Abstract

Purpose

   To correlate the differentially expressed miRNAs with
   clinico-pathological features in uveal melanoma (UM) tumors harbouring
   chromosomal 3 aberrations among South Asian Indian cohort.

Methods

   Based on chromosomal 3 aberration, UM (n = 86) were grouped into
   monosomy 3 (M3; n = 51) and disomy 3 (D3; n = 35) by chromogenic
   in-situ hybridisation (CISH). The clinico-pathological features were
   recorded. miRNA profiling was performed in formalin fixed paraffin
   embedded (FFPE) UM samples (n = 6) using Agilent, Human miRNA
   microarray, 8x15KV3 arrays. The association between miRNAs and
   clinico-pathological features were studied using univariate and
   multivariate analysis. miRNA-gene targets were predicted using
   Target-scan and MiRanda database. Significantly dys-regulated miRNAs
   were validated in FFPE UM (n = 86) and mRNAs were validated in frozen
   UM (n = 10) by qRT-PCR. Metastasis free-survival and miRNA expressions
   were analysed by Kaplen-Meier analysis in UM tissues (n = 52).

Results

   Unsupervised analysis revealed 585 differentially expressed miRNAs
   while supervised analysis demonstrated 82 miRNAs (FDR; Q = 0.0).
   Differential expression of 8 miRNAs: miR-214, miR-149*, miR-143,
   miR-146b, miR-199a, let7b, miR-1238 and miR-134 were studied. Gene
   target prediction revealed SMAD4, WISP1, HIPK1, HDAC8 and C-KIT as the
   post-transcriptional regulators of miR-146b, miR-199a, miR-1238 and
   miR-134. Five miRNAs (miR-214, miR146b, miR-143, miR-199a and miR-134)
   were found to be differentially expressed in M3/ D3 UM tumors. In UM
   patients with liver metastasis, miR-149* and miR-134 expressions were
   strongly correlated.

Conclusion

   UM can be stratified using miRNAs from FFPE sections. miRNAs predicting
   liver metastasis and survival have been identified. Mechanistic linkage
   of de-regulated miRNA/mRNA expressions provide new insights on their
   role in UM progression and aggressiveness.

Introduction

   Uveal Melanoma (UM) is a primary adult intraocular tumor. The
   prevalence of UM is 0.02% in South Asian Indian populations [[44]1].
   According to Collaborative Ocular Melanoma Study group (COMS, 2001),
   about 50% of UM patients develop liver metastasis within 10–15 years of
   enucleation [[45]2]. UM diagnosis and hepatic metastasis prediction is
   critical in prognosis and planning therapeutic regimes [[46]3,[47]4].
   The existing prognostic factors include clinical parameters,
   histopathological parameters, extra-ocular extension, immune-markers,
   chromosomal aberrations (1, 6, 8, 13q and 16p) and germ line mutations
   (BAP1 and GNA11/ GNAQ) [[48]1,[49]5,[50]6,[51]7].

   Extensive molecular studies using gene expression and chromosomal
   aberration analysis have helped to stratify UM into 2 classes—class 1
   tumors with low risk of liver metastasis, associated with disomy3 (D3),
   and class 2 tumors with high risk of liver metastasis associated with
   monosomy3 (M3) [[52]8]. Unfortunately, there is a lack of accuracy in
   the molecular genetic testing due to intra-tumoral heterogeneity
   [[53]9] and micro-deletions of genes prevailing in UM tumors decreasing
   the precision in identifying micro-metastases [[54]10].

   MicroRNAs (miRNAs) are non-coding RNAs that regulate the gene
   expression at the post-transcriptional stage and they play an important
   role in tumor progression and metastasis. miRNAs based biomarkers are
   gaining importance in cancer diagnosis and for prognosis
   [[55]11,[56]12]. There are a few earlier studies on miRNA profiles in
   UM. In one study, miRNA profiles in UM have been studied using primary
   tumor tissues, primary cells and cell lines [[57]13,[58]14,[59]15]. In
   the second study, 6 miRNAs (let-7b, miR-199a, miR-199a*, miR-143,
   miR-193b, and miR-652) were identified to differentiate class 1 and
   class 2 UM tumors [[60]13]. In the third study, prognostic significance
   of chromosome 3 loss and 8q gain was observed in UM archival samples,
   however a clear correlation was not observed between miRNA expression
   with metastasis and survival [[61]16].

