Micro RNAs related to early progression (EP) of cervical cancer include micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), and micro RNA 146a. -3p(hsa-miR-146a-3p), micro RNA 33a-5p (hsa-miR-33a-5p), and micro RNA 6815-5p (hsa-miR-6815-5p) were discovered, and PCK1 (Phosphoenolpyruvate carboxykinase 1) mRNA, and the mRNA of FCGR1A (High affinity immunoglobulin gamma Fc receptor I) were confirmed to be related to each other. A biomarker composition for diagnosing early progression of cervical cancer containing the above-mentioned micro RNAs and mRNA, for diagnosing early progression of cervical cancer. Provides a composition, a kit for early diagnosis of cervical cancer, and a method of providing information for early diagnosis of cervical cancer.

Description

Kit for diagnosing early progression of cervical cancer}

The present invention relates to a biomarker for diagnosing early progression of cervical cancer and its use.

Cervical cancer is a malignant tumor that frequently occurs in women, and more than 350,000 patients worldwide die from cervical cancer every year. Cervical cancer is divided into stages 0 to 4. Stage 0 cancer is also called intraepithelial cancer, and stage 1 to 4 cancer is called invasive cervical cancer. Intraepithelial cancer develops around the age of 35 to 40, about 10 years earlier than invasive cervical cancer, and invasive cervical cancer is known to start increasing after the age of 30, peak in the 50s, and then show a sharp decline. In Korea, the prevalence level of cervical cancer is about 31 per 100,000 people and the mortality rate is about 6.8 per 100,000 people, showing no significant changes over the past 10 years. Looking at the frequency of incidence and prevalence by age, it is in the order of those in their 50s, 60s, and 40s. The incidence rate is 3 times that of the United States, 2.5 times that of Japan, and 1/3 that of Brazil. Mortality due to cervical cancer accounts for a proportion of cancer mortality. This 6% is higher than the around 2% in the United States, Japan, and Switzerland. Currently, the sexually transmitted infectious disease model is most widely accepted for the development of cervical cancer, with early onset sexual activity, multiple sexual partners, male factors, human papillomavirus (HPV) infection, and human immunodeficiency virus. Infections are known to be risk factors for cervical cancer.

The recurrence rate of cervical cancer after treatment is approximately 50% within 1 year, 25% within 2 years, and 15% within 3 years, with approximately 85% of patients experiencing recurrence within 3 years. In particular, the recurrence rate after radiation treatment for cervical cancer also exceeds 55%. Treatment for recurrent cervical cancer is determined differently depending on the type of treatment previously received and the patient's condition. In general, if surgery was the primary treatment, radiation therapy is considered in case of recurrence, and if radiation therapy was the primary treatment, surgery is considered. If both treatments are not possible, chemotherapy is performed. However, there is no standard treatment, and appropriate treatment is administered depending on the site of recurrence. In general, the treatment is aimed at alleviating symptoms rather than curing the disease.

The results of treatment for patients receiving chemotherapy and radiation therapy for cervical cancer can be predicted depending on the degree of disease progression, but sometimes it progresses much faster than we expected and leads to bad results. This phenomenon has been reported in all three major cancer treatments: surgery, chemotherapy, and radiation therapy. However, there is no clear explanation for this so far. One hypothesis that could explain this is that treated patients do not respond normally to inflammation and stress. Radiation therapy is accompanied by particularly strong inflammation and stress responses, so if it is difficult to maintain a normal acute stress response, an uncontrolled inflammatory response may lead to the support of cancer cells. Therefore, in order to clinically solve the above problems, accurate prognosis and treatment response prediction tools are needed to predict them. Although clinical results are simple, they have complex biological meaning behind them, so a more meaningful, high-level approach is needed.

Meanwhile, exosomes are extracellular vesicles of 40-150 nm that are secreted by cancer cells or other normal cells. They perform various physiological functions through signal transmission between cells and play a role in the development, metastasis, and development of cancer. It is known to be involved in the regulation of immunity, inflammation, and stress response. They contain specific non-coding/coding RNAs, and miRNAs that regulate several coding RNAs play a key role in regulating these functions. Therefore, exosome miRNAs can be considered as high-level regulators that can be considered at the present time. In particular, because blood is rich in exosomes originating from not only cancer cells but also normal cells, it is easy to understand the relationship between the physical responses of cancer patients and cancer cells, and at the same time, it is possible to examine the relationship between miRNAs and coding genes.

Korean Patent No. 10-2096498 (announced on May 27, 2020)

The present invention relates to a biomarker for diagnosing early progression of cervical cancer and its use. The present inventors collect blood samples from cervical cancer patients receiving chemotherapy before and after treatment, and extract plasma exosome RNA from these. After isolating, micro RNAs related to early progression (EP) of cervical cancer are detected through NGS analysis, and these are provided as biomarkers for diagnosing early progression of cervical cancer.

The present invention relates to a group consisting of micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), and micro RNA 146a-3p (hsa-miR-146a-3p). Provided is a biomarker composition for diagnosing early progression of cervical cancer comprising one or more selected from.

Additionally, the present invention provides micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), and micro RNA 146a-3p (hsa-miR-146a-3p). Provided is a composition for diagnosing early progression of cervical cancer, comprising an agent for measuring the expression level of one or more RNAs selected from the group consisting of.

