网状蛋白1C水平与三阴性乳腺癌新辅助化疗疗效的相关性研究

doi:10.11958/20220641

天津医药 ›› 2023, Vol. 51 ›› Issue (1): 69-73.doi: 10.11958/20220641

网状蛋白1C水平与三阴性乳腺癌新辅助化疗疗效的相关性研究

张曼丽¹(), 刘唯唯¹, 王丽娟², 李卫东³

1 沧州市人民医院乳腺中心（邮编061000）
2 沧州市人民医院手术室（邮编061000）
3 沧州市人民医院甲乳外科（邮编061000）

收稿日期:2022-04-26 修回日期:2022-05-13 出版日期:2023-01-15 发布日期:2023-01-17
作者简介:张曼丽（1977），女，副主任医师，主要从事乳腺相关疾病治疗方面研究及科研工作。E-mail：mlzhang7777@163.com
基金资助:
河北省医学科学研究项目(20200285)

The correlation between the level of reticulin 1C in peripheral blood mononuclear cells and the efficacy of neoadjuvant chemotherapy for triple negative breast cancer

ZHANG Manli¹(), LIU Weiwei¹, WANG Lijuan², LI Weidong³

1 Breast Center,, Cangzhou People's Hospital, Cangzhou 061000, China
2 Operating Room,, Cangzhou People's Hospital, Cangzhou 061000, China
3 Thyroid and Breast Surgery, Cangzhou People's Hospital, Cangzhou 061000, China

Received:2022-04-26 Revised:2022-05-13 Published:2023-01-15 Online:2023-01-17

张曼丽, 刘唯唯, 王丽娟, 李卫东. 网状蛋白1C水平与三阴性乳腺癌新辅助化疗疗效的相关性研究[J]. 天津医药, 2023, 51(1): 69-73.

ZHANG Manli, LIU Weiwei, WANG Lijuan, LI Weidong. The correlation between the level of reticulin 1C in peripheral blood mononuclear cells and the efficacy of neoadjuvant chemotherapy for triple negative breast cancer[J]. Tianjin Medical Journal, 2023, 51(1): 69-73.

摘要/Abstract

摘要：

目的探究三阴性乳腺癌（TNBC）患者外周血单个核细胞中网状蛋白1C（RTN-1C）表达水平与新辅助化疗疗效的关系。方法选取154例TNBC患者作为研究对象。收集所有受试者年龄、月经状态、病理类型、TNM分期、组织学分级和Ki-67表达>30%情况、肿瘤直径。抽取TNBC患者化疗前（T₀）、化疗7 d（T₁）、化疗14 d（T₂）和化疗21 d（T₃）的空腹肘正中静脉血，用Ficoll密度梯度离心法分离外周血中单个核细胞，蛋白质免疫印迹法检测单个核细胞中RTN-1C表达水平。受试者工作特征（ROC）曲线评价RTN-1C判断新辅助化疗疗效的效能，Logistic回归分析新辅助化疗疗效的风险因素，构建列线图回归模型预测新辅助化疗后病理学完全缓解，一致性指数（C-index）、校准曲线和决策曲线评估模型效能。结果根据新辅助化疗疗效分为完全缓解组（n=47）和未完全缓解组（n=107）。在T₁和T₃完全缓解组的RTN-1C均低于未完全缓解组（P<0.05）;T₀、T₁和T₂的2组RTN-1C相对表达水平随时间进展均降低（P<0.01）。T₃-RTN-1C判断新辅助化疗后病理学完全缓解的ROC曲线下面积（AUC）高于T₀-RTN-1C、T₁-RTN-1C和T₂-RTN-1C（P<0.01）。Logistic回归分析结果显示T₃-RTN-1C>0.91（OR=12.178，95%CI：4.796~30.924）、N1期或N2期（OR=2.180，95%CI：1.100~4.322）、组织学分级Ⅲ级（OR=3.609，95%CI：1.453~8.969）是新辅助化疗后病理学未完全缓解的独立危险因素（P<0.05）。模型A（N分期、组织学分级和T₃-RTN-1C构建）的拟合曲线和理想曲线重合度较高，模型B（由N分期和组织学分级构建）的拟合曲线和理想曲线重合度较差。模型A、B的C-index分别为0.866和0.772。当阈值概率大于0.40时，模型A判断新辅助化疗后病理学完全缓解的净收益高于模型B。结论 N分期、组织学分级和T₃-RTN-1C构建的模型对判断新辅助化疗后病理学完全缓解有较高的区分度、精准度和临床应用价值。

