Biomarker for diagnosing renal clear cell carcinoma and application thereof

Abstract

The invention provides a biomarker for diagnosing renal clear cell carcinoma and application of the biomarker, and relates to the technical field of biomedical diagnosis. The biomarker for diagnosing the renal clear cell carcinoma is characterized in that the biomarker is plasma CHMP1A protein. The plasma protein CHMP1A is used as the marker for early diagnosis of the renal clear cell carcinoma, firstly, the detection method is simple and rapid, conventional detection methods such as ELISA (enzyme-linked immunosorbent assay) and the like can be adopted, and the kit is easy to popularize and apply clinically; secondly, the non-invasive property is realized, only the plasma sample needs to be collected, and the invasive operation of histopathology examination is avoided; and 3, the specificity and the sensitivity are relatively high.

Description

Technical Field

[0001] The present invention relates to the field of biomedical diagnostic technologies, and particularly to a biomarker for diagnosing renal clear cell carcinoma and its applications. Background Art

[0002] Renal clear cell carcinoma is the most common type of renal cancer, accounting for about 70%-80% of all renal cancer cases. Its early symptoms are hidden, and most patients are diagnosed at the middle or advanced stage, missing the best treatment opportunity, resulting in a relatively low five-year survival rate. Currently, the diagnosis of renal clear cell carcinoma mainly relies on imaging examinations (such as CT, MRI, etc.) and histopathological examinations, but these methods have certain limitations in early diagnosis. The detection rate of imaging examinations for small tumors is not high, while histopathological examinations require obtaining tissue samples through surgery or puncture, which is invasive and cannot achieve early screening. Therefore, developing a method that can diagnose renal clear cell carcinoma early and accurately has important clinical significance.

[0003] In recent years, more and more studies have focused on finding biomarkers that can diagnose renal clear cell carcinoma early. Some studies have found some potential biomarkers, such as certain proteins in urine, circulating tumor cells in blood, etc., but these biomarkers still have certain deficiencies in terms of specificity and sensitivity and cannot meet the clinical needs. For example, some studies have found that the expression levels of certain proteins in urine are related to the occurrence of renal clear cell carcinoma, but these proteins may also show abnormal expression in other kidney diseases, resulting in insufficient specificity. In addition, the detection technology for circulating tumor cells is complex, and the number of circulating tumor cells in early tumors is small, making it difficult to detect.

[0004] Currently, the methods for early diagnosis of renal clear cell carcinoma mainly include the following several:

[0005] 1. Imaging examinations: Through imaging technologies such as CT and MRI, using the differences in the absorption of rays or the response to magnetic fields by different tissues, images of renal clear cell carcinoma are generated to discover information such as the location, size, and shape of the tumor. The detection rate for small tumors is not high, and it cannot provide molecular characteristic information of the tumor, making it difficult to achieve early screening.

[0006] 2. Circulating tumor cells (CTCs): CTCs are cancer cells that naturally detach from primary or metastatic tumors and enter the peripheral blood. Through antibody-mediated or size-based methods, CTCs are isolated and detected from the blood to assist in the diagnosis of renal clear cell carcinoma. However, the content of CTCs in the blood is extremely low, making it difficult to detect, and currently, there is a lack of standardized detection methods.

[0007] 3. Circulating tumor DNA (ctDNA): ctDNA is the DNA fragment released from tumor cells into the blood, containing information such as specific gene mutations and methylation of tumors. However, the content of ctDNA in the blood is low and it is mixed with cell-free DNA (cfDNA), which needs to be distinguished by tumor-specific genomic alterations, increasing the complexity of detection. In addition, the detection cost of ctDNA is high, limiting its wide application in clinical practice.

[0008] 4. Circulating RNA: cfRNA is the RNA molecule released from tumor cells into the blood, including microRNA (miRNA), long non-coding RNA (lncRNA), circular RNA (circRNA), etc. There are differences in the expression levels and types between tumor patients and healthy individuals. cfRNA has poor stability in the blood, is easily affected by degradation, and the standardization and automation levels of detection methods are not high.

[0009] 5. Detection of extracellular vesicles (exosomes): Exosomes are vesicles secreted by cells and rich in various substances (such as DNA, miRNA, mRNA, proteins, etc.). The components in exosomes are separated and detected by methods such as ultracentrifugation and microfluidic chips to obtain relevant information about tumors. Currently, there is a lack of standardized separation methods, and there are significant differences in the purity and yield of exosomes obtained by different separation methods. At the same time, the complexity of the components in exosomes also increases the difficulty of detection and analysis.

