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SYMPOSIUM |
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Year : 2015 | Volume
: 63
| Issue : 2 | Page : 110-116 |
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Using risk factors for detection and prognostication of uveal melanoma
Pukhraj Rishi1, Vikram V Koundanya1, Carol L Shields2
1 Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, Tamil Nadu, India 2 Ocular Oncology Service, Wills Eye Hospital, Philadelphia, PA 19107, USA
Date of Submission | 04-Mar-2014 |
Date of Acceptance | 20-Sep-2014 |
Date of Web Publication | 1-Apr-2015 |
Correspondence Address: Dr. Pukhraj Rishi Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, 18 College Road, Chennai - 600 006, Tamil Nadu India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/0301-4738.154373
The early detection of malignancy, particularly uveal melanoma, is crucial in protecting visual acuity, salvaging the eye, and preventing metastasis. Risk factors for early detection of uveal melanoma have been clearly delineated in the literature and allow identification of melanoma when it is tiny and simulates a nevus. These factors include thickness >2 mm, presence of subretinal fluid (SRF), symptoms, the orange pigment, margin near optic disc, acoustic hollowness, surrounding halo, and absence of drusen. The importance of early detection is realized when one considers melanoma thickness, as each millimeter increase in melanoma thickness imparts 5% increased risk for metastatic disease. Newer imaging modalities like enhanced depth imaging optical coherence tomography and fundus autoflouroscence facilitate in detection of SRF and orange pigment. Additional molecular biomarkers and cytological features have been identified which can predict the clinical behavior of a small melanocytic lesion. Features that suggest a poor prognosis include higher blood levels of tyrosinase m-RNA, vascular endothelial growth factor, insulin-like growth factor; monosomy 3 and gains in chromosome 8. Management of uveal melanoma includes enucleation (for large), local eye wall resection, brachytherapy, charged particle irradiation, and thermotherapy (for small to medium tumors). Although the role of a good clinical evaluation cannot be underestimated, it is advisable to evaluate the various radiological, molecular, and cytological features, to enhance the accuracy of early diagnosis and improved prognosis. Keywords: Autoflouroscence, enhanced depth imaging, eye, gene expression profiling, malignancy, metastasis, monosomy 3, nevus, optical coherence tomography, tumor, uveal melanoma
How to cite this article: Rishi P, Koundanya VV, Shields CL. Using risk factors for detection and prognostication of uveal melanoma. Indian J Ophthalmol 2015;63:110-6 |
Uveal melanoma is the most common primary intraocular malignancy in adults. It also happens to be one of the few intraocular diseases which can prove fatal. [1] Like cutaneous melanoma, early detection of malignancy is crucial in preventing metastasis and saving the patients' life with appropriate therapy. A uveal melanoma can arise either de novo or from a nevus or congenital ocular melanocytosis. [2] Choroidal nevus has a variety of features depending on patient age [Figure 1]a-c. Older patients are more likely to have multiple nevi (10%), slightly thicker lesion (mean = 1.6 mm) and greater number of drusen overlying the lesion (58%) as compared to young patient (2%, 1.2 mm and 11% respectively). Choroidal nevi have also been shown to have chronic features such as retinal pigment epithelial hyperplasia (7%) and retinal pigment epithelial atrophy (10%); however, they can also show features that overlap melanoma such as associated subretinal fluid (SRF) (9%) and overlying orange pigment (6%). [3] | Figure 1: Clinical and imaging features of choroidal melanocytic lesions. Case 1: Circumpapillary pigmented choroidal lesion lacking orange pigment (a). Fundus autoflouroscense (b) is indistinct with no lipofuscin. Enhanced depth imaging-optical coherence tomography (c) normal photoreceptors and absence of SRF, consistent with choroidal nevus. Case 2: Pigmented choroidal lesion with overlying orange pigment, diffuse hyperautofluorescence (e) and the subfoveal fluid with shaggy photoreceptors (f) suggestive of choroidal melanoma. Case 3: Pigmented choroidal lesion with orange pigment (g), patchy hyperautofluorescence with sedimentation (h), and overlying SRF and shaggy photoreceptors (i), suggestive of choroidal melanoma
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Although the lesion is ophthalmoscopically visualized, because of these features, it can be considerably difficult to differentiate a nevus from a small choroidal melanoma. The management decision at this juncture is important due to the prognostic implications and psychological impact of the disease. Many studies have been undertaken to address this issue, and many authors have listed various risk factors [Table 1], [Table 2], [Table 3], for proper identification and subsequent management of small choroidal melanoma. With the advent of molecular biology and cytogenetics, several biological and cytological markers have been identified which can further predict the prognosis and help the clinician with decision making.
