Gastric cancer prognosis risk model based on endoplasmic reticulum stress characteristic gene and application
The invention belongs to the technical field of tumor markers and biomedical detection, and particularly relates to a gastric cancer prognosis risk model based on an endoplasmic reticulum stress characteristic gene and application. Data collected from a TCGA database is used as a training set, and 375 gastric cancer samples and 32 para-carcinoma samples are included. And 387 stomach cancer samples in the GEO database are used as an external verification set for verification. The six endoplasmic reticulum stress characteristic genes NOS3, PON1, CXCR4, MATN3, ANXA5 and SERPINE1 are successfully screened out according to the comprehensive mining transcriptional spectrum and tumor microenvironment characteristics. The prediction model shows good performance of predicting the overall survival rate of the gastric cancer in a training set and a test set. Based on the risk score of the six endoplasmic reticulum stress related genes, the gastric cancer patients can be well divided into high-risk and low-risk people, which may contribute to the selection of clinical treatment schemes..
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Patent| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Europäisches Patentamt - (2022) vom: 20. Dez. Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
ZHANG YIFAN [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Sonstige Themen: |
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| Anmerkungen: |
Source: www.epo.org (no modifications made), First posted: 2022-12-20, Last update posted on www.tib.eu: 2023-06-29, Last updated: 2023-07-08 |
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| Patentnummer: |
CN115497552 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA016901797 |
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| 520 | |a The invention belongs to the technical field of tumor markers and biomedical detection, and particularly relates to a gastric cancer prognosis risk model based on an endoplasmic reticulum stress characteristic gene and application. Data collected from a TCGA database is used as a training set, and 375 gastric cancer samples and 32 para-carcinoma samples are included. And 387 stomach cancer samples in the GEO database are used as an external verification set for verification. The six endoplasmic reticulum stress characteristic genes NOS3, PON1, CXCR4, MATN3, ANXA5 and SERPINE1 are successfully screened out according to the comprehensive mining transcriptional spectrum and tumor microenvironment characteristics. The prediction model shows good performance of predicting the overall survival rate of the gastric cancer in a training set and a test set. Based on the risk score of the six endoplasmic reticulum stress related genes, the gastric cancer patients can be well divided into high-risk and low-risk people, which may contribute to the selection of clinical treatment schemes. | ||
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