1
|
Homeyer A, Geißler C, Schwen LO, Zakrzewski F, Evans T, Strohmenger K, Westphal M, Bülow RD, Kargl M, Karjauv A, Munné-Bertran I, Retzlaff CO, Romero-López A, Sołtysiński T, Plass M, Carvalho R, Steinbach P, Lan YC, Bouteldja N, Haber D, Rojas-Carulla M, Vafaei Sadr A, Kraft M, Krüger D, Fick R, Lang T, Boor P, Müller H, Hufnagl P, Zerbe N. Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology. Mod Pathol 2022; 35:1759-1769. [PMID: 36088478 PMCID: PMC9708586 DOI: 10.1038/s41379-022-01147-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 07/24/2022] [Accepted: 07/25/2022] [Indexed: 12/24/2022]
Abstract
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance and obtain regulatory approval. This assessment requires appropriate test datasets. However, compiling such datasets is challenging and specific recommendations are missing. A committee of various stakeholders, including commercial AI developers, pathologists, and researchers, discussed key aspects and conducted extensive literature reviews on test datasets in pathology. Here, we summarize the results and derive general recommendations on compiling test datasets. We address several questions: Which and how many images are needed? How to deal with low-prevalence subsets? How can potential bias be detected? How should datasets be reported? What are the regulatory requirements in different countries? The recommendations are intended to help AI developers demonstrate the utility of their products and to help pathologists and regulatory agencies verify reported performance measures. Further research is needed to formulate criteria for sufficiently representative test datasets so that AI solutions can operate with less user intervention and better support diagnostic workflows in the future.
Collapse
Affiliation(s)
- André Homeyer
- Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359, Bremen, Germany.
| | - Christian Geißler
- grid.6734.60000 0001 2292 8254Technische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, Germany
| | - Lars Ole Schwen
- grid.428590.20000 0004 0496 8246Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359 Bremen, Germany
| | - Falk Zakrzewski
- grid.412282.f0000 0001 1091 2917Institute of Pathology, Carl Gustav Carus University Hospital Dresden (UKD), TU Dresden (TUD), Fetscherstrasse 74, 01307 Dresden, Germany
| | - Theodore Evans
- grid.6734.60000 0001 2292 8254Technische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, Germany
| | - Klaus Strohmenger
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Max Westphal
- grid.428590.20000 0004 0496 8246Fraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359 Bremen, Germany
| | - Roman David Bülow
- grid.412301.50000 0000 8653 1507Institute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Michaela Kargl
- grid.11598.340000 0000 8988 2476Medical University of Graz, Diagnostic and Research Center for Molecular BioMedicine, Diagnostic & Research Institute of Pathology, Neue Stiftingtalstrasse 6, 8010 Graz, Austria
| | - Aray Karjauv
- grid.6734.60000 0001 2292 8254Technische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, Germany
| | - Isidre Munné-Bertran
- MoticEurope, S.L.U., C. Les Corts, 12 Poligono Industrial, 08349 Barcelona, Spain
| | - Carl Orge Retzlaff
- grid.6734.60000 0001 2292 8254Technische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, Germany
| | | | | | - Markus Plass
- grid.11598.340000 0000 8988 2476Medical University of Graz, Diagnostic and Research Center for Molecular BioMedicine, Diagnostic & Research Institute of Pathology, Neue Stiftingtalstrasse 6, 8010 Graz, Austria
| | - Rita Carvalho
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Peter Steinbach
- grid.40602.300000 0001 2158 0612Helmholtz-Zentrum Dresden Rossendorf, Bautzner Landstraße 400, 01328 Dresden, Germany
| | - Yu-Chia Lan
- grid.412301.50000 0000 8653 1507Institute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Nassim Bouteldja
- grid.412301.50000 0000 8653 1507Institute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany
| | - David Haber
- Lakera AI AG, Zelgstrasse 7, 8003 Zürich, Switzerland
| | | | - Alireza Vafaei Sadr
- grid.412301.50000 0000 8653 1507Institute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany
| | | | - Daniel Krüger
- grid.474385.90000 0004 4676 7928Olympus Soft Imaging Solutions GmbH, Johann-Krane-Weg 39, 48149 Münster, Germany
| | - Rutger Fick
- Tribun Health, 2 Rue du Capitaine Scott, 75015 Paris, France
| | - Tobias Lang
- Mindpeak GmbH, Zirkusweg 2, 20359 Hamburg, Germany
| | - Peter Boor
- grid.412301.50000 0000 8653 1507Institute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Heimo Müller
- grid.11598.340000 0000 8988 2476Medical University of Graz, Diagnostic and Research Center for Molecular BioMedicine, Diagnostic & Research Institute of Pathology, Neue Stiftingtalstrasse 6, 8010 Graz, Austria
| | - Peter Hufnagl
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| | - Norman Zerbe
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany
| |
Collapse
|
2
|
Ku J, Kim R, Kim D, Kim D, Song S, Lee K, Lee N, Kim M, Yoon SS, Kwon NH, Kim S, Kim Y, Koh Y. Single-cell analysis of AIMP2 splice variants informs on drug sensitivity and prognosis in hematologic cancer. Commun Biol 2020; 3:630. [PMID: 33128014 PMCID: PMC7599330 DOI: 10.1038/s42003-020-01353-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 09/22/2020] [Indexed: 11/21/2022] Open
