Unveiling immunological and prognostic potential of FBXO2 in BC based on Pan-Cancer and Single cell analyses

doi:10.21203/rs.3.rs-4904750/v1

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Unveiling immunological and prognostic potential of FBXO2 in BC based on Pan-Cancer and Single cell analyses

https://doi.org/10.21203/rs.3.rs-4904750/v1

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Background

Breast cancer (BC) is a typical females’ malignant tumors. Ubiquitin-proteasome system (UPS) is a critical pathway for pathogenesis of BC. Activation of UPS determined by SKP1–cullin 1–F-box protein (SCF) E3 ligase complexes. F-Box Protein 2 (FBXO2), a pivotal member of F-box proteins family, is related with UPS and mitophagy. FBXO2 have attracted increasing attention in multiple cancers. The relationship between FBXO2 and many cancers is still unclear. Therefore, systematic research on FBXO2 and pan-cancer is very important for the development and drug resistance of BC.

Method

Transcriptome expression data of 33 cancer types were acquired from the Cancer Genome Atlas (TCGA) database. Wilcoxon’s test was performed to estimate molecular characteristic of FBOX2 in human pan-cancer. To confirmed the relationship between FBXO2 and BC, mendelian randomization (MR) was performed. Kaplan–Meier (KM) curves to analyze the survival features of FBXO2. Additionally, the protein level and methylation level of FBXO2 was explored based on Wilcoxon’s test. Single cell sequence analyses were used to furtherly confirmed the importance of FBXO2. Finally, underlying mechanism of FBXO2 was explored from various perspectives, including gene function, immune checkpoint and tumor microenvironment.

Result

Our research revealed that FBXO2 expression were up-regulation in multiple cancers through pan-cancer analyses. It was first found to be downregulated in BC. MR analyses confirmed the caused relationship on FBXO2 and BC. Protein level analyses of FBXO2 revealed that FXBO2 was downregulated in BC. KM analyses indicated that Low FXBO2 expression had poor overall survival (OS) and recurrence free survival (DFS) in BC. Single cell sequence analyses revealed that FBXO2 obviously enriched in malignant epithelial cell. Our research unveiled that FBXO2 was a pivotal role in BC.

Conclusion

Comprehensive analysis unveiling immunological and promising potential value of FBXO2 in BC. It provided a new insight in pathogenesis of BC.

FBXO2

Breast cancer

immune cells

single cell sequence

pan-cancer

survival

Breast cancer (BC) is one of the most common females’ malignant tumors in worldwide^1,2. Its incidence and mortality rates still are still increasing³. Despite great progress have achieve in the pathogenesis and treatment of breast cancer, the prognosis remains poor⁴. Therefore, in-depth research is still needed to reveal its complex molecular mechanisms and to identify new therapeutic targets.

Ubiquitin-proteasome system (UPS) is a critical pathway for protein degradation^5,6. Accumulated researches unveil that protein degradation is associated with development and proliferation of cancer⁷. The activation of UPS determined by E3 ligase⁸. F-box proteins, the substrate-recognition subunits of SKP1–cullin 1–F-box protein (SCF) E3 ligase complexes^9,10, played vital roles in proteins degradation through ubiquitylation^11,12. F-Box Protein 2 (FBXO2) is a pivotal member of F-box proteins family. Previous studies reveal that FBXO2 can mediates ubiquitination process of glycosylated SUN2 to promote ovarian cancer¹³. Low expression of FBXO2 can inhibits the growth and metastasis of gastric cancer cells by regulating epithelial mesenchymal transition (EMT)¹⁴. Although FBXO2 have attracted increasing attention, the relationship between FBXO2 and many cancers still gaps. Systematic study of FBXO2 in breast cancer is very important for the development and drug resistance of breast cancer.

