According to the invention, 22 related genes of
lactic acid metabolism are analyzed and researched, the 22 related genes are divided into 3
ovarian cancer subgroups, and immune cells, tumor purity, stromal cells and the like infiltrated by the 3
ovarian cancer subgroups in a
tumor microenvironment are obviously different and have statistical differences. On the basis, a neural network
algorithm is introduced, 22
lactic acid modified genes are used as prediction indexes, and a prediction model is established to evaluate the sensitivity degree of an
ovarian cancer patient in receiving anti-PD-1 treatment. For example, 22 related genes of
lactic acid metabolism mentioned in the invention are collected and arranged from previous literatures and reports, and are derived from a medical
library (pubard, website: https: / / pubmec.ncbi.nlm.nih.gov / ) subordinate to the National Institute of Health, 'lactate /
lactation 'is used as a keyword to search, and queried related researches are manually filtered and screened. According to the present invention, the 22 lactic acid modification genes comprise STC1, PLOD2, VCAN, HBB, SLC2A3, ATF3, DUSP1, AURKA, RRM2, SLC1A4, TXNIP, HELLS, NFS1, ABCC1, SLC16A3, SLC5A8, SLC5A12, NDRG3, HIF1A, LDHA, LDHB and SLC16A1;