关键词: 三阴性乳腺癌, 化学疗法，辅助, 单核细胞, 网状蛋白1C, 病理学完全缓解

Abstract:

Objective To explore the relationship between the expression level of reticulin 1C (RTN-1C) in peripheral blood mononuclear cells of patients with triple negative breast cancer (TNBC) and the efficacy of neoadjuvant chemotherapy. Methods A total of 154 TNBC patients were selected as the study subjects. Patients were divided into the complete remission group (n=47) and the incomplete remission group (n=107) according to the efficacy of neoadjuvant chemotherapy. Data of age, menstrual status, type of pathology, TNM stage, histological grade, Ki-67 expression >30% and tumour diameter were collected from all subjects. Fasting elbow venous blood samples were collected from TNBC patients before chemotherapy (T₀), 7 days after chemotherapy (T₁), 14 days after chemotherapy (T₂) and 21 days after chemotherapy (T₃). Peripheral blood mononuclear cells were isolated by Ficoll density gradient centrifugation. The expression levels of RTN-1C in mononuclear cells were detected by Western blot assay. The receiver operating characteristic curve (ROC) was used to evaluate the efficacy of RTN-1C in determining neoadjuvant chemotherapy efficacy. Logistic regression was used to analyse risk factors for neoadjuvant chemotherapy efficacy. Nomogram regression models were constructed to predict complete remission of pathology after neoadjuvant chemotherapy, and consistency index (C-index), calibration curves and decision tree curves were used to assess model efficacy. Results The relative expression levels of RTN-1C were lower at T₁ and T₃ in the complete remission group than those in the incomplete remission group (P<0.05). The relative expression levels of RTN-1C at T₀, T₁ and T₂ decreased over time in the 2 groups (P<0.01). The area under the ROC curve (AUC) of T₃-RTN-1C was higher than T₀-RTN-1C, T₁-RTN-1C and T₂-RTN-1C in judging pathological complete remission after neoadjuvant chemotherapy (P<0.01). Logistic regression analysis showed that T₃-RTN-1C>0.91 (OR=12.178, 95%CI: 4.796-30.924), N1 or N2 (OR=2.180, 95%CI: 1.100-4.322) and histological grade Ⅲ (OR=3.609, 95%CI: 1.453-8.969) were independent risk factors for pathological incomplete remission after neoadjuvant chemotherapy (P<0.05). Model A (constructed by N stage, histological grade and T₃-RTN-1C) had a high degree of coincidence between the fitting curve and the ideal curve, while model B (constructed by N stage and histological grade) had a poor degree of coincidence between the fitting curve and the ideal curve. The C-index of model A and model B were 0.866 and 0.772, respectively. When the threshold probability was higher than 0.40, the net benefit of model A in judging pathological complete response after neoadjuvant chemotherapy was higher than that of model B. Conclusion The model constructed by N stage, histological grade and T₃-RTN-1C has a high degree of differentiation, accuracy and clinical application value in judging pathological complete response after neoadjuvant chemotherapy.

Key words: triple negative breast neoplasms, chemotherapy, adjuvant, monocytes, reticulin 1C, pathological complete remission

中图分类号:

R737.9

图/表 7

参考文献 20

[1]	DESANTIS C E, MA J, GODING SAUER A, et al. Breast cancer statistics,2017,racial disparity in mortality by state[J]. CA Cancer J Clin,2017, 67(6):439-448. doi:10.3322/caac.21412.
[2]	MIAO K, LEI J H, VALECHA M V, et al. NOTCH1 activation compensates BRCA1 deficiency and promotes triple-negative breast cancer formation[J]. Nat Commun, 2020, 11(1):3256. doi:10.1038/s41467-020-16936-9.
[3]	陈茂山, 莫琳龙, 杨宏伟, 等. FAT4在三阴性乳腺癌组织中的表达及其临床意义[J]. 中国普通外科杂志, 2020, 29(5):525-531.
	CHEN M S, MO L L, YANG H W, et al. FAT4 expression in triple negative breast cancer and its clinical significance[J]. Chinese Journal of General Surgery, 2020, 29(5):525-531. doi:10.7659/j.issn.1005-6947.2020.05.002.
[4]	CORTAZAR P, ZHANG L, UNTCH M, et al. Pathological complete response and long-term clinical benefit in breast cancer:the CTNeoBC pooled analysis[J]. Lancet, 2014, 384(9938):164-172. doi:10.1016/S0140-6736(13)62422-8.
[5]	刘杰娜, 张建国, 郭宝良, 等. 乳腺癌患者Ki-67表达水平对新辅助化疗后病理学完全缓解的预测价值[J]. 中国普通外科杂志, 2018, 27(5):608-614.
	LIU J N, ZHANG J G, GUO B L, et al. Predictive value of Ki-67 expression level in breast cancer patients for pathological complete remission after neoadjuvant chemotherapy[J]. Chinese Journal of General Surgery, 2018, 27(5):608-614. doi:10.3978/j.issn.1005-6947.2018.05.013.
[6]	FAZI B, MELINO S, DE RUBEIS S, et al. Acetylation of RTN-1C regulates the induction of ER stress by the inhibition of HDAC activity in neuroectodermal tumors[J]. Oncogene, 2009, 28(43):3814-3824. doi:10.1038/onc.2009.233.
[7]	D' ELETTO M, RISUGLIA A, OLIVERIO S, et al. Modulation of autophagy by RTN-1C:role in autophagosome biogenesis[J]. Cell Death Dis, 2019, 10(12):868. doi:10.1038/s41419-019-2099-7.
[8]	LI T, ZHANG S, CHEN F, et al. Formononetin ameliorates the drug resistance of Taxol resistant triple negative breast cancer by inhibiting autophagy[J]. Am J Transl Res, 2021, 13(2):497-514.
[9]	ASHRAFIZADEH M, MOHAMMADINEJAD R, TAVAKOL S, et al. New insight into triple-negative breast cancer therapy:The potential roles of endoplasmic reticulum stress and autophagy mechanisms[J]. Anticancer Agents Med Chem, 2021, 21(6):679-691. doi:10.2174/1871520620666200619180716.
[10]	LI Q W, ZHANG G L, HAO C X, et al. SANT,a novel Chinese herbal monomer combination, decreasing tumor growth and angiogenesis via modulating autophagy in heparanase overexpressed triple-negative breast cancer[J]. J Ethnopharmacol, 2021, 266:113430. doi:10.1016/j.jep.2020.113430.
[11]	中国抗癌协会乳腺癌专业委员会. 中国抗癌协会乳腺癌诊治指南与规范(2019年版)[J]. 中国癌症杂志, 2019, 29(8):609-679.
	Breast Cancer Professional Committee of China Anti-Cancer Association. Guidelines and Specifications for Breast Cancer Diagnosis and Treatment of China Anti-Cancer Association(2019 Edition)[J]. China Oncology, 2019, 29(8):609-679. doi:10.19401/j.cnki.1007-3639.2019.08.009.
[12]	LEE A, DJAMGOZ M. Triple negative breast cancer:Emerging therapeutic modalities and novel combination therapies[J]. Cancer Treat Rev, 2018, 62:110-122. doi:10.1016/j.ctrv.2017.11.003.
[13]	刘德樟, 周小忠, 黄鑫, 等. 动态对比增强磁共振成像特征对三阴性乳腺癌新辅助化疗肿瘤反应的预测价值研究[J]. 实用放射学杂志, 2019, 35(6):909-913.
	LIU D Z, ZHOU X Z, HUANG X, et al. The value of DCEGMRI in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer[J]. Journal of Practical Radiology, 2019, 35(6):909-913. doi:10.3969/j.issn.1002G1671.2019.06.014.
[14]	HU Y, ZHANG H R, DONG L, et al. Enhancing tumor chemotherapy and overcoming drug resistance through autophagy-mediated intracellular dissolution of zinc oxide nanoparticles[J]. Nanoscale, 2019, 11(24):11789-11807. doi:10.1039/c8nr08442d.
[15]	LIMAGNE E, NUTTIN L, THIBAUDIN M, et al. MEK inhibition overcomes chemoimmunotherapy resistance by inducing CXCL10 in cancer cells[J]. Cancer Cell, 2022, 40(2):136-152.e12. doi:10.1016/j.ccell.2021.12.009.
[16]	NARDONE V, BARBARINO M, ANGRISANI A, et al. CDK4,CDK6/cyclin-D1 complex inhibition and radiotherapy for cancer control:A role for autophagy[J]. Int J Mol Sci, 2021, 22(16):8391. doi:10.3390/ijms22168391.
[17]	LI Y, CHO M H, LEE S S, et al. Hydroxychloroquine-loaded hollow mesoporous silica nanoparticles for enhanced autophagy inhibition and radiation therapy[J]. J Control Release, 2020, 325:100-110. doi:10.1016/j.jconrel.2020.06.025.
[18]	GAO L, WANG Q, REN W, et al. The RBP1-CKAP4 axis activates oncogenic autophagy and promotes cancer progression in oral squamous cell carcinoma[J]. Cell Death Dis, 2020, 11(6):488. doi:10.1038/s41419-020-2693-8.
[19]	REALI V, MEHDAWY B, NARDACCI R, et al. Reticulon protein-1C is a key component of MAMs[J]. Biochim Biophys Acta, 2015, 1853(3):733-745. doi:10.1016/j.bbamcr.2014.12.031.
[20]	何浪. 基于基因表达谱的乳腺癌外周血与肿瘤局部免疫微环境关联性研究[D]. 成都: 电子科技大学, 2016.
	HE L. Relationship between breast cancer peripheral blood and tumor local immune microenvironment based on gene expression profile[D]. Chengdu: University of Electronic Science and Technology of China, 2016. doi:10.7666/d.D00991103.