Additionally, the present invention provides a kit for diagnosing early progression of cervical cancer, including the composition for diagnosing early progression of cervical cancer.

In addition, the present invention provides micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), or micro RNA 146a-3p (hsa-miR) in a biological sample derived from a subject. Provides a method of providing information for early diagnosis of cervical cancer, including the step of measuring the expression level of -146a-3p).

According to the present invention, as a result of analyzing microRNAs contained in exosomes isolated from the blood before and after treatment of cervical cancer patients receiving chemotherapy and radiation therapy, microRNAs associated with early progression (EP) of cervical cancer were found. micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), micro RNA 146a-3p (hsa-miR-146a-3p), micro RNA 33a- 5p (hsa-miR-33a-5p), and micro RNA 6815-5p (hsa-miR-6815-5p) were discovered, mRNA for PCK1 (Phosphoenolpyruvate carboxykinase 1), and FCGR1A (High affinity immunoglobulin gamma Fc receptor I). As it was confirmed that it is related to mRNA, the micro RNAs and mRNA can be used as a means of diagnosing early progression (EP) of cervical cancer, and can be used as clinical biomarkers useful in predicting the prognosis after treatment and surgery. It is expected that it will be used effectively.

Figure 1 is a diagram showing the mechanisms of microRNAs and mRNA related to early progression (EP) of cervical cancer.
Figure 2 is a schematic diagram explaining the treatment process, blood collection time, MRI imaging time, and follow-up process for cervical cancer patients who underwent anti-cancer radiation therapy.
Figure 3 displays cervical cancer patients who underwent chemotherapy and radiotherapy according to follow-up observation and progression time, and explains early progression, site of progression, secondary treatment, and survival.
Figure 4 shows the results of selection of miRNAs through subgroup analysis of miRNAs (log2FC) with significant correlation with early progression (EP) of cervical cancer.
Figure 5 shows the results of analyzing the correlation between the selected miRNAs in Figure 4.
Figure 6 shows the results of network analysis by dividing the selected group of miRNAs and their associated miRNAs into network subgroups.
Figure 7 shows the results of network analysis identifying the structure between the selected group of miRNAs and related mRNAs.
Figure 8 shows the results of selecting related genes, including mRNA (A), which is highly related to each clinical factor, and miRNA and mRNA (B) obtained through network analysis.
Figure 9 shows the results of IPA (Ingenuity pathway analysis) analysis of miRNAs and mRNAs related to early progression (EP) of cervical cancer.
Figure 10 is the result of drawing a Venn diagram of four function categories related to early progression (EP) of cervical cancer.
Figure 11 shows the results of network analysis of the mRNAs and miRNAs reselected in Figure 10.
Figure 12 shows the results of analyzing the log2FC values of the RNAs included in Figure 11 using the IPA database to analyze categories showing statistically significant differences depending on whether cervical cancer progressed early (Early progression (EP)).
Figure 13 is a graphical representation of the relative proportions of selected categories for major miRNAs related to early progression (EP) of cervical cancer.
Figure 14 is a graphical representation of significantly changed mRNA and miRNA according to changes in major miRNAs related to early progression (EP) of cervical cancer.
Figure 15 is a table summarizing the functions of RNAs that change significantly according to changes in main miRNAs related to early progression (EP) of cervical cancer.
Figure 16 shows the results of analyzing the relationship between the peripheral HPA axis and main miRNA.
Figure 17 shows the results of subgroup analysis for early progression (EP) of cervical cancer targeting the mRNAs in Figure 11.
Figure 18 shows the results of analyzing the correlation between the selected miRNAs in Figure 17.

The terms used in this specification are general terms that are currently widely used as much as possible while considering the function in the present invention, but this may vary depending on the intention or precedent of a person skilled in the art, the emergence of new technology, etc. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the relevant invention. Therefore, the terms used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, rather than simply the name of the term.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless clearly defined in the present application, should not be interpreted in an ideal or excessively formal sense. No.

The numerical range includes the values defined in the range above. Every maximum numerical limit given throughout this specification includes all lower numerical limits as if the lower numerical limit were explicitly written out. Every minimum numerical limit given throughout this specification includes every higher numerical limit as if such higher numerical limit was clearly written. All numerical limits given throughout this specification will include all better numerical ranges within the broader numerical range, as if the narrower numerical limits were clearly written.

Hereinafter, the present invention will be described in more detail.

To determine whether plasma exosomal miRNAs are biomarkers that can predict early progression (EP) of cervical cancer in patients who underwent chemotherapy, the present inventors analyzed the data before and after radiation therapy (2 weeks). Plasma exosomal miRNAs were analyzed to detect miRNAs showing clinical variables through fold change.

The present invention relates to a group consisting of micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), and micro RNA 146a-3p (hsa-miR-146a-3p). Provided is a biomarker composition for diagnosing early progression of cervical cancer comprising one or more selected from.

When diagnosing cancer, when determining the stage of cancer progression according to the extent to which cancer cells have spread, the stage of cancer according to the TNM method is determined as Stage 1, Stage 2, Stage 3, and Stage 4, and the early progression of cervical cancer (Early) Progression (EP) refers to the first stage of cancer progression, in which cancer tissue exists only in the cervix, has not spread to lymph nodes or other organs, and is expected to show a good prognosis, such as complete cure, after treatment such as surgery.

