A piRNA molecular marker and diagnostic model for endometrial cancer
By identifying and using piRNA molecular markers such as hsa_piR_009183, hsa_piR_014592 and hsa_piR_006767 in endometrial cancer, a diagnostic model was constructed, which solved the problem of low diagnostic sensitivity of early endometrial cancer in the prior art, and achieved non-invasive, high sensitivity and specific diagnostic effects.
Patent Information
- Application Number
- CN202411302930.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2025-02-28
- Estimated Expiration
- 2044-09-19
AI Technical Summary
The prior art is difficult to achieve non-invasive and accurate diagnosis of early endometrial cancer. Existing tumor markers such as CA125 are low in sensitivity in diagnosis, and invasive endometrial biopsy has pain and surgical risks.
A molecular marker of endometrial cancer piRNA, including hsa_piR_009183, hsa_piR_014592 and hsa_piR_006767, was provided, and a diagnostic model based on these piRNAs was constructed to detect the expression of piRNA by serum samples to conduct early diagnosis of endometrial cancer.
High sensitivity and specific diagnosis of endometrial cancer, including early endometrial cancer, is achieved, providing a non-invasive and simple diagnostic method, reducing the mortality rate of endometrial cancer.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to the field of biomedical technology, and more specifically, to a piRNA molecular marker and a diagnostic model for endometrial cancer. Background Art
[0002] Evidence-based treatment options for patients with advanced endometrial cancer (EC) are limited. Therefore, early diagnosis is crucial when available treatments are curative. Early diagnosis can also minimize radical treatment and provide conservative treatment options for women of childbearing age and patients with contraindications to surgery.
[0003] Transvaginal ultrasound scanning (TVS) is the preferred imaging modality for the initial evaluation of suspected endometrial cancer. TVS is noninvasive and sensitive in measuring endometrial thickness (ET), but its specificity is low, so women with endometrial thickening require further invasive endometrial biopsy to confirm the diagnosis.
[0004] Endometrial biopsy under hysteroscopy is the gold standard for diagnosing endometrial diseases, but most patients feel pain, especially women who have not given birth. The resulting discomfort is the most common reason for failure of diagnostic examinations. Therefore, some patients need to undergo the operation under anesthesia, which increases the risk of surgery and treatment costs. In rare cases, serious complications such as embolism, uterine perforation, and cervical laceration may also occur.
[0005] Serum is an ideal sample type for rapid diagnosis of clinical diseases. However, there is currently no non-invasive method that can accurately detect early endometrial cancer. As a tumor marker, the carbohydrate antigen CA125 currently used in clinical practice has limited diagnostic value. Therefore, there is an urgent need for a non-invasive, convenient, and accurate serum biomarker for the diagnosis of endometrial cancer, especially for the differential diagnosis of early endometrial cancer.
[0006] Exosomes are membrane vesicles released into the extracellular matrix after the fusion of intracellular multivesicular bodies (MVBs) with the cell membrane. They are lipid inclusion structures with a diameter of 30 to 150 nm and play an important role in intercellular communication. As a transport system for various cell-derived molecular components, exosomes contain components such as proteins, lipids, DNA, non-coding RNA and mRNA. Under different physiological and pathological conditions, their contents are often different, reflecting the physiological and pathological states of the original host cells, which makes exosomes a reliable carrier for precision medicine and liquid biopsy.
[0007] Exosomes are known to be involved in a wide range of physiological and pathological processes. Many recent studies have shown that exosomes are associated with various stages of tumor progression, including immune regulation, angiogenesis, metastasis, drug resistance, and cell proliferation. In the field of diagnosis, exosomes have great advantages because their contents can be protected by the lipid bilayer structure in vitro and not degraded.
[0008] As a newly discovered non-coding RNA, piRNA can regulate gene expression at the transcriptional and post-transcriptional levels, thereby affecting various processes of cancer cells, including proliferation, migration, invasion, metastasis and apoptosis. Recent studies have shown that piRNA in serum exosomes has the potential to become an efficient biomarker for cancer screening and diagnosis.
[0009] At present, piRNAs associated with EC have not been studied and explored. Finding early diagnostic standards for EC based on serum exosomal piRNAs has important clinical value for improving patient prognosis, increasing survival rate and lifestyle treatment. Summary of the invention
[0010] In order to make up for the deficiencies of the prior art, the present invention provides a piRNA molecular marker and a diagnostic model for endometrial cancer.