Mendelian randomization (MR) is an alternative method for inferring potential causal relationships^15–17, using single nucleotide polymorphism (SNP) as an instrumental variable for exposure factors to estimate the causal relationship between exposure and outcomes. Therefore, we firstly performed MR analyses to confirm causal relationship which FBXO2 expressed difference led to development of BC, rather than BC causing FBXO2 expressed difference. Subsequently, we systematically analyzed FBXO2 specific expression in pan-cancer. Finally, we explored the underlying mechanism of FBXO2 combining bulk RNA and single cell RNA sequence. Our findings gain a deeper understanding of the functions and regulatory mechanisms of FBXO2 in breast cancer, providing new insight.

Data acquisition

Transcriptome expression data of 33 cancer types were acquired from the Cancer Genome Atlas (TCGA) database. GWAS summary data of FBXO2 (eqtl-a-ENSG00000116661) and BC (ieu-a-1130) were obtained from IEU Open GWAS dataset through TwoSampleMR R package. Methylation data of BC came from TGCA databases. Proteomics data of breast cancer derived from the Clinical Proteomic Tumor Analysis Consortium (CTPC) databases.

Molecular characteristic of FBOX2 in human pan-cancer

To understood the specificity of FBXO2 in human pan-cancer, Wilcoxon’s test was used to investigate FBXO2 expression differences in 33 TCGA cancer types. P < 0.05 existed statistical significance (*P < 0.05; **P < 0.01; ***P < 0.001).

Bidirectional mendelian randomization analyses

To confirm causal relationship that FBXO2 expressed difference led to development of BC, rather than BC causing FBXO2 expressed difference. A bidirectional MR analyses was performed. In our analysis, SNPs with P < 5x10-8 were selected out for instrumental variables (IVs). Standard clumping parameter (r² < 0.001 and clump distance = 10000 kb) was executed. IVs with F < 10 were identified as weak instrumental variables and excluded. The MR analyses were completed by using TwoSampleMR R package. Inverse variance weighted method (ivw) was used to judge significance. Directional pleiotropy was checked by horizontal pleiotropy test. The leave-one-out sensitivity test was used to confirmed stability of MR results¹⁸.

Single cell RNA sequence analyses

Single cell RNA sequence of BC samples and normal breast samples were acquired from GSE161529. The scanpy python package was used to analysis single cell RNA sequence. Low-quality samples with cells number < 1500 were excluded. Low-quality cells with gene number < 200 and > 7000 and a percentage of mitochondrial genes < 20% were filtered out. BBKNN method was used for batch alignment. Subsequently, cell cluster was performed using leiden method. Infercnvpy python package was performed to identify malignant epithelial cells.

Gene set enrichment analyses (GSEA)

GSEA was used to estimate the signaling pathways of FBXO2. A gene list was generated by using limma R package. Samples with the highest quartile of FBXO2 expression levels were identified as high FBXO2 group. Samples with the lowest quartile of FBXO2 expression levels were identified as low FBXO2 group. Subsequently, GSEA were performed to decipher the enriched signaling pathways of FBXO2 by using clusterProfiler R package. Pathway with adjust P value < 0.05 were considered statistically significant.

Correlation between FBXO2 and immune in pan-cancer

IOBR R package was utilized to analyses immune cell infiltration of TCGA samples. Pearson correlation analyses was used to estimate the association of FBXO2 and immune checkpoint or immune cell.

Statistical Analyses

Our analyses were conducted by using R and python. Wilcoxon’s test was used to estimate statistic difference of FBXO2 protein level and promoter methylation. Kruskal-Wallis’ test was used to investigate the relationship between FBXO2 and tumor stage. KM analyses was performed in kmplot database (https://kmplot.com/analysis/). P < 0.05. were deemed significant in all statistical analyses.

Molecular characteristics of FBOX2 in human pan-cancer

FBXO2 existed significant difference between cancer tissue and paracaner in multiple cancers. FBXO2 was up-regulation in bladder cancer (BRCA), cervical squamous cell endocervical adenocarcinoma (CESC), esophageal carcinoma (ESCA), head and neck squamous cell cancer (HNSC), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) pheochromocytoma and paraganglioma (PCPG), stomach adenocarcinoma (STAD) and thyroid carcinoma (THCA). Interestingly, FBXO2 was down-regulation in only four cancers, including BC glioblastoma multiforme (GBM), kidney renal clear cell carcinoma (KIRC) and prostate adenocarcinoma (PRAD) (Fig. 1A). Significant difference was also more evident in cancer and pair paracaner (Fig. 1B). Our results illustrated that FBXO2 is specificity in different cancers and a pivotal target gene.