Host and environmental risk factors for melanoma
Host factors
It is important to look at the patient as a whole because ocular melanoma can be a part of a rather generalized disease. The presence of related ocular or cutaneous melanocytic lesions can be associated with a higher incidence of choroidal melanoma. The cutaneous conditions most frequently associated with uveal melanoma include primarily oculodermal melanocytosis (nevus of Ota) and rarely familial atypical mole and cutaneous melanoma. [4] Fair complexion and light irides are generally considered risk factors for uveal melanoma. [5] Weis et al. after their comprehensive meta-analysis, calculated the odds ratio of 1.75 (1.31-2.34) and 1.80 (1.31-2.47) for light irides and fair complexion, respectively, for the risk of developing uveal melanoma which was statistically significant. [6]
Environmental factors
Several environmental factors like sun exposure, and occupation like arc-welders are believed to be associated with an increased risk of ocular melanoma. [4],[7]
Risk factors for early detection of melanoma
Early detection of a small choroidal melanoma can be a challenge and requires a detailed evaluation of the lesion, keeping in mind the subtle clinical features of the lesion suggestive of melanoma.
Clinical
Documented tumor growth has been widely accepted as a risk factor for malignant potential of the lesion. [8],[9] Small pigmented lesions that grow have been shown to be malignant melanoma histopathologically. [10] But the growth is not always an indicator of malignancy. [8],[11] Choroidal nevi can also show growth, but the amount and rate of growth are generally very little and over a long period of time. On the other hand, some melanomas remain clinically stable, and there have been cases of histopathologically confirmed melanoma that were stable for many years. [12]
In 1994, Collaborative Ocular Melanoma Study (COMS) group [13] reported that risk factors for growth and possible malignant transformation were:
- Greater initial tumor thickness and diameter
- Presence of orange pigment
- Absence of drusen, and
- Absence of areas of retinal pigment epithelial changes adjacent to the tumor.
In 1995, Shields et al. [14] statistically derived five risk factors for malignant behavior of small melanocytic choroidal lesions. These features were all based on routine funduscopic examination, making their use practical and significant. They proposed the use of mnemonic TFSOM (To Find Small Ocular Melanoma) to assist the clinician in early detection of small choroidal melanoma at risk for growth and metastasis [Figure 1]d-i. TFSOM stands for:
- T-Thickness greater than 2 mm
- F-Subretinal fluid
- S-Symptoms
- O-Orange pigment present
- M-Margin within 3 mm of the disc.
In their study of 1287 patients, [15] they reported that if none of the above risk factors were present, growth was detected in only 4%. Tumor growth was documented in 30% and 41% of patients with one risk factor, 35% to 58% of patients with 2 risk factors, 36% to 63% of patients with 3 risk factors, and 39% to 62% of patients with 4 risk factors, and 56% of patients with all risk factors. The relative risk (RR) for growth was 1.6-2.3 for 1 factor, 2.8-5.0 for 2 factors, 5.5-9.6 for 3 factors, 11.6-17.3 for 4 factors, and 27.1 for all 5 risk factors combined. The greatest RR for growth occurred when all 5 risks were present, giving 27.1 times greater risk for growth than a tumor with no risk factors [Table 4]. | Table 4: Risk factors predicting tumor growth of a suspected small uveal melanoma (Shields et al.)
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In 2009, Shields et al. [16] after a retrospective analysis of 2514 patients, further modified their mnemonic to include 'acoustic hollowness' on ultrasound and "halo" surrounding the tumor. In their study of 408 nevi with ultrasound hollowness, 25% showed growth into melanoma compared to 4% tumors that showed growth "without hollowness." The COMS also reported low to medium internal reflectivity, often compatible with acoustic hollowness on B scans, in 88% of choroidal melanomas; further strengthening its role in diagnosis. [17] The halo nevus is a pigmented choroidal nevus surrounded by a halo or a circular band of depigmentation. The absence of such a halo around the lesion has been found to be associated with tumor growth (The halo phenomenon can be found with dysplastic nevus and even with melanoma). In their study, the presence of halo suggested nevus stability. The modified mnemonic proposed was "to find small ocular melanoma using helpful hints daily" which stands for:
- T-Thickness greater than 2 mm
- F-Subretinal fluid
- S-Symptoms
- O-Presence of orange pigment
- M-Margin within 3 mm of the disc
- H-Ultrasound hollowness
- H-Halo absent and
- D-Drusen absent.
