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Balikó A, Szakács Z, Kajtár B, Ritter Z, Gyenesei A, Farkas N, Kereskai L, Vályi-Nagy I, Alizadeh H, Pajor L. Clinicopathological analysis of diffuse large B-cell lymphoma using molecular biomarkers: a retrospective analysis from 7 Hungarian centers. Front Oncol 2023; 13:1224733. [PMID: 37746254 PMCID: PMC10514474 DOI: 10.3389/fonc.2023.1224733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 08/21/2023] [Indexed: 09/26/2023] Open
Abstract
Background The clinical and genetic heterogeneity of diffuse large B-cell lymphoma (DLBCL) presents distinct challenges in predicting response to therapy and overall prognosis. The main objective of this study was to assess the application of the immunohistochemistry- and interphase fluorescence in situ hybridization (FISH)-based molecular markers in the diagnosis of DLBCL and its prognostic value in patients treated with rituximab-based immunochemotherapy. Methods This is a multicenter, retrospective study, which analyzed data from 7 Hungarian hematology centers. Eligible patients were adults, had a histologically confirmed diagnosis of DLBCL, were treated with rituximab-based immunochemotherapy in the first line, and had available clinicopathological data including International Prognostic Index (IPI). On the specimens, immunohistochemistry and FISH methods were performed. Germinal center B-cell like (GCB) and non-GCB subtypes were classified by the Hans algorithm. Outcomes included overall survival (OS), event-free survival (EFS), and EFS at 2 years (EFS24). For survival analysis, we used Kaplan-Meier curves with the log-rank test and multivariate Cox regression. Results A total of 247 DLBCL cases were included. Cases were positive for MYC, BCL2, BCL6, and MUM1 expression in 52.1%, 66.2%, 72.6%, and 77.8%, respectively. BCL6 translocation, BCL2 gene copy number (GCN) gain, IGH::MYC translocation, MYC GCN gain, IGH::BCL2 translocation, and BCL6 GCN gain were detected in 21.4%, 14.1%, 7.3%, 1.8%, 7.3%, and 0.9%, respectively. At a median follow-up of 52 months, 140 patients (56.7%) had disease progression or relapse. The Kaplan-Meier estimate for EFS24 was 56.2% (CI: 50.4-62.8%). In univariate analysis, only IPI and BCL6 expression were significant predictors of both OS and EFS, whereas MUM1 predicted EFS only. In multivariate analysis, the IPI score was a significant independent negative, whereas MIB-1 and BCL6 protein expressions were significant independent positive predictors of both OS and EFS. Conclusion In our study, we found that only IPI, BCL6 protein expression and MIB-1 protein expression are independent predictors of survival outcomes in DLBCL. We did not find any difference in survival by GCB vs. non-GCB subtypes. These findings may improve prognostication in DLBCL and can contribute to designing further research in the area.
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Affiliation(s)
- Anett Balikó
- Tolna County Balassa János Hospital, Szekszárd, ;Hungary
- PhD Doctoral School – Interdisciplinary Medical Sciences (D93), Medical School, University of Pécs, Pécs, ;Hungary
| | - Zsolt Szakács
- First Department of Medicine, Medical School, University of Pécs, Pécs, ;Hungary
| | - Béla Kajtár
- Department of Pathology, Medical School, University of Pécs, Pécs, ;Hungary
| | - Zsombor Ritter
- Department of Medical Imaging, Medical School, University of Pécs, Pécs, ;Hungary
| | - Attila Gyenesei
- Szentágothai Research Centre, University of Pécs, Pécs, ;Hungary
| | - Nelli Farkas
- Institute of Bioanalysis, Medical School, University of Pécs, Pécs, ;Hungary
| | - László Kereskai
- Department of Pathology, Medical School, University of Pécs, Pécs, ;Hungary
| | - István Vályi-Nagy
- South-Pest Hospital Centre – National Institute for Infectology and Haematology, Budapest, ;Hungary
| | - Hussain Alizadeh
- First Department of Medicine, Medical School, University of Pécs, Pécs, ;Hungary
| | - László Pajor
- Department of Pathology, Medical School, University of Pécs, Pécs, ;Hungary
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2
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Macintyre G, Piskorz AM, Berman A, Ross E, Morse DB, Yuan K, Ennis D, Pike JA, Goranova T, McNeish IA, Brenton JD, Markowetz F. FrenchFISH: Poisson Models for Quantifying DNA Copy Number From Fluorescence In Situ Hybridization of Tissue Sections. JCO Clin Cancer Inform 2021; 5:176-186. [PMID: 33570999 PMCID: PMC8140799 DOI: 10.1200/cci.20.00075] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 10/16/2020] [Accepted: 11/16/2020] [Indexed: 12/12/2022] Open
Abstract
PURPOSE Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. The gold standard for detecting copy number changes in tumor cells is fluorescence in situ hybridization (FISH) using locus-specific probes that are imaged as fluorescent spots. However, spot counting often does not perform well on solid tumor tissue sections due to partially represented or overlapping nuclei. MATERIALS AND METHODS To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes or a homogeneous Poisson point process model for automated spot counting. RESULTS We benchmarked the performance of FrenchFISH against previous approaches using a controlled simulation scenario and tested it experimentally in 12 ovarian carcinoma FFPE-tissue sections for copy number alterations at three loci (c-Myc, hTERC, and SE7). FrenchFISH outperformed standard spot counting with 74% of the automated counts having < 1 copy number difference from the manual counts and 17% having < 2 copy number differences, while taking less than one third of the time of manual counting. CONCLUSION FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue by both speeding up and improving the accuracy of spot count estimates.
