ME20-S as a Potential Biomarker for the Evaluation of Uveal Melanoma

PURPOSE: We previously identified the presence of the melanocyte-specific secreted (ME20-S) glycoprotein in secretomes of uveal melanoma (UM) cultures. The aim of this study was to test for the presence and levels of ME20-S in the serum of patients with choroidal nevi and UM and correlate these levels with individual clinical data. METHODS: Serum ME20-S levels were determined by ELISA in 111 patients distributed into four categories (53 choroidal nevi, 30 untreated UM, 11 10-year disease-free [DF] UM, 17 hepatic metastatic UM) and 32 age- and sex-matched controls. ME20-S levels were correlated with individual clinical data. RESULTS: The UM and the metastatic groups showed significantly higher levels of serum ME20-S than the other groups (P < 0.001). ME20-S levels in the DF patients did not differ from those in the control group. In addition, log-transformed serum ME20-S levels showed a positive correlation with the thickness of the lesion mass in UM patients (regression coefficient 0.0689, 95% confidence interval 0.0689-0.1123, R2 = 27.1%). CONCLUSIONS: Elevated ME20-S serum levels are associated with tumor size and advanced stages of UM while low levels are characteristic of DF patients. ME20-S might be a promising serum marker for UM and useful for monitoring metastatic disease

Generation and integrated analysis of advanced patient-derived orthoxenograft models (PDOX) for the rational assessment of targeted therapies in endometrial cancer

Clinical management of endometrial cancer (EC) is handicapped by the limited availability of second line treatments and bona fide molecular biomarkers to predict recurrence. These limitations have hampered the treatment of these patients, whose survival rates have not improved over the last four decades. The advent of coordinated studies such as The Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma (TCGA_UCEC) has partially solved this issue, but the lack of proper experimental systems still represents a bottleneck that precludes translational studies from successful clinical testing in EC patients. Within this context, the first study reporting the generation of a collection of endometrioid-EC-patient-derived orthoxenograft (PDOX) mouse models is presented that is believed to overcome these experimental constraints and pave the way toward state-of-the-art precision medicine in EC. The collection of primary tumors and derived PDOXs is characterized through an integrative approach based on transcriptomics, mutational profiles, and morphological analysis; and it is demonstrated that EC tumors engrafted in the mouse uterus retain the main molecular and morphological features from analogous tumor donors. Finally, the molecular properties of these tumors are harnessed to assess the therapeutic potential of trastuzumab, a human epidermal growth factor receptor 2 (HER2) inhibitor with growing interest in EC, using patient-derived organotypic multicellular tumor spheroids and in vivo experiments

Strategies to design clinical studies to identify predictive biomarkers in cancer research

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework—the DESIGN guidelines—to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field

Differences in glucose metabolic activity in liver metastasis separates two groups of metastatic uveal melanoma patients with different prognosis

Background: Uveal melanoma metastasizes to the liver. We aimed to explore the metabolic activity of liver metastases (LM) as a biomarker for survival. Methods: We analyzed newly diagnosed patients with metastatic UM (MUM) with LM detected by liver-directed imaging and had undergone a PET/CT at diagnosis. Findings: 51 patients were identified between 2004 and 2019. Median age was 62 years, 41% male and 22% ECOG ≥1. LDH, ALP, and GGT were elevated in 49%, 37%, and 57% of patients. Median LM SUVmax was 8.5 (3-42.2). Same size lesions presented a wide range of metabolic activity. Median OS was 17.3 m (95% CI:10.6-23.9). Patients with SUVmax ≥8.5 had an OS of 9.4 m (95% CI:6.4-12.3), whereas patients with SUVmax <8.5 had an OS of 38.4 m (95% CI:21.4-55.5; p < 0.0001, HR = 2.9). We observed similar results when studying M1a disease separately. Multivariate analysis showed SUVmax as an independent prognostic factor for the whole population and those with M1a disease. Interpretation: Increased metabolic activity of LM seems to be an independent predictor of survival. MUM is a heterogeneous disease and metabolic activity probably reflects a different intrinsic behavior

Ergolide mediates anti-cancer effects on metastatic uveal melanoma cells and modulates their cellular and extracellular vesicle proteomes

&lt;p&gt; Background: Uveal melanoma is a poor prognosis cancer. Ergolide, a sesquiterpene lactone isolated from Inula Brittanica, exerts anti-cancer properties. The objective of this study was to 1) evaluate whether ergolide reduced metastatic uveal melanoma (MUM) cell survival/viability in vitro and in vivo; and 2) to understand the molecular mechanism of ergolide action.&lt;/p&gt;&lt;p&gt; Methods: Ergolide bioactivity was screened via long-term proliferation assay in UM/MUM cells and in zebrafish MUM xenograft models. Mass spectrometry profiled proteins modulated by ergolide within whole cell or extracellular vesicle (EVs) lysates of the OMM2.5 MUM cell line. Protein expression was analyzed by immunoblots and correlation analyses to UM patient survival used The Cancer Genome Atlas (TCGA) data.&lt;/p&gt;&lt;p&gt; Results: Ergolide treatment resulted in significant, dose-dependent reductions (48.5 to 99.9%; p&lt;0.0001) in OMM2.5 cell survival in vitro and of normalized primary zebrafish xenograft fluorescence (56%; p&lt;0.0001) in vivo, compared to vehicle controls. Proteome-profiling of ergolide-treated OMM2.5 cells, identified 5023 proteins, with 52 and 55 proteins significantly altered at 4 and 24 hours, respectively ( p&lt;0.05; fold-change &gt;1.2). Immunoblotting of heme oxygenase 1 (HMOX1) and growth/differentiation factor 15 (GDF15) corroborated the proteomic data. Additional proteomics of EVs isolated from OMM2.5 cells treated with ergolide, detected 2931 proteins. There was a large overlap with EV proteins annotated within the Vesiclepedia compendium. Within the differentially expressed proteins, the proteasomal pathway was primarily altered. Interestingly, BRCA2 and CDKN1A Interacting Protein (BCCIP) and Chitinase Domain Containing 1 (CHID1), were the only proteins significantly differentially expressed by ergolide in both the OMM2.5 cellular and EV isolates and they displayed inverse differential expression in the cells versus the EVs.&lt;/p&gt;&lt;p&gt; Conclusions: Ergolide is a novel, promising anti-proliferative agent for UM/MUM. Proteomic profiling of OMM2.5 cellular/EV lysates identified candidate pathways elucidating the action of ergolide and putative biomarkers of UM, that require further examination.&lt;/p&gt

Strategies to design clinical studies to identify predictive biomarkers in cancer research

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field