Extracellular vesicle lncRNA AGAP2-AS1 as a non-invasive prognostic biomarker in patients with advanced renal cell carcinoma

Immune checkpoint inhibitor (ICI)-based combination therapies, such as dual ICI therapy or ICI plus vascular endothelial growth factor (VEGF) inhibitors, are recommended as first-line treatment for advanced renal cell carcinoma (aRCC). ICI-based combination therapy has improved the prognosis of patients with aRCC compared with the era of VEGF inhibitor monotherapy. Long noncoding RNAs (lncRNAs) are involved in the prognosis and metastasis of several cancers, and extracellular vesicle (EV)-derived lncRNAs play important roles in tumor progression and metastasis, serving as prognostic biomarkers. The lncRNA AGAP2-AS1 is highly expressed in RCC and is associated with poorer prognosis in patients with elevated expression levels. This study aimed to investigate the function of lncRNA AGAP2-AS1 in RCC and explore whether serum-derived EV lncRNA AGAP2-AS1 serves as a prognostic biomarker in patients with aRCC. Firstly, we examined lncRNA AGAP2-AS1 expression in RCC and normal kidney tissues with pathologically confirmed RCC at our institution. We also performed a functional analysis of lncRNA AGAP2-AS1 in RCC cell lines. Additionally, we analyzed the relationship between the EV lncRNA AGAP2-AS1 expression and the prognosis of 47 patients with aRCC treated with ICI-based combined therapy. We observed higher lncRNA AGAP2-AS1 expression in RCC tissues than in normal tissues. Furthermore, AGAP2-AS1 knockdown in RCC cells using small interfering RNA significantly decreased cell viability, invasion, and migration. Patients with progressive disease (PD) receiving ICI-based combination therapy exhibited significantly higher expression of the EV lncRNA AGAP2-AS1 than patients without PD. We then classified 47 patients into two groups by median lncRNA AGAP2-AS1 expression. Notably, the high-expression group exhibited significantly worse progression-free survival and overall survival than the low-expression group (log-rank P = 0.0193 and log-rank P = 0.0256, respectively). In multivariate analysis, high EV lncRNA AGAP2-AS1 expression was an independent risk factor for disease progression (hazard ratio = 3.6, P = 0.0287). Overall, high EV lncRNA AGAP2-AS1 expression was associated with poorer prognosis in patients with aRCC. Therefore, serum-derived EV lncRNA AGAP2-AS1 may be an effective non-invasive prognostic biomarker in patients with aRCC treated with ICI-based combination therapy.

Authors

Institutions

Publication Details

Journal
American Journal of Cancer Research
Published
2025-01-01
DOI
https://doi.org/10.62347/yceb1273
Citations
2
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
1.61
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Extracellular vesicle lncRNA AGAP2-AS1 as a non-invasive prognostic biomarker in patients with advanced renal cell carcinoma

Nakanori Fujii
2 citations
American Journal of Cancer Research
Extracellular vesicles in disease
1.61
article

Extracellular vesicle lncRNA AGAP2-AS1 as a non-invasive prognostic biomarker in patients with advanced renal cell carcinoma

Nakanori Fujii
article en
2 citations

Abstract

Immune checkpoint inhibitor (ICI)-based combination therapies, such as dual ICI therapy or ICI plus vascular endothelial growth factor (VEGF) inhibitors, are recommended as first-line treatment for advanced renal cell carcinoma (aRCC). ICI-based combination therapy has improved the prognosis of patients with aRCC compared with the era of VEGF inhibitor monotherapy. Long noncoding RNAs (lncRNAs) are involved in the prognosis and metastasis of several cancers, and extracellular vesicle (EV)-derived lncRNAs play important roles in tumor progression and metastasis, serving as prognostic biomarkers. The lncRNA AGAP2-AS1 is highly expressed in RCC and is associated with poorer prognosis in patients with elevated expression levels. This study aimed to investigate the function of lncRNA AGAP2-AS1 in RCC and explore whether serum-derived EV lncRNA AGAP2-AS1 serves as a prognostic biomarker in patients with aRCC. Firstly, we examined lncRNA AGAP2-AS1 expression in RCC and normal kidney tissues with pathologically confirmed RCC at our institution. We also performed a functional analysis of lncRNA AGAP2-AS1 in RCC cell lines. Additionally, we analyzed the relationship between the EV lncRNA AGAP2-AS1 expression and the prognosis of 47 patients with aRCC treated with ICI-based combined therapy. We observed higher lncRNA AGAP2-AS1 expression in RCC tissues than in normal tissues. Furthermore, AGAP2-AS1 knockdown in RCC cells using small interfering RNA significantly decreased cell viability, invasion, and migration. Patients with progressive disease (PD) receiving ICI-based combination therapy exhibited significantly higher expression of the EV lncRNA AGAP2-AS1 than patients without PD. We then classified 47 patients into two groups by median lncRNA AGAP2-AS1 expression. Notably, the high-expression group exhibited significantly worse progression-free survival and overall survival than the low-expression group (log-rank P = 0.0193 and log-rank P = 0.0256, respectively). In multivariate analysis, high EV lncRNA AGAP2-AS1 expression was an independent risk factor for disease progression (hazard ratio = 3.6, P = 0.0287). Overall, high EV lncRNA AGAP2-AS1 expression was associated with poorer prognosis in patients with aRCC. Therefore, serum-derived EV lncRNA AGAP2-AS1 may be an effective non-invasive prognostic biomarker in patients with aRCC treated with ICI-based combination therapy.

American Journal of Cancer ResearchVol. 15(9)
Yamaguchi University (JP)
Openalex Percentile: Top 15%
Extracellular vesicles in disease
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.