Group of genes for tumor molecular subtyping and application thereof
A technique of molecular typing and genetics, applied in the field of cancer diagnosis and molecular biology, which can solve the problems of limited types of cancer and sample size
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Embodiment 1
[0142] Training set sample collection and processing:
[0143]The present invention analyzes the clinical data of cancer patients with a large sample size and their biological sample data, including the corresponding clinical data and expression profile data of 5,800 cancer patients with 22 types of tumors from all over the world. Among them, there were 55 cases of adrenal cancer, 446 cases of brain cancer, 542 cases of breast cancer, 113 cases of cervical cancer, 439 cases of colorectal cancer, 262 cases of endometrial cancer, 530 cases of gastroesophageal cancer, 254 cases of head and neck cancer, kidney cancer 256 cases, 222 cases of liver cancer, 285 cases of lung cancer, 366 cases of lymphoma, 163 cases of melanoma, 100 cases of mesothelioma, 209 cases of neuroendocrine tumors, 225 cases of uterine cancer, 134 cases of pancreatic cancer, 458 cases of prostate cancer, 169 cases of sarcoma There were 136 cases of testicular cancer, 238 cases of thyroid tumor, and 198 case...
Embodiment 2
[0152] Validation set test:
[0153] In this example, the inventor analyzed the high-throughput sequencing data of 9626 tumors, including 79 cases of adrenal cancer, 708 cases of brain cancer, 1218 cases of breast cancer, 310 cases of cervical cancer, 434 cases of colorectal cancer, intrauterine cancer 201 cases of membrane cancer, 196 cases of gastroesophageal cancer, 566 cases of head and neck tumors, 1020 cases of kidney cancer, 469 cases of liver cancer, 1130 cases of lung cancer, 48 cases of lymphoma, 554 cases of melanoma, 87 cases of mesothelioma, neuroendocrine tumors 187 cases, 266 cases of uterine cancer, 183 cases of pancreatic cancer, 187 cases of prostate cancer, 265 cases of sarcoma, 156 cases of testicular cancer, 572 cases of thyroid tumors, 427 cases of urinary system tumors. The tissue source was identified by the classification model, and compared with the tumor tissue source recorded in the clinical and pathological data, the average coincidence rate was ...
Embodiment 3
[0157] Screening of 96 specific genes:
[0158] The inventors relaxed the screening criteria of the F test to a P value of less than 0.001, and further obtained an additional 58 genes. These genes were differentially expressed in 22 primary tumors, and the difference was statistically significant. The 58 genes were combined with the 38 genes in Example 1 to form a 96-gene set.
[0159] Table 3: 58-gene set
[0160]
[0161]
[0162] Construction of 96-gene classification model:
[0163] Based on the expression patterns of 96 specific genes in 5,800 tumor samples, the inventors used the support vector machine algorithm to establish a classification model to distinguish the tissue origin and cancer type of tumor samples. For each sample to be tested, the model calculates the similarity score between the gene expression pattern of the sample and the 22 cancer types in the database, and determines the most likely tissue source of the sample according to the principle ...
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