Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer

Li, Chanyuan; Deng, Ting; Cao, Junya; Zhou, Yun; Luo, Xiaolin; Feng, Yanling; Huang, He; Liu, Jihong

doi:10.3390/diagnostics13061169

Cited by 11 publications

(7 citation statements)

References 38 publications

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“…Whereas lysozyme (LYZ) is an antimicrobial ligand and is involved in central macrophage function and is therefore nonspecifically and highly expressed, LILRB4 is an immune checkpoint on myeloid cells, indicating a more regulatory role. High expression of the integrin ITGB2 was previously shown to be associated with poor survival outcome [88], underscoring that high expression in TAMs is crucial. In contrast, ITGB2 is also associated with CD8+ T cells, as it encodes the beta chain of the LFA-1 protein, which has been shown to be essential in the assembly of the immune synapse or to influence lymphocyte extravasation and T-cell recruitment to the tumor and is regulated by GDF-15 [89].…”

Section: Discussionmentioning

confidence: 99%

Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

Gronauer,

Madersbacher,

Monfort-Lanzas

et al. 2024

Preprint

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Background: High-grade serous ovarian cancer (HGSOC) remains the most lethal gynecologic malignancy despite new therapeutic concepts, including poly-ADP-ribose polymerase inhibitors (PARPis) and antiangiogenic therapy. The efficacy of immunotherapies is modest, but clinical trials investigating the potential of combination immunotherapy with PARPis are underway. Homologous recombination repair deficiency (HRD) or BRCAness and the composition of the tumor microenvironment appear to play a critical role in determining the therapeutic response. Methods: We conducted comprehensive immunogenomic analyses of HGSOC using data from several patient cohorts, including a new cohort from the Medical University of Innsbruck (MUI). Machine learning methods were used to develop a classification model for BRCAness from gene expression data. Integrated analysis of bulk and single-cell RNA sequencing data was used to delineate the tumor immune microenvironment and was validated by immunohistochemistry. The impact of PARPi and BRCA1 mutations on the activation of immune-related pathways was studied in vitro using ovarian cancer cell lines, RNA sequencing, and immunofluorescence analysis. Results: We identified a predictive 24-gene signature to determine BRCAness. Comprehensive analysis of the tumor microenvironment allowed us to identify patient samples with BRCAness and high immune infiltration. Further characterization of these samples revealed increased infiltration of immunosuppressive cells, including tumor-associated macrophages (TAMs) expressing TREM2, C1QA, and LILRB4, as identified by further analysis of single-cell RNA sequencing data and gene expression analysis of samples from patients receiving combination therapy with PARPi and anti-PD-1. PARPi activated the cGAS-STING signaling pathway and the downstream innate immune response in a similar manner to HGSOC patients with BRCAness status. We have developed a web application (https://ovrseq.icbi.at) and an associated R package OvRSeq, which allow for comprehensive characterization of ovarian cancer patient samples and assessment of a vulnerability score that enables stratification of patients to predict response to the mentioned combination immunotherapy. Conclusions: Genomic instability in HGSOC affects the tumor immune environment, and TAMs play a crucial role in modulating the immune response. Based on various datasets, we have developed a diagnostic application that uses RNA sequencing data not only to comprehensively characterize HGSOC but also to predict vulnerability and response to combination immunotherapy. Keywords: High-grade serous ovarian cancer, BRCAness, PARP inhibitor, immunotherapy, vulnerability, RNA sequencing, tumor-associated macrophages, tumor immune microenvironment

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Section: Discussionmentioning

confidence: 99%

Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

Gronauer,

Madersbacher,

Monfort-Lanzas

et al. 2024

Preprint

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“…Research has shown that ITGB2 is highly expressed in a number of cancers, such as colorectal cancer, renal clear-cell carcinoma, papillary thyroid cancer, and breast cancer [ 50 ]. Many studies have demonstrated that ITGB2 is overexpressed in ovarian cancer relative to normal ovarian tissue; it is linked to metastasis and poor prognosis in ovarian cancer and can be used as a prognostic immunomarker [ 51 ]. Existing ovarian cancer studies suggest that ITGB2 targeted therapy should be explored.…”

Section: Discussionmentioning

confidence: 99%

“…According to Ciucci et al, LG tumors exhibited a lower density of tumor-infiltrating CD68+ macrophage, along with an attenuated M2-skewed (CD163+) phenotype than benign and borderline tumors [ 76 ]. In another study by Li et al, M2 macrophage infiltration is strongly correlated with ITGB2 expression in ovarian cancer patients [ 51 ]. Similarly, SPP1, which is also an important DEG in our study, was reported to be significantly correlated with infiltrating levels of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells [ 75 ].…”