They reported that the median Hazard ratio (HR) for growth of nevus into melanoma with 1 or 2 risk factors was 3; for those with 3 or 4 factors, 5; for 5-6 factors, 9; and for all 7 factors, 21 [Table 5]. The highest HR found was 31 for the combination of the following factors: Symptoms (flashing and floaters), the orange pigment, margin near disc, ultrasonographic hollowness, and halo absence. It was recommended that those with 1 or 2 features should be monitored every 4-6 months. Nevi with 3 or more features should be evaluated at an experienced center for management alternatives and possible treatment owing to the high risk of ultimate growth. | Table 5: Management guidelines of melanocytic uveal lesion according to the presence of risk factors (Shields et al.)
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Newer imaging techniques
Newer imaging modalities such as enhanced depth imaging-optical coherence tomography (EDI-OCT) and Fundus Autoflouroscence are fast gaining popularity as they are capable of detecting very early changes in a melanocytic lesion harboring malignancy.
Enhanced depth imaging optical coherence tomography
Enhanced depth imaging allows for a detailed structural evaluation of a choroidal pathology. Shields et al. [18] compared the EDI-OCT features of similar sized melanoma with nevi and reported that a melanoma shows characteristic features which include increased tumor thickness, SRF, subretinal lipofuscin deposition, and retinal irregularities, including shaggy photoreceptors [Figure 1]f and i.
Fundus autofluorescence
Fundus autofluorescence (FAF) has been used by several authors to investigate the amount of lipofuscin in the retinal pigment epithelium (RPE). Shields et al. [19] after their study on 51 eyes with small choroidal melanoma, concluded that melanomas show slight intrinsic hyperautofluorescence, the brightness of which increases with pigmented tumors, larger tumors, and with associated RPE disruption [Figure 1]e and h. They also found that overlying orange pigment showed remarkably bright hyperautofluorescence. Gunduz et al. [20] classified the FAF patterns of choroidal melanocytic lesions as patchy or diffuse. The patchy pattern was defined as the presence of distinct areas of increased FAF between areas of normal autofluorescence. The diffuse pattern was characterized by the presence of increased FAF with indistinct borders over a larger part (>50%) of the tumor in the absence of such intervening areas. They found that choroidal melanomas presented with either a diffuse or patchy pattern, whereas choroidal nevi demonstrated only the patchy pattern. Lavinsky et al. [21] found that choroidal melanomas have a pattern of confluent hyper-auto-fluorescence, nevi, on the other hand, do not have such characteristic hyper-auto-fluorescent features. They, thus concluded that autofluorescence is a useful noninvasive tool to assess lipofuscin in pigmented choroidal lesions, which may contribute to the diagnosis of malignancy.
Risk factors for metastasis from melanoma
Clinical risk factors
Tumor size has been a hallmark to predict prognosis of the disease. The COMS defined choroidal nevi as any melanocytic choroidal lesion that is <5 mm in the largest basal dimension and is <1 mm in height. A choroidal melanoma is defined as small if it measures 3 mm or less in apical height and largest basal diameter of 5.0-16.0 mm, as medium-sized if 3-8 mm in apical height and a basal diameter of not more than 16.0 mm, and as large if >8 mm in apical height or a basal diameter more than 16.0 mm, when the apical height is at least 2.0 mm. [13] Large tumors are associated with poor prognosis and higher metastatic rates. A comparative analysis of the 5-year survival rates after enucleation for differently sized uveal melanomas has indicated that it was 84% for small, 68% for medium-sized, and 47% for large tumors. [22] Shields et al. in their study on 8033 patients indicated that increased tumor thickness increases the risk for metastasis. They reported that each increase millimeter in melanoma thickness imparts 5% increased risk for metastatic disease. [23] Other clinical features found to be predictive of metastasis in their analysis were increasing age (HR = 1.13), ciliary body location (HR = 1.68), brown tumor (HR = 1.41) and the presence of SRF (HR = 1.28), intraocular hemorrhage (HR = 1.22) or extraocular extension (HR = 1.41).
