CD47 Contributes to the Proliferation of Breast Cancer

Abstract

Background:

The CD47 molecule (CD47) performs a novel role in regulating immunoreactions by binding to signal-regulatory protein alpha (SIRPα), resulting in the tumorigenesis of multiple malignant neoplasms. However, its effects and mechanisms in breast cancer (BC) remain unknown.

Methods:

To explore the molecular mechanisms and explicit impacts of CD47, we screened two databases for CD47-associated signaling pathways and cellular functions. BC samples and patients’ basic information were collected to identify the statistical significance of CD47 expression. We also constructed experiments to validate the regulatory role of CD47 in BC cell proliferation.

Results:

Analysis of the TCGA-BRCA, GSE42568, and GSE15852 datasets demonstrated an elevated level of CD47 in BC tissues. A Venn diagram revealed 11,194 co-expressed genes, and pathway analysis linked elevated CD47 levels to critical signaling pathways, such as cytokine-receptor interactions and Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling, which are integral to cell proliferation and invasiveness. Clinical data from 108 BC specimens showed that CD47 localization was primarily membranous, with higher levels correlating with proliferation marker Ki-67 (Ki-67) expression (p < 0.0001) and advanced tumor/node/metastasis (TNM) stage (p < 0.0001). Additionally, functional assays demonstrated that CD47 depletion reduced cell viability (p < 0.01), migration (p < 0.001), and invasion (p < 0.05 in 4T1 cells; p < 0.001 in MDA-MB-231 cells) in vitro and led to smaller tumor volumes (p < 0.0001) in vivo.

Conclusion:

CD47 is a key regulator of BC cell proliferation and invasiveness and serves as a potential marker for assessing tumor aggressiveness and guiding therapeutic strategies.

Graphical abstract

Keywords

CD47 / breast cancer / proliferation / tumor progression

1. Introduction

Breast cancer (BC) continues to be one of the most common cancers impacting women around the world, with projections indicating approximately 2.3 million new diagnoses in 2024 [1]; therefore, it continues to represent a significant public health challenge. Recent data have highlighted demographic shifts in BC incidence, particularly an alarming increase among younger women and diverse populations, and disparities in access to healthcare exacerbate outcomes in underrepresented groups. Moreover, the mechanisms of metastasis and invasion in BC involve complex interactions between cancer cells and their microenvironment, contributing to the metastatic cascade [2, 3]. Notably, key genes such as BRCA1 DNA repair associated (BRCA1) and BRCA2 DNA repair associated (BRCA2) have been identified as crucial players in BC development, and mutations in these genes are associated with a significantly increased risk of developing the disease and with aggressive tumor behavior [4]. In response to these challenges, the treatment landscape has evolved to include targeted therapies, such as trastuzumab for Human epithelial receptor-2 (HER2)-positive tumors and immunotherapies that show promise in triple-negative BC [5]. Overall, the fight against BC continues to evolve rapidly, and future studies should concentrate on understanding the fundamental mechanisms of metastasis and enhance interventions that are customized for the various populations impacted.

CD47 molecule (CD47), a transmembrane protein primarily found on the surface of diverse cells, functions significantly in modulating immune responses. It does this by interacting with signal-regulatory protein alpha (SIRPα) present on macrophages, which consequently inhibits phagocytosis and enables cells to avoid immune clearance [6, 7, 8]. CD47 is often up-expressed in carcinomas and contributes to immune evasion and poor prognosis in various cancers, including leukemia, lymphoma, and solid tumors [9]. This overexpression facilitates tumor progression, metastasis, and resistance to therapies, prompting research into CD47 as a therapeutic target through strategies such as monoclonal antibodies that block its interaction with SIRPα [8, 10, 11]. Although some studies have indicated CD47 overexpression in specific BC subtypes, its precise involvement and clinical significance in this malignancy remain unclear, necessitating further investigation to elucidate its therapeutic potential and role in BC progression. Overall, the implications of CD47 in cancer biology are expanding; however, more research is required to determine its impact, specifically in the context of BC.

