切换至 "中华医学电子期刊资源库"

中华乳腺病杂志(电子版) ›› 2025, Vol. 19 ›› Issue (03) : 145 -153. doi: 10.3877/cma.j.issn.1674-0807.2025.03.003

论著

CD83通过ITGB1/FAK信号通路调控三阴性乳腺癌细胞迁移和侵袭
马庆东1, 万韦君2,3, 罗东林1,()   
  1. 1400042 重庆,陆军特色医学中心乳腺甲状腺外科
    2400042 重庆,陆军特色医学中心创伤与化学中毒全国重点实验室
    3400042 重庆,陆军特色医学中心干细胞与再生医学科
  • 收稿日期:2024-12-09 出版日期:2025-06-01
  • 通信作者: 罗东林
  • 基金资助:
    重庆市自然科学基金项目(CSTB2023NSCQ-BHX0199); 军事医学重点临床学科建设(普通外科)项目

CD83 regulates migration and invasion of triple negative breast cancer cells through ITGB1/FAK signaling pathway

Qingdong Ma1, Weijun Wan2,3, Donglin Luo1,()   

  1. 1Department of Breast and Thyroid Surgery, Army Medical Center, Chongqing 400042, China
    2National Key Laboratory of Trauma and Chemical Poisoning, Army Medical Center, Chongqing 400042, China
    3Department of Stem Cell and Regenerative Medicine, Army Medical Center, Chongqing 400042, China
  • Received:2024-12-09 Published:2025-06-01
  • Corresponding author: Donglin Luo
引用本文:

马庆东, 万韦君, 罗东林. CD83通过ITGB1/FAK信号通路调控三阴性乳腺癌细胞迁移和侵袭[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(03): 145-153.

Qingdong Ma, Weijun Wan, Donglin Luo. CD83 regulates migration and invasion of triple negative breast cancer cells through ITGB1/FAK signaling pathway[J/OL]. Chinese Journal of Breast Disease(Electronic Edition), 2025, 19(03): 145-153.

目的

研究CD83对三阴性乳腺癌细胞增殖、凋亡、周期、迁移和侵袭过程的影响,探讨其调控三阴性乳腺癌细胞生物学行为的机制。

方法

从TCGA数据库下载822个乳腺癌组织样本和572个正常组织样本,分析CD83在乳腺癌组织中的表达差异。并通过Western blot检测人正常乳腺上皮细胞MCF-10A和乳腺癌细胞MCF-7、BT-549、MDA-MB-231这4种细胞中CD83的蛋白表达量。使用CRISPR/Cas9方法建立稳定敲除CD83的MDA-MB-231细胞株sg-CD83-#1、sg-CD83-#2和sg-CD83-#3,提取细胞蛋白检验敲除效率,根据检测结果选取敲除效果最好的细胞株(sg-CD83)进行后续实验。采用细胞计数试剂盒8(CCK-8)、划痕愈合实验和Transwell法检测sg-CD83组的增殖、迁移和侵袭能力,sg-ctrl组作为CD83敲除的对照。通过Co-IP分析CD83与ITGB1之间的分子相互作用。通过质粒转染建立CD83过表达的MDA-MB-231细胞株,采用划痕愈合实验和Transwell法检测ov-CD83组的增殖、迁移和侵袭能力,vector组作为对照。通过敲低CD83过表达细胞中的ITGB1,检测ITGB1对CD83功能的影响,si-NC组作为ITGB1敲低的对照。定量资料的组间比较采用独立样本t检验,多组间比较采用单因素方差分析,多组两两比较采用LSD法。

