Evidence map›Paper›PMID 40998924›Full record

ArticleScientific reports2025

Lysosome-related molecular subtypes reveal prognostic signatures and immunotherapeutic implications in ovarian cancer.

Zhou Fang, Yunqing Liu, Yujie Cui, Ke Cao, Yiling Han, Zhijie Gao

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhou Fang *Department of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Yunqing Liu *Department of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Yujie Cui *Department of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Ke CaoDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China.
Yiling HanDepartment of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, People's Republic of China.
Zhijie GaoDepartment of Oncology, Third Xiangya Hospital, Central South University, Changsha, China. GaoZJie@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lysosomes are critical organelles that act as degradation centers and signaling hubs within cells, playing a significant role in various cellular processes and human diseases, including cancer. However, the extent to which they influence the heterogeneity and clinical outcomes of ovarian cancer (OC) remains inadequately understood. In this study, we used consensus clustering to identify two distinct lysosome-related clusters (LCs) in OC by analyzing the expression profiles of OC patients from The Cancer Genome Atlas (TCGA) database. Further analyses revealed the functional characteristics and immune landscapes of these subgroups, providing valuable insights into the tumor immune microenvironment (TIME) and tumor responses to immunotherapy. Additionally, we developed and validated a prognostic model based on differentially expressed genes (DEGs) between the two LCs, demonstrating its effectiveness in predicting patient prognosis, TIME characteristics, and immunotherapy potential in OC. A further investigation explored the relationship between lysosome-associated risk scores, IC50 values of standard antitumor agents, and the expression levels of prognostic genes. Finally, in vitro experiments showed that inhibiting CRHR1, a lysosome-associated prognostic gene, significantly reduced OC cell proliferation, invasion, and migration. In conclusion, our study establishes a novel lysosome-based classification and prognostic framework for OC, offering a practical tool to predict clinical outcomes and guide personalized immunotherapy strategies.

Indexed as

ImmunotherapyLysosomesOvarian NeoplasmsBiomarkers, TumorCell Line, TumorCell ProliferationFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, TumorCRHR1ImmunotherapyLysosomeMolecular subtypeOvarian cancerPrognostic signature

Identifiers

PMID40998924
PMCPMC12464291

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.