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Affiliation(s)
- Geoff Macintyre
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Anna M. Piskorz
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Adam Berman
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Edith Ross
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - David B. Morse
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, UK
| | - Ke Yuan
- University of Glasgow, Glasgow, UK
| | - Darren Ennis
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
- Department of Surgery and Cancer, Imperial College London, UK
| | - Jeremy A. Pike
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Centre of Membrane Proteins and Receptors (COMPARE), Universities of Birmingham and Nottingham, UK
| | - Teodora Goranova
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Iain A. McNeish
- Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
- Department of Surgery and Cancer, Imperial College London, UK
| | - James D. Brenton
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Florian Markowetz
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
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Höfener H, Homeyer A, Förster M, Drieschner N, Schildhaus HU, Hahn HK. Automated density-based counting of FISH amplification signals for HER2 status assessment. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 173:77-85. [PMID: 31046998 DOI: 10.1016/j.cmpb.2019.03.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/14/2019] [Accepted: 03/13/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Automated image analysis can make quantification of FISH signals in histological sections more efficient and reproducible. Current detection-based methods, however, often fail to accurately quantify densely clustered FISH signals. METHODS We propose a novel density-based approach to quantifying FISH signals. Instead of detecting individual signals, this approach quantifies FISH signals in terms of the integral over a density map predicted by Deep Learning. We apply the density-based approach to the task of counting and determining ratios of ERBB2 and CEN17 signals and compare it to common detection-based and area-based approaches. RESULTS The ratios determined by our approach were strongly correlated with results obtained by manual annotation of individual FISH signals (Pearson's r = 0.907). In addition, they were highly consistent with cutoff-scores determined by a pathologist (balanced concordance = 0.971). The density-based approach generally outperformed the other approaches. Its superiority was particularly evident in the presence of dense signal clusters. CONCLUSIONS The presented approach enables accurate and efficient automated quantification of FISH signals. Since signals in clusters can hardly be detected individually even by human observers, the density-based quantification performs better than detection-based approaches.
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Affiliation(s)
| | - André Homeyer
- Fraunhofer MEVIS, Am Fallturm 1, 28359 Bremen, Germany.
| | | | | | - Hans-Ulrich Schildhaus
- Institute of Pathology, University Hospital Göttingen, Robert-Koch-Straße 40, 37075 Göttingen, Germany; Institute of Pathology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
| | - Horst K Hahn
- Fraunhofer MEVIS, Am Fallturm 1, 28359 Bremen, Germany; Jacobs University, Campus Ring 1, 28759 Bremen, Germany.