Abstract
Aminoacyl-tRNA synthetase-interacting multifunctional protein 2 (AIMP2) is a non-enzymatic component required for the multi-tRNA synthetase complex. While exon 2 skipping alternatively spliced variant of AIMP2 (AIMP2-DX2) compromises AIMP2 activity and is associated with carcinogenesis, its clinical potential awaits further validation. Here, we found that AIMP2-DX2/AIMP2 expression ratio is strongly correlated with major cancer signaling pathways and poor prognosis, particularly in acute myeloid leukemia (AML). Analysis of a clinical patient cohort revealed that AIMP2-DX2 positive AML patients show decreased overall survival and progression-free survival. We also developed targeted RNA-sequencing and single-molecule RNA-FISH tools to quantitatively analyze AIMP2-DX2/AIMP2 ratios at the single-cell level. By subclassifying hematologic cancer cells based on their AIMP2-DX2/AIMP2 ratios, we found that downregulating AIMP2-DX2 sensitizes cells to anticancer drugs only for a subgroup of cells while it has adverse effects on others. Collectively, our study establishes AIMP2-DX2 as a potential biomarker and a therapeutic target for hematologic cancer. Ku, Kim et al develop a method to analyse the ratio of the alternatively spliced variant of AIMP2 to full length AIMP via single-molecule RNA-FISH. They can subclassify hematologic cancer based on AIMP2-DX2/AIMP2 ratio and find that cells with high AIMP2-DX2 ratio can be sensitized to chemotherapy drugs by depleting AIMP2-DX2.
Collapse
Affiliation(s)
- Jayoung Ku
- Department of Chemical and Biomolecular Engineering and KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Ryul Kim
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dongchan Kim
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Daeyoon Kim
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seulki Song
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Keonyong Lee
- Department of Chemical and Biomolecular Engineering and KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Namseok Lee
- Department of Chemical and Biomolecular Engineering and KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - MinA Kim
- Department of Chemical and Biomolecular Engineering and KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Sung-Soo Yoon
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.,Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nam Hoon Kwon
- Medicinal Bioconvergence Research Center, Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Sunghoon Kim
- Medicinal Bioconvergence Research Center, Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Yoosik Kim
- Department of Chemical and Biomolecular Engineering and KAIST Institute for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
| | - Youngil Koh
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea. .,Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
| |
Collapse
|
3
|
Kurshumliu F, Sadiku-Zehri F, Qerimi A, Vela Z, Jashari F, Bytyci S, Rashiti V, Sadiku S. Divergent immunohistochemical expression of CD21 and CD23 by follicular dendritic cells with increasing grade of follicular lymphoma. World J Surg Oncol 2019; 17:115. [PMID: 31269981 PMCID: PMC6610797 DOI: 10.1186/s12957-019-1659-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 06/26/2019] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Ultrastructural and immunohistochemical differences have been described in FDCs of primary and secondary follicles, illustrating the highly compartmentalized structure of lymph follicles. Differences in FDC immunophenotype in different grades of FL may reflect some parallelism between reactive and neoplastic conditions in terms of FDC-B cell interaction and may be used as a valuable additional tool for grading FL. METHODS A total of 60 paraffin blocks from patients with follicular lymphoma, 30 cases each of grade 1 and 3, were retrieved from our archive. Immunohistochemical analysis was carried out for CD21, CD23, cyclin A, and Ki-67. RESULTS Our study demonstrates that during evaluation, six patterns of FDC distribution were distinguished. The intensity of stain for CD21 was not statistically significant in grade 1 and grade 3 FL (p = 0.340). In contrast, grade 3 FLs exhibited a significant decrease of CD23 expression by the FDCs (p < 0.001). By CD21 stain, there was no significant difference in the distribution of pattern 1 in grades 1 and 3 (p = 0.098). In contrast, in grade 3, this pattern was significantly less observed by CD23 stain (p = 0.016). The same was observed for pattern 2 for CD21 (p = 0.940) and CD23 (p = 0.010) and pattern 4 for CD21 (p = 0.305) and CD23 (p = 0.005), respectively. Distribution of pattern 5 was significantly different between grades 1 and 3 both for CD21 (p = 0.005) and CD23 (p < 0.001). Distribution of patterns 2 and 6 was not significantly different between grades 1 and 3 for CD21 and CD23. The values of cyclin A and Mib-1 were also significantly different between grades 1 and 3 (p < 0.001). CONCLUSIONS The observed patterns of FDCs lead us to believe that similar to reactive lymph node follicles, neoplastic follicles in FL, at least in early stages, have an organized structure. Hypothetically, with CD21, CD23, and cyclin A immunohistochemistry, the sequence of events in FL progression may be traced.
