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Martino F, Ilardi G, Varricchio S, Russo D, Di Crescenzo RM, Staibano S, Merolla F. A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma. J Pathol Inform 2024; 15:100354. [PMID: 38148967 PMCID: PMC10750186 DOI: 10.1016/j.jpi.2023.100354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/14/2023] [Accepted: 11/16/2023] [Indexed: 12/28/2023] Open
Abstract
Anatomical pathology is undergoing its third revolution, transitioning from analogical to digital pathology and incorporating new artificial intelligence technologies into clinical practice. Aside from classification, detection, and segmentation models, predictive models are gaining traction since they can impact diagnostic processes and laboratory activity, lowering consumable usage and turnaround time. Our research aimed to create a deep-learning model to generate synthetic Ki-67 immunohistochemistry from Haematoxylin and Eosin (H&E) stained images. We used 175 oral squamous cell carcinoma (OSCC) from the University Federico II's Pathology Unit's archives to train our model to generate 4 Tissue Micro Arrays (TMAs). We sectioned one slide from each TMA, first stained with H&E and then re-stained with anti-Ki-67 immunohistochemistry (IHC). In digitised slides, cores were disarrayed, and the matching cores of the 2 stained were aligned to construct a dataset to train a Pix2Pix algorithm to convert H&E images to IHC. Pathologists could recognise the synthetic images in only half of the cases in a specially designed likelihood test. Hence, our model produced realistic synthetic images. We next used QuPath to quantify IHC positivity, achieving remarkable levels of agreement between genuine and synthetic IHC. Furthermore, a categorical analysis employing 3 Ki-67 positivity cut-offs (5%, 10%, and 15%) revealed high positive-predictive values. Our model is a promising tool for collecting Ki-67 positivity information directly on H&E slides, reducing laboratory demand and improving patient management. It is also a valuable option for smaller laboratories to easily and quickly screen bioptic samples and prioritise them in a digital pathology workflow.
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Affiliation(s)
- Francesco Martino
- Dedalus HealthCare, Division of Diagnostic Imaging IT, Gertrude-Frohlich-Sandner-Straße 1, Wien 1100, Austria
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Gennaro Ilardi
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Silvia Varricchio
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Daniela Russo
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Rosa Maria Di Crescenzo
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Stefania Staibano
- Department of Advanced Biomedical Sciences, University of Naples, Via Pansini, 5, Naples 80131, Italy
| | - Francesco Merolla
- Department of Medicine and Health Sciences “V. Tiberio”, University of Molise, Via De Sanctis, Campobasso 86100, Italy
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Stojkova M, Behme D, Barajas Ordonez F, Christ SM, March C, Surov A, Thormann M. Evaluation of brain metastasis edema in breast cancer patients as a marker for Ki-67 and cell count-A single center analysis. Neuroradiol J 2024; 37:178-183. [PMID: 38131219 DOI: 10.1177/19714009231224443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Peritumoral edema is an important cause of morbidity and mortality in patients with breast cancer brain metastases (BCBM). The relationship between vasogenic edema and proliferation indices or cell density in BCBM remains poorly understood. PURPOSE To assess the association between tumor volume and peritumoral edema volume and histopathological and immunohistochemical parameters in BCBM. MATERIALS AND METHODS Patients with confirmed BCBM were retrospectively identified. The tumor volume and peritumoral edema volume of each brain metastasis (BM) were semi-automatically calculated in axial T2w and axial T2-fluid attenuated inversion recovery (FLAIR) sequences using the software MIM (Cleveland, Ohio, USA). Edema volume was correlated with histological parameters, including cell count and Ki-67. Sub-analyses were conducted for luminal B, Her2-positive, and tripe negative subgroups. RESULTS Thirty-eight patients were included in the study. There were 24 patients with a single BM. Mean metastasis volume was 31.40 ± 32.52 mL and mean perifocal edema volume was 72.75 ± 58.85 mL. In the overall cohort, no correlation was found between tumor volume and Ki-67 (r = 0.046, p = .782) or cellularity (r = 0.028, p = .877). Correlation between edema volume and Ki-67 was r = 0.002 (p = .989), correlation with cellularity was r = 0.137 (p = .453). No relevant correlation was identified in any subgroup analysis. There was no relevant correlation between BM volume and edema volume. CONCLUSION In patients with breast cancer brain metastases, we did not find linear associations between edema volumes and immunohistochemical features reflecting proliferation potential. Furthermore, there was no relevant correlation between metastasis volume and edema volume.
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Affiliation(s)
- Marija Stojkova
- Clinic for Radiology and Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany
| | - Daniel Behme
- Clinic for Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany
| | - Felix Barajas Ordonez
- Clinic for Radiology and Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany
| | - Sebastian M Christ
- Department of Radiation Oncology, University Hospital Zurich, Zurich, Switzerland
| | - Christine March
- Clinic for Radiology and Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany
| | - Alexey Surov
- Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Maximilian Thormann
- Clinic for Radiology and Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany
- Clinic for Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany
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Liu X, Han T, Wang Y, Liu H, Sun Q, Xue C, Deng J, Li S, Zhou J. Whole-tumor histogram analysis of postcontrast T1-weighted and apparent diffusion coefficient in predicting the grade and proliferative activity of adult intracranial ependymomas. Neuroradiology 2024; 66:531-541. [PMID: 38400953 DOI: 10.1007/s00234-024-03319-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/20/2024] [Indexed: 02/26/2024]
Abstract
PURPOSE To investigate the value of histogram analysis of postcontrast T1-weighted (T1C) and apparent diffusion coefficient (ADC) images in predicting the grade and proliferative activity of adult intracranial ependymomas. METHODS Forty-seven adult intracranial ependymomas were enrolled and underwent histogram parameters extraction (including minimum, maximum, mean, 1st percentile (Perc.01), Perc.05, Perc.10, Perc.25, Perc.50, Perc.75, Perc.90, Perc.95, Perc.99, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, and entropy of T1C and ADC) using FireVoxel software. Differences in histogram parameters between grade 2 and grade 3 adult intracranial ependymomas were compared. Receiver operating characteristic curves and logistic regression analyses were conducted to evaluate the diagnostic performance. Spearman's correlation analysis was used to evaluate the relationship between histogram parameters and Ki-67 proliferation index. RESULTS Grade 3 intracranial ependymomas group showed significantly higher Perc.95, Perc.99, SD, variance, CV, and entropy of T1C; lower minimum, mean, Perc.01, Perc.05, Perc.10, Perc.25, Perc.50 of ADC; and higher CV and entropy of ADC than grade 2 intracranial ependymomas group (all p < 0.05). Entropy (T1C) and Perc.10 (ADC) had a higher diagnostic performance with AUCs of 0.805 and 0.827 among the histogram parameters of T1C and ADC, respectively. The diagnostic performance was improved by combining entropy (T1C) and Perc.10 (ADC), with an AUC of 0.857. Significant correlations were observed between significant histogram parameters of T1C (r = 0.296-0.417, p = 0.001-0.044) and ADC (r = -0.428-0.395, p = 0.003-0.038). CONCLUSION Whole-tumor histogram analysis of T1C and ADC may be a promising approach for predicting the grade and proliferative activity of adult intracranial ependymomas.
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Affiliation(s)
- Xianwang Liu
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Tao Han
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Yuzhu Wang
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
| | - Hong Liu
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Qiu Sun
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Caiqiang Xue
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Juan Deng
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Shenglin Li
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China
| | - Junlin Zhou
- Department of Radiology, Lanzhou University Second Hospital, Cuiyingmen No.82, Chengguan District, Lanzhou, 730030, People's Republic of China.
- Second Clinical School, Lanzhou University, Lanzhou, People's Republic of China.
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, People's Republic of China.
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, People's Republic of China.
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Liu L, Zhao L, Jing Y, Li D, Linghu H, Wang H, Zhou L, Fang Y, Li Y. Exploring a multiparameter MRI-based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma. Insights Imaging 2024; 15:74. [PMID: 38499907 PMCID: PMC10948697 DOI: 10.1186/s13244-024-01634-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 01/27/2024] [Indexed: 03/20/2024] Open
Abstract
OBJECTIVES To develop a multiparameter magnetic resonance imaging (MRI)-based radiomics approach that can accurately predict the tumor cell proliferation status of serous ovarian carcinoma (SOC). MATERIALS AND METHODS A total of 134 patients with SOC who met the inclusion and exclusion criteria were retrospectively screened from institution A, spanning from January 2016 to March 2022. Additionally, an external validation set comprising 42 SOC patients from institution B was also included. The region of interest was determined by drawing each ovarian mass boundaries manually slice-by-slice on T2-weighted imaging fat-suppressed fast spin-echo (T2FSE) and T1 with contrast enhancement (T1CE) images using ITK-SNAP software. The handcrafted radiomic features were extracted, and then were selected using variance threshold algorithm, SelectKBest algorithm, and least absolute shrinkage and selection operator. The optimal radiomic scores and the clinical/radiological independent predictors were integrated as a combined model. RESULTS Compared with the area under the curve (AUC) values of each radiomic signature of T2FSE and T1CE, respectively, the AUC value of the radiomic signature (T1CE-T2FSE) was the highest in the training set (0.999 vs. 0.965 and 0.860). The homogeneous solid component of the ovarian mass was considered the only independent predictor of tumor cell proliferation status among the clinical/radiological variables. The AUC of the radiomic-radiological model was 0.999. CONCLUSIONS The radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can accurately predict tumor cell proliferation status of SOC which has high repeatability and may enable more targeted and effective treatment strategies. CRITICAL RELEVANCE STATEMENT The proposed radiomic-radiological model combining radiomic scores and the homogeneous solid component of the ovarian mass can predict tumor cell proliferation status of SOC which has high repeatability and may guide individualized treatment programs. KEY POINTS • The radiomic-radiological nomogram may guide individualized treatment programs of SOC. • This radiomic-radiological nomogram showed a favorable prediction ability. • Homogeneous slightly higher signal intensity on T2FSE is vital for Ki-67.
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Affiliation(s)
- Li Liu
- Department of Radiology, The People's Hospital of Yubei District of Chongqing City, No. 23 ZhongyangGongyuanBei Road, Yubei District, Chongqing, 401120, China
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, Yuanjiagang, China
| | - Ling Zhao
- Department of Radiology, The People's Hospital of Yubei District of Chongqing City, No. 23 ZhongyangGongyuanBei Road, Yubei District, Chongqing, 401120, China
| | - Yang Jing
- Huiying Medical Technology Co., Ltd, Dongsheng Science and Technology Park, Room A206, B2Haidian District, Beijing, 100192, China
| | - Dan Li
- Department of Pathology, Chongqing Medical University, No.1 Medical College Road, Yuzhong District, Chongqing, 400016, China
| | - Hua Linghu
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road Yuzhong District, Chongqing, 400016, Yuanjiagang, China
| | - Haiyan Wang
- Department of Radiology, The People's Hospital of Yubei District of Chongqing City, No. 23 ZhongyangGongyuanBei Road, Yubei District, Chongqing, 401120, China
| | - Linyi Zhou
- Department of Radiology, Army Medical Center, Daping Hospital, Army Medical University, 10# Changjiangzhilu, Chongqing, 40024, China
| | - Yuan Fang
- Department of Radiology, The People's Hospital of Yubei District of Chongqing City, No. 23 ZhongyangGongyuanBei Road, Yubei District, Chongqing, 401120, China.
| | - Yongmei Li
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, Yuanjiagang, China.
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Wu S, Wang N, Ao W, Hu J, Xu W, Mao G. Deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram for predicting Ki-67 expression in rectal cancer. Abdom Radiol (NY) 2024:10.1007/s00261-024-04232-9. [PMID: 38489038 DOI: 10.1007/s00261-024-04232-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/01/2024] [Accepted: 02/01/2024] [Indexed: 03/17/2024]
Abstract
PURPOSE To explore the value of deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram in predicting the Ki-67 expression in rectal cancer. METHODS The data of 491 patients with rectal cancer from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. They were categorized into high- and low-expression group based on postoperative pathological Ki-67 expression. Each patient's mp-MRI data were analyzed to extract and select the most relevant features of deep learning, and a deep learning model was constructed. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a nomogram for the prediction of Ki-67 expression. The performance characteristics of the DL-model, clinical model, and nomogram were assessed using ROCs, calibration curve, decision curve, and clinical impact curve analysis. RESULTS The strongest deep learning features were extracted and screened from mp-MRI data. Two independent predictive factors, namely Magnetic Resonance Imaging T (mrT) staging and differentiation degree, were identified through clinical feature selection. Three models were constructed: a deep learning (DL)-model, a clinical model, and a nomogram. The AUCs of clinical model in the training, internal validation, and external validation set were 0.69, 0.78, and 0.67, respectively. The AUCs of the deep model and nomogram ranged from 0.88 to 0.98. The prediction performance of the deep learning model and nomogram was significantly better than the clinical model (P < 0.001). CONCLUSION The nomogram based on deep learning can help clinicians accurately and conveniently predict the expression status of Ki-67 in rectal cancer.
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Affiliation(s)
- Sikai Wu
- Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Neng Wang
- Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Weiqun Ao
- Department of Radiology, Tongde Hospital of Zhejiang Province, No. 234, Gucui Road, Hangzhou, 310012, Zhejiang, China
| | - Jinwen Hu
- Department of Radiology, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wenjie Xu
- Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Guoqun Mao
- Department of Radiology, Tongde Hospital of Zhejiang Province, No. 234, Gucui Road, Hangzhou, 310012, Zhejiang, China.
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Zhang D, Zhang XY, Lu WW, Liao JT, Zhang CX, Tang Q, Cui XW. Predicting Ki-67 expression in hepatocellular carcinoma: nomogram based on clinical factors and contrast-enhanced ultrasound radiomics signatures. Abdom Radiol (NY) 2024:10.1007/s00261-024-04191-1. [PMID: 38461433 DOI: 10.1007/s00261-024-04191-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/06/2024] [Accepted: 01/12/2024] [Indexed: 03/12/2024]
Abstract
PURPOSE To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC). METHODS A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated. RESULTS Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram. CONCLUSION The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.
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Affiliation(s)
- Di Zhang
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, 230022, Anhui, China
| | - Xian-Ya Zhang
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue No. 1095, Wuhan, 430030, Hubei, China
| | - Wen-Wu Lu
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, 230022, Anhui, China
| | - Jin-Tang Liao
- Department of Diagnostic Ultrasound, Xiang Ya Hospital of Central South University, Changsha, 410000, Hunan, China
| | - Chao-Xue Zhang
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, 230022, Anhui, China.
| | - Qi Tang
- Department of Ultrasonography, The First Hospital of Changsha, No. 311 Yingpan Road, Changsha, 410005, Hunan, China.
| | - Xin-Wu Cui
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue No. 1095, Wuhan, 430030, Hubei, China.
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Ma Q, Liu YB, She T, Liu XL. The Role of Ki-67 in HR+/HER2- Breast Cancer: A Real-World Study of 956 Patients. Breast Cancer (Dove Med Press) 2024; 16:117-126. [PMID: 38476641 PMCID: PMC10929654 DOI: 10.2147/bctt.s451617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/22/2024] [Indexed: 03/14/2024]
Abstract
Objective This study determined the cut-off value of Ki-67 expression and discussed the interaction between Ki-67 and histological grade, further explored the prognostic role of Ki-67 in hormone receptor-positive and human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer;. Materials and Methods We assessed the Ki-67 expression of 956 patients with HR+/HER2 breast cancer diagnosed in the General Hospital of Ningxia Medical University from 2015 to 2019 by immunohistochemistry (IHC), The disease-free survival (DFS) was defined as the time from postoperative to the first local recurrence, distant metastasis or death of the disease. The follow-up by means of inpatient or outpatient medical records and telephone. Results 22.5% was used as the cut-off for low/high Ki-67 expression in HR+/HER2- breast cancer. Compared with the value of 14%, which is commonly used in clinic at present, the consistency of the two values is moderate (Kappa = 0.484, P<0.001). The expression of Ki-67 was increased with the grade. (Median: G1:10%; G2:20%; G3:40%. Mean: G1:13%; G2:23%; G3:39%, P <0.001). Survival analysis was based on all patients for a median of 51 months (24-89 months), 63 cases had recurrence or metastasis during the follow-up, which 21 cases had low expression of Ki-67 and 42 cases had high expression. The patients with Ki-67 ≥ 22.5% had a 2.969 higher risk of early recurrence and metastasis than the patients with Ki-67 < 22.5%. There were 4 cases of local recurrence, 7 cases of regional lymph node metastasis, and 52 cases of distant metastasis in all patients, the common distant metastases were bone, liver, and lung, and rare metastases were adrenal gland, bone marrow, and pericardium. Conclusion In HR+/HER2- breast cancer, patients with Ki-67 > 22.5% have a worse prognosis and are more likely to have early recurrence and metastasis.