[0011] The present invention is achieved through the following technical solutions:
[0012] In a first aspect, the present invention provides a piRNA molecular marker for endometrial cancer, wherein the piRNA molecular markers for endometrial cancer are hsa_piR_009183, hsa_piR_014592 and hsa_piR_006767, and their nucleotide sequences are shown in SEQ ID NO.1, SEQ ID NO.2 and SEQ ID NO.3.
[0013] In a second aspect, the present invention provides a diagnostic model constructed using endometrial cancer piRNA molecular markers, the model formula is:
[0014] logit(3piRNA_panel) = - 9.2038 + -1.6374×hsa_piR_009183 + 1.7536 ×hsa_piR_014592 + 1.0598 ×hsa_piR_006767.
[0015] Compared with the prior art, the present invention has the following advantages:
[0016] (1) The present invention provides piRNA molecular markers that can be used for the diagnosis of endometrial cancer. Endometrial cancer can be diagnosed by collecting serum samples, extracting exosome RNA, and detecting the expression levels of hsa_piR_014592, hsa_piR_009183, and hsa_piR_006767. On this basis, the present invention also provides an endometrial cancer diagnostic product and diagnostic model.
[0017] (2) The diagnostic model of the present invention can diagnose endometrial cancer, including early endometrial cancer, with very high sensitivity and specificity, and can be used for early screening of endometrial cancer, thereby reducing the mortality rate of endometrial cancer. The present invention not only enriches the molecular markers that can be used for the diagnosis of endometrial cancer, but also provides a non-invasive, simple, sensitive and specific method for diagnosing endometrial cancer, overcoming the disadvantages of low sensitivity of existing tumor markers such as CA125 when used for the diagnosis of endometrial cancer, and is of great significance for the early screening and diagnosis of endometrial cancer.
[0018] (3) The endometrial cancer biomarker of the present application can be used to directly detect endometrial cancer through serum samples. Serum has the advantages of non-invasive collection, easy acquisition, and convenient large-scale use. The lipid bilayer structure of exosomes can protect its contents, allowing piRNA to exist stably in vitro, providing a new non-invasive biomarker for early screening and large-scale screening of endometrial cancer. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The present invention will be further described below in conjunction with the accompanying drawings.
[0020] Figure 1 Heat map of significantly differentially expressed piRNAs in EC patients;
[0021] Figure 2 The volcano plot of differentially expressed piRNAs shows that 14 piRNAs were selected based on the screening criteria;
[0022] Figure 3 Heat map of 14 piRNA expressions in healthy controls and endometrial cancer patients;
[0023] Figure 4 The expression of four down-regulated piRNAs in the serum of 24 healthy controls and 24 endometrial cancer patients;
[0024] Figure 5 The expression of 10 up-regulated piRNAs in the serum of 24 healthy controls and 24 endometrial cancer patients;
[0025] Figure 6To evaluate the ROC curves of the sensitivity and specificity of the six candidate piRNAs in 24 healthy controls and 24 endometrial cancer patients;
[0026] Figure 7 is the expression of 6 candidate piRNAs in the training set (64 12 HC vs 92 EC);
[0027] Figure 8 ROC curve analysis of 6 candidate piRNAs in the training set;
[0028] Fig. 9 A is the importance of the five candidate piRNAs in the random 13 forest model; B is the root mean square error (RMSE) reflecting the inclusion of different numbers;
[0029] Fig.10 A shows the logistic regression analysis of 5 candidate piRNAs: hsa_piR_006767, hsa_piR_014592 and hsa_piR_009183 showed strong statistical significance; B shows the p value obtained by logistic regression analysis of various diagnostic panels using Delong test;
[0030] Fig.11 ROC curve analysis of 5 candidate models in the training set;
[0031] Fig.12 is the ROC curve of the five candidate models in the validation set;
[0032] Fig.13 The performance of 3piRNA_panel and 4 individual piRNAs was evaluated for DCA curves;
[0033] Fig.14 3piRNA_panel scores for HC, EC stages I, II, III, and IV;
[0034] Fig.15 ROC curve of 3piRNA_panel in distinguishing stage I, II, III, and IV EC patients from HC individuals;
[0035] Fig.16A in the figure is the 3piRNA_panel score in HC, stage Ia EC and stage Ib~ EC; B is the ROC curve of 3piRNA_panel in distinguishing stage Ia and stage Ib~ patients from HC individuals; C is the ROC curve of 3piRNA_panel, CA125 or the combination of 3piRNA_panel and CA125 in all stages of EC compared with HC individuals. DETAILED DESCRIPTION
[0036] The present invention is further described below in conjunction with the accompanying drawings and specific examples, but the examples do not limit the present invention in any form. Unless otherwise specified, the reagents, methods and equipment used in the present invention are conventional reagents, methods and equipment in the art. Unless otherwise specified, the reagents and materials used in the following examples are commercially available.
