Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy
BackgroundLung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.MethodsData on clinical and pathological characteristics, gen...
Saved in:
| Main Authors: | Yi Zhang, Yuzhi Wang, Haitao Qian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-11-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1497300/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comprehensive analysis of telomere and aging-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma
by: Zhe Ye, et al.
Published: (2025-01-01) -
Integrated analysis of M2 macrophage-related gene prognostic model and single-cell sequence to predict immunotherapy response in lung adenocarcinoma
by: Meifang Li, et al.
Published: (2025-02-01) -
The prognosis and adjuvant chemotherapy in KRAS mutation patients with stage I lung adenocarcinoma
by: Shangshang Ma, et al.
Published: (2024-12-01) -
SMARCA4 mutations and expression in lung adenocarcinoma: prognostic significance and impact on the immunotherapy response
by: Yuming Zhang, et al.
Published: (2024-12-01) -
HEG1 as a novel potential biomarker for the prognosis of lung adenocarcinoma
by: Xin Zou, et al.
Published: (2023-02-01)