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Affiliation(s)
- Qin Ma
- Department of Radiation Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China
| | - Yao-Bang Liu
- Department of Surgical Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China
| | - Tong She
- Hospital of Zhongwei, Zhongwei, People’s Republic of China
| | - Xin-Lan Liu
- Department of Medical Oncology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, People’s Republic of China
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Oba K, Adachi M, Kobayashi T, Takaya E, Shimokawa D, Fukuda T, Takahashi K, Yagishita K, Ueda T, Tsunoda H. Deep learning model to predict Ki-67 expression of breast cancer using digital breast tomosynthesis. Breast Cancer 2024:10.1007/s12282-024-01549-7. [PMID: 38448777 DOI: 10.1007/s12282-024-01549-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/24/2024] [Indexed: 03/08/2024]
Abstract
BACKGROUND Developing a deep learning (DL) model for digital breast tomosynthesis (DBT) images to predict Ki-67 expression. METHODS The institutional review board approved this retrospective study and waived the requirement for informed consent from the patients. Initially, 499 patients (mean age: 50.5 years, range: 29-90 years) referred to our hospital for breast cancer were participated, 126 patients with pathologically confirmed breast cancer were selected and their Ki-67 expression measured. The Xception architecture was used in the DL model to predict Ki-67 expression levels. The high Ki-67 vs low Ki-67 expression diagnostic performance of our DL model was assessed by accuracy, sensitivity, specificity, areas under the receiver operating characteristic curve (AUC), and by using sub-datasets divided by the radiological characteristics of breast cancer. RESULTS The average accuracy, sensitivity, specificity, and AUC were 0.912, 0.629, 0.985, and 0.883, respectively. The AUC of the four subgroups separated by radiological findings for the mass, calcification, distortion, and focal asymmetric density sub-datasets were 0.890, 0.750, 0.870, and 0.660, respectively. CONCLUSIONS Our results suggest the potential application of our DL model to predict the expression of Ki-67 using DBT, which may be useful for preoperatively determining the treatment strategy for breast cancer.
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Affiliation(s)
- Ken Oba
- Department of Radiology, St. Luke's International Hospital, 9-1 Akashi-Cho, Chuo-Ku, Tokyo, 104-8560, Japan
| | - Maki Adachi
- Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Tomoya Kobayashi
- Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Eichi Takaya
- AI Lab, Tohoku University Hospital, 1-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8574, Japan
| | - Daiki Shimokawa
- Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Toshinori Fukuda
- Department of Radiology, Oregon Health of Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239-2098, USA
| | - Kengo Takahashi
- Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan
| | - Kazuyo Yagishita
- Department of Radiology, St. Luke's International Hospital, 9-1 Akashi-Cho, Chuo-Ku, Tokyo, 104-8560, Japan
| | - Takuya Ueda
- Department of Clinical Imaging, Tohoku University Graduate School of Medicine, 2-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8575, Japan.
- AI Lab, Tohoku University Hospital, 1-1 Seiryo-Machi, Aoba-Ku, Sendai, Miyagi, 980-8574, Japan.
| | - Hiroko Tsunoda
- Department of Radiology, St. Luke's International Hospital, 9-1 Akashi-Cho, Chuo-Ku, Tokyo, 104-8560, Japan
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Ni J, Zhang H, Yang Q, Fan X, Xu J, Sun J, Zhang J, Hu Y, Xiao Z, Zhao Y, Zhu H, Shi X, Feng W, Wang J, Wan C, Zhang X, Liu Y, You Y, Yu Y. Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data. Acad Radiol 2024:S1076-6332(24)00079-5. [PMID: 38458887 DOI: 10.1016/j.acra.2024.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 01/25/2024] [Accepted: 02/06/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Gliomas are the most common primary brain tumours and constitute approximately half of all malignant glioblastomas. Unfortunately, patients diagnosed with malignant glioblastomas typically survive for less than a year. In light of this circumstance, genotyping is an effective means of categorising gliomas. The Ki67 proliferation index, a widely used marker of cellular proliferation in clinical contexts, has demonstrated potential for predicting tumour classification and prognosis. In particular, magnetic resonance imaging (MRI) plays a vital role in the diagnosis of brain tumours. Using MRI to extract glioma-related features and construct a machine learning model offers a viable avenue to classify and predict the level of Ki67 expression. METHODS This study retrospectively collected MRI data and postoperative immunohistochemical results from 613 glioma patients from the First Affliated Hospital of Nanjing Medical University. Subsequently, we performed registration and skull stripping on the four MRI modalities: T1-weighted (T1), T2-weighted (T2), T1-weighted with contrast enhancement (T1CE), and Fluid Attenuated Inversion Recovery (FLAIR). Each modality's segmentation yielded three distinct tumour regions. Following segmentation, a comprehensive set of features encompassing texture, first-order, and shape attributes were extracted from these delineated regions. Feature selection was conducted using the least absolute shrinkage and selection operator (LASSO) algorithm with subsequent sorting to identify the most important features. These selected features were further analysed using correlation analysis to finalise the selection for machine learning model development. Eight models: logistic regression (LR), naive bayes, decision tree, gradient boosting tree, and support vector classification (SVM), random forest (RF), XGBoost, and LightGBM were used to objectively classify Ki67 expression. RESULTS In total, 613 patients were enroled in the study, and 24,455 radiomic features were extracted from each patient's MRI. These features were eventually reduced to 36 after LASSO screening, RF importance ranking, and correlation analysis. Among all the tested machine learning models, LR and linear SVM exhibited superior performance. LR achieved the highest area under the curve score of 0.912 ± 0.036, while linear SVM obtained the top accuracy with a score of 0.884 ± 0.031. CONCLUSION This study introduced a novel approach for classifying Ki67 expression levels using MRI, which has been proven to be highly effective. With the LR model at its core, our method demonstrated its potential in signalling a promising avenue for future research. This innovative approach of predicting Ki67 expression based on MRI features not only enhances our understanding of cell activity but also represents a significant leap forward in brain glioma research. This underscores the potential of integrating machine learning with medical imaging to aid in the diagnosis and prognosis of complex diseases.
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Affiliation(s)
- Jiaying Ni
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Hongjian Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Qing Yang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Xiao Fan
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Junqing Xu
- The second Clinical Medical School, Nanjing Medical University, Nanjing 211166, China
| | - Jianing Sun
- School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Junxia Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yifang Hu
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Zheming Xiao
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yuhong Zhao
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Hongli Zhu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Xian Shi
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Wei Feng
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Junjie Wang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Medical Informatics and Management, Nanjing Medical University, Jiangsu 210029, China
| | - Cheng Wan
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Medical Informatics and Management, Nanjing Medical University, Jiangsu 210029, China
| | - Xin Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Medical Informatics and Management, Nanjing Medical University, Jiangsu 210029, China
| | - Yun Liu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Medical Informatics and Management, Nanjing Medical University, Jiangsu 210029, China
| | - Yongping You
- Department of Neurosurgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Yun Yu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China; Institute of Medical Informatics and Management, Nanjing Medical University, Jiangsu 210029, China.
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Li X, Koyama Y, Taura K, Nishio T, Yoh T, Nishino H, Uemoto Y, Kimura Y, Nakamura D, Nam NH, Sato M, Seo S, Iwaisako K, Hatano E. High expression of autotaxin is associated with poor recurrence-free survival in cholangiocarcinoma. Hepatol Res 2024. [PMID: 38430513 DOI: 10.1111/hepr.14031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/08/2024] [Accepted: 02/12/2024] [Indexed: 03/04/2024]
Abstract
BACKGROUND AND AIM Autotaxin (ATX) is an extracellular lysophospholipase D that catalyzes the hydrolysis of lysophosphatidylcholine into lysophosphatidic acid (LPA). Recent accumulating evidence indicates the biological roles of ATX in malignant tumors. However, the expression and clinical implications of ATX in human cholangiocarcinoma (CCA) remain elusive. METHODS In this study, the expression of ATX in 97 human CCA tissues was evaluated by immunohistochemistry. Serum ATX levels were determined in CCA patients (n = 26) and healthy subjects (n = 8). Autotaxin expression in cell types within the tumor microenvironment was characterized by immunofluorescence staining. RESULTS High ATX expression in CCA tissue was significantly associated with a higher frequency of lymph node metastasis (p = 0.050). High ATX expression was correlated with shorter overall survival (p = 0.032) and recurrence-free survival (RFS) (p = 0.001) than low ATX expression. In multivariate Cox analysis, high ATX expression (p = 0.019) was an independent factor for shorter RFS. Compared with low ATX expression, high ATX expression was significantly associated with higher Ki-67-positive cell counts (p < 0.001). Serum ATX levels were significantly higher in male CCA patients than in healthy male subjects (p = 0.030). In the tumor microenvironment of CCA, ATX protein was predominantly expressed in tumor cells, cancer-associated fibroblasts, plasma cells, and biliary epithelial cells. CONCLUSIONS Our study highlights the clinical evidence and independent prognostic value of ATX in human CCA.
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Affiliation(s)
- Xuefeng Li
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yukinori Koyama
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kojiro Taura
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Gastroenterological Surgery and Oncology, Tazuke Kofukai Medical Research Institute, Kitano Hospital, Osaka, Japan
| | - Takahiro Nishio
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomoaki Yoh
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hiroto Nishino
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yusuke Uemoto
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yusuke Kimura
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Daichi Nakamura
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nguyen Hai Nam
- Department of Liver Tumor, Cancer Center, Cho Ray Hospital, Ho Chi Minh City, Vietnam
| | - Motohiko Sato
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoru Seo
- Department of Surgery, Kochi Medical School, Kochi, Japan
| | - Keiko Iwaisako
- Department of Medical Life Systems, Faculty of Life and Medical Sciences, Doshisha University, Kyotanabe, Japan
| | - Etsuro Hatano
- Division of Hepatobiliary-Pancreatic Surgery and Transplantation, Department of Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Tabnak P, HajiEsmailPoor Z, Baradaran B, Pashazadeh F, Aghebati Maleki L. MRI-Based Radiomics Methods for Predicting Ki-67 Expression in Breast Cancer: A Systematic Review and Meta-analysis. Acad Radiol 2024; 31:763-787. [PMID: 37925343 DOI: 10.1016/j.acra.2023.10.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/01/2023] [Accepted: 10/04/2023] [Indexed: 11/06/2023]
Abstract
RATIONALE AND OBJECTIVES The purpose of this systematic review and meta-analysis was to assess the quality and diagnostic accuracy of MRI-based radiomics for predicting Ki-67 expression in breast cancer. MATERIALS AND METHODS A systematic literature search was performed to find relevant studies published in different databases, including PubMed, Web of Science, and Embase up until March 10, 2023. All papers were independently evaluated for eligibility by two reviewers. Studies that matched research questions and provided sufficient data for quantitative synthesis were included in the systematic review and meta-analysis, respectively. The quality of the articles was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) and Radiomics Quality Score (RQS) tools. The predictive value of MRI-based radiomics for Ki-67 antigen in patients with breast cancer was assessed using pooled sensitivity (SEN), specificity, and area under the curve (AUC). Meta-regression was performed to explore the cause of heterogeneity. Different covariates were used for subgroup analysis. RESULTS 31 studies were included in the systematic review; among them, 21 reported sufficient data for meta-analysis. 20 training cohorts and five validation cohorts were pooled separately. The pooled sensitivity, specificity, and AUC of MRI-based radiomics for predicting Ki-67 expression in training cohorts were 0.80 [95% CI, 0.73-0.86], 0.82 [95% CI, 0.78-0.86], and 0.88 [95%CI, 0.85-0.91], respectively. The corresponding values for validation cohorts were 0.81 [95% CI, 0.72-0.87], 0.73 [95% CI, 0.62-0.82], and 0.84 [95%CI, 0.80-0.87], respectively. Based on QUADAS-2, some risks of bias were detected for reference standard and flow and timing domains. However, the quality of the included article was acceptable. The mean RQS score of the included articles was close to 6, corresponding to 16.6% of the maximum possible score. Significant heterogeneity was observed in pooled sensitivity and specificity of training cohorts (I2 > 75%). We found that using deep learning radiomic methods, magnetic field strength (3 T vs. 1.5 T), scanner manufacturer, region of interest structure (2D vs. 3D), route of tissue sampling, Ki-67 cut-off, logistic regression for model construction, and LASSO for feature reduction as well as PyRadiomics software for feature extraction had a great impact on heterogeneity according to our joint model analysis. Diagnostic performance in studies that used deep learning-based radiomics and multiple MRI sequences (e.g., DWI+DCE) was slightly higher. In addition, radiomic features derived from DWI sequences performed better than contrast-enhanced sequences in terms of specificity and sensitivity. No publication bias was found based on Deeks' funnel plot. Sensitivity analysis showed that eliminating every study one by one does not impact overall results. CONCLUSION This meta-analysis showed that MRI-based radiomics has a good diagnostic accuracy in differentiating breast cancer patients with high Ki-67 expression from low-expressing groups. However, the sensitivity and specificity of these methods still do not surpass 90%, restricting them from being used as a supplement to current pathological assessments (e.g., biopsy or surgery) to predict Ki-67 expression accurately.
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Affiliation(s)
- Peyman Tabnak
- Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H.); Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.); Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.)
| | - Zanyar HajiEsmailPoor
- Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H.); Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.); Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.)
| | - Behzad Baradaran
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.); Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.)
| | - Fariba Pashazadeh
- Research Center for Evidence-Based Medicine, Iranian Evidence-Based Medicine (EBM) Centre: A Joanna Briggs Institute (JBI) Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (F.P.)
| | - Leili Aghebati Maleki
- Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.); Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran (P.T., Z.H., B.B., L.A.M.).
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12
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Ling G, Guo T, Guo F, Piao H. Effectiveness and Safety of Ultra-low-dose Fluorescein Sodium-Guided Resection of Malignant Glioma. World Neurosurg 2024:S1878-8750(24)00344-9. [PMID: 38432505 DOI: 10.1016/j.wneu.2024.02.131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/23/2024] [Accepted: 02/24/2024] [Indexed: 03/05/2024]
Abstract
BACKGROUND This study analyzed the effectiveness and safety of ultra-low dose fluorescein sodium (FL)-guided malignant glioma resection and its potential to predict the pathological characteristics of glioma. METHODS Sixty patients who underwent FL-guided glioma resection were randomly divided into test (1 mg/kg) and control (5 mg/kg) groups. A retrospective analysis included 30 patients with gliomas who did not undergo FL-guided surgery; these patients were included as a blank control group. Surgical outcomes, Karnofsky performance scores (KPS), and progression-free survival (PFS) at 6 months postoperatively were compared between the 3 groups. The sensitivity and specificity of FL and the relationship between the intensity of FL and Glial fibrillary acidic protein (GFAP) or Ki-67 expression were compared. RESULTS The total tumor resection rates in the test, control, and blank control groups were 90% (27/30), 86.7% (26/30), and 60% (18/30), respectively. There were significant differences (P < 0.05) in the extent of resection, KPS, and PFS at 6 months after surgery between the test and control groups and the blank control group; however, no significant differences (P > 0.05) were observed between the test and control groups. The intensity of FL and the Ki67 positivity rate (P < 0.05) were directly proportional, but this relationship was not observed with GFAP. CONCLUSIONS Ultra-low-dose FL-guided resection of malignant gliomas is safe and effective. The Ki67 positivity rate was directly proportional to the intensity of FL, indicating its potential to predict gliomas during pathological examination.
