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Han J, Hua H, Fei J, Liu J, Guo Y, Ma W, Chen J. Prediction of Disease-Free Survival in Breast Cancer using Deep Learning with Ultrasound and Mammography: A Multicenter Study. Clin Breast Cancer 2024; 24:215-226. [PMID: 38281863 DOI: 10.1016/j.clbc.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 01/04/2024] [Accepted: 01/10/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved. MATERIALS AND METHODS Patients (from January 2013 to December 2018) were recruited and divided into a training group and a testing group. All patients were followed for more than 3 years. Patients were divided into a disease-free group and a recurrence group based on follow up results at 3 years. Ultrasound (US) and mammography (MG) images were collected to establish deep learning models (DLMs) using ResNet50. Clinical data, MG, and US characteristics were collected to select independent prognostic factors using a cox proportional hazards model to establish a clinical model. DLM and independent prognostic factors were combined to establish a combined model. RESULTS In total, 1242 patients were included. Independent prognostic factors included age, neoadjuvant chemotherapy, HER2, orientation, blood flow, dubious calcification, and size. We established 5 models: the US DLM, MG DLM, US + MG DLM, clinical and combined model. The combined model using US images, MG images, and pathological, clinical, and radiographic characteristics had the highest predictive performance (AUC = 0.882 in the training group, AUC = 0.739 in the testing group). CONCLUSION DLMs based on the combination of US, MG, and clinical data have potential as predictive tools for breast cancer prognosis.
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Affiliation(s)
- Junqi Han
- Department of Breast Imaging, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China
| | - Hui Hua
- Department of Thyroid Surgery, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China
| | - Jie Fei
- Department of Breast Imaging, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China
| | - Jingjing Liu
- Department of Breast Imaging, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China
| | - Yijun Guo
- Department of Breast Imaging Diagnosis, National Clinical Research Center for Cancer, Tianjin Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, People's Republic of China
| | - Wenjuan Ma
- Department of Breast Imaging Diagnosis, National Clinical Research Center for Cancer, Tianjin Clinical Research Center for Cancer, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, People's Republic of China
| | - Jingjing Chen
- Department of Breast Imaging, The Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
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Abdul Wahab MR, Palaniyandi T, Viswanathan S, Baskar G, Surendran H, Gangadharan SGD, Sugumaran A, Sivaji A, Kaliamoorthy S, Kumarasamy S. Biomarker-specific biosensors revolutionise breast cancer diagnosis. Clin Chim Acta 2024; 555:117792. [PMID: 38266968 DOI: 10.1016/j.cca.2024.117792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/19/2024] [Accepted: 01/19/2024] [Indexed: 01/26/2024]
Abstract
Breast cancer is the most common cancer among women across the globe. In order to treat breast cancer successfully, it is crucial to conduct a comprehensive assessment of the condition during its initial stages. Although mammogram screening has long been a common method of breast cancer screening, high rates of type I error and type II error results as well as radiation exposure have always been of concern. The outgrowth cancer mortality rate is primarily due to delayed diagnosis, which occurs most frequently in a metastatic III or IV stage, resulting in a poor prognosis after therapy. Traditional detection techniques require identifying carcinogenic properties of cells, such as DNA or RNA alterations, conformational changes and overexpression of certain proteins, and cell shape, which are referred to as biomarkers or analytes. These procedures are complex, long-drawn-out, and expensive. Biosensors have recently acquired appeal as low-cost, simple, and super sensitive detection methods for analysis. The biosensor approach requires the existence of biomarkers in the sample. Thus, the development of novel molecular markers for diverse forms of cancer is a rising complementary affair. These biosensor devices offer two major advantages: (1) a tiny amount of blood collected from the patient is sufficient for analysis, and (2) it could help clinicians swiftly select and decide on the best therapy routine for the individual. This review will include updates on prospective cancer markers and biosensors in cancer diagnosis, as well as the associated detection limitations, with a focus on biosensor development for marker detection.
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Affiliation(s)
| | - Thirunavukkarasu Palaniyandi
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India; Department of Anatomy, Biomedical Research Unit and Laboratory Animal Centre, Saveetha Dental College and Hospital, SIMATS, Saveetha University, Chennai, India.