Collapse
Affiliation(s)
- Fisnik Kurshumliu
- Institute of Anatomic Pathology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Fatlinda Sadiku-Zehri
- Institute of Anatomic Pathology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Ardita Qerimi
- Institute of Histology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Zana Vela
- Institute of Histology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Fisnik Jashari
- Institute of Histology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Samir Bytyci
- Institute of Histology, University Clinical Center/Faculty of Medicine, University of Pristina, Pristina, Kosovo
| | - Vlore Rashiti
- Institute of Anatomic Pathology, University Clinical Center of Pristina, Pristina, Kosovo
| | - Shemsedin Sadiku
- Hematology Clinic, University Clinical Center/Faculty of Medicine, University of Pristina, Rr.Bulevardi i Dëshmorëve, 10000, Pristina, PN, Kosovo.
| |
Collapse
|
4
|
Multicenter Analysis of Advanced Stage Grade 3A Follicular Lymphoma Outcomes by Frontline Treatment Regimen. CLINICAL LYMPHOMA MYELOMA & LEUKEMIA 2018; 19:95-102. [PMID: 30581160 DOI: 10.1016/j.clml.2018.11.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 10/22/2018] [Accepted: 11/02/2018] [Indexed: 11/23/2022]
Abstract
BACKGROUND Follicular lymphoma (FL) is a common form of non-Hodgkin lymphoma with a wide spectrum of presentation. While grade 1/2 FL is considered low grade and grade 3B FL is approached as an aggressive lymphoma, the management of grade 3A FL remains controversial. PATIENTS AND METHODS We performed a retrospective, multicenter analysis of patients aged ≥ 18 years with advanced stage 3/4 grade 3A FL diagnosed between January 2006 and July 2016. Patients were stratified by frontline chemotherapy regimen: anthracycline based (ATC), bendamustine (BD), and cyclophosphamide, vincristine, and prednisone (CVP). A total of 103 patients were identified from 6 contributing centers: 65 patients received ATC chemotherapy, 30 BD, and 8 CVP. The primary outcome was time to progression (TTP). Secondary outcomes included progression-free survival, overall survival, complete response rates, large cell transformation, and impact of standardized maximum uptake value on positron emission tomography/computed tomography with outcomes. Patient characteristics were similar among the 3 treatment groups. RESULTS For TTP at 24 months from initiation of treatment, 72% of ATC, 79% of BD, and 50% of CVP patients had not experienced disease progression (P = .01). Multivariate analysis demonstrated a TTP benefit for ATC compared to CVP (hazard ratio 3.22; 95% confidence interval, 1.26-8.25; P = .01) but no difference when compared to BD. Similar findings were seen with progression-free survival. While overall survival was similar among the 3 arms, there was a higher risk of large cell transformation following BD and CVP. Last, standardized maximum uptake value on positron emission tomography/computed tomography did not affect TTP when comparing BD- and ATC-treated patients. CONCLUSION Although ATC was superior to CVP, clinical outcomes (TTP, progression-free survival, and overall survival) were similar compared to BD chemotherapy for patients with grade 3A FL.
