Liverpool Ocular Oncology Molecular Pathology Service (LOOMPS)
The Liverpool Ocular Oncology Molecular Pathology Service provides a genetic testing service for uveal melanoma.
Uveal melanoma
Despite successful ocular treatment, around 50% of all uveal melanoma patients will develop metastatic disease. Mortality correlates with: (1) clinical stage (ie, tumour size and extent); (2) histological grade (ie, melanoma cytomorphology, mitotic rate and extravascular matrix patterns); (3) non-random genetic abnormalities, particularly loss of one copy of chromosome 3 (monosomy 3). The discovery of a strong association between the presence of monosomy 3 in primary uveal melanoma and metastatic spread was later followed by the detection of other chromosomal changes associated with prognosis such as loss of 1p and gains of 6p and 8q. In 1999, the Liverpool Ocular Oncology Centre became the first centre to perform genetic typing of uveal melanoma as a prognostic service. Using neural networks, we have developed an on-line prognostic tool, which analyses all major risk factors and generates a personalised survival curve for individual patient management.
Tests performed:
1. Multiplex Ligation Dependent Probe Amplification
2. Microsatellite analysis
3. Tests in Development
Uveal melanoma
Despite successful ocular treatment, around 50% of all uveal melanoma patients will develop metastatic disease. Mortality correlates with: (1) clinical stage (ie, tumour size and extent); (2) histological grade (ie, melanoma cytomorphology, mitotic rate and extravascular matrix patterns); (3) non-random genetic abnormalities, particularly loss of one copy of chromosome 3 (monosomy 3). The discovery of a strong association between the presence of monosomy 3 in primary uveal melanoma and metastatic spread was later followed by the detection of other chromosomal changes associated with prognosis such as loss of 1p and gains of 6p and 8q. In 1999, the Liverpool Ocular Oncology Centre became the first centre to perform genetic typing of uveal melanoma as a prognostic service. Using neural networks, we have developed an on-line prognostic tool, which analyses all major risk factors and generates a personalised survival curve for individual patient management.
Tests performed:
1. Multiplex Ligation Dependent Probe Amplification
2. Microsatellite analysis
3. Tests in Development
Liverpool Uveal Melanoma Prognosticator Online
Various clinical, histological and genetic parameters are strong predictors of UM metastatic risk. LOORG and LOOC have developed a prognostic algorithm for UM patients. In 2008, LOORG developed a neural network model to predict an individualised survival curve in UM patients combining the demographic, clinical, and histomorphological predictors. Based on data from a cohort of UM patients (n=3,653) with a follow-up of approximately 20 years, Coupland and LOOC colleagues refined the neural network model using an Accelerated Failure Time model, which was implemented as a freely-available online prognostication tool in 2012
This tool, which is globally used, employs demographic, clinical, histomorphological and genetic predictors, to produce an individualised survival curve for each patient. LUMPO has been validated externally by US and European ocular oncology centres. A revised version; LUMPO3 LUMPO III (liverpool.ac.uk), incorporating additional chromosome predictors and calculating mortality using a competing-risk methodology to reduce bias, has also been demonstrated as robust by a multicentre study, involving seven international ocular oncology centres and anonymised data from 1,836 UM patients. To date, LUMPO has been applied to an estimated 9,000 UM patients nationally, and has been used worldwide, aiding liver surveillance regimens.
Associated publications
Cost-utility analysis of a decade of liver screening for metastases using the Liverpool Uveal Melanoma Prognosticator Online (LUMPO)
Antonio Eleuteria, Alda Cunha Rola, Helen Kalirai, Rumana Hussain, Joseph Sacco, Bertil E.Damato, Heinrich Heimann, Sarah E.Coupland, Azzam F.G.Taktak
doi.org/10.1016/j.compbiomed.2021.104221
Multicenter External Validation of the Liverpool Uveal Melanoma Prognosticator Online: An OOG Collaborative Study.
