Transcriptomic analysis of the anti-tumor effects of leflunomide in prolactinoma

Leflunomide's anti-tumor effects have been investigated in various types of tumors; however, its impact on pituitary adenoma, particularly prolactinoma, is unclear. Hence, the current study evaluates the effects of leflunomide on prolactinoma cells in vitro and in vivo and elucidates the potential underlying mechanism(s). Cell Counting Kit-8 results revealed that leflunomide inhibits the proliferation of rat pituitary tumor cell lines (GH3 and MMQ) in a concentration-dependent manner in vitro. However, combination therapy of cabergoline and leflunomide exerted stronger inhibitory effects than cabergoline in MMQ cells in vitro and in vivo. Transcriptomics and gene ontology (GO) analyses identified genes significantly enriched in apoptotic processes and programmed cell death. Protein-Protein Interaction (PPI) networks defined the roles of hub genes (Mdm2, Cdkn1a, Plk2, and Ccng1) in leflunomide-induced cell death. GO and pathway enrichment analyses showed that the combination drug-specific differentially expressed genes were associated with inhibiting protein translation, but were active in gene expression processes. Hence, the anti-proliferative effects of leflunomide on prolactinoma cell lines may be mediated through programmed cell death pathways. Importantly, combining cabergoline with leflunomide effectively enhances the toxic effect of cabergoline, suggesting a potential therapeutic role for leflunomide in drug-resistant prolactinoma.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-04-05
DOI
https://doi.org/10.1038/s41598-025-95509-6
Primary Topic
Neuroblastoma Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transcriptomic analysis of the anti-tumor effects of leflunomide in prolactinoma

Kai‐Feng Shen, Huachun Yin, Zhenle Zang, Xiangdong Pei et al.
Scientific Reports
Neuroblastoma Research and Treatments
article

Transcriptomic analysis of the anti-tumor effects of leflunomide in prolactinoma

Kai‐Feng Shen, Huachun Yin, Zhenle Zang, Xiangdong Pei, Song Li, Yuyang Peng, Chunqing Zhang
article en

Abstract

Leflunomide's anti-tumor effects have been investigated in various types of tumors; however, its impact on pituitary adenoma, particularly prolactinoma, is unclear. Hence, the current study evaluates the effects of leflunomide on prolactinoma cells in vitro and in vivo and elucidates the potential underlying mechanism(s). Cell Counting Kit-8 results revealed that leflunomide inhibits the proliferation of rat pituitary tumor cell lines (GH3 and MMQ) in a concentration-dependent manner in vitro. However, combination therapy of cabergoline and leflunomide exerted stronger inhibitory effects than cabergoline in MMQ cells in vitro and in vivo. Transcriptomics and gene ontology (GO) analyses identified genes significantly enriched in apoptotic processes and programmed cell death. Protein-Protein Interaction (PPI) networks defined the roles of hub genes (Mdm2, Cdkn1a, Plk2, and Ccng1) in leflunomide-induced cell death. GO and pathway enrichment analyses showed that the combination drug-specific differentially expressed genes were associated with inhibiting protein translation, but were active in gene expression processes. Hence, the anti-proliferative effects of leflunomide on prolactinoma cell lines may be mediated through programmed cell death pathways. Importantly, combining cabergoline with leflunomide effectively enhances the toxic effect of cabergoline, suggesting a potential therapeutic role for leflunomide in drug-resistant prolactinoma.

Scientific ReportsVol. 15(1)
Army Medical University (CN), Xinqiao Hospital (CN)
Natural Science Foundation of Chongqing, Centre Scientifique et Technique du Bâtiment
Good health and well-being
Openalex Percentile: Top 89%
Neuroblastoma Research and Treatments
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.