Collapse
|
5
|
Mitotic Index Determined by Phosphohistone H3 Immunohistochemistry for Precise Grading in Follicular Lymphoma. Appl Immunohistochem Mol Morphol 2018; 26:579-585. [DOI: 10.1097/pai.0000000000000481] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
|
6
|
Marcondes N, Fernandes F, Faulhaber G. Ki-67 expression in mature B-cell neoplasms: a flow cytometry study. Rev Assoc Med Bras (1992) 2018; 64:525-529. [DOI: 10.1590/1806-9282.64.06.525] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 11/02/2017] [Indexed: 12/21/2022] Open
Abstract
SUMMARY OBJECTIVE: Ki-67 is a nuclear protein associated with cellular proliferation in normal or leukemic conditions that can help identify more aggressive diseases and is usually evaluated with immunohistochemistry. The aim of this was to assess Ki-67 expression on mature B-cell neoplasms samples with flow cytometry immunophenotyping. METHOD: After surface staining with CD19 and CD45, intracellular staining for Ki-67 was performed in leukemic mature B-cells. Ki-67 expression was evaluated with flow cytometry. RESULTS: Ki-67 expression was higher in mantle cell lymphoma, Burkitt lymphoma, and diffuse large B-cell lymphoma cases. It was also associated with CD38 mean fluorescence intensity. CONCLUSIONS: Ki-67 expression evaluated by flow cytometry can be a useful tool in the diagnosis of mature B-cell neoplasms. More studies are needed to validate Ki-67 assessment with flow cytometry immunophenotyping.
Collapse
Affiliation(s)
- Natália Marcondes
- Universidade Federal do Rio Grande do Sul, Brasil; Laboratório Zanol, Brasil
| | | | - Gustavo Faulhaber
- Universidade Federal do Rio Grande do Sul, Brasil; Laboratório Zanol, Brasil; Universidade Federal do Rio Grande do Sul, Brasil
| |
Collapse
|
7
|
Sensitivity of fine-needle aspiration biopsy for diagnosing and grading follicular lymphomas using a multiparameter approach in a cancer center. J Am Soc Cytopathol 2016; 6:80-88. [PMID: 31042638 DOI: 10.1016/j.jasc.2016.12.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 12/14/2016] [Accepted: 12/19/2016] [Indexed: 11/20/2022]
Abstract
OBJECTIVES The diagnosis and grading of follicular lymphomas (FLs) by fine-needle aspiration biopsy (FNAB) has not been systematically compared with core needle biopsy (CNB). We evaluated the sensitivity of FNAB in diagnosing and grading FLs using a multiparameter approach in a large cancer center. METHODS We retrospectively identified CNBs of lymph nodes diagnosed as FL that also had a concurrently acquired FNAB on the same site. The majority of cases had flow cytometric analysis and these results were available for interpretation of both the FNAB and CNB. RESULTS Out of 342 patients, CNB diagnoses included 291 (85%) low-grade (LG) FLs, 30 (9%) high-grade (HG) FLs, and 21 (6%) non-graded FLs/other. FNAB diagnoses included 194 (57%) LG FLs, 19 (6%) HG FLs, 93 (27%) non-graded FLs, 9 (3%) large B-cell lymphomas (LBCL) of follicle center origin, and 27 (7%) insufficient for diagnosis/other. Review of non-graded FLs showed 45% LG, 35% indeterminate due to polymorphous lymphoid cells with increased numbers of large cells, and 20% scant cellularity. Sensitivity of FNAB for diagnosing FL was 89%, and 66% for LG FL. The latter increased (94%), however, when grading was performed. CONCLUSION FNAB is highly sensitive for diagnosing FLs when cellular material for cytomorphology and flow cytometric analysis is obtained, and grading is feasible for most LG FLs. A subset of FLs composed of a polymorphous lymphoid population with increased numbers of large cells may be more difficult to grade, and HG FLs can be difficult to distinguish from CD10-positive diffuse LBCLs.
Collapse
|
8
|
Klopčič U, Lavrenčak J, Gašljević G, Bračko M, Pohar-Marinšek Ž, Kloboves-Prevodnik V. Grading of follicular lymphoma in cytological samples. Cytopathology 2016; 27:390-397. [PMID: 26869534 DOI: 10.1111/cyt.12319] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/14/2015] [Indexed: 11/27/2022]
Abstract
OBJECTIVE The treatment of follicular lymphoma (FL) depends on its grade. The current World Health Organization (WHO) 2008 Classification of Tumours of Haematopoietic and Lymphoid Tissues recommends the grading of FL on histological samples according to the Mann and Berard method, taking into consideration the number of centroblasts. There is no generally accepted method for the grading of FL in fine needle aspiration biopsy (FNAB) samples. The aim of the present study was to devise a grading system for FL in cytological samples. METHODS Flow cytometry (FC) was performed on 60 FNAB samples of patients with primary FL. We assumed that FL cells larger than reactive T lymphocytes on FC histograms corresponded to centroblasts. The percentage of large cells was calculated and compared with histological grade, proliferative activity and number of centroblasts per high-power field (HPF) on histological slides, and with survival. RESULTS The histological analysis of lymph nodes revealed 20 patients with high-grade and 40 patients with low-grade FL. The percentage of large cells in FNAB samples correlated significantly with histological grade (P = 0.02), MIB1 status (P < 0.001) and the number of centroblasts per HPF (P < 0.001). An age over 60 years and a percentage of large cells over 50% in FNAB samples were found to have a statistically significant impact on survival by univariate analysis (P = 0.001 and P = 0.006, respectively). CONCLUSIONS The percentage of large lymphoma cells in FNAB samples of FL determined by FC can be used as a reliable method for FL grading, as it is comparable with the histological grading system.
