Morphological, Genetic and Tumour Microenvironment Characterisation in Uveal Melanoma
NCT ID: NCT05889481
Last Updated: 2023-06-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
100 participants
OBSERVATIONAL
2008-01-31
2025-05-31
Brief Summary
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These objectives will be achieved through immunohistochemical and genetic analyses.
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Detailed Description
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The pseudoanonymised slides, which will be prepared by clinical practice, will be sent to the Institute of Pathological Histology and Molecular Diagnostics of the Azienda Ospedaliero- Universitaria Careggi, Florence for immunohistochemical analysis, which will be carried out as reported below. Once the following analysis has been performed, the slides will be destroyed.
Sections of 3 μm thickness derived from FFPE samples will be prepared for immunohistochemical analysis. Sample processing will be performed using an automated immunostainer (Ventana Discovery ULTRA, Ventana Medical Systems, Tucson, AZ). Sections will be deparaffinised in EZ prep (#950-102; Ventana Medical Systems, Tucson, AZ), followed by treatment with Cell Conditioning 1 (CC1) buffer (#950-124; Ventana Medical Systems, Tucson, AZ) in order to promote antigenic recovery. Finally, primary antibodies will be dispensed according to the desired staining and the signal will be developed with Ultramap anti-mouse or anti-rabbit detection kits. For TME characterisation, samples will be stained with the following primary antibodies: CD3, CD4, CD8, CD68, CD163. All sections processed with IHC will be digitally scanned in Whole Slide Images (WSI) using the Aperio AT2 platform (Leica Biosystems, Wetzlar, DE).Digital Pathology, which will be performed at the University of Florence, is an emerging discipline that allows the quantitative analysis of digital images using highly standardised approaches. It will allow quantitative measurements of the interactions between immune cells and characterise their relative spatial distribution. In addition, it will be able to generate further information that will allow the TME of the MU to be studied in depth.
The HALO image analysis platform, present at the University of Florence, will allow: i) cell quantification, evaluation of the intensity of the marking, recognition of cell compartments (nucleus, cytoplasm, membrane); ii) spatial analysis through the identification of the relative distributions of cells in the intra- and peri-tumour portion; iii) sharing of the database generated together with the digital images.
Samples labelled with single or multiple IHC will be evaluated using this automated digital quantification system in order to characterise the various cell subsets that make up the TME. By combining multiple immunohistochemistry with digital analysis, the data will be accurately analysed, thus producing a new analysis work-flow for finding new signatures. All data derived from the digital analysis will be correlated with the progression of the pathology, with the aim of identifying new prognostic factors in the pathology of MU.
The analysis for the identification of cytogenetic alterations, whose data are already available to us since they are regularly performed in clinical practice, was conducted on the entire cohort of patients enrolled for the study at the Genetics Institute of the Fondazione Policlinico Gemelli on fresh tissue samples taken in the operating theatre as per clinical practice. Array-CGH methods on oligonucleotide platforms from Agilent Technologies were used. Tumour DNA from MU samples was extracted using the Gentra Pure Gene commercial kit (QIAGEN) as per clinical practice; once extracted, the quantity and purity of the DNA obtained was evaluated. All samples deemed suitable for quality were processed following the protocol indicated by Agilent Technologies. The data obtained were analysed using Cytogenomics software. These analyses will allow a genotypic characterisation of the tumour to be obtained.
Conditions
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Study Design
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COHORT
OTHER
Study Groups
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Retrospective cohort
Patients diagnosed with uveal melanoma undergoing histological and cytogenetic analysis. The cases will be identified from patients referred to the Ocular Oncology Unit and they finished the follow-up
cytogenetic analysis on tumour tissue
Array-CGH methods on oligonucleotide platforms from Agilent Technologies were used. Tumour DNA from MU samples was extracted using the Gentra Pure Gene commercial kit (QIAGEN), as per clinical practice. Once extracted, the quantity and purity of the DNA obtained were evaluated. All samples deemed suitable for quality were processed following the protocol indicated by Agilent Technologies. The data obtained were analysed using Cytogenomics software. These analyses will allow a genotypic characterisation of the tumour to be obtained.
