Integrative analysis from multi‐center studies identifies a weighted gene co‐expression network analysis‐based Tregs signature in ovarian cancer

Abstract

Ovarian cancer (OC) is a malignancy associated with poor prognosis and has been linked to regulatory T cells (Tregs) in the immune microenvironment. Nevertheless, the association between Tregs‐related genes (TRGs) and OC prognosis remains incompletely understood. The xCell algorithm was used to analyze Tregs scores across multiple cohorts. Weighted gene co‐expression network analysis (WGCNA) was utilized to identify potential TRGs and molecular subtypes. Furthermore, we used nine machine learning algorithms to create risk models with prognostic indicators for patients. Reverse transcription‐quantitative polymerase chain reaction and immunofluorescence staining were used to demonstrate the immunosuppressive ability of Tregs and the expression of key TRGs in clinical samples. Our study found that higher Tregs scores were significantly correlated with poorer overall survival. Recurrent patients exhibited increased Tregs infiltration and reduced CD8+ T cell. Moreover, molecular subtyping using seven key TRGs revealed that subtype B exhibited higher enrichment of multiple oncogenic pathways and had a worse prognosis. Notably, subtype B exhibited high Tregs levels, suggesting immune suppression. In addition, we validated machine learning‐derived prognostic models across multiple platform cohorts to better distinguish patient survival and predict immunotherapy efficacy. Finally, the differential expression of key TRGs was validated using clinical samples. Our study provides novel insights into the role of Tregs in the immune microenvironment of OC. We identified potential therapeutic targets derived from Tregs (CD24, FHL2, GPM6A, HOXD8, NAP1L5, REN, and TOX3) for personalized treatment and created a machining learning‐based prognostic model for OC patients, which could be useful in clinical practice.

Promotion of non-small cell lung cancer tumor growth by FHL2 via inducing angiogenesis and vascular permeability

“…FHL2 , a member of FHL family, has been reported to be associated with the development of many types of cancers ( 10 , 12 , 25 ), playing different roles as a tumor-suppressor gene or an oncogene in different cancer types. For instance, FHL2 may suppress the growth and differentiation of colorectal cancer cells ( 26 ) but promote cervical cancer cell tumor progression through the regulation of AKT-mTOR pathway ( 27 ).…”