Along with tumor thickness, the greatest basal diameter of the tumor also has an impact on patient prognosis. This is of particular relevance in cases with diffuse melanoma in which growth is seen more in a horizontal than vertical direction. Diffuse melanoma has been defined as a tumor with thickness <20% of the tumor base. [24] Damato and Coupland [25] found that metastatic deaths correlated with tumor diameter and found this feature to be a valuable predictor of survival in a cohort of 1,776 patients with uveal melanoma. In a subset analysis of 1751 patients with small melanoma of 3 mm or less in thickness, Shields et al. [26] compared prognosis based on diffuse versus nondiffuse configuration. They proved statistically that diffuse choroidal melanoma had a greater risk of metastasis and death. They found that an increase in basal dimension of the tumor by 5 mm increases the risk of metastasis by 5.6 times. Melanocytosis is another risk factor for uveal melanoma development and uveal metastasis. Melanocytosis involving eyelid, sclera or uvea is present in 3% of patients with uveal melanoma. Shields et al. [27] studied 7872 patients with uveal melanoma and concluded that the presence of oculodermal melanocytosis doubles the risk for metastasis in melanoma patients when compared with those with no melanocytosis.
Histopathological risk factors
Histopathological features are the gold standard for diagnosing ocular melanoma and differentiating it from a nevus. Following histopathological features have been associated with a poorer prognosis in a melanocytic lesion.
Cell type
The relationship between cell type and prognosis was suspected for nearly a century ago by authors such as Fuchs, [28] Knapp, [29] and Jackson. [30] It was Colonel George Callender in 1931 [31] who first proposed a classification for choroidal melanomas. He classified them on the basis of cellular morphology of the tumor into six types, that is, spindle A, spindle B, fascicular, epithelioid, mixed, and necrotic. The latter three were associated with a poorer prognosis. This classification was subsequently modified by McLean and associates [32] at the Armed Forces Institute of Pathology (AFIP) in 1983 to consist of:
- Spindle cell nevus
- Spindle cell malignant melanoma
- Mixed cell melanoma, and
- Epithelioid cell melanoma.
Using the AFIP modification of the Callender classification, spindle cell tumors carry the best prognosis and epithelioid cell tumors the worst.
Location
Juxtapapillary placed and more anteriorly placed tumors are more likely to be of epitheloid cell and are also more likely to metastasize and progress. [33]
Growth pattern
Diffuse growth pattern has been shown to be associated with a higher incidence of extraocular extensions and higher metastatic potential. [33]
Mitotic figures
Presence of mitotic figures is highly suggestive of malignancy and is a well-known risk factor for metastasis. [33]
Pigmentation
Heavy pigmentation has been found to be associated with epithelioid cell type and larger sized tumors. Increased pigmentation of the tumor is also associated with necrosis and the presence of macrophages, which increases the risk of malignancy. [33]
Necrosis and inflammatory components
The presence of necrosis and inflammatory components within the lesion is associated more with a melanoma. [33]
Vascularity
A choroidal melanoma shows more prominent vasculature and the vascular prominence is often associated with epitheloid cell type and larger size of the tumor. [33]
Molecular risk factors
Micro-metastasis of uveal melanoma is known to occur even prior to primary treatment, which explains substantial rate of metastasis despite treatment. [34] Such metastasis can remain dormant for a prolonged period of time, before becoming clinically detectable. [35] Identifying patients who are at high-risk of harboring undetectable micro-metastases is a challenging but rewarding task. The dissemination of tumor cells into the blood circulation occurs due to lack of lymphatics in the uveal tract. Hematological markers may, therefore, be useful for the detection of distant metastases. This rationale has led for identification of potential molecular markers for the early detection of disseminated tumor cells.
