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      Computer‐aided assessment of the chemokine receptors CXCR3, CXCR4 and CXCR7 expression in gallbladder carcinoma

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          Abstract

          Gallbladder carcinoma (GBC) is a vicious and invasive disease. The major challenge in the clinical treatment of GBC is the lack of a suitable prognosis method. Chemokine receptors such as CXCR3, CXCR4 and CXCR7 play vital roles in the process of tumour progression and metastasis. Their expression levels and distribution are proven to be indicative of the progression of GBC, but are hard to be decoded by conventional pathological methods, and therefore, not commonly used in the prognosis of GBC. In this study, we developed a computer‐aided image analysis method, which we used to quantitatively measure the expression levels of CXCR3, CXCR4 and CXCR7 in the nuclei and cytoplasm of glandular and interstitial cells from a cohort of 55 GBC patients. We found that CXCR3, CXCR4 and CXCR7 expressions are associated with the clinicopathological variables of GBC. Cytoplasmic CXCR3, nuclear CXCR7 and cytoplasmic CXCR7 were significant predictive factors of histology invasion, whereas cytoplasmic CXCR4 and nuclear CXCR4 were significantly correlated with T and N stage and were associated with the overall survival and disease‐free survival. These results suggest that the quantification and localisation of CXCR3, CXCR4 and CXCR7 expressions in different cell types should be considered using computer‐aided assessment to improve the accuracy of prognosis in GBC.

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          The role of CXC chemokines and their receptors in cancer.

          Chemokines, or chemotactic cytokines, and their receptors have been discovered as essential and selective mediators in leukocyte migration to inflammatory sites and to secondary lymphoid organs. Besides their functions in the immune system, they also play a critical role in tumor initiation, promotion and progression. There are four subgroups of chemokines: CXC, CC, CX(3)C, and C chemokine ligands. The CXC or alpha subgroup is further subdivided in the ELR(+) and ELR(-) chemokines. Members that contain the ELR motif bind to CXC chemokine receptor 2 (CXCR2) and are angiogenic. In contrast, most of the CXC chemokines without ELR motif bind to CXCR3 and are angiostatic. An exception is the angiogenic ELR(-)CXC chemokine stromal cell-derived factor-1 (CXCL12/SDF-1), which binds to CXCR4 and CXCR7 and is implicated in tumor metastasis. This review is focusing on the role of CXC chemokines and their receptors in tumorigenesis, including angiogenesis, attraction of leukocytes to tumor sites and induction of tumor cell migration and homing in metastatic sites. Finally, their therapeutic use in cancer treatment is discussed.
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            ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67

            Introduction Accurate assessment of estrogen receptor (ER), progesterone receptor (PR), and Ki-67 is essential in the histopathologic diagnostics of breast cancer. Commercially available image analysis systems are usually bundled with dedicated analysis hardware and, to our knowledge, no easily installable, free software for immunostained slide scoring has been described. In this study, we describe a free, Internet-based web application for quantitative image analysis of ER, PR, and Ki-67 immunohistochemistry in breast cancer tissue sections. Methods The application, named ImmunoRatio, calculates the percentage of positively stained nuclear area (labeling index) by using a color deconvolution algorithm for separating the staining components (diaminobenzidine and hematoxylin) and adaptive thresholding for nuclear area segmentation. ImmunoRatio was calibrated using cell counts defined visually as the gold standard (training set, n = 50). Validation was done using a separate set of 50 ER, PR, and Ki-67 stained slides (test set, n = 50). In addition, Ki-67 labeling indexes determined by ImmunoRatio were studied for their prognostic value in a retrospective cohort of 123 breast cancer patients. Results The labeling indexes by calibrated ImmunoRatio analyses correlated well with those defined visually in the test set (correlation coefficient r = 0.98). Using the median Ki-67 labeling index (20%) as a cutoff, a hazard ratio of 2.2 was obtained in the survival analysis (n = 123, P = 0.01). ImmunoRatio was shown to adapt to various staining protocols, microscope setups, digital camera models, and image acquisition settings. The application can be used directly with web browsers running on modern operating systems (e.g., Microsoft Windows, Linux distributions, and Mac OS). No software downloads or installations are required. ImmunoRatio is open source software, and the web application is publicly accessible on our website. Conclusions We anticipate that free web applications, such as ImmunoRatio, will make the quantitative image analysis of ER, PR, and Ki-67 easy and straightforward in the diagnostic assessment of breast cancer specimens.
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              CXCR4 over-expression and survival in cancer: A system review and meta-analysis