Given the unclear applications of CD47 gene expression in BC, this study conducted an in-depth investigation using several methodologies, including bioinformatics analysis through database retrieval, statistical analysis of clinical sample data, and immunohistochemical staining of tissue samples. By integrating these approaches, our goal was to clarify how CD47 is expressed in breast cancer and to evaluate its possible significance in relation to disease progression and patient outcomes. These comprehensive analyses support valuable insights into the role of CD47 in BC and contribute to inform future therapeutic strategies targeting this gene.

2. Materials and Methods

2.1 Data Acquisition and Processing

The Cancer Genome Atlas-Breast Cancer (TCGA-BRCA)-related data were downloaded from the Gene Expression Datasets Associated with BC using the Genomic Data Commons (GDC) data portal (https://portal.gdc.cancer.gov/) and the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). The analysis of the differential expression of CD47 in breast cancer and adjacent non-cancerous tissues was conducted using Gene Expression Profiling Interactive Analysis (GEPHIA2; http://gepia2.cancer-pku.cn/).

2.2 Bioinformatic Analysis of Differential Expression Gene (DEGs)

In the TCGA-BRCA, GSE15852, and GSE42568 datasets, using the “DESeq2” software package (dds - DESeqDataSetFromMatrix (countData, colData, design = ~ condition); alpha = 0.05; lfcThreshold >1; Version 3.0; Michael Love and Wolfgang Huber; London, USA), we screened out the DEGs in the samples with high and low expression of CD47 in tumor tissues. Venn diagrams showed co-expressed genes, and functional enrichment analysis utilizing Gene Ontology (GO) alongside Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was conducted through the cluster-Profiler R package 4.3.2 (Michael Love and Wolfgang Huber; NY, USA) [12]. This analysis aimed to categorize a range of biological processes, molecular functions, cellular components, and pathways associated with the identified marker genes within the target clusters [13, 14] (Supplementary Fig. 1A,B).

2.3 Clinical Samples and Immunohistochemistry (IHC)

This research conducted a retrospective analysis of breast cancer cases stored in the Pathology Department at Shandong Third Hospital from 2020 to 2022. The analysis included 108 patients who had been diagnosed with invasive ductal carcinoma of the breast, all of whom did not receive preoperative chemotherapy, radiotherapy, or endocrine treatment. This study was conducted in accordance with the Declaration of Helsinki and was approved by the relevant ethics committee. The Ethics Committee and Institutional Review Board of the Third Hospital of Shandong Province approved the study, and the necessity for informed consent was signed (No. KYLL-2021066). An immunohistochemical staining assay was used to detect 108 paired BC tissue samples. Rabbit anti-human CD47 monoclonal antibody was purchased (ab300124, Cell Signaling Technology, Inc. Boston, USA; Dilution concentration: 1:200). Staining results were analyzed using ImageJ software (Version 1.8.0.345; National Institutes of Health; NY, USA) [15] and interpreted according to the semi-quantitative method utilized to assess the expression of CD47 in BC and paraneoplastic samples.

2.4 Cell Culture

Human BC cells (MDA-MB-231 cell line; ZQ0118) and mouse BC 4T-1 cells (ZQ0201; Shanghai Zhongqiao Xinzhou Biological Company, Shanghai, China) were inoculated in Dulbecco’s Modified Eagle Medium (Gibcp 11885084, Suzhou, Jiangsu, China) with 10% fetal bovine serum (Suolaibao technology company, Beijing, China) and 100 IU/mL penicillin/streptomycin at 37 °C with 5% CO₂. All cell lines were validated by STR profiling and tested negative for Mycoplasma.