However, despite the early progression (EP) of cervical cancer, cancer may progress in areas other than the treated area within 6-7 months or 1 year after diagnosis even after appropriate anti-cancer radiation treatment. It may or may not be included. This usually progresses according to the stage of cervical cancer, and the disease progresses within a shorter period of time than the progression-free survival expected when chemotherapy is administered to cervical cancer, and the patient does not respond to secondary treatment or dies without time to attempt secondary treatment. The likelihood of reaching this increases. Referring to Table 1 and Figure 3, three of the seven early progression patients died within one year after diagnosis.

The micro RNA 1228-5p (hsa-miR-1228-5p) consists of the base sequence shown in SEQ ID NO: 1, and the micro RNA 3200-3p (hsa-miR-3200-3p) consists of the base sequence shown in SEQ ID NO: 2. It consists of a base sequence, and the micro RNA 146a-3p (hsa-miR-146a-3p) consists of a base sequence represented by SEQ ID NO: 3.

The biomarker composition includes micro RNA 33a-5p (hsa-miR-33a-5p), micro RNA 6815-5p (hsa-miR-6815-5p), PCK1 (Phosphoenolpyruvate carboxykinase 1) mRNA, and FCGR1A (High affinity immunoglobulin) It may additionally include one or more selected from the group consisting of gamma Fc receptor I) mRNA.

The micro RNA 33a-5p (hsa-miR-33a-5p) consists of the base sequence shown in SEQ ID NO: 4, and the micro RNA 6815-5p (hsa-miR-6815-5p) consists of the base sequence shown in SEQ ID NO: 5. It consists of a base sequence, and the mRNA of PCK1 (Phosphoenolpyruvate carboxykinase 1) consists of a base sequence shown in SEQ ID NO: 6, and the mRNA of FCGR1A (High affinity immunoglobulin gamma Fc receptor I) consists of a base sequence shown in SEQ ID NO: 7 It consists of

Additionally, the present invention provides micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), and micro RNA 146a-3p (hsa-miR-146a-3p). Provided is a composition for diagnosing early progression of cervical cancer, comprising an agent for measuring the expression level of one or more RNAs selected from the group consisting of.

Agents for measuring the expression level may be sense and antisense primers or probes that bind complementary to the micro RNA.

The primer is a short gene sequence that serves as the starting point for DNA synthesis, and refers to an oligonucleotide synthesized for use in diagnosis, DNA sequencing, etc. The primers can generally be synthesized and used in a length of 15 to 30 base pairs, but may vary depending on the purpose of use, and can be modified by methylation, capping, etc. by known methods.

The probe refers to a nucleic acid that can specifically bind to mRNA of a few bases to hundreds of bases in length, produced through enzyme-chemical separation purification or synthesis. The presence or absence of mRNA can be confirmed by labeling it with a radioactive isotope or enzyme, and it can be designed, modified and used by known methods.

The diagnostic composition includes micro RNA 33a-5p (hsa-miR-33a-5p), micro RNA 6815-5p (hsa-miR-6815-5p), PCK1 (Phosphoenolpyruvate carboxykinase 1) mRNA, and FCGR1A (High affinity immunoglobulin gamma). It may further include an agent for measuring the expression level of one or more RNAs selected from the group consisting of Fc receptor I) mRNA.

Additionally, the present invention provides a kit for diagnosing early progression of cervical cancer, including the composition for diagnosing early progression of cervical cancer.

The kit consists of one or more different component compositions, solutions or devices suitable for the analytical method. For example, in order to perform PCR, the kit includes genomic DNA derived from the sample to be analyzed, a primer set specific for the marker gene of the present invention, an appropriate amount of DNA polymerase, dNTP mixture, PCR buffer, and water. It could be a kit. The PCR buffer solution may contain KCl, Tris-HCl, and MgCl2. In addition, the kit may additionally include components required to perform electrophoresis to check whether amplification of the PCR product has occurred.

Additionally, the kit may be a kit containing essential elements required to perform RT-PCR. In addition to each primer pair specific for the marker gene, the RT-PCR kit contains test tubes or other suitable containers, reaction buffer, deoxynucleotides (dNTPs), enzymes such as Taq-polymerase and reverse transcriptase, DNase, RNase inhibitors, and DEPC. -Can include DEPC-water, sterilized water, etc. It may also include a pair of primers specific to the gene used as a quantitative control.

In addition, the present invention provides micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p), or micro RNA 146a-3p (hsa-miR) in a biological sample derived from a subject. Provides a method of providing information for early diagnosis of cervical cancer, including the step of measuring the expression level of -146a-3p).

The biological sample is blood or plasma derived exosomes.

The expression level was determined by next generation sequencing (NGS), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), and RNase protection assay. It can be measured using one or more methods selected from the group consisting of (RNase protection assay (RPA)), microarray, and northern blotting.

The method of providing is to obtain micro RNA 33a-5p (hsa-miR-33a-5p), micro RNA 6815-5p (hsa-miR-6815-5p), mRNA of PCK1 (Phosphoenolpyruvate carboxykinase 1) from a biological sample derived from a subject, and It may further include measuring the expression level of one or more RNAs selected from the group consisting of mRNA of FCGR1A (high affinity immunoglobulin gamma Fc receptor I).

The subject may be a patient receiving radiation therapy to treat cervical cancer.