   In India, majority of the melanomas are enucleated by the
   ophthalmologist and a small fraction of the patients who are treated at
   tertiary referral eye centre also have opportunity for plaque therapy
   [[62]17]. Currently, much emphasis is laid on the largest tumor
   diameter (LTD) and a few centres do offer in-situ hybridisation (CISH)
   based M3 detection [[63]18]. Here, we explored the potential of miRNAs
   as in UM with M3/D3, and their association with liver metastasis in
   South Asian Indian cohort of uveal melanomas. The merits of the present
   study are the availability of the clinico-pathological records along
   with the corresponding formalin-fixed paraffin embedded (FFPE) melanoma
   tissues for miRNA analysis. FFPE samples can be used for miRNA
   expression analysis as the secondary structures are not altered even
   after fixation processes [[64]19].

Materials and Methods

Sample collection

   FFPE eyeballs (n = 86) diagnosed as UM at Medical Research Foundation,
   Sankara Nethralaya, (2009–2013) were included in the study. Duly signed
   consent forms from the patient/guardian as a part of clinical
   management were obtained from enrolled patients. Normal melanocytes (n
   = 5) were collected from the human cadaveric eyeballs received at CU
   Shah Eye bank ([65]http://www.sankaranethralaya.org/eye-bank.html)
   during 2011–2012. The study was reviewed and approved by the local
   ethics committee at Vision Research Foundation, Sankara Nethralaya and
   the committee deemed that it conformed to the principles of research,
   in accordance with Helsinki Declaration (Ethics number: 146b-2009-P).

Specimen selection

Clinico-pathological features

   Study cohort included 58 male and 28 female patients with the median
   age of 48.5 years. The study group consisted of 12 patients diagnosed
   with ciliary body melanoma and 74 with choroidal melanoma. Mean of the
   largest tumor diameter (LTD) was 13.7mm X 9.6mm. Haematoxylin and Eosin
   slides were reviewed and 1–2 representative tumor tissue blocks were
   selected. History of liver metastasis was obtained from patient medical
   records. The study included UM tumors with cell types: spindle cells (n
   = 27), epitheliod (n = 15) and mixed cell type (n = 44). These 86 UM
   tumors includes 37 UM with scleral extension; 8 UM with extension into
   vortex veins and 11 UM with extension into orbit. The 52 patients
   (60.46% corresponding to 52/86 cohort) with 2–5 years of follow-up were
   considered for the metastasis-free survival analysis (Kaplen-Meier).
   The clinical follow-up study revealed 17 patients diagnosed with liver
   metastasis. The clinico-pathological variables (age, sex, specimen
   obtained, cell type and LTD) provided as [66]S1 Table.

Chromogenic in-situ hybridisation

   Centromeric probes (Invitrogen, USA) were used to detect chromosome 3
   aberrations and disomy 18 (control). Hybridisation and scoring
   protocols were followed as reported earlier [[67]18].

Immunohistochemistry

   Immunohistochemical detection of HSP27 on FFPE tumor sections was
   performed by using a rabbit polyclonal antibody (AM171-10M, Biogenex,
   CA, USA), Super Sensitive ^TM Polymer- HRP detection system (Biogenex,
   CA, USA) and aminoethyl carbazole according to the manufacturer’s
   instructions. Breast cancer cell line (MCF-7) served as positive
   control [[68]20]. The immune-score ranges from 0–12 [[69]21].

miRNA profiling

   Three M3 and three D3 uveal melanoma tumors were taken for expression
   studies. The study was carried out using technical duplicates. The
   small RNA was extracted from the FFPE tissues using miRVANA kit
   (Ambion, Life Technologies, USA) following manufacturer’s protocol. The
   processed samples were hybridized on the Human miRNA microarray,
   8x15KV3 array as per manufacturer’s instruction. The microarray slide
   was scanned using Agilent Scanner (Agilent Technologies, Part Number
   G2565CA).