Tyrosinase m-RNA
Serum tyrosinase m-RNA levels have been shown to be increased in patients with primary uveal melanoma. Tyrosinase is an enzyme involved in the synthesis of melanin by melanocytes and melanoma cells. Tyrosinase m-RNA can be used for the indirect quantification of circulating tumor cells, and it has been shown that they even correlate with the size of the primary tumor. [36]
Vascular endothelial growth factor
Overexpression of vascular endothelial growth factor (VEGF) in melanoma cases is a well-documented fact. It originates from abnormal new vessels within the tumor and hypoxia induced by the irregular blood flow. It is proposed that this overexpression is associated with a proliferative stage of the tumor with metastatic potential. [37],[38] Levels of VEGF have been associated with the metastatic potential of uveal melanoma, [39] and serum levels are increased in the presence of micrometastases, and they parallel the extent of liver disease. [38],[39]
Hepatocyte growth factor
Hepatocyte growth factor and its receptor c-Met have an important role in the growth of cells in the liver. Increased levels of c-Met in uveal melanoma have been shown to be associated with a high risk of metastatic potential. [40]
Insulin-like growth factor-1
Insulin-like growth factor-1 (IGF-1) is also produced in the liver. IGF-1 binds to IGF-1R, a surface membrane glycoprotein. Expression of IGF-1R has been associated with a worse prognosis in uveal melanoma. [41] Activation of IGF-1R by binding of circulating IGF-1 increases cell proliferation, prevents apoptosis and is important for integrin adhesion to the extracellular matrix and invasion of basement membranes. [42] Hence in the presence of metastatic disease, serum IGF-1 levels fall. [43] The co-expression of IGF-1 and c-met in uveal melanoma samples is highly predictive of metastasis. [44]
Despite the promising role of serum molecular markers in determining metastatic disease at a subclinical level, their application in metastatic surveillance is limited as there is a wide variability in the normal range of values within the population.
Cytological risk factors
The advances in treatment for choroidal melanoma have allowed for more and more patients to receive conservative treatment. This has one downside as it precludes obtaining a sample for evaluation of prognostic markers. Naus et al. [45] first reported that fine-needle aspiration biopsy (FNAB) could be reliably used to sample tumors for genetic testing of uveal melanoma. In 2007, Shields et al. [46] demonstrated in 140 consecutive eyes with choroidal melanoma that tissue sample obtained by FNAB immediately before plaque radiotherapy provides adequate DNA for genetic analysis of uveal melanoma using microsatellite assay.
Chromosomal alterations
Prescher et al. [47] were the first to describe the chromosome alterations seen specifically in uveal melanoma. The major chromosome alterations have been described in chromosomes 3, 6, 8, and 11. [48] Interestingly, these chromosomal alterations are significantly correlated with the clinical high-risk factors for metastasis in uveal melanoma such as tumor size at diagnosis and epithelioid cell histology. [48] Loss of one copy of chromosome 3 in tumor cell is seen in nearly half of choroidal melanomas and is a risk factor most strongly associated with metastatic death. Monosomy 3 is associated with a 5-year survival of approximately 50%, whereas disomy 3 has been reported to predict 100% survival. [49] Shields et al. in their study on 500 melanoma cases concluded that patients with uveal melanoma demonstrating complete monosomy 3 have substantially poorer prognosis at 3 years than those with partial monosomy 3 or disomy 3. [50]
Using gene expression profiling, melanomas have been categorized into two groups:
- Class I denotes tumors with two copies of chromosome 3 (disomy 3) and other beneficial chromosome changes including gain in chromosome 6p
- Class II denotes tumors with only one copy of chromosome 3 (monosomy 3) and other deleterious chromosome changes including gain of chromosome 8p and/or isochromosome 8p.
It is believed that as the tumor undergoes subsequent growth it either, gains a fragment of chromosome 6p and becomes a less aggressive Class I melanoma or it loses a copy of chromosome 3 and develops into a Class II melanoma with high metastatic potential. Class II tumors have a greater chromosomal aneuploidy and a significantly different proliferative capacity as indicated by the expression of Ki-67 antigen. [51] Patients with Class II tumors need increased metastatic surveillance and entry into adjuvant treatment trials.
Gene alterations
Mutations in genes GNAQ and GNA11 have been associated with the development of uveal melanoma. [44] GNAQ and GNA11 have overlapping functions in melanocytes, and both genes up-regulate the MAP kinase pathway when constitutively active. Nearly 83.0% of uveal melanomas have been found to have a constitutively active mutation in either GNAQ or GNA11, suggesting that activation of the Gαq-Gα11 pathway is the predominant route to the development of uveal melanoma. GNAQ and GNA11 mutations at codon 209 were encountered in 21.7% and 56.5% of metastatic uveal melanoma samples, respectively. [52] In the same study, GNA11 mutations were more common in locally advanced tumors and tumors of the ciliochoroidal region. In addition, no association was found with chromosome status reinforcing the notion that these mutations are an early pathogenetic event. [53] The various risk factors for metastasis from melanoma are summarized in [Table 3].
