Uveal Melanoma Research Articles

What's New in Ocular Drug Delivery: Advances in Suprachoroidal Injection since 2023.

Despite significant advancements in ocular drug delivery, challenges persist in treating posterior segment diseases like macular edema (ME) and age-related macular degeneration (AMD). Suprachoroidal (SC) injections are a promising new method for targeted drug delivery to the posterior segment of the eye, providing direct access to the choroid and retina while minimizing systemic exposure and side effects. This review examines the anatomical and physiological foundations of the SC space; evaluates delivery devices such as microcatheters, hypodermic needles, and microneedles; and discusses pharmacokinetic principles. Additionally, advancements in gene delivery through SC injections are explored, emphasizing their potential to transform ocular disease management. This review also highlights clinical applications in treating macular edema, diabetic macular edema, age-related macular degeneration, choroidal melanoma, and glaucoma. Overall, SC injections are emerging as a promising novel route for administering ophthalmic treatments, with high bioavailability, reduced systemic exposure, and favorable safety profiles. Key therapeutic agents such as triamcinolone acetonide, dexamethasone, AAV-based gene therapy, and axitinib have shown promise. The field of suprachoroidal injection is progressing rapidly, and this review article, while attempting to encapsulate most of the published preclinical and clinical studies, mainly focuses on those that are published within 2023 and 2024.

Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma

BackgroundAlthough there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached consensus. Although more than half of metastatic tumors (62%) are diagnosed within five years after primary tumor treatment, the remainder are only detected in the following 25 years. The mechanisms of UVM metastasis and its impact on prognosis are not yet fully understood.MethodsscRNA-seq data of UVM samples were obtained and processed, followed by cell type identification and characterization of macrophage subpopulations. High-dimensional weighted gene co-expression network analysis (HdWGCNA) was performed to identify key gene modules associated with metastatic protective macrophages (MPMφ) in primary samples, and functional analyses were conducted. Non-negative matrix factorization (NMF) clustering and immune cell infiltration analyses were performed using the MPMφ gene signatures. Machine learning models were developed using the identified metastatic protective macrophages related genes (MPMRGs) to distinguish primary from metastatic patients. A deep learning convolutional neural network (CNN) model was constructed based on MPMRGs and cell type associations. Lastly, a prognostic model was established using the MPMRGs and validated in independent cohorts.ResultsSingle-cell RNA-seq analysis revealed a unique immune microenvironment landscape in primary samples compared to metastatic samples, with an enrichment of macrophage cells. Using HdWGCNA, MPMφ and marker genes were identified. Functional analysis showed an enrichment of genes related to antigen processing progress and immune response. Machine learning and deep learning models based on key genes showed significant effectiveness in distinguishing between primary and metastatic patients. The prognostic model based on key genes demonstrated substantial predictive value for the survival of UVM patients.ConclusionOur study identified key macrophage subpopulations related to metastatic samples, which have a profound impact on shaping the tumor immune microenvironment. A prognostic model based on macrophage cell genes can be used to predict the prognosis of UVM patients.

Impact of Tumor Pigmentation in 6934 Patients with Uveal Melanoma at a Single Center

PurposeTo evaluate clinical features and outcomes associated with degree of tumor pigmentation in patients with uveal melanoma (UM) of the choroid and ciliary body. DesignRetrospective observational study. Subjects6,934 consecutive patients with choroidal or ciliary body melanoma between 1971 and 2007 from a single ocular oncology center. MethodsData on patient demographics, tumor characteristics, treatment approach, and clinical outcomes were collected. Comparisons between pigmented (>80% pigmentation by surface area), partially pigmented (20-80%), and non-pigmented tumors (<20%) were performed using relevant hypothesis testing. Survival analyses for metastasis and melanoma-related death were conducted using the Kaplan-Meier method with log-rank tests for univariate comparisons. A multivariate Cox regression analysis was performed to assess the independent effects of multiple covariates on time-to-metastasis. Main Outcome MeasuresExtraocular extension, ocular melanocytosis, time to tumor recurrence, tumor location, and melanoma-related metastasis and death. ResultsThere were 6,934 eyes with UM and the degree of tumor pigmentation was classified as pigmented (n=3,762; 54%), partially pigmented (n=2,115; 31%) or non-pigmented (n=1,057; 15%). Pigmented UM was associated with extraocular extension (p<0.001), ocular melanocytosis (p=0.003), earlier tumor recurrence (p<0.001), and more anterior tumor epicenter location (ciliary body, and equator to ora serrata) (p<0.001). Pigmented UMs also exhibited the highest 10-year metastasis rate at 26%, compared to 19% for partially pigmented UMs and 16% for non-pigmented UMs (p<0.001). Kaplan-Meier survival curves demonstrated differences among the tumor pigmentation groups for melanoma-related metastasis (p<0.001) and melanoma-related death (p<0.001). Multivariate Cox regression analysis for melanoma-related metastasis showed that pigmented UMs had a 29% higher relative risk of developing metastasis compared to partially pigmented UMs (p=0.002) and a 54% higher relative risk of developing metastasis compared to non-pigmented UMs (p<0.001). ConclusionPigmented choroidal and ciliary body melanoma is more often associated with ocular melanocytosis, extraocular extension, anterior tumor epicenter, and earlier tumor recurrence. We also revealed that patients with pigmented UMs demonstrate a higher 10-year rate of metastatic disease and have decreased metastatic survival relative to partially pigmented and non-pigmented UMs.