| | - Sandhiya Viswanathan
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - Gomathy Baskar
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - Hemapreethi Surendran
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - S G D Gangadharan
- Department of Medical Oncology, Madras Medical College, R. G. G. G. H., Chennai, Tamil Nadu, India
| | - Abimanyu Sugumaran
- Department of Pharmaceutical Sciences, Assam University, (A Central University), Silchar, Assam, India
| | - Asha Sivaji
- Department of Biochemistry, DKM College for Women, Vellore, India
| | - Senthilkumar Kaliamoorthy
- Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, Tamil Nadu, India
| | - Saravanan Kumarasamy
- Department of Electrical and Electronics Engineering, Dr. M.G.R Educational and Research Institute, Chennai, Tamil Nadu, India
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Xiu Y, Jiang C, Huang Q, Yu X, Qiao K, Wu D, Yang X, Zhang S, Lu X, Huang Y. Naples score: a novel prognostic biomarker for breast cancer patients undergoing neoadjuvant chemotherapy. J Cancer Res Clin Oncol 2023; 149:16097-16110. [PMID: 37698677 DOI: 10.1007/s00432-023-05366-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/28/2023] [Indexed: 09/13/2023]
Abstract
BACKGROUND AND PURPOSE The Naples Score (NPS) is a novel prognostic indicator that has been used in various cancers, but its potential in breast malignant tumor patients receiving neoadjuvant chemotherapy (NAC) has not been discovered. This study aimed to investigate the relationship between NPS and overall survival (OS) and disease-free survival (DFS) in breast cancer patients. METHODS A total of 217 breast cancer patients undergoing NAC were incorporated into this retrospectively research. K-M survival curves and log-rank tests are used to determine OS and DFS. Cox regression model was used to evaluate the relationship between NPS and OS and DFS. Nomogram was developed based on the results of multivariate Cox regression analysis. Prognostic models were internally validated using bootstrapping and the consistency index (C-index). RESULTS Age group was correlated with NPS (p < 0.05). Low and moderate Naples risk patients had higher 5-year OS and DFS rates than high risk Naples patients (93.8% vs. 75.4% vs. 60.0%; X2 = 9.2, P = 0.01; 82.4% vs 64.5% vs 43.7%; X2 = 7.4, P = 0.024; respectively). The nomogram based on demonstrated good performance in predicting OS and DFS (AUC = 0.728, 0.630; respectively). CONCLUSIONS In breast cancer patients who have undergone NAC, NPS is a novel prognostic indicator. NPS combined with clinicopathological features showed good predictive ability, and its performance was better than that of traditional pathological TNM staging.
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Affiliation(s)
- Yuting Xiu
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Cong Jiang
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Qinghua Huang
- Department of Breast Surgery, Wuzhou Red Cross Hospital, Wuzhou, 543000, China
| | - Xiao Yu
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Kun Qiao
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Danping Wu
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Xiaotian Yang
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Shiyuan Zhang
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China
| | - Xiangshi Lu
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China.
| | - Yuanxi Huang
- Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin, 150086, China.
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Liu G, Xing Z, Guo C, Dai Q, Cheng H, Wang X, Tang Y, Wang Y. Identifying clinicopathological risk factors for regional lymph node metastasis in Chinese patients with T1 breast cancer: a population-based study. Front Oncol 2023; 13:1217869. [PMID: 37601676 PMCID: PMC10436470 DOI: 10.3389/fonc.2023.1217869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 07/21/2023] [Indexed: 08/22/2023] Open
Abstract
Objectives To analyze clinicopathological risk factors and regular pattern of regional lymph node metastasis (LNM) in Chinese patients with T1 breast cancer and the effect on overall survival (OS) and disease-free survival (DFS). Materials and methods Between 1999 and 2020, breast cancer patients meeting inclusion criteria of unilateral, no distant metastatic site, and T1 invasive ductal carcinoma were reviewed. Clinical pathology characteristics were retrieved from medical records. Survival analysis was performed using Kaplan-Meier methods and an adjusted Cox proportional hazards model. Results We enrolled 11,407 eligible patients as a discovery cohort to explore risk factors for LNM and 3484 patients with stage T1N0 as a survival analysis cohort to identify the effect of those risk factors on OS and DFS. Compared with patients with N- status, patients with N+ status had a younger age, larger tumor size, higher Ki67 level, higher grade, higher HR+ and HER2+ percentages, and higher luminal B and HER2-positive subtype percentages. Logistic regression indicated that age was a protective factor and tumor size/higher grade/HR+ and HER2+ risk factors for LNM. Compared with limited LNM (N1) patients, extensive LNM (N2/3) patients had larger tumor sizes, higher Ki67 levels, higher grades, higher HR- and HER2+ percentages, and lower luminal A subtype percentages. Logistic regression indicated that HR+ was a protective factor and tumor size/higher grade/HER2+ risk factors for extensive LNM. Kaplan-Meier analysis indicated that grade was a predictor of both OS and DFS; HR was a predictor of OS but not DFS. Multivariate survival analysis using the Cox regression model demonstrated age and Ki67 level to be predictors of OS and grade and HER2 status of DFS in stage T1N0 patients. Conclusion In T1 breast cancer patients, there were several differences between N- and N+ patients, limited LNM and extensive LNM patients. Besides, HR+ plays a dual role in regional LNM. In patients without LNM, age and Ki67 level are predictors of OS, and grade and HER2 are predictors of DFS.
