The invention discloses a multi-omicspathological analysis system and method for colorectal cancer liver metastasis risk prediction, and relates to the technical field of biomedicine and cancer diagnosis, the system comprises a data acquisition module, a data preprocessing module, a cell analysis module, a score construction module, a model construction and training module and a prediction and evaluation module; according to the method, multiple omics data including the single celldata set, the space transcriptome data, the batch RNA-seq data, the clinical data and the full slice image WSIs are integrated, comprehensive and accurate prediction of the colorectal cancer liver metastasis risk is achieved, cross-dimensional data fusion and analysis improve the prediction accuracy and reliability, and the risk of the colorectal cancer liver metastasis is reduced. The invention also provides a powerful tool for deeply exploring the molecular mechanism of tumorigenesis, development and metastasis, and particularly in a cell analysis module, cell subtypes and molecular characteristics closely related to liver metastasis can be disclosed by identifying and analyzing malignant cell subgroups LMTMCs triggering liver metastasis, so that the liver metastasis can be discovered. And a scientific basis is provided for formulating a personalized treatment scheme.
The invention discloses an intestinal cancermetastasis prediction method and device based on spatial omics, a medium and equipment, and the method comprises the steps: collecting original multi-omics data, and carrying out modal alignment and quality controlprocessing to obtain pre-processed multi-omics data comprising second spatial transcriptome data, second single-cellRNAsequencing data and second pathological image data; performing cross-modal semantic embedding on the second spatial transcriptome data based on the second single-cellRNAsequencing data to generate a spatial enhanced expression profile; performing multi-scale graph construction on the second spatial transcriptome data and the second pathological image data, and extracting spatial heterogeneity features; inputting the spatial enhancement expression spectrum and the spatial heterogeneity features into a pre-trained metastasis risk prediction model, and outputting a liver metastasis probability spatial heat map and a key driving feature list; and finally generating a clinical prediction report containing high-risk area positioning. According to the method, through dynamic optimization of spatial resolution and multi-scale feature collaborative modeling, the sensitivity of early transfer detection is remarkably improved.
Drug delivery nanoparticle compositions and methods for the treatment of a cancer are provided that can be used individually or in combination. These compositions and methods include: (1) exogenous vaccination using neoantigens or tumor-associated antigens to potentiate an anti-tumor immune response; (2) nanoparticle-based drug delivery targeting the liver, aimed at reprogramming the hepatic immune environment to reduce or eliminate tumor antigen tolerance, thereby enhancing the immune system's ability to combat metastatic cancer; and (3) expansion of the liver metastasis treatment platform to target tumor-associated lymphoid structures, supporting the immune response at the primary tumor site. Any of these methods may be optionally combined with chemo-immunotherapy for enhanced efficacy.
The application discloses a multi-omicspathological analysis system and method for predicting the risk of colorectal liver metastasis, relates to the technical field of biomedical and cancer diagnosis, and comprises a data acquisition module, a data preprocessing module, a cell analysis module, a score construction module, a model construction and training module and a prediction and evaluation module; the application realizes comprehensive and accurate prediction of the risk of colorectal liver metastasis by integrating multi-omics data, including single-cell data sets, spatial transcriptome data, batch RNA-seq data, clinical data and whole slide image WSIs; the cross-dimension data fusion and analysis not only improve the accuracy and reliability of prediction, but also provide a powerful tool for in-depth exploration of the molecular mechanism of tumor occurrence, development and metastasis, especially in the cell analysis module, identification and analysis of the malignant cell subpopulation LMTMCs triggering liver metastasis can reveal cell subtypes and molecular characteristics closely related to liver metastasis, thereby providing a scientific basis for formulating a personalized treatment plan.
PendingCN122445575AColorectal cancer cell lineOncology
The application belongs to the technical field of biotechnology, and particularly relates to a colorectal cancer high liver metastasiscell line and a preparation method and application thereof. The cell line was preserved in the China Center for Type Culture Collection on January 14, 2026, and the preservation number is CCTCC NO: C202618. The cell line is derived from a mouse colorectal cancer cell line MC38, and is constructed by lentivirustransfection to express luciferase stably, and is obtained by continuously performing at least five rounds of liver metastasis tumor orthotopic iteration screening in C57BL / 6 mice through rectal submucosal injection. The MC38-P06 cell line provided by the application has a significantly enhanced liver metastasis ability, a shorter MC38-P01 model time, a higher liver tumor load, and a shorter mouse survival period, and can be used for screening and evaluating anti-liver metastasis drugs, researching liver microenvironment regulation mechanisms, and identifying liver metastasis related diagnostic markers.