Nodular posterior scleritis mimicking melanotic choroidal melanoma: A diagnostic dilemma.

To report a case of atypical nodular posterior scleritis mimicking as a melanotic choroidal melanoma. Descriptive case report. A 38-year-old female presented with sudden onset diminution of vision, severe pain and redness in her right eye. She was diagnosed to have choroidal melanoma in her left eye one year ago and underwent enucleation. On examination, conjunctiva was injected in right eye with cells in anterior vitreous face (AVF). Fundus examination revealed a large pigmented choroidal mass temporal to macula with exudative retinal detachment. Systemic evaluation and multimodal imaging ruled out the possibility of a choroidal melanoma or metastasis, with a presumptive diagnosis of nodular posterior scleritis. Three cycles of intravenous methyl prednisolone (IVMP) with a tapering dose of oral corticosteroids showed drastic improvement in symptoms with resolution of choroidal mass - further confirming the diagnosis. In cases of choroidal mass with an inflammatory component, a trial of steroids is worthwhile to prevent clinical misjudgement and devastating treatment outcomes including enucleation.

15-Gene Expression Profile and PRAME as Integrated Prognostic Test for Uveal Melanoma: First Report of Collaborative Ocular Oncology Group Study No. 2 (COOG2.1).

Validated and accurate prognostic testing is critical for precision medicine in uveal melanoma (UM). Our aims were to (1) prospectively validate an integrated prognostic classifier combining a 15-gene expression profile (15-GEP) and PRAME RNA expression and (2) identify clinical variables that enhance the prognostic accuracy of the 15-GEP/PRAME classifier. This study included 1,577 patients with UM of the choroid and/or ciliary body who were enrolled in the Collaborative Ocular Oncology Group Study Number 2 (COOG2) and prospectively monitored across 26 North American centers. Test results for 15-GEP (class 1 or class 2) and PRAME expression status (negative or positive) were available for all patients. The primary end point was metastasis-free survival (MFS). 15-GEP was class 1 in 1,082 (68.6%) and class 2 in 495 (31.4%) patients. PRAME status was negative in 1,106 (70.1%) and positive in 471 (29.9%) patients. Five-year MFS was 95.6% (95% CI, 93.9 to 97.4) for class 1/PRAME(-), 80.6% (95% CI, 73.9 to 87.9) for class 1/PRAME(+), 58.3% (95% CI, 51.1 to 66.4) for class 2/PRAME(-), and 44.8% (95% CI, 37.9 to 52.8) for class 2/PRAME(+). By multivariable Cox proportional hazards analysis, 15-GEP was the most important independent predictor of MFS (hazard ratio [HR], 5.95 [95% CI, 4.43 to 7.99]; P < .001), followed by PRAME status (HR, 1.82 [95% CI, 1.42 to 2.33]; P < .001). The only clinical variable demonstrating additional prognostic value was tumor diameter. In the largest prospective multicenter prognostic biomarker study performed to date in UM to our knowledge, the COOG2 study validated the superior prognostic accuracy of the integrated 15-GEP/PRAME classifier over 15-GEP alone and clinical prognostic variables. Tumor diameter was found to be the only clinical variable to provide additional prognostic information. This prognostic classifier provides an advanced resource for risk-adjusted metastatic surveillance and adjuvant trial stratification in patients with UM.