Cunha Rola A, Taktak A, Eleuteri A, Kalirai H, Heimann H, Hussain R, Bonnett LJ, Hill CJ, Traynor M, Jager MJ, Marinkovic M, Luyten GPM, Dogrusöz M, Kilic E, de Klein A, Smit K, van Poppelen NM, Damato BE, Afshar A, Guthoff RF, Scheef BO, Kakkassery V, Saakyan S, Tsygankov A, Mosci C, Ligorio P, Viaggi S, Le Guin CHD, Bornfeld N, Bechrakis NE, Coupland SE.
Cancers (Basel). 2020. doi: 10.3390/cancers12020477.
Prognostication of metastatic death in uveal melanoma patients: A Markov multi-state model.
Computers in Biology and Medicine. 2018.
Eleuteri A, Taktak A, Coupland SE, Heimann H, Kalirai H, Damato B. doi:10.1016/j.compbiomed.2018.09.024
Damato B, Eleuteri A, Taktak AF, Coupland SE.
Estimating prognosis for survival after treatment of choroidal melanoma. Prog Retin Eye Res.
2011 May 30.
Damato B, Eleuteri A, Fisher AC, Coupland SE, Taktak A.
Artificial Neural Networks Estimating Survival Probability after Treatment of Choroidal Melanoma. Ophthalmology. 2008. doi:10.1016/j.ophtha.2008.01.032
Various clinical, histological and genetic parameters are strong predictors of UM metastatic risk. LOORG and LOOC have developed a prognostic algorithm for UM patients. In 2008, LOORG developed a neural network model to predict an individualised survival curve in UM patients combining the demographic, clinical, and histomorphological predictors. Based on data from a cohort of UM patients (n=3,653) with a follow-up of approximately 20 years, Coupland and LOOC colleagues refined the neural network model using an Accelerated Failure Time model, which was implemented as a freely-available online prognostication tool in 2012
This tool, which is globally used, employs demographic, clinical, histomorphological and genetic predictors, to produce an individualised survival curve for each patient. LUMPO has been validated externally by US and European ocular oncology centres. A revised version; LUMPO3 LUMPO III (liverpool.ac.uk), incorporating additional chromosome predictors and calculating mortality using a competing-risk methodology to reduce bias, has also been demonstrated as robust by a multicentre study, involving seven international ocular oncology centres and anonymised data from 1,836 UM patients. To date, LUMPO has been applied to an estimated 9,000 UM patients nationally, and has been used worldwide, aiding liver surveillance regimens.
Associated publications
Cost-utility analysis of a decade of liver screening for metastases using the Liverpool Uveal Melanoma Prognosticator Online (LUMPO)
Antonio Eleuteria, Alda Cunha Rola, Helen Kalirai, Rumana Hussain, Joseph Sacco, Bertil E.Damato, Heinrich Heimann, Sarah E.Coupland, Azzam F.G.Taktak
doi.org/10.1016/j.compbiomed.2021.104221
Multicenter External Validation of the Liverpool Uveal Melanoma Prognosticator Online: An OOG Collaborative Study.
Cunha Rola A, Taktak A, Eleuteri A, Kalirai H, Heimann H, Hussain R, Bonnett LJ, Hill CJ, Traynor M, Jager MJ, Marinkovic M, Luyten GPM, Dogrusöz M, Kilic E, de Klein A, Smit K, van Poppelen NM, Damato BE, Afshar A, Guthoff RF, Scheef BO, Kakkassery V, Saakyan S, Tsygankov A, Mosci C, Ligorio P, Viaggi S, Le Guin CHD, Bornfeld N, Bechrakis NE, Coupland SE.
Cancers (Basel). 2020. doi: 10.3390/cancers12020477.
Prognostication of metastatic death in uveal melanoma patients: A Markov multi-state model.
Computers in Biology and Medicine. 2018.
Eleuteri A, Taktak A, Coupland SE, Heimann H, Kalirai H, Damato B. doi:10.1016/j.compbiomed.2018.09.024
Damato B, Eleuteri A, Taktak AF, Coupland SE.
Estimating prognosis for survival after treatment of choroidal melanoma. Prog Retin Eye Res.
2011 May 30.
Damato B, Eleuteri A, Fisher AC, Coupland SE, Taktak A.
Artificial Neural Networks Estimating Survival Probability after Treatment of Choroidal Melanoma. Ophthalmology. 2008. doi:10.1016/j.ophtha.2008.01.032