qRT-PCR

   Total RNA was isolated from FFPE tissues using Recover All^™ total
   nucleic acid isolation (Ambion, Life technologies, USA) as per
   manufacturer’s protocol. Reverse transcription (RT) of mature miRNA in
   100 ng/μl of total RNA using TaqMan MicroRNA RT kit (Applied
   Biosystems, Foster City, CA) was carried out following manufacturer’s
   protocol. For gene expression studies, RT was carried out using oligo
   dT random primers and Sensiscript II kit (205211, Qiagen, Santa Clara,
   CA). Real-time PCR was performed using 1X Universal PCR Master Mix,
   taqman miRNA probes (ABI Applied Biosystem, USA) and 1X Universal RT^2
   Real Time ^™ SyBr Green/ROX PCR master Mix (Catalogue No: 330520,
   SABiosciences, USA) according to the manufacturer’s instructions.
   Description of taqman probes and primers were tabulated ([70]S2 Table).
   The unit expression is log[2] transformed ratios.

Statistical analysis

qRT- PCR data analysis

   The miRNA expressions were derived after normalizing with the mean
   expression of normal melanocytes (n = 5). Cut-offs used for
   de-regulation in miRNA expression was: greater than 1(log[2] ratio) as
   positive expression and less than—0.5 (log[2] ratio) as negative.
   Pearson’s correlation, chi-square test, independent student‘s-t test
   and ANOVA were used to derive the significance between the variables.
   Paired student’s-t test was used to derive the significance among miRNA
   expressions between M3/D3 tumors. Kaplen-Meier’s test was used to
   assess the survival rates for the presence of eight miRNAs.

Microarray analysis

   Cut-offs used for de-regulation in miRNA expression was: greater than 1
   (log[2] transformed value) in M3 detected tumors and less than 1
   (log[2]transformed value) in chromosome 3 balanced tumors. ANOVA was
   used to identify the highly expressed miRNA in the M3 tumors compared
   with D3 tumors. Significance Analysis of Microarray (SAM) was performed
   to derive the significant miRNAs (Q = 0.0). Experimentally validated
   targets for the differentially expressed miRNAs were obtained from
   TargetScan, MiRanda and miRTarbase. Further, they were subjected to GO
   and Pathway enrichment analysis using PANTHER data base with p-value
   cut-off ≤ 0.05 along with Boneferroni FDR correction. Downstream
   effects analysis was performed to identify the biological processes and
   functions that are likely to be causally affected by identified
   regulated genes. We used the Ingenuity Pathway Analysis (IPA,
   Ingenuity^® Systems) regulation z-score algorithm to identify
   biological functions that are expected to be more active in UM
   (increased—positive z-score) and less active (decreased—negative
   z-score). The p-value was calculated using the Fischer's exact test and
   reflects the likelihood that the association between a set of
   genes/miRNAs in our dataset and a biological function is significant
   (p-value ≤ 0.05).

Results and Discussion

Grouping of UM into monosomy of chromosome 3 (M3) / disomy of chromosome 3
(D3)

   Chromosome 3 loss was detected in 59.30% [51/86] of UM, and presence of
   both the copies of chromosome 3 was detected in 40.69% [35/86] UM using
   chromogenic in-situ hybridisation (CISH). Among the UM which had
   metastasized to liver (n = 17), M3 was detected in 64.7% [11/17] and D3
   was detected in 35.29% [6/17] UM ([71]S1 Fig). Here, emphasis was laid
   on the observation of D3 in UM that had metastasized to the liver.
   Existence of intra-tumoral heterogeneity in UM [[72]9] might have
   contributed to this variation in metastatic prediction.

   Based on an earlier report, UM were further grouped in to M3/D3 by
   analysing the expression of Heat shock protein 27 (HSP27) protein using
   immunohistochemistry [[73]21]. [74]S1 Table indicates the distribution
   of HSP27 protein expression in UM. Photomicrographs reveal the
   cytoplasmic positivity of HSP27 expression in UM sections ([75]S2 Fig).
   A significant association was observed between HSP27 expression and M3
   (p-value = 0.021) as indicated earlier [[76]21]. Clinico-pathological
   descriptions of tumors, hybridization scores and immuno-scores for
   individual UM are tabulated in [77]S1 Table. Their statistical
   significance with M3 and liver metastasis are indicated in [78]S3 and
   [79]S4 Tables. A significant association of M3 to tumor base (p =
   0.002) was observed.