Collapse
Affiliation(s)
- U Klopčič
- Department of Cytopathology, Institute of Oncology, Ljubljana, Slovenia
| | - J Lavrenčak
- Department of Cytopathology, Institute of Oncology, Ljubljana, Slovenia
| | - G Gašljević
- Department of Pathology of the , Institute of Oncology Ljubljana, Slovenia , Ljubljana
| | - M Bračko
- Department of Pathology, University Clinical Center Ljubljana, Zaloška cesta 2, Ljubljana, Slovenia
| | - Ž Pohar-Marinšek
- Department of Cytopathology, Institute of Oncology, Ljubljana, Slovenia
| | | |
Collapse
|
9
|
|
10
|
Oricchio E, Ciriello G, Jiang M, Boice MH, Schatz JH, Heguy A, Viale A, de Stanchina E, Teruya-Feldstein J, Bouska A, McKeithan T, Sander C, Tam W, Seshan VE, Chan WC, Chaganti RSK, Wendel HG. Frequent disruption of the RB pathway in indolent follicular lymphoma suggests a new combination therapy. ACTA ACUST UNITED AC 2014; 211:1379-91. [PMID: 24913233 PMCID: PMC4076578 DOI: 10.1084/jem.20132120] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Loss of cell cycle controls is a hallmark of cancer and has a well-established role in aggressive B cell malignancies. However, the role of such lesions in indolent follicular lymphoma (FL) is unclear and individual lesions have been observed with low frequency. By analyzing genomic data from two large cohorts of indolent FLs, we identify a pattern of mutually exclusive (P = 0.003) genomic lesions that impair the retinoblastoma (RB) pathway in nearly 50% of FLs. These alterations include homozygous and heterozygous deletions of the p16/CDKN2a/b (7%) and RB1 (12%) loci, and more frequent gains of chromosome 12 that include CDK4 (29%). These aberrations are associated with high-risk disease by the FL prognostic index (FLIPI), and studies in a murine FL model confirm their pathogenic role in indolent FL. Increased CDK4 kinase activity toward RB1 is readily measured in tumor samples and indicates an opportunity for CDK4 inhibition. We find that dual CDK4 and BCL2 inhibitor treatment is safe and effective against available models of FL. In summary, frequent RB pathway lesions in indolent, high-risk FLs indicate an untapped therapeutic opportunity.
Collapse
Affiliation(s)
- Elisa Oricchio
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Giovanni Ciriello
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Man Jiang
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Michael H Boice
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Jonathan H Schatz
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Adriana Heguy
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Agnes Viale
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Elisa de Stanchina
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Julie Teruya-Feldstein
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Alyssa Bouska
- Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198
| | - Tim McKeithan
- Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198
| | - Chris Sander
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Wayne Tam
- Department of Pathology, Weill-Cornell Medical School, New York, NY 10065
| | - Venkatraman E Seshan
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Wing-Chung Chan
- Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198
| | - R S K Chaganti
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| | - Hans-Guido Wendel
- Cancer Biology & Genetics Program, Computational Biology Program, Department of Medicine, Human Oncology and Pathogenesis Program, Genomics Core Facility, Molecular Pharmacology Program, Department of Pathology, Department of Epidemiology and Biostatistics, and Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065
| |
Collapse
|
11
|
Bowen JM, Perry AM, Laurini JA, Smith LM, Klinetobe K, Bast M, Vose JM, Aoun P, Fu K, Greiner TC, Chan WC, Armitage JO, Weisenburger DD. Lymphoma diagnosis at an academic centre: rate of revision and impact on patient care. Br J Haematol 2014; 166:202-8. [DOI: 10.1111/bjh.12880] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Accepted: 03/04/2014] [Indexed: 12/01/2022]
Affiliation(s)
- Joslin M. Bowen
- Department of Pathology and Microbiology; University of Nebraska Medical Center; Omaha NE USA
| | | | | | - Lynette M. Smith
- Department of Biostatistics; University of Nebraska Medical Center; Omaha NE USA
| | - Kimberly Klinetobe
- Department of Internal Medicine; University of Nebraska Medical Center; Omaha NE USA
| | - Martin Bast
- Department of Internal Medicine; University of Nebraska Medical Center; Omaha NE USA
| | - Julie M. Vose
- Department of Internal Medicine; University of Nebraska Medical Center; Omaha NE USA
| | - Patricia Aoun
- Department of Pathology; City of Hope National Medical Center; Duarte CA USA
| | - Kai Fu
