2020
DOI: 10.18632/aging.102914
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A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer

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 analysi… Show more

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Cited by 31 publications
(28 citation statements)
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References 70 publications
(73 reference statements)
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“…Very recently, upregulation of CXCL-11 was identified as a protective prognostic factor that significantly associated with overall survival of ovarian cancer. 49 Indeed, it has been shown in other study that CXCL-11 occurred in the serum of patients with cancer 2 weeks post-treatment of anti-PD1/PDL-1 and sustained up to 6 weeks post-treatment. 50 Interestingly, patients who developed immune-related adverse events had lower levels of CXCL-11 at baseline.…”
mentioning
confidence: 90%
“…Very recently, upregulation of CXCL-11 was identified as a protective prognostic factor that significantly associated with overall survival of ovarian cancer. 49 Indeed, it has been shown in other study that CXCL-11 occurred in the serum of patients with cancer 2 weeks post-treatment of anti-PD1/PDL-1 and sustained up to 6 weeks post-treatment. 50 Interestingly, patients who developed immune-related adverse events had lower levels of CXCL-11 at baseline.…”
mentioning
confidence: 90%
“…In glioblastoma, the TME is strongly linked to gene expression and prognosis ( Cooper et al, 2012 ). In addition, cancer-associated fibroblasts (CAFs) enhance OC metastasis and induce upregulation of lipoma-preferred partner, which contributes to chemoresistance in OC ( Ding et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…Owing to advances in sequencing technologies, large amounts of bioinformatic data are available from public databases, including The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, enabling exploration of the association between TME and prognosis in tumors ( Zhang et al, 2019 ). The recently developed ESTIMATE algorithm can predict infiltration of non-tumor cells by evaluating specific gene expression in immune and stromal cells ( Ding et al, 2020 ). The ESTIMATE algorithm has been applied to various cancers, including prostate cancer, breast cancer, colon cancer, cutaneous melanoma, glioblastoma, and clear cell renal cell carcinoma ( Piperi et al, 2019 ; Bangbei et al, 2020 ; Yang H. et al, 2020 ; Yang S. et al, 2020 ; Zhang Z. et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…Previous studies have widely applied the ESTIMATE algorithm and clarified the meaningful relationship between microenvironment and multiple tumors, including glioblastoma [24], lung adenocarcinoma [25], gastric cancer [26], ovarian cancer [27],etc. The role of TME in AML has been explored and become a hotspot as well.…”
Section: Introductionmentioning
confidence: 99%