en Radiation Biology Radiation Biology تحقيق بديع Original Research <div style="text-align: justify;"><span style="font-size:10pt"><span style="text-justify:newspaper"><span style="text-kashida-space:50%"><span style="line-height:119%"><span style="font-family:Calibri"><span style="color:black"><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="color:#1f497d"><span style="font-style:italic"><span style="font-weight:bold"><span style="language:en-US">Background</span></span></span></span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="color:#1f497d"><span style="font-weight:bold"><span style="language:en-US">:</span></span></span></span></span> <span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="language:en-US">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. </span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="color:#1f497d"><span style="font-style:italic"><span style="font-weight:bold"><span style="language:en-US">Materials and methods:</span></span></span></span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="language:en-US"> The microarray data of ovarian cancer samples from na&iuml;ve 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. </span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="color:#1f497d"><span style="font-style:italic"><span style="font-weight:bold"><span style="language:en-US">Results: </span></span></span></span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="language:en-US">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. </span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="color:#1f497d"><span style="font-style:italic"><span style="font-weight:bold"><span style="language:en-US">Conclusion: </span></span></span></span></span></span><span lang="en-US" style="font-size:9.0pt"><span style="font-family:Calibri"><span style="language:en-US">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.</span></span></span></span></span></span></span></span></span></div> Ovarian cancer, neoadjuvant chemotherapy, cytoreductive surgery, differentially expressed genes, tertiary lymphoid structure, immune infiltration. 1009 1017 http://ijrr.com/browse.php?a_code=A-10-1-1270&slc_lang=en&sid=1 L. Luo 7900319475328460028742 7900319475328460028742 No Department of Gynaecology, Affiliated Hospital of Southwest Medical University, Sichuan Provincial Center for Gynaecology & Breast Disease, China W. He 7900319475328460028743 7900319475328460028743 No Department of Gynaecology, Affiliated Hospital of Southwest Medical University, Sichuan Provincial Center for Gynaecology & Breast Disease, China Q. Guo 7900319475328460028744 7900319475328460028744 No Department of Gynaecology, Affiliated Hospital of Southwest Medical University, Sichuan Provincial Center for Gynaecology & Breast Disease, China CY. Wang wangchunyan0215@126.com 7900319475328460028745 7900319475328460028745 Yes Department of Gynaecology, Affiliated Hospital of Southwest Medical University, Sichuan Provincial Center for Gynaecology & Breast Disease, China