- Department of Pathology and Microbiology; University of Nebraska Medical Center; Omaha NE USA
| | - Timothy C. Greiner
- Department of Pathology and Microbiology; University of Nebraska Medical Center; Omaha NE USA
| | - Wing C. Chan
- Department of Pathology; City of Hope National Medical Center; Duarte CA USA
| | - James O. Armitage
- Department of Internal Medicine; University of Nebraska Medical Center; Omaha NE USA
| | | |
Collapse
|
12
|
Kedmi M, Hedvat CV, Maragulia J, Zhang Z, Zelenetz AD. Association of quantitative assessment of the intrafollicular proliferation index with outcome in follicular lymphoma. Br J Haematol 2013; 164:646-52. [DOI: 10.1111/bjh.12667] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2013] [Accepted: 09/17/2013] [Indexed: 01/27/2023]
Affiliation(s)
- Meirav Kedmi
- Lymphoma Service; Memorial Sloan-Kettering Cancer Center; New York NY, USA
- Hematology Division; Chaim Sheba Medical Center; Ramat Gan Israel
| | - Cyrus V. Hedvat
- Department of Pathology; Memorial Sloan-Kettering Cancer Center; New York NY USA
| | - Jocelyn Maragulia
- Lymphoma Service; Memorial Sloan-Kettering Cancer Center; New York NY, USA
| | - Zhigang Zhang
- Department of Epidemiology and Biostatistics; Memorial Sloan-Kettering Cancer Center; New York NY USA
| | - Andrew D. Zelenetz
- Lymphoma Service; Memorial Sloan-Kettering Cancer Center; New York NY, USA
| |
Collapse
|
13
|
Samols MA, Smith NE, Gerber JM, Vuica-Ross M, Gocke CD, Burns KH, Borowitz MJ, Cornish TC, Duffield AS. Software-automated counting of Ki-67 proliferation index correlates with pathologic grade and disease progression of follicular lymphomas. Am J Clin Pathol 2013; 140:579-87. [PMID: 24045557 DOI: 10.1309/ajcptma1f6lwytqv] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022] Open
Abstract
OBJECTIVES To examine the accuracy of software-assisted measurement of the Ki-67 proliferation index (PI) and its correlation with the grade and clinical progression of follicular lymphoma (FL). METHODS High-power field equivalents were extracted from H&E- and Ki-67-immunostained slides of FL, and a nuclear quantitation algorithm was used to calculate a PI. Representative fields were manually counted for validation with close agreement. RESULTS The PI was significantly higher in World Health Organization grade 3 FL than grade 1 to 2 FL. Disease progression, as defined by subsequent treatment with radiation or cytotoxic chemotherapy, was also significantly associated with elevated PI but not pathologic grade. CONCLUSIONS These data show that software-automated quantitation of Ki-67 can provide both a useful adjunct to pathologic grade in FL and improved prognostic information for patients.
Collapse
Affiliation(s)
- Mark A. Samols
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nathan E. Smith
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jonathan M. Gerber
- Division of Hematology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Milena Vuica-Ross
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Christopher D. Gocke
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Kathleen H. Burns
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Michael J. Borowitz
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Toby C. Cornish
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Amy S. Duffield
- Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD
| |
Collapse
|
14
|
Levenson RM, Fornari A, Loda M. Multispectral imaging and pathology: seeing and doing more. ACTA ACUST UNITED AC 2013; 2:1067-81. [PMID: 23495926 DOI: 10.1517/17530059.2.9.1067] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND The current appreciation of the biological complexity of disease has led to increasing demands on pathologists to provide clinically relevant, quantitative morphological and molecular information while preserving cellular and tissue context. This can be technically challenging, especially when signals of interest are colocalized. With fluorescence-based methods, sensitivity and quantitative reliability may be compromised by spectral cross-talk between labels and by autofluorescence. In brightfield microscopy, overlapping chromogenic signals pose similar imaging difficulties. APPROACH These challenges can be addressed using commercially available multispectral imaging technologies attached to standard microscope platforms, or alternatively, integrated into whole-slide scanning instruments. ASSESSMENT Multispectral techniques, along with other developments in digital analysis, will allow pathologists to deliver appropriate quantitative and multiplexed analyses in a reproducible and timely manner. Caveats apply - as the complexity of the sample preparation and analysis components increases, commensurate attention must be paid to the use of appropriate controls for all stages of the process.
