Application of gastric cancer genes
一种基因、胃癌的技术,应用在重组DNA技术、微生物的测定/检验、DNA / RNA片段等方向,能够解决尚未有胃癌等问题,达到降低医疗成本、避免过度用药的效果
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Embodiment 1
[0033] System verification using the TCGA public database of gastric cancer patients:
[0034] The prognostic scoring system was applied to 253 TCGA gastric cancer patients with survival data. Prognostic scores were used to predict the probability of survival for each individual patient. We divided the patients into two groups according to the prognostic score. If the prediction score ≤ -2, we defined the patient as having a good prognosis gene signature; if the prediction score > -2, we defined the patient as having a poor prognosis gene signature. Such as Figure 5 As shown, the survival time of the former was significantly longer than that of the latter. More than 50% of patients in the former were still alive after 100 months, while all patients in the latter died within 80 months.
[0035] In the literature, the expression difference method has been used to show the correlation of genes or multiple gene groups with the prognosis of gastric cancer. One question is whe...
Embodiment 2
[0037] Using the GSE15459 public database for gastric cancer patients to verify survival:
[0038] Using the same method, we verified the application value of the prognostic scoring system in the GSE15459 public database. Although the gastric cancer tissue gene expression value of this database is determined by Affymetrix chip technology, resulting in differences in the expression level baseline and scale, resulting in differences in the absolute value of the prediction score, but the scoring system of the present invention can still successfully predict gastric cancer prognosis ( Image 6 ).
Embodiment 3
[0040] To predict the prognosis of clinical gastric cancer patients:
[0041] Collect and extract RNA from tumor tissues of gastric cancer patients received clinically. Tumor tissues may include fresh biopsy tissues, postoperative tissues, fixed tissues and paraffin-embedded tissues. Then, the expression level of the 53 genes of the prognosis scoring system was quantitatively detected by using the kit developed by the present invention and corresponding instruments. The expression level of 53 genes is entered into the prognosis scoring formula that the present invention establishes:
[0042]
[0043] After calculating the predictive score of the patient, the doctor predicts the prognosis of the patient (see Example 1), such as the 5-year survival rate, according to the score. At present, we have established a model through retrospective research and successfully verified it in different databases. And started a prospective study to further improve the scoring system.
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