组别	n	T₀	T₁	T₂	T₃	F
完全缓解组	47	2.15±0.32	1.52±0.21^a	1.06±0.17^ab	0.88±0.09^abc	320.408^＊＊
未完全缓解组	107	2.16±0.34	1.65±0.31^a	1.02±0.20^ab	0.97±0.08^ab	510.894^＊＊
t		0.088	3.128^＊＊	1.028	6.797^＊＊

组别	n	T₀	T₁	T₂	T₃	F
完全缓解组	47	2.15±0.32	1.52±0.21^a	1.06±0.17^ab	0.88±0.09^abc	320.408^＊＊
未完全缓解组	107	2.16±0.34	1.65±0.31^a	1.02±0.20^ab	0.97±0.08^ab	510.894^＊＊
t		0.088	3.128^＊＊	1.028	6.797^＊＊

指标	AUC	95%CI	最佳截断点	敏感度	特异度
T₀-RTN-1C	0.503	0.421~0.584	2.39	0.794	0.298
T₁-RTN-1C	0.615	0.534~0.693	1.82	0.308	1.000
T₂-RTN-1C	0.546	0.464~0.626	0.82	0.224	0.915
T₃-RTN-1C	0.806	0.735~0.866	0.91	0.804	0.787

指标	AUC	95%CI	最佳截断点	敏感度	特异度
T₀-RTN-1C	0.503	0.421~0.584	2.39	0.794	0.298
T₁-RTN-1C	0.615	0.534~0.693	1.82	0.308	1.000
T₂-RTN-1C	0.546	0.464~0.626	0.82	0.224	0.915
T₃-RTN-1C	0.806	0.735~0.866	0.91	0.804	0.787

组别		n	年龄					月经状态				病理类型						Ki-67
组别		n	≤45岁		>45岁			绝经前		绝经后		浸润性导管癌		浸润性小叶癌		髓样癌		≤30%		>30%
完全缓解组		47	22（46.8）		25（53.2）			27（57.4）		20（42.6）		41（87.2）		4（8.5）		2（4.3）		3（6.4）		44（93.6）
未完全缓解组		107	59（55.1）		48（44.9）			72（67.3）		35（32.7）		93（86.9）		9（8.4）		5（4.7）		29（27.1）		78（72.9）
χ²			0.909					1.378				0.016						8.517^＊＊
组别	T₃-RTN-1C					肿瘤直径					N分期						组织学分级
组别	≤0.91			>0.91		≤2 cm	2~5 cm		>5 cm		N0		N1		N2		Ⅰ		Ⅱ		Ⅲ
完全缓解组	37（78.7）			10（21.3）		3（6.4）	33（70.2）		11（23.4）		23（48.9）		20（42.6）		4（8.5）		18（38.3）		26（55.3）		3（6.4）
未完全缓解组	21（19.6）			86（80.4）		8（7.5）	73（68.2）		26（24.3）		19（17.8）		50（46.7）		38（35.5）		9（8.4）		79（73.8）		19（17.8）
χ²	48.578^＊＊					0.084					20.497^＊＊						21.236^＊＊

网状蛋白1C水平与三阴性乳腺癌新辅助化疗疗效的相关性研究

The correlation between the level of reticulin 1C in peripheral blood mononuclear cells and the efficacy of neoadjuvant chemotherapy for triple negative breast cancer

引用本文

RichHTML

PDF (PC)