Selection of significantly dys-regulated miRNAs using a high throughput
analysis

   The miRNAs were filtered using unsupervised and supervised data
   analysis. The common pool of miRNAs thus obtained was selected for
   validation by qRT-PCR. Data of miRNA profiling has been submitted to
   GEO database ([80]GSE68828).

Data analysis of miRNA profiling

   In unsupervised analysis, Principal Component Analysis (PCA) revealed
   clustering of three M3 UM tumors forming a single group and correlated
   with the CISH based classification. The slight difference within the D3
   UM tumors could be due to the heterogeneity in the tumor infiltrating
   lymphocytes and the cell type ([81]Fig 1A). The miRNA profiling of the
   tumors (n = 6) revealed a total of 585 differentially expressed miRNAs
   between M3 (n = 3) and D3 (n = 3) samples. [82]S3 Fig shows the
   hierarchical cluster for the top 100 differentially expressed miRNAs
   with p<0.05. Data analysis using ANOVA listed 25 up-regulated miRNAs
   and 26 down-regulated miRNAs in M3 tumors relative to D3 tumors.
   ([83]S5 Table shows top 10 miRNAs).

Fig 1. Unsupervised and supervised analysis of miRNA expression in UM.

   [84]Fig 1
   [85]Open in a new tab

   A: Graphical representation of the unsupervised analysis: principal
   component analysis (PCA) for the UM tumor tissues: M3 (n = 3), and D3
   (n = 3) showing the clustering of samples correspondingly in to two
   distinct groups (M3 and D3). Blue colored triangle denotes M3 UM tumors
   while red colored spheres denotes D3 UM tumors. B: Supervised analysis:
   The significance analysis of microarray (SAM) plot reveals the de
   regulated miRNAs between the monosomy and disomy formalin fixed UM
   primary tumors. The false discovery rate (FDR) has set at Q = 0.78%.
   The list of miRNAs with Q = 0.0 has been considered for the validation
   by qRT-PCR. C: Venn diagram on intersection of miRNAs obtained from
   ANOVA and SAM. miR-134, miR-1238, miR-149* are the common select miRNAs
   observed from this study.

   In supervised analysis, SAM, we observed 82 differentially expressed
   miRNAs with the false discovery rate (FDR); Q = 0.0 ([86]Fig 1B). Top
   10 up-regulated miRNAs with maximum score and high fold change were:
   miR-317-5p, miR-373, miR-1268, miR-191*, miR-150, miR-1275, miR-188-5p,
   miR-1238, miR-134 and miR-296-5p.

   On intersection of miRNAs detected in both ANOVA and SAM analysis here,
   we observed 14 up-regulated miRNAs in common ([87]Fig 1C). Absolute
   expression levels of key miRNAs identified to be differentially
   expressed by ANOVA and SAM methods showed ([88]Fig 2A) discriminating
   profiles in M3 and D3 tumors, indicating the sensitivity of detection.
   Further, these key miRNAs subjected to unsupervised hierarchical
   clustering clearly identified miRNA clusters that could indicate
   co-expression pattern across M3 and D3 tumors ([89]Fig 2B). Analysis of
   key gene ontology (GO) and pathways regulated by the differentially
   expressed miRNAs were identified by ways of genes that are validated
   and to be targeted by these miRNAs. Some of the GO and pathways
   targeted by these differentially expressed miRNAs include Wnt
   signaling; angiogenesis and p53 pathway ([90]Fig 2C). Since,
   dys-regulation of p53 pathway has been reported in UM earlier [[91]22],
   we explored the miRNAs and their targets and subjected to regulatory
   network modeling to understand the differential regulation of p53
   pathway in M3 and D3 UM tumors.

Fig 2. Significantly dys-regulated miRNAs and pathways in UM.