2.5 Cell Transfection

Cells were placed in six-well plates at a density of 2 \times 10⁵ cells per well and allowed to incubate overnight to achieve 90% confluency. For each well, plasmid DNA [2 µg CD47-short hairpin RNA (shRNA); D010003, GenePharma company; Shanghai, China] was diluted in 250 µL of DMEM (ZQ-100; Shanghai Zhong Qiao Xin Zhou Biotechnology Co, Shanghai, China) and mixed gently. Separately, 10 µL of transfection reagent (e.g., Lipofectamine 3000, ThermoFisher, Shanghai, China) incubated for 5 min at 24 °C. The diluted DNA and transfection reagent were then combined, incubated for 20 min, and were added dropwise to the cells, which were then incubated at 37 °C in a CO₂ incubator. After 6 hours, the medium was replaced with a fresh fetal medium. Transfection efficiency was assessed 24–48 h post-transfection using quantitative real-time (qPCR) and Western blot (WB) assays (Supplementary Tables 1,2).

2.6 Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)

Total RNA was extracted from cultured cells by Easy Pure RNA Isolation Kit (R0018S; Beyotime Biotechnology, Shanghai, China) and a reverse-transcription (RT) Kit (D7153; BeyoRT M-MuLV, Beyotime Biotechnlogy Company, Shanghai, China). The cDNA was subjected to qRT-PCR with gene-specific primers in the presence of qPCR Master Mix (BeyoRT II cDNA, Beyotime Biotechnlogy Company, Shanghai, China). Relative mRNA expression levels were calculated using the 2-ΔΔCt method, where ΔCt represents the difference in threshold cycle (Ct) values between the target gene and a reference gene (e.g., GAPDH (Supplementary Table 3). All samples were analyzed in triplicate.

2.7 Western Blot Assay

The total protein was extracted from the cells using the Radio Immunoprecipitation Assay (RIPA) extraction reagent (Beyotime Biotechnology Company, Shanghai, China), and the protein concentration was determined using a bicinchoninic acid protein assay (Beyotime Biotechnology Company, Shanghai, China). Subsequently, the samples were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The primary antibody (anti-CD47:1:2000, 20305–1-AP; anti-\beta-actin: 1:2000, 10494-1-AP, Proteintech, Rosemont, IL, Beijing, China) and the secondary antibody (IgG-HRP, 1:3000, AS014; Wolburn, Boston, MA, USA) were incubated, respectively. Protein bands were visualized using chemiluminescence and analyzed using the ImageJ software (Version 2.0; available from the National Institutes of Health, USA) (Supplementary Fig. 2).

2.8 Cell Counting Kit-8 (CCK8) Assay

Experimental cells were plated in a 96-well plate with a density of 5000 cells per well. The proliferation rates of 4T-1 and MB-231 cells from both the short hairpin (sh)-CD47 and control groups were assessed. Cell viability measurements occurred every 12 hours. Daily, 10 µL of CCK-8 reagent (MCE, Shanghai, China) was added to each well of the 96-well plates and incubated at 37 °C for one hour. Optical density values were then determined using a microplate reader (Infinite® M1000PRO, TECAN, Männedorf, Switzerland) at a 450-nm wavelength.

2.9 Colony Formation Assay

In summary, 400 cells were placed in a six-well plate and allowed to incubate in culture medium containing 10% fetal bovine serum at a temperature of 37 °C with 5% CO₂ for a duration of 2 weeks. The culture medium was replaced every three days. Prior to staining with 0.1% crystal violet, the cells were fixed using 4% paraformaldehyde for 30 minutes. The clones were then quantified using ImageJ software.

2.10 Wound Healing Assay

Cells from each group were inoculated in six-well plates (2 \times 10⁵ cells/well). When the cell growth reached 85% confluence, the bottom of the six-well plate was scratched vertically and cultured in Dulbecco’s Modified Eagle Medium with DMEM. The scratches were observed under a microscope (Olympus, IX-71, Tokyo, Japan,) and photographed at 0, 24, and 48 h. The healing rate was determined using the formula ((initial scratch area - scratch area at time t)/(initial scratch area)) \times 100%.

2.11 Cell Migration Assay

The capability of cell migration was assessed using 24-well transwell chambers (with an 8-µm pore size; Sigma-Aldrich, Corning, NY, USA). In the upper compartment, 100 µL of serum-free medium was combined with 2 \times 10⁴ cells, while the lower compartment contained 600 µL of medium supplemented with 10% fetal bovine serum. Following 48 hours of culture in a 37 °C incubator, the cells were fixed using 4% paraformaldehyde and subsequently treated with 0.4% crystal violet solution (Sigma-Aldrich, V5265, Shanghai, China). The stained cells were then photographed (Olympus, Tokyo, Japan) and quantified.

