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Additional file 1 of Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer

NIAID Data Ecosystem2026-03-13 收录

子宫内膜癌预后预测

免疫基因模型

数据链接：

https://figshare.com/articles/dataset/Additional_file_1_of_Construction_of_a_microenvironment_immune_gene_model_for_predicting_the_prognosis_of_endometrial_cancer/16994348 数据链接链接失效反馈

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资源简介：

Additional file 1.

应用场景：

创建时间：

2021-11-11

乳腺癌新辅助治疗反应预测

免疫基因模型

Breast cancer (BC) is the most common malignancy worldwide and neoadjuvant therapy (NAT) plays an important role in the treatment of patients with early BC. However, only a subset of BC patients can a

NIAID Data Ecosystem40

Table_3_Identification of a Metabolism-Related Signature for the Prediction of Survival in Endometrial Cancer Patients.xlsx

子宫内膜癌预后预测

代谢物生物标志物

ObjectiveEndometrial cancer (EC) is one of the most common gynecologic malignancies. The present study aims to identify a metabolism-related biosignature for EC and explore the molecular immune-relate

NIAID Data Ecosystem40

Table_2_ImmuneScore of eight-gene signature predicts prognosis and survival in patients with endometrial cancer.xlsx

子宫内膜癌预后预测

基因标志物

BackgroundEndometrial cancer (EC) is a common gynecological cancer worldwide and the sixth most common female malignant tumor. A large number of studies conducted through database mining have identifi

NIAID Data Ecosystem30

Construction and validation of an immune gene-based model for diagnosis and risk prediction of severe asthma

重症哮喘诊断

免疫基因模型

Severe asthma (SA) is a serious disease with limited treatment options, which is closely linked to immune dysfunction. Therefore, immune-associated biomarkers may diagnose SA and offer therapeutic tar

Taylor & Francis Group2025-03-20 更新40

Table_2_Identification of EMT-Related Gene Signatures to Predict the Prognosis of Patients With Endometrial Cancer.XLSX

子宫内膜癌预后预测

EMT基因特征

BackgroundEndometrial cancer (EC) is one of the most common gynecological cancers. Epithelial–mesenchymal transition (EMT) is believed to be significantly associated with the malignant progression of

NIAID Data Ecosystem30

Additional file 1 of Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer

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