结果

TCGA数据库的生物信息学分析发现在Luminal A型(4.63±0.79)、Luminal B型(4.57±0.77)、HER-2过表达型(4.62±0.75)、TNBC(5.40±1.13)和正常组织(3.30±1.17)中的CD83的mRNA表达量比较,差异有统计学意义(F=196.802,P<0.001)。TNBC中CD83表达高于其他3种类型(P均<0.001)。MCF-10A、MCF-7、BT-549、MDA-MB-231细胞中CD83的蛋白表达量分别为1.00±0.01、1.44±0.02、1.71±0.02、1.89±0.07,差异有统计学意义(F=353.070,P<0.001)。sg-ctrl、sg-CD83-#1、sg-CD83-#2、sg-CD83-#3组MDA-MB-231细胞中CD83的蛋白表达量分别为1.00±0.02、0.79±0.18、0.32±0.03、0.23±0.05,差异有统计学意义(F=48.758,P<0.001)。sg-CD83-#3组敲除效果最好,因此选取sg-CD83-#3组细胞株作为敲除组用于后续实验(sg-CD83)。sg-ctrl组和sg-CD83组的细胞在24、48、72和96 h时450 nm处的吸光度分别为0.63±0.05比0.51±0.03、0.92±0.03比0.70±0.06、1.27±0.02比0.90±0.09、1.54±0.14比1.06±0.09,差异有统计学意义(P均<0.050)。sg-ctrl组和sg-CD83组凋亡率[(5.96±0.06)%比(12.82±0.07)%;t=−128.877,P<0.001]、G0/G1期细胞比例[(31.87±0.76)%比(44.75±1.50)%;t=−13.229,P<0.001]、细胞划痕愈合率[(34.47±0.87)%比(16.63±0.70)%;t=27.554,P<0.001]、迁移细胞数(143.67±4.16比62.67±1.53;t=31.636,P<0.001)、侵袭细胞数(123.67±3.06比26.33±2.52;t=42.593,P<0.001)比较,差异均有统计学意义。sg-ctrl组和sg-CD83组中ITGB1表达量分别为1.00±0.02、0.34±0.02,差异有统计学意义(t=40.417,P<0.001);黏着斑激酶(FAK)表达量分别为1.00±0.01、0.79±0.07,差异有统计学意义(t=5.144,P=0.033);磷酸化FAK(p-FAK)表达量分别为0.99±0.03、0.35±0.05,差异有统计学意义(t=19.395,P<0.001)。Co-IP实验中,CD83与ITGB1被共同沉淀。vector组和ov-CD83组细胞划痕愈合率[(8.40±2.73)%比(45.08±1.51)%;t=−20.340,P<0.001]、迁移细胞数(151.00±2.65比337.67±3.51;t=-73.532,P<0.001)、侵袭细胞数(120.33±4.16比288.67±4.51;t=−47.506,P<0.001)比较,差异均有统计学意义。si-NC组和si-ITGB1组细胞划痕愈合率[(44.63±2.11)%比(13.93±2.90)%;t=14.839,P<0.001]、迁移细胞数(339.67±3.06比181.67±2.31;t=71.458,P<0.001)、侵袭细胞数(289.00±5.29比170.33±5.03;t=28.144,P<0.001)比较,差异均有统计学意义。

结论

CD83通过ITGB1/FAK信号轴调控三阴性乳腺癌细胞迁移和侵袭,可能作为潜在的乳腺癌治疗靶点。

Objective

To investigate the effect of CD83 on the proliferation, apoptosis, cell cycle progression, migration, and invasion of triple negative breast cancer cells, and to explore the mechanisms underlying its regulation of the biological behaviors of these malignant cells.

Methods

To evaluate CD83 expression in breast cancer, we retrieved 822 breast cancer and 572 normal tissue samples from TCGA. This dataset enabled analysis of CD83 expression differences in breast cancer. We also used Western blot to measure CD83 protein levels in MCF-10A (normal breast epithelial cells) and breast cancer cells (MCF-7, BT-549, MDA-MB-231) . This method facilitated direct CD83 protein level comparison between normal and cancerous breast cells, enhancing insights into CD83’s role in breast cancer. Using the CRISPR/Cas9, we established stable CD83 knockout MDA-MB-231 cell lines (sg-CD83-#1, sg-CD83-#2, sg-CD83-#3) and selected sg-CD83 for further study based on protein extraction and CD83 disruption efficiency. Functional assays including CCK-8, scratch wound healing, and Transwell were conducted on sg-CD83 versus sg-ctrl, sg-ctrl as the negative control for CD83 knockout. Co-IP was used to examine CD83-ITGB1 interactions. Establishment of MDA-MB-231 cell line overexpressing CD83 through plasmid transfection, and created an ov-CD83 group to study CD83 overexpression effects, assessing proliferation, migration, and invasion via scratch and Transwell assays against vector, which as a control for CD83 overexpression. The impact of ITGB1 on CD83 function was assessed by silencing ITGB1 in CD83-overexpressing cells, using the si-NC as a control for ITGB1 knockdown. Statistical analysis involved independent t-tests for intergroup comparisons and one-way ANOVA with LSD post hoc tests for multiple groups, ensuring robustness of findings.

