Application of biomarker and risk model based on amino acid metabolism related gene

• Main Authors: YAN ZECHEN, REN YILIN, LIU TONGHU, WANG YU, XU PENGCHAO, SUN WEIBO, ZHU CONGCONG, ZHAO LUYANG, LI JIANHUI, LUAN YONGKUN, NIU GUODONG, WU YONGJI, GAO YUKUI, LEE JI-WON, XIA KUNKUN
• Format: Patent
• Language: Chinese; English
• Published: 15.03.2024
• Subjects: BEER; BIOCHEMISTRY; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; ENZYMOLOGY; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES; MEASURING; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; PHYSICS; PROCESSES OF PREPARING SUCH COMPOSITIONS; SPIRITS; TESTING; VINEGAR; WINE

The invention provides an application of a biomarker based on an amino acid metabolism related gene and construction of a risk model in prediction of pheochromocytoma diagnosis, treatment and prognosis, and belongs to the technical field of tumor diagnosis markers. Researches find that the amino acid metabolism related gene DDC and/or SYT11 shows a high expression level in pheochromocytoma, has an obvious influence effect on pheochromocytoma diagnosis and prognosis, can accurately evaluate the prognosis risk of a patient, and can become a novel target for treating pheochromocytoma. Meanwhile, expression levels of DDC, SYT11, GCLM, PSMB7, TYRO3 and/or AGMAT are used as parameters to construct a risk model capable of assisting in judging diagnosis and treatment of a patient. The risk model has a very strong prediction capability for selection of immunotherapy modes, can be used as an important index for selection of the immunotherapy modes, can identify patients with high-risk factors in an early stage, and pro