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Affiliation(s)
- Guoyuan Ling
- Graduate School, Dalian Medical University, Liaoning Province, China; Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Tangjun Guo
- Department of Neurosurgery, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu Province, China
| | - Fangzhou Guo
- Department of Neurosurgery, Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Autonomous Region, China
| | - Haozhe Piao
- Department of Neurosurgery, Liaoning Cancer Hospital & Institute, Shenyang, Liaoning Province, China.
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Xing X, Miao H, Wang H, Sun J, Wu C, Wang Y, Zhou X, Wang H. A Model Combining Conventional Ultrasound Characteristics, Strain Elastography and Clinicopathological Features to Predict Ki-67 Expression in Small Breast Cancer. Ultrason Imaging 2024; 46:121-129. [PMID: 38197383 DOI: 10.1177/01617346231218933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
To establish a predictive model incorporating conventional ultrasound, strain elastography and clinicopathological features for Ki-67 expression in small breast cancer (SBC) which defined as maximum diameter less than2 cm. In this retrospective study, 165 SBC patients from our hospital were allocated to a high Ki-67 group (n = 104) and a low Ki-67 group (n = 61). Multivariate regression analysis was performed to identify independent indicators for developing predictive models. The area under the receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. The corresponding sensitivities and specificities of different models at the cutoff value were compared. Conventional ultrasound parameters (spiculated margin, absence of posterior shadowing and Adler grade 2-3), strain elastic scores and clinicopathological information (HER2 positive) were significantly correlated with high expression of Ki-67 in SBC (all p < .05). Model 2, which incorporated conventional ultrasound features and strain elastic scores, yielded good diagnostic performance (AUC = 0.774) with better sensitivity than model 1, which only incorporated ultrasound characteristics (78.85%vs. 55.77%, p = .000), with specificities of 77.05% and 62.30% (p = .035), respectively. Model 3, which incorporated conventional ultrasound, strain elastography and clinicopathological features, yielded better performance (AUC = 0.853) than model 1 (AUC = 0.694) and model 2 (AUC = 0.774), and the specificity was higher than model 1 (86.89% vs. 77.05%, p = .001). The predictive model combining conventional ultrasound, strain elastic scores and clinicopathological features could improve the predictive performance of Ki-67 expression in SBC.
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Affiliation(s)
- Xuesha Xing
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Huanhuan Miao
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Hong Wang
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiawei Sun
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chengwei Wu
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yichun Wang
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xianli Zhou
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Hongbo Wang
- In-Patient Ultrasound Department, Second Affiliated Hospital of Harbin Medical University, Harbin, China
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Wu J, Wang R, Chen W, Wu Y, Xiao L. Immunohistochemical markers Ki67 and P16 help predict prognosis in locally advanced cervical cancer. Eur J Obstet Gynecol Reprod Biol 2024; 294:210-216. [PMID: 38301499 DOI: 10.1016/j.ejogrb.2024.01.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/05/2023] [Accepted: 01/24/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE To investigate the relationship between Ki-67 and P16 expression levels after neoadjuvant chemotherapy, and the clinicopathological characteristics and prognosis of patients with locally advanced cervical cancer. METHODS Patients with FIGO 2009 stage IB2 or IIA2 cervical cancer, who underwent neoadjuvant chemotherapy combined with radical hysterectomy at the First Affiliated Hospital of Chongqing Medical University between January 2015 and December 2019, were identified retrospectively to correlate postoperative Ki-67 and P16 expression levels with clinicopathological factors. The optimal threshold for predicting recurrence was analysed using receiver operating characteristic (ROC) curves for the Ki-67 index, and univariate and multi-factorial Cox regression analysis were used to investigate the association between clinicpathological features including Ki-67 and P16 and recurrence-free survival. RESULTS In total, 334 patients were included after screening. The cut-off value of Ki-67 for determining recurrence was 67.5 % according to the ROC curve. On multi-factorial Cox analysis, lymphatic vascular space (p = 0.003) and Ki-67 index (p = 0.005) were shown to increase the risk of recurrence, and were independent prognostic factors for recurrence, while the expression of P16 was not significantly associated with the risk of recurrence (p = 0.097, odds ratio = 0.319). Patients with cervical cancer in the high Ki-67 expression group (Ki-67 ≥ 67.5 %) had lower recurrence-free survival and overall survival than patients in the low Ki-67 expression group (Ki-67 < 67.5 %) (p = 0.001 and 0.036, respectively). CONCLUSION The expression levels of Ki-67 and P16 after neoadjuvant chemotherapy for locally advanced cervical cancer correlated with tumour differentiation. High expression of Ki-67 (Ki-67 ≥ 67.5 %) may indicate poorer recurrence-free survival and overall survival.
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Affiliation(s)
- Jialin Wu
- Department of Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Rong Wang
- Department of Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wanli Chen
- Department of Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yingyu Wu
- Department of Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lin Xiao
- Department of Gynaecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
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Razmi M, Tajik F, Hashemi F, Yazdanpanah A, Hashemi-Niasari F, Divsalar A. The Prognostic Importance of Ki-67 in Gastrointestinal Carcinomas: A Meta-analysis and Multi-omics Approach. J Gastrointest Cancer 2024:10.1007/s12029-024-01022-w. [PMID: 38411875 DOI: 10.1007/s12029-024-01022-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/23/2024] [Indexed: 02/28/2024]
Abstract
PURPOSE This study aimed to determine if Ki-67, a commonly used marker to measure tumor proliferation, is a reliable prognostic factor in various types of gastrointestinal (GI) cancers based on current high-quality multivariable evidence. METHODS A comprehensive search was conducted in PubMed, Embase, Scopus, and ISI Web of Science databases to investigate the association between Ki-67 positivity and overall survival (OS) and disease/recurrence-free survival (DFS/RFS) in GI cancers. Heterogeneity was assessed using Chi-square-based Q and I2 analyses and publication bias using funnel plots and Egger's analysis. In addition, Ki-67 levels in different GI cancers were examined by different platforms. The prognostic capability of Ki-67, gene ontology (GO), and pathway enrichment analysis were obtained from GEPIA2 and STRING. RESULTS Totally, 61 studies, involving 13,034 patients, were deemed eligible for our evaluation. The combined hazard ratios (HRs) demonstrated the prediction ability of overexpressed Ki-67 for a worse OS (HR: 1.67, P < 0.001; HR: 1.37, P = 0.021) and DFS/RFS (HR: 2.06, P < 0.001) in hepatocellular and pancreatic malignancies, respectively, as confirmed by multi-omics databases. However, similar correlation was not found in esophageal, gastric, and colorectal cancers. Furthermore, most of the associations were identified to be robust based on different subcategories and publication bias assessment. Finally, enriched Ki-67-related genes were found to be involved in various important signaling pathways, such as cell cycle, P53 signaling network, and DNA damage responses. CONCLUSION This study supports that Ki-67 can serve as an independent prognostic biomarker for pancreatic and hepatocellular malignancies in clinical settings.
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Affiliation(s)
- Mahdieh Razmi
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran, Iran.
| | - Fatemeh Tajik
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran, Iran
- Department of Surgery, University of California, Irvine, CA, USA
| | - Farideh Hashemi
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Ayna Yazdanpanah
- Department of Tissue Engineering and Regenerative Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Hashemi-Niasari
- Department of Biochemistry, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Adeleh Divsalar
- Department of Cell and Molecular Sciences, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran
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Yücel Z, Akal F, Oltulu P. Automated AI-based grading of neuroendocrine tumors using Ki-67 proliferation index: comparative evaluation and performance analysis. Med Biol Eng Comput 2024:10.1007/s11517-024-03045-8. [PMID: 38409645 DOI: 10.1007/s11517-024-03045-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 02/03/2024] [Indexed: 02/28/2024]
Abstract
Early detection is critical for successfully diagnosing cancer, and timely analysis of diagnostic tests is increasingly important. In the context of neuroendocrine tumors, the Ki-67 proliferation index serves as a fundamental biomarker, aiding pathologists in grading and diagnosing these tumors based on histopathological images. The appropriate treatment plan for the patient is determined based on the tumor grade. An artificial intelligence-based method is proposed to aid pathologists in the automated calculation and grading of the Ki-67 proliferation index. The proposed system first performs preprocessing to enhance image quality. Then, segmentation process is performed using the U-Net architecture, which is a deep learning algorithm, to separate the nuclei from the background. The identified nuclei are then evaluated as Ki-67 positive or negative based on basic color space information and other features. The Ki-67 proliferation index is then calculated, and the neuroendocrine tumor is graded accordingly. The proposed system's performance was evaluated on a dataset obtained from the Department of Pathology at Meram Faculty of Medicine Hospital, Necmettin Erbakan University. The results of the pathologist and the proposed system were compared, and the proposed system was found to have an accuracy of 95% in tumor grading when compared to the pathologist's report.
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Affiliation(s)
- Zehra Yücel
- Necmettin Erbakan University, Department of Computer Technologies, Konya, Turkey.
- Hacettepe University, Graduate School of Science and Engineering, Ankara, Turkey.
| | - Fuat Akal
- Hacettepe University, Faculty of Engineering, Department of Computer Engineering, Ankara, Turkey
| | - Pembe Oltulu
- Necmettin Erbakan University, Faculty of Medicine, Department of Pathology, Konya, Turkey
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17
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Chouchane A, Kirchner P, Marinoni I, Sticová E, Jirásek T, Perren A. Pancreatic Neuroendocrine Microtumors (WHO 2022) Are Not Always Low-Grade Neoplasms: A Case with a Highly Increased Proliferation Rate. Endocr Pathol 2024:10.1007/s12022-024-09802-7. [PMID: 38403790 DOI: 10.1007/s12022-024-09802-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/31/2024] [Indexed: 02/27/2024]
Abstract
Traditionally considered non-functional low proliferative benign neuroendocrine proliferations measuring less than 5 mm, pancreatic (neuro)endocrine microadenomas are now classified as pancreatic neuroendocrine microtumors in the 2022 WHO classification of endocrine and neuroendocrine tumors. This case report discussed the features of an incidentally identified 4.7-mm glucagon-expressing pancreatic neuroendocrine microtumor with MEN1 mutation only, chromosomally stable and an epigenetic alpha-like phenotype. The tumor was associated with an unexplained increased proliferation rate in Ki-67 of 15%. There was no associated DAXX/ATRX deficiency. The presented case challenges the conventional thought of a low proliferative disease of the so-called "pancreatic neuroendocrine microadenomas" and provides additional support to the 2022 WHO classification that also requires grading of these neoplasms. Despite exhibiting molecular features of less aggressive behavior, the case also underscores the biological complexity of pancreatic neuroendocrine microtumors. By recognizing the heterogenous spectrum of neuroendocrine neoplasms, the current case also contributes to ongoing discussions on how to optimize the clinical management of such tumors.
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Affiliation(s)
- Aziz Chouchane
- Institute For Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
| | - Philipp Kirchner
- Institute For Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
| | - Ilaria Marinoni
- Institute For Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
| | - Eva Sticová
- Clinical and Transplant Pathology Centre, Institute of Clinical and Experimental Medicine, Prague, Czech Republic
| | - Tomáš Jirásek
- Department of Pathology, Liberec Regional Hospital, Liberec, Czech Republic
| | - Aurel Perren
- Institute For Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
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18
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Hwang I, Song JS, Cho E, Song KH, Ra SH, Choi CM, Kim TW, Kim SH, Kim JW, Chung JY. PPIB/Cyclophilin B expression associates with tumor progression and unfavorable survival in patients with pulmonary adenocarcinoma. Am J Cancer Res 2024; 14:917-930. [PMID: 38455410 PMCID: PMC10915315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 02/22/2024] [Indexed: 03/09/2024] Open
Abstract
Cyclophilin B (CypB), encoded by peptidylprolyl isomerase B (PPIB), is involved in cellular transcriptional regulation, immune responses, chemotaxis, and proliferation. Recent studies have shown that PPIB/CypB is associated with tumor progression and chemoresistance in various cancers. However, the clinicopathologic significance and mechanism of action of PPIB/CypB in non-small cell lung cancer (NSCLC) remain unclear. In this study, we used RNA in situ hybridization to examine PPIB expression in 431 NSCLC tissue microarrays consisting of 295 adenocarcinomas (ADCs) and 136 squamous cell carcinomas (SCCs). Additionally, Ki-67 expression was evaluated using immunohistochemistry. The role of PPIB/CypB was assessed in five human NSCLC cell lines. There was a significant correlation between PPIB/CypB expression and Ki-67 expression in ADC (Spearman correlation r=0.374, P<0.001) and a weak correlation in SCC (r=0.229, P=0.007). In ADCs, high PPIB expression (PPIBhigh) was associated with lymph node metastasis (P=0.023), advanced disease stage (P=0.014), disease recurrence (P=0.013), and patient mortality (P=0.015). Meanwhile, high Ki-67 expression (Ki-67high) was correlated with male sex, smoking history, high pT stage, lymph node metastasis, advanced stage, disease recurrence, and patient mortality in ADC (all P<0.001). However, there was no association between either marker or clinicopathological factors, except for old age and PPIBhigh (P=0.038) in SCC. Survival analyses revealed that the combined expression of PPIBhigh/Ki-67high was an independent prognosis factor for poor disease-free survival (HR 1.424, 95% CI 1.177-1.723, P<0.001) and overall survival (HR 1.266, 95% CI 1.036-1.548, P=0.021) in ADC, but not in SCC. Furthermore, PPIB/CypB promoted the proliferation, colony formation, and migration of NSCLC cells. We also observed the oncogenic properties of PPIB/CypB expression in human bronchial epithelial cells. In conclusion, PPIB/CypB contributes to tumor growth in NSCLC, and elevated PPIB/Ki-67 levels are linked to unfavorable survival, especially in ADC.
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Affiliation(s)
- Ilseon Hwang
- Department of Pathology, Keimyung University School of Medicine, Dongsan Medical CenterDaegu 42601, Republic of Korea
| | - Joon Seon Song
- Department of Pathology, Asan Medical Center, University of Ulsan College of MedicineSeoul 05505, Republic of Korea
| | - Eunho Cho
- Department of Biochemistry and Molecular Biology, Korea University College of MedicineSeoul 02841, Republic of Korea
- Department of Biomedical Science, Korea University College of MedicineSeoul 02841, Republic of Korea
- BK21 Graduate Program, Department of Biomedical Science, Korea University College of MedicineSeoul 02841, Republic of Korea
| | - Kwon-Ho Song
- Department of Cell Biology, Daegu Catholic University School of MedicineDaegu 42472, Republic of Korea
| | - Sang Hyun Ra
- Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of MedicineSeoul 05505, Republic of Korea
| | - Chang-Min Choi
- Department of Pulmonary and Critical Care Medicine and Oncology, Asan Medical Center, University of Ulsan College of MedicineSeoul 05505, Republic of Korea
| | - Tae Woo Kim
- Department of Biochemistry and Molecular Biology, Korea University College of MedicineSeoul 02841, Republic of Korea
- Department of Biomedical Science, Korea University College of MedicineSeoul 02841, Republic of Korea
- BK21 Graduate Program, Department of Biomedical Science, Korea University College of MedicineSeoul 02841, Republic of Korea
| | - Sung-Han Kim
- Department of Infectious Diseases, Asan Medical Center, University of Ulsan College of MedicineSeoul 05505, Republic of Korea
| | - Jeong Won Kim
- Department of Pathology, Kangnam Sacred Heart Hospital, Hallym University College of MedicineSeoul 07441, Republic of Korea
| | - Joon-Yong Chung
- Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of HealthBethesda, MD 20852, USA
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Di Palma S, Koliou P, Simonovic A, Costa D, Faulkes C, Kobutungi B, Paterson F, Horsnell JD, Pakzad F, Irvine T, Partlett P, Clayton E, Collins N. Breast Cancer Molecular Subtyping in Practice: A Real-World Study of the APIS Breast Cancer Subtyping Assay in a Consecutive Series of Breast Core Biopsies. Int J Mol Sci 2024; 25:2616. [PMID: 38473863 DOI: 10.3390/ijms25052616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 03/14/2024] Open
Abstract
The APIS Breast Cancer Subtyping Kit is an mRNA-based assessment of the seven parameters including three biomarkers routinely assessed in all the newly diagnosed breast cancers (BC), oestrogen receptor (ER), progesterone receptor (PR) and HER-2 and an additional four genes that create a novel proliferation signature, MKI67, PCNA, CCNA2 and KIF23. Taken together, the data are used to produce a molecular subtype for every sample. The kit was evaluated against the current standard protocol of immunohistochemistry (IHC) and/or in situ hybridisation (ISH) in breast cancer patients. The data were presented at the weekly breast multidisciplinary team (MDT) meeting. A total of 98 consecutive cases of pre-operative breast cancer core biopsies and two core biopsies of nodal metastases yielding 100 cases were assessed. IHC and APIS results were available for 100 and 99 cases. ER was concordant in 97% cases, PR was concordant in 89% and HER-2 results were concordant with IHC/ISH in 100% of the cases. Ki-67 IHC was discordant in 3% of cases when compared with MK167 alone but discordant in 24% when compared with the four-gene proliferation signature. In conclusion, our study indicates that the APIS Breast Cancer Subtyping Kit is highly concordant when compared to the results produced for ER/PR/HER-2 by IHC and/or ISH. The assay could play a role in the routine assessment of newly diagnosed breast cancer (BC) specimens.