Results

TCGA database analysis revealed significant CD83 mRNA expression differences among breast cancer subtypes and normal tissue. CD83 levels were 4.63±0.79 in lunimal A subtype, 4.57±0.77 in luminal B subtype, 4.62±0.75 in HER-2 overexpression subtype and 5.40±1.13 in TNBC subtype and 3.30±1.17 in normal tissue. Statistical analysis showed highly significant differences (F=196.802, P<0.001) , with TNBC showing notably higher CD83 expression than other subtypes (P<0.001) . This suggests CD83’s potential as a TNBC biomarker and therapeutic target, highlighting the need for further functional studies in this breast cancer subtype. The protein expression levels of CD83 in MCF-10A, MCF-7, BT-549, and MDA-MB-231 cells were 1.00±0.01, 1.44±0.02, 1.71±0.02, and 1.89±0.07, respectively, showing statistical significance (F=353.070, P<0.001) . The sg-CD83-#3 group showed the best CD83 knockout efficiency. Thus, it was selected as the CD83 knockout model (sg-CD83) for further experiments. The protein expression of CD83 in MDA-MB-231 cells in the four groups of sg-ctrl, sg-CD83-#1, sg-CD83-#2, and sg-CD83-#3 were 1.00±0.02, 0.79±0.18, 0.32±0.03, and 0.23±0.05, respectively, with statistical significance (F=48.758, P<0.001) . The absorbance at 450 nm for the sg-ctrl group and the sg-CD83 group at 24, 48, 72, and 96 hours was as follows: 0.63±0.05 vs 0.51±0.03, 0.92±0.03 vs 0.70±0.06, 1.27±0.02 vs 0.90±0.09, and 1.54±0.14 vs 1.06±0.09. These differences were statistically significant (all P<0.050) . The apoptosis rates in the sg-ctrl group and sg-CD83 group were [ (5.96±0.06) % vs (12.82±0.07) %, (t=-128.877, P<0.001) ], the G0/G1 phase cell ratio was [ (31.87±0.76) % vs (44.75±1.50) %, (t=-13.229, P<0.001) ]; There were statistically significant differences in cell scratch healing rate [ (34.47±0.87) % vs (16.63±0.70) %, (t=27.554, P<0.001) ], the number of migrating cells (143.67±4.16 vs 62.67±1.53, t=31.636, P<0.001) , and the number of invasive cells (123.67±3.06 vs 26.33±2.52, t=42.593, P<0.001) . The expression levels of ITGB1 were 1.00±0.02 in the sg-ctrl group and 0.34±0.02 in the sg-CD83 group, showing statistical significance (t=40.417, P<0.001) . Similarly, FAK expression was 1.00±0.01 in the sg-ctrl group and 0.79±0.07 in the sg-CD83 group (t=5.144, P=0.033) . The p-FAK levels were 0.99±0.03 and 0.35±0.05, respectively, with a statistically significant difference (t=19.395, P<0.001) . In the co-immunoprecipitation (Co-IP) assay, CD83 and ITGB1 were co-precipitated. There were statistically significant differences in scratch wound healing rates [ (8.40±2.73) % vs (45.08±1.51) %, t=-20.340, P<0.001], migratory cell counts (151.00±2.65 vs 337.67±3.51, t=-73.532, P<0.001) , and invasive cell counts (120.33±4.16 vs 288.67±4.51, t=-47.506, P<0.001] between the vector group and ov-CD83 group. There were statistically significant differences in scratch wound healing rates [ (44.63±2.11) % vs (13.93±2.90) %, t=14.839, P<0.001], migratory cell counts (339.67±3.06 vs 181.67±2.31, t=71.458, P<0.001) , and invasive cell counts (289.00±5.29 vs 170.33±5.03, t=28.144, P<0.001) between the si-NC group and si-ITGB1 group.