[0010] 6. Proteomics: Some proteins are abnormally expressed in patients with clear cell renal cell carcinoma. The protein levels in blood or urine can be detected by methods such as enzyme-linked immunosorbent assay (ELISA) and immunoblotting to serve as diagnostic markers. The specificity and sensitivity of a single protein marker are limited, and protein detection is easily affected by factors such as sample processing and preservation, resulting in poor repeatability and stability of the results.

[0011] 7. Metabolomics: The metabolic pathways of tumor cells are different from those of normal cells and will produce some specific metabolites. By techniques such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS), the metabolites in urine or blood are detected to assist in the diagnosis of clear cell renal cell carcinoma. However, there are a large number of metabolites, and they are affected by various factors such as diet and drugs, with relatively low specificity and sensitivity. In addition, metabolite detection requires complex sample pretreatment and data analysis, limiting its clinical application.

[0012] 8. Lack of evidence of causal association for existing markers: Existing markers are mostly based on correlation studies and have not verified the causal relationship through Mendelian randomization.

[0013] In summary, the current imaging examinations have a low detection rate for small lesions and cannot achieve early screening. Although liquid biopsy technology has the advantages of being non-invasive and allowing repeated sampling, it still faces some challenges in the early diagnosis of clear cell renal cell carcinoma. First, the detection methods for various liquid biopsy markers need to be further optimized and standardized to improve the accuracy and reliability of detection. Second, the cost of liquid biopsy technology is relatively high, which limits its application in large-scale population screening. In addition, the specificity and sensitivity of liquid biopsy markers still need to be improved, and new markers need to be further explored and verified to meet the needs of early diagnosis of clear cell renal cell carcinoma. Summary of the Invention

[0014] To solve the technical problems existing in the prior art, an embodiment of the present invention provides a biomarker for diagnosing clear cell renal cell carcinoma and its application. The technical solution is as follows:

[0015] A biomarker for diagnosing clear cell renal cell carcinoma, wherein the biomarker is plasma CHMP1A protein.

[0016] Use of plasma CHMP1A protein in the preparation of a product for diagnosing clear cell renal cell carcinoma, wherein the plasma CHMP1A protein is used as a biomarker in the preparation of a product for diagnosing clear cell renal cell carcinoma.

[0017] Optionally, the product for diagnosing clear cell renal cell carcinoma is a kit for diagnosing clear cell renal cell carcinoma,

[0018] and / or, the test sample of the product for diagnosing clear cell renal cell carcinoma is a blood sample.

[0019] Use of a reagent for detecting the content of plasma CHMP1A protein in the preparation of a product for diagnosing clear cell renal cell carcinoma.

[0020] Optionally, the product for diagnosing clear cell renal cell carcinoma is a kit for diagnosing clear cell renal cell carcinoma,

[0021] and / or, the test sample of the product for diagnosing clear cell renal cell carcinoma is a blood sample.

[0022] A product for diagnosing clear cell renal cell carcinoma, the product comprising a reagent, a kit and / or a detection device for detecting the content of plasma CHMP1A protein in a test sample.

[0023] Optionally, the product for diagnosing clear cell renal cell carcinoma is a kit for diagnosing clear cell renal cell carcinoma, and the kit comprises:

[0024] (i)A reagent for detecting the content of plasma CHMP1A protein in a test sample;

[0025] (ii)Optionally, at least one substance selected from the following group: container packaging and / or instructions,

[0026] wherein, the method of using the kit includes: determining the content of plasma CHMP1A protein in the sample.

[0027] The beneficial effects brought by the technical solutions provided by the embodiments of the present invention at least include:

[0028] The present invention first discovers the causal association between CHMP1A and clear cell renal cell carcinoma through Mendelian randomization analysis (p < 0.001), and verifies the sensitivity and specificity of the detection in 86 plasma samples (43 of which are patients with clear cell renal cell carcinoma diagnosed pathologically and 43 are normal healthy people). It is found that the sensitivity of plasma protein CHMP1A is 0.93, the specificity is 0.93, and the AUC for diagnosing clear cell renal cell carcinoma is 0.97, which is significantly better than the prior art.