In a broad sense, the above diagnosis means judging the actual condition of the patient's disease in all aspects. The contents of the judgment include the name of the disease, etiology, type, severity, detailed conditions of the disease, and the presence or absence of complications. The prognosis refers to a prediction regarding the progression and recovery of the disease, and refers to an outlook or preliminary evaluation.

The above method of providing information for diagnosis provides objective basic information necessary as a preliminary step for diagnosis or prognosis prediction, and excludes the doctor's clinical judgment or opinion.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for illustrating the present invention, and it will be apparent to those skilled in the art that the scope of the present invention is not to be construed as limited by these examples.

[Example]

1. Patients and specimens

Among patients who received anti-cancer radiation therapy after being diagnosed with cervical cancer, patients whose cancer progressed to multiple locations outside of the radiation range and scope were selected as the clinical end point. Cases where cancer progressed locally within the radiation treatment range, even within 1 year, were not included. The Institutional Review Board of Ajou University Hospital obtained informed consent from donors and approved this study.

The stage of cervical cancer was set based on the FIGO 2018 (The 2018 International Federation of Gynecology and Obstetrics) stage.

As shown in Figure 2, the treatment process, blood collection time, MRI imaging time, and follow-up process were conducted for 28 cervical cancer patients who underwent anti-cancer radiation therapy.

As a result, as shown in Figure 3, the median f/u of all patients was 16.9 months, and the 7 patients at the top of the graph were patients who experienced early progression (EP), and the disease progressed outside the area where radiation treatment was performed. (out-field) All cases showed signs of progression, and the time of progression was less than 10 months after diagnosis. Of these, two died before chemotherapy was administered, one patient voluntarily gave up treatment after chemotherapy, and one patient progressed rapidly and died during third-line chemotherapy. Two patients showed partial treatment response with second-line chemotherapy, and the remaining patient is maintaining well after complete remission.

There were patients with local recurrence after 1 year in the treatment area (in filed only), but this was not included in the category of early progression (EP). One of these patients did not undergo brachytherapy due to personal refusal, so it was re-administered after recurrence was confirmed, and the other patient had a large tumor that had metastasized to the lymph nodes and was not controlled. The clinical results of the patients are shown in Table 1 below.

Patients who experienced early progression (EP) of cervical cancer had a relatively higher incidence of adenocarcinoma than squamous cell carcinoma and often died. In addition, there were more cases where additional steroids were prescribed after radiation therapy, and all had good acute treatment responses. Patients who experienced early progression (EP) of cervical cancer showed no significant difference in stage, and although there were more cases of IVB, they were evenly distributed in local stage.

2. Construction of dataset for exosomal miRNA and mRNA

Before radiation treatment and during the second week of radiation treatment, 5-10 cc of blood was collected from patients. Plasma was separated from the collected blood, and additionally, 3-5 cc of plasma samples from 29 people stored in the human derivatives storage were distributed and used in experiments. Exosomes were isolated from plasma samples and NGS (Next Generation Sequencing) analysis was performed. Samples with low expression levels from plasma were excluded from the analysis.

2-1. Small RNA library construction and sequencing

Exosomes were isolated by mixing plasma with Exo2D RNA solution (Exosomeplus). Exosomal RNA from plasma-derived exosomes was extracted using the miRNeasy Serum/Plasma Kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. The concentration of extracted RNA was calculated by Quant-IT RiboGreen (Invitrogen). The size of RNA was confirmed using the Agilent RNA 6000 Pico Kit and Small RNA Kit in an Agilent 2100 Bioanalyzer (Agilent Technologies, Boblingen, Germany).

10 ng of RNA isolated from each sample was used to construct a sequencing library with the SMARTer smRNA-Seq kit for Illumina according to the manufacturer's protocol. Input RNA was first polyadenylated to provide a priming sequence for oligo (dT) primers. cDNA synthesis was primed by a 3'smRNA dT Primer that incorporated an adapter sequence at the 5' end of each RNA template, followed by the addition of non-template nucleotides bound by SMRT smRNA Oligo enhanced by locked nucleic acid (LNA) technology. In the template conversion step, PrimeScript RT used SMART smRNA Oligo as a template to add a second adapter sequence to the 3' end of each first-strand cDNA molecule. After this, full-length Illumina adapters containing the index sequence for sample multiplexing during PCR amplification were added. Forward PCR Primer bound to the sequence added by SMART smRNA Oligo, while Reverse PCR Primer bound to the sequence added by 3’smRNA dT Primer.

The amplified library was purified on a 6% Novex TBE-PAGE gel (Thermo Fisher, MA), and a fraction of more than 138 bp (cDNA 18 bp or more + adapter 120 bp or more) was excised. The resulting library cDNA molecules contained the sequences required for clustering on an Illumina flow cell.

The library was gel purified and verified for size, purity, and concentration on an Agilent Bioanalyzer. Libraries were quantified using qPCR according to the qPCR Quantification Protocol Guide (KAPA Library Quantificatoin Kit for Illumina Sequecing Platforms) and verified using TapeStation D1000 ScreenTape (Agilent Technologies, Waldbronn, Germany). Libraries were pooled in equimolar amounts and sequenced on an Illumina HiSeq 2500 (Illumina, San Diego, USA) instrument, generating 51 base reads. Image decomposition and quality value calculation were performed using modules of the Illumina pipeline.