Conclusion

CD83 regulates the migration and invasion of triple negative breast cancer cells through the ITGB1/FAK signaling pathway and may serve as a potential target for breast cancer.

表1 正常组织和各亚型乳腺癌组织中CD83 mRNA表达比较
图1 Western blot检测人正常乳腺上皮细胞和3种乳腺癌细胞中CD83的表达注:a、b、c、d分别为MCF-10A、MCF-7、BT-549和MDA-MB-231细胞;GAPDH为甘油醛-3-磷酸脱氢酶
图2 Western blot检测敲除CD83的MDA-MB-231细胞株中CD83蛋白的表达水平注:a为阴性载体对照sg-ctrl组;b、c、d分别为sg-CD83-#1、sg-CD83-#2、sg-CD83-#3基因敲除的MDA-MB-231细胞;GAPDH为甘油醛-3-磷酸脱氢酶
表2 CD83敲除后不同时间点MDA-MB-231细胞吸光度值的变化
图3 CD83敲除后MDA-MB-231细胞凋亡率变化 a、b图分别为sg-ctrl组和sg-CD83组的凋亡检测结果(碘化丙啶染色 ×40)注:Q1为坏死细胞百分率;Q2为晚期凋亡细胞百分率;Q3为正常细胞百分率;Q4为早期凋亡细胞百分率
表3 CD83敲除后MDA-MB-231细胞凋亡率和细胞周期比较(%)
图4 CD83敲除的MDA-MB-231细胞划痕愈合实验结果(×100) a、b图分别为sg-ctrl组划痕实验开始和24 h后对比图;c、d图分别为sg-CD83组划痕实验开始和24 h后对比图注:sg-ctrl为阴性载体对照组;sg-CD83为CD83基因敲除的MDA-MB-231细胞
图5 CD83敲除的MDA-MB-231细胞Transwell迁移和侵袭实验结果(结晶紫染色 ×200) a、b图分别为sg-ctrl和sg-CD83组MDA-MB-231细胞Transwell迁移实验结果;c、d图分别为sg-ctrl和sg-CD83组MDA-MB-231细胞Transwell侵袭实验结果注:sg-ctrl为阴性载体对照组;sg-CD83为CD83基因敲除的MDA-MB-231细胞
图6 CD83敲除和过表达后ITGB1、FAK和p-FAK的表达情况注:a为阴性载体对照sg-ctrl组、b为CD83基因敲除的sg-CD83组;c为空载体对照vector组、d为CD83基因过表达的ov-CD83组;GAPDH为甘油醛-3-磷酸脱氢酶;ITGB1为整合素β1,FAK为黏着斑激酶,p-FAK为磷酸化的黏着斑激酶
图7 免疫共沉淀实验检测CD83与ITGB1的相互作用注:a为Input组,确定目标蛋白的初始表达水平;b为IgG组,作为阴性对照,评估非特异性结合的背景水平;c为IP-CD83组,使用针对CD83的特异性抗体进行免疫共沉淀,富集和检测CD83蛋白及其相互作用蛋白;ITGB1为整合素β1
图8 CD83过表达的MDA-MB-231细胞划痕愈合实验结果(×100) a、b图分别为vector组划痕实验开始和24 h后对比图;c、d图分别为ov-CD83组划痕实验开始和24 h后对比图注:vector为CD83过表达空载体对照组,ov-CD83为CD83基因过表达的MDA-MB-231细胞
图9 CD83过表达的MDA-MB-231细胞Transwell迁移和侵袭实验结果(结晶紫染色 ×200) a、b图分别为vector组和ov-CD83组迁移实验结果;c、d图分别为vector组和ov-CD83组侵袭实验结果注:vector为CD83过表达空载体对照组,ov-CD83为CD83基因过表达的MDA-MB-231细胞
图10 ITGB1敲低的CD83过表达MDA-MB-231细胞划痕愈合实验结果(×100) a、b图分别为si-NC组划痕实验开始和24 h后对比图;c、d图分别为si-ITGB1组划痕实验开始和24 h后对比图注:si-NC为ITGB1敲低阴性载体对照组,si-ITGB1为ITGB1基因敲低的MDA-MB-231细胞
图11 ITGB1敲低的CD83过表达MDA-MB-231细胞Transwell迁移和侵袭实验结果(结晶紫染色 ×200) a、b图分别为si-NC和si-ITGB1组迁移实验结果;c、d图分别为si-NC组和si-ITGB1组侵袭实验结果注:si-NC为ITGB1敲低阴性载体对照组,si-ITGB1为ITGB1基因敲低的MDA-MB-231细胞
[1]
Bray FLaversanne MSung H,et al. Global cancer statistics 2022:globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA Cancer J Clin202474(3):229-263.
[2]
Jokar NVelikyan IAhmadzadehfar H,et al. Theranostic approach in breast cancer:a treasured tailor for future oncology [J]. Clin Nucl Med202146(8):e410-e420.
[3]
Riaz BIslam SRyu HM,et al. CD83 regulates the immune responses in inflammatory disorders [J]. Int J Mol Sci202324(3):2831.