[0029] The present invention has the following advantages in verifying the causal relationship through Mendelian randomization: In traditional observational studies, plasma protein levels may be affected by various factors, such as lifestyle, environmental factors, etc. These confounding factors may lead to biases in the results. Mendelian randomization analysis uses genetic variations as instrumental variables. These genetic factors are determined at birth and remain stable throughout an individual's life, not affected by acquired confounding factors. Therefore, through Mendelian randomization analysis, the interference of confounding factors on the judgment of causal relationships can be effectively avoided, thereby more accurately evaluating the causal relationship between plasma proteins and clear cell renal cell carcinoma. In addition, with the continuous development of genome-wide association studies (GWAS), a large amount of genetic data resources have been made public. These data provide a rich source of instrumental variables for Mendelian randomization analysis, enabling researchers to more comprehensively evaluate the causal relationship between plasma proteins and clear cell renal cell carcinoma. By integrating these publicly available genetic data, the efficiency and statistical power of the research can be improved.

[0030] The present invention uses plasma protein CHMP1A as a biomarker for the early diagnosis of clear cell renal cell carcinoma, and has the following beneficial effects: First, the detection method is simple and fast, and conventional detection methods such as ELISA can be used, which is easy to be popularized and applied clinically; second, it is non-invasive, only requiring the collection of plasma samples, avoiding the invasive operation of histopathological examination; third, it has relatively high specificity and sensitivity. Through the verification of 86 human plasma samples in the early stage, it can accurately distinguish patients with clear cell renal cell carcinoma and healthy people, providing a more reliable basis for early diagnosis.

[0031] The clear cell renal cell carcinoma diagnosis product and kit based on the detection of the content of CHMP1A protein in plasma of the present invention achieve non-invasive and highly sensitive tumor screening through biomarkers. Brief Description of the Drawings

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0033] Figure 1 It is a causal association diagram of rQTLs analysis of PPR and clear cell renal cell carcinoma provided in Embodiment 1 of the present invention;

[0034] Figures 2A to 2D It is a Mendelian randomization sensitivity analysis diagram of CD84.CDKN1A in FinnGen data provided in Embodiment 1 of the present invention (verify whether it is accurate); among them, Figure 2A It is a scatter plot of MR analysis, Figure 2B It is a forest plot of single SNP analysis, Figure 2C It is a funnel plot of Funnel analysis, Figure 2D It is a forest plot of Leave-one-out analysis;

[0035] Figure 3 It is a multivariable Mendelian randomization analysis and Lasso regression diagram provided in Embodiment 1 of the present invention;

[0036] Figure 4 It is an ROC curve diagram of CHMP1A provided in Embodiment 2 of the present invention;

[0037] Figure 5 It is an ROC curve diagram of SNAP29 provided in Embodiment 2 of the present invention. Specific embodiments

[0038] The following will describe the technical solutions in the present invention with reference to the drawings.

[0039] The present invention aims to solve the deficiencies in the existing early diagnosis technology for clear cell renal cell carcinoma, and provides an early diagnosis product based on the content of plasma protein CHMP1A to improve the specificity and sensitivity of diagnosis and achieve the purpose of non-invasive and early screening of clear cell renal cell carcinoma.

[0040] In this study, through three large-scale human GWAS datasets, using the MR method, the FinnGen clear cell renal cell carcinoma (ccRCC) data was used as the discovery set, and the META-analysis data of two ccRCCs, GCST90320055 and GCST90320058, was used as the validation set to preliminarily explore the causal relationship between the levels of 2,821 plasma protein ratios and the incidence of ccRCC. The inverse-variance weighted (IVW) method was used as the standard to judge whether there was a causal relationship. Steiger filtering analysis and reverse MR were used to judge whether there was a reverse causal relationship. Cochran's Q test was used to evaluate the heterogeneity among instrumental variables (IVs). P>0.05 indicated low heterogeneity, that is, the estimated values of each instrumental variable were randomly distributed, with little impact on the inverse-variance weighted (IVW) results. MR-Egger regression and the IVW method were used to explore the presence of horizontal pleiotropy. To further narrow down the research scope, the inventors used multivariable MR analysis and variable screening through Lassco regression to obtain the most stable protein ratio, CHMP1A / SNAP29. Finally, the diagnostic application value of CHMP1A and SNAP29 in ccRCC was verified in human plasma samples. It was ultimately found that the plasma protein CHMP1A had the highest diagnostic efficiency for diagnosing ccRCC and could be used as an early diagnostic marker for ccRCC.

