367 results about "SCC - Squamous cell carcinoma" patented technology

The invention provides an esophageal squamous carcinoma detection method and system based on combination of multi-modal information fusion and artificial intelligence, and relates to the technical field of detection. And inputting the fusion feature map corresponding to the multi-modal image information into a pre-trained esophageal squamous carcinoma detection model to perform focus area detection and segmentation on the fusion feature map, and based on a detection result, performing benign and malignant classification and staging prediction on a detected focus by using an integrated learning method in combination with a classification algorithm to obtain the esophageal squamous carcinoma. Outputting a classification result and a visual heat map; converting the extracted focus area information into three-dimensional point cloud data by using an improved point cloud reconstruction algorithm; performing space division and noise reduction processing on the three-dimensional point cloud data by adopting a self-adaptive octree structure; and generating a smooth lesion three-dimensional model by using an improved Poisson surface reconstruction algorithm in combination with a curved surface subdivision technology.

The invention provides an early-stage esophageal squamous carcinoma detection method and system based on deep learning, and relates to the technical field of image processing, and the method comprises the steps: obtaining an esophageal endoscope image, carrying out the enhancement processing, carrying out the multi-stage decomposition, generating a first image, carrying out the background separation of the first image, generating a region of interest, and carrying out the morphological filtering and edge extraction; generating a binary mask image and performing normalization processing to obtain a standard image; extracting semantic features of the standard image, performing pixel-level classification on the semantic features to obtain a region segmentation result, calculating morphological features and textural features of an esophageal squamous cell carcinoma region, performing classification to obtain an esophageal squamous cell carcinoma classification result, adding the esophageal squamous cell carcinoma classification result as an input feature into a first classification model, and judging esophageal tissues according to a judgment standard to obtain an esophageal squamous cell carcinoma classification result; generating a first judgment result, performing nonlinear mapping and classification to obtain a second judgment result, and performing fine segmentation to obtain an accurate boundary of the early esophageal squamous carcinoma tissue.

The invention discloses a lung squamous cell carcinoma survival prediction method and system based on SHAP interpretability, and relates to the technical field of medical data analysis. Comprising the following steps: constructing a dynamically updated physiological feature information table based on a lung squamous cell carcinoma clinical data set of a target under multiple time nodes; and associating different survival analysis models with the physiological feature information table to predict the survival probability of the lung squamous cell carcinoma in the target body, the marginal contribution of each input feature to the output of each model is obtained by using the SHAP interpretation algorithm, and the feature uniqueness score is transparently displayed in the fusion process, so that the survival probability of the lung squamous cell carcinoma in the target body can be predicted in the actual use process. The method can visually understand how each feature affects the final prediction, and achieves automatic arbitration or manual recheck through providing a model to explain conflict measurement, invalid variable elimination and pseudo high risk verification and weighted scoring, thereby guaranteeing the reasonability and safety of prediction and intervention suggestions, reducing the decision risk, and enhancing the clinical trust.

The invention discloses an NSD3 degradation agent as well as a preparation method and application thereof, and belongs to the technical field of drug synthesis. The invention provides a compound as shown in a formula I. The compound has a good effect of degrading NSD3 protein in vitro, can inhibit proliferation of a squamous carcinoma cell line NCI-H1703, and is expected to serve as a new way for preventing and treating NSD3 related diseases. # imgabs0 #

The invention belongs to the technical field of medical image processing, and particularly relates to an esophageal cancer treatment effect and survival combined prediction method and system based on multiple modalities, and the method comprises the steps: obtaining a preoperative CT image and Hamp of an esophageal squamous cell carcinoma patient; e, the dyed digital pathological image, transcriptome data and clinical diagnosis and treatment information are preprocessed and subjected to feature extraction, and radiomics embedding representation, pathomics embedding representation and pipeline branch embedding representation are obtained respectively; the radiomics embedded representation, the pathomics embedded representation and the pipeline branch embedded representation are aligned and input into a multi-modal fusion module based on a multi-head self-attention mechanism for feature fusion, and fusion feature representation is generated; and based on the fusion feature representation, synchronously outputting a curative effect prediction result and a survival prediction result by using a multi-task output module, and evaluating model prediction performance by using a curative effect evaluation index and a survival analysis index.