2-2. Adapter trimming

Raw sequence reads of small RNAs obtained from different experimental samples were preprocessed with miRDeep2 and analyzed. Adapter trimming used the cutadapt program to remove adapter sequences to which miRNAs were attached during the construction of the smRNA library. The first 3 nt of all reads were trimmed to remove additional bases inserted during the SMART template-switching activity process. The adapter sequence and all 3' sides of the adapter were also removed. If a read matched more than the first 5 bp of the 3' adapter sequence, the sequence was considered to actually be an adapter sequence and was then trimmed from the read. For analysis, only trimmed reads of at least 18bp were considered reliable. The remaining adapter sequences were classified as non-adapter reads. In this analysis, trimmed and non-adapter reads were combined and considered processed reads for downstream analysis.

2-3. Clustering

To minimize sequence uniqueness and computational intensity, reads processed with adapter sequences were collected to form clusters. This cluster contains reads with 100% match by sequence ID and read length, and a provisional cluster ID and number of retained reads were provided.

2-4. Ribosomal RNA filtering

Most RNA components are known as rRNA. To eliminate the effect of large amounts of rRNA, reads were aligned and matched to the 45S pre-rRNA and mitochondrial rRNA of Homo sapiens .

2-5. miRNA read

Sequence alignment and detection of microRNAs were performed using the miRDeep2 software algorithm. Before performing sequence alignment, the Homo sapiens reference genome release hg19 was searched in the UCSC genome browser and indexed using Bowtie (1.1.2) to align sequencing reads to the reference sequence. Precursor miRNAs obtained from miRBase v21 were aligned with reference sequences. The miRDeep2 algorithm is based on the miRNA biogenesis model and aligned reads to potential hairpin structures in a manner consistent with Dicer processing and assigned a score indicating the likelihood that the hairpin is a true miRNA precursor.

2-6. Proportion of miRNA and other RNA categories

Clustered reads were sequentially aligned to the reference genome, miRBase v21, and the non-coding RNA database RNAcentral release 10.0, to identify known miRNAs and other types of RNA.

All data and visualizations were performed using R 4.0.2 version (www.r-project.org), and all comparative analyzes were assumed to be non-parametric. The NGS data included small RNA, non-mRNA, and mRNA, and among these, miRNA and mRNA were used for analysis. Among these, cases where the read count was 0 in more than 14 patients were excluded from the analysis. There were 586 cases of miRNA and 15,324 cases of mRNA used in the analysis. The values of all transcriptome data used the log2 fold change (log2FC) value of the read count values 2 weeks after the start of radiation treatment compared to the read count values of plasma exosomes before treatment. For each of the 28 patients, the read count value before radiation treatment was used as a control, and the change in read count value 2 weeks after radiation treatment was calculated as the log2 fold change (log2FC) value. TMM normalization was performed using edgeR and log2FC values were obtained.

3. Analysis process and results

The analysis process and results for selecting biomarkers proceeded in the following steps.

Stage I

We selected miRNAs that could predict clinical end points, and analyzed their correlation (Figures 4 and 4). Correlation analysis consisted of the following three steps.

Step 1: Hmisc package - rcorr function - pearson’s correlation

Step 2: Leaps package - regsubsets function - exhaustive algorithm (set max variable 10 or 7)

Step 3: Mean comparison (Wincoxon rank sum test or Kruskal-Wallis test) and boxplots

As shown in Figure 4, miRNAs with a significant correlation (|R|>0.4) with early progression (EP) were selected through subgroup analysis of miRNAs (log2FC). When all possible combinations of cases were calculated based on the Adjusted R value, consistently included miRNAs were selected. miR-501-3p was also selected, but was excluded because the difference between the EP group and the non-EP group was greater than the Wilcoxon test.

As shown in Figure 5, after obtaining directionality through multiple line regression combination of selected miRNA variables, the (log2FC) values of each selected miRNA were calculated as: -3200-3p - As a result of calculating the value by adding and subtracting in the order of miR-146a-3p, the value was significantly lower in patients who experienced early progression (EP).

Stage II

The main miRNA groups and their associated miRNAs were divided into network subgroups and network analyzed. The influence of major miRNA families and subgroups was described according to clinical end points.

Network analysis used the Igraph package - prim algorithm, and in all networks, red edges indicated positive directions and blue edges indicated negative directions.

For the miRNA group stratification, group A refers to the main miRNA group, group B refers to the group of miRNAs associated with several major miRNA groups, and group C refers to the group of miRNAs that show negative feedbacks due to radiation therapy, which are associated with early progression (EP). In order to see the effect on Among the groups, this refers to the group containing the miRNAs of patients who experienced early progression (EP).

With a network using miRNAs related to early progression (EP), the number of increased and decreased number of miRNAs at each level was compared according to EP and non-EP for each community containing major miRNAs (increase: log2FC>1.5, decrease: log2FC <-1.5).

As shown in Figure 6, the number of A levels significantly increased or decreased in the same direction as shown in Figure 4. This means that each level A miRNA independently contributes to EP. The miR-1228-5p/33a-5p community in the upper left shows a significant decrease in EP even at the B level, and the miR-146a-3p community next to it shows a significant decrease in EP at the C level without B level. It turned out that there were a lot of teeth. These two groups can be considered as significant downstream miRNAs because there are many influential miRNAs. On the contrary, the remaining communities centered on miR-6815-5p and miR-3200-3p had little correlation to lower levels, so it is possible that they were not appropriate connections of miRNAs or performed other functions simultaneously.