   [92]Fig 2
   [93]Open in a new tab

   A: Trendline graph shows the absolute expression of key miRNAs
   identified by ANOVA and SAM. The differentially expressed miRNAs
   indicates the discriminating profiles in M3 and D3 UM tumors. The blue
   line indicates the miRNA expression in D3 UM tumors while red line
   indicates the miRNA expression in M3 tumors. B: Hierarchical cluster
   shows key miRNAs subjected to unsupervised analysis. The differentially
   expressed miRNAs indicates the co-expression pattern across M3 and D3
   UM tumors. The green colour indicates the down-regulated miRNAs while
   the red colour indicates the up-regulated miRNAs in M3 and D3 UM
   tumors. C: Analysis of key gene ontology (GO) and Pathway Enrichment by
   the differentially expressed miRNAs. A few of the pathways (i) and GO
   (ii and iii) targeted by these differentially expressed miRNAs using
   miRTarbase and PANTHER data base with p-value cut-off ≤0.05 along with
   Boneferroni FDR correction.

miRNAs expression in UM using qRT-PR

   Three miRNAs: miR-149*, miR-1238 and miR-134 (which were in common with
   supervised and unsupervised data analysis; [94]Fig 1C) and 5 miRNAs:
   miR-214, miR-143, miR146b, miR-199a and let7b (earlier shown as class
   1/ class 2 discriminators) [[95]13] were selected for validation. Also,
   the analysed expressions were associated with M3, D3 and liver
   metastasis in UM.

   Among M3 UM with liver metastasis (n = 11), higher expressions of
   miR-149* (72.72%), miR-1238 (100%), miR-134 (100%), miR-214 (54.54%),
   miR-146b (54.54%), miR-199a (100%) while moderate expression of miR-143
   (45.45%) and negative expression of let-7b (100%) was observed. Among
   M3 UM with no history of liver metastasis (n = 40), higher expressions
   of miR-149* (90.0%), miR-1238 (97.5%) and miR-134 (57.5%), miR-214
   (62.5%), miR-146b (67.5%), miR-143 (65.0%), miR-199a (90.0%) and lower
   expression of let-7b (30.0%) were observed.

   Among D3 UM with liver metastasis (n = 6), higher expressions of
   miR-149* (83.3%), miR-1238 (83.3%), miR-199a (100%); moderate
   expressions in miR-134 (50%), miR-214 (50.0%), while lower expressions
   of miR-146b (33.33%) and let-7b (25%) and negative expression in
   miR-143 (100%) were observed. Among D3 UM with no liver metastasis (n =
   29), higher expressions of miR-149* (72.41%), miR-1238 (86.2%),
   miR-199a (82.75%), miR-134 (41.37%), miR-214 (41.37%) and miR-146b
   (58.62%), while lower expression of miR-143 (37.93%), let-7b (13.79%)
   were observed ([96]S6 Table and [97]Fig 3). Relative miRNA expressions
   quantified by qRT-PCR in UM tumors are indicated as [98]S7 Table.

Fig 3. Graphical representation of the miRNA expression (fold change in log 2
ratio) in M3 / D3 UMs derived using Graph pad Prism.

   [99]Fig 3
   [100]Open in a new tab

   The dotted line represents the mean fold change of miRNA expressions
   while "M" denotes the mean fold change of the respective miRNA
   expression in UM groups.

   Glycogen synthase kinase-3α (GSK-3α), a known gene target of miR-149*
   is an important melanoma growth regulator [[101]23,[102]24]. MiR-1238
   is known to regulate SASH1 (SAM and SH3 domain-containing protein 1, a
   tumor suppressor gene), contributing to breast cancer aggressiveness
   [[103]25]. Although miR-1238 expression among the two UM groups were
   not significant, a higher percentage of miR-1238 (94.18%) suggests its
   possible role in uveal melanoma tumorigenesis. miR-134 is associated
   with invasiveness and metastasis in other cancers [[104]26] with the
   putative gene targets such as VEGFA, FOXM1, MYCN, CD9 and WWOX1 genes
   [[105]26,[106]27,[107]28]. In the present study, higher percentage of
   miR-134 (94.11%) in UM with liver metastasis, irrespective of
   chromosome 3 aberrations, suggests it could be a potential biomarker
   for class 2 tumors.