The invention provides an esophageal squamous cell carcinoma resisting pharmaceutical composition containing tageteoside and application of the esophageal squamous cell carcinoma resisting pharmaceutical composition. According to the pharmaceutical composition disclosed by the invention, the tageteoside and the cis-platinum have a synergistic anti-cancer effect, and the pharmaceutical composition of the tageteoside and the cis-platinum has an enhanced esophageal squamous cell carcinoma resisting effect and can be used for effectively preventing and treating the esophageal squamous cell carcinoma.

The invention discloses a lung squamous cell carcinoma survival probability prediction system fusing multiple models, and relates to the technical field of medical data analysis. Comprising a data acquisition module used for acquiring a lung squamous carcinoma clinical data set and an inspection index of a patient; the data preprocessing and dynamic feature table construction module is used for preprocessing the lung squamous cell carcinoma clinical data set in existing data processing and dynamically updating a physiological feature information table; the model training and predicting module is used for carrying out training and online prediction on various survival analysis models; and the SHAP interpretation and weight calculation module is used for calling a corresponding SHAP algorithm to obtain an average absolute SHAP value of each input feature. According to the method, model interpretation conflict measurement, invalid variable elimination and pseudo high risk verification are provided, and automatic arbitration or artificial recheck is realized through weighted scoring, so that the reasonability and safety of prediction and intervention suggestions are ensured, the decision risk is reduced, and the clinical trust is enhanced.

The invention discloses a micromolecule NSD3 degradation agent as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The invention provides a micromolecular NSD3 degradation agent, which has a structure as shown in a formula I or a formula II, has a remarkable inhibition effect on NSD3 protein expression, and has remarkable killing and growth inhibition effects on lung squamous carcinoma cells. The small molecule NSD3 degradation agent provides a new scheme for treatment of lung squamous cell carcinoma, and has a good clinical application prospect. # imgabs0 # imgabs1 #

The invention discloses application of an lncRNA biomarker in esophageal squamous cell carcinoma diagnosis, and relates to the technical field of esophageal squamous cell carcinoma diagnosis. The esophageal squamous cell carcinoma marker comprises LINC00482. The lncRNA marker screened by the invention has the technical advantages of high esophageal squamous cell carcinoma diagnosis sensitivity and strong specificity, has good diagnosis characteristics, and has important significance on early diagnosis, early intervention, deep understanding of the pathological mechanism of esophageal squamous cell carcinoma and the like. In addition, the method for auxiliary diagnosis or diagnosis of esophageal squamous cell carcinoma by using the biomarker has the technical advantages of simple operation, low price and short detection period, and can meet the detection requirements of various samples such as blood, tissues and the like.

The invention relates to a multi-modal survival prediction method fusing a digital pathological image and omics data. The method comprises the following steps: acquiring a full-view digital pathological image and omics data of an esophageal squamous cell carcinoma patient; carrying out preprocessing and feature extraction on the full-view digital pathological image and the omics data to respectively obtain a pathological embedding representation and an omics embedding representation; fusing the pathological embedding representation and the omics embedding representation by using a multi-head attention mechanism of Transform to obtain a preliminary fusion feature; performing deep interaction on the pathological embedding representation and the preliminary fusion feature to obtain a final fusion feature; and predicting a survival result based on the final fusion feature. According to the method, bimodal sharing of pathological images and omics data and full fusion of features are realized, and prognosis survival prediction of esophageal squamous cell carcinoma cancer patients can be better realized.

The invention discloses an engineered bionic nucleic acid nano-vesicle as well as a preparation method and application thereof, relates to the technical field of nano biomedicine, and aims at solving the problems that in-vivo targeting efficiency and immunogenicity of a traditional cationic lipid nano-carrier are limited due to deletion and cleavage obstacles of GSDMD expression in tumor cells. The technical key point of the invention is as follows: the engineered bionic nucleic acid nano-vesicle is provided and is prepared by wrapping a cationic lipid nucleic acid drug with an exosome derived from engineered macrophages; wherein the exosome from the engineered macrophage is the exosome from the macrophage with high expression of PD1, which is as shown in SEQ. ID. NO.1. The exosome from the engineered macrophage is the exosome from the macrophage with high expression of PD1; the lipid nucleic acid medicine is prepared by loading GSDMD-N mRNA (messenger Ribonucleic Acid) shown on the basis of SEQ.ID.NO.2 on a cationic liposome. The engineered bionic nucleic acid nano-vesicle is used for preparing an oral squamous cell carcinoma diagnostic kit and a therapeutic drug.