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Affiliation(s)
- Silvana Di Palma
- Department of Cellular Pathology, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, University of Surrey, Egerton Road, Guildford GU2 7XX, UK
| | - Panagiotis Koliou
- Department of Oncology, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Alex Simonovic
- Department of Cellular Pathology, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, University of Surrey, Egerton Road, Guildford GU2 7XX, UK
| | - Daniela Costa
- Molecular Diagnostics, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Catherine Faulkes
- Molecular Diagnostics, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Brenda Kobutungi
- Molecular Diagnostics, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Felicity Paterson
- Department of Oncology, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Jonathan David Horsnell
- Breast Unit, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Farrokh Pakzad
- Breast Unit, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Tracey Irvine
- Breast Unit, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Polly Partlett
- Breast Unit, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Elizabeth Clayton
- Breast Unit, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
| | - Nadine Collins
- Molecular Diagnostics, Berkshire & Surrey Pathology Services, The Royal Surrey Hospital NHS Foundation Trust, Egerton Road, Guildford GU2 7XX, UK
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20
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Mohammed A, Bakry A, Gharieb S, Hanna A, Obaya A, Abdelhady W, Metwalli A. Predictive Value of Tumor-Infiltrating Lymphocytes and Ki-67 for Pathological Response to Total Neoadjuvant Therapy in Rectal Cancer. J Gastrointest Cancer 2024:10.1007/s12029-024-01026-6. [PMID: 38358621 DOI: 10.1007/s12029-024-01026-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2024] [Indexed: 02/16/2024]
Abstract
PURPOSE Patients with locally advanced rectal cancer (LARC) who underwent total neoadjuvant therapy (TNT) showed an increase in the percentage of complete pathological response (pCR). The purpose of this study was to determine the correlation between Ki-67, tumor-infiltrating lymphocytes (TIL), and TNT in LARC patients. METHOD In total, one hundred fifty-nine patients with LARC were included in this prospective study. The international working group was used to categorize the TIL into three groups based on the percentage and density of staining: group 0 (0-10%), group 1 (11-59%), and group 2 (≥ 60%). Ki-67 expression was classified as low (≤ 50%) or high (> 50%). RESULT Most patients had tumor grade III (74.2%) and T2-T3 (78.6%). Lymph node involvement (48.7%) and tumor size ≥ 3 cm were detected in approximately half of the patients. Forty-four percent of patients had a high Ki-67 index; 15.7% of patients belonged to group 1, and 21.4% belonged to group 2. pCR was detected in 18.2% of the patients. TIL and Ki-67 levels were significantly correlated with pCR (p = 0.001 and 0.003 for multivariate analysis and 0.001 and 0.03 for univariate analysis, respectively). CONCLUSION There was a statistically significant correlation between Ki-67, TIL, and pCR following TNT protocol, which may help maximize the therapeutic outcome.
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Affiliation(s)
- Amrallah Mohammed
- Medical Oncology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt.
| | - Adel Bakry
- Medical Oncology Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Shimaa Gharieb
- Department of Clinical Oncology & Nuclear Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Amira Hanna
- Department of Clinical Oncology & Nuclear Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ahmed Obaya
- Department of Clinical Oncology & Nuclear Medicine, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Waleed Abdelhady
- Surgical Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
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21
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Wen Y, Song Z, Li Q, Zhang D, Li X, Yu J, Li Z, Ren X, Zhang J, Liu Q, Huang J, Zeng D, Tang Z. Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters. Insights Imaging 2024; 15:41. [PMID: 38353857 PMCID: PMC10866831 DOI: 10.1186/s13244-024-01617-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/21/2023] [Indexed: 02/17/2024] Open
Abstract
OBJECTIVE To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. RESULTS Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency. CONCLUSIONS The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. CRITICAL RELEVANCE STATEMENT The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. KEY POINTS • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.
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Affiliation(s)
- Youjia Wen
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zuhua Song
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Qian Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Dan Zhang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Xiaojiao Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jiayi Yu
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zongwen Li
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Xiaofang Ren
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jiayan Zhang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Qian Liu
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Jie Huang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Dan Zeng
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China
| | - Zhuoyue Tang
- Chongqing General Hospital, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, China.
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22
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Hu Y, Mo S, Xiao J, Cui M, Zheng Q, Chen T, Chang X, Liao Q. The significance of an immunohistochemical marker-based panel in assisting the diagnosis of parathyroid carcinoma. Endocrine 2024:10.1007/s12020-024-03687-6. [PMID: 38340242 DOI: 10.1007/s12020-024-03687-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/03/2024] [Indexed: 02/12/2024]
Abstract
PURPOSE Parathyroid carcinoma (PC) is an endocrine malignancy with a poor prognosis. However, the diagnosis of PC is still a difficult problem. A model with immunohistochemical (IHC) staining of 5 biomarkers has been reported from limited samples for the differential diagnosis of PC. In the present study, a series of IHC markers was applied in relatively large samples to optimize the diagnostic model for PC. METHODS In this study, 44 patients with PC, 6 patients with atypical parathyroid tumors and 57 patients with parathyroid adenomas were included. IHC staining for parafibromin, Ki-67, galectin-3, protein-encoding gene product 9.5 (PGP9.5), E-cadherin, and enhancer of zeste homolog 2 (EZH2) was performed on formalin-fixed, paraffin-embedded tissue samples. The effects of clinical characteristics, surgical procedure, and IHC staining results of tumor tissues on the diagnosis and prognosis of PC were evaluated retrospectively. RESULTS A logistic regression model with IHC results of parafibromin, Ki-67, and E-cadherin was created to differentiate PC with an area under the curve of 0.843. Cox proportional hazards analysis showed that negative parafibromin staining (hazard ratio: 3.26, 95% confidence interval: 1.28-8.34, P = 0.013) was related to the recurrence of PC. CONCLUSION An IHC panel of parafibromin, Ki-67 and E-cadherin may help to distinguish PC from parathyroid neoplasms. Among the 6 IHC markers and clinical features examined, the risk factor related to PC recurrence was parafibromin staining loss.
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Affiliation(s)
- Ya Hu
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Shengwei Mo
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinheng Xiao
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Ming Cui
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Qingyuan Zheng
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Tianqi Chen
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoyan Chang
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Quan Liao
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
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Shaker N, Shen R, Limbach AL, Satturwar S, Kobalka P, Ahmadian S, Sun S, Chen W, Lujan G, Esnakula A, Parwani A, Li Z. Automated imaging analysis of Ki-67 immunohistochemistry on whole slide images of cell blocks from pancreatic neuroendocrine neoplasms. J Am Soc Cytopathol 2024:S2213-2945(24)00005-X. [PMID: 38433072 DOI: 10.1016/j.jasc.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/06/2024] [Accepted: 02/06/2024] [Indexed: 03/05/2024]
Abstract
INTRODUCTION Accurate grading of pancreatic neuroendocrine tumors (PanNETs) relies on the assessment of Ki-67 immunohistochemistry (IHC). While digital imaging analysis (DIA) has been employed for Ki-67 IHC assessment in surgical specimens, its applicability to cytologic specimens remains underexplored. This study aimed to evaluate an automated DIA for assessing Ki-67 IHC on PanNET cell blocks. MATERIALS AND METHODS The study included 61 consecutive PanNETs and 5 pancreatic neuroendocrine carcinomas. Ki-67 IHC slides from cell blocks were digitally scanned into whole slide images using Philips IntelliSite Scanners and analyzed in batches using the Visiopharm Ki-67 App in a digital workflow. Ki-67 scores obtained through DIA were compared to pathologists' manual scores. RESULTS The Pearson correlation coefficient of the percentage of Ki-67-stained nuclei between DIA reads and the originally reported reads was 0.9681. Concordance between DIA Ki-67 grades and pathologists' Ki-67 grades was observed in 92.4% (61/66) of cases with the calculated Cohen's Kappa coefficient of 0.862 (almost perfect agreement). Discordance between DIA and pathologists' consensus reads occurred in 5 PanNET cases which were upgraded from G1 to G2 by DIA due to contaminated Ki-67-stained inflammatory cells. CONCLUSIONS DIA demonstrated excellent concordance with pathologists' assessments, with only minor grading discrepancies. However, the essential role of pathologists in confirming results is emphasized to enhance overall accuracy.
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Affiliation(s)
- Nada Shaker
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Rulong Shen
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | | | - Swati Satturwar
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Peter Kobalka
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Saman Ahmadian
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Shaoli Sun
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Wei Chen
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Giovanni Lujan
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Ashwini Esnakula
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Anil Parwani
- Department of Pathology, The Ohio State University, Columbus, Ohio
| | - Zaibo Li
- Department of Pathology, The Ohio State University, Columbus, Ohio.
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24
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Luo X, Zheng R, Zhang J, He J, Luo W, Jiang Z, Li Q. CT-based radiomics for predicting Ki-67 expression in lung cancer: a systematic review and meta-analysis. Front Oncol 2024; 14:1329801. [PMID: 38384802 PMCID: PMC10879429 DOI: 10.3389/fonc.2024.1329801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Accepted: 01/22/2024] [Indexed: 02/23/2024] Open
Abstract
Background Radiomics, an emerging field, presents a promising avenue for the accurate prediction of biomarkers in different solid cancers. Lung cancer remains a significant global health challenge, contributing substantially to cancer-related mortality. Accurate assessment of Ki-67, a marker reflecting cellular proliferation, is crucial for evaluating tumor aggressiveness and treatment responsiveness, particularly in non-small cell lung cancer (NSCLC). Methods A systematic review and meta-analysis conducted following the preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA) guidelines. Two authors independently conducted a literature search until September 23, 2023, in PubMed, Embase, and Web of Science. The focus was on identifying radiomics studies that predict Ki-67 expression in lung cancer. We evaluated quality using both Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. For statistical analysis in the meta-analysis, we used STATA 14.2 to assess sensitivity, specificity, heterogeneity, and diagnostic values. Results Ten retrospective studies were pooled in the meta-analysis. The findings demonstrated that the use of computed tomography (CT) scan-based radiomics for predicting Ki-67 expression in lung cancer exhibited encouraging diagnostic performance. Pooled sensitivity, specificity, and area under the curve (AUC) in training cohorts were 0.78, 0.81, and 0.85, respectively. In validation cohorts, these values were 0.78, 0.70, and 0.81. Quality assessment using QUADAS-2 and RQS indicated generally acceptable study quality. Heterogeneity in training cohorts, attributed to factors like contrast-enhanced CT scans and specific Ki-67 thresholds, was observed. Notably, publication bias was detected in the training cohort, indicating that positive results are more likely to be published than non-significant or negative results. Thus, journals are encouraged to publish negative results as well. Conclusion In summary, CT-based radiomics exhibit promise in predicting Ki-67 expression in lung cancer. While the results suggest potential clinical utility, additional research efforts should concentrate on enhancing diagnostic accuracy. This could pave the way for the integration of radiomics methods as a less invasive alternative to current procedures like biopsy and surgery in the assessment of Ki-67 expression.
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Affiliation(s)
- Xinmin Luo
- Department of Radiology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Renying Zheng
- Department of Oncology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Jiao Zhang
- Department of Radiology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Juan He
- Department of Radiology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Wei Luo
- Department of Radiology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Zhi Jiang
- Department of Radiology, People’s Hospital of Yuechi County, Guang’an, Sichuan, China
| | - Qiang Li
- Department of Radiology, Yuechi County Traditional Chinese Medicine Hospital in Sichuan Province, Guang’an, Sichuan, China
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He Y, Zhao L, Tang X, Jiang Q, Zhao X, Cao Y. Prognostic implications of synaptophysin, CD56, thyroid transcription factor-1, and Ki-67 in pulmonary high-grade neuroendocrine carcinomas. Ann Diagn Pathol 2024; 68:152239. [PMID: 38006863 DOI: 10.1016/j.anndiagpath.2023.152239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 11/13/2023] [Accepted: 11/16/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND The correlation between the expression of immunohistochemical markers and the clinicopathological characteristics of pulmonary high-grade neuroendocrine carcinomas (HGNEC) and its impact on the clinical outcomes of individuals with HGNEC has not yet been explored. METHODS This study enrolled patients diagnosed with HGNEC between April 2015 and July 2023. Based on the expression levels of synaptophysin (Syn), the neural cell adhesion molecule (CD56), thyroid transcription factor-1 (TTF-1), and Ki-67, a comprehensive analysis was conducted. This involved a comparison of clinicopathological characteristics, chemosensitivity, overall survival (OS), and progression-free survival (PFS). Furthermore, the study identified prognostic factors associated with patient survival through univariate and multivariate analyses. RESULTS Eighty-two patients were analyzed. Significant differences were identified in tumor stage (χ2 = 5.473, P = 0.019), lymphatic invasion (χ2 = 8.839, P = 0.003), and distant metastasis (χ2 = 5.473, P = 0.019), respectively, between the CD56 positive and negative groups. A significant difference in lymphatic invasion was observed (χ2 = 9.949, P = 0.002) between the CD56 positive and negative groups. A significant difference in vascular invasion was observed (χ2 = 5.106, P = 0.024) between the low and high Ki-67 groups. Compared to the Syn negative group, the Syn positive group had significantly shorter PFS (P = 0.006). Compared to the Syn negative group, the Syn positive group had significantly shorter OS (P = 0.004). The CD56 positive group also had significantly shorter OS than the CD56 negative group (P = 0.027). Univariate analysis revealed that tumor stage and Syn expression were associated with OS and PFS. Lymphatic invasion and CD56 expression were associated with OS. Multivariate analysis revealed that tumor stage was the strongest predictor of poor prognosis for OS (hazard ratio [HR] 0.551, 95 % confidence interval [CI] 0.328-0.927, P = 0.025) and PFS (HR 0.409, 95 % CI 0.247-0.676, P < 0.001). CONCLUSIONS Positive expression of Syn was associated with reduced PFS and OS, while positive CD56 expression was correlated with a shorter OS in HGNEC. The TNM stage was an independent risk factor that significantly influenced PFS and OS in patients with HGNEC. More studies are needed to make further progress in future treatment.
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Affiliation(s)
- Yulong He
- Department of Oncology, Nanxishan Hospital of the Guangxi Zhuang Autonomous Region, Guilin 541002, China
| | - Lei Zhao
- Department of Pathology, Nanxishan Hospital of the Guangxi Zhuang Autonomous Region, Guilin 541002, China
| | - Xiaorong Tang
- Department of Spine Surgery, Guilin People's Hospital, Guilin 541002, China
| | - Qinling Jiang
- Department of Oncology, Nanxishan Hospital of the Guangxi Zhuang Autonomous Region, Guilin 541002, China
| | - Xianling Zhao
- Department of Oncology, Nanxishan Hospital of the Guangxi Zhuang Autonomous Region, Guilin 541002, China
| | - Yilin Cao
- Department of Oncology, Nanxishan Hospital of the Guangxi Zhuang Autonomous Region, Guilin 541002, China.