Genome-Wide Methylation Patterns in Primary Uveal Melanoma: Development of MethylSig-UM, an Epigenomic Prognostic Signature to Improve Patient Stratification.

Despite studies highlighting the prognostic utility of DNA methylation in primary uveal melanoma (pUM), it has not been translated into a clinically useful tool. We sought to define a methylation signature to identify newly diagnosed individuals at high risk for developing metastasis. Methylation profiling was performed on 41 patients with pUM with stage T2-T4 and at least three years of follow-up using the Illumina Infinium HumanMethylation450K BeadChip (N = 24) and the EPIC BeadChip (N = 17). Findings were validated in the TCGA cohort with known metastatic outcome (N = 69). Differentially methylated probes were identified in patients who developed metastasis. Unsupervised consensus clustering revealed three epigenomic subtypes associated with metastasis. To identify a prognostic signature, recursive feature elimination and random forest models were utilized within repeated cross-validation iterations. The 250 most commonly selected probes comprised the final signature, named MethylSig-UM. MethylSig-UM could distinguish individuals with pUM at diagnosis who develop future metastasis with an area under the curve of ~81% in the independent validation cohort, and remained significant in Cox proportional hazard models when combined with clinical features and established genomic biomarkers. Altered expression of immune-modulating genes were detected in MethylSig-UM positive tumors, providing clues for pUM resistance to immunotherapy. The MethylSig-UM model is available to enable additional validation in larger cohort sizes including T1 tumors.

Isolated conjunctival cavernous hemangioma: a rare case report

Vascular conjunctival tumors are uncommon, usually benign lesions. Here, we report a 65-year-old male who presented with a nasal interpalpebral bulbar firm, oval, and dark-brown and non-mobile conjunctival mass. The systemic and ocular examinations including fundoscopy and gonioscopy were within normal limits. With a diagnosis of conjunctival malignant melanoma (CMM), the patient underwent excisional biopsy, partial sclerectomy, and cryotherapy. Microscopic examination revealed dilated vascular channels filled by red blood cells, separated by fibrous interstitium and no sign of malignancy. Therefore, a diagnosis of conjunctival cavernous hemangioma was made. Our case demonstrates that the conjunctival cavernous hemangioma can mimic malignant conjunctival lesions as well as extrascleral extension of uveal melanoma or uveal prolapse due to scleral necrosis.

Iris melanoma in an Australian cohort.

To report the clinicopathological features and epidemiology of iris melanoma in Queensland, Australia. This was a retrospective study of 86 patients with iris melanoma treated between 2001 and 2022 at the Queensland Ocular Oncology Service, Brisbane, Australia. Main outcome measures included demographics, clinical and phenotypic features, age-adjusted incidence and relative survival. Eighty-six patients (63% female) were included. Mean age was 54 years (range 17-82 years). The majority of patients (97%) were Caucasian, with blue eyes, fair skin and Fitzpatrick Skin Type I or II. Demographic features and clinical history showed a tendency for high ultraviolet radiation (UVR) exposure in the cohort. Histopathology was available in 69 cases (82%), and of these, 77% tumours were of spindle cell origin, with low-risk genetic profiles. Patients were followed for a mean of 8 years (median 7, range 1-21 years) after diagnosis, and only one case of metastasis was documented. The association of iris freckles, history of UVR exposure and dermatologic findings supports the role of UVR in iris melanoma. Occupation and avocation history, as well as evaluation of iris freckles may offer an easily accessible way of stratifying the risk of an individual for development of UVR-related uveal melanoma.

TRP channel-related LncRNAs, AC092535.4 and LINC01637, as novel prognostic biomarkers for uveal melanoma.