Summary | |  |
The importance of early identification of a potential metastatic melanoma and the underlying prognostic implications cannot be understated. By combining the various clinical features of the disease with its histopathological, molecular, and cytological features, it is now possible to identify the tumor early in the disease process. Although the role of a good clinical evaluation cannot be underestimated, it is advisable to evaluate the various imaging and molecular and cytological features of small melanocytic choroidal tumors to improve our accuracy to diagnose and provide more favorable prognosis to the patient.
References | |  |
1. | Papastefanou VP, Cohen VM. Uveal melanoma. J Skin Cancer 2011:573974. |
2. | Gass JD. Problems in the differential diagnosis of choroidal nevi and malignant melanomas. The XXXIII Edward Jackson Memorial Lecture. Am J Ophthalmol 1977;83:299-323. |
3. | Shields CL, Furuta M, Mashayekhi A, Berman EL, Zahler JD, Hoberman DM, et al. Clinical spectrum of choroidal nevi based on age at presentation in 3422 consecutive eyes. Ophthalmology 2008;115:546-52.e2. |
4. | Seddon JM, Young TA. Epidemiology of uveal melanoma. In: Ryan SJ, editor. The Retina. 4 th ed. St. Louis: Elsevier-Mosby; 2006. p. 691-8. |
5. | Mudhar HS, Parsons MA, Sisley K, Rundle P, Singh A, Rennie IG. A critical appraisal of the prognostic and predictive factors for uveal malignant melanoma. Histopathology 2004;45:1-12. |
6. | Weis E, Shah CP, Lajous M, Shields JA, Shields CL. The association between host susceptibility factors and uveal melanoma: A meta-analysis. Arch Ophthalmol 2006;124:54-60. |
7. | Singh AD, Rennie IG, Seregard S, Giblin M, McKenzie J. Sunlight exposure and pathogenesis of uveal melanoma. Surv Ophthalmol 2004;49:419-28. |
8. | Gass JD. Observation of suspected choroidal and ciliary body melanomas for evidence of growth prior to enucleation. Ophthalmology 1980;87:523-8. |
9. | Char DH, Heilbron DC, Juster RP, Stone RD. Choroidal melanoma growth patterns. Br J Ophthalmol 1983;67:575-8. |
10. | Gass JD. Problems in the differential diagnosis of malignant melanomas of the choroid and ciliary body. Am J Ophthalmol 1977;83:299-323. |
11. | Zimmerman LE, McLean IW. Do growth and onset of symptoms of uveal melanomas indicate subclinical metastasis? Ophthalmology 1984;91:685-91. |
12. | MacIlwaine WA 4 th , Anderson B Jr, Klintworth GK. Enlargement of a histologically documented choroidal nevus. Am J Ophthalmol 1979;87:480-6. |
13. | Factors predictive of growth and treatment of small choroidal melanoma: COMS report no 5. The Collaborative Ocular Melanoma Study Group. Arch Ophthalmol 1997;115:1537-44. |
14. | Shields CL, Shields JA, Kiratli H, De Potter P, Cater JR. Risk factors for growth and metastasis of small choroidal melanocytic lesions. Ophthalmology 1995;102:1351-61. |
15. | Shields CL, Cater J, Shields JA, Singh AD, Santos MC, Carvalho C. Combination of clinical factors predictive of growth of small choroidal melanocytic tumors. Arch Ophthalmol 2000;118:360-4. |
16. | Shields CL, Furuta M, Berman EL, Zahler JD, Hoberman DM, Dinh DH, et al. Choroidal nevus transformation into melanoma: Analysis of 2514 consecutive cases. Arch Ophthalmol 2009;127:981-7. |
17. | Collaborative Ocular Melanoma Study Group, Boldt HC, Byrne SF, Gilson MM, Finger PT, Green RL, et al. Baseline echographic characteristics of tumors in eyes of patients enrolled in the Collaborative Ocular Melanoma Study: COMS report no 29. Ophthalmology 2008;115:1390-7.e1. |