[0041] In all MR analyses, three basic assumptions must be strictly adhered to: First, the selected genetic instruments must show a robust association with the exposure factor; second, they must be unaffected by confounding variables; third, their effect on the outcome must be mediated entirely by the specified exposure factor.

[0042] Example 1

[0043] 1. Data source

[0044] In this study, the genetic data of plasma protein ratios (PPRs) were derived from a recent genome-wide association study (GWAS), in which researchers used Olink proteomics data from 52,705 samples provided by the UK Biobank to identify genetic association loci (rQTLs) related to 2,821 PPRs [PMID: 38412862]. GWAS summary data genetically related to clear cell renal cell carcinoma were from the Finnish database FinnGen (release R11, 1,354 cases and 345,118 controls), the GWAS database (GCST90320055, 16,321 cases and 835,670 controls) (PMID 38671320), and the GWAS Catalog database (GCST90320058, 11,176 cases and 738,462 controls) (PMID 38671320). See Table 1 for details. The website was accessed on October 28, 2024. All the data used in this study are publicly available summary data and do not require submission to an ethics committee for approval.

[0045] Table 1 Data sources

[0046]

[0047] 2. Conditions for instrumental variables

[0048] This Mendelian randomization (MR) study selected single nucleotide polymorphisms (SNPs) as instrumental variables (IVs). The IVs in this study needed to meet the following criteria: (1) First, a genome-wide screening of SNPs was performed to evaluate their significant causal associations with plasma protein ratios and clear cell renal cell carcinoma (P < 5×10 -8 ); (2) SNPs with a minor allele frequency (MAF) > 0.01 were screened; (3) According to the conditions of R² < 0.001 and window size = 10,000 kb, the IVs were screened to exclude linkage disequilibrium (LD) among SNPs; (4) When the selected IVs were missing in the summary result data, SNPs with high LD (R 2 > 0.8 and within 250 kb) with the IVs were searched for as alternative SNPs to replace the existing IVs; (5) The F value of each SNP in the IVs was calculated to evaluate the strength of the IVs, so as to exclude potential weak instrument bias between the IV and the exposure factor. The calculation formula is F = R 2 × (N - 2) / (1 - R 2 ), where R 2Indicates the proportion of SNPs in the IV that explain the exposure variation. The F value is required to be >10; (6) The p-value of the exposure instrumental variable SNP must be less than the p-value of the outcome SNP.

[0049] 3. MR analysis of plasma protein ratio and clear cell renal cell carcinoma

[0050] The present inventors used the "TwoSampleMR" package (version 0.6.8) in R language (version 4.3.2) to perform MR analysis to evaluate the causal relationship between protein ratio and clear cell renal cell carcinoma.

[0051] To evaluate the causal relationship between plasma protein ratio and the risk of clear cell renal cell carcinoma, the present inventors used the Mendelian randomization (MR) method for analysis, mainly using inverse variance weighting (IVW) for evaluation. The specific implementation steps of the inverse variance weighting method can be found in the literature [PMID: 37996402]. The estimated results of the causal effect are expressed as the odds ratio (OR) of clear cell renal cell carcinoma risk corresponding to each one standard deviation (SD) increase in the plasma protein ratio level. Cochran's Q test was used for heterogeneity testing, and MR-Egger regression and IVW were used for pleiotropy testing. If heterogeneity or pleiotropy occurred, to evaluate the reliability of the results, the present inventors performed a series of sensitivity analyses on the results with heterogeneity or pleiotropy, including: (1) using multiple MR methods including egger regression, egger regression bootstrap, weighted median mode, simple mode, and weighted mode for evaluation; (2) performing sensitivity analysis using the Leave-one-out analysis method; (3) performing sensitivity analysis using the single SNP method; (4) using the funnel plot to judge whether the distribution of instrumental variables is balanced.

[0052] In addition, two analytical methods, Steiger filtering analysis and reverse MR, were used to judge whether there is reverse causality. Steiger filtering is based on the assumption that an effective instrumental variable (IV) should explain more of the variation in the exposure than in the outcome. If the test result is TRUE, it indicates that there is no reverse causality; if it is FALSE, it suggests the presence of reverse causality. In reverse MR analysis, if there is not enough IV to support the analysis, it means there is no reverse causality. P<0.05 is considered a statistically significant result.