Digital Pathology
Digital Pathology is an emerging discipline that enables quantitative analysis of digital images using highly standardised approaches. It will allow quantitative measurements of the interactions between immune cells and characterise their relative spatial distribution. In addition, it will be able to generate further information that will allow in-depth study of the tumour microenvironment of uveal melanoma
Prospective cohort
Patients diagnosed with uveal melanoma undergoing histological and cytogenetic analysis. The cases will be identified from patients referred to the Ocular Oncology and they still have to complete the follow-up
cytogenetic analysis on tumour tissue
Array-CGH methods on oligonucleotide platforms from Agilent Technologies were used. Tumour DNA from MU samples was extracted using the Gentra Pure Gene commercial kit (QIAGEN), as per clinical practice. Once extracted, the quantity and purity of the DNA obtained were evaluated. All samples deemed suitable for quality were processed following the protocol indicated by Agilent Technologies. The data obtained were analysed using Cytogenomics software. These analyses will allow a genotypic characterisation of the tumour to be obtained.
Digital Pathology
Digital Pathology is an emerging discipline that enables quantitative analysis of digital images using highly standardised approaches. It will allow quantitative measurements of the interactions between immune cells and characterise their relative spatial distribution. In addition, it will be able to generate further information that will allow in-depth study of the tumour microenvironment of uveal melanoma
Interventions
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cytogenetic analysis on tumour tissue
Array-CGH methods on oligonucleotide platforms from Agilent Technologies were used. Tumour DNA from MU samples was extracted using the Gentra Pure Gene commercial kit (QIAGEN), as per clinical practice. Once extracted, the quantity and purity of the DNA obtained were evaluated. All samples deemed suitable for quality were processed following the protocol indicated by Agilent Technologies. The data obtained were analysed using Cytogenomics software. These analyses will allow a genotypic characterisation of the tumour to be obtained.
Digital Pathology
Digital Pathology is an emerging discipline that enables quantitative analysis of digital images using highly standardised approaches. It will allow quantitative measurements of the interactions between immune cells and characterise their relative spatial distribution. In addition, it will be able to generate further information that will allow in-depth study of the tumour microenvironment of uveal melanoma
Eligibility Criteria
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Inclusion Criteria
2. Clinical and histological diagnosis of uveal melanoma;
3. Ability to obtain formalin-fixed, paraffin-embedded tissue (FFPE).
4. Availability of genetic analysis results from tumour tissue obtained by enucleation or fine-needle biopsy.
5. Follow-up of at least 5 years from enucleation or fine-needle biopsy.
6. Written informed consent to use the data for research purposes.
Exclusion Criteria
2. Lack of sufficient clinical data on selected patients.
3. Follow-up of less than 5 years.
4. Refusal to give informed consent to data processing for research purposes.
18 Years
ALL
No
Sponsors
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Fondazione Policlinico Universitario Agostino Gemelli IRCCS
OTHER
Responsible Party
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Pagliara Monica Maria
Principal Investigator
Locations
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Monica Maria Pagliara - Oncologia Oculare
Rome, , Italy
Countries
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Central Contacts
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Facility Contacts
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Monica Maria Pagliara, MD
Role: primary
References
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Singh AD, Turell ME, Topham AK. Uveal melanoma: trends in incidence, treatment, and survival. Ophthalmology. 2011 Sep;118(9):1881-5. doi: 10.1016/j.ophtha.2011.01.040. Epub 2011 Jun 24.
Damato B. Progress in the management of patients with uveal melanoma. The 2012 Ashton Lecture. Eye (Lond). 2012 Sep;26(9):1157-72. doi: 10.1038/eye.2012.126. Epub 2012 Jun 29.
Kujala E, Makitie T, Kivela T. Very long-term prognosis of patients with malignant uveal melanoma. Invest Ophthalmol Vis Sci. 2003 Nov;44(11):4651-9. doi: 10.1167/iovs.03-0538.
Gill HS, Char DH. Uveal melanoma prognostication: from lesion size and cell type to molecular class. Can J Ophthalmol. 2012 Jun;47(3):246-53. doi: 10.1016/j.jcjo.2012.03.038.