Transient receptor potential (TRP) channels function as cellular sensors with a broad impact, and their dysregulation is linked to numerous cancers. The influence of TRP channel-related long noncoding RNAs (TCRLs) on uveal melanoma (UM) remains poorly understood. We employed bioinformatics to examine the RNA-seq data and relevant clinical information of UM in the TCGA databases. By implementing coexpression analysis, we identified differentially expressed TCRLs. Using univariate Cox regression analysis, selection operator (LASSO) algorithm and stepwise regression, five key prognostic biomarkers were chosen. The high- and low-risk groups were divided based on the risk scores. Afterwards, the prediction performance of the signature was evaluated by receiver operating characteristic (ROC) curve and Kaplan-Meier (K-M) survival analysis. The functional enrichment analysis of TCRLs was also investigated. Following that, we examined immune cell infiltration, immune checkpoint expression, and tumor immune microenvironment between patients in high and low risk groups. TCRLs were validated using Random forests and multifactor Cox analysis. Candidate biomarkers were identified and screened. Finally, the effects of the candidate biomarkers on the proliferation, migration and invasion of UM cells were detected by CCK-8 assay, migration assay and perforation invasion assay. The risk score generated by five TCRLs demonstrated robust predictive power. The high-risk group exhibited a poorer prognosis, increased immune cell infiltration, and an active tumor immune microenvironment compared to the low-risk group. Furthermore, two TCRLs of risk score, AC092535.4 and LINC01637, were screened to multiplex modelling. The in vitro experiments demonstrated that UM cells were suppressed following AC092535.4 or LINC01637 knockdown. Two TCRLs, AC092535.4 and LINC01637, serve as novel prognostic biomarkers for uveal melanoma and may present potential therapeutic targets.

Shared Care Planning for a pregnant patient with uveal melanoma treated with interventional radiotherapy (brachytherapy)

Introduction: Uveal melanoma (UM) is the most prevalent primary intraocular tumor in adulthood, with an important risk of metastasis, notably to the liver, rendering standard chemotherapy ineffective. Cases of UM onset during pregnancy are rare but can exhibit accelerated tumor growth. For these cases the best conservative treatment is interventional radiotherapy (IRT) also known as brachytherapy (BT). It is a form of radiotherapy that demonstrates efficacy comparable to the more common enucleation, while mitigating any risks of intrauterine toxicity. Objective: We reported the case of M., a 39-year-old pregnant patient, diagnosed with UM and undergoing brachytherapy treatment. Our aim is to make pertinent ethical considerations about: a. The ethical and clinical approach favouring a treatment strategy that preserves the affected organ and its functionality, b. The advance care planning process conducted within a multidisciplinary team. Case discussion: With the objective of preserving the mother’s health and ensuring the protection of the foetus, the team unanimously agreed, through a collaborative decision-making process, to proceed with the viable brachytherapy intervention. This approach results in a lower burden and maximizes benefits for both the patient and the unborn child. Conclusions: Considering a holistic evaluation, especially considering the patient’s pregnancy, the multidisciplinary approach proves fundamental. Collaboration between bioethicists and health-care professionals facilitated the development of a shared document for healthcare ethics planning, expressing the team’s ethical-clinical considerations.

Detection of neoplastic-immune hybrid cells with metastatic properties in uveal melanoma

BackgroundUveal melanoma is the most common non-cutaneous melanoma and is an intraocular malignancy affecting nearly 7,000 individuals per year worldwide. Of these, approximately 50% will progress to metastatic disease for which there are currently no effective curative therapies. Despite advances in molecular profiling and metastatic stratification of uveal melanoma tumors, little is known regarding their underlying biology of metastasis. Our group has identified a disseminated neoplastic cell population characterized by co-expression of immune and melanoma proteins, circulating hybrid cells (hybrids), in patients with uveal melanoma. Compared to circulating tumor cells, which lack expression of immune proteins, hybrids are detected at an increased prevalence in peripheral blood and can be used as a non-invasive biomarker to predict metastatic progression.MethodsTo ascertain mechanisms underlying enhanced hybrid cell dissemination we identified hybrid cells within primary uveal melanoma tumors using single cell RNA sequencing (n = 8) and evaluated their gene expression and predicted ligand-receptor interactions in relation to other melanoma and immune cells within the primary tumor. We then verified expression of upregulated hybrid pathways within patient-matched tumor and peripheral blood hybrids (n = 4) using cyclic immunofluorescence and quantified their protein expression relative to other non-hybrid tumor and disseminated tumor cells.ResultsAmong the top upregulated genes and pathways in hybrid cells were those involved in enhanced cell motility and cytoskeletal rearrangement, immune evasion, and altered cellular metabolism. In patient-matched tumor and peripheral blood, we verified gene expression by examining concordant protein expression for each pathway category: TMSB10 (cell motility), CD74 (immune evasion) and GPX1 (metabolism). Both TMSB10 and GPX1 were expressed on significantly higher numbers of disseminated hybrid cells compared to circulating tumor cells, and CD74 and GPX1 were expressed on more disseminated hybrids than tumor-resident hybrids. Lastly, we identified that hybrid cells express ligand-receptor signaling pathways implicated in promoting metastasis including GAS6-AXL, CXCL12-CXCR4, LGALS9-P4HB and IGF1-IGFR1.ConclusionThese findings highlight the importance of TMSB10, GPX1 and CD74 for successful hybrid cell dissemination and survival in circulation. Our results contribute to the understanding of uveal melanoma tumor progression and interactions between tumor cells and immune cells in the tumor microenvironment that may promote metastasis.