[0053] 4. Multivariable MR analysis and lasso regression

[0054] To further screen for stable protein ratios with potential for clinical application, the inventors used multivariable Mendelian randomization (Multivariable MR) analysis and lasso regression for variable screening. Multivariable MR analysis simultaneously considers the combined effects of multiple protein ratios on the risk of clear cell renal cell carcinoma.

[0055] Experimental results

[0056] 1. Number of instrumental variables

[0057] After strict selection and matching, with 2821 plasma protein ratios as the exposure and clear cell renal cell carcinoma as the outcome. In FinnGen, the number of instrumental variables ranged from 3 to 43. In GCST90320055, the range of the number of instrumental variables was 2 - 43, while in GCST90320058, the range was 2 - 40. The F-statistics of all selected genetic instruments exceeded 10, emphasizing that this study can mitigate the bias caused by weak instrumental variables and increase the reliability of the MR analysis results.

[0058] 2. Relationship between plasma proteins and protein ratios and clear cell renal cell carcinoma

[0059] Using rQTLs as instrumental variables, a MR analysis was performed with clear cell renal cell carcinoma to analyze the causal association between PRR and clear cell renal cell carcinoma. The results are shown in Figure 1 . Results from the FinnGen dataset showed that there were a total of 108 plasma proteins and protein ratios with a causal relationship with the risk of clear cell renal cell carcinoma, while in GCST90320055, there were 143 plasma proteins and protein ratios with a causal relationship. The analysis results of GCST90320058 showed that there were 165 plasma proteins and protein ratios with a causal relationship. Notably, 13 plasma proteins and protein ratios showed a causal relationship with the risk of clear cell renal cell carcinoma in all three populations.

[0060] Steiger direction test analysis all indicated that these 13 protein ratios had no reverse causal relationship with clear cell renal cell carcinoma. The specific results are shown in Table 2.

[0061] Table 2 Results of the directional test in Mendelian randomization analysis

[0062]

[0063] As shown in Table 3, for every 1 standard deviation increase in the gene-predicted plasma protein-to-protein ratio in the FinnGen data, there corresponded different risks of clear cell renal cell carcinoma, ranging from 0.53 (95% CI: 0.33, 0.85) for the CHMP1A / EIF4B protein level ratio to 1.28 (95% CI: 1.02, 1.61) for the CDKN1A / FOXO1 protein level ratio. As Figure 1 shown in Table 3 and in the other two validation studies, all 13 plasma protein-to-protein ratios showed an association in the same direction with the risk of clear cell renal cell carcinoma, which was consistent with the observations in the FinnGen study.

[0064] Table 3 Results of Mendelian randomization analysis of 13 plasma protein ratios

[0065]

[0066] Although heterogeneity and pleiotropy analyses showed that some of the 13 protein ratios had heterogeneity or pleiotropy in the MR results of the 3 datasets, the inventors used multiple MR methods to perform sensitivity analyses on the results with heterogeneity or pleiotropy. As Figures 2A to 2D shown, in the FinnGen dataset, CD84.CDKN1A showed heterogeneity. The single SNP showed that 2 significant SNPs were consistent with the IVW results, and the others were not significant. IVW was consistent with 4 other methods and opposite to simple mode. Leave one out showed that there were no individual SNPs with a very large impact, and most supported this causal relationship. The funnel plot also did not show any particular imbalance. Therefore, the causal relationship between CD84.CDKN1A and clear cell renal cell carcinoma is somewhat reliable. In summary, most plasma protein ratios are causally associated with clear cell renal cell carcinoma.

[0067] 3. Multivariable MR analysis

[0068] In the three datasets of FinnGen, GCST90320055, and GCST90320058, the inventors performed multivariable MR analysis on these 13 protein ratios and screened variables by the lasso regression method. As Figure 3 shown, in the FinnGen data, which was used as the discovery dataset, only 4 protein ratios were retained, and only 2 were significant (CD84.CDKN1A, CHMP1A.SNAP29). Among them, CD84.CDKN1A was not significant in both GCST90320055 and GCST90320058, while CHMP1A.SNAP29 was retained in all three datasets, and p = 0.0269 in the GCST90320055 dataset.