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Affiliation(s)
- Gang Liu
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zeyu Xing
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Changyuan Guo
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qichen Dai
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Han Cheng
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiang Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Tang
- GCP center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yipeng Wang
- Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Rezaei A, Shayan N, Shirazinia S, Mollazadeh S, Ghiyasi-Moghaddam N. The Prognostic Significance of P16 Immunohistochemical Expression Pattern in Women with Invasive Ductal Breast Carcinoma. Rep Biochem Mol Biol 2023; 12:83-91. [PMID: 37724141 PMCID: PMC10505467 DOI: 10.52547/rbmb.12.1.83] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 05/08/2023] [Indexed: 09/20/2023]
Abstract
Background Breast cancer is the most common malignancy in women worldwide. The p16 protein is a cell cycle regulator and tumor suppressor implicated in several types of cancers. However, its relationship to breast cancer is still unknown. The present study aimed to assess the association of p16 protein expression with clinicopathological features in breast cancer.This study aimed to investigate the anti-cancer effects of different gum extracts on metabolic changes and their impact on gene expression in HT-29 cell. Methods The study enrolled 100 patients with invasive ductal carcinoma. The samples were collected before any adjuvant chemotherapy, and p16 protein expression was determined using immunohistochemistry. Clinicopathological features were obtained from the patient's medical records. Results Our findings demonstrated that p16 protein expression increased in estrogen receptor-positive tumor tissues (P< 0.01). However, no significant correlation was found between the p16 protein expression and the other clinicopathological features. Conclusions Our study demonstrated that p16 protein expression increased in ER-positive tumor tissue from patients with invasive ductal breast carcinoma. However, no correlation was found between the p16 protein expression and the other clinicopathological features.
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Affiliation(s)
- Alireza Rezaei
- Department of Pathology, Faculty of Medicine, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
| | - Navidreza Shayan
- Department of Pathology, Faculty of Medicine, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
| | - Saman Shirazinia
- Department of Pathology, Faculty of Medicine, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
| | - Sara Mollazadeh
- Department of Pathology, Faculty of Medicine, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
| | - Negin Ghiyasi-Moghaddam
- Department of Pathology, Faculty of Medicine, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
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Zhang X, Cui H, Hu N, Han P, Fan W, Wang P, Zuo X, Zhao D, Huang H, Li S, Kong H, Peng F, Tian J, Zhang L. Correlation of androgen receptor with ultrasound, clinicopathological features and clinical outcomes in breast cancer. Insights Imaging 2023; 14:46. [PMID: 36929229 PMCID: PMC10020396 DOI: 10.1186/s13244-023-01387-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 02/04/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND This study aimed to explore whether there is an association between androgen receptor (AR) expression and ultrasound, clinicopathological features and prognosis of breast cancer. METHODS A total of 141 breast cancer patients were included in this retrospective study. AR expression was analyzed by immunohistochemistry. The images of B-mode, color Doppler and strain elastography from 104 patients were collected continuously, and the corresponding ultrasound characteristics were obtained. The differences in ultrasound and clinicopathological features in different AR status were analyzed. Progression-free survival (PFS) of patients was obtained through up to 90 months of follow-up; then, the effect of AR on PFS was analyzed. Subsequently, a nomogram was constructed to predict the AR status. The predictive accuracy was calculated using C-index. RESULTS The positive expression of AR (AR +) was associated with lower histological grade (p = 0.034) and lower Ki-67 level (p = 0.029). Triple-negative breast cancer (TNBC) had the lowest probability of AR + (p < 0.001). The AR + group mostly showed unsmooth margin (p < 0.001), posterior acoustic shadowing (p = 0.002) and higher elasticity score (p = 0.022) on ultrasound. The echo pattern of most tumors with AR + was heterogeneous (p = 0.024) in Luminal A subtype. AR + could be a sign of a better prognosis in overall breast cancer (p < 0.001), as well as in human epidermal growth factor receptor 2 (HER2) overexpression and Luminal B subtypes (p = 0.001 and 0.025). The nomogram showed relatively reliable performance with a C-index of 0.799. CONCLUSION Our research demonstrated that AR expression was closely related to ultrasound, clinicopathological features and prognosis of breast cancer.
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Affiliation(s)
- Xudong Zhang
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Hao Cui
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Nana Hu
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Peng Han
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Wei Fan
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Panting Wang
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Xiaoxuan Zuo
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Dantong Zhao
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - He Huang
- Department of Clinical Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Shuo Li
- Department of Clinical Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Hanqing Kong
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Fuhui Peng
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Jiawei Tian
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086
| | - Lei Zhang
- Department of Ultrasound Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China, 150086.