Pan‑cancer analysis on the role of KMT2C expression in tumor progression and immunotherapy.

Histone lysine N-methyltransferase 2C (KMT2C) is involved in transcriptional regulation and DNA damage repair. Mutations in KMT2C have been implicated in the progression, metastasis, and drug resistance of multiple cancer types. However, the roles of KMT2C in the regulation of tumor prognosis, immune cell infiltration and the immune microenvironment in these multiple cancer types remain unclear. Therefore, in the present study, data from The Cancer Genome Atlas and Genotype-Tissue Expression databases were used for KMT2C expression analyses. Kaplan-Meier and univariate Cox regression analyses were also performed to investigate the prognostic role of KMT2C. In addition, Gene Set Enrichment Analysis (GSEA) was conducted to study the KMT2C-related signaling pathways. Tumor immune estimation resource 2 and single-sample GSEA were conducted to investigate the correlation between KMT2C expression and immune cell infiltrations, and Spearman's analysis was conducted to study the correlations among KMT2C, tumor mutational burden, microsatellite instability, immune regulators, chemokines and immune receptors. Immunohistochemistry of patient kidney tumor samples was performed to verify the correlation between KMT2C and programmed death-ligand 1 (PD-L1) expression. Finally, RNA interference, wound healing and colony formation assays were conducted to evaluate the effects of KMT2C expression on cell proliferation and metastasis. The results of the present study demonstrated that KMT2C was highly expressed in multiple cancer types, was a protective factor in kidney renal clear cell carcinoma and ovarian serous cystadenocarcinoma, and a risk factor for lung squamous cell carcinoma and uveal melanoma. In addition, KMT2C levels were negatively correlated with immune-activated pathways and the infiltration of immune cells, and positively correlated with inhibitory immune factors and tumor angiogenesis. Patients with low KMT2C expression had higher objective response rates to immunotherapy, and drug sensitivity analysis indicated that topoisomerase, histone deacetylase, DOT1-like histone H3K79 methyltransferase and G9A nuclear histone lysine methyltransferase inhibitors could potentially be used to treat tumors with high KMT2C expression levels. Finally, the KMT2C and PD-L1 expression levels were shown to be positively correlated, and KMT2C knockdown markedly promoted the proliferation and invasion capacities of A549 cells. In conclusion, the present study revealed that low KMT2C expression may be a promising biomarker for predicting the response of patients with cancer to immunotherapy. Conversely, high KMT2C expression was shown to promote tumor angiogenesis, which may contribute to the formation of the immunosuppressive tumor microenvironment.

Detection of human papillomavirus (HPV) in malignant melanoma

The most common type of melanoma is cutaneous melanoma (CM). The predominant mutational signature is that of ultraviolet radiation (UVR) exposure. The Cancer Genome Atlas (TCGA) molecular classification includes four major subtypes of CM based on common genetic alterations involving the following genes: BRAF, NRAS, and NF1, with a small fraction being “triple” wild-type. The two main signaling pathway abnormalities in CM are the mitogen-activated protein kinase (MAPK) pathway and the phosphoinositol-3-kinase (PI3K) pathway. Other less common types include mucosal melanomas (MM) and uveal melanoma (UM), which have a significantly different genomic landscape. Although few studies reported rare cases with HPV-positive (HPV+) melanoma, the clinicopathological and molecular characteristic of this entity has not been well-described. Among the 2084 melanoma cases queried at our institution, we identified seven patients diagnosed with HPV+ melanoma (prevalence 0.03 %), including five instances of CM and two of MM. The majority of cases were positive for HPV16 (n = 6). Most of the patients were elderly and with advanced disease (n = 6), although this finding may be attributed to the relative frequency of our institution testing advanced-stage tumors. Histologically, most cases showed high degree of pleomorphism and high mitotic count (5 or more mitoses/mm2) (n = 6). UVR signature was present in the CM, but not in the MM cases. Alterations in either MAPK and/or PI3K pathways were detected in the majority of cases (n = 6). The most common genetic abnormalities detected in this study occurred in the TERT promoter (TERTp) (n = 5), a finding that has been reported to be associated with aggressive disease. Our data shows that while HPV+ melanoma is rare, identifying this disease entity could help guide therapy given the demonstrated genomic alterations.