The invention belongs to the technical field of tumor prognosis prediction, and relates to a colorectal cancer allotropic liver metastasis prediction method and system.The method comprises the steps that colorectal adenocarcinoma cases are collected, the volume of an intra-tumor region-of-interest is delineated and automatically expanded to generate the volume of a peritumor region-of-interest, image omics characteristics are extracted through a pyradiomics packet, core omics characteristics are screened out, and the colorectal cancer allotropic liver metastasis prediction result is obtained. The method comprises the following steps: respectively constructing an intratumoral model and a peritumoral model, analyzing and integrating intratumoral and peritumoral core omics characteristics through logistic regression to form a combined radiomics model, integrating the combined radiomics model and clinical risk factors, establishing a column diagram for predicting the non-hepatic metastasis lifetime, and dividing patients into a low-risk group and a high-risk group according to a column diagram score threshold value; according to the method, LMFS prediction results of 1-5 years can be quickly output, and 0.6911 is set as a standardized risk stratificationcut-off value so as to support risk stratification and personalized treatment decision of a patient.
The invention belongs to the technical field of biomedicine, and particularly relates to a flora marker for predicting colorectal cancer liver metastasis and application of the flora marker. According to the present invention, the bacterial group marker is the combination of Acinetobacter, Streptococcus, Pseudomonas, Brevundimonas and Sphingomonas, and the bacterial group marker combination provides extremely high specificity (95.29%) and sensitivity (91.43%) when the early liver metastasis of colorectal cancer is predicted, such that the liver metastasis risk of the patient can be accurately assisted in the determination, and the early liver metastasis risk of the colorectal cancer can be accurately determined; the method has the advantages that reliable basis is provided for clinical decision making, the colorectal cancer liver metastasis can be predicted only by taking the abundance of the specific bacteria as an input index, the method is not limited by specific measurement means, and dependence on a detection technology is greatly reduced.
This invention discloses the application of a branched-chain amino acid (BCAA) restricted diet in the preparation of drugs for treating liver metastases of tumors. Through mouse model experiments, this invention found that restricting the intake of BCAAs (valine, isoleucine, and leucine) in the diet, or using the SCD1 inhibitor A939572, can significantly inhibit liver metastases of tumors, especially pancreatic cancer liver metastases. Experimental results show that a BCAA restricted diet or SCD1 inhibitor can reduce the number and volume of liver metastases and inhibit their growth. This invention also reveals its mechanism of action: BCAA restriction reduces the propionylation modification of SREBP1, downregulates the transcriptional expression of its target gene SCD1, and thus reduces lipid synthesis, thereby exerting an anti-tumor liver metastasis effect. This invention provides a novel dietary intervention strategy and drug target for the treatment of liver metastases of tumors.
The present invention discloses an application of RARRES2 gene in the diagnosis and treatment of brain metastasis of breast cancer. We first compared the gene expression differences between primary tumors of human breastcancer and brain metastases by mining public databases such as GEO and MET500, screened and compared the RARRES2 gene, and compared the expression of the RARRES2 gene in breast cancerbone metastasis, lungmetastasis and liver metastasis. Secondly, single-celltranscriptome sequencing was performed on brain metastases of breast cancer patients. The results showed that the expression level of RARRES2 in brain metastasis of breast cancer was significantly lower than that in primary tumors, but the expression of RARRES2 in bone, lung and liver metastases of breast cancer was not significantly different from that in primary tumors, suggesting that it is specifically related to brain metastasis of breast cancer. By constructing RARRES2 overexpression and knockdown human breast cancer brain metastasiscell (MDA-MB-231) lines, it was found that RARRES2 overexpression significantly inhibited the proliferation and invasion of the cells. By constructing a luciferase-labeled RARRES2 overexpression breast cancer brain metastasis mouse model, it was found that RARRES2 overexpression can significantly inhibit the proliferation of breast cancer cells in the brain.
The present application relates to the field of animal model construction, and in particular to a melanoma liver metastasis model construction method, which uses a spleen injection method to construct a human melanoma A375-M1 cell line liver metastasis model, and is identified in vivo by PET-CT and MRI, and is identified ex vivo by Bouin's and H&E.The human melanoma liver metastasis tumor model constructed by the present application has the advantages of short construction time, simple method and 100% modeling success rate.This metastasis model simulates the development process and pathological characteristics of melanoma liver metastasis, solves the problem of the lack of an ideal animal model for human melanoma during liver metastasis, and helps to explore and screen the development of anti-liver metastasis drugs for human melanoma, and plays a positive promoting role in new strategies for anti-melanoma liver metastasis.