18. | Shields CL, Kaliki S, Rojanaporn D, Ferenczy SR, Shields JA. Enhanced depth imaging optical coherence tomography of small choroidal melanoma: Comparison with choroidal nevus. Arch Ophthalmol 2012;130:850-6. |
19. | Shields CL, Bianciotto C, Pirondini C, Materin MA, Harmon SA, Shields JA. Autofluorescence of choroidal melanoma in 51 cases. Br J Ophthalmol 2008;92:617-22. |
20. | Gündüz K, Pulido JS, Ezzat K, Salomao D, Hann C. Review of fundus autofluorescence in choroidal melanocytic lesions. Eye (Lond) 2009;23:497-503. |
21. | Lavinsky D, Belfort RN, Navajas E, Torres V, Martins MC, Belfort R Jr. Fundus autofluorescence of choroidal nevus and melanoma. Br J Ophthalmol 2007;91:1299-302. |
22. | Diener-West M, Hawkins BS, Markowitz JA, Schachat AP. A review of mortality from choroidal melanoma. II. A meta-analysis of 5-year mortality rates following enucleation, 1966 through 1988. Arch Ophthalmol 1992;110:245-50. |
23. | Shields CL, Furuta M, Thangappan A, Nagori S, Mashayekhi A, Lally DR, et al. Metastasis of uveal melanoma millimeter-by-millimeter in 8033 consecutive eyes. Arch Ophthalmol 2009;127:989-98. |
24. | Shields CL, Shields JA, De Potter P, Cater J, Tardio D, Barrett J. Diffuse choroidal melanoma. Clinical features predictive of metastasis. Arch Ophthalmol 1996;114:956-63. |
25. | Damato B, Coupland SE. A reappraisal of the significance of largest basal diameter of posterior uveal melanoma. Eye (Lond) 2009;23:2152-60. |
26. | Shields CL, Kaliki S, Furuta M, Shields JA. Diffuse versus nondiffuse small (=3 MM thickness) choroidal melanoma: Comparative analysis in 1,751 cases. The 2012 F. Phinizy Calhoun lecture. Retina 2013;33:1763-76. |
27. | Shields CL, Kaliki S, Livesey M, Walker B, Garoon R, Bucci M, et al. Association of ocular and oculodermal melanocytosis with the rate of uveal melanoma metastasis: Analysis of 7872 consecutive eyes. JAMA Ophthalmol 2013;131:993-1003. |
28. | Demirci H, Shields CL, Shields JA, Eagle RC Jr, Honavar SG. Diffuse iris melanoma: A report of 25 cases. Ophthalmology 2002;109:1553-60. |
29. | Damato B. Progress in the management of patients with uveal melanoma. The 2012 Ashton Lecture. Eye (Lond) 2012;26:1157-72. |
30. | Jackson E. A Manual of the Diagnosis and Treatment of the Diseases of the Eye. 2 nd ed. Philadelphia: Saunders; 1907. |
31. | Callender GR. Malignant melanotic tumors of the eye: A study of histologic types in 111 cases. Trans Am Acad Ophthalmol Otolaryngol 1931;36:131-42. |
32. | McLean IW, Foster WD, Zimmerman LE, Gamel JW. Modifications of Callender's classification of uveal melanoma at the Armed Forces Institute of Pathology. Am J Ophthalmol 1983;96:502-9. |
33. | Histopathologic characteristics of uveal melanomas in eyes enucleated from the Collaborative Ocular Melanoma Study. COMS report no 6. Am J Ophthalmol 1998;125:745-66. |
34. | Zimmerman LE, McLean IW, Foster WD. Does enucleation of the eye containing a malignant melanoma prevent or accelerate the dissemination of tumour cells. Br J Ophthalmol 1978;62:420-5. |
35. | Eskelin S, Pyrhönen S, Summanen P, Hahka-Kemppinen M, Kivelä T. Tumor doubling times in metastatic malignant melanoma of the uvea: Tumor progression before and after treatment. Ophthalmology 2000;107:1443-9. |
36. | Pinzani P, Mazzini C, Salvianti F, Massi D, Grifoni R, Paoletti C, et al. Tyrosinase mRNA levels in the blood of uveal melanoma patients: Correlation with the number of circulating tumor cells and tumor progression. Melanoma Res 2010;20:303-10. |
