A prognosis‑predictive nomogram of ovarian cancer with two immune‑related genes: <em>CDC20B</em> and <em>PNPLA5</em>

Abstract

Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3-and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3-and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.

Effect of forsythoside A on the transcriptional profile of bovine mammary epithelial cells challenged with lipoteichoic acid

“…Han Lin et al found that CDC20B is one of the prognostic genes in ovarian cancer patients through sequencing and data analysis. The gene is overexpressed in ovarian cancer tissue (Lin et al, 2020). Longfei Yang et al found that CDC20B is one of the therapeutic targets of the novel anti-tumour peptide SA12, which can provide targeted therapy for breast cancer (Yang et al, 2015).…”

Identification of a glycolysis‐related gene signature for survival prediction of ovarian cancer patients

“…The included studies 11,35–47,54–61 used models built based on the TCGA cohort and involved all types of breast cancer. The final results showed that our signature and three other prognostic signatures, namely, a 21 immune‐related gene signature, 35 17 immune‐related gene signature 36 and 17 TF‐related gene signature 37 performed better than the other hallmark signatures in the prediction of OS in patients with OV 11,35,38–47,54–61 . Additionally, Yu et al has constructed a five GRG signature (ANGPTL4, PYGB, ISG20, SEH1L and IRS2) for patients with OV 62 .…”

“…To further explore the predictive ability of our signature, a comparison was performed among several significant molecular signatures that were employed for predicting OS in patients with OV. The included studies 11 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 used models built based on the TCGA cohort and involved all types of breast cancer. The final results showed that our signature and three other prognostic signatures, namely, a 21 immune‐related gene signature, 35 17 immune‐related gene signature 36 and 17 TF‐related gene signature 37 performed better than the other hallmark signatures in the prediction of OS in patients with OV.…”

“…The final results showed that our signature and three other prognostic signatures, namely, a 21 immune‐related gene signature, 35 17 immune‐related gene signature 36 and 17 TF‐related gene signature 37 performed better than the other hallmark signatures in the prediction of OS in patients with OV. 11 , 35 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 Additionally, Yu et al has constructed a five GRG signature (ANGPTL4, PYGB, ISG20, SEH1L and IRS2) for patients with OV. 62 The AUCs of the signature in Yu's study at 5‐years were 0.680.…”

The Dual Blockade of the TIGIT and PD-1/PD-L1 Pathway as a New Hope for Ovarian Cancer Patients

“…Despite the advances in the field of OC treatment and implementation of standard therapy, the prognosis for OC patients is poor, and the five-year survival rate is only 47% [ 2 ]. For comparison, the five-year survival rate for cervical cancer totals 66% and for uterine cancer 81% [ 3 ].…”