Using Deep Learning to Distinguish Highly Malignant Uveal Melanoma from Benign Choroidal Nevi.

Background: This study aimed to evaluate the potential of human-machine interaction (HMI) in a deep learning software for discerning the malignancy of choroidal melanocytic lesions based on fundus photographs. Methods: The study enrolled individuals diagnosed with a choroidal melanocytic lesion at a tertiary clinic between 2011 and 2023, resulting in a cohort of 762 eligible cases. A deep learning-based assistant integrated into the software underwent training using a dataset comprising 762 color fundus photographs (CFPs) of choroidal lesions captured by various fundus cameras. The dataset was categorized into benign nevi, untreated choroidal melanomas, and irradiated choroidal melanomas. The reference standard for evaluation was established by retinal specialists using multimodal imaging. Trinary and binary models were trained, and their classification performance was evaluated on a test set consisting of 100 independent images. The discriminative performance of deep learning models was evaluated based on accuracy, recall, and specificity. Results: The final accuracy rates on the independent test set for multi-class and binary (benign vs. malignant) classification were 84.8% and 90.9%, respectively. Recall and specificity ranged from 0.85 to 0.90 and 0.91 to 0.92, respectively. The mean area under the curve (AUC) values were 0.96 and 0.99, respectively. Optimal discriminative performance was observed in binary classification with the incorporation of a single imaging modality, achieving an accuracy of 95.8%. Conclusions: The deep learning models demonstrated commendable performance in distinguishing the malignancy of choroidal lesions. The software exhibits promise for resource-efficient and cost-effective pre-stratification.

Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation

Mathematical models of biochemical reaction networks are an important and emerging tool for the study of cell signaling networks involved in disease processes. One promising potential application of such mathematical models is the study of how disease-causing mutations promote the signaling phenotype that contributes to the disease. It is commonly assumed that one must have a thorough characterization of the network readily available for mathematical modeling to be useful, but we hypothesized that mathematical modeling could be useful when there is incomplete knowledge and that it could be a tool for discovery that opens new areas for further exploration. In the present study, we first develop a mechanistic mathematical model of a G-protein coupled receptor signaling network that is mutated in almost all cases of uveal melanoma and use model-driven explorations to uncover and explore multiple new areas for investigating this disease. Modeling the two major, mutually-exclusive, oncogenic mutations (Gαq/11 and CysLT2R) revealed the potential for previously unknown qualitative differences between seemingly interchangeable disease-promoting mutations, and our experiments confirmed oncogenic CysLT2R was impaired at activating the FAK/YAP/TAZ pathway relative to Gαq/11. This led us to hypothesize that CYSLTR2 mutations in UM must co-occur with other mutations to activate FAK/YAP/TAZ signaling, and our bioinformatic analysis uncovers a role for co-occurring mutations involving the plexin/semaphorin pathway, which has been shown capable of activating this pathway. Overall, this work highlights the power of mechanism-based computational systems biology as a discovery tool that can leverage available information to open new research areas.

Radiation-Induced Acquired Lacrimal Drainage Obstructions: Management and Outcomes

