Extracellular matrix-related genes-based prognostic signature for cervical cancer: association of LAMA4 expression with prognosis and response to immunotherapy.

Background: Extracellular matrix-related genes (ERGs) are crucial in the tumorigenesis of various malignancies, including cervical cancer (CC), but their prognostic significance in CC has not been thoroughly investigated.

Methods: We interrogated RNA-seq expression profiles from the public datasets to identify differentially expressed ERGs. Cox regression analysis was utilized to evaluate their prognostic significance. Consensus clustering classified CC patients into distinct subgroups with varying survival outcomes, immune infiltration, and pathway activation. We constructed an ERGs-based prognostic model using Lasso-Cox regression and examined the expression of LAMA4 in CC by RT-qPCR and immunohistochemistry (IHC), along with its correlation with patient outcomes and response to immunotherapy.

Results: ERGs exhibited significant differential expression between CC and normal tissues, with LAMA4 standing out as a hub gene linked to unfavorable prognosis. Consensus clustering sorted CC patients into two major subgroups with notable differences in survival. A prognostic model consisting of key ERGs robustly predicted overall survival. Evidence from our clinical samples, validated by RT-qPCR and immunohistochemistry (IHC), suggests that elevated LAMA4 expression is significantly associated with poor prognosis and response to immunotherapy.

Conclusions: This investigation underscores the prognostic value of ERGs in CC and identifies LAMA4 as a potential marker for prognosis and immunotherapy response.