[0069] Considering that CHMP1A.SNAP29 has a causal relationship with clear cell renal cell carcinoma in the previous analysis and there is no heterogeneity or pleiotropy, the present inventors selected CHMP1A.SNAP29 for subsequent experimental verification.

[0070] Example 2 Enzyme-linked immunosorbent assay (ELISA) of plasma CHMP1A and SNAP29

[0071] A total of 43 healthy controls and 43 plasma samples from patients with pathologically confirmed clear cell renal cell carcinoma were included in the study. The plasma samples of patients with clear cell renal cell carcinoma were all collected before surgery. The fasting venous blood of patients and healthy control individuals was collected into EDTA tubes, centrifuged at 3000×g for 10 minutes immediately after collection, and the supernatant was quickly placed in a -80°C refrigerator for storage to ensure protein stability. This study was approved by the Ethics Committee of Chinese PLA General Hospital (HZKY-PJ-2025-8). All participants signed informed consent forms before sample collection. The study followed the relevant regulations of the Helsinki Declaration to ensure the full protection of the privacy and rights of participants.

[0072] The expression levels of CHMP1A and SNAP29 in plasma were detected by enzyme-linked immunosorbent assay (ELISA). The kits were purchased from Reddot Biotech, RD-CHMP1A-HU, Canada; Reddot Biotech, RD-SNAP29-HU, Canada, and the operation was carried out strictly according to the kit instructions. The receiver operating characteristic curve (ROC curve) was used to analyze the diagnostic efficacy of the plasma protein content of CHMP1A and SNAP29 for clear cell renal cell carcinoma, and the area under the curve (AUC), sensitivity, and specificity were calculated.

[0073] All data analyses were completed using R language (version 4.3.2). A P value less than 0.05 was considered statistically significant.

[0074] Experimental results

[0075] Detection of human plasma protein samples

[0076] First, 86 plasma samples were collected (43 of which were patients with pathologically diagnosed clear cell renal cell carcinoma and 43 were normal healthy people), and the protein expression levels of CHMP1A and SNAP29 were detected by ELISA method. The results are shown in Table 4.

[0077] Table 4 Measured values of plasma protein content

[0078]

[0079]

[0080] Calculate the ROC curve based on the results. The AUC value of CHMP1A for diagnosing clear cell renal cell carcinoma is 0.97, the sensitivity is 0.93, and the specificity is 0.93. For the specific results, see Figure 4 ; the AUC value of SNAP29 for diagnosing clear cell renal cell carcinoma is 0.70, the sensitivity is 0.698, and the specificity is 0.651. For the specific results, see Figure 5 . It can be seen from the above results that the plasma protein CHMP1A has excellent diagnostic efficacy for clear cell renal cell carcinoma.

[0081] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A biomarker for diagnosing renal clear cell carcinoma, characterized in that: The biomarker is plasma CHMP1A protein.

2. Use of plasma CHMP1A protein in the preparation of a product for diagnosing renal clear cell carcinoma, characterized in that: The plasma CHMP1A protein is used as a biomarker to prepare products for diagnosing renal clear cell carcinoma.

3. The use according to claim 2, characterized in that: The product for diagnosing renal clear cell carcinoma is a kit for diagnosing renal clear cell carcinoma. And / or, the test sample of the product for diagnosing renal clear cell carcinoma is a blood sample.

4. Use of a reagent for detecting the content of plasma CHMP1A protein in the preparation of a product for diagnosing renal clear cell carcinoma.

5. The use according to claim 4, characterized in that: The product for diagnosing renal clear cell carcinoma is a kit for diagnosing renal clear cell carcinoma. And / or, the test sample of the product for diagnosing renal clear cell carcinoma is a blood sample.

6. A product for diagnosing renal clear cell carcinoma, characterized in that: The product includes a reagent, a kit and / or a detection device for detecting the content of plasma CHMP1A protein in a sample.

7. The product according to claim 6, characterized in that The product for diagnosing renal clear cell carcinoma is a kit for diagnosing renal clear cell carcinoma, and the kit comprises: (i) a reagent for detecting the content of plasma CHMP1A protein in a sample; (ii) optionally, at least one substance selected from the group consisting of: container packaging and / or instructions, The method for using the kit includes: determining the content of plasma CHMP1A protein in the sample.

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