Stage III

Through network analysis, the overall structure of the miRNA-mRNA was identified, including the main miRNA group, related mRNAs, and miRNAs included in stage II. The shortest pathway connecting major miRNAs was described, and the locations of clinically relevant subgroup miRNAs were identified in the level II network. Network analysis was visualized under the same conditions as in step II above.

As shown in Figure 7, a network was constructed by combining (|R| >0.6) mRNAs associated with A level miRNAs and the miRNAs in Figure 6, and the shortest distance on the A level miRNAs (arrows) is indicated by a red line. MiR-1228-5p, MiR-146a-3p, and MiR-33a-5p were linked centered on PDE3A (marked with a star), and were shown to be associated with MiR-6815-5p and MiR-3200-3p. It was found to be connected through 10 or more TTPAL, E2F2, PLAUR, PDE3A, CLIP2, TNIK, hsa.miR.590.3p, PIGX, TNIP1, and TYMP. It can be seen that part of the B/C level is observed on the network, which shows that the structure of the miRNA-mRNA is appropriate.

Stage IV

mRNAs related to clinical end points and miRNAs and mRNAs included in the stage III network were selected (Figure 8), and significant diseases/functions were identified from the existing IPA (Ingenuity Pathway Analysis) database. Function categories and subcategories were extracted (Figure 9).

As shown in Figure 9, after performing IPA analysis with the miRNAs and mRNAs related to early progression (EP), the inflammatory response was identified as the relevant regions among the 30 significant function categories. , inflammatory disease, metabolic disease, cancer, and cellular growth and proliferation were selected. Specific sub-functions of the above items include severe inflammatory disorder, antigen presentation of macrophages, Th2 immune response, and chemotaxis of regulatory T cells. ) was selected.

Stage V

Diseases/function categories with a degree of significance and possible association with clinical end points were selected, and a vendiagram was drawn using the mRNA and miRNA corresponding to each group (Figure 10 ). Using the Venn diagram shown, mRNAs and miRNAs commonly associated with cancer and specific functions were re-selected.

As shown in Figure 10, a Venn diagram of four function categories selected in relation to early progression (EP) was drawn and mRNA and miRNA of items overlapping with the cancer region were selected.

Stage VI

The re-selected mRNAs and miRNAs were formed into a network using the short pathway of the main miRNA in Figure 7. Network analysis was visualized under the same conditions as in step II above.

As shown in Figure 11, a network was formed using the short pathway including the main miRNAs and the selected miRNAs and mRNAs in Figure 10, and the change in each main miRNA (log2FC>1.5 (up), log2FC <-1.5 (down) ), others - no change), the mRNAs and miRNAs that changed statistically significantly were indicated (red numbers indicate decrease, blue numbers indicate increase). miR-3200-3p and miR-1228-5p were associated with PCK1 through SLAMF1, and miR-146a-3p was strongly associated with PCK1 through CCNO. MiR-1228-5p was associated with changes in FCGR1A, and PDE3A, which integrates MiR-146a-3p, MiR-33a-5p, and MiR-1228-5p, was associated with PCK1 (red edges are positive). direction, blue means negative direction).

Stage VII

The log2FC values of RNAs constituting the network of stage VI were uploaded to the IPA database for each 28 people, and the z-score of the significant disease/function category was obtained. Only the items for which significant z scores were obtained in all patients were selected, and items that showed statistically significant differences according to clinical end point were analyzed.

As shown in Figure 12, all log2FC values of RNA included in the network of Figure 11 were analyzed in the IPA database for each patient to obtain z scores for each category, and then statistically significant depending on whether there was early progression (EP). After describing the categories that showed one difference, no items were found that were related to current clinical outcomes and assumptions.

Stage VIII

For the RNA groups that changed significantly in all networks, we analyzed the change in the ratio of RNAs for the selected subcategories to the main miRNA.

As shown in Figure 13, the network of Figure 11 contains about 65-70% of RNAs associated with inflammatory disease/response, about 15-20% of RNAs associated with metabolic disease, and about 15-20% of cells. RNAs related to cellular growth and proliferation accounted for approximately 10-15%. Relatively, the functions of RNAs that significantly change according to changes in miR-33a-5p had a high proportion of inflammatory diseases/responses, and in particular, severe inflammatory disorders. miR-1228-5p and miR-3200-3p had a high proportion of metabolic diseases and were associated with antigen presentation of macrophages. In the case of miR-6815-5p, the proportion of cellular growth and proliferation was high.

Stage IX

Significantly changed mRNAs and miRNAs were analyzed according to changes in the main miRNA.

As shown in Figure 14, changes in the same direction are indicated in red, changes in the opposite direction are indicated in blue, and changes exceeding 1.5 log2FC are indicated in shade. Sub-ID stands for severe inflammatory disorder and Sub-IR stands for antigen presentation of macrophages.

X level

In Figure 12, for items that do not exist in the existing database, the changing items according to each main miRNA are categorized according to items such as inflammatory signaling/anti-inflammatory signaling/cancer proliferation. Organized.

As shown in Figure 15, the functions of RNAs that significantly change according to changes in each major miRNA have been summarized.

Stage XI

To analyze the relationship between the HPA axis and major miRNAs in peripheral tissues, the relationship with miR-3200-3p was described using CRH, POMC, CYP11B1, and HSD11B1 values. Network analysis was visualized under the same conditions as in step II above.