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4
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Merkel D, Soffer S, Novikov I, Avigdor A, Amariglio N, Nagler A, Trakhtenbrot L. Is fluorescence in-situ hybridization sufficient in patients with myelodysplastic syndromes and insufficient cytogenetic testing? Leuk Lymphoma 2018; 60:764-771. [PMID: 30187812 DOI: 10.1080/10428194.2018.1493729] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Chromosome banding analysis (CBA) in myelodysplastic syndromes (MDS) remains the 'gold standard' for identification of chromosomal abnormalities, while interphase fluorescence in-situ hybridization (I-FISH) is mainly used to complement CBA. This study, retrospectively, evaluated CBA and I-FISH results in 600 patients with suspected MDS and determined the effect of CBA/FISH reallocation on IPSS-R. Our result demonstrated that in 7/586 (1.2%) patients with satisfactory karyotype, I-FISH provided additional information. In 25/453 (5.5%) of the patients with normal I-FISH, CBA detected chromosomal abnormalities, and in 68/147 (46%) of the patients with abnormal I-FISH, CBA detected additional chromosomal aberrations. When 5q- aberration was alone or accompanied by additional abnormalities by I-FISH, CBA revealed a complex karyotype (16/25;64%, 35/43;81%, respectively). Our results suggest that in cases of karyotype failure, if I-FISH is used alone, patients are at risk of being misclassified into the wrong cytogenetic risk groups and a repeat sample for CBA should be attempted.
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Affiliation(s)
- Drorit Merkel
- a Division of Hematology , Chaim Sheba Medical Center, Tel Hashomer , Ramat Gan , Israel.,b Sackler School of Medicine , Tel Aviv University , Tel Aviv , Israel
| | - Shelly Soffer
- b Sackler School of Medicine , Tel Aviv University , Tel Aviv , Israel
| | - Iliya Novikov
- c Biostatistical Unit , Gertner Institute of Epidemiology and Health Policy Research , Ramat Gan , Israel
| | - Abraham Avigdor
- a Division of Hematology , Chaim Sheba Medical Center, Tel Hashomer , Ramat Gan , Israel.,b Sackler School of Medicine , Tel Aviv University , Tel Aviv , Israel
| | - Ninette Amariglio
- d Hematology Laboratory , Cancer Research Center, Sheba Medical Center , Ramat Gan , Israel
| | - Arnon Nagler
- a Division of Hematology , Chaim Sheba Medical Center, Tel Hashomer , Ramat Gan , Israel.,b Sackler School of Medicine , Tel Aviv University , Tel Aviv , Israel
| | - Luba Trakhtenbrot
- d Hematology Laboratory , Cancer Research Center, Sheba Medical Center , Ramat Gan , Israel
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Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice. Sci Rep 2018; 8:12108. [PMID: 30108260 PMCID: PMC6092416 DOI: 10.1038/s41598-018-30557-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Accepted: 08/01/2018] [Indexed: 11/08/2022] Open
Abstract
Homologous recombination (HR) events are key drivers of cancer-promoting mutations, and the ability to visualize these events in situ provides important information regarding mutant cell type, location, and clonal expansion. We have previously created the Rosa26 Direct Repeat (RaDR) mouse model wherein HR at an integrated substrate gives rise to a fluorescent cell. To fully leverage this in situ approach, we need better ways to quantify rare fluorescent cells deep within tissues. Here, we present a robust, automated event quantification algorithm that uses image intensity and gradient features to detect fluorescent cells in deep tissue specimens. To analyze the performance of our algorithm, we simulate fluorescence behavior in tissue using Monte Carlo methods. Importantly, this approach reduces the potential for bias in manual counting and enables quantification of samples with highly dense HR events. Using this approach, we measured the relative frequency of HR within a chromosome and between chromosomes and found that HR within a chromosome is more frequent, which is consistent with the close proximity of sister chromatids. Our approach is both objective and highly rapid, providing a powerful tool, not only to researchers interested in HR, but also to many other researchers who are similarly using fluorescence as a marker for understanding mammalian biology in tissues.
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Smuk G, Tornóczky T, Pajor L, Chudoba I, Kajtár B, Sárosi V, Pajor G. Immense random colocalization, revealed by automated high content image cytometry, seriously questions FISH as gold standard for detecting EML4-ALK fusion. Cytometry A 2018; 93:653-661. [DOI: 10.1002/cyto.a.23489] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 02/23/2018] [Accepted: 04/13/2018] [Indexed: 01/27/2023]
Affiliation(s)
- Gábor Smuk
- Department of Pathology; University of Pécs Medical School; Hungary
| | - Tamás Tornóczky
- Department of Pathology; University of Pécs Medical School; Hungary
| | - László Pajor
- Department of Pathology; University of Pécs Medical School; Hungary
| | | | - Béla Kajtár
- Department of Pathology; University of Pécs Medical School; Hungary
| | - Veronika Sárosi
- Department of Internal Medicine; University of Pécs Medical School; Hungary
| | - Gábor Pajor
- Department of Pathology; University of Pécs Medical School; Hungary
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Reljin N, Slavkovic-Ilic M, Tapia C, Cihoric N, Stankovic S. Multifractal-based nuclei segmentation in fish images. Biomed Microdevices 2018; 19:67. [PMID: 28776236 PMCID: PMC5543204 DOI: 10.1007/s10544-017-0208-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.