2.12 Cell Transwell Assay

Culture the cells until they reach 70–80% confluence, then detach and re-suspend them in fresh medium. Use diluted Matrigel (3 mg/mL; M8370, Suolaibao company, Beijing, China) coated on the upper surface of the transwell inserts and add a predetermined number of cells to the upper chamber, while adding complete medium to the lower chamber. This process should be performed on ice, allowing the Matrigel to solidify at 37 °C for 45 minutes. Incubate the setup at 37 °C with 5% CO₂ for 24–48 hours. After incubation, fix the migrated cells on the lower surface of the insert using a fixative solution, followed by staining with a crystal violet. Once stained, rinse to remove excess dye, allow the inserts to dry, and then examine them under a microscope to count the number of invaded cells.

2.13 In Vivo Growth Assays

Female BALB/C nude mice (5-weeks-old; 17.54 \pm 0.867 g; 45 in all; Beijing Viewsolid Biotech Co., Ltd., Beijing, China) were utilized to construct the xenograft model. Knocked-down 4T-1/sh-NC (Negative Control) and 4T-1/sh-CD47 cells were suspended in 100 µL of PBS and injected subcutaneously. Tumors were measured every 2–3 d. After 33 days, mice were euthanized with a 20% concentration of isoflurane (1217828, Shanghai Yuyan Scientific Instrument Co., LTD, Shanghai, China) in airtight equipment for three minutes according to the ethical guidelines [16], and xenograft tumors were dissected for subsequent experiments. All animal experimental processes were approved by the Laboratory Animal Center of Shandong Third Hospital (No. DWKYLL-2021023).

2.14 Statistical Analysis

Statistical analyses were conducted utilizing IBM SPSS Statistics software (IBM Corp., Armonk, NY, USA) version 29.0, along with GraphPad Prism 10.0 (GraphPad Software, La Jolla, CA, USA), and R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria) [12]. The results of the IHC were evaluated employing the chi-square test. A p-value of less than 0.05 was deemed statistically significant. To compare the two sample groups, an independent samples t-test was used, whereas a one-way ANOVA was applied for comparisons involving multiple groups. Following one-way ANOVA, post-hoc multiple comparisons were performed using the Tukey’s HSD (Honestly Significant Difference) test to evaluate differences between group means. This method was chosen for its ability to control the Type I error rate while comparing all pairs of means. All statistical tests were two-sided, and each experiment was conducted three times for every group.

3. Results

3.1 Bioinformatic Information of CD47 in Breast Cancer

To elucidate the divergence in CD47 expression in BC, we analyzed two datasets derived from TCGA-BRCA databases: GSE42568 and GSE15852. Our findings indicated that CD47 expression was significantly high in BC samples comparing to normal breast samples (Fig. 1A,B). Subsequently, we used a Venn gram to identify approximately 11,194 genes co-expressed across the three datasets (Fig. 1C,D). To conduct a comprehensive analysis of the signaling pathways correlated to the regulation of activated CD47 from KEGG database [13], we established that elevated CD47 levels in BC were linked to several critical pathways, including cytokine-cytokine receptor interactions, the JAK/STAT signaling pathway, chemokine signaling pathway, and cell adhesion molecule pathways. These pathways are pivotal in driving processes such as cell proliferation, apoptosis, metabolism, and invasiveness (Fig. 1E; Supplementary Fig. 3). Additionally, the GO analysis indicated that differentially expressed genes (DEGs) associated with elevated CD47 expression were connected to the enhancement of cytokine production, activity of receptor ligands, and the activation of signaling receptors (Fig. 1F).