As shown in Figure 16, assuming the HPA axis in peripheral tissue, mRNA CRH (Corticotropin releasing hormone), POMC (proopiomelanocortin), CYP11B1 (Cytochrome P450 family 11 subfamily B member 1), and HSD11B1 (Hydroxysteroid 11) As a result of analyzing the relationship between -beta dehydrogenase 1), it was found that miR-3200-3p mediates CRH and CYP11B1. An increase in cortisol was observed through an increase in CRH, a decrease in miR-3200-3p, and an increase in CYP11B1 due to inflammation. In patients with early progression (EP), CRH significantly increased and miR-3200-3p significantly decreased, but CYP11B1 tended to increase. It is assumed that the above results are influenced by the Central HPA axis.

Stage XII

Using the mRNAs obtained in Figure 11, mRNAs that can predict clinical end points are extracted, and the clinical significance between these and the main miRNAs is described. Correlation analysis was performed in the same steps as step I above.

As shown in Figure 17, mRNAs that were consistently included were selected when all possible combinations were calculated based on the Adjusted R value. PCK1 and FCGR1A were selected.

As shown in Figure 18, the FCGR1A - PCK1 (log2FC) value can be seen to be significantly lower in patients with early progression (EP). miR-1228-5p+miR- was selected through subgroup analysis using PCK1, FCGR1A, miR-1228-5p, miR-33a-5p, miR-6815-5p, miR-3200-30, and miR-146a-3p. 33a-5p+miR-6815-5p+FCGR1A-PCK1(log2FC) can further increase the difference between EP and non-EP.

As the specific parts of the present invention have been described in detail above, it is clear to those skilled in the art that these specific techniques are merely preferred embodiments and do not limit the scope of the present invention. do. That is, the practical scope of the present invention is defined by the appended claims and their equivalents.

<110> Ajou University <120> Biomarkers for diagnosing early progression of cervical cancer, and uses it <130> ADP-2023-0212 <160> 7 <170> KoPatentIn 3.0 <210> 1 <211> 21 <212> DNA <213> Artificial Sequence <220> <223>hsa-miR-1228-5p <400> 1 gugggcgggg gcaggugugu g 21 <210> 2 <211> 22 <212> DNA <213> Artificial Sequence <220> <223>hsa-miR-3200-3p <400> 2 caccuugcgc uacucagguc ug 22 <210> 3 <211> 22 <212> DNA <213> Artificial Sequence <220> <223> hsa-miR-146a-3p <400> 3 ccucugaaau ucaguucuuc ag 22 <210> 4 <211> 21 <212> DNA <213> Artificial Sequence <220> <223> hsa-miR-33a-5p <400> 4 gugcauugua gugcauugc a 21 <210> 5 <211> 23 <212> DNA <213> Artificial Sequence <220> <223>hsa-miR-6815-5p <400> 5 uagguggcgc cggaggaguc auu 23 <210> 6 <211> 1869 <212> DNA <213> Artificial Sequence <220> <223> PCK1 mRNA <400> 6 atgcctcctc agctgcaaaa cggcctgaac ctctcggcca aagttgtcca gggaagcctg 60 gacagcctac cccaggcagt gagggagttt ctcgagaata acgctgagct gtgtcagcct 120 gatcacatcc acatctgtga cggctctgag gaggagaatg ggcggcttct gggccagatg 180 gaggaagagg gcatcctcag gcggctgaag aagtatgaca actgctggtt ggctctcact 240 gaccccaggg atgtggccag gatcgaaagc aagacggtta tcgtcaccca agagcaaaga 300 gacacagtgc ccatccccaa aacaggcctc agccagctcg gtcgctggat gtcagaggag 360 gattttgaga aagcgttcaa tgccaggttc ccagggtgca tgaaaggtcg caccatgtac 420 gtcatcccat tcagcatggg gccgctgggc tcgcctctgt caaagatcgg catcgagctg 480 acggattcac cctacgtggt ggccagcatg cggatcatga cgcggatggg cacgcccgtc 540 ctggaagcag tgggcgatgg ggagtttgtc aaatgcctcc attctgtggg gtgccctctg 600 cctttacaaa agcctttggt caacaactgg ccctgcaacc cggagctgac gctcatcgcc 660 cacctgcctg accgcagaga gatcatctcc tttggcagtg ggtacggcgg gaactcgctg 720 ctcgggaaga agtgctttgc tctcaggatg gccagccggc tggccaagga ggaagggtgg 780 ctggcagagc acatgctgat tctgggtata accaaccctg agggtgagaa gaagtacctg 840 gcggccgcat ttcccagcgc ctgcgggaag accaacctgg ccatgatgaa ccccagcctc 900 cccgggtgga aggttgagtg cgtcggggat gacattgcct ggatgaagtt tgacgcacaa 960 ggtcatttaa gggccatcaa cccagaaaat ggctttttcg gtgtcgctcc tgggacttca 1020 gtgaagacca accccaatgc catcaagacc atccagaaga acacaatctt taccaatgtg 1080 gccgagacca gcgacggggg cgtttactgg gaaggcattg atgagccgct agcttcaggt 1140 gtcaccatca cgtcctggaa gaataaggag tggagctcag aggatgggga accttgtgcc 1200 caccccaact cgaggttctg cacccctgcc agccagtgcc ccatcattga tgctgcctgg 1260 gagtctccgg aaggtgttcc cattgaaggc attatctttg gaggccgtag acctgctggt 1320 gtccctctag tctatgaagc tctcagctgg caacatggag tctttgtggg ggcggccatg 1380 agatcagagg ccacagcggc tgcagaacat aaaggcaaaa tcatcatgca tgaccccttt 1440 gccatgcggc ccttctttgg ctacaacttc ggcaaatacc tggcccactg gcttagcatg 1500 gcccagcacc cagcagccaa actgcccaag atcttccatg tcaactggtt ccggaaggac 1560 aaggaaggca aattcctctg gccaggcttt ggagagaact ccagggtgct ggagtggatg 1620 ttcaaccgga tcgatggaaa agccagcacc aagctcacgc ccataggcta catccccaag 1680 gaggatgccc tgaacctgaa aggcctgggg cacatcaaca tgatggagct tttcagcatc 1740 tccaaggaat tctggggagaa ggaggtggaa gacatcgaga agtatctgga ggatcaagtc 1800 aatgccgacc tcccctgtga aatcgagaga gagatccttg ccttgaagca aagaataagc 1860 cagatgtaa 1869 <210> 7 <211> 1125 <212> DNA <213> Artificial Sequence <220> <223> FCGR1A mRNA <400> 7 atgtggttct tgacaactct gctcctttgg gttccagttg atgggcaagt ggacaccaca 60 aaggcagtga tcactttgca gcctccatgg gtcagcgtgt tccaagagga aaccgtaacc 120 ttgcactgtg aggtgctcca tctgcctggg agcagctcta cacagtggtt tctcaatggc 180 acagccactc agacctcgac ccccagctac agaatcacct ctgccagtgt caatgacagt 240 ggtgaataca ggtgccagag aggtctctca gggcgaagtg accccataca gctggaaatc 300 cacagaggct ggctactact gcaggtctcc agcagagtct tcacggaagg agaacctctg 360 gccttgaggt gtcatgcgtg gaaggataag ctggtgtaca atgtgcttta ctatcgaaat 420 ggcaaagcct ttaagttttt ccactggaat tctaacctca ccattctgaa aaccaacata 480 agtcacaatg gcacctacca ttgctcaggc atgggaaagc atcgctacac atcagcagga 540 atatctgtca ctgtgaaaga gctatttcca gctccagtgc tgaatgcatc tgtgacatcc 600 ccactcctgg aggggaatct ggtcaccctg agctgtgaaa caaagttgct cttgcagagg 660 cctggtttgc agctttactt ctccttctac atgggcagca agaccctgcg aggcaggaac 720 acatcctctg aataccaaat actaactgct agaagagaag actctgggtt atactggtgc 780 gaggctgcca cagaggatgg aaatgtcctt aagcgcagcc ctgagttgga gcttcaagtg 840 cttggcctcc agttaccaac tcctgtctgg tttcatgtcc ttttctatct ggcagtggga 900 ataatgtttt tagtgaacac tgttctctgg gtgacaatac gtaaagaact gaaaagaaag 960 aaaaagtggg atttagaaat ctctttggat tctggtcatg agaagaaggt aatttccagc 1020 cttcaagaag acagacattt agaagaagag ctgaaatgtc aggaaacaaaa agaagaacag 1080 ctgcaggaag gggtgcaccg gaaggagccc cagggggcca cgtag 1125