   Among the five miRNAs previously shown as class 2 tumor discriminators
   [[108]13], four up-regulated miRNAs (miR-214, miR-143, miR-146b and
   miR-199a) showed a significant association with M3 tumors while the
   other miRNA, let-7b did not show any significant association with M3 UM
   ([109]Fig 3). miR-214 regulates cell cycle regulatory genes:
   phosphatase and tensin homolog (PTEN) [[110]29], adipocyte protein 2
   (AP2) and tumour protein 53 (TP53) genes [[111]30]. miR-143 is known
   for its oncogenic activity together with KRAS (Kirsten rat sarcoma
   viral oncogene homolog), NF-kB (Nuclear factor kappa B) genes in
   cancers [[112]31,[113]32]. miR-146b, is known for its oncogenic role in
   UM cells [[114]33] with its reported gene targets NF-kB and SMAD4
   (Mothers against decapentaplegic Homolog 4). Deregulation of NF-kB
   pathways is known to regulate UM metastasis [[115]34].

   Interestingly, miR-199a, another regulator of SMAD4 was also
   up-regulated in the present study ([116]S6 Table). The tumorigenic role
   of this miRNA is substantiated by earlier reports in UM [[117]13]. Let
   7b, a known tumor suppressor miRNA is down-regulated in various cancers
   namely acute lymphoblastic leukaemia [[118]35] and retinoblastoma
   [[119]36]. Restoration of let-7b is considered as a potential
   therapeutic option in cancers [[120]37]. Earlier, let-7, has been
   stated as a strong significant discriminator in primary UM [[121]13]
   while let-7b* is reported at low levels in OCM1 cells [[122]15]. Here,
   we observed let-7b de-regulation in the present UM cohort.

Validation of target genes regulated by select miRNAs in UM

   Earlier, Harbour et al have reported a PCR based platform
   (DecisionDx-UM) consisting of 15 genes list to measure the risk
   stratification of UM tumors [[123]4,[124]38]. However, the additional
   prognostic factors specific to UM tumors such as cytogenetic analysis
   and miRNA expressions would confirm the uveal melanoma risk
   stratification [[125]39]. Here, we have explored gene targets of select
   miRNAs to implicate miRNA/mRNA’s role in UM progression. Downstream
   analysis ([126]S8 Table) revealed the role of up-regulated miRNAs,
   their regulated genes in apoptotic and cell signalling pathways.
   Further, gene targets prediction of the differentially expressed miRNAs
   revealed the negative regulation of gene lists namely (i) SMAD4, WISP1,
   HDAC8 and C-KIT by miR-146b, (ii) WISP1 by miR-1238, miR-134 and (iii)
   SMAD4 by miR-199a ([127]Fig 4). Among these interactions, we observed
   SMAD4 and WISP1 as the common regulators.

Fig 4. Network interaction between the dysregulated miRNAs and their gene
targets in UM.

   [128]Fig 4
   [129]Open in a new tab

   A: D3 UM tumor; B: M3 UM tumor. The network is drawn with the
   expressions obtained by qRT-PCR using cytoscape v.2.8. Green colour
   indicates the down-regulation of miRNAs/ genes; red colour indicates
   the up-regulation of miRNAs/ genes; Yellow colour indicates varied
   miRNA/ gene expression.

   SMAD4 and WISP1 are known to regulate p53 pathway [[130]40,[131]41].
   Infrequent mutation of p53 pathway is reported in melanoma [[132]22].
   Thus, the down-regulation of SMAD4 gene and varied expression of WISP1
   gene ([133]S9 Table) substantiates the varied activation of p53 pathway
   in UM. Here, inactivation of p53 pathway in UM was supported by the
   over-expression of HIPK1 gene ([134]S9 Table) which corroborates with
   an earlier report in other cancer (colorectal cancer) [[135]42].
   Further, we observed the de-regulation of HDAC8 and C-KIT genes, the
   known targets of miR-146b [[136]43]. The role of these target genes
   needs further investigations. Thus, the elevated level of these miRNAs
   together with its target genes suppression might contribute to the UM
   aggressiveness.

miRNAs associated with metastasis in UM

   Association of miRNAs with metastasis-free survival is essential for
   better understanding of miRNA’s involvement in UM micro-metastasis. In
   a very recent report by Herlihy et al (2015), de-regulation of genes
   coding for epigenetic modifiers have been linked with poor prognosis in
   UM with M3/ class 2 [[137]44]. The data derived from metastasis-free
   survival analysis is presented in [138]S6 Table and [139]Fig 5. These
   results indicate that the expression of miR-214, miR-149*, miR-146b,
   miR-199a, miR-1238 and miR-134 can be used to evaluate the
   metastasis-free survival in UM patients. miR-149* and miR-134
   expressions show a statistically significant association with liver
   metastasis.