The invention provides a micro-fluidic chip capable of culturing oral squamous cell carcinoma organoid and a preparation method thereof, and relates to the technical field of micro-fluidic chips, the chip comprises a four-layer structure: the first layer is a closed layer, the second layer is a culture solution / drug pool layer (containing a concentration gradient injection channel and a slow flow channel), the third layer is a matrix culture pool layer, and the fourth layer is a matrix culture pool layer. The fourth layer is a matrigel inflow layer (containing an S-shaped flow channel); the second layer and the third layer are integrally formed, and all the layers are connected through oxygen plasma welding; the problems that in the prior art, matrigel is prone to shifting, drug gradient regulation and control is poor, operation is tedious, and adaptability is insufficient are solved, the matrigel and organoids can be stably fixed, the drug concentration gradient can be precisely regulated and controlled, the nutrition supply efficiency is enhanced, the structural integration level and operation convenience are improved, and the application prospect is wide. The method is suitable for oral squamous cell carcinoma organoid culture, drug screening and tumor mechanism research.

The invention discloses a lung squamous cell carcinoma drug discovery method and system based on disturbance response scanning analysis, and belongs to the field of biological medicines.The method comprises the steps that lung squamous cell carcinoma protein expression profile data is downloaded and preprocessed, a robust network module is constructed and multi-scale analysis and evaluation are conducted, and drug genomic data are obtained based on drug genomic data. Predicting the drug sensitivity of the patient by using machine learning, and generating a DRN through difference analysis of the drug sensitivity; predicting drug-target protein binding affinity in combination with deep learning, quantifying node sensitivity through a PRS technology, calculating a DPI disturbance score and ranking drug priorities; high-ranking drugs are screened through comprehensive sensitivity analysis and literature investigation; a drug for a lung squamous carcinoma cell line is screened out through a pre-experiment and is relocated. According to the framework developed by the invention, by integrating proteomics, pharmacogenomics and dynamic network analysis, systematic analysis is provided for relocation drug identification of lung squamous cell carcinoma, and good news is brought to treatment of lung squamous cell carcinoma.

The invention provides equipment, a method and a system for evaluating prognosis of cervical cancer, squamous carcinoma and adenocarcinoma and application of the equipment, the method and the system, and belongs to the technical field of medical evaluation. Two biomarkers, namely adenylate kinase 4 and cavernous malformation 2 protein, for evaluating prognosis of cervical squamous cell carcinoma and adenocarcinoma are obtained through multivariate statistical analysis, difference screening, COX regression analysis and other biosignal analysis methods. Based on the biomarker, evaluation equipment, a computer execution method, a computer system and the like for evaluating the prognosis of cervical squamous cell carcinoma and adenocarcinoma are constructed, and the evaluation equipment, the computer execution method, the computer system and the like are used for accurately judging the prognosis condition of a cervical cancer patient.

The invention discloses a compound as well as a preparation method and application thereof, and belongs to the technical field of biological medicines. The invention provides a compound which has a structure as shown in a formula I or a formula II, has a remarkable inhibition effect on NSD3 protein expression, and has remarkable killing and growth inhibition effects on lung squamous carcinoma cells. The compound provided by the invention provides a new scheme for treating lung squamous cell carcinoma, and has a good clinical application prospect. # imgabs0 # imgabs1 #

The invention relates to a prediction model for lung squamous cell carcinoma, and belongs to the technical field of disease prediction. On the basis of proteomics, protein molecule changes with specific execution functions in the lung squamous cell carcinoma occurrence process are screened, and a lung squamous cell carcinoma occurrence prediction model is constructed in combination with multiple machine learning models and public data. The prediction model for lung squamous cell carcinoma occurrence comprises six prediction factors: DDAH1, ATP11A, NME3, PON2, SLC1A5 and LPCAT1, and the prediction effectiveness (AUC value) of the prediction model can reach 97.6% and is higher than the prediction AUC value of a single factor.