Claims (5)

RNA expression levels of micro RNA 1228-5p (hsa-miR-1228-5p), micro RNA 3200-3p (hsa-miR-3200-3p) and micro RNA 146a-3p (hsa-miR-146a-3p) A kit for diagnosing early progression of cervical cancer containing a measuring agent. The kit for diagnosing early progression of cervical cancer according to claim 1, wherein the agent for measuring the expression level is sense and antisense primers or probes that bind complementary to the micro RNA. The method of claim 1, wherein the kit includes micro RNA 33a-5p (hsa-miR-33a-5p), micro RNA 6815-5p (hsa-miR-6815-5p), mRNA of PCK1 (Phosphoenolpyruvate carboxykinase 1), and FCGR1A. A kit for diagnosing early progression of cervical cancer, characterized in that it further comprises an agent for measuring the expression level of one or more RNAs selected from the group consisting of mRNA of (high affinity immunoglobulin gamma Fc receptor I). The method of claim 1, wherein the micro RNA 1228-5p (hsa-miR-1228-5p) consists of a base sequence represented by SEQ ID NO: 1, and the micro RNA 3200-3p (hsa-miR-3200-3p) A kit for diagnosing early progression of cervical cancer, characterized in that it consists of a base sequence shown in SEQ ID NO: 2, and the micro RNA 146a-3p (hsa-miR-146a-3p) consists of a base sequence shown in SEQ ID NO: 3. The method of claim 3, wherein the micro RNA 33a-5p (hsa-miR-33a-5p) consists of the base sequence represented by SEQ ID NO: 4, and the micro RNA 6815-5p (hsa-miR-6815-5p) It consists of a nucleotide sequence represented by SEQ ID NO: 5, the mRNA of PCK1 (Phosphoenolpyruvate carboxykinase 1) consists of a nucleotide sequence represented by SEQ ID NO: 6, and the mRNA of FCGR1A (High affinity immunoglobulin gamma Fc receptor I) has SEQ ID NO: A kit for diagnosing early progression of cervical cancer, characterized in that it consists of a base sequence indicated by 7.