Yu-tuan Wu, Xin Li, Lin-jie Lu, Lu Gan, Wei Dai, Yan-ling Shi, Vishnu Prasad Adhikari, Kai-nan Wu, Ling-quan Kong. Effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese breast cancer patients: A retrospective study of 525 patients[J]. The Journal of Biomedical Research, 2018, 32(3): 191-197. DOI: 10.7555/JBR.32.20170059
Citation:
Yu-tuan Wu, Xin Li, Lin-jie Lu, Lu Gan, Wei Dai, Yan-ling Shi, Vishnu Prasad Adhikari, Kai-nan Wu, Ling-quan Kong. Effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese breast cancer patients: A retrospective study of 525 patients[J]. The Journal of Biomedical Research, 2018, 32(3): 191-197. DOI: 10.7555/JBR.32.20170059
Yu-tuan Wu, Xin Li, Lin-jie Lu, Lu Gan, Wei Dai, Yan-ling Shi, Vishnu Prasad Adhikari, Kai-nan Wu, Ling-quan Kong. Effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese breast cancer patients: A retrospective study of 525 patients[J]. The Journal of Biomedical Research, 2018, 32(3): 191-197. DOI: 10.7555/JBR.32.20170059
Citation:
Yu-tuan Wu, Xin Li, Lin-jie Lu, Lu Gan, Wei Dai, Yan-ling Shi, Vishnu Prasad Adhikari, Kai-nan Wu, Ling-quan Kong. Effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese breast cancer patients: A retrospective study of 525 patients[J]. The Journal of Biomedical Research, 2018, 32(3): 191-197. DOI: 10.7555/JBR.32.20170059
Effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese breast cancer patients: A retrospective study of 525 patients
This study was designed to investigate the effect of neoadjuvant chemotherapy on the expression of hormone receptors and Ki67 in Chinese female breast cancer patients. The expression of estrogen receptor (ER), progesterone receptor (PR) and Ki67 among 525 neoadjuvant chemotherapy cases was studied by immunohistochemistry. Differences between specimens made through preoperative core needle biopsy and excised tissue biopsy were observed. The positive rates of ER, PR and Ki67 in core needle biopsy and excised tissue biopsy were 65.3% and
63.2%, 51.0% and 42.6%, 65.6% and 43.4%, respectively. The expression of ER, PR and Ki67 in core needle biopsy and excised tissue biopsy had no statistically significant difference. However, after neoadjuvant chemotherapy, the discordance rates of ER, PR and Ki67 were 15.2% (79/521), 26.9% (140/520) and 44.8% (225/502), respectively. The ER, PR and Ki67 status changed from positive to negative in 7.5% (39/521), 13.3% (69/520) and 21.1% (106/502) of the patients, whereas ER, PR and Ki67 status changed from negative to positive in 7.7% (40/521), 13.6% (71/520) and 23.7% (119/502) of the patients, respectively. These results showed that the status of some biomarkers changes after neoadjuvant chemotherapy and biomarker status needs to be reexamined to optimize adjuvant systemic therapy and better prognosis assessment.
Yu F, Zhao LX, Chu S. TCHH as a Novel Prognostic Biomarker for Patients with Gastric Cancer by Bioinformatics Analysis. Clin Exp Gastroenterol, 2024, 17: 61-74.
DOI:10.2147/CEG.S451676
2.
Li K, Qiu Y, Liu X, et al. Biomimetic Nanosystems for the Synergistic Delivery of miR-144/451a for Oral Squamous Cell Carcinoma. Balkan Med J, 2022, 39(3): 178-186.
DOI:10.4274/balkanmedj.galenos.2022.2021-11-1
3.
Yu CC, Chan MWY, Lin HY, et al. IRAK2, an IL1R/TLR Immune Mediator, Enhances Radiosensitivity via Modulating Caspase 8/3-Mediated Apoptosis in Oral Squamous Cell Carcinoma. Front Oncol, 2021, 11: 647175.
DOI:10.3389/fonc.2021.647175
4.
Amiri-Dashatan N, Koushki M, Jalilian A, et al. Integrated Bioinformatics Analysis of mRNAs and miRNAs Identified Potential Biomarkers of Oral Squamous Cell Carcinoma. Asian Pac J Cancer Prev, 2020, 21(6): 1841-1848.
DOI:10.31557/APJCP.2020.21.6.1841
5.
Xu GQ, Li LH, Wei JN, et al. Identification and profiling of microRNAs expressed in oral buccal mucosa squamous cell carcinoma of Chinese hamster. Sci Rep, 2019, 9(1): 15616.
DOI:10.1038/s41598-019-52197-3
6.
Li CY, Zhang WW, Xiang JL, et al. Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma. Oncol Rep, 2019, 42(6): 2583-2599.
DOI:10.3892/or.2019.7377
7.
Zhong L, Liu Y, Wang K, et al. Biomarkers: paving stones on the road towards the personalized precision medicine for oral squamous cell carcinoma. BMC Cancer, 2018, 18(1): 911.
DOI:10.1186/s12885-018-4806-7
8.
Willett CS, Wilson EM. Evolution of Melanoma Antigen-A11 (MAGEA11) During Primate Phylogeny. J Mol Evol, 2018, 86(3-4): 240-253.
DOI:10.1007/s00239-018-9838-8
9.
Li J, Zhou D, Qiu W, et al. Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design. Sci Rep, 2018, 8(1): 622.
DOI:10.1038/s41598-017-18705-z
10.
Mallik S, Zhao Z. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis. Genes (Basel), 2017, 9(1): 7.
DOI:10.3390/genes9010007
11.
Irimie AI, Braicu C, Pileczki V, et al. Knocking down of p53 triggers apoptosis and autophagy, concomitantly with inhibition of migration on SSC-4 oral squamous carcinoma cells. Mol Cell Biochem, 2016, 419(1-2): 75-82.
DOI:10.1007/s11010-016-2751-9