RB1 Is an Immune-Related Prognostic Biomarker for Ovarian Cancer

Xie, Biao; Tan, Guangqing; Ren, Jingyi; Lu, Wei-Yu; Pervaz, Sadaf; Ren, Xinyi; Otoo, Antonia; Tang, Jing; Li, Fangfang; Wang, Yingxiong; Wang, Meijiao

doi:10.3389/fonc.2022.830908

Cited by 10 publications

(5 citation statements)

References 57 publications

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“… enhances immunotherapy sensitivity [ 54 , 55 ]. predicts the poor prognosis of OC [ 56 , 57 ]. ZBP1 mediates innate immunity, balance inflammation and cell death [ 58 ].…”

Section: Discussionmentioning

confidence: 99%

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

Cai,

Lin,

Liu

et al. 2024

BMC Cancer

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Background Ovarian cancer (OC) is a gynecological malignancy tumor with high recurrence and mortality rates. Programmed cell death (PCD) is an essential regulator in cancer metabolism, whose functions are still unknown in OC. Therefore, it is vital to determine the prognostic value and therapy response of PCD-related genes in OC. Methods By mining The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Genecards databases, we constructed a prognostic PCD-related genes model and performed Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic (ROC) curve for its predictive ability. A nomogram was created via Cox regression. We validated our model in train and test sets. Quantitative real-time PCR (qRT-PCR) was applied to identify the expression of our model genes. Finally, we analyzed functional analysis, immune infiltration, genomic mutation, tumor mutational burden (TMB) and drug sensitivity of patients in low- and high-risk group based on median scores. Results A ten-PCD-related gene signature including protein phosphatase 1 regulatory subunit 15 A (PPP1R15A), 8-oxoguanine-DNA glycosylase (OGG1), HECT and RLD domain containing E3 ubiquitin protein ligase family member 1 (HERC1), Caspase-2.(CASP2), Caspase activity and apoptosis inhibitor 1(CAAP1), RB transcriptional corepressor 1(RB1), Z-DNA binding protein 1 (ZBP1), CD3-epsilon (CD3E), Clathrin heavy chain like 1(CLTCL1), and CCAAT/enhancer-binding protein beta (CEBPB) was constructed. Risk score performed well with good area under curve (AUC) (AUC3 − year =0.728, AUC5 − year = 0.730). The nomogram based on risk score has good performance in predicting the prognosis of OC patients (AUC1 − year =0.781, AUC3 − year =0.759, AUC5 − year = 0.670). Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the erythroblastic leukemia viral oncogene homolog (ERBB) signaling pathway and focal adhesion were enriched in the high-risk group. Meanwhile, patients with high-risk scores had worse OS. In addition, patients with low-risk scores had higher immune-infiltrating cells and enhanced expression of checkpoints, programmed cell death 1 ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO-1) and lymphocyte activation gene-3 (LAG3), and were more sensitive to A.443,654, GDC.0449, paclitaxel, gefitinib and cisplatin. Finally, qRT-PCR confirmed RB1, CAAP1, ZBP1, CEBPB and CLTCL1 over-expressed, while PPP1R15A, OGG1, CASP2, CD3E and HERC1 under-expressed in OC cell lines. Conclusion Our model could precisely predict the prognosis, immune status and drug sensitivity of OC patients.

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“… enhances immunotherapy sensitivity [ 54 , 55 ]. predicts the poor prognosis of OC [ 56 , 57 ]. ZBP1 mediates innate immunity, balance inflammation and cell death [ 58 ].…”

Section: Discussionmentioning

confidence: 99%

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

Cai,

Lin,

Liu

et al. 2024

BMC Cancer

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“…Micro-RNA and short hairpin-RNA were used in vitro and in vivo in mice to downregulate CCND1 resulting in a substantial benefit in OC management (tier-IVA) 30,31 . Other genes like, POLE, RB1, TERT, GNAS, CTNNB1, RNF43 and SPOP have prognostic values or are frequently altered/upregulated in certain histologic subtypes, but are currently not considered as targets matched to specific treatments (tier-X) [32][33][34][35][36][37][38] .…”

Section: Discussionmentioning

confidence: 99%

Identification of potentially actionable genetic variants in epithelial ovarian cancer: a retrospective cohort study

Fieuws,

Van der Meulen,

Proesmans

et al. 2024

npj Precis. Onc.