37. | el Filali M, Missotten GS, Maat W, Ly LV, Luyten GP, van der Velden PA, et al. Regulation of VEGF-A in uveal melanoma. Invest Ophthalmol Vis Sci 2010;51:2329-37. |
38. | Missotten GS, Notting IC, Schlingemann RO, Zijlmans HJ, Lau C, Eilers PH, et al. Vascular endothelial growth factor a in eyes with uveal melanoma. Arch Ophthalmol 2006;124:1428-34. |
39. | Sheidow TG, Hooper PL, Crukley C, Young J, Heathcote JG. Expression of vascular endothelial growth factor in uveal melanoma and its correlation with metastasis. Br J Ophthalmol 2000;84:750-6. |
40. | Mallikarjuna K, Pushparaj V, Biswas J, Krishnakumar S. Expression of epidermal growth factor receptor, ezrin, hepatocyte growth factor, and c-Met in uveal melanoma: An immunohistochemical study. Curr Eye Res 2007;32:281-90. |
41. | All-Ericsson C, Girnita L, Seregard S, Bartolazzi A, Jager MJ, Larsson O. Insulin-like growth factor-1 receptor in uveal melanoma: A predictor for metastatic disease and a potential therapeutic target. Invest Ophthalmol Vis Sci 2002;43:1-8. |
42. | Frenkel S, Barak V, Zioto O, Pe'er J. Novel Biomarkers for Detecting Uveal Melanoma Metastases in Proceedings of the Spring Meeting of Ocular Oncology Group, Copenhagen, Denmark; April, 2011. |
43. | Bakalian S, Marshall JC, Logan P, Faingold D, Maloney S, Di Cesare S, et al. Molecular pathways mediating liver metastasis in patients with uveal melanoma. Clin Cancer Res 2008;14:951-6. |
44. | Economou MA, All-Ericsson C, Bykov V, Girnita L, Bartolazzi A, Larsson O, et al. Receptors for the liver synthesized growth factors IGF-1 and HGF/SF in uveal melanoma: Intercorrelation and prognostic implications. Invest Ophthalmol Vis Sci 2005;46:4372-5. |
45. | Naus NC, Verhoeven AC, van Drunen E, Slater R, Mooy CM, Paridaens DA, et al. Detection of genetic prognostic markers in uveal melanoma biopsies using fluorescence in situ hybridization. Clin Cancer Res 2002;8:534-9. |
46. | Shields CL, Ganguly A, Materin MA, Teixeira L, Mashayekhi A, Swanson LA, et al. Chromosome 3 analysis of uveal melanoma using fine-needle aspiration biopsy at the time of plaque radiotherapy in 140 consecutive cases: The Deborah Iverson, MD, Lectureship. Arch Ophthalmol 2007;125:1017-24. |
47. | Prescher G, Bornfeld N, Hirche H, Horsthemke B, Jöckel KH, Becher R. Prognostic implications of monosomy 3 in uveal melanoma. Lancet 1996;347:1222-5. |
48. | Damato B, Duke C, Coupland SE, Hiscott P, Smith PA, Campbell I, et al. Cytogenetics of uveal melanoma: A 7-year clinical experience. Ophthalmology 2007;114:1925-31. |
49. | Onken MD, Worley LA, Harbour JW. Association between gene expression profile, proliferation and metastasis in uveal melanoma. Curr Eye Res 2010;35:857-63. |
50. | Shields CL, Ganguly A, Bianciotto CG, Turaka K, Tavallali A, Shields JA. Prognosis of uveal melanoma in 500 cases using genetic testing of fine-needle aspiration biopsy specimens. Ophthalmology 2011;118:396-401. |
51. | Landreville S, Agapova OA, Harbour JW. Emerging insights into the molecular pathogenesis of uveal melanoma. Future Oncol 2008;4:629-36. |
52. | Van Raamsdonk CD, Griewank KG, Crosby MB, Garrido MC, Vemula S, Wiesner T, et al. Mutations in GNA11 in uveal melanoma. N Engl J Med 2010;363:2191-9. |
53. | Bauer J, Kilic E, Vaarwater J, Bastian BC, Garbe C, de Klein A. Oncogenic GNAQ mutations are not correlated with disease-free survival in uveal melanoma. Br J Cancer 2009;101:813-5. |
[Figure 1]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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