Collapse
Affiliation(s)
- Richard M Levenson
- CRI, 35B Cabot Road, Woburn, MA 01801, USA +1 781 935 9099, ext. 204 ; +1 781 935 3388 ;
| | | | | |
Collapse
|
15
|
Abstract
Imaging contributes to management of follicular lymphoma (FL) through guiding biopsy, determining disease stage and assessing therapeutic response. Molecular imaging with positron emission tomography (PET), especially when combined with computer tomography (PET/CT), is more accurate than conventional imaging and extends the role of imaging to lesion characterisation, including non-invasive assessment of high-grade transformation. There is strong data to support the use of FDG PET/CT for primary staging, resulting in significant management change. In patients with early stage follicular lymphoma (stage I or II), there is a clear role for PET/CT to avoid futile involved-field radiotherapy in patients with widespread disease and to optimise the treatment field in patients with confirmed localised disease. For restaging, use of PET/CT allows discrimination between scar tissue and viable tumour in residual masses. Molecular imaging is likely to play an increasing role in selection of patients for specific treatments and in prognostic stratification.
Collapse
Affiliation(s)
- M S Hofman
- Centre for Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Australia.
| | | |
Collapse
|
16
|
Sertel O, Lozanski G, Shana'ah A, Gurcan MN. Computer-aided detection of centroblasts for follicular lymphoma grading using adaptive likelihood-based cell segmentation. IEEE Trans Biomed Eng 2010; 57:2613-6. [PMID: 20595077 DOI: 10.1109/tbme.2010.2055058] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL has a variable clinical course, and important clinical treatment decisions for FL patients are based on histological grading, which is done by manually counting the large malignant cells called centroblasts (CB) in ten standard microscopic high-power fields from H&E-stained tissue sections. This method is tedious and subjective; as a result, suffers from considerable inter and intrareader variability even when used by expert pathologists. In this paper, we present a computer-aided detection system for automated identification of CB cells from H&E-stained FL tissue samples. The proposed system uses a unitone conversion to obtain a single-channel image that has the highest contrast. From the resulting image, which has a bimodal distribution due to the H&E stain, a cell-likelihood image is generated. Finally, a two-step CB detection procedure is applied. In the first step, we identify evident nonCB cells based on size and shape. In the second step, the CB detection is further refined by learning and utilizing the texture distribution of nonCB cells. We evaluated the proposed approach on 100 region-of-interest images extracted from ten distinct tissue samples and obtained a promising 80.7% detection accuracy.
Collapse
Affiliation(s)
- Olcay Sertel
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
| | | | | | | |
Collapse
|
17
|
Facchetti F, Ungari M. Advances in the molecular morphology of hematopathology. Int J Surg Pathol 2010; 18:128S-132S. [PMID: 20484277 DOI: 10.1177/1066896910370613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Fabio Facchetti
- Department of Pathology, University of Brescia, Brescia, Italy.
| | | |
Collapse
|
18
|
Survival in non-Hodgkin's lymphoma by histology and family history. J Cancer Res Clin Oncol 2009; 135:1711-6. [PMID: 19533171 DOI: 10.1007/s00432-009-0618-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2008] [Accepted: 06/02/2009] [Indexed: 10/20/2022]
Abstract
PURPOSE Although survival has been studied for various subtypes of non-Hodgkin's lymphoma (NHL), there have been few comprehensive studies to quantify the prognosis, including all specific histologies. The effect of family history on survival in NHL has not been examined. METHODS We used the Swedish Family-Cancer Database to estimate hazard ratios in NHL by histology and family history. RESULTS Using diffuse centroblastic lymphoma as reference (HR 1.0), patients with Waldenström's macroglobulinemia and hairy-cell leukemia had the best survival. Survival advantage was also noted among patients with lymphoplasmacytic lymphoma and different kinds of follicular lymphomas. For T-cell lymphoma, mycosis fungoides showed a favorable prognosis. As for survival by family history, a total of 98 familial cases were noted in our Database with a similar prognosis compared to sporadic cases in both parental and offspring generations. A non-significant familial concordance of either good or poor survival was noted among family members when probands' prognosis was stratified by survival time. CONCLUSIONS Our results provide quantitative prognosis data for patients with NHL according to specific histologies. Patients with a familial NHL had a similar prognosis compared to patients with sporadic disease. The data suggest familial concordance in either good or poor survival among family members.