3.2 The Significance of CD47 in Clinical Breast Cancer

To investigate the relationship between CD47 level and BC, we collected data from 108 clinical cases between January 2020 and January 2022. IHC staining demonstrated that CD47 was primarily localized on the membrane of BC cells, and these levels were significantly higher in cancer tissues than in para-cancerous tissues (Fig. 2A,B; Table 1; p 0.0001). Furthermore, statistical analyses uncovered that increased CD47 expression was associated with several factors, including high Ki-67 levels, age >60 years, and TNM stage. Nevertheless, there were no statistically significant differences in CD47 levels between the estrogen receptor-, progesterone receptor, or Human Epidermal Growth Factor Receptor-positive and negative groups (Table 2).

3.3 CD47 Maintained the Proliferation of Breast Cancer

We performed in vitro and in vivo experiments to verify the function of CD47 in BC. Given the elevated levels of CD47, we transfected three shRNA plasmids into 4T1 and MB-231 cells to downregulate CD47 expression (Supplementary Fig. 1). Notably, cell viability was overtly lower in the sh-CD47 group than that in the control group, which was further corroborated by monoclonal proliferation results using CCK-8 staining (Fig. 3). The wound healing assay results for 4T1 and MB-231 cells demonstrated that the migratory ratios at 24 and 48 hours were reduced in the sh-CD47 group compared with the control groups (p 0.0001; Fig. 4A–D). Combined with the outcomes of the cell migration assay, the invasive ability of sh-CD47 cancer cells decreased compared to that of normal cancer cells (p 0.05 in 4T1 cells; p 0.001 in MB-231 cells; Fig. 4E,F). Furthermore, we established subcutaneous tumors in nude mice using sh-CD47 4T1, control 4T1, and 4T1 cells with empty plasmids. The results indicated that the tumor volume was distinctly lower in the sh-CD47 group than that in the other two groups (Fig. 5A–E). In terms of the proliferative markers, Cyclin dependent kinase 4 (CDK4) and cyclin dependent kinase 6 (CDK6) expression in BC tumors in the sh-CD47 group had lower levels than that in the control groups (Fig. 5F–I).

4. Discussion

The involvement of CD47 in cancer research has gained considerable attention since many tumors overexpress this protein to avoid being targeted by the immune system. High levels of CD47 expression have been correlated with poor prognoses in several malignancies, including breast, prostate, and lung cancers [9, 17, 18, 19]. Consequently, therapeutic strategies have emerged, such as the development of monoclonal antibodies against CD47, which have shown promise for enhancing the phagocytosis of cancer cells in preclinical and clinical trials.

The modulation of CD47 presents new avenues for therapies aimed at adjusting immune responses in autoimmune conditions. Finally, in infectious diseases, CD47 may influence the immune response to pathogens, with certain viruses potentially exploiting the CD47 pathway to evade phagocytosis, thereby prolonging survival in host cells [20]. In summary, CD47 serves as a critical regulator of the immune response and cellular homeostasis across a spectrum of human diseases. Ongoing research is focused on elucidating its complex role and exploring potential therapeutic interventions that target CD47 to improve treatment outcomes in various conditions. The CD47 gene plays a crucial role in the mechanism of malignancies primarily through its functions in immune evasion, tumor growth promotion, and modulation of the tumor microenvironment. As a “don’t eat me” signaling protein, CD47 interacts with SIRPα on macrophages, inhibiting phagocytosis and allowing tumor cells to escape immune surveillance [8, 10, 21]. CD47 contributes to tumor cell proliferation and survival through various signaling pathways, including integrin signaling, which promotes tumor cell migration and invasion. Moreover, CD47 affects the tumor microenvironment by regulating the activity and composition of immune cells. It can polarize tumor-associated macrophages towards a pro-tumor phenotype, further aiding tumor progression [22, 23, 24]. Therapeutically, CD47 has emerged as a promising target in cancer immunotherapy, with the development of monoclonal antibodies that block CD47-SIRPα interactions, thereby enhancing the phagocytic activity of macrophages against tumor cells. Overall, the multifaceted role of CD47 in malignancy represents a vital area for ongoing research and potential therapeutic interventions.