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Wang Y, Hong L, Yang C, Lv G, Wang K, Huang X, Shen H. Ultrasound combined with Ki-67 to construct the prognostic model for radioactive iodine therapy outcomes in Graves' disease patients. Endocr Connect 2024; 13:e230429. [PMID: 38108761 PMCID: PMC10831585 DOI: 10.1530/ec-23-0429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/18/2023] [Indexed: 12/19/2023]
Abstract
The aim of this study was to develop a prognostic model for radioactive iodine (RAI) therapy outcome in patients with Graves' disease. We enrolled 127 patients. Information on RAI therapy, ultrasound indexes of thyroid, and other lifestyle factors was collected. The competing risk model was used to estimate the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for nonhealing or recurrence of hyperthyroidism (NHRH). The performance of the model was assessed by receiver operator characteristic analysis and the Brier score and internally validated by bootstrap resampling. Then, a nomogram was developed. Forty-one cases (32.2%) of NHRH were documented. Positive Ki-67 expression, a higher dose of per-unit thyroid volume, and females showed lower risks of NHRH (all P < 0.05). The HR values (95% CI) were 0.42 (0.23, 0.79), 0.01 (0.00, 0.02), and 0.47 (0.25, 0.89), respectively. The bootstrap validation showed that the model had the highest accuracy and good calibration for predicting cumulative risk of NHRH at 180 days after RAI therapy (AUC = 0.772; 95% CI: 0.640-0.889, Brier score = 0.153). By decision curve analysis, the nomogram was shown to have a satisfactory net benefit between thresholds of 0.20 and 0.40. Ki-67, ultrasound volumetry, and scintigraphy techniques can play important roles in evaluating RAI therapy outcome in Graves' disease patients. The prediction nomogram shows reasonable accuracy in predicting NHRH.
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Affiliation(s)
- Yuegui Wang
- Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
| | - Liwei Hong
- Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
| | - Caiyun Yang
- Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
- School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China
| | - Guorong Lv
- School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China
- Quanzhou Medical College, Quanzhou, Fujian, China
| | - Kangjian Wang
- Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
| | - Xuepeng Huang
- Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
| | - Haolin Shen
- Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
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Ziegler C, Sotlar K, Hofmann DM, Kolben T, Harbeck N, Wuerstlein R. Use of the Gene Expression Test Prosigna ® in Premenopausal Patients with HR+, HER2- Early Breast Cancer: Correlation of the Results with the Proliferation Marker Ki-67. Breast Care (Basel) 2024; 19:34-42. [PMID: 38384489 PMCID: PMC10878706 DOI: 10.1159/000534634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 10/14/2023] [Indexed: 02/23/2024] Open
Abstract
Introduction In hormone receptor-positive (ER+/PR+) and human epidermal growth factor receptor 2-negative (HER2-) early-stage breast cancer (EBC), gene expression tests such as the Prosigna are increasingly used since classic clinicopathological parameters and the proliferation factor Ki-67 often do not allow a definite therapy decision regarding an adjuvant chemotherapy. While the Prosigna test has been validated for postmenopausal patients, few data are available regarding its use in premenopausal patients. The present study compared the Prosigna test with the Ki-67 index in premenopausal patients. Materials and Methods Premenopausal patients with HR+ HER2-, pN0-1, G1-2 EBC were retrospectively enrolled (n = 55). The Prosigna assay was performed in formalin-fixed paraffin-embedded tumor samples of surgical resection specimens. Ki-67 was reassessed in original diagnostic core needle biopsy specimens and defined as low, intermediate, or high with the threshold of <10%, 10-24%, ≥25%. Results According to Ki-67, patients were in the low (LR)-, intermediate (IR)-, and high-risk (HR) groups in 40%, 36%, and 24% of the cases. The Prosigna gene signature assay assessed the risk of recurrence as LR for 45% of the patients, IR for 35%, and HR for 20%. The most frequent intrinsic subtypes were luminal A in 73% and luminal B in 24% of the patients. A moderate correlation was found between Prosigna and Ki-67 scores with a Pearson correlation coefficient of 0.51. In the overall cohort, 47% of the Ki-67-based therapy decision would correspond to those based on the Prosigna score. After exclusion of IR patients, matching of low/low or high/high results was observed in 57% of the cases. Conclusion According to the present study, there is only limited concordance regarding the risk group stratification between Ki-67 and Prosigna-based risk assessment. The relevance and frequency of premenopausal breast cancer emphasizes the need for further evaluation of gene expression analyses in this setting and the correlation with classic clinicopathological parameters regarding therapy decision-making.
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Affiliation(s)
- Cordula Ziegler
- Department of Obstetrics and Gynecology, BreastCenter and CCC Munich LMU, LMU University Hospital, Munich, Germany
| | - Karl Sotlar
- Institute of Pathology, University Hospital Salzburg, Paracelsus Medical University Salzburg, Salzburg, Austria
- Institute of Pathology, Ludwig Maximilians University Munich, Munich, Germany
| | - Daniel Maria Hofmann
- Institute of Pathology, Ludwig Maximilians University Munich, Munich, Germany
- University Clinics Munich (LMU), Division of Hand, Plastic and Aesthetic Surgery, Munich, Germany
| | - Thomas Kolben
- Department of Obstetrics and Gynecology, BreastCenter and CCC Munich LMU, LMU University Hospital, Munich, Germany
| | - Nadia Harbeck
- Department of Obstetrics and Gynecology, BreastCenter and CCC Munich LMU, LMU University Hospital, Munich, Germany
| | - Rachel Wuerstlein
- Department of Obstetrics and Gynecology, BreastCenter and CCC Munich LMU, LMU University Hospital, Munich, Germany
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Dawe M, Shi W, Liu TY, Lajkosz K, Shibahara Y, Gopal NEK, Geread R, Mirjahanmardi S, Wei CX, Butt S, Abdalla M, Manolescu S, Liang SB, Chadwick D, Roehrl MHA, McKee TD, Adeoye A, McCready D, Khademi A, Liu FF, Fyles A, Done SJ. Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer. J Transl Med 2024; 104:100341. [PMID: 38280634 DOI: 10.1016/j.labinv.2024.100341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 11/20/2023] [Accepted: 01/19/2024] [Indexed: 01/29/2024] Open
Abstract
Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.
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Affiliation(s)
- Melanie Dawe
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Wei Shi
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Tian Y Liu
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Katherine Lajkosz
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Yukiko Shibahara
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Laboratory Medicine Program, University Health Network, Toronto, Canada
| | - Nakita E K Gopal
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Rokshana Geread
- Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, Canada
| | - Seyed Mirjahanmardi
- Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, Canada; Division of Medical Physics, Department of Radiation Oncology, Stanford University, Stanford, California
| | - Carrie X Wei
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Sehrish Butt
- STTARR Innovation Centre, University Health Network, Toronto, Canada
| | - Moustafa Abdalla
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Sabrina Manolescu
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Sheng-Ben Liang
- Princess Margaret Cancer Biobank, University Health Network, Toronto, Canada
| | - Dianne Chadwick
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Laboratory Medicine Program, University Health Network, Toronto, Canada; Princess Margaret Cancer Biobank, University Health Network, Toronto, Canada; Ontario Tumour Bank, Ontario Institute for Cancer Research, Toronto, Canada
| | - Michael H A Roehrl
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Laboratory Medicine Program, University Health Network, Toronto, Canada; Princess Margaret Cancer Biobank, University Health Network, Toronto, Canada; Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Trevor D McKee
- STTARR Innovation Centre, University Health Network, Toronto, Canada
| | - Adewunmi Adeoye
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - David McCready
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - April Khademi
- Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, Canada; St Michael's Hospital, Unity Health Network, Toronto, Canada
| | - Fei-Fei Liu
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Anthony Fyles
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Susan J Done
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada; Laboratory Medicine Program, University Health Network, Toronto, Canada.
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29
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Liang Y, Xu F, Mou Q, Wang Z, Xiao C, Zhou T, Zhang N, Yang J, Wu H. A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma. BMC Med Imaging 2024; 24:27. [PMID: 38273242 PMCID: PMC10811868 DOI: 10.1186/s12880-024-01204-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/17/2024] [Indexed: 01/27/2024] Open
Abstract
PURPOSE To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features. METHODS A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves. RESULTS The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076). CONCLUSIONS Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.
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Affiliation(s)
- Yingying Liang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Fan Xu
- Department of Radiology, Guangzhou Red Cross Hospital, Medical College, Jinan University, 396 Tongfu Road, Guangzhou, Guangdong Province, 510220, China
| | - Qiuju Mou
- Department of Pathology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Zihua Wang
- Department of Radiology, Foshan Hospital of Traditional Chinese Medicine, Foshan, Guangdong Province, 528000, China
| | - Chuyin Xiao
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Tingwen Zhou
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Nianru Zhang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China
| | - Jing Yang
- Department of Pathology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China.
| | - Hongzhen Wu
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1Panfu Road, Guangzhou, Guangdong Province, 510180, China.
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Hokkoku D, Sasaki K, Kobayashi S, Iwagami Y, Yamada D, Tomimaru Y, Asaoka T, Noda T, Takahashi H, Shimizu J, Doki Y, Eguchi H. Apparent diffusion coefficient in intrahepatic cholangiocarcinoma diffusion-weighted magnetic resonance imaging noninvasively predicts Ki-67 expression. Hepatol Res 2024. [PMID: 38254248 DOI: 10.1111/hepr.14015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 12/23/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024]
Abstract
AIM Tumor Ki-67 expression reflects prognosis and cancer grade, and biopsy-based preoperative assessment of Ki-67 expression is key to treatment. Apparent diffusion coefficient (ADC) values obtained with this imaging may noninvasively predict Ki-67 by reflecting tumor cell density and limited water molecule movement from irregular alignment. This study aimed to investigate the ability of ADC values to predict Ki-67 expression in intrahepatic cholangiocarcinoma (ICC). METHOD We retrospectively analyzed 39 cases of ICC confirmed by surgical pathology. All patients had undergone magnetic resonance imaging, and ADC values (mean, minimum, and maximum) were calculated. Ki-67 expression was assessed by immunohistochemistry, and patients were divided into groups of high (n = 18) and low (n = 21) Ki-67 expression. To assess the diagnostic performance of the ADC values for Ki-67 expression, we used the receiver operating characteristic curve and compared the areas under the curve (AUC). RESULTS The mean and minimum ADC values were significantly lower in the group with high Ki-67 expression. For predicting high Ki-67 expression, the AUC values were 0.701 for mean ADC, 0.818 for minimum ADC, and 0.571 for maximum ADC. The diagnostic sensitivity and specificity of the minimum ADC values were 88.9% and 76.2%, respectively. In addition, with ADC values combined, the AUC increased to 0.831. Apparent diffusion coefficient is a useful predictor of Ki-67 expression level in ICC. CONCLUSION Apparent diffusion coefficient values, especially minimum ADC values, can noninvasively predict ICC associated with high Ki-67 expression.
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Affiliation(s)
- Daiki Hokkoku
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Kazuki Sasaki
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Shogo Kobayashi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Yoshifumi Iwagami
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Daisaku Yamada
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Yoshito Tomimaru
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Tadafumi Asaoka
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Takehiro Noda
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Hidenori Takahashi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Junzo Shimizu
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Yuichiro Doki
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Hidetoshi Eguchi
- Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Suita, Japan
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Wang J, Yu Z, Jiang Y, Le T, Wu Y, Li Z, Zhang G, Wu F, Ma H. Downregulation of MTHFD2 Inhibits Proliferation and Enhances Chemosensitivity in Hepatocellular Carcinoma via PI3K/AKT Pathway. FRONT BIOSCI-LANDMRK 2024; 29:35. [PMID: 38287824 DOI: 10.31083/j.fbl2901035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/03/2023] [Accepted: 11/27/2023] [Indexed: 01/31/2024]
Abstract
BACKGROUND Despite the substantial impact of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) on cancer progression, its significance in the regulation of hepatocellular carcinoma (HCC) cell proliferation and chemosensitivity remains poorly defined. METHODS We evaluated MTHFD2 expression in a total of 95 HCC tissues by immunohistochemistry and analyzed the association of MTHFD2 with clinicopathologic features. qRT-PCR and Western blotting were conducted to verify MTHFD2 expression levels. Bioinformatics analysis such as gene set enrichment analysis (GSEA) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were used to predict the signaling pathways involved in MTHFD2. In addition, to investigate the anti-tumor effects of MTHFD2 knockdown, Cell Counting Kit-8 (CCK-8) and EdU assays were used. RESULTS We found that MTHFD2 was frequently upregulated in HCC, and the combination of increased expression of MTHFD2 and Ki67 was associated with poor HCC prognosis. MTHFD2 knockdown significantly inhibited HCC cell proliferation and effectively sensitized HCC cells to sorafenib and lenvatinib. PI3K/AKT pathway was involved in MTHFD2-mediated modulation of proliferation and chemosensitivity. CONCLUSIONS These findings indicate that MTHFD2 plays an important role in proliferation and chemosensitivity of HCC, indicating that it may serve as a novel pharmacological target for improving HCC therapy.
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Affiliation(s)
- Jie Wang
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
| | - Ze Yu
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
| | - Yixiao Jiang
- Department of General Surgery, Zhoushan Hospital, 316021 Zhoushan, Zhejiang, China
| | - Ting Le
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
| | - Yixin Wu
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
| | - Ziqi Li
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
| | - Guoqiang Zhang
- Department of General Surgery, Zhoushan Hospital, 316021 Zhoushan, Zhejiang, China
| | - Feiyue Wu
- Department of Pharmacy, Zhoushan Hospital, 316021 Zhoushan, Zhejiang, China
| | - Haijie Ma
- Cellular and Molecular Biology Laboratory, Zhoushan Hospital, Wenzhou Medical University, 316021 Zhoushan, Zhejiang, China
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Demyashkin G, Karakaeva E, Saakian S, Tarusova N, Guseinova A, Vays A, Gotovtsev K, Atiakshin D, Shegai P, Kaprin A. Comparative Characterisation of Proliferation and Apoptosis of Colonic Epithelium after Electron Irradiation with 2 GY and 25 GY. Int J Mol Sci 2024; 25:1196. [PMID: 38256269 PMCID: PMC10817034 DOI: 10.3390/ijms25021196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/03/2024] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Development of new techniques for multimodal treatment and diagnostics of various neoplasms and the improvement of current techniques can significantly increase the life expectancy of patients with carcinomas of the colon and abdominal-cavity organs, since prevention of various side effects of radiation therapy is one of the main problems of oncological care. Electron irradiation is one of the most promising types of radiation therapy. There are no data on proliferation and apoptosis of the colon epithelium after irradiation with electrons, especially in different modes (single and summary). Morphological evaluation of apoptosis and proliferation of colonic epithelium after local irradiation with electrons were conducted at doses of 2 Gy (Gray) and 25 Gy. Colon fragments from sexually mature Wistar rats (n = 50, body weight 200 ± 10 g) were divided into three groups: I-control (n = 10); II-experimental group (n = 20; local single electron irradiation at a dose of 2 Gy); III-experimental group (n = 30) with local fractional irradiation with electrons at a total dose of 25 Gy. They were studied using light microscopy using hematoxylin and eosin staining and immunohistochemical reactions with antibodies to Ki-67 and caspase-3 (Cas3). Morphological disorders were accompanied by increased expression of pro-apoptotic molecules (caspase-3), and the period of regeneration by proliferative marker (Ki-67). Colon electron irradiation led to disturbances in the histoarchitecture of varying severity, and an increase in cell apoptosis was observed (increased expression of caspase-3 and decrease in Ki-67). In addition, modulation of the PI3K/AKT and MAPK/ERK signalling pathways was detected. The most pronounced destructive changes were observed in the group of 25 Gy fractionated electron irradiation.