[4]
Wu ZYoshikawa TInoue S,et al. CD83 expression characterizes precursor exhausted T cell population [J]. Commun Biol20236(1):258.
[5]
Peckert-Maier KWild ABSprissler L,et al. Soluble CD83 modulates human-monocyte-derived macrophages toward alternative phenotype,function,and metabolism [J]. Front Immunol202314:1293828.
[6]
Kapoor S. CD83 antigen expression and its role in the progression of systemic malignancies [J]. Sao Paulo Med J2013131(2):137.
[7]
Kashimura SSaze ZTerashima M,et al. CD83(+) dendritic cells and Foxp3(+) regulatory T cells in primary lesions and regional lymph nodes are inversely correlated with prognosis of gastric cancer [J]. Gastric Cancer201215(2):144-153.
[8]
Hayati ARZulkarnaen M. An immunohistochemical study of CD1a and CD83-positive infiltrating dendritic cell density in cervical neoplasia [J]. Int J Gynecol Pathol200726(1):83-88.
[9]
Zheng JWei YLi X,et al. Higher CD1a levels correlate with PD-L1 expression and predict worse overall survival in triple-negative breast carcinoma [J]. Breast Care (Basel)202217(1):31-39.
[10]
Jinek MChylinski KFonfara I,et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity [J]. Science2012337(6096):816-821.
[11]
Riggio AIVarley KEWelm AL. The lingering mysteries of metastatic recurrence in breast cancer [J]. Br J Cancer2021124(1):13-26.
[12]
Lopez CBosch RKorzynska A,et al. CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients [J]. Breast Cancer202229(4):618-635.
[13]
Giorello MBMatas AMarenco P,et al. CD1a- and CD83-positive dendritic cells as prognostic markers of metastasis development in early breast cancer patients [J]. Breast Cancer202128(6):1328-1339.
[14]
Abdellateif MSShaarawy SMKandeel EZ,et al. A novel potential effective strategy for enhancing the antitumor immune response in breast cancer patients using a viable cancer cell-dendritic cell-based vaccine [J]. Oncol Lett201816(1):529-535.
[15]
Hernandez-Juarez JGonzalez-Cruz AOMiranda-Espino R,et al. Effects of siRNA-mediated silencing of ERBB2,IGF-1R,and ITGB1 in HER2-positive breast cancer cells [J]. Cancer Diagn Progn20233(2):183-188.
[16]
Xu ZZou LMa G,et al. Integrin β1 is a critical effector in promoting metastasis and chemo-resistance of esophageal squamous cell carcinoma [J]. Am J Cancer Res20177(3):531-542.
[17]
Lv YWei CZhao B. Study on the mechanism of low shear stress restoring the viability of damaged breast tumor cells [J]. Tissue Cell202279:101947.