Collapse
|
19
|
Broyde A, Boycov O, Strenov Y, Okon E, Shpilberg O, Bairey O. Role and prognostic significance of the Ki-67 index in non-Hodgkin's lymphoma. Am J Hematol 2009; 84:338-43. [PMID: 19384938 DOI: 10.1002/ajh.21406] [Citation(s) in RCA: 92] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Expression of Ki-67, a nuclear antigen protein present in all cycling cells, is used to determine the growth fraction of tumors. The aim of this study was to evaluate the role and prognostic significance of the Ki-67 proliferation index (PI) in non-Hodgkin's lymphoma. Ki-67 was assayed immunohistochemically in tissue samples of 319 patients with newly-diagnosed non-Hodgkin's lymphoma. In 268 patients, the Ki-67 PI was correlated with clinical course and outcome. The mean Ki-67 PI ranged from 26.6% in indolent lymphomas to 97.6% in very aggressive lymphomas (P < 0.001). The index was <45% in 82.8% of indolent lymphomas and >45% in 85% of aggressive lymphomas (AUC = 0.877, P < 0.001). In patients with diffuse large B-cell lymphoma (n = 141), a Ki-67 PI of 70% was found to significantly discriminate patients with good or bad prognosis (AUC = 0.65, P = 0.004). Three-year survival was 75% +/- 5.6% in patients with a low Ki-67 index compared with 55.9% +/- 6% in patients with a high index (P = 0.015). In patients with a low IPI (<or=2), 3-year survival was 94% +/- 4% in those with a Ki-67 index <or=70% and 64% +/- 8.1% in those with a higher index (P = 0.002); in patients with bulky disease (>10 cm), the corresponding 3-year survival by Ki-67 index was 100% and 25% +/- 12% (P = 0.012). Our results suggest that the mean Ki-67 PI differs by type of lymphoma. A cut-off value of 45% can help differentiate indolent from aggressive disease. In diffuse large B-cell lymphoma, a cut-off value of 70% can distinguish patients with a good and bad prognosis when combined with other prognostic factors of low IPI score and bulky disease.
Collapse
Affiliation(s)
- Adi Broyde
- Institute of Hematology, Rabin Medical Center, Beilinson Hospital, Petah Tiqwa, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | | | | | | | | | | |
Collapse
|
20
|
Zhou M, Fadlelmola FM, Cohn JB, Skinnider B, Gascoyne RD, Banerjee D. Constitutive overexpression of a novel 21 kDa protein by Hodgkin lymphoma and aggressive non-Hodgkin lymphomas. Mol Cancer 2008; 7:12. [PMID: 18218123 PMCID: PMC2267462 DOI: 10.1186/1476-4598-7-12] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2007] [Accepted: 01/24/2008] [Indexed: 12/27/2022] Open
Abstract
Background CD30, a 120 kDa surface phosphorylated protein is a member of tumour necrosis/nerve growth factor receptor (TNF/NGFR) family and constitutively expressed by Hodgkin and Reed-Sternberg (HRS) cells of Hodgkin lymphoma (HL) and the neoplastic cells of Anaplastic Large Cell Lymphoma (ALCL). A disease-specific protein marker is yet to be identified in Hodgkin lymphoma cells. In order to define HL-specific biomarkers, novel murine monoclonal antibodies were developed in our laboratory. Results Murine monoclonal antibodies (mabs) were raised against the B3 sub clone of HL-derived cell line KM-H2. Two of these mabs (clone R23.1 mab and clone R24.1 mab) are IgG1 class antibodies that recognize a 21 kDa protein present at the cell membrane and in the cytoplasm in HL-derived cell lines. Clone R24.1 mab recognizes a formalin-resistant epitope and labels HRS cells in tissue samples from patients with HL of the classical type, ALCL, and subsets of T and B cell aggressive Non-Hodgkin Lymphomas (NHL). The antigen recognized by the clone R23.1 mab and clone R24.1 mab does not share epitopes with CD30 cluster regions A, B, or C, and, unlike CD30, is not expressed by phytohemagglutinin (PHA) activated T cells. Conclusion The 21 kDa protein detected by clone R23.1 and clone R24.1 mabs is a novel membrane-associated protein that may be a potential marker for the diagnosis and targeted therapy of HL and aggressive T and B cell NHL.
Collapse
Affiliation(s)
- Minglong Zhou
- Centre for Translational and Applied Genomics (CTAG), Department of Pathology and Laboratory Medicine, British Columbia Cancer Agency, Vancouver Cancer Centre, BC V5Z 4E6, Canada.
| | | | | | | | | | | |
Collapse
|