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Affiliation(s)
- Nikola Reljin
- Academic Technology Services, Princeton University, Princeton, NJ USA
| | - Marijeta Slavkovic-Ilic
- Innovation Center of the School of Electrical Engineering, University of Belgrade, Belgrade, Serbia
| | - Coya Tapia
- Division of Clinical Pathology, Institute of Pathology, University of Bern, Bern, Switzerland
| | - Nikola Cihoric
- Department of Radiation Oncology, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Srdjan Stankovic
- School of Electrical Engineering, University of Belgrade, Belgrade, Serbia
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8
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Automated Image Analysis of HER2 Fluorescence In Situ Hybridization to Refine Definitions of Genetic Heterogeneity in Breast Cancer Tissue. BIOMED RESEARCH INTERNATIONAL 2017; 2017:2321916. [PMID: 28752092 PMCID: PMC5511668 DOI: 10.1155/2017/2321916] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Revised: 03/20/2017] [Accepted: 04/26/2017] [Indexed: 12/15/2022]
Abstract
Human epidermal growth factor receptor 2 gene- (HER2-) targeted therapy for breast cancer relies primarily on HER2 overexpression established by immunohistochemistry (IHC) with borderline cases being further tested for amplification by fluorescence in situ hybridization (FISH). Manual interpretation of HER2 FISH is based on a limited number of cells and rather complex definitions of equivocal, polysomic, and genetically heterogeneous (GH) cases. Image analysis (IA) can extract high-capacity data and potentially improve HER2 testing in borderline cases. We investigated statistically derived indicators of HER2 heterogeneity in HER2 FISH data obtained by automated IA of 50 IHC borderline (2+) cases of invasive ductal breast carcinoma. Overall, IA significantly underestimated the conventional HER2, CEP17 counts, and HER2/CEP17 ratio; however, it collected more amplified cells in some cases below the lower limit of GH definition by manual procedure. Indicators for amplification, polysomy, and bimodality were extracted by factor analysis and allowed clustering of the tumors into amplified, nonamplified, and equivocal/polysomy categories. The bimodality indicator provided independent cell diversity characteristics for all clusters. Tumors classified as bimodal only partially coincided with the conventional GH heterogeneity category. We conclude that automated high-capacity nonselective tumor cell assay can generate evidence-based HER2 intratumor heterogeneity indicators to refine GH definitions.
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Du Q, Li Q, Sun D, Chen X, Yu B, Ying Y. Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models. Cytometry A 2015; 89:239-45. [PMID: 26580488 DOI: 10.1002/cyto.a.22797] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 07/05/2015] [Accepted: 10/23/2015] [Indexed: 02/01/2023]
Abstract
Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff.
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Affiliation(s)
- Qinghua Du
- Department of Hematology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Qingshan Li
- Department of Hematology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Daochun Sun
- School of Mathematics Science, South China Normal University, Guangzhou, China
| | - Xiaoyan Chen
- Department of Hematology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Bizhen Yu
- Department of Hematology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Yi Ying
- Department of Hematology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
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10
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van der Logt EMJ, Kuperus DAJ, van Setten JW, van den Heuvel MC, Boers JE, Schuuring E, Kibbelaar RE. Fully automated fluorescent in situ hybridization (FISH) staining and digital analysis of HER2 in breast cancer: a validation study. PLoS One 2015; 10:e0123201. [PMID: 25844540 PMCID: PMC4386817 DOI: 10.1371/journal.pone.0123201] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2014] [Accepted: 02/19/2015] [Indexed: 01/31/2023] Open
Abstract
HER2 assessment is routinely used to select patients with invasive breast cancer that might benefit from HER2-targeted therapy. The aim of this study was to validate a fully automated in situ hybridization (ISH) procedure that combines the automated Leica HER2 fluorescent ISH system for Bond with supervised automated analysis with the Visia imaging D-Sight digital imaging platform. HER2 assessment was performed on 328 formalin-fixed/paraffin-embedded invasive breast cancer tumors on tissue microarrays (TMA) and 100 (50 selected IHC 2+ and 50 random IHC scores) full-sized slides of resections/biopsies obtained for diagnostic purposes previously. For digital analysis slides were pre-screened at 20x and 100x magnification for all fluorescent signals and supervised-automated scoring was performed on at least two pictures (in total at least 20 nuclei were counted) with the D-Sight HER2 FISH analysis module by two observers independently. Results were compared to data obtained previously with the manual Abbott FISH test. The overall agreement with Abbott FISH data among TMA samples and 50 selected IHC 2+ cases was 98.8% (κ = 0.94) and 93.8% (κ = 0.88), respectively. The results of 50 additionally tested unselected IHC cases were concordant with previously obtained IHC and/or FISH data. The combination of the Leica FISH system with the D-Sight digital imaging platform is a feasible method for HER2 assessment in routine clinical practice for patients with invasive breast cancer.
