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

doi:10.11958/20220641

Abstract

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

CLC Number:

R737.9

Figures/Tables 7

References 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^＊＊