The invention discloses an engineered bionic nucleic acid nano diagnosis and treatment agent as well as a preparation method and application thereof, relates to the technical field of biological targeting, and aims to solve the problems that an engineered macrophage membrane modified bionic nucleic acid nano diagnosis and treatment agent for oral squamous cell carcinoma is lacked in the prior art, and the curative effect on invasive tumors of the oral squamous cell carcinoma is poor. According to the engineering bionic nucleic acid nano diagnosis and treatment agent, a cationic lipid nucleic acid medicine is wrapped with a macrophage membrane, and PD1 shown as SEQ.ID.NO.1 is stably expressed on the macrophage membrane; the cationic lipid nucleic acid medicine is prepared by loading Cip2a siRNA (small interfering Ribonucleic Acid) on a cationic liposome. The bionic nucleic acid nano diagnosis and treatment agent has a huge application prospect in preparation of oral squamous cell carcinoma diagnosis kits and medicines.

The invention relates to application of recombinant humanized III-type collagen in preparation of an esophageal squamous cell carcinoma inhibitor. The invention discovers that the recombinant humanized III-type collagen can significantly inhibit the proliferation of esophageal squamous carcinoma cells and prevent the generation of malignant phenotypes of esophageal squamous carcinoma cells. Therefore, the invention can be used for preparing medicines for preventing and treating esophageal squamous carcinoma.

The invention belongs to the technical field of gene engineering, and relates to an esophageal squamous cell carcinoma diagnostic kit based on a peripheral blood mononuclear cell methylation marker and application. The kit comprises a primer pair which is used for detecting the methylation of a cg05914150 site, a cg06769875 site, a cg07475126 site, a cg08433285 site, a cg10038907 site, a cg17968322 site, a cg19572487 site, a cg20184330 site, a cg22741248 site and a cg22823192 site. According to the detection kit provided by the invention, the type of a detected sample is peripheral blood, the sample is relatively easy to obtain and non-invasive, and the patient compliance is relatively good. Abnormal methylation changes mostly exist in the early progression process of tumors, early diagnosis of ESCC can be achieved through the methylation detection method provided by the invention, and the five-year survival rate of ESCC patients is effectively increased.

The invention provides application of combination of tageteoside and difacitinib or ponatinib to blocking of esophageal squamous cell carcinoma progression. The tageteoside is combined with an FAK inhibitor defacitinib or an Src family kinase inhibitor ponatinib, so that the metastasis of esophageal squamous carcinoma, especially lymphatic metastasis, can be inhibited, the growth of primary focus and metastatic focus esophageal squamous carcinoma cells can be inhibited, and a synergistic anti-cancer effect is achieved.

The invention belongs to the technical field of biological medicine, and provides CKS1B serving as an immunotherapy response prediction biomarker and application of the CKS1B, and according to the application, CKS1B serves as an immunotherapy response marker, and a CKS1B inhibitor is combined with an active component to treat a model mouse. In-vitro cell experiments are adopted to evaluate the immunotherapy prediction effect of the CKS1B as a biomarker on esophageal squamous carcinoma, a Cks1b overexpression tumor mouse model, a homologous mouse model and a human immune reconstruction mouse model are established, and a CKS1B inhibitor is combined with active ingredients to treat the two models; results show that the CKS1B inhibitor combined with the active component can promote removal of esophageal squamous carcinoma cells by CD8 + T cells, inhibit interferon signal channels and antigen presentation, effectively recover immune response, inhibit tumor cell proliferation and significantly reduce tumor volume, so as to achieve the purpose of treating esophageal squamous carcinoma.

The invention relates to the technical field of medical image processing and intelligent grading recognition of tumors, and discloses a head and neck squamous cell carcinoma early recognition method based on radiomics and deep learning, which comprises the following steps: acquiring head and neck CT (Computed Tomography), MRI (Magnetic Resonance Imaging) and PET (Positron Emission Tomography) three-mode image data; a two-stage dynamic structure alignment mechanism is adopted for registration; extracting fusion radiomics features; constructing a tumor sub-feature map; outputting a tumor level and a prediction confidence coefficient through the uncertainty prediction model; and generating a saliency interpretation heat map. In the prior art, a single-mode image or a superficial layer texture feature extraction model is depended on, and especially under the condition that a heterogeneity tumor region boundary is fuzzy and different modes have significant structure offset, high-confidence accurate discrimination of a real staging state of a tumor cannot be realized. According to the method, the accuracy of early stage identification of the head and neck squamous cell carcinoma is improved by introducing the significance guide registration mechanism and the improved graph convolutional neural network and combining Dropout reasoning.