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Affiliation(s)
- Elise M. J. van der Logt
- Department of Pathology, Pathology Friesland, Leeuwarden, The Netherlands
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- * E-mail:
| | | | - Jan W. van Setten
- Department of Pathology, Pathology Friesland, Leeuwarden, The Netherlands
| | | | - James. E. Boers
- Department of Pathology, Isala Klinieken, Zwolle, The Netherlands
| | - Ed Schuuring
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Robby E. Kibbelaar
- Department of Pathology, Pathology Friesland, Leeuwarden, The Netherlands
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Al-Jafar HA, Al-Mulla A, AlDallal S, Buhamad JH, Askar H. Successful nilotinib treatment in a child with chronic myeloid leukemia. Case Rep Oncol 2015; 8:122-7. [PMID: 25873877 PMCID: PMC4376925 DOI: 10.1159/000380905] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
A 16-year-old female was diagnosed incedentally with chronic myeloid leukemia (CML) in the chronic phase. She showed complete remission after 3 months of nilotinib treatment. CML is a rare malignant neoplasm in pediatric age. It is characterized by a Philadelphia chromosome, which comes from a genetic translocation between chromosomes 9 and 22. This translocation results in an abnormal fusion called BCR-ABL oncogene which encodes a chimeric BCR-ABL protein. This protein is the underlying cause of CML. Nilotinib is a newly licensed drug for CML in adults. Structurally, it is similar to imatinib (the older tyrosine kinase inhibitor), but it is much more potent in inhibiting BCR-ABL due to its much increased affinity for its binding site. Specific guidelines for CML treatment in children have yet to be determined. In our patient, nilotinib was used as an off-label drug because it is not licensed for children. According to the pharmacokinetic response to drugs, children cannot be considered small adults irrespective of their weight. Off-label drug use based on evidence that it is the best treatment available is an important tool in the hands of expert treating physicians.
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Affiliation(s)
| | - Ali Al-Mulla
- Leukemia Center, Sabah Hospital, Shuwaikh, Kuwait
| | | | | | - Haifa Askar
- Amiri Hospital, Kuwait City, Shuwaikh, Kuwait
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12
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Caria P, Vanni R. FISH molecular testing in cytological preparations from solid tumors. Mol Cytogenet 2014; 7:56. [PMID: 25478010 PMCID: PMC4255722 DOI: 10.1186/s13039-014-0056-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Accepted: 07/30/2014] [Indexed: 11/10/2022] Open
Abstract
Many of the exciting new developments in solid tumor molecular cytogenetics impact classical and molecular pathology. Fluorescence in situ hybridization to identify specific DNA target sequences in nuclei of non-dividing cells in solid neoplasms has contributed to the integration of molecular cytogenetics into cytology in spite of the remarkable promiscuity of cancer genes. Indeed, although it is a low-throughput assay, fluorescence in situ hybridization enables the direct disclosure and localization of genetic markers in single nuclei. Gene fusions are among the most prominent genetic alterations in cancer, providing markers that may be determinant in needle biopsies that are negative or suspicious for malignancy, and may contribute to the correct classification of the tumors. In view of the expanding use of fluorescence in situ hybridization in cytology, future challenges include automated sample evaluation and the specification of common criteria for interpreting and reporting results.
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Affiliation(s)
- Paola Caria
- Department of Biomedical Sciences, University of Cagliari – Cittadella Universitaria, 09042 Monserrato (CA), Cagliari, Italy
| | - Roberta Vanni
- Department of Biomedical Sciences, University of Cagliari – Cittadella Universitaria, 09042 Monserrato (CA), Cagliari, Italy
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