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Affiliation(s)
- Grigory Demyashkin
- Laboratory of Histology and Immunohistochemistry, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
| | - Elza Karakaeva
- Department of Pathomorphology, National Medical Research Centre of Radiology, Ministry of Health of Russia, 125284 Moscow, Russia
| | - Susanna Saakian
- Department of Pathomorphology, National Medical Research Centre of Radiology, Ministry of Health of Russia, 125284 Moscow, Russia
| | - Natalia Tarusova
- Laboratory of Histology and Immunohistochemistry, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
| | - Amina Guseinova
- Laboratory of Histology and Immunohistochemistry, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
| | - Anita Vays
- Laboratory of Histology and Immunohistochemistry, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
| | - Konstantin Gotovtsev
- Laboratory of Histology and Immunohistochemistry, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia
| | - Dmitrii Atiakshin
- Research and Educational Resource Center for Immunophenotyping, Digital Spatial Profiling and Ultrastructural Analysis Innovative Technologies, RUDN University, 117198 Moscow, Russia
| | - Petr Shegai
- Department of Pathomorphology, National Medical Research Centre of Radiology, Ministry of Health of Russia, 125284 Moscow, Russia
| | - Andrey Kaprin
- Department of Pathomorphology, National Medical Research Centre of Radiology, Ministry of Health of Russia, 125284 Moscow, Russia
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Chung YC, Chen SJ, Huang CC, Liu WC, Lai MT, Kao TY, Yang WS, Yang CH, Hsu CP, Chang JF. Tocilizumab Exerts Anti-Tumor Effects on Colorectal Carcinoma Cell Xenografts Corresponding to Expression Levels of Interleukin-6 Receptor. Pharmaceuticals (Basel) 2024; 17:127. [PMID: 38256960 PMCID: PMC10820566 DOI: 10.3390/ph17010127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 12/29/2023] [Accepted: 01/11/2024] [Indexed: 01/24/2024] Open
Abstract
The use of tocilizumab against the interleukin-6 receptor (IL-6R) has been demonstrated as inhibiting the progression of diverse cancers in vitro and in vivo. Nonetheless, evidence regarding the anti-tumor effects of tocilizumab on human colorectal carcinoma (CRC) corresponding to IL-6R expression levels remains scarce. To investigate the influence of IL-6R expression, SW480 and HT-29 cells inoculated subcutaneously into NU/NU mice were used as human CRC xenograft models with anti-IL-6R antibody (tocilizumab) therapy. The IL-6R expression levels, histology of CRC growth/invasiveness, and tumor growth-related signaling pathway were estimated by H&E and immunohistochemical staining. SW480 tumor cells with higher IL-6R expression levels showed better responsiveness in tocilizumab therapy than in the treated HT-29 group. Likewise, therapeutic effects of tocilizumab on the proliferative ability with mitotic index and Ki-67 expressions, invasiveness with MMP-9 proteinase expressions, and ERK 1/2 and STAT3 signaling transduction in the SW480 treatment group were superior to the HT-29 treatment group. In light of our results, IL-6R is the key indicator for the efficacy of tocilizumab treatment in CRC xenografts. From the perspective of precision medicine, tumor response to anti-IL-6R antibody therapy could be predicted on the basis of IL-6R expression levels. In this manner, tocilizumab may serve as a targeted and promising anti-CRC therapy.
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Affiliation(s)
- Yuan-Chiang Chung
- Department of Surgery, Kuang Tien General Hospital, Taichung 433, Taiwan;
- Department of Surgery, Chung-Kang Branch, Cheng-Ching General Hospital, Taichung 407, Taiwan
| | - Szu-Jung Chen
- Department of Radiation Oncology, Taoyuan General Hospital, Ministry of Health and Welfare, Taoyuan 330, Taiwan;
| | - Chiu-Chen Huang
- Department of Post-Baccalaureate Veterinary Medicine, Asia University, Taichung 413, Taiwan;
| | - Wei-Chun Liu
- Department of Pathology, Hsin-Chu Branch, National Taiwan University Hospital, Hsinchu 300, Taiwan;
| | - Ming-Tsung Lai
- Department of Pathology, Taichung Hospital, Ministry of Health and Welfare, Taichung 403, Taiwan;
| | - Ting-Yu Kao
- Department of Medical Laboratory Science and Biotechnology, Yuanpei University of Medical Technology, Hsinchu 300, Taiwan;
| | - Wei-Shun Yang
- Department of Internal Medicine, Hsin-Chu Branch, National Taiwan University Hospital, Hsinchu 300, Taiwan;
| | - Chien-Hui Yang
- Department of Business Administration, Yuanpei University of Medical Technology, Hsinchu 300, Taiwan;
| | - Chih-Ping Hsu
- Department of Medical Laboratory Science and Biotechnology, Yuanpei University of Medical Technology, Hsinchu 300, Taiwan;
- Department of Biotechnology and Pharmaceutical Technology, Yuanpei University of Medical Technology, Hsinchu 300, Taiwan
| | - Jia-Feng Chang
- Division of Nephrology, Department of Internal Medicine, Taoyuan Branch, Taipei Veterans General Hospital, Taoyuan 330, Taiwan
- Department of Nursing, Yuanpei University of Medical Technology, Hsinchu 300, Taiwan
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Brigandì E, Valenti P, Bacci B, Brunetti B, Avallone G. Prognostic impact of Ki-67 in canine splenic hemangiosarcoma: A preliminary study. Vet Pathol 2024:3009858231225507. [PMID: 38214328 DOI: 10.1177/03009858231225507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2024]
Abstract
Canine splenic hemangiosarcoma has a high metastatic rate and short survival time. Currently, the main prognostic parameters are tumor stage and therapy, while data on histologic parameters, such as grade and Ki-67 expression, are scarce. The aims of this study were to compare two methods of assessment of Ki-67, verify their prognostic impact, and define a threshold value based on survival. Thirty-one cases of histologically diagnosed canine splenic hemangiosarcoma, which were treated with splenectomy and had full staging and follow-up information, were collected. Three were stage I, 17 stage II, and 11 stage III. The mean mitotic count (MC) was 23.9 (standard deviation [SD]: 22.1) and the median was 15 (range, 1-93). Immunohistochemistry for Ki-67 was performed, the Ki-67 labeling index (Ki-67LI) was assessed as a percentage of positive neoplastic nuclei per ≥500 cell, and the Ki-67 count (KI-67C) was defined as the average number of positive nuclei using a 1 cm2 optical grid performed in 5, 40× fields. The mean Ki-67LI and Ki-67C were 56.4% (SD: 38.7) and 27.2 (SD: 12.9) and medians were 51% (range, 8.2-55.2) and 26 (range, 5.5-148), respectively. Using a cut-off of 56% and 9, respectively, Kaplan-Meier survival curves showed an association of overall survival with Ki-67LI and MC. In addition to clinical stage, Ki-67LI maintained its prognostic value on multivariate analysis, supporting the role of Ki-67LI as an independent prognostic parameter. Based on these results, we propose a diagnostically applicable cut-off value of 56% for Ki-67LI as a prognostic parameter for canine splenic hemangiosarcoma.
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Arabul S, Melikoglu M, Kirimlioglu E, Boneval BC, Karaguzel G. Renal regenerative capacity related to stem cell reserve in nephrectomized rats. World J Urol 2024; 42:25. [PMID: 38206410 DOI: 10.1007/s00345-023-04702-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 11/17/2023] [Indexed: 01/12/2024] Open
Abstract
PURPOSE On the new era of stem cell therapy, the present experimental study was conducted to investigate renal regenerative capacity related to kidney stem cell reserve in different nephrectomy (Nx) models. METHODS Three- and eight-week-old rats (n = 168) were randomly divided into four groups to include control and three Nx subgroups (1/6 Nx, 1/2 Nx, and 5/6 Nx) (Fig. 1). On post-Nx days 15, 30 and 60, kidney specimens were obtained to determine renal regenerative capacity. The specimens were examined with immunofluorescence. CD90/CD105 and Ki-67 expressions were determined as stem cell and cellular proliferation markers, respectively. Fig. 1 Intraoperative photographs showing three different types of nephrectomies (unilateral total Nx has not been shown in 5/6 Nx group) RESULTS: CD90 and CD105 expressions were stronger in glomeruli, but Ki-67 expressions were present only in tubuli. When all Nx types and post-Nx days were considered, both 3- and 8-week-old rats undergone 5/6 Nx had the highest glomerular CD90 and CD105 double expressions. While the expressions gradually increased toward the day 60 in 3-weeks old rats, 8-week-old rats had almost stable double expressions. The strongest tubular Ki-67 expressions were seen in 5/6 Nx groups of both in 3- and 8-week-old rats. The expressions were strongest on day 15 and then gradually decreased. Ipsilateral 1/6 Nx groups had stronger Ki-67 expression than contralateral ones in both age groups. CONCLUSIONS Kidneys may pose a regenerative response to tissue/volume loss through its own CD90- and CD105-related stem cell reserve which mainly takes place in glomeruli and seems to have some interactions with Ki-67-related tubular proliferative process. This response supports that kidney stem cells may have a potential to overcome tissue/volume loss-related damage.
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Affiliation(s)
- Songul Arabul
- Department of Pediatric Surgery, Akdeniz University Faculty of Medicine, Antalya, Türkiye.
| | - Mustafa Melikoglu
- Department of Pediatric Surgery, Akdeniz University Faculty of Medicine, Antalya, Türkiye
| | - Esma Kirimlioglu
- Department of Histology and Embryology, Akdeniz University Faculty of Medicine, Antalya, Türkiye
| | - Bezmi Cem Boneval
- Department of Pediatric Surgery, Akdeniz University Faculty of Medicine, Antalya, Türkiye
| | - Gungor Karaguzel
- Department of Pediatric Surgery, Akdeniz University Faculty of Medicine, Antalya, Türkiye
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Zhang H, Niu S, Chen H, Wang L, Wang X, Wu Y, Shi J, Li Z, Hu Y, Yang Z, Jiang X. Radiomics signatures for predicting the Ki-67 level and HER-2 status based on bone metastasis from primary breast cancer. Front Cell Dev Biol 2024; 11:1220320. [PMID: 38264355 PMCID: PMC10804450 DOI: 10.3389/fcell.2023.1220320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 12/18/2023] [Indexed: 01/25/2024] Open
Abstract
This study explores the potential of radiomics to predict the proliferation marker protein Ki-67 levels and human epidermal growth factor receptor 2 (HER-2) status based on MRI images of patients with spinal metastasis from primary breast cancer. A total of 110 patients with pathologically confirmed spinal metastases from primary breast cancer were enrolled between Dec. 2017 and Dec. 2021. All patients underwent T1-weighted contrast-enhanced MRI scans. The PyRadiomics package was used to extract features from the MRI images based on the intraclass correlation coefficient and least absolute shrinkage and selection operator. The most predictive features were used to develop the radiomics signature. The Chi-Square test, Fisher's exact test, Student's t-test, and Mann-Whitney U test were used to evaluate the clinical and pathological characteristics between the high- and low-level Ki-67 groups and the HER-2 positive/negative groups. The radiomics models were compared using receiver operating characteristic curve analysis. The area under the receiver operating characteristic curve (AUC), sensitivity (SEN), and specificity (SPE) were generated as comparison metrics. From the spinal MRI scans, five and two features were identified as the most predictive for the Ki-67 level and HER-2 status, respectively. The developed radiomics signatures generated good prediction performance for the Ki-67 level in the training (AUC = 0.812, 95% CI: 0.710-0.914, SEN = 0.667, SPE = 0.846) and validation (AUC = 0.799, 95% CI: 0.652-0.947, SEN = 0.722, SPE = 0.833) cohorts. Good prediction performance for the HER-2 status was also achieved in the training (AUC = 0.796, 95% CI: 0.686-0.906, SEN = 0.720, SPE = 0.776) and validation (AUC = 0.705, 95% CI: 0.506-0.904, SEN = 0.733, SPE = 0.762) cohorts. The results of this study provide a better understanding of the potential clinical implications of spinal MRI-based radiomics on the prediction of Ki-67 levels and HER-2 status in breast cancer.
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Affiliation(s)
- Hongxiao Zhang
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
| | - Shuxian Niu
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
| | - Huanhuan Chen
- Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Lihua Wang
- Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China
| | - Xiaoyu Wang
- Department of Radiology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China
| | - Yujiao Wu
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
| | - Jiaxin Shi
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
| | - Zhuoning Li
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
| | - Yanjun Hu
- Department of Medical Imaging, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China
| | - Zhiguang Yang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xiran Jiang
- School of Intelligent Medicine, China Medical University, Shenyang, Liaoning, China
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Marouda C, Anagnostou T, Brunetti B, Savvas I, Papazoglou LG, Psalla D. Cutaneous Canine Mast Cell Tumor: The Use of Proliferative Markers ( Ki-67 and Ki-67 × AgNOR) in Cytological Samples for Diagnosis and Prognosis. Vet Sci 2024; 11:23. [PMID: 38250929 PMCID: PMC10821150 DOI: 10.3390/vetsci11010023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/23/2024] Open
Abstract
A cytological grading system for canine mast cell tumors (MCTs) has been developed, but its integration into clinical routine has been hindered due to its diagnostic limitations. The aim of this study was to assess the prognostic value of Ki-67 and argyrophilic nucleolar organizing region (AgNOR) markers in cytological MCT samples and to determine cut-off values for these markers in correlation with histopathological grading. Cytological samples were collected prior to surgical excision, and histopathological samples were obtained postsurgery from 45 dogs diagnosed with cutaneous mast cell tumors (MCTs). The cytological specimens were classified using a two-tier grading system, and their Ki-67 (average immunopositive nuclei per 100 cells) and AgNOR (average AgNOR counts per 100 nuclei) signaling was assessed. Through receiver operating characteristic (ROC) analysis, cut-off values for Ki-67 and Ki-67 × AgNOR were determined to better align with histopathological grading (classified as low or high grade according to Kiupel's scoring system). Without the inclusion of proliferative markers, there was a 73% agreement between cytological and histopathological grading. The prediction of histopathological grade was slightly more accurate when assessing Ki-67 and Ki-67 × AgNOR signaling in cytological specimens (75% and 80%, respectively) compared to the initial cytological grading. The cytological assessment of canine MCTs proves beneficial for the initial evaluation, and the incorporation of the evaluation of Ki-67 and AgNOR markers may assist in identifying diagnostically highly malignant MCTs.
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Affiliation(s)
- Christina Marouda
- Laboratory of Pathology, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Tilemahos Anagnostou
- Unit of Anaesthesiology and Intensive Care, Companion Animal Clinic, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54627 Thessaloniki, Greece
| | - Barbara Brunetti
- Department of Veterinary Medical Sciences, University of Bologna, 40064 Bologna, Italy
| | - Ioannis Savvas
- Unit of Anaesthesiology and Intensive Care, Companion Animal Clinic, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54627 Thessaloniki, Greece
| | - Lysimachos G. Papazoglou
- Unit of Surgery and Obstetrics, Companion Animal Clinic, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54627 Thessaloniki, Greece
| | - Dimitra Psalla
- Laboratory of Pathology, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
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Liang Y, Sheng G, Guo Y, Zou Y, Guo H, Li Z, Chang S, Man Q, Gao S, Hao J. Prognostic significance of grade of malignancy based on histopathological differentiation and Ki-67 in pancreatic ductal adenocarcinoma. Cancer Biol Med 2024:j.issn.2095-3941.2023.0363. [PMID: 38172499 DOI: 10.20892/j.issn.2095-3941.2023.0363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024] Open
Abstract
OBJECTIVE Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation. Ki-67, an indicator of cellular proliferation, has been used for tumor grading and classification in breast cancer and neuroendocrine tumors. However, its prognostic significance in pancreatic ductal adenocarcinoma (PDAC) remains uncertain. METHODS Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled, and relevant prognostic factors were examined. Grade of malignancy (GOM), a novel index based on histopathological differentiation and Ki-67, is proposed, and its clinical significance was evaluated. RESULTS The optimal threshold for Ki-67 was determined to be 30%. Patients with a Ki-67 expression level > 30% rather than ≤ 30% had significantly shorter 5-year overall survival (OS) and recurrence-free survival (RFS). In multivariate analysis, both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS. The GOM was used to independently stratify OS and RFS into 3 tiers, regardless of TNM stage and other established prognostic factors. The tumor-node-metastasis-GOM stage was used to stratify survival into 5 distinct tiers, and surpassed the predictive performance of TNM stage for OS and RFS. CONCLUSIONS Ki-67 is a valuable prognostic indicator for PDAC. Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.