[0037] Example 1
[0038] Experimental Materials
[0039] Serum samples from patients with endometrial cancer and healthy controls were obtained from the Second Hospital of Shandong University and Qilu Hospital of Shandong University. The patients were informed and consented to the use of the kits. Serum exosome extraction kit (MiRNeasy Micro Kit, QIAGEN, Cat#: 217084, GERMANY), reverse transcription kit (Evo M-MLV RT Kit for qPCR, Cat No.AG11707, China, which is suitable for reverse transcription of piRNA), SYBR Green Premix Pro Taq HS qPCRKit (Cat No. AG11701, China).
[0040] Experimental methods
[0041] After extracting serum exosome RNA from endometrial cancer patients and healthy subjects, it was reverse transcribed into cDNA, and the expression levels of piRNAs were detected by qPCR.
[0042] The specific steps are:
[0043] (1) Exosomes were extracted from serum samples of 152 endometrial cancer patients and 108 healthy subjects using a serum exosome extraction kit;
[0044] (2) Use MiRNeasy Micro Kit to extract exosome RNA from 250 μl of serum; the final extracted RNA dilution was 16 μl;
[0045] (3) Reverse transcribe the RNA into cDNA using a reverse transcription kit. The reverse transcription system is 10 μL, containing 4.5 μl RNA.
[0046] (4) Using the cDNA obtained in (3) as a template, a qPCR reaction system was prepared using the SYBR Green Premix Pro Taq HS qPCR Kit to quantitatively detect the expression level of piRNAs.
[0047] Example 2
[0048] Screening of piRNA molecules and construction of diagnostic models
[0049] 1. Screening of piRNA molecules
[0050] Serum samples from 6 endometrial cancer patients and 5 healthy subjects were selected for Small RNA sequencing. Total RNA was isolated using miRNeasy Mini Kit (50) (Qiagen, Germany) according to the manufacturer's procedure. The concentration and quality of RNA were determined using Qubit 2.0 Fluorometer (Life Technologies, USA) and Nanodrop One Spectrophotometer (Thermo Fisher Scientific, USA). The integrity of RNA was detected using Agilent 2100 Bioanalyzer (Agilent Technologies, USA), and samples with RNA integrity number (RIN) values greater than 7.0 were sequenced.
[0051] According to the TruSeq™ RNA sample preparation guide, the QIAseq miRNA library kit (Qaigen, Germany) was used to synthesize paired-end libraries. The products were then purified and PCR enriched to establish the final cDNA library. The purified library was quantified using a Qubit® 2.0 fluorometer (Life Technologies, USA) and verified using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) to determine the insert size and calculate the molar concentration. The library was diluted to 10 pM by cBot to generate Cluster, and then small RNA sequencing was performed on an Illumina Hiseq Xten (Illumina, USA) according to the supplier's recommended procedures. Library construction and sequencing were completed by Shanghai Zhongke Genomics Co., Ltd., China.
[0052] CLC genomics_workbench 5.5 was used to map the reads of each sequencing sample to piRbank to calculate the expression level (count) of piRNA. The abundance of piRNA was expressed by TPM (transcripts per million). The differentially expressed candidate piRNAs were screened with |log2 (foldchange)|>2 and p value <0.05, FDR <0.05 and relative expression >0.
[0053] After screening, 14 piRNAs were obtained, of which 4 were downregulated and 10 were upregulated.
[0054] Table 1 is a list of 14 piRNAs sequences
[0055] .
[0056] Design specific fluorescent quantitative PCR primers for piRNAs markers; in this example, MiRNeasy MicroKit (QIAGEN Cat#: 217084, Germany) was used to isolate total exosome RNA, and the exosome samples were processed according to the manufacturer's instructions. The extracted RNA was then resuspended in 16 µl of nuclease-free water, and its concentration and quality were assessed using a NanoDrop spectrophotometer (ThermoFisher Scientific, Lafayette, USA). Real-time fluorescent quantitative PCR (qRT-PCR) was used to detect the expression level of serum exosome piRNAs. 4.5 µl of template RNA was used to synthesize cDNA, and the reaction volume was 10 µl. AG11707, China). In addition, qPCR detection was performed using SYBR Green Premix Pro Taq HS qPCR Kit (CatNo. 1). CFX96 Real-time Detection System (BioRad Laboratories, USA) PiRNA primers were customized by genepharma (Shanghai, China), and each qRT-PCR experiment was repeated 3 times. The piRNA expression levels were normalized to U6, and the relative fold changes were assessed based on the threshold cycle (Ct) values using the − ΔCt method. The sequences of each miRNA were verified in piRNAdb (https: / / www.pirnadb.org).