Fig 5. Graphical representation of metastasis-free survival was analysed by
Kaplan-Meier analysis.

   [140]Fig 5
   [141]Open in a new tab

   The cumulative proportion surviving at end of the interval (60 months)
   is represented in percentage. Follow up of 52 patients (2–5 years of
   duration) were considered in the study.

   The non-availability of 2–5 years clinical follow-up data for some
   patients in the cohort was a limitation in this study. We hope further
   studies with larger sample size and complete clinical follow-up will be
   able to determine the panel of miRNAs as metastatic predictors and
   prognostic indicators.

Supporting Information

   S1 Fig. Photomicrographs of chromosome 3 abbrerations by Chromogenic
   in-situ hybridisation (CISH).

   The arrow heads indicates the hybridized spots. A: Normal retina with
   disomy 18 (control). B: Uveal melanoma tumour with monosomy 3, C: Uveal
   melanoma tumour with disomy 3.

   (TIF)
   [142]Click here for additional data file.^ (7.8MB, tif)
   S2 Fig. Photomicrographs of HSP27 protein expression by
   Immunohistochemistry.

   A: Positive control, High expression of HSP27 protein in the MCF-7
   cells (Breast carcinoma cell line); B: Negative control (performed by
   the exclusion of primary antibody), Absence of HSP27 protein in the
   MCF-7 cells (Breast carcinoma cell line); C & D: High to Moderate
   expression of HSP27 in the D3 melanoma tumors; E: Low to Negative
   expression of HSP27 in the M3 melanoma tumors.

   (TIF)
   [143]Click here for additional data file.^ (13.3MB, tif)
   S3 Fig. Unsupervised analysis: Hierarchical cluster of the top 100
   differentially expressed miRNAs between M3 and D3 UM primary tumours
   (FFPE).

   The green colour indicates the down-regulated miRNAs while red color
   indicates the up-regulated miRNAs. The range of the significant
   de-regulation is -2.0 to +2.0 log[2] ratio.

   (TIF)
   [144]Click here for additional data file.^ (4.8MB, tif)
   S1 Table. Clinico-pathological description, chromosome 3 aberration and
   HSP27 protein expression in UM tumor tissues.

   (DOC)
   [145]Click here for additional data file.^ (166KB, doc)
   S2 Table. Details of taqman probes and primers used in qRT-PCR.

   (DOC)
   [146]Click here for additional data file.^ (42KB, doc)
   S3 Table. Correlation analysis of Chromosome 3 aberration with clinico-
   pathological parameters in UM patients.

   (DOC)
   [147]Click here for additional data file.^ (34KB, doc)
   S4 Table. Correlation analysis of liver metastasis with clinico-
   pathological parameters in UM patients.

   (DOC)
   [148]Click here for additional data file.^ (33KB, doc)
   S5 Table. List of top 10 up-regulated miRNAs obtained by ANOVA and SAM.

   (DOC)
   [149]Click here for additional data file.^ (39.5KB, doc)
   S6 Table. Clinico-pathological descriptions of the tumors mean and
   median fold change of individual miRNAs, statistical significance
   (p-value ≤ 0.05) derived between the clinico-pathological parameters
   and mean fold change of miRNAs expression.

   (DOC)
   [150]Click here for additional data file.^ (99.5KB, doc)
   S7 Table. Data of miRNA expressions in UM quantified by qRT-PCR.

   (XLS)
   [151]Click here for additional data file.^ (76.5KB, xls)
   S8 Table. Downstream effect analysis of genes and miRNAs over-expressed
   in UM.

   (DOC)
   [152]Click here for additional data file.^ (51.5KB, doc)
   S9 Table. mRNA expression analysis by qRT-PCR.

   (DOC)
   [153]Click here for additional data file.^ (33.5KB, doc)

Acknowledgments