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Affiliation(s)
- Yuexiang Liang
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
- Department of Gastrointestinal Oncology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
| | - Guannan Sheng
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Yu Guo
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Yiping Zou
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Hanhan Guo
- Department of Gastrointestinal Oncology, The First Affiliated Hospital of Hainan Medical University, Haikou 570102, China
| | - Zhifei Li
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Shaofei Chang
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
- Department of Gastrointestinal Pancreatic Surgery, Shanxi Provincial People's Hospital, Taiyuan 030012, China
| | - Quan Man
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Song Gao
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
| | - Jihui Hao
- Department of Pancreatic Cancer, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China
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Zhou L, Chen Y, Li Y, Wu C, Xue C, Wang X. Diagnostic value of radiomics in predicting Ki-67 and cytokeratin 19 expression in hepatocellular carcinoma: a systematic review and meta-analysis. Front Oncol 2024; 13:1323534. [PMID: 38234405 PMCID: PMC10792117 DOI: 10.3389/fonc.2023.1323534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Background Radiomics have been increasingly used in the clinical management of hepatocellular carcinoma (HCC), such as markers prediction. Ki-67 and cytokeratin 19 (CK-19) are important prognostic markers of HCC. Radiomics has been introduced by many researchers in the prediction of these markers expression, but its diagnostic value remains controversial. Therefore, this review aims to assess the diagnostic value of radiomics in predicting Ki-67 and CK-19 expression in HCC. Methods Original studies were systematically searched in PubMed, EMBASE, Cochrane Library, and Web of Science from inception to May 2023. All included studies were evaluated by the radiomics quality score. The C-index was used as the effect size of the performance of radiomics in predicting Ki-67and CK-19 expression, and the positive cutoff values of Ki-67 label index (LI) were determined by subgroup analysis and meta-regression. Results We identified 34 eligible studies for Ki-67 (18 studies) and CK-19 (16 studies). The most common radiomics source was magnetic resonance imaging (MRI; 25/34). The pooled C-index of MRI-based models in predicting Ki-67 was 0.89 (95% CI:0.86-0.92) in the training set, and 0.87 (95% CI: 0.82-0.92) in the validation set. The pooled C-index of MRI-based models in predicting CK-19 was 0.86 (95% CI:0.81-0.90) in the training set, and 0.79 (95% CI: 0.73-0.84) in the validation set. Subgroup analysis suggested Ki-67 LI cutoff was a significant source of heterogeneity (I 2 = 0.0% P>0.05), and meta-regression showed that the C-index increased as Ki-67 LI increased. Conclusion Radiomics shows promising diagnostic value in predicting positive Ki-67 or CK-19 expression. But lacks standardized guidelines, which makes the model and variables selection dependent on researcher experience, leading to study heterogeneity. Therefore, standardized guidelines are warranted for future research. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023427953.
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Affiliation(s)
- Lu Zhou
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yiheng Chen
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Yan Li
- Traditional Chinese Medicine (Zhong Jing) School, Henan University of Chinese Medicine, Zhengzhou, Henan, China
| | - Chaoyong Wu
- Shenzhen Hospital of Beijing University of Chinese Medicine, Shenzhen, China
| | - Chongxiang Xue
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Xihong Wang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China
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Wu Y, Ma Q, Fan L, Wu S, Wang J. An Automated Breast Volume Scanner-Based Intra- and Peritumoral Radiomics Nomogram for the Preoperative Prediction of Expression of Ki-67 in Breast Malignancy. Acad Radiol 2024; 31:93-103. [PMID: 37544789 DOI: 10.1016/j.acra.2023.07.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023]
Abstract
RATIONALE AND OBJECTIVES This study aimed to create and verify a nomogram for preoperative prediction of Ki-67 expression in breast malignancy to assist in the development of personalized treatment strategies. MATERIALS AND METHODS This retrospective study received approval from the institutional review board and included a cohort of 197 patients with breast malignancy who were admitted to our hospital. Ki-67 expression was divided into two groups based on a 14% threshold: low and high. A radiomics signature was built utilizing 1702 radiomics features based on an intra- and peritumoral (10 mm) regions of interest. Using multivariate logistic regression, radiomics signature, and ultrasound (US) characteristics, the nomogram was developed. To evaluate the model's calibration, clinical application, and predictive ability, decision curve analysis (DCA), the calibration curve, and the receiver operating characteristic curve were used, respectively. RESULTS The final nomogram included three independent predictors: tumor size (P = .037), radiomics signature (P < .001), and US-reported lymph node status (P = .018). The nomogram exhibited satisfactory performance in the training cohort, demonstrating a specificity of 0.944, a sensitivity of 0.745, and an area under the curve (AUC) of 0.905. The validation cohort recorded a specificity of 0.909, a sensitivity of 0.727, and an AUC of 0.882. The DCA showed the nomogram's clinical utility, and the calibration curve revealed a high consistency among the expected and detected values. CONCLUSION The nomogram used in this investigation can accurately predict Ki-67 expression in people with malignant breast tumors, helping to develop personalized treatment approaches.
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Affiliation(s)
- Yimin Wu
- Department of Ultrasound, WuHu Hospital, East China Normal University (The Second People's Hospital, WuHu), Wuhu, Anhui, PR China (Y.W., J.W.)
| | - Qianqing Ma
- Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, PR China (Q.M.)
| | - Lifang Fan
- Department of Medical Imaging, Wannan Medical College, Wuhu, Anhui, PR China (L.F.)
| | - Shujian Wu
- Yijishan Hospital Affiliated to Wannan Medical College, Wuhu, Anhui, PR China (S.W.)
| | - Junli Wang
- Department of Ultrasound, WuHu Hospital, East China Normal University (The Second People's Hospital, WuHu), Wuhu, Anhui, PR China (Y.W., J.W.).
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Deutsch TM, Fischer C, Riedel F, Haßdenteufel K, Michel LL, Sütterlin M, Riethdorf S, Pantel K, Wallwiener M, Schneeweiss A, Stefanovic S. Relationship of Ki-67 index in biopsies of metastatic breast cancer tissue and circulating tumor cells (CTCs) at the time of biopsy collection. Arch Gynecol Obstet 2024; 309:235-248. [PMID: 37480379 PMCID: PMC10769933 DOI: 10.1007/s00404-023-07080-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 05/11/2023] [Indexed: 07/24/2023]
Abstract
BACKGROUND The proliferation marker Ki-67 is a major pathological feature for the description of the state of disease in breast cancer. It helps to define the molecular subtype and to stratify between therapy regimens in early breast cancer and helps to assess the therapy response. Circulating tumor cells (CTCs) are a negative prognostic biomarker for progression free (PFS) and overall survival (OS) in patients with metastatic breast cancer. Therefore, the CTC count is often described as surrogate for the tumor burden. Both, decrease of Ki-67 and CTC count are considered as evidence for therapy response. The presented work analyzed the correlation between the Ki-67 indices of metastatic tissue biopsies and CTC counts in biopsy time-adjacent peripheral blood samples. PATIENTS AND METHODS Blood samples from 70 metastatic breast cancer patients were obtained before the start of a new line of systemic therapy. CTCs were enumerated using CellSearch® (Menarini Silicon Biosystems, Bologna, Italy) whereas intact CTCs (iCTCs) and non-intact or apoptotic CTCs (aCTCs) were distinguished using morphologic criteria. The proportion of cells expressing Ki-67 was evaluated using immunohistochemistry on biopsies of metastases obtained concurrently with CTC sampling before the start of a new line of systemic therapy. RESULTS 65.7% of patients had a Ki-67 index of > 25%. 28.6% of patients had ≥ 5, 47.1% ≥ 1 iCTCs. 37.1% had ≥ 5, 51.4% ≥ 1 aCTCs. No correlation was shown between Ki-67 index and iCTC and aCTC count (r = 0.05 resp. r = 0.05, Spearman's correlation index). High CTC-counts did not coincide with high Ki-67 index. High Ki-67, ≥ 5 iCTCs and aCTCs are associated with poor progression free (PFS) and overall survival (OS). CONCLUSION CTCs and Ki-67 are independent prognostic markers in metastatic breast cancer. High Ki-67 in metastatic tumor tissue is not correlated to high iCTC or aCTC counts in peripheral blood.
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Affiliation(s)
- Thomas M Deutsch
- Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany.
| | - Chiara Fischer
- Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Fabian Riedel
- Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Kathrin Haßdenteufel
- Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Laura L Michel
- National Center for Tumor Diseases, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany
| | - Marc Sütterlin
- Department of Gynecology and Obstetrics, Mannheim University Hospital, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany
| | - Sabine Riethdorf
- Institute of Tumor Biology, University Hospital Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany
| | - Klaus Pantel
- Institute of Tumor Biology, University Hospital Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany
| | - Markus Wallwiener
- Department of Obstetrics and Gynecology, University of Heidelberg, Im Neuenheimer Feld 440, 69120, Heidelberg, Germany
| | - Andreas Schneeweiss
- National Center for Tumor Diseases, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
| | - Stefan Stefanovic
- Department of Gynecology and Obstetrics, Mannheim University Hospital, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany
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Liu Y, Zhen T, Fu Y, Wang Y, He Y, Han A, Shi H. AI-Powered Segmentation of Invasive Carcinoma Regions in Breast Cancer Immunohistochemical Whole-Slide Images. Cancers (Basel) 2023; 16:167. [PMID: 38201594 PMCID: PMC10778369 DOI: 10.3390/cancers16010167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 12/24/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024] Open
Abstract
AIMS The automation of quantitative evaluation for breast immunohistochemistry (IHC) plays a crucial role in reducing the workload of pathologists and enhancing the objectivity of diagnoses. However, current methods face challenges in achieving fully automated immunohistochemistry quantification due to the complexity of segmenting the tumor area into distinct ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) regions. Moreover, the quantitative analysis of immunohistochemistry requires a specific focus on invasive carcinoma regions. METHODS AND RESULTS In this study, we propose an innovative approach to automatically identify invasive carcinoma regions in breast cancer immunohistochemistry whole-slide images (WSIs). Our method leverages a neural network that combines multi-scale morphological features with boundary features, enabling precise segmentation of invasive carcinoma regions without the need for additional H&E and P63 staining slides. In addition, we introduced an advanced semi-supervised learning algorithm, allowing efficient training of the model using unlabeled data. To evaluate the effectiveness of our approach, we constructed a dataset consisting of 618 IHC-stained WSIs from 170 cases, including four types of staining (ER, PR, HER2, and Ki-67). Notably, the model demonstrated an impressive intersection over union (IoU) score exceeding 80% on the test set. Furthermore, to ascertain the practical utility of our model in IHC quantitative evaluation, we constructed a fully automated Ki-67 scoring system based on the model's predictions. Comparative experiments convincingly demonstrated that our system exhibited high consistency with the scores given by experienced pathologists. CONCLUSIONS Our developed model excels in accurately distinguishing between DCIS and invasive carcinoma regions in breast cancer immunohistochemistry WSIs. This method paves the way for a clinically available, fully automated immunohistochemistry quantitative scoring system.
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Affiliation(s)
- Yiqing Liu
- Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China; (Y.L.); (Y.F.); (Y.W.); (Y.H.)
| | - Tiantian Zhen
- Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China;
| | - Yuqiu Fu
- Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China; (Y.L.); (Y.F.); (Y.W.); (Y.H.)
| | - Yizhi Wang
- Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China; (Y.L.); (Y.F.); (Y.W.); (Y.H.)
| | - Yonghong He
- Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China; (Y.L.); (Y.F.); (Y.W.); (Y.H.)
| | - Anjia Han
- Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China;
| | - Huijuan Shi
- Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China;
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Arora R, Alam F, Zaka-Ur-Rab A, Maheshwari V, Alam K, Hasan M. Peripheral Neutrophil to Lymphocyte Ratio (NLR), a cogent clinical adjunct for Ki-67 in breast cancer. J Egypt Natl Canc Inst 2023; 35:43. [PMID: 38143264 DOI: 10.1186/s43046-023-00200-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 11/29/2023] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND Clinical utility of Ki-67 immunohistochemistry (IHC) in breast cancer (BC) is mainly limited to decide for the use of chemotherapy and estimate prognosis in patients with either Ki-67 index < 5% or > 30%; however, lacunae still exists pertaining to its analytical validity. Neutrophilia is common in cancer with accompanying lymphocytopenia. Neutrophil to lymphocyte ratio (NLR) captures the intricate balance between pro-tumor neutrophilia and anti-tumor lymphocyte immunity. This study aimed to correlate cellular proliferation in breast cancer with NLR. METHODS An observational study was carried out including 73 cases of BC; pre-treatment NLR and Ki-67 grading were performed. NLR < 3 was considered low, while ≥ 3 was high. The Ki-67 expression was graded as low ≤ 5%, intermediate 6-29%, or high ≥ 30%. Various clinico-pathological variables were studied, and the association of categorical variables was analyzed using Pearson's chi-square test, and a p-value of < 0.05 was taken as significant. RESULTS Ki-67 correlated significantly with modified Scarff-Bloom-Richardson (SBR) grade (p < 0.01), and tumor-node-metastasis (TNM) stage (p < 0.001). Correlation of NLR was not significant with SBR grade (p > 0.05) and molecular subtype (p > 0.05); however, NLR was found to be significantly correlated with TNM stage (p < 0.001) and Ki-67 (p < 0.001). CONCLUSION NLR is fast emerging as a personalized theranostic marker in breast cancer. Instead of determining a generalized cut-off value, individual baseline NLR and its dynamics with disease progression will help manage patients better, obviating some of the drawbacks associated with Ki-67.
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Affiliation(s)
- Radhika Arora
- Department of Pathology, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, 202002, U.P, India
| | - Feroz Alam
- Department of Pathology, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, 202002, U.P, India.
| | - Atia Zaka-Ur-Rab
- Department of General Surgery, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, India
| | - Veena Maheshwari
- Department of Pathology, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, 202002, U.P, India
| | - Kiran Alam
- Department of Pathology, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, 202002, U.P, India
| | - Mahboob Hasan
- Department of Pathology, Jawaharlal Nehru Medical College, Aligarh Muslim University, Aligarh, 202002, U.P, India
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Bai L, Jiang J, Zhou J. Assessment of Ki-67 expression levels in IDH-wildtype glioblastoma using logistic regression modelling of VASARI features. Neurosurg Rev 2023; 47:20. [PMID: 38135816 DOI: 10.1007/s10143-023-02258-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/29/2023] [Accepted: 12/18/2023] [Indexed: 12/24/2023]
Abstract
To investigate the value of using VASARI signs preoperatively to assess Ki-67 proliferation index levels in patients with IDH-wildtype glioblastoma (GB).Pathological and imaging data of 154 patients with GB confirmed by surgical pathology were retrospectively analysed, and the level of Ki-67 proliferative index was assessed in tumour tissue samples from patients using immunohistochemistry (IHC) staining. Patients were divided into a high and low Ki-67 proliferation index expression group. Two radiologists analysed MRI images of patients with IDH-wildtype GB using the VASARI features system. VASARI parameters between the two groups were statistically analysed to identify characteristic parameters with significant differences and their predictive performance was determined using ROC curves.Among the obtained clinical and VASARI features of IDH-wildtype GB patients, the distribution of Maximum diameter, Proportion of necrosis and Hemorrhage was significantly different between the two groups (all p < 0.05). Multivariate logistic regression analysis showed that Maximum diameter and Hemorrhage were independent risk factors distinguishing the group with high and low expression of Ki-67 proliferative index. ROC curve analysis showed that the logistic regression model achieved an AUC value of 0.730 (95% CI: 0.639, 0.822), sensitivity of 0.628 and specificity of 0.756.Logistic regression modelling of preoperative VASARI features can be used as a reliable tool for predicting the level of Ki-67 proliferative index in IDH-wildtype GB patients, which can help in preoperative development of treatment and follow-up strategies for patients.
