Microflora marker for predicting tumor cell generation and metastasis risk and treating tumor and application product thereof
By screening microorganisms unique to healthy and tumor tissues and making kit products, the accuracy of tumor cell detection and prediction is solved, early diagnosis and personalized treatment of tumors are achieved, and the accuracy of predicting tumor cell occurrence and metastasis risks is improved.
Patent Information
- Application Number
- CN202410133677.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-26
- Publication Date
- 2025-07-29
AI Technical Summary
The prior art is difficult to detect and predict the risk of tumor cells quickly and accurately, and there is a lack of effective tumor treatment methods.
By screening microorganisms unique to healthy and tumor tissues, using richness-distribution indicators and random tests, specific microorganisms are screened as detection targets and treatment methods, and kit products are made for detection and treatment of tumor cells.
Early detection and personalized treatment of tumor cells are achieved, the accuracy of predicting tumor cell occurrence and metastasis risks is improved, and auxiliary means for early diagnosis and personalized treatment of tumors are provided.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of microorganisms. In particular, it has invented microbial flora markers for predicting the occurrence and metastasis risks of tumor cells and products for their application, and a method for treating tumors. One type of microorganisms unique to tumor cell tissues is used to predict the occurrence and metastasis risks of tumor cells, and another type of microorganisms unique to healthy tissues is used to treat tumors. Through strict statistical tests, the present invention has screened microorganisms unique to healthy cell tissues and tumor cell tissues, including archaea, bacteria, and viruses, and used them as markers for tumor cell tissues and the core method for treating tumors. Through a product kit with such special microorganisms as the detection target, the occurrence and metastasis risks of tumor cells are predicted, and the microorganisms unique to healthy tissues are used as a treatment means for tumor cells. Background Art
[0002] More than a hundred years ago, microorganisms were detected in tumor tissues. However, due to the low abundance of microorganisms in tumor tissues, the description and research of such microorganisms have been restricted in various ways. Whether there is a causal relationship between microorganisms in tumor tissues and the occurrence of tumors is still undetermined. Existing research shows that microorganisms in tumor tissues have tumor tissue type specificity, that is, some bacteria are enriched in certain tumor tissues, which may be related to the special metabolic functions of tumor tissue cells. And by using the method of machine learning, some microorganisms unique to tumor tissues or blood can be screened out.
[0003] The determination of microorganisms unique to tumor tissues and enriched microorganisms in existing research mainly relies on "wet experiments" (WetLab) (non-computational means) and high-throughput sequencing to determine the types and abundances of microorganisms. Moreover, the definition of "enriched" and "unique" microorganisms by machine learning also mainly depends on the relative abundances of the detected microorganisms. The inventors of the present invention have redefined the "enriched" and "unique" microbial species in tumor tissues by comprehensively applying the relative abundances and occurrence frequencies of microorganisms, applying the "specificity" index, and strict statistical tests (random tests). This method eliminates the influence of sample differences on the results, comprehensively considers the relative abundances and frequencies of microorganisms, and the screening results are more reliable. By using the specificity of cell tissue microorganisms, the diffusion of tumor tissue cells can be detected. Once the tumor tissue cells spread, it indicates the further deterioration of the tumor disease. However, the current means for rapidly detecting the metastasis of tumor tissue cells are still insufficient or immature. By using the microorganisms enriched in and unique to tumor tissue cells as detection targets for specific tumor tissue cells, and using a kit product for detecting such microorganisms, the metastasis of tumor tissue cells can be diagnosed and detected. In addition, some microorganisms unique to healthy tissues are lost during the carcinogenesis of tumor cells, and these microorganisms may play a key role in tumor treatment. Summary of the Invention
[0004] The object of the present invention is to: The object of the present invention is to apply the specific microbial species of various healthy tissues and tumor tissue cells screened out as the target for predicting the occurrence or metastasis risk of tumor tissue cells and the core method for treating tumors, and apply it to related products to detect the occurrence or metastasis of tumor tissue cells and treat tumors, so as to provide technical support for the personalized diagnosis and treatment of tumor diseases. The flora and method of the present invention are applicable to a variety of tumor diseases.
