Patent Application
20230377755
The present disclosure relates to the field of medical technologies and in particular to a construction method for a treatment reactivity predicating model of hepatocellular carcinoma based on a gene expression quantity.
Transarterial chemoembolization (TACE) is currently recognized as the most common non-surgical treatment for liver cancer, and it is widely used in patients with stage IIb-IIIa liver cancer in China. Chemoembolization can be achieved by injecting chemotherapy drugs and embolic agents or drug-loaded microspheres after inserting a catheter selectively into a tumor-feeding artery. Because of the heterogeneity of intermediate-stage hepatoma and the widespread use of TACE, patients' responses and effectiveness vary greatly. As a result, it is critical to screen patients who respond well to TACE for appropriate treatment.
The current scoring systems for predicting the postoperative effects of TACE mainly rely on indicators of routine clinical measurement for evaluation. Since the existing prediction of TACE reactivity is more dependent on indicators that are readily available in clinical practice, the accuracy of the prediction is greatly reduced, although it is simple and convenient, but also impairs the reliability and validity. Furthermore, the majority of current indicators are hepatoma-specific, rather than TACE-specific.
To address the aforementioned issues, we propose a method for predicting the treatment reactivity model of hepatocellular carcinoma based on gene expression quantity.
The present disclosure provides a construction method for a treatment reactivity predicating model of hepatocellular carcinoma based on a gene expression quantity, in order to solve at least one of the problems in the background art.
A construction method for a treatment reactivity predicating model of hepatocellular carcinoma based on a gene expression quantity, including the following steps of:
As a preferred embodiment, the 10 related genes are AQP1, FABP4, HERC6, LOX, PEG10, S100A8, SPARCL1, TIAM1, TSPAN8, and TYRO3, respectively.
As a preferred embodiment, in step 3, the risk score is calculated by the following formula: X=A1*B1+A2*B2+ . . . +A10*B10, where B1, B2, . . . and B10 are expression levels of 10 genes included in the model, and A1, A2, . . . and A10 are weight coefficients of 10 genes calculated by LASSO regression.
As a preferred embodiment, the construction method for the treatment reactivity predicating model of the hepatocellular carcinoma based on the gene expression quantity further includes step 4: testing the predictive ability of the TACE treatment reactivity model of hepatocellular carcinoma in the external validation set.
As a preferred embodiment, in step 4, the risk score of each sample in the validation set is calculated by the same formula.
As a preferred embodiment, after the risk score of each sample in the validation set is calculated, patients are divided into a TACE reaction group and a TACE non-reaction group based on a median risk score in the training set as the boundary value, and analysis is carried out on the overall survival time between the two groups for statistical differences.
As a preferred embodiment, in step 4, the number of tumor tissue samples of the patients with hepatocellular carcinoma is not less than 100.
As a preferred embodiment, in steps 3 and 4, the step of evaluating the performance of the predictive TACE treatment reactivity model of hepatocellular carcinoma is as follows:
Beneficial effects: from a medical standpoint, the method of the present disclosure selectively distinguishes samples based on the expression quantity of 10 genes, which can more accurately predict patient response to TACE treatment and guide the next treatment for patients. TACE specificity solves the problem of TACE prediction accuracy being greatly reduced because the existing prediction of TACE reactivity is more dependent on clinically available indicators, thereby increasing the reliability and validity.
The present disclosure is further described in detail in combination with the accompanying drawings. These drawings are simplified schematics that only composition related to the present disclosure and only illustrate the basic structure of the present disclosure in a schematic manner. For those skilled in the art, the specific meanings of the above terms in the present disclosure can be understood in accordance with specific cases.
As shown in
In steps 3 and 4, the step of evaluating the performance of the predictive model for TACE treatment reactivity of hepatocellular carcinoma is; evaluating the performance of the predictive model for TACE treatment reactivity of hepatocellular carcinoma by multivariate COX proportional hazard regression analysis and ROC curve.
From the medical standpoint, the present disclosure's method selectively distinguishes samples based on the expression quantity of 10 genes, which can more accurately predict patient response to TACE treatment and guide patients' next treatment. TACE specificity solves the problem of TACE prediction accuracy being greatly reduced because the existing prediction of TACE reactivity is more dependent on clinically available indicators, thereby increasing the reliability and validity.
In the description of the present disclosure, the description of reference terms “one embodiment”, “certain embodiments”, “schematic embodiments”, “examples”, “specific examples”, or “some examples” means that specific features, structures, materials, or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present disclosure. In the description, the schematic expressions of the above terms do not always refer to the same embodiments or examples. Furthermore, the specific features, structures, materials or characteristics described may be combined in any or more embodiments or examples in an appropriate number.
The preceding illustrates and describes the fundamental principles, key features and advantages of the present disclosure. For those skilled in the art, it is obvious that the present disclosure is not limited to the details of the exemplary embodiments discussed above, and that it can be realized in other specific forms without departing from the spirit or basic features of the present disclosure. As a result, the embodiments should be regarded as exemplary and non-restrictive from any perspective. The appended claims, rather than the above description, define the scope of the present disclosure. Therefore, all changes within the meaning and scope of the equivalent elements of the claims in the present disclosure are intended to be included. Any reference sign in the claims is not intended to limit the scope of the claims.
In addition, while the Description is organized according to the embodiments, not every embodiment contains only an independent technical solution. This representation of the Description is only for the sake of clarity. Those skilled in the art should consider the Description as a whole, and the technical solutions in each embodiment can be properly combined to form other embodiments that those skilled in the art can understand.
| Number | Date | Country | Kind |
|---|---|---|---|
| 202210559298.4 | May 2022 | CN | national |