Bidirectional MR analyses

To confirm causal relationship that FBXO2 expressed difference led to development of BC, rather than BC causing FBXO2 expressed difference. Bidirectional MR analyses was performed. Our results revealed that low FBXO2 had significant associated with risk of BC (P = 0.042, Fig. 2). Moreover, there was no evidence of horizontal pleiotropy (Intercept = -0.06, se = 0.03, p = 0.19, Table 1). The robustness of results was confirmed by the leave-one-out sensitivity test (Figure S1). While our results did not find that BC caused FBXO2 expressed alteration (p = 0.99, Fig. 2).

Table 1

The result of horizontal pleiotropy
exposure	outcome	pleiotropy test
exposure	outcome	Intercept	Se	P value
FBXO2	Breast Cancer	-0.06	0.03	0.19
Breast Cancer	FBXO2	0.00096	0.01	0.94

FBXO2 feature and prognostic value in breast cancer

Above analyses had revealed that FBXO2 mRNA level was down-regulated gene in BC. However, FBXO2 mRNA level were not associated with tumor stage (Fig. 3D). In addition, our analyses shown that FBXO2 protein level was also down-regulation in BC (Fig. 3B). The promoter methylation of FBXO2 was largely augmented compared with paracaner (Fig. 3C). It indicated that promoter methylation might lead to FBXO2 low expression in BC. In Kaplan-Meier (KM) analyses, low expression FBXO2 was related with poor survival (Fig. 3D-3E).

FBXO2 expression in single cell sequencing level

In our analyses, 263929 cells were clustered into 8 cell types based on their expression of known lineage markers (Fig. 4A-4B), including epithelial cells (EPCAM, KRT18 and KRT14), B cells (JCHAIN and CD79A), T/NK cells (GNLY and CD3D), myeloid cells (LYZ and CD68), mast cells (TPSAB1 and TPSB2), endothelial cells (PLVAP and PECAM1), perivascular (PVL) cells (RGS5) and CAFs cells (DCN and COL3A1). 8 cell types all clustered in BC samples and normal samples (Figure S2). FBXO2 was most obviously expressed in epithelial cells. FBXO2 was also obviously expressed in B cells apart from epithelial cells (Fig. 4C). Moreover, FBXO2 was largely augmented in BC compared with normal in epithelial cells (Fig. 4D). Infercnvpy analyses revealed that chr1 and chr19 obviously amplified in malignant epithelial cells (Figure S3). 57807 cells were identified as malignant epithelial cells. Results revealed that FBXO2 was significantly attenuated in malignant cells compared with normal epithelial cells (Fig. 4E). Our single cell RNA sequence analyses unveiled FBXO2 was a pivotal role in BC.

Gene set enrichment analysis

Our results showed that multiple signaling pathways were associated with FBXO2, including oxidative phosphorylation, neutrophil extracellular trap formation, estrogen signaling pathway, glycolysis/gluconeogenesis and so on (Fig. 5A). Biological process (BP) analyses showed that FBXO2 was related with multiple immune related processes (Fig. 5B). Cellular component (CC) analyses revealed that FBXO2 was associated with multiple mitochondrial function (Fig. 5C). Molecular Function (MF) analyses indicated that FBXO2 was associated with antigen binding (Fig. 5D). Above results indicated that FBXO2 involved in immune and mitochondrial function in BC.