The role of CD47 in BC has emerged as a critical area of research, particularly due to its implications for tumor growth and immune evasion [18, 19, 25]. Our findings demonstrate that the knockdown of CD47 significantly decreases the proliferation of BC cells and reduces tumor size in animal models, which is consistent with the existing literature that highlights CD47’s essential role in maintaining BC. This conclusion was affirmed by the finding that high CD47 expression correlated with high Ki-67 levels. Ki-67 is a nuclear protein that is associated with cell proliferation [26]. It is widely used as a cellular marker to assess the growth fraction of a given tissue, particularly in tumor pathology. The presence of Ki-67 in a cell indicates that it is actively dividing or preparing to divide, making it a valuable tool for evaluating the proliferative activity of tumors [27, 28]. Additionally, CD47 is involved in promoting tumor survival through various signaling pathways, such as the Phosphoinositide 3-kinase/ Protein Kinase B (PI3K/Akt) pathway, which enhances cell proliferation and resistance to apoptosis [29].

This study centers on the phenotypic impacts of CD47 in enhancing the proliferation and invasion of BC cells. Nevertheless, we did not examine the fundamental mechanisms through which CD47 influences these processes, including the activation of cellular signaling pathways. Subsequent research should delve into these internal mechanisms to achieve a more thorough comprehension of CD47’s function in BC, potentially facilitating the identification of therapeutic targets.

5. Conclusion

Our study underscores the pivotal role of CD47 in BC pathogenesis and highlights its dual function in promoting tumor cell propagation. Elevated CD47 expression in BC tissues, as evidenced by bioinformatics analyses and clinical correlations, is associated with increased Ki-67 levels, suggesting a direct link to cellular proliferation. Furthermore, findings from in vitro and in vivo experiments reinforce the critical involvement of CD47 in maintaining the malignancy of BC cells. The potential of CD47 as a therapeutic target offers exciting avenues for the development of innovative treatments aimed at enhancing antitumor responses. Future research should focus on elucidating the intricate mechanisms governing CD47 signaling and exploring the clinical applicability of CD47-targeted interventions to improve outcomes in patients with BC.

Declaration of AI and AI-assisted Technologies in the Writing Process

During the preparation of this work the authors used ChatGPT in order to check spell and grammar. After using this tool, the authors reviewed and edited the content as needed and takes full responsibility for the content of the publication.

Availability of Data and Materials

The datasets used and analyzed during the current study can be available from the corresponding author on reasonable request.

References

[1] Benitez Fuentes JD, Morgan E, de Luna Aguilar A, Mafra A, Shah R, Giusti F, et al. Global Stage Distribution of Breast Cancer at Diagnosis: A Systematic Review and Meta-Analysis. JAMA Oncology. 2024; 10: 71–78. https://doi.org/10.1001/jamaoncol.2023.4837.

[2] Ge A, He Q, Zhao D, Li Y, Chen J, Deng Y, et al. Mechanism of ferroptosis in breast cancer and research progress of natural compounds regulating ferroptosis. Journal of Cellular and Molecular Medicine. 2024; 28: e18044. https://doi.org/10.1111/jcmm.18044.

[3] Kundu M, Butti R, Panda VK, Malhotra D, Das S, Mitra T, et al. Modulation of the tumor microenvironment and mechanism of immunotherapy-based drug resistance in breast cancer. Molecular Cancer. 2024; 23: 92. https://doi.org/10.1186/s12943-024-01990-4.

[4] Kleiblová P, Novotný J, Cibula D, Curtisová V, Dubová O, Foretová L, et al. The guidelines for clinical practice for carriers of germline mutations in hereditary breast, ovarian, prostate, and pancreatic cancer predisposition genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 (4.2024). Klinicka Onkologie: Casopis Ceske a Slovenske Onkologicke Spolecnosti. 2024; 38: 292–299. https://doi.org/10.48095/ccko2024292.

[5] Dogan I, Ahmed MA, Yıldız A, Vatansever S. Rechallenge of Trastuzumab-based Therapy in HER2-Positive Breast Cancer Patients who Progressed Under TDM-1. Indian Journal of Surgical Oncology. 2024; 15: 484–488. https://doi.org/10.1007/s13193-024-01935-9.