[0057] The PCR primer sequence is the sequence of the reagent used for PCR detection. The primer sequence is customized according to the RNA sequence. See the table below:
[0058] Table 2 PCR primer sequences
[0059]
[0060] .
[0061] Serum samples from 24 patients with endometrial cancer and 24 healthy controls were selected for exosomal total RNA isolation using MiRNeasy MicroKit (QIAGEN Cat#: 217084, Germany), and exosome samples were processed according to the manufacturer's instructions. The extracted RNA was then resuspended in 16 µl of nuclease-free water, and its concentration and quality were assessed using a NanoDrop spectrophotometer (ThermoFisher Scientific, Lafayette, USA). Real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expression level of serum exosomal piRNAs. 4.5 µl of template RNA was used to synthesize cDNA, and the reaction system was 10 µl (AG11707, China). In addition, qPCR detection was performed using the SYBR Green Premix Pro Taq HS qPCR Kit (CatNo. 1). PiRNA primers were customized by genepharma (Shanghai, China), and each qRT-PCR experiment was repeated 3 times. The piRNA expression levels were normalized to U6, and the relative fold changes were evaluated according to the threshold cycle (Ct) value using the -ΔCt method. The piRNAs screened in step (2) were validated, and serum exosomal piRNA molecules associated with endometrial cancer were further screened.
[0062] In this step, exosomal piRNAs were extracted from 24 EC patients and 24 healthy controls, and the sequencing results were verified by qRT-PCR; 3 piRNAs (hsa_piR_009947, hsa_piR_003805, and hsa_piR_009183) were downregulated in EC patients, and 3 piRNAs (hsa_piR_014592, hsa_piR_006767, and hsa_piR_019179) were upregulated, which was consistent with the sequencing results.
[0063] ROC curves were drawn to evaluate the sensitivity and specificity of the six candidate piRNAs in identifying 24 EC and 24 HC subjects. The expression of the six candidate piRNAs in 40 HC individuals and 68 EC patients was then further detected, and ROC curves were drawn. hsa_piR_009947, hsa_piR_003805, and hsa_piR_009183 were downregulated in the serum of EC patients, hsa_piR_014592 and hsa_piR_006767 were upregulated, and there was no statistically significant difference in hsa_piR_019179 between HC and EC patients.
[0064] Random forest algorithm, logistic regression analysis, Delong test and ROC curve were used to establish and screen 3piRNA_panel as a diagnostic model.
[0065] Example 3
[0066] Validation of diagnostic model’s diagnostic performance
[0067] The present invention constructs a model for the diagnosis of endometrial cancer by univariate logistic regression modeling, and the model formula is: logit(3piRNA_panel) = - 9.2038 + -1.6374 × hsa_piR_009183 + 1.7536 × hsa_piR_014592 + 1.0598 × hsa_piR_006767. The above model uses the relative expression of hsa_piR_014592, hsa_piR_009183, and hsa_piR_006767piRNAs. The ROC curves of the training set and the validation set are drawn.
[0068] The AUC of 3piRNA_panel for distinguishing endometrial cancer patients from healthy controls was 0.942 (95%CI=0.909 ~ 0.982). Fig.11 When using this model to diagnose early endometrial cancer, it is necessary to first perform quantitative detection on hsa_piR_014592, hsa_piR_009183, and hsa_piR_006767 in the sample. After obtaining the relative expression, substitute it into the model for calculation. If the calculated value is higher than the cutoff value, the diagnosis result is positive, that is, early endometrial cancer. If it is lower than the cutoff value, the diagnosis result is negative, not early endometrial cancer.
[0069] The AUC of 3piRNA_panel for distinguishing HC individuals from stage I EC patients was 0.974 (0.955-0.993). Figure 14-15 As shown in Figure 3, the AUC of 3piRNA_panel for distinguishing HC individuals from stage Ia EC patients was 0.977 (0.959-0.996). Fig.16 A in Fig.16 As shown in B.
[0070] 3The diagnostic efficiency of piRNA_panel for EC and Ia EC is significantly higher than that of CA125. Fig.16 As shown in C.
Claims
1. Use of a reagent for detecting piRNA molecular markers derived from serum exosomes in the preparation of a diagnostic product for endometrial cancer, characterized in that: The piRNA molecular markers for endometrial cancer are hsa_piR_009183, hsa_piR_014592 and hsa_piR_006767, and their nucleotide sequences are shown in SEQ ID NO.1, SEQ ID NO.2 and SEQ ID NO.3.