The invention discloses application of neutrophile granulocyte number level in prediction of tumor treatment effect. Through verification of the embodiment of the invention, the number level of neutrophils in blood of a tumor patient before treatment is closely associated with the curative effect of tumor treatment, especially OH2 treatment, and the applicable tumor adaptation diseases are common; comprising at least one of melanoma, esophageal cancer, right breast invasive ductal cancer, intestinal cancer, head and neck tumor, gastric cancer, ovarian cancer, biliary system tumor, left foot back squamous cell carcinoma, sarcoma and osteosarcoma, lung cancer, thymosquamous cell carcinoma and brain glioma. In the application disclosed by the invention, the threshold value of the number of neutrophils for predicting the tumor treatment effect is 3.5 * 10 < 9 > / L; the treatment is predicted to be effective when the number of sexual granulocytes in a tumor patient is below 3.5 * 109 / L before the tumor patient is treated, and the treatment is predicted to be ineffective or invalid when the number of sexual granulocytes in the tumor patient is higher than 3.5 * 109 / L. The application method is simple, low in cost and good in stability, and can become a potential prediction means for clinicians.

The invention relates to an mRNA (messenger Ribonucleic Acid) vaccine targeting FomA and application of the mRNA vaccine in immunotherapy of esophageal squamous carcinoma in the technical field of tumor immunotherapy. The problems that in the prior art, a specific targeting vaccine for the fusobacterium nucleatum membrane protein FomA lacks, traditional antibiotics can only kill extracellular bacteria and cannot remove intracellular colonized fusobacterium nucleatum, and cellular immunity cannot be effectively activated to remove fusobacterium nucleatum colonized in tumor tissue; the immunotherapy drug resistance of esophageal squamous carcinoma caused by fusobacterium nucleatum infection is difficult to reverse. According to the technical scheme, an mRNA molecule with a fusobacterium nucleatum FomA extracellular domain tandem repeat sequence and a lipid nanoparticle delivery system are coded, an extramembrane segment tandem repeat immune enhancement technology is adopted for design, two extracellular ring sequences are repeated for 2-5 times and connected through a connector sequence, lipid nanoparticles are composed of optimized quaternary lipids, and the lipid nanoparticles are prepared from the quaternary lipids. And a PD-1 monoclonal antibody is combined to activate FomA specific CD8 + T cell immunoreaction, so that comprehensive removal of intracellular and extracellular bacteria and bacteria targeted immune remodeling are realized.

The embodiment of the invention provides a training method of an esophageal squamous carcinoma risk prediction model, and an esophageal squamous carcinoma risk prediction method and system, and belongs to the technical field of medical treatment. According to the scheme, a training feature set is obtained, global importance analysis is carried out on the training feature set through a plurality of different feature selection algorithms, and an importance scoring result of each feature selection algorithm and consensus feature results of all the feature selection algorithms are obtained; performing screening processing according to each importance scoring result to obtain a feature subset corresponding to each feature selection algorithm; inputting each feature subset into a plurality of different classifier algorithms for training to obtain a corresponding basic model; a plurality of high-performance models are screened out from all the basic models through a multi-criterion decision classification fusion framework for weighted fusion, input features after model fusion are determined according to consensus feature results, an esophageal squamous cell carcinoma risk prediction model is obtained, the accuracy of esophageal squamous cell carcinoma risk prediction can be improved, and potential patients can be found in advance.

The invention relates to a biomarker-based near infrared spectrum characteristic wave band screening and pan cancer grading detection system and a working method thereof, and the working method comprises the following steps: a spectrum collection unit collects the near infrared spectrum of a to-be-detected plasma sample to obtain spectrum data; a spectrum abnormal value eliminating unit eliminates abnormal values; the clinical biochemical data abnormal value eliminating unit is used for eliminating abnormal values of the biochemical detection data; selecting a sample set division method and a division proportion; the spectrum pretreatment unit is used for pretreating a near infrared spectrum of a to-be-detected plasma sample; the spectral characteristic wave band screening unit screens spectral characteristic wave bands in combination with clinical biochemical indexes and near infrared spectrums, so that the accuracy of pan cancer recognition is improved; and the data analysis unit performs qualitative discriminant analysis on the near infrared spectrum data, constructs an accurate cancer primary detection model and an accurate cancer accurate detection model, preliminarily identifies cancers and finely screens esophageal squamous cell carcinoma, gastric cancer, colorectal cancer and lung cancer samples. The method has good practical application and reference value for large-scale screening of cancers.