可视化

摘要/Abstract

使用本文

图/表 7

参考文献 20

相关文章 15

编辑推荐

Metrics

本文评价

变量	β	SE	Wald χ²	P	OR	OR95%CI
Ki-67	-1.217	0.736	2.731	0.098	0.296	0.070~1.254
T₃-RTN-1C	2.500	0.475	27.639	<0.001	12.178	4.796~30.924
N分期	0.779	0.349	4.983	0.026	2.180	1.100~4.322
组织学分级	1.284	0.464	7.640	0.006	3.609	1.453~8.969
常数项	-2.530	1.106	5.235	0.022	0.080

[1]	满祎, 许娅, 何先成, 宋少锋, 刘爱国. 三阴性乳腺癌EGFR、Ki-67、P53及CTC表达与预后的关系研究[J]. 天津医药, 2024, 52(8): 862-867.
[2]	王娴, 刘霞明, 陈曼玉, 赵君, 王立东. 基于机器学习对2型糖尿病肾病预测模型的构建及验证[J]. 天津医药, 2024, 52(7): 775-780.
[3]	杜凤娇, 杜博平, 贾红彦, 邢爱英, 李自慧, 朱传智, 李华. 液态芯片技术筛选胸腔积液细胞因子对结核性胸膜炎的诊断价值[J]. 天津医药, 2024, 52(3): 319-323.
[4]	孙瑞雪, 刘霄霄, 岳欣怡, 杨冬梅, 任鲁宁, 王菲, 杜红阳. 术前血液学炎症指标对基底细胞癌复发风险的预测价值[J]. 天津医药, 2024, 52(12): 1274-1277.
[5]	卢鑫怡, 杜伟坡, 李景刚, 郭芳芳, 张晓雷, 刘静. 血清miR-193a-3p、ATF5水平与三阴性乳腺癌患者化疗疗效的相关性[J]. 天津医药, 2024, 52(12): 1313-1316.
[6]	杨凯, 侯丁聪, 段少先, 毕怡, 谢炎, 张骊, 蒋文涛. PNI、LMR、MELD对肝移植术后早期肺部感染的预测价值[J]. 天津医药, 2024, 52(10): 1041-1045.
[7]	张志强, 王威威, 董腾靖, 连鸿凯. 强直性脊柱炎患者外周血TLR4、JAK3基因表达与Th17/Treg失衡的关系[J]. 天津医药, 2024, 52(10): 1065-1068.
[8]	张晓宇, 任悦, 刘伟, 苗彦玲, 张辉, 靳丽君, 张恒乐, 康晓宁, 白杰, 王遵义. 新辅助化疗联合PD-1抑制剂治疗三阴性乳腺癌的临床疗效[J]. 天津医药, 2023, 51(8): 847-850.
[9]	杨国红, 余芳芳, 蔡伟, 牛秀珑, 张芯, 赵季红, 李玉明, 陈少伯. VEGFR-3⁺单核细胞对高血压小鼠左心室重塑的影响[J]. 天津医药, 2023, 51(2): 144-148.
[10]	许莉敏, 谢燕. 外周血单核细胞DNMT1及血清IL-6在糖尿病肾脏病中的表达及意义[J]. 天津医药, 2023, 51(2): 194-197.
[11]	刘淑娟, 刘梦莹, 苏乌云, 窦佳, 王薇. 肿瘤相关巨噬细胞通过激活IGF-1R信号通路诱导三阴性乳腺癌细胞对白蛋白紫杉醇耐药的研究[J]. 天津医药, 2023, 51(11): 1158-1163.
[12]	陈聪, 吴元肇, 郑克思, 应文兵, 胡逸人. 钙蛋白酶2通过诱导三阴乳腺癌细胞上皮间质转化抵抗紫杉醇的机制探讨[J]. 天津医药, 2023, 51(11): 1176-1180.
[13]	李宇翔, 李葛, 高振芳, 侯春梅, 韩根成, 孙慧燕, 王立生. Mesothelin对乳腺癌细胞MDA-MB-231生物学行为的影响[J]. 天津医药, 2023, 51(10): 1032-1039.
[14]	张岑, 王志华, 杨磊. 肺炎支原体社区获得性呼吸窘迫综合征毒素对单核细胞亚群的影响[J]. 天津医药, 2023, 51(10): 1080-1083.
[15]	田园, 牟雅君, 杨文秀, 豆晓伟. Notch3调控Hes2逆转三阴性乳腺癌上皮-间质转化的机制研究[J]. 天津医药, 2022, 50(8): 785-790.