Correlation between FBXO2 and immune

FBXO2 was associated with multiple immune checkpoint Immune checkpoint inhibitors (ICIs) and immune cells (Fig. 6A-6B). The relationship between FBXO2 and ICIs or immune cells varied in different cancers. In breast cancer, FBXO2 was associated with TIGIT, PDCD1LG2, HAVCR2 and CTLA4 (Fig. 6A). Additionally, FBXO2 was positively related with Tregs, NK cells activated, plasma cells and CD8 T cell (Fig. 6B).

Previous studies had illustrated that FBXO2 was associated with development of cancer^19,20. FBXO2, a member of F-box family, had attracted increasing attention at present. However, the role of FBXO2 in many cancers remained unclear. Our findings showed that FBXO2 was up-regulation or down-regulation in different cancers. MR analyses illustrated that FBXO2 was a suppressor gene of BC, rather than BC causing downregulation of FBXO2. KM analyses also supported that FBXO2 was a suppressor gene.

Accumulated studies revealed that FBXO2 was crucial factors in most cancers. Up-regulation of FBXO2 could induce ubiquitination degradation of FBN1 and promote proliferation of endometrial carcinoma²¹. FBXO2 could impact the chemoresistance of high-grade serous ovarian carcinoma²². Proliferation of osteosarcoma was regulated by FBXO2-STAT3 signaling pathway²³. Xin et al found that FBXO2 was an independent prognostic factor in colorectal cancer patients²⁴.Our analyses also confirmed the importance of FBXO2 in cancer.

Single cell RNA sequence analyses of BC illustrated that FBXO2 was significantly enriched in epithelial cells, suggesting that FBXO2 affected behaviors of epithelial cells. That might be a potential mechanism of FBXO2 in BC. Tan et al also showed that FBXO2 was mainly enriched in epithelial cells²². Dong et al found that Epithelial mesenchymal transition was an underlying reason of FBXO2-induced gastric cancer metastasis¹⁴. Functional enrichment analyses showed that FBXO2 was involved in multiple oncogenic signaling pathways in BC. Previous studies had confirmed that oxidative phosphorylation, estrogen signaling pathway and neutrophil extracellular trap formation played an important role in BC^25–27. Neutrophil extracellular trap formation had received more attention at present. Additionally, FBXO2 could affect mitochondrial function in our analyses. It indicated that FBXO2 might be involved in mitophagy. It was consistent with previous studies²⁸. This suggested that our analysis is reliable. Above results indicated that FBXO2 may be a potential suppressor target for BC.

The association of FBXO2 and immune infiltration was major direction of BC work. The change of immune checkpoint inhibitors affected development and treatment of BC^29,30. Our analyses shown that FBXO2 was associated with multiple ICIs, including TIGIT, PDCD1LG2, HAVCR2 and CTLA4. In immune infiltration analyses, FBXO2 was positively correlated with Tregs, NK cells activated, plasma cells and CD8 T cell. Low FBXO2 affecting Tregs, NK cells activated, plasma cells and CD8 T cell might be a potential immune mechanism in BC. CD8⁺ Tcell infiltration were related with prognosis of BC³¹. Natural killer (NK) cells are an essential component of innate immunity. Activation of NK is critical in destroying BC cells³². Tregs was an important modulators of breast cancer progression and metastasis³³. These results indicated FBXO2 had an important value for further exploration in immune regulation of BC.

Our research systematically unveiled the potential role of FBXO2 in BC. But it had a limitation. We needed more experiments to verify the results.

Overall, FBXO2 may be a potential suppressor gene and drug target in BC. Exploration of FBXO2 will provide a novel insight for pathogenesis of BC.

BC (Breast cancer)

UPS (Ubiquitin

proteasome system)

SCF (SKP1

cullin 1-F-box protein)

FBXO2 (F

Box Protein 2)

OS (overall survival)

RFS (recurrence free survival)

MR (mendelian randomization)

KM (Kaplan

Meier)

GSEA (Gene set enrichment analyses)

IVs (instrumental variables)

SNP (single nucleotide polymorphism)

ICIs (Immune checkpoint inhibitors)

KEGG (Kyoto Encyclopedia of Genes and Genomes)

CC (Cellular component)

BP (Biological process)

MF (Molecular Function).