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Ovarian cancer is the most lethal gynecologic malignancy, mainly due to late-stage diagnosis, frequent recurrences, and eventually therapy resistance. To identify potentially actionable genetic variants, sequencing data of 351 Belgian ovarian cancer patients were retrospectively captured from electronic health records. The cohort included 286 (81%) patients with high-grade serous ovarian cancer, 17 (5%) with low-grade serous ovarian cancer, and 48 (14%) with other histotypes. Firstly, an overview of the prevalence and spectrum of the BRCA1/2 variants highlighted germline variants in 4% (11/250) and somatic variants in 11% (37/348) of patients. Secondly, application of a multi-gene panel in 168 tumors revealed a total of 214 variants in 28 genes beyond BRCA1/2 with a median of 1 (IQR, 1–2) genetic variant per patient. The ten most often altered genes were (in descending order): TP53, BRCA1, PIK3CA, BRCA2, KRAS, ERBB2 (HER2), TERT promotor, RB1, PIK3R1 and PTEN. Of note, the genetic landscape vastly differed between the studied histotypes. Finally, using ESCAT the clinical evidence of utility for every genetic variant was scored. Only BRCA1/2 pathogenic variants were classified as tier-I. Nearly all patients (151/168; 90%) had an ESCAT tier-II variant, most frequently in TP53 (74%), PIK3CA (9%) and KRAS (7%). In conclusion, our findings imply that although only a small proportion of genetic variants currently have direct impact on ovarian cancer treatment decisions, other variants could help to identify novel (personalized) treatment options to address the poor prognosis of ovarian cancer, particularly in rare histotypes.

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“…The TIMER and THPA sites con rmed higher levels of CYBB gene expression in tumor tissues compared to normal tissues, but ovarian cancer studies are lacking and more data are needed [ 42 ]. RB 1 is a novel immune-related prognostic biomarker for ovarian cancer and may be a promising therapeutic target for ovarian cancer, which is consistent with previous reports by Biao Xie, Guangqing Tan, et al studies [42] VE GF A is an angiogenic drug and a therapeutic target in ovarian cancer [43]. Together, these biomarkers have many potential therapeutic and prognostic implications for the management of ovarian cancer patients.…”

Section: Discussionmentioning

confidence: 99%

Study on the relationship between Ferroptosis gene and immune microenvironment in ovarian cancer and related prognostic model construction

Gao

hua

2023

Preprint

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Ovarian cancer (OC) has a high recurrence rate and insufficient early screening methods, with a 5-year survival rate of less than 50% However, in many cases, simple standard treatment results are not satisfactory. Therefore, more effective treatments are being sought Ferroptosis is a recently discovered form of cell death associated with loss of glutathione peroxidase 4 (GPX 4) activity and accumulation of reactive lipid oxygen species (ROS), which shows great potential for anticancer therapy[1]. The results of immunotherapy for ovarian cancer are not ideal, but some studies have shown that the results of immunotherapy are significantly improved when combined with other treatments. Gene expression profiling allows researchers to explore and elucidate the molecular mechanisms underlying disease at the genomic and transcriptomic levels. integration of genomic technology and bioinformatics analysis Although these tools allow researchers to screen for tumor-associated genes and identify key prognostic factors, single-gene biomarkers that provide effective survival predictions are limited. Multigene-based risk models may provide better prognostic factors to predict patient survival[2]. identify multigene risk score characteristics by bioinformatic analysis and find more potential biomarkers for effective diagnosis and prognosis assessment of ovarian cancer patients. Based on TCGA and GEO transcript expression data and associated clinical data, a scoring system was developed using consensus cluster analysis, univariate Cox regression analysis, and lasso regression and validated against GEO database data. The results of univariate and multivariate risk analysis showed that the score can be used as an independent prognostic marker of ovarian cancer.

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RB1 Is an Immune-Related Prognostic Biomarker for Ovarian Cancer

Cited by 10 publications

References 57 publications

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

Identification of potentially actionable genetic variants in epithelial ovarian cancer: a retrospective cohort study

Study on the relationship between Ferroptosis gene and immune microenvironment in ovarian cancer and related prognostic model construction

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