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Prognosis evaluation method for immunotherapy of non-small cell lung cancer patient

A non-small cell lung cancer and immunotherapy technology, applied in the field of medical molecular biology, can solve the problems of short patients and poor specificity

Active Publication Date: 2021-12-28
求臻医学科技(浙江)有限公司
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Problems solved by technology

However, there are a large number of reports pointing out that when using TMB as an indicator to divide the population benefiting from immunotherapy, there is a situation of poor specificity, specifically manifested in the presence of patients with shorter OS after immunotherapy in the TMB-H non-small cell lung cancer population

Method used

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  • Prognosis evaluation method for immunotherapy of non-small cell lung cancer patient

Examples

Experimental program
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Embodiment 1

[0029] Randomly select 155 patients in the TMB-H group, perform targeted gene sequencing on each patient sample, and input the gene mutation list and prognosis of each patient into the supervised learning decision tree model, based on the CART algorithm, using Python (3.7.0) sklearn .tree module DecisionTreeClassifier function for feature selection and pruning; use sklearn.model_selection module cross_val_score function for 5-fold cross-validation, and calculate model accuracy; use joblib module for model persistence; use graphviz module to draw the decision tree model, the final decision tree The model contains 13 optimal eigengenes, including 9 negative predictor genes (SMARCB1, TSC2, BAP1, SDHB, RIT1, ESR1, SOCS1, SH2B3, IDH2) and 4 positive predictor genes ( MET, BRIP1, NTRK3, FGFR4); according to the screened 13 optimal characteristic genes, construct a prediction model containing 13 optimal characteristic genes (Formula 1), (Equation 1), and perform univariate cox regre...

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Abstract

The invention relates to the technical field of medical molecular biology, in particular to a prognosis evaluation method for immunotherapy of a non-small cell lung cancer patient, which comprises the following steps: detecting gene variation through sequencing, creating a decision tree model, screening 13 optimal characteristic genes, and constructing a prediction model to carry out prognosis risk scoring on the non-small cell lung cancer TMB-H patient. Therefore, the prognosis condition of the patient is predicted. Compared with the prior art, the prognosis evaluation method for the immunotherapy of the non-small cell lung cancer TMB-H patient, provided by the invention, has the advantages that the non-small cell lung cancer TMB-H patient sample is sequenced, the prediction model containing 13 optimal characteristic genes is constructed based on a CART algorithm, prognosis risk scoring is carried out on non-small cell lung cancer TMB-H patients according to the prediction model, TMB-H people are divided into a good prognosis group and a poor prognosis group, and the accuracy rate is up to 0.85.

Description

technical field [0001] The invention relates to the technical field of medical molecular biology, in particular to a prognosis assessment method for immunotherapy of patients with non-small cell lung cancer. Background technique [0002] Immunotherapy drugs mobilize the patient's own immune system to eliminate tumors by inhibiting the immune escape of tumor cells. At present, immunotherapy has made breakthroughs in the treatment of various advanced solid tumors, especially it can effectively prolong the overall survival (OS) of patients, and the adverse reactions are controllable. However, due to the lack of suitable clinical molecular markers, only 20%-30% of the population benefited from PD-1 / PD-L1 immunotherapy drugs. Precise measurement of TMB can predict the efficacy of immune checkpoint inhibitors, giving cancer patients the opportunity to receive more precise treatments. Previous clinical studies and translational studies have shown that tissue-based detection of tu...

Claims

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Application Information

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IPC IPC(8): G16B5/00G16B20/50G16B40/00G16H50/30G16H50/50C12Q1/6886
CPCG16B5/00G16B20/50G16B40/00G16H50/30G16H50/50C12Q1/6886C12Q2600/156C12Q2600/118
Inventor 孙大伟刘思瑶廖蕊张怡然顾丽清王冰王东亮
Owner 求臻医学科技(浙江)有限公司
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