[6] Liu Y, Weng L, Wang Y, Zhang J, Wu Q, Zhao P, et al. Deciphering the role of CD47 in cancer immunotherapy. Journal of Advanced Research. 2024; 63: 129–158. https://doi.org/10.1016/j.jare.2023.10.009.

[7] Zhang T, Wang F, Xu L, Yang YG. Structural-functional diversity of CD47 proteoforms. Frontiers in Immunology. 2024; 15: 1329562. https://doi.org/10.3389/fimmu.2024.1329562.

[8] Zhao P, Xie L, Yu L, Wang P. Targeting CD47-SIRPα axis for Hodgkin and non-Hodgkin lymphoma immunotherapy. Genes & Diseases. 2023; 11: 205–217. https://doi.org/10.1016/j.gendis.2022.12.008.

[9] Chuang CH, Zhen YY, Ma JY, Lee TH, Hung HY, Wu CC, et al. CD47-mediated immune evasion in early-stage lung cancer progression. Biochemical and Biophysical Research Communications. 2024; 720: 150066. https://doi.org/10.1016/j.bbrc.2024.150066.

[10] Huang C, Wang X, Wang Y, Feng Y, Wang X, Chen S, et al. Sirpα on tumor-associated myeloid cells restrains antitumor immunity in colorectal cancer independent of its interaction with CD47. Nature Cancer. 2024; 5: 500–516. https://doi.org/10.1038/s43018-023-00691-z.

[11] Zhang K, Xu Y, Chang X, Xu C, Xue W, Ding D, et al. Co-targeting CD47 and VEGF elicited potent anti-tumor effects in gastric cancer. Cancer Immunology, Immunotherapy. 2024; 73: 75. https://doi.org/10.1007/s00262-024-03667-9.

[12] Wilson KJ, Roldán-Nofuentes JA, Henrion MYR. testCompareR: an R package to compare two binary diagnostic tests using paired data. Wellcome Open Research. 2024; 9: 351. https://doi.org/10.12688/wellcomeopenres.22411.3.

[13] Kanehisa M, Furumichi M, Sato Y, Kawashima M, Ishiguro-Watanabe M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research. 2023; 51: D587–D592. https://doi.org/10.1093/nar/gkac963.

[14] Sato N, Uematsu M, Fujimoto K, Uematsu S, Imoto S. ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics. Bioinformatics. 2023; 39: btad622. https://doi.org/10.1093/bioinformatics/btad622.

[15] Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nature Methods. 2012; 9: 671–675. https://doi.org/10.1038/nmeth.2089.

[16] Cicero L, Fazzotta S, Palumbo VD, Cassata G, Lo Monte AI. Anesthesia protocols in laboratory animals used for scientific purposes. Acta Bio-Medica: Atenei Parmensis. 2018; 89: 337–342. https://doi.org/10.23750/abm.v89i3.5824.

[17] Wang Q, Feng C, Chen Y, Peng T, Li Y, Wu K, et al. Evaluation of CD47 in the Suppressive Tumor Microenvironment and Immunotherapy in Prostate Cancer. Journal of Immunology Research. 2023; 2023: 2473075. https://doi.org/10.1155/2023/2473075.

[18] Chantaraamporn J, Pothipan P, Sakulterdkiat T, Khiankaew B, Lumkul L, Mutapat P, et al. CD47 and Calreticulin Expression in Breast Cancer Subtypes and Anti-CD47 Inhibitory Effects in Macrophage-mediated Phagocytosis. Anticancer Research. 2024; 44: 4929–4940. https://doi.org/10.21873/anticanres.17318.

[19] Zhang B, Shi J, Shi X, Xu X, Gao L, Li S, et al. Development and evaluation of a human CD47/HER2 bispecific antibody for Trastuzumab-resistant breast cancer immunotherapy. Drug Resistance Updates. 2024; 74: 101068. https://doi.org/10.1016/j.drup.2024.101068.