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Affiliation(s)
- Liangcai Bai
- Department of Radiology, The Second Hospital of Lanzhou University, Cuiyingmen No. 82, Chengguan District, Lanzhou, 730030, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
| | - Jian Jiang
- Department of Radiology, The Second Hospital of Lanzhou University, Cuiyingmen No. 82, Chengguan District, Lanzhou, 730030, China
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China
- Second Clinical School, Lanzhou University, Lanzhou, China
| | - Junlin Zhou
- Department of Radiology, The Second Hospital of Lanzhou University, Cuiyingmen No. 82, Chengguan District, Lanzhou, 730030, China.
- Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.
- Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou, China.
- Second Clinical School, Lanzhou University, Lanzhou, China.
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Hamad M, Mehana RA, Abd-Al haseeb MM, Houssen M. Potential antitumour effect of all-trans retinoic acid on regorafenib-treated human colon cancer cell lines. Contemp Oncol (Pozn) 2023; 27:198-210. [PMID: 38239861 PMCID: PMC10793621 DOI: 10.5114/wo.2023.133742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 11/12/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Colorectal cancer (CRC) is a significant contributor to cancer-related mortality worldwide, ranking as the second leading cause of such deaths. Central to the progression of this malignancy is angiogenesis - a complex process orchestrated by vascular endothelial growth factor (VEGF). Regorafenib, a potent multikinase inhibitor, acts as a critical antagonist of multiple kinases involved in angiogenesis, proliferation, and metastasis. Conversely, all-trans retinoic acid (ATRA) has demonstrated compelling antitumour effects across various cancer types. This study aims to comprehensively evaluate the combined antitumour potential of ATRA and regorafenib in human colon cancer cell lines while elucidating the intricate molecular mechanisms that underlie their action. Material and methods Our investigative approach involved an enzyme-linked immunosorbent assay to meticulously analyse the levels of key players in the VEGF signalling pathway, including VEGF itself, activated protein kinase (AMPK), extracellular signal-regulated protein kinase 1 (ERK1), and nuclear factor kappa B (NF-κB). Additionally, we assessed caspase-3 activity as a fundamental marker of apoptosis. Results The combined use of ATRA and regorafenib exhibited a remarkable augmentation in both AMPK and caspase-3 activities. This was accompanied by a significant reduction in VEGF, ERK1, and NF-κB levels within human colon cancer cell lines subjected to regorafenib treatment. Conclusions Our findings underscore the remarkable antiproliferative, antiangiogenic, and proapoptotic effects resulting from the combined use of ATRA and regorafenib in the context of CRC. This modulation of tumourigenic processes is predominantly mediated through the VEGF signalling axis.
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Affiliation(s)
- Mariam Hamad
- Biochemistry Department Faculty, Pharmacy Damanhour University, Egypt
| | - Radwa Ali Mehana
- Medical Physiology Department, Faculty of Medicine, Alexandria University, Egypt
| | | | - Maha Houssen
- Biochemistry Department Faculty, Pharmacy Damanhour University, Egypt
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Patterson KC, Miller WT, Hancock WW, Akimova T. FOXP3+ regulatory T cells are associated with the severity and prognosis of sarcoidosis. Front Immunol 2023; 14:1301991. [PMID: 38173720 PMCID: PMC10761433 DOI: 10.3389/fimmu.2023.1301991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024] Open
Abstract
Rationale Sarcoidosis is an inflammatory granulomatous disease of unknown etiology with predominant lung involvement. Organ involvement and disease severity, as well as the nature of immune alterations, vary among patients leading to a range of clinical phenotypes and outcomes. Our objective was to evaluate the association of disease course and immune responses in pulmonary sarcoidosis. Methods In this prospective cohort study of 30 subjects, most of whom were followed for one year, we evaluated 14 inflammatory markers in plasma, 13 Treg/T cell flow cytometry markers and 8 parameters of FOXP3+ Treg biology, including suppressive function, epigenetic features and stability. Results We identified a set of 13 immunological parameters that differ in sarcoidosis subjects in comparison with healthy donors. Five of those were inversely correlated with suppressive function of Tregs in sarcoidosis, and six (TNFα, TNFR I and II, sCD25, Ki-67 and number of Tregs) were particularly upregulated or increased in subjects with thoracic lymphadenopathy. Treg suppressive function was significantly lower in patients with thoracic lymphadenopathy, and in patients with higher burdens of pulmonary and systemic symptoms. A combination of five inflammatory markers, Ki-67 expression, Treg function, and lung diffusion capacity evaluated at study entry predicted need for therapy at one year follow-up in 90% of cases. Conclusion Tregs may suppress ongoing inflammation at local and systemic levels, and TNFα, TNFR I and II, sCD25 and Ki-67 emerge as attractive biomarkers for in vivo sarcoid inflammatory activity.
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Affiliation(s)
- Karen C. Patterson
- Division of Pulmonary, Allergy, and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Wallace T. Miller
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Wayne W. Hancock
- Division of Transplant Immunology, Department of Pathology and Laboratory Medicine, and Biesecker Center for Pediatric Liver Diseases, Children’s Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Tatiana Akimova
- Division of Transplant Immunology, Department of Pathology and Laboratory Medicine, and Biesecker Center for Pediatric Liver Diseases, Children’s Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Li Z, Zhang H, Wang X, Yang Y, Zhang Y, Zhuang Y, Wei Z, Yang Q, Gao E, Zhang Y, Cai S, Chen Z, Cai C, Bao J, Cheng J. Preoperative Subtyping of WHO Grade 1 Meningiomas Using a Single-Shot Ultrafast MR T2 Mapping. J Magn Reson Imaging 2023. [PMID: 38112331 DOI: 10.1002/jmri.29183] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Meningioma subtype is crucial in treatment planning and prognosis delineation, for grade 1 meningiomas. T2 relaxometry could provide detailed microscopic information but is often limited by long scanning times. PURPOSE To investigate the potential of T2 maps derived from multiple overlapping-echo detachment imaging (MOLED) for predicting meningioma subtypes and Ki-67 index, and to compare the diagnostic efficiency of two different region-of-interest (ROI) placements (whole-tumor and contrast-enhanced, respectively). STUDY TYPE Prospective. PHANTOM/SUBJECTS A phantom containing 11 tubes of MnCl2 at different concentrations, eight healthy volunteers, and 75 patients with grade 1 meningioma. FIELD STRENGTH/SEQUENCE 3 T scanner. MOLED, T2-weighted spin-echo sequence, T2-dark-fluid sequence, and postcontrast T1-weighted gradient echo sequence. ASSESSMENT Two ROIs were delineated: the whole-tumor area (ROI1) and contrast-enhanced area (ROI2). Histogram parameters were extracted from T2 maps. Meningioma subtypes and Ki-67 index were reviewed by a neuropathologist according to the 2021 classification criteria. STATISTICAL TESTS Linear regression, Bland-Altman analysis, Pearson's correlation analysis, independent t test, Mann-Whitney U test, Kruskal-Wallis test with Bonferroni correction, and multivariate logistic regression analysis with the P-value significance level of 0.05. RESULTS The MOLED T2 sequence demonstrated excellent accuracy for phantoms and volunteers (Meandiff = -1.29%, SDdiff = 1.25% and Meandiff = 0.36%, SDdiff = 2.70%, respectively), and good repeatability for volunteers (average coefficient of variance = 1.13%; intraclass correlation coefficient = 0.877). For both ROI1 and ROI2, T2 variance had the highest area under the curves (area under the ROC curve = 0.768 and 0.761, respectively) for meningioma subtyping. There was no significant difference between the two ROIs (P = 0.875). Significant correlations were observed between T2 parameters and Ki-67 index (r = 0.237-0.374). DATA CONCLUSION MOLED T2 maps can effectively differentiate between meningothelial, fibrous, and transitional meningiomas. Moreover, T2 histogram parameters were significantly correlated with the Ki-67 index. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zongye Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hongyan Zhang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yijie Yang
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Yue Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuchuan Zhuang
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Qinqin Yang
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Eryuan Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuhui Cai
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Zhong Chen
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Congbo Cai
- Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Research, Xiamen University, Xiamen, China
| | - Jianfeng Bao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Zappe K, Pühringer K, Pflug S, Berger D, Weis S, Spiegl-Kreinecker S, Cichna-Markl M. Association of MGMT Promoter and Enhancer Methylation with Genetic Variants, Clinical Parameters, and Demographic Characteristics in Glioblastoma. Cancers (Basel) 2023; 15:5777. [PMID: 38136323 PMCID: PMC10742072 DOI: 10.3390/cancers15245777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 12/24/2023] Open
Abstract
The response of glioblastoma (GBM) patients to the alkylating agent temozolomide (TMZ) vitally depends on the expression level of the repair protein O6-methylguanine-DNA methyltransferase (MGMT). Since MGMT is strongly regulated by promoter methylation, the methylation status of the MGMT promoter has emerged as a prognostic and predictive biomarker for GBM patients. By determining the methylation levels of the four enhancers located within or close to the MGMT gene, we recently found that enhancer methylation contributes to MGMT regulation. In this study, we investigated if methylation of the four enhancers is associated with SNP rs16906252, TERT promoter mutations C228T and C250T, TERT SNP rs2853669, proliferation index Ki-67, overall survival (OS), age, and sex of the patients. In general, associations with genetic variants, clinical parameters, and demographic characteristics were caused by a complex interplay of multiple CpGs in the MGMT promoter and of multiple CpGs in enhancer regions. The observed associations for intragenic enhancer 4, located in intron 2 of MGMT, differed from associations observed for the three intergenic enhancers. Some findings were restricted to subgroups of samples with either methylated or unmethylated MGMT promoters, underpinning the relevance of the MGMT promoter status in GBMs.
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Affiliation(s)
- Katja Zappe
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria; (K.Z.); (K.P.); (S.P.); (D.B.)
| | - Katharina Pühringer
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria; (K.Z.); (K.P.); (S.P.); (D.B.)
| | - Simon Pflug
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria; (K.Z.); (K.P.); (S.P.); (D.B.)
| | - Daniel Berger
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria; (K.Z.); (K.P.); (S.P.); (D.B.)
| | - Serge Weis
- Division of Neuropathology, Department of Pathology and Molecular Pathology, Kepler University Hospital GmbH, Johannes Kepler University, 4040 Linz, Austria;
| | - Sabine Spiegl-Kreinecker
- Department of Neurosurgery, Kepler University Hospital GmbH, Johannes Kepler University, 4040 Linz, Austria;
| | - Margit Cichna-Markl
- Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, 1090 Vienna, Austria; (K.Z.); (K.P.); (S.P.); (D.B.)
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Li B, Yin X, Ding X, Zhang G, Jiang H, Chen C, Guo S, Jin G. Combined utility of Ki-67 index and tumor grade to stratify patients with pancreatic ductal adenocarcinoma who underwent upfront surgery. BMC Surg 2023; 23:370. [PMID: 38066512 PMCID: PMC10704770 DOI: 10.1186/s12893-023-02256-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/02/2023] [Indexed: 12/18/2023] Open
Abstract
OBJECTIVE To investigate the prognostic prediction of a new indicator, combined by tumor grade and Ki-67, in patients with resected pancreatic ductal adenocarcinoma (PDAC). METHODS Data were retrospectively collected from consecutive patients who underwent primary resection of pancreas from December 2012 to December 2017. Tumor grade and Ki-67 were reviewed from routine pathological reports. G-Ki67 was classified as three categories as I (G1/2 and Ki-67 < 40%), II (G1/2 and Ki-67 ≥ 40%), and III(G3/4 and all Ki-67). RESULTS Cox regression analyses revealed that tumor stage (II vs. I: hazard ratio (HR), 3.781; 95% confidence index (CI), 2.844-5.025; P < 0.001; III vs. I: HR, 7.476; 95% CI, 5.481-10.20; P < 0.001) and G-Ki67 (II vs. I: HR, 1.299; 95% CI, 1.038-1.624; P = 0.022; III vs. I: HR, 1.942; 95% CI, 1.477-2.554; P < 0.001) were independent prognostic factors in the developing cohort. The result was rectified in the validation cohort. In subgroups analysis, G-Ki67 (II vs. I: HR, 1.866 ; 95% CI, 1.045-3.334; P = 0.035; III vs. I: HR, 2.333 ; 95% CI, 1.156-4.705; P = 0.018) also had a high differentiation for survival prediction. CONCLUSION Our findings indicate that three-categories of G-Ki67 in resectable PDAC according to the routine pathological descriptions provided additional prognostic information complementary to the TNM staging system.
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Affiliation(s)
- Bo Li
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China
- Department of Hepatobiliary Pancreatic Surgery, Naval Medical Center of People's Liberation Army, Naval Medical University (Second Military Medical University), 338 West Huaihai Road, Shanghai, 200052, China
| | - Xiaoyi Yin
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China
| | - Xiuwen Ding
- Clinical Research Center, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China
| | - Guoxiao Zhang
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China
| | - Hui Jiang
- Department of Pathology, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China
| | - Cuimin Chen
- Clinical Research Center, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China.
| | - Shiwei Guo
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China.
| | - Gang Jin
- Department of Hepatobiliary Pancreatic Surgery, Changhai Hospital, Naval Medical University (Second Military Medical University), 168 Changhai Road, Shanghai, 200433, China.
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Codini M, Fiorani F, Mandarano M, Cataldi S, Arcuri C, Mirarchi A, Ceccarini MR, Beccari T, Kobayashi T, Tomishige N, Sidoni A, Albi E. Sphingomyelin Metabolism Modifies Luminal A Breast Cancer Cell Line under a High Dose of Vitamin C. Int J Mol Sci 2023; 24:17263. [PMID: 38139092 PMCID: PMC10743617 DOI: 10.3390/ijms242417263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/01/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023] Open
Abstract
The role of sphingomyelin metabolism and vitamin C in cancer has been widely described with conflicting results ranging from a total absence of effect to possible preventive and/or protective effects. The aim of this study was to establish the possible involvement of sphingomyelin metabolism in the changes induced by vitamin C in breast cancer cells. The MCF7 cell line reproducing luminal A breast cancer and the MDA-MB-231 cell line reproducing triple-negative breast cancer were used. Cell phenotype was tested by estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 expression, and proliferation index percentage. Sphingomyelin was localized by an EGFP-NT-Lys fluorescent probe. Sphingomyelin metabolism was analyzed by RT-PCR, Western blotting and UFLC-MS/MS. The results showed that a high dose of vitamin C produced reduced cell viability, modulated cell cycle related genes, and changed the cell phenotype with estrogen receptor downregulation in MCF7 cell. In these cells, the catabolism of sphingomyelin was promoted with a large increase in ceramide content. No changes in viability and molecular expression were observed in MB231 cells. In conclusion, a high dose of vitamin C induces changes in the luminal A cell line involving sphingomyelin metabolism.
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Affiliation(s)
- Michela Codini
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
| | - Federico Fiorani
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
| | - Martina Mandarano
- Section of Anatomic Pathology and Histology, Department of Medicine and Surgery, University of Perugia, 06126 Perugia, Italy; (M.M.); (A.S.)
| | - Samuela Cataldi
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
| | - Cataldo Arcuri
- Section of Anatomy, Department of Medicine and Surgery, University of Perugia, 06126 Perugia, Italy; (C.A.); (A.M.)
| | - Alessandra Mirarchi
- Section of Anatomy, Department of Medicine and Surgery, University of Perugia, 06126 Perugia, Italy; (C.A.); (A.M.)
| | - Maria Rachele Ceccarini
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
| | - Tommaso Beccari
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
| | - Toshihide Kobayashi
- UMR 7021 CNRS, Faculté de Pharmacie, Universitè de Strasbourg, 67401 Illkirch, France; (T.K.); (N.T.)
- Cellular Informatics Laboratory, RIKEN, Wako 351-0198, Saitama, Japan
| | - Nario Tomishige
- UMR 7021 CNRS, Faculté de Pharmacie, Universitè de Strasbourg, 67401 Illkirch, France; (T.K.); (N.T.)
- Cellular Informatics Laboratory, RIKEN, Wako 351-0198, Saitama, Japan
| | - Angelo Sidoni
- Section of Anatomic Pathology and Histology, Department of Medicine and Surgery, University of Perugia, 06126 Perugia, Italy; (M.M.); (A.S.)
| | - Elisabetta Albi
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy; (F.F.); (S.C.); (M.R.C.); (T.B.)
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