Ethics approval and consent to participate

Ethical approval and consent to participate were waived since we used only publicly available data and materials in this study.

Consent for publication

All authors have agreed to publish this manuscript.

Availability of data and materials

The original contributions presented in the study are included in the article Further inquiries can be directed to the corresponding authors. The code of article can be acquired for GitHub (https://github.com/ARONGZHI/FBXO2).

Author information

Authors and Affiliations

Department of Thyroid and Breast Surgery, The First People's Hospital of Qinzhou, Qinzhou, Guangxi 535000, China

Min Mao & Shenglian Lai

The First Affiliated Hospital of Guangxi Medical University, Nanning, The Guangxi Zhuang Autonomous Region, 530021, China.

Rongzhi Huang

Author contributions

MM: Writing - original draft. SL: Writing – review. RZ: Writing – original draft and analyses

Corresponding authors

Correspondence to Min Mao.

Finding

This work is supported by the Youth Science Foundation of Guangxi Medical University [Grant number GXMUYSF202239 to MM].

Acknowledgements

The authors gratefully acknowledge contributions from IEU Open GWAS databases, TCGA databases and GEO databases for free use.

Sedeta ET, Jobre B, Avezbakiyev B. Breast cancer: Global patterns of incidence, mortality, and trends. JCO. 2023;41:10528–10528.
Bray F et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 10.3322/caac.21834
HUANG X, ZHANG SONGC, ZHU J, L., TANG H. Circular RNAs in breast cancer diagnosis, treatment and prognosis. Oncol Res 32, 241–9.
Tufail M. The MALAT1-breast cancer interplay: insights and implications. Expert Rev Mol Diagn. 2023;23:665–78.
Chirnomas D, Hornberger KR, Crews CM. Protein degraders enter the clinic — a new approach to cancer therapy. Nat Rev Clin Oncol. 2023;20:265–78.
Dale B, et al. Advancing targeted protein degradation for cancer therapy. Nat Rev Cancer. 2021;21:638–54.
Park J, Cho J, Song EJ. Ubiquitin–proteasome system (UPS) as a target for anticancer treatment. Arch Pharm Res. 2020;43:1144–61.
Humphreys LM, Smith P, Chen Z, Fouad S, D’Angiolella V. The role of E3 ubiquitin ligases in the development and progression of glioblastoma. Cell Death Differ. 2021;28:522–37.
Liu EA et al. Fbxo2 mediates clearance of damaged lysosomes and modifies neurodegeneration in the Niemann-Pick C brain. JCI Insight 5, (2020).
Xie C-M, Wei W, Sun Y. Role of SKP1-CUL1-F-Box-Protein (SCF) E3 Ubiquitin Ligases in Skin Cancer. J Genet Genomics. 2013;40. 10.1016/j.jgg.2013.02.001.
Yoshida Y, Mizushima T, Tanaka K. Sugar-Recognizing Ubiquitin Ligases: Action Mechanisms and Physiology. Front Physiol 10, (2019).
Wang Z, Liu P, Inuzuka H, Wei W. Roles of F-box proteins in cancer. Nat Rev Cancer. 2014;14:233–47.
Ji J, et al. FBXO2 targets glycosylated SUN2 for ubiquitination and degradation to promote ovarian cancer development. Cell Death Dis. 2022;13:442.
Sun X, et al. FBXO2, a novel marker for metastasis in human gastric cancer. Biochem Biophys Res Commun. 2018;495:2158–64.
Zheng J, et al. Recent Developments in Mendelian Randomization Studies. Curr Epidemiol Rep. 2017;4:330–45.
Boef AGC, Dekkers OM, le Cessie. Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol. 2015;44:496–511.
Lawlor DA, Harbord RM, Sterne JAC, Timpson N. Davey Smith, G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27:1133–63.
Zheng J, et al. Recent Developments in Mendelian Randomization Studies. Curr Epidemiol Rep. 2017;4:330–45.
Sharma S, Kumar P. Decoding the Role of MDM2 as a Potential Ubiquitin E3 Ligase and Identifying the Therapeutic Efficiency of Alkaloids against MDM2 in Combating Glioblastoma. ACS Omega. 2023;8:5072–87.
Zhao X, Guo W, Zou L, Hu B. FBXO2 modulates STAT3 signaling to regulate proliferation and tumorigenicity of osteosarcoma cells. Cancer Cell Int. 2020;20:245.
Che X, et al. FBXO2 Promotes Proliferation of Endometrial Cancer by Ubiquitin-Mediated Degradation of FBN1 in the Regulation of the Cell Cycle and the Autophagy Pathway. Front Cell Dev Biol. 2020;8:843.
Lai W, et al. Integrated analysis of scRNA-seq and bulk RNA-seq identifies FBXO2 as a candidate biomarker associated with chemoresistance in HGSOC. Heliyon. 2024;10:e28490.
Zhao X, Guo W, Zou L, Hu B. FBXO2 modulates STAT3 signaling to regulate proliferation and tumorigenicity of osteosarcoma cells. Cancer Cell Int. 2020;20:245.
Wei X, et al. The prognostic significance of FBXO2 expression in colorectal cancer. Int J Clin Exp Pathol. 2018;11:5054–62.
Santen RJ, et al. The role of mitogen-activated protein (MAP) kinase in breast cancer. J Steroid Biochem Mol Biol. 2002;80:239–56.
Hu Y, et al. OXPHOS-dependent metabolic reprogramming prompts metastatic potential of breast cancer cells under osteogenic differentiation. Br J Cancer. 2020;123:1644–55.
Lipovka Y, Konhilas JP. The complex nature of oestrogen signalling in breast cancer: enemy or ally? Biosci Rep. 2016;36:e00352.
Yumimoto K, Yamauchi Y, Nakayama K. I. F-box proteins and cancer. Cancers (Basel). 2020;12:1249.
Jacob SL, Huppert LA, Rugo HS. Role of Immunotherapy in Breast Cancer. JCO Oncol Pract. 2023;19:167–79.
Debien V, et al. Immunotherapy in breast cancer: an overview of current strategies and perspectives. npj Breast Cancer. 2023;9:1–10.
Sun Y-P, Ke Y-L, Li X. Prognostic value of CD8 + tumor-infiltrating T cells in patients with breast cancer: A systematic review and meta-analysis. Oncol Lett. 2022;25:39.
Kiaei SZF, et al. Advances in natural killer cell therapies for breast cancer. Immunol Cell Biology. 2023;101:705–26.
Kos K, de Visser KE. The Multifaceted Role of Regulatory T Cells in Breast Cancer. Annu Rev Cancer Biol. 2021;5:291–310.

