Abstract
BackgroundOvarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Therefore, searching for new treatment methods plays an important role in improving the prognosis of OC.MethodsWe downloaded the MAF files, RNA-seq data and clinical information from the TCGA database. The “maftools” package in R software was used to visualize the OC mutation data. We calculated the tumor mutation burden (TMB) of OC and analyzed its correlation with clinicopathological parameters and prognostic value. Tumor mutation burden related signature model was constructed to predict the overall survival (OS) of OC.ResultsThe results revealed that there was a statistical correlation between TMB and FIGO stage, grade and tumor residual size of ovarian cancer patients. The Kaplan–Meier curve indicated that a high TMB is associated with better clinical outcomes of OC. The difference analysis indicated 24 upregulated genes and 619 downregulated genes in the high-TMB group compared with the low-TMB group. Besides, the TMBRS model based on five hub genes (RBMS3, PLA2G5, CDH2, AMHR2 and ADAMTS8) was constructed to predict the OS of OC. The ROC curve and validation data sets all revealed that the TMBRS model was reliable in predicting recurrence risk. Immune microenvironment analysis indicated the correlations between TMB and infiltrating immune cells.ConclusionsOur results suggest that TMB plays an important role in the prognosis and guiding immunotherapy of OC. By detecting the TMB of OC, clinicians can more accurately treat patients with immunotherapy, thereby improving their survival rate.
Highlights
Ovarian cancer (OC) is the most malignant tumor in the female reproductive system
Immunocheckpoint inhibitors have been used in melanoma [5], non-small cell lung cancer [6], Hodgkin’s lymphoma [7] and many other tumors
Somatic mutations in the OC data To identify the somatic mutations of the patients with OC in the TCGA database, mutation data were downloaded and visualized using the “maftools” package in R software
Summary
Ovarian cancer (OC) is the most malignant tumor in the female reproductive system. About 75% of OC in complete remission of clinical symptoms still develop a recurrence. Searching for new treatment methods plays an important role in improving the prognosis of OC. Ovarian cancer is one of the most malignant tumors in the female reproductive system and ranks second only to cervical cancer in global incidence and mortality [1]. Immunotherapy is a kind of therapy that can enhance the autoimmune ability of patients to kill or eliminate cancer cells. Immunocheckpoint inhibitors play a very important role in tumor treatment. Immunocheckpoint inhibitors have been used in melanoma [5], non-small cell lung cancer [6], Hodgkin’s lymphoma [7] and many other tumors. The overall response rate of patients to these inhibitors is still low [8]
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