              C-X-C chemokine receptor 4 (CXCR4) is frequently over-expressed in various types of cancer; many agents against CXCR4 are in clinical development currently despite variable data for the prognostic impact of CXCR4 expression. Here eighty-five studies with a total of 11,032 subjects were included to explore the association between CXCR4 and progression-free survival (PFS) or overall survival (OS) in subjects with cancer. Pooled analysis shows that CXCR4 over-expression is significantly associated with poorer PFS (HR 2.04; 95% CI, 1.72-2.42) and OS (HR=1.94; 95% CI, 1.71-2.20) irrespective of cancer types. Subgroup analysis indicates significant association between CXCR4 and shorter PFS in hematological malignancy, breast cancer, colorectal cancer, esophageal cancer, renal cancer, gynecologic cancer, pancreatic cancer and liver cancer; the prognostic effects remained consistent across age, risk of bias, levels of adjustment, median follow-up period, geographical area, detection methods, publication year and size of studies. CXCR4 over-expression predicts unfavorable OS in hematological malignancy, breast cancer, colorectal cancer, esophageal cancer, head and neck cancer, renal cancer, lung cancer, gynecologic cancer, liver cancer, prostate cancer and gallbladder cancer; these effects were independence of age, levels of adjustment, publication year, detection methods and follow-up period. In conclusion, CXCR4 over-expression is associated with poor prognosis in cancer.
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                Author and article information

                Contributors
                liuyingbin@xinhuamed.com.cn
                lisheng_1996@163.com
                Journal
                J Cell Mol Med
                J. Cell. Mol. Med
                10.1111/(ISSN)1582-4934
                JCMM
                Journal of Cellular and Molecular Medicine
                John Wiley and Sons Inc. (Hoboken )
                1582-1838
                1582-4934
                08 June 2020
                July 2020
                : 24
                : 13 ( doiID: 10.1111/jcmm.v24.13 )
                : 7670-7674
                Affiliations
                [ 1 ] Department of Pathology and Forensic Medicine Dalian Medical University Dalian China
                [ 2 ] Department of General Surgery School of Medicine Xinhua Hospital Shanghai JiaoTong University Shanghai China
                [ 3 ] Institute of Biliary Tract Diseases Research Shanghai JiaoTong University School of Medicine Shanghai China
                [ 4 ] Invitrocue Pte Ltd. Singapore City Singapore
                [ 5 ] Department of Radiology Sun Yat‐sen University Cancer Center Guangzhou China
                [ 6 ] Department of Urology the second Affiliated Hospital of Dalian Medical University Dalian China
                [ 7 ] Department of Gastrointestinal Surgery Xu Zhou Center Hospital Affiliated to Medical College of Southeast University Jiangsu China
                [ 8 ] National-Local Engineering Research Center for Drug Research and Development (R&D) of Neurodegenerative Diesases Department of Biochemistry Dalian Medical University Dalian China
                Author notes
                [*] [* ] Correspondence

                Sheng Li, Department of Biochemistry, National‐Local Joint Engineering Research Center for Drug‐Research and Development (R&D) of Neurodegenerative Diseases, Dalian Medical University, Lvshun South Road 9, Dalian 116044, China.

                Email: lisheng_1996@ 123456163.com

                Author information
                https://orcid.org/0000-0002-1933-5981
                https://orcid.org/0000-0002-8297-8007
                Article
                JCMM15219
                10.1111/jcmm.15219
                7339221
                32512633
                8866a41b-2ecc-4529-aa65-018042236191
                © 2020 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 February 2019
                : 30 January 2020
                : 06 March 2020
                Page count
                Figures: 2, Tables: 0, Pages: 5, Words: 2538
                Funding
                Funded by: LiaoNing Revitalization Talents Program
                Award ID: XLYC1808031
                Funded by: International S&T Cooperation Program of China
                Award ID: 2013DFA11150
                Funded by: Clinical Research Plan of Shanghai Hospital Development Center
                Award ID: 16CR3037A
                Categories
                Short Communication
                Short Communications
                Custom metadata
                2.0
                July 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.5 mode:remove_FC converted:07.07.2020

                Molecular medicine
                computer‐aided,cxcr3,cxcr4,cxcr7,gallbladder cancer,quantitative assessment
                Molecular medicine
                computer‐aided, cxcr3, cxcr4, cxcr7, gallbladder cancer, quantitative assessment

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