No competing interests reported.

FigureS1.eps
Figure S1: Leave one out of sensitivity tests. Calculate the MR results of the remaining IVs after removing the IVs one by one.
FigureS2.eps
Figure S2: (A) UMAP plot of 8 district cell types of BC sample. (B) UMAP plot of 8 district cell types of normal breast sample. (C) The proportion of immune cell in BC and normal breast samples
FigureS3.eps
Figure S3: the result of Infercnvpy analyses. The red represented amplification. The blue represented deletion.

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You are reading this latest preprint version

Unveiling immunological and prognostic potential of FBXO2 in BC based on Pan-Cancer and Single cell analyses

Status:

Version 1

Abstract

Background

Method

Result

Conclusion

Figures

Introduction

Method

Data acquisition

Molecular characteristic of FBOX2 in human pan-cancer

Bidirectional mendelian randomization analyses

Single cell RNA sequence analyses

Gene set enrichment analyses (GSEA)

Correlation between FBXO2 and immune in pan-cancer

Statistical Analyses

Result

Molecular characteristics of FBOX2 in human pan-cancer

Bidirectional MR analyses

FBXO2 feature and prognostic value in breast cancer

FBXO2 expression in single cell sequencing level

Gene set enrichment analysis

Correlation between FBXO2 and immune

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1