To provide a combination pharmaceutical for treating liver metastasis in a subject in need of treatment thereof.SOLUTION: A combination pharmaceutical includes a therapeutically effective amount of a combination of active agents. The combination includes cobimetinib or a pharmaceutically acceptable salt thereof and ponatinib or a pharmaceutically acceptable salt thereof. The cobimetinib or a pharmaceutically acceptable salt thereof is present in an amount of 45-75 mg. The ponatinib or a pharmaceutically acceptable salt thereof is present in an amount of 30-60 mg.SELECTED DRAWING: Figure 20A
The invention belongs to the field of biological medicine, and particularly relates to application of nicotinic acid and derivatives thereof in prevention or treatment of colorectal cancer growth and metastasis. It is found for the first time that nicotinic acid and novel derivatives thereof can effectively and remarkably inhibit proliferation, migration and invasion of colorectal cancer cells, and can inhibit growth and liver metastasis of the colorectal cancer cells in a mouse model. Experiments prove that the medicinereagent prepared from the nicotinic acid or the combination of the nicotinic acid and other medicines is safe and effective, and a new thought is provided for preparing the medicines for preventing or treating the liver cancer.
The invention provides application of a PTGIS gene and / or PTGIS protein in preparation of medicines for treating colorectal cancer and preventing and treating liver metastasis of colorectal cancer. The invention proves that PTGIS obviously inhibits colorectal cancer liver metastasis for the first time, and in-vitro and animal experiments show that proliferation, migration and liver metastasis load of colorectal cancer cells can be reduced through overexpression of PTGIS; meanwhile, the immunotherapy effect can be further enhanced by combining the PTGIS and the PD-L1 antibody, and the curative effect is superior to that of a single drug. PTGIS is expected to become a novel intervention target, provides a new molecular regulation thought for immune combined treatment of colorectal cancer liver metastasis, and has theoretical and transformation values.
The invention relates to a construction method and application of a colorectal cancer liver metastasis promoting animal model of quail chicken enterococcus, and the construction method specifically comprises the following steps: constructing an in-situ starting colorectal cancer liver metastasisanimal model, and carrying out isolated culture and identification on live bacteria in a liver metastasis focus of the model, so as to determine the quail chicken enterococcus as candidate bacteria; clinical sample analysis is further combined, and it is clear that the quail chicken enterococcus can play a role in the colorectal cancer liver metastasis process; and finally, further verifying the function of the quail chicken enterococcus SY2-1 with the preservation number of CCTCC (China Center For Type Culture Collection) NO: M20241929 by using two colorectal cancer liver metastasis models. The experiment result shows that the abundance and the detection positive rate of the quail chicken enterococcus in a clinical sample in the colorectal cancer liver metastasis focus of a patient are obviously higher than those of normal liver tissues, which indicates that the quail chicken enterococcus has the potential of serving as a predictive marker for occurrence and development of the colorectal cancer liver metastasis and serving as a biological intervention target of the colorectal cancer liver metastasis; and the enterococcus quail chicken SY2-1 can promote the construction of a colorectal cancer liver metastasis animal model.
This invention provides a combination of bile protein biomarkers for predicting liver metastasis of pancreatic cancer and its application. The combination of bile protein biomarkers includes at least MMP9, PRTN3, and S100A12. This application transforms bile, previously considered biological waste, into a high-value diagnostic sample. Based on the differences in bile proteins among patients with benign disease, patients with pancreatic cancer without liver metastasis, and patients with pancreatic cancer with liver metastasis, four optimal biomarker combinations are screened for the first time to establish a method for predicting the risk of pancreatic cancer liver metastasis for early preoperative assessment of pancreatic cancer liver metastasis risk.
The human livermetastasis-derived colon cancer cell line CRC-X1 and its application belong to the field of microbial animal cell lines. The human coloncancercell line is named Homo sapiens CRC-X1, and was preserved in the China Center for Type Culture Collection on November 22, 2025, with the preservation number CCTCC NO: C2025354. The human livermetastasis-derived colon cancer cell line CRC-X1 can be applied in the establishment of a cell model of colon cancer occurrence, development or metastasis; CRC-X1 can be applied in the cell model of studying the differentiation mechanism of colon cancer, cell morphology and functional abnormalities, tumor infiltration and metastasis mechanism, and guiding clinical comprehensive diagnosis and treatment. CRC-X1 can be applied in the study of the mechanism of colon cancer and the screening of drugs for preventing and treating colon cancer. CRC-X1 can be applied in the establishment of an animal model of colon cancer.
The invention relates to a quail chicken enterococcusbacteriophage PhiEgSY1 and application of the quail chicken enterococcusbacteriophage PhiEgSY1 in prevention or treatment of colorectal cancer liver metastasis. According to the invention, the specific bacteriophage of the quail chicken enterococcus SY2-1 is screened, the form and the splitting effect of the specific bacteriophage are confirmed, and the safety of intervention of the specific bacteriophage in mice is verified through an animal model. According to the invention, a colorectal cancer liver metastasisanimal model is also constructed, the phage PhiEgSY1 is utilized to accurately regulate and control quail chicken enterococcus which has a promoting effect on colorectal cancer liver metastasis in a microbiota, and it is verified that the phage PhiEgSY1 can significantly reduce the abundance of Eg in intestinal tracts and can inhibit liver metastasis or reduce the degree of liver metastasis, so that prevention or auxiliary intervention on liver metastasis is realized.