Epithelial Ovarian Cancer and the Immune System: Biology, Interactions, Challenges and Potential Advances for Immunotherapy

Macpherson, Anne M.; Barry, Simon C.; Ricciardelli, Carmela; Oehler, Martin K.

doi:10.3390/jcm9092967

Cited by 24 publications

(9 citation statements)

References 364 publications

(628 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The TME has an essential role in suppressing or enhancing the immune response (6). Recent studies have shown that an immunosuppressive TME is a major obstacle to successful implementation of tumor immunotherapy in OC patients (7,8). Therefore, understanding how the immune microenvironment of OC may hinder effective immune attack could guide the prediction of OC patients and promote more practical applications of immunotherapy in OC.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Landscape of Ovarian Cancer Immune Microenvironment Based on Integrated Multi-Omics Analysis

et al. 2021

View full text Add to dashboard Cite

Epithelial ovarian cancer has a low response rate to immunotherapy and a complex immune microenvironment that regulates its treatment outcomes. Understanding the immune microenvironment and its molecular basis is of great clinical significance in the effort to improve immunotherapy response and outcomes. To determine the characteristics of the immune microenvironment in ovarian cancer, we stratified ovarian cancer patients into three immune subtypes (C1, C2, and C3) using immune-related genes based on gene expression data from The Cancer Genome Atlas and found that these three subtypes had significant differences in immune characteristics and prognosis. Methylation and copy number variant analysis showed that the immune checkpoint genes that influenced immune response were significantly hypermethylated and highly deleted in the immunosuppressive C3 subtype, suggesting that epigenetic therapy may be able to reverse the efficacy of immunotherapy. In addition, the mutation frequencies of BRCA2 and CDK12 were significantly higher in the C2 subtype than in the other two subtypes, suggesting that mutation of DNA repair-related genes significantly affects the prognosis of ovarian cancer patients. Our study further elucidated the molecular characteristics of the immune microenvironment of ovarian cancer, which providing an effective hierarchical method for the immunotherapy of ovarian cancer patients, and has clinical relevance to the design of new immunotherapies and a reasonable combination strategies.

show abstract

Section: Introductionmentioning

confidence: 99%

Comprehensive Landscape of Ovarian Cancer Immune Microenvironment Based on Integrated Multi-Omics Analysis

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In our study, we found that the contents of the antigen presentation process were signi cantly different between the PRRIPM-low and PRRIPM-high groups in both the TCGA and ICGC cohorts. One possible speculation is that platinum-related chemotherapy will trigger tumor starvation, destruction of tumor cells and subsequent release of cell debris and tumor neo-antigens that are ingested by antigen presenting cells [37]. In addition, the PRRIPM-high groups in both the TCGA and ICGC cohorts had lower fractions of TILs and decreased type I IFN responses.…”

Section: Discussionmentioning

confidence: 99%

A Novel Platinum Resistance-related Immune Gene Signature for Overall Survival Prediction in Patients with Ovarian Cancer

Zhou

Ma²,

Luo

et al. 2022

Preprint

View full text Add to dashboard Cite

Background Ovarian cancer (OV) is a highly heterogeneous gynaecological tumor that makes the prognostic prediction challenging. Resistance to platinum-based chemotherapy is associated with a poor prognosis in OV. There seems to be an overlap between molecular mechanisms responsible for platinum resistance and immunogenicity in OV. However, the predictive role of platinum-resistance-related immune genes for OV prognosis needs to be further explored. Methods In our study, the mRNA expression data of OV patients with corresponding clinical information was collected from the TCGA and ICGC cohort. A multigene signature was constructed for OV patients in the TCGA cohort using the least absolute shrinkage and selection operator (LASSO) Cox regression model, and was validated in the ICGC cohort. Furthermore, we performed functional analysis to explore the immune status between the two risk groups. Results Our data showed that there were 41.1% of the platinum resistance-related genes differentially expressed between immune score low and high OV patients in the TCGA cohort. Univariate Cox regression analysis identified 30 differentially expressed genes (DEGs) associated with overall survival (OS) (P < 0.05). A 14-gene signature was established to classify OV patients into a low- and high-risk group. Patients in the low-risk group showed significantly higher OS than those in the high-risk group (P < 0.0001 in the both TCGA and ICGC cohort), which was associated with different immune status for the two risk groups. Conclusion A novel platinum resistance-related immune model can be used for prognostic prediction in OV. Targeting tumor immunity may be a therapeutic alternative for OV with platinum resistance.

show abstract

“…The immune checkpoint inhibitor-based antibody has improved survival for patients with various cancer types, such as lung cancer, malignant melanoma, and bladder cancer [ 67 ]. High levels of CD80 contribute to the maintenance of tolerance and immunosuppression in epithelial OC [ 68 ]. The OC microenvironment can induce migration of CTLA4 + regulatory T cells via C-C motif chemokine ligand 22 (CCL22) and C-C motif chemokine receptor 4 (CCR4) [ 54 , 69 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

Wei

Liu

Wang

et al. 2021

International Journal of Endocrinology

View full text Add to dashboard Cite

Background. The 5-year overall survival rate of ovarian cancer (OC) patients is less than 40%. Hypoxia promotes the proliferation of OC cells and leads to the decline of cell immunity. It is crucial to find potential predictors or risk model related to OC prognosis. This study aimed at establishing the hypoxia-associated gene signature to assess tumor immune microenvironment and predicting the prognosis of OC. Methods. The gene expression data of 378 OC patients and 370 OC patients were downloaded from datasets. The hypoxia risk model was constructed to reflect the immune microenvironment in OC and predict prognosis. Results. 8 genes (AKAP12, ALDOC, ANGPTL4, CITED2, ISG20, PPP1R15A, PRDX5, and TGFBI) were included in the hypoxic gene signature. Patients in the high hypoxia risk group showed worse survival. Hypoxia signature significantly related to clinical features and may serve as an independent prognostic factor for OC patients. 2 types of immune cells, plasmacytoid dendritic cell and regulatory T cell, showed a significant infiltration in the tissues of the high hypoxia risk group patients. Most of the immunosuppressive genes (such as ARG1, CD160, CD244, CXCL12, DNMT1, and HAVCR1) and immune checkpoints (such as CD80, CTLA4, and CD274) were upregulated in the high hypoxia risk group. Gene sets related to the high hypoxia risk group were associated with signaling pathways of cell cycle, MAPK, mTOR, PI3K-Akt, VEGF, and AMPK. Conclusion. The hypoxia risk model could serve as an independent prognostic indicator and reflect overall immune response intensity in the OC microenvironment.

show abstract

Epithelial Ovarian Cancer and the Immune System: Biology, Interactions, Challenges and Potential Advances for Immunotherapy

Cited by 24 publications

References 364 publications

Comprehensive Landscape of Ovarian Cancer Immune Microenvironment Based on Integrated Multi-Omics Analysis

Comprehensive Landscape of Ovarian Cancer Immune Microenvironment Based on Integrated Multi-Omics Analysis

A Novel Platinum Resistance-related Immune Gene Signature for Overall Survival Prediction in Patients with Ovarian Cancer

Identification of Hypoxia Signature to Assess the Tumor Immune Microenvironment and Predict Prognosis in Patients with Ovarian Cancer

Contact Info

Product

Resources

About