ABSTRACT Objective To describe the management and outcomes of patients with radiation-induced acquired lacrimal duct obstructions (RALDO). Methods A retrospective chart review from July 2018 to December 2023 of all cases undergoing surgical intervention for RALDO by a single surgeon. Data collected included demographics, tumor type and anatomic location, radiation treatment (including radiation type, dosage, and duration), interval between radiation and reported onset of epiphora, oculoplastic clinical examination, management, and outcomes. Lacrimal irrigation was done prior to surgery in all patients. Results Seventeen eyes of 16 patients with a mean age at presentation of 63.3 years and over half the patients being females (56.3%) were included in the study. The right lacrimal drainage system (LDS) was involved in 4 (23.6%), and the left side was involved in 13 (76.4%). The mean onset of epiphora symptoms after radiation was 9.5 months. The underlying tumor type were intraocular having uveal melanoma in four, cutaneous squamous cell carcinoma in 2, basal cell carcinoma involving forehead and nose in one and sino-nasal indications present in 8 patients. One patient had metastasis to the orbit and eyelid. Four patients (25%) received external beam radiotherapy (XRT) (one case had bilateral LDS involvement), 6 patients (37.5%) received intensity-modulated radiation therapy (IMRT), 5 patients (31.25%) received proton beam irradiation (PBI), and one (6.25%) received stereotactic body radiotherapy (SBRT). Mean radiation dosage was 61.31 Gy in 15 patients (data was missing in 1 patient). Punctum was effaced in 3, canalicular stenosis in 1, proximal canalicular obstruction in 8, distal canalicular obstruction in 2, and nasolacrimal duct obstruction (NLDO) in 3. Treatment was based on the site and nature of obstruction and varied from minimally invasive techniques like serial dilatation with bicanalicular silicone tube or Guibor tube to surgical interventions like dacryocystorhinostomy (DCR) or conjunctivo-dacryocystorhinostomy (C-DCR). Only 10% with primary lacrimal intubation had good response. Of the six cases that underwent C-DCR with Jones tube either as primary or secondary procedure, four cases showed improvement in epiphora (67%). Three with NLDO did well after external DCR. In total, four patients had a secondary procedure after the first failed while 7 with failed initial surgery elected against secondary surgery. The mean follow-up was 9.6 months (range 2–24 months). Conclusions In patients with RALDO, salvage treatment with silicone lacrimal intubation has poor results, CDCR with Jones tube has better results, although imperfect and in cases with NLDO, DCR has good outcomes.

Assessing large language models' accuracy in providing patient support for choroidal melanoma.

This study aimed to evaluate the accuracy of information that patients can obtain from large language models (LLMs) when seeking answers to common questions about choroidal melanoma. Comparative study comparing frequently asked questions from choroidal melanoma patients and queried three major LLMs-ChatGPT 3.5, Bing AI, and DocsGPT. Answers were reviewed by three ocular oncology experts and scored as accurate, partially accurate, or inaccurate. Statistical analysis compared the quality of responses across models. For medical advice questions, ChatGPT gave 92% accurate responses compared to 58% for Bing AI and DocsGPT. For pre/post-op questions, ChatGPT and Bing AI were 86% accurate while DocsGPT was 73% accurate. There were no statistically significant differences between models. ChatGPT responses were the longest while Bing AI responses were the shortest, but length did not affect accuracy. All LLMs appropriately directed patients to seek medical advice from professionals. LLMs show promising capability to address common choroidal melanoma patient questions at generally acceptable accuracy levels. However, inconsistent, and inaccurate responses do occur, highlighting the need for improved fine-tuning and oversight before integration into clinical practice.

Prognostic value of clinical and radiomic parameters in patients with liver metastases from uveal melanoma.

Approximately every second patient with uveal melanoma develops distant metastases, with the liver as the predominant target organ. While the median survival after diagnosis of distant metastases is limited to a year, yet-to-be-defined subgroups of patients experience a more favorable outcome. Therefore, prognostic biomarkers could help identify distinct risk groups to guide patient counseling, therapeutic decision-making, and stratification of study populations. To this end, we retrospectively analyzed a cohort of 101 patients with newly diagnosed hepatic metastases from uveal melanoma by using Cox-Lasso regression machine learning, adapted to a high-dimensional input parameter space. We show that substantial binary risk stratification can be performed, based on (i) clinical and laboratory parameters, (ii) measures of quantitative overall hepatic tumor burden, and (iii) radiomic parameters. Yet, combining two or all three domains failed to improve prognostic separation of patients. Additionally, we identified highly relevant clinical parameters (including lactate dehydrogenase, thrombocyte counts, aspartate transaminase, and the metastasis-free interval) at first diagnosis of metastatic disease as predictors for time-to-treatment failure and overall survival. Taken together, the risk stratification models, built by our machine-learning algorithm, identified a comparable and independent prognostic value of clinical, radiological, and radiomic parameters in uveal melanoma patients with hepatic metastases.