The invention discloses an angiogenesis model as well as a preparation method and application thereof. The method comprises the following steps: extracting from oral squamous cell carcinoma tissues to obtain cancer-related fibroblasts in the oral squamous cell carcinoma tissues; the human umbilical cord vein endothelial cells capable of stably expressing the m-Chryry red fluorescent protein are obtained; co-culturing cancer-related fibroblasts in the oral squamous cell carcinoma tissue and the human umbilical vein endothelial cells stably expressing the m-Chryry red fluorescent protein in an ultralow adsorption plate to obtain a co-cultured cell cluster; and adding a co-culture medium into the co-culture cell cluster system to obtain the angiogenesis model. The close contact type co-culture of the two cells is realized through close contact type co-culture of the two cells, and compared with a traditional indirect co-culture model for treating the cells by using a conditioned culture medium, the close contact type co-culture model disclosed by the invention can better simulate direct interaction between the cells in an in-vivo tumor microenvironment.

The invention discloses application of a reagent for detecting an esophageal squamous cell carcinoma marker in preparation of an esophageal squamous cell carcinoma auxiliary diagnosis or diagnosis product, and relates to the technical field of esophageal squamous cell carcinoma diagnosis. The esophageal squamous cell carcinoma marker is selected from at least one of CST1, IBSP, HOXA11, METTL11B, PRDM13, GBX2 and TSBP1. The biomarker provided by the invention has the technical advantages of simple operation, high diagnosis sensitivity and strong specificity in auxiliary diagnosis of esophageal squamous cell carcinoma, and has good diagnosis characteristics. Compared with imaging detection, the diagnostic detection cost provided by the invention is lower, the detection period is short, the esophageal squamous cell carcinoma can be rapidly identified and diagnosed by detecting the biomarker, and the kit is suitable for large-scale clinical diagnosis of the esophageal squamous cell carcinoma in people.

The invention belongs to the technical field of biological medicine and molecular biology, and provides application of GJB6 in preparation of an esophageal squamous cell carcinoma prognosis evaluation reagent and screening of drugs for targeted treatment of esophageal squamous cell carcinoma. The low expression of the GJB6 is applied to preparation of an esophageal squamous cell carcinoma prognosis evaluation reagent. GJB6 is low in expression in ESCC patients, and ESCC prognosis is poor. And the prognosis of patients with high expression of GJB6 is better. Overexpression of GJB6 inhibits ESCC cell proliferation, migration and invasion and in-vivo tumor enlargement. The GJB6 plays a role of a cancer suppressor gene in ESCC and inhibits cell proliferation, migration and invasion. The AKT signal channel is one of downstream channels for GJB6 to regulate the occurrence and development of ESCC. The AKT inhibitor effectively inhibits GJB6 low-expression ESCC malignant phenotypes, including enhancement of cell proliferation and migration invasion ability and in-vivo tumor enlargement. The AKT is a key therapeutic target of the GJB6 low expression type ESCC.

The invention relates to the field of tumor immunotherapy, in particular to an mRNA vaccine targeting fusobacterium nucleatum membrane protein FomA and application of the mRNA vaccine in esophageal squamous cell carcinoma immunotherapy. The vaccine comprises a nucleotide sequence for coding a specific epitope of FomA, and the specific epitope contains 1-10'GGSGGGGSGG 'repetitive sequences and has homology gt in different strains; 95%. The mRNA is encapsulated in lipid nanoparticles (the particle size is 80-150 nm, the polydispersity coefficient is lt; and the liposome is composed of 38-42% of cationic lipid, 18-22% of neutral lipid, 33-37% of cholesterol and 3-5% of PEG modified lipid, and the encapsulation efficiency is 85-95%. The vaccine can specifically reduce the abundance of fusobacterium in tumors by 72.4 + / -8.0%, the tumor microenvironment is converted into an immune activation type, and the proportion of CD8 + T cells is increased from 5.2 + / -1.0% to 14.5 + / -2.0%. When the compound is combined with a PD-1 inhibitor, the objective remission rate reaches 70%, the tumor volume is reduced by 78.5 + / -8.0%, and the compound is suitable for treating clostridium-enriched esophageal squamous carcinoma.