A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer.

Qi Ding,Shanshan Dong,Weigang Wang,Keqiang Zhang,Kee Wong,Yong Zeng,Ranran Wang,Xiao Zhou,Jing Wang,Ying Long,Huayi Ren,Hui Wang,Shuai Zhu

doi:10.18632/aging.102914

Abstract

Mounting evidence suggests that immune cell infiltration within the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in ovarian cancer (OC). In this study, 593 OC patients from TCGA were divided into high and low score groups based on their immune/stromal scores resulting from analysis utilizing the ESTIMATE algorithm. Differential expression analysis revealed 294 intersecting genes that influencing both the immune and stromal scores. Further Cox regression analysis identified 34 differentially expressed genes (DEGs) as prognostic-related genes. Finally, the nine-gene signature was derived from the prognostic-related genes using a Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression. This nine-gene signature could effectively distinguish the high-risk patients in the training (TCGA database) and validation (GSE17260) cohorts (all p < 0.01). A time-dependent receiver operating characteristic (ROC) analysis showed that the nine-gene signature had a reasonable predictive accuracy (AUC = 0.707, AUC =0.696) in both cohorts. In addition, this nine-gene signature is associated with immune infiltration in TME by Gene Set Variation Analysis (GSVA), and can be used to predict the survival of patients with OC.

Highlights

Ovarian cancer (OC) is one of the highest mortality rate malignant tumors of the female reproductive system [1]
Our work is the first to use the ESTIMATE algorithm combined with Least Absolute Shrinkage and Selection Operator (LASSO)-Cox to explore molecular markers associated with OC prognosis
We derived a series of TMEassociated differentially expressed genes (DEGs) by comparing the transcriptional expression profiles in 593 OC patients with high versus low stromal/immune scores based on The Cancer Genome Atlas (TCGA) data

Summary

Introduction

Ovarian cancer (OC) is one of the highest mortality rate malignant tumors of the female reproductive system [1]. The standard treatment plan for this disease is tumor cytoreductive surgery combined with platinum-based chemotherapy [3]. In this treatment mode, more than two-thirds of patients have a total survival of less than. Majority of the patients carry p53 mutation and possible BRCA1 and BRCA2 mutations Clinical observations of this type of patients are usually accompanied by metastatic lesions and poor prognosis [7]. From the perspective of treatment efficacy, the global loss of 5-Hydroxymethylcytosine is associated with platinum drug resistance, shortened progressionfree survival (PFS), and shortened overall survival (OS) in patients with high grade serous OC [8]. A number of studies in transcription and epigenetics have confirmed that the occurrence, development, and therapeutic efficacy of OC are influenced by the dynamic changes of multiple oncogenes and tumor suppressor genes [10,11,12,13,14,15]

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Results

Conclusion