[0005] To achieve the above object, the technical solution adopted by the present invention is as follows: (1) The present invention studied a total of 18,116 samples of 33 tumor diseases, including tumor tissue samples, blood samples and samples of healthy control tissues. The method of combining the richness-distribution index and random test proposed by the inventor of the present invention was used to calculate the richness-distribution index of each microorganism in the sample, and strict statistical tests (random tests) were carried out to exclude the influence of sample individual differences on the results. Microorganisms specific to healthy tissues and tumor tissues were screened (p < 0.05, after FDR correction), and the microorganisms specific to each type of tumor tissue and the microorganisms specific to healthy tissues are listed in claim 1. These microorganisms can be used as detection targets for predicting the occurrence and metastasis risk of tumor cells and can be used as a key means for tumor treatment. The inventor adopted strict statistical tests and carried out false positive correction. The microorganisms specific to tumor tissues screened out have high accuracy in detecting the occurrence or metastasis of cancer cells; the microorganisms specific to healthy tissues play a key role in the treatment of tumor diseases. (2) Collect the tissue to be tested of the subject, and use products such as the kit of the microbial marker specific to tumor tissue to test the tissue to be tested. If the test is positive, it indicates that the tissue may have canceration or will have canceration. (3) The reagents required for the implementation mode of the present invention include at least one of metagenomic sequencing reagents, 16S rRNA amplicon sequencing reagents, droplet digital PCR detection reagents, and qPCR quantitative detection reagents. The products of the present invention will detect all sequences or any part of all sequences or their barcode marker sequences of the specific species. Using the microorganisms specific to tumor tissues screened out as the detection target, at least one of the above methods is used to determine whether there is one or several types of microbial markers in the tumor tissue. (4) The focus of the present invention is the microorganisms specific to various tumor tissues screened out and the microorganisms specific to healthy tissues relative to tumor tissues. The microorganisms specific to tumor tissues are used as targets to predict the occurrence and metastasis risk of tumor cells. And corresponding kit products are made to detect whether there is one or several types of microbial markers specific to tumor tissues in the tissue to be tested. Using the microorganisms specific to healthy tissues relative to tumor tissues as the core means of the tumor treatment plan. (5) The present invention uses specific microbial markers to detect the occurrence or metastasis of tumor cells, without being limited to the measurement methods and means of microbial markers, as long as it can detect whether one or several types of microbial markers unique to tumor tissues exist in the tissue to be tested. (6) The present invention uses the microorganisms unique to healthy tissues as the core method for treating tumors, without being limited to the ways of treating tumors, as long as one or several species of microorganisms unique to healthy tissues are used as the core means of treatment. (7) The present invention can detect whether the cells in the initial stage (stage I or II) of tumors have metastasized, can detect whether the tumor cells have metastasized and spread before the cells undergo significant carcinogenesis, and can predict the occurrence of carcinogenesis when the cells have not yet undergone carcinogenesis or are in the initial stage of carcinogenesis. (8) The microorganisms unique to healthy tissues screened by the present invention can be used as a means for treating tumor diseases by changing the metabolic mode of specific tumor cells or any other method. This includes any drugs, health products, probiotics, medical devices, etc. that use this as the core to treat tumors.
[0006] The effects of the present invention are as follows: A class of microbial markers for predicting the occurrence and metastasis risks of tumor cells and their application products for treating tumors are invented. By detecting the microorganisms unique to tumor cell tissues, the occurrence and metastasis of tumor cells can be predicted or detected before the tumor occurs, in the early stage of its occurrence, and in subsequent stages. This product can be used as an auxiliary detection means for early tumor diagnosis and personalized precision treatment. By screening out the microorganisms unique to healthy tissues compared to tumor tissues, it is used as a method for treating tumor diseases. The products of the present invention can be used for a variety of tumor diseases. Detailed implementation manners
[0007] To better illustrate the technical solutions and advantages of the present invention, the present invention will be further described below in conjunction with a specific analysis process.
[0008] The inventor of the present invention collected a total of 18,116 samples of 33 types of tumor diseases from the database. These samples include tumor tissue samples, blood samples, and samples of healthy control tissues. The specificity index of each species is calculated using the richness-distribution index: represents the extent of the distribution of the i-th species in tumor tissues, represents the relative abundance of the i-th species in tumor tissues among all samples. The richness-distribution index comprehensively evaluates the species by combining the distribution frequency and relative abundance of the species in tumor tissues.
