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Igbo BT, Jentsch C, Linge A, Plesca I, Kuzay Y, Löck S, Kumaravadivel MS, Doms S, Stolz-Kieslich L, Pollack D, Brückmann S, Tittlbach H, Weitz J, Aust D, Apolle R, Schmitz M, Troost EGC. Correlation of microscopic tumor extension with tumor microenvironment in esophageal cancer patients. Strahlenther Onkol 2024; 200:595-604. [PMID: 38727811 PMCID: PMC11186916 DOI: 10.1007/s00066-024-02234-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 03/17/2024] [Indexed: 06/21/2024]
Abstract
OBJECTIVE In the era of image-guided adaptive radiotherapy, definition of the clinical target volume (CTV) is a challenge in various solid tumors, including esophageal cancer (EC). Many tumor microenvironmental factors, e.g., tumor cell proliferation or cancer stem cells, are hypothesized to be involved in microscopic tumor extension (MTE). Therefore, this study assessed the expression of FAK, ILK, CD44, HIF-1α, and Ki67 in EC patients after neoadjuvant radiochemotherapy followed by tumor resection (NRCHT+R) and correlated these markers with the MTE. METHODS Formalin-fixed paraffin-embedded tumor resection specimens of ten EC patients were analyzed using multiplex immunofluorescence staining. Since gold fiducial markers had been endoscopically implanted at the proximal and distal tumor borders prior to NRCHT+R, correlation of the markers with the MTE was feasible. RESULTS In tumor resection specimens of EC patients, the overall percentages of FAK+, CD44+, HIF-1α+, and Ki67+ cells were higher in tumor nests than in the tumor stroma, with the outcome for Ki67+ cells reaching statistical significance (p < 0.001). Conversely, expression of ILK+ cells was higher in tumor stroma, albeit not statistically significantly. In three patients, MTE beyond the fiducial markers was found, reaching up to 31 mm. CONCLUSION Our findings indicate that the overall expression of FAK, HIF-1α, Ki67, and CD44 was higher in tumor nests, whereas that of ILK was higher in tumor stroma. Differences in the TME between patients with residual tumor cells in the original CTV compared to those without were not found. Thus, there is insufficient evidence that the TME influences the required CTV margin on an individual patient basis. TRIAL REGISTRATION NUMBER AND DATE BO-EK-148042017 and BO-EK-177042022 on 20.06.2022, DRKS00011886, https://drks.de/search/de/trial/DRKS00011886 .
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Affiliation(s)
- Benjamin Terfa Igbo
- Institute of Radiooncology-OncoRay, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Christina Jentsch
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
| | - Annett Linge
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
| | - Ioana Plesca
- Institute of immunology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Yalçin Kuzay
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
| | - Steffen Löck
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
| | - Mani Sankari Kumaravadivel
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
| | - Susanne Doms
- Institute of immunology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Liane Stolz-Kieslich
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
| | - Daniela Pollack
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
| | - Sascha Brückmann
- Institute for Pathology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Hannes Tittlbach
- Institute for Pathology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Jürgen Weitz
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- Department of Visceral, Thoracic and Vascular Surgery (VTG), Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Daniela Aust
- Institute of immunology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Institute for Pathology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Rudi Apolle
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
| | - Marc Schmitz
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- Institute of immunology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Esther G C Troost
- Institute of Radiooncology-OncoRay, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
- OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, 01307, Dresden, Germany.
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Partner Site Dresden, Dresden, Germany.
- National Center for Tumor Diseases (NCT/UCC), Dresden, Germany, German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany.
- Institute for Pathology and Tumor and Normal Tissue Bank of the University Cancer Center (UCC), Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
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Andronache I, Peptenatu D, Ahammer H, Radulovic M, Djuričić GJ, Jelinek HF, Russo C, Di Ieva A. Fractals in the Neurosciences: A Translational Geographical Approach. ADVANCES IN NEUROBIOLOGY 2024; 36:953-981. [PMID: 38468071 DOI: 10.1007/978-3-031-47606-8_47] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
The chapter presents three new fractal indices (fractal fragmentation index, fractal tentacularity index, and fractal anisotropy index) and normalized Kolmogorov complexity with proven applicability in geographic research, developed by the authors, and the possibility of their future use in neuroscience. The research demonstrates the relevance of fractal analysis in different fields and the basic concepts and principles of fractal geometry being sufficient for the development of models relevant to the studied reality. Also, the research highlighted the need to continue interdisciplinary research based on known fractal indicators, as well as the development of new analysis methods with the translational potential between fields.
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Affiliation(s)
- Ion Andronache
- Research Center for Integrated Analysis and Territorial Management, Faculty of Geography, University of Bucharest, Bucharest, Romania.
