Subtype-specific analysis of gene co-expression networks and immune cell profiling reveals high grade serous ovarian cancer subtype linkage to variable immune microenvironment DOI Creative Commons

Kaylin Carey,

Corey D. Young, A. J. Clark

et al.

Journal of Ovarian Research, Journal Year: 2024, Volume and Issue: 17(1)

Published: Dec. 3, 2024

High-grade serous ovarian cancer (HGSOC) is marked by significant molecular diversity, presenting a major clinical challenge due to its aggressive nature and poor prognosis. This study aims deepen the understanding of HGSOC characterizing mRNA subtypes examining their immune microenvironment (TIME) role in disease progression. Using transcriptomic data an advanced computational pipeline, we investigated four subtypes: immunoreactive, differentiated, proliferative, mesenchymal, each associated with distinct gene expression profiles behaviors. We performed differential analysis among using DESeq2 conducted Weighted Gene Co-Expression Network Analysis (WGCNA) identify co-expressed modules related traits, e.g., age, survival, subtype classification. Ontology (GO) highlighted key pathways involved tumor progression evasion. Additionally, utilized TIMER 2.0 assess cell infiltration across different subtypes, providing insights into interplay between (TIME). Our findings show that immunoreactive subtype, particularly M3 module-associated network, was high infiltration, including M1 (p < 0.0001) M2 macrophages 0.01), Th1 cells 0.01) along LAIR-1 = 1.63e-101). The M18 module exhibited strong B signatures 6.24e-28), FCRL5 (adj. p 3.09e-30) IRF4 coexpression. In contrast, M5 significantly mesenchymal fibroblasts 0.0001). proliferative characterized M15 module-driven cellular growth proliferation signatures, stromal involvement reveals complex suggests genes contributing underscoring important implications subtyping HGSOC.

Language: Английский

Ovarian cancer and the heart: pathophysiology, chemotherapy-induced cardiotoxicity, and new therapeutic strategies DOI Creative Commons

Megha Nair,

Arun Samidurai,

Anindita Das

et al.

Journal of Ovarian Research, Journal Year: 2025, Volume and Issue: 18(1)

Published: April 5, 2025

Ovarian Cancer (OC) is recognized as the most lethal gynecologic malignancy, characterized by numerous genetic mutations that trigger uncontrolled cellular growth and replication. Emerging evidence suggests non-coding RNAs including miRNAs lncRNAs significantly influence OC through their multiple roles tumor initiation, progression, metastasis, immune evasion, chemoresistance, making them promising diagnostic markers therapeutic targets. The primary approach to treating typically involves cytoreductive surgery followed chemotherapy. However, chemotherapeutic agents, particularly anthracyclines such doxorubicin (DOX), are known for cardiotoxic effects, which can range from acute chronic, potentially leading heart failure death. To enhance overall treatment response minimize cardiotoxicity, alternative strategies have been explored. These include use of liposomal (DOXIL) a substitute DOX, various radiotherapies, immunotherapies, co-administration angiotensin-converting enzyme inhibitors and/or beta-blockers. Phosphodiesterase-5 (PDE5i) also demonstrated efficacy in reducing cardiotoxicity linked cancer treatments promoting apoptosis cells across types. Although there no current clinical trial directly examining impact PDE5i on OC, however emerging therapies Withaferin A, PARP inhibitors, nanoparticle combination therapy show promise. Additional research essential develop both effective against less harmful heart.

Language: Английский

Citations

0
Subtype-specific analysis of gene co-expression networks and immune cell profiling reveals high grade serous ovarian cancer subtype linkage to variable immune microenvironment DOI Creative Commons

Kaylin Carey,

Corey D. Young, A. J. Clark

et al.

Journal of Ovarian Research, Journal Year: 2024, Volume and Issue: 17(1)

Published: Dec. 3, 2024

High-grade serous ovarian cancer (HGSOC) is marked by significant molecular diversity, presenting a major clinical challenge due to its aggressive nature and poor prognosis. This study aims deepen the understanding of HGSOC characterizing mRNA subtypes examining their immune microenvironment (TIME) role in disease progression. Using transcriptomic data an advanced computational pipeline, we investigated four subtypes: immunoreactive, differentiated, proliferative, mesenchymal, each associated with distinct gene expression profiles behaviors. We performed differential analysis among using DESeq2 conducted Weighted Gene Co-Expression Network Analysis (WGCNA) identify co-expressed modules related traits, e.g., age, survival, subtype classification. Ontology (GO) highlighted key pathways involved tumor progression evasion. Additionally, utilized TIMER 2.0 assess cell infiltration across different subtypes, providing insights into interplay between (TIME). Our findings show that immunoreactive subtype, particularly M3 module-associated network, was high infiltration, including M1 (p < 0.0001) M2 macrophages 0.01), Th1 cells 0.01) along LAIR-1 = 1.63e-101). The M18 module exhibited strong B signatures 6.24e-28), FCRL5 (adj. p 3.09e-30) IRF4 coexpression. In contrast, M5 significantly mesenchymal fibroblasts 0.0001). proliferative characterized M15 module-driven cellular growth proliferation signatures, stromal involvement reveals complex suggests genes contributing underscoring important implications subtyping HGSOC.

Language: Английский

Citations

3