Genotype-immunophenotype analysis reveals the immunogenomic subtype and prognosis of multiple myeloma
| Autor: | Peng Liu, Wanjing Feng, Yue Wang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Oncology Adult Male Cancer Research medicine.medical_specialty Genotype Malignancy 03 medical and health sciences 0302 clinical medicine Immunophenotyping Immune system Text mining Internal medicine medicine Biomarkers Tumor Immunogenetics Humans Multiple myeloma Aged business.industry Microarray analysis techniques General Medicine Middle Aged medicine.disease Prognosis Gene Expression Regulation Neoplastic Survival Rate 030104 developmental biology 030220 oncology & carcinogenesis Female business Multiple Myeloma Transcriptome Selection operator Follow-Up Studies Signal Transduction |
| Zdroj: | Carcinogenesis. 41(12) |
| ISSN: | 1460-2180 |
| Popis: | Immune dysfunction plays an important role in tumour development, recurrence, therapeutic responses and overall survival (OS). Multiple myeloma (MM) is a clonal B-cell malignancy which characterized by anti-tumoural immune dysfunction. In this study, we analysed 28 tumour-immune-related pathways and calculated the immune pathway score through published microarray data from the Gene Expression Omnibus (GEO) data portal. A training set of 345 patients and a validation set of 214 patients with primary MM were chosen. We performed least absolute shrinkage and selection operator (LASSO) analysis to identify prognostic factors. Then, we used cluster analysis to divide patients into three immunogenomic subtypes, which named abnormal immune activated type, common type and anti-myeloma immune activated type. Log‑rank tests showed that anti-myeloma immune activated type had the best prognosis and abnormal immune activated type had the shortest OS (P = 0.000) and event-free survival (EFS) (P = 0.000). Multivariate Cox also indicated that the immunogenomic subtype was an independent predictor of OS (P = 0.001) and EFS (P = 0.000). We also analysed the characteristics and the immune-response patterns of different subtypes. Then, we established a mathematical model to classify patients in the validation set. In the validation set, patients with different immunogenomic subtypes also had a significantly different OS (P = 0.001) and EFS (P = 0.005). Our study explored tumour-immune-related pathways at a multi-dimensional level and found the immunogenomic subtype of MM. Potential mechanisms on the genetic level of how tumour-immunity influences the prognosis and therapeutic responses are provided. The immunogenomic subtype may be feasible for deciding clinical treatment in the future. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|