Section: Discussionmentioning

confidence: 99%

In Silico Approach to Molecular Profiling of the Transition from Ovarian Epithelial Cells to Low-Grade Serous Ovarian Tumors for Targeted Therapeutic Insights

Leblebici,

Sancar,

Tercan

et al. 2024

CIMB

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This paper aims to elucidate the differentially coexpressed genes, their potential mechanisms, and possible drug targets in low-grade invasive serous ovarian carcinoma (LGSC) in terms of the biologic continuity of normal, borderline, and malignant LGSC. We performed a bioinformatics analysis, integrating datasets generated using the GPL570 platform from different studies from the GEO database to identify changes in this transition, gene expression, drug targets, and their relationships with tumor microenvironmental characteristics. In the transition from ovarian epithelial cells to the serous borderline, the FGFR3 gene in the “Estrogen Response Late” pathway, the ITGB2 gene in the “Cell Adhesion Molecule”, the CD74 gene in the “Regulation of Cell Migration”, and the IGF1 gene in the “Xenobiotic Metabolism” pathway were upregulated in the transition from borderline to LGSC. The ERBB4 gene in “Proteoglycan in Cancer”, the AR gene in “Pathways in Cancer” and “Estrogen Response Early” pathways, were upregulated in the transition from ovarian epithelial cells to LGSC. In addition, SPP1 and ITGB2 genes were correlated with macrophage infiltration in the LGSC group. This research provides a valuable framework for the development of personalized therapeutic approaches in the context of LGSC, with the aim of improving patient outcomes and quality of life. Furthermore, the main goal of the current study is a preliminary study designed to generate in silico inferences, and it is also important to note that subsequent in vitro and in vivo studies will be necessary to confirm the results before considering these results as fully reliable.

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“…High expression in cancer-associated fibroblast (CAF) could promote oral squamous cell carcinoma proliferation by regulating PI3K/AKT/mTOR pathways to enhance glycolysis activity in CAFs (64). Moreover, high expression of ITGB2 was also reported to be correlated with poor prognosis in some cancers (65,66). However, ITGB2 presented with opposite functions in NSCLC.…”

Section: B C D E F G Amentioning

confidence: 99%

Comprehensive analyses for the coagulation and macrophage-related genes to reveal their joint roles in the prognosis and immunotherapy of lung adenocarcinoma patients

Li,

Yin,

Luan

et al. 2023

Front. Immunol.

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PurposeThis study aims to explore novel biomarkers related to the coagulation process and tumor-associated macrophage (TAM) infiltration in lung adenocarcinoma (LUAD).MethodsThe macrophage M2-related genes were obtained by Weighted Gene Co-expression Network Analysis (WGCNA) in bulk RNA-seq data, while the TAM marker genes were identified by analyzing the scRNA-seq data, and the coagulation-associated genes were obtained from MSigDB and KEGG databases. Survival analysis was performed for the intersectional genes. A risk score model was subsequently constructed based on the survival-related genes for prognosis prediction and validated in external datasets.ResultsIn total, 33 coagulation and macrophage-related (COMAR) genes were obtained, 19 of which were selected for the risk score model construction. Finally, 10 survival-associated genes (APOE, ARRB2, C1QB, F13A1, FCGR2A, FYN, ITGB2, MMP9, OLR1, and VSIG4) were involved in the COMAR risk score model. According to the risk score, patients were equally divided into low- and high-risk groups, and the prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. The ROC curve indicated that the risk score model had high sensitivity and specificity, which was validated in multiple external datasets. Moreover, the model also had high efficacy in predicting the clinical outcomes of LUAD patients who received anti-PD-1/PD-L1 immunotherapy.ConclusionThe COMAR risk score model constructed in this study has excellent predictive value for the prognosis and immunotherapeutic clinical outcomes of patients with LUAD, which provides potential biomarkers for the treatment and prognostic prediction.

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Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer

Cited by 11 publications

References 38 publications

Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

Integrated immunogenomic analyses of high-grade serous ovarian cancer reveal vulnerability to combination immunotherapy

In Silico Approach to Molecular Profiling of the Transition from Ovarian Epithelial Cells to Low-Grade Serous Ovarian Tumors for Targeted Therapeutic Insights

Comprehensive analyses for the coagulation and macrophage-related genes to reveal their joint roles in the prognosis and immunotherapy of lung adenocarcinoma patients

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