Impact of neoadjuvant chemotherapy and cytoreductive surgery on patients with advanced ovarian cancer based on bioinformatics analysis

Background: surgery (crs) and neoadjuvant chemotherapy (nact) are recommended for advanced ovarian cancer (aoc) treatment. this study aimed to investigate the therapy-induced genomic changes and immune microenvironment alteration in patients with aoc. materials and methods: the microarray data of ovarian cancer samples from naïve or treated patients were collected from the gene expression omnibus (geo) database, and the differentially expressed genes (degs) between samples were screened. consensus clustering was conducted to explore the molecular subtypes of ovarian cancer samples. the correlation between tertiary lymphoid structure (tls) signatures with the molecular subtypes was subject to gene set variation analysis (gsva). the prognostic signature of aoc was constructed using machine learning based on lasso-cox regression. finally, immune infiltration analysis was performed for immune landscape evaluation in aoc. results: totally 28 degs were found between the control and treatment groups. enrichment analysis indicated the association of these genes with the immune changes. moreover, the cluster 1/2 (c1/c2) of ovarian cancer were identified, and the c1 subtype had higher enrichment of tls-related biomarkers. moreover, 15 genes were revealed as independent factors for the prediction of ovarian cancer prognosis. immune infiltration levels were significantly higher in the c1 subtype, which indicated the distinct immune landscape between the two molecular subtypes of ovarian cancer. conclusion: the nact and crs induced genomic changes were related to immune response in aoc. the findings of our study might deepen our understanding of the tls-related signature and immune pattern in aoc patients.