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Mohammadi K, Salimi M, Angaji SA, Saniotis A, Mahjoobi F. Association study of Bif-1 gene expression with histopathological characteristics and hormone receptors in breast cancer. BMC Womens Health 2022; 22:471. [PMID: 36434659 PMCID: PMC9701003 DOI: 10.1186/s12905-022-02075-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 11/15/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Breast cancer is a heterogeneous disease that has various clinical outcomes. Bax-interacting factor-1 (Bif-1) is a member of the endophilin B family that generates the pro-apoptotic BCL2-Associated X (BAX) protein in response to apoptotic signals. Lack of Bif-1 inhibits the intrinsic pathway of apoptosis and enhancements the risk of tumor genesis. The present study aimed to investigate the relationship between hormone receptors (ER, PR, and HER2) status and different levels of Bif-1 gene expression in breast cancer patients. METHODS Bif-1 gene expression was evaluated in 50 breast cancer tumors and 50 normal breast mammary tissues using the SYBR Green real-time RT-PCR technique. Multivariate and univariate analyses were used to appraise the relationship between the prognostic significance of the Bif-1 gene using SPSS software. In this study, the Bif-1 was selected as a candidate for a molecular biomarker and its expression status in breast cancer patients with hormone receptors (ER, RR, and HER2) compared to patients without these hormone receptors. RESULTS The study showed that the relative expression of the Bif-1 gene in tissues of patients with hormone receptors in breast cancer compared to those without hormone receptors was not statistically significant. The expression levels of the Bif-1 gene in different groups were evaluated for hormone receptor status. No significant relationship was found between the Bif-1 gene expression and hormone receptors (ER, PR, and HER2) (p > 0.05). CONCLUSION Bif-1 gene expression may be a useful prognostic marker in breast cancer.
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Affiliation(s)
- Kazhaleh Mohammadi
- grid.513517.40000 0005 0233 0078Department of Pharmacy, College of Pharmacy, Knowledge University, Erbil, 44001 Iraq
| | - Mahdieh Salimi
- grid.419420.a0000 0000 8676 7464Department of Medical Genetic, Institute of Medical Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
| | - S. Abdolhamid Angaji
- grid.412265.60000 0004 0406 5813Department of Cell and Molecular Biology Sciences, Kharazmi University, Tehran, Iran
| | - Arthur Saniotis
- Bachelors of Doctor Assistant Department, DDT College of Medicine, Gaborone, Botswana ,grid.1010.00000 0004 1936 7304Biological and Comparative Anatomy Research Unit, School of Biomedicine, The University of Adelaide, Adelaide, Australia
| | - Foroozandeh Mahjoobi
- grid.419420.a0000 0000 8676 7464Department of Medical Genetic, Institute of Medical Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
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Xuan Z, Ma T, Qin Y, Guo Y. Role of Ultrasound Imaging in the Prediction of TRIM67 in Brain Metastases From Breast Cancer. Front Neurol 2022; 13:889106. [PMID: 35795796 PMCID: PMC9251422 DOI: 10.3389/fneur.2022.889106] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 05/16/2022] [Indexed: 12/13/2022] Open
Abstract
Objectives Ultrasound (US) imaging is a relatively novel strategy to monitor the activity of the blood–brain barrier, which can facilitate the diagnosis and treatment of neurovascular-related metastatic tumors. The purpose of this study was to investigate the clinical significance of applying a combination of US imaging outcomes and the associated genes. This was performed to construct line drawings to facilitate the prediction of brain metastases arising from breast cancer. Methods The RNA transcript data from The Cancer Genome Atlas (TCGA) database was obtained for breast cancer, and the differentially expressed genes (DEGs) associated with tumor and brain tumor metastases were identified. Subsequently, key genes associated with survival prognosis were subsequently identified from the DEGs. Results Tripartite motif-containing protein 67 (TRIM67) was identified and the differential; in addition, the survival analyses of the TCGA database revealed that it was associated with brain tumor metastases and overall survival prognosis. Applying independent clinical cohort data, US-related features (microcalcification and lymph node metastasis) were associated with breast cancer tumor metastasis. Furthermore, ultrasonographic findings of microcalcifications showed correlations with TRIM67 expression. The study results revealed that six variables [stage, TRIM67, tumor size, regional lymph node staging (N), age, and HER2 status] were suitable predictors of tumor metastasis by applying support vector machine–recursive feature elimination. Among these, US-predicted tumor size correlated with tumor size classification, whereas US-predicted lymph node metastasis correlated with tumor N classification. The TRIM67 upregulation was accompanied by upregulation of the integrated breast cancer pathway; however, it leads to the downregulation of the miRNA targets in ECM and membrane receptors and the miRNAs involved in DNA damage response pathways. Conclusions The TRIM67 is a risk factor associated with brain metastases from breast cancer and it is considered a prognostic survival factor. The nomogram constructed from six variables—stage, TRIM67, tumor size, N, age, HER2 status—is an appropriate predictor to estimate the occurrence of breast cancer metastasis.
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