| | - Daniel Peptenatu
- Research Center for Integrated Analysis and Territorial Management, Faculty of Geography, University of Bucharest, Bucharest, Romania
| | - Helmut Ahammer
- GSRC, Division of Medical Physics and Biophysics, Medical University of Graz, Graz, Austria
| | - Marko Radulovic
- Department of Experimental Oncology, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia
| | - Goran J Djuričić
- Department of Radiology, Faculty of Medicine, University of Belgrade, University Children's Hospital, Belgrade, Serbia
| | - Herbert F Jelinek
- Department of Medical Sciences and Biotechnology Center, Khalifa University, Abu Dhabi, UAE
| | - Carlo Russo
- Computational NeuroSurgery (CNS) Lab, Faculty of Medicine, Health and Human Sciences, Macquarie Medical School, Macquarie University, Sydney, NSW, Australia
| | - Antonio Di Ieva
- Computational NeuroSurgery (CNS) Lab, Faculty of Medicine, Health and Human Sciences, Macquarie Medical School, Macquarie University, Sydney, NSW, Australia
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Yang L, Xu P, Zhang Y, Cui N, Wang M, Peng M, Gao C, Wang T. A deep learning radiomics model may help to improve the prediction performance of preoperative grading in meningioma. Neuroradiology 2022; 64:1373-1382. [PMID: 35037985 DOI: 10.1007/s00234-022-02894-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 01/04/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE This study aimed to investigate the clinical usefulness of the enhanced-T1WI-based deep learning radiomics model (DLRM) in differentiating low- and high-grade meningiomas. METHODS A total of 132 patients with pathologically confirmed meningiomas were consecutively enrolled (105 in the training cohort and 27 in the test cohort). Radiomics features and deep learning features were extracted from T1 weighted images (T1WI) (both axial and sagittal) and the maximum slice of the axial tumor lesion, respectively. Then, the synthetic minority oversampling technique (SMOTE) was utilized to balance the sample numbers. The optimal discriminative features were selected for model building. LightGBM algorithm was used to develop DLRM by a combination of radiomics features and deep learning features. For comparison, a radiomics model (RM) and a deep learning model (DLM) were constructed using a similar method as well. Differentiating efficacy was determined by using the receiver operating characteristic (ROC) analysis. RESULTS A total of 15 features were selected to construct the DLRM with SMOTE, which showed good discrimination performance in both the training and test cohorts. The DLRM outperformed RM and DLM for differentiating low- and high-grade meningiomas (training AUC: 0.988 vs. 0.980 vs. 0.892; test AUC: 0.935 vs. 0.918 vs. 0.718). The accuracy, sensitivity, and specificity of the DLRM with SMOTE were 0.926, 0.900, and 0.924 in the test cohort, respectively. CONCLUSION The DLRM with SMOTE based on enhanced T1WI images has favorable performance for noninvasively individualized prediction of meningioma grades, which exhibited favorable clinical usefulness superior over the radiomics features.
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Affiliation(s)
- Liping Yang
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Panpan Xu
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Ying Zhang
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Nan Cui
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Menglu Wang
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Mengye Peng
- PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, China
| | - Chao Gao
- Medical Imaging Department, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tianzuo Wang
- Medical Imaging Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
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Kennedy JJ, Whiteaker JR, Kennedy LC, Bosch DE, Lerch ML, Schoenherr RM, Zhao L, Lin C, Chowdhury S, Kilgore MR, Allison KH, Wang P, Hoofnagle AN, Baird GS, Paulovich AG. Quantification of Human Epidermal Growth Factor Receptor 2 by Immunopeptide Enrichment and Targeted Mass Spectrometry in Formalin-Fixed Paraffin-Embedded and Frozen Breast Cancer Tissues. Clin Chem 2021; 67:1008-1018. [PMID: 34136904 DOI: 10.1093/clinchem/hvab047] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 03/03/2021] [Indexed: 11/12/2022]
Abstract
BACKGROUND Conventional HER2-targeting therapies improve outcomes for patients with HER2-positive breast cancer (BC), defined as tumors showing HER2 protein overexpression by immunohistochemistry and/or ERBB2 gene amplification determined by in situ hybridization (ISH). Emerging HER2-targeting compounds show benefit in some patients with neither HER2 protein overexpression nor ERBB2 gene amplification, creating a need for new assays to select HER2-low tumors for treatment with these compounds. We evaluated the analytical performance of a targeted mass spectrometry-based assay for quantifying HER2 protein in formalin-fixed paraffin-embedded (FFPE) and frozen BC biopsies. METHODS We used immunoaffinity-enrichment coupled to multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) to quantify HER2 protein (as peptide GLQSLPTHDPSPLQR) in 96 frozen and 119 FFPE BC biopsies. We characterized linearity, lower limit of quantification (LLOQ), and intra- and inter-day variation of the assay in frozen and FFPE tissue matrices. We determined concordance between HER2 immuno-MRM-MS and predicate immunohistochemistry and ISH assays and examined the benefit of multiplexing the assay to include proteins expressed in tumor subcompartments (e.g., stroma, adipose, lymphocytes, epithelium) to account for tissue heterogeneity. RESULTS HER2 immuno-MRM-MS assay linearity was ≥103, assay coefficient of variation was 7.8% (FFPE) and 5.9% (frozen) for spiked-in analyte, and 7.7% (FFPE) and 7.9% (frozen) for endogenous measurements. Immuno-MRM-MS-based HER2 measurements strongly correlated with predicate assay HER2 determinations, and concordance was improved by normalizing to glyceraldehyde-3-phosphate dehydrogenase. HER2 was quantified above the LLOQ in all tumors. CONCLUSIONS Immuno-MRM-MS can be used to quantify HER2 in FFPE and frozen BC biopsies, even at low HER2 expression levels.
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Affiliation(s)
- Jacob J Kennedy
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jeffrey R Whiteaker
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Laura C Kennedy
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dustin E Bosch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Melissa L Lerch
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Regine M Schoenherr
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lei Zhao
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - ChenWei Lin
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Shrabanti Chowdhury
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mark R Kilgore
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Kimberly H Allison
- Department of Pathology, Stanford University Medical Center, Palo Alto, CA, USA
| | - Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew N Hoofnagle
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Geoffrey Stuart Baird
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amanda G Paulovich
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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