Novel expression of CD11b in epithelial ovarian cancer: Potential therapeutic target

Saed, Ghassan M.; Fletcher, N.M.; Diamond, Michael P.; Morris, Robert T.; Gomez‐Lopez, Nardhy; Memaj, Ira

doi:10.1016/j.ygyno.2017.12.018

Cited by 17 publications

(16 citation statements)

References 23 publications

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“…Moreover, we were able to describe the occurrence of CTCs expressing CD11b, as it has been previously described in primary HGSOC cancer tissue [5]. Genomically altered (frequent genome-wide CNA) Type A-cells, one Type B-cell, as well as one cell of a not further specified type showed detectable CD11b expression.…”

Section: Discussionsupporting

confidence: 56%

“…4 Six Cycles Carboplatin and Paclitaxel. 5 Six Cycles Carboplatin. 6 Six Cycles Carboplatin and Paclitaxel, Bevacizumab every three Weeks and Durvalumab/Placebo + Olaparib/Placebo.…”

Section: Characterization Of Study Patientsmentioning

confidence: 99%

“…Most cancers can be linked to driver mutations, causing disease progression, whereas OC is commonly characterized by a chromosomal instability (CIN), resulting in great amounts of copy number alterations (CNA) with TP53 mutations being only one of the genetic driving forces [2][3][4]. Currently, novel surface antigen expressions such as CD11b, unexpectedly expressed in OC tissues, are expanding the knowledge of potential actionable targets in OC [5]. However, there is still an insufficient understanding of OC disease evolution, since tumor tissue is usually only available at primary diagnosis.…”

Section: Introductionmentioning

confidence: 99%

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Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

Salmon

Levermann

Neves

et al. 2021

Cancers

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In Ovarian Cancer (OC), the analysis of single circulating tumor cells (sCTCs) might help to investigate genetic tumor evolution during the course of treatment. Since common CTC identification features failed to reliably detect CTCs in OC, we here present a workflow for their detection and genomic analysis. Blood of 13 high-grade serous primary OC patients was analyzed, using negative immunomagnetic enrichment, followed by immunofluorescence staining and imaging for Hoechst, ERCC1, CD45, CD11b and cytokeratin (CK) and sCTC sorting with the DEPArrayTM NxT. The whole genome of single cells was amplified and profiled for copy number variation (CNV). We detected: Type A-cells, epithelial (Hoechstpos, ERCC1pos, CD45neg, CD11bpos, CKpos); Type B-cells, potentially epithelial (Hoechstpos, ERCC1pos, CD45neg, CD11bpos, CKneg) and Type C-cells, potentially mesenchymal (Hoechstpos, ERCC1pos, CD45neg, CD11bneg, CKneg). In total, we identified five (38.5%) patients harboring sCTCs with an altered CN profile, which were mainly Type A-cells (80%). In addition to inter-and intra-patient genomic heterogeneity, high numbers of Type B- and C-cells were identified in every patient with their aberrant character only confirmed in 6.25% and 4.76% of cases. Further identification markers and studies in the course of treatment are under way to expand sCTC analysis for the identification of tumor evolution in OC.

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Section: Discussionsupporting

confidence: 56%

“…4 Six Cycles Carboplatin and Paclitaxel. 5 Six Cycles Carboplatin. 6 Six Cycles Carboplatin and Paclitaxel, Bevacizumab every three Weeks and Durvalumab/Placebo + Olaparib/Placebo.…”

Section: Characterization Of Study Patientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

Salmon

Levermann

Neves

et al. 2021

Cancers

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“…As illustrated in the PPI network, CXCR4 as a chemokine receptor has been found to be upregulated in cancer metastasis, and it has been used as a prognostic marker in various types of cancer, including leukemia, breast cancer, and prostate cancer [35][36][37]. As a major surface antigen family on human leukocyte family member, previous studies have reported the key role of ITGAM in the development and prognosis of human leukemia [38], ovarian cancer [39], and colorectal cancer [40]. ITGAM has been found to be upregulated PRAD after analyzing the patient samples [41], but there was no research on the role of ITGAM gene in PRAD, indicating the need for additional research to clarify its role in the prognosis of PRAD.…”