[20] Zuo H, van Lierop MJC, Kaspers J, Bos R, Reurs A, Sarkar S, et al. Transfer of Cellular Content from the Allogeneic Cell-Based Cancer Vaccine DCP-001 to Host Dendritic Cells Hinges on Phosphatidylserine and Is Enhanced by CD47 Blockade. Cells. 2021; 10: 3233. https://doi.org/10.3390/cells10113233.

[21] Hutter G, Theruvath J, Graef CM, Zhang M, Schoen MK, Manz EM, et al. Microglia are effector cells of CD47-SIRPα antiphagocytic axis disruption against glioblastoma. Proceedings of the National Academy of Sciences of the United States of America. 2019; 116: 997–1006. https://doi.org/10.1073/pnas.1721434116.

[22] Dawoud MM, Abd El Samie Aiad H, Kasem NS, El Khouly EAB, Al-Sharaky DR. Is overexpression of CD163 and CD47 in tumour cells of breast carcinoma implicated in the recruitment of tumour-associated macrophages (TAMs) in tumour microenvironment? immunohistochemical prognostic study. Journal of Immunoassay & Immunochemistry. 2024; 45: 342–361. https://doi.org/10.1080/15321819.2024.2358879.

[23] Gautam PK, Acharya A. Suppressed expression of homotypic multinucleation, extracellular domains of CD172α (SIRP-α) and CD47 (IAP) receptors in TAMs upregulated by Hsp70-peptide complex in Dalton’s lymphoma. Scandinavian Journal of Immunology. 2014; 80: 22–35. https://doi.org/10.1111/sji.12180.

[24] Lu J, Li J, Lin Z, Li H, Lou L, Ding W, et al. Reprogramming of TAMs via the STAT3/CD47-SIRPα axis promotes acquired resistance to EGFR-TKIs in lung cancer. Cancer Letters. 2023; 564: 216205. https://doi.org/10.1016/j.canlet.2023.216205.

[25] Tong S, Zhu Y, Leng Y, Wu Y, Xiao X, Zhao W, et al. Restoration of miR-299-3p promotes macrophage phagocytosis and suppresses malignant phenotypes in breast cancer carcinogenesis via dual-targeting CD47 and ABCE1. International Immunopharmacology. 2024; 130: 111708. https://doi.org/10.1016/j.intimp.2024.111708.

[26] Ding Z, Hagan M, Yan F, Schroer NWY, Polmear J, Good-Jacobson KL, et al. Ki67 deficiency impedes chromatin accessibility and BCR gene rearrangement. The Journal of Experimental Medicine. 2024; 221: e20232160. https://doi.org/10.1084/jem.20232160.

[27] Ramos-Santillan V, Oshi M, Nelson E, Endo I, Takabe K. High Ki67 Gene Expression Is Associated With Aggressive Phenotype in Hepatocellular Carcinoma. World Journal of Oncology. 2024; 15: 257–267. https://doi.org/10.14740/wjon1751.

[28] Sprenger F, da Silva Junior EB, Ramina R, Cavalcanti MS, Martins SB, Cerqueira MA, et al. Ki67 Index Correlates with Tumoral Volumetry and 5-ALA Residual Fluorescence in Glioblastoma. World Neurosurgery. 2024; 189: e230–e237. https://doi.org/10.1016/j.wneu.2024.06.023.

[29] Liu Y, Chang Y, He X, Cai Y, Jiang H, Jia R, et al. CD47 Enhances Cell Viability and Migration Ability but Inhibits Apoptosis in Endometrial Carcinoma Cells via the PI3K/Akt/mTOR Signaling Pathway. Frontiers in Oncology. 2020; 10: 1525. https://doi.org/10.3389/fonc.2020.01525.

Funding

Science and Technology Development Program of Shandong Geriatrics Society(LKJGG2021Z005)

Scientific research cultivation fund of Shandong provincial third hospital(M2023004/sjzd004)

Medical and Health Science and Technology Project of Shandong Province(2023BJ000037)