Kit for detecting prognosis condition of pancreatic cancer

Abstract

The invention discloses a kit for detecting the prognosis condition of pancreatic cancer, the kit comprises upstream and downstream primer sequences of miRNA, upstream and downstream primer sequences of U6 and auxiliary components, miRNA comprises one or more of miRNA934, miRNA4444-2, miRNA3655 and miRNA1301 molecules, the kit is used for detecting miRNA in a treated pancreatic cancer patient prognosis in-vitro sample, and the prognosis condition of the pancreatic cancer is detected through the kit. According to the present invention, the expression conditions of the four miRNAs specifically expressed in the patient sample are detected, and the diagnostic kit for distinguishing the poor prognosis of the pancreatic cancer patient is established, such that the pancreatic cancer prognosis condition of the patient is determined according to the expression conditions of the four miRNAs specifically expressed in the patient sample, the pancreatic cancer prognosis curative effect and the accuracy of predicting metastasis and relapse can be comprehensively improved.

Description

technical field [0001] The invention relates to the field of biomedicine, in particular to a kit for detecting the prognosis of pancreatic cancer. Background technique [0002] Pancreatic cancer (PAAD) is one of the most lethal cancers overall. Due to the insidious onset and strong heterogeneity of PAAD, it is difficult to detect in the early stage and only appears in the late stage of the disease, resulting in an extremely low 5-year survival rate of only ~10%. The proportion of patients who have the opportunity to undergo surgical resection is less than 20%. Furthermore, patients with PAAD who undergo complete tumor resection typically experience local or distant recurrence within 2 years. Therefore, PAAD treatment remains a major challenge, [0003] The poor prognosis of PAAD may be due to its invasion and metastasis, drug resistance to treatment, and lack of early screening markers and diagnostic methods. Traditional prognostic prediction methods are based on patient...

AI Technical Summary

Problems solved by technology

Although molecular subtypes are interesting from a biological point of view, since each subtype is characterized by hundreds of genes and various molecular subtype classification criteria have been introduced for subtypes with poor Difficulty performing transcriptome analysis, whose translation into clinical practice has been challenging

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