Van Raamsdonk CD, Bezrookove V, Green G, Bauer J, Gaugler L, O'Brien JM, Simpson EM, Barsh GS, Bastian BC. Frequent somatic mutations of GNAQ in uveal melanoma and blue naevi. Nature. 2009 Jan 29;457(7229):599-602. doi: 10.1038/nature07586. Epub 2008 Dec 10.
Robertson AG, Shih J, Yau C, Gibb EA, Oba J, Mungall KL, Hess JM, Uzunangelov V, Walter V, Danilova L, Lichtenberg TM, Kucherlapati M, Kimes PK, Tang M, Penson A, Babur O, Akbani R, Bristow CA, Hoadley KA, Iype L, Chang MT; TCGA Research Network; Cherniack AD, Benz C, Mills GB, Verhaak RGW, Griewank KG, Felau I, Zenklusen JC, Gershenwald JE, Schoenfield L, Lazar AJ, Abdel-Rahman MH, Roman-Roman S, Stern MH, Cebulla CM, Williams MD, Jager MJ, Coupland SE, Esmaeli B, Kandoth C, Woodman SE. Integrative Analysis Identifies Four Molecular and Clinical Subsets in Uveal Melanoma. Cancer Cell. 2017 Aug 14;32(2):204-220.e15. doi: 10.1016/j.ccell.2017.07.003.
Jager MJ, Shields CL, Cebulla CM, Abdel-Rahman MH, Grossniklaus HE, Stern MH, Carvajal RD, Belfort RN, Jia R, Shields JA, Damato BE. Uveal melanoma. Nat Rev Dis Primers. 2020 Apr 9;6(1):24. doi: 10.1038/s41572-020-0158-0.
Seedor RS, Orloff M, Sato T. Genetic Landscape and Emerging Therapies in Uveal Melanoma. Cancers (Basel). 2021 Nov 2;13(21):5503. doi: 10.3390/cancers13215503.
Triozzi PL, Schoenfield L, Plesec T, Saunthararajah Y, Tubbs RR, Singh AD. Molecular profiling of primary uveal melanomas with tumor-infiltrating lymphocytes. Oncoimmunology. 2014 Oct 31;8(10):e947169. doi: 10.4161/21624011.2014.947169. eCollection 2019.
Maat W, Ly LV, Jordanova ES, de Wolff-Rouendaal D, Schalij-Delfos NE, Jager MJ. Monosomy of chromosome 3 and an inflammatory phenotype occur together in uveal melanoma. Invest Ophthalmol Vis Sci. 2008 Feb;49(2):505-10. doi: 10.1167/iovs.07-0786.
Kaler CJ, Dollar JJ, Cruz AM, Kuznetsoff JN, Sanchez MI, Decatur CL, Licht JD, Smalley KSM, Correa ZM, Kurtenbach S, Harbour JW. BAP1 Loss Promotes Suppressive Tumor Immune Microenvironment via Upregulation of PROS1 in Class 2 Uveal Melanomas. Cancers (Basel). 2022 Jul 28;14(15):3678. doi: 10.3390/cancers14153678.
Bronkhorst IH, Jager MJ. Inflammation in uveal melanoma. Eye (Lond). 2013 Feb;27(2):217-23. doi: 10.1038/eye.2012.253. Epub 2012 Dec 14.
van Smeden M, Moons KG, de Groot JA, Collins GS, Altman DG, Eijkemans MJ, Reitsma JB. Sample size for binary logistic prediction models: Beyond events per variable criteria. Stat Methods Med Res. 2019 Aug;28(8):2455-2474. doi: 10.1177/0962280218784726. Epub 2018 Jul 3.
Moons KG, Altman DG, Reitsma JB, Ioannidis JP, Macaskill P, Steyerberg EW, Vickers AJ, Ransohoff DF, Collins GS. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015 Jan 6;162(1):W1-73. doi: 10.7326/M14-0698.
Other Identifiers
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5703
Identifier Type: -
Identifier Source: org_study_id
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