[0009] Randomly test the richness-distribution index of each microorganism in healthy tissues and tumor tissues, exclude the influence of individual factors on the results, and screen out the microorganisms unique to each type of tumor tissue (p < 0.05, after FDR correction). The microorganisms unique to each type of tumor tissue and the microorganisms unique to healthy tissues relative to tumor tissues are listed in claim 1. The random test is carried out through the following steps: S1: Calculate the richness-distribution index of each species in healthy tissues and tumor tissues respectively, and calculate the absolute value Δ of the difference in the richness-distribution index of each species between healthy tissues and tumor tissues; S2: Mix the samples of healthy tissues and tumor tissues, and randomly divide them into two groups A' and B'. Calculate the richness-distribution index of each species in the two groups of samples A' and B', and calculate the absolute value Δ' of the difference in the richness-distribution index of each species between A' and B'; S3: Repeat step S2 1000 times to obtain 1000 Δ'; S4: According to the formula p = n / 1000, calculate the p-value of each species, where n represents the number of the 1000 Δ' in S3 that are greater than Δ; S5: The species unique to healthy tissues need to meet the conditions: p < 0.05, the richness-distribution index in healthy tissues is not equal to 0, and the richness-distribution index in tumor tissues is equal to 0; S6: The species unique to tumor tissues need to meet the conditions: p < 0.05, the richness-distribution index in tumor tissues is not equal to 0, and the richness-distribution index in healthy tissues is equal to 0; S7: The dominant species in healthy tissues (species with a significantly increased richness-distribution index relative to tumor tissues) need to meet the conditions: p < 0.05, the richness-distribution indices in healthy tissues and B are not equal to 0, and the richness-distribution index in healthy tissues is greater than that in tumor tissues; S8: The dominant species in tumor tissues (species with a significantly increased richness-distribution index relative to healthy tissues) need to meet the conditions: p < 0.05, the richness-distribution indices in healthy tissues and B are not equal to 0, and the richness-distribution index in tumor tissues is greater than that in healthy tissues;
[0010] According to the above steps, we have screened out the species unique to various tumor cells, enriched species, species unique to healthy tissues, and enriched species. The list of species unique to various tumors is as follows: The microorganisms unique to each type of healthy tissue relative to tumor tissue are as follows:
Claims
1. A microbial flora marker for predicting the risk of occurrence and metastasis of tumor cells and treating tumors, and an application product thereof, characterized in that The signature microorganisms are the microorganisms unique to tumor cell tissues and healthy tissues respectively. One type of tumor-specific microorganisms is used to predict the risk of tumor cell occurrence and metastasis, and another type of microorganisms unique to healthy tissues compared to tumor tissues is used to treat tumors. Each type of tumor tissue-specific microorganisms is as follows: Each type of microorganisms unique to healthy tissues compared to tumor tissues is as follows:
2. The product according to claim 1, wherein The types of signature microorganisms of the tumor tissues and healthy tissues include one or several of archaea, bacteria, and viruses.
3. The product according to claim 1, wherein The signature microorganisms are a combination of one or several of them or all the microorganisms.
4. The product according to claim 1, and the types of tumors used to predict the risk of occurrence and metastasis are: Colon Adenocarcinoma, Head and Neck Squamous Cell Carcinoma, Kidney Renal Clear Cell Carcinoma, Kidney Renal Papillary Cell Carcinoma, Liver Hepatocellular Carcinoma, Lung Squamous Cell Carcinoma, Prostate Adenocarcinoma, Stomach Adenocarcinoma, Thyroid Carcinoma; the types of tumors that can be treated are: Breast Invasive Carcinoma, Head and Neck Squamous Cell Carcinoma, Kidney Renal Clear Cell Carcinoma, Prostate Adenocarcinoma, Uveal Melanoma, Esophageal Carcinoma, Colon Adenocarcinoma, Stomach Adenocarcinoma.
5. The product according to claim 1, characterized in that A product using all the gene sequences of the signature microorganisms unique to tumor tissues, any part of all the sequences, or the characteristic barcode sequences as detection targets.
6. The product according to claim 1, wherein The application of signature microorganisms in the preparation of kits and sub-products for detecting the occurrence or metastasis of tumor cells.
7. The product according to claim 1, wherein Software, hardware, and firmware products that use tumor tissue-specific microorganisms as detection targets to predict the risk of tumor cell occurrence and metastasis.
8. The product according to claim 1, characterized in that Used to predict the risk of occurrence or metastasis of tumor cells at all stages of one or more tumors.
9. The product according to claim 1, characterized in that Using the entire gene sequence of a healthy tissue - marked microorganism, any part of the entire sequence, or a characteristic barcode sequence as a product for treating tumor diseases.
10. The product according to claim 1, characterized in that Preparing tumor - treating drugs, foods, and probiotic products using one or more bacterial communities of a specific species in healthy tissues.
11. The product according to claim 1, wherein Software and hardware products using one or more bacterial communities of specific microbial species in healthy tissues as a treatment means.
12. The product according to claim 1, characterized in that For the treatment of all stages of one or more tumor diseases.