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis. Therefore, the information on UM patients from the SEER database (2000-2020) was split into a 7:3 ratio training set and an internal test set based on distant metastasis presence. Univariate and multivariate logistic regression analyses assessed distant metastasis risk factors. Six machine learning methods constructed a predictive model post-feature variable selection. The model evaluation identified the multilayer perceptron (MLP) as optimal. Shapley additive explanations (SHAP) interpreted the chosen model. A web-based calculator personalized risk probabilities for UM patients. The results show that nine feature variables contributed to the machine learning model. The MLP model demonstrated superior predictive accuracy (Precision = 0.788; ROC AUC = 0.876; PR AUC = 0.788). Grade recode, age, primary site, time from diagnosis to treatment initiation, and total number of malignant tumors were identified as distant metastasis risk factors. Diagnostic method, laterality, rural-urban continuum code, and radiation recode emerged as protective factors. The developed web calculator utilizes the MLP model for personalized risk assessments. In conclusion, the MLP machine learning model emerges as the optimal tool for predicting distant metastasis in UM patients. This model facilitates personalized risk assessments, empowering early and tailored treatment strategies.

Diagnosis of metastatic melanoma by fine-needle aspiration biopsy and primary melanoma by using the skin and mucousa imprints

BACKGROUND: Determination of the cytogenetic origin and morphological type of metastatic or primary tumor determines the prescription of therapy and affects the efficiency of patient’s treatment. Currently, a number of publications evaluate the potential of cytological diagnostics of melanoma. AIM: To evaluate the significance of diagnosing metastatic melanoma by fine-needle aspiration biopsy and primary melanoma by using the skin and mucosa imprints. METHODS: In a retrospective study, a comparative analysis of cytological melanoma samples, in comparison with clinical and anamnestic information and the results of histological, immunohistochemical, and molecular genetic studies, was carried out. Information about 109 patients from the cancer registry of the Altai Regional Oncology Dispensary (Barnaul, Russia) for 2022 was used in the study. Traditional and liquid-based methods for preparing samples were used. The samples were stained using Pappenheim and Papanicolaou methods. In some observations, cytological material was used for molecular genetic studies. Using the cancer registry data of the dispensary, the results of histological and of molecular genetic studies, and a final conclusion was given about each patient. RESULTS: Fine-needle aspiration biopsy was carried out in 80 patients. Tumor smears were obtained from 29 patients. The cytological diagnose “melanoma” was consistent with the data of histological and immunohistochemical studies (p 0.001) for all 109 patients. Melanoma was diagnosed for the first time in 66 (60.5%) patients. In other cases, the process of progression was noted within the period from one year to 20 years. Epidermal melanoma was noted in 101 (92.7%) cases, including 9 patients with acral melanoma, and 2 cases with localization on the vulva. Melanomas of mucosa were found in 5 cases (4.5%): in the rectum and anal canal, vagina, and in 2 cases on the hard palate. Non-epidermal (uveal) melanomas metastases were diagnosed in liver by fine-needle aspiration biopsy in 3 patients (2.8%). Based on the cellular composition, epithelioid cell melanoma was determined in 81 (74.3%) patients, mixed cell in 14 (12.8%) cases, spindle cell in 9 (8.2%), pigmentless in 2 (1.8%) cases and nevoid melanoma in 1 (0.9%) case. The mutation status was determined in 96 patients (88.1%). Of these, in 8 patients it was determined using cytological material. In epidermal melanomas, mutations in codon 600 of exon 15 of the BRAF gene were found in 43 (44.8%) patients, including 2 cases of acral melanoma. Mutations V600K, V600E/Ec were found in one patient each. In mucousal melanomas: Q61R mutation was found in exon 3 of the NRAS gene (vaginal melanoma), G12C mutation was identified in exon 2 of the NRAS gene (anal canal melanoma). In uveal melanomas, the assessed mutations were absent (it is necessary to determine mutation is GNAQ11 and BAP1 genes). CONCLUSION: Cytological diagnosis of melanoma by fine-needle aspiration biopsies and imprints from the tumor mass is a highly informative method that allows diagnosing melanoma and verifying the tumor subtype. The obtained results indicate tumor heterogeneity and differences in mutational status depending on the location of melanomas. The molecular classification of melanoma is important when choosing individualized therapy.