[18]
Polyak KWeinberg RA. Transitions between epithelial and mesenchymal states:acquisition of malignant and stem cell traits [J]. Nat Rev Cancer20099(4):265-273.
[19]
Zhang LQu JQi Y,et al. EZH2 engages TGFβ signaling to promote breast cancer bone metastasis via integrin β1-FAK activation [J]. Nat Commun202213(1):2543.
[20]
Yang JHou YZhou M,et al. Twist induces epithelial-mesenchymal transition and cell motility in breast cancer via ITGB1-FAK/ILK signaling axis and its associated downstream network [J]. Int J Biochem Cell Biol201671:62-71.
[21]
Baleeiro RBBarbuto JA. Local secretion/shedding of tumor-derived CD83 molecules as a novel tumor escape mechanism [J]. Mol Immunol200845(12):3502-3504.
[1] 姜明霞, 李俏, 徐兵河. 局部晚期HER-2阳性乳腺癌的新辅助治疗[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(03): 129-138.
[2] 徐颖, 宋雨, 黄欣, 周易冬, 孙强, 林燕. 精准医学时代局部晚期乳腺癌的诊治热点[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(03): 139-144.
[3] 张毅. 铂类药物在三阴性乳腺癌新辅助治疗中的临床及转化研究[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(03): 192-192.
[4] 柴效科, 周海存, 杨涛, 卫翀羿, 魏赟, 张旭, 隆建萍. HER-2状态与AR/p53/Ki-67表达对三阴性乳腺癌新辅助化疗疗效及预后的影响[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 84-91.
[5] 张国锋, 徐向升, 刘蕾, 张春, 孔蕾, 房立柱. 早期浸润性乳腺癌保留乳房患者的腋窝分期研究[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 92-96.
[6] 李昕宇, 李玉东, 刘强. 乳腺癌前哨淋巴结活组织检查的临床应用[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 108-112.
[7] 乔平, 杜华, 师迎旭. 选择性多聚腺苷酸化在乳腺癌中的研究进展[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 113-118.
[8] 史福军, 魏巍, 林晓华, 廖玥, 郭志容. 单孔机器人辅助乳腺癌手术一例[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 125-127.
[9] 金钰婷, 苑龙, 齐晓伟, 姜军. 乳腺癌非根治性手术临床研究证据[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 65-69.
[10] 李金泽, 彭雅琪, 刘月平, 马力. 乳腺癌HER-2低表达及超低表达临床研究进展[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 70-75.
[11] 肖锦怡, 周金妹, 王涛. 2024年乳腺癌全身系统治疗十大热点[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(02): 76-83.
[12] 王昭雨, 姜军. 乳腺癌外科治疗理论和技术的发展与挑战[J/OL]. 中华乳腺病杂志(电子版), 2025, 19(01): 1-5.
[13] 慕春燕, 杨大伟, 张云东, 崔兆清. E1A结合蛋白P300与乳腺癌发生发展的关系研究进展[J/OL]. 中华普通外科学文献(电子版), 2025, 19(02): 111-115.
[14] 张克俭, 赵建红, 尚培中, 张克勤, 张少斌, 王铁山. 乳腺癌肺转移术后化疗并发骨髓增生异常和Sweet综合征一例报道[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(04): 471-472.
[15] 苏明, 唐丹萍, 王萍, 何谦. 乳腺癌改良根治术后即刻乳房重建的方法选择研究进展[J/OL]. 中华普外科手术学杂志(电子版), 2025, 19(02): 231-234.
阅读次数
全文


摘要


AI


AI小编
你好!我是《中华医学电子期刊资源库》AI小编,有什么可以帮您的吗?