Proteomic analysis of energy metabolism and signal transduction in irradiated melanoma cells

Proteomics of Primary Uveal Melanoma: Insights into Metastasis and Protein Biomarkers

Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.

Blood Biomarkers of Uveal Melanoma: Current Perspectives

The detection of metastases in patients with a diagnosis of uveal melanoma (UM) is a controversial issue. While only 1% of the patients have detectable metastases at the time of diagnosis, up to 30% of them will develop liver metastases within 5 years of treatment. UM spreads hematogenously, therefore, blood biomarkers may be helpful for prognosis and monitoring the disease progression. Despite the great progress achieved thanks to the genetic analysis of UM biopsies, this is an invasive technique and is limited by the heterogeneity of the tumor. The present review considers the current understanding in the field regarding biomarkers for the diagnosis and prognosis of UM and its metastasis, primarily to the liver. General covered topics include non-conventional markers such as proteins previously identified in cutaneous melanoma and UM cell lines, circulating tumor cells, microRNAs (miRNA), and circulating DNA, and how each may be critical in the development of novel blood biomarkers for UM.

An Insight into the Proteome of Uveal Melanoma-Derived Ectosomes Reveals the Presence of Potentially Useful Biomarkers

Cancer cells are known to release extracellular vesicles that often promote disease development and progression. The present study investigated the protein content and glycosylation pattern of ectosomes released in vitro by a human primary uveal melanoma Mel202 cell line. Ectosomes released by Mel202 cells were isolated from conditioned media using sequential centrifugation, and a nano-LC-MS/MS approach was used to determine their protein content. Subsequently, proteins from ectosomes, the whole cell extracts, and the membrane fractions were probed with a panel of lectins using Western blotting and flow cytometry to reveal characteristic glycan structures. As many as 2527 unique proteins were identified, and many of them are known to be involved in cancer cell proliferation and altered metabolism, tumor invasion, metastasis, or drug resistance. Lectin-based studies revealed a distinct glycosylation pattern between Mel202-derived ectosomes and the parental cell membranes. Selective enrichment of ectosomal proteins with bisected complex type N-glycans and α2,6-linked sialic acids may be significant for ectosome formation and sequestration. Differences in the surface glycosylation of Mel202 cells and ectosomes supports recent findings that the budding of ectosomes occurs within strictly determined fragments of the plasma membrane, and thus ectosomes contain a unique protein and glycan composition.

iTRAQ Quantitative Proteomic Comparison of Metastatic and Non-Metastatic Uveal Melanoma Tumors

BACKGROUND

Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis.

METHODS

Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch's membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery ≤ 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p ≤ 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors.

RESULTS

Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in ≥ 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens.

CONCLUSIONS

The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and heat shock protein beta-1 as candidate biomarkers of uveal melanoma metastasis and establish a quantitative proteomic database for uveal melanoma primary tumors.

Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis

AIM

To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.

METHODS

Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus (GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes. The function of the genes were annotated by gene ontology (GO).

RESULTS

In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location (sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter (LTD). Additionally, we identified the hug gene (top connectivity with other genes) in each module. The hub gene RPS15A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.

CONCLUSION

From WGCNA analysis and hub gene calculation, we identified RPS15A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.