Section: Discussionmentioning

confidence: 99%

Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas

Zhao

et al. 2020

BioMed Research International

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Background. Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find potential related genes for predicting the prognosis of patients with PRAD. Methods. We downloaded gene expression profiles and clinical sample information from TCGA for 490 patients with PRAD (patient age: 41-78 years). We calculated stromal and immune scores using the ESTIMATE algorithm to predict the level of stromal and immune cell infiltration. We categorized patients with PRAD in TCGA into high and low score arrays according to their median immune/stromal scores and identified differentially expressed genes (DEGs) that were significantly correlated with the prognosis of PRAD. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The association between DEGs and overall survival was investigated by weighted Kaplan–Meier survival analysis and multivariate analysis. Furthermore, the protein-protein interaction network (PPI) of DEGs was constructed using the STRING tool. Finally, the hub genes were identified by analyzing the degree of association of PPI networks. Results. We found that 8 individual DEGs, C6, S100A12, MLC1, PAX5, C7, FAM162B, CAMK1G, and TCEAL5, were significantly predictive of favorable overall survival and one DEG, EPYC, was associated with poor overall survival. GO and KEGG pathway analyses revealed that the DEGs were associated with immune responses. Moreover, 30 hub genes were obtained using the PPI network of DEGs: ITGAM, CD4, CD3E, IL-10, LCP2, ITGB2, ZAP-70, C3, CCL19, CXCL13, CXCL9, BTK, CCL21, CD247, CD28, CD3D, FCER1G, PTPRC, TYROBP, CCR5, ITK, CCL13, CCR1, CCR2, CD79B, CYBB, IL2RG, JAK3, PLCG2, and CD19. These prominent nodes had the most associations with other genes, indicating that they might play crucial roles in the prognosis of PRAD. Conclusions. We extracted a list of genes associated with the prostate adenocarcinoma microenvironment, which might contribute to the prediction and interpretation of PRAD prognosis.

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“…Besides CD83 , a large number of the CD83 highly-associated genes (Person correlation >0.5, p < 0.01) within ovarian cancer transcriptome showed higher expression in ovarian cancer cells, especially in the EpCAM + /CD45 + subtypes ( Figure S1 ). CD83 highly-associated genes, such as ITGAM , IL1B , CYBB , PIK3R5 , BTK, and OSM , ectopically express in ovarian cancer cells or tissues, involving in ovarian cancer progression, hypoxia networks, and the development of chemoresistance [ 44 , 45 , 46 , 47 , 48 , 49 ]. Finally, we found that ovarian cancer patients’ survival inversely correlated with the level of CD83 expression in 907 ovarian cancer patients (low CD83 expression: 652, the high expression: 255), as patients with high CD83 expression lived significantly shorter compared with their counterparts with low CD83 expression ( Figure 1 d).…”

Section: Resultsmentioning

confidence: 99%

CD83, a Novel MAPK Signaling Pathway Interactor, Determines Ovarian Cancer Cell Fate

Batool

Líu

Liu

et al. 2020

Cancers

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Ovarian cancer is a leading cause of death from gynecologic malignancies worldwide. Although CD83 is widely described as a solid marker for mature dendritic cells, emerging pieces of evidence indicate the expression of membrane protein CD83 by various tumor cells, including ovarian cancer cells. However, the potential role of CD83 in ovarian cancer cell properties and development remains absolutely unknown. By using human CD83 stable overexpression and knockdown sublines of several ovarian cancer cells, we observed that CD83 advanced the growth proliferation, colony formation ability, spheroid formation, and in vivo tumorigenicity of ovarian cancer cells; surprisingly, CD83 limited their migration and invasion potentials. Positive regulation of proliferation/stemness factors (e.g., cyclin-CDKs and KIT/CD44) but negative regulation of matrix metallopeptidases (e.g., MMP1 and 7) by CD83 were revealed by the integrated analysis of transcriptome and proteome. Furthermore, immunoprecipitation-mass spectrometry (IP-MS) and co-immunoprecipitation (Co-IP) first identified the association of CD83 with MAP3K7 (also known as TAK1) and MAP3K7-binding protein TAB1 on the cell membrane. Moreover, CD83 functions through the activation of MAP3K7-MEK1/2-ERK1/2 cascades to further regulate downstream FOXO1/p21/CDK2/CCNB1 and STAT3/DKK1 signaling pathways, thus activating proliferation and spheroid formation of ovarian cancer cells, respectively. Collectively, our findings define a CD83-MAPK pathway in the regulation of proliferation and stemness in ovarian cancer cells, with potential therapeutic applications in blocking their progression.

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Novel expression of CD11b in epithelial ovarian cancer: Potential therapeutic target

Cited by 17 publications

References 23 publications

Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas

CD83, a Novel MAPK Signaling Pathway Interactor, Determines Ovarian Cancer Cell Fate

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